An understanding of the genetic control of porcine female reproductive performance would offer the opportunity to utilize natural variation and improve selective breeding programs through marker-assisted selection. The Chinese Meishan is one of the most prolific pig breeds known, farrowing three to five more viable piglets per litter than the European Large White breed. This difference in prolificacy is attributed to the Meishan's superior prenatal survival levels. The present study utilized a three-generation cross in which the founder grandparental animals were purebred Meishan and Large White pigs in a scan for quantitative trait loci (QTL) on porcine chromosome 8 (SSC8) associated with reproductive performance. Reproductive traits, including number of corpora lutea (ovulation rate), teat number, litter size, and prenatal survival, were recorded for as many as 220 F2 females. Putative QTL for the related traits of litter size and prenatal survival were identified at the distal end of the long arm of SSC8. A physiological candidate gene, SPP1, was found to lie within the 95% confidence interval of these QTL. A suggestive QTL for teat number was revealed on the short arm of SSC8. The present study demonstrates, to our knowledge, the first independent confirmation of QTL for fecundity on SSC8, and these QTL regions provide a crucial starting point in the search for the causal genetic variants.
Background: Over the last decade, several studies have identified quantitative trait loci (QTL) affecting variation of immune related traits in mammals. Recent studies in humans and mice suggest that part of this variation may be caused by polymorphisms in genes involved in Toll-like receptor (TLR) signalling. In this project, we used a comparative approach to investigate the importance of TLR-related genes in comparison with other immunologically relevant genes for resistance traits in five species by associating their genomic location with previously published immune-related QTL regions.
SummaryGenome‐wide association (GWA) studies based on GBLUP models are a common practice in animal breeding. However, effect sizes of GWA tests are small, requiring larger sample sizes to enhance power of detection of rare variants. Because of difficulties in increasing sample size in animal populations, one alternative is to implement a meta‐analysis (MA), combining information and results from independent GWA studies. Although this methodology has been used widely in human genetics, implementation in animal breeding has been limited. Thus, we present methods to implement a MA of GWA, describing the proper approach to compute weights derived from multiple genomic evaluations based on animal‐centric GBLUP models. Application to real datasets shows that MA increases power of detection of associations in comparison with population‐level GWA, allowing for population structure and heterogeneity of variance components across populations to be accounted for. Another advantage of MA is that it does not require access to genotype data that is required for a joint analysis. Scripts related to the implementation of this approach, which consider the strength of association as well as the sign, are distributed and thus account for heterogeneity in association phase between QTL and SNPs. Thus, MA of GWA is an attractive alternative to summarizing results from multiple genomic studies, avoiding restrictions with genotype data sharing, definition of fixed effects and different scales of measurement of evaluated traits.
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