Small RNA technology for plant abiotic stress tolerance

CHAPTER

Small RNA technology for plant abiotic stress tolerance

23

Binod Kumar Mahtoa,b, Amit Katiyarc, Sangram K. Lenkaa, Kailash C. Bansala a

TERI-Deakin NanoBiotechnology Centre, The Energy and Resources Institute, New Delhi, India b TERI School of Advanced Studies, New Delhi, India c ICMR-AIIMS Computational Genomics Centre, Division of I.S.R.M., Indian Council of Medical Research, New Delhi, India

­Introduction Various types of environmental stresses prevent plants from accomplishing their complete genetic potential and largely influence plant development and crop productivity. Abiotic stresses are becoming a major limitation to food security due to the constant changes of climate and worsening environment caused by human activity. For instance, salt stress has become a severe environmental issue because 7% of the total land, 20% of the arable land, and 50% of irrigated land in the world face salinity problems [1]. To adapt to such stresses, plants respond by triggering physiological, molecular, and cellular changes. With the advancement of molecular biology, many approaches like precision breeding and genetic engineering technology, are getting increased attention for developing climate-resilient crops for improved performance under a range of abiotic stresses. Likewise, genomic approaches, including structural genomics, comparative genomics, and functional genomics, are being used to unravel gene functions and to search for novel genes for use in developing superior stress-tolerant crops. In recent decades, small RNAs (sRNAs) technology has evolved as one of the most advanced approaches for crop improvement. Many sRNAs (18–30 nt), identified by using high-throughput sequencing and bioinformatics tools, are involved in sequence-specific gene regulation by small non-coding RNAs (ncRNAs) such as small interfering RNA (siRNA) and microRNA (miRNA) [2]. In earnest, research on sRNAs began in the late 1980s and early 1990s. Napoli et al. [3] and van der Krol et al. [4] demonstrated enhancement of anthocyanin pigment content in petunia flowers by overexpressing the CHS (chalcone synthase) gene, but unpredictably it resulted in the generation of white flowers due to co-­ suppression or silencing of the CHS in transgenic plants. Lindbo et al. [5] generated Tobacco Etch Virus (TEV)-resistant tobacco transgenic plants by overexpressing Plant Small RNA. https://doi.org/10.1016/B978-0-12-817112-7.00023-7 © 2020 Elsevier Inc. All rights reserved.

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TEV coat protein. Subsequent studies showed that, even though the TEV coat protein transgene was transcribed, the transcript was immediately degraded in the cytoplasm. It was speculated that the degraded RNA molecules perhaps lead to the suppression of coat protein production thus inhibiting the assembly of viral particles (because of the non-production of the coat protein). As a consequence, this rendered the plants free from further TEV infection. In Neurospora crassa, overexpressed carotenogenic al-3 (albino-3) and al-1 (albino-1) genes also were found to silence gene at the post-transcriptional level, a phenomenon called quelling [6]. In 1996, gene silencing by RNA interference was first recognized in plants by Baulcombe [7], and it was termed post-transcriptional gene silencing (PTGS). It was suggested that PTGS is an outcome of the mechanism that suppresses RNA accumulation in a sequence-specific manner. Subsequently, Waterhouse et al. [7a], by incorporating the viral protease (Pro) gene against potato virus Y (PVY) infestation, demonstrated that RNAi is highly effective in controlling the viral disease in plants. Fire et  al. [8], working on Caenorhabditis elegans, contributed immensely toward understanding the mechanism involved in RNAi-mediated gene silencing, for which they were awarded the Nobel Prize in 2006. Thereafter, this technology has grown considerably and is now being widely used as a major tool for plant improvement and functional genomics. We will briefly discuss the application of sRNA technology for enhancing crop abiotic stress tolerance.

