The miR-144/Hmgn2 regulatory axis orchestrates chromatin organization during erythropoiesis.

Differentiation of stem and progenitor cells is a highly regulated process that involves the coordinated action of multiple layers of regulation. Here we show how the post-transcriptional regulatory layer instructs the level of chromatin regulation via miR-144 and its targets to orchestrate chromatin condensation during erythropoiesis. The loss of miR-144 leads to impaired chromatin condensation during erythrocyte maturation. Among the several targets of miR-144 that influence chromatin organization, the miR-144-dependent regulation of Hmgn2 is conserved from fish to humans. Our genetic probing of the miR-144/Hmgn2 regulatory axis establish that intact miR-144 target sites in the Hmgn2 3'UTR are necessary for the proper maturation of erythrocytes in both zebrafish and human iPSC-derived erythroid cells while loss of Hmgn2 rescues in part the miR-144 null phenotype. Altogether, our results uncover miR-144 and its target Hmgn2 as the backbone of the genetic regulatory circuit that controls the terminal differentiation of erythrocytes in vertebrates.

The miR-144/Hmgn2 regulatory axis orchestrates chromatin organization during erythropoiesis.

Differentiation of stem and progenitor cells is a highly regulated process that involves the coordinated action of multiple layers of regulation. Here we show how the post-transcriptional regulatory layer instructs the level of chromatin regulation via miR-144 and its targets to orchestrate chromatin condensation during erythropoiesis. The loss of miR-144 leads to impaired chromatin condensation during erythrocyte maturation. Among the several targets of miR-144 that influence chromatin organization, the miR-144-dependent regulation of Hmgn2 is conserved from fish to humans. Our genetic probing of the miR-144/Hmgn2 regulatory axis established that intact miR-144 target sites in the Hmgn2 3'UTR are necessary for the proper maturation of erythrocytes in both zebrafish and human iPSC-derived erythroid cells while loss of Hmgn2 rescues in part the miR-144 null phenotype. Altogether, our results uncover miR-144 and its target Hmgn2 as the backbone of the genetic regulatory circuit that controls the terminal differentiation of erythrocytes in vertebrates.

Absence of the primary cilia formation gene Talpid3 impairs muscle stem cell function.

Skeletal muscle stem cells (MuSC) are crucial for tissue homoeostasis and repair after injury. Following activation, they proliferate to generate differentiating myoblasts. A proportion of cells self-renew, re-enter the MuSC niche under the basal lamina outside the myofiber and become quiescent. Quiescent MuSC have a primary cilium, which is disassembled upon cell cycle entry. Ex vivo experiments suggest cilia are important for MuSC self-renewal, however, their requirement for muscle regeneration in vivo remains poorly understood. Talpid3 (TA3) is essential for primary cilia formation and Hedgehog (Hh) signalling. Here we use tamoxifen-inducible conditional deletion of TA3 in MuSC (iSC-KO) and show that regeneration is impaired in response to cytotoxic injury. Depletion of MuSC after regeneration suggests impaired self-renewal, also consistent with an exacerbated phenotype in TA3iSC-KO mice after repeat injury. Single cell transcriptomics of MuSC progeny isolated from myofibers identifies components of several signalling pathways, which are deregulated in absence of TA3, including Hh and Wnt. Pharmacological activation of Wnt restores muscle regeneration, while purmorphamine, an activator of the Smoothened (Smo) co-receptor in the Hh pathway, has no effect. Together, our data show that TA3 and primary cilia are important for MuSC self-renewal and pharmacological treatment can efficiently restore muscle regeneration.

Sex-biased gene expression in nutrient-sensing pathways.

