QuadBase2: web server for multiplexed guanine quadruplex mining and visualization

DNA guanine quadruplexes or G4s are non-canonical DNA secondary structures which affect genomic processes like replication, transcription and recombination. G4s are computationally identified by specific nucleotide motifs which are also called putative G4 (PG4) motifs. Despite the general relevance of these structures, there is currently no tool available that can allow batch queries and genome-wide analysis of these motifs in a user-friendly interface. QuadBase2 (quadbase.igib.res.in) presents a completely reinvented web server version of previously published QuadBase database. QuadBase2 enables users to mine PG4 motifs in up to 178 eukaryotes through the EuQuad module. This module interfaces with Ensembl Compara database, to allow users mine PG4 motifs in the orthologues of genes of interest across eukaryotes. PG4 motifs can be mined across genes and their promoter sequences in 1719 prokaryotes through ProQuad module. This module includes a feature that allows genome-wide mining of PG4 motifs and their visualization as circular histograms. TetraplexFinder, the module for mining PG4 motifs in user-provided sequences is now capable of handling up to 20 MB of data. QuadBase2 is a comprehensive PG4 motif mining tool that further expands the configurations and algorithms for mining PG4 motifs in a user-friendly way

BreCAN-DB: a repository cum browser of personalized DNA breakpoint profiles of cancer genomes

BreCAN-DB (http://brecandb.igib.res.in) is a repository cum browser of whole genome somatic DNA breakpoint profiles of cancer genomes, mapped at single nucleotide resolution using deep sequencing data. These breakpoints are associated with deletions, insertions, inversions, tandem duplications, translocations and a combination of these structural genomic alterations. The current release of BreCAN-DB features breakpoint profiles from 99 cancer-normal pairs, comprising five cancer types. We identified DNA breakpoints across genomes using high-coverage next-generation sequencing data obtained from TCGA and dbGaP. Further, in these cancer genomes, we methodically identified breakpoint hotspots which were significantly enriched with somatic structural alterations. To visualize the breakpoint profiles, a next-generation genome browser was integrated with BreCAN-DB. Moreover, we also included previously reported breakpoint profiles from 138 cancer-normal pairs, spanning 10 cancer types into the browser. Additionally, BreCAN-DB allows one to identify breakpoint hotspots in user uploaded data set. We have also included a functionality to query overlap of any breakpoint profile with regions of user's interest. Users can download breakpoint profiles from the database or may submit their data to be integrated in BreCAN-DB. We believe that BreCAN-DB will be useful resource for genomics scientific community and is a step towards personalized cancer genomics

TRIMETHOPRIM-SULFAMETHOXAZOLE AND SODIUM VALPROATE-INDUCED TOXIC EPIDERMAL NECROLYSIS: A CASE SERIES

Toxic epidermal necrolysis (TEN) is a rare and serious but life-threatening dermolytic cutaneous reaction characterized by diffuse and severe exfoliation and destruction of the epidermis of skin and mucosa due to immunological damage of the epidermis which can bring about sepsis and respiratory distress. Drugs are the most common inflicting agents in the generation of TEN. Among drugs, antiepileptics, antipsychotics, and sulfa-drugs are common causes of TEN. Valproate is one of the most common drugs prescribed for epilepsy, was found as causative agent in TEN in very few cases. Among sulfonamides, sulfamethoxazole is commonly used antibiotic which can cause TEN. The evidence-based treatment guidelines are lacking, so the best approach is to recognize and evade potential risk factors and to deliver intensive supportive care immediately to reduce morbidity and mortality. The aim of this case series is to focus on valproate and trimethoprim-sulfamethoxazole (TMP-SMX)-induced TEN, which are commonly used drugs. Here, we present a case series of TEN inflicted by TMP-SMX and sodium valproate in a 23-year-old female and 10-year-old boy, respectively, with successful recovery

Epigenetic suppression of human telomerase ( hTERT ) is mediated by the metastasis suppressor NME2 in a G-quadruplex–dependent fashion

Transcriptional activation of the human telomerase reverse transcriptase (hTERT) gene, which remains repressed in adult somatic cells, is critical during tumorigenesis. Several transcription factors and the epigenetic state of the hTERT promoter are known to be important for tight control of hTERT in normal tissues, but the molecular mechanisms leading to hTERT reactivation in cancer are not well-understood. Surprisingly, here we found occupancy of the metastasis suppressor non-metastatic 2 (NME2) within the hTERT core promoter in HT1080 fibrosarcoma cells and HCT116 colon cancer cells and NME2-mediated transcriptional repression of hTERT in these cells. We also report that loss of NME2 results in up-regulated hTERT expression. Mechanistically, additional results indicated that the RE1-silencing transcription factor (REST)–lysine-specific histone demethylase 1 (LSD1) co-repressor complex associates with the hTERT promoter in an NME2-dependent way and that this assembly is required for maintaining repressive chromatin at the hTERT promoter. Interestingly, a G-quadruplex motif at the hTERT promoter was essential for occupancy of NME2 and the REST repressor complex on the hTERT promoter. In light of this mechanistic insight, we studied the effects of G-quadruplex–binding ligands on hTERT expression and observed that several of these ligands repressed hTERT expression. Together, our results support a mechanism of hTERT epigenetic control involving a G-quadruplex promoter motif, which potentially can be targeted by tailored small molecules

