Biology subjects

Johnsson, M.

Publications and source records attributed to Johnsson, M..

6 recordsLinked to original sources

bioRxiv2018

Analysis of a large data set reveals haplotypes carrying putatively recessive lethal alleles with pleiotropic effects on economically important traits in beef cattle

BackgroundDeleterious recessive alleles can result in reduced economic performance in livestock in multiple ways in homozygous individuals: from early embryonic death, death soon after birth, to being non-lethal but causing reduced viability. While death is an easy phenotype to score, reduced viability is not as easy to identify. However, it can sometimes be observed as reduced artificial insemination (AI) conception rates, longer calving intervals, or higher hazard for live born animals.\n\nMethodsIn this paper, we searched for haplotypes carrying putatively recessive lethal alleles in 132,725 genotyped Irish beef cattle from five breeds: Aberdeen Angus, Charolais, Hereford, Limousin, and Simmental. We phased the genotypes in sliding windows along the genome and used five tests to identify haplotypes with absence of or reduced homozygosity. We then corroborated the identified haplotypes with reproduction records, indicating early embryonic death, and postnatal survival records. Finally, we assessed haplotype pleiotropy by estimating substitution effects on national estimates of breeding values for 15 economically important traits in beef production.\n\nResultsWe found support for three haplotypes with carrying putatively recessive lethal alleles. The haplotypes were located on chromosome 14 in Aberdeen Angus, chromosome 19 in Charolais and chromosome 16 in Simmental. Their population frequencies is 15.2%, 14.4%, and 8.8%, respectively. All of the haplotypes showed pleiotropic effects on economically important traits for beef production. Their allele substitution effects are {euro}3.23, {euro}1.47, and {euro}2.30 for the terminal index and -{euro}3.15, -{euro}0.75, and {euro}1.12 for the replacement index, where one standard deviations are {euro}18.32, {euro}22.54, and {euro}22.33 for terminal index and {euro}29.52, {euro}35.62, and {euro}30.97 for the replacement index. We identified ZFAT as the candidate gene for lethality in Aberdeen Angus, several candidate genes for the Simmental haplotype, and no candidate genes for the Charolais haplotype.\n\nConclusionsWe analysed genotype, reproduction, survival, and production data to discover haplotypes carrying putatively recessive lethal alleles in Irish beef cattle. We found support for three haplotypes. All three haplotypes have pleiotropic effects on economically important traits in beef production.

genetics↗

bioRxiv2018

Impact of index hopping and bias towards the reference allele on accuracy of genotype calls from low-coverage sequencing

BackgroundInherent sources of error and bias that affect the quality of the sequence data include index hopping and bias towards the reference allele. The impact of these artefacts is likely greater for low-coverage data than for high-coverage data because low-coverage data has scant information and standard tools for processing sequence data were designed for high-coverage data. With the proliferation of cost-effective low-coverage sequencing there is a need to understand the impact of these errors and bias on resulting genotype calls.\n\nResultsWe used a dataset of 26 pigs sequenced both at 2x with multiplexing and at 30x without multiplexing to show that index hopping and bias towards the reference allele due to alignment had little impact on genotype calls. However, pruning of alternative haplotypes supported by a number of reads below a predefined threshold, a default and desired step for removing potential sequencing errors in high-coverage data, introduced an unexpected bias towards the reference allele when applied to low-coverage data. This bias reduced best-guess genotype concordance of low-coverage sequence data by 19.0 absolute percentage points.\n\nConclusionsWe propose a simple pipeline to correct this bias and we recommend that users of low-coverage sequencing be wary of unexpected biases produced by tools designed for high-coverage sequencing.

