Construction of a genetic linkage map and QTL mapping of fruit quality traits in guava (Psidium guajava L.).

Guava (Psidium guajava L.) is an important fruit crop of the Indian sub-continent, with potential for improvements in quality and yield. The goal of the present study was to construct a genetic linkage map in an intraspecific cross between the elite cultivar 'Allahabad Safeda' and the Purple Guava landrace to identify the genomic regions responsible for important fruit quality traits, viz., total soluble solids, titratable acidity, vitamin C, and sugars. This population was phenotyped in field trials (as a winter crop) for three consecutive years, and showed moderate-to-high values of heterogeneity coefficients along with higher heritability (60.0%-97.0%) and genetic-advance-over-mean values (13.23%-31.17%), suggesting minimal environmental influence on the expression of fruit-quality traits and indicating that these traits can be improved by phenotypic selection methods. Significant correlations and strong associations were also detected among fruit physico-chemical traits in segregating progeny. The constructed linkage map consisted of 195 markers distributed across 11 chromosomes, spanning a length of 1,604.47 cM (average inter-loci distance of 8.80 markers) and with 88.00% coverage of the guava genome. Fifty-eight quantitative trait loci (QTLs) were detected in three environments with best linear unbiased prediction (BLUP) values using the composite interval mapping algorithm of the BIP (biparental populations) module. The QTLs were distributed on seven different chromosomes, explaining 10.95%-17.77% of phenotypic variance, with the highest LOD score being 5.96 for qTSS.AS.pau-6.2. Thirteen QTLs detected across multiple environments with BLUPs indicate stability and utility in a future breeding program for guava. Furthermore, seven QTL clusters with stable or common individual QTLs affecting two or more different traits were located on six linkage groups (LGs), explaining the correlation among fruit-quality traits. Thus, the multiple environmental evaluations conducted here have increased our understanding of the molecular basis of phenotypic variation, providing the basis for future high-resolution fine-mapping and paving the way for marker-assisted breeding of fruit-quality traits.

Validation of Novel spot blotch disease resistance alleles identified in unexplored wheat (Triticum aestivum L.) germplasm lines through KASP markers.

BACKGROUND: During the last few decades, the diverse sources of resistance, several genes and QTLs for spot blotch resistance have been identified. However, a large set of germplasm lines are still unexplored that have the potential to develop highly resistant wheat cultivars for the target environments. Therefore, the identification of new sources of resistance to spot blotch is essential for breeding programmes to develop spot blotch resistant cultivars and sustain wheat production. The association mapping panel of 294 diverse bread wheat accessions was used to explore new sources of spot blotch disease resistance and to identify genomic regions using genome wide association analysis (GWAS). The genotypes were tested in replicated trials for spot blotch disease at three major hot spots in India (Varanasi in UP, Pusa in Bihar, and Cooch Behar in West Bengal). The area under the disease progress curve (AUDPC) was calculated to assess the level of resistance in each genotype. RESULTS: A total of 19 highly and 76 moderately resistant lines were identified. Three accessions (EC664204, IC534306 and IC535188) were nearly immune to spot blotch disease. The genotyping of all accessions resulted in a total of 16,787 high-quality polymorphic SNPs. The GWAS was performed using a Compressed Mixed Linear Model (CMLM) and a Mixed Linear Model (MLM). A total of seven significant MTAs, common in both the models and consistent across the environment, were further validated to develop KASP markers. Four MTAs (AX-94710084, AX-94865722, AX-95135556, and AX-94529408) on three chromosomes (2AL, 2BL, and 3BL) have been successfully validated through the KASP marker. CONCLUSIONS: The new source of resistance was identified from unexplored germplasm lines. The genomic regions identified through GWAS were validated through KASP markers. The marker information and the highly resistant sources are valuable resources to rapidly develop immune or near immune wheat varieties.

Genome-wide Association Study for Yield and Yield-Related Traits in Diverse Blackgram Panel (Vigna mungo L. Hepper) Reveals Novel Putative Alleles for Future Breeding Programs.

