Journal articles: 'Genomics analyses'

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Caulfield, Mark. "6 Translating genomics for clinical benefit." Postgraduate Medical Journal 95, no. 1130 (November 21, 2019): 686.3–686. http://dx.doi.org/10.1136/postgradmedj-2019-fpm.6.

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The UK 100,000 Genomes Project has focussed on transforming genomic medicine in the National Health Service using whole genome sequencing in rare disease, cancer and infection. Genomics England partnering with the NHS established 13 Genomic Medicine Centres, the NHS whole genome sequencing centre and the Genomics England Clinical Interpretation Partnership (3337 researchers from 24 countries). We sequenced the 100,000th genome on the 5th December 2019 and completed an initial analysis for participants in July 2019. Alongside these genomes we have assembled a longitudinal life course dataset for research and diagnosis including 2.6 billion clinical data points for the 3000 plus researchers to work on to drive up the value of the genomes for direct healthcare. In parallel we have partnered the NHS to establish one of the world’s most advanced Genomic Medicine Service where we re-evaluated 300,000 genomic tests and upgraded 25% of tests to newer technologies with an annual review. The Department of Health have announced the ambition to undertake 5 million genome analyses over the next 5 years focused on new areas tractable to health gain.

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Alam, Intikhab, Mike Cornell, Darren M. Soanes, Cornelia Hedeler, Han Min Wong, Magnus Rattray, Simon J. Hubbard, Nicholas J. Talbot, Stephen G. Oliver, and Norman W. Paton. "A Methodology for Comparative Functional Genomics." Journal of Integrative Bioinformatics 4, no. 3 (December 1, 2007): 112–22. http://dx.doi.org/10.1515/jib-2007-69.

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Abstract The continuing and rapid increase in the number of fully sequenced genomes is creating new opportunities for comparative studies. However, although many genomic databases store data from multiple organisms, for the most part they provide limited support for comparative genomics. We argue that refocusing genomic data management to provide more direct support for comparative studies enables systematic identification of important relationships between species, thereby increasing the value that can be obtained from sequenced genomes. The principal result of the paper is a methodology, in which comparative analyses are constructed over a foundation based on sequence clusters and evolutionary relationships. This methodology has been applied in a systematic study of the fungi, and we describe how comparative analyses have been implemented as an analysis library over the e-Fungi data warehouse.

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Nguyen, Nga Thi Thuy, Pierre Vincens, Jean François Dufayard, Hugues Roest Crollius, and Alexandra Louis. "Genomicus in 2022: comparative tools for thousands of genomes and reconstructed ancestors." Nucleic Acids Research 50, no. D1 (November 18, 2021): D1025—D1031. http://dx.doi.org/10.1093/nar/gkab1091.

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Abstract Genomicus is a database and web-server dedicated to comparative genomics in eukaryotes. Its main functionality is to graphically represent the conservation of genomic blocks between multiple genomes, locally around a specific gene of interest or genome-wide through karyotype comparisons. Since 2010 and its first release, Genomicus has synchronized with 60 Ensembl releases and seen the addition of functions that have expanded the type of analyses that users can perform. Today, five public instances of Genomicus are supporting a total number of 1029 extant genomes and 621 ancestral reconstructions from all eukaryotes kingdoms available in Ensembl and Ensembl Genomes databases complemented with four additional instances specific to taxonomic groups of interest. New visualization and query tools are described in this manuscript. Genomicus is freely available at http://www.genomicus.bio.ens.psl.eu/genomicus.

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Whitworth, David E., Natashia Sydney, and Emily J. Radford. "Myxobacterial Genomics and Post-Genomics: A Review of Genome Biology, Genome Sequences and Related ‘Omics Studies." Microorganisms 9, no. 10 (October 13, 2021): 2143. http://dx.doi.org/10.3390/microorganisms9102143.

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Myxobacteria are fascinating and complex microbes. They prey upon other members of the soil microbiome by secreting antimicrobial proteins and metabolites, and will undergo multicellular development if starved. The genome sequence of the model myxobacterium Myxococcus xanthus DK1622 was published in 2006 and 15 years later, 163 myxobacterial genome sequences have now been made public. This explosion in genomic data has enabled comparative genomics analyses to be performed across the taxon, providing important insights into myxobacterial gene conservation and evolution. The availability of myxobacterial genome sequences has allowed system-wide functional genomic investigations into entire classes of genes. It has also enabled post-genomic technologies to be applied to myxobacteria, including transcriptome analyses (microarrays and RNA-seq), proteome studies (gel-based and gel-free), investigations into protein–DNA interactions (ChIP-seq) and metabolism. Here, we review myxobacterial genome sequencing, and summarise the insights into myxobacterial biology that have emerged as a result. We also outline the application of functional genomics and post-genomic approaches in myxobacterial research, highlighting important findings to emerge from seminal studies. The review also provides a comprehensive guide to the genomic datasets available in mid-2021 for myxobacteria (including 24 genomes that we have sequenced and which are described here for the first time).

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Nagy, László G., Zsolt Merényi, Botond Hegedüs, and Balázs Bálint. "Novel phylogenetic methods are needed for understanding gene function in the era of mega-scale genome sequencing." Nucleic Acids Research 48, no. 5 (January 16, 2020): 2209–19. http://dx.doi.org/10.1093/nar/gkz1241.

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Abstract Ongoing large-scale genome sequencing projects are forecasting a data deluge that will almost certainly overwhelm current analytical capabilities of evolutionary genomics. In contrast to population genomics, there are no standardized methods in evolutionary genomics for extracting evolutionary and functional (e.g. gene-trait association) signal from genomic data. Here, we examine how current practices of multi-species comparative genomics perform in this aspect and point out that many genomic datasets are under-utilized due to the lack of powerful methodologies. As a result, many current analyses emphasize gene families for which some functional data is already available, resulting in a growing gap between functionally well-characterized genes/organisms and the universe of unknowns. This leaves unknown genes on the ‘dark side’ of genomes, a problem that will not be mitigated by sequencing more and more genomes, unless we develop tools to infer functional hypotheses for unknown genes in a systematic manner. We provide an inventory of recently developed methods capable of predicting gene-gene and gene-trait associations based on comparative data, then argue that realizing the full potential of whole genome datasets requires the integration of phylogenetic comparative methods into genomics, a rich but underutilized toolbox for looking into the past.

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Clark, Melody S., Andrew Clarke, Charles S. Cockell, Peter Convey, H. William Detrich III, Keiron P. P. Fraser, Ian A. Johnston, et al. "Antarctic Genomics." Comparative and Functional Genomics 5, no. 3 (2004): 230–38. http://dx.doi.org/10.1002/cfg.398.

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With the development of genomic science and its battery of technologies, polar biology stands on the threshold of a revolution, one that will enable the investigation of important questions of unprecedented scope and with extraordinary depth and precision. The exotic organisms of polar ecosystems are ideal candidates for genomic analysis. Through such analyses, it will be possible to learn not only the novel features that enable polar organisms to survive, and indeed thrive, in their extreme environments, but also fundamental biological principles that are common to most, if not all, organisms. This article aims to review recent developments in Antarctic genomics and to demonstrate the global context of such studies.

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Kui, Ling, Zhe Zhang, Yangzi Wang, Yesheng Zhang, Shiming Li, Xiao Dong, Qiuju Xia, Jun Sheng, Jian Wang, and Yang Dong. "Genome Assembly and Analyses of the Macrofungus Macrocybe gigantea." BioMed Research International 2021 (January 18, 2021): 1–14. http://dx.doi.org/10.1155/2021/6656365.

