bioRxiv Science⌕ Search

Biology subjects

Randhawa, I.

Publications and source records attributed to Randhawa, I..

2 recordsLinked to original sources

In-situ genomic prediction using low-coverage Nanopore sequencing

Most traits in livestock, crops and humans are polygenic, that is, a large number of loci contribute to genetic variation. Effects at these loci lie along a continuum ranging from common low-effect to rare high-effect variants that cumulatively contribute to the overall phenotype. Statistical methods to calculate the effect of these loci have been developed and can be used to predict phenotypes in new individuals. In agriculture, these methods are used to select superior individuals using genomic breeding values; in humans these methods are used to quantitatively measure an individuals disease risk, termed polygenic risk scores. Both fields typically use SNP array genotypes for the analysis. Recently, genotyping-by-sequencing has become popular, due to lower cost and greater genome coverage (including structural variants). Oxford Nanopore Technologies (ONT) portable sequencers have the potential to combine the benefits genotyping-by-sequencing with portability and decreased turn-around time. This introduces the potential for in-house clinical genetic disease risk screening in humans or calculating genomic breeding values on-farm in agriculture. Here we demonstrate the potential of the later by calculating genomic breeding values for four traits in cattle using low-coverage ONT sequence data and comparing these breeding values to breeding values calculated from SNP arrays. At sequencing coverages between 2X and 4X the correlation between ONT breeding values and SNP array-based breeding values was > 0.92 when imputation was used and > 0.88 when no imputation was used. With an average sequencing coverage of 0.5x the correlation between the two methods was between 0.85 and 0.92 using imputation, depending on the trait. This demonstrates that ONT sequencing has great potential for in clinic or on-farm genomic prediction. Author SummaryGenomic prediction is a method that uses a large number of genetic markers to predict complex phenotypes in livestock, crops and humans. Currently the techniques we use to determine genotypes requires complex equipment which can only be used in laboratories. However, Oxford Nanopore Technologies have released a portable DNA sequencer, which can genotype a range of organisms in the field. As a result of the devices higher error rate, it has largely only been considered for specific applications, such as characterising large mutations. Here we demonstrated that despite the devices error rate, accurate genomic prediction is also possible using this portable device. The ability to accurately predict complex phenotypes such as the predisposition to schizophrenia in humans or lifetime fertility in livestock in-situ would decrease the turnaround time and ultimately increase the utility of this method in the human clinical and on-farm settings.

genetics↗

Genomic characterisation and conservation genetics of the indigenous Irish Kerry cattle breed

Kerry cattle are an endangered landrace heritage breed of cultural importance to Ireland. In the present study we have used genome-wide SNP data (Illumina(R) BovineSNP50 array) to evaluate genomic diversity within the Kerry cattle population and between Kerry cattle and other European cattle breeds. Visualisation of patterns of genetic differentiation and gene flow among cattle breeds using phylogenetic trees with ancestry graphs highlighted, in particular, historical gene flow from the British Shorthorn breed into the ancestral population of modern Kerry cattle. Principal component analysis (PCA) and genetic clustering emphasised the genetic distinctiveness of Kerry cattle relative to comparator British and European cattle breeds. Modelling of genetic effective population size (Ne) revealed a demographic trend of diminishing Ne over time and that recent estimated Ne values for the Kerry breed may be less than the threshold for sustainable genetic conservation. In addition, analysis of genome-wide autozygosity (FROH) showed that genomic inbreeding has increased significantly during the 20 years between 1992 and 2012. Finally, signatures of selection revealed genomic regions subject to natural and artificial selection as Kerry cattle adapted to the climate, physical geography and agro-ecology of southwest Ireland.\n\nNote 1: This is an Associate Editor (D.E.M) Inaugural Article submission to Frontiers in Genetics: Livestock Genomics\n\nNote 2: British English language style preferred for publication of this article.

genomics↗