PaperPlayer biorxiv bioinformatics

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.23.212787v1?rss=1

Authors: Espinoza, D. A., Mortlock, R. D., Koelle, S. J., Wu, C., Dunbar, C. E.

Abstract:

Clonal tracking methods provide quantitative insights into the cellular output of genetically labelled progenitor cells across time and cellular compartments. However, the absence of a toolbox by which to interrogate these data has precluded the development of standardized analytical frameworks within the field. Thus, we developed barcodetrackR, an R package that provides users with tools for the analysis and visualization of clonal dynamics across time and cellular compartments in clonal tracking experiments. Here, we demonstrate the utility of barcodetrackR in exploring longitudinal clonal patterns and lineage relationships in the context of clonal tracking studies of hematopoietic stem and progenitor cells.

Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.23.217976v1?rss=1

Authors: Bigio, B., Seeleuthner, Y., Kerner, G., Migaud, M., Rosain, J., Boisson, B., Nasca, C., Puel, A., Bustamante, J., Casanova, J.-L., Abel, L., Cobat, A.

Abstract:

The detection of copy number variations (CNVs) in whole-exome sequencing (WES) data is important, as CNVs may underlie a number of human genetic disorders. The recently developed HMZDelFinder algorithm can detect rare homozygous and hemizygous (HMZ) deletions in WES data more effectively than other widely used tools. Here, we present HMZDelFinder_opt, an approach that outperforms HMZDelFinder for the detection of HMZ deletions, including partial exon deletions in particular, in typical laboratory cohorts that are generated over time under different experimental conditions. We show that using an optimized reference control set of WES data, based on a PCA-derived Euclidean distance for coverage, strongly improves the detection of HMZ deletions both in real patients carrying validated disease-causing deletions and in simulated data. Furthermore, we develop a sliding window approach enabling HMZDelFinder-opt to identify HMZ partial deletions of exons that are otherwise undiscovered by HMZDelFinder. HMZDelFinder_opt is a timely and powerful approach for detecting HMZ deletions, particularly partial exon deletions, in laboratory cohorts, which are typically heterogeneous.

Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.23.216507v1?rss=1

Authors: Hansen, J., Sealfon, R., Menon, R., Eadon, M. T., Lake, B. B., Steck, B., Dobi, D., Parikh, S., Sidgel, T. K., Alexandrov, T., Schroeder, A., Otto, E. A., Anderton, C. R., Barwinska, D., Zheng, G., Rose, M. P., Shapiro, J. P., Velickovic, D., Pamreddy, A., Winfree, S., He, Y., de Boer, I. H., Hodgin, J. B., Nair, A., Sharma, K., Sarwal, M., Zhang, K., Himmelfarb, J., Laszik, Z., Rovin, B., Dagher, P. C., He, J. C., El-Achkar, T. M., Jain, S., Troyanskaya, O. G., Kretzler, M., Iyengar, R., Azeloglu, E. U.

Abstract:

The Kidney Precision Medicine Project (KPMP) plans to construct a spatially specified tissue atlas of the human kidney at a cellular resolution with near comprehensive molecular details. The atlas will have maps of healthy, acute kidney injury and chronic kidney disease tissues. To construct such maps, we integrate different data sets that profile mRNAs, proteins and metabolites collected by five KPMP Tissue Interrogation Sites. Here, we describe a set of hierarchical analytical methods to process, combine, and harmonize single-cell, single-nucleus and subsegmental laser microdissection (LMD) transcriptomics with LMD and near single-cell proteomics, 3-D nondestructive and immunofluorescence-based Codex imaging and spatial metabolomics datasets. We use nephrectomy, healthy living donor and surveillance transplant biopsy tissues to create a harmonized reference tissue map. Our results demonstrate that different assays produce reliable and coherent identification of cell types and tissue subsegments. They further show that the molecular profiles and pathways are partially overlapping yet complementary for cell type-specific and subsegmental physiological processes. Focusing on the proximal tubules, we find that our integrated systems biology-based analyses identify different subtypes of tubular cells with potential for different levels of lipid oxidation and energy generation. Integration of our omics data with pathways from the literature, enables us to construct predictive computational models to develop a smart kidney atlas. These integrated models can describe physiological capabilities of the tissues based on the underlying cell types and pathways in health and disease.

Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.23.218487v1?rss=1

Authors: Liu, R., Krishnan, A.

Abstract:

Learning low-dimensional representations (embeddings) of nodes in large graphs is key to applying machine learning on massive biological networks. Node2vec is the most widely used method for node embedding. However, its original Python and C++ implementations scale poorly with network density, failing for dense biological networks with hundreds of millions of edges. We have developed PecanPy, a new Python implementation of node2vec that uses cache-optimized compact graph data structures and precomputing/parallelization to result in fast, high-quality node embeddings for biological networks of all sizes and densities. PecanPy software and documentation are available at https://github.com/krishnanlab/pecanpy.

Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.23.218552v1?rss=1

Authors: van der Velde, A. G., Fan, K., Tsuji, J., Moore, J. E., Purcaro, M., Pratt, H., Weng, Z.

Abstract:

The morphologically and functionally distinct cell types of a multicellular organism are maintained by epigenomes and gene expression programs. Phase III of the ENCODE Project profiled 66 mouse epigenomes across twelve tissues at daily intervals from embryonic day 10.5 to birth. Applying the ChromHMM algorithm to these epigenomes, we annotated eighteen chromatin states with characteristics of promoters, enhancers, transcribed regions, repressed regions, and quiescent regions throughout the developmental time course. Our integrative analyses delineate the tissue specificity and developmental trajectory of the loci in these chromatin states. Approximately 0.3% of each epigenome is assigned to a bivalent chromatin state, which harbors both active marks and the repressive mark H3K27me3. Highly evolutionarily conserved, these loci are enriched in silencers bound by Polycomb Repressive Complex proteins and the transcription start sites of their silenced target genes. This collection of chromatin state assignments provides a useful resource for studying mammalian development.

Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.24.215889v1?rss=1

Authors: Matlock, W., Chau, K. K., AbuOun, M., Stubberfield, E., Barker, L., Kavanagh, J., Pickford, H., Gilson, D., Smith, R. P., Gweon, H. S., Hoosdally, S. J., Swann, J., Sebra, R., Bailey, M. J., Peto, T. E. A., Crook, D. W., Anjum, M. F., Read, D. S., Walker, A. S., Stoesser, N., Shaw, L. P., REHAB Consortium

Abstract:

IncF plasmids are diverse and of great clinical significance, often carrying genes conferring antimicrobial resistance (AMR) such as extended-spectrum {beta}-lactamases, particularly in Enterobacteriaceae. Organising this plasmid diversity is challenging, and current knowledge is largely based on plasmids from clinical settings. Here, we present a network community analysis of a large survey of IncF plasmids from environmental (influent, effluent, and upstream/downstream waterways surrounding wastewater treatment works) and livestock settings. We use a tractable and scalable methodology to examine the relationship between plasmid metadata and network communities. This reveals how niche (sampling compartment and host genera) partition and shape plasmid diversity. We also perform pangenome-style analyses on network communities. We show that such communities define unique combinations of core genes, with limited overlap. Building plasmid phylogenies based on alignments of these core genes, we demonstrate that plasmid accessory function is closely linked to core gene content. Taken together, our results suggest that stable IncF plasmid backbone structures can persist in environmental settings while allowing dramatic variation in accessory gene content that may be linked to niche adaptation. The recent association of IncF plasmids with AMR likely reflects their suitability for rapid niche adaptation.

Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.23.218529v1?rss=1

Authors: Banerjee, S., Majumder, K., Gutierrez, G. J., Gupta, D., Mittal, B.

