Delineating meta-quantitative trait loci for anthracnose resistance in common bean (Phaseolus vulgaris L.)

High Genetic Diversity in the Himalayan Common Bean (Phaseolus vulgaris) Germplasm with Divergence from Its Center of Origin in the Mesoamerica and Andes

The common bean is found in the Himalayan region of Pakistan with substantial morphological variability. Genetic diversity within any crop species is a precursor for genetic improvement; however, little is known about common bean genetic diversity in this region. We explored the genetic diversity in the common bean from the Himalayan region (Khyber Pakhtunkhwa, Gilgit-Baltistan, Kashmir) of Pakistan. Microsatellite genotyping was carried out for 147 samples with 40 simple sequence repeat (SSR) markers. The results revealed a clear divergence of the Pakistani population from the primary gene pool (with FST values of 0.2 with Andes and 0.27 with Mesoamerica). However, within the Himalayan germplasm, no clear evidence of spatial structure was observed (with the maximum FST values of only 0.025), probably due to the dispersal of seeds by human activity within the region. This was further elucidated by the discriminant analyses of principal components. Considering the diversity parameters, high genotypic diversity was observed for the indigenous lines (0.990), comparable to the primary gene pool (0.976 for Mesoamerica and 0.976 for Andes populations). A high genotypic diversity was observed within the Himalayan population (ranging from 0.500 for Upper Dir to 0.952 for Mansehra). Gene diversity across loci varied between 0.28 for Chitral to 0.38 for Kurram. Our results suggested a divergent and independent evolution of the Himalayan population, which might have led to the diversification of the common bean germplasm in the region postintroduction into the region. The diversity observed could also be exploited in future breeding programs for the development and introduction of climate-resilient varieties.

Comprehensive biochemical approach for understanding the interaction between host "common bean" and pathogen "Colletotrichum lindemuthianum" causing bean anthracnose

Anthracnose (ANT) caused by Colletotrichum lindemuthianum is the most devastating seed-borne fungal disease of common bean. In response to fungal infections, it is hypothesized that pathogen-plant interactions typically cause hypersensitive reactions by producing reactive oxygen species, hydrogen peroxide and lipid peroxidation of cell membranes. esent study was conducted by inoculating susceptible bean genotype "SB174" and resistant bean genotype "E10" with pathogen "C. lindemuthianum". Defense-related enzymes (ascorbate peroxidase, peroxidase, lipid peroxidase, and catalase) and C-based compounds (total phenols and flavonoids) were studied using the detached bean leaf method. Comparative defense response was studied in different plant tissues (pod, stem, and seed) in susceptible and resistant bean genotypes under uninoculated and pathogen-inoculated conditions. The host‒pathogen interaction was studied at mock inoculation, 2, 4 and 6 days after inoculation (dai). Comparing the pathogen-inoculated bean leaves to water-treated bean leaves, defense enzymes as well as total phenols and flavonoids exhibited differential expression. In a comparative study, the enzyme activity also displayed differential biochemical responses in pods, stems and seeds in both contrasting genotypes. For example, 5.1-fold (pod), 1.5-fold (stem) and 1.06-fold (seed) increases in ascorbate peroxidase activity were observed in the susceptible genotype at 6 dai compared to mock inoculation. Similarly, catalase activity in pods was upregulated (1.47-fold) in the resistant genotype and downregulated (1.30-fold) in the susceptible genotype at 6 dai. The study revealed that defense-related antioxidative enzymes, phenols and flavonoids are fine-tuned to detoxify important reactive oxygen species (ROS) molecules, induce systemic resistance and are successfully controlled in common bean plants against pathogen invasion.

Unravelling the genetic framework associated with grain quality and yield-related traits in maize (Zea mays L.)

Maize serves as a crucial nutrient reservoir for a significant portion of the global population. However, to effectively address the growing world population's hidden hunger, it is essential to focus on two key aspects: biofortification of maize and improving its yield potential through advanced breeding techniques. Moreover, the coordination of multiple targets within a single breeding program poses a complex challenge. This study compiled mapping studies conducted over the past decade, identifying quantitative trait loci associated with grain quality and yield related traits in maize. Meta-QTL analysis of 2,974 QTLs for 169 component traits (associated with quality and yield related traits) revealed 68 MQTLs across different genetic backgrounds and environments. Most of these MQTLs were further validated using the data from genome-wide association studies (GWAS). Further, ten MQTLs, referred to as breeding-friendly MQTLs (BF-MQTLs), with a significant phenotypic variation explained over 10% and confidence interval less than 2 Mb, were shortlisted. BF-MQTLs were further used to identify potential candidate genes, including 59 genes encoding important proteins/products involved in essential metabolic pathways. Five BF-MQTLs associated with both quality and yield traits were also recommended to be utilized in future breeding programs. Synteny analysis with wheat and rice genomes revealed conserved regions across the genomes, indicating these hotspot regions as validated targets for developing biofortified, high-yielding maize varieties in future breeding programs. After validation, the identified candidate genes can also be utilized to effectively model the plant architecture and enhance desirable quality traits through various approaches such as marker-assisted breeding, genetic engineering, and genome editing.

