STIFDB2: an updated version of plant stress-responsive transcription factor database with additional stress signals, stress-responsive transcription factor binding sites and stress-responsive genes in Arabidopsis and rice

ASPTF: A computational tool to predict abiotic stress-responsive transcription factors in plants by employing machine learning algorithms

BACKGROUND

Abiotic stresses pose serious threat to the growth and yield of crop plants. Several studies suggest that in plants, transcription factors (TFs) are important regulators of gene expression, especially when it comes to coping with abiotic stresses. Therefore, it is crucial to identify TFs associated with abiotic stress response for breeding of abiotic stress tolerant crop cultivars.

METHODS

Based on a machine learning framework, a computational model was envisaged to predict TFs associated with abiotic stress response in plants. To numerically encode TF sequences, four distinct sequence derived features were generated. The prediction was performed using ten shallow learning and four deep learning algorithms. For prediction using more pertinent and informative features, feature selection techniques were also employed.

RESULTS

Using the features chosen by the light-gradient boosting machine-variable importance measure (LGBM-VIM), the LGBM achieved the highest cross-validation performance metrics (accuracy: 86.81%, auROC: 92.98%, and auPRC: 94.03%). Further evaluation of the proposed model (LGBM prediction method + LGBM-VIM selected features) was also done using an independent test dataset, where the accuracy, auROC and auPRC were observed 81.98%, 90.65% and 91.30%, respectively.

CONCLUSIONS

To facilitate the adoption of the proposed strategy by users, the approach was implemented as a prediction server called ASPTF, accessible at https://iasri-sg.icar.gov.in/asptf/. The developed approach and the corresponding web application are anticipated to supplement experimental methods in the identification of transcription factors (TFs) responsive to abiotic stress in plants.

ASRpro: A machine-learning computational model for identifying proteins associated with multiple abiotic stress in plants

One of the thrust areas of research in plant breeding is to develop crop cultivars with enhanced tolerance to abiotic stresses. Thus, identifying abiotic stress-responsive genes (SRGs) and proteins is important for plant breeding research. However, identifying such genes via established genetic approaches is laborious and resource intensive. Although transcriptome profiling has remained a reliable method of SRG identification, it is species specific. Additionally, identifying multistress responsive genes using gene expression studies is cumbersome. Thus, endorsing the need to develop a computational method for identifying the genes associated with different abiotic stresses. In this work, we aimed to develop a computational model for identifying genes responsive to six abiotic stresses: cold, drought, heat, light, oxidative, and salt. The predictions were performed using support vector machine (SVM), random forest, adaptive boosting (ADB), and extreme gradient boosting (XGB), where the autocross covariance (ACC) and K-mer compositional features were used as input. With ACC, K-mer, and ACC + K-mer compositional features, the overall accuracy of ∼60-77, ∼75-86, and ∼61-78% were respectively obtained using the SVM algorithm with fivefold cross-validation. The SVM also achieved higher accuracy than the other three algorithms. The proposed model was also assessed with an independent dataset and obtained an accuracy consistent with cross-validation. The proposed model is the first of its kind and is expected to serve the requirement of experimental biologists; however, the prediction accuracy was modest. Given its importance for the research community, the online prediction application, ASRpro, is made freely available (https://iasri-sg.icar.gov.in/asrpro/) for predicting abiotic SRGs and proteins.

Bio Prospecting of Endophytes and PGPRs in Artemisinin Production for the Socio-economic Advancement

The growing demand for Artemisia annua plants in healthcare, food, and pharmaceutical industries has led to increased cultivation efforts to extract a vital compound, Artemisinin. The efficacy of Artemisinin as a potent drug against malaria disease is well established but its limited natural abundance. However, the common practice of using chemical fertilizers for maximum yield has adverse effects on plant growth, development, and the quality of phytochemicals. To address these issues, the review discusses the alternative approach of harnessing beneficial rhizosphere microbiota, particularly plant growth-promoting rhizobacteria (PGPR). Microbes hold substantial biotechnological potential for augmenting medicinal plant production, offering an environmentally friendly and cost-effective means to enhance medicinal plant production. This review article aims to identify a suitable endophytic population capable of enabling Artemisia sp. to thrive amidst abiotic stress while simultaneously enhancing Artemisinin production, thereby broadening its availability to a larger population. Furthermore, by subjecting endophytes to diverse combinations of harsh conditions, this review sheds light on the modulation of essential artemisinin biosynthesis pathway genes, both up regulated and down regulated. The collective findings suggest that through the in vitro engineering of endophytic communities and their in vivo application to Artemisia plants cultivated in tribal population fields, artemisinin production can be significantly augmented. The overall aim of this review to explore the potential of harnessing microbial communities, their functions, and services to enhance the cultivation of medicinal plants. It outlines a promising path toward bolstering artemisinin production, which holds immense promise in the fight against malaria.

Genetic Databases and Gene Editing Tools for Enhancing Crop Resistance against Abiotic Stress

Abiotic stresses extensively reduce agricultural crop production globally. Traditional breeding technology has been the fundamental approach used to cope with abiotic stresses. The development of gene editing technology for modifying genes responsible for the stresses and the related genetic networks has established the foundation for sustainable agriculture against environmental stress. Integrated approaches based on functional genomics and transcriptomics are now expanding the opportunities to elucidate the molecular mechanisms underlying abiotic stress responses. This review summarizes some of the features and weblinks of plant genome databases related to abiotic stress genes utilized for improving crops. The gene-editing tool based on clustered, regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) has revolutionized stress tolerance research due to its simplicity, versatility, adaptability, flexibility, and broader applications. However, off-target and low cleavage efficiency hinder the successful application of CRISPR/Cas systems. Computational tools have been developed for designing highly competent gRNA with better cleavage efficiency. This powerful genome editing tool offers tremendous crop improvement opportunities, overcoming conventional breeding techniques' shortcomings. Furthermore, we also discuss the mechanistic insights of the CRISPR/Cas9-based genome editing technology. This review focused on the current advances in understanding plant species' abiotic stress response mechanism and applying the CRISPR/Cas system genome editing technology to develop crop resilience against drought, salinity, temperature, heavy metals, and herbicides.

Stress combinations and their interactions in plants database: a one-stop resource on combined stress responses in plants

We have developed a compendium and interactive platform, named Stress Combinations and their Interactions in Plants Database (SCIPDb; http://www.nipgr.ac.in/scipdb.php), which offers information on morpho-physio-biochemical (phenome) and molecular (transcriptome and metabolome) responses of plants to different stress combinations. SCIPDb is a plant stress informatics hub for data mining on phenome, transcriptome, trait-gene ontology, and data-driven research for advancing mechanistic understanding of combined stress biology. We analyzed global phenome data from 939 studies to delineate the effects of various stress combinations on yield in major crops and found that yield was substantially affected under abiotic-abiotic stresses. Transcriptome datasets from 36 studies hosted in SCIPDb identified novel genes, whose roles have not been earlier established in combined stress. Integretome analysis under combined drought-heat stress pinpointed carbohydrate, amino acid, and energy metabolism pathways as the crucial metabolic, proteomic, and transcriptional components in plant tolerance to combined stress. These examples illustrate the application of SCIPDb in identifying novel genes and pathways involved in combined stress tolerance. Further, we showed the application of this database in identifying novel candidate genes and pathways for combined drought and pathogen stress tolerance. To our knowledge, SCIPDb is the only publicly available platform offering combined stress-specific omics big data visualization tools, such as an interactive scrollbar, stress matrix, radial tree, global distribution map, meta-phenome analysis, search, BLAST, transcript expression pattern table, Manhattan plot, and co-expression network. These tools facilitate a better understanding of the mechanisms underlying plant responses to combined stresses.

