Relevant bibliographies by topics / Genomics analyses

Academic literature on the topic 'Genomics analyses'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "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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Dissertations / Theses on the topic "Genomics analyses"

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Seibert, Sara Rose. "Host-parasite interactions: comparative analyses of population genomics, disease-associated genomic regions, and host use." Wright State University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1590585260282244.

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Steinberg, Julia. "Functional genomics analyses of neuropsychiatric and neurodevelopmental disorders." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:e47d1ac2-de92-47d8-864b-dac0bf6669e8.

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Recent large-scale genome-wide studies for many human disorders have identified associations with numerous genetic variants. The biological interpretation of these variants presents a major challenge. In particular, the identification of biological pathways underlying the association could provide crucial insights into the disease aetiologies. In this thesis, I used functional genomics approaches to increase our understanding of neuropsychiatric and neurodevelopmental disorders. Firstly, in an integrative analysis of autism spectrum disorder (ASD), I looked into the role of genes targeted by Fragile-X Mental Retardation Protein ("FMRP targets"). I found evidence that FMRP targets contribute to ASD via two distinct aetiologies: (1) ultra-rare and highly penetrant single disruptions of embryonically upregulated FMRP targets ("single-hit aetiology") or (2) the combination of multiple less penetrant disruptions of synaptic FMRP targets ("multiple-hit aetiology"). In particular, I developed a pathway-association test sensitive to multiple-hit aetiologies. Secondly, I carried out an integrative analysis of bipolar disorder, following up a previously identified association with long-term potentiation. The association was not consistent across independent SNP and CNV datasets. Thirdly, I addressed the difficulty in identifying functional relationships between genes by integrating different datasets into a gene functional-linkage network tuned to the nervous system ("NsNet"). NsNet identified functional links between the genes disrupted by de novo loss-of-function mutations in ASD and, separately, in schizophrenia probands more sensitively than a general functional-linkage network. Fourthly, I considered the challenge of interpreting the phenotypic impact of gene disruptions, focusing on the identification of haploinsufficient genes. I constructed a gene haploinsufficiency score based on genome-wide datasets. Compared to existing approaches, the new score performed better in identifying less-studied haploinsufficient genes. This work both extends the methodology to detect the contribution of genetic variation to neuropsychiatric disorders and also yields insights into the variant genes and the pathways that underlie them. Firstly, in an integrative analysis of autism spectrum disorder (ASD), I looked into the role of genes targeted by Fragile-X Mental Retardation Protein ("FMRP targets"). I found evidence that FMRP targets contribute to ASD via two distinct aetiologies: (1) ultra-rare and highly penetrant single disruptions of embryonically upregulated FMRP targets ("single-hit aetiology") or (2) the combination of multiple less penetrant disruptions of synaptic FMRP targets ("multiple-hit aetiology"). In particular, I developed a pathway-association test sensitive to multiple-hit aetiologies. Secondly, I carried out an integrative analysis of bipolar disorder, following up a previously identified association with long-term potentiation. The association was not consistent across independent SNP and CNV datasets. Thirdly, I addressed the difficulty in identifying functional relationships between genes by integrating different datasets into a gene functional-linkage network tuned to the nervous system ("NsNet"). NsNet identified functional links between the genes disrupted by de novo loss-of-function mutations in ASD and, separately, in schizophrenia probands more sensitively than a general functional-linkage network. Fourthly, I considered the challenge of interpreting the phenotypic impact of gene disruptions, focusing on the identification of haploinsufficient genes. I constructed a gene haploinsufficiency score based on genome-wide datasets. Compared to existing approaches, the new score performed better in identifying less-studied haploinsufficient genes. This work both extends the methodology to detect the contribution of genetic variation to neuropsychiatric disorders and also yields insights into the variant genes and the pathways that underlie them.
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Beghini, Francesco. "Integrative computational microbial genomics for large-scale metagenomic analyses." Doctoral thesis, Università degli studi di Trento, 2021. http://hdl.handle.net/11572/296396.

