Abstract

The discovery of non-coding RNAs (ncRNAs), and the subsequent elucidation of their functional roles, was largely delayed due to the misidentification of non-protein-coding parts of DNA as “junk DNA,” which forced ncRNAs into the shadows of their protein-coding counterparts. However, over the past decade, insight into the important regulatory roles of ncRNAs has led to rapid progress in their identification and characterization. Of the different types of ncRNAs, long non-coding RNAs (lncRNAs), has attracted considerable attention due to their mRNA-like structures and gene regulatory functions in plant stress responses. While RNA sequencing has been commonly used for mining lncRNAs, a lack of widespread conservation at the sequence level in addition to relatively low and highly tissue-specific expression patterns challenges high-throughput in silico identification approaches. The complex folding characteristics of lncRNA molecules also complicate target predictions, as the knowledge about the interaction interfaces between lncRNAs and potential targets is insufficient. Progress in characterizing lncRNAs and their targets from different species may hold the key to efficient identification of this class of ncRNAs from transcriptomic and potentially genomic resources. In wheat and barley, two of the most important crops, the knowledge about lncRNAs is very limited. However, recently published high-quality genomes of these crops are considered as promising resources for the identification of not only lncRNAs, but any class of molecules. Considering the increasing demand for food, these resources should be used efficiently to discover molecular mechanisms lying behind development and a/biotic stress responses. As our understanding of lncRNAs expands, interactions among ncRNA classes, as well as interactions with the coding sequences, will likely define novel functional networks that may be modulated for crop improvement.

Highlights

  • Since the realization of regulatory information contained within the non-proteincoding parts of DNA, efforts to identify non-coding RNA molecules have greatly accelerated

  • This study reported that 3% of the identified Kiziltan long non-coding RNAs (lncRNAs), 6% of the identified TR39477 lncRNAs, and 4% of the durum wheat lncRNAs were differentially expressed in response to drought and called as ‘drought-responsive’ lncRNAs, with most only expressed under drought (Cagirici et al, 2017)

  • Drawbacks that has been encountered in currentlyused lncRNA identification strategies should be overcome for a better understanding of mechanisms lying behind important traits to be used for developing more resistant and more yielding cultivars

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Summary

INTRODUCTION

Since the realization of regulatory information contained within the non-proteincoding parts of DNA, efforts to identify non-coding RNA molecules have greatly accelerated. Advances in RNA sequencing technology have contributed to this acceleration and the discovery of non-coding RNAs, including lncRNAs, which elucidated their structures and functions. As our understanding of the regulatory roles of lncRNAs has improved, the importance of these non-coding molecules has. A step further to understand both coding and non-coding elements was taken recently for wheat and barley: highquality reference sequences have been published (Mascher et al, 2017; IWGSC, 2018). Having a reference genome in hand improved the accuracy of the analyzes to find the origins of favorable traits and regulatory mechanisms that control the expression of the genes responsible for those traits. Wheat and barley reference sequences have opened a new era in the field of multiomics research, allowing more accuracy and robustness toward the lightening of the undiscovered mechanisms within these important crops

BIOGENESIS OF lncRNAs
INFLUENCE OF RNA SEQUENCING TECHNOLOGIES ON THE DISCOVERY OF lncRNAs
Protein relocalization
Uncharacterized Chromotin modifications
DRAWBACKS IN lncRNA IDENTIFICATION AND TARGET PREDICTION
Findings
FUTURE PERSPECTIVES AND CONCLUSION
Full Text
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