Differences in lifespan between males and females are found across many taxa and may be determined, at least in part, by differential responses to diet. Here we tested the hypothesis that the higher dietary sensitivity of female lifespan is mediated by higher and more dynamic expression in nutrient-sensing pathways in females. We first reanalysed existing RNA-seq data, focusing on 17 nutrient-sensing genes with reported lifespan effects. This revealed, consistent with the hypothesis, a dominant pattern of female-biased gene expression, and among sex-biased genes there tended to be a loss of female-bias after mating. We then tested directly the expression of these 17 nutrient-sensing genes in wild-type third instar larvae, once-mated 5- and 16-day-old adults. This confirmed sex-biased gene expression and showed that it was generally absent in larvae, but frequent and stable in adults. Overall, the findings suggest a proximate explanation for the sensitivity of female lifespan to dietary manipulations. We suggest that the contrasting selective pressures to which males and females are subject create differing nutritional demands and requirements, resulting in sex differences in lifespan. This underscores the potential importance of the health impacts of sex-specific dietary responses.

Degradome Assisted Plant MicroRNA Prediction Under Alternative Annotation Criteria.

Current microRNA (miRNA) prediction methods are generally based on annotation criteria that tend to miss potential functional miRNAs. Recently, new miRNA annotation criteria have been proposed that could lead to improvements in miRNA prediction methods in plants. Here, we investigate the effect of the new criteria on miRNA prediction in Arabidopsis thaliana and present a new degradome assisted functional miRNA prediction approach. We investigated the effect by applying the new criteria, and a more permissive criteria on miRNA prediction using existing miRNA prediction tools. We also developed an approach to miRNA prediction that is assisted by the functional information extracted from the analysis of degradome sequencing. We demonstrate the improved performance of degradome assisted miRNA prediction compared to unassisted prediction and evaluate the approach using miRNA differential expression analysis. We observe how the miRNA predictions fit under the different criteria and show a potential novel miRNA that has been missed within Arabidopsis thaliana. Additionally, we introduce a freely available software 'PAREfirst' that employs the degradome assisted approach. The study shows that some miRNAs could be missed due to the stringency of the former annotation criteria, and combining a degradome assisted approach with more permissive miRNA criteria can expand confident miRNA predictions.

Small-RNA Sequencing Reveals Altered Skeletal Muscle microRNAs and snoRNAs Signatures in Weanling Male Offspring from Mouse Dams Fed a Low Protein Diet during Lactation.

Maternal diet during gestation and lactation affects the development of skeletal muscles in offspring and determines muscle health in later life. In this paper, we describe the association between maternal low protein diet-induced changes in offspring skeletal muscle and the differential expression (DE) of small non-coding RNAs (sncRNAs). We used a mouse model of maternal protein restriction, where dams were fed either a normal (N, 20%) or a low protein (L, 8%) diet during gestation and newborns were cross-fostered to N or L lactating dams, resulting in the generation of NN, NL and LN offspring groups. Total body and tibialis anterior (TA) weights were decreased in weanling NL male offspring but were not different in the LN group, as compared to NN. However, histological evaluation of TA muscle revealed reduced muscle fibre size in both groups at weaning. Small RNA-sequencing demonstrated DE of multiple miRs, snoRNAs and snRNAs. Bioinformatic analyses of miRs-15a, -34a, -122 and -199a, in combination with known myomiRs, confirmed their implication in key muscle-specific biological processes. This is the first comprehensive report for the DE of sncRNAs in nutrition-associated programming of skeletal muscle development, highlighting the need for further research to unravel the detailed molecular mechanisms.

Characterising open chromatin in chick embryos identifies cis-regulatory elements important for paraxial mesoderm formation and axis extension.

Somites arising from paraxial mesoderm are a hallmark of the segmented vertebrate body plan. They form sequentially during axis extension and generate musculoskeletal cell lineages. How paraxial mesoderm becomes regionalised along the axis and how this correlates with dynamic changes of chromatin accessibility and the transcriptome remains unknown. Here, we report a spatiotemporal series of ATAC-seq and RNA-seq along the chick embryonic axis. Footprint analysis shows differential coverage of binding sites for several key transcription factors, including CDX2, LEF1 and members of HOX clusters. Associating accessible chromatin with nearby expressed genes identifies cis-regulatory elements (CRE) for TCF15 and MEOX1. We determine their spatiotemporal activity and evolutionary conservation in Xenopus and human. Epigenome silencing of endogenous CREs disrupts TCF15 and MEOX1 gene expression and recapitulates phenotypic abnormalities of anterior-posterior axis extension. Our integrated approach allows dissection of paraxial mesoderm regulatory circuits in vivo and has implications for investigating gene regulatory networks.