Rapid, nonparallel genomic evolution of Brassica rapa (field mustard) under experimental drought

While we know that climate change can potentially cause rapid phenotypic evolution, our understanding of the genetic basis and degree of genetic parallelism of rapid evolutionary responses to climate change is limited. In this study, we combined the resurrection approach with an evolve-and-resequence design to examine genome-wide evolutionary changes following drought. We exposed genetically similar replicate populations of the annual plant Brassica rapa derived from a field population in southern California to four generations of experimental drought or watered conditions in a greenhouse. Genome-wide sequencing of ancestral and descendant population pools identified hundreds of SNPs that showed evidence of rapidly evolving in response to drought. Several of these were in stress response genes, and two were identified in a prior study of drought response in this species. However, almost all genetic changes were unique among experimental populations, indicating that the evolutionary changes were largely nonparallel, despite the fact that genetically similar replicates of the same founder population had experienced controlled and consistent selection regimes. This nonparallelism of evolution at the genetic level is potentially because of polygenetic adaptation allowing for multiple different genetic routes to similar phenotypic outcomes. Our findings help to elucidate the relationship between rapid phenotypic and genomic evolution and shed light on the degree of parallelism and predictability of genomic evolution to environmental change.

Differential alternative splicing genes and isoform co-expression networks of Brassica napus under multiple abiotic stresses

Alternative splicing (AS) is an important regulatory process that affects plant development and stress responses by greatly increasing the complexity of transcriptome and proteome. To understand how the AS landscape of B. napus changes in response to abiotic stresses, we investigated 26 RNA-seq libraries, including control and treatments with cold, dehydration, salt, and abscisic acid (ABA) at two different time points, to perform comparative alternative splicing analysis. Apparently, AS events increased under all stresses except dehydration for 1 h, and intron retention was the most common AS mode. In addition, a total of 357 differential alternative splicing (DAS) genes were identified under four abiotic stresses, among which 81 DAS genes existed in at least two stresses, and 276 DAS genes were presented under only one stress. A weighted gene co-expression network analysis (WGCNA) based on the splicing isoforms, rather than the genes, pinpointed out 23 co-expression modules associated with different abiotic stresses. Among them, a number of significant hub genes were also found to be DAS genes, which encode key isoforms involved in responses to single stress or multiple stresses, including RNA-binding proteins, transcription factors, and other important genes, such as RBP45C, LHY, MYB59, SCL30A, RS40, MAJ23.10, and DWF4. The splicing isoforms of candidate genes identified in this study could be a valuable resource for improving tolerance of B. napus against multiple abiotic stresses.

A microRNA-microRNA crosstalk network inferred from genome-wide single nucleotide polymorphism variants in natural populations of Arabidopsis thaliana

To adapt to variable natural conditions, plants have evolved several strategies to respond to different environmental stresses. MicroRNA (miRNA)-mediated gene regulation is one of such strategies. Variants, e.g., single nucleotide polymorphisms (SNPs) within the mature miRNAs or their target sites may cause the alteration of regulatory networks and serious phenotype changes. In this study, we proposed a novel approach to construct a miRNA-miRNA crosstalk network in Arabidopsis thaliana based on the notion that two cooperative miRNAs toward common targets are under a strong pressure to be inherited together across ecotypes. By performing a genome-wide scan of the SNPs within the mature miRNAs and their target sites, we defined a "regulation fate profile" to describe a miRNA-target regulation being static (kept) or dynamic (gained or lost) across 1,135 ecotypes compared with the reference genome of Col-0. The cooperative miRNA pairs were identified by estimating the similarity of their regulation fate profiles toward the common targets. The reliability of the cooperative miRNA pairs was supported by solid expressional correlation, high PPImiRFS scores, and similar stress responses. Different combinations of static and dynamic miRNA-target regulations account for the cooperative miRNA pairs acting on various biological characteristics of miRNA conservation, expression, homology, and stress response. Interestingly, the targets that are co-regulated dynamically by both cooperative miRNAs are more likely to be responsive to stress. Hence, stress-related genes probably bear selective pressures in a certain group of ecotypes, in which miRNA regulations on the stress genes reprogram. Finally, three case studies showed that reprogramming miRNA-miRNA crosstalk toward the targets in specific ecotypes was associated with these ecotypes' climatic variables and geographical locations. Our study highlights the potential of miRNA-miRNA crosstalk as a genetic basis underlying environmental adaptation in natural populations.

A bZIP transcription factor VabZIP12 from blueberry induced by dark septate endocyte improving the salt tolerance of transgenic Arabidopsis

Dark septate endophytes (DSEs) have attracted much attention due to their positive roles in plant growth as well as resistance to various abiotic stresses. However, there are no reports on the molecular mechanisms of DSE fungi to improve salt tolerance in plants. In this study, the blueberry seedlings inoculated with T010, a beneficial DSE fungus reported previously, grew more vigorously than the non-inoculated control under salt stress. Physiological indicators showed that T010 inoculation increased antioxidant activities of blueberry roots. To explore its molecular mechanism, we focused on the bZIP TFs VabZIP12, who was highly up-regulated with T010 inoculation under salt stress. Further studies showed that VabZIP12, as a transcription activator, could combine both G-Box 1 and G-Box 2 motifs. Moreover, overexpression of VabZIP12 enhanced salt stress tolerance through increasing the activities of the enzymatic antioxidants in the transgenic Arabidopsis with up-regulation the related genes. These results indicated that the induction of VabZIP12 contribute to improving the tolerance of blueberry to salt stress by T010 inoculation.

Applying HPLC to Screening QTLs for BLB Resistance in Rice

Bacterial leaf blight (BLB) is caused by Xanthomonas oryzae pv. oryzae and is a major cause of rice yield reductions around the world. When diseased, plants produce a variety of metabolites to resist pathogens. In this study, the various defense metabolites were quantified using high-performance liquid chromatography (HPLC) after Xoo inoculation in a 120 Cheongcheong/Nagdong double haploid (CNDH) population. Quantitative trait locus (QTL) mapping was conducted using the concentration of the plant defense metabolites. HPLC analyzes the concentration of substances according to the severity of disease symptoms. Searching for BLB resistance candidate genes by applying this analysis method is very effective when mapping related genes. These resistance genes can be mapped directly to the causative pathogens. A total of 17 metabolites were detected by means of HPLC analysis after Xoo inoculation in the 120 CNDH population. QTL mapping of the metabolite concentrations resulted in the detection of the BLB resistance candidate gene, OsWRKYq6, in RM3343 of chromosome 6. OsWRKYq6 has a very high homology sequence with WRKY transcription factor 39, and when inoculated with Xoo, the relative expression level of the resistant population was higher than that of the susceptible population. Resistance genes have previously been detected using only phenotypic change data. In this study, resistance candidate genes were detected using the concentration of metabolites produced in plants after inoculation with pathogens. This newly developed analysis method can be used to effectively detect and identify genes directly involved in disease resistance for future studies.

Transcription Factor ChbZIP1 from Alkaliphilic Microalgae Chlorella sp. BLD Enhancing Alkaline Tolerance in Transgenic Arabidopsis thaliana

Saline-alkali soil has become an important environmental problem for crop productivity. One of the most effective approaches is to cultivate new stress-tolerant plants through genetic engineering. Through RNA-seq analysis and RT-PCR validation, a novel bZIP transcription factor ChbZIP1, which is significantly upregulated at alkali conditions, was obtained from alkaliphilic microalgae Chlorella sp. BLD. Overexpression of ChbZIP1 in Saccharomyces cerevisiae and Arabidopsis increased their alkali resistance, indicating ChbZIP1 may play important roles in alkali stress response. Through subcellular localization and transcriptional activation activity analyses, we found that ChbZIP1 is a nuclear-localized bZIP TF with transactivation activity to bind with the motif of G-box 2 (TGACGT). Functional analysis found that genes such as GPX1, DOX1, CAT2, and EMB, which contained G-box 2 and were associated with oxidative stress, were significantly upregulated in Arabidopsis with ChbZIP1 overexpression. The antioxidant ability was also enhanced in transgenic Arabidopsis. These results indicate that ChbZIP1 might mediate plant adaptation to alkali stress through the active oxygen detoxification pathway. Thus, ChbZIP1 may contribute to genetically improving plants’ tolerance to alkali stress.

