Comparison of genome-wide association and genomic prediction methods for milk production traits in Korean Holstein cattle

Lee, SeokHyun; Dang, Chang Gwon; Choy, Yun Ho; Do, Chang-Hee; Cho, Kwang-Hyun; Kim, Jongjoo; Kim, You-Sam; Lee, J.

doi:10.5713/ajas.18.0847

Cited by 7 publications

(7 citation statements)

References 28 publications

(44 reference statements)

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“…Abdelsayed et al [ 18 ] found out the milk yield of 8,887 kg produced in the period between 305 to 610 days, with the range 2,891 to 19,631 kg milk. Holstein cattle from various countries reached different milk yield per lactation [ 4 , 5 , 17 ].…”

Section: Resultsmentioning

confidence: 99%

“…The description of lactation curve is still current in livestock research and was analysed by others [ 1 – 3 ]. Lactations are described for many reasons, for example estimating of genetic parameters, analysing of genomic evaluation and comparison of data from milking system and test-day records [ 4 – 6 ]. The conventional length of a lactation period is 305 days.…”

Section: Introductionmentioning

confidence: 99%

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The effect of extended lactation on parameters of Wood’s model of lactation curve in dairy Simmental cows

et al. 2021

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Objective: This study was focused on the estimation of parameters of Wood's model and description of the lactation curve using the cows which were lactated over 24 months on the first lactation. Methods: The database included 1 333 pure-bred dairy Simmental primiparous cows which lactated for 24 months (732 days). The initial dataset entering the procedure of assessment of parameters of Wood's function included 35 826 milk yield records. Milk yield was recorded throughout lactation, with the earliest record taken on day 6 and the latest on day 1 348 of lactation. This dataset was used for the assessment of parameters a, b, c of Wood's model using the non-linear statistical procedure. These parameters were estimated for different length of lactation. The assessed parameters were used for calculation of some characteristics of lactation curves. Results: The lowest value of a parameter (15.2317) of Wood's model of lactation curve was found out in lactations up to 305 days long, contrary to b and c parameters which were highest in those lactations (0.1029 and 0.0015, respectively). The maximum value of a parameter (17.4329) was found out in lactations up to 640 days long, unlike b and c parameters which were minimal in those lactations (0.0603 and 0.0010, respectively). Conclusion: It can be concluded that the parameters of Wood's model and the shape of lactation curve are changing with the growing number of milk yield records. Also, the assessed parameters revealed a significant milk production potential after 305 days of lactation.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The effect of extended lactation on parameters of Wood’s model of lactation curve in dairy Simmental cows

et al. 2021

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“…Genome-wide association studies (GWAS) have been widely used to analyze the genetic architecture of reproduction, meat quality, and production traits in the pig population ( Verardo et al, 2016 ; Schmid et al, 2018 ; Ding et al, 2019 ). Previous GWAS found that several single nucleotide polymorphisms (SNPs) in or near the bone morphogenetic protein 2 ( BMP2 ) gene were associated with body length and body height, and many reported that the vertebrae development-associated ( VRTN ) gene was significantly associated with total teat number in pigs ( Lee et al, 2014 , 2019 ; Arakawa et al, 2015 ; Wang et al, 2017 ). Almost all GWAS for body length, body height, and total teat number were performed by single-locus GWAS.…”

Section: Introductionmentioning

confidence: 99%

“…Almost all GWAS for body length, body height, and total teat number were performed by single-locus GWAS. Weighted single-step GWAS (WssGWAS) is widely used in association analysis to increase the number of genotyped animals in livestock ( Suwannasing et al, 2018 ; Lee et al, 2019 ; Fu et al, 2020 ). WssGWAS is a promising method allowing utilization of phenotypes from ungenotyped animals based on pedigree information, so we compared the result from two methods on body length, body height, and total teat number in pigs.…”

Section: Introductionmentioning

confidence: 99%

Genome-Wide Association Study for Body Length, Body Height, and Total Teat Number in Large White Pigs

Hong

Dong

et al. 2021

Front. Genet.