Blackgram (Vigna mungo L. Hepper) is an important tropical and sub-tropical short-duration legume that is rich in dietary protein and micronutrients. Producing high-yielding blackgram varieties is hampered by insufficient genetic variability, absence of suitable ideotypes, low harvest index and susceptibility to biotic-abiotic stresses. Seed yield, a complex trait resulting from the expression and interaction of multiple genes, necessitates the evaluation of diverse germplasm for the identification of novel yield contributing traits. Henceforth, a panel of 100 blackgram genotypes was evaluated at two locations (Ludhiana and Gurdaspur) across two seasons (Spring 2019 and Spring 2020) for 14 different yield related traits. A wide range of variability, high broad-sense heritability and a high correlation of grain yield were observed for 12 out of 14 traits studied among all environments. Investigation of population structure in the panel using a set of 4,623 filtered SNPs led to identification of four sub-populations based on ad-hoc delta K and Cross entropy value. Using Farm CPU model and Mixed Linear Model algorithms, a total of 49 significant SNP associations representing 42 QTLs were identified. Allelic effects were found to be statistically significant at 37 out of 42 QTLs and 50 known candidate genes were identified in 24 of QTLs.

Marker-assisted introgression of genes into rye translocation leads to the improvement in bread making quality of wheat (Triticum aestivum L.).

Introgression of genes from related species can be a powerful way to genetically improve crop yields, but selection for one trait can come at the cost to others. Wheat varieties with translocation of the short arm of chromosome 1 from the B genome of wheat (1BS) with the short arm of chromosome 1 from rye (1RS) are popular globally for their positive effect on yield and stress resistance. Unfortunately, this translocation (1BL.1RS) is also associated with poor bread making quality, mainly due to the presence of Sec-1 on its proximal end, encoding secalin proteins, and the absence of Glu-B3/Gli-B1-linked loci on its distal end, encoding low molecular weight glutenin subunits (LMW-GS). The present study aims to replace these two important loci on the 1RS arm with the wheat 1BS loci, in two popular Indian wheat varieties, PBW550 and DBW17, to improve their bread-making quality. Two donor lines in the cultivar Pavon background with absence of the Sec-1 locus and presence of the Glu-B3/Gli-B1 locus, respectively, were crossed and backcrossed with these two selected wheat varieties. In the advancing generations, marker assisted foreground selection was done for Sec-1- and Glu-B3/Gli-B1+ loci while recurrent parent recovery was done with the help of SSR markers. BC2F5 and BC2F6 near isosgenic lines (NILs) with absence of Sec-1 and presence of Glu-B3/Gli-B1 loci were evaluated for two years in replicated yield trials. As a result of this selection, thirty promising lines were generated that demonstrated improved bread making quality but also balanced with improved yield-related traits compared to the parental strains. The study demonstrates the benefits of using marker-assisted selection to replace a few loci with negative effects within larger alien translocations for crop improvement.

Residual effect of defeated stripe rust resistance genes/QTLs in bread wheat against prevalent pathotypes of Puccinia striiformis f. sp. tritici.

The periodic breakdowns of stripe rust resistance due to emergence of new virulent and more aggressive pathotypes of Puccinia striiformis f. sp. tritici have resulted in severe epidemics in India. This necessitates the search for new and more durable resistance sources against stripe rust. The three bread wheat cultivars PBW 343 (carries Yr9 and Yr27), PBW 621 (carries Yr17) and HD 2967 (gene not known) were highly popular among the farmers after their release in 2011. But presently all three cultivars are highly susceptible to stripe rust at seedling as well as at adult plant stages as their resistance has been broken down due to emergence of new pathotypes of the pathogen (110S119, 238S119). In previous study, the crosses of PBW 621 with PBW 343 and HD 2967 and evaluation of further generations (up to F4) against pathotype 78S84 resulted in resistant segregants. In the present study, the F5 and F6 RIL populations have been evaluated against new pathotypes of Pst. The RILs categorized based on the disease severity on the P (Penultimate leaf) and F (flag) leaf into three categories i.e., high, moderate and low level of APR (adult plant resistance) having 1-200, 201-400 and >400 values of AUDPC, respectively, upon infection with stripe rust. The various APR components (latent period, lesion growth rate, spore production and uredial density) were studied on each category, i.e., resistant, moderately resistant and susceptible. The values of APR parameters decreased as the level of resistance increased. Based on molecular analysis, the lines (representing different categories of cross PBW 621 X PBW 343) containing the genes Yr9 and Yr17 due to their interactive effect provide resistance. Based on BSA using 35k SNPs and KASP markers association with phenotypic data of the RIL population (PBW 621 X HD 2967) showed the presence of two QTLs (Q.Pst.pau-6B, Q.Pst.pau-5B) responsible for the residual resistance and two SNPs AX-94891670 and AX-94454107 were found to be associated with the trait of interest on chromosome 6B and 5B respectively. The present study concludes that in the population of both the crosses (PBW 621 X PBW 343 and PBW 621 X HD 2967) major defeated gene contributed towards residual resistance by interacting with minor gene/QTLs.

