Unravelling the Genetic Basis of Moisture Deficit Stress Tolerance in Wheat for Seedling Vigour-Related Traits and Root Traits Using Genome-Wide Association Study.

A key abiotic stress that negatively affects seed germination, plant development, and crop yield is moisture deficit stress. Achieving higher vigour and uniform germination under stress conditions is essential for crop establishment and productivity and to enhance the yield. Hence, revealing wheat's capacity to withstand moisture deficit stress during seed germination and early growth stages is fundamental in improving its overall performance. However, the genetic regulation of moisture deficit stress tolerance during the seed germination phase remains largely unexplored. In this study, a total of 193 wheat genotypes were subjected to simulated moisture deficit stress using PEG-6000 (-0.4 MPa) during the seed germination stage. The induced moisture deficit stress significantly reduced various seedling-vigour-related traits. The genetic regions linked to these traits were found using a genome-wide association study (GWAS). The analysis identified 235 MTAs with a significance -log10(p) value of >4. After applying the Bonferroni correction, the study identified 47 unique single nucleotide polymorphisms (SNPs) that are linked to candidate genes important for the trait of interest. The current study emphasises the effectiveness of genome-wide association studies (GWAS) in identifying promising candidate genes, improving wheat seedling vigour and root traits, and offering essential information for the development of wheat cultivars tolerant to moisture deficit stress.

Genetic analysis of heat tolerance in hot pepper: insights from comprehensive phenotyping and QTL mapping.

High temperatures present a formidable challenge to the cultivation of hot pepper, profoundly impacting not only vegetative growth but also leading to flower and fruit abscission, thereby causing a significant reduction in yield. To unravel the intricate genetic mechanisms governing heat tolerance in hot pepper, an F2 population was developed through the crossing of two distinct genotypes exhibiting contrasting heat tolerance characteristics: DLS-161-1 (heat tolerant) and DChBL-240 (heat susceptible). The F2 population, along with the parental lines, was subjected to comprehensive phenotyping encompassing diverse morphological, physiological, and biochemical heat-related traits under high temperature conditions (with maximum temperature ranging from 31 to 46.5°C and minimum temperature from 15.4 to 30.5°C). Leveraging the Illumina Nova Seq-6000 platform, Double digest restriction-site associated DNA sequencing (ddRAD-seq) was employed to generate 67.215 Gb data, with subsequent alignment of 218.93 million processed reads against the reference genome of Capsicum annuum. Subsequent variant calling and ordering resulted in 5806 polymorphic SNP markers grouped into 12 LGs. Further QTL analysis identified 64 QTLs with LOD values ranging from 2.517 to 11.170 and explained phenotypic variance ranging from 4.05 to 19.39%. Among them, 21 QTLs, explaining more than 10% phenotypic variance, were identified as major QTLs controlling 9 morphological, 3 physiological, and 2 biochemical traits. Interestingly, several QTLs governing distinct parameters were found to be colocalized, suggesting either a profound correlation between the QTLs regulating these traits or their significant genomic proximity. In addition to the QTLs, we also identified 368380 SSR loci within the identified QTL regions, dinucleotides being the most abundant type (211,381). These findings provide valuable insights into the genetics of heat tolerance in hot peppers. The identified QTLs and SSR markers offer opportunities to develop heat-tolerant varieties, ensuring better crop performance under high-temperature conditions.

Multivariate analysis and genetic dissection of staygreen and stem reserve mobilisation under combined drought and heat stress in wheat (Triticum aestivum L.).

