Widespread dysregulation of mRNA splicing implicates RNA processing in the development and progression of Huntington's disease

Background In Huntington's disease (HD), a CAG repeat expansion mutation in the Huntingtin (HTT) gene drives a gain-of-function toxicity that disrupts mRNA processing. Although dysregulation of gene splicing has been shown in human HD post-mortem brain tissue, post-mortem analyses are likely confounded by cell type composition changes in late-stage HD, limiting the ability to identify dysregulation related to early pathogenesis. Methods To investigate gene splicing changes in early HD, we performed alternative splicing analyses coupled with a proteogenomics approach to identify early CAG length-associated splicing changes in an established isogenic HD cell model. Findings We report widespread neuronal differentiation stage- and CAG length-dependent splicing changes, and find an enrichment of RNA processing, neuronal function, and epigenetic modification-related genes with mutant HTT-associated splicing. When integrated with a proteomics dataset, we identified several of these differential splicing events at the protein level. By comparing with human post-mortem and mouse model data, we identified common patterns of altered splicing from embryonic stem cells through to post-mortem striatal tissue. Interpretation We show that widespread splicing dysregulation in HD occurs in an early cell model of neuronal development. Importantly, we observe HD-associated splicing changes in our HD cell model that were also identified in human HD striatum and mouse model HD striatum, suggesting that splicing-associated pathogenesis possibly occurs early in neuronal development and persists to later stages of disease. Together, our results highlight splicing dysregulation in HD which may lead to disrupted neuronal function and neuropathology. Funding This research is supported by the Lee Kong Chian School of Medicine, Nanyang Technological University Singapore Nanyang Assistant Professorship Start-Up Grant, the Singapore Ministry of Education under its Singapore Ministry of Education Academic Research Fund Tier 1 (RG23/22), the BC Children's Hospital Research Institute Investigator Grant Award (IGAP), and a Scholar Award from the Michael Smith Health Research BC

Molecular subgroups of intrahepatic cholangiocarcinoma discovered by single-cell RNA sequencing–assisted multiomics analysis

Intrahepatic cholangiocarcinoma (ICC) is a relatively rare but highly aggressive tumor type that responds poorly to chemotherapy and immunotherapy. Comprehensive molecular characterization of ICC is essential for the development of novel therapeutics. Here, we constructed two independent cohorts from two clinic centers. A comprehensive multiomics analysis of ICC via proteomic, whole-exome sequencing (WES), and single-cell RNA sequencing (scRNA-seq) was performed. Novel ICC tumor subtypes were derived in the training cohort (n = 110) using proteomic signatures and their associated activated pathways, which were further validated in a validation cohort (n = 41). Three molecular subtypes, chromatin remodeling, metabolism, and chronic inflammation, with distinct prognoses in ICC were identified. The chronic inflammation subtype was associated with a poor prognosis. Our random forest algorithm revealed that mutation of lysine methyltransferase 2D (KMT2D) frequently occurred in the metabolism subtype and was associated with lower inflammatory activity. scRNA-seq further identified an APOE+C1QB+ macrophage subtype, which showed the capacity to reshape the chronic inflammation subtype and contribute to a poor prognosis in ICC. Altogether, with single-cell transcriptome-assisted multiomics analysis, we identified novel molecular subtypes of ICC and validated APOE+C1QB+ tumor-associated macrophages as potential immunotherapy targets against ICC

TrawlerWeb: an online de novo motif discovery tool for next-generation sequencing datasets

