PaperPlayer biorxiv genomics

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.19.210971v1?rss=1

Authors: Torres, E. B.

Abstract:

The art of observing and describing behaviors has driven diagnosis and informed basic science in Psychiatry. In recent times, studies of mental illness are focused on understanding the brains neurobiology but there is a paucity of information on the potential contributions from peripheral activity to mental health. In Precision Medicine, this common practice leaves a gap between bodily behaviors and genomics that we here propose to address with a new layer of inquiry that includes genes expression on tissues inclusive of brain, heart, muscle-skeletal and organs for vital bodily functions. We interrogate genes expression on human tissue as a function of disease-associated genes. By removing genes linked to disease from the typical human set, and recomputing the genes expressions on the tissues, we can compare the outcomes across mental illnesses, well-known neurological conditions, and non-neurological ones. We find that major neuropsychiatric conditions that are behaviorally defined today (e.g. Autism, Schizophrenia, Depression) through DSM-observation criteria, have strong convergence with well-known neurological ones (e.g. Ataxias, Parkinson), but less overlap with non-neurological ones. Surprisingly, tissues majorly involved in the central control, coordination, adaptation and learning of movements, emotion and memory are maximally affected in psychiatric diagnoses along with peripheral heart and muscle-skeletal tissues. Our results underscore the importance of considering both the brain-body connection and the contributions of the peripheral nervous systems to mental health.

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

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.19.211029v1?rss=1

Authors: Santos, H. P., Bhattacharya, A., Joseph, R. M., Smeester, L., Kuban, K. C., Marsit, C. J., O'Shea, T. M., Fry, R. C.

Abstract:

BackgroundChildren born extremely preterm are at heightened risk for intellectual and social impairment. There is increasing evidence for a key role of the placenta in prenatal neurodevelopmental programming, suggesting that the placenta serves as a role in the origins of neurodevelopmental outcomes.

MethodsWe examined associations between genomic and epigenomic profiles in the placenta and assessed their ability to predict intellectual and social impairment at age 10 years in 379 children from the Extremely Low Gestational Age Newborn (ELGAN) cohort. Assessment of intellectual ability (IQ) and social function was completed with the Differential Ability Scales-II (DAS-II) and Social Responsiveness Scale (SRS), respectively. Genome-wide mRNA, CpG methylation and miRNA were assessed with the Illumina Hiseq 2500, HTG EdgeSeq miRNA Whole Transcriptome Assay, and Illumina EPIC/850K array, respectively. We conducted genome-wide differential mRNA/miRNA and epigenome-wide placenta analyses. These molecular features were then integrated for a predictive analysis of IQ and SRS outcomes using kernel aggregation regression.

ResultsWe found that genes with important roles in placenta angiogenesis and neural function were associated with intellectual and social impairment. Multi-omic predictions of intellectual and social function were strong, explaining approximately 10% and 12% of the variance in SRS and IQ scores via cross-validation, respectively.

ConclusionsOur findings demonstrate that aggregating information from biomarkers within and between molecular data types improves prediction of complex traits like social and intellectual ability in children born extremely preterm, suggesting that traits influenced by the placenta-brain axis may be omnigenic.

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

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.20.211813v1?rss=1

Authors: Bernabeu, E., Canela-Xandri, O., Rawlik, K., Talenti, A., Prendergast, J., Tenesa, A.

Abstract:

Sex is arguably the most important differentiating characteristic in most mammalian species, separating populations into different groups, with varying behaviors, morphologies, and physiologies based on their complement of sex chromosomes. In humans, despite males and females sharing nearly identical genomes, there are differences between the sexes in complex traits and in the risk of a wide array of diseases. Gene by sex interactions (GxS) are thought to account for some of this sexual dimorphism. However, the extent and basis of these interactions are poorly understood.

Here we provide insights into both the scope and mechanism of GxS across the genome of circa 450,000 individuals of European ancestry and 530 complex traits in the UK Biobank. We found small yet widespread differences in genetic architecture across traits through the calculation of sex-specific heritability, genetic correlations, and sex-stratified genome-wide association studies (GWAS). We also found that, in some cases, sex-agnostic GWAS efforts might be missing loci of interest, and looked into possible improvements in the prediction of high-level phenotypes. Finally, we studied the potential functional role of the dimorphism observed through sex-biased eQTL and gene-level analyses.

This study marks a broad examination of the genetics of sexual dimorphism. Our findings parallel previous reports, suggesting the presence of sexual genetic heterogeneity across complex traits of generally modest magnitude. Our results suggest the need to consider sex-stratified analyses for future studies in order to shed light into possible sex-specific molecular mechanisms.

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

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.20.212886v1?rss=1

Authors: Cheng, Y., Saville, L., Gollen, B., Isaac, C., Mehla, J., Mohajerani, M., Zovoilis, A.