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Advancements of DNA sequencing technologies and improvement of analytic methods changed the way we analyze complex microbial communities (metagenomics). In only a few years, these methods have evolved so far as to ease a more precise community profiling and to allow high-level strain resolution. A typical computational metagenomic analysis relies on mapping raw DNA sequencing reads against sets of “reference” microbial genomes usually obtained through single-isolate sequencing. With an almost exponential increase in the number of reference genomes deposited daily in public data sets, current computational methods are incapable of managing and exploiting such a rich reference set, limiting the potential of metagenomic investigations.In my doctoral thesis, I will present my contribution towards fully exploiting the available reference data for metagenomic analysis. I developed ChocoPhlAn, an integrated pipeline for automatic retrieval, organization, and annotation of reference genomes and gene families as the foundation for bioBakery 3, an improved set of computational methods for the analysis of shotgun metagenomics data. Using the latest set of microbial genomic reference data available and processed through ChocoPhlAn, the six bioBakery 3 tools that I updated resulted in more comprehensive and higher resolution taxonomic and functional profiling of microbiomes and allowed strain-level characterization of their constituent strains. After extensive benchmarks with previous versions and competitors, we applied those methods on more than 10,000 real metagenomes and showed how metagenomics can be a more powerful tool for identifying novel links between the gut microbiome and disease conditions such as colorectal cancer and Inflammatory Bowel Disease. Accurate strain-level phylogeny reconstruction and pangenomic analysis of 7,783 metagenomes revealed novel functional, phylogenetic, and geographic diversity of Ruminococcus bromii, a common and highprevalent gut inhabitant. We then focused on the influence of the Eukaryotic fraction of the human microbiome and its potential impact on human gut health, which is a frequently overlooked aspect of microbial communities. To this end, we assessed the presence of the Eukaryotic parasite Blastocystis spp., in more than 2,000 metagenomes from 5 continents for understanding associations with disease statuses and geographic conditions. We showed that Blastocystis is the most common Eukaryotic colonizer of the human gut, and it is particularly prevalent in healthy subjects and non-westernized populations. We further explored intra-subtype diversity by reconstructing and functionally profiling new metagenomic-assembled Blastocystis genomes, showing how metagenomics can be valuable to unravel protists' genomics and providing a genomic resource for additional integration of non-bacterial taxa in metagenomic pipelines.9 By developing and implementing ChocoPhlAn and the new bioBakery tools, we provided the community with improved and efficient microbiome profiling tools and started identifying novel patterns of association between host and niche-associated microbiomes and discovering previously uncharacterized species from human and non-human hosts.
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Shultz, Randall William. "Genomic and Molecular Analyses of the Core DNA Replication Machinery in Plants." NCSU, 2007. http://www.lib.ncsu.edu/theses/available/etd-03132007-124000/.

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Accurate and complete DNA replication is essential for maintaining the integrity of the genome. In eukaryotes, this process requires the coordinated action of numerous molecular machines. Based on yeast and animal model systems, we defined a set of fifty-one ?core DNA replication proteins? that are integral to the initiation, DNA synthesis, and Okazaki fragment maturation functions of DNA replication. We used computational analyses to identify putative homologs in the genomes of two plants, Arabidopsis thaliana (Arabidopsis) and Oryza sativa (rice), providing the first comprehensive view of the core DNA replication machinery in plants. Our results indicated that the overall composition of this apparatus is conserved, but plants are unique in that multiple DNA replication genes exist as small gene families. Fourteen of the genes we annotated in this study have not been previously reported in the literature, and we have provided revised gene models for seventeen plant proteins. To better understand how the DNA replication machinery functions in plants, we cloned multiple subunits of the pre-replication complex (pre-RC) from Arabidopsis and generated antibodies against four key components of this complex ? AtORC1, AtORC2, AtMCM5, and AtMCM7. We demonstrated that the pre-RC is developmentally regulated in Arabidopsis and, consistent with a role in DNA replication, is abundant in proliferating tissues. We used immunocytochemical and biochemical methods to characterize MCM7 in plants. We observed two distinct localization patterns for plant MCM7 proteins. In most cells, MCM7 was nuclear and colocalized with DNA. In a small fraction of cells, MCM7 was dispersed throughout the cytoplasmic compartment. Biochemical analysis confirmed that MCM7 binds to chromatin and that it is present in the nucleus at least during the G1, S and G2 cell cycle stages. Together, these analyses support a model where the MCM complex is loaded onto DNA in late M and early G1, released into the nucleoplasm during S phase followed by a brief dispersion into the cytoplasmic compartment concurrent with nuclear envelope breakdown in mitosis.
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Herzog, Rebecca [Verfasser]. "Global change genomics - comparative genomic analyses on environmental associated speciation and adaptation processes in Odonata / Rebecca Herzog." Hannover : Gottfried Wilhelm Leibniz Universität, 2021. http://d-nb.info/1238221785/34.

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Soares, Siomar de Castro. "Pan-genomic analyses of Corynebacterium pseudotuberculosis and characterization of the biovars ovis and equi through comparative genomics." Universidade Federal de Minas Gerais, 2013. http://hdl.handle.net/1843/BUOS-9B8JTZ.

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Corynebacterium pseudotuberculosis is the causative agent of diverse communicable diseases in small ruminants (biovar ovis), horses, camels, buffalo and other animals (biovar equi), which mainly differ in symptoms and site of infection. Additionally, the diseases present a highly important economic problem worldwide and there is still a lack of efficient treatments against C. pseudotuberculosis. In this work, we describe the steps from the first genome sequencing of a strain of C. pseudotuberculosis to the pangenomic analyses of 15 strains isolated from different hosts and countries with diverse symptoms. Briefly, we introduce the genus Corynebacterium and the in silico analyses performed in pathogenic species of this genus to date. Then, we describe the implementation of a software for the prediction of pathogenicity islands (PAIs) in bacteria (PIPS), which outperformed the other available software, and identified 7 PAIs with important virulence factors in C. pseudotuberculosis biovar ovis. Moreover, we extend the analyses of PAIs to strains of C. pseudotuberculosis biovar equi and predict 49 putative vaccine targets, in silico, which are commonly shared by both biovars, ovis and equi. Finally, we present the phylogenomic, pan-genomic, core genomic, singletons and genomic plasticity analyses of the 15 strains of C. pseudotuberculosis, from both biovars. All the analyses performed here point for a clonal-like behavior of C. pseudotuberculosis, which could be the result of the facultative intracellular behavior of the species. Moreover, the biovar equi presents a higher variability in gene content when compared to biovar ovis, specially in PAI regions. Noteworthy, the strains from biovar ovis present a high degree of similarity in pili clusters of genes, whereas the biovar equi strains are very variable. The conservation of pili clusters of genes in biovar ovis could account for the ability of these strains to spread inside host tissues and penetrate live cells to live intracellularly, where they would have less contact to other organisms, thus, possibly explaining the clonal-like behavior of the biovar ovis.
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Itou, Junji. "Functional and comparative genomics analyses of pmp22 in medaka fish." Kyoto University, 2009. http://hdl.handle.net/2433/126464.

