Integration of heterogeneous functional genomics data in gerontology research to find genes and pathway underlying aging across species

Abstract

Understanding the biological mechanisms behind aging, lifespan and healthspan is becoming increasingly important as the proportion of the world's population over the age of 65 grows, along with the cost and complexity of their care. BigData oriented approaches and analysis methods enable current and future bio-gerontologists to synthesize, distill and interpret vast, heterogeneous data from functional genomics studies of aging. GeneWeaver is an analysis system for integration of data that allows investigators to store, search, and analyze immense amounts of data including user-submitted experimental data, data from primary publications, and data in other databases. Aging related genome-wide gene sets from primary publications were curated into this system in concert with data from other model-organism and aging-specific databases, and applied to several questions in genrontology using. For example, we identified Cd63 as a frequently represented gene among aging-related genome-wide results. To evaluate the role of Cd63 in aging, we performed RNAi knockdown of the C . elegans ortholog, tsp-7 , demonstrating that this manipulation is capable of extending lifespan. The tools in GeneWeaver enable aging researchers to make new discoveries into the associations between the genes, normal biological processes, and diseases that affect aging, healthspan, and lifespan.

Computational tools for geroscience

“…It contains almost 200,000 public gene sets incorporated from databases, including the Kyoto Encyclopedia of Genes and Genomes (KEGG), Molecular Signatures Database (MSigDB), the drug-related gene database of the Neuroscience Information Framework (NIF), and Online Mendelian Inheritance of Man (OMIM), among many others. Types of GeneWeaver Data that are returned when searching for “senescence OR aging OR longevity” include aging-related (1655 datasets), Gene Ontology (GO) term-based (71), Mammalian and Human Phenotype (63 and 109, respectively), Quantitative Trait Loci (409), Medical Subject Headings (231), gene expression (169), and drug-related gene sets (253) [ 34 ]. GeneWeaver is freely accessible and allows for the uploading of one’s own datasets (with the option to make public or private) to facilitate meta-analysis.…”

“…Among the GeneWeaver tools available for use are the Combine, Jaccard Similarity, GeneSet Graph, STRING, and Ingenuity Pathway Analysis (IGA) tools. A more in-depth application of these tools and of the use of GeneWeaver in aging-related studies can be found in a recent publication [ 34 ]. Briefly, the Combine tool returns a single gene set from multiple input gene sets that counts the number of sets in which each gene is found.…”

“…The GeneSet Graph tool, similar to the Combine tool, identifies common genes among multiple input gene sets, but instead of returning a single gene set, GeneSet Graph returns a partitioned set of genes and gene sets. For example, the GeneSet Graph tool has been used to identify the three most highly connected genes from 73 aging-related gene sets across six different species [ 34 ]. This tool could be used to rapidly identify genes that are common in many different gene sets and establish orthogonal relationships across species that were previously unknown.…”

“…One possible application of GeneWeaver will be to identify mechanisms of lifespan extension that are common across species. GeneWeaver has been used to identify cross-species gene homologues that are transcriptionally regulated by DR and by lifespan extending drugs in mouse and Drosophila [ 34 ]. GeneWeaver has also been used to identify a novel C. elegans lifespan regulator, Cd63 , on the basis that it is present in a large number of aging-associated gene sets across multiple species [ 34 ].…”

“…GeneWeaver has been used to identify cross-species gene homologues that are transcriptionally regulated by DR and by lifespan extending drugs in mouse and Drosophila [ 34 ]. GeneWeaver has also been used to identify a novel C. elegans lifespan regulator, Cd63 , on the basis that it is present in a large number of aging-associated gene sets across multiple species [ 34 ]. In the future, GeneWeaver might be useful to identify genes whose transcriptional upregulation serves as a biomarker, to identify drugs that extend lifespan across species, and to identify the conserved mechanisms by which interventions extend lifespan across taxa.…”