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BMC Genetics

, 17:77

Functional genetics

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.

KeywordsThiosulfate sulfurtransferase TST Rhodanese Regulatory elements Map Obesity Lean Gene variants Polymorphism Bioinformatics Electronic supplementary materialThe online version of this article doi:10.1186-s12863-016-0381-6 contains supplementary material, which is available to authorized users.

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Autor: Jasmina Beltram - Nicholas M. Morton - Tanja Kunej - Simon Horvat

Fuente: https://link.springer.com/







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