Meta-QTL analysis in wheat: progress, challenges and opportunities.

Wheat, an important cereal crop globally, faces major challenges due to increasing global population and changing climates. The production and productivity are challenged by several biotic and abiotic stresses. There is also a pressing demand to enhance grain yield and quality/nutrition to ensure global food and nutritional security. To address these multifaceted concerns, researchers have conducted numerous meta-QTL (MQTL) studies in wheat, resulting in the identification of candidate genes that govern these complex quantitative traits. MQTL analysis has successfully unraveled the complex genetic architecture of polygenic quantitative traits in wheat. Candidate genes associated with stress adaptation have been pinpointed for abiotic and biotic traits, facilitating targeted breeding efforts to enhance stress tolerance. Furthermore, high-confidence candidate genes (CGs) and flanking markers to MQTLs will help in marker-assisted breeding programs aimed at enhancing stress tolerance, yield, quality and nutrition. Functional analysis of these CGs can enhance our understanding of intricate trait-related genetics. The discovery of orthologous MQTLs shared between wheat and other crops sheds light on common evolutionary pathways governing these traits. Breeders can leverage the most promising MQTLs and CGs associated with multiple traits to develop superior next-generation wheat cultivars with improved trait performance. This review provides a comprehensive overview of MQTL analysis in wheat, highlighting progress, challenges, validation methods and future opportunities in wheat genetics and breeding, contributing to global food security and sustainable agriculture.

Genome-wide association mapping reveals key genomic regions for physiological and yield-related traits under salinity stress in wheat (Triticum aestivum L.).

A genome-wide association study (GWAS) was conducted using six different multi-locus GWAS models and 35K SNP array to demarcate genomic regions underlying reproductive stage salinity tolerance. Marker-trait association analysis was performed for salt tolerance indices (STI) of 11 morpho-physiological traits, and the actual concentrations of Na+ and K+, and the Na+/K+ ratio in flag leaf. A total of 293 significantly associated quantitative trait nucleotides (QTNs) for 14 morpho-physiological traits were identified. Of these 293 QTNs, 12 major QTNs with R2 ≥ 10.0% were detected in three or more GWAS models. Novel major QTNs were identified for plant height, number of effective tillers, biomass, grain yield, thousand grain weight, Na+ and K+ content, and the Na+/K+ ratio in flag leaf. Moreover, 48 candidate genes were identified from the associated genomic regions. The QTNs identified in this study could potentially be targeted for improving salinity tolerance in wheat.

Identification and evolutionary analysis of polycistronic miRNA clusters in domesticated and wild wheat.

MicroRNAs are ~22 nucleotide long non-coding RNAs that regulate gene expression at posttranscriptional level. Genome-wide analysis was performed to identify polycistronic miRNAs from wheat. Total 89 polycistronic miRNAs were identified in bread wheat which were distributed on three component sub-genomes (A = 26, B = 33 and D = 30). Except some, most of the identified polycistronic miRNAs were also present in other cultivated and wild wheat species. Expression of 11 identified polycistronic miRNAs could be validated using previously assembled transcriptomes, RNA-seq/s-RNA seq data of cultivated and wild wheats and RT-PCR. Polycistronic miRNAs orthologs were also localized on rice and Brachypodium genomes. As a case study, we also analyzed molecular evolution of miR395 family polycistrons in wheat. Both tandem and segmental duplications contributed to expansion of miR395 family polycistrons. Our findings provide a comprehensive view on wheat polycitronic miRNAs that will enable their in-depth functional analysis in the future.

Genetic Dissection of Seedling Root System Architectural Traits in a Diverse Panel of Hexaploid Wheat through Multi-Locus Genome-Wide Association Mapping for Improving Drought Tolerance.

Cultivars with efficient root systems play a major role in enhancing resource use efficiency, particularly water absorption, and thus in drought tolerance. In this study, a diverse wheat association panel of 136 wheat accessions including mini core subset was genotyped using Axiom 35k Breeders' Array to identify genomic regions associated with seedling stage root architecture and shoot traits using multi-locus genome-wide association studies (ML-GWAS). The association panel revealed a wide variation of 1.5- to 50-fold and were grouped into six clusters based on 15 traits. Six different ML-GWAS models revealed 456 significant quantitative trait nucleotides (QTNs) for various traits with phenotypic variance in the range of 0.12-38.60%. Of these, 87 QTNs were repeatedly detected by two or more models and were considered reliable genomic regions for the respective traits. Among these QTNs, eleven were associated with average diameter and nine each for second order lateral root number (SOLRN), root volume (RV) and root length density (RLD). A total of eleven genomic regions were pleiotropic and each controlled two or three traits. Some important candidate genes such as Formin homology 1, Ubiquitin-like domain superfamily and ATP-dependent 6-phosphofructokinase were identified from the associated genomic regions. The genomic regions/genes identified in this study could potentially be targeted for improving root traits and drought tolerance in wheat.

