Meta-Analysis of Quantitative Traits Loci (QTL) Identified in Drought Response in Rice (Oryza sativa L.)

Transcriptional networks revealed late embryogenesis abundant genes regulating drought mitigation in aromatic Keteki Joha rice

Climate change has become increasingly intertwined with the occurrence and severity of droughts. As global temperatures rise due to greenhouse gas emissions, weather patterns are altered, leading to shifts in precipitation levels and distribution. These exacerbate the risk of drought in many regions, with potentially devastating consequences. A comprehensive transcriptome analysis was performed on Keteki Joha, an aromatic rice from North East India, with the aim of elucidating molecular responses to drought. Numerous genes linked to drought were activated, with both ABA-dependent and ABA-independent pathways playing crucial roles. Upregulated genes were enriched with gene ontology terms with response to abscisic acid and abscisic acid-activated signalling pathway, suggesting the existence of an ABA-dependent pathway for drought mitigation. The upregulated genes were also enriched with responses to stress, water, heat, jasmonic acid, and hydrogen peroxide, indicating the presence of an ABA-independent pathway alongside the ABA-dependent mechanism. Weighted Correlation Network Analysis (WGCNA) identified 267 genes that specifically govern drought mitigation in Keteki Joha. The late embryogenesis abundant (LEA) gene family emerges as the most overrepresented in both RNA sequencing data and WGCNA analysis, suggesting their dominant role in mitigating drought. Notably, 31 LEA genes were induced in seedlings and 32 in mature stages under drought stress. The LEA3-1, LEA14/WSI18, RAB16A, RAB16B, DHN1, DHN6, LEA1, LEA3, LEA17, and LEA33 exhibited and established co-expression with numerous other drought stress-related genes, indicating their inseparable role in alleviating drought. Consequently, LEA genes have been proposed to be primary and crucial responders to drought in Keteki Joha.

Integrated meta-analysis and transcriptomics pinpoint genomic loci and novel candidate genes associated with submergence tolerance in rice

BACKGROUND

Due to rising costs, water shortages, and labour shortages, farmers across the globe now prefer a direct seeding approach. However, submergence stress remains a major bottleneck limiting the success of this approach in rice cultivation. The merger of accumulated rice genetic resources provides an opportunity to detect key genomic loci and candidate genes that influence the flooding tolerance of rice.

RESULTS

In the present study, a whole-genome meta-analysis was conducted on 120 quantitative trait loci (QTL) obtained from 16 independent QTL studies reported from 2004 to 2023. These QTL were confined to 18 meta-QTL (MQTL), and ten MQTL were successfully validated by independent genome-wide association studies from diverse natural populations. The mean confidence interval (CI) of the identified MQTL was 3.44 times narrower than the mean CI of the initial QTL. Moreover, four core MQTL loci with genetic distance less than 2 cM were obtained. By combining differentially expressed genes (DEG) from two transcriptome datasets with 858 candidate genes identified in the core MQTL regions, we found 38 common differentially expressed candidate genes (DECGs). In silico expression analysis of these DECGs led to the identification of 21 genes with high expression in embryo and coleoptile under submerged conditions. These DECGs encode proteins with known functions involved in submergence tolerance including WRKY, F-box, zinc fingers, glycosyltransferase, protein kinase, cytochrome P450, PP2C, hypoxia-responsive family, and DUF domain. By haplotype analysis, the 21 DECGs demonstrated distinct genetic differentiation and substantial genetic distance mainly between indica and japonica subspecies. Further, the MQTL7.1 was successfully validated using flanked marker S2329 on a set of genotypes with phenotypic variation.

CONCLUSION

This study provides a new perspective on understanding the genetic basis of submergence tolerance in rice. The identified MQTL and novel candidate genes lay the foundation for marker-assisted breeding/engineering of flooding-tolerant cultivars conducive to direct seeding.

