Article ; Online: Genome maps across 26 human populations reveal population-specific patterns of structural variation.
2019 Volume 10, Issue 1, Page(s) 1025
Abstract: Large structural variants (SVs) in the human genome are difficult to detect and study by conventional sequencing technologies. With long-range genome analysis platforms, such as optical mapping, one can identify large SVs (>2 kb) across the genome in one ...
Abstract | Large structural variants (SVs) in the human genome are difficult to detect and study by conventional sequencing technologies. With long-range genome analysis platforms, such as optical mapping, one can identify large SVs (>2 kb) across the genome in one experiment. Analyzing optical genome maps of 154 individuals from the 26 populations sequenced in the 1000 Genomes Project, we find that phylogenetic population patterns of large SVs are similar to those of single nucleotide variations in 86% of the human genome, while ~2% of the genome has high structural complexity. We are able to characterize SVs in many intractable regions of the genome, including segmental duplications and subtelomeric, pericentromeric, and acrocentric areas. In addition, we discover ~60 Mb of non-redundant genome content missing in the reference genome sequence assembly. Our results highlight the need for a comprehensive set of alternate haplotypes from different populations to represent SV patterns in the genome. |
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MeSH term(s) | Algorithms ; Base Sequence ; Chromosome Mapping/methods ; Chromosomes, Human, Y ; Computational Biology ; Female ; Gene Dosage ; Genetic Linkage ; Genome, Human ; Genomic Structural Variation ; Genomics ; Humans ; Male ; Mutation ; Phylogeny ; Segmental Duplications, Genomic/genetics ; Sequence Analysis, DNA |
Language | English |
Publishing date | 2019-03-04 |
Publishing country | England |
Document type | Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't |
ZDB-ID | 2553671-0 |
ISSN | 2041-1723 ; 2041-1723 |
ISSN (online) | 2041-1723 |
ISSN | 2041-1723 |
DOI | 10.1038/s41467-019-08992-7 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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