NATpare: a pipeline for high-throughput prediction and functional analysis of nat-siRNAs.

Natural antisense transcript-derived small interfering RNAs (nat-siRNAs) are a class of functional small RNA (sRNA) that have been found in both plant and animals kingdoms. In plants, these sRNAs have been shown to suppress the translation of messenger RNAs (mRNAs) by directing the RNA-induced silencing complex (RISC) to their sequence-specific mRNA target(s). Current computational tools for classification of nat-siRNAs are limited in number and can be computationally infeasible to use. In addition, current methods do not provide any indication of the function of the predicted nat-siRNAs. Here, we present a new software pipeline, called NATpare, for prediction and functional analysis of nat-siRNAs using sRNA and degradome sequencing data. Based on our benchmarking in multiple plant species, NATpare substantially reduces the time required to perform prediction with minimal resource requirements allowing for comprehensive analysis of nat-siRNAs in larger and more complex organisms for the first time. We then exemplify the use of NATpare by identifying tissue and stress specific nat-siRNAs in multiple Arabidopsis thaliana datasets.

PAREsnip2: a tool for high-throughput prediction of small RNA targets from degradome sequencing data using configurable targeting rules.

Small RNAs (sRNAs) are short, non-coding RNAs that play critical roles in many important biological pathways. They suppress the translation of messenger RNAs (mRNAs) by directing the RNA-induced silencing complex to their sequence-specific mRNA target(s). In plants, this typically results in mRNA cleavage and subsequent degradation of the mRNA. The resulting mRNA fragments, or degradome, provide evidence for these interactions, and thus degradome analysis has become an important tool for sRNA target prediction. Even so, with the continuing advances in sequencing technologies, not only are larger and more complex genomes being sequenced, but also degradome and associated datasets are growing both in number and read count. As a result, existing degradome analysis tools are unable to process the volume of data being produced without imposing huge resource and time requirements. Moreover, these tools use stringent, non-configurable targeting rules, which reduces their flexibility. Here, we present a new and user configurable software tool for degradome analysis, which employs a novel search algorithm and sequence encoding technique to reduce the search space during analysis. The tool significantly reduces the time and resources required to perform degradome analysis, in some cases providing more than two orders of magnitude speed-up over current methods.

The UEA Small RNA Workbench: A Suite of Computational Tools for Small RNA Analysis.

RNA silencing (RNA interference, RNAi) is a complex, highly conserved mechanism mediated by short, typically 20-24 nt in length, noncoding RNAs known as small RNAs (sRNAs). They act as guides for the sequence-specific transcriptional and posttranscriptional regulation of target mRNAs and play a key role in the fine-tuning of biological processes such as growth, response to stresses, or defense mechanism.High-throughput sequencing (HTS) technologies are employed to capture the expression levels of sRNA populations. The processing of the resulting big data sets facilitated the computational analysis of the sRNA patterns of variation within biological samples such as time point experiments, tissue series or various treatments. Rapid technological advances enable larger experiments, often with biological replicates leading to a vast amount of raw data. As a result, in this fast-evolving field, the existing methods for sequence characterization and prediction of interaction (regulatory) networks periodically require adapting or in extreme cases, a complete redesign to cope with the data deluge. In addition, the presence of numerous tools focused only on particular steps of HTS analysis hinders the systematic parsing of the results and their interpretation.The UEA small RNA Workbench (v1-4), described in this chapter, provides a user-friendly, modular, interactive analysis in the form of a suite of computational tools designed to process and mine sRNA datasets for interesting characteristics that can be linked back to the observed phenotypes. First, we show how to preprocess the raw sequencing output and prepare it for downstream analysis. Then we review some quality checks that can be used as a first indication of sources of variability between samples. Next we show how the Workbench can provide a comparison of the effects of different normalization approaches on the distributions of expression, enhanced methods for the identification of differentially expressed transcripts and a summary of their corresponding patterns. Finally we describe individual analysis tools such as PAREsnip, for the analysis of PARE (degradome) data or CoLIde for the identification of sRNA loci based on their expression patterns and the visualization of the results using the software. We illustrate the features of the UEA sRNA Workbench on Arabidopsis thaliana and Homo sapiens datasets.