Detection of consensus genomic regions and candidate genes for quality traits in barley using QTL meta-analysis

Improving barley grain quality is a major goal in barley breeding. In this study, a total of 35 papers focusing on quantitative trait loci (QTLs) mapping for barley quality traits published since 2000 were collected. Among the 454 QTLs identified in these studies, 349 of them were mapped onto high-density consensus maps, which were used for QTL meta-analysis. Through QTL meta-analysis, the initial QTLs were integrated into 41 meta-QTLs (MQTLs) with an average confidence interval (CI) of 1. 66 cM, which is 88.9% narrower than that of the initial QTLs. Among the 41 identified MQTLs, 25 were subsequently validated in publications using genome-wide association study (GWAS). From these 25 validated MQTLs, ten breeder's MQTLs were selected. Synteny analysis comparing barley and wheat MQTLs revealed orthologous relationships between eight breeder's MQTLs and 45 wheat MQTLs. Additionally, 17 barley homologs associated with rice quality traits were identified within the regions of the breeder's MQTLs through comparative analysis. The findings of this study provide valuable insights for molecular marker-assisted breeding and the identification of candidate genes related to quality traits in barley.

Meta-QTL s and haplotypes for efficient zinc biofortification of rice

Biofortification of rice with improved grain zinc (Zn) content is the most sustainable and cost-effective approach to address Zn malnutrition in Asia. Genomics-assisted breeding using precise and consistent Zn quantitative trait loci (QTLs), genes, and haplotypes can fast-track the development of Zn biofortified rice varieties. We conducted the meta-analysis of 155 Zn QTLs reported from 26 different studies. Results revealed 57 meta-QTLs with a significant reduction of 63.2% and 80% in the number and confidence interval of the Zn QTLs, respectively. Meta-quantitative trait loci (MQTLs) regions were found to be enriched with diverse metal homeostasis genes; at least 11 MQTLs were colocated with 20 known major genes involved in the production of root exudates, metal uptake, transport, partitioning, and loading into grains in rice. These genes were differentially expressed in vegetative and reproductive tissues, and a complex web of interactions were observed among them. We identified superior haplotypes and their combinations for nine candidate genes (CGs), and the frequency and allelic effects of superior haplotypes varied in different subgroups. The precise MQTLs with high phenotypic variance, CGs, and superior haplotypes identified in our study are useful for an efficient Zn biofortification of rice and to ensure Zn as an essential component of all the future rice varieties through mainstreaming of Zn breeding.

A meta-QTL analysis highlights genomic hotspots associated with phosphorus use efficiency in rice (Oryza sativa L.)

Phosphorus use efficiency (PUE) is a complex trait, governed by many minor quantitative trait loci (QTLs) with small effects. Advances in molecular marker technology have led to the identification of QTLs underlying PUE. However, their practical use in breeding programs remains challenging due to the unstable effects in different genetic backgrounds and environments, interaction with soil status, and linkage drag. Here, we compiled PUE QTL information from 16 independent studies. A total of 192 QTLs were subjected to meta-QTL (MQTL) analysis and were projected into a high-density SNP consensus map. A total of 60 MQTLs, with significantly reduced number of initial QTLs and confidence intervals (CI), were identified across the rice genome. Candidate gene (CG) mining was carried out for the 38 MQTLs supported by multiple QTLs from at least two independent studies. Genes related to amino and organic acid transport and auxin response were found to be abundant in the MQTLs linked to PUE. CGs were cross validated using a root transcriptome database (RiceXPro) and haplotype analysis. This led to the identification of the eight CGs (OsARF8, OsSPX-MFS3, OsRING141, OsMIOX, HsfC2b, OsFER2, OsWRKY64, and OsYUCCA11) modulating PUE. Potential donors for superior PUE CG haplotypes were identified through haplotype analysis. The distribution of superior haplotypes varied among subspecies being mostly found in indica but were largely scarce in japonica. Our study offers an insight on the complex genetic networks that modulate PUE in rice. The MQTLs, CGs, and superior CG haplotypes identified in our study are useful in the combination of beneficial alleles for PUE in rice.

Multi-Omics Pipeline and Omics-Integration Approach to Decipher Plant's Abiotic Stress Tolerance Responses

