Peak-valley-peak pattern of histone modifications delineates active regulatory elements and their directionality

Formation of nucleosome free region (NFR) accompanied by specific histone modifications at flanking nucleosomes is an important prerequisite for enhancer and promoter activity. Due to this process, active regulatory elements often exhibit a distinct shape of histone signal in the form of a peak-valley-peak (PVP) pattern. However, different features of PVP patterns and their robustness in predicting active regulatory elements have never been systematically analyzed. Here, we present PARE, a novel computational method that systematically analyzes the H3K4me1 or H3K4me3 PVP patterns to predict NFRs. We show that NFRs predicted by H3K4me1 and me3 patterns are associated with active enhancers and promoters, respectively. Furthermore, asymmetry in the height of peaks flanking the central valley can predict the directionality of stable transcription at promoters. Using PARE on ChIP-seq histone modifications from four ENCODE cell lines and four hematopoietic differentiation stages, we identified several enhancers whose regulatory activity is stage specific and correlates positively with the expression of proximal genes in a particular stage. In conclusion, our results demonstrate that PVP patterns delineate both the histone modification landscape and the transcriptional activities governed by active enhancers and promoters, and therefore can be used for their prediction. PARE is freely available at http://servers.binf.ku.dk/pare

The splicing factor RBM25 controls MYC activity in acute myeloid leukemia

Splicing factors are often mutated in hematological malignancies. Here, the authors perform an in vivo shRNA screen in a CEBPA mutant AML mouse model and identify that RBM25 controls the splicing of pre-mRNAs encoding BCL-X and BIN1 to exert its tumour suppressor activities in AML

Classification of low quality cells from single-cell RNA-seq data.

Single-cell RNA sequencing (scRNA-seq) has broad applications across biomedical research. One of the key challenges is to ensure that only single, live cells are included in downstream analysis, as the inclusion of compromised cells inevitably affects data interpretation. Here, we present a generic approach for processing scRNA-seq data and detecting low quality cells, using a curated set of over 20 biological and technical features. Our approach improves classification accuracy by over 30 % compared to traditional methods when tested on over 5,000 cells, including CD4+ T cells, bone marrow dendritic cells, and mouse embryonic stem cells

HemaExplorer: a database of mRNA expression profiles in normal and malignant haematopoiesis

The HemaExplorer (http://servers.binf.ku.dk/hemaexplorer) is a curated database of processed mRNA Gene expression profiles (GEPs) that provides an easy display of gene expression in haematopoietic cells. HemaExplorer contains GEPs derived from mouse/human haematopoietic stem and progenitor cells as well as from more differentiated cell types. Moreover, data from distinct subtypes of human acute myeloid leukemia is included in the database allowing researchers to directly compare gene expression of leukemic cells with those of their closest normal counterpart. Normalization and batch correction lead to full integrity of the data in the database. The HemaExplorer has comprehensive visualization interface that can make it useful as a daily tool for biologists and cancer researchers to assess the expression patterns of genes encountered in research or literature. HemaExplorer is relevant for all research within the fields of leukemia, immunology, cell differentiation and the biology of the haematopoietic system

Single-cell RNA-seq and computational analysis using temporal mixture modelling resolves Th1/Tfh fate bifurcation in malaria.

Differentiation of naïve CD4+ T cells into functionally distinct T helper subsets is crucial for the orchestration of immune responses. Due to extensive heterogeneity and multiple overlapping transcriptional programs in differentiating T cell populations, this process has remained a challenge for systematic dissection in vivo. By using single-cell transcriptomics and computational analysis using a temporal mixtures of Gaussian processes model, termed GPfates, we reconstructed the developmental trajectories of Th1 and Tfh cells during blood-stage Plasmodium infection in mice. By tracking clonality using endogenous TCR sequences, we first demonstrated that Th1/Tfh bifurcation had occurred at both population and single-clone levels. Next, we identified genes whose expression was associated with Th1 or Tfh fates, and demonstrated a T-cell intrinsic role for Galectin-1 in supporting a Th1 differentiation. We also revealed the close molecular relationship between Th1 and IL-10-producing Tr1 cells in this infection. Th1 and Tfh fates emerged from a highly proliferative precursor that upregulated aerobic glycolysis and accelerated cell cycling as cytokine expression began. Dynamic gene expression of chemokine receptors around bifurcation predicted roles for cell-cell in driving Th1/Tfh fates. In particular, we found that precursor Th cells were coached towards a Th1 but not a Tfh fate by inflammatory monocytes. Thus, by integrating genomic and computational approaches, our study has provided two unique resources, a database www.PlasmoTH.org, which facilitates discovery of novel factors controlling Th1/Tfh fate commitment, and more generally, GPfates, a modelling framework for characterizing cell differentiation towards multiple fates