Meta-QTL for resistance to white mold in common bean

Screening for resistance to four fungal diseases and associated genomic regions in a snap bean diversity panel

Anthracnose, white mold, powdery mildew, and root rot caused by Colletotrichum lindemuthianum, Scletorinia sclerotiorum, Erysiphe spp., and Pythium ultimum, respectively, are among the most frequent diseases that cause significant production losses worldwide in common bean (Phaseolus vulgaris L.). Reactions against these four fungal diseases were investigated under controlled conditions using a diversity panel of 311 bean lines for snap consumption (Snap bean Panel). The genomic regions involved in these resistance responses were identified based on a genome-wide association study conducted with 16,242 SNP markers. The highest number of resistant lines was observed against the three C. lindemuthianum isolates evaluated: 156 lines were resistant to CL124 isolate, 146 lines resistant to CL18, and 109 lines were resistant to C531 isolate. Two well-known anthracnose resistance clusters were identified, the Co-2 on chromosome Pv11 for isolates CL124 and CL18, and the Co-3 on chromosome Pv04 for isolates CL124 and C531. In addition, other lesser-known regions of anthracnose resistance were identified on chromosomes Pv02, Pv06, Pv08, and Pv10. For the white mold isolate tested, 24 resistant lines were identified and the resistance was localized to three different positions on chromosome Pv08. For the powdery mildew local isolate, only 12 resistant lines were identified, and along with the two previous resistance genes on chromosomes Pv04 and Pv11, a new region on chromosome Pv06 was also identified. For root rot caused by Pythium, 31 resistant lines were identified and two main regions were located on chromosomes Pv04 and Pv05. Relevant information for snap bean breeding programs was provided in this work. A total of 20 lines showed resistant or intermediate responses against four or five isolates, which can be suitable for sustainable farm production and could be used as resistance donors. Potential genes and genomic regions to be considered for targeted improvement were provided, including new or less characterized regions that should be validated in future works. Powdery mildew disease was identified as a potential risk for snap bean production and should be considered a main goal in breeding programs.

Genome-Wide Association Study Reveals a QTL Region for Ashy Stem Blight Resistance in PRA154 Andean Common Bean

Ashy stem blight (ASB) caused by Macrophomina phaseolina (Tassi) Goidanich affects the common bean (Phaseolus vulgaris L.) at all growing stages. Higher levels of resistance were observed in Andean common beans, but specific resistant quantitative trait loci (QTLs) conferring resistance to this pathogen have not been reported in this gene pool. The objectives of this research were to: (i) conduct a genome-wide association study (GWAS) and QTL mapping for resistance in the Andean breeding line PRA154; and (ii) identify single nucleotide polymorphism (SNP) markers and candidate genes for ASB resistance. Phenotyping was conducted under greenhouse conditions by inoculating the 107 F6:7 recombinant inbred lines (RILs) derived from the cross between the susceptible cultivar 'Verano' and the partial-resistant breeding line PRA154 twice with the M. phaseolina isolate PRI21. Genotyping was performed with 109,040 SNPs distributed across all 11 P. vulgaris chromosomes. A novel major QTL was located between 28,761,668 and 31,263,845 bp, extending 2.5 Mbp on chromosome Pv07, and the highest significant SNP markers were Chr07_28761668_A_G, Chr07_29131720_G_A, and Chr07_31263845_C_T with the highest LOD (more than 10 in most of the cases) and R-squared values, explaining 40% of the phenotypic variance of the PRI21 isolate. The gene Phvul.007G173900 (methylcrotonyl-CoA carboxylase alpha chain and mitochondrial 3-methylcrotonyl-CoA carboxylase 1 [MCCA]) with a size of 10,891 bp, located between 29,131,591 and 29,142,481 bp on Pv07, was identified as one candidate for ASB resistance in PRA154, and it contained Chr07_29131720_G_A. The QTL and genetic marker information could be used to assist common bean breeders to develop germplasm and cultivars with ASB resistance through molecular breeding.

