Whole‐genome prediction of fatty acid composition in meat of Japanese Black cattle

Onogi, Akio; Ogino, Akifumi; Komatsu, Takafumi; Shoji, Nobuyuki; Shimizu, Kazuhiro; Kurogi, Kazuhito; Yasumori, Takanori; Kenji, Togashi; Iwata, Hiroyoshi

doi:10.1111/age.12300

Cited by 24 publications

(21 citation statements)

References 10 publications

(14 reference statements)

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“…Previous studies have investigated predictive abilities of genomic selection for fatty acid composition in American Angus [32], Japanese Black cattle [61] and Canadian beef cattle [33]. In the current study, we explored, for the first time, genomic prediction for fatty acid composition in Chinese Simmental cattle.…”

Section: Discussionmentioning

confidence: 99%

Genome wide association study and genomic prediction for fatty acid composition in Chinese Simmental beef cattle using high density SNP array

et al. 2017

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BackgroundFatty acid composition of muscle is an important trait contributing to meat quality. Recently, genome-wide association study (GWAS) has been extensively used to explore the molecular mechanism underlying important traits in cattle. In this study, we performed GWAS using high density SNP array to analyze the association between SNPs and fatty acids and evaluated the accuracy of genomic prediction for fatty acids in Chinese Simmental cattle.ResultsUsing the BayesB method, we identified 35 and 7 regions in Chinese Simmental cattle that displayed significant associations with individual fatty acids and fatty acid groups, respectively. We further obtained several candidate genes which may be involved in fatty acid biosynthesis including elongation of very long chain fatty acids protein 5 (ELOVL5), fatty acid synthase (FASN), caspase 2 (CASP2) and thyroglobulin (TG). Specifically, we obtained strong evidence of association signals for one SNP located at 51.3 Mb for FASN using Genome-wide Rapid Association Mixed Model and Regression-Genomic Control (GRAMMAR-GC) approaches. Also, region-based association test identified multiple SNPs within FASN and ELOVL5 for C14:0. In addition, our result revealed that the effectiveness of genomic prediction for fatty acid composition using BayesB was slightly superior over GBLUP in Chinese Simmental cattle.ConclusionsWe identified several significantly associated regions and loci which can be considered as potential candidate markers for genomics-assisted breeding programs. Using multiple methods, our results revealed that FASN and ELOVL5 are associated with fatty acids with strong evidence. Our finding also suggested that it is feasible to perform genomic selection for fatty acids in Chinese Simmental cattle.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-017-3847-7) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

Genome wide association study and genomic prediction for fatty acid composition in Chinese Simmental beef cattle using high density SNP array

et al. 2017

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“…Moreover, Onogi et al [68] evaluated the predictive ability of genomic selection in FA composition of Japanese Black catle, using single-step genomic-best linear unbiased method. Recently, Chiaia et al [69] evaluated the genomic predictability for beef faty proile in Nelore breed and concluded that genomic information can assist in improving FA proile in Zebu animals, since the use of genomic information yielded genomic values for FA proile with accuracies ranging from low to moderate.…”

Section: Genomic Selection and Genome-wide Association Studies For Bementioning

confidence: 99%

Genetic Factors that Determine the Meat Fatty Acids Composition

Lemos¹,

Pereira²,

Regatieri³

et al. 2017

Fatty Acids

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In relation the nutritional atributes of beef meat quality, the composition of faty acid is important not only because it afects the meat palatability, but also it can afect the human health. The faty acids harmful to human health have received atenuating atention in recent years. Some studies, with taurine breed, have shown that there is a genetic variation for the trait faty acid proile of the meat and, therefore, the possibility of genetic improvement of this trait in beef catle. Meantime, in zebu catle, the genetic parameter estimates for faty acid proile are scarce. Furthermore, the trait meat faty acid proile is something diicult and costly to measure and for this kind of trait is indicated the use of genomic selection, which is a type of marker-assisted selection. The objective of this chapter is showing the genetic variability of meat faty acid proile diferent catle breeds and makes an approach of the implement models and methods that use genomic information to improve the faty acid composition of beef meat.

