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Multi-trait meta-analyses reveal 25 quantitative trait loci for economically important traits in Brown Swiss cattle.

ABSTRACT: BACKGROUND:Little is known about the genetic architecture of economically important traits in Brown Swiss cattle because only few genome-wide association studies (GWAS) have been carried out in this breed. Moreover, most GWAS have been performed for single traits, thus not providing detailed insights into potentially existing pleiotropic effects of trait-associated loci. RESULTS:To compile a comprehensive catalogue of large-effect quantitative trait loci (QTL) segregating in Brown Swiss cattle, we carried out association tests between partially imputed genotypes at 598,016 SNPs and daughter-derived phenotypes for more than 50 economically important traits, including milk production, growth and carcass quality, body conformation, reproduction and calving traits in 4578 artificial insemination bulls from two cohorts of Brown Swiss cattle (Austrian-German and Swiss populations). Across-cohort multi-trait meta-analyses of the results from the single-trait GWAS revealed 25 quantitative trait loci (QTL; P?

SUBMITTER: Fang ZH

PROVIDER: S-EPMC6724290 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Multi-trait meta-analyses reveal 25 quantitative trait loci for economically important traits in Brown Swiss cattle.

Fang Zih-Hua ZH Pausch Hubert H

BMC genomics 20190903 1

<h4>Background</h4>Little is known about the genetic architecture of economically important traits in Brown Swiss cattle because only few genome-wide association studies (GWAS) have been carried out in this breed. Moreover, most GWAS have been performed for single traits, thus not providing detailed insights into potentially existing pleiotropic effects of trait-associated loci.<h4>Results</h4>To compile a comprehensive catalogue of large-effect quantitative trait loci (QTL) segregating in Brown ...[more]

PMID: 31481029

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Project description:BackgroundA number of molecular marker linkage maps have been developed for melon (Cucumis melo L.) over the last two decades. However, these maps were constructed using different marker sets, thus, making comparative analysis among maps difficult. In order to solve this problem, a consensus genetic map in melon was constructed using primarily highly transferable anchor markers that have broad potential use for mapping, synteny, and comparative quantitative trait loci (QTL) analysis, increasing breeding effectiveness and efficiency via marker-assisted selection (MAS).ResultsUnder the framework of the International Cucurbit Genomics Initiative (ICuGI, http://www.icugi.org), an integrated genetic map has been constructed by merging data from eight independent mapping experiments using a genetically diverse array of parental lines. The consensus map spans 1150 cM across the 12 melon linkage groups and is composed of 1592 markers (640 SSRs, 330 SNPs, 252 AFLPs, 239 RFLPs, 89 RAPDs, 15 IMAs, 16 indels and 11 morphological traits) with a mean marker density of 0.72 cM/marker. One hundred and ninety-six of these markers (157 SSRs, 32 SNPs, 6 indels and 1 RAPD) were newly developed, mapped or provided by industry representatives as released markers, including 27 SNPs and 5 indels from genes involved in the organic acid metabolism and transport, and 58 EST-SSRs. Additionally, 85 of 822 SSR markers contributed by Syngenta Seeds were included in the integrated map. In addition, 370 QTL controlling 62 traits from 18 previously reported mapping experiments using genetically diverse parental genotypes were also integrated into the consensus map. Some QTL associated with economically important traits detected in separate studies mapped to similar genomic positions. For example, independently identified QTL controlling fruit shape were mapped on similar genomic positions, suggesting that such QTL are possibly responsible for the phenotypic variability observed for this trait in a broad array of melon germplasm.ConclusionsEven though relatively unsaturated genetic maps in a diverse set of melon market types have been published, the integrated saturated map presented herein should be considered the initial reference map for melon. Most of the mapped markers contained in the reference map are polymorphic in diverse collection of germplasm, and thus are potentially transferrable to a broad array of genetic experimentation (e.g., integration of physical and genetic maps, colinearity analysis, map-based gene cloning, epistasis dissection, and marker-assisted selection).

