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dc.contributor.authorLu, Tsung-Yu
dc.contributor.authorChaisson, Mark J P
dc.date.accessioned2021-08-02T13:11:38Z
dc.date.available2021-08-02T13:11:38Z
dc.date.issued2021-07-12
dc.identifier.urihttp://hdl.handle.net/10713/16279
dc.description.abstractVariable 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. © 2021, The Author(s).en_US
dc.description.urihttps://doi.org/10.1038/s41467-021-24378-0en_US
dc.language.isoenen_US
dc.publisherSpringer Natureen_US
dc.relation.ispartofNature Communicationsen_US
dc.rights© 2021. The Author(s).en_US
dc.subjectrepeat-pangenome graph (RPGG)en_US
dc.subjectvariable-number tandem repeatsen_US
dc.subjectVNTRsen_US
dc.subject.meshGenome, Humanen_US
dc.subject.meshMinisatellite Repeatsen_US
dc.titleProfiling variable-number tandem repeat variation across populations using repeat-pangenome graphsen_US
dc.typeArticleen_US
dc.identifier.doi10.1038/s41467-021-24378-0
dc.identifier.pmid34253730
dc.source.volume12
dc.source.issue1
dc.source.beginpage4250
dc.source.endpage
dc.source.countryUnited States
dc.source.countryEngland


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