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Body length, body height, and total teat number are economically important traits in pig breeding, as these traits are usually associated with the growth, reproductivity, and longevity potential of piglets. Here, we report a genetic analysis of these traits using a population comprising 2,068 Large White pigs. A genotyping-by-sequencing (GBS) approach was used to provide high-density genome-wide SNP discovery and genotyping. Univariate and bivariate animal models were used to estimate heritability and genetic correlations. The results showed that heritability estimates for body length, body height, and total teat number were 0.25 ± 0.04, 0.11 ± 0.03, and 0.22 ± 0.04, respectively. The genetic correlation between body length and body height exhibited a strongly positive correlation (0.63 ± 0.15), while a positive but low genetic correlation was observed between total teat number and body length. Furthermore, we used two different genome-wide association study (GWAS) approaches: single-locus GWAS and weighted single-step GWAS (WssGWAS), to identify candidate genes for these traits. Single-locus GWAS detected 76, 13, and 29 significant single-nucleotide polymorphisms (SNPs) associated with body length, body height, and total teat number. Notably, the most significant SNP (S17_15781294), which is located 20 kb downstream of the BMP2 gene, explained 9.09% of the genetic variance for body length traits, and it also explained 9.57% of the genetic variance for body height traits. In addition, another significant SNP (S7_97595973), which is located in the ABCD4 gene, explained 8.92% of the genetic variance for total teat number traits. GWAS results for these traits identified some candidate genomic regions, such as SSC6: 14.96–15.02 Mb, SSC7: 97.18–98.18 Mb, SSC14: 128.29–131.15 Mb, SSC17: 15.39–17.27 Mb, and SSC17: 22.04–24.15 Mb, providing a starting point for further inheritance research. Most quantitative trait loci were detected by single-locus GWAS and WssGWAS. These findings reveal the complexity of the genetic mechanism of the three traits and provide guidance for subsequent genetic improvement through genome selection.

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“…In addition, GWAS performed using the BovineHD SNP777K BeadChip in Canadian Holstein cattle for milk production, fat production, and protein production traits found many candidate SNPs and chromosomal regions [ 9 ], and many other candidate genes related to milk production, such as diacylglycerol O-acyltransferase 1 ( DGAT1 ), transcriptional repressor GATA binding 1 ( TRPS1 ), stearoyl-CoA desaturase ( SCD ), and growth hormone receptor ( GHR ) were found in GWAS using a high-density SNP chip platform [ 10 , 11 , 12 , 13 , 14 , 15 ]. GWAS of Korean Holstein were also performed using the Bovine SNP50K BeadChip platform (Illumina), indicating significant genetic regions such as DGAT1 related to milk production, fat, and protein [ 16 , 17 ].…”

Section: Introductionmentioning

confidence: 99%

Genome-Wide Identification of Candidate Genes for Milk Production Traits in Korean Holstein Cattle

Kim

Lim

Cho³

et al. 2021

Animals

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We performed a genome-wide association study and fine mapping using two methods (single marker regression: frequentist approach and Bayesian C (BayesC): fitting selected single nucleotide polymorphisms (SNPs) in a Bayesian framework) through three high-density SNP chip platforms to analyze milk production phenotypes in Korean Holstein cattle (n = 2780). We identified four significant SNPs for each phenotype in the single marker regression model: AX-311625843 and AX-115099068 on Bos taurus autosome (BTA) 14 for milk yield (MY) and adjusted 305-d fat yield (FY), respectively, AX-428357234 on BTA 18 for adjusted 305-d protein yield (PY), and AX-185120896 on BTA 5 for somatic cell score (SCS). Using the BayesC model, we discovered significant 1-Mb window regions that harbored over 0.5% of the additive genetic variance effects for four milk production phenotypes. The concordant significant SNPs and 1-Mb window regions were characterized into quantitative trait loci (QTL). Among the QTL regions, we focused on a well-known gene (diacylglycerol O-acyltransferase 1 (DGAT1)) and newly identified genes (phosphodiesterase 4B (PDE4B), and anoctamin 2 (ANO2)) for MY and FY, and observed that DGAT1 is involved in glycerolipid metabolism, fat digestion and absorption, metabolic pathways, and retinol metabolism, and PDE4B is involved in cAMP signaling. Our findings suggest that the candidate genes in QTL are strongly related to physiological mechanisms related to the fat production and consequent total MY in Korean Holstein cattle.

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Comparison of genome-wide association and genomic prediction methods for milk production traits in Korean Holstein cattle

Cited by 7 publications

References 28 publications

The effect of extended lactation on parameters of Wood’s model of lactation curve in dairy Simmental cows

The effect of extended lactation on parameters of Wood’s model of lactation curve in dairy Simmental cows

Genome-Wide Association Study for Body Length, Body Height, and Total Teat Number in Large White Pigs

Genome-Wide Identification of Candidate Genes for Milk Production Traits in Korean Holstein Cattle

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