EXPath 2.0: An Updated Database for Integrating High-Throughput Gene Expression Data with Biological Pathways

Co-expressed genes tend to have regulatory relationships and participate in similar biological processes. Construction of gene correlation networks from microarray or RNA-seq expression data has been widely applied to study transcriptional regulatory mechanisms and metabolic pathways under specific conditions. Furthermore, since transcription factors (TFs) are critical regulators of gene expression, it is worth investigating TFs on the promoters of co-expressed genes. Although co-expressed genes and their related metabolic pathways can be easily identified from previous resources, such as EXPath and EXPath Tool, this information is not simultaneously available to identify their regulatory TFs. EXPath 2.0 is an updated database for the investigation of regulatory mechanisms in various plant metabolic pathways with 1,881 microarray and 978 RNA-seq samples. There are six significant improvements in EXPath 2.0: (i) the number of species has been extended from three to six to include Arabidopsis, rice, maize, Medicago, soybean and tomato; (ii) gene expression at various developmental stages have been added; (iii) construction of correlation networks according to a group of genes is available; (iv) hierarchical figures of the enriched Gene Ontology (GO) terms are accessible; (v) promoter analysis of genes in a metabolic pathway or correlation network is provided; and (vi) user's gene expression data can be uploaded and analyzed. Thus, EXPath 2.0 is an updated platform for investigating gene expression profiles and metabolic pathways under specific conditions. It facilitates users to access the regulatory mechanisms of plant biological processes. The new version is available at http://EXPath.itps.ncku.edu.tw.

Identification and expression analysis of candidate genes associated with stem gall disease in Coriander (Coriandrum sativum L.) cultivars

Coriander (Coriandrum sativum L.) is a well-known spice and aromatic crop cultivated globally. Stem gall disease is one of the major constraints for its leaf and seed quality used for consumption and also affecting the yield. The identification of resistance genes and further characterization of such genes could help to understand the molecular basis of resistance and lay a solid ground for cloning of stem gall resistance genes in coriander. To evaluate the genetic expression of disease resistance-relevant genes in popularly grown coriander cultivars in India such as Pant Haritma, Hisar Sugandh, Hisar Surabhi, Hisar Anand, Rajendra Swathi, ACr-1, ACr-2, AgCr-1, CO-2 and CS-6 were used for LRR, GDSL, USP, ANK and PDR gene expression using Real Time PCR along with 18S housekeeping gene as internal control for the normalization. Result revealed the different expression pattern of genes among the cultivars tested. Highest expression was shown in cultivar AgCr-1 followed by Pant Haritma, Hisar Sugandh and ACr-1, and least expression in Hisar Anand, ACr-2, CO-2, Rajendra Swathi and CS-6. Domain analysis revealed the conserved domain relevance of the genes. This is the first report on stem gall resistance gene expression in coriander. The identified genes have a potential role in coriander and further utilize in crop improvement program. We hypothesize that contrasting cultivars can be a good source for candidate gene evaluation and further to use them as potential markers and used in hybridization program focus on incorporating and develop durable disease-resistance into the adapted cultivars of the region.

Bioinformatics Resources for Plant Abiotic Stress Responses: State of the Art and Opportunities in the Fast Evolving -Omics Era

Abiotic stresses are among the principal limiting factors for productivity in agriculture. In the current era of continuous climate changes, the understanding of the molecular aspects involved in abiotic stress response in plants is a priority. The rise of -omics approaches provides key strategies to promote effective research in the field, facilitating the investigations from reference models to an increasing number of species, tolerant and sensitive genotypes. Integrated multilevel approaches, based on molecular investigations at genomics, transcriptomics, proteomics and metabolomics levels, are now feasible, expanding the opportunities to clarify key molecular aspects involved in responses to abiotic stresses. To this aim, bioinformatics has become fundamental for data production, mining and integration, and necessary for extracting valuable information and for comparative efforts, paving the way to the modeling of the involved processes. We provide here an overview of bioinformatics resources for research on plant abiotic stresses, describing collections from -omics efforts in the field, ranging from raw data to complete databases or platforms, highlighting opportunities and still open challenges in abiotic stress research based on -omics technologies.

Distinct Evolutionary Origins of Intron Retention Splicing Events in NHX1 Antiporter Transcripts Relate to Sequence Specific Distinctions in Oryza Species

The genome of Asian cultivated rice (Oryza sativa L.) shows the presence of six organelle-specific and one plasma membrane (OsNHX1-7) NHX-type cation proton antiporters. Of these, vacuolar-localized OsNHX1 is extensively characterized. The genus Oryza consists of 27 species and 11 genome-types, with cultivated rice, diploid O. sativa, having an AA-type genome. Oryza NHX1 orthologous regions (gene organization, 5' upstream cis elements, amino acid residues/motifs) from closely related Oryza AA genomes cluster distinctly from NHX1 regions from more ancestral Oryza BB, FF and KKLL genomes. These sequence-specific distinctions also extend to two separate intron retention (IR) events involving Oryza NHX1 transcripts that occur at the 5' and 3' ends of the NHX1 transcripts. We demonstrate that the IR event involving the 5' UTR is present only in more recently evolved Oryza AA genomes while the IR event governing retention of the 13th intron of Oryza NHX1 (terminal intron) is more ancient in origin, also occurring in halophytic wild rice, Oryza coarctata (KKLL). We also report presence of a retro-copy of the OcNHX1 cDNA in the genome of O. coarctata (rOcNHX1). Preferential species and tissue specific up- or down-regulation of the correctly spliced NHX1 transcript/5' UTR/13th intron-retaining splice variants under salinity was observed. The implications of IR on NHX1 mRNA stability and ORF diversity in Oryza spp. is discussed.

Genome-wide identification of cold responsive transcription factors in Brassica napus L

BACKGROUND

Cold stress is one of the primary environmental factors that affect plant growth and productivity, especially for crops like Brassica napus that live through cold seasons. Till recently, although a number of genes and pathways involved in B. napus cold response have been revealed by independent studies, a genome-wide identification of the key regulators and the regulatory networks is still lack. In this study, we investigated the transcriptomes of cold stressed semi-winter and winter type rapeseeds in short day condition, mainly with the purpose to systematically identify the functional conserved transcription factors (TFs) in cold response of B. napus.

RESULTS

Global modulation of gene expression was observed in both the semi-winter type line (158A) and the winter type line (SGDH284) rapeseeds, in response to a seven-day chilling stress in short-day condition. Function analysis of differentially expressed genes (DEGs) revealed enhanced stresses response mechanisms and inhibited photosynthesis in both lines, as well as a more extensive inhibition of some primary biological processes in the semi-winter type line. Over 400 TFs were differentially expressed in response to cold stress, including 56 of them showed high similarity to the known cold response TFs and were consistently regulated in 158A and SGDH284, as well as 25 TFs which targets were over-represented in the total DEGs. A further investigation based on their interactions indicated the critical roles of several TFs in cold response of B. napus.

CONCLUSION

In summary, our results revealed the alteration of gene expression in cold stressed semi-winter and winter ecotype B. napus lines and provided a valuable collection of candidate key regulators involved in B. napus response to cold stress, which could expand our understanding of plant stress response and benefit the future improvement of the breed of rapeseeds.

Rice Stress-Resistant SNP Database

BACKGROUND

Rice (Oryza sativa L.) yield is limited inherently by environmental stresses, including biotic and abiotic stresses. Thus, it is of great importance to perform in-depth explorations on the genes that are closely associated with the stress-resistant traits in rice. The existing rice SNP databases have made considerable contributions to rice genomic variation information but none of them have a particular focus on integrating stress-resistant variation and related phenotype data into one web resource.

RESULTS

Rice Stress-Resistant SNP database (http://bioinformatics.fafu.edu.cn/RSRS) mainly focuses on SNPs specific to biotic and abiotic stress-resistant ability in rice, and presents them in a unified web resource platform. The Rice Stress-Resistant SNP (RSRS) database contains over 9.5 million stress-resistant SNPs and 797 stress-resistant candidate genes in rice, which were detected from more than 400 stress-resistant rice varieties. We incorporated the SNPs function, genome annotation and phenotype information into this database. Besides, the database has a user-friendly web interface for users to query, browse and visualize a specific SNP efficiently. RSRS database allows users to query the SNP information and their relevant annotations for individual variety or more varieties. The search results can be visualized graphically in a genome browser or displayed in formatted tables. Users can also align SNPs between two or more rice accessions.

CONCLUSION

RSRS database shows great utility for scientists to further characterize the function of variants related to environmental stress-resistant ability in rice.

Comprehensive functional analysis and mapping of SSR markers in the chickpea genome (Cicer arietinum L.)

