Journal articles on the topic 'Very high throughput sequencing'
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1
Bray, Paul F., Paolo M. Fortina, Srikanth Nagalla, Kathleen Delgrosso, Adam Ertel, Isidore Rigoutsos, and Steven E. McKenzie. "High-Throughput Sequencing of the Human Platelet Transcriptome." Blood 116, no. 21 (November 19, 2010): 481. http://dx.doi.org/10.1182/blood.v116.21.481.481.
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Abstract Abstract 481 Most successful DNA-based genome wide association studies identify genomic regions, not genes themselves, and the findings are often devoid of context or mechanism. To identify the genetic basis of disease and disease traits, it is imperative to characterize the quantity and forms of the genes that are expressed in the tissue of interest. It is not feasible to use primary megakaryocytes to profile mRNA from large numbers of subjects, but platelet RNA is easy to obtain. Others and we have previously surveyed genome-wide platelet RNA expression using microarrays, an approach that has had a major impact on systems biology. However, microarrays have a number of limitations, including the use of probes only to known transcripts, a limited dynamic range for quantifying very low and high levels of transcripts, high background levels from cross-hybridization, and complicated normalization schemes to compare expression levels across experiments. Novel high-throughput sequencing approaches that overcome the limitations of microarrays have recently become available. RNA sequencing (RNAseq) has a remarkable ability to quantify mRNAs and provide information about transcript sequence variations, including single nucleotide changes and alternately spliced exons. The goal of these studies was to apply RNAseq to capture platelet transcriptome complexity. Total RNA was prepared using leukocyte-depleted platelets (LDP; less than 1 WBC per 5 million platelets) from 4 donors; 2 were studied twice each. Analysis of this material showed that compared to nucleated cells (HeLa, Meg-01), platelets had 50%-90% less ribosomal RNA, and high levels of messenger and small RNAs (Agilent 2100). The major reduction in platelet rRNA was confirmed by RNA gel analysis. The platelet whole transcriptomes were analyzed via the Applied Biosystems (AB) SOLiD 3Plus next generation sequencing protocols and platform. A typical sequence run generated ∼250 million reads of 50 bp each. We observed more than 30,000 independent platelet mRNA-coding transcripts from about 10,000 genes, demonstrating substantial numbers of variant isoforms. The increased sensitivity of RNAseq for low copy number is clear from these results, because prior platelet transcriptome studies using microarrays have identified only 1500–6000 expressed genes. As an example, the platelet-specific transcript, ITGA2B, showed very high copy number in platelets, but no expression in HeLa cells and modest expression in the megakaryocyte cell line, Meg-01. As is expected for RNA-Seq data, the density of mapped reads varies by exon and local sequence. We also provide examples of newly discovered SNPs that encode non-conservative amino acid changes (AKT2 1209A/T; PIK3CB 837C/G) and alter consensus exon/intron splice junction sites (P2YR12 nt 65 G/A). We have also identified a major difference in the ratio of two splice variants of the FcRg chain, 4:1 in one human platelet donor and 49:1 in another. In summary, we have demonstrated that RNAseq can accurately and sensitively determine the quantity and quality of variations in individual platelet transcriptomes. It appears that the the platelet transcriptome is approximately 10 times more complex than previously thought. The major relative reduction in platelet rRNA may be an advantage for characterizing functional platelet transcripts. RNAseq should permit better understanding of the molecular mechanisms regulating platelet physiology and identify novel genetic variants that contribute to disorders of thrombosis and hemostasis. Disclosures: No relevant conflicts of interest to declare.
2
Hoffman, Joseph I., Fraser Simpson, Patrice David, Jolianne M. Rijks, Thijs Kuiken, Michael A. S. Thorne, Robert C. Lacy, and Kanchon K. Dasmahapatra. "High-throughput sequencing reveals inbreeding depression in a natural population." Proceedings of the National Academy of Sciences 111, no. 10 (February 28, 2014): 3775–80. http://dx.doi.org/10.1073/pnas.1318945111.
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Proxy measures of genome-wide heterozygosity based on approximately 10 microsatellites have been used to uncover heterozygosity fitness correlations (HFCs) for a wealth of important fitness traits in natural populations. However, effect sizes are typically very small and the underlying mechanisms remain contentious, as a handful of markers usually provides little power to detect inbreeding. We therefore used restriction site associated DNA (RAD) sequencing to accurately estimate genome-wide heterozygosity, an approach transferrable to any organism. As a proof of concept, we first RAD sequenced oldfield mice (Peromyscus polionotus) from a known pedigree, finding strong concordance between the inbreeding coefficient and heterozygosity measured at 13,198 single-nucleotide polymorphisms (SNPs). When applied to a natural population of harbor seals (Phoca vitulina), a weak HFC for parasite infection based on 27 microsatellites strengthened considerably with 14,585 SNPs, the deviance explained by heterozygosity increasing almost fivefold to a remarkable 49%. These findings arguably provide the strongest evidence to date of an HFC being due to inbreeding depression in a natural population lacking a pedigree. They also suggest that under some circumstances heterozygosity may explain far more variation in fitness than previously envisaged.
3
Chen, Yanwu, Bin Wu, Cheng Zhang, Zhiqi Fan, Ying Chen, Bingmu Xin, and Qiong Xie. "Current Progression: Application of High-Throughput Sequencing Technique in Space Microbiology." BioMed Research International 2020 (June 22, 2020): 1–13. http://dx.doi.org/10.1155/2020/4094191.
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During a spaceflight, astronauts need to live in a spacecraft on orbit for a long time, and the relationship between humans and microorganisms in the closed environment of space is not the same as on the ground. The dynamic study of microorganisms in confined space shows that with the extension of the isolation time, harmful bacteria gradually accumulate. Monitoring and controlling microbial pollution in a confined environment system are very important for crew health and the sustainable operation of a space life support system. Culture-based assays have been used traditionally to assess the microbial loads in a spacecraft, and uncultured-based techniques are already under way according to the NASA global exploration roadmap. High-throughput sequencing technology has been used generally to study the communities of the environment and human on the ground and shows its broad prospects applied onboard. We here review the recent application of high-throughput sequencing on space microbiology and analyze its feasibility and potential as an on-orbit detection technology.
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Drees, Alissa, and Markus Fischer. "High-Throughput Selection and Characterisation of Aptamers on Optical Next-Generation Sequencers." International Journal of Molecular Sciences 22, no. 17 (August 25, 2021): 9202. http://dx.doi.org/10.3390/ijms22179202.
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Aptamers feature a number of advantages, compared to antibodies. However, their application has been limited so far, mainly because of the complex selection process. ‘High-throughput sequencing fluorescent ligand interaction profiling’ (HiTS–FLIP) significantly increases the selection efficiency and is consequently a very powerful and versatile technology for the selection of high-performance aptamers. It is the first experiment to allow the direct and quantitative measurement of the affinity and specificity of millions of aptamers simultaneously by harnessing the potential of optical next-generation sequencing platforms to perform fluorescence-based binding assays on the clusters displayed on the flow cells and determining their sequence and position in regular high-throughput sequencing. Many variants of the experiment have been developed that allow automation and in situ conversion of DNA clusters into base-modified DNA, RNA, peptides, and even proteins. In addition, the information from mutational assays, performed with HiTS–FLIP, provides deep insights into the relationship between the sequence, structure, and function of aptamers. This enables a detailed understanding of the sequence-specific rules that determine affinity, and thus, supports the evolution of aptamers. Current variants of the HiTS–FLIP experiment and its application in the field of aptamer selection, characterisation, and optimisation are presented in this review.
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Zheng, Huiquan, Dehuo Hu, Ruping Wei, Shu Yan, and Runhui Wang. "Chinese Fir Breeding in the High-Throughput Sequencing Era: Insights from SNPs." Forests 10, no. 8 (August 12, 2019): 681. http://dx.doi.org/10.3390/f10080681.
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Knowledge on population diversity and structure is of fundamental importance for conifer breeding programs. In this study, we concentrated on the development and application of high-density single nucleotide polymorphism (SNP) markers through a high-throughput sequencing technique termed as specific-locus amplified fragment sequencing (SLAF-seq) for the economically important conifer tree species, Chinese fir (Cunninghamia lanceolata). Based on the SLAF-seq, we successfully established a high-density SNP panel consisting of 108,753 genomic SNPs from Chinese fir. This SNP panel facilitated us in gaining insight into the genetic base of the Chinese fir advance breeding population with 221 genotypes for its genetic variation, relationship and diversity, and population structure status. Overall, the present population appears to have considerable genetic variability. Most (94.15%) of the variability was attributed to the genetic differentiation of genotypes, very limited (5.85%) variation occurred on the population (sub-origin set) level. Correspondingly, low FST (0.0285–0.0990) values were seen for the sub-origin sets. When viewing the genetic structure of the population regardless of its sub-origin set feature, the present SNP data opened a new population picture where the advanced Chinese fir breeding population could be divided into four genetic sets, as evidenced by phylogenetic tree and population structure analysis results, albeit some difference in membership of the corresponding set (cluster vs. group). It also suggested that all the genetic sets were admixed clades revealing a complex relationship of the genotypes of this population. With a step wise pruning procedure, we captured a core collection (core 0.650) harboring 143 genotypes that maintains all the allele, diversity, and specific genetic structure of the whole population. This generalist core is valuable for the Chinese fir advanced breeding program and further genetic/genomic studies.
6
Bao, Ergude, Fei Xie, Changjin Song, and Dandan Song. "FLAS: fast and high-throughput algorithm for PacBio long-read self-correction." Bioinformatics 35, no. 20 (March 21, 2019): 3953–60. http://dx.doi.org/10.1093/bioinformatics/btz206.
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Abstract Motivation The third generation PacBio long reads have greatly facilitated sequencing projects with very large read lengths, but they contain about 15% sequencing errors and need error correction. For the projects with long reads only, it is challenging to make correction with fast speed, and also challenging to correct a sufficient amount of read bases, i.e. to achieve high-throughput self-correction. MECAT is currently among the fastest self-correction algorithms, but its throughput is relatively small (Xiao et al., 2017). Results Here, we introduce FLAS, a wrapper algorithm of MECAT, to achieve high-throughput long-read self-correction while keeping MECAT’s fast speed. FLAS finds additional alignments from MECAT prealigned long reads to improve the correction throughput, and removes misalignments for accuracy. In addition, FLAS also uses the corrected long-read regions to correct the uncorrected ones to further improve the throughput. In our performance tests on Escherichia coli, Saccharomyces cerevisiae, Arabidopsis thaliana and human long reads, FLAS can achieve 22.0–50.6% larger throughput than MECAT. FLAS is 2–13× faster compared to the self-correction algorithms other than MECAT, and its throughput is also 9.8–281.8% larger. The FLAS corrected long reads can be assembled into contigs of 13.1–29.8% larger N50 sizes than MECAT. Availability and implementation The FLAS software can be downloaded for free from this site: https://github.com/baoe/flas. Supplementary information Supplementary data are available at Bioinformatics online.
7
Bokulich, Nicholas A., and David A. Mills. "Improved Selection of Internal Transcribed Spacer-Specific Primers Enables Quantitative, Ultra-High-Throughput Profiling of Fungal Communities." Applied and Environmental Microbiology 79, no. 8 (February 1, 2013): 2519–26. http://dx.doi.org/10.1128/aem.03870-12.
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ABSTRACTUltra-high-throughput sequencing (HTS) of fungal communities has been restricted by short read lengths and primer amplification bias, slowing the adoption of newer sequencing technologies to fungal community profiling. To address these issues, we evaluated the performance of several common internal transcribed spacer (ITS) primers and designed a novel primer set and work flow for simultaneous quantification and species-level interrogation of fungal consortia. Primer comparison and validation were predictedin silicoand by sequencing a “mock community” of mixed yeast species to explore the challenges of amplicon length and amplification bias for reconstructing defined yeast community structures. The amplicon size and distribution of this primer set are smaller than for all preexisting ITS primer sets, maximizing sequencing coverage of hypervariable ITS domains by very-short-amplicon, high-throughput sequencing platforms. This feature also enables the optional integration of quantitative PCR (qPCR) directly into the HTS preparatory work flow by substituting qPCR with these primers for standard PCR, yielding quantification of individual community members. The complete work flow described here, utilizing any of the qualified primer sets evaluated, can rapidly profile mixed fungal communities and capably reconstructed well-characterized beer and wine fermentation fungal communities.
