Investigation of genetic markers for intramuscular fat in the hybrid Wagyu cattle with bulked segregant analysis

Zhu, Yun; Han, Liyun; Kang, Xiaolong; Dan, Xingang; Ma, Yun; Shi, Yiting

doi:10.1038/s41598-021-91101-w

Cited by 2 publications

(1 citation statement)

References 22 publications

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“…This method is widely used in molecular marker screening and quantitative trait locus (QTL) mapping analysis to target traits in plants and animals ( Kurlovs et al, 2019 ; Li and Xu, 2022 ). BSA has been successfully used to analyze the F2 and F3 populations of the crossover between Wagyu and Qinchuan cattle and has identified four potential SNPs related to intramuscular fat traits ( Zhu et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Genome-wide analysis for the melatonin trait associated genes and SNPs in dairy goat (Capra hircus) as the molecular breeding markers

et al. 2023

Front. Genet.

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Previous studies have reported that the endogenous melatonin level is positively associated with the quality and yield of milk of cows. In the current study, a total of 34,921 SNPs involving 1,177 genes were identified in dairy goats by using the whole genome resequencing bulked segregant analysis (BSA) analysis. These SNPs have been used to match the melatonin levels of the dairy goats. Among them, 3 SNPs has been identified to significantly correlate with melatonin levels. These 3 SNPs include CC genotype 147316, GG genotype 147379 and CC genotype 1389193 which all locate in the exon regions of ASMT and MT2 genes. Dairy goats with these SNPs have approximately 5-fold-higher melatonin levels in milk and serum than the average melatonin level detected in the current goat population. If the melatonin level impacts the milk production in goats as in cows, the results strongly suggest that these 3 SNPs can serve as the molecular markers to select the goats having the improved milk quality and yield. This is a goal of our future study.

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Section: Introductionmentioning

confidence: 99%

Genome-wide analysis for the melatonin trait associated genes and SNPs in dairy goat (Capra hircus) as the molecular breeding markers

et al. 2023

Front. Genet.

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Predicting the genomic resolution of bulk segregant analysis

Shen

Messer

2022

G3 Genes|Genomes|Genetics

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Bulk segregant analysis is a technique for identifying the genetic loci that underlie phenotypic trait differences. The basic approach is to compare two pools of individuals from the opposing tails of the phenotypic distribution, sampled from an interbred population. Each pool is sequenced and scanned for alleles that show divergent frequencies between the pools, indicating potential association with the observed trait differences. Bulk segregant analysis has already been successfully applied to the mapping of various quantitative trait loci in organisms ranging from yeast to maize. However, these studies have typically suffered from rather low mapping resolution, and we still lack a detailed understanding of how this resolution is affected by experimental parameters. Here, we use coalescence theory to calculate the expected genomic resolution of bulk segregant analysis for a simple monogenic trait. We first show that in an idealized interbreeding population of infinite size, the expected length of the mapped region is inversely proportional to the recombination rate, the number of generations of interbreeding, and the number of genomes sampled, as intuitively expected. In a finite population, coalescence events in the genealogy of the sample reduce the number of potentially informative recombination events during interbreeding, thereby increasing the length of the mapped region. This is incorporated into our model by an effective population size parameter that specifies the pairwise coalescence rate of the interbreeding population. The mapping resolution predicted by our calculations closely matches numerical simulations and is surprisingly robust to moderate levels of contamination of the segregant pools with alternative alleles. Furthermore, we show that the approach can easily be extended to modifications of the crossing scheme. Our framework will allow researchers to predict the expected power of their mapping experiments, and to evaluate how their experimental design could be tuned to optimize mapping resolution.

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Investigation of genetic markers for intramuscular fat in the hybrid Wagyu cattle with bulked segregant analysis

Cited by 2 publications

References 22 publications

Genome-wide analysis for the melatonin trait associated genes and SNPs in dairy goat (Capra hircus) as the molecular breeding markers

Genome-wide analysis for the melatonin trait associated genes and SNPs in dairy goat (Capra hircus) as the molecular breeding markers

Predicting the genomic resolution of bulk segregant analysis

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