Over the last century, the earth’s climate has changed. It is a serious global, long-term problem which involves complex interactions. A lot of evidence suggests that most of the observed factors contributing to the crisis over the last 50 years can be attributed to human activities. Malaysia has always been vulnerable to extreme climatic events such as typhoons, floods and drought. We expect climate change to exacerbate these vulnerabilities. To ensure, that our water resources will always be secure and ready for use. We need to create awareness in the public and the policy makers so that they will acknowledge that the climate change issue is real. They also need to accept that actions to adapt with our vulnerabilities should be immediately put in place. We can do this by integrating the various sector policies and securing the participation of all stakeholders in Malaysia and other countries.
Studies conducted on the various geometric properties of skeletons of water bodies have shown highly promising results. However, these studies were made under the assumption that water bodies were static objects and that they remained constant over time. Water bodies are actually dynamic objects; they go through significant spatio-temporal changes due to drought and flood. In this study, the characterization of skeletons of simulated drought and flood of water bodies was performed. It was observed that as the drought level increased from 1 to 9, the average length of the skeletons decreased due to reduction in the size of the water bodies and increase in the number of water bodies. As the drought level increased from 9 to 15, the average length of the skeletons increased further due to vanishing of small water bodies. Flood caused an increase in the average length of the skeletons due to merging of adjacent water bodies. Power law relationships were observed between the average length of the skeletons of the simulated drought/flood and the level of drought/flood. The scaling exponent of these power laws which was named as a fractal dimension, indicated the rate of change of the average length of the skeletons of simulated drought/flood of water bodies over varying levels of drought/flood. However, errors observed in the goodness of fit of the plots indicated that monofractals were not sufficient to characterise the skeletons of simulated drought and flood of water bodies. Multifractals and lacunarity analysis were required for more accurate characterisation.
Three drought yield QTLs, qDTY 2.2, qDTY 3.1, and qDTY 12.1 with consistent effect on grain yield under reproductive stage drought stress were pyramided through marker assisted breeding with the objective of improving the grain yield of the elite Malaysian rice cultivar MR219 under reproductive stage drought stress. Foreground selection using QTL specific markers, recombinant selection using flanking markers, and background selection were performed. BC1F3-derived lines with different combinations of qDTY 2.2 , qDTY 3.1, and qDTY 12.1 were evaluated under both reproductive stage drought stress and non-stress during the dry seasons of 2013 and 2014 at IRRI.
Developing drought-tolerant rice varieties with higher yield under water stressed conditions provides a viable solution to serious yield-reduction impact of drought. Understanding the molecular regulation of this polygenic trait is crucial for the eventual success of rice molecular breeding programmes. microRNAs have received tremendous attention recently due to its importance in negative regulation. In plants, apart from regulating developmental and physiological processes, microRNAs have also been associated with different biotic and abiotic stresses. Hence here we chose to analyze the differential expression profiles of microRNAs in three drought treated rice varieties: Vandana (drought-tolerant), Aday Sel (drought-tolerant) and IR64 (drought-susceptible) in greenhouse conditions via high-throughput sequencing.
BACKGROUND: Assessment of segregating populations for their ability to withstand drought stress conditions is one of the best approaches to develop breeding lines and drought tolerant varieties. Bambara groundnut (Vigna subterranea L. Verdc.) is a leguminous crop, capable of growing in low-input agricultural systems in semi-arid areas. An F4 bi-parental segregating population obtained from S19-3 × DodR was developed to evaluate the effect of drought stress on photosynthetic parameters and identify QTLs associated with these traits under drought-stressed and well-watered conditions in a rainout shelter.
