A global role for KLF1 in erythropoiesis revealed by ChIP-seq in primary erythroid cells

KLF1 regulates a diverse suite of genes to direct erythroid cell differentiation from bipotent progenitors. To determine the local cis-regulatory contexts and transcription factor networks in which KLF1 operates, we performed KLF1 ChIP-seq in the mouse. We found at least 945 sites in the genome of E14.5 fetal liver erythroid cells which are occupied by endogenous KLF1. Many of these recovered sites reside in erythroid gene promoters such as Hbb-bl, but the majority are distant to any known gene. Our data suggests KLF1 directly regulates most aspects of terminal erythroid differentiation including production of alpha- and beta-globin protein chains, heme biosynthesis, coordination of proliferation and anti-apoptotic pathways, and construction of the red cell membrane and cytoskeleton by functioning primarily as a transcriptional activator. Additionally, we suggest new mechanisms for KLF1 cooperation with other transcription factors, in particular the erythroid transcription factor GATA1, to maintain homeostasis in the erythroid compartment

Overexpression of miRNA-25-3p inhibits Notch1 signaling and TGF-β-induced collagen expression in hepatic stellate cells

During chronic liver injury hepatic stellate cells (HSCs), the principal source of extracellular matrix in the fibrotic liver, transdifferentiate into pro-fibrotic myofibroblast-like cells - a process potentially regulated by microRNAs (miRNAs). Recently, we found serum miRNA-25-3p (miR-25) levels were upregulated in children with Cystic Fibrosis (CF) without liver disease, compared to children with CF-associated liver disease and healthy individuals. Here we examine the role of miR-25 in HSC biology. MiR-25 was detected in the human HSC cell line LX-2 and in primary murine HSCs, and increased with culture-induced activation. Transient overexpression of miR-25 inhibited TGF-β and its type 1 receptor (TGFBR1) mRNA expression, TGF-β-induced Smad2 phosphorylation and subsequent collagen1α1 induction in LX-2 cells. Pull-down experiments with biotinylated miR-25 revealed Notch signaling (co-)activators ADAM-17 and FKBP14 as miR-25 targets in HSCs. NanoString analysis confirmed miR-25 regulation of Notch- and Wnt-signaling pathways. Expression of Notch signaling pathway components and endogenous Notch1 signaling was downregulated in miR-25 overexpressing LX-2 cells, as were components of Wnt signaling such as Wnt5a. We propose that miR-25 acts as a negative feedback anti-fibrotic control during HSC activation by reducing the reactivity of HSCs to TGF-β-induced collagen expression and modulating the cross-talk between Notch, Wnt and TGF-β signaling

Methods to study splicing from high-throughput RNA Sequencing data

The development of novel high-throughput sequencing (HTS) methods for RNA (RNA-Seq) has provided a very powerful mean to study splicing under multiple conditions at unprecedented depth. However, the complexity of the information to be analyzed has turned this into a challenging task. In the last few years, a plethora of tools have been developed, allowing researchers to process RNA-Seq data to study the expression of isoforms and splicing events, and their relative changes under different conditions. We provide an overview of the methods available to study splicing from short RNA-Seq data. We group the methods according to the different questions they address: 1) Assignment of the sequencing reads to their likely gene of origin. This is addressed by methods that map reads to the genome and/or to the available gene annotations. 2) Recovering the sequence of splicing events and isoforms. This is addressed by transcript reconstruction and de novo assembly methods. 3) Quantification of events and isoforms. Either after reconstructing transcripts or using an annotation, many methods estimate the expression level or the relative usage of isoforms and/or events. 4) Providing an isoform or event view of differential splicing or expression. These include methods that compare relative event/isoform abundance or isoform expression across two or more conditions. 5) Visualizing splicing regulation. Various tools facilitate the visualization of the RNA-Seq data in the context of alternative splicing. In this review, we do not describe the specific mathematical models behind each method. Our aim is rather to provide an overview that could serve as an entry point for users who need to decide on a suitable tool for a specific analysis. We also attempt to propose a classification of the tools according to the operations they do, to facilitate the comparison and choice of methods.Comment: 31 pages, 1 figure, 9 tables. Small corrections adde

