Perera, D. | bioRxiv Science

bioRxiv2018

Multi-Omic Profiling Reveals Dynamics of the Phased Progression of Pluripotency

Pluripotency is highly dynamic and progresses through a continuum of pluripotent stem-cell states. The two states that bookend the pluripotency continuum, naive and primed, are well characterized, but our understanding of the intermediate states and transitions between them remain incomplete. Here, we dissect the dynamics of pluripotent state transitions underlying pre-to post-implantation epiblast differentiation. Through comprehensive mapping of the proteome, phosphoproteome, transcriptome, and epigenome of mouse embryonic stem cells transitioning from naive to primed pluripotency, we find that rapid, acute, and widespread changes to the phosphoproteome precede ordered changes to the epigenome, transcriptome, and proteome. Reconstruction of kinase-substrate networks reveals signaling cascades, dynamics, and crosstalk. Distinct waves of global proteomic changes demarcate discrete phases of pluripotency, characterized by cell-state-specific surface marker expression. Our data provide new insights into the multi-layered control of the phased progression of pluripotency and a foundation for modeling mechanisms underlying pre-to post-implantation epiblast differentiation.\n\nHIGHLIGHTSO_LIMulti-ome maps of cells transitioning from naive to primed pluripotency\nC_LIO_LIPhosphoproteome dynamics precede changes to epigenome, transcriptome, and proteome\nC_LIO_LIKinase-substrate network reconstruction uncovers signaling dynamics and crosstalk\nC_LIO_LIProteins and cell surface markers that track pluripotent state transitions\nC_LIO_LIComparative analysis of mouse and human pluripotent states\nC_LI

genomics↗

bioRxiv2018

Transcriptome-wide profiling of mammalian spliceosome and branchpoints with iCLIP

Studies of spliceosomal interactions are challenging due to their dynamic nature. Here we employed spliceosome iCLIP, which immunoprecipitates SmB along with snRNPs and auxiliary RNA binding proteins (RBPs), to map human spliceosome engagement with snRNAs and pre-mRNAs. This identified over 50,000 branchpoints (BPs) that have canonical sequence and structural features. Moreover, it revealed 7 binding peaks around BPs and splice sites, each precisely overlapping with binding profiles of specific splicing factors. We show how the binding patterns of these RBPs are affected by the position and strength of BPs. For example, strong or proximally located BPs preferentially bind SF3 rather than U2AF complex. Notably, these effects are partly neutralized during spliceosomal assembly in a way that depends on the core spliceosomal protein PRPF8. These insights exemplify spliceosome iCLIP as a broadly applicable method for transcriptomic studies of splicing mechanisms.

genomics↗

bioRxiv2018

In search of non-coding driver mutations by deep sequencing of regulatory elements in colorectal cancer

Large-scale whole cancer-genome sequencing projects have led to the identification of a handful of cis-regulatory driver mutations in cancer genomes. However, recent studies have demonstrated that very large cancer cohorts will be required in order to identify low frequency non-coding drivers. To further this endeavour, in this study, we performed highdepth sequencing across 95 colorectal cancers and matched normal samples using a unique target capture sequencing (TCS) assay focusing on over 35 megabases of gene regulatory elements. We first assessed coverage and variant detection capability from our TCS data, and compared this with a sample that was additionally whole-genome sequenced (WGS). TCS enabled substantially deeper sequencing and thus we detected 51% more somatic single nucleotide variants (n = 2,457) and 144% more somatic insertions and deletions (n = 39) by TCS than WGS. Variants obtained from TCS data were suitable for somatic mutational signature detection, enabling us to define the signatures associated with germline deleterious variants in MSH6 and MUTYH in samples within our cohort. Finally, we surveyed regulatory mutations to find putative drivers by assessing variant recurrence and function, identifying some regulatory variants that may influence oncogenesis. Our study demonstrates TCS to be a sequencing-efficient alternative to traditional WGS, enabling improved coverage and variant detection when seeking to identify variants at specific loci among larger cohorts. Interestingly, we found no candidate variants that have a clear driver function, suggesting that regulatory drivers may be rare in a colorectal cancer cohort of this size.\n\nAuthor SummaryIn recent years, some cancer research focus has turned towards the role of somatic mutations in the 98% of the genome that is non-coding. To investigate such mutations, we performed deep sequencing of regulatory regions and a selection of coding genes across 95 colorectal cancer and matched-normal samples. To determine the ability of our targeted deep sequencing methodology to accurately detect variants, we compared our results with those from a sample that was additionally whole-genome sequenced. We found target capture sequencing to enable greater sequencing depth, allowing the detection of 51% and 144% more somatic single nucleotide and insertion/deletion mutations, respectively. Our study here demonstrates target capture sequencing to be a useful approach for researchers seeking to identify variants at specific loci among larger cohorts. Our results also enabled the generation of mutational signatures, implicating deleterious germline single nucleotide variants in coding exons of MSH6 and MUTYH in samples within our cohort. Finally, we surveyed regulatory elements in search of somatic cancer driver mutations. We identified some regulatory variants that may influence oncogenesis, but found no candidate variants with clear driver function. These findings suggest that regulatory driver mutations may be rare in a colorectal cancer cohort of this size.

biochemistry↗