TY - CHAP
T1 - Incorporation of Trait-Specific Genetic Information into Genomic Prediction Models
AU - Shi, Shaolei
AU - Zhang, Zhe
AU - Li, Bingjie
AU - Zhang, Shengli
AU - Fang, Lingzhao
N1 - © 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2022/4/22
Y1 - 2022/4/22
N2 - Due to the rapid development of high-throughput sequencing technology, we can easily obtain not only the genetic variants at the whole-genome sequence level (e.g., from 1000 Genomes project and 1000 Bull Genomes project), but also a wide range of functional annotations (e.g., enhancers and promoters from ENCODE, FAANG, and FarmGTEx projects) across a wide range of tissues, cell types, developmental stages, and environmental conditions. This huge amount of information leads to a revolution in studying genetics and genomics of complex traits in humans, livestock, and plant species. In this chapter, we focused on and reviewed the genomic prediction methods that incorporate external biological information into genomic prediction, such as sequence ontology, linkage disequilibrium (LD) of SNPs, quantitative trait loci (QTL), and multi-layer omics data (e.g., transcriptome, epigenome, and microbiome).
AB - Due to the rapid development of high-throughput sequencing technology, we can easily obtain not only the genetic variants at the whole-genome sequence level (e.g., from 1000 Genomes project and 1000 Bull Genomes project), but also a wide range of functional annotations (e.g., enhancers and promoters from ENCODE, FAANG, and FarmGTEx projects) across a wide range of tissues, cell types, developmental stages, and environmental conditions. This huge amount of information leads to a revolution in studying genetics and genomics of complex traits in humans, livestock, and plant species. In this chapter, we focused on and reviewed the genomic prediction methods that incorporate external biological information into genomic prediction, such as sequence ontology, linkage disequilibrium (LD) of SNPs, quantitative trait loci (QTL), and multi-layer omics data (e.g., transcriptome, epigenome, and microbiome).
KW - Functional annotation
KW - Genomic prediction
KW - Omics data
KW - QTL
U2 - 10.1007/978-1-0716-2205-6_11
DO - 10.1007/978-1-0716-2205-6_11
M3 - Chapter
C2 - 35451781
SN - 978-1-0716-2204-9
VL - 2467
T3 - Methods in molecular biology (Clifton, N.J.)
SP - 329
EP - 340
BT - Methods in Molecular Biology
PB - Humana, New York, NY
ER -