PaperPlayer biorxiv genomics

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.05.238949v1?rss=1

Authors: Wang, J., Roeder, K., Devlin, B.

Abstract:

When assessed over a large number of samples, bulk RNA sequencing provides reliable data for gene expression at the tissue level. Single-cell RNA sequencing (scRNA-seq) deepens those analyses by evaluating gene expression at the cellular level. Both data types lend insights into disease etiology. With current technologies, however, scRNA-seq data are known to be noisy. Moreover, constrained by costs, scRNA-seq data are typically generated from a relatively small number of subjects, which limits their utility for some analyses, such as identification of gene expression quantitative trait loci (eQTLs). To address these issues while maintaining the unique advantages of each data type, we develop a Bayesian method (bMIND) to integrate bulk and scRNA-seq data. With a prior derived from scRNA-seq data, we propose to estimate sample-level cell-type-specific (CTS) expression from bulk expression data. The CTS expression enables large-scale sample-level downstream analyses, such as detecting CTS differentially expressed genes (DEGs) and eQTLs. Through simulations, we demonstrate that bMIND improves the accuracy of sample-level CTS expression estimates and power to discover CTS-DEGs when compared to existing methods. To further our understanding of two complex phenotypes, autism spectrum disorder and Alzheimer's disease, we apply bMIND to gene expression data of relevant brain tissue to identify CTS-DEGs. Our results complement findings for CTS-DEGs obtained from snRNA-seq studies, replicating certain DEGs in specific cell types while nominating other novel genes in those cell types. Finally, we calculate CTS-eQTLs for eleven brain regions by analyzing GTEx V8 data, creating a new resource for biological insights.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.05.238600v1?rss=1

Authors: Felix, P. T., dos Santos, J. F.

Abstract:

A photomap of the polythenic chromosomes of D. malerkotliana was constructed to facilitate the identification of the chromosomal arms and their sections, in order to allow the identification of the breaking points of inversions and the location of the bands marked by in situ hybridization. The photomap included the six chromosome arms corresponding to pairs I (chromosome X), II and III, excluding pair IV and Y chromosome, because they were not visualized in the material examined, probably due to their small size. Through the in situ hybridization technique with the use of a biotined probe of a fragment of the D. melanogaster gene, the Hsp83 locus of D. malerkotliana was mapped. The probe hybridized with a frequency of 70% in section 98 of the IIIR chromosome. This is the first mapped gene in the species, and indicates that possibly the IIIR arm of D. malerkotliana corresponds to the IIIL arm of D. melanogaster, where the Hsp83 gene was located.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.05.238253v1?rss=1

Authors: Daly, A. Z., Dudley, L. A., Peel, M. T., Liebhaber, S. A., Parker, S. C., Camper, S. A.

Abstract:

Pituitary thyrotropes are specialized cells that produce thyroid stimulating hormone, a critical factor for growth and maintenance of metabolism. The transcription factors POU1F1 and GATA2 have been implicated in thyrotrope fate and regulation of Tshb transcription, but no transcriptomic or epigenetic analyses of these cells has been undertaken. The goal of this work was to discover key elements that drive thyrotrope fate. We identified the transcription factors and epigenetic changes in chromatin that are associated with differentiation of POU1F1-expressing progenitors into thyrotropes using cell lines that represent an early, undifferentiated Pou1f1 lineage progenitor (GHF-T1) or a committed thyrotrope (TT1). We generated and integrated genome-wide information about DNA accessibility, histone modification, POU1F1 transcription factor binding and RNA expression data to identify regulatory elements and candidate transcriptional regulators. We identified POU1F1 binding sites that were unique to each cell line. POU1F1 binding sites are commonly associated with bZIP transcription factor consensus binding sites in GHF-T1 cells and HLH (Helix-Turn-Helix) or basic Helix-Turn-Helix (bHLH) factors in TT1 cells, suggesting that some classes of transcription factors may recruit or cooperate with POU1F1 binding to unique sites. We validated enhancer function of novel elements we mapped near Cga, Pitx1, Gata2, and Tshb by transfection in TT1 cells. Finally, we confirmed that an enhancer element near Tshb can drive expression in thyrotropes of transgenic mice, and we demonstrate that GATA2 enhances Tshb expression through this element. These data extend the ENCODE analysis to an organ that is critical for growth and metabolism. This information may be valuable for understanding pituitary development and disease pathogenesis.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.04.231969v1?rss=1

Authors: Takahashi, H., Nishiyori-Sueki, H., Ramilowski, J. A., Itoh, M., Carninci, P.

