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Genome variants associated with RNA splicing variations in bovine are extensive shared between tissues

Authors :
Xiang, R
Hayes, BJ
Vander Jagt, CJ
MacLeod, IM
Khansefid, M
Bowman, PJ
Yuan, Z
Prowse-Wilkins, CP
Reich, CM
Mason, BA
Garner, JB
Marett, LC
Chen, Y
Bolormaa, S
Daetwyler, HD
Chamberlain, AJ
Goddard, ME
Xiang, R
Hayes, BJ
Vander Jagt, CJ
MacLeod, IM
Khansefid, M
Bowman, PJ
Yuan, Z
Prowse-Wilkins, CP
Reich, CM
Mason, BA
Garner, JB
Marett, LC
Chen, Y
Bolormaa, S
Daetwyler, HD
Chamberlain, AJ
Goddard, ME
Publication Year :
2018

Abstract

BACKGROUND: Mammalian phenotypes are shaped by numerous genome variants, many of which may regulate gene transcription or RNA splicing. To identify variants with regulatory functions in cattle, an important economic and model species, we used sequence variants to map a type of expression quantitative trait loci (expression QTLs) that are associated with variations in the RNA splicing, i.e., sQTLs. To further the understanding of regulatory variants, sQTLs were compare with other two types of expression QTLs, 1) variants associated with variations in gene expression, i.e., geQTLs and 2) variants associated with variations in exon expression, i.e., eeQTLs, in different tissues. RESULTS: Using whole genome and RNA sequence data from four tissues of over 200 cattle, sQTLs identified using exon inclusion ratios were verified by matching their effects on adjacent intron excision ratios. sQTLs contained the highest percentage of variants that are within the intronic region of genes and contained the lowest percentage of variants that are within intergenic regions, compared to eeQTLs and geQTLs. Many geQTLs and sQTLs are also detected as eeQTLs. Many expression QTLs, including sQTLs, were significant in all four tissues and had a similar effect in each tissue. To verify such expression QTL sharing between tissues, variants surrounding (±1 Mb) the exon or gene were used to build local genomic relationship matrices (LGRM) and estimated genetic correlations between tissues. For many exons, the splicing and expression level was determined by the same cis additive genetic variance in different tissues. Thus, an effective but simple-to-implement meta-analysis combining information from three tissues is introduced to increase power to detect and validate sQTLs. sQTLs and eeQTLs together were more enriched for variants associated with cattle complex traits, compared to geQTLs. Several putative causal mutations were identified, including an sQTL at Chr6:87392580 within the 5th exon

Details

Database :
OAIster
Publication Type :
Electronic Resource
Accession number :
edsoai.on1315677528
Document Type :
Electronic Resource