Integrating de novo QTL-seq and linkage mapping to identify quantitative trait loci conditioning physiological resistance and avoidance to white mold disease in dry bean

White mold (WM), caused by the ubiquitous fungus Sclerotinia sclerotiorum, is a devastating disease that limits production and quality of dry bean globally. In the present study, classic linkage mapping combined with QTL-seq were employed in two recombinant inbred line (RIL) populations, "Montrose"/I9365-25 (M25) and "Raven"/I9365-31 (R31), with the initial goal of fine-mapping QTL WM5.4 and WM7.5 that condition WM resistance. The RILs were phenotyped for WM reactions under greenhouse (straw test) and field environments. The general region of WM5.4 and WM7.5 were reconfirmed with both mapping strategies within each population. Combining the results from both mapping strategies, WM5.4 was delimited to a 22.60-36.25 Mb interval in the heterochromatic regions on Pv05, while WM7.5 was narrowed to a 0.83 Mb (3.99-4.82 Mb) region on the Pv07 chromosome. Furthermore, additional QTL WM2.2a (3.81-7.24 Mb), WM2.2b (11.18-17.37 Mb, heterochromatic region), and WM2.2c (23.33-25.94 Mb) were mapped to a narrowed genomic interval on Pv02 and WM4.2 in a 0.89 Mb physical interval at the distal end of Pv04 chromosome. Gene models encoding gibberellin 2-oxidase proteins regulating plant architecture are likely candidate genes associated with WM2.2a resistance. Nine gene models encoding a disease resistance protein (quinone reductase family protein and ATWRKY69) found within the WM5.4 QTL interval are putative candidate genes. Clusters of 13 and 5 copies of gene models encoding cysteine-rich receptor-like kinase and receptor-like protein kinase-related family proteins, respectively, are potential candidate genes associated with WM7.5 resistance and most likely trigger physiological resistance to WM. Acquired knowledge of the narrowed major QTL intervals, flanking markers, and candidate genes provides promising opportunities to develop functional molecular markers to implement marker-assisted selection for WM resistant dry bean cultivars.

Meta-analysis of the quantitative trait loci associated with agronomic traits, fertility restoration, disease resistance, and seed quality traits in pigeonpea (Cajanus cajan L.)

A meta-analysis of quantitative trait loci (QTLs), associated with agronomic traits, fertility restoration, disease resistance, and seed quality traits was conducted for the first time in pigeonpea (Cajanus cajan L.). Data on 498 QTLs was collected from 9 linkage mapping studies (involving 21 biparental populations). Of these 498, 203 QTLs were projected onto "PigeonPea_ConsensusMap_2022," saturated with 10,522 markers, which resulted in the prediction of 34 meta-QTLs (MQTLs). The average confidence interval (CI) of these MQTLs (2.54 cM) was 3.37 times lower than the CI of the initial QTLs (8.56 cM). Of the 34 MQTLs, 12 high-confidence MQTLs with CI (≤5 cM) and a greater number of initial QTLs (≥5) were utilized to extract 2255 gene models, of which 105 were believed to be associated with different traits under study. Furthermore, eight of these MQTLs were observed to overlap with several marker-trait associations or significant SNPs identified in previous genome-wide association studies. Furthermore, synteny and ortho-MQTL analyses among pigeonpea and four related legumes crops, such as chickpea, pea, cowpea, and French bean, led to the identification of 117 orthologous genes from 20 MQTL regions. Markers associated with MQTLs can be employed for MQTL-assisted breeding as well as to improve the prediction accuracy of genomic selection in pigeonpea. Additionally, MQTLs may be subjected to fine mapping, and some of the promising candidate genes may serve as potential targets for positional cloning and functional analysis to elucidate the molecular mechanisms underlying the target traits.