Introduction: Abiotic stresses significantly reduce crop yield by adversely affecting many physio-biochemical processes. Several physiological traits have been targeted and improved for yield enhancement in limiting environmental conditions. Amongst them, staygreen and stem reserve mobilisation are two important mutually exclusive traits contributing to grain filling under drought and heat stress in wheat. Henceforth, the present study was carried out to identify the QTLs governing these traits and to identify the superiors' lines through multi-trait genotype-ideotype distance index (MGIDI) Methods: A mapping population consisting of 166 recombinant inbred lines (RILs) developed from a cross between HD3086 and HI1500 was utilized in this study. The experiment was laid down in alpha lattice design in four environmental conditions viz. Control, drought, heat and combined stress (heat and drought). Genotyping of parents and RILs was carried out with 35 K Axiom® array (Wheat breeder array). Results and Discussion: Medium to high heritability with a moderate to high correlation between traits was observed. Principal component analysis (PCA) was performed to derive latent variables in the original set of traits and the relationship of these traits with latent variables.From this study, 14 QTLs were identified, out of which 11, 2, and 1 for soil plant analysis development (SPAD) value, leaf senescence rate (LSR), and stem reserve mobilisation efficiency (SRE) respectively. Quantitative trait loci (QTLs) for SPAD value harbored various genes like Dirigent protein 6-like, Protein FATTY ACID EXPORT 3, glucan synthase-3 and Ubiquitin carboxyl-terminal hydrolase, whereas QTLs for LSR were found to contain various genes like aspartyl protease family protein, potassium transporter, inositol-tetrakisphosphate 1-kinase, and DNA polymerase epsilon subunit D-like. Furthermore, the chromosomal region for SRE was found to be associated with serine-threonine protein kinase. Serine-threonine protein kinases are involved in many signaling networks such as ABA mediated ROS signaling and acclimation to environmental stimuli. After the validation of QTLs in multilocation trials, these QTLs can be used for marker-assisted selection (MAS) in breeding programs.

Marker-assisted selection for transfer of QTLs to a promising line for drought tolerance in wheat (Triticum aestivum L.).

Wheat crop is subjected to various biotic and abiotic stresses, which affect crop productivity and yield. Among various abiotic stresses, drought stress is a major problem considering the current global climate change scenario. A high-yielding wheat variety, HD3086, has been released for commercial cultivation under timely sown irrigated conditions for the North Western Plain Zone (NWPZ) and North Eastern Plain Zone NEPZ of India. Presently, HD3086 is one of the highest breeder seed indented wheat varieties and has a stable yield over the years. However, under moisture deficit conditions, its potential yield cannot be achieved. The present study was undertaken to transfer drought-tolerant QTLs in the background of the variety HD3086 using marker-assisted backcross breeding. QTLs governing Biomass (BIO), Canopy Temperature (CT), Thousand Kernel Weight (TKW), Normalized Difference Vegetation Index (NDVI), and Yield (YLD) were transferred to improve performance under moisture deficit conditions. In BC1F1, BC2F1, and BC2F2 generations, the foreground selection was carried out to identify the plants with positive QTLs conferring drought tolerance and linked to traits NDVI, CT, TKW, and yield. The positive homozygous lines for targeted QTLs were advanced from BC2F2 to BC2F4 via the pedigree-based phenotypic selection method. Background analysis was carried out in BC2F5 and obtained 78-91% recovery of the recurrent parent genome in the improved lines. Furthermore, the advanced lines were evaluated for 2 years under drought stress to assess improvement in MABB-derived lines. Increased GWPS, TKW, and NDVI and reduced CT was observed in improved lines. Seven improved lines were identified with significantly higher yields in comparison to HD3086 under stress conditions.

Genotypic capacity of post-anthesis stem reserve mobilization in wheat for yield sustainability under drought and heat stress in the subtropical region.

Wheat productivity is severely affected by drought and heat stress conditions worldwide. Currently, stem reserve mobilization (SRM) is receiving increased attention as a trait that can sustain wheat yields under adverse environments. However, the significance of SRM in sustaining wheat yields under drought and heat stress conditions remains uncertain in the tropical climate of Indo-Gangetic Plain region. Therefore, this study aimed to investigate genotypic variations in SRM in wheat and their influence on yield sustainability under drought and heat stress environments. The experiment was designed in an alpha-lattice layout, accommodating 43 genotypes under four simulated environments [timely sown and well irrigated (non-stress); timely sown and water-deficit/drought stress; late-sown and well-irrigated crop facing terminally high temperature; and late-sown and water-deficit stress (both water-deficit and heat stress)]. The water-deficit stress significantly increased SRM (16%-68%, p < 0.01) compared to the non-stress environment, while the heat stress conditions reduced SRM (12%-18%). Both SRM and stem reserve mobilization efficiency exhibited positive correlations with grain weight (grain weight spike-1) under all three different stress treatments (p < 0.05). Strong positive correlations between stem weight (at 12 days after anthesis) and grain weight were observed across the environments (p < 0.001); however, a significant positive correlation between stem weight and SRM was observed only with stress treatments. Results revealed that the SRM trait could effectively alleviate the impacts of water-deficit stress on yields. However, the SRM-mediated yield protection was uncertain under heat stress and combined water-deficit and heat stress treatments, possibly due to sink inefficiencies caused by high temperature during the reproductive period. Defoliated plants exhibited higher SRM than non-defoliated plants, with the highest increment observed in the non-stress treatment compared to all the stress treatments. Results revealed that wider genetic variability exists for the SRM trait, which could be used to improve wheat yield under drought stress conditions.