RESULTS: Stomatal conductance (gs), photosynthesis rate (A), transpiration rate (E) and intracellular CO2 (Ci) were significantly reduced (p
Drought tolerance is an important quantitative trait with multipart phenotypes that are often further complicated by plant phenology. Different types of environmental stresses, such as high irradiance, high temperatures, nutrient deficiencies, and toxicities, may challenge crops simultaneously; therefore, breeding for drought tolerance is very complicated. Interdisciplinary researchers have been attempting to dissect and comprehend the mechanisms of plant tolerance to drought stress using various methods; however, the limited success of molecular breeding and physiological approaches suggests that we rethink our strategies. Recent genetic techniques and genomics tools coupled with advances in breeding methodologies and precise phenotyping will likely reveal candidate genes and metabolic pathways underlying drought tolerance in crops. The WRKY transcription factors are involved in different biological processes in plant development. This zinc (Zn) finger protein family, particularly members that respond to and mediate stress responses, is exclusively found in plants. A total of 89 WRKY genes in japonica and 97 WRKY genes in O. nivara (OnWRKY) have been identified and mapped onto individual chromosomes. To increase the drought tolerance of rice (Oryza sativa L.), research programs should address the problem using a multidisciplinary strategy, including the interaction of plant phenology and multiple stresses, and the combination of drought tolerance traits with different genetic and genomics approaches, such as microarrays, quantitative trait loci (QTLs), WRKY gene family members with roles in drought tolerance, and transgenic crops. This review discusses the newest advances in plant physiology for the exact phenotyping of plant responses to drought to update methods of analysing drought tolerance in rice. Finally, based on the physiological/morphological and molecular mechanisms found in resistant parent lines, a strategy is suggested to select a particular environment and adapt suitable germplasm to that environment.
Rice is the most important staple crop in Malaysia and is cultivated all over the country, including the state of Sabah. The uniqueness of rice cultivation in Sabah lies in the type of rice itself, deriving mainly from local or non-commercial cultivars but with distinctive characteristics including long grains, aromatic properties, and drought tolerance. However, despite having these important agricultural traits, information on the genetic diversity of Sabah rice remains limited. Hence, the purpose of this study was to determine the genetic polymorphisms of Sabah rice using random amplification of polymorphic DNA (RAPD) markers. A total of 101 alleles were profiled, from which 94% were identified as polymorphic. Phylogenetic analysis grouped the rice samples into three clusters, with two clusters classifying the ability of rice to grow under different planting conditions, suitable for growth irrigate and upland condition. The first cluster was dominated by cultivars that could survive in wet (irrigated) areas, while the other featured those that were found in dry (upland) areas. Furthermore, two alleles, OPA-05-B2 and OPA-01-B11, were found to be unique to cultivars within the upland cluster and were thus proposed to be involved in dry environmental adaptation. The results of the present study provide an insight into the genetic relationships and diversity of Sabah rice.
BACKGROUND: Kinabalu Park, in Sabah (Malaysia) on Borneo Island, is renowned for the exceptionally high plant diversity it protects, with at least 5000 plant species enumerated to date. Discoveries of plant novelties continue to be made in Sabah, especially on isolated ultramafic outcrops, including in the genus Pittosporum (Pittosporaceae) with P. linearifolium from Bukit Hampuan on the southern border of the Park, and P. silamense from Bukit Silam in Eastern Sabah, both narrow endemics restricted to ultramafic soils.
RESULTS: A distinctive new species of Pittosporum (P. peridoticola J.B.Sugau and Ent, sp. nov.) was discovered on Mount Tambuyukon in the north of Kinabalu Park during ecological fieldwork. The diagnostic morphological characters of this taxon are discussed and information about the habitat in which it grows is provided. The soil chemistry in the rooting zone of P. peridoticola has high magnesium to calcium quotients, high extractable nickel and manganese concentrations, but low potassium and phosphorus concentrations, as is typical for ultramafic soils. Analysis of foliar samples of various Pittosporum-species originating from ultramafic and non-ultramafic soils showed a comparable foliar elemental stoichiometry that is suggestive of 'Excluder-type' ecophysiology.
CONCLUSION: Pittosporum peridoticola is an ultramafic obligate species restricted to Kinabalu Park with only two known populations within the boundaries of the protected area. It is vulnerable to any future stochastic landscape disturbance events, such as forest fires or severe droughts, and therefore its conservation status is 'Near Threatened'.