Linked candidate genes of different functions for white mold resistance in common bean (Phaseolus vulgaris L) are identified by multiple QTL mapping approaches

White mold (WM) is a major disease in common bean (Phaseolus vulgaris L.), and its complex quantitative genetic control limits the development of WM resistant cultivars. WM2.2, one of the nine meta-QTL with a major effect on WM tolerance, explains up to 35% of the phenotypic variation and was previously mapped to a large genomic interval on Pv02. Our objective was to narrow the interval of this QTL using combined approach of classic QTL mapping and QTL-based bulk segregant analysis (BSA), and confirming those results with Khufu de novo QTL-seq. The phenotypic and genotypic data from two RIL populations, 'Raven'/I9365-31 (R31) and 'AN-37'/PS02-029C-20 (Z0726-9), were used to select resistant and susceptible lines to generate subpopulations for bulk DNA sequencing. The QTL physical interval was determined by considering overlapping interval of the identified QTL or peak region in both populations by three independent QTL mapping analyses. Our findings revealed that meta-QTL WM2.2 consists of three regions, WM2.2a (4.27-5.76 Mb; euchromatic), WM 2.2b (12.19 to 17.61 Mb; heterochromatic), and WM2.2c (23.01-25.74 Mb; heterochromatic) found in both populations. Gene models encoding for gibberellin 2-oxidase 8, pentatricopeptide repeat, and heat-shock proteins are the likely candidate genes associated with WM2.2a resistance. A TIR-NBS-LRR class of disease resistance protein (Phvul.002G09200) and LRR domain containing family proteins are potential candidate genes associated with WM2.2b resistance. Nine gene models encoding disease resistance protein [pathogenesis-related thaumatin superfamily protein and disease resistance-responsive (dirigent-like protein) family protein etc] found within the WM2.2c QTL interval are putative candidate genes. WM2.2a region is most likely associated with avoidance mechanisms while WM2.2b and WM2.2c regions trigger physiological resistance based on putative candidate genes.

Genetic analysis of resistance to bean leaf crumple virus identifies a candidate LRR-RLK gene

Bean leaf crumple virus (BLCrV) is a novel begomovirus (family Geminiviridae, genus Begomovirus) infecting common bean (Phaseolus vulgaris L.), threatening bean production in Latin America. Genetic resistance is required to ensure yield stability and reduce the use of insecticides, yet the available resistance sources are limited. In this study, three common bean populations containing a total of 558 genotypes were evaluated in different yield and BLCrV resistance trials under natural infection in the field. A genome-wide association study identified the locus BLC7.1 on chromosome Pv07 at 3.31 Mbp, explaining 8 to 16% of the phenotypic variation for BLCrV resistance. In comparison, whole-genome regression models explained 51 to 78% of the variation and identified the same region on Pv07 to confer resistance. The most significantly associated markers were located within the gene model Phvul.007G040400, which encodes a leucine-rich repeat receptor-like kinase subfamily III member and is likely to be involved in the innate immune response against the virus. The allelic diversity within this gene revealed five different haplotype groups, one of which was significantly associated with BLCrV resistance. As the same genome region was previously reported to be associated with resistance against other geminiviruses affecting common bean, our study highlights the role of previous breeding efforts for virus resistance in the accumulation of positive alleles against newly emerging viruses. In addition, we provide novel diagnostic single-nucleotide polymorphism markers for marker-assisted selection to exploit BLC7.1 for breeding against geminivirus diseases in one of the most important food crops worldwide.