Abstract:

More than 97% of the mammalian genome is non-protein coding, and repetitive elements account for more than 50% of noncoding space. However, the functional importance of many non-coding RNAs generated by these elements and their connection with pathologic processes remains elusive. We have previously shown that B2 RNAs, a class of non-coding RNAs that belong to the B2 family of SINE repeats, mediate the transcriptional activation of stress response genes (SRGs) upon application of a stimulus. Notably, B2 RNAs bind RNA Polymerase II (RNA Pol II) and suppress SRG transcription during pro-stimulation state. Upon application of a stimulus, B2 RNAs are processed into fragments and degraded, which in turn releases RNA Pol II from suppression and upregulates SRGs. Here, we demonstrate a novel role for B2 RNAs in transcriptome response to amyloid beta toxicity and pathology in the mouse hippocampus. In healthy hippocampi, activation of SRGs is followed by a transient upregulation of pro-apoptotic factors, such as p53 and miRNA-34c, which target SRGs creating a negative feedback loop that facilitates transition to the pro-stimulation state. Using an integrative RNA genomics approach, we show that in mouse hippocampi of an amyloid precursor protein knock-in mouse model and in an in vitro cell culture model of amyloid beta toxicity, this regulatory loop is dysfunctional due to increased levels of B2 RNA processing, constitutively elevated SRG expression and high p53 levels. Evidence indicates that Hsf1, a master regulator of stress response, mediates B2 RNA processing in cells, and is upregulated during amyloid toxicity accelerating the processing of SINE RNAs and SRG hyper-activation. Our study reveals that in mouse, SINE RNAs constitute a novel pathway deregulated in amyloid beta pathology, with potential implications for similar cases in the human brain, such as Alzheimers disease (AD). This data attributes a role to SINE RNA processing in a pathological process as well as a new function to Hsf1 that is independent of its transcription factor activity.

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

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.20.211656v1?rss=1

Authors: Ferguson, K. B., Pannebakker, B. A., Centurion, A., van den Heuvel, J., Nieuwenhuis, R., Becker, F. F. M., Schijlen, E., Thiel, A., Zwaan, B. J., Verhulst, E. C.

Abstract:

Bracon brevicornis is an ectoparasitoid of a wide range of larval-stage Lepidopterans, including several pests of important crops, such as the corn borer, Ostrinia nubilalis. It is also one of the earliest documented cases of complementary sex determination in Hymenoptera. Here, we present the linked-read genome of B. brevicornis, complete with an ab initio-derived annotation and protein comparisons with fellow braconids, Fopius arisanus and Diachasma alloem. We demonstrate the potential of linked-read assemblies in exploring regions of heterozygosity and search for structural and homology-derived evidence of the complementary sex determiner gene (csd).

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

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.20.212969v1?rss=1

Authors: Ohnuki, H., Venzon, D. J., Lobanov, A., Tosato, G.

Abstract:

Gene expression in individual cells is epigenetically regulated by DNA modifications, histone modifications, transcription factors and other DNA-binding proteins. It has been shown that multiple histone modifications can predict gene expression and reflect future responses of bulk cells to extracellular cues. However, the predictive ability of epigenomic analysis is still limited for mechanistic research at a single cell level. To overcome this limitation, it is useful to acquire reliable signals from multiple epigenetic marks in the same single cell. Here, we propose a new approach for analysis of several components of the epigenome in the same single cell. The new method allows reanalysis of the same single cell. We found that reanalysis of the same single cell is feasible, and provides confirmation of the signals and allows application of statistical analysis to identify reliable signals using data sets generated only from the single cell. Reanalysis of the same single cell is also useful to acquire multiple-epigenetic marks from the same single cells. The method can acquire at least 4 epigenetic marks, H3K27ac, H3K27me3, mediator complex subunit 1 and a DNA modification. We predicted active signaling pathways in K562 single cells using the data. We confirmed that the prediction results showed a strong correlation with actual active signaling pathways shown by RNA-seq results. These results suggest that the new approach provides mechanistic insights for cellular phenotypes through multi-layered epigenome analysis in the same single cells.

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

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.20.211573v1?rss=1

Authors: Pacini, G., Dunkel, I., Mages, N., Mutzel, V., Timmermann, B., Marsico, A., Schulz, E. G.

Abstract:

To ensure dosage compensation between the sexes, one randomly chosen X chromosome is silenced in each female cell in the process of X-chromosome inactivation (XCI). XCI is initiated during early development through upregulation of the long non-coding RNA Xist, which mediates chromosome-wide gene silencing. Cell differentiation, Xist upregulation and silencing are thought to be coupled at multiple levels to ensure inactivation of exactly one out of two X chromosomes. Here we perform an integrated analysis of all three processes through allele-specific single-cell RNA-sequencing. Specifically, we assess the onset of random XCI with high temporal resolution in differentiating mouse embryonic stem cells, and develop dedicated analysis approaches. By exploiting the inter-cellular heterogeneity of XCI onset, we identify Nanog downregulation as its main trigger and discover additional putative Xist regulators. Moreover, we confirm several predictions of the stochastic model of XCI where monoallelic silencing is thought to be ensured through negative feedback regulation. Finally, we show that genetic variation modulates the XCI process at multiple levels, providing a potential explanation for the long-known Xce effect, which leads to preferential inactivation of a specific X chromosome in inter-strain crosses. We thus draw a detailed picture of the different levels of regulation that govern the initiation of XCI. The experimental and computational strategies we have developed here will allow us to profile random XCI in more physiological contexts, including primary human cells in vivo.