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Christoff, Ana P., Aline FR Sereia, Camila Hernandes, and Luiz FV de Oliveira. "Uncovering the hidden microbiota in hospital and built environments: New approaches and solutions." Experimental Biology and Medicine 244, no. 6 (January 7, 2019): 534–42. http://dx.doi.org/10.1177/1535370218821857.
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Microorganisms are widely distributed all over the Earth, inhabiting very diverse natural ecosystems, from the human body to inanimate indoor environments. Until recently, the methods most commonly used to study microbes have been culture-dependent approaches relying on the phenotypic evaluation of isolates that can grow in laboratory conditions. Given the advances in molecular biology and high-throughput DNA sequencing methodologies, scientists could expand their microbiome knowledge to microorganisms that do not grow well in the laboratory or have been considered too difficult and laborious to be cultivated. Culture-independent methods such as direct DNA sequencing can be performed for many samples at once, revealing the entire microbial profile of the samples and making possible the rapid characterization of the whole environmental microbiome. Investigating the microbiome profile of indoor environments such as hospitals, houses, offices and other buildings is of major concern because it could include a number of opportunistic, pathogenic or nosocomial microbes. Additionally, these environments could serve as reservoirs of virulence or antimicrobial resistance, which could be spread by humans or other vectors. High-throughput DNA sequencing has enabled large-scale microbiome screening for multiple indoor areas in a single analysis. Using this approach, we can easily track microorganisms in the environment and monitor microbiome composition related to hygiene processes or environment quality. Gaining such information and resolution regarding indoor microbiome analysis can lend very important assistance for epidemiological surveillance. Impact statement Research concerning the microbiome of indoor environments like hospitals, houses or buildings could have several implications for human health. Today, there is an ongoing shift in the paradigm of microbial analysis, from single isolated bacterial samples to entire microbiome profiles using high-throughput DNA sequencing methods. The use of sequencing methods in several studies has revealed an unprecedented microbial diversity in indoor environments, leading to a larger comprehension of the entire microbiome context. Here, we present a review of these microbiome studies using high-throughput DNA sequencing, including some new approaches and ideas that can be broadly applied in microbial tracking and epidemiological surveillance of indoor environments.
9
Schorderet, Daniel F., Alexandra Iouranova, Tatiana Favez, Leila Tiab, and Pascal Escher. "IROme, a New High-Throughput Molecular Tool for the Diagnosis of Inherited Retinal Dystrophies." BioMed Research International 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/198089.
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The molecular diagnosis of retinal dystrophies is difficult because of the very important number of genes implicated and is rarely helped by genotype-phenotype correlations. This prompted us to develop IROme, a custom designed in solution-based targeted exon capture assay (SeqCap EZ Choice library, Roche NimbleGen) for 60 retinitis pigmentosa-linked genes and three candidate genes (942 exons). Pyrosequencing was performed on a Roche 454 GS Junior benchtop high-throughput sequencing platform. In total, 23 patients affected by retinitis pigmentosa were analyzed. Per patient, 39.6 Mb were generated, and 1111 sequence variants were detected on average, at a median coverage of 17-fold. After data filtering and sequence variant prioritization, disease-causing mutations were identified inABCA4,CNGB1,GUCY2D,PROM1,PRPF8,PRPF31,PRPH2,RHO,RP2, andTULP1for twelve patients (55%), ten mutations having never been reported previously. Potential mutations were identified in 5 additional patients, and in only 6 patients no molecular diagnosis could be established (26%). In conclusion, targeted exon capture and next-generation sequencing are a valuable and efficient approach to identify disease-causing sequence variants in retinal dystrophies.
10
Zhao, Lili, Hongbo Li, Zhenbin Liu, Liangbin Hu, Dan Xu, Xiaolin Zhu, and Haizhen Mo. "Quality Changes and Fungal Microbiota Dynamics in Stored Jujube Fruits: Insights from High-Throughput Sequencing for Food Preservation." Foods 13, no. 10 (May 10, 2024): 1473. http://dx.doi.org/10.3390/foods13101473.
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Postharvest rot is an urgent problem affecting the storage of winter jujube. Therefore, the development of new technologies for efficient and safe preservation is very important. This study aimed to elucidate the fungal microbiota found on the epidermis of jujube during the storage period using high-throughput sequencing, as well as to monitor the changes in quality indexes throughout this period. Through internal transcribed spacer (ITS) sequencing, we identified two phyla (Basidiomycota and Ascomycota) and six genera (Cryptococcus, Bulleromyces, Sporidiobolus, Alternaria, Pseudozyma, and Sporobolomyces), which potentially contribute to the spoilage and deterioration of jujube, referred to as “core fungal taxa”. A high correlation was further found between preservation indices (including decay rate, firmness, and total soluble solids) and the growth of multiple core fungi over time. These findings will provide insights and a theoretical basis for further research on preservation techniques related to biological control during date fruit storage.
11
Robin, Ferrari, Sakuntala Ale, Aysha Patel, Mikel Valgañón, Hui En Foong, Mary Alikian, Kikkeri Naresh, et al. "Targeted High-Throughput Sequencing For The Detection Of Mutations Associated With Myeloproliferative Neoplasms." Blood 122, no. 21 (November 15, 2013): 1613. http://dx.doi.org/10.1182/blood.v122.21.1613.1613.
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Abstract Background Myeloproliferative neoplasms (MPNs) are clonal hematopoietic stem cell disorders characterized by the proliferation of one or more myeloid cell lineages. Polycythemia vera (PV), essential thrombocythemia (ET) and primary myelofibrosis (PMF) are the classical types of Philadelphia negative MPN. The JAK2 V617F missense mutation is found in 95% of patients with PV and in 50-60% of patients with PMF or ET. Molecular screening for JAK2 V617F mutation in suspected MPN patients by pyrosequencing has become routine method in diagnostic services. With the introduction of new methods of screening, a growing number of mutations have been described in a range of genes that code for receptor structure proteins (MPL, JAK2 exon 12), intracellular signalling proteins (CBL, SH2B3, NF1, SOCS1/3), proteins involved in leukemic progression (TP53, NRAS/KRAS, NF1, IDH1/2), or epigenetic modifications (EZH2, ASXL1, TET2). Molecular genetic screening for these targets in JAK2 V617F negative cases can be laborious, time-consuming and expensive, but the advent of benchtop-class high-throughput sequencers and custom target enrichment platforms gives the opportunity to test all relevant mutations in multiple genes in a single assay. Aims: To evaluate the Ion Torrent PGM high-throughput sequencer and custom AmpliSeq capture platform for the screening of most relevant MPN associated mutations in JAK2 V617F negative cases and validate candidate mutations using pyrosequencing. Methods 32 DNA samples (30 JAK2 V617F negative by pyrosequencing, 1 positive, 1 not tested) from patients with MPN disorders (thrombocytosis, neutrophilia or polycythemia) were screened (with appropriate ethical consent) for mutations using the Ion Torrent PGM sequencing platform. AmpliSeq multiplex primers were used for the target capture and the panel was designed via the online portal (v1.2), targeting 23 regions of 13 genes associated with MPN. The workflow involved library preparation and multiplex sample pooling following qPCR quantification (16 samples per run), emulsion PCR template preparation, Ion 318 chip loading and sequencing. Alignment and variant calling was via the Torrent Server 3.6.2 plugins, using custom coverage and hot-spot files to define the regions of interest. Variant calls were visualised using IGV and UCSC, and functionally annotated using CONDEL, Mutation Assessor and PROVEAN. Results 31 of the 32 samples were successfully sequenced, with a mean depth of 1049 reads and the FASTQC plugin indicated good quality sequencing metrics. All JAK2 V617F negative samples were called V617F negative by the PGM. The V671F positive control sample was called at a frequency of 18.1% (19% by pyrosequencing). The untested sample was called positive (10%) for JAK2 V617F and this was validated using pyrosequencing (11%). No MPL or JAK2 exon 12 mutations were detected. Novel SNPs were seen in CBL (Chr11:119149062; G>A; intron 8-9), JAK2 (Chr9:5072649; T>C; intron 13-14), SOCS3 (Chr17:76354148; C>G; 3’UTR) and SH2B3 [(Chr12: 111856076; C>T; p.R43C) and (Chr12: 111856105; T>G; p.H52Q); both in exon 2]. Of these, the SH2B3 variants were flagged as deleterious (H52Q) and highly deleterious (R43C: SIFT=0; PPH2=0.998). Five samples (4 het, 1 hom) had a SNP in IDH1 associated with poor outcome in AML (rs11554137; MAF=0.05) and a further 6 samples had variants flagged as deleterious by at least one of the annotation platforms: one in SH2B3 [p.186I (rs183913232 )] and five in TET2 [2 samples with p.G355D (rs61744960); 2 with p.L34F (rs111948941) and one p.Y867H (COSM327337)]. Additionally, one sample with a TET2 L34F also had a COSMIC annotated JAK2splice site variant (c.1864+14C>T; COSM88203). Summary This study shows the ability of the Ion Torrent PGM and AmpliSeq platforms to analyse qualitatively and quantitatively multiple samples for multiple genes with good accuracy and specificity (no false positives for V617F), making this qualitative and quantitative method more time and cost-effective than traditional sequencing techniques. Additionally, several potentially disease-associated variants were detected, which would have been missed by conventional MPN screening strategies and we are proposing to roll this approach out as a diagnostic screening in our MPN clinic in the very near future. Disclosures: Milojkovic: BMS: Honoraria; Pfizer: Honoraria; Ariad: Honoraria; Novartis: Honoraria. Apperley:Novartis: Honoraria, Research Funding; Bristol Myers Squibb: Honoraria; Pfizer, Ariad: Honoraria (not direct from company), Honoraria (not direct from company) Other.
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Li, Jing, Bertrand Llorente, Gianni Liti, and Jia-Xing Yue. "RecombineX: A generalized computational framework for automatic high-throughput gamete genotyping and tetrad-based recombination analysis." PLOS Genetics 18, no. 5 (May 9, 2022): e1010047. http://dx.doi.org/10.1371/journal.pgen.1010047.
Abstract:
Meiotic recombination is an essential biological process that ensures faithful chromosome segregation and promotes parental allele shuffling. Tetrad analysis is a powerful approach to quantify the genetic makeups and recombination landscapes of meiotic products. Here we present RecombineX (https://github.com/yjx1217/RecombineX), a generalized computational framework that automates the full workflow of marker identification, gamete genotyping, and tetrad-based recombination profiling based on any organism or genetic background with batch processing capability. Aside from conventional reference-based analysis, RecombineX can also perform analysis based on parental genome assemblies, which facilitates analyzing meiotic recombination landscapes in their native genomic contexts. Additional features such as copy number variation profiling and missing genotype inference further enhance downstream analysis. RecombineX also includes a dedicate module for simulating the genomes and reads of recombinant tetrads, which enables fine-tuned simulation-based hypothesis testing. This simulation module revealed the power and accuracy of RecombineX even when analyzing tetrads with very low sequencing depths (e.g., 1-2X). Tetrad sequencing data from the budding yeast Saccharomyces cerevisiae and green alga Chlamydomonas reinhardtii were further used to demonstrate the accuracy and robustness of RecombineX for organisms with both small and large genomes, manifesting RecombineX as an all-around one stop solution for future tetrad analysis. Interestingly, our re-analysis of the budding yeast tetrad sequencing data with RecombineX and Oxford Nanopore sequencing revealed two unusual structural rearrangement events that were not noticed before, which exemplify the occasional genome instability triggered by meiosis.
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Correia, Damien, Olivia Doppelt-Azeroual, Jean-Baptiste Denis, Mathias Vandenbogaert, and Valérie Caro. "MetaGenSense : A web application for analysis and visualization of high throughput sequencing metagenomic data." F1000Research 4 (April 2, 2015): 86. http://dx.doi.org/10.12688/f1000research.6139.1.
