Endogenous Small RNA Clusters in Plants
Yong-Xin Liu, Meng Wang, Xiu-Jie Wang
In plants, small RNAs (sRNAs) usually refer to non-coding RNAs (ncRNAs) with lengths of 20–24 nucleotides. sRNAs are involved in the regulation of many essential processes related to plant development and environmental responses. sRNAs in plants are mainly grouped into microRNAs (miRNAs) and small interfering RNAs (siRNAs), and the latter can be further classified into trans-acting siRNAs (ta-siRNAs), repeat-associated siRNAs (ra-siRNAs), natural anti-sense siRNAs (nat-siRNAs), etc. Many sRNAs exhibit a clustered distribution pattern in the genome. Here, we summarize the features and functions of cluster-distributed sRNAs, aimed to not only provide a thorough picture of sRNA clusters (SRCs) in plants, but also shed light on the identification of new classes of functional sRNAs.
Genome-wide Mapping of Cellular Protein–RNA Interactions Enabled by Chemical Crosslinking
Xiaoyu Li, Jinghui Song, Chengqi Yi
RNA–protein interactions influence many biological processes. Identifying the binding sites of RNA-binding proteins (RBPs) remains one of the most fundamental and important challenges to the studies of such interactions. Capturing RNA and RBPs via chemical crosslinking allows stringent purification procedures that significantly remove the non-specific RNA and protein interactions. Two major types of chemical crosslinking strategies have been developed to date, i.e., UV-enabled crosslinking and enzymatic mechanism-based covalent capture. In this review, we compare such strategies and their current applications, with an emphasis on the technologies themselves rather than the biology that has been revealed. We hope such methods could benefit broader audience and also urge for the development of new methods to study RNA−RBP interactions.
Characterization of miRNomes in Acute and Chronic Myeloid Leukemia Cell Lines
Qian Xiong , Yadong Yang, Hai Wang, Jie Li, Shaobin Wang, Yanming Li , Yaran Yang, Kan Cai, Xiuyan Ruan, Jiangwei Yan, Songnian Hu , Xiangdong Fang
Myeloid leukemias are highly diverse diseases and have been shown to be associated with microRNA (miRNA) expression aberrations. The present study involved an in-depth miRNome analysis of two human acute myeloid leukemia (AML) cell lines, HL-60 and THP-1, and one human chronic myeloid leukemia (CML) cell line, K562, via massively parallel signature sequencing. mRNA expression profiles of these cell lines that were established previously in our lab facilitated an integrative analysis of miRNA and mRNA expression patterns. miRNA expression profiling followed by differential expression analysis and target prediction suggested numerous miRNA signatures in AML and CML cell lines. Some miRNAs may act as either tumor suppressors or oncomiRs in AML and CML by targeting key genes in AML and CML pathways. Expression patterns of cell type-specific miRNAs could partially reflect the characteristics of K562, HL-60 and THP-1 cell lines, such as actin filament-based processes, responsiveness to stimulus and phagocytic activity. miRNAs may also regulate myeloid differentiation, since they usually suppress differentiation regulators. Our study provides a resource to further investigate the employment of miRNAs in human leukemia subtyping, leukemogenesis and myeloid development. In addition, the distinctive miRNA signatures may be potential candidates for the clinical diagnosis, prognosis and treatment of myeloid leukemias.
Mining the 3′UTR of Autism-implicated Genes for SNPs Perturbing MicroRNA Regulation
Varadharajan Vaishnavi, Mayakannan Manikandan, Arasambattu Kannan Munirajan
Autism spectrum disorder (ASD) refers to a group of childhood neurodevelopmental disorders with polygenic etiology. The expression of many genes implicated in ASD is tightly regulated by various factors including microRNAs (miRNAs), a class of noncoding RNAs ∼22 nucleotides in length that function to suppress translation by pairing with ‘miRNA recognition elements’ (MREs) present in the 3′untranslated region (3′UTR) of target mRNAs. This emphasizes the role played by miRNAs in regulating neurogenesis, brain development and differentiation and hence any perturbations in this regulatory mechanism might affect these processes as well. Recently, single nucleotide polymorphisms (SNPs) present within 3′UTRs of mRNAs have been shown to modulate existing MREs or even create new MREs. Therefore, we hypothesized that SNPs perturbing miRNA-mediated gene regulation might lead to aberrant expression of autism-implicated genes, thus resulting in disease predisposition or pathogenesis in at least a subpopulation of ASD individuals. We developed a systematic computational pipeline that integrates data from well-established databases. By following a stringent selection criterion, we identified 9 MRE-modulating SNPs and another 12 MRE-creating SNPs in the 3′UTR of autism-implicated genes. These high-confidence candidate SNPs may play roles in ASD and hence would be valuable for further functional validation.
PrimerSeq: Design and Visualization of RT-PCR Primers for Alternative Splicing Using RNA-seq Data
Collin Tokheim, Juw Won Park, Yi Xing
The vast majority of multi-exon genes in higher eukaryotes are alternatively spliced and changes in alternative splicing (AS) can impact gene function or cause disease. High-throughput RNA sequencing (RNA-seq) has become a powerful technology for transcriptome-wide analysis of AS, but RT-PCR still remains the gold-standard approach for quantifying and validating exon splicing levels. We have developed PrimerSeq, a user-friendly software for systematic design and visualization of RT-PCR primers using RNA-seq data. PrimerSeq incorporates user-provided transcriptome profiles (i.e., RNA-seq data) in the design process, and is particularly useful for large-scale quantitative analysis of AS events discovered from RNA-seq experiments. PrimerSeq features a graphical user interface (GUI) that displays the RNA-seq data juxtaposed with the expected RT-PCR results. To enable primer design and visualization on user-provided RNA-seq data and transcript annotations, we have developed PrimerSeq as a stand-alone software that runs on local computers. PrimerSeq is freely available for Windows and Mac OS X along with source code at http://primerseq.sourceforge.net/. With the growing popularity of RNA-seq for transcriptome studies, we expect PrimerSeq to help bridge the gap between high-throughput RNA-seq discovery of AS events and molecular analysis of candidate events by RT-PCR.