Top 8 Biorxiv Papers Today in Genomics


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#1. Genome-wide discovery of lupus genetic risk variant allelic regulatory activity
Xiaoming Lu, Xiaoting Chen, Carmy Forney, Omer Donmez, Daniel Miller, Sreeja Parameswaran, Ted Hong, Yongbo Huang, Mario Pujato, Tareian Cazares, Emily R Miraldi, John P Ray, Carl G de Boer, John B Harley, Matthew T Weirauch, Leah C Kottyan
Genome-wide association studies of Systemic Lupus Erythematosus (SLE) nominate 3,073 genetic variants at 91 risk loci. To systematically screen these variants for allelic transcriptional enhancer activity, we constructed a massively parallel reporter assay (MPRA) library comprising 12,396 DNA oligonucleotides containing the genomic context around every allele of each SLE variant. Transfection into EBV-infected B cells revealed 482 variants with enhancer activity, with 51 variants showing genotype-dependent (allelic) enhancer activity at 27 risk loci. In-depth analysis of allelic transcription factor (TF) binding at and around these 51 variants identified one class of TFs whose DNA-binding motif tends to be directly altered by the risk variant and a second, larger class of TFs that also bind allelically but do not have their motifs directly altered by the variant. Collectively, our approach provides a blueprint for the discovery of allelic gene regulation at risk loci for any disease and offers insight into the transcriptional...
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#2. Transcription factors involved in stem cell maintenance are downstream of Slug/Snail2 and repressed by TGF-β in bronchial epithelial progenitors from Chronic Obstructive Pulmonary Disease
Pierre de la Grange, Ariane Jolly, Charlotte Courageux, Chamseddine Ben Brahim, Pascale Leroy
Objectives: Patients with Chronic Obstructive Pulmonary Disease (COPD) have a bronchial epithelium with many anomalies and basal/progenitor cells showing a decrease of self-renewal and differentiation potential. The objective of this study was to identify deregulations in the genetic program of COPD bronchial progenitors that could account for their exhaustion. The transcription factor Slug/Snail2 is highly expressed in bronchial progenitors and we aimed at identifying genes downstream of Slug whose expression is deregulated in COPD progenitors. Results: We knocked down Slug in primary basal cells from COPD subjects and, since COPD subjects have higher levels of Transforming Growth Factor (TGF)-β and Slug is regulated by TGF-β, we selected genes downstream of Slug involved in differentiation that respond to TGF-β. We identified transcription factors involved in stem cell maintenance downstream of Slug and repressed by TGF-β in COPD but not normal progenitors. We found that the effect of TGF-β on the expression of these genes is...
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#3. Cancer-specific CTCF binding facilitates oncogenic transcriptional dysregulation
Celestia Fang, Zhenjia Wang, Cuijuan Han, Stephanie L Safgren, Kathryn A Helmin, Emmalee R Adelman, Kyle P Eagen, Alexandre Gaspar-Maia, Maria E Figueroa, Benjamin D Singer, Aakrosh Ratan, Panagiotis Ntziachristos, Chongzhi Zang
Background: The three-dimensional genome organization is critical for gene regulation and can malfunction in diseases like cancer. As a key regulator of genome organization, CCCTC-binding factor (CTCF) has been characterized as a DNA-binding protein with important functions in maintaining the topological structure of chromatin and inducing DNA looping. Among the prolific binding sites in the genome, several events with altered CTCF occupancy have been reported as associated with effects in physiology or disease. However, there is no hitherto a comprehensive survey of genome-wide CTCF binding patterns across different human cancers. Results: To dissect functions of CTCF binding, we systematically analyze over 700 CTCF ChIP-seq profiles across human tissues and cancers and identify cancer-specific CTCF binding patterns in six cancer types. We show that cancer-specific lost and gained CTCF binding events are associated with altered chromatin interactions in patient samples, but not always with DNA methylation changes or sequence...
