Biology subjects

Johnsson, M.

Publications and source records attributed to Johnsson, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Variant intolerance scores in cattle

Variant intolerance methods score the essentiality of genes based on large datasets of genetic variants and have been used in population genomics of humans and model organisms. In this paper, we estimated Residual Variation Intolerance Scores for protein-coding genes and predicted protein domains in cattle. In agreement with results from other species, the most variant-tolerant genes and domains included genes related to olfaction and adaptive immunity, whereas the least-variant tolerant genes and domains included genes involved in fundamental cellular processes. There was a moderate positive correlation with estimates from orthologous human genes. We provide estimates of variant intolerance for cattle may be useful for genomic analyses of deleterious variants and population genomics in cattle.

genetics↗

bioRxiv2026

BMP2 signaling cooperates with retinoic acid to activate a meiotic-entry transcriptional program in chicken primordial germ cells

The initiation of meiosis in germ cells is largely regulated by extrinsic cues from the gonadal environment, but the logic of these signals remains poorly understood in non-mammalian vertebrates. Retinoic acid has long been considered a principal meiosis-inducing signal, yet recent genetic and reconstitution studies indicate that retinoic acid alone is insufficient. In mice, bone morphogenetic protein 2 cooperates with retinoic acid to establish the oogenic program through the bone morphogenetic protein-responsive transcriptional regulator Zglp1, but whether this regulatory logic is conserved beyond mammals is unknown. Here, using cultured chicken (Gallus gallus) primordial germ cells, we show that bone morphogenetic protein 2 cooperates with retinoic acid to promote a meiotic-entry transcriptional program. Retinoic acid alone induced a limited retinoic acid-responsive state, whereas combined treatment reduced the primordial germ cell program and activated early meiotic genes. The resulting transcriptome matched the premeiotic-to-meiotic-entry transition of the embryonic ovary in a single-cell atlas of chicken germ cells. We also generated a genome-edited primordial germ cell line carrying an SYCP3 promoter-green fluorescent protein reporter as a platform for dissecting meiotic-entry signals in culture. Comparative genomic analysis revealed Gallus-specific pseudogenization of ZGLP1, which is intact in closely related galliform species. Retinoic acid and bone morphogenetic protein may therefore act through a different downstream regulator in chicken. Article summaryEggs and sperm are produced by meiosis, a specialized cell division that starts during embryonic development. Retinoic acid, a signal derived from vitamin A, was long thought to be enough to start meiosis, but on its own it is not. In mice, a second signal, bone morphogenetic protein 2 (BMP2), works alongside retinoic acid to push germ cells toward the egg-producing program. We asked whether birds use the same combination. Giving both signals to chicken primordial germ cells in culture switched on genes for egg development and for the first steps of meiosis; retinoic acid alone did not. Birds and mammals last shared an ancestor more than 300 million years ago, so the pairing of these two signals appears to be an old feature of vertebrate germ cells. The cells stopped short of completing meiosis, which means other signals are still missing. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=169 SRC="FIGDIR/small/740788v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@10b8b22org.highwire.dtl.DTLVardef@db9a08org.highwire.dtl.DTLVardef@15d9726org.highwire.dtl.DTLVardef@16e4dd3_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

bioRxiv2026

Two-tower models for genomic prediction of reproductive outcomes and sex-specific fertility liabilities: simulation insights

Many biological characteristics arise by interactions between more than one biological organism or unit. Fertilization success in sexually reproducing species represents such an extended phenotype where both mates are required to be fertile for a successful outcome. Consequently, predictive models should account for the joint nature of reproductive performance while offering interpretable estimates for individual mate contributions. Recent advances in genomics and machine learning (ML) provide standardized, high-dimensional genetic information on one hand and computational tools capable of modeling complex biological systems on the other. Here, we construct and evaluate two-tower (TT) machine learning architectures for genomic prediction of binary reproductive outcomes and recovery of sex-specific fertility liabilities. Simulated datasets, generated under a range of genetic architectures, were utilized to compare multilayer perceptron (TT-MLP), convolutional neural network (TT-CNN), and L1-regularized linear (TT-LASSO) two-tower models. Simulation scenarios varied sex-specific heritabilities, genetic correlations, infertility prevalence, mating structure, and sex-specific infertility rates. Models were evaluated with regard to their ability to predict reproductive success at pair level and also recover true underlying genetic values for male and female fertility. Prediction accuracy increased with the underlying heritable component as expected, while sex-specific tower-scores successfully recovered latent fertility liabilities despite models being trained only on observed joint outcomes. TT-LASSO achieved the highest overall classification performance, whereas TT-MLP provided more balanced and consistent recovery of sex-specific genetic values across scenarios. An additional simulation, incorporating genotype-dependent mate compatibility demonstrated advantages of fully-connected neural networks for capturing non-additive interactions. These results indicate that two-tower frameworks provide a powerful approach for modeling reproductive traits, enabling simultaneous prediction of aggregate reproductive outcomes and sex-specific fertility liabilities from genotypic information.

