A thorough characterization of structural variants in human genomes
A large international team of researchers from the Human Genome Structural Variation Consortium (HGSVC), including the Lansdorp laboratory and Victor Guryev at the ERIBA, published a study in Nature Communications that delves deeper into individual genomic differences than ever before.
They used a full suite of genomic technologies to extensively analyze the genomes of three family trios (parents and child). The technologies used include long-read, short-read, and strand-specific sequencing technologies, optical mapping and multiple computer algorithms for structural variation (SV) detection. The results present the most comprehensive catalog of SVs to date in the children’s genomes, including information on which set of parental chromosomes each SV was present on.
In summary, the researchers identified an average of 818,054 small insertions and deletions (genomic alterations that each affected less than 50 bases of DNA) and 27,622 SVs (genomic alterations that affected 50 bases or more of DNA) per genome. Remarkably, they also found an average of 156 inversions per genome, many of which intersected with genomic regions associated with genetic disease syndromes. Most of these inversions were only identified using the single cell Strand-seq method developed by the Lansdorp group. The more than 20 million nucleotides present in these newly identified inversions are in stark contrast to the much better studied 4-5 million “single nucleotide polymorphic (SNP)” nucleotides. The researchers found that more than 100,000 variants per individual are actually missed by routine sequencing technologies and commonly-used computer algorithms. In fact, the true numbers of SVs in a given human genome appears to be three- to seven-fold more than most studies typically identify.
Hence, SVs constitute a large amount of genetic variation not commonly captured by current genome sequencing technologies and analytical methods. This implies that the contribution of SVs to human disease has not yet been well-quantified and the expanded SV repertoire can help identify new genetic associations to diseases and improved diagnostic yields in future genetic tests.
The publication can be found here: https://www.nature.com/articles/s41467-018-08148-z
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