Never in the history of modern Malaysia, the general population at all levels are being threatened by food security. Food becoming less available and more expensive. Many factors, both long- and short-term, have contributed to the shortage. At a global level, available data seems to indicate that we have been consuming more than what we produce. Then came the shortfall in global rice production caused by the impact of climate change such as the widespread drought in India and China in 2002, typhoons in the Philippines in 2006, and the major flooding in Bangladesh in 2007. This was followed by the returns of pests such as planthoppers, and the various virus diseases transmitted particularly at regions with growing seasons having abnormally higher temperatures caused by climate change. Since the crisis started, scientists particularly breeders all over the world were requested to strengthen and upgrade the breeding program and facilities for the development of new varieties with increased tolerance to drought, flooding, and salinity as well resistant to insects and diseases. An important pre-requisite for such activities is the free flow of plant genetic resources for food and agriculture (pgrfa). The adoption of the Convention on Biological Diversity (CBD) has drastically slowed down the movement of many plant genetic resources and this has threatened the future supply of food. The International Treaty on Plant Genetic Resource for Food and Agriculture (ITPGRFA or the Treaty) is a global reaction to the rising tide of measures taken by many governments as a result CBD to extend their sovereign control over genetic resources. Many countries felt that those measures are inappropriate for food and agricultural crop genetic resources. The Treaty on the other hand recognizes that access and benefit sharing for agricultural biodiversity must be treated differently from the way it is generally treated under CBD. This paper discusses some of the key points and provisions from the treaty and some issues arising from its negotiation and future implementation in Malaysia.
Hyperdiverse tropical rainforests, such as the aseasonal forests in Southeast Asia, are supported by high annual rainfall. Its canopy is dominated by the species-rich tree family of Dipterocarpaceae (Asian dipterocarps), which has both ecological (e.g., supports flora and fauna) and economical (e.g., timber production) importance. Recent ecological studies suggested that rare irregular drought events may be an environmental stress and signal for the tropical trees. We assembled the genome of a widespread but near threatened dipterocarp, Shorea leprosula, and analyzed the transcriptome sequences of ten dipterocarp species representing seven genera. Comparative genomic and molecular dating analyses suggested a whole-genome duplication close to the Cretaceous-Paleogene extinction event followed by the diversification of major dipterocarp lineages (i.e. Dipterocarpoideae). Interestingly, the retained duplicated genes were enriched for genes upregulated by no-irrigation treatment. These findings provide molecular support for the relevance of drought for tropical trees despite the lack of an annual dry season.
Drought stress is the main abiotic factor affecting rice production. Rain-fed upland rice which is grown on unbounded fields and totally dependent on rainfall for moisture is more prone to drought stress compared to rice from other ecosystems. However, upland rice has adapted to this limited water condition, thus are more drought tolerant than rice from other ecosystems. We performed the first transcriptome sequencing of drought tolerant indica upland rice cultivar Kuku Belang to identify differentially expressed genes related to drought tolerance mechanism. Raw reads for non-treated and PEG-treated Oryza sativa subspecies indica cv. Kuku Belang were deposited in the NCBI SRA database with accession number SRP074520 (https://www.ncbi.nlm.nih.gov/sra?term=SRP074520).
Drought and pests are primary abiotic and biotic factors proposed as selective filters acting on species distributions along rainfall gradients in tropical forests and may contribute importantly to species distributional limits, performance, and diversity gradients. Recent research demonstrates linkages between species distributions along rainfall gradients and physiological drought tolerance; corresponding experimental examinations of the contribution of pest pressure to distributional limits and potential interactions between drought and herbivory are limited. This study aims to quantitate differential performance and herbivory as a function of species range limits across a climatic and floristic transition in Southeast Asia. Khao Chong Botanical Garden, Thailand and Pasoh Forest Reserve, Malaysia straddle the Kangar-Pattani Line. A reciprocal transplantation across a seasonality gradient was established using two groups of species ("widespread" taxa whose distributions include seasonally dry forests and "aseasonal" taxa whose distributions are limited to aseasonal forests). Growth, biomass allocation, survival, and herbivory were monitored for 19 months. Systematic differences in performance were a function of species distribution in relation to rainfall seasonality. In aseasonal Pasoh, aseasonal species had both greater growth and survivorship than widespread species. These differences were not a function of differential herbivory as widespread and aseasonal species experienced similar damage in the aseasonal forest. In seasonally dry Khao Chong, widespread species showed higher survivorship than aseasonal species, but these differences were only apparent during drought. We link this differential performance to physiological mechanisms as well as differential tolerance of biotic pressure during drought stress. Systematic decreases in seedling survival in aseasonal taxa during drought corresponded with previously documented physiological differences and may be exacerbated by herbivore damage. These results have important implications for tropical diversity and community composition in light of predicted increases in the frequency and severity of drought in hyperdiverse tropical forests.
