Unexpected selection to retain high GC content and splicing enhancers within exons of multiexonic lncRNA loci

The GC-content at the 5' ends of human protein-coding genes is undergoing mutational decay

BACKGROUND

In vertebrates, most protein-coding genes have a peak of GC-content near their 5' transcriptional start site (TSS). This feature promotes both the efficient nuclear export and translation of mRNAs. Despite the importance of GC-content for RNA metabolism, its general features, origin, and maintenance remain mysterious. We investigate the evolutionary forces shaping GC-content at the transcriptional start site (TSS) of genes through both comparative genomic analysis of nucleotide substitution rates between different species and by examining human de novo mutations.

RESULTS

Our data suggests that GC-peaks at TSSs were present in the last common ancestor of amniotes, and likely that of vertebrates. We observe that in apes and rodents, where recombination is directed away from TSSs by PRDM9, GC-content at the 5' end of protein-coding gene is currently undergoing mutational decay. In canids, which lack PRDM9 and perform recombination at TSSs, GC-content at the 5' end of protein-coding is increasing. We show that these patterns extend into the 5' end of the open reading frame, thus impacting synonymous codon position choices.

CONCLUSIONS

Our results indicate that the dynamics of this GC-peak in amniotes is largely shaped by historic patterns of recombination. Since decay of GC-content towards the mutation rate equilibrium is the default state for non-functional DNA, the observed decrease in GC-content at TSSs in apes and rodents indicates that the GC-peak is not being maintained by selection on most protein-coding genes in those species.

Genome-wide identification and functional profile analysis of long non-coding RNAs in Avicennia marina

Avicennia marina, known for its remarkable adaptability to the challenging coastal environment, including high salinity, tide, and anaerobic soils, holds pivotal functions in safeguarding the coastal ecosystem. Long non-coding RNAs (lncRNAs) have emerged as significant players in various natural processes of plants such as development. However, lncRNAs in A. marina remain largely unknown and uncharacterized. Here, we employed the transcriptome datasets from multiple tissues, such as root, leaf, and seed, to detect and characterize the lncRNAs of A. marina. Analyzing synthetically, we finally identified 6333 lncRNAs in the A. marina. These lncRNAs exhibited distinct features compared to messenger RNAs, including larger exons, lower guanine-cytosine contents, lower expression levels, and higher tissue specificities. Moreover, we identified thousands of tissue-specific lncRNAs across the examined tissues and further found that these tissue-specific lncRNAs were significantly enriched in biological processes related to the major functions of their corresponding tissues. For instance, leaf-specific lncRNAs showed prominent enrichment in photosynthesis, oxidation-reduction processes, and light harvesting. By providing a comprehensive dataset and functional annotations for A. marina lncRNAs, this study offers a valuable overview of lncRNAs in A. marina and lays the fundamental foundation for further functional exploring of them.

Transcription regulation by long non-coding RNAs: mechanisms and disease relevance

Long non-coding RNAs (lncRNAs) outnumber protein-coding transcripts, but their functions remain largely unknown. In this Review, we discuss the emerging roles of lncRNAs in the control of gene transcription. Some of the best characterized lncRNAs have essential transcription cis-regulatory functions that cannot be easily accomplished by DNA-interacting transcription factors, such as XIST, which controls X-chromosome inactivation, or imprinted lncRNAs that direct allele-specific repression. A growing number of lncRNA transcription units, including CHASERR, PVT1 and HASTER (also known as HNF1A-AS1) act as transcription-stabilizing elements that fine-tune the activity of dosage-sensitive genes that encode transcription factors. Genetic experiments have shown that defects in such transcription stabilizers often cause severe phenotypes. Other lncRNAs, such as lincRNA-p21 (also known as Trp53cor1) and Maenli (Gm29348) contribute to local activation of gene transcription, whereas distinct lncRNAs influence gene transcription in trans. We discuss findings of lncRNAs that elicit a function through either activation of their transcription, transcript elongation and processing or the lncRNA molecule itself. We also discuss emerging evidence of lncRNA involvement in human diseases, and their potential as therapeutic targets.

Genome composition and GC content influence loci distribution in reduced representation genomic studies

BACKGROUND

Genomic architecture is a key evolutionary trait for living organisms. Due to multiple complex adaptive and neutral forces which impose evolutionary pressures on genomes, there is a huge variability of genomic features. However, their variability and the extent to which genomic content determines the distribution of recovered loci in reduced representation sequencing studies is largely unexplored.

RESULTS

Here, by using 80 genome assemblies, we observed that whereas plants primarily increase their genome size by expanding their intergenic regions, animals expand both intergenic and intronic regions, although the expansion patterns differ between deuterostomes and protostomes. Loci mapping in introns, exons, and intergenic categories obtained by in silico digestion using 2b-enzymes are positively correlated with the percentage of these regions in the corresponding genomes, suggesting that loci distribution mostly mirrors genomic architecture of the selected taxon. However, exonic regions showed a significant enrichment of loci in all groups regardless of the used enzyme. Moreover, when using selective adaptors to obtain a secondarily reduced loci dataset, the percentage and distribution of retained loci also varied. Adaptors with G/C terminals recovered a lower percentage of selected loci, with a further enrichment of exonic regions, while adaptors with A/T terminals retained a higher percentage of loci and slightly selected more intronic regions than expected.

CONCLUSIONS

Our results highlight how genome composition, genome GC content, RAD enzyme choice and use of base-selective adaptors influence reduced genome representation techniques. This is important to acknowledge in population and conservation genomic studies, as it determines the abundance and distribution of loci.

Functional identification of cis-regulatory long noncoding RNAs at controlled false discovery rates

A key attribute of some long noncoding RNAs (lncRNAs) is their ability to regulate expression of neighbouring genes in cis. However, such 'cis-lncRNAs' are presently defined using ad hoc criteria that, we show, are prone to false-positive predictions. The resulting lack of cis-lncRNA catalogues hinders our understanding of their extent, characteristics and mechanisms. Here, we introduce TransCistor, a framework for defining and identifying cis-lncRNAs based on enrichment of targets amongst proximal genes. TransCistor's simple and conservative statistical models are compatible with functionally defined target gene maps generated by existing and future technologies. Using transcriptome-wide perturbation experiments for 268 human and 134 mouse lncRNAs, we provide the first large-scale survey of cis-lncRNAs. Known cis-lncRNAs are correctly identified, including XIST, LINC00240 and UMLILO, and predictions are consistent across analysis methods, perturbation types and independent experiments. We detect cis-activity in a minority of lncRNAs, primarily involving activators over repressors. Cis-lncRNAs are detected by both RNA interference and antisense oligonucleotide perturbations. Mechanistically, cis-lncRNA transcripts are observed to physically associate with their target genes and are weakly enriched with enhancer elements. In summary, TransCistor establishes a quantitative foundation for cis-lncRNAs, opening a path to elucidating their molecular mechanisms and biological significance.

Comparative RNA Genomics

Over the last quarter of a century it has become clear that RNA is much more than just a boring intermediate in protein expression. Ancient RNAs still appear in the core information metabolism and comprise a surprisingly large component in bacterial gene regulation. A common theme with these types of mostly small RNAs is their reliance of conserved secondary structures. Large-scale sequencing projects, on the other hand, have profoundly changed our understanding of eukaryotic genomes. Pervasively transcribed, they give rise to a plethora of large and evolutionarily extremely flexible non-coding RNAs that exert a vastly diverse array of molecule functions. In this chapter we provide a-necessarily incomplete-overview of the current state of comparative analysis of non-coding RNAs, emphasizing computational approaches as a means to gain a global picture of the modern RNA world.

