A Multiple-SNP Approach for Genome-Wide Association Study of Milk Production Traits in Chinese Holstein Cattle

Fang, Ming; Fu, Weixuan; Jiang, Dan; Zhang, Qin; Sun, Dongxiao; Ding, Xiangdong; Liu, Jianfeng

doi:10.1371/journal.pone.0099544

Cited by 27 publications

(23 citation statements)

References 17 publications

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“…The protein encoded by SLC40A1 is a cell membrane protein that may be involved in iron export from duodenal epithelial cells, and defects in this gene result in hemochromatosis (Geer et al, 2010). In cattle, SLC40A1 is suggested to be related to milk yield, but no fertility-related function is known (Fang et al, 2014). The gene GULP1 encodes an adapter protein necessary for the engulfment of apoptotic cells by phagocytes, but no fertility-related function is known for this gene.…”

Section: Fine-mapping Btamentioning

confidence: 99%

Genome-wide association study for endocrine fertility traits using single nucleotide polymorphism arrays and sequence variants in dairy cattle

Tenghe

Bouwman

Berglund

et al. 2016

Journal of Dairy Science

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Endocrine fertility traits, which are defined from progesterone concentration levels in milk, are interesting indicators of dairy cow fertility because they more directly reflect the cows own reproductive physiology than classical fertility traits, which are more biased by farm management decisions. The aim of this study was to detect quantitative trait loci (QTL) for 7 endocrine fertility traits in dairy cows by performing a genome-wide association study with 85k single nucleotide polymorphisms (SNP), and then fine-map targeted QTL regions, using imputed sequence variants. Two classical fertility traits were also analyzed for QTL with 85k SNP. The association between a SNP and a phenotype was assessed by single-locus regression for each SNP, using a linear mixed model that included a random polygenic effect. A total of 2,447 Holstein Friesian cows with 5,339 lactations with both phenotypes and genotypes were used for association analysis. Heritability estimates ranged from 0.09 to 0.15 for endocrine fertility traits and 0.03 to 0.10 for classical fertility traits. The genome-wide association study identified 17 QTL regions for endocrine fertility traits on Bos taurus autosomes (BTA) 2, 3, 8, 12, 15, 17, 23, and 25. The highest number (5) of QTL regions from the genome-wide association study was identified for the endocrine trait "proportion of samples with luteal activity." Overlapping QTL regions were found between endocrine traits on BTA 2, 3, and 17. For the classical trait calving to first service, 3 QTL regions were identified on BTA 3, 15, and 23, and an overlapping region was identified on BTA 23 with endocrine traits. Fine-mapping target regions for the endocrine traits on BTA 2 and 3 using imputed sequence variants confirmed the QTL from the genome-wide association study, and identified several associated variants that can contribute to an index of markers for genetic improvement of fertility. Several potential candidate genes underlying endocrine fertility traits were also identified in the target regions and are discussed. However, due to high linkage disequilibrium, it was not possible to specify genes or polymorphisms as causal factors for any of the regions.

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Section: Fine-mapping Btamentioning

confidence: 99%

Genome-wide association study for endocrine fertility traits using single nucleotide polymorphism arrays and sequence variants in dairy cattle

Tenghe

Bouwman

Berglund

et al. 2016

Journal of Dairy Science

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“…The dimensions of the model are first reduced by selecting a predetermined number of interactions based on their marginal correlation with the trait value [sure independence screening by Fan and Lv (2008)]. Similar strategies have been applied for main effect QTL detection in association studies Fang et al 2014). Originally, the sure independence screening is performed by multiplying a p 3 n matrix of genotypes by an n-vector of trait values and selecting d largest values of a p-vector of correlation coefficients, leading to computational complexity OðnpÞ.…”

Section: The Multilocus Methodsmentioning

confidence: 99%

An Efficient Genome-Wide Multilocus Epistasis Search

Kärkkäinen

Sillanpää

2015

Genetics

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There has been a continuing interest in approaches that analyze pairwise locus-by-locus (epistasis) interactions using multilocus association models in genome-wide data sets. In this paper, we suggest an approach that uses sure independence screening to first lower the dimension of the problem by considering the marginal importance of each interaction term within the huge loop. Subsequent multilocus association steps are executed using an extended Bayesian least absolute shrinkage and selection operator (LASSO) model and fast generalized expectation-maximization estimation algorithms. The potential of this approach is illustrated and compared with PLINK software using data examples where phenotypes have been simulated conditionally on marker data from the Quantitative Trait Loci Mapping and Marker Assisted Selection (QTLMAS) Workshop 2008 and real pig data sets.

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“…) and fat percentage (Fang et al . ) in milk. These results can be viewed as indirect evidence in support of our hypothesis that KLHL1 may play regulatory role in milk production as well.…”

Section: Identification Of Genome‐wide Significant Snps That Are Assomentioning

confidence: 99%

A genome‐wide association study suggests new candidate genes for milk production traits in Chinese Holstein cattle

Yue

Zhao

et al. 2017

Animal Genetics

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A genome-wide association study (GWAS) was conducted on 15 milk production traits in Chinese Holstein. The experimental population consisted of 445 cattle, each genotyped by the GGP (GeneSeek genomic profiling)-BovineLD V3 SNP chip, which had 26 151 public SNPs in its manifest file. After data cleaning, 20 326 SNPs were retained for the GWAS. The phenotypes were estimated breeding values of traits, provided by a public dairy herd improvement program center that had been collected once a month for 3 years. Two statistical models, a fixed-effect linear regression model and a mixed-effect linear model, were used to estimate the association effects of SNPs on each of the phenotypes. Genome-wide significant and suggestive thresholds were set at 2.46E-06 and 4.95E-05 respectively. The two statistical models concurrently identified two genome-wide significant (P < 0.05) SNPs on milk production traits in this Chinese Holstein population. The positional candidate genes, which were the ones closest to these two identified SNPs, were EEF2K (eukaryotic elongation factor 2 kinase) and KLHL1 (kelch like family member 1). These two genes could serve as new candidate genes for milk yield and lactation persistence, yet their roles need to be verified in further function studies.

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A Multiple-SNP Approach for Genome-Wide Association Study of Milk Production Traits in Chinese Holstein Cattle

Cited by 27 publications

References 17 publications

Genome-wide association study for endocrine fertility traits using single nucleotide polymorphism arrays and sequence variants in dairy cattle

Genome-wide association study for endocrine fertility traits using single nucleotide polymorphism arrays and sequence variants in dairy cattle

An Efficient Genome-Wide Multilocus Epistasis Search

A genome‐wide association study suggests new candidate genes for milk production traits in Chinese Holstein cattle

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