Genome-wide characterization of the common bean kinome: Catalog and insights into expression patterns and genetic organization

The protein kinase (PK) superfamily is one of the largest superfamilies in plants and is the core regulator of cellular signaling. Even considering this substantial importance, the kinome of common bean (Phaseolus vulgaris) has not been profiled yet. Here, we identified and characterised the complete set of kinases of common bean, performing an in-depth investigation with phylogenetic analyses and measurements of gene distribution, structural organization, protein properties, and expression patterns over a large set of RNA-Sequencing data. Being composed of 1,203 PKs distributed across all P. vulgaris chromosomes, this set represents 3.25% of all predicted proteins for the species. These PKs could be classified into 20 groups and 119 subfamilies, with a more pronounced abundance of subfamilies belonging to the receptor-like kinase (RLK)-Pelle group. In addition to provide a vast and rich reservoir of data, our study supplied insights into the compositional similarities between PK subfamilies, their evolutionary divergences, highly variable functional profile, structural diversity, and expression patterns, modeled with coexpression networks for investigating putative interactions associated with stress response.

In Silico Integrated Analysis of Genomic, Transcriptomic, and Proteomic Data Reveals QTL-Specific Genes for Bacterial Canker Resistance in Tomato (Solanum lycopersicum L.)

Bacterial canker of tomato, caused by Clavibacter michiganensis subsp. michiganensis (Cmm), is a devasting disease that leads to significant yield losses. Although QTLs originating from three wild species (Solanum arcanum, S. habrochaites, and S. pimpinellifolium) were identified, none of the QTLs was annotated for candidate gene identification. In the present study, a QTL-based physical map was constructed to reveal the meta-QTLs for Cmm resistance. As a result, seven major QTLs were mapped. Functional annotation of QTLs revealed 48 candidate genes. Additionally, experimentally validated Cmm resistance-related genes based on transcriptomic and proteomic studies were mapped in the genome and 25 genes were found to be located in the QTL regions. The present study is the first report to construct a physical map for Cmm resistance QTLs and identify QTL-specific candidate genes. The candidate genes identified in the present study are valuable targets for fine mapping and developing markers for marker-assisted selection in tomatoes for Cmm resistance breeding.

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.

Genome-Wide Association Study (GWAS) of White Mold Resistance in Snap Bean

White mold can result in snap bean yield losses of 90 to 100% when field conditions favor the pathogen. A genome-wide association study (GWAS) was conducted to detect loci significantly associated with white mold resistance in a panel of snap bean (Phaseolus vulgaris L.) cultivars. Two populations of snap bean were used in this study. The first population was the BeanCAP (Coordinated Agriculture Project) Snap Bean Diversity Panel (SBDP) (n = 136), and the second population was the Snap Bean Association Panel (SnAP) (n = 378). SBDP was evaluated for white mold reaction in the field in 2012 and 2013, and SnAP was screened in a greenhouse only using the seedling straw test in 2016. Two reference genomes representing the Andean and Middle American centers of domestication were utilized to align the genotyping-by-sequencing (GBS) data. A GWAS was performed using FarmCPU with one principal component after comparing five models. Thirty-four single-nucleotide polymorphisms (SNPs) significantly associated with white mold resistance were detected. Eleven significant SNPs were identified by the seedling straw test, and 23 significant SNPs were identified by field data. Fifteen SNPs were identified within a 100 kb window containing pentatricopeptide repeat (PPR)-encoding genes, and eleven were close to leucine-rich repeat (LRR)-encoding genes, suggesting that these two classes are of outsized importance for snap bean resistance to white mold.

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.

Characterization of fungal pathogens and germplasm screening for disease resistance in the main production area of the common bean in Argentina

The common bean (Phaseolus vulgaris L.) is the most important grain legume in the human diet, mainly in Africa and Latin America. Argentina is one of the five major producers of the common bean in the world, and the main cultivation areas are concentrated in the northwestern provinces of this country. Crop production of the common bean is often affected by biotic factors like some endemic fungal diseases, which exert a major economic impact on the region. The most important fungal diseases affecting the common bean in Argentina are white mold caused by Sclerotinia sclerotiorum, angular leaf spot caused by Pseudocercospora griseola, web blight and root rot caused by Rhizoctonia solani, which can cause production losses of up to 100% in the region. At the present, the most effective strategy for controlling these diseases is the use of genetic resistance. In this sense, population study and characterization of fungal pathogens are essential for developing cultivars with durable resistance. In this review we report diversity studies carried out on these three fungal pathogens affecting the common bean in northwestern Argentina, analyzing more than 200 isolates by means of molecular, morphological and pathogenic approaches. Also, the screening of physiological resistance in several common bean commercial lines and wild native germplasm is reviewed. This review contributes to the development of sustainable management strategies and cultural practices in bean production aimed to minimize yield losses due to fungal diseases in the common bean.