Comprehensive meta-QTL analysis for dissecting the genetic architecture of stripe rust resistance in bread wheat

BACKGROUND

Yellow or stripe rust, caused by the fungus Puccinia striiformis f. sp. tritici (Pst) is an important disease of wheat that threatens wheat production. Since developing resistant cultivars offers a viable solution for disease management, it is essential to understand the genetic basis of stripe rust resistance. In recent years, meta-QTL analysis of identified QTLs has gained popularity as a way to dissect the genetic architecture underpinning quantitative traits, including disease resistance.

RESULTS

Systematic meta-QTL analysis involving 505 QTLs from 101 linkage-based interval mapping studies was conducted for stripe rust resistance in wheat. For this purpose, publicly available high-quality genetic maps were used to create a consensus linkage map involving 138,574 markers. This map was used to project the QTLs and conduct meta-QTL analysis. A total of 67 important meta-QTLs (MQTLs) were identified which were refined to 29 high-confidence MQTLs. The confidence interval (CI) of MQTLs ranged from 0 to 11.68 cM with a mean of 1.97 cM. The mean physical CI of MQTLs was 24.01 Mb, ranging from 0.0749 to 216.23 Mb per MQTL. As many as 44 MQTLs colocalized with marker-trait associations or SNP peaks associated with stripe rust resistance in wheat. Some MQTLs also included the following major genes- Yr5, Yr7, Yr16, Yr26, Yr30, Yr43, Yr44, Yr64, YrCH52, and YrH52. Candidate gene mining in high-confidence MQTLs identified 1,562 gene models. Examining these gene models for differential expressions yielded 123 differentially expressed genes, including the 59 most promising CGs. We also studied how these genes were expressed in wheat tissues at different phases of development.

CONCLUSION

The most promising MQTLs identified in this study may facilitate marker-assisted breeding for stripe rust resistance in wheat. Information on markers flanking the MQTLs can be utilized in genomic selection models to increase the prediction accuracy for stripe rust resistance. The candidate genes identified can also be utilized for enhancing the wheat resistance against stripe rust after in vivo confirmation/validation using one or more of the following methods: gene cloning, reverse genetic methods, and omics approaches.

Meta-QTL Analysis for Yield Components in Common Bean (Phaseolus vulgaris L.)

Common bean is one of the most important legumes produced and consumed worldwide because it is a highly valuable food for the human diet. However, its production is mainly carried out by small farmers, who obtain average grain yields below the potential yield of the species. In this sense, numerous mapping studies have been conducted to identify quantitative trait loci (QTL) associated with yield components in common bean. Meta-QTL (MQTL) analysis is a useful approach to combine data sets and for creating consensus positions for the QTL detected in independent studies. Consequently, the objective of this study was to perform a MQTL analysis to identify the most reliable and stable genomic regions associated with yield-related traits of common bean. A total of 667 QTL associated with yield-related traits reported in 21 different studies were collected. A total of 42 MQTL associated with yield-related traits were identified, in which the average confidence interval (CI) of the MQTL was 3.41 times lower than the CIs of the original QTL. Most of the MQTL (28) identified in this study contain QTL associated with yield and phenological traits; therefore, these MQTL can be useful in common bean breeding programs. Finally, a total of 18 candidate genes were identified and associated with grain yield within these MQTL, with functions related to ubiquitin ligase complex, response to auxin, and translation elongation factor activity.

Genetic mapping of the Andean anthracnose resistance gene present in the common bean cultivar BRSMG Realce

