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Biology subjects

Wiener, P.

Publications and source records attributed to Wiener, P..

4 recordsLinked to original sources

Pedigree-tracking improved population monitoring of recessive disease-causing alleles in pedigreed canine populations

Background Most monogenic inherited diseases in dogs are recessive, so their successful control depends on genetic testing to identify carriers of the disease-causing allele. However, currently used methods for disease allele monitoring in canine populations typically only consider part of the entire pedigree, since not all dogs have a known genotype through genetic test or "hereditary status" (a determinable genotype assigned to offspring based on known parental genotypes). Methods This study uses probabilistic inference with unknown parent groups (UPGs) in five Royal Kennel Club (RKC)-registered pedigrees to estimate genotype probabilities for all individuals using available genetic test results for two monogenic recessive diseases: primary lens luxation (PLL) and progressive retinal atrophy rod-cone degeneration 4 (PRA-rcd4). From these estimates, the population trends in disease-causing allele frequencies were estimated, and the inference quality was assessed through leave-one-out cross-validation and simulation. Results For dogs born after the introduction of the genetic test, the estimated disease-causing allele frequencies differed between methods. For instance, dogs born in 2020 reported up to 0.092 higher disease-causing allele frequencies with estimated genotype probabilities than those based on genetic tests and hereditary status alone. Inference performance varied across breeds, dependent on population allele frequency, with Pearson correlations between true (per genetic test result) and estimated allele dosages ranging from 0.47 to 0.67. The gene drop simulations indicated a tendency to underestimate disease-causing allele frequencies in retrospective estimates, particularly for dogs born before 1990. Impact Overall, by leveraging all available pedigree and genetic test data through probabilistic pedigree-based inference, disease-causing allele frequencies were monitored more comprehensively within the pedigreed population rather than relying on genetic test results or hereditary status alone. Such monitoring can inform responsible breeding decisions, helping to conserve genetic diversity whilst supporting improvements in future canine health and welfare.

genetics↗

Evaluating genotyping strategies for a small managed population with simulation

BackgroundCollecting genomic information is crucial to advance breeding for complex traits such as health, welfare, and behaviour in domesticated populations. For that purpose, different data collection scenarios can be envisioned based on the number of individuals, the number of markers, and the genotyping technology. This study developed a simulation framework, based on a service dog population, aiming to identify an optimal and cost-effective genotyping strategy that would support the implementation of genomic selection, investigation of the genetic architecture of traits of interest, and track loci of interest. MethodsWe simulated a population based on the existing pedigree, using the gene drop method in AlphaSimR. The existing pedigree was extended with additional progeny generations to evaluate the outcomes of different genotyping strategies in the future. We generated genotype data based on existing high-coverage whole-genome sequences (WGS) for the current breeding dogs and evaluated different scenarios for genotyping the progeny. The genotyping options considered SNP arrays of various densities and WGS callsets produced from different sequencing depths. We then phased and imputed the genotype data to high-coverage WGS using AlphaPeel. ResultsAll scenarios were compared based on individual imputation accuracy against the simulated true whole-genome genotype. Averaged over five generations of simulated progeny, low-pass sequencing (0.5 to 2X depth) achieved accuracies of 0.998 to 0.999. The accuracy of SNP array genotyping (25K to 710K markers) was lower, with means of 0.911 to 0.938. ConclusionsOur simulation was tailored to identify the most cost-effective and efficient strategy for downstream use in genomic selection and genetic research into traits and loci of interest. Low-pass sequencing outperformed SNP array genotyping in imputation accuracy of whole-genome genotypes as expected. Additionally, low-pass sequencing technology was the most affordable genotyping approach currently available for dogs. Thus, it appears to be the optimal choice for balancing the goals of regimented breeding programmes such as those that produce service dogs. This simulation framework could also be adapted to address other objectives for breeding organisations working with small populations.

genomics↗

The natural adaptation and human selection history of African sheep genomes

African sheep manifest diverse but distinct physio-anatomical traits which are the outcomes of natural- and human-driven selection. Here, we generated 34.8 million variants from 150 indigenous African sheep genomes sequenced at an average depth of [~]54x for 130 samples (Ethiopia, Libya) and [~]10x for 20 samples (Sudan), representing sheep from diverse environments, tail morphology and post-Neolithic introductions to Africa. Phylogenetic and model-based admixture analysis provided evidence of four genetic groups that correspond to altitudinal geographic origins and tail morphotypes. Comparative genomic analysis identified targets of selection spanning conserved haplotype structures overlapping genes and gene families relating to hypoxia responses, caudal vertebrae and tail skeleton length, ear morphology, and tail fat-depot structure. Our findings provide novel insights underpinning variation and response to human selection and environmental adaptation, and possible pleiotropic gene interactions in indigenous African sheep genomes, which guaranteed the successful establishment of the species on the continent.

genomics↗

A cattle graph genome incorporating global breed diversity

Despite only 8% of cattle being found in Europe, European breeds dominate current genetic resources. This adversely impacts cattle research in other important global cattle breeds. To mitigate this issue, we have generated the first assemblies of African breeds, which have been integrated with genomic data for 294 diverse cattle into the first graph genome that incorporates global cattle diversity. We illustrate how this more representative reference assembly contains an extra 116.1Mb (4.2%) of sequence absent from the current Hereford sequence and consequently inaccessible to current studies. We further demonstrate how using this graph genome increases read mapping rates, reduces allelic biases and improves the agreement of structural variant calling with independent optical mapping data. Consequently, we present an improved, more representative, reference assembly that will improve global cattle research.

genomics↗