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Macrocybe gigantea (M. gigantea) is a macrofungus genus that contains a big number of fairly fleshy gilled mushrooms with white spores. This macrofungus produces diverse bioactive compounds, antioxidants, and water-soluble polysaccharides. However, the genomic resources of this species remain unknown. Here, we assembled the genome of M. gigantea (41.23 Mb) into 336 scaffolds with a N50 size of 374,455 bp and compared it with the genomes of eleven other macrofungi. Comparative genomics study confirmed that M. gigantea belonged to the Macrocybe genus, a stand-alone genus different from the Tricholoma genus. In addition, we found that glycosyl hydrolase family 28 (GH28) in M. gigantea shared conserved motifs that were significantly different from their counterparts in Tricholoma. The genomic resource uncovered by this study will enhance our understanding of fungi biology, especially the differences in their growth rates and energy metabolism.

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Gillespie, Joseph J., Alice R. Wattam, Stephen A. Cammer, Joseph L. Gabbard, Maulik P. Shukla, Oral Dalay, Timothy Driscoll, et al. "PATRIC: the Comprehensive Bacterial Bioinformatics Resource with a Focus on Human Pathogenic Species." Infection and Immunity 79, no. 11 (September 6, 2011): 4286–98. http://dx.doi.org/10.1128/iai.00207-11.

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ABSTRACTFunded by the National Institute of Allergy and Infectious Diseases, thePathosystemsResourceIntegrationCenter (PATRIC) is a genomics-centric relational database and bioinformatics resource designed to assist scientists in infectious-disease research. Specifically, PATRIC provides scientists with (i) a comprehensive bacterial genomics database, (ii) a plethora of associated data relevant to genomic analysis, and (iii) an extensive suite of computational tools and platforms for bioinformatics analysis. While the primary aim of PATRIC is to advance the knowledge underlying the biology of human pathogens, all publicly available genome-scale data for bacteria are compiled and continually updated, thereby enabling comparative analyses to reveal the basis for differences between infectious free-living and commensal species. Herein we summarize the major features available at PATRIC, dividing the resources into two major categories: (i) organisms, genomes, and comparative genomics and (ii) recurrent integration of community-derived associated data. Additionally, we present two experimental designs typical of bacterial genomics research and report on the execution of both projects using only PATRIC data and tools. These applications encompass a broad range of the data and analysis tools available, illustrating practical uses of PATRIC for the biologist. Finally, a summary of PATRIC's outreach activities, collaborative endeavors, and future research directions is provided.

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Casola, Claudio, and Esther Betrán. "The Genomic Impact of Gene Retrocopies: What Have We Learned from Comparative Genomics, Population Genomics, and Transcriptomic Analyses?" Genome Biology and Evolution 9, no. 6 (June 1, 2017): 1351–73. http://dx.doi.org/10.1093/gbe/evx081.

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Valentin, Guignon, Toure Abdel, Droc Gaëtan, Dufayard Jean-François, Conte Matthieu, and Rouard Mathieu. "GreenPhylDB v5: a comparative pangenomic database for plant genomes." Nucleic Acids Research 49, no. D1 (November 25, 2020): D1464—D1471. http://dx.doi.org/10.1093/nar/gkaa1068.

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Abstract Comparative genomics is the analysis of genomic relationships among different species and serves as a significant base for evolutionary and functional genomic studies. GreenPhylDB (https://www.greenphyl.org) is a database designed to facilitate the exploration of gene families and homologous relationships among plant genomes, including staple crops critically important for global food security. GreenPhylDB is available since 2007, after the release of the Arabidopsis thaliana and Oryza sativa genomes and has undergone multiple releases. With the number of plant genomes currently available, it becomes challenging to select a single reference for comparative genomics studies but there is still a lack of databases taking advantage several genomes by species for orthology detection. GreenPhylDBv5 introduces the concept of comparative pangenomics by harnessing multiple genome sequences by species. We created 19 pangenes and processed them with other species still relying on one genome. In total, 46 plant species were considered to build gene families and predict their homologous relationships through phylogenetic-based analyses. In addition, since the previous publication, we rejuvenated the website and included a new set of original tools including protein-domain combination, tree topologies searches and a section for users to store their own results in order to support community curation efforts.

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Considine, Michael, Hilary Parker, Yingying Wei, Xaio Xia, Leslie Cope, Michael Ochs, and Elana Fertig. "AGA: Interactive pipeline for reproducible genomics analyses." F1000Research 4 (January 28, 2015): 28. http://dx.doi.org/10.12688/f1000research.6030.1.

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Automated Genomics Analysis (AGA) is an interactive program to analyze high-throughput genomic data sets on a variety of platforms. An easy to use, point and click, guided pipeline is implemented to combine, define, and compare datasets, and customize their outputs. In contrast to other automated programs, AGA enables flexible selection of sample groups for comparison from complex sample annotations. Batch correction techniques are also included to further enable the combination of datasets from diverse studies in this comparison. AGA also allows users to save plots, tables and data, and log files containing key portions of the R script run for reproducible analyses. The link between the interface and R supports collaborative research, enabling advanced R users to extend preliminary analyses generated from bioinformatics novices.

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Utturkar, Sagar M., W. Nathan Cude, Michael S. Robeson, Zamin K. Yang, Dawn M. Klingeman, Miriam L. Land, Steve L. Allman, et al. "Enrichment of Root Endophytic Bacteria from Populus deltoides and Single-Cell-Genomics Analysis." Applied and Environmental Microbiology 82, no. 18 (July 15, 2016): 5698–708. http://dx.doi.org/10.1128/aem.01285-16.

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ABSTRACTBacterial endophytes that colonizePopulustrees contribute to nutrient acquisition, prime immunity responses, and directly or indirectly increase both above- and below-ground biomasses. Endophytes are embedded within plant material, so physical separation and isolation are difficult tasks. Application of culture-independent methods, such as metagenome or bacterial transcriptome sequencing, has been limited due to the predominance of DNA from the plant biomass. Here, we describe a modified differential and density gradient centrifugation-based protocol for the separation of endophytic bacteria fromPopulusroots. This protocol achieved substantial reduction in contaminating plant DNA, allowed enrichment of endophytic bacteria away from the plant material, and enabled single-cell genomics analysis. Four single-cell genomes were selected for whole-genome amplification based on their rarity in the microbiome (potentially uncultured taxa) as well as their inferred abilities to form associations with plants. Bioinformatics analyses, including assembly, contamination removal, and completeness estimation, were performed to obtain single-amplified genomes (SAGs) of organisms from the phylaArmatimonadetes,Verrucomicrobia, andPlanctomycetes, which were unrepresented in our previous cultivation efforts. Comparative genomic analysis revealed unique characteristics of each SAG that could facilitate future cultivation efforts for these bacteria.IMPORTANCEPlant roots harbor a diverse collection of microbes that live within host tissues. To gain a comprehensive understanding of microbial adaptations to this endophytic lifestyle from strains that cannot be cultivated, it is necessary to separate bacterial cells from the predominance of plant tissue. This study provides a valuable approach for the separation and isolation of endophytic bacteria from plant root tissue. Isolated live bacteria provide material for microbiome sequencing, single-cell genomics, and analyses of genomes of uncultured bacteria to provide genomics information that will facilitate future cultivation attempts.

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Baumler, David J., Lois M. Banta, Kai F. Hung, Jodi A. Schwarz, Eric L. Cabot, Jeremy D. Glasner, and Nicole T. Perna. "Using Comparative Genomics for Inquiry-Based Learning to Dissect Virulence of Escherichia coli O157:H7 and Yersinia pestis." CBE—Life Sciences Education 11, no. 1 (March 2012): 81–93. http://dx.doi.org/10.1187/cbe.10-04-0057.

