PAREameters: a tool for computational inference of plant miRNA–mRNA targeting rules using small RNA and degradome sequencing data

MicroRNAs (miRNAs) are short, non-coding RNAs that modulate the translation-rate of messenger RNAs (mRNAs) by directing the RNA-induced silencing complex to sequence-specific targets. In plants, this typically results in cleavage and subsequent degradation of the mRNA. Degradome sequencing is a high-throughput technique developed to capture cleaved mRNA fragments and thus can be used to support miRNA target prediction. The current criteria used for miRNA target prediction were inferred on a limited number of experimentally validated A. thaliana interactions and were adapted to fit these specific interactions; thus, these fixed criteria may not be optimal across all datasets (organisms, tissues or treatments). We present a new tool, PAREameters, for inferring targeting criteria from small RNA and degradome sequencing datasets. We evaluate its performance using a more extensive set of experimentally validated interactions in multiple A. thaliana datasets. We also perform comprehensive analyses to highlight and quantify the differences between subsets of miRNA–mRNA interactions in model and non-model organisms. Our results show increased sensitivity in A. thaliana when using the PAREameters inferred criteria and that using data-driven criteria enables the identification of additional interactions that further our understanding of the RNA silencing pathway in both model and non-model organisms

Mate choice and gene expression signatures associated with nutritional adaptation in the medfly (Ceratitis capitata)

Evolutionary responses to nutrition are key to understanding host shifts and the resulting potential for reproductive isolation. Experimental evolution has previously been used to describe the responses of the medfly (Ceratitis capitata) to larval diets with different nutritional properties. Within 30 generations this led to divergence in larval development time, egg to adult survival and adaptation in adult body size. Here we used mRNA-seq to identify differences in gene expression patterns in these same populations, using males from the 60th generation of nutritional selection. We validated differential expression by using qRT-PCR and found that genes linked to metabolism, oxidative phosphorylation and proteolysis were significantly over-represented among the differentially expressed genes. The results provide the first genome-wide survey of the putative mechanisms underpinning evolved responses to nutritional adaptation. In addition, we tested the hypothesis that nutritional adaptation can alter mating patterns. We found evidence for assortative mating by diet at generation 60, but not 90. Hence, the pattern was variable across generations and there was no evidence overall for any isolating mating divergence between the lines. Overall, the results provide insight into the mechanisms underpinning dietary adaptation and extend our knowledge of which traits represent core responses to nutritional selection

Global discovery and characterization of small non-coding RNAs in marine microalgae

Background Marine phytoplankton are responsible for 50% of the CO2 that is fixed annually worldwide and contribute massively to other biogeochemical cycles in the oceans. Diatoms and coccolithophores play a significant role as the base of the marine food web and they sequester carbon due to their ability to form blooms and to biomineralise. To discover the presence and regulation of short non-coding RNAs (sRNAs) in these two important phytoplankton groups, we sequenced short RNA transcriptomes of two diatom species (Thalassiosira pseudonana, Fragilariopsis cylindrus) and validated them by Northern blots along with the coccolithophore Emiliania huxleyi. Results Despite an exhaustive search, we did not find canonical miRNAs in diatoms. The most prominent classes of sRNAs in diatoms were repeat-associated sRNAs and tRNA-derived sRNAs. The latter were also present in E. huxleyi. tRNA-derived sRNAs in diatoms were induced under important environmental stress conditions (iron and silicate limitation, oxidative stress, alkaline pH), and they were very abundant especially in the polar diatom F. cylindrus (20.7% of all sRNAs) even under optimal growth conditions. Conclusions This study provides first experimental evidence for the existence of short non-coding RNAs in marine microalgae. Our data suggest that canonical miRNAs are absent from diatoms. However, the group of tRNA-derived sRNAs seems to be very prominent in diatoms and coccolithophores and maybe used for acclimation to environmental conditions

Profile and functional analysis of small RNAs derived from Aspergillus fumigatus infected with double-stranded RNA mycoviruses

