In diseased organs, stress-activated signalling cascades alter chromatin, thereby triggering maladaptive cell state transitions. Fibroblast activation is a common stress response in tissues that ...worsens lung, liver, kidney and heart disease, yet its mechanistic basis remains unclear
. Pharmacological inhibition of bromodomain and extra-terminal domain (BET) proteins alleviates cardiac dysfunction
, providing a tool to interrogate and modulate cardiac cell states as a potential therapeutic approach. Here we use single-cell epigenomic analyses of hearts dynamically exposed to BET inhibitors to reveal a reversible transcriptional switch that underlies the activation of fibroblasts. Resident cardiac fibroblasts demonstrated robust toggling between the quiescent and activated state in a manner directly correlating with BET inhibitor exposure and cardiac function. Single-cell chromatin accessibility revealed previously undescribed DNA elements, the accessibility of which dynamically correlated with cardiac performance. Among the most dynamic elements was an enhancer that regulated the transcription factor MEOX1, which was specifically expressed in activated fibroblasts, occupied putative regulatory elements of a broad fibrotic gene program and was required for TGFβ-induced fibroblast activation. Selective CRISPR inhibition of the single most dynamic cis-element within the enhancer blocked TGFβ-induced Meox1 activation. We identify MEOX1 as a central regulator of fibroblast activation associated with cardiac dysfunction and demonstrate its upregulation after activation of human lung, liver and kidney fibroblasts. The plasticity and specificity of BET-dependent regulation of MEOX1 in tissue fibroblasts provide previously unknown trans- and cis-targets for treating fibrotic disease.
The novel SARS-CoV-2 virus emerged in December 2019 and has few effective treatments. We applied a computational drug repositioning pipeline to SARS-CoV-2 differential gene expression signatures ...derived from publicly available data. We utilized three independent published studies to acquire or generate lists of differentially expressed genes between control and SARS-CoV-2-infected samples. Using a rank-based pattern matching strategy based on the Kolmogorov-Smirnov Statistic, the signatures were queried against drug profiles from Connectivity Map (CMap). We validated 16 of our top predicted hits in live SARS-CoV-2 antiviral assays in either Calu-3 or 293T-ACE2 cells. Validation experiments in human cell lines showed that 11 of the 16 compounds tested to date (including clofazimine, haloperidol and others) had measurable antiviral activity against SARS-CoV-2. These initial results are encouraging as we continue to work towards a further analysis of these predicted drugs as potential therapeutics for the treatment of COVID-19.
Systemic lupus erythematosus (SLE) is an autoimmune disease in which outcomes vary among different racial groups. We leverage cell-sorted RNA-seq data (CD14+ monocytes, B cells, CD4+ T cells, and NK ...cells) from 120 SLE patients (63 Asian and 57 White individuals) and apply a four-tier approach including unsupervised clustering, differential expression analyses, gene co-expression analyses, and machine learning to identify SLE subgroups within this multiethnic cohort. K-means clustering on each cell-type resulted in three clusters for CD4 and CD14, and two for B and NK cells. To understand the identified clusters, correlation analysis revealed significant positive associations between the clusters and clinical parameters including disease activity as well as ethnicity. We then explored differentially expressed genes between Asian and White groups for each cell-type. The shared differentially expressed genes across cells were involved in SLE or other autoimmune-related pathways. Co-expression analysis identified similarly regulated genes across samples and grouped these genes into modules. Finally, random forest classification of disease activity in the White and Asian cohorts showed the best classification in CD4+ T cells in White individuals. The results from these analyses will help stratify patients based on their gene expression signatures to enable SLE precision medicine.
Homology Directed Repair (HDR) enables precise genome editing, but the implementation of HDR-based therapies is hindered by limited efficiency in comparison to methods that exploit alternative DNA ...repair routes, such as Non-Homologous End Joining (NHEJ). In this study, we develop a functional, pooled screening platform to identify protein-based reagents that improve HDR in human hematopoietic stem and progenitor cells (HSPCs). We leverage this screening platform to explore sequence diversity at the binding interface of the NHEJ inhibitor i53 and its target, 53BP1, identifying optimized variants that enable new intermolecular bonds and robustly increase HDR. We show that these variants specifically reduce insertion-deletion outcomes without increasing off-target editing, synergize with a DNAPK inhibitor molecule, and can be applied at manufacturing scale to increase the fraction of cells bearing repaired alleles. This screening platform can enable the discovery of future gene editing reagents that improve HDR outcomes.
