TY - JOUR
T1 - From data to function
T2 - Functional modeling of poultry genomics data
AU - McCarthy, F. M.
AU - Lyons, E.
N1 - Funding Information:
Annotations and resources provided by the AgBase databases is supported by Agriculture and Food Research Initiative Competitive Grant no. 2011-67015-30332 from the USDA National Institute of Food and Agriculture. Eric Lyons and the CoGe browser is supported by the iPlant Collaborative, a National Science Foundation Plant Cyberinfrastructure Program (#DBI-0735191) award, and the Betty and Gordon Moore Foundation. We especially acknowledge the members of the iPlant Education, Outreach and Training Group at the DNA Learning Center of Cold Spring Harbor Laboratory (Cold Spring Harbor, NY) who developed the iAnimal portal described in this manuscript. iAni-mal is currently available for evaluation and comment by the animal research community at http://genepro. cshl.edu/ianimal/.
PY - 2013/8
Y1 - 2013/8
N2 - One of the challenges of functional genomics is to create a better understanding of the biological system being studied so that the data produced are leveraged to provide gains for agriculture, human health, and the environment. Functional modeling enables researchers to make sense of these data as it reframes a long list of genes or gene products (mRNA, ncRNA, and proteins) by grouping based upon function, be it individual molecular functions or interactions between these molecules or broader biological processes, including metabolic and signaling pathways. However, poultry researchers have been hampered by a lack of functional annotation data, tools, and training to use these data and tools. Moreover, this lack is becoming more critical as new sequencing technologies enable us to generate data not only for an increasingly diverse range of species but also individual genomes and populations of individuals. We discuss the impact of these new sequencing technologies on poultry research, with a specific focus on what functional modeling resources are available for poultry researchers. We also describe key strategies for researchers who wish to functionally model their own data, providing background information about functional modeling approaches, the data and tools to support these approaches, and the strengths and limitations of each. Specifically, we describe methods for functional analysis using Gene Ontology (GO) functional summaries, functional enrichment analysis, and pathways and network modeling. As annotation efforts begin to provide the fundamental data that underpin poultry functional modeling (such as improved gene identification, standardized gene nomenclature, temporal and spatial expression data and gene product function), tool developers are incorporating these data into new and existing tools that are used for functional modeling, and cyberinfrastructure is being developed to provide the necessary extendibility and scalability for storing and analyzing these data. This process will support the efforts of poultry researchers to make sense of their functional genomics data sets, and we provide here a starting point for researchers who wish to take advantage of these tools.
AB - One of the challenges of functional genomics is to create a better understanding of the biological system being studied so that the data produced are leveraged to provide gains for agriculture, human health, and the environment. Functional modeling enables researchers to make sense of these data as it reframes a long list of genes or gene products (mRNA, ncRNA, and proteins) by grouping based upon function, be it individual molecular functions or interactions between these molecules or broader biological processes, including metabolic and signaling pathways. However, poultry researchers have been hampered by a lack of functional annotation data, tools, and training to use these data and tools. Moreover, this lack is becoming more critical as new sequencing technologies enable us to generate data not only for an increasingly diverse range of species but also individual genomes and populations of individuals. We discuss the impact of these new sequencing technologies on poultry research, with a specific focus on what functional modeling resources are available for poultry researchers. We also describe key strategies for researchers who wish to functionally model their own data, providing background information about functional modeling approaches, the data and tools to support these approaches, and the strengths and limitations of each. Specifically, we describe methods for functional analysis using Gene Ontology (GO) functional summaries, functional enrichment analysis, and pathways and network modeling. As annotation efforts begin to provide the fundamental data that underpin poultry functional modeling (such as improved gene identification, standardized gene nomenclature, temporal and spatial expression data and gene product function), tool developers are incorporating these data into new and existing tools that are used for functional modeling, and cyberinfrastructure is being developed to provide the necessary extendibility and scalability for storing and analyzing these data. This process will support the efforts of poultry researchers to make sense of their functional genomics data sets, and we provide here a starting point for researchers who wish to take advantage of these tools.
KW - Data analysis
KW - Gene expression
KW - Microarray
KW - Sequence analysis
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U2 - 10.3382/ps.2012-02808
DO - 10.3382/ps.2012-02808
M3 - Article
AN - SCOPUS:84882669495
SN - 0032-5791
VL - 92
SP - 2519
EP - 2529
JO - Poultry science
JF - Poultry science
IS - 9
ER -