LncRNA-mediated ceRNA networks provide novel potential biomarkers for peanut drought tolerance

Elucidating the regulatory role of long non-coding RNAs in drought stress response during seed germination in leaf mustard

Leaf mustard (Brassica juncea L. Czern & Coss), an important vegetable crop, experiences pronounced adversity due to seasonal drought stress, particularly at the seed germination stage. Although there is partial comprehension of drought-responsive genes, the role of long non-coding RNAs (lncRNAs) in adjusting mustard's drought stress response is largely unexplored. In this study, we showed that the drought-tolerant cultivar 'Weiliang' manifested a markedly lower base water potential (-1.073 MPa vs -0.437 MPa) and higher germination percentage (41.2% vs 0%) than the drought-susceptible cultivar 'Shuidong' under drought conditions. High throughput RNA sequencing techniques revealed a significant repertoire of lncRNAs from both cultivars during germination under drought stress, resulting in the identification of 2,087 differentially expressed lncRNAs (DELs) and their correspondingly linked 12,433 target genes. It was noted that 84 genes targeted by DEL exhibited enrichment in the photosynthesis pathway. Gene network construction showed that MSTRG.150397, a regulatory lncRNA, was inferred to potentially modulate key photosynthetic genes (Psb27, PetC, PetH, and PsbW), whilst MSTRG.107159 was indicated as an inhibitory regulator of six drought-responsive PIP genes. Further, weighted gene co-expression network analysis (WGCNA) corroborated the involvement of light intensity and stress response genes targeted by the identified DELs. The precision and regulatory impact of lncRNA were verified through qPCR. This study extends our knowledge of the regulatory mechanisms governing drought stress responses in mustard, which will help strategies to augment drought tolerance in this crop.

Current perspectives of lncRNAs in abiotic and biotic stress tolerance in plants

Abiotic/biotic stresses pose a major threat to agriculture and food security by impacting plant growth, productivity and quality. The discovery of extensive transcription of large RNA transcripts that do not code for proteins, termed long non-coding RNAs (lncRNAs) with sizes larger than 200 nucleotides in length, provides an important new perspective on the centrality of RNA in gene regulation. In plants, lncRNAs are widespread and fulfill multiple biological functions in stress response. In this paper, the research advances on the biological function of lncRNA in plant stress response were summarized, like as Natural Antisense Transcripts (NATs), Competing Endogenous RNAs (ceRNAs) and Chromatin Modification etc. And in plants, lncRNAs act as a key regulatory hub of several phytohormone pathways, integrating abscisic acid (ABA), jasmonate (JA), salicylic acid (SA) and redox signaling in response to many abiotic/biotic stresses. Moreover, conserved sequence motifs and structural motifs enriched within stress-responsive lncRNAs may also be responsible for the stress-responsive functions of lncRNAs, it will provide a new focus and strategy for lncRNA research. Taken together, we highlight the unique role of lncRNAs in integrating plant response to adverse environmental conditions with different aspects of plant growth and development. We envisage that an improved understanding of the mechanisms by which lncRNAs regulate plant stress response may further promote the development of unconventional approaches for breeding stress-resistant crops.

Identification of LncRNAs and Functional Analysis of ceRNA Related to Fatty Acid Synthesis during Flax Seed Development

Flax is a flowering plant cultivated for its oil and contains various unsaturated fatty acids. Linseed oil is known as the "deep-sea fish oil" of plants, and is beneficial to brain and blood lipids, among other positive effects. Long non-coding RNAs (lncRNAs) play an important role in plant growth and development. There are not many studies assessing how lncRNAs are related to the fatty acid synthesis of flax. The relative oil contents of the seeds of the variety Heiya NO.14 (for fiber) and the variety Macbeth (for oil) were determined at 5 day, 10 day, 20 day, and 30 day after flowering. We found that 10-20 day is an important period for ALA accumulation in the Macbeth variety. The strand-specific transcriptome data were analyzed at these four time points, and a series of lncRNAs related to flax seed development were screened. A competing endogenous RNA (ceRNA) network was constructed and the accuracy of the network was verified using qRT-PCR. MSTRG.20631.1 could act with miR156 on the same target, squamosa promoter-binding-like protein (SPL), to influence fatty acid biosynthesis through a gluconeogenesis-related pathway during flax seed development. This study provides a theoretical basis for future studies assessing the potential functions of lncRNAs during seed development.