RNA-Seq gene expression estimation with read mapping uncertainty

Motivation: RNA-Seq is a promising new technology for accurately measuring gene expression levels. Expression estimation with RNA-Seq requires the mapping of relatively short sequencing reads to a reference genome or transcript set. Because reads are generally shorter than transcripts from which they are derived, a single read may map to multiple genes and isoforms, complicating expression analyses. Previous computational methods either discard reads that map to multiple locations or allocate them to genes heuristically

Cord blood IgG and the risk of severe Plasmodium falciparum malaria in the first year of life

Young infants are less susceptible to severe episodes of malaria but the targets and mechanisms of protection are not clear. Cord blood antibodies may play an important role in mediating protection but many studies have examined their association with the outcome of infection or non-severe malaria. Here, we investigated whether cord blood IgG to Plasmodium falciparum merozoite antigens and antibody-mediated effector functions were associated with reduced odds of developing severe malaria at different time points during the first year of life. We conducted a case-control study of well-defined severe falciparum malaria nested within a longitudinal birth cohort of Kenyan children. We measured cord blood total IgG levels against five recombinant merozoite antigens and antibody function in the growth inhibition activity and neutrophil antibody-dependent respiratory burst assays. We also assessed the decay of maternal antibodies during the first 6months of life. The mean antibody half-life range was 2.51months (95% confidence interval (CI): 2.19-2.92) to 4.91months (95% CI: 4.47-6.07). The rate of decline of maternal antibodies was inversely proportional to the starting concentration. The functional assay of antibody-dependent respiratory burst activity predicted significantly reduced odds of developing severe malaria during the first 6months of life (Odds ratio (OR) 0.07, 95% CI: 0.007-0.74, P=0.007). Identification of the targets of antibodies mediating antibody-dependent respiratory burst activity could contribute to the development of malaria vaccines that protect against severe episodes of malaria in early infancy

SNP discovery in the bovine milk transcriptome using RNA-Seq technology

High-throughput sequencing of RNA (RNA-Seq) was developed primarily to analyze global gene expression in different tissues. However, it also is an efficient way to discover coding SNPs. The objective of this study was to perform a SNP discovery analysis in the milk transcriptome using RNA-Seq. Seven milk samples from Holstein cows were analyzed by sequencing cDNAs using the Illumina Genome Analyzer system. We detected 19,175 genes expressed in milk samples corresponding to approximately 70% of the total number of genes analyzed. The SNP detection analysis revealed 100,734 SNPs in Holstein samples, and a large number of those corresponded to differences between the Holstein breed and the Hereford bovine genome assembly Btau4.0. The number of polymorphic SNPs within Holstein cows was 33,045. The accuracy of RNA-Seq SNP discovery was tested by comparing SNPs detected in a set of 42 candidate genes expressed in milk that had been resequenced earlier using Sanger sequencing technology. Seventy of 86 SNPs were detected using both RNA-Seq and Sanger sequencing technologies. The KASPar Genotyping System was used to validate unique SNPs found by RNA-Seq but not observed by Sanger technology. Our results confirm that analyzing the transcriptome using RNA-Seq technology is an efficient and cost-effective method to identify SNPs in transcribed regions. This study creates guidelines to maximize the accuracy of SNP discovery and prevention of false-positive SNP detection, and provides more than 33,000 SNPs located in coding regions of genes expressed during lactation that can be used to develop genotyping platforms to perform marker-trait association studies in Holstein cattle

Refining transcriptional programs in kidney development by integration of deep RNA-sequencing and array-based spatial profiling