­Application of sRNA technology in plants RNA interference (RNAi) is a powerful technique to analyze gene expression and function for agricultural crops for agronomic benefits. During the earlier decade, RNAi has been rapidly adopted as a general method for controlling/regulating expression of genes at a post-transcriptional level in various model and non-model plant and animal systems. Two major categories of RNAi mechanisms involve siRNAs and miRNAs, which are implicated in transcriptional and PTGS [2]. This technology has been successfully employed for the improvement of plants, including enhancement of nutritional value/secondary metabolite, shelf-life improvement, and increased tolerance to different abiotic and biotic stresses in many plant species [9]. Plants have two major endogenous siRNA-mediated regulations, heterochromatic siRNAs (hc-siRNAs) and trans-acting siRNAs (ta-siRNAs). To control or enhance the growth and development of plants against abiotic and biotic stresses, siRNA can be introduced exogenously into the plants [10]. One of the prominent technologies that is meeting considerable success and increased media attention is the sprayable double‐stranded RNA (dsRNA)‐mediated crop protection against pathogens, nematodes, arthropods, and pests [11]. Similarly, plant virus-specific designer dsRNA spray technology was also proven to be an effective and sustainable crop protection tool, which had undergone commercial trials [12, 13]. Therefore, a similar strategy could be examined for enhancing abiotic stress tolerance in plants, especially by targeting genes implicated as negative regulators of abiotic stresses.

The biology of miRNAs in plants

­General mechanism of RNAi RNAi mechanism is induced by dsRNA or hairpin-structured RNA (hpRNA), involving many factors including Dicer or Dicer-like (DCL) protein [14, 15] and Argonaute (AGO) [16, 17] family proteins. In the sRNAs pathway, dsRNA or hpRNA is processed by a Dicer or DCL protein into 20–24 nucleotide (nt) sRNA (siRNA/miRNA) duplexes with 2-nt 3′ overhang at both the flanking ends. One of the strands of siRNA duplex is integrated into an AGO and develops an RNA-induced silencing complex (RISC) [18], which in a site-specific manner enables single-stranded siRNA to anneal to the target RNA, thus subjecting it to degradation, resulting in the downregulation or knockdown of the protein expression [19, 20] (Fig. 1).

­The biology of miRNAs in plants MicroRNAs (miRNAs) are a class of small, non-coding RNAs of approximately 21–24 nucleotides in size that act predominantly in PTGS and, in some cases, transcriptional gene silencing (TGS) to modulate the expression of target gene in eukaryotes. The miRNAs from both plant and animal are varied in sequence, abundance, expression pattern, and genomic position [21–24]. The biogenesis of plant miRNAs (Fig. 2) derives from the depiction of Arabidopsis mutants showing deficient miRNA biogenesis. In plants, genes encoding miRNAs (abbreviated miR genes) are commonly transcribed by RNA polymerase II (Pol II) through their MIR promoters to

FIG. 1 Strategies for sRNAs-mediated regulation and development of abiotic stress tolerance in plants.

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CHAPTER 23  Small RNA technology for plant abiotic stress tolerance

siRNA pathway dsRNA/ hpRNA Intron/ spacer

Intron/ spacer miRNA precursor

Drosha

Dicer/ DCL protein

Dicer/ DCL protein

AGO AGO

RISC

AGO

AGO

RISC complex

RISC

Single stranded antisense RNA

RISC

miRNA duplex

miRNP

Cytoplasm

siRNA duplex

Nucleus

OR

miRNA pathway

miRNP

RISC complex

AGO

AGO

miRNP

Sense RNA or passenger RNA

Target mRNA

AGO

RISC

Target mRNA mRNA fragment mRNA fragment

FIG. 2 Schematic representation of RNAi (siRNA and miRNA) mechanisms against abiotic stresses. Dicer or dicer-like protein cleaves dsRNA in the form of siRNA or pre-miRNA into 20–24-nt dsRNA duplex, referred to as siRNA or miRNA duplex, to initiate RNAi mechanism. siRNAs have exact complementarity with the target mRNAs and results in the mRNA fragment. Whereas miRNAs with imperfect complementarity to the target mRNAs results in translation repression or deadenylation and mRNA degradation.

