KAGE: Fast alignment-free graph-based genotyping of SNPs and short indels

One of the core applications of high-throughput sequencing is the characterization of individual genetic variation. Traditionally, variants have been inferred by comparing sequenced reads to a reference genome. There has recently been an emergence of genotyping methods, which instead infer variants of an individual based on variation present in population-scale repositories like the 1000 Genomes Project. However, commonly used methods for genotyping are slow since they still require mapping of reads to a reference genome. Also, since traditional reference genomes do not include genetic variation, traditional genotypers suffer from reference bias and poor accuracy in variation-rich regions where reads cannot accurately be mapped.We here present KAGE, a genotyper for SNPs and short indels that is inspired by recent developments within graph-based genome representations and alignment-free genotyping. We propose two novel ideas to improve both the speed and accuracy: we (1) use known genotypes from thousands of individuals in a Bayesian model to predict genotypes, and (2) propose a computationally efficient method for leveraging correlation between variants.We show through experiments on experimental data that KAGE is both faster and more accurate than other alignment-free genotypers. KAGE is able to genotype a new sample (15x coverage) in less than half an hour on a consumer laptop, more than 10 times faster than the fastest existing methods, making it ideal in clinical settings or when large numbers of individuals are to be genotyped at low computational cost.

Genome editing in plants using CRISPR type I-D nuclease

Genome editing in plants has advanced greatly by applying the clustered regularly interspaced short palindromic repeats (CRISPRs)-Cas system, especially CRISPR-Cas9. However, CRISPR type I—the most abundant CRISPR system in bacteria—has not been exploited for plant genome modification. In type I CRISPR-Cas systems, e.g., type I-E, Cas3 nucleases degrade the target DNA in mammals. Here, we present a type I-D (TiD) CRISPR-Cas genome editing system in plants. TiD lacks the Cas3 nuclease domain; instead, Cas10d is the functional nuclease in vivo. TiD was active in targeted mutagenesis of tomato genomic DNA. The mutations generated by TiD differed from those of CRISPR/Cas9; both bi-directional long-range deletions and short indels mutations were detected in tomato cells. Furthermore, TiD can be used to efficiently generate bi-allelic mutant plants in the first generation. These findings indicate that TiD is a unique CRISPR system that can be used for genome engineering in plants.

Circular DNA intermediates in the generation of large human segmental duplications.

Background Duplications of large genomic segments provide genetic diversity in genome evolution. Despite their importance, how these duplications are generated remains uncertain, particularly for distant duplicated genomic segments. Results Here we provide evidence of the participation of circular DNA intermediates in the single generation of some large human segmental duplications. A specific reversion of sequence order from A-B / C-D to B-A / D-C between duplicated segments and the presence of only microhomologies and short indels at the evolutionary breakpoints suggest a circularization of the donor ancestral locus and an accidental replicative interaction with the acceptor locus. Conclusions This novel mechanism of random genomic mutation could explain several distant genomic duplications including some of the ones that took place during recent human evolution.

Circular DNA intermediates in the generation of large human segmental duplications.

Background: Duplications of large genomic segments provide genetic diversity in genome evolution. Despite their importance, how these duplications are generated remains uncertain, particularly for distant duplicated genomic segments. Results: Here we provide evidence of the participation of circular DNA intermediates in the single generation of some large human segmental duplications. A specific reversion of sequence order from A-B/C-D to B-A/D-C between duplicated segments and the presence of only microhomologies and short indels at the evolutionary breakpoints suggest a circularization of the donor ancestral locus and an accidental replicative interaction with the acceptor locus. Conclusions: This novel mechanism of random genomic mutation could explain several distant genomic duplications including some of the ones that took place during recent human evolution.

Circular DNA intermediates in the generation of large human segmental duplications.

Background: Duplications of large genomic segments provide genetic diversity in genome evolution. Despite their importance, how these duplications are generated remains uncertain, particularly for distant duplicated genomic segments. Results: Here we provide evidence of the participation of circular DNA intermediates in the single generation of some large human segmental duplications. A specific reversion of sequence order from A-B / C-D to B-A / D-C between duplicated segments and the presence of only microhomologies and short indels at the evolutionary breakpoints suggest a circularization of the donor ancestral locus and an accidental replicative interaction with the acceptor locus. Conclusions: This novel mechanism of random genomic mutation could explain several distant genomic duplications including some of the ones that took place during recent human evolution.