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Genomics and bioinformatics are topics of increasing interest in undergraduate biological science curricula. Many existing exercises focus on gene annotation and analysis of a single genome. In this paper, we present two educational modules designed to enable students to learn and apply fundamental concepts in comparative genomics using examples related to bacterial pathogenesis. Students first examine alignments of genomes of Escherichia coli O157:H7 strains isolated from three food-poisoning outbreaks using the multiple-genome alignment tool Mauve. Students investigate conservation of virulence factors using the Mauve viewer and by browsing annotations available at the A Systematic Annotation Package for Community Analysis of Genomes database. In the second module, students use an alignment of five Yersinia pestis genomes to analyze single-nucleotide polymorphisms of three genes to classify strains into biovar groups. Students are then given sequences of bacterial DNA amplified from the teeth of corpses from the first and second pandemics of the bubonic plague and asked to classify these new samples. Learning-assessment results reveal student improvement in self-efficacy and content knowledge, as well as students' ability to use BLAST to identify genomic islands and conduct analyses of virulence factors from E. coli O157:H7 or Y. pestis. Each of these educational modules offers educators new ready-to-implement resources for integrating comparative genomic topics into their curricula.

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Houde, Peter. "Special Issue: Genomic Analyses of Avian Evolution." Diversity 11, no. 10 (September 29, 2019): 178. http://dx.doi.org/10.3390/d11100178.

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“Genomic Analyses of Avian Evolution” is a “state of the art” showcase of the varied and rapidly evolving fields of inquiry enabled and driven by powerful new methods of genome sequencing and assembly as they are applied to some of the world’s most familiar and charismatic organisms—birds. The contributions to this Special Issue are as eclectic as avian genomics itself, but loosely interrelated by common underpinnings of phylogenetic inference, de novo genome assembly of non-model species, and genome organization and content.

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BLAXTER, M., M. ASLETT, D. GUILIANO, J. DAUB, and THE FILARIAL GENOME PROJECT. "Parasitic helminth genomics." Parasitology 118, no. 7 (October 1999): 39–51. http://dx.doi.org/10.1017/s0031182099004060.

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The initiation of genome projects on helminths of medical importance promises to yield new drug targets and vaccine candidates in unprecedented numbers. In order to exploit this emerging data it is essential that the user community is aware of the scope and quality of data available, and that the genome projects provide analyses of the raw data to highlight potential genes of interest. Core bioinformatics support for the parasite genome projects has promoted these approaches. In the Brugia genome project, a combination of expressed sequence tag sequencing from multiple cDNA libraries representing the complete filarial nematode lifecycle, and comparative analysis of the sequence dataset, particularly using the complete genome sequence of the model nematode C. elegans, has proved very effective in gene discovery.

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JAILLON, O., J. M. AURY, H. ROEST CROLLIUS, M. SALANOUBAT, P. WINCKER, C. DOSSAT, V. CASTELLI, et al. "Genome-wide Analyses Based on Comparative Genomics." Cold Spring Harbor Symposia on Quantitative Biology 68 (January 1, 2003): 275–82. http://dx.doi.org/10.1101/sqb.2003.68.275.

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Moreira, Leandro M., Robson F. de Souza, Nalvo F. Almeida Jr, João C. Setubal, Julio Cezar F. Oliveira, Luiz R. Furlan, Jesus A. Ferro, and Ana C. R. da Silva. "COMPARATIVE GENOMICS ANALYSES OF CITRUS-ASSOCIATED BACTERIA." Annual Review of Phytopathology 42, no. 1 (September 2004): 163–84. http://dx.doi.org/10.1146/annurev.phyto.42.040803.140310.

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Paudel, Sujan, Shefali Dobhal, Anne M. Alvarez, and Mohammad Arif. "Taxonomy and Phylogenetic Research on Ralstonia solanacearum Species Complex: A Complex Pathogen with Extraordinary Economic Consequences." Pathogens 9, no. 11 (October 25, 2020): 886. http://dx.doi.org/10.3390/pathogens9110886.

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The bacterial wilt pathogen, first known as Bacillus solanacearum, has undergone numerous taxonomic changes since its first description in 1896. The history and significance of this pathogen is covered in this review with an emphasis on the advances in technology that were used to support each reclassification that finally led to the current separation of Ralstonia solanacearum into three genomic species. Frequent name changes occurred as methodology transitioned from phenotypic, biochemical, and molecular studies, to genomics and functional genomics. The diversity, wide host range, and geographical distribution of the bacterial wilt pathogen resulted in its division into three species as genomic analyses elucidated phylogenetic relationships among strains. Current advances in phylogenetics and functional genomics now open new avenues for research into epidemiology and control of the devastating bacterial wilt disease.

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McBride, Colleen M., Kristi D. Graves, Kimberly A. Kaphingst, Caitlin G. Allen, Catharine Wang, Elva Arredondo, and William M. P. Klein. "Behavioral and social scientists’ reflections on genomics: a systematic evaluation within the Society of Behavioral Medicine." Translational Behavioral Medicine 9, no. 6 (April 5, 2019): 1012–19. http://dx.doi.org/10.1093/tbm/ibz044.

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ABSTRACT Clinical and public health translation of genomics could be facilitated by expertise from behavioral medicine, yet genomics has not been a significant focus of the Society of Behavioral Medicine (SBM). SBM convened a working group (WG) to lead a systematic exploration of members’ views on: (a) whether SBM should give a higher priority to genomic translation and (b) what efforts, if any, should be made to support this increased engagement. The WG used a stepped process over 2 years that began by gaining input from SBM leadership regarding key issues and suggestions for approach, engaging a cross section of membership to expand and record these discussions, followed by systematic qualitative analyses to inform priority action steps. Discussions with SBM leaders and members suggested that genomics was relevant to SBM, particularly for junior members. SBM members’ expertise in social and behavioral theory, and implementation study designs, were viewed as highly relevant to genomic translation. Participants expressed that behavioral and social scientists should be engaged in translational genomics work, giving special attention to health disparities. Proposed action steps are aligned with a “push–pull” framework of innovation dissemination. “Push” strategies aim to reach potential adopters and included linking members with genomics expertise to those wanting to become involved and raising awareness of evidence-based genomic applications ready for implementation. “Pull” strategies aim to expand demand and included developing partnerships with genomics societies and advocating for funding, study section modifications, and training programs.

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Handelsman, Jo. "Metagenomics: Application of Genomics to Uncultured Microorganisms." Microbiology and Molecular Biology Reviews 68, no. 4 (December 2004): 669–85. http://dx.doi.org/10.1128/mmbr.68.4.669-685.2004.

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SUMMARY Metagenomics (also referred to as environmental and community genomics) is the genomic analysis of microorganisms by direct extraction and cloning of DNA from an assemblage of microorganisms. The development of metagenomics stemmed from the ineluctable evidence that as-yet-uncultured microorganisms represent the vast majority of organisms in most environments on earth. This evidence was derived from analyses of 16S rRNA gene sequences amplified directly from the environment, an approach that avoided the bias imposed by culturing and led to the discovery of vast new lineages of microbial life. Although the portrait of the microbial world was revolutionized by analysis of 16S rRNA genes, such studies yielded only a phylogenetic description of community membership, providing little insight into the genetics, physiology, and biochemistry of the members. Metagenomics provides a second tier of technical innovation that facilitates study of the physiology and ecology of environmental microorganisms. Novel genes and gene products discovered through metagenomics include the first bacteriorhodopsin of bacterial origin; novel small molecules with antimicrobial activity; and new members of families of known proteins, such as an Na+(Li+)/H+ antiporter, RecA, DNA polymerase, and antibiotic resistance determinants. Reassembly of multiple genomes has provided insight into energy and nutrient cycling within the community, genome structure, gene function, population genetics and microheterogeneity, and lateral gene transfer among members of an uncultured community. The application of metagenomic sequence information will facilitate the design of better culturing strategies to link genomic analysis with pure culture studies.