The present day's ongoing global warming and climate change adversely affect plants through imposing environmental (abiotic) stresses and disease pressure. The major abiotic factors such as drought, heat, cold, salinity, etc., hamper a plant's innate growth and development, resulting in reduced yield and quality, with the possibility of undesired traits. In the 21st century, the advent of high-throughput sequencing tools, state-of-the-art biotechnological techniques and bioinformatic analyzing pipelines led to the easy characterization of plant traits for abiotic stress response and tolerance mechanisms by applying the 'omics' toolbox. Panomics pipeline including genomics, transcriptomics, proteomics, metabolomics, epigenomics, proteogenomics, interactomics, ionomics, phenomics, etc., have become very handy nowadays. This is important to produce climate-smart future crops with a proper understanding of the molecular mechanisms of abiotic stress responses by the plant's genes, transcripts, proteins, epigenome, cellular metabolic circuits and resultant phenotype. Instead of mono-omics, two or more (hence 'multi-omics') integrated-omics approaches can decipher the plant's abiotic stress tolerance response very well. Multi-omics-characterized plants can be used as potent genetic resources to incorporate into the future breeding program. For the practical utility of crop improvement, multi-omics approaches for particular abiotic stress tolerance can be combined with genome-assisted breeding (GAB) by being pyramided with improved crop yield, food quality and associated agronomic traits and can open a new era of omics-assisted breeding. Thus, multi-omics pipelines together are able to decipher molecular processes, biomarkers, targets for genetic engineering, regulatory networks and precision agriculture solutions for a crop's variable abiotic stress tolerance to ensure food security under changing environmental circumstances.

Plant Tolerance to Drought Stress with Emphasis on Wheat

Environmental stresses, such as drought, have negative effects on crop yield. Drought is a stress whose impact tends to increase in some critical regions. However, the worldwide population is continuously increasing and climate change may affect its food supply in the upcoming years. Therefore, there is an ongoing effort to understand the molecular processes that may contribute to improving drought tolerance of strategic crops. These investigations should contribute to delivering drought-tolerant cultivars by selective breeding. For this reason, it is worthwhile to review regularly the literature concerning the molecular mechanisms and technologies that could facilitate gene pyramiding for drought tolerance. This review summarizes achievements obtained using QTL mapping, genomics, synteny, epigenetics, and transgenics for the selective breeding of drought-tolerant wheat cultivars. Synthetic apomixis combined with the msh1 mutation opens the way to induce and stabilize epigenomes in crops, which offers the potential of accelerating selective breeding for drought tolerance in arid and semi-arid regions.

Identification of Drought Tolerant Rice (Oryza Sativa L.) Genotypes with Asian and African Backgrounds

Drought is among the major abiotic stresses on rice production that can cause yield losses of up to 100% under severe drought conditions. Neither of the rice varieties currently grown in Burundi can withstand very low and irregular precipitation. This study identified genotypes that have putative quantitative trait loci (QTLs) associated with drought tolerance and determined their performance in the field. Two hundred and fifteen genotypes were grown in the field under both drought and irrigated conditions. Genomic deoxyribonucleic acid (DNA) was extracted from rice leaves for further genotypic screening. The results revealed the presence of the QTLs qDTY12.1, qDTY3.1, qDTY2-2_1, and qDTY1.1 in 90%, 85%, 53%, and 22% of the evaluated genotypes, respectively. The results of the phenotypic evaluation showed a significant yield reduction due to drought stress. Yield components and other agronomic traits were also negatively affected by drought. Genotypes having high yield best linear unbiased predictions (BLUPs) with two or more major QTLs for drought tolerance, including IR 108044-B-B-B-3-B-B, IR 92522-45-3-1-4, and BRRI DHAN 55 are of great interest for breeding programs to improve the drought tolerance of lines or varieties with other preferred traits.

Deciphering key genomic regions controlling flag leaf size in wheat via integration of meta-QTL and in silico transcriptome assessment

BACKGROUND

Grain yield is a complex and polygenic trait influenced by the photosynthetic source-sink relationship in wheat. The top three leaves, especially the flag leaf, are considered the major sources of photo-assimilates accumulated in the grain. Determination of significant genomic regions and candidate genes affecting flag leaf size can be used in breeding for grain yield improvement.

RESULTS

With the final purpose of understanding key genomic regions for flag leaf size, a meta-analysis of 521 initial quantitative trait loci (QTLs) from 31 independent QTL mapping studies over the past decades was performed, where 333 loci eventually were refined into 64 meta-QTLs (MQTLs). The average confidence interval (CI) of these MQTLs was 5.28 times less than that of the initial QTLs. Thirty-three MQTLs overlapped the marker trait associations (MTAs) previously reported in genome-wide association studies (GWAS) for flag leaf traits in wheat. A total of 2262 candidate genes for flag leaf size, which were involved in the peroxisome, basal transcription factor, and tyrosine metabolism pathways were identified in MQTL regions by the in silico transcriptome assessment. Of these, the expression analysis of the available genes revealed that 134 genes with > 2 transcripts per million (TPM) were highly and specifically expressed in the leaf. These candidate genes could be critical to affect flag leaf size in wheat.