Exposure of volunteers to microgravity by dry immersion bed over 21 days results in gene expression changes and adaptation of T cells

The next steps of deep space exploration are manned missions to Moon and Mars. For safe space missions for crew members, it is important to understand the impact of space flight on the immune system. We studied the effects of 21 days dry immersion (DI) exposure on the transcriptomes of T cells isolated from blood samples of eight healthy volunteers. Samples were collected 7 days before DI, at day 7, 14, and 21 during DI, and 7 days after DI. RNA sequencing of CD3+ T cells revealed transcriptional alterations across all time points, with most changes occurring 14 days after DI exposure. At day 21, T cells showed evidence of adaptation with a transcriptional profile resembling that of 7 days before DI. At 7 days after DI, T cells again changed their transcriptional profile. These data suggest that T cells adapt by rewiring their transcriptomes in response to simulated weightlessness and that remodeling cues persist when reexposed to normal gravity.

Long non‐coding RNA, a supreme post‐transcriptional immune regulator of bacterial or virus‐driven immune evolution in teleost

The global aquaculture boom, fuelled by a reduction in wild population and detection of novel viruses, has created a demanding market, hence, there is a pressing need to investigate the immune system of fish, further. As the most diverse community of vertebrates and a central contributor to the progressing global aquaculture market, teleost continues to draw vast scientific interest. Recent breakthroughs in multi‐omics technologies have provided a platform to understand the role of long non‐coding RNA (lncRNA) in the host immune system during infection. Emerging evidence shows that teleost lncRNA might have a regulatory role in immune responses, mostly through lncRNA–microRNA (miRNA) sponging. Teleost lncRNA shares a functionally active short sequence complement to target the miRNA which is conserved among the several fish species. Recent report suggests that rhabdovirus exploits a lncRNA in teleost and, to dodge the host immune mechanism and negatively regulate the immune system. This observation reveals the essentiality of lncRNA in pathogen‐driven immunity in teleost. Reports available on the function of teleost lncRNA are still in early stages and experimental verifications are a limiting factor. Unravelling the lncRNA‐mediated immune regulation in fishes could be used against the invading pathogens to strengthen the aquaculture production. This review elaborates on the experimentally identified and functionally characterized lncRNA and its regulatory role in the teleost immune response during infection and pathogen‐driven host immune evolution, which could eventually lead to achieving high standards in aquaculture productivity.

False gene and chromosome losses in genome assemblies caused by GC content variation and repeats

BACKGROUND

Many short-read genome assemblies have been found to be incomplete and contain mis-assemblies. The Vertebrate Genomes Project has been producing new reference genome assemblies with an emphasis on being as complete and error-free as possible, which requires utilizing long reads, long-range scaffolding data, new assembly algorithms, and manual curation. A more thorough evaluation of the recent references relative to prior assemblies can provide a detailed overview of the types and magnitude of improvements.

RESULTS

Here we evaluate new vertebrate genome references relative to the previous assemblies for the same species and, in two cases, the same individuals, including a mammal (platypus), two birds (zebra finch, Anna's hummingbird), and a fish (climbing perch). We find that up to 11% of genomic sequence is entirely missing in the previous assemblies. In the Vertebrate Genomes Project zebra finch assembly, we identify eight new GC- and repeat-rich micro-chromosomes with high gene density. The impact of missing sequences is biased towards GC-rich 5'-proximal promoters and 5' exon regions of protein-coding genes and long non-coding RNAs. Between 26 and 60% of genes include structural or sequence errors that could lead to misunderstanding of their function when using the previous genome assemblies.

CONCLUSIONS

Our findings reveal novel regulatory landscapes and protein coding sequences that have been greatly underestimated in previous assemblies and are now present in the Vertebrate Genomes Project reference genomes.

Genome-Wide Analysis of Human Long Noncoding RNAs: A Provocative Review

Do long noncoding RNAs (lncRNAs) contribute little or substantively to human biology? To address how lncRNA loci and their transcripts, structures, interactions, and functions contribute to human traits and disease, we adopt a genome-wide perspective. We intend to provoke alternative interpretation of questionable evidence and thorough inquiry into unsubstantiated claims. We discuss pitfalls of lncRNA experimental and computational methods as well as opposing interpretations of their results. The majority of evidence, we argue, indicates that most lncRNA transcript models reflect transcriptional noise or provide minor regulatory roles, leaving relatively few human lncRNAs that contribute centrally to human development, physiology, or behavior. These important few tend to be spliced and better conserved but lack a simple syntax relating sequence to structure and mechanism, and so resist simple categorization. This genome-wide view should help investigators prioritize individual lncRNAs based on their likely contribution to human biology.

Discovering functional motifs in long noncoding RNAs

Long noncoding RNAs (lncRNAs) are products of pervasive transcription that closely resemble messenger RNAs on the molecular level, yet function through largely unknown modes of action. The current model is that the function of lncRNAs often relies on specific, typically short, conserved elements, connected by linkers in which specific sequences and/or structures are less important. This notion has fueled the development of both computational and experimental methods focused on the discovery of functional elements within lncRNA genes, based on diverse signals such as evolutionary conservation, predicted structural elements, or the ability to rescue loss-of-function phenotypes. In this review, we outline the main challenges that the different methods need to overcome, describe the recently developed approaches, and discuss their respective limitations. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs.

The activity of human enhancers is modulated by the splicing of their associated lncRNAs

Pervasive enhancer transcription is at the origin of more than half of all long noncoding RNAs in humans. Transcription of enhancer-associated long noncoding RNAs (elncRNA) contribute to their cognate enhancer activity and gene expression regulation in cis. Recently, splicing of elncRNAs was shown to be associated with elevated enhancer activity. However, whether splicing of elncRNA transcripts is a mere consequence of accessibility at highly active enhancers or if elncRNA splicing directly impacts enhancer function, remains unanswered. We analysed genetically driven changes in elncRNA splicing, in humans, to address this outstanding question. We showed that splicing related motifs within multi-exonic elncRNAs evolved under selective constraints during human evolution, suggesting the processing of these transcripts is unlikely to have resulted from transcription across spurious splice sites. Using a genome-wide and unbiased approach, we used nucleotide variants as independent genetic factors to directly assess the causal relationship that underpin elncRNA splicing and their cognate enhancer activity. We found that the splicing of most elncRNAs is associated with changes in chromatin signatures at cognate enhancers and target mRNA expression. We provide evidence that efficient and conserved processing of enhancer-associated elncRNAs contributes to enhancer activity.

Most, if not all, active enhancers are transcribed, giving rise to a plethora of transcripts, including enhancer-associated long noncoding RNAs (elncRNAs). Changes in elncRNA levels impacts cognate enhancer activity. Recently splicing of elncRNA has also been found to associate with enhancer activity. Whether this associations reflects a contribution of elncRNA splicing to increased enhancer activity or else is simply the consequence of increased chromatin accessibility that promotes transcriptional elongation and allows for spurious splicing events remains unknown. We show that natural selection has acted, at the species and population level, to preserve DNA elements required for frequent and efficient elncRNA splicing Importantly, using a genome-wide and unbiased statistical population genomics approach, we demonstrate that elncRNA splicing is associated with cognate enhancer function, contributing to chromatin status and enhancer activity. Our results provides strong evidence that efficient elncRNA splicing contributes to enhancer activity genome-wide.