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“…The single-step genomic best linear unbiased prediction (ssGBLUP) approach [20,21], a quite common procedure in GWAS, has the advantage of simultaneously using the phenotypes of genotyped and nongenotyped animals, pedigrees, and genotypes; therefore, there is no need to calculate pseudo-phenotypes. It has been reported that the use of ssGBLUP procedure increased the accuracy of genetic evaluation in many contexts and species compared with pedigree-based BLUP [22,23]. However, the ssGBLUP assumes that all SNPs explain the same amount of genetic variance, which is unlikely in the case of traits whose major genes or QTL are segregating.…”

Section: Introductionmentioning

confidence: 99%

A Genome-Wide Association Study for Calving Interval in Holstein Dairy Cows Using Weighted Single-Step Genomic BLUP Approach

Atashi

Salavati

Koster

et al. 2020

Animals

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Simple Summary: Reproductive performance is an important factor, which determines productive life and drives culling decisions in dairy herds. There are strong motives for including reproductive performance in genetic selection programs of dairy cows; however, low heritability estimates reported for reproductive performance measures limit the genetic selection efficiency. More effective genetic selection could be achieved using genomic information. The aim of this study was to identify genomic region(s) associated with the length of the calving interval in Holstein cows. The accuracies of genomic estimated breeding values (GEBVs) with single-step genomic BLUP (ssGBLUP) and the pedigree-based BLUP were compared as well. The results showed that the accuracies of GEBVs using the single-step genomic BLUP were much higher than those estimated using the pedigree-based BLUP. We identified three genomic regions (BTA3, BTA6, and BTA7) associated with the length of the calving interval in Holstein dairy cows. Abstract:The aim of the present study was to identify genomic region(s) associated with the length of the calving interval in primiparous (n = 6866) and multiparous (n = 5071) Holstein cows. The single nucleotide polymorphism (SNP) solutions were estimated using a weighted single-step genomic best linear unbiased prediction (WssGBLUP) approach and imputed high-density panel (777 k) genotypes. The effects of markers and the genomic estimated breeding values (GEBV) of the animals were obtained by five iterations of WssGBLUP. The results showed that the accuracies of GEBVs with WssGBLUP improved by +5.4 to +5.7, (primiparous cows) and +9.4 to +9.7 (multiparous cows) percent points over accuracies from the pedigree-based BLUP. The most accurate genomic evaluation was provided at the second iteration of WssGBLUP, which was used to identify associated genomic regions using a windows-based GWAS procedure. The proportion of additive genetic variance explained by windows of 50 consecutive SNPs (with an average of 165 Kb) was calculated and the region(s) that accounted for equal to or more than 0.20% of the total additive genetic variance were used to search for candidate genes. Three windows of 50 consecutive SNPs (BTA3, BTA6, and BTA7) were identified to be associated with the length of the calving interval in primi-and multiparous cows, while the window with the highest percentage of explained genetic variance was located on BTA3 position 49.42 to 49.52 Mb. There were five genes including ARHGAP29, SEC24D, METTL14, SLC36A2, and SLC36A3 inside the windows associated with the length of the calving interval. The biological

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Whole‐genome prediction of fatty acid composition in meat of Japanese Black cattle

Cited by 24 publications

References 10 publications

Genome wide association study and genomic prediction for fatty acid composition in Chinese Simmental beef cattle using high density SNP array

Genome wide association study and genomic prediction for fatty acid composition in Chinese Simmental beef cattle using high density SNP array

Genetic Factors that Determine the Meat Fatty Acids Composition

A Genome-Wide Association Study for Calving Interval in Holstein Dairy Cows Using Weighted Single-Step Genomic BLUP Approach

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