Phenomics based prediction of plant biomass and leaf area in wheat using machine learning approaches.

Introduction: Phenomics has emerged as important tool to bridge the genotype-phenotype gap. To dissect complex traits such as highly dynamic plant growth, and quantification of its component traits over a different growth phase of plant will immensely help dissect genetic basis of biomass production. Based on RGB images, models have been developed to predict biomass recently. However, it is very challenging to find a model performing stable across experiments. In this study, we recorded RGB and NIR images of wheat germplasm and Recombinant Inbred Lines (RILs) of Raj3765xHD2329, and examined the use of multimodal images from RGB, NIR sensors and machine learning models to predict biomass and leaf area non-invasively. Results: The image-based traits (i-Traits) containing geometric features, RGB based indices, RGB colour classes and NIR features were categorized into architectural traits and physiological traits. Total 77 i-Traits were selected for prediction of biomass and leaf area consisting of 35 architectural and 42 physiological traits. We have shown that different biomass related traits such as fresh weight, dry weight and shoot area can be predicted accurately from RGB and NIR images using 16 machine learning models. We applied the models on two consecutive years of experiments and found that measurement accuracies were similar suggesting the generalized nature of models. Results showed that all biomass-related traits could be estimated with about 90% accuracy but the performance of model BLASSO was relatively stable and high in all the traits and experiments. The R2 of BLASSO for fresh weight prediction was 0.96 (both year experiments), for dry weight prediction was 0.90 (Experiment 1) and 0.93 (Experiment 2) and for shoot area prediction 0.96 (Experiment 1) and 0.93 (Experiment 2). Also, the RMSRE of BLASSO for fresh weight prediction was 0.53 (Experiment 1) and 0.24 (Experiment 2), for dry weight prediction was 0.85 (Experiment 1) and 0.25 (Experiment 2) and for shoot area prediction 0.59 (Experiment 1) and 0.53 (Experiment 2). Discussion: Based on the quantification power analysis of i-Traits, the determinants of biomass accumulation were found which contains both architectural and physiological traits. The best predictor i-Trait for fresh weight and dry weight prediction was Area_SV and for shoot area prediction was projected shoot area. These results will be helpful for identification and genetic basis dissection of major determinants of biomass accumulation and also non-invasive high throughput estimation of plant growth during different phenological stages can identify hitherto uncovered genes for biomass production and its deployment in crop improvement for breaking the yield plateau.

Development of bread wheat (Triticum aestivum L) variety HD3411 following marker-assisted backcross breeding for drought tolerance.

Marker-assisted backcross breeding enables selective insertion of targeted traits into the genome to improve yield, quality, and stress resistance in wheat. In the current investigation, we transferred four drought tolerance quantitative trait loci (QTLs) controlling traits, viz canopy temperature, normalized difference vegetative index, chlorophyll content, and grain yield from the drought-tolerant donor line, C306, into a popular high-yielding, drought-sensitive variety, HD2733. Marker-assisted selection coupled with stringent phenotypic screening was used to advance each generation. This study resulted in 23 improved lines carrying combinations of four drought tolerance QTLs with a range of 85.35%-95.79% background recovery. The backcross-derived lines gave a higher yield under moisture-deficit stress conditions compared with the recipient parent. They also showed higher phenotypic mean values for physiological traits and stability characteristics of HD2733. A promising genotype, HD3411, derived from this cross was identified for release after national multi-location coordinating trials under the All India Coordinated Wheat Improvement Project. Our study is a prime example of the advantages of precision breeding using integrating markers and phenotypic selection to develop new cultivars with desirable traits like drought tolerance.

Genome-Wide Association Study for Grain Protein, Thousand Kernel Weight, and Normalized Difference Vegetation Index in Bread Wheat (Triticum aestivum L.).