Identification, analysis and development of salt responsive candidate gene based SSR markers in wheat.

BACKGROUND: Salinity severely limits wheat production in many parts of the world. Development of salt tolerant varieties represents the most practical option for enhancing wheat production from these areas. Application of marker assisted selection may assist in fast tracking development of salt tolerant wheat varieties. However, SSR markers available in the public domain are not specifically targeted to functional regions of wheat genome, therefore large numbers of these need to be analysed for identification of markers associated with traits of interest. With the availability of a fully annotated wheat genome assembly, it is possible to develop SSR markers specifically targeted to genic regions. We performed extensive analysis to identify candidate gene based SSRs and assessed their utility in characterizing molecular diversity in a panel of wheat genotypes. RESULTS: Our analysis revealed, 161 SSR motifs in 94 salt tolerance candidate genes of wheat. These SSR motifs were nearly equally distributed on the three wheat sub-genomes; 29.8% in A, 35.7% in B and 34.4% in D sub-genome. The maximum number of SSR motifs was present in exons (31.1%) followed by promoters (29.8%), 5'UTRs (21.1%), introns (14.3%) and 3'UTRs (3.7%). Out of the 65 candidate gene based SSR markers selected for validation, 30 were found polymorphic based on initial screening and employed for characterizing genetic diversity in a panel of wheat genotypes including salt tolerant and susceptible lines. These markers generated an average of 2.83 alleles/locus. Phylogenetic analysis revealed four clusters. Salt susceptible genotypes were mainly represented in clusters I and III, whereas high and moderate salt tolerant genotypes were distributed in the remaining two clusters. Population structure analysis revealed two sub-populations, sub-population 1 contained the majority of salt tolerant whereas sub-population 2 contained majority of susceptible genotypes. Moreover, we observed reasonably higher transferability of SSR markers to related wheat species. CONCLUSION: We have developed salt responsive gene based SSRs in wheat for the first time. These were highly useful in unravelling functional diversity among wheat genotypes with varying responses to salt stress. The identified gene based SSR markers will be valuable genomic resources for genetic/association mapping of salinity tolerance in wheat.

Identification of Climate-Smart Bread Wheat Germplasm Lines with Enhanced Adaptation to Global Warming.

Bread wheat (Triticum aestivum L.) is widely grown in sub-tropical and tropical areas and, as such, it is exposed to heatstress especially during the grain filling period (GFP). Global warming has further affected its production and productivity in these heat-stressed environments. We examined the effects of heatstress on 18 morpho-physiological and yield-related traits in 96 bread wheat accessions. Heat stress decreased crop growth and GFP, and consequently reduced morphological and yield-related traits in the delayed sown crop. A low heat susceptibility index and high yield stability were used for selecting tolerant accessions. Under heatstress, the days to 50% anthesis, flag-leaf area, chlorophyll content, normalized difference vegetation index (NDVI), thousand grain weight (TGW), harvest index and grain yield were significantly reduced both in tolerant and susceptible accessions. The reduction was severe in susceptible accessions (48.2% grain yield reduction in IC277741). The plant height, peduncle length and spike length showeda significant reduction in susceptible accessions, but a non-significant reduction in the tolerant accessions under the heatstress. The physiological traits like the canopy temperature depression (CTD), plant waxiness and leaf rolling were increased in tolerant accessions under heatstress. Scanning electron microscopy of matured wheat grains revealed ultrastructural changes in endosperm and aleurone cells due to heat stress. The reduction in size and density of large starch granules is the major cause of the yield and TGW decrease in the heat-stress-susceptible accessions. The most stable and high-yielding accessions, namely, IC566223, IC128454, IC335792, EC576707, IC535176, IC529207, IC446713 and IC416019 were identified as the climate-smart germplasm lines. We selected germplasm lines possessing desirable traits as potential parents for the development of bi-parent and multi-parent mapping populations.

Population structure and genetic differentiation analyses reveal high level of diversity and allelic richness in crop wild relatives of AA genome species of rice (Oryza sativa L.) in India.

