An Improved Binary Differential Evolution Algorithm to Infer Tumor Phylogenetic Trees

MVSC: A Multi-variation Simulator of Cancer Genome

BACKGROUND

Many forms of variations exist in the genome, which are the main causes of individual phenotypic differences. The detection of variants, especially those located in the tumor genome, still faces many challenges due to the complexity of the genome structure. Thus, the performance assessment of variation detection tools using next-generation sequencing platforms is urgently needed.

METHOD

We have created a software package called the Multi-Variation Simulator of Cancer genomes (MVSC) to simulate common genomic variants, including single nucleotide polymorphisms, small insertion and deletion polymorphisms, and structural variations (SVs), which are analogous to human somatically acquired variations. Three sets of variations embedded in genomic sequences in different periods were dynamically and sequentially simulated one by one.

RESULTS

In cancer genome simulation, complex SVs are important because this type of variation is characteristic of the tumor genome structure. Overlapping variations of different sizes can also coexist in the same genome regions, adding to the complexity of cancer genome architecture. Our results show that MVSC can efficiently simulate a variety of genomic variants that cannot be simulated by existing software packages.

CONCLUSION

The MVSC-simulated variants can be used to assess the performance of existing tools designed to detect SVs in next-generation sequencing data, and we also find that MVSC is memory and time-efficient compared with similar software packages.

Embracing heterogeneity: coalescing the Tree of Life and the future of phylogenomics

Building the Tree of Life (ToL) is a major challenge of modern biology, requiring advances in cyberinfrastructure, data collection, theory, and more. Here, we argue that phylogenomics stands to benefit by embracing the many heterogeneous genomic signals emerging from the first decade of large-scale phylogenetic analysis spawned by high-throughput sequencing (HTS). Such signals include those most commonly encountered in phylogenomic datasets, such as incomplete lineage sorting, but also those reticulate processes emerging with greater frequency, such as recombination and introgression. Here we focus specifically on how phylogenetic methods can accommodate the heterogeneity incurred by such population genetic processes; we do not discuss phylogenetic methods that ignore such processes, such as concatenation or supermatrix approaches or supertrees. We suggest that methods of data acquisition and the types of markers used in phylogenomics will remain restricted until a posteriori methods of marker choice are made possible with routine whole-genome sequencing of taxa of interest. We discuss limitations and potential extensions of a model supporting innovation in phylogenomics today, the multispecies coalescent model (MSC). Macroevolutionary models that use phylogenies, such as character mapping, often ignore the heterogeneity on which building phylogenies increasingly rely and suggest that assimilating such heterogeneity is an important goal moving forward. Finally, we argue that an integrative cyberinfrastructure linking all steps of the process of building the ToL, from specimen acquisition in the field to publication and tracking of phylogenomic data, as well as a culture that values contributors at each step, are essential for progress.