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Dumitriu, Alexandra. "Genome-wide expression and genomic data integration analyses in sporadic Parkinson disease." Thesis, Boston University, 2012. https://hdl.handle.net/2144/31542.

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Thesis (Ph.D.)--Boston University
Parkinson disease (PD) is the second most common neurodegenerative disorder, affecting an estimated 2% of the population above 65 years of age. Although familial forms of PD have been linked to specific mutations responsible for the onset of the disease, the majority of PD cases is still of unknown etiology. PD has been traditionally studied using individual genetic methods, such as linkage analysis, genome-wide association (GWAS), or microarray expression studies. Nevertheless, the intrinsic disease genetic variability, and the unilateral analysis approach of available datasets made the detection of robust gene or pathway signals difficult. Studies of PD that combine a range of systems genetics approaches, and integrate complementary disease-relevant genetic datasets, represent a promising approach for accommodating prior inconsistent, as well as diverse results. To investigate the genetics of idiopathic PD, I performed the largest genome-wide expression study in brain tissue to date. The study was carried out on the 1-color Agilent 60-mer Whole Human Genome Microarray, and included 26 neurologically healthy control and 27 PD samples from the frontal cortex Brodmann 9 area (BA9). The selected brain samples were of high quality (high pH and RNA integrity, no significant signs of Alzheimer disease pathology), and had rich documentation of neuropathological and clinical information available. I analyzed the microarray expression results in combination with genotyping data for PD-associated single nucleotide polymorphisms obtained for the microarray brain samples, and detected a pathway of interest for PD involving the FOXO1 (Forkhead box protein O1) gene. This result was verified in additional publically available expression datasets. I then performed a network-based canonical pathway analysis of PD, combining results from available GWAS, microarray expression, and animal model expression studies. The used analysis framework was a human functional-linkage network (FLN), consisting of genes as nodes, and weighted links indicating the confidence of gene-pair involvement in similar biological processes. I demonstrated the relevance of the used FLN for studying PD. Additionally, I ranked genes and pathways based on the available disease datasets. The frontal cortex BA9 study, and an additional non-PD microarray study were used as the positive and negative controls, respectively, for the obtained results.
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Dumitriu, Alexandra. "Genome-wide expression and genomic data integration analyses in sporadic Parkinson Disease." Thesis, Boston University, 2010. https://hdl.handle.net/2144/31542.

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Thesis (Ph.D.)--Boston University
PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you.
Parkinson disease (PD) is the second most common neurodegenerative disorder, affecting an estimated 2% of the population above 65 years of age. Although familial forms of PD have been linked to specific mutations responsible for the onset of the disease, the majority of PD cases is still of unknown etiology. PD has been traditionally studied using individual genetic methods, such as linkage analysis, genome-wide association (GWAS), or microarray expression studies. Nevertheless, the intrinsic disease genetic variability, and the unilateral analysis approach of available datasets made the detection of robust gene or pathway signals difficult. Studies of PD that combine a range of systems genetics approaches, and integrate complementary disease-relevant genetic datasets, represent a promising approach for accommodating prior inconsistent, as well as diverse results. To investigate the genetics of idiopathic PD, I performed the largest genome-wide expression study in brain tissue to date. The study was carried out on the 1-color Agilent 60-mer Whole Human Genome Microarray, and included 26 neurologically healthy control and 27 PD samples from the frontal cortex Brodmann 9 area (BA9). The selected brain samples were of high quality (high pH and RNA integrity, no significant signs of Alzheimer disease pathology), and had rich documentation of neuropathological and clinical information available. I analyzed the microarray expression results in combination with genotyping data for PD-associated single nucleotide polymorphisms obtained for the microarray brain samples, and detected a pathway of interest for PD involving the FOXO1 (Forkhead box protein O1) gene. This result was verified in additional publically available expression datasets. I then performed a network-based canonical pathway analysis of PD, combining results from available GWAS, microarray expression, and animal model expression studies. The used analysis framework was a human functional-linkage network (FLN), consisting of genes as nodes, and weighted links indicating the confidence of gene-pair involvement in similar biological processes. I demonstrated the relevance of the used FLN for studying PD. Additionally, I ranked genes and pathways based on the available disease datasets. The frontal cortex BA9 study, and an additional non-PD microarray study were used as the positive and negative controls, respectively, for the obtained results.
2031-01-01
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Dunning, Mark J. "Genome-wide analyses using bead-based microarrays." Thesis, University of Cambridge, 2008. https://www.repository.cam.ac.uk/handle/1810/218542.