Genomic regions governing grain protein content (GPC), 1000 kernel weight (TKW), and normalized difference vegetation index (NDVI) were studied in a set of 280 bread wheat genotypes. The genome-wide association (GWAS) panel was genotyped using a 35K Axiom array and phenotyped in three environments. A total of 26 marker-trait associations (MTAs) were detected on 18 chromosomes covering the A, B, and D subgenomes of bread wheat. The GPC showed the maximum MTAs (16), followed by NDVI (6), and TKW (4). A maximum of 10 MTAs was located on the B subgenome, whereas, 8 MTAs each were mapped on the A and D subgenomes. In silico analysis suggest that the SNPs were located on important putative candidate genes such as NAC domain superfamily, zinc finger RING-H2-type, aspartic peptidase domain, folylpolyglutamate synthase, serine/threonine-protein kinase LRK10, pentatricopeptide repeat, protein kinase-like domain superfamily, cytochrome P450, and expansin. These candidate genes were found to have different roles including regulation of stress tolerance, nutrient remobilization, protein accumulation, nitrogen utilization, photosynthesis, grain filling, mitochondrial function, and kernel development. The effects of newly identified MTAs will be validated in different genetic backgrounds for further utilization in marker-aided breeding.

Mapping of the QTLs governing grain micronutrients and thousand kernel weight in wheat (Triticum aestivum L.) using high density SNP markers.

Biofortification is gaining importance globally to improve human nutrition through enhancing the micronutrient content, such as vitamin A, iron, and zinc, in staple food crops. The present study aims to identify the chromosomal regions governing the grain iron concentration (GFeC), grain zinc concentration (GZnC), and thousand kernel weight (TKW) using recombinant inbred lines (RILs) in wheat, developed from a cross between HD3086 and HI1500. The experiment was conducted in four different production conditions at Delhi viz., control, drought, heat, and combined heat and drought stress and at Indore under drought stress. Grain iron and zinc content increased under heat and combined stress conditions, while thousand kernel weight decreased. Medium to high heritability with a moderate correlation between grain iron and zinc was observed. Out of 4,106 polymorphic markers between the parents, 3,407 SNP markers were used for linkage map construction which spanned over a length of 14791.18 cm. QTL analysis identified a total of 32 chromosomal regions governing the traits under study, which includes 9, 11, and 12 QTLs for GFeC, GZnC, and TKW, respectively. A QTL hotspot was identified on chromosome 4B which is associated with grain iron, grain zinc, and thousand kernel weight explaining the phenotypic variance of 29.28, 10.98, and 17.53%, respectively. Similarly, common loci were identified on chromosomes 4B and 4D for grain iron, zinc, and thousand kernel weight. In silico analysis of these chromosomal regions identified putative candidate genes that code for proteins such as Inositol 1,3,4-trisphosphate 5/6-kinase, P-loop containing nucleoside triphosphate hydrolase, Pleckstrin homology (PH) domains, Serine-threonine/tyrosine-protein kinase and F-box-like domain superfamily proteins which play role in many important biochemical or physiological process. The identified markers linked to QTLs can be used in MAS once successfully validated.

Molecular Mapping of Biofortification Traits in Bread Wheat (Triticum aestivum L.) Using a High-Density SNP Based Linkage Map.

A set of 188 recombinant inbred lines (RILs) derived from a cross between a high-yielding Indian bread wheat cultivar HD2932 and a synthetic hexaploid wheat (SHW) Synthetic 46 derived from tetraploid Triticum turgidum (AA, BB 2n = 28) and diploid Triticum tauschii (DD, 2n = 14) was used to identify novel genomic regions associated in the expression of grain iron concentration (GFeC), grain zinc concentration (GZnC), grain protein content (GPC) and thousand kernel weight (TKW). The RIL population was genotyped using SNPs from 35K Axiom® Wheat Breeder's Array and 34 SSRs and phenotyped in two environments. A total of nine QTLs including five for GPC (QGpc.iari_1B, QGpc.iari_4A, QGpc.iari_4B, QGpc.iari_5D, and QGpc.iari_6B), two for GFeC (QGfec.iari_5B and QGfec.iari_6B), and one each for GZnC (QGznc.iari_7A) and TKW (QTkw.iari_4B) were identified. A total of two stable and co-localized QTLs (QGpc.iari_4B and QTkw.iari_4B) were identified on the 4B chromosome between the flanking region of Xgwm149-AX-94559916. In silico analysis revealed that the key putative candidate genes such as P-loop containing nucleoside triphosphatehydrolase, Nodulin-like protein, NAC domain, Purine permease, Zinc-binding ribosomal protein, Cytochrome P450, Protein phosphatase 2A, Zinc finger CCCH-type, and Kinesin motor domain were located within the identified QTL regions and these putative genes are involved in the regulation of iron homeostasis, zinc transportation, Fe, Zn, and protein remobilization to the developing grain, regulation of grain size and shape, and increased nitrogen use efficiency. The identified novel QTLs, particularly stable and co-localized QTLs are useful for subsequent use in marker-assisted selection (MAS).