Abstract:
The detection and characterization of emerging infectious agents has been a continuing public health concern. High Throughput Sequencing (HTS) or Next-Generation Sequencing (NGS) technologies have proven to be promising approaches for efficient and unbiased detection of pathogens in complex biological samples, providing access to comprehensive analyses. As NGS approaches typically yield millions of putatively representative reads per sample, efficient data management and visualization resources have become mandatory. Most usually, those resources are implemented through a dedicated Laboratory Information Management System (LIMS), solely to provide perspective regarding the available information. We developed an easily deployable web-interface, facilitating management and bioinformatics analysis of metagenomics data-samples. It was engineered to run associated and dedicated Galaxy workflows for the detection and eventually classification of pathogens. The web application allows easy interaction with existing Galaxy metagenomic workflows, facilitates the organization, exploration and aggregation of the most relevant sample-specific sequences among millions of genomic sequences, allowing them to determine their relative abundance, and associate them to the most closely related organism or pathogen. The user-friendly Django-Based interface, associates the users’ input data and its metadata through a bio-IT provided set of resources (a Galaxy instance, and both sufficient storage and grid computing power). Galaxy is used to handle and analyze the user’s input data from loading, indexing, mapping, assembly and DB-searches. Interaction between our application and Galaxy is ensured by the BioBlend library, which gives API-based access to Galaxy’s main features. Metadata about samples, runs, as well as the workflow results are stored in the LIMS. For metagenomic classification and exploration purposes, we show, as a proof of concept, that integration of intuitive exploratory tools, like Krona for representation of taxonomic classification, can be achieved very easily. In the trend of Galaxy, the interface enables the sharing of scientific results to fellow team members.
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Correia, Damien, Olivia Doppelt-Azeroual, Jean-Baptiste Denis, Mathias Vandenbogaert, and Valérie Caro. "MetaGenSense: A web-application for analysis and exploration of high throughput sequencing metagenomic data." F1000Research 4 (August 22, 2016): 86. http://dx.doi.org/10.12688/f1000research.6139.2.
Abstract:
The detection and characterization of emerging infectious agents has been a continuing public health concern. High Throughput Sequencing (HTS) or Next-Generation Sequencing (NGS) technologies have proven to be promising approaches for efficient and unbiased detection of pathogens in complex biological samples, providing access to comprehensive analyses. As NGS approaches typically yield millions of putatively representative reads per sample, efficient data management and visualization resources have become mandatory. Most usually, those resources are implemented through a dedicated Laboratory Information Management System (LIMS), solely to provide perspective regarding the available information. We developed an easily deployable web-interface, facilitating management and bioinformatics analysis of metagenomics data-samples. It was engineered to run associated and dedicated Galaxy workflows for the detection and eventually classification of pathogens. The web application allows easy interaction with existing Galaxy metagenomic workflows, facilitates the organization, exploration and aggregation of the most relevant sample-specific sequences among millions of genomic sequences, allowing them to determine their relative abundance, and associate them to the most closely related organism or pathogen. The user-friendly Django-Based interface, associates the users’ input data and its metadata through a bio-IT provided set of resources (a Galaxy instance, and both sufficient storage and grid computing power). Galaxy is used to handle and analyze the user’s input data from loading, indexing, mapping, assembly and DB-searches. Interaction between our application and Galaxy is ensured by the BioBlend library, which gives API-based access to Galaxy’s main features. Metadata about samples, runs, as well as the workflow results are stored in the LIMS. For metagenomic classification and exploration purposes, we show, as a proof of concept, that integration of intuitive exploratory tools, like Krona for representation of taxonomic classification, can be achieved very easily. In the trend of Galaxy, the interface enables the sharing of scientific results to fellow team members.
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Correia, Damien, Olivia Doppelt-Azeroual, Jean-Baptiste Denis, Mathias Vandenbogaert, and Valérie Caro. "MetaGenSense: A web-application for analysis and exploration of high throughput sequencing metagenomic data." F1000Research 4 (December 1, 2016): 86. http://dx.doi.org/10.12688/f1000research.6139.3.
Abstract:
The detection and characterization of emerging infectious agents has been a continuing public health concern. High Throughput Sequencing (HTS) or Next-Generation Sequencing (NGS) technologies have proven to be promising approaches for efficient and unbiased detection of pathogens in complex biological samples, providing access to comprehensive analyses. As NGS approaches typically yield millions of putatively representative reads per sample, efficient data management and visualization resources have become mandatory. Most usually, those resources are implemented through a dedicated Laboratory Information Management System (LIMS), solely to provide perspective regarding the available information. We developed an easily deployable web-interface, facilitating management and bioinformatics analysis of metagenomics data-samples. It was engineered to run associated and dedicated Galaxy workflows for the detection and eventually classification of pathogens. The web application allows easy interaction with existing Galaxy metagenomic workflows, facilitates the organization, exploration and aggregation of the most relevant sample-specific sequences among millions of genomic sequences, allowing them to determine their relative abundance, and associate them to the most closely related organism or pathogen. The user-friendly Django-Based interface, associates the users’ input data and its metadata through a bio-IT provided set of resources (a Galaxy instance, and both sufficient storage and grid computing power). Galaxy is used to handle and analyze the user’s input data from loading, indexing, mapping, assembly and DB-searches. Interaction between our application and Galaxy is ensured by the BioBlend library, which gives API-based access to Galaxy’s main features. Metadata about samples, runs, as well as the workflow results are stored in the LIMS. For metagenomic classification and exploration purposes, we show, as a proof of concept, that integration of intuitive exploratory tools, like Krona for representation of taxonomic classification, can be achieved very easily. In the trend of Galaxy, the interface enables the sharing of scientific results to fellow team members.
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da Cunha, Bernardo Ribeiro, Paulo Zoio, Luís P. Fonseca, and Cecília R. C. Calado. "Technologies for High-Throughput Identification of Antibiotic Mechanism of Action." Antibiotics 10, no. 5 (May 12, 2021): 565. http://dx.doi.org/10.3390/antibiotics10050565.
Abstract:
There are two main strategies for antibiotic discovery: target-based and phenotypic screening. The latter has been much more successful in delivering first-in-class antibiotics, despite the major bottleneck of delayed Mechanism-of-Action (MOA) identification. Although finding new antimicrobial compounds is a very challenging task, identifying their MOA has proven equally challenging. MOA identification is important because it is a great facilitator of lead optimization and improves the chances of commercialization. Moreover, the ability to rapidly detect MOA could enable a shift from an activity-based discovery paradigm towards a mechanism-based approach. This would allow to probe the grey chemical matter, an underexplored source of structural novelty. In this study we review techniques with throughput suitable to screen large libraries and sufficient sensitivity to distinguish MOA. In particular, the techniques used in chemical genetics (e.g., based on overexpression and knockout/knockdown collections), promoter-reporter libraries, transcriptomics (e.g., using microarrays and RNA sequencing), proteomics (e.g., either gel-based or gel-free techniques), metabolomics (e.g., resourcing to nuclear magnetic resonance or mass spectrometry techniques), bacterial cytological profiling, and vibrational spectroscopy (e.g., Fourier-transform infrared or Raman scattering spectroscopy) were discussed. Ultimately, new and reinvigorated phenotypic assays bring renewed hope in the discovery of a new generation of antibiotics.
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Connon, Stephanie A., and Stephen J. Giovannoni. "High-Throughput Methods for Culturing Microorganisms in Very-Low-Nutrient Media Yield Diverse New Marine Isolates." Applied and Environmental Microbiology 68, no. 8 (August 2002): 3878–85. http://dx.doi.org/10.1128/aem.68.8.3878-3885.2002.
Abstract:
ABSTRACT Microbial diversity studies based on the cloning and sequencing of DNA from nature support the conclusion that only a fraction of the microbial diversity is currently represented in culture collections. Out of over 40 known prokaryotic phyla, only half have cultured representatives. In an effort to culture the uncultured phylotypes from oligotrophic marine ecosystems, we developed high-throughput culturing procedures that utilize the concept of extinction culturing to isolate cultures in small volumes of low-nutrient media. In these experiments, marine bacteria were isolated and cultivated at in situ substrate concentrations—typically 3 orders of magnitude less than common laboratory media. Microtiter plates and a newly developed procedure for making cell arrays were employed to raise the throughput rate and lower detection sensitivity, permitting cell enumeration from 200-μl aliquots of cultures with densities as low as 103 cells/ml. Approximately 2,500 extinction cultures from 11 separate samplings of marine bacterioplankton were screened over the course of 3 years. Up to 14% of the cells collected from coastal seawater were cultured by this method, which was 14- to 1,400-fold higher than the numbers obtained by traditional microbiological culturing techniques. Among the microorganisms cultured were four unique cell lineages that belong to previously uncultured or undescribed marine Proteobacteria clades known from environmental gene cloning studies. These cultures are related to the clades SAR11 (α subclass), OM43 (β subclass), SAR92 (γ subclass), and OM60/OM241 (γ subclass). This method proved successful for the cultivation of previously uncultured marine bacterioplankton that have consistently been found in marine clone libraries.
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Hannan, Patrick, Mark Nicol, and Maia Lesosky. "A review of common methods used in the analysis of human microbiome sequencing data." F1000Research 13 (April 23, 2024): 369. http://dx.doi.org/10.12688/f1000research.110605.1.
Abstract:
The past two decades have seen a rapid rise in the development and use of sequencing technologies. The advent of high-throughput sequencing (HTS) has allowed scientists sequence the genomic content of entire microbial communities rapidly and affordably. Methods for data management, visualization, and analysis of this microbiome sequencing data are now widespread in open and closed source software tools. In this review, we identify common analysis methods used in microbiome sequencing studies, including methods for normalisation of abundance table data, visualization of high-dimensional microbiome data and the analysis of longitudinal microbiome sequencing data. In particular we find that a very small proportion of metagenomic studies made use of compositional data analysis methods and none that made use of compositional methods for longitudinal microbiome data.
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Isom, S. C., J. R. Stevens, R. Li, L. D. Spate, W. G. Spollen, and R. S. Prather. "143 TRANSCRIPTIONAL PROFILING BY HIGH-THROUGHPUT SEQUENCING OF PORCINE PRE- AND PERI-IMPLANTATION EMBRYOS." Reproduction, Fertility and Development 24, no. 1 (2012): 184. http://dx.doi.org/10.1071/rdv24n1ab143.
Abstract:
Significant embryo mortality occurs at or around the time of implantation or attachment in virtually all mammalian species studied to date, even in naturally conceived embryos. Embryos resulting from assisted reproductive technologies (ART) are even more susceptible to peri-implantation failure. Herein we describe our effort to characterise the transcriptomes of embryonic disc (ED) and trophoblast (TE) cells from porcine embryos derived from AI, IVF, parthenogenetic oocyte activation (PA) and somatic cell nuclear transfer (NT) on Days 10, 12 and 14 of gestation. The IVF, PA and somatic cell NT embryos were generated using in vitro–matured oocytes, cultured overnight in vitro and then transferred at the 1- to 2-cell stage into appropriately synchronized recipient gilts. On the appropriate collection day, embryos were flushed from the uterus and ED was separated from TE by mechanical dissection. Double-stranded cDNA from the collected samples was sequenced using the GAII platform from Illumina (San Diego, CA, USA). The resulting sequencing reads were aligned to a custom swine transcriptome database (see Isom et al. 2010). A generalized linear model was fit for each of 41 693 genomic regions, for ED and TE samples separately, accounting for embryo type, gestation day and their interaction and using total lane read count as a normalizing offset. Genes with significant embryo type differences (controlling the false discovery rate at 0.10) were subsequently tested for differences between IVF and each of AI, PA and NT. Those genes with significant post hoc differences (either up- or down-regulated compared with IVF) were characterised in terms of gene ontologies and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways using a gene set enrichment test. Bone morphogenetic protein signalling was down-regulated (KEGG; P = 0.0099; adjusted to control for FDR at 0.05) in the ED of IVF embryos when compared with AI embryos. In TE cells from IVF embryos, ubiquitin-mediated proteolysis and ErbB signalling (adj P = 0.031 for both pathways) were aberrantly regulated when compared with AI embryos. Of particular interest is the observation that expression of genes involved in chromatin modification (GO:BiologicalProcess; q-value = 0.00005) and epigenetic regulation of transcription (q = 0.00007) was very significantly disrupted in inner cell mass cells from NT embryos compared with IVF embryos. Surprisingly, no such disruption of the epigenetic machinery was observed in the TE cells from NT embryos. In summary, we have used high-throughput sequencing technologies to compare gene expression profiles of various ART embryo types during peri-implantation development. We expect that these data will provide important insight into the root causes of (and possible opportunities for mitigation of) suboptimal development of embryos derived from ART. Funding was received from NIH R01 RR013438 and Food for the 21st Century (RSP) and the Utah Agricultural Experiment Station (UTA00151 and UTA00560 for S. C. Isom and J. R. Stevens, respectively).