Plant molecular breeding largely depends on the relationship between molecular markers and major traits. Herein, a total of 32,962 genomic simple sequence repeats (SSRs) were detected in the whole genome of chickpea with an average density of 94.93 SSRs/Mb. Chickpea chromosomes uniformity test indicated that the genomic SSRs (gSSRs) were steadily distributed across the genome. Moreover, 48,667 transcriptome sequences were analyzed and 1949 SSR-containing transcript assembly contigs (TACs) were identified. The analysis showed that di- and trinucleotide SSRs were the most frequent SSR motifs within the transcriptome sequences. Among them, AT and TTA and AG and TTC motifs within the transcriptome showed the highest frequencies among di- and trinucleotide repeat motifs, respectively. The SSRs-containing TACs were compared to the GenBank non-redundant database using BLASTX, and subsequently, gene ontology (GO) analysis was performed using QuickGO browser to reduce complexity and highlight biological processes associated with the SSRs-containing TACs. The identified SSRs-containing TACs were categorized into 35 enriched functional-related gene group. The mapping of characterized SSRs-containing TACs onto chickpea chromosomes was performed using BLASTN. The mapping result showed that, a total of 1798 SSRs-containing TACs were mapped onto the chickpea genome. Based on the functional analysis result, 249 and 242 of the mapped SSRs-containing TACs were found in the genes encoding for putative stress-related proteins and transcription factors, respectively. The results presented here can be applied to improve and speed up the chickpea breeding programs.

Genome-Wide Identification of Splicing Quantitative Trait Loci (sQTLs) in Diverse Ecotypes of Arabidopsis thaliana

Alternative splicing (AS) of pre-mRNAs contributes to transcriptome diversity and enables plants to generate different protein isoforms from a single gene and/or fine-tune gene expression during different development stages and environmental changes. Although AS is pervasive, the genetic basis for differential isoform usage in plants is still emerging. In this study, we performed genome-wide analysis in 666 geographically distributed diverse ecotypes of Arabidopsis thaliana to identify genomic regions [splicing quantitative trait loci (sQTLs)] that may regulate differential AS. These ecotypes belong to different microclimatic conditions and are part of the relict and non-relict populations. Although sQTLs were spread across the genome, we observed enrichment for trans-sQTL (trans-sQTLs hotspots) on chromosome one. Furthermore, we identified several sQTL (911) that co-localized with trait-linked single nucleotide polymorphisms (SNP) identified in the Arabidopsis genome-wide association studies (AraGWAS). Many sQTLs were enriched among circadian clock, flowering, and stress-responsive genes, suggesting a role for differential isoform usage in regulating these important processes in diverse ecotypes of Arabidopsis. In conclusion, the current study provides a deep insight into SNPs affecting isoform ratios/genes and facilitates a better mechanistic understanding of trait-associated SNPs in GWAS studies. To the best of our knowledge, this is the first report of sQTL analysis in a large set of Arabidopsis ecotypes and can be used as a reference to perform sQTL analysis in the Brassicaceae family. Since whole genome and transcriptome datasets are available for these diverse ecotypes, it could serve as a powerful resource for the biological interpretation of trait-associated loci, splice isoform ratios, and their phenotypic consequences to help produce more resilient and high yield crop varieties.

Genes, pathways and transcription factors involved in seedling stage chilling stress tolerance in indica rice through RNA-Seq analysis

BACKGROUND

Rice plants show yellowing, stunting, withering, reduced tillering and utimately low productivity in susceptible varieties under low temperature stress. Comparative transcriptome analysis was performed to identify novel transcripts, gain new insights into different gene expression and pathways involved in cold tolerance in rice.

RESULTS

Comparative transcriptome analyses of 5 treatments based on chilling stress exposure revealed more down regulated genes in susceptible and higher up regulated genes in tolerant genotypes. A total of 13930 and 10599 differentially expressed genes (DEGs) were detected in cold susceptible variety (CSV) and cold tolerant variety (CTV), respectively. A continuous increase in DEGs at 6, 12, 24 and 48 h exposure of cold stress was detected in both the genotypes. Gene ontology (GO) analysis revealed 18 CSV and 28 CTV term significantly involved in molecular function, cellular component and biological process. GO classification showed a significant role of transcription regulation, oxygen, lipid binding, catalytic and hydrolase activity for tolerance response. Absence of photosynthesis related genes, storage products like starch and synthesis of other classes of molecules like fatty acids and terpenes during the stress were noticed in susceptible genotype. However, biological regulations, generation of precursor metabolites, signal transduction, photosynthesis, regulation of cellular process, energy and carbohydrate metabolism were seen in tolerant genotype during the stress. KEGG pathway annotation revealed more number of genes regulating different pathways resulting in more tolerant. During early response phase, 24 and 11 DEGs were enriched in CTV and CSV, respectively in energy metabolism pathways. Among the 1583 DEG transcription factors (TF) genes, 69 WRKY, 46 bZIP, 41 NAC, 40 ERF, 31/14 MYB/MYB-related, 22 bHLH, 17 Nin-like 7 HSF and 4C3H were involved during early response phase. Late response phase showed 30 bHLH, 65 NAC, 30 ERF, 26/20 MYB/MYB-related, 11 C3H, 12 HSF, 86 Nin-like, 41 AP2/ERF, 55 bZIP and 98 WRKY members TF genes. The recovery phase included 18 bHLH, 50 NAC, 31 ERF, 24/13 MYB/MYB-related, 4 C3H, 4 HSF, 14 Nin-like, 31 bZIP and 114 WRKY TF genes.

CONCLUSIONS

Transcriptome analysis of contrasting genotypes for cold tolerance detected the genes, pathways and transcription factors involved in the stress tolerance.

Genes, pathways and transcription factors involved in seedling stage chilling stress tolerance in indica rice through RNA-Seq analysis

BACKGROUND

Rice plants show yellowing, stunting, withering, reduced tillering and utimately low productivity in susceptible varieties under low temperature stress. Comparative transcriptome analysis was performed to identify novel transcripts, gain new insights into different gene expression and pathways involved in cold tolerance in rice.

RESULTS

Comparative transcriptome analyses of 5 treatments based on chilling stress exposure revealed more down regulated genes in susceptible and higher up regulated genes in tolerant genotypes. A total of 13930 and 10599 differentially expressed genes (DEGs) were detected in cold susceptible variety (CSV) and cold tolerant variety (CTV), respectively. A continuous increase in DEGs at 6, 12, 24 and 48 h exposure of cold stress was detected in both the genotypes. Gene ontology (GO) analysis revealed 18 CSV and 28 CTV term significantly involved in molecular function, cellular component and biological process. GO classification showed a significant role of transcription regulation, oxygen, lipid binding, catalytic and hydrolase activity for tolerance response. Absence of photosynthesis related genes, storage products like starch and synthesis of other classes of molecules like fatty acids and terpenes during the stress were noticed in susceptible genotype. However, biological regulations, generation of precursor metabolites, signal transduction, photosynthesis, regulation of cellular process, energy and carbohydrate metabolism were seen in tolerant genotype during the stress. KEGG pathway annotation revealed more number of genes regulating different pathways resulting in more tolerant. During early response phase, 24 and 11 DEGs were enriched in CTV and CSV, respectively in energy metabolism pathways. Among the 1583 DEG transcription factors (TF) genes, 69 WRKY, 46 bZIP, 41 NAC, 40 ERF, 31/14 MYB/MYB-related, 22 bHLH, 17 Nin-like 7 HSF and 4C3H were involved during early response phase. Late response phase showed 30 bHLH, 65 NAC, 30 ERF, 26/20 MYB/MYB-related, 11 C3H, 12 HSF, 86 Nin-like, 41 AP2/ERF, 55 bZIP and 98 WRKY members TF genes. The recovery phase included 18 bHLH, 50 NAC, 31 ERF, 24/13 MYB/MYB-related, 4 C3H, 4 HSF, 14 Nin-like, 31 bZIP and 114 WRKY TF genes.

CONCLUSIONS

Transcriptome analysis of contrasting genotypes for cold tolerance detected the genes, pathways and transcription factors involved in the stress tolerance.

