No abstract

The human genome is arguably the most complete mammalian reference assembly1–3 yet more than 160 euchromatic gaps remain4–6 and aspects of its structural variation remain poorly understood ten years after its completion7–9. In order to identify missing sequence and genetic variation, we sequenced and analyzed a haploid human genome (CHM1) using single-molecule, real-time (SMRT) DNA sequencing10. We closed or extended 55% of the remaining interstitial gaps in the human GRCh37 reference genome—78% of which carried long runs of degenerate short tandem repeats (STRs) often multiple kilobases in length embedded within GC-rich genomic regions. We resolved the complete sequence of 26,079 euchromatic structural variants at the basepair level, including inversions, complex insertions, and long tracts of tandem repeats. Most have not been previously reported with the greatest increases in sensitivity occurring for events less than 5 kbp in size. Compared to the human reference, we find a significant insertional bias (3:1) in regions corresponding to complex insertions and long STRs. Our results suggest a greater complexity of the human genome in the form of variation of longer and more complex repetitive DNA that can now be largely resolved with the application of this longer-read sequencing technology.

Copy number variants affect both disease and normal phenotypic variation, but those lying within heavily duplicated, highly identical sequence have been difficult to assay. By analyzing short-read mapping depth for 159 human genomes, we demonstrated accurate estimation of absolute copy number for duplications as small as 1.9 kilobase pairs, ranging from 0 to 48 copies. We identified 4.1 million “singly unique nucleotide” positions informative in distinguishing specific copies and used them to genotype the copy and content of specific paralogs within highly duplicated gene families. These data identify human-specific expansions in genes associated with brain development, reveal extensive population genetic diversity, and detect signatures consistent with gene conversionin the human species. Our approach makes ~1000 genes accessible to genetic studies of disease association.

Despite their importance in gene innovation and phenotypic variation, duplicated regions have remained largely intractable due to difficulties in accurately resolving their structure, copy number and sequence content. We present an algorithm (mrFAST) to comprehensively map next-generation sequence reads allowing for the prediction of absolute copy-number variation of duplicated segments and genes. We examine three human genomes and experimentally validate genome-wide copy-number differences. We estimate that 73–87 genes will be on average copy-number variable between two human genomes and find that these genic differences overwhelmingly correspond to segmental duplications (OR=135; p<2.2e-16). Our method can distinguish between different copies of highly identical genes, providing a more accurate census of gene content and insight into functional constraint without the limitations of array-based technology.