Biology subjects

Wintersinger, J.

Publications and source records attributed to Wintersinger, J..

4 recordsLinked to original sources

bioRxiv2018

One species, two genomes: A critical assessment of inter isolate variation and identification of assembly incongruence in Haemonchus contortus

BackgroundNumerous quality issues may compromise genomic datas representation of its underlying organism. In this study, we compared two genomes published by different research groups for the parasitic nematode Haemonchus contortus, corresponding to divergent isolates. We analyzed differences between the genomes, attempting to ascertain which were attributable to legitimate biological differences, and which to technical error in one or both genomes.\n\nResultsWe found discrepancies between the H. contortus genomes in both assembly and annotation. The genomes differed in representation of genes that are highly conserved across eukaryotes, with clear evidence of misassembly underlying conserved genes missing from one genome or the other. Only 45% of genes in one genome were orthologous to genes in the other genome, with one genome exhibiting almost as much orthology to C. elegans as its counterpart H. contortus strain. The two genomes differed substantially in probable causes underlying this unexpectedly low orthology. One genome included many more inparalogues than the other, and more frequently assembled inparalogues together on the same portions of contiguous sequence. It also exhibited cases of better-conserved gene position relative to C. elegans.\n\nConclusionThe discrepancies between the two genomes far exceeded those expected as a consequence of biological differences between the two H. contortus isolates. This implies substantial quality issues in one or both genomes, suggesting that researchers must exercise caution when using genomic data for newly sequenced species.

genomics↗

bioRxiv2018

Portraits of genetic intra-tumour heterogeneity and subclonal selection across cancer types

Intra-tumor heterogeneity (ITH) is a mechanism of therapeutic resistance and therefore an important clinical challenge. However, the extent, origin and drivers of ITH across cancer types are poorly understood. To address this question, we extensively characterize ITH across whole-genome sequences of 2,658 cancer samples, spanning 38 cancer types. Nearly all informative samples (95.1%) contain evidence of distinct subclonal expansions, with frequent branching relationships between subclones. We observe positive selection of subclonal driver mutations across most cancer types, and identify cancer type specific subclonal patterns of driver gene mutations, fusions, structural variants and copy-number alterations, as well as dynamic changes in mutational processes between subclonal expansions. Our results underline the importance of ITH and its drivers in tumor evolution, and provide an unprecedented pan-cancer resource of comprehensively annotated subclonal events from whole-genome sequencing data.

cancer biology↗

bioRxiv2018

TrackSig: reconstructing evolutionary trajectories of mutation signature exposure

We present a new method, TrackSig, to estimate the evolutionary trajectories of signatures of different somatic mutational processes from DNA sequencing data from a single, bulk tumour sample. TrackSig uses probability distributions over mutation types, called mutational signatures, to represent different mutational processes and detects the changes in the signature activity using an optimal segmentation algorithm that groups somatic mutations based on their estimated cancer cellular fraction (CCF) and their mutation type (e.g. CAG->CTG). We use two different simulation frameworks to assess both TrackSigs reconstruction accuracy and its robustness to violations of its assumptions, as well as to compare it to a baseline approach. We find 2-4% median error in reconstructing the signature activities on simulations with varying difficulty with one to three subclones at an average depth of 30x. The size and the direction of the activity change is consistent in 83% and 95% of cases respectively. There were an average of 0.02 missed and 0.12 false positive subclones per sample. In our simulations, grouping mutations by mutation type (TrackSig), rather than by clustering CCF (baseline strategy), performs better at estimating signature activities and at identifying subclonal populations in the complex scenarios like branching, CNA gain, violation of infinite site assumption, and the inclusion of neutrally evolving mutations. TrackSig is open source software, freely available at https://github.com/morrislab/TrackSig.

bioinformatics↗

bioRxiv2017

The evolutionary history of 2,658 cancers

Cancer develops through a process of somatic evolution. Here, we use whole-genome sequencing of 2,778 tumour samples from 2,658 donors to reconstruct the life history, evolution of mutational processes, and driver mutation sequences of 39 cancer types. The early phases of oncogenesis are driven by point mutations in a small set of driver genes, often including biallelic inactivation of tumour suppressors. Early oncogenesis is also characterised by specific copy number gains, such as trisomy 7 in glioblastoma or isochromosome 17q in medulloblastoma. By contrast, increased genomic instability, a nearly four-fold diversification of driver genes, and an acceleration of point mutation processes are features of later stages. Copy-number alterations often occur in mitotic crises leading to simultaneous gains of multiple chromosomal segments. Timing analysis suggests that driver mutations often precede diagnosis by many years, and in some cases decades, providing a window of opportunity for early cancer detection.

cancer biology↗