Analysis of mRNA and Long Non-Coding RNA Expression Profiles in Developing Yorkshire Pig Spleens

Epidemic diseases cause great economic loss in pig farms each year; some of these diseases are characterized mainly in the spleen, but mRNA and lncRNA (long non-coding RNA) expression networks in developing Yorkshire pig spleens remain obscure. Here, we profiled the systematic characters of mRNA and lncRNA repertoires in three groups of spleens from nine Yorkshire pigs, each three aged at seven days, 90 days, and 180 days. By using a precise mRNA and lncRNA identification pipeline, we identified 19,647 genes and 219 known and 3219 putative lncRNA transcripts; 1729 genes and 64 lncRNAs therein were found to express differentially. The gene expression characteristics of genes and lncRNAs were found to be basically fixed before 90 days after birth. Three large gene expression modules were detected. The enrichment analyses of differentially expressed genes and the potential target genes of differentially expressed lncRNAs both displayed the crucial roles of up-regulation in immune activation and hematopoiesis, and down-regulation in cell replication and division in 90 days and 180 days compared to seven days. ENSSSCT00000001325 was the only lncRNA transcript that existed in the three groups. CDK1, PCNA, and PLK were detected to be node genes that varied with age. This study contributes to a further understanding of mRNA and lncRNA expression in different developmental pig spleens.

Identification of mRNA and Long Non-Coding RNA Expression Profiles in Developing Yorkshire Pig Spleens

Background: Epidemic diseases cause great economic loss in pig farms each year, some of which are characterized mainly in spleen. Yorkshire pig is the most popular used first dam in the commercial pork production system. But the mRNA and lncRNA expression networks in developing Yorkshire pig spleens remain obscure. Results: Here, we profiled the systematic characters of mRNA and lncRNA repertoires in three groups of spleens from nine Yorkshire pigs, each three aged at 7 days, 90 days and 180 days. By using a precise mRNA and lncRNA identification pipeline, we identified 19,647 genes and 219 known and 3,219 putative lncRNA transcripts, 1,729 genes and 64 lncRNAs therein were found to express differentially in three groups. Gene expression characteristics of genes and lncRNAs were found to be basically fixed before 90 days after birth. Enrichment analysis of differentially expressed genes and potential target genes of differentially expressed lncRNAs both displayed crucial roles of up-regulation in immune activation and hematopoiesis and down-regulation in cell replication and division in 90 and 180 days compared to 7 days. The unregulated terms and their significance levels in 90 and 180 days both showed an extremely high degree of consistency. ENSSSCT00000001325 was the only lncRNA transcript that existed in three groups. CDK1, PCNA and PLK were detected to be hub genes that varied with age. BNIP3L, IL5, CD38 and TGFβ1 were found to be common top regulators from 7 to 90 and 180 days while ERAP1, NLRC5 and IL2RG were top regulators from 90 to 180 days.Conclusions: This study provided the first mRNA and lncRNA expression profiles in Yorkshire spleens at three developmental stages. We established gene expression modules and networks in the spleen of pigs from immune system initiation to adulthood. Our results are helpful for the study of transcriptome and functional genomics of spleen tissue in farm animals.

linc2function: A deep learning model to identify and assign function to long noncoding RNA (lncRNA)

MotivationLncRNAs are much more versatile and are involved in many regulatory roles inside the cell than previously believed. Existing databases lack consistencies in lncRNA annotations, and the functionality of over 95% of the known lncRNAs are yet to be established. LncRNA transcript identification involves discriminating them from their coding counterparts, which can be done with traditional experimental approaches, or via in silico methods. The later approach employs various computational algorithms, including machine learning classifiers to predict the lncRNA forming potential of a given transcript. Such approaches provide an economical and faster alternative to the experimental methods. Current in silico methods mainly use primary-sequence based features to build predictive models limiting their accuracy and robustness. Moreover, many of these tools make use of reference genome based features, in consequence making them unsuitable for non-model species. Hence, there is a need to comprehensively evaluate the efficacy of different predictive features to build computational models. Additionally, effective models will have to provide maximum prediction performance using the least number of features in a species-agnostic manner.It is popularly known in the protein world that “structure is function”. This also applies to lncRNAs as their functional mechanisms are similar to those of proteins. Generally, lncRNA function by structurally binding to its target proteins or nucleic acid forming complexes. The secondary structures of the lncRNAs are modular providing interaction sites for their interactome made of DNA, RNA, and proteins. Through these interactions, they epigenetically regulate cellular biology, thereby forming a layer of genomic programming on top of the coding genes. We demonstrate that in addition to using transcript sequence, we can provide comprehensive functional annotation by collating their interactome and secondary structure information.ResultsHere, we evaluated an exhaustive list of sequence-based, secondary-structure, interactome, and physicochemical features for their ability to predict the lncRNA potential of a transcript. Based on our analysis, we built different machine learning models using optimum feature-set. We found our model to be on par or exceeding the execution of the state-of-the-art methods with AUC values of over 0.9 for a diverse collection of species tested. Finally, we built a pipeline called linc2function that provides the information necessary to functionally annotate a lncRNA conveniently in a single window.AvailabilityThe source code is accessible use under MIT license in standalone mode, and as a webserver (https://bioinformaticslab.erc.monash.edu/linc2function).

