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Journal articles on the topic 'Genetics and genomics/functional genomics'

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Author: Grafiati

Published: 10 December 2022

Last updated: 29 January 2023

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1

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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2

Bofkin, L., and S. Whelan. "Comparative genomics: Functional needles in a genomic haystack." Heredity 92, no. 5 (April 26, 2004): 363–64. http://dx.doi.org/10.1038/sj.hdy.6800429.

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3

Penn, Raymond B., Victor E. Ortega, and Eugene R. Bleecker. "A Roadmap to functional genomics." Physiological Genomics 30, no. 1 (June 2007): 82–88. http://dx.doi.org/10.1152/physiolgenomics.00010.2007.

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In August 2006, the Center for Human Genomics of the Wake Forest University School of Medicine in Winston-Salem, NC, hosted the National Institutes of Health-sponsored Roadmap Course entitled Models and Technologies for Defining Phenotype. Twenty-four biomedical and genomic researchers from throughout the world and with varying degrees of experience in the genomics, biological, and biomedical engineering sciences were invited to participate as students in a comprehensive course dedicated to presenting and evaluating current and future approaches that can overcome the problems experienced to date in characterizing the functional consequences of gene variation. A total of 34 senior researchers from four different academic institutions served as course faculty and employed a pedagogical approach that emphasized hands-on workshops, demonstrations, and small group discussions and tasks. Through this report we convey the complex and formidable problems unique to genomics research as we attempt to link the field of genomic research to complex human diseases. Furthermore, we describe the logic and organization of a Roadmap Course designed to teach a diverse group of researchers a multi-disciplinary approach to addressing complex biomedical scenarios in the field of human genomics.

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4

Soppa, J., A. Baumann, M. Brenneis, M. Dambeck, O. Hering, and C. Lange. "Genomics and functional genomics with haloarchaea." Archives of Microbiology 190, no. 3 (May 21, 2008): 197–215. http://dx.doi.org/10.1007/s00203-008-0376-4.

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5

Deng, Youping, Hongwei Wang, Ryuji Hamamoto, David Schaffer, and Shiwei Duan. "Functional Genomics, Genetics, and Bioinformatics." BioMed Research International 2015 (2015): 1–3. http://dx.doi.org/10.1155/2015/184824.

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6

Ludwig, Kerstin U., and Malte Spielmann. "Functional genomics meets human genetics." Medizinische Genetik 34, no. 4 (November 29, 2022): 259–60. http://dx.doi.org/10.1515/medgen-2022-2160.

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7

Coram, Tristan E., Nitin L. Mantri, Rebecca Ford, and Edwin C. K. Pang. "Functional genomics in chickpea: an emerging frontier for molecular-assisted breeding." Functional Plant Biology 34, no. 10 (2007): 861. http://dx.doi.org/10.1071/fp07169.

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Chickpea is a valuable and important agricultural crop, but yield potential is limited by a series of biotic and abiotic stresses, including Ascochyta blight, Fusarium wilt, drought, cold and salinity. To accelerate molecular breeding efforts for the discovery and introgression of stress tolerance genes into cultivated chickpea, functional genomics approaches are rapidly growing. Recently a series of genetic tools for chickpea have become available that have allowed high-powered functional genomics studies to proceed, including a dense genetic map, large insert genome libraries, expressed sequence tag libraries, microarrays, serial analysis of gene expression, transgenics and reverse genetics. This review summarises the development of these genomic tools and the achievements made in initial and emerging functional genomics studies. Much of the initial research focused on Ascochyta blight resistance, and a resistance model has been synthesised based on the results of various studies. Use of the rich comparative genomics resources from the model legumes Medicago truncatula and Lotus japonicus is also discussed. Finally, perspectives on the future directions for chickpea functional genomics, with the goal of developing elite chickpea cultivars, are discussed.

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8

Burton, Jeanne L., and Guilherme J. M. Rosa. "Physiological genomics special issue on animal functional genomics." Physiological Genomics 28, no. 1 (December 2006): 1–4. http://dx.doi.org/10.1152/physiolgenomics.00220.2006.

