Comparing allele specific expression and local expression quantitative trait loci and the influence of gene expression on complex trait variation in cattle

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Khansefid, M; Pryce, JE; Bolormaa, S; Chen, Y; Millen, CA; Chamberlain, AJ; Vander Jagt, CJ; Goddard, MEDate
2018-11-03Source Title
BMC GenomicsPublisher
BMCUniversity of Melbourne Author/s
Goddard, MichaelAffiliation
Agriculture and Food SystemsMetadata
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Khansefid, M., Pryce, J. E., Bolormaa, S., Chen, Y., Millen, C. A., Chamberlain, A. J., Vander Jagt, C. J. & Goddard, M. E. (2018). Comparing allele specific expression and local expression quantitative trait loci and the influence of gene expression on complex trait variation in cattle. BMC GENOMICS, 19 (1), https://doi.org/10.1186/s12864-018-5181-0.Access Status
Open AccessAbstract
BACKGROUND: The mutations changing the expression level of a gene, or expression quantitative trait loci (eQTL), can be identified by testing the association between genetic variants and gene expression in multiple individuals (eQTL mapping), or by comparing the expression of the alleles in a heterozygous individual (allele specific expression or ASE analysis). The aims of the study were to find and compare ASE and local eQTL in 4 bovine RNA-sequencing (RNA-Seq) datasets, validate them in an independent ASE study and investigate if they are associated with complex trait variation. RESULTS: We present a novel method for distinguishing between ASE driven by polymorphisms in cis and parent of origin effects. We found that single nucleotide polymorphisms (SNPs) driving ASE are also often local eQTL and therefore presumably cis eQTL. These SNPs often, but not always, affect gene expression in multiple tissues and, when they do, the allele increasing expression is usually the same. However, there were systematic differences between ASE and local eQTL and between tissues and breeds. We also found that SNPs significantly associated with gene expression (p < 0.001) were likely to influence some complex traits (p < 0.001), which means that some mutations influence variation in complex traits by changing the expression level of genes. CONCLUSION: We conclude that ASE detects phenomenon that overlap with local eQTL, but there are also systematic differences between the SNPs discovered by the two methods. Some mutations influencing complex traits are actually eQTL and can be discovered using RNA-Seq including eQTL in the genes CAST, CAPN1, LCORL and LEPROTL1.
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