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Profiling variable-number tandem repeat variation across populations using repeat-pangenome graphs.
Lu, Tsung-Yu; Chaisson, Mark J P.
Afiliação
  • Lu TY; Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA.
  • Chaisson MJP; Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA. mchaisso@usc.edu.
Nat Commun ; 12(1): 4250, 2021 07 12.
Article em En | MEDLINE | ID: mdl-34253730
ABSTRACT
Variable number tandem repeats (VNTRs) are composed of consecutive repetitive DNA with hypervariable repeat count and composition. They include protein coding sequences and associations with clinical disorders. It has been difficult to incorporate VNTR analysis in disease studies that use short-read sequencing because the traditional approach of mapping to the human reference is less effective for repetitive and divergent sequences. In this work, we solve VNTR mapping for short reads with a repeat-pangenome graph (RPGG), a data structure that encodes both the population diversity and repeat structure of VNTR loci from multiple haplotype-resolved assemblies. We develop software to build a RPGG, and use the RPGG to estimate VNTR composition with short reads. We use this to discover VNTRs with length stratified by continental population, and expression quantitative trait loci, indicating that RPGG analysis of VNTRs will be critical for future studies of diversity and disease.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Variação Genética / Genoma Humano / Repetições Minissatélites / Genética Populacional Limite: Humans Idioma: En Revista: Nat Commun Assunto da revista: BIOLOGIA / CIENCIA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Variação Genética / Genoma Humano / Repetições Minissatélites / Genética Populacional Limite: Humans Idioma: En Revista: Nat Commun Assunto da revista: BIOLOGIA / CIENCIA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos