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Identifying more traits of importance that can confer tolerance to various stressors, is the primary goal of scientists and breeders (Roychowdhury et al., 2020). [...]our Research Topic “Characterizing and improving traits for resilient crop development” comprises 14 manuscripts that provide new insights into crop genetic resources, quantitative trait loci (QTL) mapping, genome-wide association studies (GWAS), haplotype analysis, multi-omics approaches, gene discovery, expression and functional characterization using advanced gene editing tools. In another study,Sheela et al.reported that gene stacking or pyramiding of multiple stress-responsive genes allows rice cultivars to be tolerant to multiple limiting conditions such as moisture stress, salinity, aging, temperature, and oxidative stresses. Sugar maple is an economically important tree species for its syrup and hardwood production, and the trees are highly vulnerable to drought conditions.Mulozi et al.characterized physiological and biochemical traits, where chlorophyll biosynthesis, lipid membrane damage, and osmolyte production play a crucial role in responding to drought. Patchouli is an important medicinal plant for patchouli propagation and oil yield.Warsi et al.studied this drought susceptible plant to establish a rapid and efficient in vitro regeneration method followed by agrobacterium-mediated transformation with ACC deaminase gene.

Plants interact with diverse microbial communities and share complex relationships with each other. The intimate association between microbes and their host mutually benefit each other and provide stability against various biotic and abiotic stresses to plants. Endophytes are heterogeneous groups of microbes that live inside the host tissue without showing any apparent sign of infection. However, their functional attributes such as nutrient acquisition, phytohormone modulation, synthesis of bioactive compounds, and antioxidant enzymes of endophytes are similar to the other rhizospheric microorganisms. Nevertheless, their higher colonization efficacy and stability against abiotic stress make them superior to other microorganisms. In recent studies, the potential role of endophytes in bioprospecting has been broadly reported. However, the molecular aspect of host–endophyte interactions is still unclear. In this study, we have briefly discussed the endophyte biology, colonization efficacy and diversity pattern of endophytes. In addition, it also summarizes the molecular aspect of plant–endophyte interaction in biotic stress management.

The nucleotide-binding site (NBS)-encoding gene is a major type of resistance (R) gene, and its diverse evolutionary patterns were analyzed in different angiosperm lineages. Until now, no comparative studies have been done on the NBS encoding genes in Ipomoea species. In this study, various numbers of NBS-encoding genes were identified across the whole genome of sweet potato ( Ipomoea batatas ) (#889), Ipomoea trifida (#554), Ipomoea triloba (#571), and Ipomoea nil (#757). Gene analysis showed that the CN-type and N-type were more common than the other types of NBS-encoding genes. The phylogenetic analysis revealed that the NBS-encoding genes formed three monophyletic clades: CNL, TNL, and RNL, which were distinguished by amino acid motifs. The distribution of the NBS-encoding genes among the chromosomes was non-random and uneven; 83.13, 76.71, 90.37, and 86.39% of the genes occurred in clusters in sweet potato, I. trifida , I. triloba , and I. nil , respectively. The duplication pattern analysis reveals the presence of higher segmentally duplicated genes in sweet potatoes than tandemly duplicated ones. The opposite trend was found for the other three species. A total of 201 NBS-encoding orthologous genes were found to form synteny gene pairs between any two of the four Ipomea species, suggesting that each of the synteny gene pairs was derived from a common ancestor. The gene expression patterns were acquired by analyzing using the published datasets. To explore the candidate resistant genes in sweet potato, transcriptome analysis has been carried out using two resistant (JK20 and JK274) and susceptible cultivars (Tengfei and Santiandao) of sweet potato for stem nematodes and Ceratocystis fimbriata pathogen, respectively. A total of 11 differentially expressed genes (DEGs) were found in Tengfei and JK20 for stem nematodes and 19 DEGs in Santiandao and JK274 for C. fimbriata . Moreover, six DEGs were further selected for quantitative reverse-transcription polymerase chain reaction (qRT-PCR) analysis, and the results were consistent with the transcriptome analysis. The results may provide new insights into the evolution of NBS-encoding genes in the Ipomoea genome and contribute to the future molecular breeding of sweet potatoes.

Mungbean [Vigna radiata (L.) Wilczek] is an important food, feed, and cash crop in rice-based agricultural ecosystems in Southeast Asia and other continents. It has the potential to enhance livelihoods due to its palatability, nutritional content, and digestibility. We evaluated 166 diverse mungbean genotypes in two seasons using multivariate and multi-traits index approaches to identify superior genotypes. The total Shannon diversity index (SDI) for qualitative traits ranged from moderate for terminal leaflet shape (0.592) to high for seed colour (1.279). The analysis of variances (ANOVA) indicated a highly significant difference across the genotypes for most of the studied traits. Descriptive analyses showed high diversity among genotypes for all morphological traits. Six components with eigen values larger than one contributed 76.50% of the variability in the principal component analysis (PCA). The first three PCs accounted for the maximum 29.90%, 15.70%, and 11.20% of the total variances, respectively. Yield per plant, pod weight, hundred seed weight, pod length, days to maturity, pods per plant, harvest index, biological yield per plant, and pod per cluster contributed more to PC1 and PC2 and showed a positive association and positive direct effect on seed yield. The genotypes were grouped into seven clusters with the maximum in cluster II (34) and the minimum in cluster VII (10) along with a range of intra-cluster and inter-cluster distances of 5.15 (cluster II) to 3.60 (cluster VII) and 9.53 (between clusters II and VI) to 4.88 (clusters I and VII), suggesting extreme divergence and the possibility for use in hybridization and selection. Cluster III showed the highest yield and yield-related traits. Yield per plant positively and significantly correlated with pod traits and hundred seed weight. Depending on the multi-trait stability index (MTSI), clusters I, III, and VII might be utilized as parents in the hybridization program to generate high-yielding, disease-resistant, and small-seeded mungbean. Based on all multivariate-approaches, G45, G5, G22, G55, G143, G144, G87, G138, G110, G133, and G120 may be considered as the best parents for further breeding programs.

Lentil yield is a complicated quantitative trait; it is significantly influenced by the environment. It is crucial for improving human health and nutritional security in the country as well as for a sustainable agricultural system. The study was laid out to determine the stable genotype through the collaboration of G × E by AMMI and GGE biplot and to identify the superior genotypes using 33 parametric and non-parametric stability statistics of 10 genotypes across four different conditions. The total G × E effect was divided into two primary components by the AMMI model. For days to flowering, days to maturity, plant height, pods per plant, and hundred seed weight, IPCA1 was significant and accounted for 83%, 75%, 100%, and 62%, respectively. Both IPCA1 and IPCA2 were non-significant for yield per plant and accounted for 62% of the overall G × E interaction. An estimated set of eight stability parameters showed strong positive correlations with mean seed yield, and these measurements can be utilized to choose stable genotypes. The productivity of lentils has varied greatly in the environment, ranging from 786 kg per ha in the MYM environment to 1658 kg per ha in the ISD environment, according to the AMMI biplot. Three genotypes (G8, G7, and G2) were shown to be the most stable based on non-parametric stability scores for grain yield. G8, G7, G2, and G5 were determined as the top lentil genotypes based on grain production using numerical stability metrics such as Francis’s coefficient of variation, Shukla stability value (σi2), and Wrick’s ecovalence (Wi). Genotypes G7, G10, and G4 were the most stable with the highest yield, according to BLUP-based simultaneous selection stability characteristics. The findings of graphic stability methods such as AMMI and GGE for identifying the high-yielding and stable lentil genotypes were very similar. While the GGE biplot indicated G2, G10, and G7 as the most stable and high-producing genotypes, AMMI analysis identified G2, G9, G10, and G7. These selected genotypes would be used to release a new variety. Considering all the stability models, such as Eberhart and Russell’s regression and deviation from regression, additive main effects, multiplicative interactions (AMMI) analysis, and GGE, the genotypes G2, G9, and G7 could be used as well-adapted genotypes with moderate grain yield in all tested environments.

