Biology subjects

Brauning, R.

Publications and source records attributed to Brauning, R..

4 recordsLinked to original sources

bioRxiv2025

Bighorn sheep T2T genome assembly reveals differences in immune genes: a potential cause of high morbidity due to respiratory pathogens

The bighorn sheep (Ovis canadensis), despite its close relation to domestic sheep, suffer higher morbidity and mortality from respiratory disease complexes, likely due to genetic differences in immune responses. Unraveling highly repetitive regions such as immune loci and genetic differences was problematic until now. We generated a bighorn sheep telomere-to-telomere assembly, adding 14.28% of novel sequence compared to the previous reference. This enabled the first complete immune loci annotation revealing the IGL and TR loci are significantly short in bighorn sheep. Importantly, a critical immune gene GBP5 and ZNF501, involved in Golgi-mediated immune response, are lacking in bighorn but present in domestic sheep. Re-analysis of a Mycoplasma ovipneumoniae carriage study, using this assembly, identified the immune gene CAPN2 as a key genetic marker for disease carriage, not observable in the original study. This work provides a critical resource for identifying phenotype-linked genetic variation and exploring evolutionary adaptations of bighorn sheep.

genomics↗

bioRxiv2019

A restriction enzyme reduced representation sequencing approach for low-cost, high-throughput metagenome profiling

Microbial community profiles have been associated with a variety of traits, including methane emissions in livestock, however, these profiles can be difficult and expensive to obtain for thousands of samples. The objective of this work was to develop a low-cost, high-throughput approach to capture the diversity of the rumen microbiome. Restriction enzyme reduced representation sequencing (RE-RRS) using ApeKI or PstI, and two bioinformatic pipelines (reference-based and reference-free) were compared to 16S rRNA gene sequencing using repeated samples collected two weeks apart from 118 sheep that were phenotypically extreme (60 high and 58 low) for methane emitted per kg dry matter intake (n=236). DNA was extracted from freeze-dried rumen samples using a phenol chloroform and bead-beating protocol prior to sequencing. The resulting sequences were used to investigate the repeatability of the rumen microbial community profiles, the effect of host genetics, laboratory and analytical method, and the genetic and phenotypic correlations with methane production. The results suggested that the best method was PstI RE-RRS analyzed with the reference-free approach via a correspondence analysis, with estimates for repeatability of 0.62{+/-}0.06, heritability 0.31{+/-}0.29, and genetic and phenotypic correlation with methane emissions of 0.88{+/-}0.25 and 0.64{+/-}0.05 respectively for the first component of correspondence analysis. The reference-free approach assigned 62.0{+/-}5.7% of reads to common 65 bp tags, much higher than the reference-based approach of 6.8{+/-}1.8% of reads assigned. Sensitivity studies suggested approximately 2000 samples could be sequenced in a single lane on an Illumina HiSeq 2500, therefore the current work of 118 samples/lane and future proposed 384 samples/lane are well within that threshold. Our approach is now being used to investigate host factors affecting the rumen and its association with a variety of production and environmental traits. With minor adaptations, our approach could be used to obtain microbial profiles from other metagenomic samples.

microbiology↗

bioRxiv2019

Exclusion and genomic relatedness methods for assignment of parentage using genotyping-by-sequencing data

Genotypes are often used to assign parentage in agricultural and ecological settings. Sequencing can be used to obtain genotypes but does not provide unambiguous genotype calls, especially when sequencing depth is low in order to reduce costs. In that case, standard parentage analysis methods no longer apply. A strategy for using low-depth sequencing data for parentage assignment is developed here. It entails the use of relatedness estimates along with a metric termed excess mismatch rate which, for parent-offspring pairs or trios, is the difference between the observed mismatch rate and the rate expected under a model of inheritance and allele reads without error. When more than one putative parent has similar statistics, bootstrapping can provide a measure of the relatedness similarity. Putative parent-offspring trios can be further checked for consistency by comparing the offsprings estimated inbreeding to half the parent relatedness. Suitable thresholds are required for each metric. These methods were applied to a deer breeding operation consisting of two herds of different breeds. Relatedness estimates were more in line with expectation when the herds were analysed separately than when combined, although this did not alter which parents were the best matches with each offspring. Parentage results were largely consistent with those based on a microsatellite parentage panel with three discordant parent assignments out of 1561. Two models are investigated to allow the parentage metrics to be calculated with non-random selection of alleles. The tools and strategies given here allow parentage to be assigned from low-depth sequencing data.

genetics↗

bioRxiv2017

Linkage Disequilibrium Estimation in Low Coverage High-Throughput Sequencing Data

High-throughput sequencing methods that multiplex a large number of individuals have provided a cost-effective approach for discovering genome-wide genetic variation in large populations. These sequencing methods are increasingly being utilized in population genetic studies across a diverse range of species. One side-effect of these methods, however, is that one or more alleles at a particular locus may not be sequenced, particularly when the sequencing depth is low, resulting in some heterozygous genotypes being called as homozygous. Under-called heterozygous genotypes have a profound effect on the estimation of linkage disequilibrium and, if not taken into account, leads to inaccurate estimates. We developed a new likelihood method, GUS-LD, to estimate pairwise linkage disequilibrium using low coverage sequencing data that accounts for under-called heterozygous genotypes. Our findings show that accurate estimates were obtained using GUS-LD on low coverage sequencing data, whereas underestimation of linkage disequilibrium results if no adjustment is made for under-called heterozygotes.

genetics↗