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

Anthracnose, caused by the fungus Colletotrichum lindemuthianum, is one of the devastating disease affecting common bean production and productivity worldwide. Several quantitative trait loci (QTLs) for anthracnose resistance have been identified. In order to make use of these QTLs in common bean breeding programs, a detailed meta-QTL (MQTL) analysis has been conducted. For the MQTL analysis, 92 QTLs related to anthracnose disease reported in 18 different earlier studies involving 16 mapping populations were compiled and projected on to the consensus map. This meta-analysis led to the identification of 11 MQTLs (each involving QTLs from at least two different studies) on 06 bean chromosomes and 10 QTL hotspots each involving multiple QTLs from an individual study on 07 chromosomes. The confidence interval (CI) of the identified MQTLs was found 3.51 times lower than the CI of initial QTLs. Marker-trait associations (MTAs) reported in published genome-wide association studies (GWAS) were used to validate nine of the 11 identified MQTLs, with MQTL4.1 overlapping with as many as 40 MTAs. Functional annotation of the 11 MQTL regions revealed 1,251 genes including several R genes (such as those encoding for NBS-LRR domain-containing proteins, protein kinases, etc.) and other defense related genes. The MQTLs, QTL hotspots and the potential candidate genes identified during the present study will prove useful in common bean marker-assisted breeding programs and in basic studies involving fine mapping and cloning of genomic regions associated with anthracnose resistance in common beans.

Genetic Augmentation of Legume Crops Using Genomic Resources and Genotyping Platforms for Nutritional Food Security

Recent advances in next generation sequencing (NGS) technologies have led the surge of genomic resources for the improvement legume crops. Advances in high throughput genotyping (HTG) and high throughput phenotyping (HTP) enable legume breeders to improve legume crops more precisely and efficiently. Now, the legume breeder can reshuffle the natural gene combinations of their choice to enhance the genetic potential of crops. These genomic resources are efficiently deployed through molecular breeding approaches for genetic augmentation of important legume crops, such as chickpea, cowpea, pigeonpea, groundnut, common bean, lentil, pea, as well as other underutilized legume crops. In the future, advances in NGS, HTG, and HTP technologies will help in the identification and assembly of superior haplotypes to tailor the legume crop varieties through haplotype-based breeding. This review article focuses on the recent development of genomic resource databases and their deployment in legume molecular breeding programmes to secure global food security.

Molecular mechanisms underlying multi-level defense responses of horticultural crops to fungal pathogens

The horticultural industry helps to enrich and improve the human diet while contributing to growth of the agricultural economy. However, fungal diseases of horticultural crops frequently occur during pre- and postharvest periods, reducing yields and crop quality and causing huge economic losses and wasted food. Outcomes of fungal diseases depend on both horticultural plant defense responses and fungal pathogenicity. Plant defense responses are highly sophisticated and are generally divided into preformed and induced defense responses. Preformed defense responses include both physical barriers and phytochemicals, which are the first line of protection. Induced defense responses, which include innate immunity (pattern-triggered immunity and effector-triggered immunity), local defense responses, and systemic defense signaling, are triggered to counterstrike fungal pathogens. Therefore, to develop regulatory strategies for horticultural plant resistance, a comprehensive understanding of defense responses and their underlying mechanisms is critical. Recently, integrated multi-omics analyses, CRISPR-Cas9-based gene editing, high-throughput sequencing, and data mining have greatly contributed to identification and functional determination of novel phytochemicals, regulatory factors, and signaling molecules and their signaling pathways in plant resistance. In this review, research progress on defense responses of horticultural crops to fungal pathogens and novel regulatory strategies to regulate induction of plant resistance are summarized, and then the problems, challenges, and future research directions are examined.