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Liefeld, Ted, Qing Gao, Michael A. Chapman, Giovanni Tonon, Daniel Auclair, Michael Reich, and Todd R. Golub. "The Multiple Myeloma Genomics Portal." Blood 112, no. 11 (November 16, 2008): 5115. http://dx.doi.org/10.1182/blood.v112.11.5115.5115.

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Abstract Current integrative genomics projects are enabling new discoveries in cancer research through the ability to combine multiple modalities of data, e.g. gene expression, copy number, RNAi, exon resequencing, and epigenetics. However, the tools to access and analyze this data have traditionally been out of the reach of clinicians and research biologists, due to the widely distributed nature of the available data and the significant learning curve required to use the analytical tools. This problem is particularly relevant to the multiple myeloma research community because of the heterogeneity of genomic aberrations underlying this disease and lack of a central repository of multi-modal multiple myeloma data. To address these problems, the Broad Institute has created a pilot Multiple Myeloma Genomics Portal, http://www.broad.mit.edu/mmgp, which serves as an interface between biologists (and clinical investigators), analytical tools, and multiple myeloma datasets. The Portal provides access to a number of advanced gene expression, gene set enrichment, and copy number analyses and visualizations within an easy to use Web interface. These analyses can be performed on the datasets hosted on the Portal, which include previously published curated, high quality genomic multiple myeloma datasets as well as a new reference collection of multiple myeloma samples. The Portal is continuously updated with new datasets, data types, and analytical capabilities as they become available. The Portal’s accessibility allows it to serve as a significant venue for investigators from other fields, engaging a broader range of investigators in exploring these data, and its design is readily adaptable to integrative genomics studies of other cancer types.

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Vadlamudi, Lata, Carmen Maree Bennett, Melanie Tom, Ghusoon Abdulrasool, Kristian Brion, Ben Lundie, Hnin Aung, et al. "A Multi-Disciplinary Team Approach to Genomic Testing for Drug-Resistant Epilepsy Patients—The GENIE Study." Journal of Clinical Medicine 11, no. 14 (July 21, 2022): 4238. http://dx.doi.org/10.3390/jcm11144238.

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Background. The genomic era has led to enormous progress in clinical care and a multi-disciplinary team (MDT) approach is imperative for integration of genomics into epilepsy patient care. Methods. The MDT approach involved patient selection, genomic testing choice, variant discussions and return of results. Genomics analysis included cytogenomic testing and whole exome sequencing (WES). Neurologist surveys were undertaken at baseline and after genomic testing to determine if genomic diagnoses would alter their management, and if there was a change in confidence in genomic testing and neurologist perceptions of the MDT approach. Results. The total diagnostic yield from all genomic testing was 17% (11/66), with four diagnoses from cytogenomic analyses. All chromosomal microarray (CMA) diagnoses were in patients seen by adult neurologists. Diagnostic yield for WES was 11% (7/62). The most common gene with pathogenic variants was DCX, reported in three patients, of which two were mosaic. The genomic diagnosis impacted management in 82% (9/11). There was increased confidence with integrating genomics into clinical care (Pearson chi square = 83, p = 0.004) and qualitative comments were highly supportive of the MDT approach. Conclusions. We demonstrated diagnostic yield from genomic testing, and the impact on management in a cohort with drug-resistant epilepsy. The MDT approach increased confidence in genomic testing and neurologists valued the input from this approach. The utility of CMA was demonstrated in epilepsy patients seen by adult neurologists as was the importance of considering mosaicism for previously undiagnosed patients.

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Chadwick, Jennifer Q., Kenneth C. Copeland, Dannielle E. Branam, Julie A. Erb-Alvarez, Sohail I. Khan, Michael T. Peercy, Mark E. Rogers, Bobby R. Saunkeah, Jeanie B. Tryggestad, and David F. Wharton. "Genomic Research and American Indian Tribal Communities in Oklahoma: Learning From Past Research Misconduct and Building Future Trusting Partnerships." American Journal of Epidemiology 188, no. 7 (April 24, 2019): 1206–12. http://dx.doi.org/10.1093/aje/kwz062.

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Abstract Research misconduct and consequential harms have been inflicted upon American Indian/Alaska Native communities for decades. To protect their people and culture and to retain oversight over research, many Native communities have established tribal health research and institutional review boards. The Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) Study showcases a successful, trusting research collaboration with tribal nations and academic investigators in Oklahoma. In 2006, the TODAY Study investigators proposed a modification of the study protocol to collect biological specimens from participants for genomic analyses and indefinite storage. Partnering American Indian tribal nations elected not to participate in the genomics collection and repository proposal. Reasons included 1) protection of cultural values, 2) concerns regarding community anonymity, 3) a potential threat to tribal services eligibility, 4) broad informed consent language, and 5) vague definitions of data access and usage. The nations believed the proposed genomics analyses presented a risk of harm to their people and nations without clear benefit. Since the 2006 proposal and the advancement of genomics research, many tribal communities in Oklahoma, appreciating the potential benefits of genomic research, are developing policies regarding oversight of/access to data and biological specimens to mitigate risks and provide members and communities with opportunities to participate in safe and meaningful genomic research.

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Liu, Fuyun, Yuli Li, Hongwei Yu, Lingling Zhang, Jingjie Hu, Zhenmin Bao, and Shi Wang. "MolluscDB: an integrated functional and evolutionary genomics database for the hyper-diverse animal phylum Mollusca." Nucleic Acids Research 49, no. D1 (October 22, 2020): D988—D997. http://dx.doi.org/10.1093/nar/gkaa918.

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Abstract Mollusca represents the second largest animal phylum but remains poorly explored from a genomic perspective. While the recent increase in genomic resources holds great promise for a deep understanding of molluscan biology and evolution, access and utilization of these resources still pose a challenge. Here, we present the first comprehensive molluscan genomics database, MolluscDB (http://mgbase.qnlm.ac), which compiles and integrates current molluscan genomic/transcriptomic resources and provides convenient tools for multi-level integrative and comparative genomic analyses. MolluscDB enables a systematic view of genomic information from various aspects, such as genome assembly statistics, genome phylogenies, fossil records, gene information, expression profiles, gene families, transcription factors, transposable elements and mitogenome organization information. Moreover, MolluscDB offers valuable customized datasets or resources, such as gene coexpression networks across various developmental stages and adult tissues/organs, core gene repertoires inferred for major molluscan lineages, and macrosynteny analysis for chromosomal evolution. MolluscDB presents an integrative and comprehensive genomics platform that will allow the molluscan community to cope with ever-growing genomic resources and will expedite new scientific discoveries for understanding molluscan biology and evolution.

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Der Sarkissian, Clio, Morten E. Allentoft, María C. Ávila-Arcos, Ross Barnett, Paula F. Campos, Enrico Cappellini, Luca Ermini, et al. "Ancient genomics." Philosophical Transactions of the Royal Society B: Biological Sciences 370, no. 1660 (January 19, 2015): 20130387. http://dx.doi.org/10.1098/rstb.2013.0387.