Pigeonpea is an important leguminous food crop primarily grown in tropical and subtropical regions of the world and is a rich source of high-quality protein. Biotic (weed, disease, and insect pests) and abiotic stresses have significantly reduced the production and productivity of pigeonpea. , also known as the pod borer, is a major pest in pigeonpea. A substantial investigation is needed to comprehend the genetic and genomic underpinnings of resistance to . Genetic improvement by genomics-assisted breeding (GAB) is an effective approach for developing high-yielding -resistant cultivars. Still, no genetic markers and genes linked to this key trait have been detected in pigeonpea. In this context, a set of 146 pigeonpea minicore accessions were evaluated for four -resistant component traits, namely, pod borer resistance (PBR), days to 50% flowering (DF), days to maturity (DM), and grain yield (GY), for three consecutive seasons under field conditions. Phenotypic data of pod borer resistance and component traits, along with the whole-genome resequencing (WGRS) data for 4,99,980 single nucleotide polymorphisms (SNPs), were utilised to perform multi-locus genome-wide association study (GWAS) analysis. Two models [settlement of MLM under progressively exclusive relationship (SUPER) and fixed and random model circulating probability unification (FarmCPU)] detected 14 significant marker-trait associations (MTAs) for PBR and three component traits. The MTAs with significant effect were mainly identified on chromosomes CcLG02, CcLG04, CcLG05, CcLG07, and CcLG11. These MTAs were subsequently delineated with key candidate genes associated with pod borer resistance ( , , , and ), days to maturity ( and ), and grain yield ( and ). These research findings reported significant MTAs and candidate genes associated with pod borer resistance and component traits. Further lab-based pod bioassay screening identified four minicore accessions, namely, ICP 10503, ICP 655, ICP 9691, and ICP 9655 (moderately resistant genotypes), showing the least damage rating and larval weight gain %, compared to the susceptible checks. After validating the significant MTAs, the associated SNP markers can be effectively utilised in indirect selection, which offers potential gains for such quantitative traits with low heritability and can improve insect management more sustainably. The significant MTAs, candidate genes, and resistant accessions reported in this study may be utilised for the development of pod borer-resistant pigeonpea varieties.

Maize (Zea mays L.) is an important cereal and is affected by climate change. Therefore, the production of climate-smart maize is urgently needed by preserving diverse genetic backgrounds through the exploration of their genetic diversity. To achieve this, 96 maize inbred lines were used to screen for phenotypic yield-associated traits and grain quality parameters. These traits were studied across two different environments (Anand and Godhra) and polymorphic simple sequence repeat (SSR) markers were employed to investigate the genetic diversity, population structure, and trait-linked association. Genotype–environment interaction (GEI) reveals that most of the phenotypic traits were governed by the genotype itself across the environments, except for plant and ear height, which largely interact with the environment. The genotypic correlation was found to be positive and significant among protein, lysine and tryptophan content. Similarly, yield-attributing traits like ear girth, kernel rows ear−1, kernels row−1 and number of kernels ear−1 were strongly correlated to each other. Pair-wise genetic distance ranged from 0.0983 (1820194/T1 and 1820192/4-20) to 0.7377 (IGI-1101 and 1820168/T1). The SSRs can discriminate the maize population into three distinct groups and shortlisted two genotypes (IGI-1101 and 1820168/T1) as highly diverse lines. Out of the studied 136 SSRs, 61 were polymorphic to amplify a total of 131 alleles (2–3 per loci) with 0.46 average gene diversity. The Polymorphism Information Content (PIC) ranged from 0.24 (umc1578) to 0.58 (umc2252). Similarly, population structure analysis revealed three distinct groups with 19.79% admixture among the genotypes. Genome-wide scanning through a mixed linear model identifies the stable association of the markers umc2038, umc2050 and umc2296 with protein, umc2296 and umc2252 with tryptophan, and umc1535 and umc1303 with total soluble sugar. The obtained maize lines and SSRs can be utilized in future maize breeding programs in relation to other trait characterizations, developments, and subsequent molecular breeding performances for trait introgression into elite genotypes.

The Near East climate ranges from arid to a Mediterranean, under which local wheat landraces have been grown for over millennia, assumingly accumulating a unique repertoire of genetic adaptations. In the current study, we subjected a subset of the Israeli Palestinian Landraces (IPLR) collection (n = 19: durum and bread wheat landraces, modern wheat cultivars, and landraces mixtures) to full-field evaluation. The multifield experiment included a semiarid site (2018–2019, 2019–2020) under low (L) and high (H) supplementary irrigation, and a Mediterranean site (2019–2020). Water availability had a major impact on crop performance. This was reflected in a strong discrimination between environments for biomass productivity and yield components. Compared to landraces, modern cultivars exhibited significantly higher grain yield (GY) across environments (+102%) reflecting the effect of the Green Revolution. However, under the Gilat19 (L) environment, this productivity gap was significantly reduced (only +39%). Five excelling landraces and the durum mix exhibited good agronomic potential across all trails. This was expressed in relatively high GY (2.3–2.85 t ha−1), early phenology (86–96 days to heading) and lodging resistance. Given the growing interest of stakeholders and consumers, these might be considered future candidates for the local artisanal wheat grain market. Yet, this step should be taken only after establishing an adjustable field management protocol.

