Altered microRNA expression in patients with non-obstructive azoospermia

Background  

MicroRNAs (miRNAs), a class of small non-coding RNA molecules, are indicated to play essential roles in spermatogenesis. However, little is known about the expression patterns or function of miRNAs in human testes involved in infertility.     

Detecting microRNA activity from gene expression data

Background  

MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression by binding to the messenger RNA (mRNA) of protein coding genes. They control gene expression by either inhibiting translation or inducing mRNA degradation. A number of computational techniques have been developed to identify the targets of miRNAs. In this study we used predicted miRNA-gene interactions to analyse mRNA gene expression microarray data to predict miRNAs associated with particular diseases or conditions.     

Deep sequencing on genome-wide scale reveals the unique composition and expression patterns of microRNAs in developing pollen of <Emphasis Type="Italic">Oryza sativa</Emphasis>

Background  

Pollen development in flowering plants requires strict control of the gene expression program and genetic information stability by mechanisms possibly including the miRNA pathway. However, our understanding of the miRNA pathway in pollen development remains limited, and the dynamic profile of miRNAs in developing pollen is unknown.     

miRExpress: Analyzing high-throughput sequencing data for profiling microRNA expression

Background  

MicroRNAs (miRNAs), small non-coding RNAs of 19 to 25 nt, play important roles in gene regulation in both animals and plants. In the last few years, the oligonucleotide microarray is one high-throughput and robust method for detecting miRNA expression. However, the approach is restricted to detecting the expression of known miRNAs. Second-generation sequencing is an inexpensive and high-throughput sequencing method. This new method is a promising tool with high sensitivity and specificity and can be used to measure the abundance of small-RNA sequences in a sample. Hence, the expression profiling of miRNAs can involve use of sequencing rather than an oligonucleotide array. Additionally, this method can be adopted to discover novel miRNAs.     

microRNA evolution in a human transcription factor and microRNA regulatory network

Background  

microRNAs (miRNAs) are important cellular components. The understanding of their evolution is of critical importance for the understanding of their function. Although some specific evolutionary rules of miRNAs have been revealed, the rules of miRNA evolution in cellular networks remain largely unexplored. According to knowledge from protein-coding genes, the investigations of gene evolution in the context of biological networks often generate valuable observations that cannot be obtained by traditional approaches.     

Improving performance of mammalian microRNA target prediction

Background  

MicroRNAs (miRNAs) are single-stranded non-coding RNAs known to regulate a wide range of cellular processes by silencing the gene expression at the protein and/or mRNA levels. Computational prediction of miRNA targets is essential for elucidating the detailed functions of miRNA. However, the prediction specificity and sensitivity of the existing algorithms are still poor to generate meaningful, workable hypotheses for subsequent experimental testing. Constructing a richer and more reliable training data set and developing an algorithm that properly exploits this data set would be the key to improve the performance current prediction algorithms.     

Low genetic diversity and functional constraint of miRNA genes participating pollen–pistil interaction in rice

Key message

In this study, we sequenced and analyzed the expression and evolution of rice miRNA genesparticipating pollen-pistil interaction that is crucial to rice yield.

Abstract

Pollen–pistil interaction is an essential reproductive process for all flowering plants. While microRNAs (miRNAs) are important noncoding small RNAs that regulate mRNA levels in eukaryotic cells, there is little knowledge about which miRNAs involved in the early stages of pollen–pistil interaction in rice and how they evolve under this conserved process. In this study, we sequenced the small RNAs in rice from unpollinated pistil (R0), pistil from 5 min and 15 min after pollination, respectively, to identify known and novel miRNAs that are involved in this process. By comparing the corresponding mRNA-seq dataset, we identified a group of miRNAs with strong negative expression pattern with their target genes. Further investigation of all miRNA loci (MIRNAs) across 1083 public rice accessions revealed significantly reduced genetic diversity in MIRNAs with strong negative expression of their targets when comparing to those with little or no impact on targets during pollen–pistil interaction. Annotation of targets suggested that those MIRNAs with strong impact on targets were pronounced in cell wall related processes such as xylan metabolism. Additionally, plant conserved miRNAs, such as those with functions in gibberellic acid, auxin and nitrate signaling, were also with strong negative expression of their targets. Overall, our analyses identified key miRNAs participating pollen–pistil interaction and their evolutionary patterns in rice, which can facilitate the understanding of molecular mechanisms associated with seed setting.