genetics↗

bioRxiv2026

Genomic insights into bacterial kidney disease resistance in Arctic charr (Salvelinus alpinus) via a 72k SNP array

Selection for disease resistance forms one of the most highlighted areas of aquaculture breeding. A breeding program for Arctic charr has been operating in Sweden for over 40 years, making it the oldest of its kind worldwide for this species. However, the lack of available genomic resources prevented selection for any disease-resistance traits. A 72k Axiom SNP array was produced in this study and used to assess the potential to select for charr resistant to bacterial kidney disease (BKD), which is currently a major threat to the industry. Following a challenge experiment with Renibacterium salmoninarum, the causative agent of BKD, relevant phenotypic proxies were collected from approximately 2,000 charr. Thereafter, those animals were genotyped with the new 72k SNP array. The magnitude of the estimated variance components suggested potential for breeding for BKD resistance in charr, with relevant heritabilities ranging from 0.05 to 0.56 depending on the resistance proxy used. In addition, GWAS suggested that BKD resistance is a polygenic trait. Furthermore, genomic prediction approaches indicated that BKD-resistant animals can be identified using their SNP genotypes. Accuracies, expressed as Pearson correlation coefficients, when BKD resistance was analysed as a continuous trait, ranged from 0.42 to 0.52. In the scenario where BKD resistance was treated as a binary trait, the efficiency of genomic prediction was assessed using ROC curves, with an area under the curve of 0.72. Finally, no unfavourable correlations were found with growth traits. The developed 72k SNP array has the potential of being a pivotal tool for the Swedish Arctic charr breeding program. Moreover, our data support the use of genomic prediction in breeding BKD-resistant Arctic charr. As a critical next step, further validations in actual industry conditions would be required.

genetics↗

bioRxiv2025

Genetic parameters and sex-specific architecture of observed and latent fertility phenotypes in a closed breeding nucleus of an Arctic salmonid

Successful reproduction is a key factor for efficient breeding schemes and sustainable animal farming. Aquaculture breeding programs rely heavily on small fractions of selected breeders to yield large production stocks, given the high fecundity typically observed in these species. In Sweden, Arctic charr (Salvelinus alpinus) is a salmonid with notable commercial potential, with a selective breeding program operating for ten generations under a growth-rate focused breeding goal. Despite significant gains, the nucleus faces challenges with low and fluctuating fertility impeding expansion efforts. In this study, we estimate genetic parameters for charr milt quality phenotypes measured with specialized cytometry and Computer-Assisted Sperm Analysis (CASA). At the same time, we assess the sex-specific architecture governing egg count and sperm concentration along body size. Finally, we propose a novel analytical framework for the analysis of realized fertilization success rates by considering a multiplicative system of latent maternal and paternal contributions. Low to moderate heritability estimates and genetic correlations were obtained from multi-trait modelling for traits reflecting sperm quality along with high estimates for fork length. Genetic correlations among sperm kinematic parameters appeared strong, while the same traits showed weak positive and weak negative correlations with sperm concentration and fork length, respectively. Furthermore, a negative genetic correlation between sperm concentration and both male body size and egg count suggests a complex interplay of a possible trade-off and sexual antagonism. Our latent fertility analytical approach returned low to moderate heritability estimates depending on the modelling configuration. Overall, our study demonstrated the complexity characterizing the heritable portions of reproductive traits in Arctic charr and tested alternative tools that have the potential for integration into selective breeding programs.

