Benchmarking computational methods for B-cell receptor reconstruction from single-cell RNA-seq data.

Multiple methods have recently been developed to reconstruct full-length B-cell receptors (BCRs) from single-cell RNA sequencing (scRNA-seq) data. This need emerged from the expansion of scRNA-seq techniques, the increasing interest in antibody-based drug development and the importance of BCR repertoire changes in cancer and autoimmune disease progression. However, a comprehensive assessment of performance-influencing factors such as the sequencing depth, read length or number of somatic hypermutations (SHMs) as well as guidance regarding the choice of methodology is still lacking. In this work, we evaluated the ability of six available methods to reconstruct full-length BCRs using one simulated and three experimental SMART-seq datasets. In addition, we validated that the BCRs assembled in silico recognize their intended targets when expressed as monoclonal antibodies. We observed that methods such as BALDR, BASIC and BRACER showed the best overall performance across the tested datasets and conditions, whereas only BASIC demonstrated acceptable results on very short read libraries. Furthermore, the de novo assembly-based methods BRACER and BALDR were the most accurate in reconstructing BCRs harboring different degrees of SHMs in the variable domain, while TRUST4, MiXCR and BASIC were the fastest. Finally, we propose guidelines to select the best method based on the given data characteristics.

Computational identification of cell-specific variable regions in ChIP-seq data.

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is used to identify genome-wide DNA regions bound by proteins. Given one ChIP-seq experiment with replicates, binding sites not observed in all the replicates will usually be interpreted as noise and discarded. However, the recent discovery of high-occupancy target (HOT) regions suggests that there are regions where binding of multiple transcription factors can be identified. To investigate ChIP-seq variability, we developed a reproducibility score and a method that identifies cell-specific variable regions in ChIP-seq data by integrating replicated ChIP-seq experiments for multiple protein targets on a particular cell type. Using our method, we found variable regions in human cell lines K562, GM12878, HepG2, MCF-7 and in mouse embryonic stem cells (mESCs). These variable-occupancy target regions (VOTs) are CG dinucleotide rich, and show enrichment at promoters and R-loops. They overlap significantly with HOT regions, but are not blacklisted regions producing non-specific binding ChIP-seq peaks. Furthermore, in mESCs, VOTs are conserved among placental species suggesting that they could have a function important for this taxon. Our method can be useful to point to such regions along the genome in a given cell type of interest, to improve the downstream interpretative analysis before follow-up experiments.

GADD45 promotes locus-specific DNA demethylation and 2C cycling in embryonic stem cells.

Mouse embryonic stem cell (ESC) cultures contain a rare cell population of "2C-like" cells resembling two-cell embryos, the key stage of zygotic genome activation (ZGA). Little is known about positive regulators of the 2C-like state and two-cell stage embryos. Here we show that GADD45 (growth arrest and DNA damage 45) proteins, regulators of TET (TET methylcytosine dioxygenase)-mediated DNA demethylation, promote both states. Methylome analysis of Gadd45a,b,g triple-knockout (TKO) ESCs reveal locus-specific DNA hypermethylation of ∼7000 sites, which are enriched for enhancers and loci undergoing TET-TDG (thymine DNA glycosylase)-mediated demethylation. Gene expression is misregulated in TKOs, notably upon differentiation, and displays signatures of DNMT (DNA methyltransferase) and TET targets. TKOs manifest impaired transition into the 2C-like state and exhibit DNA hypermethylation and down-regulation of 2C-like state-specific genes. Gadd45a,b double-mutant mouse embryos display embryonic sublethality, deregulated ZGA gene expression, and developmental arrest. Our study reveals an unexpected role of GADD45 proteins in embryonic two-cell stage regulation.