The transcriptome enables the identification of candidate genes behind medicinal value of Drumstick tree (Moringa oleifera)

Moringa oleifera is a plant well-known for its nutrition value, drought resistance and medicinal properties. cDNA libraries from five different tissues (leaf, root, stem, seed and flower) of M. oleifera cultivar Bhagya were generated and sequenced. We developed a bioinformatics pipeline to assemble transcriptome, along with the previously published M. oleifera genome, to predict 17,148 gene models. Few candidate genes related to biosynthesis of secondary metabolites, vitamins and ion transporters were identified. Expressions were further confirmed by real-time quantitative PCR experiments for few promising leads. Quantitative estimation of metabolites, as well as elemental analysis, was also carried out to support our observations. Enzymes in the biosynthesis of vitamins and metabolites like quercetin and kaempferol are highly expressed in leaves, flowers and seeds. The expression of iron transporters and calcium storage proteins were observed in root and leaves. In general, leaves retain the highest amount of small molecules of interest.

Infrastructures of systems biology that facilitate functional genomic study in rice

Rice (Oryza sativa L.) is both a major staple food for the worldwide population and a model crop plant for studying the mode of action of agronomically valuable traits, providing information that can be applied to other crop plants. Due to the development of high-throughput technologies such as next generation sequencing and mass spectrometry, a huge mass of multi-omics data in rice has been accumulated. Through the integration of those data, systems biology in rice is becoming more advanced.To facilitate such systemic approaches, we have summarized current resources, such as databases and tools, for systems biology in rice. In this review, we categorize the resources using six omics levels: genomics, transcriptomics, proteomics, metabolomics, integrated omics, and functional genomics. We provide the names, websites, references, working states, and number of citations for each individual database or tool and discuss future prospects for the integrated understanding of rice gene functions.

The complete chloroplast genome of the threatened Dipentodon sinicus (Dipentodontaceae)

Dipentodon is a monotypic genus of Dipentodontaceae and the only species, Dipentodon sinicus, is scattered in southwest China as well as adjacent Myanmar, northeast India and northern Vietnam. This species was evaluated as vulnerable in 'China Species Red List'. Here, we assembled and characterized the complete chloroplast (cp) genome of D. sinicus using Illumina sequencing data for the first time. The complete cp genome was 158,795 bp in length, consisting of a pair of inverted repeats of 26,587 bp, a large single-copy region of 87,233 bp and a small single-copy region of 18,388 bp. The genome encoded 113 unique genes, including 79 protein-coding genes, 30 tRNA genes and four rRNA genes. Phylogenetic analysis based on 16 complete cp genome sequences indicated that D. sinicus is a member of Huerteales, consistent with its position in the latest classification of flowering plants (AGP IV).

Comparative transcriptome analysis reveals K+ transporter gene contributing to salt tolerance in eggplant

BACKGROUND

Soil salinization is one of the most crucial abiotic stresses that limit the growth and production of eggplant. The existing researches in eggplant were mostly focused on salt-induced morphological, biochemical and physiological changes, with only limited works centered on salt-response genes in eggplant at the transcriptomic level.

RESULTS

Our preliminary work found that Zhusiqie (No.118) is salt-tolerant and Hongqie (No.30) is salt-sensitive. Consequently, they were re-named as ST118 and SS30, respectively. ST118 showed less damaged on growth and higher K⁺/Na⁺ ratios in leaves than SS30. Comparative-transcriptome analysis was used as a powerful approach to understand the salt-response mechanisms in the leaves and roots of SS30 and ST118. And it revealed that genotype-specific and organ-specific manners exist in eggplant in response to salt stress. Strikingly, the genotype-specific differentially expressed genes (DEGs) in ST118 were considered crucial to its higher salt-tolerance, because the expression patterns of common DEGs in the leaves/roots of the two eggplant genotypes were almost the same. Among them, some transcription factors have been reported to be in response to elevated external salinity, including the members of C2C2-CO-like, WRKY, MYB and NAC family. In addition, the AKT1, KAT1 and SOS1 were up-regulated only in the leaves of ST118. Furthermore, the complementation assays demonstrated that the salt-tolerances of both yeast and Arabidopsis akt1 mutants were enhanced by heterologous expression of SmAKT1.

CONCLUSION

The comparative-transcriptome analysis indicated that the salt-tolerance can be increased by higher transcript level of some genotype-specific genes. This work revealed that eggplants seem to be more inclined to absorb K⁺ rather than to exclude Na⁺ under salt stress conditions because seven K⁺ transporters were significantly up-regulated, while only one Na⁺ transporter was similarly regulated. Finally, the complementation assays of SmAKT1, which is genotype-specific up-regulated in ST118, suggest that the other TFs and K⁺ transport genes were worthy of future investigation for their functions in salinity tolerance.

Genome-Wide Analysis of Domain-Swap Predicted Products in the Genome of Anti-Stress Medicinal Plant: Ocimum tenuiflorum

Computational approaches to high-throughput data are gaining importance because of explosion of sequences in the post-genomic era. This explosion of sequence data creates a huge gap among the domains of sequence structure and function, since the experimental techniques to determine the structure and function are very expensive, time taking, and laborious in nature. Therefore, there is an urgent need to emphasize on the development of computational approaches in the field of biological systems. Engagement of proteins in quaternary arrangements, such as domain swapping, might be relevant for higher compatibility of such genes at stress conditions. In this study, the capacity to engage in domain swapping was predicted from mere sequence information in the whole genome of holy Basil (Ocimum tenuiflorum), which is well known to be an anti-stress agent. Approximately, one-fourth of the proteins of O tenuiflorum are predicted to undergo three-dimensional (3D)-domain swapping. Furthermore, function annotation was carried out on all the predicted domain-swap sequences from the O tenuiflorum and Arabidopsis thaliana for their distribution in different Pfam protein families and gene ontology (GO) terms. These domain-swapped protein sequences are associated with many Pfam protein families with a wide range of GO annotation terms. A comparative analysis of domain-swap-predicted sequences in O tenuiflorum with gene products in A thaliana reveals that around 26% (2522 sequences) are close homologues across the 2 genomes. Functional annotation of predicted domain-swapped sequences infers that predicted domain-swap sequences are involved in diverse molecular functions, such as in gene regulation of abiotic stress conditions and adaptation to different environmental niches. Finally, the positively predicted sequences of A thaliana and O tenuiflorum were also examined for their presence in stress regulome, as recorded in our STIFDB database, to check the involvement of these proteins in different abiotic stresses.

Exploiting Genetic and Genomic Resources to Enhance Heat-Tolerance in Tomatoes

High temperature is one of the most detrimental abiotic stresses in tomatoes. Many studies highlighted that even small increases in temperature can alter the plant reproductive system, causing a significant reduction in tomato yield. The aim of this study was to exploit the phenotypic and genomic variations of a tomato landrace collection grown at high temperatures. Fifteen genotypes were selected as the best performing in two experimental fields. The selection was based on six yield-related traits, including flower earliness, number of flowers per inflorescence, fruit set, number of fruit per plant, fruit weight and yield per plant. In order to identify markers targeting traits that could be highly influenced by adverse climate conditions, such as flowering and fruit setting, an association mapping approach was undertaken exploiting a tomato high-throughput genomic array. The phenotypic variability observed allowed us to identify a total of 15 common markers associated with the studied traits. In particular, the most relevant associations co-localized with genes involved in the floral structure development, such as the style2.1 gene, or with genes directly involved in the response to abiotic stresses. These promising candidate genes will be functionally validated and transferred to a cultivated tomato to improve its performance under high temperatures.

Plant stress RNA-seq Nexus: a stress-specific transcriptome database in plant cells

Background

Abiotic and biotic stresses severely affect the growth and reproduction of plants and crops. Determining the critical molecular mechanisms and cellular processes in response to stresses will provide biological insight for addressing both climate change and food crises. RNA sequencing (RNA-Seq) is a revolutionary tool that has been used extensively in plant stress research. However, no existing large-scale RNA-Seq database has been designed to provide information on the stress-specific differentially expressed transcripts that occur across diverse plant species and various stresses.

Results

We have constructed a comprehensive database, the plant stress RNA-Seq nexus (PSRN), which includes 12 plant species, 26 plant-stress RNA-Seq datasets, and 937 samples. All samples are assigned to 133 stress-specific subsets, which are constructed into 254 subset pairs, a comparison between selected two subsets, for stress-specific differentially expressed transcript identification.