Drought is considered one of the costliest natural disasters that result in water scarcity and crop damage almost every year. Drought monitoring and forecasting are essential for the efficient management of water resources and sustainability in agriculture. However, the design of a consistent drought prediction model based on the dynamic relationship of the drought index with its antecedent values remains a challenging task. In the present research, the SVR (support vector regression) model was hybridized with two different optimization algorithms namely; Particle Swarm Optimization (PSO) and Harris Hawks Optimization (HHO) for reliable prediction of effective drought index (EDI) 1 month ahead, at different locations of Uttarakhand State of India. The inputs of the models were selected through partial autocorrelation function (PACF) analysis. The output produced by the SVR-HHO and SVR-PSO models was compared with the EDI estimated from observed data using five statistical indicators, i.e., RMSE (Root Mean Square Error), MAE (Mean Absolute Error), COC (Coefficient of Correlation), NSE (Nash-Sutcliffe Efficiency), WI (Willmott Index), and graphical inspection of radar-chart, time-variation plot, box-whisker plot, and Taylor diagram. Appraisal of results indicates that the SVR-HHO model (RMSE = 0.535-0.965, MAE = 0.363-0.622, NSE = 0.558-0.860, COC = 0.760-0.930, and WI = 0.862-0.959) outperformed the SVR-PSO model (RMSE = 0.546-0.967, MAE = 0.372-0.625, NSE = 0.556-0.855, COC = 0.758-0.929, and WI = 0.861-0.956) in predicting EDI. Visual inspection of model performances also showed a better performance of SVR-HHO compared to SVR-PSO in replicating the median, inter-quartile range, spread, and pattern of the EDI estimated from observed rainfall. The results indicate that the hybrid SVR-HHO approach can be utilized for reliable EDI predictions in the study area.
Agriculture, meteorological, and hydrological drought is a natural hazard which affects ecosystems in the central India of Maharashtra state. Due to limited historical data for drought monitoring and forecasting available in the central India of Maharashtra state, implementing machine learning (ML) algorithms could allow for the prediction of future drought events. In this paper, we have focused on the prediction accuracy of meteorological drought in the semi-arid region based on the standardized precipitation index (SPI) using the random forest (RF), random tree (RT), and Gaussian process regression (GPR-PUK kernel) models. A different combination of machine learning models and variables has been performed for the forecasting of metrological drought based on the SPI-6 and 12 months. Models were developed using monthly rainfall data for the period of 2000-2019 at two meteorological stations, namely, Karanjali and Gangawdi, each representing a geographical region of Upper Godavari river basin area in the central India of Maharashtra state which frequently experiences droughts. Historical data from the SPI from 2000 to 2013 was processed to train the model into machine learning model, and the rest of the 2014 to 2019-year data were used for testing to forecast the SPI and metrological drought. The mean square error (MSE), root mean square error (RMSE), adjusted R2, Mallows' (Cp), Akaike's (AIC), Schwarz's (SBC), and Amemiya's PC were used to identify the best combination input model and best subregression analysis for both stations of SPI-6 and 12. The correlation coefficient ([Formula: see text]), mean absolute error (MAE), root mean square error (RMSE), relative absolute error (RAE), and root relative squared error (RRSE) were used to perform evaluation for SPI-6 and 12 months of both stations with RF, RT, and GPR-PUK kernel models during the training and testing scenarios. The results during testing phase revealed that the RF was found as the best model in forecasting droughts with values of [Formula: see text], MAE, RMSE, RAE (%), and RRSE (%) being 0.856, 0.551, 0.718, 74.778, and 54.019, respectively, for SPI-6 while 0.961, 0.361, 0.538, 34.926, and 28.262, respectively, for SPI-12 scales at Gangawdi station. Further, the respective values of evaluators at Karanjali station were 0.913 and 0.966, 0.541 and 0.386, 0.604 and 0.589, 52.592 and 36.959, and 42.315 and 31.394 for PUK kernel and RT models, respectively, during SPI-6 and SPI-12. Machine learning models are potential drought warning techniques because they take less time, have fewer inputs, and are less sophisticated than dynamic or scientific models.
