Phillipe Loher

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 β-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/.

Sex hormones and their receptors play critical roles in the development and progression of the breast and prostate cancers. Here we report that a novel type of transfer RNA (tRNA)-derived small RNA, termed Sex HOrmone-dependent TRNA-derived RNAs (SHOT-RNAs), are specifically and abundantly expressed in estrogen receptor (ER)-positive breast cancer and androgen receptor (AR)-positive prostate cancer cell lines. SHOT-RNAs are not abundantly present in ER(-) breast cancer, AR(-) prostate cancer, or other examined cancer cell lines from other tissues. ER-dependent accumulation of SHOT-RNAs is not limited to a cell culture system, but it also occurs in luminal-type breast cancer patient tissues. SHOT-RNAs are produced from aminoacylated mature tRNAs by angiogenin-mediated anticodon cleavage, which is promoted by sex hormones and their receptors. Resultant 5'- and 3'-SHOT-RNAs, corresponding to 5'- and 3'-tRNA halves, bear a cyclic phosphate (cP) and an amino acid at the 3'-end, respectively. By devising a "cP-RNA-seq" method that is able to exclusively amplify and sequence cP-containing RNAs, we identified the complete repertoire of 5'-SHOT-RNAs. Furthermore, 5'-SHOT-RNA, but not 3'-SHOT-RNA, has significant functional involvement in cell proliferation. These results have unveiled a novel tRNA-engaged pathway in tumorigenesis of hormone-dependent cancers and implicate SHOT-RNAs as potential candidates for biomarkers and therapeutic targets.

Two decades after the discovery of the first animal microRNA (miRNA), the number of miRNAs in animal genomes remains a vexing question. Here, we report findings from analyzing 1,323 short RNA sequencing samples (RNA-seq) from 13 different human tissue types. Using stringent thresholding criteria, we identified 3,707 statistically significant novel mature miRNAs at a false discovery rate of ≤ 0.05 arising from 3,494 novel precursors; 91.5% of these novel miRNAs were identified independently in 10 or more of the processed samples. Analysis of these novel miRNAs revealed tissue-specific dependencies and a commensurate low Jaccard similarity index in intertissue comparisons. Of these novel miRNAs, 1,657 (45%) were identified in 43 datasets that were generated by cross-linking followed by Argonaute immunoprecipitation and sequencing (Ago CLIP-seq) and represented 3 of the 13 tissues, indicating that these miRNAs are active in the RNA interference pathway. Moreover, experimental investigation through stem-loop PCR of a random collection of newly discovered miRNAs in 12 cell lines representing 5 tissues confirmed their presence and tissue dependence. Among the newly identified miRNAs are many novel miRNA clusters, new members of known miRNA clusters, previously unreported products from uncharacterized arms of miRNA precursors, and previously unrecognized paralogues of functionally important miRNA families (e.g., miR-15/107). Examination of the sequence conservation across vertebrate and invertebrate organisms showed 56.7% of the newly discovered miRNAs to be human-specific whereas the majority (94.4%) are primate lineage-specific. Our findings suggest that the repertoire of human miRNAs is far more extensive than currently represented by public repositories and that there is a significant number of lineage- and/or tissue-specific miRNAs that are uncharacterized.

Abstract Summary: MicroRNA (miRNA) target prediction is an important problem. Given an miRNA sequence the task is to determine the identity of the messenger RNAs targeted by it, the locations within them where the interactions happen and the specifics of the formed heteroduplexes. Here, we describe a web-based application, RNA22-GUI, which we have designed and implemented for the interactive exploration and in-context visualization of predictions by RNA22, one of the popular miRNA target prediction algorithms. Central to our design has been the requirement to provide informative and comprehensive visualization that is integrated with interactive search capabilities and permits one to selectively isolate and focus on relevant information that is distilled on-the-fly from a large repository of pre-compiled predictions. RNA22-GUI is currently available for Homo sapiens, Mus musculus, Drosophila melanogaster and Caenorhabditis elegans. Availability: http://cm.jefferson.edu/rna22v1.0/. Contact: Isidore.Rigoutsos@jefferson.edu Supplementary information: Supplementary data are available at Bioinformatics online.