Conclusions

PSRN is an open resource for intuitive data exploration, providing expression profiles of coding-transcript/lncRNA and identifying which transcripts are differentially expressed between different stress-specific subsets, in order to support researchers generating new biological insights and hypotheses in molecular breeding or evolution. PSRN is freely available at http://syslab5.nchu.edu.tw/PSRN.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5367-5) contains supplementary material, which is available to authorized users.

Augmentation of crop productivity through interventions of omics technologies in India: challenges and opportunities

With the continuous increase in the population of developing countries and decline of natural resources, there is an urgent need to qualitatively and quantitatively augment crop productivity by using new tools and technologies for improvement of agriculturally important traits. The new scientific and technological omics-based approaches have enabled us to deal with several issues and challenges faced by modern agricultural system and provided us novel opportunities for ensuring food and nutritional security. Recent developments in sequencing techniques have made available huge amount of genomic and transcriptomic data on model and cultivated crop plants including Arabidopsis thaliana, Oryza sativa, Triticum aestivum etc. The sequencing data along with other data generated through several omics platforms have significantly influenced the disciplines of crop sciences. Gene discovery and expression profiling-based technologies are offering enormous opportunities to the scientific community which can now apply marker-assisted selection technology to assess and enhance diversity in their collected germplasm, introgress essential traits from new sources and investigate genes that control key traits of crop plants. Utilization of omics science and technologies for crop productivity, protection and management has recently been receiving a lot of attention; the majority of the efforts have been put into signifying the possible applications of various omics technologies in crop plant sciences. This article highlights the background of challenges and opportunities for augmentation of crop productivity through interventions of omics technologies in India.

Transcriptome changes induced by abiotic stresses in Artemisia annua

Artemisia annua is known to be the source of artemisinin worldwide which is an antimalarial compound but is synthesised in very limited amount in the plant. Most research laid emphasis on the methods of enhancing artemisinin but our study has been planned in a way that it may simultaneously address two problems encountered by the plant. Firstly, to know the effect on the artemisinin content in the era of climate change because the secondary metabolites tend to increase under stress. Secondly, to identify some of the stress responsive genes that could help in stress tolerance of the plant under abiotic stress. Hence, the A. annua plants were subjected to four abiotic stresses (salt, cold, drought and water-logging) and it was observed that the artemisinin content increased in all the stress conditions except drought. Next, in order to identify the stress responsive genes, the transcriptome sequencing of the plants under stress was carried out resulting in 89,362 transcripts for control and 81,328, 76,337, 90,470 and 96,493 transcripts for salt, cold, drought, and water logging stresses. This investigation provides new insights for functional studies of genes involved in multiple abiotic stresses and potential candidate genes for multiple stress tolerance in A. annua.

Physiological and transcriptomic responses in the seed coat of field-grown soybean (Glycine max L. Merr.) to abiotic stress

BACKGROUND

Understanding how intensification of abiotic stress due to global climate change affects crop yields is important for continued agricultural productivity. Coupling genomic technologies with physiological crop responses in a dynamic field environment is an effective approach to dissect the mechanisms underpinning crop responses to abiotic stress. Soybean (Glycine max L. Merr. cv. Pioneer 93B15) was grown in natural production environments with projected changes to environmental conditions predicted for the end of the century, including decreased precipitation, increased tropospheric ozone concentrations ([O3]), or increased temperature.

RESULTS

All three environmental stresses significantly decreased leaf-level photosynthesis and stomatal conductance, leading to significant losses in seed yield. This was driven by a significant decrease in the number of pods per node for all abiotic stress treatments. To understand the underlying transcriptomic response involved in the yield response to environmental stress, RNA-Sequencing analysis was performed on the soybean seed coat, a tissue that plays an essential role in regulating carbon and nitrogen transport to developing seeds. Gene expression analysis revealed 49, 148 and 1,576 differentially expressed genes in the soybean seed coat in response to drought, elevated [O3] and elevated temperature, respectively.

CONCLUSIONS

Elevated [O3] and drought did not elicit substantive transcriptional changes in the soybean seed coat. However, this may be due to the timing of sampling and does not preclude impacts of those stresses on different tissues or different stages in seed coat development. Expression of genes involved in DNA replication and metabolic processes were enriched in the seed coat under high temperate stress, suggesting that the timing of events that are important for cell division and proper seed development were altered in a stressful growth environment.

Eukaryotic and prokaryotic promoter databases as valuable tools in exploring the regulation of gene transcription: a comprehensive overview

The complete exploration of the regulation of gene expression remains one of the top-priority goals for researchers. As the regulation is mainly controlled at the level of transcription by promoters, study on promoters and findings are of great importance. This review summarizes forty selected databases that centralize experimental and theoretical knowledge regarding the organization of promoters, interacting transcription factors (TFs) and microRNAs (miRNAs) in many eukaryotic and prokaryotic species. The presented databases offer researchers valuable support in elucidating the regulation of gene transcription.

Stress2TF: a manually curated database of TF regulation in plant response to stress

Considerable studies demonstrate that plant transcription factors (TFs) play key regulatory roles in abiotic/biotic stress conditions, such as drought and pathogen attack. However, there is no effort dedicated to curate experimentally validated stress-TF regulatory relationships from these individual reports into a central database, which put an obstacle in the exploration of stress-TF regulations in plants. To address this issue, we presented a literature-curated database 'Stress2TF' that currently documented 1533 regulatory relationships between 71 abiotic/biotic stresses and 558 TFs in 47 plant species. Each entry in Stress2TF contains detailed information about a stress-TF relationship such as plant name, stress name, TF and brief description of stress-TF relationship. Stress2TF provided a user-friendly interface for entry browse, search and download. In addition, a submission page and several useful tools (e.g., BLAST, network visualization) were integrated. Stress2TF may be a valuable resource for the research of stress-TF regulatory mechanisms in plants. Stress2TF is available at http://csgenomics.ahau.edu.cn/Stress2TF.

Evolutionarily Conserved Alternative Splicing Across Monocots

One difficulty when identifying alternative splicing (AS) events in plants is distinguishing functional AS from splicing noise. One way to add confidence to the validity of a splice isoform is to observe that it is conserved across evolutionarily related species. We use a high throughput method to identify junction-based conserved AS events from RNA-Seq data across nine plant species, including five grass monocots (maize, sorghum, rice, Brachpodium, and foxtail millet), plus two nongrass monocots (banana and African oil palm), the eudicot Arabidopsis, and the basal angiosperm Amborella In total, 9804 AS events were found to be conserved between two or more species studied. In grasses containing large regions of conserved synteny, the frequency of conserved AS events is twice that observed for genes outside of conserved synteny blocks. In plant-specific RS and RS2Z subfamilies of the serine/arginine (SR) splice-factor proteins, we observe both conservation and divergence of AS events after the whole genome duplication in maize. In addition, plant-specific RS and RS2Z splice-factor subfamilies are highly connected with R2R3-MYB in STRING functional protein association networks built using genes exhibiting conserved AS. Furthermore, we discovered that functional protein association networks constructed around genes harboring conserved AS events are enriched for phosphatases, kinases, and ubiquitylation genes, which suggests that AS may participate in regulating signaling pathways. These data lay the foundation for identifying and studying conserved AS events in the monocots, particularly across grass species, and this conserved AS resource identifies an additional layer between genotype to phenotype that may impact future crop improvement efforts.

Identification and positional distribution analysis of transcription factor binding sites for genes from the wheat fl-cDNA sequences

The binding sites of transcription factors (TFs) in upstream DNA regions are called transcription factor binding sites (TFBSs). TFBSs are important elements for regulating gene expression. To date, there have been few studies on the profiles of TFBSs in plants. In total, 4,873 sequences with 5' upstream regions from 8530 wheat fl-cDNA sequences were used to predict TFBSs. We found 4572 TFBSs for the MADS TF family, which was twice as many as for bHLH (1951), B3 (1951), HB superfamily (1914), ERF (1820), and AP2/ERF (1725) TFs, and was approximately four times higher than the remaining TFBS types. The percentage of TFBSs and TF members showed a distinct distribution in different tissues. Overall, the distribution of TFBSs in the upstream regions of wheat fl-cDNA sequences had significant difference. Meanwhile, high frequencies of some types of TFBSs were found in specific regions in the upstream sequences. Both TFs and fl-cDNA with TFBSs predicted in the same tissues exhibited specific distribution preferences for regulating gene expression. The tissue-specific analysis of TFs and fl-cDNA with TFBSs provides useful information for functional research, and can be used to identify relationships between tissue-specific TFs and fl-cDNA with TFBSs. Moreover, the positional distribution of TFBSs indicates that some types of wheat TFBS have different positional distribution preferences in the upstream regions of genes.