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Microarrays are now an established tool for biological research and have a wide range of applications. In this thesis I investigate the BeadArray microarray technology developed by Illumina. The design of this technology is unique and gives rise to many computational and statistical challenges. However, I show how knowledge from other microarray technologies can be used to our advantage. I describe the beadarray software package, which is now used by researchers around the world. The development of this software was motivated by the fact that Illumina's software (BeadStudio) gives a summarised view of Illumina data and does not gives users any control over several processing steps that were found to be crucial for other microarray technologies. A main feature of beadarray is the ability to access raw data. The advantages of such data include the ability to perform more detailed quality assessment and greater control over the analysis at all stages. The analysis of a control experiment shows that the processing steps used in BeadStudio can be improved. In particular, utilising variances calculated from the raw data can increase the ability to detect genes which have different expression levels between samples, a common goal for microarray studies. The data from the control experiment are made available for other researchers to use and validate their own analysis methods. One issue discovered during the analysis of the control experiment was that only half of the intended genes could be reliably measured due to problems in the design of the probes targetting particular genes. By considering a large set of publicly available Illumina arrays, I show how such unreliable measurements can affect the analysis of Illumina data. I also show how potential problems can be identified in advance of an experiment and incorporated into an analysis pipeline.
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Books on the topic "Genomics analyses"

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service), ScienceDirect (Online. Cryo-EM: Analyses, interpretation, and case studies. San Diego, Calif: Academic Press/Elsevier, 2010.

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Bioinformatics: Genomics and post-genomics. Chichester, England: John Wiley & Sons, 2006.

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Bickel, David R. Genomics Data Analysis. Boca Raton, FL : CRC Press, 2019.: Chapman and Hall/CRC, 2019. http://dx.doi.org/10.1201/9780429299308.

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D, Protopapas Alex, ed. Genomics. Upper Saddle River, NJ: Prentice-Hall, 2005.

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H, Bergman Nicholas, ed. Comparative genomics. Totowa, NJ: Humana Press, 2007.

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Genome clustering: From linguistic models to classification of genetic texts. Berlin: Springer, 2010.

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Foundations of comparative genomics. Boston, MA: Elsevier Academic Press, 2006.

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Nicholas, Housby J., ed. Mass spectrometry and genomic analysis. Dordrecht: Kluwer Academic Publishers, 2001.

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Nicholas Housby, J., ed. Mass Spectrometry and Genomic Analysis. Dordrecht: Springer Netherlands, 2001. http://dx.doi.org/10.1007/0-306-47595-2.

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Pompanon, François, and Aurélie Bonin, eds. Data Production and Analysis in Population Genomics. Totowa, NJ: Humana Press, 2012. http://dx.doi.org/10.1007/978-1-61779-870-2.

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Book chapters on the topic "Genomics analyses"

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Rampitsch, Christof, and Natalia V. Bykova. "Methods for Functional Proteomic Analyses." In Plant Genomics, 93–110. Totowa, NJ: Humana Press, 2009. http://dx.doi.org/10.1007/978-1-59745-427-8_6.

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Aoki, Takashi, Carl Tucker, and Ikuo Hirono. "Expressed sequence tag analyses of the Japanese flounder, Paralichthys olivaceus." In Aquatic Genomics, 102–14. Tokyo: Springer Japan, 2003. http://dx.doi.org/10.1007/978-4-431-65938-9_9.

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Sankoff, David, Marie-Noelle Parent, and David Bryant. "Accuracy and Robustness of Analyses Based on Numbers of Genes in Observed Segments." In Comparative Genomics, 299–306. Dordrecht: Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-011-4309-7_27.

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Urano, Akihisa, and Hironori Ando. "Quantitative analyses of the levels of hormonal mRNAs in the salmon neuroendocrine system." In Aquatic Genomics, 225–35. Tokyo: Springer Japan, 2003. http://dx.doi.org/10.1007/978-4-431-65938-9_20.

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Saxena, Aditya. "Bioinformatics of Meta-analyses of Genomic Data." In Bioinformatics and Human Genomics Research, 331–34. New York: CRC Press, 2021. http://dx.doi.org/10.1201/9781003005926-15.

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Zhang, Wei, Edward G. Dudley, and Joseph T. Wade. "Genomic and Transcriptomic Analyses of Foodborne Bacterial Pathogens." In Genomics of Foodborne Bacterial Pathogens, 311–41. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-7686-4_10.

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Reid, Adam James, Sarah Addou, Robert Rentzsch, Juan Ranea, and Christine Orengo. "Domain Family Analyses to Understand Protein Function Evolution." In Evolutionary Genomics and Systems Biology, 231–50. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2010. http://dx.doi.org/10.1002/9780470570418.ch13.

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Kang, Manjit S. "Genotype-environment interaction and stability analyses: an update." In Quantitative genetics, genomics and plant breeding, 140–61. Wallingford: CABI, 2020. http://dx.doi.org/10.1079/9781789240214.0140.

