CRIS: complete reconstruction of immunoglobulin V-D-J sequences from RNA-seq data

MTG-Link: leveraging barcode information from linked-reads to assemble specific loci

BACKGROUND

Local assembly with short and long reads has proven to be very useful in many applications: reconstruction of the sequence of a locus of interest, gap-filling in draft assemblies, as well as alternative allele reconstruction of large Structural Variants. Whereas linked-read technologies have a great potential to assemble specific loci as they provide long-range information while maintaining the power and accuracy of short-read sequencing, there is a lack of local assembly tools for linked-read data.

RESULTS

We present MTG-Link, a novel local assembly tool dedicated to linked-reads. The originality of the method lies in its read subsampling step which takes advantage of the barcode information contained in linked-reads mapped in flanking regions. We validated our approach on several datasets from different linked-read technologies. We show that MTG-Link is able to assemble successfully large sequences, up to dozens of Kb. We also demonstrate that the read subsampling step of MTG-Link considerably improves the local assembly of specific loci compared to other existing short-read local assembly tools. Furthermore, MTG-Link was able to fully characterize large insertion variants and deletion breakpoints in a human genome and to reconstruct dark regions in clinically-relevant human genes. It also improved the contiguity of a 1.3 Mb locus of biological interest in several individual genomes of the mimetic butterfly Heliconius numata.

CONCLUSIONS

MTG-Link is an efficient local assembly tool designed for different linked-read sequencing technologies. MTG-Link source code is available at https://github.com/anne-gcd/MTG-Link and as a Bioconda package.

RUNX1 colludes with NOTCH1 to reprogram chromatin in T cell acute lymphoblastic leukemia

Runt-related transcription factor 1 (RUNX1) is oncogenic in diverse types of leukemia and epithelial cancers where its expression is associated with poor prognosis. Current models suggest that RUNX1 cooperates with other oncogenic factors (e.g., NOTCH1, TAL1) to drive the expression of proto-oncogenes in T cell acute lymphoblastic leukemia (T-ALL) but the molecular mechanisms controlled by RUNX1 and its cooperation with other factors remain unclear. Integrative chromatin and transcriptional analysis following inhibition of RUNX1 and NOTCH1 revealed a surprisingly widespread role of RUNX1 in the establishment of global H3K27ac levels and that RUNX1 is required by NOTCH1 for cooperative transcription activation of key NOTCH1 target genes including MYC, DTX1, HES4, IL7R, and NOTCH3. Super-enhancers were preferentially sensitive to RUNX1 knockdown and RUNX1-dependent super-enhancers were disrupted following the treatment of a pan-BET inhibitor, I-BET151.

Single-cell profiling reveals a memory B cell-like subtype of follicular lymphoma with increased transformation risk

Follicular lymphoma (FL) is an indolent cancer of mature B-cells but with ongoing risk of transformation to more aggressive histology over time. Recurrent mutations associated with transformation have been identified; however, prognostic features that can be discerned at diagnosis could be clinically useful. We present here comprehensive profiling of both tumor and immune compartments in 155 diagnostic FL biopsies at single-cell resolution by mass cytometry. This revealed a diversity of phenotypes but included two recurrent patterns, one which closely resembles germinal center B-cells (GCB) and another which appears more related to memory B-cells (MB). GCB-type tumors are enriched for EZH2, TNFRSF14, and MEF2B mutations, while MB-type tumors contain increased follicular helper T-cells. MB-type and intratumoral phenotypic diversity are independently associated with increased risk of transformation, supporting biological relevance of these features. Notably, a reduced 26-marker panel retains sufficient information to allow phenotypic profiling of future cohorts by conventional flow cytometry.