Quality checking and expression analysis of high-throughput small RNA sequencing data

The advent of high-throughput RNA sequencing (RNA-seq) methods have made it possible to sequence transcriptomes for the cell-wide identi�cation of small non-coding RNAs (sRNAs) and to assess their regulation using di�erential expression analysis by comparing two or more di�erent conditions. During an analysis of a typical set of sRNA sequencing (sRNA-seq) libraries, a large variety of tools and methods are used on the dataset in order to understand the data's quality, content, and to summarise the knowledge gained from the entire analysis. Many of the tools available to do this were created for mRNA sequencing (mRNA-seq) datasets. In this thesis, we present and implement a processing pipeline that can be used to assess the quality and the di�erential expression of sRNA-seq datasets over two or more di�erent conditions. We then utilise aspects of this pipeline in various sRNA-seq experiments. Firstly, we combine our pipeline with current tools for miRNA identi�cation to assess the regulation of miRNAs during larval caste di�erentiation in a novel genome; the European bumblebee (Bombus terrestris). Secondly, we explore the di�erential expression during cell stress of all classes of sRNAs using two cell lines in humans. We also �nd that a speci�c protein, Ro60, is required for the expression of mRNA-derived sRNAs during stress, similar to the way in which sRNAs derived from Y RNAs are regulated. Finally, we utilise our understanding of sRNA mapping patterns, alongside current tools for miRNA identi�cation, to search for functional miRNAs and other sRNAs in the novel genomes of two diatoms. The lack of canonical miRNA predictions in this study has repercussions for the evolutionary theory behind miRNAs. The implementation of our pipeline for sRNA-seq data provides an interactive and quality controlled work ow that can be used to process a dataset from raw sequences to the results of several di�erential expression experiments for all identi�ed sRNA classes within a sequenced transcriptome

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

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

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

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 genomes of two key bumblebee species with primitive eusocial organization

Background: The shift from solitary to social behavior is one of the major evolutionary transitions. Primitively eusocial bumblebees are uniquely placed to illuminate the evolution of highly eusocial insect societies. Bumblebees are also invaluable natural and agricultural pollinators, and there is widespread concern over recent population declines in some species. High-quality genomic data will inform key aspects of bumblebee biology, including susceptibility to implicated population viability threats. Results: We report the high quality draft genome sequences of Bombus terrestris and Bombus impatiens, two ecologically dominant bumblebees and widely utilized study species. Comparing these new genomes to those of the highly eusocial honeybee Apis mellifera and other Hymenoptera, we identify deeply conserved similarities, as well as novelties key to the biology of these organisms. Some honeybee genome features thought to underpin advanced eusociality are also present in bumblebees, indicating an earlier evolution in the bee lineage. Xenobiotic detoxification and immune genes are similarly depauperate in bumblebees and honeybees, and multiple categories of genes linked to social organization, including development and behavior, show high conservation. Key differences identified include a bias in bumblebee chemoreception towards gustation from olfaction, and striking differences in microRNAs, potentially responsible for gene regulation underlying social and other traits. Conclusions: These two bumblebee genomes provide a foundation for post-genomic research on these key pollinators and insect societies. Overall, gene repertoires suggest that the route to advanced eusociality in bees was mediated by many small changes in many genes and processes, and not by notable expansion or depauperation

Plant perception of β-aminobutyric acid is mediated by an aspartyl-tRNA synthetase

Specific chemicals can prime the plant immune system for augmented defense. β-aminobutyric acid (BABA) is a priming agent that provides broad-spectrum disease protection. However, BABA also suppresses plant growth when applied in high doses, which has hampered its application as a crop defense activator. Here we describe a mutant of Arabidopsis thaliana that is impaired in BABA-induced disease immunity (ibi1) but is hypersensitive to BABA-induced growth repression. IBI1 encodes an aspartyl-tRNA synthetase. Enantiomer-specific binding of the R enantiomer of BABA to IBI1 primed the protein for noncanonical defense signaling in the cytoplasm after pathogen attack. This priming was associated with aspartic acid accumulation and tRNA-induced phosphorylation of translation initiation factor eIF2α. However, mutation of eIF2α-phosphorylating GCN2 kinase did not affect BABA-induced immunity but relieved BABA-induced growth repression. Hence, BABA-activated IBI1 controls plant immunity and growth via separate pathways. Our results open new opportunities to separate broad-spectrum disease resistance from the associated costs on plant growth

Proteomic Analysis of Fractionated Toxoplasma Oocysts Reveals Clues to Their Environmental Resistance

Toxoplasma gondii is an obligate intracellular parasite that is unique in its ability to infect a broad range of birds and mammals, including humans, leading to an extremely high worldwide prevalence and distribution. This work focuses on the environmentally resistant oocyst, which is the product of sexual replication in felids and an important source of human infection. Due to the difficulty in producing and working with oocysts, relatively little is known about how this stage is able to resist extreme environmental stresses and how they initiate a new infection, once ingested. To fill this gap, the proteome of the wall and sporocyst/sporozoite fractions of mature, sporulated oocysts were characterized using one-dimensional gel electrophoresis followed by LC-MS/MS on trypsin-digested peptides. A combined total of 1021 non-redundant T. gondii proteins were identified in the sporocyst/sporozoite fraction and 226 were identified in the oocyst wall fraction. Significantly, 172 of the identified proteins have not previously been identified in Toxoplasma proteomic studies. Among these are several of interest for their likely role in conferring environmental resistance including a family of small, tyrosine-rich proteins present in the oocyst wall fractions and late embryogenesis abundant domain-containing (LEA) proteins in the cytosolic fractions. The latter are known from other systems to be key to enabling survival against desiccation

Regulation of High-Temperature Stress Response by Small RNAs

Temperature extremes constitute one of the most common environmental stresses that adversely affect the growth and development of plants. Transcriptional regulation of temperature stress responses, particularly involving protein-coding gene networks, has been intensively studied in recent years. High-throughput sequencing technologies enabled the detection of a great number of small RNAs that have been found to change during and following temperature stress. The precise molecular action of some of these has been elucidated in detail. In the present chapter, we summarize the current understanding of small RNA-mediated modulation of high- temperature stress-regulatory pathways including basal stress responses, acclimation, and thermo-memory. We gather evidence that suggests that small RNA network changes, involving multiple upregulated and downregulated small RNAs, balance the trade-off between growth/development and stress responses, in order to ensure successful adaptation. We highlight specific characteristics of small RNA-based tem- perature stress regulation in crop plants. Finally, we explore the perspectives of the use of small RNAs in breeding to improve stress tolerance, which may be relevant for agriculture in the near future

Education, implementation, and teams : 2020 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science with treatment recommendations

For this 2020 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations, the Education, Implementation, and Teams Task Force applied the population, intervention, comparator, outcome, study design, time frame format and performed 15 systematic reviews, applying the Grading of Recommendations, Assessment, Development, and Evaluation guidance. Furthermore, 4 scoping reviews and 7 evidence updates assessed any new evidence to determine if a change in any existing treatment recommendation was required. The topics covered included training for the treatment of opioid overdose; basic life support, including automated external defibrillator training; measuring implementation and performance in communities, and cardiac arrest centers; advanced life support training, including team and leadership training and rapid response teams; measuring cardiopulmonary resuscitation performance, feedback devices, and debriefing; and the use of social media to improve cardiopulmonary resuscitation application