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The past decade has witnessed a revolution in ancient DNA (aDNA) research. Although the field's focus was previously limited to mitochondrial DNA and a few nuclear markers, whole genome sequences from the deep past can now be retrieved. This breakthrough is tightly connected to the massive sequence throughput of next generation sequencing platforms and the ability to target short and degraded DNA molecules. Many ancient specimens previously unsuitable for DNA analyses because of extensive degradation can now successfully be used as source materials. Additionally, the analytical power obtained by increasing the number of sequence reads to billions effectively means that contamination issues that have haunted aDNA research for decades, particularly in human studies, can now be efficiently and confidently quantified. At present, whole genomes have been sequenced from ancient anatomically modern humans, archaic hominins, ancient pathogens and megafaunal species. Those have revealed important functional and phenotypic information, as well as unexpected adaptation, migration and admixture patterns. As such, the field of aDNA has entered the new era of genomics and has provided valuable information when testing specific hypotheses related to the past.

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Riginos, Cynthia, Eric D. Crandall, Libby Liggins, Pim Bongaerts, and Eric A. Treml. "Navigating the currents of seascape genomics: how spatial analyses can augment population genomic studies." Current Zoology 62, no. 6 (July 6, 2016): 581–601. http://dx.doi.org/10.1093/cz/zow067.

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Pedersen, Brent S., and Aaron R. Quinlan. "hts-nim: scripting high-performance genomic analyses." Bioinformatics 34, no. 19 (April 30, 2018): 3387–89. http://dx.doi.org/10.1093/bioinformatics/bty358.

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Abstract Motivation Extracting biological insight from genomic data inevitably requires custom software. In many cases, this is accomplished with scripting languages, owing to their accessibility and brevity. Unfortunately, the ease of scripting languages typically comes at a substantial performance cost that is especially acute with the scale of modern genomics datasets. Results We present hts-nim, a high-performance library written in the Nim programming language that provides a simple, scripting-like syntax without sacrificing performance. Availability and implementation hts-nim is available at https://github.com/brentp/hts-nim and the example tools are at https://github.com/brentp/hts-nim-tools both under the MIT license.

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Pavlovikj, Natasha, Joao Carlos Gomes-Neto, Jitender S. Deogun, and Andrew K. Benson. "ProkEvo: an automated, reproducible, and scalable framework for high-throughput bacterial population genomics analyses." PeerJ 9 (May 21, 2021): e11376. http://dx.doi.org/10.7717/peerj.11376.

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Whole Genome Sequence (WGS) data from bacterial species is used for a variety of applications ranging from basic microbiological research, diagnostics, and epidemiological surveillance. The availability of WGS data from hundreds of thousands of individual isolates of individual microbial species poses a tremendous opportunity for discovery and hypothesis-generating research into ecology and evolution of these microorganisms. Flexibility, scalability, and user-friendliness of existing pipelines for population-scale inquiry, however, limit applications of systematic, population-scale approaches. Here, we present ProkEvo, an automated, scalable, reproducible, and open-source framework for bacterial population genomics analyses using WGS data. ProkEvo was specifically developed to achieve the following goals: (1) Automation and scaling of complex combinations of computational analyses for many thousands of bacterial genomes from inputs of raw Illumina paired-end sequence reads; (2) Use of workflow management systems (WMS) such as Pegasus WMS to ensure reproducibility, scalability, modularity, fault-tolerance, and robust file management throughout the process; (3) Use of high-performance and high-throughput computational platforms; (4) Generation of hierarchical-based population structure analysis based on combinations of multi-locus and Bayesian statistical approaches for classification for ecological and epidemiological inquiries; (5) Association of antimicrobial resistance (AMR) genes, putative virulence factors, and plasmids from curated databases with the hierarchically-related genotypic classifications; and (6) Production of pan-genome annotations and data compilation that can be utilized for downstream analysis such as identification of population-specific genomic signatures. The scalability of ProkEvo was measured with two datasets comprising significantly different numbers of input genomes (one with ~2,400 genomes, and the second with ~23,000 genomes). Depending on the dataset and the computational platform used, the running time of ProkEvo varied from ~3-26 days. ProkEvo can be used with virtually any bacterial species, and the Pegasus WMS uniquely facilitates addition or removal of programs from the workflow or modification of options within them. To demonstrate versatility of the ProkEvo platform, we performed a hierarchical-based population structure analyses from available genomes of three distinct pathogenic bacterial species as individual case studies. The specific case studies illustrate how hierarchical analyses of population structures, genotype frequencies, and distribution of specific gene functions can be integrated into an analysis. Collectively, our study shows that ProkEvo presents a practical viable option for scalable, automated analyses of bacterial populations with direct applications for basic microbiology research, clinical microbiological diagnostics, and epidemiological surveillance.

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Chen, Lei-Shih, Yu-Lyu Yeh, Patricia Goodson, Shixi Zhao, Eunju Jung, Amber Muenzenberger, Oi-Man Kwok, and Ping Ma. "Training Texas Public Health Professionals and Professionals-In-Training in Genomics." American Journal of Health Promotion 33, no. 8 (July 8, 2019): 1159–65. http://dx.doi.org/10.1177/0890117119860040.

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Purpose: The purpose of this study is to evaluate the effects of genomics training workshops for public health professionals and professionals-in-training. Design: A pre- and post-test evaluation design with 3-month follow-up. Setting and Participants: Thirteen genomics training workshops were delivered across Texas to 377 public health professionals and professionals-in-training (66.7% were ethnic minorities). Intervention: Three-hour theory-based, face-to-face genomics training workshops focusing on family health history practice were delivered. Methods: We administered surveys prior to the workshops, immediately post-workshops, and at 3-month follow-up to examine the changes in participants’ knowledge, attitudes, intention, self-efficacy, and behavior in adopting genomics into public health practice. Linear mixed modeling analyses were used to analyze the quantitative survey data. A content analysis was also conducted for qualitative survey data analysis. Results: Genomics practice significantly improved among public health professionals at 3-month follow-up ( P < .01). For all participants, knowledge, attitudes, intention, and self-efficacy scores increased significantly immediately post-workshop compared to the pre-workshop scores (all Ps < .01). Knowledge and attitudes scores at the 3-month follow-up remained significantly higher than those scores at the pre-workshop (all Ps < .01). The feedback from workshop participants was positive. Conclusion: Our genomics training workshop is an effective program that can be disseminated at a national level to establish genomic competencies among public health professionals and professionals-in-training in the United States.

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Bertelli, Claire, Keith E. Tilley, and Fiona S. L. Brinkman. "Microbial genomic island discovery, visualization and analysis." Briefings in Bioinformatics 20, no. 5 (June 3, 2018): 1685–98. http://dx.doi.org/10.1093/bib/bby042.

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Abstract Horizontal gene transfer (also called lateral gene transfer) is a major mechanism for microbial genome evolution, enabling rapid adaptation and survival in specific niches. Genomic islands (GIs), commonly defined as clusters of bacterial or archaeal genes of probable horizontal origin, are of particular medical, environmental and/or industrial interest, as they disproportionately encode virulence factors and some antimicrobial resistance genes and may harbor entire metabolic pathways that confer a specific adaptation (solvent resistance, symbiosis properties, etc). As large-scale analyses of microbial genomes increases, such as for genomic epidemiology investigations of infectious disease outbreaks in public health, there is increased appreciation of the need to accurately predict and track GIs. Over the past decade, numerous computational tools have been developed to tackle the challenges inherent in accurate GI prediction. We review here the main types of GI prediction methods and discuss their advantages and limitations for a routine analysis of microbial genomes in this era of rapid whole-genome sequencing. An assessment is provided of 20 GI prediction software methods that use sequence-composition bias to identify the GIs, using a reference GI data set from 104 genomes obtained using an independent comparative genomics approach. Finally, we present guidelines to assist researchers in effectively identifying these key genomic regions.