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Päll, Taavi, Hannes Luidalepp, Tanel Tenson, and Ülo Maiväli. "A field-wide assessment of differential expression profiling by high-throughput sequencing reveals widespread bias." PLOS Biology 21, no. 3 (March 2, 2023): e3002007. http://dx.doi.org/10.1371/journal.pbio.3002007.
Abstract:
We assess inferential quality in the field of differential expression profiling by high-throughput sequencing (HT-seq) based on analysis of datasets submitted from 2008 to 2020 to the NCBI GEO data repository. We take advantage of the parallel differential expression testing over thousands of genes, whereby each experiment leads to a large set of p-values, the distribution of which can indicate the validity of assumptions behind the test. From a well-behaved p-value set π0, the fraction of genes that are not differentially expressed can be estimated. We found that only 25% of experiments resulted in theoretically expected p-value histogram shapes, although there is a marked improvement over time. Uniform p-value histogram shapes, indicative of <100 actual effects, were extremely few. Furthermore, although many HT-seq workflows assume that most genes are not differentially expressed, 37% of experiments have π0-s of less than 0.5, as if most genes changed their expression level. Most HT-seq experiments have very small sample sizes and are expected to be underpowered. Nevertheless, the estimated π0-s do not have the expected association with N, suggesting widespread problems of experiments with controlling false discovery rate (FDR). Both the fractions of different p-value histogram types and the π0 values are strongly associated with the differential expression analysis program used by the original authors. While we could double the proportion of theoretically expected p-value distributions by removing low-count features from the analysis, this treatment did not remove the association with the analysis program. Taken together, our results indicate widespread bias in the differential expression profiling field and the unreliability of statistical methods used to analyze HT-seq data.
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Al Rwahnih, Maher, Adib Rowhani, Nathaniel Westrick, Kristian Stevens, Alfredo Diaz-Lara, Florent P. Trouillas, John Preece, Craig Kallsen, Kristen Farrar, and Deborah Golino. "Discovery of Viruses and Virus-Like Pathogens in Pistachio using High-Throughput Sequencing." Plant Disease 102, no. 7 (July 2018): 1419–25. http://dx.doi.org/10.1094/pdis-12-17-1988-re.
Abstract:
Pistachio (Pistacia vera L.) trees from the National Clonal Germplasm Repository (NCGR) and orchards in California were surveyed for viruses and virus-like agents by high-throughput sequencing (HTS). Analyses of sequence information from 60 trees identified a novel virus, provisionally named “Pistachio ampelovirus A” (PAVA), in the NCGR that showed low amino acid sequence identity (approximately 42%) compared with members of the genus Ampelovirus (family Closteroviridae). A putative viroid, provisionally named “Citrus bark cracking viroid-pistachio” (CBCVd-pis), was also found in the NCGR and showed approximately 87% similarity to Citrus bark cracking viroid (CBCVd, genus Cocadviroid, family Pospiviroidae). Both PAVA and CBCVd-pis were graft transmissible to healthy UCB-1 hybrid rootstock seedlings (P. atlantica × P. integerrima). A field survey of 123 trees from commercial orchards found no incidence of PAVA but five (4%) samples were infected with CBCVd-pis. Of 675 NCGR trees, 16 (2.3%) were positive for PAVA and 172 (25.4%) were positive for CBCVd-pis by reverse-transcription polymerase chain reaction. Additionally, several contigs across multiple samples exhibited significant sequence similarity to a number of other plant virus species in different families. These findings require further study and confirmation. This study establishes the occurrence of viral and viroid populations infecting pistachio trees.
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Ferdous, Tahsin, and Mohammad Ohid Ullah. "An Overview of RNA-seq Data Analysis." Journal of Biology and Life Science 8, no. 2 (August 2, 2017): 57. http://dx.doi.org/10.5296/jbls.v8i2.11255.
Abstract:
Latest breakthrough in high-throughput DNA sequencing have been launched different arenas for transcriptome analyses, jointly named RNA-seq (RNA-sequencing). It exposes the existence and amount of RNA in a biotic sample at a specific time by utilizing next generation sequencing (NGS). In this review, we aimed to explore the several methods which are applied in analyzing RNA-seq data. We also discussed its importance over microarray data. As establishment of several methods have already taken place to analyze RNA-seq data, therefore, further analysis is very essential to select the best one to avoid false positive outcomes.
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Gao, Bingmiao, Chao Peng, Yabing Zhu, Yuhui Sun, Tian Zhao, Yu Huang, and Qiong Shi. "High Throughput Identification of Novel Conotoxins from the Vermivorous Oak Cone Snail (Conus quercinus) by Transcriptome Sequencing." International Journal of Molecular Sciences 19, no. 12 (December 5, 2018): 3901. http://dx.doi.org/10.3390/ijms19123901.
Abstract:
The primary objective of this study was to realize the large-scale discovery of conotoxin sequences from different organs (including the venom duct, venom bulb and salivary gland) of the vermivorous Oak cone snail, Conus quercinus. Using high-throughput transcriptome sequencing, we identified 133 putative conotoxins that belong to 34 known superfamilies, of which nine were previously reported while the remaining 124 were novel conotoxins, with 17 in new and unassigned conotoxin groups. A-, O1-, M-, and I2- superfamilies were the most abundant, and the cysteine frameworks XIII and VIII were observed for the first time in the A- and I2-superfamilies. The transcriptome data from the venom duct, venom bulb and salivary gland showed considerable inter-organizational variations. Each organ had many exclusive conotoxins, and only seven of all the inferred mature peptides were common in the three organs. As expected, most of the identified conotoxins were synthesized in the venom duct at relatively high levels; however, a number of conotoxins were also identified in the venom bulb and the salivary gland with very low transcription levels. Therefore, various organs have different conotoxins with high diversity, suggesting greater contributions from several organs to the high-throughput discovery of new conotoxins for future drug development.
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Emerson, Ryan, James Matthew, Harlan Robins, and Joseph Leventhal. "Defining the alloreactive T cell repertoire using high-throughput sequencing of mixed lymphocyte culture (TRAN3P.884)." Journal of Immunology 192, no. 1_Supplement (May 1, 2014): 202.23. http://dx.doi.org/10.4049/jimmunol.192.supp.202.23.
Abstract:
Abstract The cellular immune response is a major barrier to patient tolerance of allografts. Positive followed by negative selection in the thymus ensures that T cell populations have some binding affinity for self-HLA, but culls T cells with high specificity for peptides presented on self-HLA. However, in the context of a patient with an allograft, these processes also allow for mature T cells with off-target specificity for self-peptides presented on allo-HLA. Currently, the breadth of the alloreactive T cell repertoire is unknown, as well as whether the alloreactive T cell repertoire is stable over time. We have used high-throughput sequencing to characterize the alloreactive T cell repertoire in three pairs of healthy adults using mixed lymphocyte culture, analyzing 4 reactions per pair: duplicate MLR reactions at baseline followed by duplicate MLR reactions 3 months later. Our results indicate that thousands of T cell clones proliferate in mixed lymphocyte culture, suggesting a very broad alloreactive T cell repertoire. This repertoire is consistent across biological replicates and across a span of three months, and is dominated by relatively high-abundance T cell clones. Our results suggest the existence of a broad alloreactive T cell repertoire consisting mainly of expanded memory T cells which remain stable over time. The presence of a large, stable population alloreactive T cells should allow for long-term tracking of alloreactive clones in patients receiving allografts.
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Smith, S., T. Joss, and A. Stow. "Successful development of microsatellite markers in a challenging species: the horizontal borer Austroplatypus incompertus (Coleoptera: Curculionidae)." Bulletin of Entomological Research 101, no. 5 (April 11, 2011): 551–55. http://dx.doi.org/10.1017/s0007485311000137.
Abstract:
AbstractThe analysis of microsatellite loci has allowed significant advances in evolutionary biology and pest management. However, until very recently, the potential benefits have been compromised by the high costs of developing these neutral markers. High-throughput sequencing provides a solution to this problem. We describe the development of 13 microsatellite markers for the eusocial ambrosia beetle, Austroplatypus incompertus, a significant pest of forests in southeast Australia. The frequency of microsatellite repeats in the genome of A. incompertus was determined to be low, and previous attempts at microsatellite isolation using a traditional genomic library were problematic. Here, we utilised two protocols, microsatellite-enriched genomic library construction and high-throughput 454 sequencing and characterised 13 loci which were polymorphic among 32 individuals. Numbers of alleles per locus ranged from 2 to 17, and observed and expected heterozygosities from 0.344 to 0.767 and from 0.507 to 0.860, respectively. These microsatellites have the resolution required to analyse fine-scale colony and population genetic structure. Our work demonstrates the utility of next-generation 454 sequencing as a method for rapid and cost-effective acquisition of microsatellites where other techniques have failed, or for taxa where marker development has historically been both complicated and expensive.
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Guzzon, Raffaele, Elena Franciosi, and Annita Toffanin. "Investigation by High-Throughput Sequencing Methods of Microbiota Dynamics in Spontaneous Fermentation of Abruzzo (South Italy) Wines." Agronomy 12, no. 12 (December 7, 2022): 3104. http://dx.doi.org/10.3390/agronomy12123104.
Abstract:
Spontaneous wine fermentation is a meaningful topic that cannot be disregarded among winemakers and consumers due to the peculiarity of the organoleptic profile that it confers to the wine. Nevertheless, in this process the activity of indigenous microorganisms might be a threat. We studied the evolution of the spontaneous fermentation process in a traditional Italian winery in order to understand the origin of spoilage microorganisms, and to characterize the peculiarity of the microbiota associated with spontaneous fermentation. Six Trebbiano and Montepulciano wine production chains were monitored by plate counts made by OIV methods and by Illumina MiSeq technique. Despite some compositional deficiencies, all grape musts were characterized by a highly concentrated microbial population. Non-Saccharomyces yeasts revealed an unexpected tolerance to ethanol, which has contributed to the evolution of alcoholic fermentation. Lactic bacteria were detectable from the very first steps of the winemaking process, with a prevalence of Leuconostoc spp. which is nowadays, rarely isolated in wine. The combination between culture-dependent and high-throughput sequencing (HTS) approaches allowed to estimate microbial diversity and growth dynamics in wine fermentations of different grape varieties and under different treatments; these results could be used by winemakers as a starting point to drive a more mindful, accurate and, controlled fermentation process and to set up the most suitable environmental conditions to enhance wine singularities.
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Yang, Hui, Guillermo Garcia-Manero, Guillermo Montalban-Bravo, Kelly S. Chien, Awdesh Kalia, Zhenya Tang, Yue Wei, et al. "High-Throughput Characterization of Cytogenomic Heterogeneity of MDS Using High-Resolution Optical Genome Mapping." Blood 138, Supplement 1 (November 5, 2021): 105. http://dx.doi.org/10.1182/blood-2021-154005.
