PaperPlayer biorxiv genomics

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.29.226852v1?rss=1

Authors: Lloyd Evans, D., Joshi, S. V.

Abstract:

Since it was first introduced to Europe in 711 CE and planted in the Americas in 1506, a single type of cane dominated sugar production for 1100 years, until it was finally ousted by Tahitian cane c. 1790. This cane became known as 'Creole' and is present in the ancestry of many sugarcane hybrids, even today. Whether there was only a single variety of Creole cane or multiple varieties has been a matter of debate for decades. Creole cane remains relevant today, as a Creole cane from Jamaica is the currently chosen lecotype for Saccharum officinarum. In this study we identify 18 historical images of Creole cane, many not previously published. We employ image analyses to characterize the internodes and demonstrate evidence for only a single type of Creole in the new world. Chloroplasts and 45s ribosomal RNA sequences from the cultivar BH10/12 (known to have a Creole female parent) were determined that Java ribbon cane is the historical New World sugarcane known as Creole. We demonstrate that Creole cane is an hybrid and not a single species. Thus S. officinarum has no type specimen. We also sequence a ribbon cane (also known as Guinguam) that appeared in the Caribbean between 1790 and 1810 and demonstrate that this cane was a Sinense type from Java that links back to the work of Rumphinus (1660s).

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.30.229641v1?rss=1

Authors: Ramirez-Corona, B. A., Fruth, S. M., Ofoegbu, O., Wunderlich, Z.

Abstract:

Transcription is controlled by the interactions of cis-acting DNA elements with diffusible trans-acting factors. Changes in cis or trans factors can drive expression divergence within and between species, and the relative prevalence of each can reveal the evolutionary history and pressures that drive expression variation. Previous work delineating the mode of expression divergence in animals has largely used whole body expression measurements in a single condition. Since cis-acting elements often drive expression in a subset of cell types or conditions, these measurements may not capture the complete contribution of cis-acting changes. Here, we quantify the mode of expression divergence in the Drosophila fat body, the primary immune organ, in several conditions. We performed allele-specific expression analysis using two geographically distinct lines of D. melanogaster and their F1 hybrids. We measured expression in the absence of infection and in separate infections with Gram-negative S. marcescens or Gram-positive E. faecalis bacteria, which trigger the two primary signaling pathways in the Drosophila innate immune response. The mode of expression divergence strongly depends on the condition, with trans-acting effects dominating in response to Gram-positive infection and cis-acting effects dominating in Gram-negative and pre-infection conditions. Expression divergence in several receptor proteins may underlie the infection-specific trans effects. Before infection, when the fat body has a metabolic role, there are many compensatory effects, changes in cis and trans that counteract each other to maintain expression levels. This work demonstrates that within a single tissue, the mode of expression divergence varies between conditions and suggests that these differences reflect the diverse evolutionary histories of host-pathogen interactions.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.30.229534v1?rss=1

Authors: Stein, D. F., Chen, H., Vinyard, M. E., Pinello, L.

Abstract:

Single-cell assays have transformed our ability to model heterogeneity within cell populations and tissues. Virtual reality has recently emerged as a powerful technology to dynamically explore complex data. However, expensive hardware or advanced data preprocessing skills are required to adapt such technology to single-cell data. To address current shortcomings, we built singlecellVR, a user-friendly website for visualizing single- cell data, designed for cheap and easily available virtual reality hardware (e.g., Google Cardboard, ~$8). We provide a companion package, scvr to streamline data conversion from the most widely-adopted single-cell analysis tools and a database of pre-analyzed datasets to which users can contribute.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.30.229088v1?rss=1

Authors: Yahi, A., Hoffman, P., Brandt, M., Mohammadi, P., Tatonetti, N. P., Lappalainen, T.

Abstract:

Genome editing experiments are generating an increasing amount of targeted sequencing data with specific mutational patterns indicating the success of the experiments and genotypes of clonal cell lines. We present EdiTyper, a high-throughput command line tool specifically designed for analysis of sequencing data from polyclonal and monoclonal cell populations from CRISPR gene editing. It requires simple inputs of sequencing data and reference sequences, and provides comprehensive outputs including summary statistics, plots, and SAM/BAM alignments. Analysis of simulated data showed that EdiTyper is highly accurate for detection of both single nucleotide mutations and indels, robust to sequencing errors, as well as fast and scalable to large experimental batches. EdiTyper is available in github (https://github.com/LappalainenLab/edityper) under the MIT license.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.29.227926v1?rss=1

Authors: Shanmugam, S., Bachmann, N. L., Martinez, E., Menon, R., Narendran, G., Narayanan, S., Devi, K. R. U., Sawleshwarkar, S., Marais, B., Sintchenko, V.