yield a primary transcript or pri-miRNA [25–29]. The pri-miRNAs transcripts are significantly longer (>1 kb long), enclosing introns (one or more), and is capped at the 5′ end via polyadenylation [25, 26, 28–30]. The long pri-miRNAs are expected to adopt hairpin or imperfect stem-loop secondary structures that may contain the miRNA in one arm of the stem-loop precursor [24, 27]. The stem-loop structure of the pri-miRNA is processed by DCL RNase III enzymes DCL1 (enclosing two dsRNA-binding domains), resulting in 21–24-nt longer miRNA/miRNA* duplex. The processing of pri-miRNAs to precursor miRNAs (pre-miRNAs) by Dicer-like 1 (DCL1) needs two additional dsRNA-binding cofactors, that is, HYPONASTIC LEAVES1 (HYL1) and SERRATE (SE) in Arabidopsis [31, 32]. In plants, Hua Enhancer 1 (HEN1)-mediated methylation of miRNAs adds methyl group to both strands of the miRNA/miRNA* duplex. The HASTY (HST) homolog of exportin-5 mediates the nuclear export of miRNAs to the cytoplasm. In the cytosol, miRNA is loaded onto the Argonaute 1 (AGO1)-RISC to catalyze PTGS [33, 34]. The passenger strand (miRNA*) is degraded, resulting in the formation of RISC with one guide

­siRNA-mediated abiotic stress tolerance in plants

strand (mature miRNA). The miRNAs guide microRNA-induced silencing complex (miRISC) to precisely spot messenger RNA (mRNA) and negatively modulate the transcript levels of their target genes by PTGS mechanisms of translational repression or mRNA cleavage and hence play a significant role in development, diseases, and response to stress. A high complementary base pairing between the seed region (2nd and 8th base) at the 5′-end of the miRNA and the binding site of the mRNA is critical for the function of the miRNA [35]. The seed region of the miRNA is conserved across species and within miRNA families.

­siRNA-mediated abiotic stress tolerance in plants Abiotic stresses (drought, salt, cold, heat, heavy metals, and nutrient deficiency) are some of the major obstacles during the entire life cycle of a plant. Tolerance to these stress conditions have been enhanced via sRNA technology (siRNA and miRNA) by targeting gene expression associated with signaling and metabolic biosynthesis pathway [36–38]. siRNA controls gene expression at the PTGS level via targeting the sequence-specific mRNA degradation (Table 1). Drought stress tolerance: Drought is one of the most important abiotic stresses, which significantly influences plant growth and development as well as yield. Li et al. [39] investigated the abiotic stress-associated gene, the receptor of activated C-kinase 1 (RACK1), encoding a well-conserved scaffold protein, involved in growth and development of rice. Downregulation of this gene was achieved in rice through RNAi resulting in the development of drought-tolerant rice plant [39]. RNAi tool was successfully employed in rice plant for the inhibition of Squalene synthase (SQS) enzyme, and the resultant plants showed improved drought tolerance at the time of vegetative as well as reproductive phase of plant growth. These plants also showed delayed wilting with increased water recovery, lower stomatal conductance, and decrease in water losses during plant development [40]. Recently, Huang et al. [36] characterized OsDRAP1 (DREB2-like transcription factor) gene using RNAi in rice plant, which affected drought tolerance by maintaining redox homeostasis and water balance under water deficit conditions, and the transgenic rice plants exhibited significantly increased drought tolerance with significant negative effects on development and production of yield. Hu et al. [41] generated improved rice transgenic plants intended to drought stress by RNAi-mediated silencing of OsGRXS17 (Glutaredoxins), and the transgenic plants also revealed the modulation of ROS accumulation and stomatal closure. Salt stress tolerance: Like drought, salinity stress is also one of the leading abiotic threats to the plants. Yao et al. [68] identified sRNAs in wheat and proved the differential downregulation of three siRNAs (siRNA 007927_0100_2975.1, siRNA 005047_0654_1904.1, and siRNA 002061_0636_3054.1) under different abiotic stress situations including salinity, and it was observed that the ­corresponding siRNAs might be helpful for better survival under these conditions. Xu et al. [42] demonstrated the involvement of 24-nt small interfering RNAs in regulating AtMYB74

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Plant species

siRNA/miRNA

Target gene

Reference

RACK1 SQS OsDRAP1 OsGRXS17

Receptor of activated C-kinase 1 Squalene synthase (SQS) enzyme DREB2-like transcription factor Monothiol glutaredoxin-S17

[39] [40] [36] [41]

AtMYB74 OsCKX2

Transcription factor MYB74 Cytokinin dehydrogenase 2

[42] [43]