ASLncR: a novel computational tool for prediction of abiotic stress-responsive long non-coding RNAs in plants

Abiotic stresses are detrimental to plant growth and development and have a major negative impact on crop yields. A growing body of evidence indicates that a large number of long non-coding RNAs (lncRNAs) are key to many abiotic stress responses. Thus, identifying abiotic stress-responsive lncRNAs is essential in crop breeding programs in order to develop crop cultivars resistant to abiotic stresses. In this study, we have developed the first machine learning-based computational model for predicting abiotic stress-responsive lncRNAs. The lncRNA sequences which were responsive and non-responsive to abiotic stresses served as the two classes of the dataset for binary classification using the machine learning algorithms. The training dataset was created using 263 stress-responsive and 263 non-stress-responsive sequences, whereas the independent test set consists of 101 sequences from both classes. As the machine learning model can adopt only the numeric data, the Kmer features ranging from sizes 1 to 6 were utilized to represent lncRNAs in numeric form. To select important features, four different feature selection strategies were utilized. Among the seven learning algorithms, the support vector machine (SVM) achieved the highest cross-validation accuracy with the selected feature sets. The observed 5-fold cross-validation accuracy, AU-ROC, and AU-PRC were found to be 68.84, 72.78, and 75.86%, respectively. Furthermore, the robustness of the developed model (SVM with the selected feature) was evaluated using an independent test dataset, where the overall accuracy, AU-ROC, and AU-PRC were found to be 76.23, 87.71, and 88.49%, respectively. The developed computational approach was also implemented in an online prediction tool ASLncR accessible at https://iasri-sg.icar.gov.in/aslncr/ . The proposed computational model and the developed prediction tool are believed to supplement the existing effort for the identification of abiotic stress-responsive lncRNAs in plants.

Whole-transcriptome analyses identify key differentially expressed mRNAs, lncRNAs, and miRNAs associated with male sterility in watermelon

Male sterility is a valuable trait for watermelon breeding, as watermelon hybrids exhibit obvious heterosis. However, the underlying regulatory mechanism is still largely unknown, especially regarding the related non-coding genes. In the present study, approximately 1035 differentially expressed genes (DEGs), as well as 80 DE-lncRNAs and 10 DE-miRNAs, were identified, with the overwhelming majority down-regulated in male-sterile floral buds. Enrichment analyses revealed that the general phenylpropanoid pathway as well as its related metabolisms was predicted to be altered in a mutant compared to its fertile progenitor. Meanwhile, the conserved genetic pathway DYT1-TDF1-AMS-MS188-MS1, as well as the causal gene ClAMT1 for the male-sterile mutant Se18, was substantially disrupted during male reproductive development. In addition, some targets of the key regulators AMS and MS188 in tapetum development were also down-regulated at a transcriptional level, such as ABCG26 (Cla004479), ACOS5 (Cla022956), CYP703A2 (Cla021151), PKSA (Cla021099), and TKPR1 (Cla002563). Considering lncRNAs may act as functional endogenous target mimics of miRNAs, competitive endogenous RNA networks were subsequently constructed, with the most complex one containing three DE-miRNAs, two DE-lncRNAs, and 21 DEGs. Collectively, these findings not only contribute to a better understanding of genetic regulatory networks underlying male sterility in watermelon, but also provide valuable candidates for future research.

Long Non-Coding RNAs of Plants in Response to Abiotic Stresses and Their Regulating Roles in Promoting Environmental Adaption

Abiotic stresses triggered by climate change and human activity cause substantial agricultural and environmental problems which hamper plant growth. Plants have evolved sophisticated mechanisms in response to abiotic stresses, such as stress perception, epigenetic modification, and regulation of transcription and translation. Over the past decade, a large body of literature has revealed the various regulatory roles of long non-coding RNAs (lncRNAs) in the plant response to abiotic stresses and their irreplaceable functions in environmental adaptation. LncRNAs are recognized as a class of ncRNAs that are longer than 200 nucleotides, influencing a variety of biological processes. In this review, we mainly focused on the recent progress of plant lncRNAs, outlining their features, evolution, and functions of plant lncRNAs in response to drought, low or high temperature, salt, and heavy metal stress. The approaches to characterize the function of lncRNAs and the mechanisms of how they regulate plant responses to abiotic stresses were further reviewed. Moreover, we discuss the accumulating discoveries regarding the biological functions of lncRNAs on plant stress memory as well. The present review provides updated information and directions for us to characterize the potential functions of lncRNAs in abiotic stresses in the future.