genetics↗

bioRxiv2025

When large-effect damaging alleles enter small populations

Large-effect recessive damaging variants found at relatively high frequencies are common enough in domestic animals that they cause problems in breeding programs. There are several potential reasons. Deleterious variants may rise in frequency because of genetic drift, be driven to intermediate frequency by balancing selection by heterozygote advantage, or be spread by exceptionally influential parents, usually sires, that sometimes occur in animal breeding programs. Further, animal populations are often connected by migration. In this paper, we use a series of population genetic models to address how large-effect damaging alleles establish themselves in small populations, such as domestic animal populations or wild populations of mammals. The results confirm that a lethal allele under directional selection is fairly unlikely to become common, unless there are influential sire events with very large contributions or the population size is very small. On the other hand, a lethal allele under balancing selection can easily become common, especially if there are influential parents. When there is balancing selection, migration between connected populations effectively spreads alleles. The results accord with the many examples of recessive damaging alleles in domestic animals.

genetics↗

bioRxiv2024

Population history of Swedish cattle breeds: estimates and model checking

In this work, we use linkage disequilibrium-based methods to estimate recent population history from genotype data in Swedish cattle breeds, as well as international Holstein and Jersey cattle data for comparison. Our results suggest that these breeds have been effectively large up until recently, when they declined around the onset of systematic breeding. The inferred trajectories were qualitatively similar, with a large historical population and one decline. We used population genetic simulation to check the inferences. When comparing simulations from the inferred population histories to real data, the proportion low-frequency variants in real data was different than was implied by the inferred population histories, and there was somewhat higher genomic inbreeding in real data than implied by the inferred histories. The inferred population histories imply that much of the variation we see today is transient, and it will be lost as the populations settle into a new equilibrium, even if efforts to maintain effective population size at current levels are successful.

genetics↗

bioRxiv2024

A male-essential microRNA is key for avian sex chromosome dosage compensation

Birds have a sex chromosome system in which females are heterogametic (ZW) and males are homogametic (ZZ). The differentiation of avian sex chromosomes from ancestral autosomes entailed the loss of most genes from the W chromosome during evolution. However, to what extent mechanisms evolved that counterbalance the consequences of this extensive gene dosage reduction in female birds has remained unclear. Here we report functional in vivo and evolutionary analyses of a Z-chromosome-linked microRNA (miR-2954) with strongly male-biased expression that was previously proposed to play a key role in sex chromosome dosage compensation1. We knocked out miR-2954 in chicken, which resulted in early embryonic lethality of homozygous knockout males, likely due to the highly specific upregulation of dosage-sensitive Z-linked target genes of miR-2954. Our evolutionary gene expression analyses further revealed that these dosage-sensitive target genes have become upregulated on the single Z in female birds during evolution. Altogether, our work unveils a scenario where evolutionary pressures on females following W gene loss led to the evolution of transcriptional upregulation of dosage-sensitive genes on the Z not only in female but also in male birds. The resulting overabundance of transcripts in males resulting from the combined activity of two dosage-sensitive Z gene copies was in turn offset by the emergence of a highly targeted miR-2954-mediated transcript degradation mechanism during avian evolution. Our findings demonstrate that birds have evolved a unique sex chromosome dosage compensation system in which a microRNA has become essential for male survival.

evolutionary biology↗

bioRxiv2023

Accounting for nuclear and mito genome in dairy cattle breeding - a simulation study

Mitochondria play a significant role in numerous cellular processes through proteins encoded by both nuclear genome (nDNA) and mito genome (mDNA). While the variation in nDNA is influenced by mutations and recombination of parental genomes, the variation in mDNA is solely driven by mutations. In addition, mDNA is inherited in a haploid form, from the dam. Cattle populations show significant variation in mDNA between and within breeds. Past research suggests that variation in mDNA accounts for 1-5% of the phenotypic variation in dairy traits. Here we simulated a dairy cattle breeding program to assess the impact of accounting for mDNA variation in pedigree-based and genome-based genetic evaluations on the accuracy of estimated breeding values for mDNA and nDNA components. We also examined the impact of alternative definitions of breeding values on genetic gain, including nDNA and mDNA components that both impact phenotype expression, but mDNA is inherited only maternally. We found that accounting for mDNA variation increased accuracy between +0.01 and +0.05 for different categories of animals, especially for young bulls (+0.05) and females without genotype data (between +0.01 and +0.03). Different scenarios of modelling and breeding value definition impacted genetic gain. The standard approach of ignoring mDNA variation achieved competitive genetic gain. Modelling, but not selecting on mDNA expectedly reduced genetic gain, while optimal use of mDNA variation recovered the genetic gain.