Abstract:

The Cap Analysis of Gene Expression (CAGE) is a powerful method to identify the Transcription Start Sites (TSSs) of capped RNAs while simultaneously measuring transcripts expression level. CAGE allows mapping at single nucleotide resolution at all active promoters and enhancers. Large CAGE datasets have been produced over the years from individual laboratories and consortia, including the Encyclopedia of DNA Elements (ENCODE) and Functional Annotation Of the Mammalian Genome (FANTOM). These datasets constitute open resource for TSS annotations and gene expression analysis. Here we provide an experimental protocol for the most recent CAGE method called Low Quantity (LQ) single strand (ss) CAGE (LQ-ssCAGE), which enables cost-effective profiling of low quantity RNA samples. LQ-ssCAGE is especially useful for samples derived from cells cultured in small volumes, cellular compartments such as nuclear RNAs or for samples from developmental stages. We demonstrate the reproducibility and effectiveness of the method by constructing 240 LQ-ssCAGE libraries from 50 ng of THP-1 cell extracted RNAs and discover lowly expressed novel enhancer and promoter-derived lncRNAs.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.05.238030v1?rss=1

Authors: Singh, A., Zhong, Y., Park, C. S., Nahlawi, L., Alarcon, C., De, T., Perera, M.

Abstract:

Epigenetics is a reversible molecular mechanism that plays a critical role in many developmental, adaptive, and disease processes. DNA methylation has been shown to regulate gene expression and the advent of high throughput technologies has made genome-wide DNA methylation analysis possible. We investigated the effect of DNA methylation in eQTL mapping (methylation-adjusted eQTLs), by incorporating DNA methylation as a SNP-based covariate in eQTL mapping in African American derived hepatocytes. We found that the addition of DNA methylation uncovered new eQTLs and eGenes. Previously discovered eQTLs were significantly altered by the addition of DNA methylation data suggesting that methylation may modulate the association of SNPs to gene expression. We found that methylation-adjusted eQTLs which were less significant compared to PC-adjusted eQTLs were enriched in lipoprotein measurements (FDR = 0.0040), immune system disorders (FDR = 0.0042), and liver enzyme measurements (FDR = 0.047), suggesting a role of DNA methylation in regulating the genetic basis of these phenotypes. Our methylation-adjusted eQTL analysis also uncovered novel SNP-gene pairs. For example, our study found the SNP, rs11546996, was associated to PNKP. In a previous GWAS, this SNP was associated with primary biliary cirrhosis although the causal gene was thought to be SPIB. Our methylation-adjusted method potentially adds new understanding to the genetic basis of complex diseases that disproportionally affect African Americans.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.05.238618v1?rss=1

Authors: Jain, A., Rophina, M., Mahajan, S., Krishnan, B. B., Sharma, M., Mandal, S., Fernandez, T., Sultanji, S., Mathew, S., Sivasubbu, S., Scaria, V.

Abstract:

An isolated epidemic of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) causing Coronavirus Diseases (C0VID-19) originating in Wuhan, China has now rapidly emerged into a global pandemic affecting millions of people worldwide. Molecular detection of SARS-CoV-2 using reverse transcription polymerase chain reaction (RT-PCR) forms the mainstay in screening, diagnosis and epidemiology of disease. The virus has been evolving through base substitutions. The recent availability of genomes of SARS-CoV-2 isolates from different countries including India motivated us to assess the presence and potential impact of variations in target sites for the oligonucleotide primers and probes used in molecular diagnosis. We catalogued a total of 132 primers or probes sequences from the literature and the public domain. Our analysis revealed a total of 125 unique genetic variants in 80 either primers or probes binding sites. A total of 13 unique variants had allele frequency of [≥] 1% in Indian SARS-CoV-2 genomes mapped to the primers or probes binding sites. A total of 15 primers or probes binding sites had cumulative variant frequency of [≥] 1% in the SARS-CoV-2 genomes. These included primers or probes sites which are widely used in India and across the world for molecular diagnosis as well as approved by national and international agencies. This highlights the need for sequencing genomes of emerging pathogens to make evidence based policies for development and approval of diagnostics. To the best of our knowledge, ours is the most comprehensive analysis of genomic variants in genomes of SARS-CoV-2 isolates from India and their potential impact on efficacy of molecular diagnostics. Keywords: COVID-19, genomes, SARS-CoV-2, variations, reverse transcription polymerase chain reaction, Gibbs free energy

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.05.238360v1?rss=1

Authors: Zhang, F., Mears, J. R., Shakib, L., Beynor, J. I., Shanaj, S., Korsunsky, I., Nathan, A., Accelerating Medicines Partnership Rheumatoid Arthritis and Systemic Lupus Erythematosus,, Donlin, L. T., Raychaudhuri, S.