<p>Abstract</p> <p>Background</p> <p>The developing mouse kidney is currently the best-characterized model of organogenesis at a transcriptional level. Detailed spatial maps have been generated for gene expression profiling combined with systematic <it>in situ </it>screening. These studies, however, fall short of capturing the transcriptional complexity arising from each locus due to the limited scope of microarray-based technology, which is largely based on "gene-centric" models.</p> <p>Results</p> <p>To address this, the polyadenylated RNA and microRNA transcriptomes of the 15.5 dpc mouse kidney were profiled using strand-specific RNA-sequencing (RNA-Seq) to a depth sufficient to complement spatial maps from pre-existing microarray datasets. The transcriptional complexity of RNAs arising from mouse RefSeq loci was catalogued; including 3568 alternatively spliced transcripts and 532 uncharacterized alternate 3' UTRs. Antisense expressions for 60% of RefSeq genes was also detected including uncharacterized non-coding transcripts overlapping kidney progenitor markers, Six2 and Sall1, and were validated by section <it>in situ </it>hybridization. Analysis of genes known to be involved in kidney development, particularly during mesenchymal-to-epithelial transition, showed an enrichment of non-coding antisense transcripts extended along protein-coding RNAs.</p> <p>Conclusion</p> <p>The resulting resource further refines the transcriptomic cartography of kidney organogenesis by integrating deep RNA sequencing data with locus-based information from previously published expression atlases. The added resolution of RNA-Seq has provided the basis for a transition from classical gene-centric models of kidney development towards more accurate and detailed "transcript-centric" representations, which highlights the extent of transcriptional complexity of genes that direct complex development events.</p

COOL-LAMPS III: Discovery of a 25".9 Separation Quasar Lensed by a Merging Galaxy Cluster

In the third paper from the COOL-LAMPS Collaboration, we report the discovery of COOL J0542-2125, a gravitationally lensed quasar at $z=1.84$, observed as three images due to an intervening massive galaxy cluster at $z=0.61$. The lensed quasar images were identified in a search for lens systems in recent public optical imaging data and have separations on the sky up to 25".9, wider than any previously known lensed quasar. The galaxy cluster acting as a strong lens appears to be in the process of merging, with two sub-clusters separated by $\sim 1$ Mpc in the plane of the sky, and their central galaxies showing a radial velocity difference of $\sim 1000$ km/s. Both cluster cores show strongly lensed images of an assortment of background sources, as does the region between them. A preliminary strong lens model implies masses of $M(<250\ \rm{kpc}) = 1.79^{+0.16} _{-0.01} \times 10^{14} M_{\odot}$and$M(<250\ \rm{kpc}) = 1.48^{+0.04}_{-0.10} \times 10^{14} M_{\odot}$ for the East and West sub-clusters, respectively. This line of sight is also coincident with a ROSAT ALL-sky Survey source, centered between the two confirmed cluster halos reminiscent of other major cluster-scale mergers.Comment: 13 pages, 6 figures. Submitted to Ap

Efficiently identifying genome-wide changes with next-generation sequencing data

We propose a new and effective statistical framework for identifying genome-wide differential changes in epigenetic marks with ChIP-seq data or gene expression with mRNA-seq data, and we develop a new software tool EpiCenter that can efficiently perform data analysis. The key features of our framework are: (i) providing multiple normalization methods to achieve appropriate normalization under different scenarios, (ii) using a sequence of three statistical tests to eliminate background regions and to account for different sources of variation and (iii) allowing adjustment for multiple testing to control false discovery rate (FDR) or family-wise type I error. Our software EpiCenter can perform multiple analytic tasks including: (i) identifying genome-wide epigenetic changes or differentially expressed genes, (ii) finding transcription factor binding sites and (iii) converting multiple-sample sequencing data into a single read-count data matrix. By simulation, we show that our framework achieves a low FDR consistently over a broad range of read coverage and biological variation. Through two real examples, we demonstrate the effectiveness of our framework and the usages of our tool. In particular, we show that our novel and robust ‘parsimony’ normalization method is superior to the widely-used ‘tagRatio’ method. Our software EpiCenter is freely available to the public