Global profiling of miRNAs and the hairpin precursors: insights into miRNA processing and novel miRNA discovery

MicroRNAs (miRNAs) constitute an important class of small regulatory RNAs that are derived from distinct hairpin precursors (pre-miRNAs). In contrast to mature miRNAs, which have been characterized in numerous genome-wide studies of different organisms, research on global profiling of pre-miRNAs is limited. Here, using massive parallel sequencing, we have performed global characterization of both mouse mature and precursor miRNAs. In total, 87 369 704 and 252 003 sequencing reads derived from 887 mature and 281 precursor miRNAs were obtained, respectively. Our analysis revealed new aspects of miRNA/pre-miRNA processing and modification, including eight Ago2-cleaved pre-miRNAs, eight new instances of miRNA editing and exclusively 5' tailed mirtrons. Furthermore, based on the sequences of both mature and precursor miRNAs, we developed a miRNA discovery pipeline, miRGrep, which does not rely on the availability of genome reference sequences. In addition to 239 known mouse pre-miRNAs, miRGrep predicted 41 novel ones with high confidence. Similar as known ones, the mature miRNAs derived from most of these novel loci showed both reduced abundance following Dicer knockdown and the binding with Argonaute2. Evaluation on data sets obtained from Caenorhabditis elegans and Caenorhabditis sp.11 demonstrated that miRGrep could be widely used for miRNA discovery in metazoans, especially in those without genome reference sequences

Identification of novel and known miRNAs in deep-sequencing data with miRDeep2

miRNAs comprise an abundant class of small non-coding RNAs that play important roles in a wide range of biological processes by post-transcriptional regulation of a large fraction of animal genes. High-throughput sequencing machines and the availability of completely sequenced genomes make it possible to reliably identify miRNAs with computational methods. This unit documents how to use the miRDeep2 software package to identify novel and known microRNAs in small RNA deep-sequencing data. Moreover, the usage of miRDeep2 to profile miRNA expression across samples is illustrated

Identification of small ORFs in vertebrates using ribosome footprinting and evolutionary conservation

Identification of the coding elements in the genome is a fundamental step to understanding the building blocks of living systems. Short peptides (< 100 aa) have emerged as important regulators of development and physiology, but their identification has been limited by their size. We have leveraged the periodicity of ribosome movement on the mRNA to define actively translated ORFs by ribosome footprinting. This approach identifies several hundred translated small ORFs in zebrafish and human. Computational prediction of small ORFs from codon conservation patterns corroborates and extends these findings and identifies conserved sequences in zebrafish and human, suggesting functional peptide products (micropeptides). These results identify micropeptide-encoding genes in vertebrates, providing an entry point to define their function in vivo

Acute Phase Reactants in Infections: Evidence-Based Review and a Guide for Clinicians

Expansions of amino acid repeats occur in >20 inherited human disorders, and many occur in intrinsically disordered regions (IDRs) of transcription factors (TFs). Such diseases are associated with protein aggregation, but the contribution of aggregates to pathology has been controversial. Here, we report that alanine repeat expansions in the HOXD13 TF, which cause hereditary synpolydactyly in humans, alter its phase separation capacity and its capacity to co-condense with transcriptional co-activators. HOXD13 repeat expansions perturb the composition of HOXD13-containing condensates in vitro and in vivo and alter the transcriptional program in a cell-specific manner in a mouse model of synpolydactyly. Disease-associated repeat expansions in other TFs (HOXA13, RUNX2, and TBP) were similarly found to alter their phase separation. These results suggest that unblending of transcriptional condensates may underlie human pathologies. We present a molecular classification of TF IDRs, which provides a framework to dissect TF function in diseases associated with transcriptional dysregulation

Circular RNAs are a large class of animal RNAs with regulatory potency

Circular RNAs (circRNAs) in animals are an enigmatic class of RNA with unknown function. To explore circRNAs systematically, we sequenced and computationally analysed human, mouse and nematode RNA. We detected thousands of well-expressed, stable circRNAs, often showing tissue/developmental-stage-specific expression. Sequence analysis indicated important regulatory functions for circRNAs. We found that a human circRNA, antisense to the cerebellar degeneration-related protein 1 transcript (CDR1as), is densely bound by microRNA (miRNA) effector complexes and harbours 63 conserved binding sites for the ancient miRNA miR-7. Further analyses indicated that CDR1as functions to bind miR-7 in neuronal tissues. Human CDR1as expression in zebrafish impaired midbrain development, similar to knocking down miR-7, suggesting that CDR1as is a miRNA antagonist with a miRNA-binding capacity ten times higher than any other known transcript. Together, our data provide evidence that circRNAs form a large class of post-transcriptional regulators. Numerous circRNAs form by head-to-tail splicing of exons, suggesting previously unrecognized regulatory potential of coding sequences

Integrative analysis of the caenorhabditis elegans genome by the modENCODE project

We systematically generated large-scale data sets to improve genome annotation for the nematode Caenorhabditis elegans, a key model organism. These data sets include transcriptome profiling across a developmental time course, genome-wide identification of transcription factor-binding sites, and maps of chromatin organization. From this, we created more complete and accurate gene models, including alternative splice forms and candidate noncoding RNAs. We constructed hierarchical networks of transcription factor-binding and microRNA interactions and discovered chromosomal locations bound by an unusually large number of transcription factors. Different patterns of chromatin composition and histone modification were revealed between chromosome arms and centers, with similarly prominent differences between autosomes and the X chromosome. Integrating data types, we built statistical models relating chromatin, transcription factor binding, and gene expression. Overall, our analyses ascribed putative functions to most of the conserved genome