Abstract:
Abstract Introduction Introduction of next-generation sequencing has defined the somatic mutational landscape in MDS. Comprehensive high-throughput structural variant profiling (SVP) is as important as mutation profiling in characterizing MDS clonal architecture since these large genomic aberrations have already shown to be critical for diagnosis and risk-stratification of MDS. A subset (MECOM, KMT2A rearrangements) are therapeutic targets in clinical trials. At this time, technical advances in SVP for copy number alterations (CNAs) and fusions have not been congruent with mutation profiling due to the inability of short-read (150bp) NGS to detect SVs. Currently available long-read (10-20Kbp) and whole genome sequencing cannot detect all SVs due to the presence of repeat sequences. Hence, conventional karyotyping (CK) remains the gold standard. Optical genome mapping (OGM) is a novel single-platform technique that measures ultra-long-range sequence patterns (>300Kbp), thereby unaffected by repeat sequences, enabling unbiased evaluation of all types of SVs at a high resolution. Here, we performed comprehensive SVP and mutation profiling in a large well-characterized cohort of MDS. Methods We selected samples with available fresh/frozen BM cells from consecutive treatment-naïve MDS pts who also underwent standard-of-care tests (CK, FISH, targeted 81-gene NGS for mutations). For OGM, ultra-high-molecular-weight-DNA was extracted, followed by labeling, linearization and imaging of DNA (Saphyr, Bionano) [median coverage:>300X]. The results were analyzed using de novo (>500 bp), rare variant (>5000 bp) and copy number (>500,000 bp) pipelines. The data was compared against 200 healthy controls to exclude common germline SVs. Clinical significance of the SVs was determined based on the location/overlap with the coding region of myeloid malignancy associated genes. The detection sensitivity was 10%. Results There were 76 treatment naïve MDS patients. Baseline characteristics, comprehensive cytogenetic scoring system (CCSS) and R-IPPS risk categories and somatic mutations are in Fig 1. OGM identified all clonal abnormalities detected by CK [CNAs, inversions, inter/intra-chromosomal translocations, dicentric, complex derivative chromosomes]. Precise mapping of SVs by OGM at gene-level allowed determining the status of clinically informative biomarkers such as TET2, MECOM, TP53 and KMT2A, without the need for confirmatory assays. Detailed gene-level characterization of different SVs included KMT2A-ELL [t(11;19)] in MDS with WT1 mut, t(9;11) with SYTL2 fusion (and not KMT2A), der(1;7) leading to del(7q) in MDS with GATA2 mut/IDH2 mutand t(1;3)(p36;q21) rearrangements with potential PRDM16 disruption in SF3B1 mut/RUNX1 mutMDS, among others. Using OGM, we mapped the sequence patterns in both samples with IM with high level of confidence. Additionally, OGM identified 23 cryptic, clinically significant SVs in 14 (18%) of 76 pts. These included deletions of TET2, KMT2A, and del(5q), KMT2A amplification in MDS with FLT3-ITD/DNMT3A mut/RAS mut, NUP98-PRRX2, MECOM rearrangement in TET mut mutated NK-MDS. In addition, there were SVs of uncertain significance: duplications of chr1 (PDE41P), deletions of chr21 (involving RUNX1), chr2 (DNMT3A, ASXL2), chr12 (ETV6) and chr22 (EP300) and der(16)t(12;16)(q21.1;q12.1). These cryptic SVs were noted across all R-IPSS risk categories (highest yield in very-low and low R-IPSS) and across all cytogenetic risk-groups (very-good to very-poor). In complex karyotype setting, OGM could resolve the markers and additional genetic material, and in most cases, showed a much higher the degree of complexity within the genome than was apparent by CK. Four pts showed SV patterns typical of chromothripsis/chromoplexy. The median number of mutations per pt was 1 (0-6). When compared to mutation subsets, cryptic SVs were only identified in pts with ≤3 mutations. Majority represented either MDS with TP53 mut (6, 29%) or SF3B1 mut/TET mut (deletions of TET2, KMT2A, NOTCH1 and EP300 genes). Conclusions Unbiased, high-throughput whole genome SVP revealed cryptic, clinically significant SVs in ~18% of MDS pts. OGM is a single-platform cytogenomic tool that can facilitate SVP at a gene-level resolution. This study provides strong support for further validation in expanded cohorts to guide clinical implementation and integration of SVP for routine work-up. Figure 1 Figure 1. Disclosures Wei: Daiichi Sanko: Research Funding. Kantarjian: Ipsen Pharmaceuticals: Honoraria; Amgen: Honoraria, Research Funding; Astellas Health: Honoraria; Astra Zeneca: Honoraria; AbbVie: Honoraria, Research Funding; KAHR Medical Ltd: Honoraria; NOVA Research: Honoraria; Ascentage: Research Funding; Aptitude Health: Honoraria; Novartis: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding; Jazz: Research Funding; Immunogen: Research Funding; Daiichi-Sankyo: Research Funding; BMS: Research Funding; Precision Biosciences: Honoraria; Taiho Pharmaceutical Canada: Honoraria.
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Gaafar, Yahya Z. A., Marcel Westenberg, Marleen Botermans, Krizbai László, Kris De Jonghe, Yoika Foucart, Luca Ferretti, et al. "Interlaboratory Comparison Study on Ribodepleted Total RNA High-Throughput Sequencing for Plant Virus Diagnostics and Bioinformatic Competence." Pathogens 10, no. 9 (September 12, 2021): 1174. http://dx.doi.org/10.3390/pathogens10091174.
Abstract:
High-throughput sequencing (HTS) technologies and bioinformatic analyses are of growing interest to be used as a routine diagnostic tool in the field of plant viruses. The reliability of HTS workflows from sample preparation to data analysis and results interpretation for plant virus detection and identification must be evaluated (verified and validated) to approve this tool for diagnostics. Many different extraction methods, library preparation protocols, and sequence and bioinformatic pipelines are available for virus sequence detection. To assess the performance of plant virology diagnostic laboratories in using the HTS of ribosomal RNA depleted total RNA (ribodepleted totRNA) as a diagnostic tool, we carried out an interlaboratory comparison study in which eight participants were required to use the same samples, (RNA) extraction kit, ribosomal RNA depletion kit, and commercial sequencing provider, but also their own bioinformatics pipeline, for analysis. The accuracy of virus detection ranged from 65% to 100%. The false-positive detection rate was very low and was related to the misinterpretation of results as well as to possible cross-contaminations in the lab or sequencing provider. The bioinformatic pipeline used by each laboratory influenced the correct detection of the viruses of this study. The main difficulty was the detection of a novel virus as its sequence was not available in a publicly accessible database at the time. The raw data were reanalysed using Virtool to assess its ability for virus detection. All virus sequences were detected using Virtool in the different pools. This study revealed that the ribodepletion target enrichment for sample preparation is a reliable approach for the detection of plant viruses with different genomes. A significant level of virology expertise is needed to correctly interpret the results. It is also important to improve and complete the reference data.
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Fafián-Labora, Juan A., Miriam Morente-López, Fco Javier de Toro, and María C. Arufe. "High-Throughput Screen Detects Calcium Signaling Dysfunction in Hutchinson-Gilford Progeria Syndrome." International Journal of Molecular Sciences 22, no. 14 (July 7, 2021): 7327. http://dx.doi.org/10.3390/ijms22147327.
Abstract:
Hutchinson–Gilford progeria syndrome (HGPS) is a deadly childhood disorder, which is considered a very rare disease. It is caused by an autosomal dominant mutation on the LMNA gene, and it is characterized by accelerated aging. Human cell lines from HGPS patients and healthy parental controls were studied in parallel using next-generation sequencing (NGS) to unravel new non-previously altered molecular pathways. Nine hundred and eleven transcripts were differentially expressed when comparing healthy versus HGPS cell lines from a total of 21,872 transcripts; ITPR1, ITPR3, CACNA2D1, and CAMK2N1 stood out among them due to their links with calcium signaling, and these were validated by Western blot analysis. It was observed that the basal concentration of intracellular Ca2+ was statistically higher in HGPS cell lines compared to healthy ones. The relationship between genes involved in Ca2+ signaling and mitochondria-associated membranes (MAM) was demonstrated through cytosolic calcium handling by means of an automated fluorescent plate reading system (FlexStation 3, Molecular Devices), and apoptosis and mitochondrial ROS production were examined by means of flow cytometry analysis. Altogether, our data suggest that the Ca2+ signaling pathway is altered in HGPS at least in part due to the overproduction of reactive oxygen species (ROS). Our results unravel a new therapeutic window for the treatment of this rare disease and open new strategies to study pathologies involving both accelerated and healthy aging.
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Ibaba, Jacques Davy, and Augustine Gubba. "High-Throughput Sequencing Application in the Diagnosis and Discovery of Plant-Infecting Viruses in Africa, A Decade Later." Plants 9, no. 10 (October 16, 2020): 1376. http://dx.doi.org/10.3390/plants9101376.
Abstract:
High-throughput sequencing (HTS) application in the field of plant virology started in 2009 and has proven very successful for virus discovery and detection of viruses already known. Plant virology is still a developing science in most of Africa; the number of HTS-related studies published in the scientific literature has been increasing over the years as a result of successful collaborations. Studies using HTS to identify plant-infecting viruses have been conducted in 20 African countries, of which Kenya, South Africa and Tanzania share the most published papers. At least 29 host plants, including various agricultural economically important crops, ornamentals and medicinal plants, have been used in viromics analyses and have resulted in the detection of previously known viruses and novel ones from almost any host. Knowing that the effectiveness of any management program requires knowledge on the types, distribution, incidence, and genetic of the virus-causing disease, integrating HTS and efficient bioinformatics tools in plant virology research projects conducted in Africa is a matter of the utmost importance towards achieving and maintaining sustainable food security.
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Massart, Sebastien, Michela Chiumenti, Kris De Jonghe, Rachel Glover, Annelies Haegeman, Igor Koloniuk, Petr Komínek, et al. "Virus Detection by High-Throughput Sequencing of Small RNAs: Large-Scale Performance Testing of Sequence Analysis Strategies." Phytopathology® 109, no. 3 (March 2019): 488–97. http://dx.doi.org/10.1094/phyto-02-18-0067-r.
Abstract:
Recent developments in high-throughput sequencing (HTS), also called next-generation sequencing (NGS), technologies and bioinformatics have drastically changed research on viral pathogens and spurred growing interest in the field of virus diagnostics. However, the reliability of HTS-based virus detection protocols must be evaluated before adopting them for diagnostics. Many different bioinformatics algorithms aimed at detecting viruses in HTS data have been reported but little attention has been paid thus far to their sensitivity and reliability for diagnostic purposes. Therefore, we compared the ability of 21 plant virology laboratories, each employing a different bioinformatics pipeline, to detect 12 plant viruses through a double-blind large-scale performance test using 10 datasets of 21- to 24-nucleotide small RNA (sRNA) sequences from three different infected plants. The sensitivity of virus detection ranged between 35 and 100% among participants, with a marked negative effect when sequence depth decreased. The false-positive detection rate was very low and mainly related to the identification of host genome-integrated viral sequences or misinterpretation of the results. Reproducibility was high (91.6%). This work revealed the key influence of bioinformatics strategies for the sensitive detection of viruses in HTS sRNA datasets and, more specifically (i) the difficulty in detecting viral agents when they are novel or their sRNA abundance is low, (ii) the influence of key parameters at both assembly and annotation steps, (iii) the importance of completeness of reference sequence databases, and (iv) the significant level of scientific expertise needed when interpreting pipeline results. Overall, this work underlines key parameters and proposes recommendations for reliable sRNA-based detection of known and unknown viruses.
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Zhou, Shiguo, Wen Deng, Thomas S. Anantharaman, Alex Lim, Eileen T. Dimalanta, Jun Wang, Tian Wu, et al. "A Whole-Genome Shotgun Optical Map of Yersinia pestis Strain KIM." Applied and Environmental Microbiology 68, no. 12 (December 2002): 6321–31. http://dx.doi.org/10.1128/aem.68.12.6321-6331.2002.
Abstract:
ABSTRACT Yersinia pestis is the causative agent of the bubonic, septicemic, and pneumonic plagues (also known as black death) and has been responsible for recurrent devastating pandemics throughout history. To further understand this virulent bacterium and to accelerate an ongoing sequencing project, two whole-genome restriction maps (XhoI and PvuII) of Y. pestis strain KIM were constructed using shotgun optical mapping. This approach constructs ordered restriction maps from randomly sheared individual DNA molecules directly extracted from cells. The two maps served different purposes; the XhoI map facilitated sequence assembly by providing a scaffold for high-resolution alignment, while the PvuII map verified genome sequence assembly. Our results show that such maps facilitated the closure of sequence gaps and, most importantly, provided a purely independent means for sequence validation. Given the recent advancements to the optical mapping system, increased resolution and throughput are enabling such maps to guide sequence assembly at a very early stage of a microbial sequencing project.
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O'Hara, Andrea, Michael Stephens, Ilaria DeVito, Laure Turner, Christopher Mozdzierz, Haythem Latif, and Ginger Zhou. "Abstract LB130: High-throughput RNA sequencing directly from cell lysates enables reproducible phenotypic profiling for assessing novel compounds and treatments in cancer research." Cancer Research 82, no. 12_Supplement (June 15, 2022): LB130. http://dx.doi.org/10.1158/1538-7445.am2022-lb130.