Genome-wide identification of Aedes albopictus long noncoding RNAs and their association with dengue and Zika virus infection

The Asian tiger mosquito, Aedes albopictus (Ae. albopictus), is an important vector that transmits arboviruses such as dengue (DENV), Zika (ZIKV) and Chikungunya virus (CHIKV). Long noncoding RNAs (lncRNAs) are known to regulate various biological processes. Knowledge on Ae. albopictus lncRNAs and their functional role in virus-host interactions are still limited. Here, we identified and characterized the lncRNAs in the genome of an arbovirus vector, Ae. albopictus, and evaluated their potential involvement in DENV and ZIKV infection. We used 148 public datasets, and identified a total of 10, 867 novel lncRNA transcripts, of which 5,809, 4,139, and 919 were intergenic, intronic and antisense respectively. The Ae. albopictus lncRNAs shared many characteristics with other species such as short length, low GC content, and low sequence conservation. RNA-sequencing of Ae. albopictus cells infected with DENV and ZIKV showed that the expression of lncRNAs was altered upon virus infection. Target prediction analysis revealed that Ae. albopictus lncRNAs may regulate the expression of genes involved in immunity and other metabolic and cellular processes. To verify the role of lncRNAs in virus infection, we generated mutations in lncRNA loci using CRISPR-Cas9, and discovered that two lncRNA loci mutations, namely XLOC_029733 (novel lncRNA transcript id: lncRNA_27639.2) and LOC115270134 (known lncRNA transcript id: XR_003899061.1) resulted in enhancement of DENV and ZIKV replication. The results presented here provide an important foundation for future studies of lncRNAs and their relationship with virus infection in Ae. albopictus.

Knockdown of lncRNA TapSAKI alleviates LPS-induced injury in HK-2 cells through the miR-205/IRF3 pathway

Sepsis is a common and lethal syndrome. Long non-coding RNA (lncRNA) transcript predicting survival in AKI (TapSAKI) has recently been found to serve as an important regulator in sepsis. However, the underlying mechanism of TapSAKI in sepsis pathogenesis remains largely unknown. Our data demonstrated that lipopolysaccharide (LPS)-induced HK-2 cell injury by weakening cell viability and enhancing cell apoptosis and inflammation. TapSAKI was upregulated and miR-205 was downregulated in LPS-induced HK-2 cells. TapSAKI knockdown or miR-205 overexpression alleviated LPS-induced cytotoxicity in HK-2 cells. TapSAKI sequestered miR-205 via acting as a miR-205 sponge. Moreover, the mitigating effect of TapSAKI silencing on LPS-induced HK-2 cell injury was mediated by miR-205. Additionally, the interferon regulatory factor 3 (IRF3) signaling was involved in the regulation of the TapSAKI/miR-205 axis on LPS-induced HK-2 cell damage. Our current study suggested that TapSAKI silencing relieved LPS-induced injury in HK-2 cells at least in part by sponging miR-205 and regulating the IRF3 signaling pathway, highlighting a novel understanding for sepsis pathogenesis and a promising target for this disease treatment.

Detecting Misannotated Long Non-coding RNAs with Training Dynamics of Deep Sequence Classification

Long non-coding RNAs (lncRNAs) are the largest class of non-coding RNAs (ncRNAs). However, recent experimental evidence has shown that some lncRNAs contain small open reading frames (sORFs) that are translated into functional micropeptides. Current methods to detect misannotated lncRNAs rely on ribosome-profiling (ribo-seq) experiments, which are expensive and cell-type dependent. In addition, while very accurate machine learning models have been trained to distinguish between coding and non-coding sequences, little attention has been paid to the increasing evidence about the incorrect ground-truth labels of some lncRNAs in the underlying training datasets. We present a framework that leverages deep learning models’ training dynamics to determine whether a given lncRNA transcript is misannotated. Our models achieve AUC scores > 91% and AUPR > 93% in classifying non-coding vs. coding sequences while allowing us to identify possible misannotated lncRNAs present in the dataset. Our results overlap significantly with a set of experimentally validated misannotated lncRNAs as well as with coding sORFs within lncRNAs found by a ribo-seq dataset. The general framework applied here offers promising potential for use in curating datasets used for training coding potential predictors and assisting experimental efforts in characterizing the hidden proteome encoded by misannotated lncRNAs. Source code is available at https://github.com/nabiafshan/DetectingMisannotatedLncRNAs.

