De novo mutational signature discovery in tumor genomes using SparseSignatures.
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ABSTRACT:
SUBMITTER: Lal A
PROVIDER: S-EPMC8270462 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The identification of the mutational processes operating in tumour cells has implications for cancer diagnosis and therapy. These processes leave mutational patterns on the cancer genomes, which are referred to as mutational signatures. Recently, 81 mutational signatures have been inferred using computational algorithms on sequencing data of 23,879 samples. However, these published signatures may not always offer a comprehensive view on the biological processes underlying tumour types that are not included or underrepresented in the reference studies. To circumvent this problem, we designed CaMuS (Cancer Mutational Signatures) to construct de novo signatures while simultaneously fitting publicly available mutational signatures. Furthermore, we propose to estimate signature similarity by comparing probability distributions using the Hellinger distance. We applied CaMuS to infer signatures of mutational processes in poorly studied cancer types. We used whole genome sequencing data of 56 neuroblastoma, thus providing evidence for the versatility of CaMuS. Using simulated data, we compared the performance of CaMuS to sigfit, a recently developed algorithm with comparable inference functionalities. CaMuS and sigfit reconstructed the simulated datasets with similar accuracy; however two main features may argue for CaMuS over sigfit: (i) superior computational performance and (ii) a reliable parameter selection method to avoid spurious signatures.
| S-EPMC7653908 | biostudies-literature
Project description:Current variant discovery approaches often rely on an initial read mapping to the reference sequence. Their effectiveness is limited by the presence of gaps, potential misassemblies, regions of duplicates with a high-sequence similarity and regions of high-sequence divergence in the reference. Also, mapping-based approaches are less sensitive to large INDELs and complex variations and provide little phase information in personal genomes. A few de novo assemblers have been developed to identify variants through direct variant calling from the assembly graph, micro-assembly and whole-genome assembly, but mainly for whole-genome sequencing (WGS) data. We developed SGVar, a de novo assembly workflow for haplotype-based variant discovery from whole-exome sequencing (WES) data. Using simulated human exome data, we compared SGVar with five variation-aware de novo assemblers and with BWA-MEM together with three haplotype- or local de novo assembly-based callers. SGVar outperforms the other assemblers in sensitivity and tolerance of sequencing errors. We recapitulated the findings on whole-genome and exome data from a Utah residents with Northern and Western European ancestry (CEU) trio, showing that SGVar had high sensitivity both in the highly divergent human leukocyte antigen (HLA) region and in non-HLA regions of chromosome 6. In particular, SGVar is robust to sequencing error, k-mer selection, divergence level and coverage depth. Unlike mapping-based approaches, SGVar is capable of resolving long-range phase and identifying large INDELs from WES, more prominently from WGS. We conclude that SGVar represents an ideal platform for WES-based variant discovery in highly divergent regions and across the whole genome.
| S-EPMC6169673 | biostudies-literature
Project description:De novo genome sequence assembly is important both to generate new sequence assemblies for previously uncharacterized genomes and to identify the genome sequence of individuals in a reference-unbiased way. We present memory efficient data structures and algorithms for assembly using the FM-index derived from the compressed Burrows-Wheeler transform, and a new assembler based on these called SGA (String Graph Assembler). We describe algorithms to error-correct, assemble, and scaffold large sets of sequence data. SGA uses the overlap-based string graph model of assembly, unlike most de novo assemblers that rely on de Bruijn graphs, and is simply parallelizable. We demonstrate the error correction and assembly performance of SGA on 1.2 billion sequence reads from a human genome, which we are able to assemble using 54 GB of memory. The resulting contigs are highly accurate and contiguous, while covering 95% of the reference genome (excluding contigs <200 bp in length). Because of the low memory requirements and parallelization without requiring inter-process communication, SGA provides the first practical assembler to our knowledge for a mammalian-sized genome on a low-end computing cluster.
| S-EPMC3290790 | biostudies-literature
Project description:De novo mutations (DNMs), or mutations that appear in an individual despite not being seen in their parents, are an important source of genetic variation whose impact is relevant to studies of human evolution, genetics, and disease. Utilizing high-coverage whole-genome sequencing data as part of the Trans-Omics for Precision Medicine (TOPMed) Program, we called 93,325 single-nucleotide DNMs across 1,465 trios from an array of diverse human populations, and used them to directly estimate and analyze DNM counts, rates, and spectra. We find a significant positive correlation between local recombination rate and local DNM rate, and that DNM rate explains a substantial portion (8.98 to 34.92%, depending on the model) of the genome-wide variation in population-level genetic variation from 41K unrelated TOPMed samples. Genome-wide heterozygosity does correlate with DNM rate, but only explains <1% of variation. While we are underpowered to see small differences, we do not find significant differences in DNM rate between individuals of European, African, and Latino ancestry, nor across ancestrally distinct segments within admixed individuals. However, we did find significantly fewer DNMs in Amish individuals, even when compared with other Europeans, and even after accounting for parental age and sequencing center. Specifically, we found significant reductions in the number of C?A and T?C mutations in the Amish, which seem to underpin their overall reduction in DNMs. Finally, we calculated near-zero estimates of narrow sense heritability (h 2), which suggest that variation in DNM rate is significantly shaped by nonadditive genetic effects and the environment.