TAS3a-5′D6 (+) siARF1, siARF3

Auxin response factor (ARF) ARF

[44] [45]

Ethylene signaling F-box proteins Auxin receptor genes ARF NAC gene DREB transcription factor DREB3 transcription factor

[46] [47] [48] [49] [50] [51] [52]

siRNA-mediated abiotic stress tolerance Drought stress tolerance Rice (Oryza sativa)

Salt stress tolerance Arabidopsis thaliana Rice Cold stress tolerance Wheat Cassava

miRNA-mediated abiotic stress tolerance Drought stress tolerance Arabidopsis thaliana Rice (Oryza sativa)

Chick Pea Barley

miR164 Gma-miR394a miR393 miR167 miR164 miR408 hvumiRX

CHAPTER 23  Small RNA technology for plant abiotic stress tolerance

Table 1  A summary of small RNAs, siRNA-, and miRNA-mediated improvement in abiotic stress tolerance in plants.

Salt stress tolerance Rice (Oryza sativa)

[53] [54] [53] [53] [54] [55] [55] [55] [55] [56, 57] [56] [58] [57] [57] [59] [57] [57] [60] [61] [62]

Rice Tomato Wheat (Triticum aestivum) Prunus persica Poncirus trifoliata

miR156 miR171 miR319 miR393 miR396b

[52] [63] [64] [65] [66]

Arabidopsis thaliana

miR408

OsSPL3 - SBP-box gene family member Multiple target genes predicted Multiple target genes predicted TIR1, AFB2, AFB3 1-aminocyclopropane-1-carboxylic acid oxidase (ACO) CSD1, CSD2, GST-U25, CCS1 and SAP12

Wheat (Triticum aestivum)

Arabidopsis thaliana

Maize (Zea mays) Soybean Cold stress tolerance

[67]

527

ARF NAC family gene MYB transcription factor F-box protein Peptide chain release factor ARF ARF ATP-dependent RNA helicase Peptide chain release factor Squamosa promoter-binding protein like NAC family gene ARF Argonaute 1 TCP transcription factor F-box genes encoding auxin receptors F-box protein GRL transcription factor Squamosa promoter-binding protein like Nuclear transcription factor Y AP2/EREBP-type transcription factor

­siRNA-mediated abiotic stress tolerance in plants

miR160 miR164 miR159 miR394 miR408 miR160 miR167 miR399 miR408 miR156, miR166 miR164 miR167 miR168 miR319 miR393 miR394 miR396 mir166 miR169 miR172a

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CHAPTER 23  Small RNA technology for plant abiotic stress tolerance

transcription factor via RdDM (RNA-directed DNA methylation) in Arabidopsis thaliana in response to salinity condition. Recently, Joshi et al. [43] reported downregulation of rice floral meristem-specific OsCKX2 (cytokinin oxidase) using siRNAbased approach, and the developed rice transgenic plants showed enhanced panicle branching and maintained grain filling under salinity stress conditions. Cold stress tolerance: Low temperature stress is one of the serious abiotic stress factors, adversely affecting almost all aspects of plant development and their productivity worldwide [69, 70]. Tang et al. [44] demonstrated that, in the case of wheat plants, the siRNA TAS3a-5′D6 (+) may be involved in plant acclimatization to cold stress by controlling and cleavage of auxin response factor (ARF) in the auxin signaling pathway. Xia et al. [45] validated three TAS3 genes under cold stress condition in Manihot esculenta (cassava) plants, which targeted the ARF genes, for example, ARF3 and ARF4, both targeted by siARF1, whereas siARF3 targeted the ARF3 gene. These results suggested that the expression of siRNA-mediated temperature response may be related to auxin signaling in plants.