Increased Predictive Accuracy of Multi-Environment Genomic Prediction Model for Yield and Related Traits in Spring Wheat (Triticum aestivum L.).

Genomic selection (GS) has the potential to improve the selection gain for complex traits in crop breeding programs from resource-poor countries. The GS model performance in multi-environment (ME) trials was assessed for 141 advanced breeding lines under four field environments via cross-predictions. We compared prediction accuracy (PA) of two GS models with or without accounting for the environmental variation on four quantitative traits of significant importance, i.e., grain yield (GRYLD), thousand-grain weight, days to heading, and days to maturity, under North and Central Indian conditions. For each trait, we generated PA using the following two different ME cross-validation (CV) schemes representing actual breeding scenarios: (1) predicting untested lines in tested environments through the ME model (ME_CV1) and (2) predicting tested lines in untested environments through the ME model (ME_CV2). The ME predictions were compared with the baseline single-environment (SE) GS model (SE_CV1) representing a breeding scenario, where relationships and interactions are not leveraged across environments. Our results suggested that the ME models provide a clear advantage over SE models in terms of robust trait predictions. Both ME models provided 2-3 times higher prediction accuracies for all four traits across the four tested environments, highlighting the importance of accounting environmental variance in GS models. While the improvement in PA from SE to ME models was significant, the CV1 and CV2 schemes did not show any clear differences within ME, indicating the ME model was able to predict the untested environments and lines equally well. Overall, our results provide an important insight into the impact of environmental variation on GS in smaller breeding programs where these programs can potentially increase the rate of genetic gain by leveraging the ME wheat breeding trials.

Evaluations of Genomic Prediction and Identification of New Loci for Resistance to Stripe Rust Disease in Wheat (Triticum aestivum L.).

Stripe rust is one of the most destructive diseases of wheat (Triticum aestivum L.), caused by Puccinia striiformis f. sp. tritici (Pst), and responsible for significant yield losses worldwide. Single-nucleotide polymorphism (SNP) diagnostic markers were used to identify new sources of resistance at adult plant stage to wheat stripe rust (YR) in 141 CIMMYT advanced bread wheat lines over 3 years in replicated trials at Borlaug Institute for South Asia (BISA), Ludhiana. We performed a genome-wide association study and genomic prediction to aid the genetic gain by accumulating disease resistance alleles. The responses to YR in 141 advanced wheat breeding lines at adult plant stage were used to generate G × E (genotype × environment)-dependent rust scores for prediction and genome-wide association study (GWAS), eliminating variation due to climate and disease pressure changes. The lowest mean prediction accuracies were 0.59 for genomic best linear unbiased prediction (GBLUP) and ridge-regression BLUP (RRBLUP), while the highest mean was 0.63 for extended GBLUP (EGBLUP) and random forest (RF), using 14,563 SNPs and the G × E rust score results. RF and EGBLUP predicted higher accuracies (∼3%) than did GBLUP and RRBLUP. Promising genomic prediction demonstrates the viability and efficacy of improving quantitative rust tolerance. The resistance to YR in these lines was attributed to eight quantitative trait loci (QTLs) using the FarmCPU algorithm. Four (Q.Yr.bisa-2A.1, Q.Yr.bisa-2D, Q.Yr.bisa-5B.2, and Q.Yr.bisa-7A) of eight QTLs linked to the diagnostic markers were mapped at unique loci (previously unidentified for Pst resistance) and possibly new loci. The statistical evidence of effectiveness and distribution of the new diagnostic markers for the resistance loci would help to develop new stripe rust resistance sources. These diagnostic markers along with previously established markers would be used to create novel DNA biosensor-based microarrays for rapid detection of the resistance loci on large panels upon functional validation of the candidate genes identified in the present study to aid in rapid genetic gain in the future breeding programs.

