Identification of transcribed protein coding sequence remnants within lincRNAs

Long Non-Coding RNAs and Their "Discrete" Contribution to IBD and Johne's Disease-What Stands out in the Current Picture? A Comprehensive Review

Non-coding RNAs (ncRNA) have paved the way to new perspectives on the regulation of gene expression, not only in biology and medicine, but also in associated fields and technologies, ensuring advances in diagnostic means and therapeutic modalities. Critical in this multistep approach are the associations of long non-coding RNA (lncRNA) with diseases and their causal genes in their networks of interactions, gene enrichment and expression analysis, associated pathways, the monitoring of the involved genes and their functional roles during disease progression from one stage to another. Studies have shown that Johne's Disease (JD), caused by Mycobacterium avium subspecies partuberculosis (MAP), shares common lncRNAs, clinical findings, and other molecular entities with Crohn's Disease (CD). This has been a subject of vigorous investigation owing to the zoonotic nature of this condition, although results are still inconclusive. In this review, on one hand, the current knowledge of lncRNAs in cells is presented, focusing on the pathogenesis of gastrointestinal-related pathologies and MAP-related infections and, on the other hand, we attempt to dissect the associated genes and pathways involved. Furthermore, the recently characterized and novel lncRNAs share common pathologies with IBD and JD, including the expression, molecular networks, and dataset analysis results. These are also presented in an attempt to identify potential biomarkers pertinent to cattle and human disease phenotypes.

LncRNAs specifically overexpressed in endocervical adenocarcinoma are associated with an unfavorable recurrence prognosis and the immune response

Background

Cervical cancer is the fourth most common gynecological tumor in terms of both the incidence and mortality of females worldwide. Cervical squamous cell carcinoma (CSCC) accounts for 70–80% of cervical cancers, and endocervical adenocarcinoma (EAC) accounts for 20–25%. Unlike CSCC, EAC has worse clinical outcomes and prognosis. In this study, we explored the relationship between various types of long noncoding RNAs (lncRNAs) and pathological types of cervical cancer.

Methods

RNA sequencing (RNA-Seq) and clinical data from The Cancer Genome Atlas (TCGA) were used in this study. A single-sample gene set enrichment analysis (ssGSEA) and the ESTIMATE package were used to assess lncRNA activity and immune responses, respectively. RT-qPCR was performed to verify our findings.

Results

We explored the relationship between various types of lncRNAs and pathological types of cervical cancer. A series of long intergenic noncoding RNAs (lincRNAs) and antisense RNAs, which are the major types of lncRNAs, were identified to be specifically expressed in EAC and associated with a poor recurrence prognosis in patients with cervical cancer, suggesting that they might serve as independent prognostic markers of recurrence in patients with cervical cancer. RT-qPCR was performed to verify the 10 EAC-specific lncRNAs in cervical cancer samples we collected. Furthermore, the overexpression of these lncRNAs was positively correlated with EAC pathology levels but negatively correlated with immune responses in the microenvironment of cervical cancer.

Conclusions

These lncRNAs potentially represent new biomarkers for the prediction of the recurrence prognosis and help obtain deeper insights into potential immunotherapeutic approaches for treating cervical cancer.

DNA numerical encoding schemes for exon prediction: a recent history

Bioinformatics in the present day has been firmly established as a regulator in genomics. In recent times, applications of Signal processing in exon prediction have gained a lot of attention. The exons carry protein information. Proteins are composed of connected constituents known as amino acids that characterize the specific function. Conversion of the nucleotide character string into a numerical sequence is the gateway before analyzing it through signal processing methods. This numeric encoding is the mathematical descriptor of nucleotides and is based on some statistical properties of the structure of nucleic acids. Since the type of encoding extremely affects the exon detection accuracy, this paper is devised for the review of existing encoding (mapping) schemes. The comparative analysis is formulated to emphasize the importance of the genetic code setting of amino acids considered for application related to computational elucidation for exon detection. This work covers much helpful information for future applications.

Identification of prognostic long intergenic non-coding RNAs as competing endogenous RNAs with KRAS mutations in colorectal cancer

Colorectal cancer (CRC) is recognized as a common type of human cancer, and KRAS mutations are correlated with poor CRC survival outcomes. The evaluation and prediction of CRC results remain challenging. In the present study, RNA sequencing and clinical data from The Cancer Genome Atlas were used to identify KRAS mutation-related prognostic long intergenic non-coding RNAs (lincRNAs) in CRC. Significantly dysregulated lincRNAs and independent prognostic lincRNAs with KRAS mutations in CRC were identified. Two lincRNAs with KRAS mutations, LINC00265 and AL390719.2, were selected as key prognostic lincRNAs for both 10- and 5-year survival rates. In addition, competing endogenous (ce)RNA models were constructed to comprehensively assess the oncogenic performance of the two key lincRNAs. The ceRNA models suggested that LINC00265 and AL390719.2 are critical for the cell cycle and cancer pathways. Finally, reverse transcription-quantitative PCR was used to validate the ceRNA models in 12 pairs of CRC tissue samples. These prognostic lincRNAs may provide novel biomarkers for the prognostic prediction of CRC. The ceRNA model may also demonstrate the underlying mechanism of these lincRNAs in CRC.