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Muthuramalingam, Meenakumari, Yong-Fang Li, and Ramamurthy Mahalingam. "Genomics-Based Analyses of Environmental Stresses in Crop Plants." In Approaches to Plant Stress and their Management, 383–93. New Delhi: Springer India, 2013. http://dx.doi.org/10.1007/978-81-322-1620-9_22.

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Ahrendt, Steven R., Stephen J. Mondo, Sajeet Haridas, and Igor V. Grigoriev. "MycoCosm, the JGI’s Fungal Genome Portal for Comparative Genomic and Multiomics Data Analyses." In Microbial Environmental Genomics (MEG), 271–91. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2871-3_14.

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Conference papers on the topic "Genomics analyses"

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Considine, Michael, Hilary S. Parker, Yingying Wei, Xiao X. Xia, Leslie Cope, Michael F. Ochs, and Elana J. Fertig. "Abstract LB-317: Interactive pipeline for reproducible genomics analyses." In Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA. American Association for Cancer Research, 2014. http://dx.doi.org/10.1158/1538-7445.am2014-lb-317.

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Gorringe, Kylie L., Matthew Wakefield, Sally M. Hunter, Georgina L. Ryland, Dane Cheasley, Michael S. Anglesio, Michael Christie, et al. "Abstract B08: Genomics analyses of less common epithelial ovarian cancer subtypes." In Abstracts: AACR Special Conference: Advances in Ovarian Cancer Research: Exploiting Vulnerabilities; October 17-20, 2015; Orlando, FL. American Association for Cancer Research, 2016. http://dx.doi.org/10.1158/1557-3265.ovca15-b08.

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Jammula, Nagakishore, Sriram P. Chockalingam, and Srinivas Aluru. "Distributed Memory Partitioning of High-Throughput Sequencing Datasets for Enabling Parallel Genomics Analyses." In BCB '17: 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3107411.3107491.

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Ruddle, Roy A., Waleed Fateen, Darren Treanor, Peter Sondergeld, and Phil Ouirke. "Leveraging wall-sized high-resolution displays for comparative genomics analyses of copy number variation." In 2013 IEEE Symposium on Biological Data Visualization (BioVis). IEEE, 2013. http://dx.doi.org/10.1109/biovis.2013.6664351.

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Andersen, Jesper Boeje, Matthew Gillen, Elisabeth A. Conner, Valentina M. Factor, and Snorri S. Thorgeirsson. "Abstract 4927: Translational genomics analyses of cholangiocarcinoma identify patients who may respond to tyrosine kinase inhibitors." In Proceedings: AACR 103rd Annual Meeting 2012‐‐ Mar 31‐Apr 4, 2012; Chicago, IL. American Association for Cancer Research, 2012. http://dx.doi.org/10.1158/1538-7445.am2012-4927.

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Reinhold, William C., Sudir Varma, Yang-Hsin Wang, Fathi Elloumi, and Yves Pommier. "Abstract 2488: CellMinerCDB and CellMiner web-applications for genomics and pharmacogenomics analyses of cancer cell lines." In Proceedings: AACR Annual Meeting 2019; March 29-April 3, 2019; Atlanta, GA. American Association for Cancer Research, 2019. http://dx.doi.org/10.1158/1538-7445.sabcs18-2488.

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Reinhold, William C., Sudir Varma, Yang-Hsin Wang, Fathi Elloumi, and Yves Pommier. "Abstract 2488: CellMinerCDB and CellMiner web-applications for genomics and pharmacogenomics analyses of cancer cell lines." In Proceedings: AACR Annual Meeting 2019; March 29-April 3, 2019; Atlanta, GA. American Association for Cancer Research, 2019. http://dx.doi.org/10.1158/1538-7445.am2019-2488.

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Harris, Faye R., Geoffrey C. Halling, Marc A. Becker, Paul Haluska, George Vasmatzis, and Irina V. Kovtun. "Abstract 13: Individualized approach for ovarian cancer: Identification of potential therapeutic targets based on genomic analyses, testing efficiency of treatments, and monitoring." In Abstracts: AACR Precision Medicine Series: Integrating Clinical Genomics and Cancer Therapy; June 13-16, 2015; Salt Lake City, UT. American Association for Cancer Research, 2016. http://dx.doi.org/10.1158/1557-3265.pmsclingen15-13.

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Abdullah, Tariq, and Ahmed Ahmet. "Genomics Analyser." In UCC '17: 10th International Conference on Utility and Cloud Computing. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3148055.3148072.

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Takahashi, Hideaki, Kohei Shitara, Takeshi Kuwata, Yoichi Naito, Shingo Matsumoto, Wataru Okamoto, Seiji Niho, et al. "Abstract B29: Feasibility of amplicon sequencing using a pan-cancer gene panel with pre-treatment biopsy samples of (Japanese) patients with advanced solid tumors: Analyses of Biopsy Samples for Cancer Genomics (ABC) study." In Abstracts: AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics--Oct 19-23, 2013; Boston, MA. American Association for Cancer Research, 2013. http://dx.doi.org/10.1158/1535-7163.targ-13-b29.

