Yi Jing

Small non-coding RNAs (sncRNAs) have garnered considerable attention in recent years, following accumulating evidence of their critical roles in many cellular processes. Among sncRNAs, microRNAs (miRNAs) and their isoforms (isomiRs), tRNA-derived fragments (tRFs), rRNA-derived fragments (rRFs), and Y RNA-derived fragments (yRFs) account for more than 95% of all sncRNAs found in cells. Despite their critical regulatory roles, most sncRNAs remain uncharacterized because their functionalization is a lengthy and challenging undertaking. Knowing an sncRNA’s abundance helps prioritize among the various choices, while knowing where it localizes in the cell greatly limits the number and identity of its potential targets and helps understand its function. Most studies to date have assumed that the subcellular localization of the various sncRNA classes is understood and remains unchanged across cell types. However, as we have recently demonstrated, the subcellular distribution of sncRNAs follows complex patterns that depend on the sequence of the sncRNA, the presence or absence of post-transcriptionally added non-templated nucleotides, and the cell type. To determine the subcellular localization and abundance of sncRNAs and aid the design of targeted experimental studies of sncRNA function, we developed “Fraction-seq.” The method combines an experimental and an analytical component to remove cross-fraction contamination and reconstruct the true abundance of sncRNAs in each considered fraction. Fraction-seq can be applied to any adherent cells from any organism without modifications and can reconstruct the abundance of all categories of sncRNAs. Accompanying this detailed protocol is a newly developed port of the original SAS codes to the widely used R programming language. The codes and an example are freely available through our center’s GitHub page.

Non-coding RNAs have been commanding increasingly greater attention in recent years as the few that have been functionalized to date play important roles in key cellular processes. Here we show that N-BLR, a ~900 bp non-coding RNA, modulates the epithelial-to-mesenchymal transition, increases colorectal cancer invasion, and functions as a migration enabler by affecting the expression of ZEB1 and E-cadherin. In patients with colorectal cancer, N-BLR expression associates with tumor stage and invasion potential. As N-BLR contains several instances of a category of DNA motifs known as pyknons, we also designed a custom-made array to investigate the possibility that other pyknon loci may be transcribed. For several of the loci probed by the array we found that the corresponding pyknons are differentially expressed between cancer and normal tissue samples. Taken together the data suggest that a systematic study of other pyknon-containing non-coding RNAs like N-BLR may be warranted in the context of colorectal cancer.

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.