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biorxivpreprint: Cancer-specific CTCF binding facilitates oncogenic transcriptional dysregulation https://t.co/CArqWqPC21 #bioRxiv
biorxiv_genomic: Cancer-specific CTCF binding facilitates oncogenic transcriptional dysregulation https://t.co/quLsyEoaag #biorxiv_genomic
loops_enhancers: https://t.co/0n3CfO5NTJ
pieter_vv: RT @loops_enhancers: https://t.co/0n3CfO5NTJ
PolymorphismJ: RT @biorxiv_genomic: Cancer-specific CTCF binding facilitates oncogenic transcriptional dysregulation https://t.co/quLsyEoaag #biorxiv_gen…
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#4. BREM-SC: A Bayesian Random Effects Mixture Model for Joint Clustering Single Cell Multi-omics Data
Xinjun Wang, Zhe Sun, Yanfu Zhang, Zhongli Xu, Heng Huang, Richard H Duerr, Kong Chen, Ying Ding, Wei Chen
Droplet-based single cell transcriptome sequencing (scRNA-seq) technology, largely represented by the 10X Genomics Chromium system, is able to measure the gene expression from tens of thousands of single cells simultaneously. More recently, coupled with the cutting-edge Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq), the droplet-based system has allowed for immunophenotyping of single cells based on cell surface expression of specific proteins together with simultaneous transcriptome profiling in the same cell. Despite the rapid advances in technologies, novel statistical methods and computational tools for analyzing multi-modal CITE-Seq data are lacking. In this study, we developed BREM-SC, a novel Bayesian Random Effects Mixture model that jointly clusters paired single cell transcriptomic and proteomic data. Through simulation studies and analysis of public and in-house real data sets, we successfully demonstrated the validity and advantages of this method in fully utilizing both types of data to...
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biorxivpreprint: BREM-SC: A Bayesian Random Effects Mixture Model for Joint Clustering Single Cell Multi-omics Data https://t.co/Kcas4oeWFw #bioRxiv
biorxiv_genomic: BREM-SC: A Bayesian Random Effects Mixture Model for Joint Clustering Single Cell Multi-omics Data https://t.co/MQOijW5Fbe #biorxiv_genomic
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Novel joint clustering method with scRNA-seq and CITE-seq data

Repository: BREMSC
User: tarot0410
Language: R
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#5. Surveying Brain Tumor Heterogeneity by Single-Cell RNA Sequencing of Multi-sector Biopsies
Kai Yu, Yuqiong Hu, Fan Wu, Qiufang Guo, Zenghui Qian, Waner Hu, Jing Chen, Kuanyu Wang, Xiaoying Fan, Xinglong Wu, John EJ Rasko, Xiaolong Fan, Antonio Iavarone, Tao Jiang, Fuchou Tang, Xiao-Dong Su
Brain tumors are among the most challenging human tumors for which the mechanisms driving progression and heterogeneity remain poorly understood. We combined single-cell RNA-seq with multisector biopsies to sample and analyze single-cell expression profiles of gliomas from 13 Chinese patients. After classifying individual cells, we generated a spatial and temporal landscape of glioma that revealed the patterns of invasion between the different sub-regions of gliomas. We also used single-cell inferred CNVs and pseudotime trajectories to inform on the crucial branches that dominate tumor progression. The dynamic cell components of the multi-region biopsy analysis allowed us to spatially deconvolute with unprecedented accuracy the transcriptomic features of the core and those of the periphery of glioma at single cell level. Through this rich and geographically detailed dataset, we were also able to characterize and construct the chemokine and chemokine receptor interactions that exist among different tumor and non-tumor cells. This...
