Livestock epigenetics: laying the foundation for future benefits
Home Contact us Help Free delivery worldwide. Free delivery worldwide. Bestselling Series. Harry Potter. Popular Features. New Releases. Categories: Biology, Life Sciences. Description Livestock Epigenetics reviews advances in the understanding of the molecular basis of epigenetic mechanisms in gene expression in livestock species. Epigenetics impact many economically important traits from growth and development to more efficient reproduction and breeding strategies. The book opens with a broad introductory chapter that discusses the importance of an understanding of epigenetics to efficient and sustainable livestock production.
In subsequent chapters the role of epigenetics in specific aspects of animal production are reviewed. The final chapter provides researchers with a valuable basis for the use of comparative epigenetics research to allow research to apply advances across organisms. Livestock Epigenetics provides detailed information on this rapidly expanding field of research with contributions from a global team of experts. Table of contents Contributors vii Preface xi 1. Cindy Tian and Sadie L. Marjani 3.
The genomic regions used for fine-mapping analyses were defined by extending the QTL regions i. BFMAP attempted to determine independent association signals in a genomic region by assessing a posterior probability of causality PPC for each variant within this particular region. We used org. A total of miRNA-target networks were built as previously described This enrichment analysis is based on all variants in a GWAS study rather than the top variants passing genome-wide significance level.
Previous studies have demonstrated that this approach has at least equal power to many commonly used GWAS signal enrichment methods in human 78 , Drosophila melanogaster 79 and livestock species 80 , 81 , 82 , particularly in highly polygenic phenotypes. The sum-based statistics can be expressed as. Here, SNPs located in different genes within a genomic feature e. This approach is similar to the popular LD score regression in human studies 83 , and it controls LD patterns among variants and variant-set sizes through employing the following genotype cyclical permutation strategy 78 , In brief, we first ordered the test statistics i.
We then randomly chose one test statistic i. We calculated a new summary statistic for the tested genomic feature using its original genomic positions. We repeated this permutation procedure 10, times for each genomic feature being tested, and obtained an empirical P -value by using a one-tailed test of the proportion of random summary statistics greater than that observed.
No animal experiments were conducted in this study, and ethics committee approval was thus not required. All sperm methylation data were generated in previous studies, and references were provided where animal data were used. The sperm whole-genome bisulfite sequencing WGBS data were generated in previous studies All the semen samples used in this study were collected from bulls by an artificial insemination company using a standardized procedure with artificial vaginas.
Briefly, one semen straw 0. After thawing a semen straw, PBS buffer was used to wash away the extender for three times by mild centrifugations. In total, all of these sperm samples were from 18 fertile, age-matched and representative animals, because several animals had extreme values for multiple traits. The reliabilities of PTA for all of the 18 animals were greater than 0. FastQC v0. All the cleaned data were mapped to the cattle reference genome UMD 3.
INRA - Livestock epigenetics: laying the foundation for future benefits
The total number of mapped reads per sample ranged from ,, to ,, with an average of ,, Bismark software 85 was applied to extract methylcytosine information. Only the loci that were covered by at least 10 clean reads were kept for further analyses. More details have been described previously Because methylation alterations that are associated with complex traits often exhibit spatial correlation patterns 86 , DMR differentially methylated region instead of DMC differentially methylated cytosine were determined by using methylKit A logistic regression model implemented in the calculateDiffMeth function was employed to detect DMR: information from each sample is specified the number of methylated Cs and number of unmethylated Cs at a given region , and a logistic regression test is applied to compare fraction of methylated Cs across the two groups under comparison.
P -values were calculated through comparing the model fitness of alternative models to the null model, and were corrected to q -values for multiple testing using the SLIM method The following count-based approach was used to test whether a Reactome pathway was enriched for DMR,. Under the null hypothesis i. The null hypothesis i. Functional enrichment analyses for gene lists in DMRs were conducted using the R package clusterProfiler 90 , where a hypergeometric test was employed using the current KEGG database.
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