New genomic regions associated with white mold resistance in dry bean using a MAGIC population

Dry bean (Phaseolus vulgaris L.) production in many regions is threatened by white mold (WM) [Sclerotinia sclerotiorum (Lib.) de Bary]. Seed yield losses can be up to 100% under conditions favorable for the pathogen. The low heritability, polygenic inheritance, and cumbersome screening protocols make it difficult to breed for improved genetic resistance. Some progress in understanding genetic resistance and germplasm improvement has been accomplished, but cultivars with high levels of resistance are yet to be released. A WM multiparent advanced generation inter-cross (MAGIC) population (n = 1060) was developed to facilitate mapping and breeding efforts. A seedling straw test screening method provided a quick assay to phenotype the population for response to WM isolate 1980. Nineteen MAGIC lines were identified with improved resistance. For genome-wide association studies (GWAS), the data was transformed into three phenotypic distributions-quantitative, polynomial, and binomial-and coupled with ∼52,000 single-nucleotide polymorphisms (SNPs). The three phenotypic distributions identified 30 significant genomic intervals [-log₁₀ (P value) ≥ 3.0]. However, across distributions, four new genomic regions as well as two regions previously reported were found to be associated with resistance. Cumulative R² values were 57% for binomial distribution using 13 genomic intervals, 41% for polynomial using eight intervals, and 40% for quantitative using 11 intervals. New resistant germplasm as well as new genomic regions associated with resistance are now available for further investigation.

Genomic Approaches to Identify Molecular Bases of Crop Resistance to Diseases and to Develop Future Breeding Strategies

Plant diseases are responsible for substantial crop losses each year and affect food security and agricultural sustainability. The improvement of crop resistance to pathogens through breeding represents an environmentally sound method for managing disease and minimizing these losses. The challenge is to breed varieties with a stable and broad-spectrum resistance. Different approaches, from markers to recent genomic and 'post-genomic era' technologies, will be reviewed in order to contribute to a better understanding of the complexity of host-pathogen interactions and genes, including those with small phenotypic effects and mechanisms that underlie resistance. An efficient combination of these approaches is herein proposed as the basis to develop a successful breeding strategy to obtain resistant crop varieties that yield higher in increasing disease scenarios.

NAC Candidate Gene Marker for bgm-1 and Interaction With QTL for Resistance to Bean Golden Yellow Mosaic Virus in Common Bean

Genetic resistance is the primary means for control of Bean golden yellow mosaic virus (BGYMV) in common bean (Phaseolus vulgaris L.). Breeding for resistance is difficult because of sporadic and uneven infection across field nurseries. We sought to facilitate breeding for BGYMV resistance by improving marker-assisted selection (MAS) for the recessive bgm-1 gene and identifying and developing MAS for quantitative trait loci (QTL) conditioning resistance. Genetic linkage mapping in two recombinant inbred line populations and genome-wide association study (GWAS) in a large breeding population and two diversity panels revealed a candidate gene for bgm-1 and three QTL BGY4.1, BGY7.1, and BGY8.1 on independent chromosomes. A mutation (5 bp deletion) in a NAC (No Apical Meristem) domain transcriptional regulator superfamily protein gene Phvul.003G027100 on chromosome Pv03 corresponded with the recessive bgm-1 resistance allele. The five bp deletion in exon 2 starting at 20 bp (Pv03: 2,601,582) is expected to cause a stop codon at codon 23 (Pv03: 2,601,625), disrupting further translation of the gene. A T m -shift assay marker named PvNAC1 was developed to track bgm-1. PvNAC1 corresponded with bgm-1 across ∼1,000 lines which trace bgm-1 back to a single landrace "Garrapato" from Mexico. BGY8.1 has no effect on its own but exhibited a major effect when combined with bgm-1. BGY4.1 and BGY7.1 acted additively, and they enhanced the level of resistance when combined with bgm-1. T m -shift assay markers were generated for MAS of the QTL, but their effectiveness requires further validation.