Abstract:
Abstract New oncology therapies are driven by multiple approaches, with a heavy emphasis on small-molecule therapeutics to target cancer cells and provide a therapeutic benefit to cancer patients. These small-molecule compounds can be used as a stand-alone treatment approach or may be combined with other compounds to bring enhanced effects. Compound therapeutic discovery relies heavily on high-throughput screening assays for measurement of phenotypic responses following compound treatment of oncology cell cultures which can range from very targeted assays to wide-ranging unbiased approaches. Standard whole transcriptome RNA-seq is a preferred method for unbiased measurement of phenotypic responses but is often overlooked due to limited scalability and high sample screening costs. To address these challenges, we have developed a high-throughput gene expression (HT-GEx) assay that combines a variety of strategies to enable a low-cost and high-throughput alternative to standard RNA-seq. First, a simplified workflow removes upstream RNA isolation steps and tags transcripts directly from cell lysate. This is achieved by incorporating both a sample barcode and a unique molecular index (UMI) during the reverse transcription reaction. Next, we leverage a 3’ end counting approach to enable a reduction in sequencing depth coverage (i.e. sample cost) without compromising gene detection sensitivity. With these key advances, a high-plex and high-throughput screening assay is achievable at a reduced cost by removing the need to purify RNA, tagging transcripts early in the workflow to allow pooling of samples and reducing sequencing depth. We have combined these high-throughput and cost-saving strategies and present results which confirm HT-GEx offers results on par with standard RNA-seq. Gene detection sensitivity based on number of genes detected per millions of reads is highly similar, with gene detection sensitivity saturated at approximately 2 million reads. Additionally, the number of genes detected between replicates for RNA samples and lysate samples demonstrate strong linear correlation, implying highly reproducible results. Thus, high-throughput gene expression is an ideal method for phenotypic screening in oncology cell lines following stand-alone or combined compound treatments. Citation Format: Andrea O'Hara, Michael Stephens, Ilaria DeVito, Laure Turner, Christopher Mozdzierz, Haythem Latif, Ginger Zhou. High-throughput RNA sequencing directly from cell lysates enables reproducible phenotypic profiling for assessing novel compounds and treatments in cancer research [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr LB130.
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OZER, HATICE GULCIN, YI-WEN HUANG, JIEJUN WU, JEFFREY D. PARVIN, TIM HUI-MING HUANG, and KUN HUANG. "COMPARING MULTIPLE ChIP-SEQUENCING EXPERIMENTS." Journal of Bioinformatics and Computational Biology 09, no. 02 (April 2011): 269–82. http://dx.doi.org/10.1142/s0219720011005483.
Abstract:
New high-throughput sequencing technologies can generate millions of short sequences in a single experiment. As the size of the data increases, comparison of multiple experiments on different cell lines under different experimental conditions becomes a big challenge. In this paper, we investigate ways to compare multiple ChIP-sequencing experiments. We specifically studied epigenetic regulation of breast cancer and the effect of estrogen using 50 ChIP-sequencing data from Illumina Genome Analyzer II. First, we evaluate the correlation among different experiments focusing on the total number of reads in transcribed and promoter regions of the genome. Then, we adopt the method that is used to identify the most stable genes in RT-PCR experiments to understand background signal across all of the experiments and to identify the most variable transcribed and promoter regions of the genome. We observed that the most variable genes for transcribed regions and promoter regions are very distinct. Gene ontology and function enrichment analysis on these most variable genes demonstrate the biological relevance of the results. In this study, we present a method that can effectively select differential regions of the genome based on protein-binding profiles over multiple experiments using real data points without any normalization among the samples.
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Sun, Beili, Dongrui Zhou, Jing Tu, and Zuhong Lu. "Evaluation of the Bacterial Diversity in the Human Tongue Coating Based on Genus-Specific Primers for 16S rRNA Sequencing." BioMed Research International 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/8184160.
Abstract:
The characteristics of tongue coating are very important symbols for disease diagnosis in traditional Chinese medicine (TCM) theory. As a habitat of oral microbiota, bacteria on the tongue dorsum have been proved to be the cause of many oral diseases. The high-throughput next-generation sequencing (NGS) platforms have been widely applied in the analysis of bacterial 16S rRNA gene. We developed a methodology based on genus-specific multiprimer amplification and ligation-based sequencing for microbiota analysis. In order to validate the efficiency of the approach, we thoroughly analyzed six tongue coating samples from lung cancer patients with different TCM types, and more than 600 genera of bacteria were detected by this platform. The results showed that ligation-based parallel sequencing combined with enzyme digestion and multiamplification could expand the effective length of sequencing reads and could be applied in the microbiota analysis.
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Vardi, Anna, Evangelia Stalika, Maria Karypidou, Lesley-Ann Sutton, Vasilis Bikos, Achilles Anagnostopoulos, Sarka Pospisilova, et al. "Tracing the Ontogeny of IgG-Switched CLL: High-Throughput Immunogenetic Evidence." Blood 124, no. 21 (December 6, 2014): 3285. http://dx.doi.org/10.1182/blood.v124.21.3285.3285.
Abstract:
Abstract Immunoglobulin (IG) G-switched chronic lymphocytic leukemia (G-CLL) is highly enriched for 3 stereotyped CLL subsets, utilizing either the IGHV4-34 gene, namely mutated subsets #4 and #16, or the IGHV4-39 gene, namely unmutated subset #8. These subsets, collectively accounting for ~30% of all G-CLL, are not represented within the common IgM/D variant, thus prompting speculations about distinct ontogenetic origin and/or immune triggering, as well as raising questions regarding the timing of class-switch recombination (CSR) in relation to malignant transformation. Considering the above, we sought to investigate the potential existence of B cells expressing clonotypic mu transcripts within the bulk of IgG-switched CLL cells in cases assigned to the aforementioned subsets. Using high-throughput next-generation sequencing (NGS, MiSeq Illumina), we interrogated the IgM+ B-cell repertoire of CLL subset #4 (n=8), subset #16 (n=1) and subset #8 (n=2) for the presence of clonotypic mu transcripts. PCR amplicons were generated from cDNA using a set of IGHV4/IGHM primers. The paired-end Illumina protocol allowed sequencing of the complementarity determining region 3 (CDR3) twice/read, thus increasing the accuracy of results. For 3/8 subset #4 cases multiple blood samples of the same time point were analyzed as reproducibility controls. A purpose-built bioinformatics algorithm was developed for raw NGS data processing, which included: (i) quality filtering of reads; (ii) merging of paired-end reads via local alignment; (iii) preparation of filtered-in fasta sequences for submission to the IMGT/HighV-QUEST tool; and, (iv) IMGT/HighV-QUEST metadata mining for subset-specific B-cell receptor (BcR) IG rearrangements. Subset-specific CDR3 motifs were defined according to established criteria. Overall, 7,125,958 IGHV-IGHD-IGHJ-IGHC rearrangements (189,988-673,835/sample) were included in the search for stereotyped motifs, corresponding to 1,056,967 distinct clonotypes (i.e. BcR IG rearrangements with a particular IGHV gene and amino acid CDR3 sequence) (7,163-123,276/sample, median=76,109). Regarding subset #4, 7/8 cases exhibited mu transcripts of subset #4-specific IG rearrangements ("subset #4 M-clonotypes"); by definition, these rearrangements utilized the IGHV4-34/IGHJ6 genes and had identical CDR3 length (20 amino acids), however their CDR3 amino acid composition varied (2-75 distinct subset #4 M-clonotypes/sample, median=8). In 5/7 cases these subset #4 M-clonotypes were characterized by CDR3s that were identical and/or highly similar (≤2 amino acid differences, ≥ 90% identity) to the CDR3 of the IgG-switched CLL clone. The M-clonotypes expressing CDR3s identical to those of the IgG-switched CLL clone represented the most expanded subset #4 M-clonotype within the sample, while the less expanded, "satellite" clonotypes may represent subclones that were selected against due to lower affinity with the driving antigen. The possibility that these “satellite” clonotypes derive from PCR and/or sequencing error cannot be a priori excluded, however replicate sample analysis produced identical subset #4 M-clonotypes in all cases tested, thus raising confidence in the accuracy of the data. Analysis of the subset #16 case yielded similar results, i.e. 2 subset #16 M-clonotypes, one of which was identical to the IgG-switched clonotypic BcR IG. Both subset #8 cases also carried subset #8 M-clonotypes, yet only one case exhibited an M-clonotype with a CDR3 identical to that of the respective G-CLL clone. Interestingly, this M-clonotype was accompanied by many highly similar, less expanded “satellite” clonotypes (n=109), raising the possibility that SHM may be occurring in (pre-)CLL clones carrying truly unmutated IGHV genes, but pass unnoticed due to negative selection. Although their actual frequency cannot be conclusively determined due to the inherent limitations of PCR-based NGS analysis, subset-specific rearrangements represented a very minor fraction of the sequenced IGHV4/IGHM clonotypes in all cases tested (median frequency 0.04%). Overall, our findings suggest that while CLL clones are primed prior to CSR for malignant transformation on the basis of their BcR IG features, G-CLL quickly transits through CSR either because full-blown malignant transformation occurs at a later time point, or because CSR offers a selective advantage to the malignant clone. Disclosures No relevant conflicts of interest to declare.
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Herrera-Mejía, Julián, Rocío Campos-Vega, Abraham Wall-Medrano, and Florinda Jiménez-Vega. "A Two-Step Single Plex PCR Method for Evaluating Key Colonic Microbiota Markers in Young Mexicans with Autism Spectrum Disorders: Protocol and Pilot Epidemiological Application." Diagnostics 13, no. 14 (July 17, 2023): 2387. http://dx.doi.org/10.3390/diagnostics13142387.
Abstract:
Many neurological disorders have a distinctive colonic microbiome (CM) signature. Particularly, children with autism spectrum disorders (ASD) exhibit a very dissimilar CM when compared to neurotypical (NT) ones, mostly at the species level. Thus far, knowledge on this matter comes from high-throughput (yet very expensive and time-consuming) analytical platforms, such as massive high-throughput sequencing of bacterial 16S rRNA. Here, pure (260/280 nm, ~1.85) stool DNA samples (200 ng.µL−1) from 48 participants [39 ASD, 9 NT; 3–13 y] were used to amplify four candidate differential CM markers [Bacteroides fragilis (BF), Faecalibacterium prausnitzii (FP), Desulfovibrio vulgaris (DV), Akkermansia muciniphila (AM)], using micro-organism-specific oligonucleotide primers [265 bp (BF), 198 bp (FP), 196 bp (DV), 327 bp (AM)] and a standardized two-step [low (step 1: °Tm—5 °C) to high (stage 2: °Tm—0 °C) astringent annealing] PCR protocol (2S-PCR). The method was sensitive enough to differentiate all CM biomarkers in the studied stool donors [↑ abundance: NT (BF, FP, AM), ASD (DV)], and phylogenetic analysis confirmed the primers’ specificity.
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Evans-Holm, Martha, Nicolai Lumbres, Rwik Sen, Patricia Montilla-Perez, Marc A. Paradise, and Peter Lentz. "Abstract 332: Improved high-throughput genomic analysis of urine samples using pixelated-ultrasound to enable personalized genomic profiling and therapeutic developments in cancer." Cancer Research 84, no. 6_Supplement (March 22, 2024): 332. http://dx.doi.org/10.1158/1538-7445.am2024-332.
Abstract:
Abstract Here we address some of the existing challenges in liquid biopsy workflows which can potentially benefit urine analysis from bladder cancer patients because approximately 1/4th of all human cancers are urological tumors. Globally, bladder cancer is the 10th most prevalent, and the 9th cause of mortality due to malignancy. The challenge addressed here is an improvement to sample preparation for sequencing. Among genders and disease states, urine samples vary in terms of cell count and hence, in DNA concentration. Therefore, it is critical to obtain consistent DNA fragments from variable samples across large cohorts of patients so that the sequencing leads to accurate identification of biomarkers of disease risk, progression, and treatment-response. In this direction, we present the advantages of a novel pixelated ultrasound technology which significantly improves sample-preparation in a very fast, economical, and high-throughput manner. Here, DNA is extracted from human urine samples and subjected to sonication to generate fragment sizes. Extracted DNA was loaded onto a regular 96-well round-bottom plate, which is sealed and placed inside the system where 12 columns of the 96-well plate are individually programmed and run simultaneously, hence enabling quick optimization. The system does not require time- and labor-intensive processing of the samples before or after the sonication which is required for other similar technology. Overall, the DNA samples were processed with significant improvement over other similar technology in terms of consistency, speed, and economy. Subsequently, the fragment sizes were analyzed. Analysis of results, as presented in the figures, show that the DNA fragment had the average size as predicted, uniform shearing, and very consistent across the 96-well plate containing different samples with no cross-contamination. The time, labour, expense, and risk turned out to be very low compared to other similar technology. The sizes were appropriate for library preparation and sequencing. The technology works consistently for both low and high cell numbers which is a critical factor for heterogenous samples from patients. In conclusion, the study presents improvements to library preparation for sequencing which fit into the larger workflow of non-invasive liquid biopsy using urine samples. The ability to obtain consistent DNA fragments in a quick and economical manner will greatly enable unique fingerprinting of an individual's cancer or cancer risk across large cohorts, with the potential for integration in automation workflows. Citation Format: Martha Evans-Holm, Nicolai Lumbres, Rwik Sen, Patricia Montilla-Perez, Marc A. Paradise, Peter Lentz. Improved high-throughput genomic analysis of urine samples using pixelated-ultrasound to enable personalized genomic profiling and therapeutic developments in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 332.
