A ß-Catenin-TCF-Sensitive Locus Control Region Mediates GUCY2C Ligand Loss in Colorectal Cancer.

BACKGROUND & AIMS: Sporadic colorectal cancers arise from initiating mutations in APC, producing oncogenic ß-catenin/TCF-dependent transcriptional reprogramming. Similarly, the tumor suppressor axis regulated by the intestinal epithelial receptor GUCY2C is among the earliest pathways silenced in tumorigenesis. Retention of the receptor, but loss of its paracrine ligands, guanylin and uroguanylin, is an evolutionarily conserved feature of colorectal tumors, arising in the earliest dysplastic lesions. Here, we examined a mechanism of GUCY2C ligand transcriptional silencing by ß-catenin/TCF signaling. METHODS: We performed RNA sequencing analysis of 4 unique conditional human colon cancer cell models of ß-catenin/TCF signaling to map the core Wnt-transcriptional program. We then performed a comparative analysis of orthogonal approaches, including luciferase reporters, chromatin immunoprecipitation sequencing, CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats) knockout, and CRISPR epigenome editing, which were cross-validated with human tissue chromatin immunoprecipitation sequencing datasets, to identify functional gene enhancers mediating GUCY2C ligand loss. RESULTS: RNA sequencing analyses reveal the GUCY2C hormones as 2 of the most sensitive targets of ß-catenin/TCF signaling, reflecting transcriptional repression. The GUCY2C hormones share an insulated genomic locus containing a novel locus control region upstream of the guanylin promoter that mediates the coordinated silencing of both genes. Targeting this region with CRISPR epigenome editing reconstituted GUCY2C ligand expression, overcoming gene inactivation by mutant ß-catenin/TCF signaling. CONCLUSIONS: These studies reveal DNA elements regulating corepression of GUCY2C ligand transcription by ß-catenin/TCF signaling, reflecting a novel pathophysiological step in tumorigenesis. They offer unique genomic strategies that could reestablish hormone expression in the context of canonical oncogenic mutations to reconstitute the GUCY2C axis and oppose transformation.

iSeqQC: a tool for expression-based quality control in RNA sequencing.

BACKGROUND: Quality Control in any high-throughput sequencing technology is a critical step, which if overlooked can compromise an experiment and the resulting conclusions. A number of methods exist to identify biases during sequencing or alignment, yet not many tools exist to interpret biases due to outliers. RESULTS: Hence, we developed iSeqQC, an expression-based QC tool that detects outliers either produced due to variable laboratory conditions or due to dissimilarity within a phenotypic group. iSeqQC implements various statistical approaches including unsupervised clustering, agglomerative hierarchical clustering and correlation coefficients to provide insight into outliers. It can be utilized through command-line (Github: https://github.com/gkumar09/iSeqQC) or web-interface (http://cancerwebpa.jefferson.edu/iSeqQC). A local shiny installation can also be obtained from github (https://github.com/gkumar09/iSeqQC). CONCLUSION: iSeqQC is a fast, light-weight, expression-based QC tool that detects outliers by implementing various statistical approaches.

The complex transcriptional landscape of the anucleate human platelet.

BACKGROUND: Human blood platelets are essential to maintaining normal hemostasis, and platelet dysfunction often causes bleeding or thrombosis. Estimates of genome-wide platelet RNA expression using microarrays have provided insights to the platelet transcriptome but were limited by the number of known transcripts. The goal of this effort was to deep-sequence RNA from leukocyte-depleted platelets to capture the complex profile of all expressed transcripts. RESULTS: From each of four healthy individuals we generated long RNA (≥40 nucleotides) profiles from total and ribosomal-RNA depleted RNA preparations, as well as short RNA (<40 nucleotides) profiles. Analysis of ~1 billion reads revealed that coding and non-coding platelet transcripts span a very wide dynamic range (≥16 PCR cycles beyond ß-actin), a result we validated through qRT-PCR on many dozens of platelet messenger RNAs. Surprisingly, ribosomal-RNA depletion significantly and adversely affected estimates of the relative abundance of transcripts. Of the known protein-coding loci, ~9,500 are present in human platelets. We observed a strong correlation between mRNAs identified by RNA-seq and microarray for well-expressed mRNAs, but RNASeq identified many more transcripts of lower abundance and permitted discovery of novel transcripts. CONCLUSIONS: Our analyses revealed diverse classes of non-coding RNAs, including: pervasive antisense transcripts to protein-coding loci; numerous, previously unreported and abundant microRNAs; retrotransposons; and thousands of novel un-annotated long and short intronic transcripts, an intriguing finding considering the anucleate nature of platelets. The data are available through a local mirror of the UCSC genome browser and can be accessed at: http://cm.jefferson.edu/platelets_2012/.