CONCLUSIONS

The findings will make further insight into the genetic determinants of flag leaf size and provide some reliable MQTLs and putative candidate genes for the genetic improvement of flag leaf size in wheat.

QTL and Candidate Genes: Techniques and Advancement in Abiotic Stress Resistance Breeding of Major Cereals

At least 75% of the world's grain production comes from the three most important cereal crops: rice (Oryza sativa), wheat (Triticum aestivum), and maize (Zea mays). However, abiotic stressors such as heavy metal toxicity, salinity, low temperatures, and drought are all significant hazards to the growth and development of these grains. Quantitative trait locus (QTL) discovery and mapping have enhanced agricultural production and output by enabling plant breeders to better comprehend abiotic stress tolerance processes in cereals. Molecular markers and stable QTL are important for molecular breeding and candidate gene discovery, which may be utilized in transgenic or molecular introgression. Researchers can now study synteny between rice, maize, and wheat to gain a better understanding of the relationships between the QTL or genes that are important for a particular stress adaptation and phenotypic improvement in these cereals from analyzing reports on QTL and candidate genes. An overview of constitutive QTL, adaptive QTL, and significant stable multi-environment and multi-trait QTL is provided in this article as a solid framework for use and knowledge in genetic enhancement. Several QTL, such as DRO1 and Saltol, and other significant success cases are discussed in this review. We have highlighted techniques and advancements for abiotic stress tolerance breeding programs in cereals, the challenges encountered in introgressing beneficial QTL using traditional breeding techniques such as mutation breeding and marker-assisted selection (MAS), and the in roads made by new breeding methods such as genome-wide association studies (GWASs), the clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 system, and meta-QTL (MQTL) analysis. A combination of these conventional and modern breeding approaches can be used to apply the QTL and candidate gene information in genetic improvement of cereals against abiotic stresses.

Heterologous expression of the TaPI-PLC1-2B gene enhanced drought and salt tolerance in transgenic rice seedlings

Drought and salt stress are important factors that affect plant growth and development and cause crop yield reductions worldwide. Phospholipase C is a class of enzymes that can hydrolyze phospholipids, and it has been shown to play an important role in plant growth regulation and stress response. We used rice as a model to investigate the function of the wheat TaPI-PLC1-2B gene in salt and drought tolerance. For this purpose, we heterologously expressed the TaPI-PLC1-2B gene in rice and studied the transcriptional differences in transgenic and wide-type rice plants in the presence and absence of drought and salt stress. Our results showed that 2130 and 1759 genes expressed differentially in the TaPI-PLC1-2B overexpression rice line under salt and drought stress, respectively. Gene ontology enrichment results showed that differentially expressed genes (DEGs) were significantly enriched in cellular process, metabolic process, stimulus-response, cell, organelle, catalytic activity, and other functional processes under salt and drought stress. In addition, the Kyoto Encyclopedia of Genes and Genomes pathway analysis showed DEG enrichment in plant-pathogen interaction, phosphoinositol, plant hormones, and other signaling pathways under the two stress treatments. Furthermore, the chromosomal localization of salt and drought stress-responsive DEGs showed a clear distribution pattern on specific rice chromosomes. For instance, the greatest number of drought stress-responsive genes mapped to rice chromosomes 1 and 6. The current analysis has built the basis for future explorations to decipher the TaPI-PLC1-2B-mediated plant stress response mechanism in the relatively challenging wheat system.

