A robust linkage map of the porcine autosomes based on gene-associated SNPs

<p>Abstract</p> <p>Background</p> <p>Genetic linkage maps are necessary for mapping of mendelian traits and quantitative trait loci (QTLs). To identify the actual genes, which control these traits, a map based on gene-associated single nucleotide polymorphism (SNP) markers is highly valuable. In this study, the SNPs were genotyped in a large family material comprising more than 5,000 piglets derived from 12 Duroc boars crossed with 236 Danish Landrace/Danish Large White sows. The SNPs were identified in sequence alignments of 4,600 different amplicons obtained from the 12 boars and containing coding regions of genes derived from expressed sequence tags (ESTs) and genomic shotgun sequences.</p> <p>Results</p> <p>Linkage maps of all 18 porcine autosomes were constructed based on 456 gene-associated and six porcine EST-based SNPs. The total length of the averaged-sex whole porcine autosome was estimated to 1,711.8 cM resulting in an average SNP spacing of 3.94 cM. The female and male maps were estimated to 2,336.1 and 1,441.5 cM, respectively. The gene order was validated through comparisons to the cytogenetic and/or physical location of 203 genes, linkage to evenly spaced microsatellite markers as well as previously reported conserved synteny. A total of 330 previously unmapped genes and ESTs were mapped to the porcine autosome while ten genes were mapped to unexpected locations.</p> <p>Conclusion</p> <p>The linkage map presented here shows high accuracy in gene order. The pedigree family network as well as the large amount of meiotic events provide good reliability and make this map suitable for QTL and association studies. In addition, the linkage to the RH-map of microsatellites makes it suitable for comparison to other QTL studies.</p

Population Structure and Diversity in European Honey Bees (Apis mellifera L.)-An Empirical Comparison of Pool and Individual Whole-Genome Sequencing

Background: Whole-genome sequencing has become routine for population genetic studies. Sequencing of individuals provides maximal data but is rather expensive and fewer samples can be studied. In contrast, sequencing a pool of samples (pool-seq) can provide sufficient data, while presenting less of an economic challenge. Few studies have compared the two approaches to infer population genetic structure and diversity in real datasets. Here, we apply individual sequencing (ind-seq) and pool-seq to the study of Western honey bees (Apis mellifera). Methods: We collected honey bee workers that belonged to 14 populations, including 13 subspecies, totaling 1347 colonies, who were individually (139 individuals) and pool-sequenced (14 pools). We compared allele frequencies, genetic diversity estimates, and population structure as inferred by the two approaches. Results: Pool-seq and ind-seq revealed near identical population structure and genetic diversities, albeit at different costs. While pool-seq provides genome-wide polymorphism data at considerably lower costs, ind-seq can provide additional information, including the identification of population substructures, hybridization, or individual outliers. Conclusions: If costs are not the limiting factor, we recommend using ind-seq, as population genetic structure can be inferred similarly well, with the advantage gained from individual genetic information. Not least, it also significantly reduces the effort required for the collection of numerous samples and their further processing in the laboratory.This work was supported by National Natural Science Foundation of China (Grant No. 31902219) and Modern Agro-industry Technology Research System (Grant No. CARDS-45-KXJ1). The SmartBees project was funded by the European Commission under its FP7 KBBE programme (2013.1.3-02, SmartBees Grant Agreement number 613960). MP and J.L were supported by the Applied Genomics and Bioinformatics research group (IT1233-19) funded by the Basque Government grant IT1233-19. Additionally, JL was funded by the grant PRE_2017_2_0169 from the Department of Education of the Basque Government

A frameshift mutation in ARMC3 is associated with a tail stump sperm defect in Swedish Red (Bos taurus) cattle

Background: Artificial insemination is widely used in many cattle breeding programs. Semen samples of breeding bulls are collected and closely examined immediately after collection at artificial insemination centers. Only ejaculates without anomalous findings are retained for artificial insemination. Although morphological aberrations of the spermatozoa are a frequent reason for discarding ejaculates, the genetic determinants underlying poor semen quality are scarcely understood. Results: A tail stump sperm defect was observed in three bulls of the Swedish Red cattle breed. The spermatozoa of affected bulls were immotile because of severely disorganized tails indicating disturbed spermatogenesis. We genotyped three affected bulls and 18 unaffected male half-sibs at 46,035 SNPs and performed homozygosity mapping to map the fertility disorder to an 8.42 Mb interval on bovine chromosome 13. The analysis of whole-genome re-sequencing data of an affected bull and 300 unaffected animals from eleven cattle breeds other than Swedish Red revealed a 1 bp deletion (Chr13: 24,301,425 bp, ss1815612719) in the eleventh exon of the armadillo repeat containing 3-encoding gene (ARMC3) that was compatible with the supposed recessive mode of inheritance. The deletion is expected to alter the reading frame and to induce premature translation termination (p.A451fs26). The mutated protein is shortened by 401 amino acids (46 %) and lacks domains that are likely essential for normal protein function. Conclusions: We report the phenotypic and genetic characterization of a sterilizing tail stump sperm defect in the Swedish Red cattle breed. Exploiting high-density genotypes and massive re-sequencing data enabled us to identify the most likely causal mutation for the fertility disorder in bovine ARMC3. Our results provide the basis for monitoring the mutated variant in the Swedish Red cattle population and for the early identification of infertile animals.Peer reviewe

Authoritative subspecies diagnosis tool for European honey bees based on ancestryinformative SNPs

Background With numerous endemic subspecies representing four of its five evolutionary lineages, Europe holds a large fraction of Apis mellifera genetic diversity. This diversity and the natural distribution range have been altered by anthropogenic factors. The conservation of this natural heritage relies on the availability of accurate tools for subspecies diagnosis. Based on pool-sequence data from 2145 worker bees representing 22 populations sampled across Europe, we employed two highly discriminative approaches (PCA and F-ST) to select the most informative SNPs for ancestry inference. Results Using a supervised machine learning (ML) approach and a set of 3896 genotyped individuals, we could show that the 4094 selected single nucleotide polymorphisms (SNPs) provide an accurate prediction of ancestry inference in European honey bees. The best ML model was Linear Support Vector Classifier (Linear SVC) which correctly assigned most individuals to one of the 14 subspecies or different genetic origins with a mean accuracy of 96.2% +/- 0.8 SD. A total of 3.8% of test individuals were misclassified, most probably due to limited differentiation between the subspecies caused by close geographical proximity, or human interference of genetic integrity of reference subspecies, or a combination thereof. Conclusions The diagnostic tool presented here will contribute to a sustainable conservation and support breeding activities in order to preserve the genetic heritage of European honey bees.The SmartBees project was funded by the European Commission under its FP7 KBBE programme (2013.1.3-02, SmartBees Grant Agreement number 613960) https://ec.europa.eu/research/fp7.MP was supported by a Basque Government grant (IT1233-19). The funders provided the financial support to the research, but had no role in the design of the study, analysis, interpretations of data and in writing the manuscript