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9

González-Serna, David, Gonzalo Villanueva-Martin, Marialbert Acosta-Herrera, Ana Márquez, and Javier Martín. "Approaching Shared Pathophysiology in Immune-Mediated Diseases through Functional Genomics." Genes 11, no. 12 (December 9, 2020): 1482. http://dx.doi.org/10.3390/genes11121482.

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Immune-mediated diseases (IMDs) are complex pathologies that are strongly influenced by environmental and genetic factors. Associations between genetic loci and susceptibility to these diseases have been widely studied, and hundreds of risk variants have emerged during the last two decades, with researchers observing a shared genetic pattern among them. Nevertheless, the pathological mechanism behind these associations remains a challenge that has just started to be understood thanks to functional genomic approaches. Transcriptomics, regulatory elements, chromatin interactome, as well as the experimental characterization of genomic findings, constitute key elements in the emerging understandings of how genetics affects the etiopathogenesis of IMDs. In this review, we will focus on the latest advances in the field of functional genomics, centering our attention on systemic rheumatic IMDs.

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10

Routhier, Etienne, and Julien Mozziconacci. "Genomics enters the deep learning era." PeerJ 10 (June 24, 2022): e13613. http://dx.doi.org/10.7717/peerj.13613.

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The tremendous amount of biological sequence data available, combined with the recent methodological breakthrough in deep learning in domains such as computer vision or natural language processing, is leading today to the transformation of bioinformatics through the emergence of deep genomics, the application of deep learning to genomic sequences. We review here the new applications that the use of deep learning enables in the field, focusing on three aspects: the functional annotation of genomes, the sequence determinants of the genome functions and the possibility to write synthetic genomic sequences.

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11

Brown, Steve D. M., and Joseph H. Nadeau. "Precision and Functional Genomics." Mammalian Genome 31, no. 1-2 (February 2020): 1. http://dx.doi.org/10.1007/s00335-020-09828-2.

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12

Seldin, Michael F. "Toward Functional Genomics." Methods 13, no. 4 (December 1997): 325–26. http://dx.doi.org/10.1006/meth.1997.0540.

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13

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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14

Deng, Youping, Hongwei Wang, Ryuji Hamamoto, Shiwei Duan, Mehdi Pirooznia, and Yongsheng Bai. "Functional Genomics, Genetics, and Bioinformatics 2016." BioMed Research International 2016 (2016): 1–3. http://dx.doi.org/10.1155/2016/2625831.

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15

Cakiroglu, Ece, and Serif Senturk. "Genomics and Functional Genomics of Malignant Pleural Mesothelioma." International Journal of Molecular Sciences 21, no. 17 (September 1, 2020): 6342. http://dx.doi.org/10.3390/ijms21176342.

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Malignant pleural mesothelioma (MPM) is a rare, aggressive cancer of the mesothelial cells lining the pleural surface of the chest wall and lung. The etiology of MPM is strongly associated with prior exposure to asbestos fibers, and the median survival rate of the diagnosed patients is approximately one year. Despite the latest advancements in surgical techniques and systemic therapies, currently available treatment modalities of MPM fail to provide long-term survival. The increasing incidence of MPM highlights the need for finding effective treatments. Targeted therapies offer personalized treatments in many cancers. However, targeted therapy in MPM is not recommended by clinical guidelines mainly because of poor target definition. A better understanding of the molecular and cellular mechanisms and the predictors of poor clinical outcomes of MPM is required to identify novel targets and develop precise and effective treatments. Recent advances in the genomics and functional genomics fields have provided groundbreaking insights into the genomic and molecular profiles of MPM and enabled the functional characterization of the genetic alterations. This review provides a comprehensive overview of the relevant literature and highlights the potential of state-of-the-art genomics and functional genomics research to facilitate the development of novel diagnostics and therapeutic modalities in MPM.

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16

Liu, Edison T. "Functional genomics of cancer." Current Opinion in Genetics & Development 18, no. 3 (June 2008): 251–56. http://dx.doi.org/10.1016/j.gde.2008.07.014.

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17

Baranov, V. S. "Genomics and predictive medicine." Siberian Journal of Clinical and Experimental Medicine 36, no. 4 (December 31, 2021): 14–28. http://dx.doi.org/10.29001/2073-8552-2021-36-4-14-28.