A stable genetic polymorphism underpinning microbial syntrophy.

Syntrophies are metabolic cooperations, whereby two organisms co-metabolize a substrate in an interdependent manner. Many of the observed natural syntrophic interactions are mandatory in the absence of strong electron acceptors, such that one species in the syntrophy has to assume the role of electron sink for the other. While this presents an ecological setting for syntrophy to be beneficial, the potential genetic drivers of syntrophy remain unknown to date. Here, we show that the syntrophic sulfate-reducing species Desulfovibrio vulgaris displays a stable genetic polymorphism, where only a specific genotype is able to engage in syntrophy with the hydrogenotrophic methanogen Methanococcus maripaludis. This 'syntrophic' genotype is characterized by two genetic alterations, one of which is an in-frame deletion in the gene encoding for the ion-translocating subunit cooK of the membrane-bound COO hydrogenase. We show that this genotype presents a specific physiology, in which reshaping of energy conservation in the lactate oxidation pathway enables it to produce sufficient intermediate hydrogen for sustained M. maripaludis growth and thus, syntrophy. To our knowledge, these findings provide for the first time a genetic basis for syntrophy in nature and bring us closer to the rational engineering of syntrophy in synthetic microbial communities.

The UEA sRNA workbench: a suite of tools for analysing and visualizing next generation sequencing microRNA and small RNA datasets.

SUMMARY: RNA silencing is a complex, highly conserved mechanism mediated by small RNAs (sRNAs), such as microRNAs (miRNAs), that is known to be involved in a diverse set of biological functions including development, pathogen control, genome maintenance and response to environmental change. Advances in next generation sequencing technologies are producing increasingly large numbers of sRNA reads per sample at a fraction of the cost of previous methods. However, many bioinformatics tools do not scale accordingly, are cumbersome, or require extensive support from bioinformatics experts. Therefore, researchers need user-friendly, robust tools, capable of not only processing large sRNA datasets in a reasonable time frame but also presenting the results in an intuitive fashion and visualizing sRNA genomic features. Herein, we present the UEA sRNA workbench, a suite of tools that is a successor to the web-based UEA sRNA Toolkit, but in downloadable format and with several enhanced and additional features. AVAILABILITY: The program and help pages are available at http://srna-workbench.cmp.uea.ac.uk. CONTACT: vincent.moulton@cmp.uea.ac.uk.

PAREsnip: a tool for rapid genome-wide discovery of small RNA/target interactions evidenced through degradome sequencing.

Small RNAs (sRNAs) are a class of short (20-25 nt) non-coding RNAs that play important regulatory roles in gene expression. An essential first step in understanding their function is to confidently identify sRNA targets. In plants, several classes of sRNAs such as microRNAs (miRNAs) and trans-acting small interfering RNAs have been shown to bind with near-perfect complementarity to their messenger RNA (mRNA) targets, generally leading to cleavage of the mRNA. Recently, a high-throughput technique known as Parallel Analysis of RNA Ends (PARE) has made it possible to sequence mRNA cleavage products on a large-scale. Computational methods now exist to use these data to find targets of conserved and newly identified miRNAs. Due to speed limitations such methods rely on the user knowing which sRNA sequences are likely to target a transcript. By limiting the search to a tiny subset of sRNAs it is likely that many other sRNA/mRNA interactions will be missed. Here, we describe a new software tool called PAREsnip that allows users to search for potential targets of all sRNAs obtained from high-throughput sequencing experiments. By searching for targets of a complete 'sRNAome' we can facilitate large-scale identification of sRNA targets, allowing us to discover regulatory interaction networks.