Functional examination of lncRNAs in allotetraploid Gossypium hirsutum

BACKGROUND

An evolutionary model using diploid and allotetraploid cotton species identified 80 % of non-coding transcripts in allotetraploid cotton as being uniquely activated in comparison with its diploid ancestors. The function of the lncRNAs activated in allotetraploid cotton remain largely unknown.

RESULTS

We employed transcriptome analysis to examine the relationship between the lncRNAs and mRNAs of protein coding genes (PCGs) in cotton leaf tissue under abiotic stresses. LncRNA expression was preferentially associated with that of the flanking PCGs. Selected highly-expressed lncRNA candidates (n = 111) were subjected to a functional screening pilot test in which virus-induced gene silencing was integrated with abiotic stress treatment. From this low-throughput screen, we obtained candidate lncRNAs relating to plant height and tolerance to drought and other abiotic stresses.

CONCLUSIONS

Low-throughput screen is an effective method to find functional lncRNA for further study. LncRNAs were more active in abiotic stresses than PCG expression, especially temperature stress. LncRNA XLOC107738 may take a cis-regulatory role in response to environmental stimuli. The degree to which lncRNAs are constitutively expressed may impact expression patterns and functions on the individual gene level rather than in genome-wide aggregate.

DANCR: an emerging therapeutic target for cancer

The discovery of long non-coding RNAs (lncRNAs) revolutionized the current framework for understanding the molecular mechanisms of tumorigenesis and stimulated the search for targeted cancer treatments. Among lncRNAs, differentiation antagonizing non-protein-coding RNA (DANCR) is a newly identified oncogenic gene that is upregulated in diverse cancer types and has a critical role in cancer progression. Herein, we summarize current knowledge regarding DANCR regulatory functions related to cancer cell proliferation, invasion, metastasis, and chemo-resistance. We also synthesize the effects of DANCR on cancer stemness features, the epithelial-mesenchymal transition (EMT), and angiogenesis, which are essential for the progression of malignant cancer cells. Mechanically, the interaction between DANCR and its targets including microRNAs (miRNAs), mRNAs, and proteins are also elucidated. Finally, we propose DANCR-based therapeutic approaches to provide novel insights about cancer treatment.

Beyond classic editing: innovative CRISPR approaches for functional studies of long non-coding RNA

Long non-coding RNAs (lncRNAs) makeup a considerable part of the non-coding human genome and had been well-established as crucial players in an array of biological processes. In spite of their abundance and versatile roles, their functional characteristics remain largely undiscovered mainly due to the lack of suitable genetic manipulation tools. The emerging CRISPR/Cas9 technology has been widely adapted in several studies that aim to screen and identify novel lncRNAs as well as interrogate the functional properties of specific lncRNAs. However, the complexity of lncRNAs genes and the regulatory mechanisms that govern their transcription, as well as their unique functionality pose several limitations the utilization of classic CRISPR methods in lncRNAs functional studies. Here, we overview the unique characteristics of lncRNAs transcription and function and the suitability of the CRISPR toolbox for applications in functional characterization of lncRNAs. We discuss some of the novel variations to the classic CRISPR/Cas9 system that have been tailored and applied previously to study several aspects of lncRNAs functionality. Finally, we share perspectives on the potential applications of various CRISPR systems, including RNA-targeting, in the direct editing and manipulation of lncRNAs.

CeModule: an integrative framework for discovering regulatory patterns from genomic data in cancer

BACKGROUND

Non-coding RNAs (ncRNAs) are emerging as key regulators and play critical roles in a wide range of tumorigenesis. Recent studies have suggested that long non-coding RNAs (lncRNAs) could interact with microRNAs (miRNAs) and indirectly regulate miRNA targets through competing interactions. Therefore, uncovering the competing endogenous RNA (ceRNA) regulatory mechanism of lncRNAs, miRNAs and mRNAs in post-transcriptional level will aid in deciphering the underlying pathogenesis of human polygenic diseases and may unveil new diagnostic and therapeutic opportunities. However, the functional roles of vast majority of cancer specific ncRNAs and their combinational regulation patterns are still insufficiently understood.

RESULTS

Here we develop an integrative framework called CeModule to discover lncRNA, miRNA and mRNA-associated regulatory modules. We fully utilize the matched expression profiles of lncRNAs, miRNAs and mRNAs and establish a model based on joint orthogonality non-negative matrix factorization for identifying modules. Meanwhile, we impose the experimentally verified miRNA-lncRNA interactions, the validated miRNA-mRNA interactions and the weighted gene-gene network into this framework to improve the module accuracy through the network-based penalties. The sparse regularizations are also used to help this model obtain modular sparse solutions. Finally, an iterative multiplicative updating algorithm is adopted to solve the optimization problem.