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Progress in understanding of structural and functional human genome organization and deciphering primary DNA sequence in human cells allowed for hitherto unreachable new capabilities of medical genetics in identifying the causes and mechanisms of inherited and inborn pathology. Implementation of genetics into medicine is progressively advancing along with improvement of molecular analysis of genome. Knowledge of genome and its functions allows to provide more accurate diagnosis, predict, to a considerable extent, the presence of genetic predisposition of a person to pathology, and to assess the chances for developing one or another disease. This approach became the basis for a new area of medical genetics named predictive medicine. The progress of predictive medicine refl ects success in tremendous upgrowth of molecular genetic methods and new capabilities of studying structure and functions of genome. Within less than 15 years after deciphering genome, medical genetics has travelled a long way from a single gene analysis to whole genome studies, from screening of genetic associations to systems genetics of multifactorial diseases, from translational to high-precision genetics, and from genetic passport idea to electronic genetic health records. The development of a genetic passport, prognostic genetic testing, and genomic chart of reproductive health is especially relevant for current practical medicine.

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18

Edwards, Y. J. K. "Bioinformatics and Functional Genomics." Briefings in Functional Genomics and Proteomics 3, no. 2 (January 1, 2004): 187–90. http://dx.doi.org/10.1093/bfgp/3.2.187.

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19

Aigner, Thomas, Eckart Bartnik, Alexander Zien, and Ralf Zimmer. "Functional genomics of osteoarthritis." Pharmacogenomics 3, no. 5 (September 2002): 635–50. http://dx.doi.org/10.1517/14622416.3.5.635.

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20

Mitchell-Olds, T., M. Feder, and G. Wray. "Evolutionary and ecological functional genomics." Heredity 100, no. 2 (January 23, 2008): 101–2. http://dx.doi.org/10.1038/sj.hdy.6801015.

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21

Kague, Erika, and David Karasik. "Functional Validation of Osteoporosis Genetic Findings Using Small Fish Models." Genes 13, no. 2 (January 30, 2022): 279. http://dx.doi.org/10.3390/genes13020279.

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The advancement of human genomics has revolutionized our understanding of the genetic architecture of many skeletal diseases, including osteoporosis. However, interpreting results from human association studies remains a challenge, since index variants often reside in non-coding regions of the genome and do not possess an obvious regulatory function. To bridge the gap between genetic association and causality, a systematic functional investigation is necessary, such as the one offered by animal models. These models enable us to identify causal mechanisms, clarify the underlying biology, and apply interventions. Over the past several decades, small teleost fishes, mostly zebrafish and medaka, have emerged as powerful systems for modeling the genetics of human diseases. Due to their amenability to genetic intervention and the highly conserved genetic and physiological features, fish have become indispensable for skeletal genomic studies. The goal of this review is to summarize the evidence supporting the utility of Zebrafish (Danio rerio) for accelerating our understanding of human skeletal genomics and outlining the remaining gaps in knowledge. We provide an overview of zebrafish skeletal morphophysiology and gene homology, shedding light on the advantages of human skeletal genomic exploration and validation. Knowledge of the biology underlying osteoporosis through animal models will lead to the translation into new, better and more effective therapeutic approaches.

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22

Mohr, Stephanie E., Yanhui Hu, Kevin Kim, Benjamin E. Housden, and Norbert Perrimon. "Resources for Functional Genomics Studies inDrosophila melanogaster." Genetics 197, no. 1 (March 20, 2014): 1–18. http://dx.doi.org/10.1534/genetics.113.154344.

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23

Bhadauria, Vijai, Sabine Banniza, Yangdou Wei, and You-Liang Peng. "Reverse Genetics for Functional Genomics of Phytopathogenic Fungi and Oomycetes." Comparative and Functional Genomics 2009 (2009): 1–11. http://dx.doi.org/10.1155/2009/380719.

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Sequencing of over 40 fungal and oomycete genomes has been completed. The next major challenge in modern fungal/oomycete biology is now to translate this plethora of genome sequence information into biological functions. Reverse genetics has emerged as a seminal tool for functional genomics investigations. Techniques utilized for reverse genetics like targeted gene disruption/replacement, gene silencing, insertional mutagenesis, and targeting induced local lesions in genomes will contribute greatly to the understanding of gene function of fungal and oomycete pathogens. This paper provides an overview on high-throughput reverse genetics approaches to decode fungal/oomycete genomes.