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Check, Erika. "Fresh analyses put rice genomics on the map." Nature 420, no. 6913 (November 2002): 259. http://dx.doi.org/10.1038/420259a.

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Worden, Alexandra Z., Marie L. Cuvelier, and Douglas H. Bartlett. "In-depth analyses of marine microbial community genomics." Trends in Microbiology 14, no. 8 (August 2006): 331–36. http://dx.doi.org/10.1016/j.tim.2006.06.008.

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Rogne, Marie, and Kjetil Taskén. "Cell signalling analyses in the functional genomics era." New Biotechnology 30, no. 3 (March 2013): 333–38. http://dx.doi.org/10.1016/j.nbt.2013.01.003.

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Walton, S. P., Z. Li, and C. Chan. "Biological network analyses: computational genomics and systems approaches." Molecular Simulation 32, no. 3-4 (March 2006): 203–9. http://dx.doi.org/10.1080/08927020600647052.

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Stalker, H. T., A. K. Weissinger, S. Milla-Lewis, and C. C. Holbrook. "Genomics: An Evolving Science in Peanut." Peanut Science 36, no. 1 (January 1, 2009): 2–10. http://dx.doi.org/10.3146/at07-006.1.

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Abstract Genomic spcience offers new research tools to explore the function of genes and their effects on plants and animals. Arachis hypogaea is a polyploid species of relatively recent origin and molecular analyses with technologies available in the 1980s and 1990s resulted in little progress in the cultivated species because of apparent lack of molecular variation. Large numbers of polymorphisms existing in wild Arachis species led to evolutionary and gene introgression studies. High throughput genomic sequencing technologies have greatly expanded the possibilities for investigating gene function, but techniques are sufficiently expensive that most federal funding has been directed toward model species and ‘major’ crops. Peanut has lagged behind many other crops, but the number of researchers working on the species in the U.S. and internationally has greatly increased during recent years. In an effort to bring researchers who work with a number of legume crops together to discuss common goals, a national strategic planning workshop was held in 2001 which led to the U.S. Legume Crops Genomics Initiative. A second workshop was held in 2004 to develop a plan with specific objectives for cross-legume genomics research and to outline milestones for accomplishments. Specifically for peanut, a genomics strategic planning workshop was organized at Atlanta in 2004 by the American Peanut Council. A broad view of genomic science was adopted and goals were set by participants to include (a) improving the utility of genetic tools for peanut genomics research, (b) improving the efficacy of technology for gene manipulation in genomics, (c) developing a framework for assembling the peanut genetic blueprint, (d) improving knowledge of gene identification and regulation, and (e) providing bioinformatic management of peanut biological information. Teams of researchers, including molecular biologists, plant breeders, pathologists, and many other disciplines need to be developed to fully utilize the potential of genomics for peanut improvement.

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Rodriguez, Oscar L., Anna Ritz, Andrew J. Sharp, and Ali Bashir. "MsPAC: a tool for haplotype-phased structural variant detection." Bioinformatics 36, no. 3 (August 9, 2019): 922–24. http://dx.doi.org/10.1093/bioinformatics/btz618.

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Abstract Summary While next-generation sequencing (NGS) has dramatically increased the availability of genomic data, phased genome assembly and structural variant (SV) analyses are limited by NGS read lengths. Long-read sequencing from Pacific Biosciences and NGS barcoding from 10x Genomics hold the potential for far more comprehensive views of individual genomes. Here, we present MsPAC, a tool that combines both technologies to partition reads, assemble haplotypes (via existing software) and convert assemblies into high-quality, phased SV predictions. MsPAC represents a framework for haplotype-resolved SV calls that moves one step closer to fully resolved, diploid genomes. Availability and implementation https://github.com/oscarlr/MsPAC. Supplementary information Supplementary data are available at Bioinformatics online.

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Vilen, Heikki, Juha-Matti Aalto, Anna Kassinen, Lars Paulin, and Harri Savilahti. "A Direct Transposon Insertion Tool for Modification and Functional Analysis of Viral Genomes." Journal of Virology 77, no. 1 (January 1, 2003): 123–34. http://dx.doi.org/10.1128/jvi.77.1.123-134.2003.

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ABSTRACT Advances in DNA transposition technology have recently generated efficient tools for various types of functional genetic analyses. We demonstrate here the power of the bacteriophage Mu-derived in vitro DNA transposition system for modification and functional characterization of a complete bacterial virus genome. The linear double-stranded DNA genome of Escherichia coli bacteriophage PRD1 was studied by insertion mutagenesis with reporter mini-Mu transposons that were integrated in vitro into isolated genomic DNA. After introduction into bacterial cells by electroporation, recombinant transposon-containing virus clones were identified by autoradiography or visual blue-white screening employing α-complementation of E. coli β-galactosidase. Additionally, a modified transposon with engineered NotI sites at both ends was used to introduce novel restriction sites into the phage genome. Analysis of the transposon integration sites in the genomes of viable recombinant phage generated a functional map, collectively indicating genes and genomic regions essential and nonessential for virus propagation. Moreover, promoterless transposons defined the direction of transcription within several insert-tolerant genomic regions. These strategies for the analysis of viral genomes are of a general nature and therefore may be applied to functional genomics studies in all prokaryotic and eukaryotic cell viruses.

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Lofgren, Lotus A., Brandon S. Ross, Robert A. Cramer, and Jason E. Stajich. "The pan-genome of Aspergillus fumigatus provides a high-resolution view of its population structure revealing high levels of lineage-specific diversity driven by recombination." PLOS Biology 20, no. 11 (November 17, 2022): e3001890. http://dx.doi.org/10.1371/journal.pbio.3001890.

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Aspergillus fumigatus is a deadly agent of human fungal disease where virulence heterogeneity is thought to be at least partially structured by genetic variation between strains. While population genomic analyses based on reference genome alignments offer valuable insights into how gene variants are distributed across populations, these approaches fail to capture intraspecific variation in genes absent from the reference genome. Pan-genomic analyses based on de novo assemblies offer a promising alternative to reference-based genomics with the potential to address the full genetic repertoire of a species. Here, we evaluate 260 genome sequences of A. fumigatus including 62 newly sequenced strains, using a combination of population genomics, phylogenomics, and pan-genomics. Our results offer a high-resolution assessment of population structure and recombination frequency, phylogenetically structured gene presence–absence variation, evidence for metabolic specificity, and the distribution of putative antifungal resistance genes. Although A. fumigatus disperses primarily via asexual conidia, we identified extraordinarily high levels of recombination with the lowest linkage disequilibrium decay value reported for any fungal species to date. We provide evidence for 3 primary populations of A. fumigatus, with recombination occurring only rarely between populations and often within them. These 3 populations are structured by both gene variation and distinct patterns of gene presence–absence with unique suites of accessory genes present exclusively in each clade. Accessory genes displayed functional enrichment for nitrogen and carbohydrate metabolism suggesting that populations may be stratified by environmental niche specialization. Similarly, the distribution of antifungal resistance genes and resistance alleles were often structured by phylogeny. Altogether, the pan-genome of A. fumigatus represents one of the largest fungal pan-genomes reported to date including many genes unrepresented in the Af293 reference genome. These results highlight the inadequacy of relying on a single-reference genome-based approach for evaluating intraspecific variation and the power of combined genomic approaches to elucidate population structure, genetic diversity, and putative ecological drivers of clinically relevant fungi.