| S-EPMC7007577 | biostudies-literature
Project description:Studies of de novo mutations offer great promise to improve our understanding of human disease. After a causal gene has been identified, it is natural to hypothesize that disease relevant mutations accumulate within a sub-sequence of the gene - for example, an exon, a protein domain, or at CpG sites. These assessments are typically qualitative, because we lack methodology to assess the statistical significance of sub-gene mutational burden ultimately to infer disease-relevant biology.To address this issue, we present a generalized algorithm to grade the significance of de novo mutational burden within a gene ascertained from affected probands, based on our model for mutation rate informed by local sequence context.We applied our approach to 268 newly identified de novo germline mutations by re-sequencing the coding exons and flanking intronic regions of RB1 in 642 sporadic, bilateral probands affected with retinoblastoma (RB). We confirm enrichment of loss-of-function mutations, but demonstrate that previously noted 'hotspots' of nonsense mutations in RB1 are compatible with the elevated mutation rates expected at CpG sites, refuting a RB specific pathogenic mechanism. Our approach demonstrates an enrichment of splice-site donor mutations of exon 6 and 12 but depletion at exon 5, indicative of previously unappreciated heterogeneity in penetrance within this class of substitution. We demonstrate the enrichment of missense mutations to the pocket domain of RB1, which contains the known Arg661Trp low-penetrance mutation.Our approach is generalizable to any phenotype, and affirms the importance of statistical interpretation of de novo mutations found in human genomes.
| S-EPMC5307739 | biostudies-literature
Project description:BackgroundDe novo genome assembly using NGS data remains a computation-intensive task especially for large genomes. In practice, efficiency is often a primary concern and favors using a more efficient assembler like SOAPdenovo2. Yet SOAPdenovo2, based on de Bruijn graph, fails to take full advantage of longer NGS reads (say, 150 bp to 250 bp from Illumina HiSeq and MiSeq). Assemblers that are based on string graphs (e.g., SGA), though less popular and also very slow, are more favorable for longer reads.MethodsThis paper shows a new de novo assembler called BASE. It enhances the classic seed-extension approach by indexing the reads efficiently to generate adaptive seeds that have high probability to appear uniquely in the genome. Such seeds form the basis for BASE to build extension trees and then to use reverse validation to remove the branches based on read coverage and paired-end information, resulting in high-quality consensus sequences of reads sharing the seeds. Such consensus sequences are then extended to contigs.ResultsExperiments on two bacteria and four human datasets shows the advantage of BASE in both contig quality and speed in dealing with longer reads. In the experiment on bacteria, two datasets with read length of 100 bp and 250 bp were used.. Especially for the 250 bp dataset, BASE gives much better quality than SOAPdenovo2 and SGA and is simlilar to SPAdes. Regarding speed, BASE is consistently a few times faster than SPAdes and SGA, but still slower than SOAPdenovo2. BASE and Soapdenov2 are further compared using human datasets with read length 100 bp, 150 bp and 250 bp. BASE shows a higher N50 for all datasets, while the improvement becomes more significant when read length reaches 250 bp. Besides, BASE is more-meory efficent than SOAPdenovo2 when sequencing data with error rate.ConclusionsBASE is a practically efficient tool for constructing contig, with significant improvement in quality for long NGS reads. It is relatively easy to extend BASE to include scaffolding.
