Characterization of miRNAs in Embryonic, Larval, and Adult Lumpfish Provides a Reference miRNAome for Cyclopterus lumpus

MicroRNAs (miRNAs) are endogenous small RNA molecules involved in the post-transcriptional regulation of protein expression by binding to the mRNA of target genes. They are key regulators in teleost development, maintenance of tissue-specific functions, and immune responses. Lumpfish (Cyclopterus lumpus) is becoming an emergent aquaculture species as it has been utilized as a cleaner fish to biocontrol sea lice (e.g., Lepeophtheirus salmonis) infestation in the Atlantic Salmon (Salmo salar) aquaculture. The lumpfish miRNAs repertoire is unknown. This study identified and characterized miRNA encoding genes in lumpfish from three developmental stages (adult, embryos, and larvae). A total of 16 samples from six different adult lumpfish organs (spleen, liver, head kidney, brain, muscle, and gill), embryos, and larvae were individually small RNA sequenced. Altogether, 391 conserved miRNA precursor sequences (discovered in the majority of teleost fish species reported in miRbase), eight novel miRNA precursor sequences (so far only discovered in lumpfish), and 443 unique mature miRNAs were identified. Transcriptomics analysis suggested organ-specific and age-specific expression of miRNAs (e.g., miR-122-1-5p specific of the liver). Most of the miRNAs found in lumpfish are conserved in teleost and higher vertebrates, suggesting an essential and common role across teleost and higher vertebrates. This study is the first miRNA characterization of lumpfish that provides the reference miRNAome for future functional studies.

DANSR: A Tool for the Detection of Annotated and Novel Small RNAs

Existing small noncoding RNA analysis tools are optimized for processing short sequencing reads (17–35 nucleotides) to monitor microRNA expression. However, these strategies under-represent many biologically relevant classes of small noncoding RNAs in the 36–200 nucleotides length range (tRNAs, snoRNAs, etc.). To address this, we developed DANSR, a tool for the detection of annotated and novel small RNAs using sequencing reads with variable lengths (ranging from 17–200 nt). While DANSR is broadly applicable to any small RNA dataset, we applied it to a cohort of matched normal, primary, and distant metastatic colorectal cancer specimens to demonstrate its ability to quantify annotated small RNAs, discover novel genes, and calculate differential expression. DANSR is available as an open source tool.

RNA-sequencing of human post-mortem hypothalamus and nucleus accumbens identifies expression profiles associated with obesity.

Obesity, the accumulation of body fat to excess, may cause serious negative health effects, including increased risk of heart disease, type 2 diabetes, stroke and certain cancers. The biology of obesity is complex and not well understood, involving both environmental and genetic factors and affecting metabolic and endocrine mechanisms in tissues of the gut, adipose, and brain. Previous RNA sequencing studies have identified transcripts associated with obesity and body mass index in blood and fat, often using animal models, but RNA sequencing studies in human brain tissue related to obesity have not been previously undertaken. We conducted both large and small RNA sequencing of hypothalamus (207 samples) and nucleus accumbens (276 samples) from individuals defined as consistently obese (124 samples), consistently normal weight as controls (148 samples) or selected without respect to BMI and falling within neither case nor control definition (211 samples), based on longitudinal BMI measures. The samples were provided by three cohort studies with brain donation programs; the Framingham Heart Study (FHS), the Religious Orders Study (ROS) and the Rush Memory and Aging Project (MAP). For each brain region and large/small RNA sequencing set, differential expression of obesity, BMI, brain region and sex was performed. Analyses were done transcriptome-wide as well as with a priori defined sets of obesity or BMI-associated mRNAs and microRNAs (miRNAs). There are sixteen mRNAs and five microRNAs that are differentially expressed (adjusted p < 0.05) by obesity or BMI in these tissues, several of which were validated with qPCR data. The results include many that are BMI-associated, such as APOBR and CES1, as well as many associated with the immune system and some with addiction, such as the gene sets 'cytokine signaling in immune system' and 'opioid signaling'. In spite of the relatively large number of samples, our study was likely under-powered to detect other transcripts or miRNA with relevant but smaller effects.

