An introduction to scripting in Ruby for biologists

<p>Abstract</p> <p>The Ruby programming language has a lot to offer to any scientist with electronic data to process. Not only is the initial learning curve very shallow, but its reflection and meta-programming capabilities allow for the rapid creation of relatively complex applications while still keeping the code short and readable. This paper provides a gentle introduction to this scripting language for researchers without formal informatics training such as many wet-lab scientists. We hope this will provide such researchers an idea of how powerful a tool Ruby can be for their data management tasks and encourage them to learn more about it.</p

Comparative genomics of tadpole shrimps (Crustacea, Branchiopoda, Notostraca): Dynamic genome evolution against the backdrop of morphological stasis

This analysis presents five genome assemblies of four Notostraca taxa. Notostraca origin dates to the Permian/Upper Devonian and the extant forms show a striking morphological similarity to fossil taxa. The comparison of sequenced genomes with other Branchiopoda genomes shows that, despite the morphological stasis, Notostraca share a dynamic genome evolution with high turnover for gene families' expansion/contraction and a transposable elements content comparable to other branchiopods. While Notostraca substitutions rate appears similar or lower in comparison to other branchiopods, a subset of genes shows a faster evolutionary pace, highlighting the difficulty of generalizing about genomic stasis versus dynamism. Moreover, we found that the variation of Triops cancriformis transposable elements content appeared linked to reproductive strategies, in line with theoretical expectations. Overall, besides providing new genomic resources for the study of these organisms, which appear relevant for their ecology and evolution, we also confirmed the decoupling of morphological and molecular evolution

Effective detection of rare variants in pooled DNA samples using Cross-pool tailcurve analysis

Sequencing targeted DNA regions in large samples is necessary to discover the full spectrum of rare variants. We report an effective Illumina sequencing strategy utilizing pooled samples with novel quality (Srfim) and filtering (SERVIC4E) algorithms. We sequenced 24 exons in two cohorts of 480 samples each, identifying 47 coding variants, including 30 present once per cohort. Validation by Sanger sequencing revealed an excellent combination of sensitivity and specificity for variant detection in pooled samples of both cohorts as compared to publicly available algorithms

A primary breast cancer with distinct foci of estrogen receptor-alpha positive and negative cells derived from the same clonal origin as revealed by whole exome sequencing

© 2018, Springer Science+Business Media, LLC, part of Springer Nature. Background/purpose: Tumor heterogeneity is a now well-recognized phenomenon that can affect the classification, prognosis and treatment of human cancers. Heterogeneity is often described in primary breast cancers based upon histologic subtypes, hormone- and HER2-receptor status, and immunolabeling for various markers, which can be seen within a single tumor as mixed cellular populations, or as separate discrete foci. Experimental design/methods: Here, we present a case report of a patient’s primary breast cancer that had two separate but adjacent histologic components, one that was estrogen receptor (ER) positive, and the other ER negative. Each component was subjected to whole exome sequencing and compared for gene identity to determine clonal origin. Results: Using prior bioinformatic tools, we demonstrated that both the ER positive and negative components shared many variants, including passenger and driver alterations. Copy number variations also supported the two components were derived from a single common clone. Conclusions: These analyses strongly suggest that the two ER components of this patient’s breast cancer were derived from the same clonal origin. Our results have implications for the evolution of breast cancers with mixed histologies, and how they might be best managed for optimal therapy

Centroacinar cells are progenitors that contribute to endocrine pancreas regeneration

Diabetes is associated with a paucity of insulin-producing β-cells. With the goal of finding therapeutic routes to treat diabetes, we aim to find molecular and cellular mechanisms involved in β-cell neogenesis and regeneration. To facilitate discovery of such mechanisms, we use a vertebrate organism where pancreatic cells readily regenerate. The larval zebrafish pancreas contains Notch-responsive progenitors that during development give rise to adult ductal, endocrine, and centroacinar cells (CACs). Adult CACs are also Notch responsive and are morphologically similar to their larval predecessors. To test our hypothesis that adult CACs are also progenitors, we took two complementary approaches: 1) We established the transcriptome for adult CACs. Using gene ontology, transgenic lines, and in situ hybridization, we found that the CAC transcriptome is enriched for progenitor markers. 2) Using lineage tracing, we demonstrated that CACs do form new endocrine cells after β-cell ablation or partial pancreatectomy. We concluded that CACs and their larval predecessors are the same cell type and represent an opportune model to study both β-cell neogenesis and β-cell regeneration. Furthermore, we show that in cftr loss-of-function mutants, there is a deficiency of larval CACs, providing a possible explanation for pancreatic complications associated with cystic fibrosis

Cellular Resolution Maps of X Chromosome Inactivation: Implications for Neural Development, Function, and Disease

SummaryFemale eutherian mammals use X chromosome inactivation (XCI) to epigenetically regulate gene expression from ∼4% of the genome. To quantitatively map the topography of XCI for defined cell types at single cell resolution, we have generated female mice that carry X-linked, Cre-activated, and nuclear-localized fluorescent reporters—GFP on one X chromosome and tdTomato on the other. Using these reporters in combination with different Cre drivers, we have defined the topographies of XCI mosaicism for multiple CNS cell types and of retinal vascular dysfunction in a model of Norrie disease. Depending on cell type, fluctuations in the XCI mosaic are observed over a wide range of spatial scales, from neighboring cells to left versus right sides of the body. These data imply a major role for XCI in generating female-specific, genetically directed, stochastic diversity in eutherian mammals on spatial scales that would be predicted to affect CNS function within and between individuals

A quasi classical approach to electron impact ionization

A quasi classical approximation to quantum mechanical scattering in the Moeller formalism is developed. While keeping the numerical advantage of a standard Classical--Trajectory--Monte--Carlo calculation, our approach is no longer restricted to use stationary initial distributions. This allows one to improve the results by using better suited initial phase space distributions than the microcanonical one and to gain insight into the collision mechanism by studying the influence of different initial distributions on the cross section. A comprehensive account of results for single, double and triple differential cross sections for atomic hydrogen will be given, in comparison with experiment and other theories.Comment: 21 pages, 10 figures, submitted to J Phys

Statistical expression deconvolution from mixed tissue samples

Motivation: Global expression patterns within cells are used for purposes ranging from the identification of disease biomarkers to basic understanding of cellular processes. Unfortunately, tissue samples used in cancer studies are usually composed of multiple cell types and the non-cancerous portions can significantly affect expression profiles. This severely limits the conclusions that can be made about the specificity of gene expression in the cell-type of interest. However, statistical analysis can be used to identify differentially expressed genes that are related to the biological question being studied

Team level identification predicts perceived and actual team performance: longitudinal multilevel analyses with sports teams

Social identification and team performance literatures typically focus on the relationship between individual differences in identification and individual-level performance. By using a longitudinal multilevel approach, involving 369 members of 45 sports teams across England and Italy, we compared how team-level and individual-level variance in social identification together predicted team and individual performance outcomes. As hypothesised, team-level variance in identification significantly predicted subsequent levels of both perceived and actual team performance in cross-lagged analyses. Conversely, individual-level variance in identification did not significantly predict subsequent levels of perceived individual performance. These findings support recent calls for social identity to be considered a multilevel construct and highlight the influence of group-level social identification on group-level processes and outcomes, over and above its individual-level effects