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24

Evans, Martin J., Mark B. L. Carlton, and Andreas P. Russ. "Gene trapping and functional genomics." Trends in Genetics 13, no. 9 (September 1997): 374. http://dx.doi.org/10.1016/s0168-9525(97)81166-3.

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25

Fei, Z., J. G. Joung, X. Tang, Y. Zheng, M. Huang, J. M. Lee, R. McQuinn, et al. "Tomato Functional Genomics Database: a comprehensive resource and analysis package for tomato functional genomics." Nucleic Acids Research 39, Database (October 21, 2010): D1156—D1163. http://dx.doi.org/10.1093/nar/gkq991.

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26

Wixon, Jo. "Meeting Highlights: International Summer School, ‘From Genome to Life’." Comparative and Functional Genomics 3, no. 6 (2002): 535–50. http://dx.doi.org/10.1002/cfg.222.

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This report from the International Summer School ‘From Genome to Life’, held at the Institute d'Etudes Scientifiques de Cargèse in Corsica in July 2002, covers the talks of the invited speakers. The topics of the talks can be broadly grouped into the areas of genome annotation, comparative and evolutionary genomics, functional genomics, proteomics, structural genomics, pharmacogenomics, and organelle genomes, epigenetics and RNA.

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27

Feder, Martin E., and Thomas Mitchell-Olds. "Evolutionary and ecological functional genomics." Nature Reviews Genetics 4, no. 8 (August 2003): 649–55. http://dx.doi.org/10.1038/nrg1128.

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28

Ding, James, Antonios Frantzeskos, and Gisela Orozco. "Functional genomics in autoimmune diseases." Human Molecular Genetics 29, R1 (May 18, 2020): R59—R65. http://dx.doi.org/10.1093/hmg/ddaa097.

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Abstract Associations between genetic loci and increased susceptibility to autoimmune disease have been well characterized, however, translating this knowledge into mechanistic insight and patient benefit remains a challenge. While improvements in the precision, completeness and accuracy of our genetic understanding of autoimmune diseases will undoubtedly be helpful, meeting this challenge will require two interlinked problems to be addressed: first which of the highly correlated variants at an individual locus is responsible for increased disease risk, and second what are the downstream effects of this variant. Given that the majority of loci are thought to affect non-coding regulatory elements, the second question is often reframed as what are the target gene(s) and pathways affected by causal variants. Currently, these questions are being addressed using a wide variety of novel techniques and datasets. In many cases, these approaches are complementary and it is likely that the most accurate picture will be generated by consolidating information relating to transcription, regulatory activity, chromatin accessibility, chromatin conformation and readouts from functional experiments, such as genome editing and reporter assays. It is clear that it will be necessary to gather this information from disease relevant cell types and conditions and that by doing so our understanding of disease etiology will be improved. This review is focused on the field of autoimmune disease functional genomics with a particular focus on the most exciting and significant research to be published within the last couple of years.

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29

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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30

Oliver, S. G. "Comparative and Functional Genomics." Yeast 1, no. 1 (January 1, 2000): vii. http://dx.doi.org/10.1155/2000/672640.

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31

Oliver, S. G. "Comparative and Functional Genomics." Yeast 1, no. 1 (2000): vii. http://dx.doi.org/10.1002/(sici)1097-0061(200004)17:13.0.co;2-b.

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32

Wixon, Jo, and Joan Marsh. "ESF Programme on Functional Genomics 1st European Conference: Functional Genomics and Disease 2003." Comparative and Functional Genomics 4, no. 5 (2003): 549–57. http://dx.doi.org/10.1002/cfg.332.

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In this report from the 1st European Conference of the European Science Foundation Programme on Functional Genomics, we provide coverage of the high-profile plenary talks and a cross-section of the many presentations in the disease analysis symposia and functional genomics technologies workshops.

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33

Polacco, Mary, Ed Coe, Zhiwei Fang, Denis Hancock, Hector Sanchez-Villeda, and Steve Schroeder. "MaizeDB – A Functional Genomics Perspective." Comparative and Functional Genomics 3, no. 2 (2002): 128–31. http://dx.doi.org/10.1002/cfg.157.