Background: Mycoviruses are viruses that naturally infect and replicate in fungi. Aspergillus fumigatus, an opportunistic pathogen causing fungal lung diseases in humans and animals, was recently shown to harbour several different types of mycoviruses. A well-characterised defence against virus infection is RNA silencing. The A. fumigatus genome encodes essential components of the RNA silencing machinery, including Dicer, Argonaute and RNA-dependent RNA polymerase (RdRP) homologues. Active silencing of double-stranded (ds)RNA and the generation of small RNAs (sRNAs) has been shown for several mycoviruses and it is anticipated that a similar mechanism will be activated in A. fumigatus isolates infected with mycoviruses. Results: To investigate the existence and nature of A. fumigatus sRNAs, sRNA-seq libraries of virus-free and virus-infected isolates were created using Scriptminer adapters and compared. Three dsRNA viruses were investigated: Aspergillus fumigatus partitivirus-1 (AfuPV-1, PV), Aspergillus fumigatus chrysovirus (AfuCV, CV) and Aspergillus fumigatus tetramycovirus-1 (AfuTmV-1, NK) which were selected because they induce phenotypic changes such as coloration and sectoring. The dsRNAs of all three viruses, which included two conventionally encapsidated ones PV and CV and one unencapsidated example NK, were silenced and yielded characteristic vsiRNAs together with co-incidental silencing of host fungal genes which shared sequence homology with the viral genomes. Conclusions: Virus-derived sRNAs were detected and characterised in the presence of virus infection. Differentially expressed A. fumigatus microRNA-like (miRNA-like) sRNAs and small interfering RNAs (siRNAs) were detected and validated. Host sRNA loci which were differentially expressed as a result of virus infection were also identified. To our knowledge, this is the first study reporting the sRNA profiles of A. fumigatus isolates

Comprehensive processing of high-throughput small RNA sequencing data including quality checking, normalization, and differential expression analysis using the UEA sRNA Workbench

Recently, high-throughput sequencing (HTS) has revealed compelling details about the small RNA (sRNA) population in eukaryotes. These 20 to 25 nt noncoding RNAs can influence gene expression by acting as guides for the sequence-specific regulatory mechanism known as RNA silencing. The increase in sequencing depth and number of samples per project enables a better understanding of the role sRNAs play by facilitating the study of expression patterns. However, the intricacy of the biological hypotheses coupled with a lack of appropriate tools often leads to inadequate mining of the available data and thus, an incomplete description of the biological mechanisms involved. To enable a comprehensive study of differential expression in sRNA data sets, we present a new interactive pipeline that guides researchers through the various stages of data preprocessing and analysis. This includes various tools, some of which we specifically developed for sRNA analysis, for quality checking and normalization of sRNA samples as well as tools for the detection of differentially expressed sRNAs and identification of the resulting expression patterns. The pipeline is available within the UEA sRNA Workbench, a user-friendly software package for the processing of sRNA data sets. We demonstrate the use of the pipeline on a H. sapiens data set; additional examples on a B. terrestris data set and on an A. thaliana data set are described in the Supplemental Information. A comparison with existing approaches is also included, which exemplifies some of the issues that need to be addressed for sRNA analysis and how the new pipeline may be used to do this

MicroRNAs Associated with Caste Determination and Differentiation in a Primitively Eusocial Insect

In eusocial Hymenoptera (ants, bees and wasps), queen and worker adult castes typically arise via environmental influences. A fundamental challenge is to understand how a single genome can thereby produce alternative phenotypes. A powerful approach is to compare the molecular basis of caste determination and differentiation along the evolutionary trajectory between primitively and advanced eusocial species, which have, respectively, relatively undifferentiated and strongly differentiated adult castes. In the advanced eusocial honeybee, Apis mellifera, studies suggest that microRNAs (miRNAs) play an important role in the molecular basis of caste determination and differentiation. To investigate how miRNAs affect caste in eusocial evolution, we used deep sequencing and Northern blots to isolate caste-associated miRNAs in the primitively eusocial bumblebee Bombus terrestris. We found that the miRNAs Bte-miR-6001-5p and -3p are more highly expressed in queen- than in worker-destined late-instar larvae. These are the first caste-associated miRNAs from outside advanced eusocial Hymenoptera, so providing evidence for caste-associated miRNAs occurring relatively early in eusocial evolution. Moreover, we found little evidence that miRNAs previously shown to be associated with caste in A. mellifera were differentially expressed across caste pathways in B. terrestris, suggesting that, in eusocial evolution, the caste-associated role of individual miRNAs is not conserved