NEAT1 lncRNA and amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a representative neurological disease that is known to devastate entire motor neurons within a period of just a few years. Discoveries of the specific pathologies of relevant RNA-binding proteins, including TAR DNA-binding protein-43 (TDP-43) and fused in sarcoma/translocated in liposarcoma (FUS/TLS), and the causative genes of both familial and sporadic ALS have provided crucial information that could lead to a cure. In recent ALS research the GGGGCC-repeat expansion in the C9orf72 gene was identified as one of the most important pathological findings, suggesting the significance of both nuclear dysfunction due to dipeptide repeat proteins (DPRs) and RNA toxicity (such as pathological alterations of non-coding RNAs). In research on model animals carrying ALS-related molecules, the determination of whether a factor is protective or toxic has been controversial. Herein, we review the findings regarding NEAT1 RNA and C9orf72 GGGGCC repeats associated with ALS, from the viewpoint of conversion from the protective stage in the nucleus in early-phase ALS to late-phase induction of cell death. This review will provide insights for the development of RNA effectors as novel ALS treatments.

Pathological Bases and Clinical Application of Long Noncoding RNAs in Cardiovascular Diseases

Increasing evidence has suggested that noncoding RNAs (ncRNAs) have vital roles in cardiovascular tissue homeostasis and diseases. As a main subgroup of ncRNAs, long ncRNAs (lncRNAs) have been reported to play important roles in lipid metabolism, inflammation, vascular injury, and angiogenesis. They have also been implicated in many human diseases including atherosclerosis, arterial remodeling, hypertension, myocardial injury, cardiac remodeling, and heart failure. Importantly, it was reported that lncRNAs were dysregulated in the development and progression of cardiovascular diseases (CVDs). A variety of studies have demonstrated that lncRNAs could influence gene expression at transcription, post-transcription, translation, and post-translation level. Particularly, emerging evidence has confirmed that the crosstalk among lncRNAs, mRNA, and miRNAs is an important underlying regulatory mechanism of lncRNAs. Nevertheless, the biological functions and molecular mechanisms of lncRNAs in CVDs have not been fully explored yet. In this review, we will comprehensively summarize the main findings about lncRNAs and CVDs, highlighting the most recent discoveries in the field of lncRNAs and their pathophysiological functions in CVDs, with the aim of dissecting the intrinsic association between lncRNAs and common risk factors of CVDs including hypertension, high glucose, and high fat. Finally, the potential of lncRNAs functioning as the biomarkers, therapeutic targets, as well as specific diagnostic and prognostic indicators of CVDs will be discussed in this review.

Comparative genomics in the search for conserved long noncoding RNAs

Long noncoding RNAs (lncRNAs) have emerged as prominent regulators of gene expression in eukaryotes. The identification of lncRNA orthologs is essential in efforts to decipher their roles across model organisms, as homologous genes tend to have similar molecular and biological functions. The relatively high sequence plasticity of lncRNA genes compared with protein-coding genes, makes the identification of their orthologs a challenging task. This is why comparative genomics of lncRNAs requires the development of specific and, sometimes, complex approaches. Here, we briefly review current advancements and challenges associated with four levels of lncRNA conservation: genomic sequences, splicing signals, secondary structures and syntenic transcription.

Long non-coding RNAs and splicing

In this review I focus on the role of splicing in long non-coding RNA (lncRNA) life. First, I summarize differences between the splicing efficiency of protein-coding genes and lncRNAs and discuss why non-coding RNAs are spliced less efficiently. In the second half of the review, I speculate why splice sites are the most conserved sequences in lncRNAs and what additional roles could splicing play in lncRNA metabolism. I discuss the hypothesis that the splicing machinery can, besides its dominant role in intron removal and exon joining, protect cells from undesired transcripts.

The contributory role of long non-coding RNAs (lncRNAs) in head and neck cancers: Possible biomarkers and therapeutic targets?

Along with the developments in techniques for genome study, our understanding of its sequences has completely changed. The non-coding sequences of the human genome are no longer considered as "junk" but are rather known to be the source of high-functioning molecules. Some of the most fascinating transcripts in this regard are long non-coding RNAs (lncRNAs) ^___RNA molecules that exceed 200 nucleotides and are not transcribed from protein-coding regions of the genome. These transcripts are capable of gene regulation by various mechanisms, from epigenetic changes and chromosomal arrangements to post-transcription modulation of messenger RNAs. Furthermore, lncRNAs interact with other non-coding transcripts such as microRNAs that further affects gene expression. Considering the fact that cancer is a disease of deregulated expression, recent studies have identified lncRNAs acting as either oncogene or tumor suppressor in a wide range of human malignancies. Head and neck cancer (HNC), with a high incidence rate and unfavorable survival, is no exception in this matter and many investigations have introduced lncRNAs involved in its tumor progression and drug response, as well as those acting as promising diagnostic or prognostic markers. The present study reviews the vital regulatory roles of lncRNAs and further introduces their role in progression of HNC subtypes.

An exon-biased biophysical approach and NMR spectroscopy define the secondary structure of a conserved helical element within the HOTAIR long non-coding RNA

HOTAIR is a large, multi-exon spliced non-coding RNA proposed to function as a molecular scaffold and competes with chromatin to bind to histone modification enzymes. Previous sequence analysis and biochemical experiments identified potential conserved regions and characterized the full length HOTAIR secondary structure. Here, we examine the thermodynamic folding properties and structural propensity of the individual exonic regions of HOTAIR using an array of biophysical methods and NMR spectroscopy. We demonstrate that different exons of HOTAIR contain variable degrees of heterogeneity, and identify one exonic region, exon 4, that adopts a stable and compact fold under low magnesium concentrations. Close agreement of NMR spectroscopy and chemical probing unambiguously confirm conserved base pair interactions within the structural element, termed helix 10 of exon 4, located within domain I of human HOTAIR. This combined exon-biased and integrated biophysical approach introduces a new strategy to examine conformational heterogeneity in lncRNAs and emphasizes NMR as a key method to validate base pair interactions and corroborate large RNA secondary structures.

lncEvo: automated identification and conservation study of long noncoding RNAs

BACKGROUND

Long noncoding RNAs represent a large class of transcripts with two common features: they exceed an arbitrary length threshold of 200 nt and are assumed to not encode proteins. Although a growing body of evidence indicates that the vast majority of lncRNAs are potentially nonfunctional, hundreds of them have already been revealed to perform essential gene regulatory functions or to be linked to a number of cellular processes, including those associated with the etiology of human diseases. To better understand the biology of lncRNAs, it is essential to perform a more in-depth study of their evolution. In contrast to protein-encoding transcripts, however, they do not show the strong sequence conservation that usually results from purifying selection; therefore, software that is typically used to resolve the evolutionary relationships of protein-encoding genes and transcripts is not applicable to the study of lncRNAs.

RESULTS

To tackle this issue, we developed lncEvo, a computational pipeline that consists of three modules: (1) transcriptome assembly from RNA-Seq data, (2) prediction of lncRNAs, and (3) conservation study-a genome-wide comparison of lncRNA transcriptomes between two species of interest, including search for orthologs. Importantly, one can choose to apply lncEvo solely for transcriptome assembly or lncRNA prediction, without calling the conservation-related part.

CONCLUSIONS

lncEvo is an all-in-one tool built with the Nextflow framework, utilizing state-of-the-art software and algorithms with customizable trade-offs between speed and sensitivity, ease of use and built-in reporting functionalities. The source code of the pipeline is freely available for academic and nonacademic use under the MIT license at https://gitlab.com/spirit678/lncrna_conservation_nf .