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MaizeDB (http://www.agron.missouri.edu/) has existed since the early 90’s as a genomespecific database that is grounded in genetic maps, their documentation and annotation. The database management system is robust and has continuously been Sybase. In this brief review we provide an introduction to the database as a functional genomics tool and new accesses to the data: 1) probe tables by bin location 2) BLAST access to map data 3) cMap, a comparative map graphical tool.

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34

Samarsky, Dmitry. "RNAi in functional genomics." Expert Review of Molecular Diagnostics 5, no. 4 (July 2005): 485–86. http://dx.doi.org/10.1586/14737159.5.4.485.

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35

Sreenivasulu, Nese, Andreas Graner, and Ulrich Wobus. "Barley Genomics: An Overview." International Journal of Plant Genomics 2008 (March 13, 2008): 1–13. http://dx.doi.org/10.1155/2008/486258.

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Barley (Hordeum vulgare), first domesticated in the Near East, is a well-studied crop in terms of genetics, genomics, and breeding and qualifies as a model plant for Triticeae research. Recent advances made in barley genomics mainly include the following: (i) rapid accumulation of EST sequence data, (ii) growing number of studies on transcriptome, proteome, and metabolome, (iii) new modeling techniques, (iv) availability of genome-wide knockout collections as well as efficient transformation techniques, and (v) the recently started genome sequencing effort. These developments pave the way for a comprehensive functional analysis and understanding of gene expression networks linked to agronomically important traits. Here, we selectively review important technological developments in barley genomics and related fields and discuss the relevance for understanding genotype-phenotype relationships by using approaches such as genetical genomics and association studies. High-throughput genotyping platforms that have recently become available will allow the construction of high-density genetic maps that will further promote marker-assisted selection as well as physical map construction. Systems biology approaches will further enhance our knowledge and largely increase our abilities to design refined breeding strategies on the basis of detailed molecular physiological knowledge.

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36

Kim, Woori, and Nikolaos A. Patsopoulos. "Genetics and functional genomics of multiple sclerosis." Seminars in Immunopathology 44, no. 1 (January 2022): 63–79. http://dx.doi.org/10.1007/s00281-021-00907-3.

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37

Stacey, Gary, Marc Libault, Laurent Brechenmacher, Jinrong Wan, and Gregory D. May. "Genetics and functional genomics of legume nodulation." Current Opinion in Plant Biology 9, no. 2 (April 2006): 110–21. http://dx.doi.org/10.1016/j.pbi.2006.01.005.

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38

Perkins, Archibald. "Functional genomics in the mouse." Functional & Integrative Genomics 2, no. 3 (August 1, 2002): 81–91. http://dx.doi.org/10.1007/s10142-002-0049-3.

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39

Appels, R., M. Francki, and R. Chibbar. "Advances in cereal functional genomics." Functional & Integrative Genomics 3, no. 1 (March 2003): 1–24. http://dx.doi.org/10.1007/s10142-002-0073-3.

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40

Blomberg, Anders, and Per Sunnerhagen. "Visible trends in functional genomics." Functional & Integrative Genomics 3, no. 3 (July 1, 2003): 91–93. http://dx.doi.org/10.1007/s10142-003-0083-9.

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41

Berenfeld, Ludmilla, Olga Sokolova, Sun Hee Rim, and Dagmar Ringe. "Functional Genomics with YBL036c." Scientific World JOURNAL 2 (2002): 35. http://dx.doi.org/10.1100/tsw.2002.18.

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42

Niculescu, Alexander B., and John R. Kelsoe. "Finding Genes for Bipolar Disorder in the Functional Genomics Era: From Convergent Functional Genomics to Phenomics and Back." CNS Spectrums 7, no. 3 (March 2002): 215–26. http://dx.doi.org/10.1017/s1092852900017582.