Abstract:

Immunosuppressive and anti-cytokine treatment may have a protective effect for patients with COVID-19. Understanding the immune cell states shared between COVID-19 and other inflammatory diseases with established therapies may help nominate immunomodulatory therapies. Using an integrative strategy, we built a reference by meta-analyzing > 300,000 immune cells from COVID-19 and 5 inflammatory diseases including rheumatoid arthritis (RA), Crohn disease (CD), ulcerative colitis (UC), lupus, and interstitial lung disease. Our cross-disease analysis revealed that an FCN1+ inflammatory macrophage state is common to COVID-19 bronchoalveolar lavage samples, RA synovium, CD ileum, and UC colon. We also observed that a CXCL10+ CCL2+ inflammatory macrophage state is abundant in severe COVID-19, inflamed CD and RA, and expresses inflammatory genes such as GBP1, STAT1, and IL1B. We found that the CXCL10+ CCL2+ macrophages are transcriptionally similar to blood-derived macrophages stimulated with TNF- and IFN-{gamma} ex vivo. Our findings suggest that IFN-{gamma}, alongside TNF-, might be a key driver of this abundant inflammatory macrophage phenotype in severe COVID-19 and other inflammatory diseases, which may be targeted by existing immunomodulatory therapies.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.05.237404v1?rss=1

Authors: Gupta, S., Singh, R., Paul, P.

Abstract:

The spread of COVID-19 is a global concern that has taken a toll on entire human health. Researchers across the globe has been working in devising the strategies to combat this dreadful disease. Studies focused on genetic variability helps design effective drugs and vaccines. Considering this, the present study entails the information regarding the genome-wide mutations detected in the 108 SARS CoV-2 genomes worldwide. We identified a few hypervariable regions localized in orf1ab, spike, and nucleocapsid gene. These nucleotide polymorphisms demonstrated their effect on both codon usage as well as amino acid usage pattern. Altogether the present study provides valuable information that would be helpful to ongoing research on 2019-nCoV vaccine development.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.03.235028v1?rss=1

Authors: Smith, G. A., Pampana, A., Natarajan, P., Shokat, K., Chorba, J. S.

Abstract:

In humans, clearance of LDL cholesterol, which causes atherosclerotic heart disease, is mediated by the hepatic LDL receptor (LDLR). As a result, therapies that upregulate the LDLR are highly effective treatments for atherosclerosis. Since cardiovascular disease remains the leading cause of death in Western countries, we sought to identify regulators of the LDLR beyond the known genetic causes of familial hypercholesterolemia. Here we show that CSDE1, an RNA-binding protein involved in mRNA stability, enhances LDLR mRNA degradation to modulate LDLR expression and function. Using parallel phenotypic genome-wide screens, based on the CRISPR interference platform, we identified over 100 specific regulators of surface LDLR expression in HepG2 cells, characterized their effects on LDLR function, and leveraged pharmacologic strategies to probe their mechanistic pathways. Among our hits, we found that CSDE1 participates in post-translational control of the LDLR independent from well-established, and clinically exploited, transcriptional and lysosomal regulatory mechanisms. Overall, our results reveal a network of novel LDLR modulators left undiscovered by human genetics, many of which have phenotypic strengths similar to bona fide targets in the clinic, offering hope for new therapeutic strategies against atherosclerosis. We anticipate that our approach of modelling a clinically relevant phenotype in an in vitro experimental system amenable to a forward genetic screen, followed by high throughput validation and mechanistic pharmacologic dissection, will serve as a template for the identification of novel therapeutic targets for other disease states.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.03.235358v1?rss=1

Authors: Whelan, C. W., Handsaker, R. E., Genovese, G., Kashin, S., Lek, M., Hughes, J., McElwee, J., Lenardo, M., MacArthur, D., McCarroll, S. A.

Abstract:

Two intriguing forms of genome structural variation (SV) - dispersed duplications, and de novo rearrangements of complex, multi-allelic loci - have long escaped genomic analysis. We describe a new way to find and characterize such variation by utilizing identity-by-descent (IBD) relationships between siblings together with high-precision measurements of segmental copy number. Analyzing whole-genome sequence data from 706 families, we find hundreds of "IBD-discordant" (IBDD) CNVs: loci at which siblings' CNV measurements and IBD states are mathematically inconsistent. We found that commonly-IBDD CNVs identify dispersed duplications; we mapped 95 of these common dispersed duplications to their true genomic locations through family-based linkage and population linkage disequilibrium (LD), and found several to be in strong LD with genome-wide association (GWAS) signals for common diseases or gene expression variation at their revealed genomic locations. Other CNVs that were IBDD in a single family appear to involve de novo mutations in complex and multi-allelic loci; we identified 26 de novo structural mutations that had not been previously detected in earlier analyses of the same families by diverse SV analysis methods. These included a de novo mutation of the amylase gene locus and multiple de novo mutations at chromosome 15q14. Combining these complex mutations with more-conventional CNVs, we estimate that segmental mutations larger than 1kb arise in about one per 22 human meioses. These methods are complementary to previous techniques in that they interrogate genomic regions that are home to segmental duplication, high CNV allele frequencies, and multi-allelic CNVs.

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