Recent achievements in plant microRNA (miRNA), a large class of small and non-coding RNAs, are very exciting. A wide array of techniques involving forward genetic, molecular cloning, bioinformatic analysis, and the latest technology, deep sequencing have greatly advanced miRNA discovery. A tiny miRNA sequence has the ability to target single/multiple mRNA targets. Most of the miRNA targets are transcription factors (TFs) which have paramount importance in regulating the plant growth and development. Various families of TFs, which have regulated a range of regulatory networks, may assist plants to grow under normal and stress environmental conditions. This present review focuses on the regulatory relationships between miRNAs and different families of TFs like; NF-Y, MYB, AP2, TCP, WRKY, NAC, GRF, and SPL. For instance NF-Y play important role during drought tolerance and flower development, MYB are involved in signal transduction and biosynthesis of secondary metabolites, AP2 regulate the floral development and nodule formation, TCP direct leaf development and growth hormones signaling. WRKY have known roles in multiple stress tolerances, NAC regulate lateral root formation, GRF are involved in root growth, flower, and seed development, and SPL regulate plant transition from juvenile to adult. We also studied the relation between miRNAs and TFs by consolidating the research findings from different plant species which will help plant scientists in understanding the mechanism of action and interaction between these regulators in the plant growth and development under normal and stress environmental conditions.
Drought is a major abiotic stress that influences rice production. Although the transcriptomic data of rice against drought is widely available, the regulation of small open reading frames (sORFs) in response to drought stress in rice is yet to be investigated. Different levels of drought stress have different regulatory mechanisms in plants. In this study, drought stress was imposed on four-leaf stage rice, divided into two treatments, 40% and 30% soil moisture content (SMC). The RNAs of the samples were extracted, followed by the RNA sequencing analysis on their sORF expression changes under 40%_SMC and 30%_SMC, and lastly, the expression was validated through NanoString. A total of 122 and 143 sORFs were differentially expressed (DE) in 40%_SMC and 30%_SMC, respectively. In 40%_SMC, 69 sORFs out of 696 (9%) DEGs were found to be upregulated. On the other hand, 69 sORFs out of 449 DEGs (11%) were significantly downregulated. The trend seemed to be higher in 30%_SMC, where 112 (12%) sORFs were found to be upregulated from 928 significantly upregulated DEGs. However, only 8% (31 sORFs out of 385 DEGs) sORFs were downregulated in 30%_SMC. Among the identified sORFs, 110 sORFs with high similarity to rice proteome in the PsORF database were detected in 40%_SMC, while 126 were detected in 30%_SMC. The Gene Ontology (GO) enrichment analysis of DE sORFs revealed their involvement in defense-related biological processes, such as defense response, response to biotic stimulus, and cellular homeostasis, whereas enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways indicated that DE sORFs were associated with tryptophan and phenylalanine metabolisms. Several DE sORFs were identified, including the top five sORFs (OsisORF_3394, OsisORF_0050, OsisORF_3007, OsisORF_6407, and OsisORF_7805), which have yet to be characterised. Since these sORFs were responsive to drought stress, they might hold significant potential as targets for future climate-resilient rice development.