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Reports on the topic "Genomics analyses"

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Katzir, Nurit, James Giovannoni, Marla Binzel, Efraim Lewinsohn, Joseph Burger, and Arthur Schaffer. Genomic Approach to the Improvement of Fruit Quality in Melon (Cucumis melo) and Related Cucurbit Crops II: Functional Genomics. United States Department of Agriculture, January 2010. http://dx.doi.org/10.32747/2010.7592123.bard.

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Background: Genomics tools for enhancement of melon research, with an emphasis on fruit, were developed through a previous BARD project of the PIs (IS -333-02). These included the first public melon EST collection, a database to relay this information to the research community and a publicly available microarray. The current project (IS-3877- 06) aimed to apply these tools for identification of important genes for improvement of melon (Cucumis melo) fruit quality. Specifically, the research plans included expression analysis using the microarray and functional analyses of selected genes. The original project objectives, as they appeared in the approved project, were: Objective 1: Utilization of a public melon microarray developed under the existing project to characterize melon transcriptome activity during the ripening of normal melon fruit (cv. Galia) in order to provide a basis for both a general view of melon transcriptome activity during ripening and for comparison with existing transcriptome data of developing tomato and pepper fruit. Objective 2: Utilization of the same public melon microarray to characterize melon transcriptome activity in lines available in the collection of the Israeli group, focusing on sugar, organic acids and aroma metabolism, so as to identify potentially useful candidates for functional analysis and possible manipulation, through comparison with the general fruit development profile resulting from (1) above. Objective 3: Expansion of our existing melon EST database to include publicly available gene expression data and query tools, as the US group has done with tomato. Objective 4: Selection of 6-8 candidate genes for functional analysis and development of DNA constructs for repression or over-expression. Objective 5: Creation of transgenic melon lines, or transgenic heterologous systems (e.g. E. coli or tomato), to assess putative functions and potential as tools for molecular enhancement of melon fruit quality, using the candidate gene constructs from (4).
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Zhang, Hongbin B., David J. Bonfil, and Shahal Abbo. Genomics Tools for Legume Agronomic Gene Mapping and Cloning, and Genome Analysis: Chickpea as a Model. United States Department of Agriculture, March 2003. http://dx.doi.org/10.32747/2003.7586464.bard.

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The goals of this project were to develop essential genomic tools for modern chickpea genetics and genomics research, map the genes and quantitative traits of importance to chickpea production and generate DNA markers that are well-suited for enhanced chickpea germplasm analysis and breeding. To achieve these research goals, we proposed the following research objectives in this period of the project: 1) Develop an ordered BAC library with an average insert size of 150 - 200 kb (USA); 2) Develop 300 simple sequence repeat (SSR) markers with an aid of the BAC library (USA); 3) Develop SSR marker tags for Ascochyta response, flowering date and grain weight (USA); 4) Develop a molecular genetic map consisting of at least 200 SSR markers (Israel and USA); 5) Map genes and QTLs most important to chickpea production in the U.S. and Israel: Ascochyta response, flowering and seed set date, grain weight, and grain yield under extreme dryland conditions (Israel); and 6) Determine the genetic correlation between the above four traits (Israel). Chickpea is the third most important pulse crop in the world and ranks the first in the Middle East. Chickpea seeds are a good source of plant protein (12.4-31.5%) and carbohydrates (52.4-70.9%). Although it has been demonstrated in other major crops that the modern genetics and genomics research is essential to enhance our capacity for crop genetic improvement and breeding, little work was pursued in these research areas for chickpea. It was absent in resources, tools and infrastructure that are essential for chickpea genomics and modern genetics research. For instance, there were no large-insert BAC and BIBAC libraries, no sufficient and user- friendly DNA markers, and no intraspecific genetic map. Grain sizes, flowering time and Ascochyta response are three main constraints to chickpea production in drylands. Combination of large seeds, early flowering time and Ascochyta blight resistance is desirable and of significance for further genetic improvement of chickpea. However, it was unknown how many genes and/or loci contribute to each of the traits and what correlations occur among them, making breeders difficult to combine these desirable traits. In this period of the project, we developed the resources, tools and infrastructure that are essential for chickpea genomics and modern genetics research. In particular, we constructed the proposed large-insert BAC library and an additional plant-transformation-competent BIBAC library from an Israeli advanced chickpea cultivar, Hadas. The BAC library contains 30,720 clones and has an average insert size of 151 kb, equivalent to 6.3 x chickpea haploid genomes. The BIBAC library contains 18,432 clones and has an average insert size of 135 kb, equivalent to 3.4 x chickpea haploid genomes. The combined libraries contain 49,152 clones, equivalent to 10.7 x chickpea haploid genomes. We identified all SSR loci-containing clones from the chickpea BAC library, generated sequences for 536 SSR loci from a part of the SSR-containing BACs and developed 310 new SSR markers. From the new SSR markers and selected existing SSR markers, we developed a SSR marker-based molecular genetic map of the chickpea genome. The BAC and BIBAC libraries, SSR markers and the molecular genetic map have provided essential resources and tools for modern genetic and genomic analyses of the chickpea genome. Using the SSR markers and genetic map, we mapped the genes and loci for flowering time and Ascochyta responses; one major QTL and a few minor QTLs have been identified for Ascochyta response and one major QTL has been identified for flowering time. The genetic correlations between flowering time, grain weight and Ascochyta response have been established. These results have provided essential tools and knowledge for effective manipulation and enhanced breeding of the traits in chickpea.
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Katzir, Nurit, James Giovannoni, and Joseph Burger. Genomic approach to the improvement of fruit quality in melon (Cucumis melo) and related cucurbit crops. United States Department of Agriculture, June 2006. http://dx.doi.org/10.32747/2006.7587224.bard.

