Investigating mobile element variations by statistical genetics

• Published in: Human genome variation Vol. 11; no. 1; pp. 23 - 6
• Main Author: Kojima, Shohei
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 30.05.2024; Springer Nature B.V; Nature Publishing Group
• Subjects: 631/208/205/2138; 631/208/457/649/2157; Artificial intelligence; Biomedical and Life Sciences; Biomedicine; Disease; Gene Expression; Gene Function; Gene Therapy; Genetic disorders; Genetic diversity; Genetic factors; Genome-wide association studies; Genomes; Genotyping; Haplotypes; Human Genetics; Integration; Molecular Medicine; Nucleotide sequence; Population genetics; Population studies; Quantitative trait loci; Review Article; Skin diseases; Statistical genetics; Statistics; Structure-function relationships; Whole genome sequencing
• DOI: 10.1038/s41439-024-00280-1
• ISSN: 2054-345X

The integration of structural variations (SVs) in statistical genetics provides an opportunity to understand the genetic factors influencing complex human traits and disease. Recent advances in long-read technology and variant calling methods for short reads have improved the accurate discovery and genotyping of SVs, enabling their use in expression quantitative trait loci (eQTL) analysis and genome-wide association studies (GWAS). Mobile elements are DNA sequences that insert themselves into various genome locations. Insertional polymorphisms of mobile elements between humans, called mobile element variations (MEVs), contribute to approximately 25% of human SVs. We recently developed a variant caller that can accurately identify and genotype MEVs from biobank-scale short-read whole-genome sequencing (WGS) datasets and integrate them into statistical genetics. The use of MEVs in eQTL analysis and GWAS has a minimal impact on the discovery of genome loci associated with gene expression and disease; most disease-associated haplotypes can be identified by single nucleotide variations (SNVs). On the other hand, it helps make hypotheses about causal variants or effector variants. Focusing on MEVs, we identified multiple MEVs that contribute to differential gene expression and one of them is a potential cause of skin disease, emphasizing the importance of the integration of MEVs in medical genetics. Here, I will provide an overview of MEVs, MEV calling from WGS, and the integration of MEVs in statistical genetics. Finally, I will discuss the unanswered questions about MEVs, such as rare variants. Genetic insights: mobile element variations influence human complex traits This research investigates how mobile elements contribute to human genetic diversity and disease. Researchers conducted a review using various sequencing technologies to analyze MEs in different human populations, focusing on three main families: Alu , LINE-1, and SVA. They studied these elements in over 2,500 individuals worldwide, finding that MEs significantly contribute to genetic variation and are linked to certain diseases. Using the short-read sequencing method, they identified thousands of ME variations, some linked to genetic disorders. These methods help uncover how MEs affect genome structure and function. The results show that MEs account for a large part of human structural variations, influencing gene expression and contributing to populations’ genetic makeup. Future studies may clarify how MEs contribute to genetic diversity and disease, leading to new diagnostic and therapeutic strategies. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.