Development of Genome-Wide Functional Markers Using Draft Genome Assembly of Guava (Psidium guajava L.) cv. Allahabad Safeda to Expedite Molecular Breeding.

Guava (Psidium guajava L.), a rich source of nutrients, is an important tropical and subtropical fruit of the Myrtaceae family and exhibits magnificent diversity. Genetic diversity analysis is the first step toward the identification of parents for hybridization, genetic mapping, and molecular breeding in any crop species. A diversity analysis based on whole-genome functional markers increases the chances of identifying genetic associations with agronomically important traits. Therefore, here, we sequenced the genome of guava cv. Allahabad Safeda on an Illumina platform and generated a draft assembly of ~304 MB. The assembly of the Allahabad Safeda genome constituted >37.95% repeat sequences, gene prediction with RNA-seq data as evidence identified 14,115 genes, and BLAST n/r, Interproscan, PfamScan, BLAST2GO, and KEGG annotated 13,957 genes. A comparative protein transcript analysis of tree species revealed the close relatedness of guava with Eucalyptus. Comparative transcriptomics-based SSR/InDel/SNP-PCR ready genome-wide markers in greenish-yellow skinned and white fleshed-Allahabad Safeda to four contrasting cultivars viz apple-color-skinned and white-fleshed-Lalima, greenish-yellow-skinned and pink-fleshed-Punjab Pink, purple-black-skinned and purple-fleshed-Purple Local and widely used rootstock-Lucknow-49 were developed. The molecular markers developed here revealed a high level of individual heterozygosity within genotypes in 22 phenotypically diverse guava cultivars. Principal coordinate, STRUCTURE clustering, and neighbor-joining-based genetic diversity analysis identified distinct clusters associated with fruit skin and flesh color. The genome sequencing of guava, functional annotation, comparative transcriptomics-based genome-wide markers, and genetic diversity analysis will expand the knowledge of genomes of climacteric fruits, facilitating trait-based molecular breeding and diversifying the nutritional basket.

Elucidating SNP-based genetic diversity and population structure of advanced breeding lines of bread wheat (Triticum aestivum L.).

Genetic diversity and population structure information are crucial for enhancing traits of interest and the development of superlative varieties for commercialization. The present study elucidated the population structure and genetic diversity of 141 advanced wheat breeding lines using single nucleotide polymorphism markers. A total of 14,563 high-quality identified genotyping-by-sequencing (GBS) markers were distributed covering 13.9 GB wheat genome, with a minimum of 1,026 SNPs on the homoeologous group four and a maximum of 2,838 SNPs on group seven. The average minor allele frequency was found 0.233, although the average polymorphism information content (PIC) and heterozygosity were 0.201 and 0.015, respectively. Principal component analyses (PCA) and population structure identified two major groups (sub-populations) based on SNPs information. The results indicated a substantial gene flow/exchange with many migrants (Nm = 86.428) and a considerable genetic diversity (number of different alleles, Na = 1.977; the number of effective alleles, Ne = 1.519; and Shannon's information index, I = 0.477) within the population, illustrating a good source for wheat improvement. The average PIC of 0.201 demonstrates moderate genetic diversity of the present evaluated advanced breeding panel. Analysis of molecular variance (AMOVA) detected 1% and 99% variance between and within subgroups. It is indicative of excessive gene traffic (less genetic differentiation) among the populations. These conclusions deliver important information with the potential to contribute new beneficial alleles using genome-wide association studies (GWAS) and marker-assisted selection to enhance genetic gain in South Asian wheat breeding programs.

Characterization and Mapping of Spot Blotch in Triticum durum-Aegilops speltoides Introgression Lines Using SNP Markers.

