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Towards a Cost-Effective Implementation of Genomic Prediction Based on Low Coverage Whole Genome Sequencing in Dezhou Donkey.

ABSTRACT: Low-coverage whole genome sequencing is a low-cost genotyping technology. Combined with genotype imputation approaches, it is likely to become a critical component of cost-effective genomic selection programs in agricultural livestock. Here, we used the low-coverage sequence data of 617 Dezhou donkeys to investigate the performance of genotype imputation for low-coverage whole genome sequence data and genomic prediction based on the imputed genotype data. The specific aims were as follows: 1) to measure the accuracy of genotype imputation under different sequencing depths, sample sizes, minor allele frequency (MAF), and imputation pipelines and 2) to assess the accuracy of genomic prediction under different marker densities derived from the imputed sequence data, different strategies for constructing the genomic relationship matrixes, and single-vs. multi-trait models. We found that a high imputation accuracy (>0.95) can be achieved for sequence data with a sequencing depth as low as 1x and the number of sequenced individuals ≥400. For genomic prediction, the best performance was obtained by using a marker density of 410K and a G matrix constructed using expected marker dosages. Multi-trait genomic best linear unbiased prediction (GBLUP) performed better than single-trait GBLUP. Our study demonstrates that low-coverage whole genome sequencing would be a cost-effective approach for genomic prediction in Dezhou donkey.

SUBMITTER: Zhao C

PROVIDER: S-EPMC8595392 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Corn silage can usually improve the growth performance and the meat quality of ruminants, and subsequently increase the economic benefits of farming. However, little is known about the effects of corn silage on donkeys. This experiment investigated the effects of corn silage on the weight gain, gut microbiota and metabolites of Dezhou donkeys. A total of 24 Dezhou donkeys, sourced from the same farm and exhibiting similar age and average body weight, were utilized in this experiment. The donkeys were allocated into two groups: a control group receiving a basic diet and a test group receiving a basic diet supplemented with 30% corn silage. Each group comprised 12 donkeys, evenly distributed by sex (6 males and 6 females). The experiment lasted for 100 days. Results showed that dietary supplementation with corn silage significantly (P < 0.05) improved the weight gain of Dezhou donkeys at the end of the experiment. And the supplementation of corn silage in the diet significantly altered the bacterial community composition and metabolome in the feces of the donkeys. Notably, the relative abundance ratio of Bacteroidetes to Firmicutes was 0.76 in the control group compared to 0.96 in the test group. Furthermore, members of the Bacteroidetes and Firmicutes phyla were associated with differentiated metabolites enriched in the arachidonic acid metabolism and pentose and glucuronate interconversion pathways, both of which have been reported to be related to animal growth. Specifically, Bacteroidia exhibited statistically (P < 0.05) positive correlations with 15S-HpETE, while Bacilli demonstrated statistically (P < 0.05) negative correlations with D-Xylulose. The findings of this study can advance our mechanistic understanding of the remodeling of intestinal microbiota and metabolome induced by corn silage, as well as their relationships with the growth performance of Dezhou donkeys, which in turn favor the improvement in nutrition of Dezhou donkeys.

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Towards a Cost-Effective Implementation of Genomic Prediction Based on Low Coverage Whole Genome Sequencing in Dezhou Donkey.

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