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Druet, T.

Publications and source records attributed to Druet, T..

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Updating the RZooRoH package for the analysis of inbreeding, identity-by-descent and relatedness from genomic data

The RZooRoH R package was implemented to characterize individual inbreeding levels. It identifies DNA segments inherited twice from a common ancestor through different paths, which are known as homozygous-by-descent (HBD) segments. The package accepts different data formats and provides multiple outputs: HBD segments, inbreeding rates and genome-wide and locus-specific HBD probabilities. In addition, it partitions HBD levels into multiple HBD classes. The length distribution varies between these classes, which therefore correspond to distinct groups of ancestors that can be traced back to different generations in the past. This provides information about mating structure and recent demographic history. The computational performance of the package has been substantially improved, enabling, for example, computing times to be reduced when working with whole-genome sequence data and more HBD classes to be fitted. It is now possible to fit one class per past generation, which facilitates interpretation of the results. Since we have previously demonstrated that the ZooRoH model can be used to characterize identity-by-descent (IBD) between haploid individuals or phased haplotypes, this option has been included in the new package version. Estimating kinship by characterizing IBD levels between the four possible pairs of haplotypes from two individuals is another feature we added to the package. Finally, new options allow models to be refined, for instance by defining HBD classes as intervals or constant inbreeding rates for neighboring classes. Overall, the new version of the package offers improved computational efficiency and interpretability when characterizing inbreeding, IBD and relatedness levels.

genomics↗

Genomic prediction of individual inbreeding levels for the management of genetic diversity in populations with small effective size

In populations of small effective size (Ne), such as those in conservation programs, companion animals or livestock species, management of diversity and inbreeding is essential. Homozygosity-by-descent (HBD) segments provide relevant information in that context, as they allow efficient estimation of the inbreeding coefficient, provide locus-specific information and their length is informative about the "age" of inbreeding. Therefore, our objective was to evaluate tools for predicting HBD in future offspring based on parental genotypes, a problem equivalent to identifying segments identical-by-descent (IBD) among the four parental chromosomes. In total, we reviewed and evaluated 16 approaches using simulated and real data with small Ne. The methods included model-based approaches, mostly hidden Markov models (HMMs), which considered up to 15 IBD configurations among the four parental chromosomes, as well as more computationally efficient rule-based approaches. The accuracy of the methods was then evaluated, including with low-density marker panels, genotyping-by-sequencing data and small groups of individuals, typical features in such populations. Two HMMs performed consistently well, while two rule-based approaches proved efficient for genome-wide predictions. The model-based approaches were particularly efficient when information was reduced (low marker density, locus-specific estimation). Methods using phased data proved to be more efficient, while some approaches relying on unphased genotype data proved to be sensitive to the allele frequencies used. In some settings, pedigree information was competitive in predicting recent inbreeding levels. Finally, we showed that our evaluation is also informative about the accuracy of the methods for estimating relatedness and identifying IBD segments between pairs of individuals.

genomics↗

Genomic reconstruction of the successful establishment of a feralized bovine population on the subantarctic island of Amsterdam

The feral cattle of the subantarctic island of Amsterdam provide an outstanding case study of a large mammalian population that was established by a handful of founders and thrived within a few generations in a seemingly inhospitable environment. Here, we investigated the genetic history and composition of this population using genotyping and sequencing data. Our inference showed an intense but brief founding bottleneck around the late 19th century and revealed contributions from European taurine and Indian Ocean zebu in the founder ancestry. Comparative analysis of whole genome sequences further revealed a moderate reduction in genetic diversity despite high levels of inbreeding. The brief and intense bottleneck was associated with high levels of drift, a flattening of the site frequency spectrum and a slight relaxation of purifying selection on mildly deleterious variants. However, we did not observe any significant purge of highly deleterious variants. Interestingly, the populations success in the harsh environment can be attributed to pre-adaptation from their European taurine ancestry, suggesting no strong bioclimatic challenge, and also contradicting evidence for insular dwarfism. Genome scan for footprints of selection uncovered a majority of candidate genes related to nervous system function, likely reflecting rapid feralization driven by behavioral changes and complex social restructuring. This unprecedented case study provides valuable insights into rapid population establishment, feralization, and genetic adaptation in challenging environments. It highlights the importance of preserving the unique genetic legacies of feral populations and raises ethical questions in the eyes of conservation efforts.

evolutionary biology↗

Sequenced-based GWAS for linear classification traits in Belgian Blue beef cattle reveals new coding variants in genes regulating body size in mammals