Spot blotch (SB) of wheat is emerging as a major threat to successful wheat production in warm and humid areas of the world. SB, also called leaf blight, is caused by Bipolaris sorokiniana, and is responsible for high yield losses in Eastern Gangetic Plains Zone in India. More recently, SB is extending gradually toward cooler, traditional wheat-growing North-Western part of the country which is a major contributor to the national cereal basket. Deployment of resistant cultivars is considered as the most economical and ecologically sound measure to avoid losses due to this disease. In the present study, 89 backcross introgression lines (DSBILs) derived from Triticum durum (cv. PDW274-susceptible) × Aegilops speltoides (resistant) were evaluated against SB for four consecutive years, 2016-2020. Phenotypic evaluation of these lines showed a continuous variation in disease severity indicating that the resistance to SB is certainly quantitative in nature. Phenotypic data of DSBILs were further used for mapping QTLs using SNPs obtained by genotyping by sequencing. To identify QTLs stable across the environments, Best Linear Unbiased Estimates (BLUEs) and Predictions (BLUPs) were used for mapping QTLs based on stepwise regression-based Likelihood Ratio Test (RSTEP-LRT) for additive effect of markers and single marker analysis (SMA). Five QTLs, Q.Sb.pau-2A, Q.Sb.pau-2B, Q.Sb.pau-3B, Q.Sb.pau-5B, and Q.Sb.pau-6A, linked to SB resistance were mapped across chromosomes 2A, 2B, 3B, 5B, and 6A. Genes found adjacent to the SNP markers linked to these QTLs were literature mined to identify possible candidate genes by studying their role in plant pathogenesis. Further, highly resistant DSBIL (DSBIL-13) was selected to cross with a susceptible hexaploidy cultivar (HD3086) generating BC2F1 population. The QTL Q.Sb.pau-5B, linked to SNP S5B_703858864, was validated on this BC2F1 population and thus, may prove to be a potential diagnostic marker for SB resistance.

New QTLs for Spot Blotch Disease Resistance in Wheat (Triticum aestivum L.) Using Genome-Wide Association Mapping.

Spot blotch disease caused by Bipolaris sorokiniana is a major constraint for wheat production in tropics and subtropics. The introgression of spot blotch resistance alleles to the disease susceptible lines is critical to securing the wheat production in these regions. Although genome-wide association studies (GWASs) for spot blotch were attempted earlier, the present study focused on identifying new quantitative trait loci (QTLs) for spot blotch under natural disease pressure in diverse field conditions. A total of 139 advanced spring wheat lines were evaluated in three environments (three years and two locations) in India and Bangladesh. The GWAS using 14,063 polymorphic genotyping-by-sequencing (GBS) markers identified eight QTLs associated with spot blotch disease resistance belonging to eight chromosomes across the wheat genome. Here, we report the identified marker-trait associations (MTAs), along with the allele effects associated with the disease. The functional annotation of the significant markers identified NBS-LRR, MADS-box transcription factor, and 34 other plant-related protein families across multiple chromosomal regions. The results indicate four promising new QTLs on chromosomes 1A (497.2 Mb), 1D (89.84 Mb), 2B (421.92 Mb), and 6D (6.84 Mb) associated with several disease resistance protein families. These results provide insights into new genomic regions associated with spot blotch disease, and with additional validation, could be utilized in disease resistance breeding efforts in wheat development.

Pyramiding of High Grain Weight With Stripe Rust and Leaf Rust Resistance in Elite Indian Wheat Cultivar Using a Combination of Marker Assisted and Phenotypic Selection.

Wheat (Triticum aestivum L.) is an important cereal crop globally as well as in India and yield improvement programs encounter a strong impediment from ever-evolving rust pathogens. Hence, durable rust resistance is always a priority trait for wheat breeders globally. Grain weight, represented as thousand grain weight (TGW), is the most important yield-contributing trait in wheat. In the present study high TGW has been transferred into two elite Indian wheat cultivars PBW343 and PBW550 from a high TGW genotype, Rye selection 111, selected from local germplasm. In the background of PBW343 and PBW550, an increase in TGW upto 27.34 and 18% was observed, respectively (with respect to recipient parents), through conventional backcross breeding with phenotypic selections in 3 years replicated RBD trials. Resistance to leaf rust and stripe rust has been incorporated in the high TGW version of PBW550 through marker assisted pyramiding of stripe rust resistance gene Yr15 using marker Xuhw302, and a pair of linked leaf rust and stripe rust resistance genes Lr57-Yr40 using marker Ta5DS-2754099_kasp23. Improved versions of PBW550 with increased TGW ranging from 45.0 to 46.2 g (up to a 9% increase) and stacked genes for stripe and leaf rust resistance have been developed. This study serves as proof of utilizing conventional breeding and phenotypic selection combined with modern marker assisted selection in improvement of important wheat cultivars as a symbiont of conventional and moderan techniques.