Abstract
BackgroundGiven the abundance of new genomic projects and gene annotations, researchers trying to pinpoint causal genetic variants are faced with a challenging task of how to efficiently integrate all current genomic information. The objective of the study was to develop an approach to integrate various genomic annotations for a recently positionally-cloned Tst gene (Thiosulfate Sulfur Transferase, synonym Rhodanese) responsible for the Fob3b2 QTL effect on leanness and improved metabolic parameters. The second aim was to identify and prioritize Tst genetic variants that may be causal for the phenotypic effects.ResultsA bioinformatics approach was developed to integrate existing knowledge of regulatory elements of the Tst gene. The entire Tst locus along with flanking segments was sequenced between our unique polygenic mouse Fat and Lean strains that were generated by divergent selection on adiposity for over 60 generations. The bioinformatics-generated regulatory element map of the Tst locus was then combined with genetic variants between the Fat and Lean mice and with comparative analyses of polymorphisms across 17 mouse strains in order to prioritise likely causal polymorphisms. Two candidate regulatory variants were identified, one overlapping an evolutionary constrained Tst intronic element and the other residing in the seed region of a predicted 3′UTR miRNA binding site.ConclusionsThis study developed a map of regulatory elements for the Tst locus in mice and identified candidate genetic variants with increased causal likelihood. This map provides a basis for experimental validation and functional analyses of this novel candidate leanness and antidiabetic gene. Our methodological approach is of general utility for analyzing regulation of loci that have limited annotations and experimental evidence and for identifying candidate causal regulatory genetic variants in post-GWAS or post-QTL- cloning studies.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-016-0381-6) contains supplementary material, which is available to authorized users.
Highlights
Given the abundance of new genomic projects and gene annotations, researchers trying to pinpoint causal genetic variants are faced with a challenging task of how to efficiently integrate all current genomic information
In the present study we focus on the nuclear-encoded mitochondrial thiosulfate sulfur-transferase (Tst, known by synonym Rhodanese) that we recently identified in a positional cloning experiment as a causal gene for the Fob3b2 quantitative trait loci (QTL) phenotypic effect [22]
Even when such projects result in identification of a gene responsible for the phenotypic effect we are still faced with a task of identifying the gene variant that is causal
Summary
Given the abundance of new genomic projects and gene annotations, researchers trying to pinpoint causal genetic variants are faced with a challenging task of how to efficiently integrate all current genomic information. For example, genome wide association studies (GWAS) have identified several thousand gene variants associated with complex traits and diseases [1]. These gene variants can include structural variants such as insertion/deletions, in-frame deletions (indels), inversions, copy-number variants (CNVs) and most frequently (over 95 %) single nucleotide polymorphism (SNP) markers [2, 3]. A majority of variants mapped to candidate regions are unlikely to be causal for the effect on the trait [4]. In animal models loci for complex traits (quantitative trait loci; QTL), can be detected using GWAS approaches, especially in outbred species. In inbred laboratory animal models complex trait loci are more frequently identified using genetic analyses of crosses between strains differing in the trait(s) of interest
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