genetics↗

bioRxiv2023

The regulation of methylation on the Z chromosome and the identification of multiple novel Male Hyper-Methylated regions in the chicken

DNA methylation is a key regulator of eukaryote genomes, and is of particular relevance in the regulation of gene expression on the sex chromosomes, with a key role in dosage compensation in mammalian XY systems. In the case of birds, dosage compensation is largely absent, with it being restricted to two small Male Hyper-Methylated (MHM) regions on the Z chromosome. To investigate how variation in DNA methylation is regulated on the Z chromosome we utilised a wild x domestic advanced intercross in the chicken, with both hypothalamic methylomes and transcriptomes assayed in 124 individuals. The relatively large numbers of individuals allowed us to identify additional genomic MHM regions on the Z chromosome that were significantly differentially methylated between the sexes. These regions appear to down-regulate local gene expression in males, but not remove it entirely (unlike the lncRNAs identified in the initial MHM regions). In addition, trans effect hotspots were also identified that were based on the autosomes but affected the Z, and also that were based on the Z chromosome but that affected autosomal DNA methylation regulation. In addition, quantitative trait loci (QTL) that regulate variation in methylation on the Z chromosome, and those loci that regulate methylation on the autosomes that derive from the Z chromosome were mapped. Trans-effect hotspots were also identified that were based on the autosomes but affected the Z, and also one that was based on the Z chromosome but that affected both autosomal and sex chromosome DNA methylation regulation. Our results highlight how additional MHM regions are actually present on the Z chromosome, and they appear to have smaller-scale effects on gene expression in males. Quantitative variation in methylation is also regulated both from the autosomes to the Z chromosome, and from the Z chromosome to the autosomes.

evolutionary biology↗

bioRxiv2022

Genomic prediction with whole-genome sequence data in intensely selected pig lines

BackgroundEarly simulations indicated that whole-genome sequence data (WGS) could improve genomic prediction accuracy and its persistence across generations and breeds. However, empirical results have been ambiguous so far. Large data sets that capture most of the genome diversity in a population must be assembled so that allele substitution effects are estimated with high accuracy. The objectives of this study were to use a large pig dataset to assess the benefits of using WGS for genomic prediction compared to using commercial marker arrays, to identify scenarios in which WGS provides the largest advantage, and to identify potential pitfalls for its effective implementation. MethodsWe sequenced 6,931 individuals from seven commercial pig lines with different numerical size. Genotypes of 32.8 million variants were imputed for 396,100 individuals (17,224 to 104,661 per line). We used BayesR to perform genomic prediction for eight complex traits. Genomic predictions were performed using either data from a marker array or variants preselected from WGS based on association tests. ResultsThe prediction accuracy with each set of preselected WGS variants was not robust across traits and lines and the improvements in prediction accuracy that we achieved so far with WGS compared to marker arrays were generally small. The most favourable results for WGS were obtained when the largest training sets were available and used to preselect variants with statistically significant associations to the trait for augmenting the established marker array. With this method and training sets of around 80k individuals, average improvements of genomic prediction accuracy of 0.025 were observed in within-line scenarios. ConclusionsOur results showed that WGS has a small potential to improve genomic prediction accuracy compared to marker arrays in intensely selected pig lines in some settings. Thus, although we expect that more robust improvements could be attained with a combination of larger training sets and optimised pipelines, the use of WGS in the current implementations of genomic prediction should be carefully evaluated on a case-by-case basis against the cost of generating WGS at a large scale.