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Ward, Linda D., Celestina Barbosa-Leiker, and Brian F. French. "Item and Structure Evaluation of the Genomic Nursing Concept Inventory." Journal of Nursing Measurement 26, no. 1 (May 2018): 163–75. http://dx.doi.org/10.1891/1061-3749.26.1.163.

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Background and Purpose:Genomic nursing education requires a genomic literacy assessment supported by evidence of reliability and validity. This study applied psychometric analyses to provide support for the Genomic Nursing Concept Inventory (GNCI).Methods:Over nine semesters, baccalaureate nursing students (N = 1,065) completed the GNCI on the first and last days of genomics instruction. Psychometric analyses assessed scale and item performance pre- and post-instruction.Results:Exploratory factor analysis supported scale unidimensionality and identified items with low pattern coefficients. Analyses supported test–retest and internal consistency reliability and criterion validity. Scale difficulty decreased by 28% from pre- to post-instruction. Underperforming items were identified for further inventory refinement.Conclusions:Findings support use of the GNCI to measure learning needs pre-instruction and learning gains post-instruction. Data also inform planned inventory revision.

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Riley, Robert, Sajeet Haridas, Kenneth H. Wolfe, Mariana R. Lopes, Chris Todd Hittinger, Markus Göker, Asaf A. Salamov, et al. "Comparative genomics of biotechnologically important yeasts." Proceedings of the National Academy of Sciences 113, no. 35 (August 17, 2016): 9882–87. http://dx.doi.org/10.1073/pnas.1603941113.

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Ascomycete yeasts are metabolically diverse, with great potential for biotechnology. Here, we report the comparative genome analysis of 29 taxonomically and biotechnologically important yeasts, including 16 newly sequenced. We identify a genetic code change, CUG-Ala, in Pachysolen tannophilus in the clade sister to the known CUG-Ser clade. Our well-resolved yeast phylogeny shows that some traits, such as methylotrophy, are restricted to single clades, whereas others, such as l-rhamnose utilization, have patchy phylogenetic distributions. Gene clusters, with variable organization and distribution, encode many pathways of interest. Genomics can predict some biochemical traits precisely, but the genomic basis of others, such as xylose utilization, remains unresolved. Our data also provide insight into early evolution of ascomycetes. We document the loss of H3K9me2/3 heterochromatin, the origin of ascomycete mating-type switching, and panascomycete synteny at the MAT locus. These data and analyses will facilitate the engineering of efficient biosynthetic and degradative pathways and gateways for genomic manipulation.

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Mühleisen, Thomas W., Andreas J. Forstner, Per Hoffmann, and Sven Cichon. "Brain imaging genomics: influences of genomic variability on the structure and function of the human brain." Medizinische Genetik 32, no. 1 (May 1, 2020): 47–56. http://dx.doi.org/10.1515/medgen-2020-2007.

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Abstract Brain imaging genomics is an emerging discipline in which genomic and brain imaging data are integrated in order to elucidate the molecular mechanisms that underly brain phenotypes and diseases, including neuropsychiatric disorders. As with all genetic analyses of complex traits and diseases, brain imaging genomics has evolved from small, individual candidate gene investigations towards large, collaborative genome-wide association studies. Recent investigations, mostly population-based, have studied well-powered cohorts comprising tens of thousands of individuals and identified multiple robust associations of single-nucleotide polymorphisms and copy number variants with structural and functional brain phenotypes. Such systematic genomic screens of millions of genetic variants have generated initial insights into the genetic architecture of brain phenotypes and demonstrated that their etiology is polygenic in nature, involving multiple common variants with small effect sizes and rare variants with larger effect sizes. Ongoing international collaborative initiatives are now working to obtain a more complete picture of the underlying biology. As in other complex phenotypes, novel approaches – such as gene–gene interaction, gene–environment interaction, and epigenetic analyses – are being implemented in order to investigate their contribution to the observed phenotypic variability. An important consideration for future research will be the translation of brain imaging genomics findings into clinical practice.

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Silva, Fabíola de Jesus, Larissa Carvalho Ferreira, Vicente Paulo Campos, Valter Cruz-Magalhães, Aline Ferreira Barros, Jackeline Pereira Andrade, Daniel P. Roberts, and Jorge Teodoro de Souza. "Complete Genome Sequence of the Biocontrol Agent Bacillus velezensis UFLA258 and Its Comparison with Related Species: Diversity within the Commons." Genome Biology and Evolution 11, no. 10 (October 1, 2019): 2818–23. http://dx.doi.org/10.1093/gbe/evz208.

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Abstract In this study, the full genome sequence of Bacillus velezensis strain UFLA258, a biological control agent of plant pathogens was obtained, assembled, and annotated. With a comparative genomics approach, in silico analyses of all complete genomes of B. velezensis and closely related species available in the database were performed. The genome of B. velezensis UFLA258 consisted of a single circular chromosome of 3.95 Mb in length, with a mean GC content of 46.69%. It contained 3,949 genes encoding proteins and 27 RNA genes. Analyses based on Average Nucleotide Identity and Digital DNA–DNA Hybridization and a phylogeny with complete sequences of the rpoB gene confirmed that 19 strains deposited in the database as Bacillus amyloliquefaciens were in fact B. velezensis. In total, 115 genomes were analyzed and taxonomically classified as follows: 105 were B. velezensis, 9 were B. amyloliquefaciens, and 1 was Bacillus siamensis. Although these species are phylogenetically close, the combined analyses of several genomic characteristics, such as the presence of biosynthetic genes encoding secondary metabolites, CRISPr/Cas arrays, Average Nucleotide Identity and Digital DNA–DNA Hybridization, and other information on the strains, including isolation source, allowed their unequivocal classification. This genomic analysis expands our knowledge about the closely related species, B. velezensis, B. amyloliquefaciens, and B. siamensis, with emphasis on their taxonomical status.

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Nakagawa, Hidewaki. "Prostate cancer genomics by high-throughput technologies: genome-wide association study and sequencing analysis." Endocrine-Related Cancer 20, no. 4 (April 26, 2013): R171—R181. http://dx.doi.org/10.1530/erc-13-0113.

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Prostate cancer (PC) is the most common malignancy in males. It is evident that genetic factors at both germline and somatic levels play critical roles in prostate carcinogenesis. Recently, genome-wide association studies (GWAS) by high-throughput genotyping technology have identified more than 70 germline variants of various genes or chromosome loci that are significantly associated with PC susceptibility. They include multiple 8q24 loci, prostate-specific genes, and metabolism-related genes. Somatic alterations in PC genomes have been explored by high-throughput sequencing technologies such as whole-genome sequencing and RNA sequencing, which have identified a variety of androgen-responsive events and fusion transcripts represented by E26 transformation-specific (ETS) gene fusions. Recent innovations in high-throughput genomic technologies have enabled us to analyze PC genomics more comprehensively, more precisely, and on a larger scale in multiple ethnic groups to increase our understanding of PC genomics and biology in germline and somatic studies, which can ultimately lead to personalized medicine for PC diagnosis, prevention, and therapy. However, these data indicate that the PC genome is more complex and heterogeneous than we expected from GWAS and sequencing analyses.

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Klinger, Christie R., Jennifer A. Lau, and Katy D. Heath. "Ecological genomics of mutualism decline in nitrogen-fixing bacteria." Proceedings of the Royal Society B: Biological Sciences 283, no. 1826 (March 16, 2016): 20152563. http://dx.doi.org/10.1098/rspb.2015.2563.