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

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.20.212753v1?rss=1

Authors: Mu, Z., Wei, W., Fair, B. J., Miao, J., Zhu, P., Li, Y.

Abstract:

The effects of trait-associated variants are often studied in a single relevant cell-type or context. However, for many complex traits, multiple cell-types are involved. This applies particularly to immune-related traits, for which many immune cell-types and contexts play a role. Here, we studied the impact of immune gene regulatory variants on complex traits to better understand genetic risk mediated through immune cell-types. We identified 26,271 expression quantitative trait loci (QTLs) and 23,121 splicing QTLs in 18 immune cell-types, and analyzed their overlap with trait-associated loci from 72 genome-wide association studies (GWAS). We showed that effects on RNA expression and splicing in immune cells colocalize with an average of 40.4% and 27.7% GWAS loci for immune-related and non-immune traits, respectively. Notably, we found that a large number of loci (mean: 14%) colocalize with splicing QTLs but not expression QTLs. The 60% GWAS loci without colocalization harbor genes that have lower expression levels, are less tolerant to loss-of-function mutations, and more enhancerrich than genes at colocalized loci. To further investigate the 60% GWAS loci not explained by our regulatory QTLs, we collected H3K27ac CUT&Tag data from rheumatoid arthritis (RA) and healthy controls. We found several unexplained GWAS hits lying within regions with higher H3K27ac activity in RA patients. We also observed that enrichment of RA GWAS heritability is greater in H3K27ac regions in immune cell-types from RA patients compared to healthy controls. Our study paves the way for future QTL studies to elucidate the mechanisms of as yet unexplained GWAS loci.

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

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.21.213603v1?rss=1

Authors: Shehata, S., Spradlin, S., Swearingen, A., Wheeler, G., Das, A., Corbet, G., Nebenfuehr, B., Ahrens, D., Tauber, D., Lennon, S., Choi, K., Huynh, T., Weiser, T., Schneider, K., Bradshaw, M., Lai, M., Baskin, J., Read, T., Demasi, J., Hynes-Grace, M., Timmons, D., Smallegan, M., Rinn, J. L.

Abstract:

A key aspect in defining cell state is the complex choreography of DNA binding events in a given cell type, which in turn establishes a cell-specific gene-expression program. In the past two decades since the sequencing of the human genome there has been a deluge of genome-wide experiments which have measured gene-expression and DNA binding events across numerous cell-types and tissues. Here we re-analyze ENCODE data in a highly reproducible manner by utilizing standardized analysis pipelines, containerization, and literate programming with Rmarkdown. Our approach validated many findings from previous independent studies, underscoring the importance of ENCODEs goals in providing these reproducible data resources. This approach also revealed several new findings: (i) 1,362 promoters, termed reservoirs, have up to 111 different DNA binding-proteins localized on one promoter yet do not have any expression of steady-state RNA (ii) The human specific SVA repeat element may have been co-opted for enhancer regulation. Collectively, this study performed by the students of a CU Boulder computational biology class (BCHM 5631 - Spring 2020) demonstrates the value of reproducible findings and how resources like ENCODE that prioritize data standards can foster new findings with existing data in a didactic environment.

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

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.19.179101v1?rss=1

Authors: Kawano-Sugaya, T., Yatsu, K., Sekizuka, T., Itokawa, K., Hashino, M., Tanaka, R., Kuroda, M.

Abstract:

The worldwide eruption of COVID-19 that began in Wuhan, China in late 2019 reached 10 million cases by late June 2020. In order to understand the epidemiological landscape of the COVID-19 pandemic, many studies have attempted to elucidate phylogenetic relationships between collected viral genome sequences using haplotype networks. However, currently available applications for network visualization are not suited to understand the COVID-19 epidemic spatiotemporally, due to functional limitations That motivated us to develop Haplotype Explorer, an intuitive tool for visualizing and exploring haplotype networks. Haplotype Explorer enables people to dissect epidemiological consequences via interactive node filters to provide spatiotemporal perspectives on multimodal spectra of infectious diseases, including introduction, outbreak, expansion, and containment, for given regions and time spans. Here, we demonstrate the effectiveness of Haplotype Explorer by showing an example of its visualization and features. The demo using SARS-CoV-2 genome sequences is available at https://github.com/TKSjp/HaplotypeExplorer

SummaryA lot of software for network visualization are available, but existing software have not been optimized to infection cluster visualization against the current worldwide invasion of COVID-19 started since 2019. To reach the spatiotemporal understanding of its epidemics, we developed Haplotype Explorer. It is superior to other applications in the point of generating HTML distribution files with metadata searches which interactively reflects GISAID IDs, locations, and collection dates. Here, we introduce the features and products of Haplotype Explorer, demonstrating the time-dependent snapshots of haplotype networks inferred from total of 4,282 SARS-CoV-2 genomes.

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