Abstract Background A strong focus of the post-genomic era is mining of the non-coding regulatory genome in order to unravel the function of regulatory elements that coordinate gene expression (Nat 489:57–74, 2012; Nat 507:462–70, 2014; Nat 507:455–61, 2014; Nat 518:317–30, 2015). Whole-genome approaches based on next-generation sequencing (NGS) have provided insight into the genomic location of regulatory elements throughout different cell types, organs and organisms. These technologies are now widespread and commonly used in laboratories from various fields of research. This highlights the need for fast and user-friendly software tools dedicated to extracting cis-regulatory information contained in these regulatory regions; for instance transcription factor binding site (TFBS) composition. Ideally, such tools should not require prior programming knowledge to ensure they are accessible for all users. Results We present TrawlerWeb, a web-based version of the Trawler_standalone tool (Nat Methods 4:563–5, 2007; Nat Protoc 5:323–34, 2010), to allow for the identification of enriched motifs in DNA sequences obtained from next-generation sequencing experiments in order to predict their TFBS composition. TrawlerWeb is designed for online queries with standard options common to web-based motif discovery tools. In addition, TrawlerWeb provides three unique new features: 1) TrawlerWeb allows the input of BED files directly generated from NGS experiments, 2) it automatically generates an input-matched biologically relevant background, and 3) it displays resulting conservation scores for each instance of the motif found in the input sequences, which assists the researcher in prioritising the motifs to validate experimentally. Finally, to date, this web-based version of Trawler_standalone remains the fastest online de novo motif discovery tool compared to other popular web-based software, while generating predictions with high accuracy. Conclusions TrawlerWeb provides users with a fast, simple and easy-to-use web interface for de novo motif discovery. This will assist in rapidly analysing NGS datasets that are now being routinely generated. TrawlerWeb is freely available and accessible at: http://trawler.erc.monash.edu.au

Mitchell-Riley syndrome iPSCs exhibit reduced pancreatic endoderm differentiation due to a mutation in RFX6

Mitchell-Riley syndrome (MRS) is caused by recessive mutations in the regulatory factor X6 gene (RFX6) and is characterised by pancreatic hypoplasia and neonatal diabetes. To determine why individuals with MRS specifically lack pancreatic endocrine cells, we micro-CT imaged a 12-week-old foetus homozygous for the nonsense mutation RFX6 c.1129C>T, which revealed loss of the pancreas body and tail. From this foetus, we derived iPSCs and show that differentiation of these cells in vitro proceeds normally until generation of pancreatic endoderm, which is significantly reduced. We additionally generated an RFX6HA reporter allele by gene targeting in wild-type H9 cells to precisely define RFX6 expression and in parallel performed in situ hybridisation for RFX6 in the dorsal pancreatic bud of a Carnegie stage 14 human embryo. Both in vitro and in vivo, we find that RFX6 specifically labels a subset of PDX1-expressing pancreatic endoderm. In summary, RFX6 is essential for efficient differentiation of pancreatic endoderm, and its absence in individuals with MRS specifically impairs formation of endocrine cells of the pancreas head and tail

Additional file 1: of TrawlerWeb: an online de novo motif discovery tool for next-generation sequencing datasets

Table S1. Details of the assessment of TrawlerWeb. Detailed table of Fig. 1b showing, for each ChIP experiment, the ability of individual programs to uncover the correct binding site in yeast. For each individual ChIP experiment, the success or failure of 8 different algorithms including TrawlerWeb is shown. The results from the 6 algorithms (Coverage, AlignACE, Kellis, mdscan, MEME, and MEME-c) were extracted from Harbison et al. 2004 [38]. The matching motifs found by TrawlerWeb are identical to that found by Trawler_standalone (detailed previously in Ettwiller et al. 2007 [5]). The results from RSAT were performed by this study, where the matching motifs found by RSAT were described in the last column. (XLSX 190 kb

Additional file 2: of TrawlerWeb: an online de novo motif discovery tool for next-generation sequencing datasets

Table S2. Details of motif occurrence comparison between web-based motif discovery software. The highest scoring motifs discovered in DREME, MEME, RSAT peak-motifs, and TrawlerWeb and their corresponding occurrences are illustrated here. For the highest scoring motif, the number of motif occurrences were expressed as a percentage of the total number of input sequences. *MEME-ChIP pre-processes submitted sequences longer than 100 by trimming them evenly from both ends to get the centered 100 bp sequence and discards trimmed sequences containing only Ns from repeat masking. **MEME motif discovery automatically limits the run to a randomly sampled 600 sequences to reduce run time. (XLSX 576 kb