Crop wild relatives (CWRs) are vital sources of variation for genetic improvement, but their populations are few in genebanks, eroded in natural habitats and inadequately characterized. With a view to explore genetic diversity in CWRs of AA genome rice (Oryza sativa L.) species in India, we analyzed 96 accessions of 10 Oryza species by using 17 quantitative traits and 45 microsatellite markers. The morpho-quantitative traits revealed a high extent of phenotypic variation in the germplasm. Diversity index (H') revealed a high level of within-species variability in O. nivara (H' = 1.09) and O. rufipogon (H' = 1.12). Principal component (PC) analysis explained 79.22% variance with five PCs. Among the traits related to phenology, morphology, and yield, days to heading showed strong positive association with days to 50% flowering (r = 0.99). However, filled grains per panicle revealed positive association with spikelet fertility (0.71) but negative with awn length (- 0.58) and panicle bearing tillers (- 0.39). Cluster analysis grouped all the accessions into three major clusters. Microsatellite analysis revealed 676 alleles with 15.02 alleles per locus. High polymorphism information content (PIC = 0.83) and Shannon's information index (I = 2.31) indicated a high level of genetic variation in the CWRs. Structure analysis revealed four subpopulations; first and second subpopulations comprised only of O. nivara accessions, while the third subpopulation included both O. nivara and O. rufipogon accessions. Population statistics revealed a moderate level of genetic differentiation (FST = 0.14), high gene diversity (HE = 0.87), and high gene flow (Nm = 1.53) among the subpopulations. We found a high level of molecular variance among the genotypes (70%) and low among populations (11%) and within genotypes (19%). The high level of molecular and morphological variability detected in the germplasm of CWRs could be utilized for the improvement of cultivated rice.

Association mapping reveals novel genes and genomic regions controlling grain size architecture in mini core accessions of Indian National Genebank wheat germplasm collection.

Wheat (Triticum aestivum L.) is a staple food crop for the global human population, and thus wheat breeders are consistently working to enhance its yield worldwide. In this study, we utilized a sub-set of Indian wheat mini core germplasm to underpin the genetic architecture for seed shape-associated traits. The wheat mini core subset (125 accessions) was genotyped using 35K SNP array and evaluated for grain shape traits such as grain length (GL), grain width (GW), grain length, width ratio (GLWR), and thousand grain weight (TGW) across the seven different environments (E1, E2, E3, E4, E5, E5, E6, and E7). Marker-trait associations were determined using a multi-locus random-SNP-effect Mixed Linear Model (mrMLM) program. A total of 160 non-redundant quantitative trait nucleotides (QTNs) were identified for four grain shape traits using two or more GWAS models. Among these 160 QTNs, 27, 36, 38, and 35 QTNs were associated for GL, GW, GLWR, and TGW respectively while 24 QTNs were associated with more than one trait. Of these 160 QTNs, 73 were detected in two or more environments and were considered reliable QTLs for the respective traits. A total of 135 associated QTNs were annotated and located within the genes, including ABC transporter, Cytochrome450, Thioredoxin_M-type, and hypothetical proteins. Furthermore, the expression pattern of annotated QTNs demonstrated that only 122 were differentially expressed, suggesting these could potentially be related to seed development. The genomic regions/candidate genes for grain size traits identified in the present study represent valuable genomic resources that can potentially be utilized in the markers-assisted breeding programs to develop high-yielding varieties.

Transcriptome Analysis of Bread Wheat Genotype KRL3-4 Provides a New Insight Into Regulatory Mechanisms Associated With Sodicity (High pH) Tolerance.

Globally, sodicity is one of the major abiotic stresses limiting the wheat productivity in arid and semi-arid regions. With due consideration, an investigation of the complex gene network associated with sodicity stress tolerance is required to identify transcriptional changes in plants during abiotic stress conditions. For this purpose, we sequenced the flag leaf transcriptome of a highly tolerant bread wheat germplasm (KRL 3-4) in order to extend our knowledge and better understanding of the molecular basis of sodicity tolerance. A total of 1,980 genes were differentially expressed in the flag leaf due to sodicity stress. Among these genes, 872 DEGs were upregulated and 1,108 were downregulated. Furthermore, annotation of DEGs revealed that a total of 1,384 genes were assigned to 2,267 GO terms corresponding to 502 (biological process), 638 (cellular component), and 1,127 (molecular function). GO annotation also revealed the involvement of genes related to several transcription factors; the important ones are expansins, peroxidase, glutathione-S-transferase, and metal ion transporters in response to sodicity. Additionally, from 127 KEGG pathways, only 40 were confidently enriched at a p-value <0.05 covering the five main KEGG categories of metabolism, i.e., environmental information processing, genetic information processing, organismal systems, and cellular processes. Most enriched pathways were prioritized using MapMan software and revealed that lipid metabolism, nutrient uptake, and protein homeostasis were paramount. We have also found 39 SNPs that mapped to the important sodicity stress-responsive genes associated with various pathways such as ROS scavenging, serine/threonine protein kinase, calcium signaling, and metal ion transporters. In a nutshell, only 19 important candidate genes contributing to sodicity tolerance in bread wheat were identified, and these genes might be helpful for better understanding and further improvement of sodicity tolerance in bread wheat.