­MicroRNA-mediated abiotic stress tolerance in plants The plant adaptation to abiotic stresses are accomplished through the regulation of miRNA gene (MIR) expression signifying specific response pathways. Stressregulated genes are well acknowledged to be regulated by miRNAs. MicroRNAs play a crucial role in post-transcriptional regulation of gene expression and hence play an important role in growth, nutrient acquisition, and tolerance to many environmental stresses including abiotic and biotic [71]. Several studies have also unraveled their significant role in the post-transcriptional regulation of genes, essential for plant responses to different stresses [72]. Therefore, identification of miRNA-mRNA regulatory modules is essential to highlight the important biological functions of miRNAs. Computational approaches are used widely as a speedy, correct, and affordable method to identify miRNAs. The miRNA prediction using bioinformatic approaches is feasible due to the evolutionarily conserved nature of miRNA and unique secondary structure of pri-miRNAs in plant species [73]. Bioinformatics-based methods have been relatively suitable for miRNA screening in several plant species such as Arabidopsis [74], rice [75], corn [76], cotton [71], mustard [77], wheat [78], Medicago truncatula [79], soybean [80], potato [81], tomato [82], citrus [83], switch grass [84], sugarcane [85], and sorghum [86]. The homology-based tools for the identification of potential miRNAs and their target genes are listed in Table 2. The recent development of high-throughput “omics” technologies has brought a new era by permitting the sequencing of millions of sRNA molecules. Over the last few decades, several stress‐specific miRNAs have been identified in model and non-model plants under diverse abiotic stress conditions. Drought stress tolerance: Drought stress is one of the most predominant abiotic stresses, which adversely affect crop growth, quality, and yield [110]. The consequences of drought stress results in the closure of stomata, suppression of photosynthesis,

­MicroRNA-mediated abiotic stress tolerance in plants

Table 2  Widely used tools and databases for miRNAs and their target prediction, public repositories of abiotic stress-related genes and miRNAs, and network-based biomarker and annotation tools. Abiotic stress-related databases Name

Description

Web

References

CSTD

Crops stress-tolerance database Plant stress protein database miRNA molecular regulation in plant response to abiotic stress Stress responsive transcription factor database Abiotic stress responsive quantitative trait loci (QTLs) in rice Plant stress gene database

http://pcsb.ahau.edu. cn:8080/CSTDB http://www.bioclues. org/pspdb/ http://pcsb.ahau.edu. cn:8080/PASmiR/

[87]

PSPDB PASmiR

STIFDB

QlicRice

PSGD

[88] [89]

http://caps.ncbs.res.in/ stifdb2/

[90]

http://nabg.iasri.res. in:8080/qlic-rice/

[91]

http://ccbb.jnu.ac.in/ stressgenes/

[92]

http://pmirexat.nabi. res.in/ http://www.mirbase. org/ http://rfam.xfam.org/

[93]

miRNA databases PmiRExAt miRBase Rfam

miRNEST

PMRD

Plant miRNA expression atlas database Primary microRNA sequence repository A resource for predicted miR targets and expression Integrative collection of animal, plant and virus microRNA data Plant microRNA database

http://rhesus.amu.edu. pl/mirnest/copy/home. php http://bioinformatics. cau.edu.cn/PMRD/

[94] [95]

[96]

[97]

miRNA prediction tools miRCat

Predicts miRs from HTS data without requiring the precursor sequence

triplet-SVM

miRFinder

Computational pre-miR prediction tool

http://srna-workbench. cmp.uea.ac.uk/ mircat-2/ http://bioinfo. au.tsinghua.edu.cn/ mirnasvm/ http://www. bioinformatics.org/ mirfinder/

[98]

[99]

[100]

Continued

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Table 2  Widely used tools and databases for miRNAs and their target prediction, public repositories of abiotic stress-related genes and miRNAs, and network-based biomarker and annotation tools—cont'd Abiotic stress-related databases Name

Description

Web

References

http://plantgrn.noble. org/psRNATarget/ http://omicslab. genetics.ac.cn/ psMimic/ http://tarhunter. genetics.ac.cn/

[101]

miRNA target prediction tools psRNATarget psMimic

TarHunter

miRTarBase

psRobot

PAREsnip

Plant small RNA target analysis server MicroRNA target mimics prediction in plants Tool for predicting conserved microRNA targets and target mimics in plants Experimentally validated microRNA-target interactions Plant small RNA analysis toolbox Finds target of sRNA using degradome data

[101a]

[102]

http://miRTarBase.mbc. nctu.edu.tw/

[103]

http://omicslab. genetics.ac.cn/ psRobot/ http://srna-workbench. cmp.uea.ac.uk/ paresnip/

[104]

[105]

