Haplotype-based genome-wide association study identifies loci and candidate genes for milk yield in Holsteins

Chen, Zhenliang; Yao, Yunqiu; Ma, Peipei; Wang, Qishan; Pan, Yuchun

doi:10.1371/journal.pone.0192695

Cited by 41 publications

(37 citation statements)

References 26 publications

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“…As suggested by Glusman et al [ 36 ], haplotypes are more specific than less complex variants, such as single nucleotide variants (SNP variants). A haplotype-based empirical model inherited from an SNP-based method was followed as suggested by Chen et al [ 37 ]. We identified 48 single nucleotide polymorphisms (SNPs) present in the casein complex of 159 unrelated individuals of diverse ancestry, which were organized the SNPs into 86 different haplotypes.…”

Section: Methodsmentioning

confidence: 99%

Bayesian Analysis of the Association between Casein Complex Haplotype Variants and Milk Yield, Composition, and Curve Shape Parameters in Murciano-Granadina Goats

Inostroza

González

Landi

et al. 2020

Animals

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Considering casein haplotype variants rather than SNPs may maximize the understanding of heritable mechanisms and their implication on the expression of functional traits related to milk production. Effects of casein complex haplotypes on milk yield, milk composition, and curve shape parameters were used using a Bayesian inference for ANOVA. We identified 48 single nucleotide polymorphisms (SNPs) present in the casein complex of 159 unrelated individuals of diverse ancestry, which were organized into 86 haplotypes. The Ali and Schaeffer model was chosen as the best fitting model for milk yield (Kg), protein, fat, dry matter, and lactose (%), while parabolic yield-density was chosen as the best fitting model for somatic cells count (SCC × 103 sc/mL). Peak and persistence for all traits were computed respectively. Statistically significant differences (p < 0.05) were found for milk yield and components. However, no significant difference was found for any curve shape parameter except for protein percentage peak. Those haplotypes for which higher milk yields were reported were the ones that had higher percentages for protein, fat, dry matter, and lactose, while the opposite trend was described by somatic cells counts. Conclusively, casein complex haplotypes can be considered in selection strategies for economically important traits in dairy goats.

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Section: Methodsmentioning

confidence: 99%

Bayesian Analysis of the Association between Casein Complex Haplotype Variants and Milk Yield, Composition, and Curve Shape Parameters in Murciano-Granadina Goats

Inostroza

González

Landi

et al. 2020

Animals

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show abstract

“…The dataset used for this work was obtained from Chen's work (Chen et al, 2018). Data is publicly available from https://doi.org/10.5061/dryad.cs133.…”

Section: Samples Datasetmentioning

confidence: 99%

“…In order to implement a classification of cows using genome-wide genotypic information, we selected the EBV for the 305-days' average milk yield as the phenotype of interest. This value was already included in the data from Chen's work (Chen et al, 2018). Its original values ranged from -8.576 to 16.838.…”

Section: Samples Categorization By Milk Productionmentioning

confidence: 99%

Research Article Genome-wide classification of dairy cows using decision trees and artificial neural network algorithms

Rodríguez¹,

Waissman²,

Mahadevan³

et al. 2019

Genet. Mol. Res.

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We compared two techniques of machine learning for the identification of cows that will be good producers of milk based on their genome-wide information. Data from a genome-wide genotyping panel, consisting of 164312 single nucleotide polymorphism markers (SNPs), within the 29 autosomal chromosomes, from 1092 Holstein cow samples were used for this study. Sample cows were divided as high-milk producers and lowmilk producers based on their estimated breeding value of the 305 day average milk yield. Seven data sets were generated that grouped chromosomes with the highest number of SNPs related to milk production for prediction. Decision trees and artificial neural network algorithms were trained and tested, and the performance of prediction was computed. The mean prediction accuracy obtained with the decision tree algorithm was 92.44%, with a maximum of 94.5%, while the mean prediction accuracy obtained with the artificial neural network algorithm was 82.19%, with a maximum of 87.3%. Also, the decision tree algorithm permitted the identification ©FUNPEC-RP www.funpecrp.com.br Genetics and Molecular Research 18 (4): gmr18407 E. Rodríguez et al. 2 of the most dominant single nucleotide polymorphism for prediction, which is situated within a milk-related quantitative trait locus in chromosome 14. Finally, our results add new evidence to support that machine learning algorithms may be used for managing genomewide SNP markers, for implementing classification and prediction tools in the cattle industry.

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“…(2011) developed an efficient approach to accelerate the phasing process and reduce the potential bias generated by unrealistic assumptions in the phasing process. Recently, haplotyped-based GWASs have been conducted and have obtained some useful results ( Wu et al., 2014 , Sato et al., 2016 , Chen et al., 2018 ). In chickens, GWAS identified genetic variation that has been associated with disease ( Raeesi et al., 2017 ), carcass ( Huang et al., 2018 ), growth ( Guo et al., 2017 , Pértille et al., 2017 ), and meat quantitative traits ( Moreira et al., 2018 ).…”

Section: Introductionmentioning

confidence: 99%

Haplotype-based genome-wide association studies for carcass and growth traits in chicken

Zhang

Shen

et al. 2020

Poultry Science

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There have been several genome-wide association study ( GWAS ) reported for carcass, growth, and meat traits in chickens. Most of these studies have been based on single SNPs GWAS. In contrast, haplotype-based GWAS reports have been limited. In the present study, 2 Northeast Agricultural University broiler lines divergently selected for abdominal fat content ( NEAUHLF ) and genotyped with the chicken 60K SNP chip were used to perform a haplotype-based GWAS. The lean and fat chicken lines were selected for abdominal fat content for 11 yr. Abdominal fat weight was significantly different between the 2 lines; however, there was no difference for body weight between the lean and fat lines. A total of 132 haplotype windows were significantly associated with abdominal fat weight. These significantly associated haplotype windows were primarily located on chromosomes 2, 4, 8, 10, and 26. Seven candidate genes, including SHH , LMBR1 , FGF7 , IL16 , PLIN1 , IGF1R , and SLC16A1 , were located within these associated regions. These genes may play important roles in the control of abdominal fat content. Two regions on chromosomes 3 and 10 were significantly associated with testis weight. These 2 regions were previously detected by the single SNP GWAS using this same resource population. TCF21 on chromosome 3 was identified as a potentially important candidate gene for testis growth and development based on gene expression analysis and the reported function of this gene. TCF12 , which was previously detected in our SNP by SNP interaction analysis, was located in a region on chromosome 10 that was significantly associated with testis weight. Six candidate genes, including TNFRSF1B , PLOD1 , NPPC , MTHFR , EPHB2 , and SLC35A3 , on chromosome 21 may play important roles in bone development based on the known function of these genes. In addition, several regions were significantly associated with other carcass and growth traits, but no candidate genes were identified. The results of the present study may be helpful in understanding the genetic mechanisms of carcass and growth traits in chickens.

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Haplotype-based genome-wide association study identifies loci and candidate genes for milk yield in Holsteins

Cited by 41 publications

References 26 publications

Bayesian Analysis of the Association between Casein Complex Haplotype Variants and Milk Yield, Composition, and Curve Shape Parameters in Murciano-Granadina Goats

Bayesian Analysis of the Association between Casein Complex Haplotype Variants and Milk Yield, Composition, and Curve Shape Parameters in Murciano-Granadina Goats

Research Article Genome-wide classification of dairy cows using decision trees and artificial neural network algorithms

Haplotype-based genome-wide association studies for carcass and growth traits in chicken

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