QTL mapping: insights into genomic regions governing component traits of yield under combined heat and drought stress in wheat.

Drought and heat frequently co-occur during crop growth leading to devastating yield loss. The knowledge of the genetic loci governing component traits of yield under combined drought and heat stress is essential for enhancing the climate resilience. The present study employed a mapping population of 180 recombinant inbred lines (RILs) derived from a cross between GW322 and KAUZ to identify quantitative trait loci (QTLs) governing the component traits of yield under heat and combined stress conditions. Phenotypic evaluation was conducted across two consecutive crop seasons (2021-2022 and 2022-2023) under late sown irrigation (LSIR) and late sown restricted irrigation (LSRI) conditions at the Indian Council of Agricultural Research Institute-Indian Agricultural Research Institute (ICAR-IARI), New Delhi. Various physiological and agronomic traits of importance were measured. Genotyping was carried out with 35K SNP Axiom breeder's genotyping array. The linkage map spanned a length of 6769.45 cM, ranging from 2.28 cM/marker in 1A to 14.21 cM/marker in 5D. A total of 35 QTLs were identified across 14 chromosomes with 6B containing the highest (seven) number of QTLs. Out of 35 QTLs, 16 were major QTLs explaining the phenotypic variance greater than 10%. The study identified eight stable QTLs along with two hotspots on chromosomes 6B and 5B. Five QTLs associated with traits thousand-grain weight (TGW), normalized difference vegetation index (NDVI), and plant height (PH) were successfully validated. Candidate genes encoding antioxidant enzymes, transcription factors, and growth-related proteins were identified in the QTL regions. In silico expression analysis highlighted higher expression of transcripts TraesCS2D02G021000.1, TraesCS2D02G031000, TraesCS6A02G247900, and TraesCS6B02G421700 under stress conditions. These findings contribute to a deeper understanding of the genetic architecture underlying combined heat and drought tolerance in wheat, providing valuable insights for wheat improvement strategies under changing climatic conditions.

Marker-assisted backcross breeding for heat tolerance in bread wheat (Triticum aestivum L.).

Manipulation of flowering time for adaptation through natural or genetic approaches may combat heat-stress damage that occurs at the reproductive stages in production conditions. HD2733, a popular wheat variety of the eastern plains of India, is largely sensitive to heat stress. Therefore, the current study aims to improve heat tolerance of HD2733 by introgression of QTLs associated with early anthesis and high kernel weight linked to markers Xbarc186 and Xgwm190, respectively, through marker-assisted backcross breeding (MABB) from a tolerant donor, WH730. A total of 124 simple sequence repeat (SSR) markers distributed evenly across the genome were used for the background selection. The alleles of Xbarc186 and Xgwm190 were fixed in BC2F1 and BC1F2 generations by selecting individual plants heterozygous for both marker loci and backcrossed with HD2733 and simultaneously selfed to generate BC2F1 and BC1F2 populations, respectively. Furthermore, the selected BC1F2 were selfed to generate the BC1F4 population. By background screening, a total of 39 BC2F3 and 21 BC1F4 families homozygous for the targeted QTLs with 90.9-97.9% and 86.8-88.3% RPG recoveries were selected. The best performing 17 BC2F3 and 10 BC1F4 lines were evaluated for various morpho-physiological traits. Phenotypic evaluation and multi-location trials of the introgressed lines under late sown conditions led to the selection of three promising lines with early anthesis and higher grain yield. The improved lines will serve as an excellent genetic material for functional genomics and expression studies to understand the molecular mechanisms and pathways underlying the stress tolerance.

Marker assisted improvement for leaf rust and moisture deficit stress tolerance in wheat variety HD3086.

