Bio::NEXUS: a Perl API for the NEXUS format for comparative biological data

<p>Abstract</p> <p>Background</p> <p>Evolutionary analysis provides a formal framework for comparative analysis of genomic and other data. In evolutionary analysis, observed data are treated as the terminal states of characters that have evolved (via transitions between states) along the branches of a tree. The NEXUS standard of Maddison, et al. (1997; <it>Syst. Biol</it>. 46: 590–621) provides a portable, expressive and flexible text format for representing character-state data and trees. However, due to its complexity, NEXUS is not well supported by software and is not easily accessible to bioinformatics users and developers.</p> <p>Results</p> <p>Bio::NEXUS is an application programming interface (API) implemented in Perl, available from CPAN and SourceForge. The 22 Bio::NEXUS modules define 351 methods in 4229 lines of code, with 2706 lines of POD (Plain Old Documentation). Bio::NEXUS provides an object-oriented interface to reading, writing and manipulating the contents of NEXUS files. It closely follows the extensive explanation of the NEXUS format provided by Maddison et al., supplemented with a few extensions such as support for the NHX (New Hampshire Extended) tree format.</p> <p>Conclusion</p> <p>In spite of some limitations owing to the complexity of NEXUS files and the lack of a formal grammar, NEXUS will continue to be useful for years to come. Bio::NEXUS provides a user-friendly API for NEXUS supplemented with an extensive set of methods for manipulations such as re-rooting trees and selecting subsets of data. Bio::NEXUS can be used as glue code for connecting existing software that uses NEXUS, or as a framework for new applications.</p

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

High recombination rates and hotspots in a Plasmodium falciparum genetic cross

Using the universal P2/P8 primers, we were able to obtain the gene segments of chromo-helicase-DNA binding protein (CHD)-Z and CHD-W from ten species of ardeid birds including Chinese egret (Egretta eulophotes), little egret (E. garzetta), eastern reef egret (E. sacra), great egret (Ardea alba), grey heron (A. cinerea), Chinese pond-heron (Ardeola bacchus), cattle egret (Bubulcus ibis), black-crowned night-heron (Nycticorax nycticorax), cinnamon bittern (Ixobrychus cinnamomeus) and yellow bittern (I. sinensis). Based on conserved regions inside the P2/P8-derived sequences, we designed new PCR primers for sex identification in these ardeid species. Using agarose gel electrophoresis, the PCR products showed two bands for females (140 bp derived from CHD-W and the other 250 bp from CHD-ZW), whereas the males showed only the 250 bp band. The results indicated that our new primers could be used for accurate and convenient sex identification in ardeid species.National Natural Science Foundation of China[30970380, 40876077]; Fujian Natural Science Foundation of China[2008S0007, 2009J01195

Androgen Receptor Signaling Regulates DNA Repair in Prostate Cancers

We demonstrate that the androgen receptor (AR) regulates a transcriptional program of DNA repair genes that promotes prostate cancer radioresistance, providing a potential mechanism by which androgen deprivation therapy (ADT) synergizes with ionizing radiation (IR). Using a model of castration-resistant prostate cancer, we show that second-generation antiandrogen therapy results in downregulation of DNA repair genes. Next, we demonstrate that primary prostate cancers display a significant spectrum of AR transcriptional output which correlates with expression of a set of DNA repair genes. Employing RNA-seq and ChIP-seq, we define which of these DNA repair genes are both induced by androgen and represent direct AR targets. We establish that prostate cancer cells treated with IR plus androgen demonstrate enhanced DNA repair and decreased DNA damage and furthermore that antiandrogen treatment causes increased DNA damage and decreased clonogenic survival. Finally, we demonstrate that antiandrogen treatment results in decreased classical non-homologous end joining

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

Analyses of protein domains and genomic elements using bioinformatics approaches

Ph.DDOCTOR OF PHILOSOPH

An automated sample allocation system for multiplexed Next-Generation Sequencing

The Illumina Next-Generation Sequencing (NGS) technology enables us to sequence several samples together. This is made possible by adding unique barcode to each sample sequenced. The multiplexing of the samples should be done in such a way that there is not barcode clash and samples loaded into the flowcell should provide high sequencing throughput. In addition, when there is a pool of libraries, the samples with higher priority should be given preference for selection. Currently, there is no program available that can prepare an optimal run plan for the Illumina sequencing runs. The sequencing team spends several manual hours to generate a run plan. Some of the complicated run plans can take up to 24 hours to prepare. Despite spending several hours to prepare run plan it can still have errors and be non-optimal. In this study, we present an automated system to generate run plan for a given sequencing run. Our system utilizes constraint optimization framework to make optimal run plan. We use MiniZinc software to develop the constraint optimization framework. Our method takes input library barcode sequence, data amount needed, priority and sample identifier to generate the optimal run plan. The method is programmed to maximize the inclusion of samples per lane and give priority to sample with high priority. The model provides with an optimal plan for 80 libraries within 18 seconds. In addition to several advantages we observed that this method provides better utilization of flow-cell to provide maximum throughput. This system was widely validated on previous runs. The system is available as web-based tool and we are in process to integrate it with our Laboratory Information Management System (LIMS)

Statistical model based gender prediction for targeted NGS clinical panels

In the NGS based clinical diagnosis, the gender information plays key roles such as Mendelian inheritance study, clerical or sampling error identification, quality control over clinical samples (e.g., transfusion performed blood samples). For this purpose, the gender determination using the sequenced NGS targeted panel data is crucial need irrespective of gender information from Test Requisition Form (TRF) in clinical diagnosis. But, sample impurities and its quantity, coverage over sex chromosomes in targeted panels and depth over sex chromosomes are limiting factors for the targeted NGS panels. Three common approaches such as genotype (Hom/Het) composition in ChrX, read depth proportion between ChrX vs ChrY and ChrX vs selected autosomal chromosome are being used for gender determination. As an improvement from MedGenome’s current gender prediction (based on “genotype composition in ChrX”) approach, we have developed a new statistical model based approach for targeted panels which can be used to predict gender with increased sensitivity especially for captured NGS panels such as Whole Exome and Clinical Exome panels. In this new approach, instead of considering a single approach for gender prediction, we included three approaches together with built statistical reference model. The model has been built with a set of 700 control clinical dataset (sequenced in NGS targeted panels) as training data. The clinical data such as confirmed gender from clinician on TRF (as response variable), genotype proportion in ChrX, depth ratio between ChrX and ChrY and depth ratio between ChrX and Chr17 (as predictor variables) have been used as training criteria. A multi-regression model has been developed for each targeted panel in MedGenome. The prediction score of being male/female (with respect to the built reference model) gives the confidence on the gender of clinical dataset. The reference test dataset are being used to test the model. The sensitivity on predicting the gender has been increased from the current “genotype composition in ChrX” based approach. In addition, the prediction score given by the model can be used to evaluate the quality of clinical dataset. The higher prediction score towards its respective gender indicates the higher quality of sequenced data