Pleiotropic effects of recombinant protease inhibitors in plants

Recombinant gene encoded protease inhibitors have been identified as some of the most effective antidigestive molecules to guard against proteolysis of essential proteins and plant attacking proteases from herbivorous pests and pathogenic microorganisms. Protease inhibitors (PIs) can be over expressed in transgenic plants to complement internal host defense systems, Bt toxins in genetically modified pest resistance and abiotic stress tolerance achieved through cystatins expression. Although the understanding of the role of proteolytic enzymes and their inhibitors encoded by both endogenous and transgenes expressed in crop plants has significantly advanced, their implication in biological systems still requires further elucidations. This paper, therefore, succinctly reviewed most recently published literature on recombinant proteases inhibitors (RPIs), focusing mainly on their unintended consequences in plants, other living organisms, and the environment. The review discusses major negative and unintended effects of RPIs involving the inhibitors' non-specificity on protease enzymes, non-target organisms and ubiquitous versatility in their mechanism of inhibition. The paper also discusses some direct and indirect effects of RPIs such as degradation by distinct classes of proteases, reduced functionality due to plant exposure to severe environmental stress and any other potential negative influences exerted on both the host plant as well as the environment. These pleiotropic effects must be decisively monitored to eliminate and prevent any potential adverse effects that transgenic plants carrying recombinant inhibitor genes may have on non-target organisms and biodiversity.

Consensus genomic regions associated with multiple abiotic stress tolerance in wheat and implications for wheat breeding

In wheat, a meta-analysis was performed using previously identified QTLs associated with drought stress (DS), heat stress (HS), salinity stress (SS), water-logging stress (WS), pre-harvest sprouting (PHS), and aluminium stress (AS) which predicted a total of 134 meta-QTLs (MQTLs) that involved at least 28 consistent and stable MQTLs conferring tolerance to five or all six abiotic stresses under study. Seventy-six MQTLs out of the 132 physically anchored MQTLs were also verified with genome-wide association studies. Around 43% of MQTLs had genetic and physical confidence intervals of less than 1 cM and 5 Mb, respectively. Consequently, 539 genes were identified in some selected MQTLs providing tolerance to 5 or all 6 abiotic stresses. Comparative analysis of genes underlying MQTLs with four RNA-seq based transcriptomic datasets unravelled a total of 189 differentially expressed genes which also included at least 11 most promising candidate genes common among different datasets. The promoter analysis showed that the promoters of these genes include many stress responsiveness cis-regulatory elements, such as ARE, MBS, TC-rich repeats, As-1 element, STRE, LTR, WRE3, and WUN-motif among others. Further, some MQTLs also overlapped with as many as 34 known abiotic stress tolerance genes. In addition, numerous ortho-MQTLs among the wheat, maize, and rice genomes were discovered. These findings could help with fine mapping and gene cloning, as well as marker-assisted breeding for multiple abiotic stress tolerances in wheat.

Consensus genomic regions associated with multiple abiotic stress tolerance in wheat and implications for wheat breeding

In wheat, a meta-analysis was performed using previously identified QTLs associated with drought stress (DS), heat stress (HS), salinity stress (SS), water-logging stress (WS), pre-harvest sprouting (PHS), and aluminium stress (AS) which predicted a total of 134 meta-QTLs (MQTLs) that involved at least 28 consistent and stable MQTLs conferring tolerance to five or all six abiotic stresses under study. Seventy-six MQTLs out of the 132 physically anchored MQTLs were also verified with genome-wide association studies. Around 43% of MQTLs had genetic and physical confidence intervals of less than 1 cM and 5 Mb, respectively. Consequently, 539 genes were identified in some selected MQTLs providing tolerance to 5 or all 6 abiotic stresses. Comparative analysis of genes underlying MQTLs with four RNA-seq based transcriptomic datasets unravelled a total of 189 differentially expressed genes which also included at least 11 most promising candidate genes common among different datasets. The promoter analysis showed that the promoters of these genes include many stress responsiveness cis-regulatory elements, such as ARE, MBS, TC-rich repeats, As-1 element, STRE, LTR, WRE3, and WUN-motif among others. Further, some MQTLs also overlapped with as many as 34 known abiotic stress tolerance genes. In addition, numerous ortho-MQTLs among the wheat, maize, and rice genomes were discovered. These findings could help with fine mapping and gene cloning, as well as marker-assisted breeding for multiple abiotic stress tolerances in wheat.

Identification of key genes controlling L-ascorbic acid during Jujube (Ziziphus jujuba Mill.) fruit development by integrating transcriptome and metabolome analysis

Chinese jujube (Ziziphus jujuba) is a vital economic tree native to China. Jujube fruit with abundant L-Ascorbic Acid (AsA) is an ideal material for studying the mechanism of AsA biosynthesis and metabolism. However, the key transcription factors regulating AsA anabolism in jujube have not been reported. Here, we used jujube variety "Mazao" as the experimental material, conducted an integrative analysis of transcriptome and metabolome to investigate changes in differential genes and metabolites, and find the key genes regulating AsA during jujube fruit growth. The results showed that AsA was mostly synthesized in the young stage and enlargement stage, ZjMDHAR gene takes an important part in the AsA recycling. Three gene networks/modules were highly correlated with AsA, among them, three genes were identified as candidates controlling AsA, including ZjERF17 (LOC107404975), ZjbZIP9 (LOC107406320), and ZjGBF4 (LOC107421670). These results provide new directions and insights for further study on the regulation mechanism of AsA in jujube.