Insertion and deletion evolution reflects antibiotics selection pressure in a Mycobacterium tuberculosis outbreak

In genome evolution, genetic variants are the source of diversity, which natural selection acts upon. Treatment of human tuberculosis (TB) induces a strong selection pressure for the emergence of antibiotic resistance in the infecting Mycobacterium tuberculosis (MTB) strains. MTB evolution in response to treatment has been intensively studied and mainly attributed to point substitutions. However, the contribution of insertions and deletions (indels) to MTB genome evolution remains poorly understood. Here, we analyzed a multi-drug resistant MTB outbreak for the presence of high-quality indels and substitutions. We find that indels are significantly enriched in genes conferring antibiotic resistance. Furthermore, we show that indels are inherited during the outbreak and follow a molecular clock with an evolutionary rate of 5.37e-9 indels/site/year, which is 23x lower compared to the substitution rate. Inherited indels may co-occur with substitutions in genes along related biological pathways; examples are iron storage and resistance to second-line antibiotics. This suggests that epistatic interactions between indels and substitutions affect antibiotic resistance and compensatory evolution in MTB.Author summaryMycobacterium tuberculosis (MTB) is a human pathogen causing millions of deaths every year. Its genome evolution has been intensively characterized through point substitutions, i.e., nucleotide exchanges that are inherited. Additional mutations are short or long insertions and deletions of nucleotides, termed indels. Short indels in genes might change the reading frame and disrupt the gene product. Here we show that antibiotic treatment has a strong impact on indel evolution in an MTB outbreak. Namely, indels occur frequently in genes causing antibiotic resistance upon disruption. Furthermore, we show that the molecular clock, i.e., the temporal emergence of variants over time, holds for short indels in MTB genomes. Finally, we observe that indels may co-occur with substitutions in genes along related biological pathways. These results support the notion that indels are important contributors to MTB evolution. We anticipate that including indels in the analyses of MTB outbreaks will improve our understanding of antibiotic resistance evolution.

CAPICE: a computational method for Consequence-Agnostic Pathogenicity Interpretation of Clinical Exome variations

ABSTRACTExome sequencing is now mainstream in clinical practice, however, identification of pathogenic Mendelian variants remains time consuming, partly because limited accuracy of current computational prediction methods leaves much manual classification. Here we introduce CAPICE, a new machine-learning based method for prioritizing pathogenic variants, including SNVs and short InDels, that outperforms best general (CADD, GAVIN) and consequence-type-specific (REVEL, ClinPred) computational prediction methods, for both rare and ultra-rare variants. CAPICE is easily integrated into diagnostic pipelines and is available as free and open source command-line software, file of pre-computed scores, and as a web application with web service API.

Genome-Wide Analysis of Non-Coding Alterations in Pan-Myeloid Cancers Using Whole Genome Sequencing