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Fruit quality is determined by numerous genetic traits that affect taste, aroma, texture, pigmentation, nutritional value and duration of shelf-life. The molecular basis of many of these important traits is poorly understood and it’s understanding offers an excellent opportunity for adding value to agricultural products. Improvement of melon fruit quality was the primary goal of the project. The original objectives of the project were: The isolation of a minimum of 1000 fruit specific ESTs. The development of a microarray of melon fruit ESTs. The analysis of gene expression in melon using melon and tomato fruit enriched microarrays. A comprehensive study of fruit gene expression of the major cucurbit crops. In our current project we have focused on the development of genomics tools for the enhancement of melon research with an emphasis on fruit, specifically the first public melon EST collection. We have also developed a database to relay this information to the research community and developed a publicly available microarray. The release of this information was one of the catalysts for the establishment of the International Cucurbit Genomic Initiative (ICuGI, Barcelona, Spain, July 2005) aimed at collecting and generating up to 100,000 melon EST sequences in 2006, leveraging a significant expansion of melon genomic resources. A total of 1000 ESTs were promised under the original proposal (Objective 1). Non-subtracted mature fruit and young fruit flesh of a climacteric variety in addition to a non-climacteric variety resulted in the majority of additional EST sequences for a total of 4800 attempted reads. 3731 high quality sequences from independent ESTs were assembled, representing 2,467 melon unigenes (1,873 singletons, 594 contigs). In comparison, as of June 2004, a total of 170 melon mRNA sequences had been deposited in GENBANK. The current project has thus resulted in nearly five- fold the number of ESTs promised and ca. 15-fold increase in the depth of publicly available melon gene sequences. All of these sequences have been deposited in GENBANK and are also available and searchable via multiple approaches in the public database (http://melon.bti.cornell.edu). Our database was selected as the central location for presentation of public melon EST data of the International Cucurbit Genomic Initiative. With the available unigenes we recently constructed a microarray, which was successfully applied in hybridizations (planned public release by August 2006). Current gene expression analyses focus on fruit development and on comparative studies between climacteric and non-climacteric melons. Earlier, expression profiling was conducted using macroarrays developed at the preliminary stage of the project. This analysis replaced the study of tomato microarray following the recommendations of the reviewers and the panel of the original project. Comparative study between melon and other cucurbit crops have begun, mainly with watermelon, in collaboration with Dr. Amnon Levi (USDA-ARS). In conclusion, all four objectives have been addressed and achieved. In the continuation project that have been approved we plan to apply the genomic tools developed here to achieve detailed functional analyses of genes associated with major metabolic pathway.
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Lers, Amnon, and Gan Susheng. Study of the regulatory mechanism involved in dark-induced Postharvest leaf senescence. United States Department of Agriculture, January 2009. http://dx.doi.org/10.32747/2009.7591734.bard.

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Postharvest leaf senescence contributes to quality losses in flowers and leafy vegetables. The general goal of this research project was to investigate the regulatory mechanisms involved in dark-induced leaf senescence. The regulatory system involved in senescence induction and control is highly complex and possibly involves a network of senescence promoting pathways responsible for activation of the senescence-associated genes. Pathways involving different internal signals and environmental factors may have distinctive importance in different leaf senescence systems. Darkness is known to have a role in enhancement of postharvest leaf senescence and for getting an insight into its regulatory mechanism/s we have applied molecular genetics and functional genomics approaches. The original objectives were: 1. Identification of dark-induced SAGs in Arabidopsis using enhancer/promoter trap lines and microarray approaches; 2. Molecular and functional characterization of the identified genes by analyzing their expression and examining the phenotypes in related knockout mutant plants; 3. Initial studies of promoter sequences for selected early dark-induced SAGs. Since genomic studies of senescence, with emphasis on dark-induced senescence, were early-on published which included information on potential regulatory genes we decided to use this new information. This is instead of using the uncharacterized enhancer/promoter trap lines as originally planned. We have also focused on specific relevant genes identified in the two laboratories. Based on the available genomic analyses of leaf senescence 10 candidate genes hypothesized to have a regulatory role in dark-induced senescence were subjected to both expression as well as functional analyses. For most of these genes senescence-specific regulation was confirmed, however, functional analyses using knock-out mutants indicated no consequence to senescence progression. The transcription factor WARK75 was found to be specifically expressed during natural and dark-induced leaf senescence. Functional analysis demonstrated that in detached leaves senescence under darkness was significantly delayed while no phenotypic consequences could be observed on growth and development, including no effect on natural leaf senescence,. Thus, WARKY75 is suggested to have a role in dark-induced senescence, but not in natural senescence. Another regulatory gene identified to have a role in senescence is MKK9 encoding for a Mitogen-Activated Protein Kinase Kinase 9 which is upregulated during senescence in harvested leaves as well as in naturally senescing leaves. MKK9 can specifically phosphorylate another kinase, MPK6. Both knockouts of MKK9 and MPK6 displayed a significantly senescence delay in harvested leaves and possibly function as a phosphorelay that regulates senescence. To our knowledge, this is the first report that clearly demonstrates the involvement of a MAP kinase pathway in senescence. This research not only revealed a new signal transduction pathway, but more important provided significant insights into the regulatory mechanisms underlying senescence in harvested leaves. In an additional line of research we have employed the promoter of the senescence-induced BFN1 gene as a handle for identifying components of the regulatory mechanism. This gene was shown to be activated during darkinduced senescence of detached leaves, as well as natural senescence. This was shown by following protein accumulation and promoter activity which demonstrated that this promoter is activated during dark-induced senescence. Analysis of the promoter established that, at least some of the regulatory sequences reside in an 80 bps long fragment of the promoter. Overall, progress was made in identification of components with a role in dark-induced senescence in this project. Further studies should be done in order to better understand the function of these components and develop approaches for modulating the progress of senescence in crop plants for the benefit of agriculture.
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Collins, Colin C. A Genomics Approach to Tumor Gemome Analysis. Fort Belvoir, VA: Defense Technical Information Center, August 2002. http://dx.doi.org/10.21236/ada410900.