Abstract:

Differentiation between relapse and reinfection in cases with tuberculosis (TB) recurrence has important implications for public health, especially in patients with human immunodeficiency virus (HIV) co-infection. Forty-one paired M. tuberculosis isolates collected from 20 HIV-positive and 21 HIV-negative patients, who experienced TB recurrence after previous successful treatment, were subjected to whole genome sequencing (WGS) in addition to spoligotyping and mycobacterial interspersed repeat unit (MIRU) typing. Comparison of M. tuberculosis genomes indicated that 95% of TB recurrences in the HIV-negative cohort were due to relapse, while the majority of TB recurrences (75%) in the HIV-positive cohort was due to re-infection (P=0.0001). Drug resistance conferring mutations were documented in four pairs (9%) of isolates associated with relapse. The high contribution of re-infection to TB among HIV patients warrants further study to explore risk factors for TB exposure in the community.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.29.226555v1?rss=1

Authors: Mahmud, A. S. M., Taznin, T., Sarkar, M. M. H., Uzzaman, M. S., Osman, E., Habib, M. A., Akter, S., Banu, T. A., Goswami, B., Jahan, I., Hossain, M. S., Khan, M. S.

Abstract:

Genomic mutation of the virus may impact the viral adaptation to the local environment, their transmission, disease manifestation, and the effectiveness of existing treatment and vaccination. The objectives of this study were to characterize genomic variations, non-synonymous amino acid substitutions especially in target proteins, mutation events per samples, rate, and overall scenario of coronaviruses across the country. To investigate the genetic diversity, a total of 184 genomes of virus strains sampled from different divisions of Bangladesh with sampling dates between 10 May 2019 and 27 June 2020 were analyzed. To date, a total of 634 mutations located along the entire genome resulting in nonsynonymous 274 amino acid substitutions in 22 different proteins were detected. The mutation rate estimated to be 23.715 substitutions per year. The highest non-synonymous amino acid substitutions were observed at 48 different positions of the papain-like protease (nsp3). Although no mutations were observed in nsp7, nsp9, nsp10, and nsp11, yet orf1ab accounts for 56% of total mutations. Among the structural proteins, the highest mutations at 36 different positions have identified in spike proteins. A total of 9 mutations at spike proteins were found unique in relative to the global mutations including mutations at position 516 in the boundary of the ACE2 binding region of the spike protein. The most dominated variant G614 (95%) based in spike protein is circulating across the country followed by coevolving other variants including L323 (94%) in RNA dependent RNA polymerase (RdRp), K203 (82%) and R204 (82%) in nucleocapsid, and F120 (78%) in NSP2. These variants are mostly seen as linked mutations and are part of a haplotype observed high in Europe. Data suggest effective containment of clade G strains (4.8%) with sub-clusters GR covered by 82.4%, and GH clade 6.4%. Whereas 2.7 and 3.2 % of variants belonged to clade S and O clade, respectively.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.28.225185v1?rss=1

Authors: Schmidt, M., Maie, T., Dahl, E., Gesteira Costa Filho, I., Wagner, W.

Abstract:

Background: The complex composition of different cell types within a tissue can be estimated by deconvolution of omics datasets. For example, DNA methylation (DNAm) profiles have been used to establish an atlas for multiple human tissues and cell types. In this study, we investigated if deconvolution is also feasible with individual cell-type-specific CG dinucleotides (CpG sites), which can be addressed by targeted analysis, such as pyrosequencing. Results: We compiled and curated a dataset of 579 samples from Illumina 450k BeadChip technology that comprised 14 different purified and characterized human cell types. A training and validation strategy was applied to identify and test cell-type-specific CpGs. Initially, the amount of fibroblasts was estimated using two CpGs that were either hypermethylated or hypomethylated in fibroblasts. This FibroScore correlated with the state of fibrosis and was associated with overall survival in various types of cancer. Furthermore, we identified hypomethylated CpGs for leukocytes, endothelial cells, epithelial cells, hepatocytes, glia, neurons, fibroblasts and induced pluripotent stem cells. Using previously published BeadChip datasets with cell mixtures the accuracy of this eight CpG signature was comparable to previously published signatures based on several thousand CpGs. Finally, we established and validated pyrosequencing assays for the relevant CpGs that can be utilized for classification and deconvolution of cell types. Conclusion: This proof of concept study demonstrates that DNAm analysis at individual CpGs reflects the cellular composition of cellular mixtures and different tissues. Targeted analysis of these genomic regions facilitates robust methods for application in basic research and clinical settings.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.28.224782v1?rss=1

Authors: Pain, O., Glanville, K. P., Hagenaars, S. P., Selzam, S. P., Fürtjes, A. E., Gaspar, H. A., Coleman, J. R., Rimfeld, K., Breen, G., Plomin, R., Folkersen, L., Lewis, C. M.