LncRNAs as Architects in Cancer Biomarkers with Interface of Epitranscriptomics- Incipient Targets in Cancer Therapy

Long non-coding RNAs (LncRNAs) epitomize a class of non-coding regulatory RNAs with more than 200 nucleotides, which are long and situated in the nucleus or cytoplasm and rarely encode proteins. Accruing evidence signposts that lncRNAs act as molecular switches in different cellular activities like differentiation, apoptosis, as well as reprogramming of cellular states by modifying gene expression patterns. The revelation of immense numbers of lncRNA with their wide variety of expression patterns in different kinds of malignancy, tumor explicitness, and their steadiness in circulating body fluids deliver an innovative groundwork for emerging diagnosis and treatments for cancer. Mechanisms associating lncRNAs in carcinogenesis are conquered by deregulation of cellular signaling pathways and altered epitranscriptome along with their expression. Specified these attributes, it becomes clear that the improvement of new tools to identify lncRNAs with higher affectability will be fundamental to allow the identification of the expression pattern of lncRNAs in various kinds of malignant growth and may likewise be utilized to envisage cancer prognosis in addition to the patients' outcome. Improvement of RNA targeting-based therapeutics is delivering incredible prospects to modulate lncRNAs for anti-cancer initiatives. Henceforth, lncRNAs can be used exclusively as possible cancer biomarkers for early diagnosis and anticipation of malignancy, as well as metastasis. In addition to the basic curative targets and along these, lncRNAs hold resilient assurance towards the revelation of innovative diagnostics and therapeutics for malignant growth with the interface of epitranscriptomics information. This review aims to briefly discuss the latest findings regarding the roles and mechanisms of some important lncRNAs in the pathogenesis, regulation, and lncRNA-associated epigenetics of cancer along with targeting lncRNAs with potential approaches for impending diagnosis and therapeutic intervention in malignancies.

GC-content biases in protein-coding genes act as an "mRNA identity" feature for nuclear export

It has long been observed that human protein-coding genes have a particular distribution of GC-content: the 5' end of these genes has high GC-content while the 3' end has low GC-content. In 2012, it was proposed that this pattern of GC-content could act as an mRNA identity feature that would lead to it being better recognized by the cellular machinery to promote its nuclear export. In contrast, junk RNA, which largely lacks this feature, would be retained in the nucleus and targeted for decay. Now two recent papers have provided evidence that GC-content does promote the nuclear export of many mRNAs in human cells.

CircRNA-1926 Promotes the Differentiation of Goat SHF Stem Cells into Hair Follicle Lineage by miR-148a/b-3p/CDK19 Axis

Simple Summary

Cashmere is the fiber derived from cashmere goats. Its textiles have been favored by consumers due to their typical features, like fine, light, softness, and comfort. Circular RNAs (circRNAs) are thought to play roles in cashmere growth of cashmere goats. CircRNA-1926 was previously identified in cashmere goats, but its functional roles are unclear. In this study, we firstly confirmed the expression of circRNA-1926 in secondary hair follicle bulge of cashmere goats with a significantly higher level at anagen than the counterpart of telogen. Next, we showed that circRNA-1926 promotes the differentiation of hair follicle stem cell into hair follicle lineage in cashmere goats. Mechanistically, we found that circRNA-1926 regulated the CDK19 expression via sponging miR-148a/b-3p. Our results have demonstrated that circRNA-1926 promotes the differentiation of secondary hair follicle stem cells into hair follicle lineages in cashmere goats through sponging miR-148a/b-3p to promote the expression of the CDK19 gene. The results from this study provided novel insight into the functional roles of circRNA-1926 in hair follicle regeneration and cashmere growth.

Abstract

Circular RNAs (CircRNAs) are a type of non-coding RNAs, which contain a covalently closed loop structure without 5′ to 3′ free ends. CircRNAs play essential roles in the regeneration of secondary hair follicle (SHF) and cashmere growth in goats. CircRNA-1926 was previously identified in SHF of cashmere goats, but its potential roles are unclear. In this study, we confirmed the expression of circRNA-1926 in SHF bulge of nine cashmere goats with a significantly higher level at anagen than that of telogen. Through the use of both overexpression and siRNA interference, we showed that circRNA-1926 promoted the differentiation of SHF stem cell into hair follicle lineage in cashmere goats which was evaluated via indictor genes Keratin 7 and Keratin 17. Using RNA pull-down, we found that circRNA-1926 bound with miR-148a/b-3p. Additionally, our data indicated that circRNA-1926 promoted the expression of the CDK19 gene. Using dual-luciferase reporter assays, it was revealed that circRNA-1926 positively regulated the CDK19 expression through miR-148a/b-3p. The results from this study demonstrated that circRNA-1926 contributes the differentiation of SHF stem cells into hair follicle lineages in cashmere goats via sponging miR-148a/b-3p to enhance CDK19 expression.

LncRNA-599547 contributes the inductive property of dermal papilla cells in cashmere goat through miR-15b-5p/Wnt10b axis

The lncRNA-599547 (619-nt in length) is identified in secondary hair follicle (SHF) of cashmere goat, but its functional roles in regulating the inductive property of dermal papilla cells (DPCs) remains unknown. We found that lncRNA-599547 had significantly higher expression in dermal papilla of cashmere goat SHF at anagen than its counterpart at telogen. The overexpression of lncRNA-599547 led to a significant increase of ALP and LEF1 expression in DPCs (p < 0.05), whereas, the siLncRNA-1 mediated silencing of lncRNA-599547 significantly down-regulated the expression of ALP and LEF1 in DPCs (p < 0.05). Based on biotin-labeled RNA pull-down assay, we found that lncRNA-599547 directly interacted with chi-miR-15b-5p in DPCs. Based on both overexpression and silencing analysis of lncRNA-599547, our results indicate that lncRNA-599547 promotes the expression of Wnt10b in DPCs but without modulating its promoter methylation level. Using the mRNA-3'UTR fragments of goat Wnt10b containing the predicted binding sites of chi-miR-15b-5p in Dual-luciferase Reporter Assays, we show that lncRNA-599547 modulates the expression of Wnt10b at the chi-miR-15b-5p mediated post-transcriptional level. Taken together, our results indicate that lncRNA-599547 sponges miR-15b-5p to positively regulate the expression of Wnt10 gene, and thereby contributes the inductive property of DPCs in cashmere goat.

Functional impacts of non-coding RNA processing on enhancer activity and target gene expression

Tight regulation of gene expression is orchestrated by enhancers. Through recent research advancements, it is becoming clear that enhancers are not solely distal regulatory elements harboring transcription factor binding sites and decorated with specific histone marks, but they rather display signatures of active transcription, showing distinct degrees of transcription unit organization. Thereby, a substantial fraction of enhancers give rise to different species of non-coding RNA transcripts with an unprecedented range of potential functions. In this review, we bring together data from recent studies indicating that non-coding RNA transcription from active enhancers, as well as enhancer-produced long non-coding RNA transcripts, may modulate or define the functional regulatory potential of the cognate enhancer. In addition, we summarize supporting evidence that RNA processing of the enhancer-associated long non-coding RNA transcripts may constitute an additional layer of regulation of enhancer activity, which contributes to the control and final outcome of enhancer-targeted gene expression.

Challenges and Strategies in Ascribing Functions to Long Noncoding RNAs

Long noncoding RNAs (lncRNAs) are involved in many physiological and pathological processes, such as development, aging, immunity, and cancer. Mechanistically, lncRNAs exert their functions through interaction with proteins, genomic DNA, and other RNA, leading to transcriptional and post-transcriptional regulation of gene expression, either in cis or in trans; it is often difficult to distinguish between these two regulatory mechanisms. A variety of approaches, including RNA interference, antisense oligonucleotides, CRISPR-based methods, and genetically engineered mouse models, have yielded abundant information about lncRNA functions and underlying mechanisms, albeit with many discrepancies. In this review, we elaborate on the challenges in ascribing functions to lncRNAs based on the features of lncRNAs, including the genomic location, copy number, domain structure, subcellular localization, stability, evolution, and expression pattern. We also describe a framework for the investigation of lncRNA functions and mechanisms of action. Rigorous characterization of cancer-implicated lncRNAs is critical for the identification of bona fide anticancer targets.