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Trosvik, Pål, Beate Skånseng, Kjetill S. Jakobsen, Nils C. Stenseth, Tormod Næs, and Knut Rudi. "Multivariate Analysis of Complex DNA Sequence Electropherograms for High-Throughput Quantitative Analysis of Mixed Microbial Populations." Applied and Environmental Microbiology 73, no. 15 (June 15, 2007): 4975–83. http://dx.doi.org/10.1128/aem.00128-07.
Abstract:
ABSTRACT High-throughput quantification of genetically coherent units (GCUs) is essential for deciphering population dynamics and species interactions within a community of microbes. Current techniques for microbial community analyses are, however, not suitable for this kind of high-throughput application. Here, we demonstrate the use of multivariate statistical analysis of complex DNA sequence electropherograms for the effective and accurate estimation of relative genotype abundance in cell samples from mixed microbial populations. The procedure is no more labor-intensive than standard automated DNA sequencing and provides a very effective means of quantitative data acquisition from experimental microbial communities. We present results with the Campylobacter jejuni strain-specific marker gene gltA, as well as the 16S rRNA gene, which is a universal marker across bacterial assemblages. The statistical models computed for these genes are applied to genetic data from two different experimental settings, namely, a chicken infection model and a multispecies anaerobic fermentation model, demonstrating collection of time series data from model bacterial communities. The method presented here is, however, applicable to any experimental scenario where the interest is quantification of GCUs in genetically heterogeneous DNA samples.
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Barturen, Guillermo, Antonio Rueda, José L. Oliver, and Michael Hackenberg. "MethylExtract: High-Quality methylation maps and SNV calling from whole genome bisulfite sequencing data." F1000Research 2 (October 15, 2013): 217. http://dx.doi.org/10.12688/f1000research.2-217.v1.
Abstract:
Whole genome methylation profiling at a single cytosine resolution is now feasible due to the advent of high-throughput sequencing techniques together with bisulfite treatment of the DNA. To obtain the methylation value of each individual cytosine, the bisulfite-treated sequence reads are first aligned to a reference genome, and then the profiling of the methylation levels is done from the alignments. A huge effort has been made to quickly and correctly align the reads and many different algorithms and programs to do this have been created. However, the second step is just as crucial and non-trivial, but much less attention has been paid to the final inference of the methylation states. Important error sources do exist, such as sequencing errors, bisulfite failure, clonal reads, and single nucleotide variants.We developed MethylExtract, a user friendly tool to: i) generate high quality, whole genome methylation maps and ii) detect sequence variation within the same sample preparation. The program is implemented into a single script and takes into account all major error sources. MethylExtract detects variation (SNVs – Single Nucleotide Variants) in a similar way to VarScan, a very sensitive method extensively used in SNV and genotype calling based on non-bisulfite-treated reads. The usefulness of MethylExtract is shown by means of extensive benchmarking based on artificial bisulfite-treated reads and a comparison to a recently published method, called Bis-SNP.MethylExtract is able to detect SNVs within High-Throughput Sequencing experiments of bisulfite treated DNA at the same time as it generates high quality methylation maps. This simultaneous detection of DNA methylation and sequence variation is crucial for many downstream analyses, for example when deciphering the impact of SNVs on differential methylation. An exclusive feature of MethylExtract, in comparison with existing software, is the possibility to assess the bisulfite failure in a statistical way. The source code, tutorial and artificial bisulfite datasets are available at http://bioinfo2.ugr.es/MethylExtract/ and http://sourceforge.net/projects/methylextract/, and also permanently accessible from 10.5281/zenodo.7144.
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Barturen, Guillermo, Antonio Rueda, José L. Oliver, and Michael Hackenberg. "MethylExtract: High-Quality methylation maps and SNV calling from whole genome bisulfite sequencing data." F1000Research 2 (February 21, 2014): 217. http://dx.doi.org/10.12688/f1000research.2-217.v2.
Abstract:
Whole genome methylation profiling at a single cytosine resolution is now feasible due to the advent of high-throughput sequencing techniques together with bisulfite treatment of the DNA. To obtain the methylation value of each individual cytosine, the bisulfite-treated sequence reads are first aligned to a reference genome, and then the profiling of the methylation levels is done from the alignments. A huge effort has been made to quickly and correctly align the reads and many different algorithms and programs to do this have been created. However, the second step is just as crucial and non-trivial, but much less attention has been paid to the final inference of the methylation states. Important error sources do exist, such as sequencing errors, bisulfite failure, clonal reads, and single nucleotide variants.We developed MethylExtract, a user friendly tool to: i) generate high quality, whole genome methylation maps and ii) detect sequence variation within the same sample preparation. The program is implemented into a single script and takes into account all major error sources. MethylExtract detects variation (SNVs – Single Nucleotide Variants) in a similar way to VarScan, a very sensitive method extensively used in SNV and genotype calling based on non-bisulfite-treated reads. The usefulness of MethylExtract is shown by means of extensive benchmarking based on artificial bisulfite-treated reads and a comparison to a recently published method, called Bis-SNP.MethylExtract is able to detect SNVs within High-Throughput Sequencing experiments of bisulfite treated DNA at the same time as it generates high quality methylation maps. This simultaneous detection of DNA methylation and sequence variation is crucial for many downstream analyses, for example when deciphering the impact of SNVs on differential methylation. An exclusive feature of MethylExtract, in comparison with existing software, is the possibility to assess the bisulfite failure in a statistical way. The source code, tutorial and artificial bisulfite datasets are available at http://bioinfo2.ugr.es/MethylExtract/ and http://sourceforge.net/projects/methylextract/, and also permanently accessible from 10.5281/zenodo.7144.
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de Biase, Dario, Michela Visani, Giorgia Acquaviva, Adele Fornelli, Michele Masetti, Carlo Fabbri, Annalisa Pession, and Giovanni Tallini. "The Role of Next-Generation Sequencing in the Cytologic Diagnosis of Pancreatic Lesions." Archives of Pathology & Laboratory Medicine 142, no. 4 (April 1, 2018): 458–64. http://dx.doi.org/10.5858/arpa.2017-0215-ra.
Abstract:
Context.— Integration of the analysis of genetic markers with endoscopic ultrasound–guided fine-needle aspiration and cytologic evaluation has increased the accuracy of the preoperative diagnosis of pancreatic lesions. The application of high-throughput gene panel analysis using next-generation sequencing platforms is now offering a great opportunity for further improvements. Objective.— To review the application of next-generation sequencing to the preoperative diagnosis of pancreatic lesions. Data Sources.— For data acquisition, a PubMed search using the terms next-generation sequencing, pancreas, pancreatic lesions, pancreatic tumors, and EUS-FNA was performed covering the years 2000–2017. Conclusions.— KRAS remains the gene most widely studied for preoperative single-gene tests. Next-generation sequencing reliably allows analysis of multiple gene markers starting from limited amounts of DNA. The study of multigene panels has become a very attractive option for the management and preoperative risk stratification of patients with pancreatic cancer.
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Ferretti, Luca, Chandana Tennakoon, Adrian Silesian, and Graham Freimanis andPaolo Ribeca. "SiNPle: Fast and Sensitive Variant Calling for Deep Sequencing Data." Genes 10, no. 8 (July 25, 2019): 561. http://dx.doi.org/10.3390/genes10080561.
Abstract:
Current high-throughput sequencing technologies can generate sequence data and provide information on the genetic composition of samples at very high coverage. Deep sequencing approaches enable the detection of rare variants in heterogeneous samples, such as viral quasi-species, but also have the undesired effect of amplifying sequencing errors and artefacts. Distinguishing real variants from such noise is not straightforward. Variant callers that can handle pooled samples can be in trouble at extremely high read depths, while at lower depths sensitivity is often sacrificed to specificity. In this paper, we propose SiNPle (Simplified Inference of Novel Polymorphisms from Large coveragE), a fast and effective software for variant calling. SiNPle is based on a simplified Bayesian approach to compute the posterior probability that a variant is not generated by sequencing errors or PCR artefacts. The Bayesian model takes into consideration individual base qualities as well as their distribution, the baseline error rates during both the sequencing and the PCR stage, the prior distribution of variant frequencies and their strandedness. Our approach leads to an approximate but extremely fast computation of posterior probabilities even for very high coverage data, since the expression for the posterior distribution is a simple analytical formula in terms of summary statistics for the variants appearing at each site in the genome. These statistics can be used to filter out putative SNPs and indels according to the required level of sensitivity. We tested SiNPle on several simulated and real-life viral datasets to show that it is faster and more sensitive than existing methods. The source code for SiNPle is freely available to download and compile, or as a Conda/Bioconda package.
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Liu, Sen, Hongyu Liu, Yunlong Dong, Fengbiao Wang, Huijuan Wang, and Jun Chen. "Gastric carcinoma with a gastrointestinal stromal tumor." médecine/sciences 34 (October 2018): 15–19. http://dx.doi.org/10.1051/medsci/201834f103.
Abstract:
Gastric carcinoma (GC) with gastrointestinal stromal tumor (GIST) is encountered very rarely in the clinic, and few cases have been reported in the literature. Here, we present a case involving a 72-year-old man who was diagnosed with gastric antrum adenocarcinoma accompanied by neuroendocrine differentiation and a GIST in the fundus, according to a preoperative examination and postoperative pathology. The patient then underwent a distal radical gastrectomy and GIST resection. After the operation, the patient was administered combined chemo-radiotherapy and subsequently underwent a 9-month follow-up examination. The gene mutations involved in this case were explored via high-throughput sequencing. The high-throughput gene mutation analysis indicated an exon5 mutation in the TP53 gene and copy number amplification of FGF19, CCND1, and FGFR2 in the gastric antrum adenocarcinoma. A gene sequencing analysis of the gastric fundus stromal tumor demonstrated an exon11 non-frame shift deletion mutation in the KIT gene. These findings suggested that this patient’s cancer might be sensitive to AZD1775 (a TP53-targeted drug) or targeted drugs such as FGF19, CCND1 and FGFR2, and should be sensitive to imatinib.
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Bentley, Stephen D., and Julian Parkhill. "Genomic perspectives on the evolution and spread of bacterial pathogens." Proceedings of the Royal Society B: Biological Sciences 282, no. 1821 (December 22, 2015): 20150488. http://dx.doi.org/10.1098/rspb.2015.0488.
Abstract:
Since the first complete sequencing of a free-living organism, Haemophilus influenzae , genomics has been used to probe both the biology of bacterial pathogens and their evolution. Single-genome approaches provided information on the repertoire of virulence determinants and host-interaction factors, and, along with comparative analyses, allowed the proposal of hypotheses to explain the evolution of many of these traits. These analyses suggested many bacterial pathogens to be of relatively recent origin and identified genome degradation as a key aspect of host adaptation. The advent of very-high-throughput sequencing has allowed for detailed phylogenetic analysis of many important pathogens, revealing patterns of global and local spread, and recent evolution in response to pressure from therapeutics and the human immune system. Such analyses have shown that bacteria can evolve and transmit very rapidly, with emerging clones showing adaptation and global spread over years or decades. The resolution achieved with whole-genome sequencing has shown considerable benefits in clinical microbiology, enabling accurate outbreak tracking within hospitals and across continents. Continued large-scale sequencing promises many further insights into genetic determinants of drug resistance, virulence and transmission in bacterial pathogens.