CONCLUSIONS

We applied CeModule to two cancer datasets including ovarian cancer (OV) and uterine corpus endometrial carcinoma (UCEC) obtained from TCGA. The modular analysis indicated that the identified modules involving lncRNAs, miRNAs and mRNAs are significantly associated and functionally enriched in cancer-related biological processes and pathways, which may provide new insights into the complex regulatory mechanism of human diseases at the system level.

Probing the functions of long non-coding RNAs by exploiting the topology of global association and interaction network

Long non-coding RNAs (lncRNAs) are involved in many biological processes, such as immune response, development, differentiation and gene imprinting and are associated with diseases and cancers. But the functions of the vast majority of lncRNAs are still unknown. Predicting the biological functions of lncRNAs is one of the key challenges in the post-genomic era. In our work, We first build a global network including a lncRNA similarity network, a lncRNA-protein association network and a protein-protein interaction network according to the expressions and interactions, then extract the topological feature vectors of the global network. Using these features, we present an SVM-based machine learning approach, PLNRGO, to annotate human lncRNAs. In PLNRGO, we construct a training data set according to the proteins with GO annotations and train a binary classifier for each GO term. We assess the performance of PLNRGO on our manually annotated lncRNA benchmark and a protein-coding gene benchmark with known functional annotations. As a result, the performance of our method is significantly better than that of other state-of-the-art methods in terms of maximum F-measure and coverage.

State of the art technologies to explore long non-coding RNAs in cancer

Long non‐coding RNAs (lncRNAs) comprise a vast repertoire of RNAs playing a wide variety of crucial roles in tissue physiology in a cell‐specific manner. Despite being engaged in myriads of regulatory mechanisms, many lncRNAs have still remained to be assigned any functions. A constellation of experimental techniques including single‐molecule RNA in situ hybridization (sm‐RNA FISH), cross‐linking and immunoprecipitation (CLIP), RNA interference (RNAi), Clustered regularly interspaced short palindromic repeats (CRISPR) and so forth has been employed to shed light on lncRNA cellular localization, structure, interaction networks and functions. Here, we review these and other experimental approaches in common use for identification and characterization of lncRNAs, particularly those involved in different types of cancer, with focus on merits and demerits of each technique.

Methods to Study Long Noncoding RNA Biology in Cancer

Thousands of long noncoding RNAs (lncRNAs) have been discovered in recent years. The functions of lncRNAs range broadly from regulating chromatin structure and gene expression in the nucleus to controlling messenger RNA (mRNA) processing, mRNA posttranscriptional regulation, cellular signaling, and protein activity in the cytoplasm. Experimental and computational techniques have been developed to characterize lncRNAs in high-throughput scale, to study the lncRNA function in vitro and in vivo, to map lncRNA binding sites on the genome, and to capture lncRNA-protein interactions with the identification of lncRNA-binding partners, binding sites, and interaction determinants. In this chapter, we will discuss these technologies and their applications in decoding the functions of lncRNAs. Understanding these techniques including their advantages and disadvantages and developing them in the future will be essential to elaborate the roles of lncRNAs in cancer and other diseases.

oskar RNA plays multiple noncoding roles to support oogenesis and maintain integrity of the germline/soma distinction

The Drosophila oskar (osk) mRNA is unusual in that it has both coding and noncoding functions. As an mRNA, osk encodes a protein required for embryonic patterning and germ cell formation. Independent of that function, the absence of osk mRNA disrupts formation of the karyosome and blocks progression through oogenesis. Here we show that loss of osk mRNA also affects the distribution of regulatory proteins, relaxing their association with large RNPs within the germline, and allowing them to accumulate in the somatic follicle cells. This and other noncoding functions of the osk mRNA are mediated by multiple sequence elements with distinct roles. One role, provided by numerous binding sites in two distinct regions of the osk 3' UTR, is to sequester the translational regulator Bruno (Bru), which itself controls translation of osk mRNA. This defines a novel regulatory circuit, with Bru restricting the activity of osk, and osk in turn restricting the activity of Bru. Other functional elements, which do not bind Bru and are positioned close to the 3' end of the RNA, act in the oocyte and are essential. Despite the different roles played by the different types of elements contributing to RNA function, mutation of any leads to accumulation of the germline regulatory factors in the follicle cells.