Stable intronic sequence RNAs (sisRNAs) are selected regions in introns with distinct properties

Background

Stable introns and intronic fragments make up the largest population of RNA in the oocyte nucleus of the frog Xenopus tropicalis. These stable intronic sequence RNAs (sisRNAs) persist through the onset of zygotic transcription when synchronous cell division has ended, and the developing embryo consists of approximately 8000 cells. Despite their abundance, the sequence properties and biological function of sisRNAs are just beginning to be understood.

Results

To characterize this population of non-coding RNA, we identified all of the sisRNAs in the X. tropicalis oocyte nucleus using published high-throughput RNA sequencing data. Our analysis revealed that sisRNAs, have an average length of ~ 360 nt, are widely expressed from genes with multiple introns, and are derived from specific regions of introns that are GC and TG rich, while CpG poor. They are enriched in introns at both ends of transcripts but preferentially at the 3′ end. The consensus binding sites of specific transcription factors such as Stat3 are enriched in sisRNAs, suggesting an association between sisRNAs and transcription factors involved in early development. Evolutionary conservation analysis of sisRNA sequences in seven vertebrate genomes indicates that sisRNAs are as conserved as other parts of introns, but much less conserved than exons.

Conclusion

In total, our results indicate sisRNAs are selected intron regions with distinct properties and may play a role in gene expression regulation.

A Depletion of Stop Codons in lincRNA is Owing to Transfer of Selective Constraint from Coding Sequences

Although the constraints on a gene’s sequence are often assumed to reflect the functioning of that gene, here we propose transfer selection, a constraint operating on one class of genes transferred to another, mediated by shared binding factors. We show that such transfer can explain an otherwise paradoxical depletion of stop codons in long intergenic noncoding RNAs (lincRNAs). Serine/arginine-rich proteins direct the splicing machinery by binding exonic splice enhancers (ESEs) in immature mRNA. As coding exons cannot contain stop codons in one reading frame, stop codons should be rare within ESEs. We confirm that the stop codon density (SCD) in ESE motifs is low, even accounting for nucleotide biases. Given that serine/arginine-rich proteins binding ESEs also facilitate lincRNA splicing, a low SCD could transfer to lincRNAs. As predicted, multiexon lincRNA exons are depleted in stop codons, a result not explained by open reading frame (ORF) contamination. Consistent with transfer selection, stop codon depletion in lincRNAs is most acute in exonic regions with the highest ESE density, disappears when ESEs are masked, is consistent with stop codon usage skews in ESEs, and is diminished in both single-exon lincRNAs and introns. Owing to low SCD, the maximum lengths of pseudo-ORFs frequently exceed null expectations. This has implications for ORF annotation and the evolution of de novo protein-coding genes from lincRNAs. We conclude that not all constraints operating on genes need be explained by the functioning of the gene but may instead be transferred owing to shared binding factors.

RNAsamba: neural network-based assessment of the protein-coding potential of RNA sequences

The advent of high-throughput sequencing technologies made it possible to obtain large volumes of genetic information, quickly and inexpensively. Thus, many efforts are devoted to unveiling the biological roles of genomic elements, being the distinction between protein-coding and long non-coding RNAs one of the most important tasks. We describe RNAsamba, a tool to predict the coding potential of RNA molecules from sequence information using a neural network-based that models both the whole sequence and the ORF to identify patterns that distinguish coding from non-coding transcripts. We evaluated RNAsamba's classification performance using transcripts coming from humans and several other model organisms and show that it recurrently outperforms other state-of-the-art methods. Our results also show that RNAsamba can identify coding signals in partial-length ORFs and UTR sequences, evidencing that its algorithm is not dependent on complete transcript sequences. Furthermore, RNAsamba can also predict small ORFs, traditionally identified with ribosome profiling experiments. We believe that RNAsamba will enable faster and more accurate biological findings from genomic data of species that are being sequenced for the first time. A user-friendly web interface, the documentation containing instructions for local installation and usage, and the source code of RNAsamba can be found at https://rnasamba.lge.ibi.unicamp.br/.

Splicing of enhancer-associated lincRNAs contributes to enhancer activity

Transcription is common at active mammalian enhancers sometimes giving rise to stable enhancer-associated long intergenic noncoding RNAs (elincRNAs). Expression of elincRNA is associated with changes in neighboring gene product abundance and local chromosomal topology, suggesting that transcription at these loci contributes to gene expression regulation in cis Despite the lack of evidence supporting sequence-dependent functions for most elincRNAs, splicing of these transcripts is unexpectedly common. Whether elincRNA splicing is a mere consequence of cognate enhancer activity or if it directly impacts enhancer function remains unresolved. Here, we investigate the association between elincRNA splicing and enhancer activity in mouse embryonic stem cells. We show that multi-exonic elincRNAs are enriched at conserved enhancers, and the efficient processing of elincRNAs is strongly associated with their cognate enhancer activity. This association is supported by their enrichment in enhancer-specific chromatin signatures; elevated binding of co-transcriptional regulators; increased local intra-chromosomal DNA contacts; and strengthened cis-regulation on target gene expression. Our results support the role of efficient RNA processing of enhancer-associated transcripts to cognate enhancer activity.

Comparative Transcriptomics Analyses across Species, Organs, and Developmental Stages Reveal Functionally Constrained lncRNAs

The functionality of long noncoding RNAs (lncRNAs) is disputed. In general, lncRNAs are under weak selective pressures, suggesting that the majority of lncRNAs may be nonfunctional. However, although some surveys showed negligible phenotypic effects upon lncRNA perturbation, key biological roles were demonstrated for individual lncRNAs. Most lncRNAs with proven functions were implicated in gene expression regulation, in pathways related to cellular pluripotency, differentiation, and organ morphogenesis, suggesting that functional lncRNAs may be more abundant in embryonic development, rather than in adult organs. To test this hypothesis, we perform a multidimensional comparative transcriptomics analysis, across five developmental time points (two embryonic stages, newborn, adult, and aged individuals), four organs (brain, kidney, liver, and testes), and three species (mouse, rat, and chicken). We find that, overwhelmingly, lncRNAs are preferentially expressed in adult and aged testes, consistent with the presence of permissive transcription during spermatogenesis. LncRNAs are often differentially expressed among developmental stages and are less abundant in embryos and newborns compared with adult individuals, in agreement with a requirement for tighter expression control and less tolerance for noisy transcription early in development. For differentially expressed lncRNAs, we find that the patterns of expression variation among developmental stages are generally conserved between mouse and rat. Moreover, lncRNAs expressed above noise levels in somatic organs and during development show higher evolutionary conservation, in particular, at their promoter regions. Thus, we show that functionally constrained lncRNA loci are enriched in developing organs, and we suggest that many of these loci may function in an RNA-independent manner.