Meta-analysis of QTLs and candidate genes associated with seed germination in rice (Oryza sativa L.)

Seed germination is one of the critical stages of plant life, and many quantitative trait loci (QTLs) control this complex trait. Meta-analysis of QTLs is a powerful computational technique for estimating the most stable QTLs regardless of the population's genetic background. Besides, this analysis effectively narrows down the confidence interval (CI) to identify candidate genes (CGs) and marker development. In the current study, a comprehensive genome-wide meta-analysis was performed on QTLs associated with germination in rice. This analysis was conducted based on the data reported over the last two decades. In this case, various analyses were performed, including seed germination rate, plumule length, radicle length, germination percentage, coleoptile length, coleorhiza length, radicle fresh weight, germination potential, and germination index. A total of 67 QTLs were projected onto a reference map for these traits and then integrated into 32 meta-QTLs (MQTLs) to provide a genetic framework for seed germination. The average CI of MQTLs was considerably reduced from 15.125 to 8.73 cM compared to the initial QTLs. This situation identified 728 well-known functionally characterized genes and novel putative CGs for investigated traits. The fold change calculation demonstrated that 155 CGs had significant changes in expression analysis. In this case, 112 and 43 CGs were up-regulated and down-regulated during germination, respectively. This study provides an overview and compares genetic loci controlling traits related to seed germination in rice. The findings can bridge the gap between QTLs and CGs for seed germination.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12298-022-01232-1.

Candidate Genes and Pathways in Rice Co-Responding to Drought and Salt Identified by gcHap Network

Drought and salinity stresses are significant abiotic factors that limit rice yield. Exploring the co-response mechanism to drought and salt stress will be conducive to future rice breeding. A total of 1748 drought and salt co-responsive genes were screened, most of which are enriched in plant hormone signal transduction, protein processing in the endoplasmic reticulum, and the MAPK signaling pathways. We performed gene-coding sequence haplotype (gcHap) network analysis on nine important genes out of the total amount, which showed significant differences between the Xian/indica and Geng/japonica population. These genes were combined with related pathways, resulting in an interesting mechanistic draft called the ‘gcHap-network pathway’. Meanwhile, we collected a lot of drought and salt breeding varieties, especially the introgression lines (ILs) with HHZ as the parent, which contained the above-mentioned nine genes. This might imply that these ILs have the potential to improve the tolerance to drought and salt. In this paper, we focus on the relationship of drought and salt co-response gene gcHaps and their related pathways using a novel angle. The haplotype network will be helpful to explore the desired haplotypes that can be implemented in haplotype-based breeding programs.

Favorable QTLs from Oryza longistaminata improve rice drought resistance

BACKGROUND

Drought is the major abiotic stress to rice grain production under unpredictable changing climatic environments. Wild rice of O. longistaminata show diverse responses and strong tolerance to stress environments. In order to identify whether the O. longistaminata can improve the rice drought resistance or not, a BIL population of 143 BC₂F₂₀ lines derived from the cross between the cultivar rice 9311 and O. longistaminata were assessed under stress of 20% PEG6000.

RESULTS

In total, 28 QTLs related to drought resistance based on eight agronomic traits of seedlings were identified. Of which, thirteen QTLs including two QTLs for leaf drying, one QTL for leaf rolling, one QTL for leaf number, five QTLs for dry weight of root, two QTLs for dry weight of shoot, one QTL for maximum root length and two QTLs for maximum shoot length were derived from O. longistaminata. What's more, qDWR8.1 for dry weight of root was repeatedly detected and fine-mapped to an interval about 36.2 Kb. The unique allele of MH08g0242800 annotated as ATP-dependent Clp protease proteolytic subunit from O. longistaminata was suggested as the candidate gene for drought resistance. Further, six representative BIL lines were stably characterized showing significantly stronger drought resistance than 9311 based on principle component analysis, they each contained 2 ~ 5 QTLs including qDWR8.1 from O. longistaminata.