There is a significant yield reduction in the wheat crop as a result of different biotic and abiotic stresses, and changing climate, among them moisture deficit stress and leaf rust are the major ones affecting wheat worldwide. HD3086 is a high-yielding wheat variety that has been released for commercial cultivation under timely sown irrigated conditions in the Indo-Gangetic plains of India. Variety HD3086 provides a good, stable yield, and it is the choice of millions of farmers in India. It becomes susceptible to the most prevalent pathotypes 77-5 and 77-9 of Puccinia triticina (causing leaf rust) in the production environment and its potential yield cannot be realized under moisture deficit stress. The present study demonstrates the use of a marker-assisted back cross breeding approach to the successful transfer of leaf rust resistance gene Lr24 and QTLs linked to moisture deficit stress tolerance in the background of HD3086. The genotype HI1500 was used as a donor parent that possesses leaf rust-resistant gene Lr24, which confers resistance against the major pathotypes found in the production environment. It possesses inbuilt tolerance under abiotic stresses with superior quality traits. Foreground selection for gene Lr24 and moisture deficit stress tolerance QTLs linked to Canopy temperature (CT), Normal Differential Vegetation Index (NDVI) and Thousand Kernel Weight (TKW) in different generations of the backcrossing and selection. In BC2F2, foreground selection was carried out to identify homozygous lines based on the linked markers and were advanced following pedigree based phenotypic selection. The selected lines were evaluated against P. triticina pathotypes 77-5 and 77-9 under controlled conditions. Recurrent parent recovery of the selected lines ranged from 78-94%. The identified lines were evaluated for their tolerance to moisture stress under field conditions and their resistance to rust under artificial epiphytotic conditions for two years. In BC2F5 generation, eight positive lines for marker alleles were selected which showed resistance to leaf rust and recorded an improvement in component traits of moisture deficit stress tolerance such as CT, NDVI, TKW and yield compared to the recurrent parent HD3086. The derived line is named HD3471 and is nominated for national trials for testing and further release for commercial cultivation.

Identification of genomic regions of wheat associated with grain Fe and Zn content under drought and heat stress using genome-wide association study.

Wheat is the staple food crop of global importance for its grain nutrient quality. Grain iron and zinc content of the wheat grain is an important quantitatively inherited trait that is influenced by the environmental factors such as drought and heat stress. Phenotypic evaluation of 295 advanced breeding lines from the wheat stress breeding program of IARI was carried out under timely sown irrigated (IR), restricted irrigated, and late-sown conditions at New Delhi during the cropping season of 2020-21, and grain iron (GFeC) and zinc (GZnC) contents were estimated from both control and treatments. A statistically significant increase in GFeC and GZnC was observed under stress conditions compared to that of the control. Genotyping was carried out with the SNPs from the 35K Axiom Breeder's array, and marker-trait association was identified by GWAS analysis. Of the 23 MTAs identified, seven were linked with GFeC and sixteen were linked with GZnC. In silico analysis revealed a few important transcripts involved in various plant metabolism, growth, and development activities such as auxin response factor, root UVB sensitive proteins, potassium transporter, glycosyl transferase, COBRA, and F-box-like domain. The identified MTAs can be used for molecular breeding after validation and also for rapid development of micronutrient-rich varieties of wheat to mitigate hidden hunger.

Genome-wide association mapping for component traits of drought and heat tolerance in wheat.

Identification of marker trait association is a prerequisite for marker-assisted breeding. To find markers linked with traits under heat and drought stress in bread wheat (Triticum aestivum L.), we performed a genome-wide association study (GWAS). GWAS mapping panel used in this study consists of advanced breeding lines from the IARI stress breeding programme produced by pairwise and complex crosses. Phenotyping was done at multi locations namely New Delhi, Karnal, Indore, Jharkhand and Pune with augmented-RCBD design under different moisture and heat stress regimes, namely timely sown irrigated (IR), timely sown restricted irrigated (RI) and late sown (LS) conditions. Yield and its component traits, viz., Days to Heading (DH), Days to Maturity (DM), Normalized Difference Vegetation Index (NDVI), Chlorophyll Content (SPAD), Canopy temperature (CT), Plant Height (PH), Thousand grain weight (TGW), Grain weight per spike (GWPS), Plot Yield (PLTY) and Biomass (BMS) were phenotyped. Analysis of variance and descriptive statistics revealed significant differences among the studied traits. Genotyping was done using the 35k SNP Wheat Breeder's Genotyping Array. Population structure and diversity analysis using filtered 10,546 markers revealed two subpopulations with sufficient diversity. A large whole genome LD block size of 7.15 MB was obtained at half LD decay value. Genome-wide association search identified 57 unique markers associated with various traits across the locations. Twenty-three markers were identified to be stable, among them nine pleiotropic markers were also identified. In silico search of the identified markers against the IWGSC ref genome revealed the presence of a majority of the SNPs at or near the gene coding region. These SNPs can be used for marker-assisted transfer of genes/QTLs after validation to develop climate-resilient cultivars.

