Biology subjects

Chakrabarti, A. M.

Publications and source records attributed to Chakrabarti, A. M..

3 recordsLinked to original sources

bioRxiv2018

Target-specific precision of CRISPR-mediated genome editing

The CRISPR-Cas9 system has successfully been adapted to edit the genome of various organisms. However, our ability to predict editing accuracy, efficacy and outcome at specific sites is limited by an incomplete understanding of how the bacterial system interacts with eukaryotic genomes and DNA repair machineries. Here, we performed the largest comparison of indel profiles to date, examining over one thousand sites in the genome of human cells, and uncovered general principles guiding CRISPR-mediated DNA editing. We find that precision of DNA editing varies considerably among sites, with some targets showing one highly-preferred indel and others displaying a wide range of infrequent indels. Editing precision correlates with editing efficiency, homology-associated end-joining for both insertions and deletions, and a preference for single-nucleotide insertions. Precise targets and the identity of their preferred indel can be predicted based on simple rules that mainly depend on the fourth nucleotide upstream of the PAM sequence. Regardless of precision, site-specific indel profiles are highly robust and depend on both DNA sequence and chromatin features. Our findings have important implications for clinical applications of CRISPR technology and reveal general patterns of broken end-joining that can inform us on DNA repair mechanisms in human cells.

molecular biology↗

bioRxiv2018

Heteromeric RNP assembly at LINEs controls lineage-specific RNA processing

It is challenging for RNA processing machineries to select exons within long intronic regions. We find that intronic LINE repeat sequences (LINEs) contribute to this selection by recruiting dozens of RNA-binding proteins (RBPs). This includes MATR3, which promotes binding of PTBP1 to multivalent binding sites in LINEs. Both RBPs repress splicing and 3 end processing within and around LINEs, as demonstrated in cultured human cells and mouse brain. Notably, repressive RBPs preferentially bind to evolutionarily young LINEs, which are confined to deep intronic regions. These RBPs insulate both LINEs and surrounding regions from RNA processing. Upon evolutionary divergence, gradual loss of insulation diversifies the roles of LINEs. Older LINEs are located closer to exons, are a common source of tissue-specific exons, and increasingly bind to RBPs that enhance RNA processing. Thus, LINEs are hubs for assembly of repressive RBPs, and contribute to evolution of new, lineage-specific transcripts in mammals.

genomics↗

bioRxiv2017

Data Science Issues in Understanding Protein-RNA Interactions

An interplay of experimental and computational methods is required to achieve a comprehensive understanding of protein-RNA interactions. Crosslinking and immunoprecipitation (CLIP) identifies endogenous interactions by sequencing RNA fragments that co-purify with a selected RBP under stringent conditions. Here we focus on approaches for the analysis of resulting data and appraise the methods for peak calling, visualisation, analysis and computational modelling of protein-RNA binding sites. We advocate a combined assessment of cDNA complexity and specificity for data quality control. Moreover, we demonstrate the value of analysing sequence motif enrichment in peaks assigned from CLIP data, and of visualising RNA maps, which examine the positional distribution of peaks around regulated landmarks in transcripts. We use these to assess how variations in CLIP data quality, and in different peak calling methods, affect the insights into regulatory mechanisms. We conclude by discussing future opportunities for the computational analysis of protein-RNA interaction experiments.

bioinformatics↗