Biological Network Approach for the Identification of Regulatory Long Non-Coding RNAs Associated With Metabolic Efficiency in Cattle

Background: Genomic regions associated with divergent livestock feed efficiency have been found predominantly outside protein coding sequences. Long non-coding RNAs (lncRNA) can modulate chromatin accessibility, gene expression and act as important metabolic regulators in mammals. By integrating phenotypic, transcriptomic, and metabolomic data with quantitative trait locus data in prioritizing co-expression network analyses, we aimed to identify and functionally characterize lncRNAs with a potential key regulatory role in metabolic efficiency in cattle. Materials and Methods: Crossbred animals (n = 48) of a Charolais x Holstein F₂-population were allocated to groups of high or low metabolic efficiency based on residual feed intake in bulls, energy corrected milk in cows and intramuscular fat content in both genders. Tissue samples from jejunum, liver, skeletal muscle and rumen were subjected to global transcriptomic analysis via stranded total RNA sequencing (RNAseq) and blood plasma samples were used for profiling of 640 metabolites. To identify lncRNAs within the indicated tissues, a project-specific transcriptome annotation was established. Subsequently, novel transcripts were categorized for potential lncRNA status, yielding a total of 7,646 predicted lncRNA transcripts belonging to 3,287 loci. A regulatory impact factor approach highlighted 92, 55, 35, and 73 lncRNAs in jejunum, liver, muscle, and rumen, respectively. Their ensuing high regulatory impact factor scores indicated a potential regulatory key function in a gene set comprising loci displaying differential expression, tissue specificity and loci overlapping with quantitative trait locus regions for residual feed intake or milk production. These were subjected to a partial correlation and information theory analysis with the prioritized gene set. Results and Conclusions: Independent, significant and group-specific correlations (|r| > 0.8) were used to build a network for the high and the low metabolic efficiency group resulting in 1,522 and 1,732 nodes, respectively. Eight lncRNAs displayed a particularly high connectivity (>100 nodes). Metabolites and genes from the partial correlation and information theory networks, which each correlated significantly with the respective lncRNA, were included in an enrichment analysis indicating distinct affected pathways for the eight lncRNAs. LncRNAs associated with metabolic efficiency were classified to be functionally involved in hepatic amino acid metabolism and protein synthesis and in calcium signaling and neuronal nitric oxide synthase signaling in skeletal muscle cells.

The Emerging Role of Major Regulatory RNAs in Cancer Control

Alterations and personal variations of RNA interactions have been mechanistically coupled with disease etiology and phenotypical variations. RNA biomarkers, RNA mimics, and RNA antagonists have been developed for diagnostic, prognostic, and therapeutic uses. Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) are two major types of RNA molecules with regulatory roles, deregulation of which has been implicated in the initiation and progression of many human malignancies. Accumulating evidence indicated the clinical roles of regulatory RNAs in cancer control, stimulating a surge in exploring the functionalities of regulatory RNAs for improved understanding on disease pathogenesis and management. In this review, we highlight the critical roles of lncRNAs and miRNAs played in tumorigenesis, scrutinize their potential functionalities as diagnostic/prognostic biomarkers and/or therapeutic targets in clinics, outline opportunities that ncRNAs may bring to complement current clinical practice for improved cancer management and identify challenges faced by translating frontier knowledge on non-coding RNAs (ncRNAs) to bedside clinics as well as possible solutions.

Molecular Traits of Long Non-protein Coding RNAs from Diverse Plant Species Show Little Evidence of Phylogenetic Relationships

Long non-coding RNAs (lncRNAs) represent a diverse class of regulatory loci with roles in development and stress responses throughout all kingdoms of life. LncRNAs, however, remain under-studied in plants compared to animal systems. To address this deficiency, we applied a machine learning prediction tool, Classifying RNA by Ensemble Machine learning Algorithm (CREMA), to analyze RNAseq data from 11 plant species chosen to represent a wide range of evolutionary histories. Transcript sequences of all expressed and/or annotated loci from plants grown in unstressed (control) conditions were assembled and input into CREMA for comparative analyses. On average, 6.4% of the plant transcripts were identified by CREMA as encoding lncRNAs. Gene annotation associated with the transcripts showed that up to 99% of all predicted lncRNAs for Solanum tuberosum and Amborella trichopoda were missing from their reference annotations whereas the reference annotation for the genetic model plant Arabidopsis thaliana contains 96% of all predicted lncRNAs for this species. Thus a reliance on reference annotations for use in lncRNA research in less well-studied plants can be impeded by the near absence of annotations associated with these regulatory transcripts. Moreover, our work using phylogenetic signal analyses suggests that molecular traits of plant lncRNAs display different evolutionary patterns than all other transcripts in plants and have molecular traits that do not follow a classic evolutionary pattern. Specifically, GC content was the only tested trait of lncRNAs with consistently significant and high phylogenetic signal, contrary to high signal in all tested molecular traits for the other transcripts in our tested plant species.

Global Positioning System: Understanding Long Noncoding RNAs through Subcellular Localization

The localization of long noncoding RNAs (lncRNAs) within the cell is the primary determinant of their molecular functions. LncRNAs are often thought of as chromatin-restricted regulators of gene transcription and chromatin structure. However, a rich population of cytoplasmic lncRNAs has come to light, with diverse roles including translational regulation, signaling, and respiration. RNA maps of increasing resolution and scope are revealing a subcellular world of highly specific localization patterns and hint at sequence-based address codes specifying lncRNA fates. We propose a new framework for analyzing sequencing-based data, which suggests that numbers of cytoplasmic lncRNA molecules rival those in the nucleus. New techniques promise to create high-resolution, transcriptome-wide maps associated with all organelles of the mammalian cell. Given its intimate link to molecular roles, subcellular localization provides a means of unlocking the mystery of lncRNA functions.

Transcriptomic analyses reveal groups of co-expressed, syntenic lncRNAs in four species of the genus Caenorhabditis

Long non-coding RNAs (lncRNAs) are a heterogeneous class of genes that do not code for proteins. Since lncRNAs (or a fraction thereof) are expected to be functional, many efforts have been dedicated to catalog lncRNAs in numerous organisms, but our knowledge of lncRNAs in non vertebrate species remains very limited. Here, we annotated lncRNAs using transcriptomic data from the same larval stage of four Caenorhabditis species. The number of annotated lncRNAs in self-fertile nematodes was lower than in out-crossing species. We used a combination of approaches to identify putatively homologous lncRNAs: synteny, sequence conservation, and structural conservation. We classified a total of 1,532 out of 7,635 genes from the four species into families of lncRNAs with conserved synteny and expression at the larval stage, suggesting that a large fraction of the predicted lncRNAs may be species specific. Despite both sequence and local secondary structure seem to be poorly conserved, sequences within families frequently shared BLASTn hits and short sequence motifs, which were more likely to be unpaired in the predicted structures. We provide the first multi-species catalog of lncRNAs in nematodes and identify groups of lncRNAs with conserved synteny and expression, that share exposed motifs.

Identification of functional long non-coding RNAs in C. elegans

BACKGROUND

Functional characterisation of the compact genome of the model organism Caenorhabditis elegans remains incomplete despite its sequencing 20 years ago. The last decade of research has seen a tremendous increase in the number of non-coding RNAs identified in various organisms. While we have mechanistic understandings of small non-coding RNA pathways, long non-coding RNAs represent a diverse class of active transcripts whose function remains less well characterised.

RESULTS

By analysing hundreds of published transcriptome datasets, we annotated 3392 potential lncRNAs including 143 multi-exonic loci that showed increased nucleotide conservation and GC content relative to other non-coding regions. Using CRISPR/Cas9 genome editing, we generated deletion mutants for ten long non-coding RNA loci. Using automated microscopy for in-depth phenotyping, we show that six of the long non-coding RNA loci are required for normal development and fertility. Using RNA interference-mediated gene knock-down, we provide evidence that for two of the long non-coding RNA loci, the observed phenotypes are dependent on the corresponding RNA transcripts.

CONCLUSIONS

Our results highlight that a large section of the non-coding regions of the C. elegans genome remains unexplored. Based on our in vivo analysis of a selection of high-confidence lncRNA loci, we expect that a significant proportion of these high-confidence regions is likely to have a biological function at either the genomic or the transcript level.