Abstract:

The novel Corona Virus Disease (COVID-19) pandemic has spread a blaze of increasing fatality rates across the world. The dearth of potential vaccines has left the survival of mankind with doubts. The development of multi-epitope vaccine in this current situation could be a possible COVID treatment. We have designed a novel multi-epitope, multi-protein vaccine with different proteins of Severe Acute Respiratory Syndrome - Corona Virus -2 (SARS-CoV-2) with immuno-informatics approaches, which has been validated in silico to be stable and potential. It has been prepared with Cytotoxic T-cell (TC ) and Helper T-cell (TH ) cell binding epitopes overlapping with B-cell binding epitopes predicted for 6 proteins conserved among 4 different viral strains isolated across the world. Both the humoral and cell-mediated immune responses are ensured due to the presence of T cell and B-cell inducing epitopes along with interferon-gamma inducing epitopes. The final vaccine construct comprises of an adjuvant at the N terminal, Cytotoxic T Lymphocyte and Helper T Lymphocyte epitopes. The construct showed potential antigenicity and was non-allergic. The molecular docking of the refined, validated tertiary structure model of the vaccine was performed with immune-stimulatory Toll Like Receptors (TLR), TLR-2,3,4. The molecular dynamics simulations of docking revealed binding interactions of receptor with vaccine. The immune simulation of the vaccine even confirmed the initiation of elevated host immune responses. The efficient translation of the vaccine in an expression vector was confirmed with in-silico cloning approach. Certainly, the development of such vaccine candidate could possibly be an effective therapy for COVID-19.

Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.24.219071v1?rss=1

Authors: Kaiser, F., Plach, M. G., Leberecht, C., Schubert, T., Haupt, V. J.

Abstract:

During the discovery and development of new drugs, candidates with undesired and potentially harmful side-effects can arise at all stages, which poses significant scientific and economic risks. Most of such phenotypic side-effects can be attributed to binding of the drug candidate to unintended proteins, so-called off-targets. The early identification of potential off-targets is therefore of utmost importance to mitigate any downstream risks. We showcase how the combination of knowledge-based in silico off-target screening and state-of-the-art biophysics can be applied to rapidly identify off-targets for a MAPK14 inhibitor. Out of 13 predicted off-targets, six proteins were confirmed to interact with the inhibitor in vitro, which translates to an exceptional hit rate of 46%. For two proteins, affinities in the lower micromolar range were obtained: The kinase IRE1 and the Hematopoietic Prostaglandin D Synthase, which is entirely unrelated to MAPK14 and is involved in different cell-regulatory processes. The whole off-target identification/validation pipeline can be completed as fast as within two months, excluding delivery times of proteins. These results emphasize how computational off-target screening in combination with MicroScale Thermophoresis can effectively reduce downstream development risks in a very competitive time frame and at low cost.

Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.24.217752v1?rss=1

Authors: Fan, Y., Wang, X., Wang, C.

Abstract:

14-3-3s present in multiple isoforms in human cells and mediate signal transduction by binding to phosphoserine-containing proteins. Recent findings have demonstrated that 14-3-3s act as a key factor in promoting chemoresistance of cancer. Here, we aimed to develop the predictive models that can determine the binding affinity of phosphopeptide fragments against 14-3-3s. It is found that the hydrophobic property of residues in phosphopeptides has a significant contribution to the binding affinity for most of 14-3-3 isoforms. The conserved patterns of 14-3-3 biding motifs were verified by our predictions. A group of peptide sequences were predicted with high binding affinity and high sequence conservation, which had agreement with 14-3-3s ligands. Overall, our results demonstrate that how the residues are likely to function in 14-3-3s interaction and the computational methods we introduced may contribute to the further research.

Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.23.206391v1?rss=1

Authors: Al Bkhetan, Z., Chana, G., Soon Ong, C., Goudey, B., Kotagiri, R.

Abstract:

Motivation: The high accuracy of current haplotype phasing tools has enabled the interrogation of haplotype (or phase) information more widely in genetic investigations. Including such information in eQTL analysis complements SNP-based approaches as it has the potential to detect associations that may otherwise be missed. Results: We have developed a haplotype-based eQTL approach called eQTLHap to investigate associations between gene expression and haplotype blocks. Using simulations, we demonstrate that eQTLHap significantly outperforms typical SNP-based eQTL methods when the causal genetic architecture involves multiple SNPs. We show that phasing errors slightly impact the sensitivity of the proposed method (< 4%). Finally, the application of eQTLHap to real GEUVADIS and GTEx datasets finds 22 associations that replicated in larger studies or other tissues and could not be detected using a single-SNP approach. Availability: https://github.com/ziadbkh/eQTLHap

Copy rights belong to original authors. Visit the link for more info