Haloxylon persicum is an endangered western Asiatic desert plant species, which survives under extreme environmental conditions. In this study, we focused on transcriptome analysis of H. persicum to understand the molecular mechanisms associated with drought tolerance. Two different periods of polyethylene glycol (PEG)-induced drought stress (48 h and 72 h) were imposed on H. persicum under in vitro conditions, which resulted in 18 million reads, subsequently assembled by de novo method with more than 8000 transcripts in each treatment. The N50 values were 1437, 1467, and 1524 for the control sample, 48 h samples, and 72 h samples, respectively. The gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis resulted in enrichment of mitogen-activated protein kinase (MAPK) and plant hormone signal transduction pathways under PEG-induced drought conditions. The differential gene expression analysis (DGEs) revealed significant changes in the expression pattern between the control and the treated samples. The KEGG analysis resulted in mapping transcripts with 138 different pathways reported in plants. The differential expression of drought-responsive transcription factors depicts the possible signaling cascades involved in drought tolerance. The present study provides greater insight into the fundamental transcriptome reprogramming of desert plants under drought.
Bambara groundnut (Vigna subterranea (L.) Verdc.) is an underutilised legume crop, which has long been recognised as a protein-rich and drought-tolerant crop, used extensively in Sub-Saharan Africa. The aim of the study was to identify quantitative trait loci (QTL) involved in agronomic and drought-related traits using an expression marker-based genetic map based on major crop resources developed in soybean. The gene expression markers (GEMs) were generated at the (unmasked) probe-pair level after cross-hybridisation of bambara groundnut leaf RNA to the Affymetrix Soybean Genome GeneChip. A total of 753 markers grouped at an LOD (Logarithm of odds) of three, with 527 markers mapped into linkage groups. From this initial map, a spaced expression marker-based genetic map consisting of 13 linkage groups containing 218 GEMs, spanning 982.7 cM (centimorgan) of the bambara groundnut genome, was developed. Of the QTL detected, 46% were detected in both control and drought treatment populations, suggesting that they are the result of intrinsic trait differences between the parental lines used to construct the cross, with 31% detected in only one of the conditions. The present GEM map in bambara groundnut provides one technically feasible route for the translation of information and resources from major and model plant species to underutilised and resource-poor crops.
This study was carried out to evaluate the genetic effect of quantitative trait loci (QTLs) conferring drought tolerance in wheat. A population of 120 F(2) individuals from the cross between the drought-tolerant S-78-11 and drought-sensitive Tajan cultivars were analyzed for their segregation under drought stress conditions. The relative water content under drought stress conditions exhibited continuous variation, indicating the minor gene effects on the trait. Single-marker analysis (SMA) was carried out to detect the main QTL association with drought tolerance. The SMA results revealed that the simple sequence repeat markers GWM182 and GWM292 on chromosome 5D and GWM410 on chromosome 5A exhibited significant association with drought tolerance, accounting for 30, 22, and 21% of the total variation, respectively. The 3 genetic loci, especially GWM182, can be used in marker-assisted selection methods in drought tolerance breeding in wheat.
Maximizing the research output from a limited investment is often the major challenge for minor and underutilized crops. However, such crops may be tolerant to biotic and abiotic stresses and are adapted to local, marginal, and low-input environments. Their development through breeding will provide an important resource for future agricultural system resilience and diversification in the context of changing climates and the need to achieve food security. The African Orphan Crops Consortium recognizes the values of genomic resources in facilitating the improvement of such crops. Prior to beginning genome sequencing there is a need for an assessment of line varietal purity and to estimate any residual heterozygosity. Here we present an example from bambara groundnut (Vigna subterranea (L.) Verdc.), an underutilized drought tolerant African legume. Two released varieties from Zimbabwe, identified as potential genotypes for whole genome sequencing (WGS), were genotyped with 20 species-specific SSR markers. The results indicate that the cultivars are actually a mix of related inbred genotypes, and the analysis allowed a strategy of single plant selection to be used to generate non-heterogeneous DNA for WGS. The markers also confirmed very low levels of heterozygosity within individual plants. The application of a pre-screen using co-dominant microsatellite markers is expected to substantially improve the genome assembly, compared to a cultivar bulking approach that could have been adopted.