Network/Enrichment tools OmicsNet NetworkAnalyst DAVID BiNGO

Network analysis and visualization tool Network analysis and visualization tool Functional enrichment tool Functional enrichment tool

http://www.omicsnet. ca/ http://www. networkanalyst.ca https://david.ncifcrf. gov/conversion.jsp https://www.psb.ugent. be/cbd/papers/BiNGO/ Home.html

[106] [107] [108] [109]

enhancement of respiration, and reduced plant growth and crop production [111]. Many recent studies have revealed that drought stress can decrease yields by 50%. Genome-wide analysis of miRNAome in Brassica juncea revealed seven conserved miRNAs (miR828_1, miR169_3, miR168_1, miR390_1, miR172_2, miR394_1, and miR395_2) in response to various abiotic stresses including drought [112]. This study also identified six novel miRNAs (Bju-N5, Bju-N30, Bju-N31, Bju-N29, Bju-N21, and Bju-N35) in response to different abiotic stresses; two of these, Bju-N29 and Bju-N21, showed upregulation in drought stress [112]. The overexpression of osa-miR394 and miR319 showed increased drought tolerance in

­MicroRNA-mediated abiotic stress tolerance in plants

transgenic creeping bentgrass and Arabidopsis [47, 113]. Overexpression of droughtinducible miRNAs—miR164, miR394, miR396, miR408, and miR2118—in various plants such as rice, Arabidopsis, Chickpea, etc. enhanced drought stress tolerance [50, 114, 115]. High-throughput analysis of sRNAs in sorghum showed miRNA response to abiotic stress in a genotype-dependent manner that may contribute, at least in part, to the differential drought-resistant genotype of sorghum [116]. This study showed that the sorghum plants contain eight conserved miRNAs (miR160a, miR169d-l, miR396b-c, miR396d-e, miR529, miR2118e, miR2275, and miR5385). Likewise, Zhang et al. [117] investigated tissue-specific miRNAs expression analyses of miR2118c, miR827, and miR5337a, and showed upregulation and downregulation of miR3980, miR1425, and miR2090 in response to drought stress in shoots and exhibited drought adaption of rice plants. Salt stress tolerance: Salinity stress retards plant development and yield in plants. So, the functional characterizations of sRNAs using high-throughput sequencing of important plants are necessary for the plant improvement. Genome-wide miRNA analysis of Brassica juncea plants revealed plant responses to salt and other stresses [112]. Among these miRNAs, miR395_2, miR390_1, miR172_2, Bju-N29, and Bju-N21 showed differential expressions under salt stress conditions [112]. In Arabidopsis, the overexpression of mTIR1 (miR393-resistant TIR1 gene) resulted in higher germination rate, reduction in water loss, stable chlorophyll content, and improved salt tolerance [59]. The overexpression of Oryza sativa miR528 (a monocotspecific conserved miRNA) in transgenic Agrostis stolonifera plant confirmed the improved salt tolerance under saline environment and also showed increased tiller number and shortened internodes [117a]. Li et al. [118] demonstrated that the overexpression of gma-miR172 in A. thaliana plants showed tolerance to salinity condition with increased rate of germination, longer root and greening cotyledon, and also offered hypersensitivity to abscisic acid (ABA) during growth phase (germination and post-germination). Similarly, Pan et al. [62] also suggested the significance of miR172a via targeting or degrading SSAC1 (AP2/EREBP-type transcription factor) gene involved in protein inhibition of thiamine biosynthesis pathway gene THI1 (encodes a positive regulator of salt tolerance) in soybean plant and showed enhanced tolerance to salt stress in soybean. Cold stress tolerance: Like drought and salt stresses, cold stress is also an essential abiotic stress factor affecting plant production. The availability of high-quality genome sequence information facilitates tolerance of transgenic plants against cold and other abiotic stresses. Jeong et al. [119] identified the roles of miR319, miR812q, miR167, and miR1425 miRNAs in the response to cold stress. Another study demonstrated that the overexpression of miR319 in rice plants showed enhanced tolerance to cold after chilling acclimation and also played an important role in leaf morphogenesis [120]. Zhang et al. [66] demonstrated that mir396b of trifoliate orange (Poncirus trifoliate or Citrus trifoliate) plant positively regulates cold tolerance by regulating the ACC-oxidase gene. In a recent study, overexpression of OsmiR156 (rice miRNA156) revealed increased cold tolerance in Arabidopsis, rice, and pine by targeting OsSPL3 under cold conditions [52]. Likewise, Yang et al. [121] ­investigated