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Heifetz, Yael, and Michael Bender. Success and failure in insect fertilization and reproduction - the role of the female accessory glands. United States Department of Agriculture, December 2006. http://dx.doi.org/10.32747/2006.7695586.bard.

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The research problem. Understanding of insect reproduction has been critical to the design of insect pest control strategies including disruptions of mate-finding, courtship and sperm transfer by male insects. It is well known that males transfer proteins to females during mating that profoundly affect female reproductive physiology, but little is known about the molecular basis of female mating response and no attempts have yet been made to interfere with female post-mating responses that directly bear on the efficacy of fertilization. The female reproductive tract provides a crucial environment for the events of fertilization yet thus far those events and the role of the female tract in influencing them are poorly understood. For this project, we have chosen to focus on the lower reproductive tract because it is the site of two processes critical to reproduction: sperm management (storage, maintenance, and release from storage) and fertilization. E,fforts during this project period centered on the elucidation of mating responses in the female lower reproductive tract The central goals of this project were: 1. To identify mating-responsive genes in the female lower reproductive tract using DNA microarray technology. 2. In parallel, to identify mating-responsive genes in these tissues using proteomic assays (2D gels and LC-MS/MS techniques). 3. To integrate proteomic and genomic analyses of reproductive tract gene expression to identify significant genes for functional analysis. Our main achievements were: 1. Identification of mating-responsive genes in the female lower reproductive tract. We identified 539 mating-responsive genes using genomic and proteomic approaches. This analysis revealed a shift from gene silencing to gene activation soon after mating and a peak in differential gene expression at 6 hours post-mating. In addition, comparison of the two datasets revealed an expression pattern consistent with the model that important reproductive proteins are pre-programmed for synthesis prior to mating. This work was published in Mack et al. (2006). Validation experiments using real-time PCR techniques suggest that microarray assays provide a conservativestimate of the true transcriptional activity in reproductive tissues. 2.lntegration of proteomics and genomics data sets. We compared the expression profiles from DNA microarray data with the proteins identified in our proteomic experiments. Although comparing the two data sets poses analyical challenges, it provides a more complete view of gene expression as well as insights into how specific genes may be regulated. This work was published in Mack et al. (2006). 3. Development of primary reproductive tract cell cultures. We developed primary cell cultures of dispersed reproductive tract cell types and determined conditions for organ culture of the entire reproductive tract. This work will allow us to rapidly screen mating-responsive genes for a variety of reproductive-tract specifi c functions. Scientific and agricultural significance. Together, these studies have defined the genetic response to mating in a part of the female reproductive tract that is critical for successful fertllization and have identified alarge set of mating-responsive genes. This work is the first to combine both genomic and proteomic approaches in determining female mating response in these tissues and has provided important insights into insect reproductive behavior.
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El-Sayed, Najib M. A. High Throughput Technologies for Functional Analysis of Archael Genomics. Office of Scientific and Technical Information (OSTI), September 1998. http://dx.doi.org/10.2172/899965.

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Tamanaha, C. R., S. P. Mulvaney, K. A. Wahowski, M. C. Tondra, L. J. Whitman, and R. J. Colton. Cellular Genomic Analysis with GMR Sensor Arrays. Fort Belvoir, VA: Defense Technical Information Center, October 2003. http://dx.doi.org/10.21236/ada482671.

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Stern, David. Hidden Chloroplast Functions Revealed Through Deep Genomic Analysis. Office of Scientific and Technical Information (OSTI), November 2017. http://dx.doi.org/10.2172/1409823.

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Price, Lance B. Genomic Analysis of Complex Microbial Communities in Wounds. Fort Belvoir, VA: Defense Technical Information Center, July 2009. http://dx.doi.org/10.21236/ada585789.

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