genomics↗

bioRxiv2022

Rare and population-specific functional variation across pig lines

BackgroundIt is expected that functional, mainly missense and loss-of-function (LOF), and regulatory variants are responsible for phenotypic differences among breeds, genetic lines, and varieties of livestock and crop species that have undergone diverse selection histories. However, there is still limited knowledge about the existing missense and LOF variation in livestock commercial populations, in particular regarding population-specific variation and how it can affect applications such as across-breed genomic prediction. MethodsWe re-sequenced the whole genome of 7,848 individuals from nine commercial pig breeding lines (average sequencing coverage: 4.1x) and imputed whole-genome genotypes for 440,610 pedigree-related individuals. The called variants were categorized according to predicted functional annotation (from LOF to intergenic) and prevalence level (number of lines in which the variant segregated; from private to widespread). Variants in each category were examined in terms of distribution along the genome, minor allele frequency, Wrights fixation index (FST), individual load, and association to production traits. ResultsOf the 46 million called variants, 28% were private (called in only one line) and 21% were widespread (called in all nine lines). Genomic regions with low recombination rate were enriched with private variants. Low-prevalence variants (called in one or a few lines only) were enriched for lower allele frequencies, lower FST, and putatively functional and regulatory roles (including loss-of-function and deleterious missense variants). Only a small subset of low-prevalence variants was found at intermediate allele frequencies and had large estimated effects on production traits. Individuals on average carried less private deleterious missense alleles than expected compared to other predicted consequence types. A small subset of low-prevalence variants with intermediate allele frequencies and higher FST were detected as significantly associated to the production traits and explained small fractions of phenotypic variance (up to 3.2%). These associations were tagged by other more widespread variants, including intergenic variants. ConclusionsMost low-prevalence variants are kept at very low allele frequency and only a small subset contributed detectable fractions of phenotypic variance. Not accounting for low-prevalence variants is therefore unlikely to hinder across-breed analyses, in particular for genomic prediction of breeding values using reference populations of a different genetic background.

genomics↗

bioRxiv2021

Genetics of tibia bone properties of crossbred commercial laying hens in different housing systems

Osteoporosis and bone fractures are a severe problem for the welfare of laying hens, with genetics and environment, such as housing system, each making substantial contributions to bone strength. In this work, we performed genetic analyses of bone strength, bone mineral density and bone composition, as well as body weight, in 860 commercial crossbred laying hens from two different companies, kept in either furnished cages or floor pens. We compared bone traits between housing systems and crossbreds, and performed a genome-wide association study of bone properties and body weight. As expected, the two housing systems produced a large difference in bone strength, with layers housed in floor pens having stronger bones. These differences were accompanied by differences in bone geometry, mineralisation and chemical composition. Genome-scans either combining or independently analysing the two housing systems revealed no genome-wide significant loci for bone breaking strength. We detected three loci for body weight that were shared between the housing systems on chromosomes 4, 6 and 27 (either genome-wide significant or suggestive when the housing systems were analysed individually) and these coincide with associations for bone length. In summary, we found substantial differences in bone strength, content and composition between hens kept in floor pens and furnished cages that could be attributed to greater physical activity in pen housing. We found little evidence for large-effect loci for bone strength in commercial crossbred hens, consistent with a highly polygenic architecture for bone strength in the production environment. The lack of consistent genetic associations between housing systems in combination with the differences in bone phenotypes support gene-by-environment interactions with housing system.

genetics↗

bioRxiv2021

Profiling of open chromatin in developing pig (Sus scrofa) muscle to identify regulatory regions

There is very little information about how the genome is regulated in domestic pigs (Sus scrofa). This lack of knowledge hinders efforts to define and predict the effects of genetic variants in pig breeding programmes. In order to address this knowledge gap, we need to identify regulatory sequences in the pig genome starting with regions of open chromatin. We have optimised the Improved Protocol for the Assay for Transposase-Accessible Chromatin (Omni-ATAC-Seq) to profile regions of open chromatin in flash frozen pig muscle tissue samples. This protocol has allowed us to identify putative regulatory regions in semitendinosus muscle from 24 male piglets. We collected samples from the smallest, average, and largest sized male piglets from each litter through five developmental time points. The ATAC-Seq data were mapped to Sscrofa11.1 using Bowtie2 and Genrich was used for post-alignment peak-calling. Of the 4,661 ATAC-Seq peaks identified that represent regions of open chromatin, >50% were within 1 kb of known transcription start sites. Differential read count analysis revealed 377 ATAC-Seq defined genomic regions where chromatin accessibility differed significantly across developmental time points. We found regions of open chromatin associated with down regulation of genes involved in muscle development that were present in small sized foetal piglets but absent in large foetal piglets at day 90 of gestation. The dataset that we have generated provides: i) a resource for studies of genome regulation in pigs, and ii) contributes valuable functional annotation information to filter genetic variants for use in genomic selection in pig breeding programmes.