Identification of pregnancies at risk of preterm birth (PTB), the leading cause of newborn deaths, remains challenging given the syndromic nature of the disease. We report a longitudinal multi-omics ...study coupled with a DREAM challenge to develop predictive models of PTB. The findings indicate that whole-blood gene expression predicts ultrasound-based gestational ages in normal and complicated pregnancies (r = 0.83) and, using data collected before 37 weeks of gestation, also predicts the delivery date in both normal pregnancies (r = 0.86) and those with spontaneous preterm birth (r = 0.75). Based on samples collected before 33 weeks in asymptomatic women, our analysis suggests that expression changes preceding preterm prelabor rupture of the membranes are consistent across time points and cohorts and involve leukocyte-mediated immunity. Models built from plasma proteomic data predict spontaneous preterm delivery with intact membranes with higher accuracy and earlier in pregnancy than transcriptomic models (AUROC = 0.76 versus AUROC = 0.6 at 27–33 weeks of gestation).
Display omitted
Blood gene expression predicts gestational age in normal and complicated pregnanciesRNA changes preceding preterm prelabor rupture of the membranes are shared between cohortsPlasma proteomic profiles from asymptomatic women predict spontaneous preterm birth
Harnessing the wisdom of crowds in a DREAM Challenge, Tarca et al. developed methods to predict gestational age and preterm birth from longitudinal multi-omics data. The authors show that blood RNAs predict ultrasound-based gestational age, and they identify molecular changes preceding a diagnosis of spontaneous preterm birth in asymptomatic women.
Pediatric inflammatory bowel disease (pIBD) is a chronic heterogeneous disorder. This study looks at the burden of common and rare coding mutations within 41 genes comprising the NOD signaling ...pathway in pIBD patients. 136 pIBD and 106 control samples underwent whole-exome sequencing. We compared the burden of common, rare and private mutation between these two groups using the SKAT-O test. An independent replication cohort of 33 cases and 111 controls was used to validate significant findings. We observed variation in 40 of 41 genes comprising the NOD signaling pathway. Four genes were significantly associated with disease in the discovery cohort (BIRC2 p = 0.004, NFKB1 p = 0.005, NOD2 p = 0.029 and SUGT1 p = 0.047). Statistical significance was replicated for BIRC2 (p = 0.041) and NOD2 (p = 0.045) in an independent validation cohort. A gene based test on the combined discovery and replication cohort confirmed association for BIRC2 (p = 0.030). We successfully applied burden of mutation testing that jointly assesses common and rare variants, identifying two previously implicated genes (NFKB1 and NOD2) and confirmed a possible role in disease risk in a previously unreported gene (BIRC2). The identification of this novel gene provides a wider role for the inhibitor of apoptosis gene family in IBD pathogenesis.
is a tumor suppressor gene on chromosome 11 encoding a multivalent adaptor protein with E3 ubiquitin ligase activity. Germline
mutations are dominant. Pathogenic
mutations result in a phenotype that ...overlaps Noonan syndrome (1). Some patients with
mutations go on to develop juvenile myelomonocytic leukemia (JMML), an aggressive malignancy that usually necessitates bone marrow transplantation. Using whole exome sequencing methods, we identified a known mutation in
in a 4-year-old Caucasian boy with atypical hemolytic uremic syndrome, moyamoya phenomenon, and dysmorphology consistent with a mild Noonan-like phenotype. Exome data revealed loss of heterozygosity across chromosome 11q consistent with JMML but in the absence of clinical leukemia. Our finding challenges conventional clinical diagnostics since we have identified a pathogenic variant in the
gene previously only ascertained in children presenting with leukemia. The increasing affordability of expansive sequencing is likely to increase the scope of clinical profiles observed for previously identified pathogenic variants and calls into question the interpretability and indications for clinical management.
Interpretation of genomic variation plays an essential role in the analysis of cancer and monogenic disease, and increasingly also in complex trait disease, with applications ranging from basic ...research to clinical decisions. Many computational impact prediction methods have been developed, yet the field lacks a clear consensus on their appropriate use and interpretation. The Critical Assessment of Genome Interpretation (CAGI, /'kā‐jē/) is a community experiment to objectively assess computational methods for predicting the phenotypic impacts of genomic variation. CAGI participants are provided genetic variants and make blind predictions of resulting phenotype. Independent assessors evaluate the predictions by comparing with experimental and clinical data.
CAGI has completed five editions with the goals of establishing the state of art in genome interpretation and of encouraging new methodological developments. This special issue (https://onlinelibrary.wiley.com/toc/10981004/2019/40/9) comprises reports from CAGI, focusing on the fifth edition that culminated in a conference that took place 5 to 7 July 2018. CAGI5 was comprised of 14 challenges and engaged hundreds of participants from a dozen countries. This edition had a notable increase in splicing and expression regulatory variant challenges, while also continuing challenges on clinical genomics, as well as complex disease datasets and missense variants in diseases ranging from cancer to Pompe disease to schizophrenia. Full information about CAGI is at https://genomeinterpretation.org.
PDF