CONCLUSIONS

Together, our results indicate that the QTLs from O. longistaminata can effectively enhance the drought tolerance of rice, showing great potential value in breeding of elite rice varieties, which will lay a novel insight into the genetic network for drought tolerance of rice.

Meta-QTLs, ortho-meta-QTLs and candidate genes for grain yield and associated traits in wheat (Triticum aestivum L.)

In wheat, 2852 major QTLs of 8998 QTLs available for yield and related traits were used for meta-analysis; 141 meta-QTLs were identified, which included 13 breeder's MQTLs and 24 ortho-MQTLs; 1202 candidate genes and 50 homologues of genes for yield from other cereals were also identified. Meta-QTL analysis was conducted using 2852 of the 8998 known QTLs, retrieved from 230 reports published during 1999-2020 (including 19 studies on tetraploid wheat) for grain yield (GY) and the following ten component traits: (i) grain weight (GWei), (ii) grain morphology-related traits (GMRTs), (iii) grain number (GN), (iv) spikes-related traits (SRTs), (v) plant height (PH), (vi) tiller number (TN), (vii) harvest index (HI), (viii) biomass yield (BY), (ix) days to heading/flowering and maturity (DTH/F/M), and (x) grain filling duration (GFD). The study resulted in the identification of 141 meta-QTLs (MQTLs), with an average confidence interval (CI) of 1.4 cM as against a CI of > 12.1 cM (8.8 fold reduction) in the QTLs that were used. The corresponding physical length of CI ranged from 0.01 Mb to 661.9 Mb (mean, 31.5 Mb). Seventy-seven (77) of these 141 MQTLs overlapped marker-trait associations (MTAs) reported in genome-wide association studies. Also, 63 MQTLs (each based on at least 10 QTLs) were considered stable and robust, with 13 MQTLs described as breeder's MQTLs (selected based on small CI, large LOD, and high level of phenotypic variation explained). Thirty-five yield-related genes from rice, barley, and maize were also utilized to identify 50 wheat homologues in MQTLs. Further, the use of synteny and collinearity allowed the identification of 24 ortho-MQTLs which were common among the wheat, barley, rice, and maize. The results of the present study should prove useful for wheat breeding and future basic research in cereals including wheat, barley, rice, and maize.

Omics-Facilitated Crop Improvement for Climate Resilience and Superior Nutritive Value

Novel crop improvement approaches, including those that facilitate for the exploitation of crop wild relatives and underutilized species harboring the much-needed natural allelic variation are indispensable if we are to develop climate-smart crops with enhanced abiotic and biotic stress tolerance, higher nutritive value, and superior traits of agronomic importance. Top among these approaches are the "omics" technologies, including genomics, transcriptomics, proteomics, metabolomics, phenomics, and their integration, whose deployment has been vital in revealing several key genes, proteins and metabolic pathways underlying numerous traits of agronomic importance, and aiding marker-assisted breeding in major crop species. Here, citing several relevant examples, we appraise our understanding on the recent developments in omics technologies and how they are driving our quest to breed climate resilient crops. Large-scale genome resequencing, pan-genomes and genome-wide association studies are aiding the identification and analysis of species-level genome variations, whilst RNA-sequencing driven transcriptomics has provided unprecedented opportunities for conducting crop abiotic and biotic stress response studies. Meanwhile, single cell transcriptomics is slowly becoming an indispensable tool for decoding cell-specific stress responses, although several technical and experimental design challenges still need to be resolved. Additionally, the refinement of the conventional techniques and advent of modern, high-resolution proteomics technologies necessitated a gradual shift from the general descriptive studies of plant protein abundances to large scale analysis of protein-metabolite interactions. Especially, metabolomics is currently receiving special attention, owing to the role metabolites play as metabolic intermediates and close links to the phenotypic expression. Further, high throughput phenomics applications are driving the targeting of new research domains such as root system architecture analysis, and exploration of plant root-associated microbes for improved crop health and climate resilience. Overall, coupling these multi-omics technologies to modern plant breeding and genetic engineering methods ensures an all-encompassing approach to developing nutritionally-rich and climate-smart crops whose productivity can sustainably and sufficiently meet the current and future food, nutrition and energy demands.