Project description:BACKGROUND: Modern watermelon (Citrullus lanatus L.) cultivars share a narrow genetic base due to many years of selection for desirable horticultural qualities. Wild subspecies within C. lanatus are important potential sources of novel alleles for watermelon breeding, but successful trait introgression into elite cultivars has had limited success. The application of marker assisted selection (MAS) in watermelon is yet to be realized, mainly due to the past lack of high quality genetic maps. Recently, a number of useful maps have become available, however these maps have few common markers, and were constructed using different marker sets, thus, making integration and comparative analysis among maps difficult. The objective of this research was to use single-nucleotide polymorphism (SNP) anchor markers to construct an integrated genetic map for C. lanatus. RESULTS: Under the framework of the high density genetic map, an integrated genetic map was constructed by merging data from four independent mapping experiments using a genetically diverse array of parental lines, which included three subspecies of watermelon. The 698 simple sequence repeat (SSR), 219 insertion-deletion (InDel), 36 structure variation (SV) and 386 SNP markers from the four maps were used to construct an integrated map. This integrated map contained 1339 markers, spanning 798 cM with an average marker interval of 0.6 cM. Fifty-eight previously reported quantitative trait loci (QTL) for 12 traits in these populations were also integrated into the map. In addition, new QTL identified for brix, fructose, glucose and sucrose were added. Some QTL associated with economically important traits detected in different genetic backgrounds mapped to similar genomic regions of the integrated map, suggesting that such QTL are responsible for the phenotypic variability observed in a broad array of watermelon germplasm. CONCLUSIONS: The integrated map described herein enhances the utility of genomic tools over previous watermelon genetic maps. A large proportion of the markers in the integrated map are SSRs, InDels and SNPs, which are easily transferable across laboratories. Moreover, the populations used to construct the integrated map include all three watermelon subspecies, making this integrated map useful for the selection of breeding traits, identification of QTL, MAS, analysis of germplasm and commercial hybrid seed detection.

Project description:BackgroundThe genome-wide association study (GWAS) is a useful approach to identify genes affecting economically important traits in dairy cattle. Here, we report the results from a GWAS based on high-density SNP genotype data and estimated breeding values for nine production, fertility, body conformation, udder health and workability traits in the Brown Swiss cattle population that is part of the international genomic evaluation program.ResultGWASs were performed using 50 k SNP chip data and deregressed estimated breeding values (DEBVs) for nine traits from between 2061 and 5043 bulls that were part of the international genomic evaluation program coordinated by Interbull Center. The nine traits were milk yield (MY), fat yield (FY), protein yield (PY), lactating cow's ability to recycle after calving (CRC), angularity (ANG), body depth (BDE), stature (STA), milk somatic cell score (SCS) and milk speed (MSP). Analyses were performed using a linear mixed model correcting for population confounding. A total of 74 SNPs were detected to be genome-wide significantly associated with one or several of the nine analyzed traits. The strongest signal was identified on chromosome 25 for milk production traits, stature and body depth. Other signals were on chromosome 11 for angularity, chromosome 24 for somatic cell score, and chromosome 6 for milking speed. Some signals overlapped with earlier reported QTL for similar traits in other cattle populations and were located close to interesting candidate genes worthy of further investigations.ConclusionsOur study shows that international genetic evaluation data is a useful resource for identifying genetic factors influencing complex traits in livestock. Several genome wide significant association signals could be identified in the Brown Swiss population, including a major signal on BTA25. Our findings report several associations and plausible candidate genes that deserve further exploration in other populations and molecular dissection to explore the potential economic impact and the genetic mechanisms underlying these production traits in cattle.

Project description:The detection of quantitative trait loci has accelerated with recent developments in genomics. The introduction of genomic selection in combination with sequencing efforts has made a large amount of genotypic data available. Functional traits such as fertility and calving traits have been included in routine genomic estimation of breeding values making large quantities of phenotypic data available for these traits. This data was used to investigate the genetics underlying fertility and calving traits and to identify potentially causative genomic regions and variants. We performed genome-wide association studies for 13 functional traits related to female fertility as well as for direct and maternal calving ease based on imputed whole-genome sequences. Deregressed breeding values from ~1000-5000 bulls per trait were used to test for associations with approximately 10 million imputed sequence SNPs.We identified a QTL on BTA17 associated with non-return rate at 56 days and with interval from first to last insemination. We found two significantly associated non-synonymous SNPs within this QTL region. Two more QTL for fertility traits were identified on BTA25 and 29. A single QTL was identified for maternal calving traits on BTA13 whereas three QTL on BTA19, 21 and 25 were identified for direct calving traits. The QTL on BTA19 co-localizes with the reported BH2 haplotype. The QTL on BTA25 is concordant for fertility and calving traits and co-localizes with a QTL previously reported to influence stature and related traits in Brown Swiss dairy cattle.The detection of QTL and their causative variants remains challenging. Combining comprehensive phenotypic data with imputed whole genome sequences seems promising. We present a QTL on BTA17 for female fertility in dairy cattle with two significantly associated non-synonymous SNPs, along with five additional QTL for fertility traits and calving traits. For all of these we fine mapped the regions and suggest candidate genes and candidate variants.

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Multi-trait meta-analyses reveal 25 quantitative trait loci for economically important traits in Brown Swiss cattle.

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Multi-trait meta-analyses reveal 25 quantitative trait loci for economically important traits in Brown Swiss cattle.

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