The rajado seeded Andean bean (Phaseolus vulgaris L.) cultivar BRSMG Realce (striped seed coat) developed by Embrapa expressed a high level of anthracnose resistance, caused by Colletotrichum lindemuthianum, in field and greenhouse screenings. The main goal of this study was to evaluate the inheritance of anthracnose resistance in BRSMG Realce, map the resistance locus or major gene cluster previously named as Co-Realce, identify resistance-related positional genes, and analyze potential markers linked to the resistance allele. F₂ plants derived from the cross BRSMG Realce × BRS FC104 (Mesoamerican) and from the cross BRSMG Realce × BRS Notável (Mesoamerican) were inoculated with the C. lindemuthianum races 475 and 81, respectively. The BRSMG Realce × BRS FC104 F₂ population was also genotyped using the DArTseq technology. Crosses between BRSMG Realce and BAT 93 (Mesoamerican) were also conducted and resulting F₂ plants were inoculated with the C. lindemuthianum races 65 and 1609, individually. The results shown that anthracnose resistance in BRSMG Realce is controlled by a single locus with complete dominance. A genetic map including 1,118 SNP markers was built and shown 78% of the markers mapped at a distances less than 5.0 cM, with a total genetic length of 4,473.4 cM. A major locus (Co-Realce) explaining 54.6% of the phenotypic variation of symptoms caused by the race 475 was identified in Pv04, flanked by the markers snp1327 and snp12782 and 4.48 cM apart each other. These SNPs are useful for marker-assisted selection, due to an estimated selection efficiency of 99.2%. The identified resistance allele segregates independently of the resistance allele Co-3³ (Pv04) present in BAT 93. The mapped genomic region with 704,867 bp comprising 63 putative genes, 44 of which were related to the pathogen-host interaction. Based on all these results and evidence, anthracnose resistance in BRSMG Realce should be considered as monogenic, useful for breeding purpose. It is proposed that locus Co-Realce is unique and be provisionally designated as CoPv04^R until be officially nominated in accordance with the rules established by the Bean Improvement Cooperative Genetics Committee.

Genome-wide meta-QTL analyses provide novel insight into disease resistance repertoires in common bean

BACKGROUND

Common bean (Phaseolus vulgaris) is considered a staple food in a number of developing countries. Several diseases attack the crop leading to substantial economic losses around the globe. However, the crop has rarely been investigated for multiple disease resistance traits using Meta-analysis approach.

RESULTS AND CONCLUSIONS

In this study, in order to identify the most reliable and stable quantitative trait loci (QTL) conveying disease resistance in common bean, we carried out a meta-QTL (MQTL) analysis using 152 QTLs belonging to 44 populations reported in 33 publications within the past 20 years. These QTLs were decreased into nine MQTLs and the average of confidence interval (CI) was reduced by 2.64 folds with an average of 5.12 cM in MQTLs. Uneven distribution of MQTLs across common bean genome was noted where sub-telomeric regions carry most of the corresponding genes and MQTLs. One MQTL was identified to be specifically associated with resistance to halo blight disease caused by the bacterial pathogen Pseudomonas savastanoi pv. phaseolicola, while three and one MQTLs were specifically associated with resistance to white mold and anthracnose caused by the fungal pathogens Sclerotinia sclerotiorum and Colletotrichum lindemuthianum, respectively. Furthermore, two MQTLs were detected governing resistance to halo blight and anthracnose, while two MQTLs were detected for resistance against anthracnose and white mold, suggesting putative genes governing resistance against these diseases at a shared locus. Comparative genomics and synteny analyses provide a valuable strategy to identify a number of well‑known functionally described genes as well as numerous putative novels candidate genes in common bean, Arabidopsis and soybean genomes.

Consensus genomic regions associated with grain protein content in hexaploid and tetraploid wheat

A meta-analysis of QTLs associated with grain protein content (GPC) was conducted in hexaploid and tetraploid wheat to identify robust and stable meta-QTLs (MQTLs). For this purpose, as many as 459 GPC-related QTLs retrieved from 48 linkage-based QTL mapping studies were projected onto the newly developed wheat consensus map. The analysis resulted in the prediction of 57 MQTLs and 7 QTL hotspots located on all wheat chromosomes (except chromosomes 1D and 4D) and the average confidence interval reduced 2.71-fold in the MQTLs and QTL hotspots compared to the initial QTLs. The physical regions occupied by the MQTLs ranged from 140 bp to 224.02 Mb with an average of 15.2 Mb, whereas the physical regions occupied by QTL hotspots ranged from 1.81 Mb to 36.03 Mb with a mean of 8.82 Mb. Nineteen MQTLs and two QTL hotspots were also found to be co-localized with 45 significant SNPs identified in 16 previously published genome-wide association studies in wheat. Candidate gene (CG) investigation within some selected MQTLs led to the identification of 705 gene models which also included 96 high-confidence CGs showing significant expressions in different grain-related tissues and having probable roles in GPC regulation. These significantly expressed CGs mainly involved the genes/gene families encoding for the following proteins: aminotransferases, early nodulin 93, glutamine synthetases, invertase/pectin methylesterase inhibitors, protein BIG GRAIN 1-like, cytochrome P450, glycosyl transferases, hexokinases, small GTPases, UDP-glucuronosyl/UDP-glucosyltransferases, and EamA, SANT/Myb, GNAT, thioredoxin, phytocyanin, and homeobox domains containing proteins. Further, eight genes including GPC-B1, Glu-B1-1b, Glu-1By9, TaBiP1, GSr, TaNAC019-A, TaNAC019-D, and bZIP-TF SPA already known to be associated with GPC were also detected within some of the MQTL regions confirming the efficacy of MQTLs predicted during the current study.