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Meyer, Julia A., Laura E. Hogan, Jinhua Wang, Jun J. Yang, Jay Patel, Ross L. Levine, Stephen P. Hunger, Elizabeth Raetz, Christopher Mason, and William L. Carroll. "High Throughput Transcriptome Sequencing of Pediatric Relapsed Acute Lymphoblastic Leukemia (ALL) Identifies Relapse Specific Mutations and Expression." Blood 116, no. 21 (November 19, 2010): 3233. http://dx.doi.org/10.1182/blood.v116.21.3233.3233.
Abstract:
Abstract Abstract 3233 Introduction: Relapsed ALL carries a very poor prognosis despite intensive therapy, indicating the need for new insights into disease mechanisms. We have previously used gene expression profiling (Hogan et al. ASH 2009) and copy number analysis (Yang et al. Blood 2008) in paired diagnosis and relapsed ALL samples to better understand the biologic mechanisms leading to recurrent disease. To create an integrated genomic profile of ALL, we have now focused on high throughput RNA sequencing to detect changes in the transcriptome from diagnosis to relapse. Patients/Methods: To date we have sequenced 6 matched diagnosis/relapse pairs (i.e. 12 marrow samples) from B-precursor ALL patients enrolled on Children's Oncology Group (COG) P9906 and AALL0232 trials. RNA libraries were prepared from poly-A selected RNA and sequenced using 54 base pair single end reads using the Illumina Genome Analyzer IIx. Each sample was sequenced in at least 7 lanes, generating an average of 100 million reads per sample. BWA (v0.5.8) was used to align the reads to the human genome, producing an average of 53 million mapped reads. Samtools (v0.1.8) was then used to predict genetic variants across the genome, filtering out variants with a low mapping quality (<Q20), sub-optimal alignment (X:1>0), low coverage (<8X), or overlap with known single nucleotide polymorphisms (SNPs) from dbSNP (r131) or the 1000 Genomes Project. Results: We observed a total of 119,000 genetic variants across all samples, with comparable overall mutational burden at relapse and diagnosis. To identify candidate lesions that may indicate a selection for common chemoresistance pathways, we focused our analysis on relapse-enriched, non-synonymous variants. 8,486 non-synonymous variants (insertions/deletions and single nucleotide variants [SNV]) were identified that occurred more often at relapse compared to diagnosis. Our analysis was focused on relapse-enriched SNVs that coded for non-synonymous changes, of which 154 were prioritized for validation. Validation was completed using matched genomic DNA samples and PCR products were directly sequenced. Mutation calls were made by manual review of tracings using the Mutation Surveyor program from Softgenetics. Thirty-three percent of predicted SNV loci were validated, but upon further sequencing of matched germline samples, five relapse specific mutations were confirmed. Mutations in COBRA1, FAM120A, RGS12, SND2, and SMEK2 were found in individual patient relapse samples. Validation is currently ongoing to confirm additional SNVs and an expanded validation of mutations will be completed in an additional 66 matched diagnosis/relapse pairs from COG 9906 and AALL 0232 and 0331 studies. Relapse specific isoforms identifying alternative exon usage was also detected in 15 genes, all of which were shared amongst multiple patients. In addition, a significant increase (p=6.7×10−6) was observed in the number of poly-adenylation sites in the genes of the relapse samples. Conclusions: While, isoform specific expression was shared amongst patients at relapse, all relapse specific mutations were private and our data to date indicate that a diversity of mechanisms contribute to relapsed disease. Further sequencing analysis of our expanded cohort of samples will determine the mutation and isoform expression prevalence, as well as the functional significance and the potential therapeutic relevance. Disclosures: No relevant conflicts of interest to declare.
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Zhao, Yuming, Fang Wang, Su Chen, Jun Wan, and Guohua Wang. "Methods of MicroRNA Promoter Prediction and Transcription Factor Mediated Regulatory Network." BioMed Research International 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/7049406.
Abstract:
MicroRNAs (miRNAs) are short (~22 nucleotides) noncoding RNAs and disseminated throughout the genome, either in the intergenic regions or in the intronic sequences of protein-coding genes. MiRNAs have been proved to play important roles in regulating gene expression. Hence, understanding the transcriptional mechanism of miRNA genes is a very critical step to uncover the whole regulatory network. A number of miRNA promoter prediction models have been proposed in the past decade. This review summarized several most popular miRNA promoter prediction models which used genome sequence features, or other features, for example, histone markers, RNA Pol II binding sites, and nucleosome-free regions, achieved by high-throughput sequencing data. Some databases were described as resources for miRNA promoter information. We then performed comprehensive discussion on prediction and identification of transcription factor mediated microRNA regulatory networks.
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Pipis, Menelaos, Alexander M. Rossor, Carolynne M. Doherty, Matilde Laura, and Mary M. Reilly. "15.21 Next-generation sequencing in charcot-marie-tooth disease: opportunities and challenges." Journal of Neurology, Neurosurgery & Psychiatry 90, no. 12 (November 14, 2019): e5.1-e5. http://dx.doi.org/10.1136/jnnp-2019-abn-2.14.
Abstract:
Charcot-Marie-Tooth (CMT) disease and related disorders encompass a phenotypically and genetically heterogeneous group of disorders. Our diagnostic approach to CMT has been revolutionised by the advent and use of next-generation sequencing (NGS) technologies with applications in CMT gene panels, whole exome and whole genome sequencing, mitochondrial sequencing and high-throughput transcriptome sequencing.We present the up to date evidence pertaining to the application of these technologies in CMT diagnostics and also discuss what challenges they bring in relation to variant interpretation. Phenotypic, genetic and bioinformatic evidence should be used to overcome these challenges, and we discuss how setting a maximum credible population allele frequency for pathogenic variants in dominant and recessive CMT genes is crucial in filtering efficiently NGS-derived variants.Whole genome sequencing as a single molecular genetic test is very appealing and, in the context of the 100,000 Genome Project, we suggest how its application into CMT clinical practice can happen with a balance between improved diagnostic yield and burden of variant analysis.
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Jingyao, Ma, Zhenping Chen, Huiqing LIU, Jialu Zhang, Hao GU, and Runhui Wu. "Application of High-Throughput Sequencing in the Diagnosis of Inherited Immune-Thrombocytopenia from Children Chronic/Refractory ITP." Blood 134, Supplement_1 (November 13, 2019): 86. http://dx.doi.org/10.1182/blood-2019-126771.
Abstract:
BACKGROUND: Inherited thrombocytopenias are a group of hereditary diseases with reduced platelet counts and associated bruising and bleeding as the main clinical manifestations. These entities may be hard to distinguish from ITP, particularly difficult immune thrombocytopenia complicates primary immunodeficiency and immunological treatments are effective in increasing the platelet count. Then when the course of thrombocytopenia is prolonged and other abnormalities, eg. infection, either are non-existent or subtle, distinguishing such diseases from ITP may be clinically almost impossible. However, in order to carry out proper disease management, accurate diagnosis is very necessary and urgently needed, especially in childhood. OBJECTIVES: To evaluate: 1) the detection rate of inherited immune thrombocytopenia by high-throughput, next-generation sequencing (NGS) from children with apparent chronic and refractory ITP, and 2) the value of NGS in screening and diagnosis of inherited "immune" thrombocytopenia. METHODS: We retrospectively collected 245 cases of chronic and refractory ITP in children with transient response to Intravenous Immunoglobulin (IVIG) and/ or glucocorticoid and/ or other immunosuppressive therapy, all of whom underwent genetic testing from April 2016 to April 2019. Their clinical data were systematically recorded and analyzed. We introduced a high-throughput, NGS platform into the routing diagnosis of those patients and analyzed the gene-sequencing results. We compared the differences between patients with positive gene mutations and those who carried suspected gene mutations. All subjects and their legal guardians gave written informed consent to the investigation. RESULTS: Sixteen patients were excluded as their final diagnosis was malignancy, aplastic anemia (AA), or myelodysplastic syndrome (MDS). Among the remaining 229 cases, 32 patients (14%) received a genetic diagnosis. Twenty-five patients (11%) had pathogenic mutations in 12 genes including CASP10(2), WAS(12), LRBA(1), CARD(1), ITGA2B(2), ITGB(1), CD36(1), NFKB2(1), NBEAL2(1), UNC13D(1), KMT2D(1), TNFRS13B(1) known to be included in lymphoproliferation or autoimmunity, whereas 7 patients (3%) carried a suspected pathogenic variant in 6 genes including: GATA(1), MYH-9(1), PTPN-11(1), RUNX(1), SLX4(2), TUBB1(1) that had not been reported in the context of autoimmune diseases. Among the 25 patients with known mutations, 16 patients (7%) could be definitely diagnosed as inherited immune thrombocytopenia and formed the Diagnosed Group (DG) according to their phenotype, inheritance and pathogenicity of the mutated gene, while 9 cases in this category and 7 patients who carried probable pathogenic variants constitute the Suspected Diagnosed Group (SDG). We compared their clinical and laboratory phenotype with the biggest difference identified in age of onset (median: 4.08 months in DG vs 54.00 months in SDG, P =0.002). Other variables analyzed included duration of time with misdiagnosis (median: 13.5 months vs 26.0 months, P=0.430), baseline platelet count (median: 6×109/L vs 5×109/L, P=.0.282), level of IL-4 (median: 0 vs 0, P=0.232), level of IL-6 (median: 13.32 vs 7.48 P=1.000), bleeding severity (without any bleeding: 1 vs 0; merely petechia/ecchymosis: 3 vs 6; bleeding in skin and one another location: 6 vs 4; bleeding in more than 2 location: 2 vs 2. P=0.542) and rate of identification of autoimmune antibodies between the two groups (P=0.662). CONCLUSIONS: Definite or suspected genetic etiologies consistent with inherited immune thrombocytopenia were identified in approximately one-seventh of cases of apparent chronic ITP. These cases would have been classified as "routine" cases of childhood ITP based on response to standard first-line ITP treatments and the absence of overt other findings. Eventually, their chronicity would have increased suspicion of an underlying etiology and the correct diagnosis made. The definite diagnosis group and the suspected group were identical clinically and in laboratory testing in every way except for age of onset suggesting that the suspected group was also likely inherited immune thrombocytopenia. Wide-ranging genetic screening (NGS) should be offered in children chronic/refractory ITP. The genetic findings have prognostic significance and may guide the choice of a targeted treatment in the future. Disclosures No relevant conflicts of interest to declare.
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Kolarikova, Kristyna, Radek Vodicka, Radek Vrtel, Julia Stellmachova, Martin Prochazka, Katerina Mensikova, Tereza Bartonikova, Tomas Furst, Petr Kanovsky, and Jan Geryk. "High-Throughput Sequencing Haplotype Analysis Indicates in LRRK2 Gene a Potential Risk Factor for Endemic Parkinsonism in Southeastern Moravia, Czech Republic." Life 12, no. 1 (January 14, 2022): 121. http://dx.doi.org/10.3390/life12010121.
Abstract:
Parkinson’s disease and parkinsonism are relatively common neurodegenerative disorders. This study aimed to assess potential genetic risk factors of haplotypes in genes associated with parkinsonism in a population in which endemic parkinsonism and atypical parkinsonism have recently been found. The genes ADH1C, EIF4G1, FBXO7, GBA, GIGYF2, HTRA2, LRRK2, MAPT, PARK2, PARK7, PINK1 PLA2G6, SNCA, UCHL1, and VPS35 were analyzed in 62 patients (P) and 69 age-matched controls from the researched area (C1). Variants were acquired by high-throughput sequencing using Ion Torrent workflow. As another set of controls, the whole genome sequencing data from 100 healthy non-related individuals from the Czech population were used (C2); the results were also compared with the Genome Project data (C3). We observed shared findings of four intron (rs11564187, rs36220738, rs200829235, and rs3789329) and one exon variant (rs33995883) in the LRRK2 gene in six patients. A comparison of the C1–C3 groups revealed significant differences in haplotype frequencies between ratio of 2.09 for C1, 1.65 for C2, and 6.3 for C3, and odds ratios of 13.15 for C1, 2.58 for C2, and 7.6 for C3 were estimated. The co-occurrence of five variants in the LRRK2 gene (very probably in haplotype) could be an important potential risk factor for the development of parkinsonism, even outside the recently described pedigrees in the researched area where endemic parkinsonism is present.