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the miRNA (ScmiR393) role in sugarcane by overexpressing it in Arabidopsis, and the overexpressed ScmiR393 A. thaliana plants showed improved growth as well as enhanced cold tolerance under the cold stress environment. In addition, transcriptomic analysis confirmed that the overexpression of ScmiR393 repressed the auxin signaling pathway by targeting TIR1 [121]. High-throughput sequence analysis of cold–resistant eggplant Solanum aculeatissimum [122] and Brassica rapa revealed the role of cold stress-responsive microRNAs (miR166e, miR319, and Bra-novelmiR3936-5p) in cold stress [123]. The expression patterns of conserved miRNA families in response to the same abiotic stresses among different cultivars or species suggest a species/genotype-specific response of miRNA. Furthermore, species/genotype-specific expression patterns of the identified miRNA targets could also be investigated by transcriptome-based gene profiling to find novel understandings into plant growth, development, and stress responses [124, 125]. For instance, comparative analysis of the drought‐responsive transcriptome in Indica rice genotypes with contrasting drought tolerance revealed significant upregulation of α‐linolenic acid metabolic pathway in rice landrace N22 under drought, which seems to be in decent covenant with high-drought tolerance of this genotype [126]. Genetic targets of α‐linolenic pathway and its precursors could be regulated by miRNAs, as there are 71 novel miRNAs that are differentially expressed by drought stress in this rice genotype [127]. Therefore, it would be interesting to study the species/genotype-specific differential regulation of miRNAs and their genetic targets across the contrasting stress-tolerant genotypes in rice and other crops. Cross-talk between miRNAs and genes linked with various abiotic pressures such as salt, drought, heat, and cadmium tolerance have been observed in sunflower, suggesting a critical role of miR172 and miR403 in epigenetic responses to stress [128]. Mining of QTLs associated with abiotic stress-responsive miRNAs of plants is another important approach to predict molecular markers that can be used to genetically improve agronomically important crops through genetic engineering or marker‐ assisted selection (MAS) breeding [129]. The accessibility of whole genome data of model plants, databases of abiotic stress-related mRNAs/genes, and network-based tools facilitates genomics‐wide discovery of genes, miRNAs, and transcription factors for abiotic stress tolerance (Fig. 3 and Table 2).

­Conclusion sRNA mechanism involving miRNA and siRNA has emerged as a powerful tool for crop improvement. Plant biologists use this technology not only for the study of the functional analysis of genes responsive to abiotic stresses but also to improve crop plants by manipulating their target genes. sRNA technology has certain advantages than other approaches. For instance, the silencing is sequence-specific and can be targeted to more than one gene. The identification and characterization of sRNAs (siRNAs and miRNAs) and their targeted genes play a crucial role in crop improvement for abiotic stress tolerance. This chapter has given an overview and assessed

­Conclusion

FIG. 3 Different strategies for the development of abiotic stress-associated biomarkers in plants.

as to how the plant’s sRNAs, including siRNAs and miRNAs, may act as key gene regulators to respond to and counteract the various effects of major abiotic stresses (drought, cold, and salt) in major crop plants, and presented information on their target validation and prediction, and the available database and computational tools for plant small RNAs. We also discussed sRNA roles in abiotic stresses, especially highlighting the utilization of sRNAs for abiotic stresses tolerance in plants through genetic engineering. However, most of the studies are on overexpression of the selected miRNAs for miRNA-mediated increased abiotic stresses tolerance in plants with few reports on silencing of the target genes by siRNA-mediated strategy. This indicates a need for better utilization of siRNAs for developing abiotic stress tolerance in plants. We have witnessed a tremendous growth in the availability of plant sRNAs across a wide range of plant species, and these can be used to engineer climate-resilient crops in diverse plant species. Thus, targeting the plant sRNAs for conferring abiotic stress tolerance in plants holds a lot of promise for crop improvement. However, more attention is needed to understand this powerful tool for its effective use in enhancing plant’s abiotic stress tolerance.

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­References

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