Phosphate (P) is a crucial macronutrient for normal plant growth and development. The P availability in soils is a limitation factor, and understanding genetic factors playing roles in plant adaptation for improving P uptake is of great biological importance. Genome-wide association studies (GWAS) have become indispensable tools in unraveling the genetic basis of complex traits in various plant species. In this study, a comprehensive GWAS was conducted on diverse tomato (Solanum lycopersicum L.) accessions grown under normal and low P conditions for two weeks. Plant traits such as shoot height, primary root length, plant biomass, shoot inorganic content (SiP), and root inorganic content (RiP) were measured. Among several models of GWAS tested, the Bayesian-information and linkage disequilibrium iteratively nested keyway (BLINK) models were used for the identification of single nucleotide polymorphisms (SNPs). Among all the traits analyzed, significantly associated SNPs were recorded for PB, i.e., 1 SNP (SSL4.0CH10_49261145) under control P, SiP, i.e., 1 SNP (SSL4.0CH08_58433186) under control P and 1 SNP (SSL4.0CH08_51271168) under low P and RiP i.e., 2 SNPs (SSL4.0CH04_37267952 and SSL4.0CH09_4609062) under control P and 1 SNP (SSL4.0CH09_3930922) under low P condition. The identified SNPs served as genetic markers pinpointing regions of the tomato genome linked to P-responsive traits. The novel candidate genes associated with the identified SNPs were further analyzed for their protein-protein interactions using STRING. The study provided novel candidate genes, viz. Solyc10g050370 for PB under control, Solyc08g062490, and Solyc08g062500 for SiP and Solyc09g010450, Solyc09g010460, Solyc09g010690, and Solyc09g010710 for RiP under low P condition. These findings offer a glimpse into the genetic diversity of tomato accessions’ responses to P uptake, highlighting the potential for tailored breeding programs to develop P-efficient tomato varieties that could adapt to varying soil conditions, making them crucial for sustainable agriculture and addressing global challenges, such as soil depletion and food security.

Rice (Oryza sativa L.) is an important cereal crop worldwide due to its long domestication history. North-Eastern India (NEI) is one of the origins of indica rice and contains various native landraces that can withstand climatic changes. The present study compared NEI rice landraces to a check variety for phenological, morpho-physiological, and yield-associated traits under high temperatures (HTs) and elevated CO2 (eCO2) levels using molecular markers. The first experiment tested 75 rice landraces for HT tolerance. Seven better-performing landraces and the check variety (N22) were evaluated for the above traits in bioreactors for two years (2019 and 2020) under control (T1) and two stress treatments [mild stress or T2 (eCO2 550 ppm + 4 °C more than ambient temperature) and severe stress or T3 (eCO2 750 ppm + 6 °C more than ambient temperature)]. The findings showed that moderate stress (T2) improved plant height (PH), leaf number (LN), leaf area (LA), spikelets panicle−1 (S/P), thousand-grain weight (TGW), harvest index (HI), and grain production. HT and eCO2 in T3 significantly decreased all genotypes’ metrics, including grain yield (GY). Pollen traits are strongly and positively associated with spikelet fertility at maturity and GY under stress conditions. Shoot biomass positively affected yield-associated traits including S/P, TGW, HI, and GY. This study recorded an average reduction of 8.09% GY across two seasons in response to the conditions simulated in T3. Overall, two landraces—Kohima special and Lisem—were found to be more responsive compared to other the landraces as well as N22 under stress conditions, with a higher yield and biomass increment. SCoT-marker-assisted genotyping amplified 77 alleles, 55 of which were polymorphic, with polymorphism information content (PIC) values from 0.22 to 0.67. The study reveals genetic variation among the rice lines and supports Kohima Special and Lisem’s close relationship. These two better-performing rice landraces are useful pre-breeding resources for future rice-breeding programs to increase stress tolerance, especially to HT and high eCO2 levels under changing climatic situations.