Depletion of abscisic acid levels in roots of flooded Carrizo citrange (Poncirus trifoliata L. Raf. × Citrus sinensis L. Osb.) plants is a stress-specific response associated to the differential expression of PYR/PYL/RCAR receptors

Soil flooding reduces root abscisic acid (ABA) levels in citrus, conversely to what happens under drought. Despite this reduction, microarray analyses suggested the existence of a residual ABA signaling in roots of flooded Carrizo citrange seedlings. The comparison of ABA metabolism and signaling in roots of flooded and water stressed plants of Carrizo citrange revealed that the hormone depletion was linked to the upregulation of CsAOG, involved in ABA glycosyl ester (ABAGE) synthesis, and to a moderate induction of catabolism (CsCYP707A, an ABA 8'-hydroxylase) and buildup of dehydrophaseic acid (DPA). Drought strongly induced both ABA biosynthesis and catabolism (CsNCED1, 9-cis-neoxanthin epoxycarotenoid dioxygenase 1, and CsCYP707A) rendering a significant hormone accumulation. In roots of flooded plants, restoration of control ABA levels after stress release was associated to the upregulation of CsBGLU18 (an ABA β-glycosidase) that cleaves ABAGE. Transcriptional profile of ABA receptor genes revealed a different induction in response to soil flooding (CsPYL5) or drought (CsPYL8). These two receptor genes along with CsPYL1 were cloned and expressed in a heterologous system. Recombinant CsPYL5 inhibited ΔNHAB1 activity in vitro at lower ABA concentrations than CsPYL8 or CsPYL1, suggesting its better performance under soil flooding conditions. Both stress conditions induced ABA-responsive genes CsABI5 and CsDREB2A similarly, suggesting the occurrence of ABA signaling in roots of flooded citrus seedlings. The impact of reduced ABA levels in flooded roots on CsPYL5 expression along with its higher hormone affinity reinforce the role of this ABA receptor under soil-flooding conditions and explain the expression of certain ABA-responsive genes.

Genomewide Expression and Functional Interactions of Genes under Drought Stress in Maize

A genomewide transcriptome assay of two subtropical genotypes of maize was used to observe the expression of genes at seedling stage of drought stress. The number of genes expressed differentially was greater in HKI1532 (a drought tolerant genotype) than in PC3 (a drought sensitive genotype), indicating primary differences at the transcriptional level in stress tolerance. The global coexpression networks of the two genotypes differed significantly with respect to the number of modules and the coexpression pattern within the modules. A total of 174 drought-responsive genes were selected from HKI1532, and their coexpression network revealed key correlations between different adaptive pathways, each cluster of the network representing a specific biological function. Transcription factors related to ABA-dependent stomatal closure, signalling, and phosphoprotein cascades work in concert to compensate for reduced photosynthesis. Under stress, water balance was maintained by coexpression of the genes involved in osmotic adjustments and transporter proteins. Metabolism was maintained by the coexpression of genes involved in cell wall modification and protein and lipid metabolism. The interaction of genes involved in crucial biological functions during stress was identified and the results will be useful in targeting important gene interactions to understand drought tolerance in greater detail.

Rice Improvement Through Genome-Based Functional Analysis and Molecular Breeding in India

Rice is one of the main pillars of food security in India. Its improvement for higher yield in sustainable agriculture system is also vital to provide energy and nutritional needs of growing world population, expected to reach more than 9 billion by 2050. The high quality genome sequence of rice has provided a rich resource to mine information about diversity of genes and alleles which can contribute to improvement of useful agronomic traits. Defining the function of each gene and regulatory element of rice remains a challenge for the rice community in the coming years. Subsequent to participation in IRGSP, India has continued to contribute in the areas of diversity analysis, transcriptomics, functional genomics, marker development, QTL mapping and molecular breeding, through national and multi-national research programs. These efforts have helped generate resources for rice improvement, some of which have already been deployed to mitigate loss due to environmental stress and pathogens. With renewed efforts, Indian researchers are making new strides, along with the international scientific community, in both basic research and realization of its translational impact.

Overexpression of Grain Amaranth (Amaranthus hypochondriacus) AhERF or AhDOF Transcription Factors in Arabidopsis thaliana Increases Water Deficit- and Salt-Stress Tolerance, Respectively, via Contrasting Stress-Amelioration Mechanisms

Two grain amaranth transcription factor (TF) genes were overexpressed in Arabidopsis plants. The first, coding for a group VII ethylene response factor TF (i.e., AhERF-VII) conferred tolerance to water-deficit stress (WS) in transgenic Arabidopsis without affecting vegetative or reproductive growth. A significantly lower water-loss rate in detached leaves coupled to a reduced stomatal opening in leaves of plants subjected to WS was associated with this trait. WS tolerance was also associated with an increased antioxidant enzyme activity and the accumulation of putative stress-related secondary metabolites. However, microarray and GO data did not indicate an obvious correlation between WS tolerance, stomatal closure, and abscisic acid (ABA)-related signaling. This scenario suggested that stomatal closure during WS in these plants involved ABA-independent mechanisms, possibly involving reactive oxygen species (ROS). WS tolerance may have also involved other protective processes, such as those employed for methyl glyoxal detoxification. The second, coding for a class A and cluster I DNA binding with one finger TF (i.e., AhDof-AI) provided salt-stress (SS) tolerance with no evident fitness penalties. The lack of an obvious development-related phenotype contrasted with microarray and GO data showing an enrichment of categories and genes related to developmental processes, particularly flowering. SS tolerance also correlated with increased superoxide dismutase activity but not with augmented stomatal closure. Additionally, microarray and GO data indicated that, contrary to AhERF-VII, SS tolerance conferred by AhDof-AI in Arabidopsis involved ABA-dependent and ABA-independent stress amelioration mechanisms.

More than meets the eye: Emergent properties of transcription factors networks in Arabidopsis

Uncovering and mathematically modeling Transcription Factor Networks (TFNs) are the first steps in engineering plants with traits that are better equipped to respond to changing environments. Although several plant TFNs are well known, the framework for systematically modeling complex characteristics such as switch-like behavior, oscillations, and homeostasis that emerge from them remain elusive. This review highlights literature that provides, in part, experimental and computational techniques for characterizing TFNs. This review also outlines methodologies that have been used to mathematically model the dynamic characteristics of TFNs. We present several examples of TFNs in plants that are involved in developmental and stress response. In several cases, advanced algorithms capture or quantify emergent properties that serve as the basis for robustness and adaptability in plant responses. Increasing the use of mathematical approaches will shed new light on these regulatory properties that control plant growth and development, leading to mathematical models that predict plant behavior. This article is part of a Special Issue entitled: Plant Gene Regulatory Mechanisms and Networks, edited by Dr. Erich Grotewold and Dr. Nathan Springer.

India's Computational Biology Growth and Challenges

India's computational science is growing swiftly due to the outburst of internet and information technology services. The bioinformatics sector of India has been transforming rapidly by creating a competitive position in global bioinformatics market. Bioinformatics is widely used across India to address a wide range of biological issues. Recently, computational researchers and biologists are collaborating in projects such as database development, sequence analysis, genomic prospects and algorithm generations. In this paper, we have presented the Indian computational biology scenario highlighting bioinformatics-related educational activities, manpower development, internet boom, service industry, research activities, conferences and trainings undertaken by the corporate and government sectors. Nonetheless, this new field of science faces lots of challenges.