Splicing of long non-coding RNAs primarily depends on polypyrimidine tract and 5' splice-site sequences due to weak interactions with SR proteins

Many nascent long non-coding RNAs (lncRNAs) undergo the same maturation steps as pre-mRNAs of protein-coding genes (PCGs), but they are often poorly spliced. To identify the underlying mechanisms for this phenomenon, we searched for putative splicing inhibitory sequences using the ncRNA-a2 as a model. Genome-wide analyses of intergenic lncRNAs (lincRNAs) revealed that lincRNA splicing efficiency positively correlates with 5'ss strength while no such correlation was identified for PCGs. In addition, efficiently spliced lincRNAs have higher thymidine content in the polypyrimidine tract (PPT) compared to efficiently spliced PCGs. Using model lincRNAs, we provide experimental evidence that strengthening the 5'ss and increasing the T content in PPT significantly enhances lincRNA splicing. We further showed that lincRNA exons contain less putative binding sites for SR proteins. To map binding of SR proteins to lincRNAs, we performed iCLIP with SRSF2, SRSF5 and SRSF6 and analyzed eCLIP data for SRSF1, SRSF7 and SRSF9. All examined SR proteins bind lincRNA exons to a much lower extent than expression-matched PCGs. We propose that lincRNAs lack the cooperative interaction network that enhances splicing, which renders their splicing outcome more dependent on the optimality of splice sites.

LncRNA-000133 from secondary hair follicle of Cashmere goat: identification, regulatory network and its effects on inductive property of dermal papilla cells

Long noncoding RNAs (lncRNAs), a class of non-protein conding RNAs > 200 nt in length, were thought to play critical roles in regulating the expression of protein-coding genes. Here, we identified and characterized a novel lncRNA-000133 from the secondary hair follicle (SHF) of cashmere goat with its ceRNA network analysis, as well as, its potential effects on inductive property of dermal papilla cells were evaluated through overexpression analysis. Expression analysis indicated that lncRNA-000133 had a significantly higher expression at anagen than that at telogen in SHF of Cashmere goat, suggesting that lncRNA-000133 might be involved in the reconstruction of SHF with the formation and growth of cashmere fiber. Taken together with methylation analysis, we showed that 5' regulatory region methylation of the lncRNA-000133 gene might be involved in its expression suppression in SHF of Cashmere goat. The ceRNA regulatory network showed that a rich and complex regulatory relationship between lncRNA-000133 and related miRNAs with their target genes. The overexpression of lncRNA-000133 led to a significant increasing in the relative expression of ET-1, SCF, ALP and LEF1 in dermal papilla cells suggesting that lncRNA-000133 appears to contribute the inductive property of dermal papilla cells.

CRlncRC: a machine learning-based method for cancer-related long noncoding RNA identification using integrated features

BACKGROUND

Long noncoding RNAs (lncRNAs) are widely involved in the initiation and development of cancer. Although some computational methods have been proposed to identify cancer-related lncRNAs, there is still a demanding to improve the prediction accuracy and efficiency. In addition, the quick-update data of cancer, as well as the discovery of new mechanism, also underlay the possibility of improvement of cancer-related lncRNA prediction algorithm. In this study, we introduced CRlncRC, a novel Cancer-Related lncRNA Classifier by integrating manifold features with five machine-learning techniques.

RESULTS

CRlncRC was built on the integration of genomic, expression, epigenetic and network, totally in four categories of features. Five learning techniques were exploited to develop the effective classification model including Random Forest (RF), Naïve bayes (NB), Support Vector Machine (SVM), Logistic Regression (LR) and K-Nearest Neighbors (KNN). Using ten-fold cross-validation, we showed that RF is the best model for classifying cancer-related lncRNAs (AUC = 0.82). The feature importance analysis indicated that epigenetic and network features play key roles in the classification. In addition, compared with other existing classifiers, CRlncRC exhibited a better performance both in sensitivity and specificity. We further applied CRlncRC to lncRNAs from the TANRIC (The Atlas of non-coding RNA in Cancer) dataset, and identified 121 cancer-related lncRNA candidates. These potential cancer-related lncRNAs showed a certain kind of cancer-related indications, and many of them could find convincing literature supports.

CONCLUSIONS

Our results indicate that CRlncRC is a powerful method for identifying cancer-related lncRNAs. Machine-learning-based integration of multiple features, especially epigenetic and network features, had a great contribution to the cancer-related lncRNA prediction. RF outperforms other learning techniques on measurement of model sensitivity and specificity. In addition, using CRlncRC method, we predicted a set of cancer-related lncRNAs, all of which displayed a strong relevance to cancer as a valuable conception for the further cancer-related lncRNA function studies.

Identifying sequence features that drive ribosomal association for lncRNA

BACKGROUND

With the increasing number of annotated long noncoding RNAs (lncRNAs) from the genome, researchers are continually updating their understanding of lncRNAs. Recently, thousands of lncRNAs have been reported to be associated with ribosomes in mammals. However, their biological functions or mechanisms are still unclear.

RESULTS

In this study, we tried to investigate the sequence features involved in the ribosomal association of lncRNA. We have extracted ninety-nine sequence features corresponding to different biological mechanisms (i.e., RNA splicing, putative ORF, k-mer frequency, RNA modification, RNA secondary structure, and repeat element). An [Formula: see text]-regularized logistic regression model was applied to screen these features. Finally, we obtained fifteen and nine important features for the ribosomal association of human and mouse lncRNAs, respectively.

CONCLUSION

To our knowledge, this is the first study to characterize ribosome-associated lncRNAs and ribosome-free lncRNAs from the perspective of sequence features. These sequence features that were identified in this study may shed light on the biological mechanism of the ribosomal association and provide important clues for functional analysis of lncRNAs.

RNA splicing analysis in genomic medicine

High-throughput next-generation sequencing technologies have led to a rapid increase in the number of sequence variants identified in clinical practice via diagnostic genetic tests. Current bioinformatic analysis pipelines fail to take adequate account of the possible splicing effects of such variants, particularly where variants fall outwith canonical splice site sequences, and consequently the pathogenicity of such variants may often be missed. The regulation of splicing is highly complex and as a result, in silico prediction tools lack sufficient sensitivity and specificity for reliable use. Variants of all kinds can be linked to aberrant splicing in disease and the need for correct identification and diagnosis grows ever more crucial as novel splice-switching antisense oligonucleotide therapies start to enter clinical usage. RT-PCR provides a useful targeted assay of the splicing effects of identified variants, while minigene assays, massive parallel reporter assays and animal models can also be used for more detailed study of a particular splicing system, given enough time and resources. However, RNA-sequencing (RNA-seq) has the potential to be used as a rapid diagnostic tool in genomic medicine. By utilising data science approaches and machine learning, it may prove possible to finally understand and interpret the 'splicing code' and apply this knowledge in human disease diagnostics.

Production of Spliced Long Noncoding RNAs Specifies Regions with Increased Enhancer Activity

Active enhancers in mammals produce enhancer RNAs (eRNAs) that are bidirectionally transcribed, unspliced, and unstable. Enhancer regions are also enriched with long noncoding RNA (lncRNA) transcripts, which are typically spliced and substantially more stable. In order to explore the relationship between these two classes of RNAs, we analyzed DNase hypersensitive sites with evidence of bidirectional transcription, which we termed eRNA-producing centers (EPCs). EPCs found very close to transcription start sites of lncRNAs exhibit attributes of both enhancers and promoters, including distinctive DNA motifs and a characteristic chromatin landscape. These EPCs are associated with higher enhancer activity, driven at least in part by the presence of conserved, directional splicing signals that promote lncRNA production, pointing at a causal role of lncRNA processing in enhancer activity. Together, our results suggest that the conserved ability of some enhancers to produce lncRNAs augments their activity in a manner likely mediated through lncRNA maturation.

