No abstract

Summary: Computational genomics seeks to draw biological inferences from genomic datasets, often by integrating and contextualizing next-generation sequencing data. CGAT provides an extensive suite of tools designed to assist in the analysis of genome scale data from a range of standard file formats. The toolkit enables filtering, comparison, conversion, summarization and annotation of genomic intervals, gene sets and sequences. The tools can both be run from the Unix command line and installed into visual workflow builders, such as Galaxy.Availability: The toolkit is freely available from http://github.com/CGATOxford/cgatContact: andreas.heger@dpag.ox.ac.uk

Unique Molecular Identifiers (UMIs) are random oligonucleotide barcodes that are increasingly used in high-throughout sequencing experiments. Through a UMI, identical copies arising from distinct molecules can be distinguished from those arising through PCR amplification of the same molecule. However, bioinformatic methods to leverage the information from UMIs have yet to be formalised. In particular, sequencing errors in the UMI sequence are often ignored, or else resolved in an ad-hoc manner. We show that errors in the UMI sequence are common and introduce network-based methods to account for these errors when identifying PCR duplicates. Using these methods, we demonstrate improved quantification accuracy both under simulated conditions and real iCLIP and single cell RNA-Seq datasets. Reproducibility between iCLIP replicates and single cell RNA-Seq clustering are both improved using our proposed network-based method, demonstrating the value of properly accounting for errors in UMIs. These methods are implemented in the open source UMI-tools software package (https://github.com/CGATOxford/UMI-tools).

Unmutated (UM) immunoglobulin heavy chain variable region (IgHV) status or IgHV3-21 gene usage is associated with poor prognosis in chronic lymphocytic leukemia (CLL) patients. Interestingly, IgHV3-21 is often co-expressed with light chain IgLV3-21, which is potentially able to trigger cell-autonomous BCR-mediated signaling. However, this light chain has never been characterized independently of the heavy chain IgHV3-21. We performed total RNA sequencing in 32 patients and investigated IgLV3-21 prognostic impact in terms of treatment-free survival (TFS) and overall survival (OS) in 3 other independent cohorts for a total of 813 patients. IgLV3-21 presence was tested by real-time PCR and confirmed by Sanger sequencing. Using total RNA sequencing to characterize 32 patients with high-risk CLL, we found a high frequency (28%) of IgLV3-21 rearrangements. Gene set enrichment analysis revealed that these patients express higher levels of genes responsible for ribosome biogenesis and translation initiation ( < 0.0001) as well as MYC target genes ( = 0.0003). Patients with IgLV3-21 rearrangements displayed a significantly shorter TFS and OS ( < 0.05), particularly those with IgHV mutation. In each of the three independent validation cohorts, we showed that IgLV3-21 rearrangements-similar to UM IgHV status-conferred poor prognosis compared with mutated IgHV ( < 0.0001). Importantly, we confirmed by multivariate analysis that this was independent of IgHV mutational status or subset #2 stereotyped receptor ( < 0.0001). We have demonstrated for the first time that a light chain can affect CLL prognosis and that IgLV3-21 light chain usage defines a new subgroup of CLL patients with poor prognosis. .