Refinement of Draft Genome Assemblies of Pigeonpea (Cajanus cajan).

Genome assembly of short reads from large plant genomes remains a challenge in computational biology despite major developments in next generation sequencing. Of late several draft assemblies have been reported in sequenced plant genomes. The reported draft genome assemblies of Cajanus cajan have different levels of genome completeness, a large number of repeats, gaps, and segmental duplications. Draft assemblies with portions of genome missing are shorter than the referenced original genome. These assemblies come with low map accuracy affecting further functional annotation and the prediction of gene components as desired by crop researchers. Genome coverage, i.e., the number of sequenced raw reads mapped onto a certain location of the genome is an important quality indicator of completeness and assembly quality in draft assemblies. The present work aimed to improve the coverage in reported de novo sequenced draft genomes (GCA_000340665.1 and GCA_000230855.2) of pigeonpea, a legume widely cultivated in India. The two recently sequenced assemblies, A1 and A2 comprised 72% and 75% of the estimated coverage of the genome, respectively. We employed an assembly reconciliation approach to compare the draft assemblies and merge them, filling the gaps by employing an algorithm size sorting mate-pair library to generate a high quality and near complete assembly with enhanced contiguity. The majority of gaps present within scaffolds were filled with right-sized mate-pair reads. The improved assembly reduced the number of gaps than those reported in draft assemblies resulting in an improved genome coverage of 82.4%. Map accuracy of the improved assembly was evaluated using various quality metrics and for the presence of specific trait-related functional genes. Employed pair-end and mate-pair local libraries helped us to reduce gaps, repeats, and other sequence errors resulting in lengthier scaffolds compared to the two draft assemblies. We reported the prediction of putative host resistance genes against Fusarium wilt disease by their performance and evaluated them both in wet laboratory and field phenotypic conditions.

Comparative genomics in phytopathogenic prokaryotes reveals the higher relative abundance and density of long-SSRs in the smallest prokaryotic genome.

Frequency and distribution of long-SSRs were studied in 18 phytopathogenic prokaryotes. Higher relative abundance of the long-SSRs was observed in phytopathogenic prokaryotes when compared to non-pathogenic control. The frequency of these SSRs was positively correlated with size and GC content of the genomes of phytopathogenic prokaryotes. Interestingly, phytopathogens with higher GC content in the genome were found to posses longer repeat motifs of SSRs, whereas those having lesser GC content were harbouring shorter repeat motifs. Higher abundance of tri- and hexa-nucleotide repeat motifs were the characteristic of actinomycetes, where as higher abundance of mono- and tetra-nucleotide repeats were the characteristic of the mollicutes. The maximum relative abundance and relative density of SSR were found in the smallest genome of host-adapted pathogen Aster yellow, however, length of microsatellite repeat units was the least. On the basis of presence of SSRs in the housekeeping genes, a phylogenetic relationship between these phytopathogenic prokaryotes was deduced and compared with the phylogeny developed based on 16S ribosomal RNA gene.

Microsatellite repeat dynamics in mitochondrial genomes of phytopathogenic fungi: frequency and distribution in the genic and intergenic regions.

The frequency and distribution of microsatellites were analyzed in the 19 mitogenomes of phytopathogenic fungi covering five phyla. Our analysis revealed that in all the mitogenomes studied, the frequency and relative abundance varied, and it was neither influenced by genome size nor by GC content. SSRs were found to be differential distributed in genic and intergenic regions. An average of 5.14 (23.6%) SSRs were present in genic sequences and 21.7 (76.4%) SSRs were located in the intergenic sequences. Relative abundance of SSRs in mitogenomes was the highest in Aspergillus tubigensis, whereas, it was the least in Phaeosphaeria nodurum, the average being 0.45. Trinucleotide repeats were the most abundant motifs in the genic and intergenic regions of the mitogenomes of the phytopathogenic fungi. Among the genes, cox1 harbors the maximum SSRs, whereas cox3 and nad 7 contain the least. Based on the presence of SSRs in a particular gene, genetic relationships among individual organisms were also established.