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| http://dx.doi.org/10.1186/ar2303 | DOI Listing |
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Imputation strategies for low-coverage whole-genome sequencing data and their effects on genomic prediction and genome-wide association studies in pigs.
Animal
September 2024
State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China. Electronic address:
The uncertainty resulting from missing genotypes in low-coverage whole-genome sequencing (LCWGS) data complicates genotype imputation. The aim of this study is to find out an optimal strategy for accurately imputing LCWGS data and assess its effectiveness for genomic prediction (GP) and genome-wide association study (GWAS) on economically important traits of Large White pigs. The LCWGS data of 1 423 Large White pigs were imputed using three different strategies: (1) using the high-coverage whole-genome sequencing (HCWGS) of 30 key progenitors as the reference panel (Ref_LG); (2) mixing HCWGS of key progenitors with LCWGS (Mix_HLG) and (3) self-imputation in LCWGS (Within_LG).
View Article and Find Full Text PDFGenetic basis of phenotypic convergence in pig terminal sires using pathway-based selection signature detection methods.
Anim Genet
August 2024
Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of the Ministry of Education & Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture, Huazhong Agricultural University, Wuhan, China.
The primary purpose of genetic improvement in lean pig breeds is to enhance production performance. Owing to their similar breeding directions, Duroc and Pietrain pigs are ideal models for investigating the phenotypic convergence underlying artificial selection. However, most important economic traits are controlled by a polygenic basis, so traditional strategies for detecting selection signatures may not fully reveal the genetic basis of complex traits.
View Article and Find Full Text PDFPhenotypic, Genomic, and Transcriptomic Heterogeneity in a Pancreatic Cancer Cell Line.
Pancreas
October 2024
From the Department of Biomedical Sciences, College of Medicine, Florida State University, Tallahassee, FL.
Objective: To evaluate the suitability of the MIA PaCa-2 cell line for studying pancreatic cancer intratumor heterogeneity, we aim to further characterize the nature of MIA PaCa-2 cells' phenotypic, genomic, and transcriptomic heterogeneity.
Materials And Methods: MIA PaCa-2 single-cell clones were established through flow cytometry. For the phenotypic study, we quantified the cellular morphology, proliferation rate, migration potential, and drug sensitivity of the clones.
Whole-genome resequencing reveals new mutations in candidate genes for Beichuan-white goat prolificacya.
Anim Biotechnol
November 2024
Animal Husbandry Research Institute, Mianyang Academy of Agricultural Sciences, Mianyang, P. R. China.
In this study, we evaluated the copy number variation in the genomes of two groups of Beichuan-white goat populations with large differences in litter size by method, and identified 1739 genes and 485 missense mutations in the genes subject to positive selection. Through functional enrichment, and genes, involved in , were essential for litter size trait, which received intensive attention. In addition, some mutation sites of these genes have been proposed (: c.
View Article and Find Full Text PDFAn Integrated Computational Analysis of High-Risk SNPs in Angiopoietin-like Proteins (ANGPTL3 and ANGPTL8) Reveals Perturbed Protein Dynamics Associated with Cancer.
Molecules
June 2023
Oujiang Laboratory (Zhejiang Laboratory for Regenerative Medicine, Vision and Brain Health), Wenzhou 325000, China.
Angiopoietin-like proteins (ANGPTL) constitute a family of eight proteins (1-8) which play a pivotal role in the regulation of various pathophysiological processes. The current study sought to identify high-risk, "non-synonymous, single-nucleotide polymorphisms" (nsSNPs) in both ANGPTL3 and ANGPTL8 to evaluate the role that these nsSNPs play in various types of cancer. We retrieved a total of 301 nsSNPs from various databases; 79 of these candidates constitute high-risk nsSNPs.
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