Genome-wide association study for grain yield and component traits in bread wheat (Triticum aestivum L.).

Genomic regions governing days to heading (DH), grain filling duration (GFD), grain number per spike (GNPS), grain weight per spike (GWPS), plant height (PH), and grain yield (GY) were investigated in a set of 280 diverse bread wheat genotypes. The genome-wide association studies (GWAS) panel was genotyped using a 35K Axiom Array and phenotyped in five environments. The GWAS analysis showed a total of 27 Bonferroni-corrected marker-trait associations (MTAs) on 15 chromosomes representing all three wheat subgenomes. The GFD showed the highest MTAs (8), followed by GWPS (7), GY (4), GNPS (3), PH (3), and DH (2). Furthermore, 20 MTAs were identified with more than 10% phenotypic variation. A total of five stable MTAs (AX-95024590, AX-94425015, AX-95210025 AX-94539354, and AX-94978133) were identified in more than one environment and associated with the expression of DH, GFD, GNPS, and GY. Similarly, two novel pleiotropic genomic regions with associated MTAs i.e. AX-94978133 (4D) and AX-94539354 (6A) harboring co-localized QTLs governing two or more traits were also identified. In silico analysis revealed that the SNPs were located on important putative candidate genes such as F-box-like domain superfamily, Lateral organ boundaries, LOB, Thioredoxin-like superfamily Glutathione S-transferase, RNA-binding domain superfamily, UDP-glycosyltransferase family, Serine/threonine-protein kinase, Expansin, Patatin, Exocyst complex component Exo70, DUF1618 domain, Protein kinase domain involved in the regulation of grain size, grain number, growth and development, grain filling duration, and abiotic stress tolerance. The identified novel MTAs will be validated to estimate their effects in different genetic backgrounds for subsequent use in marker-assisted selection (MAS).

Genetic dissection of grain iron and zinc, and thousand kernel weight in wheat (Triticum aestivum L.) using genome-wide association study.

Genetic biofortification is recognized as a cost-effective and sustainable strategy to reduce micronutrient malnutrition. Genomic regions governing grain iron concentration (GFeC), grain zinc concentration (GZnC), and thousand kernel weight (TKW) were investigated in a set of 280 diverse bread wheat genotypes. The genome-wide association (GWAS) panel was genotyped using 35 K Axiom Array and phenotyped in five environments. The GWAS analysis showed a total of 17 Bonferroni-corrected marker-trait associations (MTAs) in nine chromosomes representing all the three wheat subgenomes. The TKW showed the highest MTAs (7), followed by GZnC (5) and GFeC (5). Furthermore, 14 MTAs were identified with more than 10% phenotypic variation. One stable MTA i.e. AX-95025823 was identified for TKW in both E4 and E5 environments along with pooled data, which is located at 68.9 Mb on 6A chromosome. In silico analysis revealed that the SNPs were located on important putative candidate genes such as Multi antimicrobial extrusion protein, F-box domain, Late embryogenesis abundant protein, LEA-18, Leucine-rich repeat domain superfamily, and C3H4 type zinc finger protein, involved in iron translocation, iron and zinc homeostasis, and grain size modifications. The identified novel MTAs will be validated to estimate their effects in different genetic backgrounds for subsequent use in marker-assisted selection. The identified SNPs will be valuable in the rapid development of biofortified wheat varieties to ameliorate the malnutrition problems.

Genome-wide association study identifies loci and candidate genes for grain micronutrients and quality traits in wheat (Triticum aestivum L.).

Malnutrition due to micronutrients and protein deficiency is recognized among the major global health issues. Genetic biofortification of wheat is a cost-effective and sustainable strategy to mitigate the global micronutrient and protein malnutrition. Genomic regions governing grain zinc concentration (GZnC), grain iron concentration (GFeC), grain protein content (GPC), test weight (TW), and thousand kernel weight (TKW) were investigated in a set of 184 diverse bread wheat genotypes through genome-wide association study (GWAS). The GWAS panel was genotyped using Breeders' 35 K Axiom Array and phenotyped in three different environments during 2019-2020. A total of 55 marker-trait associations (MTAs) were identified representing all three sub-genomes of wheat. The highest number of MTAs were identified for GPC (23), followed by TKW (15), TW (11), GFeC (4), and GZnC (2). Further, a stable SNP was identified for TKW, and also pleiotropic regions were identified for GPC and TKW. In silico analysis revealed important putative candidate genes underlying the identified genomic regions such as F-box-like domain superfamily, Zinc finger CCCH-type proteins, Serine-threonine/tyrosine-protein kinase, Histone deacetylase domain superfamily, and SANT/Myb domain superfamily proteins, etc. The identified novel MTAs will be validated to estimate their effects in different genetic backgrounds for subsequent use in marker-assisted selection.