Cohorts of individuals that have been genotyped and phenotyped for genomic selection programs offer the opportunity to better understand genetic variation associated with complex traits. Here, we perform an association study for traits related to body size and muscular development in intensively selected beef cattle. We leveraged multiple trait information to refine and interpret the significant associations. After a multiple-step genotype imputation to the sequence-level for 14,762 Belgian Blue beef (BBB) cattle cows, we performed a GWAS for 11 traits related to muscular development and body size. The 37 identified genome-wide significant QTL could be condensed in 11 unique QTL regions based on their position. There was evidence for pleiotropic effects in most of these regions (e.g., correlated association signals, overlap between credible sets of candidate variants - CSCV). We consequently applied a multiple-trait approach to combine information from different traits to refine the CSCV. In several QTL regions, we identified strong candidate genes known to be related to growth and height in other species such as LCORL-NCAPG or CCND2. For some of these genes, relevant candidate variants were identified in the CSCV, including three new missense variants in EZH2, PAPPA2 and ADAM12, possibly two additional coding variants in LCORL, and candidate regulatory variants linked to CCND2 and ARMC12. Strikingly, four other QTL regions were related to five (recessive) deleterious coding variants previously identified. Heterozygotes for several of these mutations have favorable effects for muscular development traits. Our study further supports that a set of common genes controls body size across mammalian species. In particular, we added new genes to the list of those associated with height in both human and cattle. We also identified new strong candidate causing variants in some of those genes, strengthening the evidence of the causality of these genes. Several breed-specific recessive deleterious variants were identified in our QTL regions, probably as a result of the extreme selection for muscular development in BBB cattle.

genetics↗

Benchmarking phasing software with a whole-genome sequenced cattle pedigree

BackgroundAccurate haplotype reconstruction is required in many applications in quantitative and population genomics. Different phasing methods are available but their accuracy must be evaluated for samples with different properties (population structure, marker density, etc.). We herein took advantage of whole-genome sequence data available for a Holstein cattle pedigree containing 264 individuals, including 98 trios, to evaluate several population-based phasing methods. This data represents a typical example of a livestock population, with low effective population size, high levels of relatedness and long-range linkage disequilibrium. ResultsAfter stringent filtering of our sequence data, we evaluated several population-based phasing programs including one or more versions of AlphaPhase, ShapeIT, Beagle, Eagle and FImpute. To that end we used 98 individuals having both parents sequenced for validation. Their haplotypes reconstructed based on Mendelian segregation rules were considered the gold standard to assess the performance of population-based methods in two scenarios. In the first one, only these 98 individuals were phased, while in the second one, all the 264 sequenced individuals were phased simultaneously, ignoring the pedigree relationships. We assessed phasing accuracy based on switch error counts (SEC) and rates (SER), lengths of correctly phased haplotypes and pairwise SNP phasing accuracies (the probability that a pair of SNPs is correctly phased as a function of their distance). For most evaluated metrics or scenarios, the best software was either ShapeIT4.1 or Beagle5.2, both methods resulting in particularly high phasing accuracies. For instance, ShapeIT4.1 achieved a median SEC of 50 per individual and a mean haplotype block length of 24.1 Mb in the second scenario. These statistics are remarkable since the methods were evaluated with a map of 8,400,000 SNPs, and this corresponds to only one switch error every 40,000 phased informative markers. When more relatives were included in the data, FImpute3.0 reconstructed extremely long segments without errors. ConclusionsWe report extremely high phasing accuracies in a typical livestock sample of 100 sequenced individuals. ShapeIT4.1 and Beagle5.2 proved to be the most accurate, particularly for phasing long segments. Nevertheless, most tools achieved high accuracy at short distances and would be suitable for applications requiring only local haplotypes.

genomics↗

The genetic history of Mayotte and Madagascar cattle breeds mirrors the complex pattern of human exchanges in Western Indian Ocean

Despite their central economic and cultural role, the origin of cattle populations living in Indian Ocean islands still remains poorly documented. Here, we unravel the demographic and adaptive histories of the extant Zebus from the Mayotte and Madagascar islands using high-density SNP genotyping data. We found that these populations are very closely related and both display a predominant indicine ancestry. They diverged in the 16th century at the arrival of European people who transformed the trade network in the area. Their common ancestral cattle population originates from an admixture between an admixed African zebu population and an Indian zebu that occurred around the 12th century at the time of the earliest contacts between human African populations of the Swahili corridor and Austronesian people from Southeast Asia in Comoros and Madagascar. A steep increase of the estimated population sizes from the beginning of the 16th to the 17th century coincides with the expansion of the cattle trade. By carrying out genome scans for recent selection in the two cattle populations from Mayotte and Madagascar, we identified sets of candidate genes involved in biological functions (cancer, skin structure and UV-protection, nervous system and behavior, organ development, metabolism and immune response) broadly representative of the physiological adaptation to tropical conditions. Overall, the origin of the cattle populations from Western Indian Ocean islands mirrors the complex history of human migrations and trade in this area.

evolutionary biology↗

An improved hidden Markov model for the characterization of homozygous-by-descent segments in individual genomes