| S-EPMC5009518 | biostudies-literature
Project description:Assembling a large genome using next generation sequencing reads requires large computer memory and a long execution time. To reduce these requirements, we propose an extension-based assembler, called JR-Assembler, where J and R stand for "jumping" extension and read "remapping." First, it uses the read count to select good quality reads as seeds. Second, it extends each seed by a whole-read extension process, which expedites the extension process and can jump over short repeats. Third, it uses a dynamic back trimming process to avoid extension termination due to sequencing errors. Fourth, it remaps reads to each assembled sequence, and if an assembly error occurs by the presence of a repeat, it breaks the contig at the repeat boundaries. Fifth, it applies a less stringent extension criterion to connect low-coverage regions. Finally, it merges contigs by unused reads. An extensive comparison of JR-Assembler with current assemblers using datasets from small, medium, and large genomes shows that JR-Assembler achieves a better or comparable overall assembly quality and requires lower memory use and less central processing unit time, especially for large genomes. Finally, a simulation study shows that JR-Assembler achieves a superior performance on memory use and central processing unit time than most current assemblers when the read length is 150 bp or longer, indicating that the advantages of JR-Assembler over current assemblers will increase as the read length increases with advances in next generation sequencing technology.
| S-EPMC3767511 | biostudies-literature
Project description:Leptosphaeria maculans and Leptosphaeria biglobosa are ascomycete phytopathogens of Brassica napus (oilseed rape, canola). Here we report the complete sequence of three Leptosphaeria genomes (L. maculans JN3, L. maculans Nz-T4 and L. biglobosa G12-14). Nz-T4 and G12-14 genome assemblies were generated de novo and the reference JN3 genome assembly was improved using Oxford Nanopore MinION reads. The new assembly of L. biglobosa showed the existence of AT rich regions and pointed to a genome compartmentalization previously unsuspected following Illumina sequencing. Moreover nanopore sequencing allowed us to generate a chromosome-level assembly for the L. maculans reference isolate, JN3. The genome annotation was supported by integrating conserved proteins and RNA sequencing from Leptosphaeria-infected samples. The newly produced high-quality assemblies and annotations of those three Leptosphaeria genomes will allow further studies, notably focused on the tripartite interaction between L. maculans, L. biglobosa and oilseed rape. The discovery of as yet unknown effectors will notably allow progress in B. napus breeding towards L. maculans resistance.
| S-EPMC6219404 | biostudies-literature
Project description:BackgroundTraditionally, mutational burden and mutational signatures have been assessed by tumor-normal pair DNA sequencing. The requirement of having both normal and tumor samples is not always feasible from a clinical perspective, and led us to investigate the efficacy of using RNA sequencing of only the tumor sample to determine the mutational burden and signatures, and subsequently molecular cause of the cancer. The potential advantages include reducing the cost of testing, and simultaneously providing information on the gene expression profile and gene fusions present in the tumor.ResultsIn this study, we devised supervised and unsupervised learning methods to determine mutational signatures from tumor RNA-seq data. As applications, we applied the methods to a training set of 587 TCGA uterine cancer RNA-seq samples, and examined in an independent testing set of 521 TCGA colorectal cancer RNA-seq samples. Both diseases are known associated with microsatellite instable high (MSI-H) and driver defects in DNA polymerase ɛ (POLɛ). From RNA-seq called variants, we found majority (> 95%) are likely germline variants, leading to C > T enriched germline variants (dbSNP) widely applicable in tumor and normal RNA-seq samples. We found significant associations between RNA-derived mutational burdens and MSI/POLɛ status, and insignificant relationship between RNA-seq total coverage and derived mutational burdens. Additionally we found that over 80% of variants could be explained by using the COSMIC mutational signature-5, -6 and -10, which are implicated in natural aging, MSI-H, and POLɛ, respectively. For classifying tumor type, within UCEC we achieved a recall of 0.56 and 0.78, and specificity of 0.66 and 0.99 for MSI and POLɛ respectively. By applying learnt RNA signatures from UCEC to COAD, we were able to improve our classification of both MSI and POLɛ.ConclusionsTaken together, our work provides a novel method to detect RNA-seq derived mutational signatures with effective procedures to remove likely germline variants. It can leads to accurate classification of underlying driving mechanisms of DNA damage deficiency.
| S-EPMC7923324 | biostudies-literature
Project description:Despite its high heritability, a large fraction of individuals with schizophrenia do not have a family history of the disease (sporadic cases). Here we examined the possibility that rare de novo protein-altering mutations contribute to the genetic component of schizophrenia by sequencing the exomes of 53 sporadic cases, 22 unaffected controls and their parents. We identified 40 de novo mutations in 27 cases affecting 40 genes, including a potentially disruptive mutation in DGCR2, a gene located in the schizophrenia-predisposing 22q11.2 microdeletion region. A comparison to rare inherited variants indicated that the identified de novo mutations show a large excess of non-synonymous changes in schizophrenia cases, as well as a greater potential to affect protein structure and function. Our analyses suggest a major role for de novo mutations in schizophrenia as well as a large mutational target, which together provide a plausible explanation for the high global incidence and persistence of the disease.
| S-EPMC3196550 | biostudies-literature