Genome-wide identification of Aedes albopictus long noncoding RNAs and their association with dengue and zika virus infection

The Asian tiger mosquito, Aedes albopictus (Ae. albopictus), is an important vector that transmits arboviruses such as dengue (DENV), Zika (ZIKV) and Chikungunya virus (CHIKV). On the other hand, long noncoding RNAs (lncRNAs) are known to regulate various biological processes. Knowledge on Ae. albopictus lncRNAs and their functional role in virus-host interactions are still limited. Here, we identified and characterized the lncRNAs in the genome of an arbovirus vector, Ae. albopictus, and evaluated their potential involvement in DENV and ZIKV infection. We used 148 public datasets, and identified a total of 10, 867 novel lncRNA transcripts, of which 5,809, 4,139, and 919 were intergenic, intronic and antisense respectively. The Ae. albopictus lncRNAs shared many characteristics with other species such as short length, low GC content, and low sequence conservation. RNA-sequencing of Ae. albopictus cells infected with DENV and ZIKV showed that the expression of lncRNAs was altered upon virus infection. Target prediction analysis revealed that Ae. albopictus lncRNAs may regulate the expression of genes involved in immunity and other metabolic and cellular processes. To verify the role of lncRNAs in virus infection, we generated mutation in lncRNA loci using CRISPR-Cas9, and discovered that two lncRNA loci mutations, namely XLOC_029733 (novel lncRNA transcript id: lncRNA_27639.2) and LOC115270134 (known lncRNA transcript id: XR_003899061.1) resulted in enhancement of DENV and ZIKV replication. The results presented here provide an important foundation for future studies of lncRNAs and their relationship with virus infection in Ae. albopictus.Author summaryAe. albopictus is an important vector of arboviruses such as dengue and Zika. Studies on virus-host interaction at gene expression and molecular level are crucial especially in devising methods to inhibit virus replication in Aedes mosquito. Previous reports showed that, besides protein-coding genes, noncoding RNAs such as lncRNAs are also involved in virus-host interaction. In this study, we report a comprehensive catalog of novel lncRNA transcripts in the genome of Ae. albopictus. We also show that the expression of lncRNAs was altered upon infection with dengue and Zika. Additionally, depletion of certain lncRNAs resulted in increased replication of dengue and Zika; hence, suggesting potential association of lncRNAs in virus infection. Results of this study provide a new avenue to the investigation of mosquito-virus interactions that may potentially pave way to the development of novel methods in vector control.

Polymorphisms of a novel long non-coding RNA RP11-108K3.2 with colorectal cancer susceptibility and their effects on its expression

Background: RP11-108K3.2 was recently identified as a novel long non-coding RNA (lncRNA) transcript, and several single nucleotide polymorphisms (SNPs) have been identified in its coding region. This study aimed to explore the associations of tagSNPs in RP11-108K3.2 with the risk of colorectal cancer and their effects on its expression. Methods: A total of 821 colorectal cancer cases and 857 healthy controls were enrolled into this two-stage case-control study. Demographic characteristics and lifestyle information were collected by a validated questionnaire. Six tagSNPs were genotyped by using Sequenom MassARRAY platform. A total of 71 additional colorectal cancer cases were recruited, of which the genotypes of potential polymorphisms and the RP11-108K3.2 expression levels were determined. Results: In the discovery set, only the rs2470151 C/T polymorphism was found to have a promising association with the risk of colorectal cancer, and this polymorphism was further replicated in the validation set with a significantly decreased risk of colorectal cancer (adjusted odds ratio 0.73; 95% confidence interval 0.55, 0.97). Combined discovery set and validation set together, this negative association was found both in the heterozygote codominant model and the dominant model. Furthermore, colorectal cancer patients carrying rs2470151 CT/TT genotypes had a marginally lower RNA expression of RP11-108K3.2 than those carrying the CC genotype. Stratified analyses showed the association between rs2470151 and the risk of colorectal cancer were influenced by family history of cancer, smoking, alcohol consumption, and tea drinking. Conclusions: These findings suggest that RP11-108K3.2 rs2470151 had a significant association with the risk of colorectal cancer; this may help to predict the susceptibility of colorectal cancer in Chinese populations.

The Firre locus produces a trans-acting RNA molecule that functions in hematopoiesis

ABSTRACTRNA has been classically known to play central roles in biology, including maintaining telomeres1, protein synthesis2, and in sex chromosome compensation in certain species3,4. At the center of these important biological systems are noncoding RNAs. While thousands of long noncoding RNAs (lncRNAs) have been identified in mammalian genomes5–8, attributing RNA-based roles to lncRNA loci requires an assessment of whether the observed effect could be due to DNA regulatory elements, the act of transcription, or the lncRNA transcript. Here, we use the syntenically conserved lncRNA locus, Functional intergenic repeating RNA element (Firre), that is located on the X chromosome as a model to discriminate between DNA- and RNA-mediated effects in vivo. To this end, we generated genetically defined loss-of-function, gain-of-function, and rescue mouse models for Firre and provide genetic evidence that the Firre locus produces a trans-acting RNA. We report that: (i) Firre mutant mice have cell-specific defects during hematopoiesis and changes in gene expression that can be rescued by induction of Firre RNA from a transgene in the Firre knockout background, (ii) mice overexpressing Firre from a transgene exhibit increased levels of pro-inflammatory cytokines and impaired survival upon exposure to lipopolysaccharide, and (iii) deletion of the Firre locus did not result in changes in local gene expression on the X chromosome in 9 different biological contexts, suggesting that Firre does not function by cis-acting RNA or DNA elements. Together, our results provide genetic evidence that the Firre locus produces a trans-acting lncRNA that has physiological roles in hematopoiesis and immune function.