DiseaseLinc: Disease Enrichment Analysis of Sets of Differentially Expressed LincRNAs

Long intergenic non-coding RNAs (LincRNAs) are long RNAs that do not encode proteins. Functional evidence is lacking for most of them. Their biogenesis is not well-known, but it is thought that many lincRNAs originate from genomic duplication of coding material, resulting in pseudogenes, gene copies that lose their original function and can accumulate mutations. While most pseudogenes eventually stop producing a transcript and become erased by mutations, many of these pseudogene-based lincRNAs keep similarity to the parental gene from which they originated, possibly for functional reasons. For example, they can act as decoys for miRNAs targeting the parental gene. Enrichment analysis of function is a powerful tool to discover the functional effects of a treatment producing differential expression of transcripts. However, in the case of lincRNAs, since their function is not easy to define experimentally, such a tool is lacking. To address this problem, we have developed an enrichment analysis tool that focuses on lincRNAs exploiting their functional association, using as a proxy function that of the parental genes and has a focus on human diseases.

Formation of human long intergenic non-coding RNA genes, pseudogenes, and protein genes: Ancestral sequences are key players

Pathways leading to formation of non-coding RNA and protein genes are varied and complex. We report finding a conserved repeat sequence present in human and chimpanzee genomes that appears to have originated from a common primate ancestor. This sequence is repeatedly copied in human chromosome 22 (chr22) low copy repeats (LCR22) or segmental duplications and forms twenty-one different genes, which include the human long intergenic non-coding RNA (lincRNA) family FAM230, a newly discovered lincRNA gene family termed conserved long intergenic non-coding RNAs (clincRNA), pseudogene families, as well as the gamma-glutamyltransferase (GGT) protein gene family and the RNA pseudogenes that originate from GGT sequences. Of particular interest are the GGT5 and USP18 protein genes that appear to have formed from an homologous repeat sequence that also forms the clincRNA gene family. The data point to ancestral DNA sequences, conserved through evolution and duplicated in humans by chromosomal repeat sequences that may serve as functional genomic elements in the development of diverse genes.

Computational Methods for Mapping, Assembly and Quantification for Coding and Non-coding Transcripts

The measurement of gene expression has long provided significant insight into biological functions. The development of high-throughput short-read sequencing technology has revealed transcriptional complexity at an unprecedented scale, and informed almost all areas of biology. However, as researchers have sought to gather more insights from the data, these new technologies have also increased the computational analysis burden. In this review, we describe typical computational pipelines for RNA-Seq analysis and discuss their strengths and weaknesses for the assembly, quantification and analysis of coding and non-coding RNAs. We also discuss the assembly of transposable elements into transcripts, and the difficulty these repetitive elements pose. In summary, RNA-Seq is a powerful technology that is likely to remain a key asset in the biologist's toolkit.

Multi-Omics Approaches to Study Long Non-coding RNA Function in Atherosclerosis

Atherosclerosis is a complex inflammatory disease of the vessel wall involving the interplay of multiple cell types including vascular smooth muscle cells, endothelial cells, and macrophages. Large-scale genome-wide association studies (GWAS) and the advancement of next generation sequencing technologies have rapidly expanded the number of long non-coding RNA (lncRNA) transcripts predicted to play critical roles in the pathogenesis of the disease. In this review, we highlight several lncRNAs whose functional role in atherosclerosis is well-documented through traditional biochemical approaches as well as those identified through RNA-sequencing and other high-throughput assays. We describe novel genomics approaches to study both evolutionarily conserved and divergent lncRNA functions and interactions with DNA, RNA, and proteins. We also highlight assays to resolve the complex spatial and temporal regulation of lncRNAs. Finally, we summarize the latest suite of computational tools designed to improve genomic and functional annotation of these transcripts in the human genome. Deep characterization of lncRNAs is fundamental to unravel coronary atherosclerosis and other cardiovascular diseases, as these regulatory molecules represent a new class of potential therapeutic targets and/or diagnostic markers to mitigate both genetic and environmental risk factors.