The UEA sRNA Workbench (version 4.4): a comprehensive suite of tools for analyzing miRNAs and sRNAs

Motivation: RNA interference, a highly conserved regulatory mechanism, is mediated via small RNAs (sRNA). Recent technical advances enabled the analysis of larger, complex datasets and the investigation of microRNAs and the less known small interfering RNAs. However, the size and intricacy of current data requires a comprehensive set of tools, able to discriminate the patterns from the low-level, noise-like, variation; numerous and varied suggestions from the community represent an invaluable source of ideas for future tools, the ability of the community to contribute to this software is essential. Results: We present a new version of the UEA sRNA Workbench, reconfigured to allow an easy insertion of new tools/workflows. In its released form, it comprises of a suite of tools in a user-friendly environment, with enhanced capabilities for a comprehensive processing of sRNA-seq data e.g. tools for an accurate prediction of sRNA loci (CoLIde) and miRNA loci (miRCat2), as well as workflows to guide the users through common steps such as quality checking of the input data, normalization of abundances or detection of differential expression represent the first step in sRNA-seq analyses

miRCat2: Accurate prediction of plant and animal microRNAs from next-generation sequencing datasets

Motivation: MicroRNAs are a class of ∼21-22 nucleotide small RNAs which are excised from a stable hairpin-like secondary structure. They have important gene regulatory functions and are involved in many pathways including developmental timing, organogenesis and development in eukaryotes. There are several computational tools for miRNA detection from next-generation sequencing (NGS) datasets. However, many of these tools suffer from high false positive and false negative rates. Here we present a novel miRNA prediction algorithm, miRCat2. miRCat2 incorporates a new entropy-based approach to detect miRNA loci, which is designed to cope with the high sequencing depth of current NGS datasets. It has a user-friendly interface and produces graphical representations of the hairpin structure and plots depicting the alignment of sequences on the secondary structure. Results: We tested miRCat2 on a number of animal and plant datasets and present a comparative analysis with miRCat, miRDeep2, miRPlant and miReap. We also use mutants in the miRNA biogenesis pathway to evaluate the predictions of these tools. Results indicate that miRCat2 has an improved accuracy compared with other methods tested. Moreover, miRCat2 predicts several new miRNAs that are differentially expressed in wildtype versus mutants in the miRNA biogenesis pathway. Availability: miRCat2 is part of the UEA small RNA Workbench and is freely available from http://srnaworkbench.cmp.uea.ac.uk

Integrative Single-Cell RNA-Seq and ATAC-Seq Analysis of Human Developmental Hematopoiesis.

Regulation of hematopoiesis during human development remains poorly defined. Here we applied single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) to over 8,000 human immunophenotypic blood cells from fetal liver and bone marrow. We inferred their differentiation trajectory and identified three highly proliferative oligopotent progenitor populations downstream of hematopoietic stem cells (HSCs)/multipotent progenitors (MPPs). Along this trajectory, we observed opposing patterns of chromatin accessibility and differentiation that coincided with dynamic changes in the activity of distinct lineage-specific transcription factors. Integrative analysis of chromatin accessibility and gene expression revealed extensive epigenetic but not transcriptional priming of HSCs/MPPs prior to their lineage commitment. Finally, we refined and functionally validated the sorting strategy for the HSCs/MPPs and achieved around 90% enrichment. Our study provides a useful framework for future investigation of human developmental hematopoiesis in the context of blood pathologies and regenerative medicine.The study was supported by European Research Council project 677501 – ZF_Blood (to A.C. and A.M.R), EMBO small grant (to A.C.) and a core support grant from the Wellcome Trust and MRC to the Wellcome Trust – Medical Research Council Cambridge Stem Cell Institute