Integrated analysis of long noncoding RNA and mRNA expression profiles reveals the potential role of long noncoding RNA in different bovine lactation stages

Long noncoding RNA (lncRNA) play a critical role in mammary development and breast cancer biology. Despite their important role in the mammary gland, little is known of the roles of lncRNA in bovine lactation, particularly regarding the molecular processes underlying it. To characterize the role of lncRNA in bovine lactation, 4 samples of Holstein cow mammary gland tissue at peak and late lactation stages were examined after biopsy. We then profiled the transcriptome of the mammary gland using RNA sequencing technology. Further, functional lncRNA-mRNA coexpression pairs were constructed to infer the function of lncRNA using a generalized linear model, followed by gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. More than 1,000 putative lncRNA were identified, 117 of which were differentially expressed between peak and late lactation stages. Bovine lncRNA were shorter, with fewer exon numbers, and expressed at significantly lower levels than protein-coding genes. Seventy-two differentially expressed (DE) lncRNA were coexpressed with 340 different protein-coding genes. The KEGG pathway analysis showed that target mRNA for DE lncRNA were mainly related to lipid and glucose metabolism, including the peroxisome proliferator-activated receptors and 5' adenosine monophosphate-activated protein kinase signaling pathways. Further bioinformatics and integrative analyses revealed that 12 DE lncRNA potentially played important roles in bovine lactation. Our findings provide a valuable resource for future bovine transcriptome studies, facilitate the understanding of bovine lactation biology, and offer functional information for cattle lactation.

Towards a complete map of the human long non-coding RNA transcriptome

Gene maps, or annotations, enable us to navigate the functional landscape of our genome. They are a resource upon which virtually all studies depend, from single-gene to genome-wide scales and from basic molecular biology to medical genetics. Yet present-day annotations suffer from trade-offs between quality and size, with serious but often unappreciated consequences for downstream studies. This is particularly true for long non-coding RNAs (lncRNAs), which are poorly characterized compared to protein-coding genes. Long-read sequencing technologies promise to improve current annotations, paving the way towards a complete annotation of lncRNAs expressed throughout a human lifetime.

Exploration of the Germline Genome of the Ciliate Chilodonella uncinata through Single-Cell Omics (Transcriptomics and Genomics)

Separate germline and somatic genomes are found in numerous lineages across the eukaryotic tree of life, often separated into distinct tissues (e.g., in plants, animals, and fungi) or distinct nuclei sharing a common cytoplasm (e.g., in ciliates and some foraminifera). In ciliates, germline-limited (i.e., micronuclear-specific) DNA is eliminated during the development of a new somatic (i.e., macronuclear) genome in a process that is tightly linked to large-scale genome rearrangements, such as deletions and reordering of protein-coding sequences. Most studies of germline genome architecture in ciliates have focused on the model ciliates Oxytricha trifallax, Paramecium tetraurelia, and Tetrahymena thermophila, for which the complete germline genome sequences are known. Outside of these model taxa, only a few dozen germline loci have been characterized from a limited number of cultivable species, which is likely due to difficulties in obtaining sufficient quantities of “purified” germline DNA in these taxa. Combining single-cell transcriptomics and genomics, we have overcome these limitations and provide the first insights into the structure of the germline genome of the ciliate Chilodonella uncinata, a member of the understudied class Phyllopharyngea. Our analyses reveal the following: (i) large gene families contain a disproportionate number of genes from scrambled germline loci; (ii) germline-soma boundaries in the germline genome are demarcated by substantial shifts in GC content; (iii) single-cell omics techniques provide large-scale quality germline genome data with limited effort, at least for ciliates with extensively fragmented somatic genomes. Our approach provides an efficient means to understand better the evolution of genome rearrangements between germline and soma in ciliates.

Our understanding of the distinctions between germline and somatic genomes in ciliates has largely relied on studies of a few model genera (e.g., Oxytricha, Paramecium, Tetrahymena). We have used single-cell omics to explore germline-soma distinctions in the ciliate Chilodonella uncinata, which likely diverged from the better-studied ciliates ~700 million years ago. The analyses presented here indicate that developmentally regulated genome rearrangements between germline and soma are demarcated by rapid transitions in local GC composition and lead to diversification of protein families. The approaches used here provide the basis for future work aimed at discerning the evolutionary impacts of germline-soma distinctions among diverse ciliates.

Comparative RNA Genomics

Over the last two decades it has become clear that RNA is much more than just a boring intermediate in protein expression. Ancient RNAs still appear in the core information metabolism and comprise a surprisingly large component in bacterial gene regulation. A common theme with these types of mostly small RNAs is their reliance of conserved secondary structures. Large scale sequencing projects, on the other hand, have profoundly changed our understanding of eukaryotic genomes. Pervasively transcribed, they give rise to a plethora of large and evolutionarily extremely flexible noncoding RNAs that exert a vastly diverse array of molecule functions. In this chapter we provide a-necessarily incomplete-overview of the current state of comparative analysis of noncoding RNAs, emphasizing computational approaches as a means to gain a global picture of the modern RNA world.

Deep RNA Sequencing Uncovers a Repertoire of Human Macrophage Long Intergenic Noncoding RNAs Modulated by Macrophage Activation and Associated With Cardiometabolic Diseases

Background

Sustained and dysfunctional macrophage activation promotes inflammatory cardiometabolic disorders, but the role of long intergenic noncoding RNA (lincRNA) in human macrophage activation and cardiometabolic disorders is poorly defined. Through transcriptomics, bioinformatics, and selective functional studies, we sought to elucidate the lincRNA landscape of human macrophages.

Methods and Results

We used deep RNA sequencing to assemble the lincRNA transcriptome of human monocyte‐derived macrophages at rest and following stimulation with lipopolysaccharide and IFN‐γ (interferon γ) for M1 activation and IL‐4 (interleukin 4) for M2 activation. Through de novo assembly, we identified 2766 macrophage lincRNAs, including 861 that were previously unannotated. The majority (≈85%) was nonsyntenic or was syntenic but not annotated as expressed in mouse. Many macrophage lincRNAs demonstrated tissue‐enriched transcription patterns (21.5%) and enhancer‐like chromatin signatures (60.9%). Macrophage activation, particularly to the M1 phenotype, markedly altered the lincRNA expression profiles, revealing 96 lincRNAs differentially expressed, suggesting potential roles in regulating macrophage inflammatory functions. A subset of lincRNAs overlapped genomewide association study loci for cardiometabolic disorders. MacORIS (macrophage‐enriched obesity‐associated lincRNA serving as a repressor of IFN‐γ signaling), a macrophage‐enriched lincRNA not expressed in mouse macrophages, harbors variants associated with central obesity. Knockdown of MacORIS, which is located in the cytoplasm, enhanced IFN‐γ–induced JAK2 (Janus kinase 2) and STAT1 (signal transducer and activator of transcription 1) phosphorylation in THP‐1 macrophages, suggesting a potential role as a repressor of IFN‐γ signaling. Induced pluripotent stem cell–derived macrophages recapitulated the lincRNA transcriptome of human monocyte‐derived macrophages and provided a high‐fidelity model with which to study lincRNAs in human macrophage biology, particularly those not conserved in mouse.

Conclusions

High‐resolution transcriptomics identified lincRNAs that form part of the coordinated response during macrophage activation, including specific macrophage lincRNAs associated with human cardiometabolic disorders that modulate macrophage inflammatory functions.