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Anthropogenic changes can influence mutualism evolution; however, the genomic regions underpinning mutualism that are most affected by environmental change are generally unknown, even in well-studied model mutualisms like the interaction between legumes and their nitrogen (N)-fixing rhizobia. Such genomic information can shed light on the agents and targets of selection maintaining cooperation in nature. We recently demonstrated that N-fertilization has caused an evolutionary decline in mutualistic partner quality in the rhizobia that form symbiosis with clover. Here, population genomic analyses of N-fertilized versus control rhizobium populations indicate that evolutionary differentiation at a key symbiosis gene region on the symbiotic plasmid (pSym) contributes to partner quality decline. Moreover, patterns of genetic variation at selected loci were consistent with recent positive selection within N-fertilized environments, suggesting that N-rich environments might select for less beneficial rhizobia. By studying the molecular population genomics of a natural bacterial population within a long-term ecological field experiment, we find that: (i) the N environment is indeed a potent selective force mediating mutualism evolution in this symbiosis, (ii) natural variation in rhizobium partner quality is mediated in part by key symbiosis genes on the symbiotic plasmid, and (iii) differentiation at selected genes occurred in the context of otherwise recombining genomes, resembling eukaryotic models of adaptation.

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Khorraminezhad, Leila, Mickael Leclercq, Arnaud Droit, Jean-François Bilodeau, and Iwona Rudkowska. "Statistical and Machine-Learning Analyses in Nutritional Genomics Studies." Nutrients 12, no. 10 (October 14, 2020): 3140. http://dx.doi.org/10.3390/nu12103140.

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Nutritional compounds may have an influence on different OMICs levels, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, and metagenomics. The integration of OMICs data is challenging but may provide new knowledge to explain the mechanisms involved in the metabolism of nutrients and diseases. Traditional statistical analyses play an important role in description and data association; however, these statistical procedures are not sufficiently enough powered to interpret the large integrated multiple OMICs (multi-OMICS) datasets. Machine learning (ML) approaches can play a major role in the interpretation of multi-OMICS in nutrition research. Specifically, ML can be used for data mining, sample clustering, and classification to produce predictive models and algorithms for integration of multi-OMICs in response to dietary intake. The objective of this review was to investigate the strategies used for the analysis of multi-OMICs data in nutrition studies. Sixteen recent studies aimed to understand the association between dietary intake and multi-OMICs data are summarized. Multivariate analysis in multi-OMICs nutrition studies is used more commonly for analyses. Overall, as nutrition research incorporated multi-OMICs data, the use of novel approaches of analysis such as ML needs to complement the traditional statistical analyses to fully explain the impact of nutrition on health and disease.

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Craig, Rory J., Ahmed R. Hasan, Rob W. Ness, and Peter D. Keightley. "Comparative genomics of Chlamydomonas." Plant Cell 33, no. 4 (February 2, 2021): 1016–41. http://dx.doi.org/10.1093/plcell/koab026.

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Abstract Despite its role as a reference organism in the plant sciences, the green alga Chlamydomonas reinhardtii entirely lacks genomic resources from closely related species. We present highly contiguous and well-annotated genome assemblies for three unicellular C. reinhardtii relatives: Chlamydomonas incerta, Chlamydomonas schloesseri, and the more distantly related Edaphochlamys debaryana. The three Chlamydomonas genomes are highly syntenous with similar gene contents, although the 129.2 Mb C. incerta and 130.2 Mb C. schloesseri assemblies are more repeat-rich than the 111.1 Mb C. reinhardtii genome. We identify the major centromeric repeat in C. reinhardtii as a LINE transposable element homologous to Zepp (the centromeric repeat in Coccomyxa subellipsoidea) and infer that centromere locations and structure are likely conserved in C. incerta and C. schloesseri. We report extensive rearrangements, but limited gene turnover, between the minus mating type loci of these Chlamydomonas species. We produce an eight-species core-Reinhardtinia whole-genome alignment, which we use to identify several hundred false positive and missing genes in the C. reinhardtii annotation and >260,000 evolutionarily conserved elements in the C. reinhardtii genome. In summary, these resources will enable comparative genomics analyses for C. reinhardtii, significantly extending the analytical toolkit for this emerging model system.

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Raz, Ofir, Liming Tao, Tamir Biezuner, Tzipy Marx, Yaara Neumeier, Narek Tumanyan, and Ehud Shapiro. "Whole-Genome Amplification—Surveying Yield, Reproducibility, and Heterozygous Balance, Reported by STR-Targeting MIPs." International Journal of Molecular Sciences 23, no. 11 (May 31, 2022): 6161. http://dx.doi.org/10.3390/ijms23116161.

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Whole-genome amplification is a crucial first step in nearly all single-cell genomic analyses, with the following steps focused on its products. Bias and variance caused by the whole-genome amplification process add numerous challenges to the world of single-cell genomics. Short tandem repeats are sensitive genomic markers used widely in population genetics, forensics, and retrospective lineage tracing. A previous evaluation of common whole-genome amplification targeting ~1000 non-autosomal short tandem repeat loci is extended here to ~12,000 loci across the entire genome via duplex molecular inversion probes. Other than its improved scale and reduced noise, this system detects an abundance of heterogeneous short tandem repeat loci, allowing the allelic balance to be reported. We show here that while the best overall yield is obtained using RepliG-SC, the maximum uniformity between alleles and reproducibility across cells are maximized by Ampli1, rendering it the best candidate for the comparative heterozygous analysis of single-cell genomes.

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Laso-Jadart, Romuald, Christophe Ambroise, Pierre Peterlongo, and Mohammed-Amin Madoui. "metaVaR: Introducing metavariant species models for reference-free metagenomic-based population genomics." PLOS ONE 15, no. 12 (December 30, 2020): e0244637. http://dx.doi.org/10.1371/journal.pone.0244637.

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The availability of large metagenomic data offers great opportunities for the population genomic analysis of uncultured organisms, which represent a large part of the unexplored biosphere and play a key ecological role. However, the majority of these organisms lack a reference genome or transcriptome, which constitutes a technical obstacle for classical population genomic analyses. We introduce the metavariant species (MVS) model, in which a species is represented only by intra-species nucleotide polymorphism. We designed a method combining reference-free variant calling, multiple density-based clustering and maximum-weighted independent set algorithms to cluster intra-species variants into MVSs directly from multisample metagenomic raw reads without a reference genome or read assembly. The frequencies of the MVS variants are then used to compute population genomic statistics such as FST, in order to estimate genomic differentiation between populations and to identify loci under natural selection. The MVS construction was tested on simulated and real metagenomic data. MVSs showed the required quality for robust population genomics and allowed an accurate estimation of genomic differentiation (ΔFST < 0.0001 and <0.03 on simulated and real data respectively). Loci predicted under natural selection on real data were all detected by MVSs. MVSs represent a new paradigm that may simplify and enhance holistic approaches for population genomics and the evolution of microorganisms.

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MINNING, CHIN, NORFILZA MOHD MOKHTAR, NORLIA ABDULLAH, ROHAIZAK MUHAMMAD, NOR AINA EMRAN, SITI AISHAH MD ALI, ROSLAN HARUN, and RAHMAN JAMAL. "Exploring breast carcinogenesis through integrative genomics and epigenomics analyses." International Journal of Oncology 45, no. 5 (August 27, 2014): 1959–68. http://dx.doi.org/10.3892/ijo.2014.2625.

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Yu, Su-May, Swee-Suak Ko, Chwan-Yang Hong, Hsou-Jan Sun, Yue-Ie Hsing, Chii-Gong Tong, and Tuan-Hua David Ho. "Global functional analyses of rice promoters by genomics approaches." Plant Molecular Biology 65, no. 4 (October 9, 2007): 417–25. http://dx.doi.org/10.1007/s11103-007-9232-1.

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Journal articles on the topic 'Genomics analyses'

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