bioinformatics↗

bioRxiv2018

Sequence variability, constraint and selection in the CD163 gene in pigs

BackgroundIn this paper, we investigate sequence variability, evolutionary constraint, and selection on the CD163 gene in pigs. The pig CD163 gene is required for infection by porcine reproductive and respiratory syndrome virus (PRRSV), a serious pathogen with major impact on pig production.\n\nResultsWe used targeted pooled sequencing of the exons of CD163 to detect sequence variants in 35,000 pigs of diverse genetic backgrounds and search for potential knock-out variants. We then used whole genome sequence data from three pig lines to calculate a variant intolerance score, which measures the tolerance of genes to protein coding variation, a selection test on protein coding variation over evolutionary time, and haplotype diversity statistics to detect recent selective sweeps during breeding.\n\nConclusionsWe performed a deep survey of sequence variation in the CD163 gene in domestic pigs. We found no potential knock-out variants. CD163 was moderately intolerant to variation, and showed evidence of positive selection in the lineage leading up to the pig, but no evidence of selective sweeps during breeding.

genomics↗

bioRxiv2018

Removal of alleles by genome editing -- RAGE against the deleterious load

BackgroundIn this paper, we simulate deleterious load in an animal breeding program, and compare the efficiency of genome editing and selection for decreasing load. Deleterious variants can be identified by bioinformatics screening methods that use sequence conservation and biological prior information about protein function. Once deleterious variants have been identified, how can they be used in breeding?\n\nResultsWe simulated a closed animal breeding population subject to both natural selection against deleterious load and artificial selection for a quantitative trait representing the breeding goal. Deleterious load was polygenic and due to either codominant or recessive variants. We compared strategies for removal of deleterious alleles by genome editing (RAGE) to selection against carriers. Each strategy varied in how animals and variants were prioritized for editing or selection.\n\nConclusionsGenome editing of deleterious alleles reduces deleterious load, but requires simultaneous editing of multiple deleterious variants in the same sire to be effective when deleterious variants are recessive. In the short term, selection against carriers is a possible alternative to genome editing when variants are recessive. The dominance of deleterious variants affects both the efficiency of genome editing and selection against carriers, and which variant prioritization strategy is the most efficient. Our results suggest that in the future, there is the potential to use RAGE against deleterious load in animal breeding.

genetics↗

bioRxiv2018

CREBBP and WDR 24 Affects Quantitative Variation in Red Colouration in the Chicken

Plumage colouration in birds is important for a plethora of reasons, ranging from camouflage, sexual signaling, and species recognition. The genes underlying colour variation have been vital in understanding how genes can affect a phenotype. Multiple genes have been identified that affect plumage variation, but research has principally focused on major-effect genes (such as those causing albinism, barring, and the like), rather than the smaller effect modifier loci that more subtly influence colour. By utilizing a domestic x wild advanced intercross with a combination of classical QTL mapping of red colouration as a quantitative trait and a targeted genetical genomics approach, we have identified five separate candidate genes (CREBBP, WDR24, ARL8A, PHLDA3, LAD1) that putatively influence quantitative variation in red colouration in chickens. Such small effect loci are potentially far more prevalent in wild populations, and can therefore potentially be highly relevant to colour evolution.

genetics↗

bioRxiv2017

Genetics and genomics of social behaviour in a chicken model

The identification of genes affecting behaviour can be problematic, yet their identification allows a raft of possibilities. Sociality and social behaviour can have multiple definitions, though at its core it is the desire to seek contact with con- or hetero-specifics. The identification of genes affecting sociality can therefore give insights into the maintenance and establishment of sociality. In this study we used the combination of an advanced intercross between wild and domestic chickens with a combined QTL and eQTL genetical genomics approach to identify genes for social reinstatement (SR) behaviour. A total of 24 SR QTL were identified and overlaid with over 600 eQTL obtained from the same birds using hypothalamus tissue. Correlations between overlapping QTL and eQTL indicated 5 strong candidate genes, with the gene TTRAP being strongly significantly correlated with multiple aspects of SR behaviour, as well as possessing a highly significant eQTL. The distribution of eQTL can also indicate the genetic mechanisms underlying domestication itself. Multiple eQTL were found to in discrete clusters, however tests for pleiotropy show that these blocks were primarily linked in origin. This suggests that clustered genetic modules, rather than pure pleiotropy (as hypothesised by the neural crest theory) appears to be driving domestication in the chicken.

genetics↗