Weight Change Alters the Small RNA Profile of Urinary Extracellular Vesicles in Obesity

Introduction: Various kidney diseases reportedly show different urinary extracellular vesicles (EVs) RNA profiles. Although obesity is one of the main causes of chronic kidney disease, the expression pattern of urinary EVs RNA in obesity is uncertain. Our aim was to sequence the small RNA profiles of urinary EVs in obese patients before and after weight reduction and compared them to those of healthy volunteers (HVs). Methods: We recruited age-sex matched obese patients and HVs. The small RNA profiles of urinary EVs were analyzed using RNA sequencing. To evaluate the effect of weight reduction, small RNA profiles of urinary EVs 6 months after bariatric surgery were also analyzed. Results: The proportion of urinary EVs transfer RNA and microRNA of obese patients differed from that of HVs. Obese patients showed differential expression of 1343 small RNAs in urinary EVs compared to HVs (|fold change| ≥ 2 and p value < 0.05). Among those, 61 small RNAs were upregulated in obese patients and downregulated after weight reduction, whereas 167 small RNAs were downregulated in obese patients and upregulated after weight reduction. RNA sequencing revealed the correlation between the specific urinary EVs small RNAs and clinical parameters including body weight, low-density lipoprotein cholesterol, triglyceride, high-density lipoprotein cholesterol, serum glucose, estimated glomerular filtration rate, and albuminuria. Conclusion: Obese patients showed distinct urinary EVs small RNA profiles compared to HVs. Weight reduction altered urinary EVs small RNA profiles in obese patients.

CRISPR guides induce gene silencing in plants in the absence of Cas

Background RNA-targeting CRISPR-Cas can provide potential advantages over DNA editing, such as avoiding pleiotropic effects of genome editing, providing precise spatiotemporal regulation, and expanded function including antiviral immunity. Results Here, we report the use of CRISPR-Cas13 in plants to reduce both viral and endogenous RNA. Unexpectedly, we observe that crRNA designed to guide Cas13 could, in the absence of the Cas13 protein, cause substantial reduction in RNA levels as well. We demonstrate Cas13-independent guide-induced gene silencing (GIGS) in three plant species, including stable transgenic Arabidopsis. Small RNA sequencing during GIGS identifies the production of small RNA that extend beyond the crRNA expressed sequence in samples expressing multi-guide crRNA. Additionally, we demonstrate that mismatches in guide sequences at position 10 and 11 abolish GIGS. Finally, we show that GIGS is elicited by guides that lack the Cas13 direct repeat and can extend to Cas9 designed crRNA of at least 28 base pairs, indicating that GIGS can be elicited through a variety of guide designs and is not dependent on Cas13 crRNA sequences or design. Conclusions Collectively, our results suggest that GIGS utilizes endogenous RNAi machinery despite the fact that crRNA are unlike canonical triggers of RNAi such as miRNA, hairpins, or long double-stranded RNA. Given similar evidence of Cas13-independent silencing in an insect system, it is likely GIGS is active across many eukaryotes. Our results show that GIGS offers a novel and flexible approach to RNA reduction with potential benefits over existing technologies for crop improvement and functional genomics.

Analysis of Small RNA Sequencing Data in Plants

Over the past decades, next-generation sequencing (NGS) has been employed extensively for investigating the regulatory mechanisms of small RNAs. Several bioinformatics tools are available for aiding biologists to extract meaningful information from enormous amounts of data generated by NGS platforms. This chapter describes a detailed methodology for analyzing small RNA sequencing data using different open source tools. We elaborate on various steps involved in analysis, from processing the raw sequencing reads to identifying miRNAs, their targets, and differential expression studies.