Inbreeding results from the mating of related individuals and has negative consequences because it brings together deleterious variants in one individual. Genomic estimates of the inbreeding coefficients are preferred to pedigree-based estimators as they measure the realized inbreeding levels and they are more robust to pedigree errors. Several methods identifying homozygous-by-descent (HBD) segments with hidden Markov models (HMM) have been recently developed and are particularly valuable when the information is degraded or heterogeneous (e.g., low-fold sequencing, low marker density, heterogeneous genotype quality or variable marker spacing). We previously developed a multiple HBD class HMM where HBD segments are classified in different groups based on their length (e.g., recent versus old HBD segments) but we recently observed that for high inbreeding levels with many HBD segments, the estimated contributions might be biased towards more recent classes (i.e., associated with large HBD segments) although the overall estimated level of inbreeding remained unbiased. We herein propose a new model in which the HBD classification is modeled in successive nested levels with decreasing expected HBD segment lengths, the underlying exponential rates being directly related to the number of generations to the common ancestor. The non-HBD classes are now modeled as a mixture of HBD segments from later generations and shorter non-HBD segments (i.e., both with higher rates). The new model has improved statistical properties and performs better on simulated data compared to our previous version. We also show that the parameters of the model are easier to interpret and that the model is more robust to the choice of the number of classes. Overall, the new model results in an improved partitioning of inbreeding in different HBD classes and should be preferred.

genetics↗

A 12 kb multi-allelic copy number variation encompassing a GC gene enhancer is associated with mastitis resistance in dairy cattle

Clinical mastitis (CM) is an inflammatory disease occurring in the mammary glands of lactating cows. CM is under genetic control, and a prominent CM resistance QTL located on chromosome 6 was reported in various dairy cattle breeds. Nevertheless, the biological mechanism underpinning this QTL has been lacking. Herein, we mapped, fine-mapped, and discovered the putative causal variant underlying this CM resistance QTL in the Dutch dairy cattle population. We identified a ~12 kb multi-allelic copy number variant (CNV), that is in perfect linkage disequilibrium with a GWAS lead SNP, as a promising candidate variant. By implementing a genome-wide association study (GWAS) and through expression QTL mapping, we showed that the group-specific component gene (GC), a gene encoding a vitamin D binding protein, is an excellent candidate causal gene for the QTL. The multiplicated alleles are associated with increased GC expression and low CM resistance. Ample evidence from functional genomics data supports the presence of an enhancer within this CNV, which would exert cis-regulatory effect on GC. We observed that strong positive selection swept the region near the CNV, and haplotypes associated with the multiplicated allele were strongly selected for. Moreover, the multiplicated allele showed pleiotropic effects for increased milk yield and reduced fertility, hinting that a shared underlying biology for these effects may revolve around the vitamin D pathway. These findings together suggest a putative causal variant of a CM resistance QTL, where a cis-regulatory element located within a CNV can alter gene expression and affect multiple economically important traits. Author summaryClinical mastitis (CM) is an inflammatory disease that negatively influences dairy production and compromises animal welfare. Although one major genetic locus for CM resistance was mapped on bovine chromosome 6, a mechanistic description of this association has been lacking. Herein, we report a 12-kb multiallelic copy number variant (CNV), encompassing a strong enhancer for group-specific component gene (GC), as a likely causal variant for this locus. This CNV is associated with high GC expression and low CM resistance. We speculate that upregulation of GC leads to a large amount of vitamin D binding protein, which in turn, reduces biologically available vitamin D, resulting in vitamin D deficiency and low CM resistance. Despite the negative effect on CM resistance, the CNV contributes to increased milk production, hinting at balancing selection. Our results highlight how multiplication of a regulatory element can shape economically important traits in dairy cattle, both in favourable and unfavourable directions.

genomics↗

Age-based partitioning of individual genomic inbreeding using an exponential mixture model

Inbreeding results from the mating of related individuals and has negative consequence because it brings together deleterious variants in one individual. Inbreeding is associated with recessive diseases and reduced production or fitness. In general, inbreeding is estimated with respect to a base population that needs to be defined. Ancestors in generations anterior to the base population are considered unrelated. We herein propose a model that estimates inbreeding relative to multiple age-based classes. Each inbreeding distribution is associated to a different time in the past: recent inbreeding generating longer homozygous stretches than more ancient. Our model is a mixture of exponential distribution implemented in a hidden Markov model framework that uses marker allele frequencies, genetic distances, genotyping error rates and the sequences of observed genotypes. Based on simulations studies, we show that the inbreeding coefficients and the age of inbreeding are correctly estimated. Mean absolute errors of estimators are low, the efficiency depending on the available information. When several inbreeding classes are simulated, the model captures them if their ages are sufficiently different. Genotyping errors or low-fold sequencing data are easily accommodated in the hidden Markov model framework. Application to real data sets illustrate that the method can reveal recent different demographic histories among populations, some of them presenting very recent bottlenecks or founder effects. The method also clearly identifies individuals resulting from extreme consanguineous matings.

genetics↗