Complex traits in livestock shape production, reproduction, disease susceptibility and numerous other phenotypic characteristics. Variation in key genes can influence these phenotypic characteristics and can be exploited for breeding programs or as gene editing targets for the improvement of livestock health, welfare and productivity.
Several recent publications suggest that many of the mutations that give rise to variations in complex traits in animals are located within regulatory elements that alter gene expression (reviewed in Pai et al. 2015). Cis expression quantitative trait loci (cis eQTL) is the name given to mutations affecting the expression of an allele on the same chromosome. If an animal is heterozygous for such a mutation causing the two alleles of the gene to be expressed unequally then ‘allele specific expression’ (ASE) occurs. Allele specific expression can range from being mono-allelic to only slight over-expression of the major allele.
RNA Sequencing (RNASeq) can be used to detect ASE if the heterozygous site is in the coding region of the gene. Recent research has shown that ASE is pervasive and often tissue specific in cattle (Chamberlain et al. 2015). This raises several key questions with relevance to livestock breeding. Crucially, whether we can identify the causative regulatory variants giving rise to phenotypic effects and exploit them for genomic selection to enhance current breeding programs. Other key questions include; to what extent ASE is tissue specific? is only one of the two alleles expressed more often? and is there a genome wide bias towards the maternal or paternal allele?
We have generated an RNA-Seq dataset for goats which is a ‘mini’ version of the high resolution of atlas of gene expression for the domestic sheep which we published last year (Clark et al. 2017). Allele specific expression can be tissue specific and the dataset, which encompasses 12 tissues from 8 animals and two cell types per animal, offers the potential to explore this at considerable depth. Since there is limited knowledge of the extent of ASE and genetic imprinting in goats this represents an excellent opportunity to address the questions listed above.
The first stage of the project will involve applying the allele specific expression analysis pipelines we have been developing for sheep to the dataset from goats to address the key questions listed above. Once a set of potential candidate alleles exhibiting evidence of ASE are established these can be experimentally verified using quantitative real-time PCR. The project will be primarily bioinformatics and data analysis based with some laboratory work including, cell culture, RNA extraction, cDNA synthesis and qPCR. Training will be provided in bioinformatics and laboratory work. The project offers the opportunity to work within the International Goat Genomics Consortium (IGGC) and the international Functional Annotation of ANimal Genomes (FAANG) consortium. This provides significant travel, collaboration and training opportunities, providing an excellent start to any research career.
Pai AA, Pritchard JK, Gilad Y (2015) The genetic and mechanistic basis for variation in gene regulation. PLoS Genetics, 11(1):e1004857.
Chamberlain, AJ, Vander Jagt CJ, Hayes BJ, Khanesfid M, Marret LC, Millen CA, Nguyen TTT, Goddard ME (2015) Extensive variation between tissues in allele specific expression in an outbred mammal. BMC Genomics, 16:993.
Clark EL, McCulloch MB, Bush SJ, Farquhar IL, Young R, Lefevre L, C. Pridans, Wu C, Afrasiabi C, Whitelaw CB, Watson M, Freeman T, Summers KM, Archibald AL and Hume DA (2017) A high resolution atlas of gene expression in the domestic sheep (Ovis aries). PLoS Genetics, 13(9):e1006997.