Tracking early mammalian organogenesis – prediction and validation of differentiation trajectories at whole organism scale

Early organogenesis represents a key step in animal development, during which pluripotent cells diversify to initiate organ formation. Here, we sampled 300,000 single-cell transcriptomes from mouse embryos between E8.5 and E9.5 in 6-h intervals and combined this new dataset with our previous atlas (E6.5-E8.5) to produce a densely sampled timecourse of >400,000 cells from early gastrulation to organogenesis. Computational lineage reconstruction identified complex waves of blood and endothelial development, including a new programme for somite-derived endothelium. We also dissected the E7.5 primitive streak into four adjacent regions, performed scRNA-seq and predicted cell fates computationally. Finally, we defined developmental state/fate relationships by combining orthotopic grafting, microscopic analysis and scRNA-seq to transcriptionally determine cell fates of grafted primitive streak regions after 24 h of in vitro embryo culture. Experimentally determined fate outcomes were in good agreement with computationally predicted fates, demonstrating how classical grafting experiments can be revisited to establish high-resolution cell state/fate relationships. Such interdisciplinary approaches will benefit future studies in developmental biology and guide the in vitro production of cells for organ regeneration and repair

Computational Single-Cell Genomics Methods for Cell State Estimation and their Application to Hematopoietic Systems

The focus of this doctoral dissertation was to develop novel and scalable computational genomics methods for analysing single-cell genomic modalities. Scarf, a highly memory-efficient single-cell data analysis toolkit, was developed to enable an analysis of very large-scale datasets on personal computers, and the execution of parallel workflows on server-scale computational systems. The advances in data chunking algorithms were leveraged, and several optimisations in current workflows were established to reduce memory usage across multiple analysis steps dramatically. A systematic benchmarking across atlas-scale single-cell RNA-Seq and ATAC-Seq datasets was performed to validate Scarf's robust memory efficiency, even under the most demanding parameter sets. Within Scarf's framework, a graph-based hierarchical clustering algorithm was introduced that reveals complex nested cellular hierarchies at a single-cell resolution. Scarf contains a data subsampling algorithm for retaining rare cells and preserving cell state change trajectories. This topology-assisted cell downsampling algorithm (TopACeDo) was benchmarked on atlas-scale datasets and found superior to existing solutions on multiple metrics.Single-cell genomics has opened new avenues for investigating the heterogeneity of complex cellular populations. Human CD34+ hematopoietic cells are known to harbour stem cells and lineage progenitors responsible for populating the entire blood tissue. A combination of the surface proteome and transcriptome data revealed that cord blood-derived CD34+ hematopoietic cells have a higher proportion of multipotent progenitors than the bone marrow-derived population. Further, the CD38-CD35+ immunophenotype was identified as marking the most primitive stem cells in the bone marrow-derived population. Chromatin accessibility profiles were generated for CD34+, CD34+CD38- and CD34+CD38-CD35+ cells using scATAC-Seq. A comparison of these profiles showed that CD35+ immunophenotype marks a stable epigenomic cell state corresponding to primitive hemopoietic stem cell identity. A unique enhancer signature was derived for these primitive cells, which was found to be enriched in NFAT and STAT family transcription factor motifs. The mouse hematopoietic stem and progenitor cell (HSPC) population is, immunophenotypically, one of the most well-characterised cell systems. However, the underlying chromatin basis of multiple intermediate cell states in the early differentiation steps is unknown. By applying scATAC-Seq on multiple sorted HSPC populations, we uncovered regulatory elements associated with differentiation stages, linage specification and loss of multipotentiality. Furthermore, focussing on the FLT3 intermediate population (FLT3int), an understudied population within the HSPC pool, it was found that FLT3intCD9+ cells retained multilineage potential while FLT3intCD9- cells did not.Single-cell genomics has the potential to reveal cell-of-origin in case of neoplastic cell transformation. The existing computational approaches treat the transcriptomic shifts in the neoplasm as batch effects to reveal the healthy equivalent cells that could be cells of origin. However, this can lead to misleading results in conditions where technical batch effects confound the transcriptomic shifts. To solve this, we developed a computational method called Nabo that uses a projection-based approach such that the cell populations suspected of containing neoplastic cells can be interpreted within the heterogeneity context of a reference healthy cell population. Nabo's dynamic feature rejection algorithm considers only the relevant features for comparison. In murine HSPC hierarchy, primitive HSCs are known to be insensitive to MLL-ENL-induced leukemic transformation; however, GMLPs are sensitive to such transformation. Comparison of single-cell RNA-Seq profiles of wild type GMLPs and MLL-ENL-induced GMLPs using Nabo showed that the leukemic cells reflected the transcriptomic state of most primitive GMLPs. Projection of both the populations onto cKit+ HSPCs showed Nabo's ability to identify the cells of origin in a leukemic context and indicate how MLL-ENL induction leads to differentiation arrests in GMLP cells

safi_et_al_seq_data

This repository contains the data and code that can be used to reproduce the findings and figures in the manuscrip