Abstract:

Background: The predictive utility of polygenic scores is increasing, and many polygenic scoring methods are available, but it is unclear which method performs best. This study evaluates the predictive utility of polygenic scoring methods within a reference-standardized framework, which uses a common set of variants and reference-based estimates of linkage disequilibrium and allele frequencies to construct scores. Methods: Six polygenic score methods were tested: p-value thresholding and clumping (pT+clump), SBLUP, lassosum, LDPred, PRScs and SBayesR, evaluating their performance to predict outcomes in UK Biobank and the Twins Early Development Study (TEDS). Strategies to identify optimal p-value threshold and shrinkage parameters were compared, including 10-fold cross validation, pseudovalidation (with no validation sample), and multi-polygenic score elastic net models. Results: lassosum, PRScs and LDPred performed strongly using 10-fold cross-validation to identify the most predictive p-value threshold or shrinkage parameter, giving a relative improvement of 14-17% over pT+clump in the correlation between observed and predicted outcome values. Using pseudovalidation, the best method was PRScs, with a relative improvement of >11% over other pseudovalidation methods (lassosum, SBLUP, SBayesR, LDPred), and only 1% less than the best polygenic score identified by 10-fold cross validation. Elastic net models containing polygenic scores based on a range of parameters consistently improved prediction over any single polygenic score. Conclusion: Within a reference-standardized framework, the best polygenic prediction was achieved using lassosum and PRScs, modeling multiple polygenic scores derived using multiple parameters. This study will help researchers performing polygenic score studies to select the most powerful and predictive analysis methods.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.28.225276v1?rss=1

Authors: Perez-Coronel, E., Beman, J. M.

Abstract:

Aquatic ecosystems are globally significant sources of the greenhouse gas methane to the atmosphere. However, methane is produced paradoxically in oxygenated water via at least three mechanisms, fundamentally limiting our understanding of overall methane production. Here we resolve these methane production mechanisms through methane measurements, {delta}13CH4 analyses, 16S rRNA sequencing, and metagenomics/transcriptomics applied to freshwater incubation experiments with multiple time points and treatments (addition of a methanogenesis inhibitor, dark, high-light). We captured significant paradoxical methane production, but show that methanogenesis was an unlikely methane source. In contrast, abundant freshwater bacteria metabolized methylphosphonate, similar to observations in marine ecosystems. Metatranscriptomics and stable isotopic analyses applied to experimental treatments also identified a potential methane production mechanism linked to (bacterio)chlorophyll metabolism by Cyanobacteria and especially Proteobacteria. Variability in these mechanisms across experiments indicates that multiple, widely-distributed bacterial groups and pathways can produce substantial quantities of methane in aquatic ecosystems.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.27.224147v1?rss=1

Authors: Mitsuhashi, S., Nakagawa, S., Frith, M., Mitsuhashi, H.

Abstract:

Facioscapulohumeral muscular dystrophy (FSHD) is an inherited muscle disease caused by misexpression of the DUX4 gene in skeletal muscle. DUX4 is a transcription factor which is normally expressed in the cleavage-stage embryo and regulates gene expression involved in early embryonic development. Recent studies revealed that DUX4 also activates the transcription of repetitive elements such as endogenous retroviruses (ERVs), mammalian apparent LTR-retrotransposons (MaLRs), and pericentromeric satellite repeats (HSATII). DUX4-bound ERV sequences also create alternative promoters for genes or long non-coding RNAs (lncRNAs), producing fusion transcripts. To further understand transcriptional regulation by DUX4, we performed nanopore long-read direct RNA sequencing (dRNA-seq) of human muscle cells induced by DUX4, because long reads show whole isoforms with greater confidence. We successfully detected differential expression of known DUX4-induced genes, and discovered 61 differentially-expressed repeat loci, which are near DUX4-ChIP peaks. We also identified 247 gene-ERV fusion transcripts, of which 216 were not reported previously. In addition, long-read dRNA-seq clearly shows that RNA splicing is a common event in DUX4-activated ERV transcripts. Long-read analysis showed non-LTR transposons including Alu are also transcribed from LTRs. Our findings revealed further complexity of DUX4-induced ERV transcripts. This catalogue of DUX4-activated repetitive elements may provide useful information to elucidate the pathology of FSHD. Also, our results indicate that nanopore dRNA-seq has complementary strengths to conventional short read cDNA sequencing.

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