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biorxivpreprint: Surveying Brain Tumor Heterogeneity by Single-Cell RNA Sequencing of Multi-sector Biopsies https://t.co/dKfldOncP3 #bioRxiv
biorxiv_genomic: Surveying Brain Tumor Heterogeneity by Single-Cell RNA Sequencing of Multi-sector Biopsies https://t.co/luuwWzdSWi #biorxiv_genomic
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#6. Super-resolution visualization of distinct stalled and broken replication fork structures
Donna R Whelan, Wei Ting Chelsea Lee, Frances Marks, Yu Tina Kong, Yandong Yin, Eli Rothenberg
Endogenous genotoxic stress occurs in healthy cells due to competition between DNA replication machinery, and transcription and topographic relaxation processes. This causes replication fork (RF) stalling and regression, which can further collapse to form single-ended double strand breaks (seDSBs). To avoid mutagenesis, these breaks require repair via Homologous Recombination (HR). Here we apply multicolor single molecule super resolution microscopy to visualize individual RFs under mild stress from the trapping of Topoisomerase I cleavage complexes, a damage induction which closely mimics endogenous replicative stress. We identify RAD51 and RAD52, alongside RECQ1, as the first responder proteins to stalled but unbroken forks, whereas Ku and MRE11 are initially recruited to seDSBs. Ku loads directly onto the DSB end whereas MRE11 associates with nascent DNA away from the break, and both proteins colocalize contemporaneously with a single seDSB. We are thus able to discern closely related RF stress motifs and their repair pathways...
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science_SRH: RT @biorxivpreprint: Super-resolution visualization of distinct stalled and broken replication fork structures https://t.co/nmsotEIKZ0 #bi…
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#7. Three genomes of Osteoglossidae shed light on ancient teleost evolution
Shijie Hao, Kai Han, Lingfeng Meng, Xiaoyun Huang, Chengcheng Shi, Mengqi Zhang, Yilin Wang, Qun Liu, Yaolei Zhang, Inge Seim, Xun Xu, Xin Liu, Guangyi Fan
Osteoglossiformes is a basal clade of teleost, originated from late Jurassic and had seen the process of continental drift. The genomic differences amongst Osteoglossiformes species should reflect the unique evolve history of that time. Here, we presented the chromosome-level genome of Heterotis niloticus which is the only omnivore species of Osteoglossidae spreading in Africa. Together with other two Osteoglossidae species genomes of Arapaima gigas and Scleropages formosus which spread in South America and Australia respectively, we found great evolutionary differences in gene families and transposable elements. Phylogenetic analysis showed that the ancestor of H. niloticus and A. gigas diverged with S. formosus at ~106.1Mya, consistent with the time of Afro-South American drift and A. gigas speciated from the ancestor of H. niloticus and A. gigas at ~59.2 Mya, consistent with the separation of Eurasia and North American continents. And we proposed the evolutionary traces of Osteoglossidae species based on comparative genomics...
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#8. Strategies for cellular deconvolution in human brain RNA sequencing data
Olukayode A Sosina, Matthew N Tran, Kristen Maynard, Ran Tao, Margaret A Taub, Keri Martinowich, Stephen A Semick, Daniel Weinberger, Bryan C Quach, Thomas M Hyde, Dana B Hancock, Joel E Kleinman, Jeffrey T Leek, Andrew E Jaffe
Statistical deconvolution strategies have emerged over the past decade to estimate the proportion of various cell populations in homogenate tissue sources like brain using gene expression data. Here we show that several existing deconvolution algorithms which estimate the RNA composition of homogenate tissue, relates to the amount of RNA attributable to each cell type, and not the cellular composition relating to the underlying fraction of cells. Incorporating "cell size" parameters into RNA-based deconvolution algorithms can successfully recover cellular fractions in homogenate brain RNA-seq data. We lastly show that using both cell sizes and cell type-specific gene expression profiles from brain regions other than the target/user-provided bulk tissue RNA-seq dataset consistently results in biased cell fractions. We report several independently constructed cell size estimates as a community resource and extend the MuSiC framework to accommodate these cell size estimates (https://github.com/xuranw/MuSiC/).
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