A Multi-Omics Perspective of Quantitative Trait Loci in Precision Medicine

The enormous volume of genotyping data provides opportunities to discover novel types of QTLs. Various types of QTLs have emerged through advances in high-throughput technologies, including those for the transcriptome, epigenome, proteome, metabolome, and microbiome. Advanced algorithms enable the identification and inference of the causal effects of molQTLs. Integrative analysis of multi-omics data advances our understanding of the functional significance of genetic variants. Quantitative trait loci (QTL) analysis is an important approach to investigate the effects of genetic variants identified through an increasing number of large-scale, multidimensional 'omics data sets. In this 'big data' era, the research community has identified a significant number of molecular QTLs (molQTLs) and increased our understanding of their effects. Herein, we review multiple categories of molQTLs, including those associated with transcriptome, post-transcriptional regulation, epigenetics, proteomics, metabolomics, and the microbiome. We summarize approaches to identify molQTLs and to infer their causal effects. We further discuss the integrative analysis of molQTLs through a multi-omics perspective. Our review highlights future opportunities to better understand the functional significance of genetic variants and to utilize the discovery of molQTLs in precision medicine. Quantitative trait loci (QTL) analysis is an important approach to investigate the effects of genetic variants identified through an increasing number of large-scale, multidimensional 'omics data sets. In this 'big data' era, the research community has identified a significant number of molecular QTLs (molQTLs) and increased our understanding of their effects. Herein, we review multiple categories of molQTLs, including those associated with transcriptome, post-transcriptional regulation, epigenetics, proteomics, metabolomics, and the microbiome. We summarize approaches to identify molQTLs and to infer their causal effects. We further discuss the integrative analysis of molQTLs through a multi-omics perspective. Our review highlights future opportunities to better understand the functional significance of genetic variants and to utilize the discovery of molQTLs in precision medicine. a post-transcriptional regulation that processes splice sites in precursor mRNA to produce multiple distinct RNA isoforms. type of single-stranded RNA that forms a covalently closed continuous loop. public repository created by The National Center for Biotechnology Information for genotypes and phenotypes, and the associations among them. epigenetic mechanism that is tightly associated with gene expression by influencing DNA accessibility and transcription factor occupancy in the eukaryotic genome. genome-wide approach to reveal associations between genetic variations and phenotypic traits. modifications of histone proteins, including methylation, phosphorylation, acetylation, ubiquitylation, and sumoylation. model that integrates linear models and other statistical modes to infer parameters. basic chemical reactions that sustain the essential biological processes in an organism, producing abundant metabolites. genetic material of all microbes, including bacteria, fungi, protozoa, and viruses. type of small ncRNAs involved in the post-transcriptional regulation of gene expression. poly(A) tail on the 3′-end of mRNA that determines multiple important biological processes of mRNA, including nuclear export, translation, and stability. enzymatic modification of proteins following their translation. approach to customize individual healthcare based on the understanding of the disease features. genomic region and/or loci associated with a particular phenotypic trait. DNA sequences, including promoters and enhancers, that regulate gene expression. post-transcriptional regulation that confers specific and reproducible nucleotide changes in RNA transcripts. the most common type of genetic variant at a single base pair among a population.