genomics↗

bioRxiv2020

Genetics of recombination rate variation in the pig

BackgroundIn this paper, we estimated recombination rate variation within the genome and between individuals in the pig using multiocus iterative peeling for 150,000 pigs across nine genotyped pedigrees. We used this to estimate the heritability of recombination and perform a genome-wide association study of recombination in the pig. ResultsOur results confirmed known features of the pig recombination landscape, including differences in chromosome length, and marked sex differences. The recombination landscape was repeatable between lines, but at the same time, the lines also showed differences in average genome-wide recombination rate. The heritability of genome-wide recombination was low but non-zero (on average 0.07 for females and 0.05 for males). We found three genomic regions associated with recombination rate, one of them harbouring the RNF212 gene, previously associated with recombination rate in several other species. ConclusionOur results from the pig agree with the picture of recombination rate variation in vertebrates, with low but nonzero heritability, and a major locus that is homologous to one detected in several other species. This work also highlights the utility of using large-scale livestock data to understand biological processes.

genetics↗

bioRxiv2019

Genomic data enables genetic evaluation using data recorded on LMIC smallholder dairy farms

BackgroundGenetic evaluation is a central component of a breeding program. In advanced economies, most genetic evaluations depend on large quantities of data that are recorded on commercial farms. Large herd sizes and widespread use of artificial insemination create strong genetic connectedness that enables the genetic and environmental effects of an individual animals phenotype to be accurately separated. In contrast to this, herds are neither large nor have strong genetic connectedness in smallholder dairy production systems of many low to middle-income countries (LMIC). This limits genetic evaluation, and furthermore, the pedigree information needed for traditional genetic evaluation is typically unavailable. Genomic information keeps track of shared haplotypes rather than shared relatives. This information could capture and strengthen genetic connectedness between herds and through this may enable genetic evaluations for LMIC smallholder dairy farms. The objective of this study was to use simulation to quantify the power of genomic information to enable genetic evaluation under such conditions.\n\nResultsThe results from this study show: (i) the genetic evaluation of phenotyped cows using genomic information had higher accuracy compared to pedigree information across all breeding designs; (ii) the genetic evaluation of phenotyped cows with genomic information and modelling herd as a random effect had higher or equal accuracy compared to modelling herd as a fixed effect; (iii) the genetic evaluation of phenotyped cows from breeding designs with strong genetic connectedness had higher accuracy compared to breeding designs with weaker genetic connectedness; (iv) genomic prediction of young bulls was possible using marker estimates from the genetic evaluations of their phenotyped dams. For example, the accuracy of genomic prediction of young bulls from an average herd size of 1 (=1.58) was 0.40 under a breeding design with 1,000 sires mated per generation and a training set of 8,000 phenotyped and genotyped cows.\n\nConclusionsThis study demonstrates the potential of genomic information to be an enabling technology in LMIC smallholder dairy production systems by facilitating genetic evaluations with in-situ records collected from farms with herd sizes of four cows or less. Across a range of breeding designs, genomic data enabled accurate genetic evaluation of phenotyped cows and genomic prediction of young bulls using data sets that contained small herds with weak genetic connections. The use of smallholder dairy data in genetic evaluations would enable the establishment of breeding programs to improve in-situ germplasm and, if required, would enable the importation of the most suitable external germplasm. This could be individually tailored for each target environment. Together this would increase the productivity, profitability and sustainability of LMIC smallholder dairy production systems. However, data collection, including genomic data, is expensive and business models will need to be carefully constructed so that the costs are sustainably offset.

genetics↗

bioRxiv2019

Intra-individual behavioural variability: a trait under genetic control

When individuals are measured more than once in the same context they do not behave in exactly the same way each time. The degree of predictability differs between individuals, with some individuals showing low levels of variation around their behavioural mean while others show high levels of variation. This intra-individual variation in behaviour has received much less attention than between-individual variance in behaviour and very little is known about the underlying mechanisms that affect this potentially large but understudied component of behavioural variation. In this study, we combine standardized behavioural tests to estimate intra-individual behavioural variance with a large-scale genetical genomics analysis to identify genes affecting intra-individual variability in an avian population. Our study shows that within-individual variance in behaviour has a direct genetic basis which is largely unique compared to the genetic architecture for the standard behavioural measures they are based on. We identify six candidate genes underlying variation in intra-individual behavioural variability many of which have previously been linked to behaviour and mental health. These findings demonstrate that within-individual variability in behavioural is a heritable trait in and of itself on which evolution can act.

evolutionary biology↗

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↗