Integration of small RNAs, degradome and transcriptome sequencing in hyperaccumulator Sedum alfredii uncovers a complex regulatory network and provides insights into cadmium phytoremediation

The hyperaccumulating ecotype of Sedum alfredii Hance is a cadmium (Cd)/zinc/lead co-hyperaccumulating species of Crassulaceae. It is a promising phytoremediation candidate accumulating substantial heavy metal ions without obvious signs of poisoning. However, few studies have focused on the regulatory roles of miRNAs and their targets in the hyperaccumulating ecotype of S. alfredii. Here, we combined analyses of the transcriptomics, sRNAs and the degradome to generate a comprehensive resource focused on identifying key regulatory miRNA-target circuits under Cd stress. A total of 87 721 unigenes and 356 miRNAs were identified by deep sequencing, and 79 miRNAs were differentially expressed under Cd stress. Furthermore, 754 target genes of 194 miRNAs were validated by degradome sequencing. A gene ontology (GO) enrichment analysis of differential miRNA targets revealed that auxin, redox-related secondary metabolism and metal transport pathways responded to Cd stress. An integrated analysis uncovered 39 pairs of miRNA targets that displayed negatively correlated expression profiles. Ten miRNA-target pairs also exhibited negative correlations according to a real-time quantitative PCR analysis. Moreover, a coexpression regulatory network was constructed based on profiles of differentially expressed genes. Two hub genes, ARF4 (auxin response factor 4) and AAP3 (amino acid permease 3), which might play central roles in the regulation of Cd-responsive genes, were uncovered. These results suggest that comprehensive analyses of the transcriptomics, sRNAs and the degradome provided a useful platform for investigating Cd hyperaccumulation in S. alfredii, and may provide new insights into the genetic engineering of phytoremediation.

Comprehensive Analysis of the Soybean (Glycine max) GmLAX Auxin Transporter Gene Family

The phytohormone auxin plays a critical role in regulation of plant growth and development as well as plant responses to abiotic stresses. This is mainly achieved through its uneven distribution in plant via a polar auxin transport process. Auxin transporters are major players in polar auxin transport. The AUXIN RESISTENT 1/LIKE AUX1 (AUX/LAX) auxin influx carriers belong to the amino acid permease family of proton-driven transporters and function in the uptake of indole-3-acetic acid (IAA). In this study, genome-wide comprehensive analysis of the soybean AUX/LAX (GmLAX) gene family, including phylogenic relationships, chromosome localization, and gene structure, was carried out. A total of 15 GmLAX genes, including seven duplicated gene pairs, were identified in the soybean genome. They were distributed on 10 chromosomes. Despite their higher percentage identities at the protein level, GmLAXs exhibited versatile tissue-specific expression patterns, indicating coordinated functioning during plant growth and development. Most GmLAXs were responsive to drought and dehydration stresses and auxin and abscisic acid (ABA) stimuli, in a tissue- and/or time point- sensitive mode. Several GmLAX members were involved in responding to salt stress. Sequence analysis revealed that promoters of GmLAXs contained different combinations of stress-related cis-regulatory elements. These studies suggest that the soybean GmLAXs were under control of a very complex regulatory network, responding to various internal and external signals. This study helps to identity candidate GmLAXs for further analysis of their roles in soybean development and adaption to adverse environments.

Tolerant and Susceptible Sesame Genotypes Reveal Waterlogging Stress Response Patterns

Waterlogging is a common adverse environmental condition that limits plant growth. Sesame (Sesamum indicum) is considered a drought-tolerant oil crop but is typically susceptible to harmful effects from waterlogging. The present study used comparative analysis to explore the waterlogging stress response associated with two sesame genotypes. The RNA-seq dataset generated during a time course of 0, 3, 9 and 15 h of waterlogging as well as 20 h post-drainage indicated that stress gradually suppressed the expression of sesame genes, with 9 h as the critical time point for the response of sesame to waterlogging stress. Of the 19,316 genes expressed during waterlogging, 72.1% were affected significantly. Sesame of both tolerant and susceptible genotypes showed decreased numbers of upregulated differentially expressed genes (DEGs) but increased numbers of downregulated DEGs at the onset of waterlogging. However, the tolerant-genotype sesame exhibited 25.5% more upregulated DEGs and 29.7% fewer downregulated DEGs than those of the susceptible-genotype strain between 3 and 15 h. The results indicated that the tolerant sesame displayed a more positive gene response to waterlogging. A total of 1,379 genes were significantly induced and commonly expressed in sesame under waterlogging conditions from 3 to 15 h regardless of tolerance level; of these genes, 98 are known homologous stress responsive genes, while the remaining 1,281 are newly reported here. This gene set may represent the core genes that function in response to waterlogging, including those related mainly to energy metabolism and phenylpropanoid biosynthesis. Furthermore, a set of 3,016 genes functioning in energy supply and cell repair or formation was activated in sesame recovery from waterlogging stress. A comparative analysis between sesame of the tolerant and susceptible genotypes revealed 66 genes that may be candidates for improving sesame tolerance to waterlogging. This study provided a comprehensive picture of the sesame gene expression pattern in response to waterlogging stress. These results will help dissect the mechanism of the sesame response to waterlogging and identify candidate genes to improve its tolerance.

Heavy Metal Tolerance in Plants: Role of Transcriptomics, Proteomics, Metabolomics, and Ionomics

Heavy metal contamination of soil and water causing toxicity/stress has become one important constraint to crop productivity and quality. This situation has further worsened by the increasing population growth and inherent food demand. It has been reported in several studies that counterbalancing toxicity due to heavy metal requires complex mechanisms at molecular, biochemical, physiological, cellular, tissue, and whole plant level, which might manifest in terms of improved crop productivity. Recent advances in various disciplines of biological sciences such as metabolomics, transcriptomics, proteomics, etc., have assisted in the characterization of metabolites, transcription factors, and stress-inducible proteins involved in heavy metal tolerance, which in turn can be utilized for generating heavy metal-tolerant crops. This review summarizes various tolerance strategies of plants under heavy metal toxicity covering the role of metabolites (metabolomics), trace elements (ionomics), transcription factors (transcriptomics), various stress-inducible proteins (proteomics) as well as the role of plant hormones. We also provide a glance of some strategies adopted by metal-accumulating plants, also known as "metallophytes."

Microarray Analysis of Rice d1 (RGA1) Mutant Reveals the Potential Role of G-Protein Alpha Subunit in Regulating Multiple Abiotic Stresses Such as Drought, Salinity, Heat, and Cold

The genome-wide role of heterotrimeric G-proteins in abiotic stress response in rice has not been examined from a functional genomics perspective, despite the availability of mutants and evidences involving individual genes/processes/stresses. Our rice whole transcriptome microarray analysis (GSE 20925 at NCBI GEO) using the G-alpha subunit (RGA1) null mutant (Daikoku 1 or d1) and its corresponding wild type (Oryza sativa Japonica Nipponbare) identified 2270 unique differentially expressed genes (DEGs). Out of them, we mined for all the potentially abiotic stress-responsive genes using Gene Ontology terms, STIFDB2.0 and Rice DB. The first two approaches produced smaller subsets of the 1886 genes found at Rice DB. The GO approach revealed similar regulation of several families of stress-responsive genes in RGA1 mutant. The Genevestigator analysis of the stress-responsive subset of the RGA1-regulated genes from STIFDB revealed cold and drought-responsive clusters. Meta data analysis at Rice DB revealed large stress-response categories such as cold (878 up/810 down), drought (882 up/837 down), heat (913 up/777 down), and salt stress (889 up/841 down). One thousand four hundred ninety-eight of them are common to all the four abiotic stresses, followed by fewer genes common to smaller groups of stresses. The RGA1-regulated genes that uniquely respond to individual stresses include 111 in heat stress, eight each in cold only and drought only stresses, and two genes in salt stress only. The common DEGs (1498) belong to pathways such as the synthesis of polyamine, glycine-betaine, proline, and trehalose. Some of the common DEGs belong to abiotic stress signaling pathways such as calcium-dependent pathway, ABA independent and dependent pathway, and MAP kinase pathway in the RGA1 mutant. Gene ontology of the common stress responsive DEGs revealed 62 unique molecular functions such as transporters, enzyme regulators, transferases, hydrolases, carbon and protein metabolism, binding to nucleotides, carbohydrates, receptors and lipids, morphogenesis, flower development, and cell homeostasis. We also mined 63 miRNAs that bind to the stress responsive transcripts identified in this study, indicating their post-transcriptional regulation. Overall, these results indicate the potentially extensive role of RGA1 in the regulation of multiple abiotic stresses in rice for further validation.