NeoFuse: predicting fusion neoantigens from RNA sequencing data.

SUMMARY: Gene fusions can generate immunogenic neoantigens that mediate anticancer immune responses. However, their computational prediction from RNA sequencing (RNA-seq) data requires deep bioinformatics expertise to assembly a computational workflow covering the prediction of: fusion transcripts, their translated proteins and peptides, Human Leukocyte Antigen (HLA) types, and peptide-HLA binding affinity. Here, we present NeoFuse, a computational pipeline for the prediction of fusion neoantigens from tumor RNA-seq data. NeoFuse can be applied to cancer patients' RNA-seq data to identify fusion neoantigens that might expand the repertoire of suitable targets for immunotherapy. AVAILABILITY AND IMPLEMENTATION: NeoFuse source code and documentation are available under GPLv3 license at https://icbi.i-med.ac.at/NeoFuse/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Scirpy: a Scanpy extension for analyzing single-cell T-cell receptor-sequencing data.

SUMMARY: Advances in single-cell technologies have enabled the investigation of T-cell phenotypes and repertoires at unprecedented resolution and scale. Bioinformatic methods for the efficient analysis of these large-scale datasets are instrumental for advancing our understanding of adaptive immune responses. However, while well-established solutions are accessible for the processing of single-cell transcriptomes, no streamlined pipelines are available for the comprehensive characterization of T-cell receptors. Here, we propose single-cell immune repertoires in Python (Scirpy), a scalable Python toolkit that provides simplified access to the analysis and visualization of immune repertoires from single cells and seamless integration with transcriptomic data. AVAILABILITY AND IMPLEMENTATION: Scirpy source code and documentation are available at https://github.com/icbi-lab/scirpy. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Evolutionary history of an Alpine Archaeognath (Machilis pallida): Insights from different variant.

Reconstruction of species histories is a central aspect of evolutionary biology. Patterns of genetic variation within and among populations can be leveraged to elucidate evolutionary processes and demographic histories. However, interpreting genetic signatures and unraveling the contributing processes can be challenging, in particular for non-model organisms with complex reproductive modes and genome organization. One way forward is the combined consideration of patterns revealed by different molecular markers (nuclear vs. mitochondrial) and types of variants (common vs. rare) that differ in their age, mode, and rate of evolution. Here, we applied this approach to RNAseq data generated for Machilis pallida (Archaeognatha), an Alpine jumping bristletail considered parthenogenetic and triploid. We generated de novo transcriptome and mitochondrial assemblies to obtain high-density data to investigate patterns of mitochondrial and common and rare nuclear variation in 17 M. pallida individuals sampled from all known populations. We find that the different variant types capture distinct aspects of the evolutionary history and discuss the observed patterns in the context of parthenogenesis, polyploidy, and survival during glaciation. This study highlights the potential of different variant types to gain insights into evolutionary scenarios even from challenging but often available data and the suitability of M. pallida and the genus Machilis as a study system for the evolution of sexual strategies and polyploidization during environmental change. We also emphasize the need for further research which will be stimulated and facilitated by these newly generated resources and insights.

Major range loss predicted from lack of heat adaptability in an alpine Drosophila species.

Climate warming is threatening biodiversity worldwide. Climate specialists such as alpine species are especially likely to be vulnerable. Adaptation by rapid evolution is the only long-term option for survival of many species, but the adaptive evolutionary potential of heat resistance has not been assessed in an alpine invertebrate. Here, we show that the alpine fly Drosophila nigrosparsa cannot readily adapt to heat stress. Heat-exposed flies from a regime with increased ambient temperature and a regime with increased temperature plus artificial selection for heat tolerance were less heat tolerant than the control group. Increased ambient temperature affected negatively both fitness and competitiveness. Ecological niche models predicted the loss of three quarters of the climatically habitable areas of this fly by the end of this century. Our findings suggest that, alongside with other climate specialists, species from mountainous regions are highly vulnerable to climate warming and unlikely to adapt through evolutionary genetic changes.