Assessing Sustainability Factors for Rural Household Sanitation Coverage in Bhutan, Kenya, Nepal, and Zambia: A Qualitative Analysis.

BACKGROUND: Few countries are likely to achieve universal sanitation within the next decade as sustaining household sanitation coverage remains a critical challenge. This study aimed to investigate factors that may have supported or hindered sustainability of sanitation coverage 1-2 years after the completion of an integrated, area-wide sanitation program in 4 countries. METHODS: We conducted qualitative analyses to identify factors related to the sustainability of sanitation coverage in Bhutan, Kenya, Nepal, and Zambia, 2 years after completion of the Sustainable Sanitation and Hygiene for All program. From November 2019 to March 2020, we conducted focus group discussions and key informant interviews with community members, project implementers, and decision makers. We triangulated the qualitative findings with data from household surveys to characterize subnational sanitation coverage throughout implementation and 1-2 years after. RESULTS: Our data revealed behavioral, contextual, and service delivery factors that were related to the sustainability of sanitation improvements. Service delivery factors included follow-up hygiene promotion, access to construction materials, local government commitment postimplementation, functioning monitoring systems, private sector uptake of supply chain improvements, and capacity for innovation. Contextual and behavioral factors included poverty, soil type, road networks, social cohesion, desire for improved latrines, maintenance and cleaning, and knowledge of sanitation benefits. CONCLUSION: The presence or absence of sustainability factors identified through this research may have implications on where certain programmatic approaches will work and where adaptations may be required. By comparing sustainability factors with subnational slippage rates, we were able to illustrate how local service delivery systems may respond to barriers and enablers. Understanding the programmatic and contextual factors that either drive or hinder long-term sanitation coverage may allow for greater program impact through adapting implementation based on existing challenges in service delivery and context.

Genetic dissection of marker trait associations for grain micro-nutrients and thousand grain weight under heat and drought stress conditions in wheat.

Introduction: Wheat is grown and consumed worldwide, making it an important staple food crop for both its calorific and nutritional content. In places where wheat is used as a staple food, suboptimal micronutrient content levels, especially of grain iron (Fe) and zinc (Zn), can lead to malnutrition. Grain nutrient content is influenced by abiotic stresses, such as drought and heat stress. The best method for addressing micronutrient deficiencies is the biofortification of food crops. The prerequisites for marker-assisted varietal development are the identification of the genomic region responsible for high grain iron and zinc contents and an understanding of their genetics. Methods: A total of 193 diverse wheat genotypes were evaluated under drought and heat stress conditions across the years at the Indian Agricultural Research Institute (IARI), New Delhi, under timely sown irrigated (IR), restricted irrigated (RI) and late sown (LS) conditions. Grain iron content (GFeC) and grain zinc content (GZnC) were estimated from both the control and treatment groups. Genotyping of all the lines under study was carried out with the single nucleotide polymorphisms (SNPs) from Breeder's 35K Axiom Array. Result and Discussion: Three subgroups were observed in the association panel based on both principal component analysis (PCA) and dendrogram analysis. A large whole-genome linkage disequilibrium (LD) block size of 3.49 Mb was observed. A genome-wide association study identified 16 unique stringent marker trait associations for GFeC, GZnC, and 1000-grain weight (TGW). In silico analysis demonstrated the presence of 28 potential candidate genes in the flanking region of 16 linked SNPs, such as synaptotagmin-like mitochondrial-lipid-binding domain, HAUS augmin-like complex, di-copper center-containing domain, protein kinase, chaperonin Cpn60, zinc finger, NUDIX hydrolase, etc. Expression levels of these genes in vegetative tissues and grain were also found. Utilization of identified markers in marker-assisted breeding may lead to the rapid development of biofortified wheat genotypes to combat malnutrition.