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ABSTRACTPsychiatric genetics, while promising to unravel the mechanisms of psychiatric disorders, has proven to be a challenging field. Psychiatric disorders, like other common genetic traits, are complex and heterogeneous. Psychiatric genetics has also suffered from a lack of quantifiable, biology-based phenotypes. However, the field is currently at an opportune moment. The work of various investigators is on the verge of paying rich dividends. Efforts at positional cloning are being greatly accelerated by the fruits of the Human Genome Project. New tools of functional genomics, such as expression profiling and proteomics, are being applied to animal models. These two methods can complement each other in an approach we have termed convergent functional genomics. Lastly, improvements in the measurement of biologically distinct endophenotypes—or phenomics—will lead to a better understanding of the mapping of genes to phenotypes in both animal and human systems.

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43

Caudy, Amy A., Yuanfang Guan, Yue Jia, Christina Hansen, Chris DeSevo, Alicia P. Hayes, Joy Agee, et al. "A New System for Comparative Functional Genomics ofSaccharomycesYeasts." Genetics 195, no. 1 (July 12, 2013): 275–87. http://dx.doi.org/10.1534/genetics.113.152918.

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44

Giuffra, Elisabetta, and Christopher K. Tuggle. "Functional Annotation of Animal Genomes (FAANG): Current Achievements and Roadmap." Annual Review of Animal Biosciences 7, no. 1 (February 15, 2019): 65–88. http://dx.doi.org/10.1146/annurev-animal-020518-114913.

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Functional annotation of genomes is a prerequisite for contemporary basic and applied genomic research, yet farmed animal genomics is deficient in such annotation. To address this, the FAANG (Functional Annotation of Animal Genomes) Consortium is producing genome-wide data sets on RNA expression, DNA methylation, and chromatin modification, as well as chromatin accessibility and interactions. In addition to informing our understanding of genome function, including comparative approaches to elucidate constrained sequence or epigenetic elements, these annotation maps will improve the precision and sensitivity of genomic selection for animal improvement. A scientific community–driven effort has already created a coordinated data collection and analysis enterprise crucial for the success of this global effort. Although it is early in this continuing process, functional data have already been produced and application to genetic improvement reported. The functional annotation delivered by the FAANG initiative will add value and utility to the greatly improved genome sequences being established for domesticated animal species.

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45

Kuwabara, P. E. "Functional Genomics: Methods and Protocols." Briefings in Functional Genomics and Proteomics 2, no. 3 (January 1, 2003): 268–69. http://dx.doi.org/10.1093/bfgp/2.3.268.

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Kawai, J., P. Carninci, and Y. Hayashizaki. "Transcriptomics resources for functional genomics." Briefings in Functional Genomics and Proteomics 6, no. 3 (August 20, 2007): 171–79. http://dx.doi.org/10.1093/bfgp/elm024.

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Pesaresi, Paolo, Claudio Varotto, Erik Richly, Joachim Kurth, Francesco Salamini, and Dario Leister. "Functional genomics of Arabidopsis photosynthesis." Plant Physiology and Biochemistry 39, no. 3-4 (March 2001): 285–94. http://dx.doi.org/10.1016/s0981-9428(01)01238-4.

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Attur, Mukundan G., Mandar N. Dave, and Ashok R. Amin. "Functional Genomics Approaches in Arthritis." American Journal of PharmacoGenomics 4, no. 1 (2004): 29–43. http://dx.doi.org/10.2165/00129785-200404010-00004.

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Gannon, Frank. "The discovery of functional genomics." EMBO reports 1, no. 5 (November 2000): 386–87. http://dx.doi.org/10.1093/embo-reports/kvd104.

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Matthew, Louisa. "RNAi for Plant Functional Genomics." Comparative and Functional Genomics 5, no. 3 (2004): 240–44. http://dx.doi.org/10.1002/cfg.396.

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Abstract:

A major challenge in the post-genome era of plant biology is to determine the functions of all the genes in the plant genome. A straightforward approach to this problem is to reduce or knock out expression of a gene with the hope of seeing a phenotype that is suggestive of its function. Insertional mutagenesis is a useful tool for this type of study, but it is limited by gene redundancy, lethal knock-outs, nontagged mutants and the inability to target the inserted element to a specific gene. RNA interference (RNAi) of plant genes, using constructs encoding self-complementary ‘hairpin’ RNA, largely overcomes these problems. RNAi has been used very effectively inCaenorhabditis elegansfunctional genomics, and resources are currently being developed for the application of RNAi to high-throughput plant functional genomics.

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