Biology subjects

Snell, R. G.

Publications and source records attributed to Snell, R. G..

3 recordsLinked to original sources

bioRxiv2018

Multiple QTL underlie milk phenotypes at the CSF2RB locus

BackgroundBovine milk provides an important source of nutrition in much of the Western world, forming components of many food products. Over many years, artificial selection has substantially improved milk production by cows. However, the genes underlying milk production quantitative trait loci (QTL) remain relatively poorly characterised. Here, we investigate a previously-reported QTL located at the CSF2RB locus, for several milk production phenotypes, to better understand its underlying genetic and molecular causes.\n\nResultsUsing a population of 29,350 taurine dairy cattle, we conducted association analyses for milk yield and composition traits, and identified highly significant QTL for milk yield, milk fat concentration, and milk protein concentration. Strikingly, protein concentration and milk yield appear to show co-located yet genetically distinct QTL. To attempt to understand the molecular mechanisms that might be mediating these effects, gene expression data were used to investigate eQTL for eleven genes in the broader interval. This analysis highlighted genetic impacts on CSF2RB and NCF4 expression that share similar association signatures to those observed for lactation QTL, strongly implicating one or both of these genes as the cause of these effects. Using the same gene expression dataset representing 357 lactating cows, we also identified 38 novel RNA editing sites in the 3' UTR of CSF2RB transcripts. The extent to which two of these sites were edited also appears to be genetically co-regulated with lactation QTL, highlighting a further layer of regulatory complexity implicating the CSF2RB gene.\n\nConclusionsThis chromosome 5 locus presents a diversity of molecular and lactation QTL, likely representing multiple overlapping effects that, at a minimum, highlight the CSF2RB gene as having a causal role in these processes.

genomics↗

bioRxiv2018

RBV: Read balance validator, a tool for prioritising copy number variations in germline conditions

BackgroundThe popularisation and decreased cost of genome resequencing has resulted in an increased use in molecular diagnostics. While there are a number of established and high quality bioinfomatic tools for identifying small genetic variants including single nucleotide variants and indels, currently there is no established standard for the detection of copy number variants (CNVs) from sequence data. The requirement for CNV detection from high throughput sequencing has resulted in the development of a large number of software packages. These tools typically utilise the sequence data characteristics: read depth, split reads, read pairs, and assembly-based techniques. However the additional source of information from read balance, defined as relative proportion of reads of each allele at each position, has been underutilised in the existing applications.\n\nResultsWe present Read Balance Validator (RBV), a bioinformatic tool which uses read balance for prioritisation and validation of putative CNVs. The software simultaneously interrogates nominated regions for the presence of deletions or multiplications, and can differentiate larger CNVs from diploid regions. Additionally, the utility of RBV to test for inheritance of CNVs is demonstrated in this report.\n\nConclusionsRBV is a CNV validation and prioritisation bioinformatic tool for both genome and exome sequencing available as a python package from https://github.com/whitneywhitford/RBV

bioinformatics↗

bioRxiv2018

Widespread cis-regulation of RNA-editing in a large mammal

Post-transcriptional RNA editing may regulate transcript expression and diversity in cells, with potential impacts on various aspects of physiology and environmental adaptation. A small number of recent genome-wide studies in Drosophila, mouse, and human have shown that RNA editing can be genetically modulated, highlighting loci that quantitatively impact editing of transcripts. The potential gene expression and physiological consequences of these RNA editing quantitative trait loci (edQTL), however, are almost entirely unknown. Here, we present analyses of RNA editing in a large domestic mammal (Bos taurus), where we use whole genome and high depth RNA sequencing to discover, characterise, and conduct genetic mapping studies of novel transcript edits. Using a discovery population of nine deeply-sequenced cows, we identify 2,001 edit sites in the mammary transcriptome, the majority of which are adenosine to inosine edits (97.4%). Most sites are predicted to reside in double-stranded secondary structures (85.7%), and quantification of the rates of editing in an additional 355 cows reveals editing is negatively correlated with gene expression in the majority of cases. Genetic analyses of RNA editing and gene expression highlights 67 cis-regulated edQTL, of which seven appear to co-segregate with expression QTL effects. Trait association analyses in a separate population of 9,988 lactating cows also shows nine of the cis-edQTL coincide with at least one co-segregating lactation QTL. Together, these results enhance our understanding of RNA editing dynamics in mammals, and suggest mechanistic links by which loci may impact phenotype through RNA-editing mediated processes.

genomics↗