Background Intensive efforts of genome sequencing studies during the past decade identified >100 driver genes recurrently mutated in one or more subtypes of myeloid neoplasms, which collectively account for the pathogenesis of >90% of the cases. However, approximately 10% of the cases have no alterations in known drivers and their pathogenesis is still unclear. A possible explanation might be the presence of alterations in non-coding regions that are not detected by conventional exome/panel sequencing; mutations and complex structural variations (SVs) affecting these regions have been shown to deregulate expression of relevant genes in a variety of solid cancers. Unfortunately, however, no large studies have ever been performed, in which a large cohort of myeloid malignancies were analyzed using whole genome sequencing (WGS) in an attempt to identify a full spectrum of non-coding alterations, even though its efficacy have been demonstrated in many solid cancers. In this study, we performed WGS in a large cohort of pan-myeloid cancers, in which both coding and non-coding lesions were comprehensively analyzed. Patients and methods A total of 338 cases of myeloid malignancies, including 212 with MDS, 70 with AML, 17 with MDS/MPN, 23 with t-AML/MDS, and 16 with MPN were analyzed with WGS, of which 173 were also analyzed by transcriptome sequencing. Tumor samples were obtained from patients' bone marrow (N=269) or peripheral blood (N=69), while normal controls were derived from buccal smear (N=263) or peripheral T cells (N=75). Sequencing of target panel of 86 genes were performed for all samples. Sequencing data were processed using in-house pipelines, which were optimized for detection of complex structural variations (SVs) and abnormalities in non-coding sequences. Results WGS identified a median of 586,612 single nucleotide variants (SNVs) and 124,863 short indels per genome. NMF-based decomposition of the variants disclosed three major mutational signatures, which were characterized by age-related C>T transitions at CpG sites (Sig. A), C>T transitions at CpT sites (Sig. B), and T>C transitions at ApTpN context (Sig. C). Among these, Sig. C showed a prominent strand bias and corresponds to COSMIC signature 16, which has recently been implicated in alcohol drinking. Significant clustering of SNVs and short indels were interrogated across the genome divided into different window sizes (1Kbp, 10Kbp, 100Kbp) or confining the targets to coding exons and known regulatory regions, such as promoters, enhancers/super enhances, and DNase I hypersensitive sites. Recapitulating previous findings, SNVs in the coding exons were significantly enriched in known drivers, including TP53, TET2, ASXL1, DNMT3A, SF3B1, RUNX1, EZH2, and STAG2. We detected significant enrichment of SNVs in CpG islands, and promoters/enhancers. We also detected a total of 8,242 SVs with a median of 15 SVs/sample, which is more prevalent than expected from conventional karyotype analysis. Focal clusters of complex rearrangements compatible with chromothripsis were found in 8 cases, of which 7 carried biallelic TP53 alterations. NMF-based signature analysis of SVs revealed that large (>1Mb) deletions, inversions, and tandem duplications and translocations are clustered together and were strongly associated with TP53 mutations, while smaller deletions and tandem duplications, but not inversions, constitute another cluster. As expected, FLT3-ITD (N=15) and MLL-PTD (N=12) were among the most frequent SVs. Unexpectedly, in addition to known SVs associated with t(8;21) (RUNX1-RUNX1T1) (N=6) and t(3;21) (RUNX1-MECOM) (n=1) as well as non-synonymous SNVs within the coding exons (N=30), we detected frequent non-coding alterations affecting RUNX1, including SVs (N=15) and SNVs around splicing acceptor sites (N=5), suggesting that RUNX1 was affected by multiple mechanism, where as many as 38% of RUNX1 lesions were explained by non-coding alterations. Other recurrent targets of non-coding lesions included ASXL1, NF1, and ETV6. Conclusions WGS was successfully used to reveal a comprehensive registry of genetic alterations in pan-myeloid cancers. Non-coding alterations affecting known driver genes were more common than expected, suggesting the importance of detecting non-coding abnormalities in diagnostic sequencing. Disclosures Nakagawa: Sumitomo Dainippon Pharma Co., Ltd.: Research Funding. Usuki:Mochida Pharmaceutical: Speakers Bureau; Astellas Pharma Inc.: Research Funding; Sanofi K.K.: Research Funding; GlaxoSmithKline K.K.: Research Funding; Otsuka Pharmaceutical Co., Ltd.: Research Funding; Kyowa Hakko Kirin Co., Ltd.: Research Funding; Daiichi Sankyo: Research Funding; Celgene Corporation: Research Funding, Speakers Bureau; SymBio Pharmaceuticals Limited.: Research Funding; Shire Japan: Research Funding; Janssen Pharmaceutical K.K: Research Funding; Boehringer-Ingelheim Japan: Research Funding; Sumitomo Dainippon Pharma: Research Funding, Speakers Bureau; Pfizer Japan: Research Funding, Speakers Bureau; Novartis: Speakers Bureau; Nippon Shinyaku: Speakers Bureau; Chugai Pharmaceutical: Speakers Bureau; Takeda Pharmaceutical: Speakers Bureau; Ono Pharmaceutical: Speakers Bureau; MSD K.K.: Speakers Bureau. Chiba:Bristol Myers Squibb, Astellas Pharma, Kyowa Hakko Kirin: Research Funding. Miyawaki:Otsuka Pharmaceutical Co., Ltd.: Consultancy; Novartis Pharma KK: Consultancy; Astellas Pharma Inc.: Consultancy.