Genome-Wide Association Study (GWAS) for Resistance to Sclerotinia sclerotiorum in Common Bean

White mold (WM) is a devastating fungal disease affecting common bean (Phaseolus vulgaris L.). In this research, a genome-wide association study (GWAS) for WM resistance was conducted using 294 lines of the Spanish diversity panel. One single-locus method and six multi-locus methods were used in the GWAS. Response to this fungus showed a continuous distribution, and 28 lines were identified as potential resistance sources, including lines of Andean and Mesoamerican origin, as well as intermediate lines between the two gene pools. Twenty-two significant associations were identified, which were organized into 15 quantitative trait intervals (QTIs) located on chromosomes Pv01, Pv02, Pv03, Pv04, Pv08, and Pv09. Seven of these QTIs were identified for the first time, whereas eight corresponded to chromosome regions previously identified in the WM resistance. In all, 468 genes were annotated in these regions, 61 of which were proposed potential candidate genes for WM resistance, based on their function related to the three main defense stages on the host: recognition (22), signal transduction (8), and defense response (31). Results obtained from this work will contribute to a better understanding of the complex quantitative resistance to WM in common bean and reveal information of significance for future breeding programs.

Characterization of black spot resistance in diploid roses with QTL detection, meta-analysis and candidate-gene identification

Two environmentally stable QTLs linked to black spot disease resistance in the Rosa wichurana genetic background were detected, in different connected populations, on linkage groups 3 and 5. Co-localization between R-genes and defense response genes was revealed via meta-analysis. The widespread rose black spot disease (BSD) caused by the hemibiotrophic fungus Diplocarpon rosae Wolf. is efficiently controlled with fungicides. However, in the actual context of reducing agrochemical use, the demand for rose bushes with higher levels of resistance has increased. Qualitative resistance conferred by major genes (Rdr genes) has been widely studied but quantitative resistance to BSD requires further investigation. In this study, segregating populations connected through the BSD resistant Rosa wichurana male parent were phenotyped for disease resistance over several years and locations. A pseudo-testcross approach was used, resulting in six parental maps across three populations. A total of 45 individual QTLs with significant effect on BSD resistance were mapped on the male maps (on linkage groups (LG) B3, B4, B5 and B6), and 12 on the female maps (on LG A1, A2, A3, A4 and A5). Two major regions linked to BSD resistance were identified on LG B3 and B5 of the male maps and were integrated into a consensus map built from all three of the male maps. A meta-analysis was used to narrow down the confidence intervals of individual QTLs from three populations by generating meta-QTLs. Two 'hot spots' or meta-QTLs were found per LG, enabling reduction of the confidence interval to 10.42 cM for B3 and 11.47 cM for B5. An expert annotation of NBS-LRR encoding genes of the genome assembly of Hibrand et al. was performed and used to explore potential co-localization with R-genes. Co-localization with defense response genes was also investigated.

Mapping quantitative trait loci (QTLs) and estimating the epistasis controlling stem rot resistance in cultivated peanut (Arachis hypogaea)

A total of 33 additive stem rot QTLs were identified in peanut genome with nine of them consistently detected in multiple years or locations. And 12 pairs of epistatic QTLs were firstly reported for peanut stem rot disease. Stem rot in peanut (Arachis hypogaea) is caused by the Sclerotium rolfsii and can result in great economic loss during production. In this study, a recombinant inbred line population from the cross between NC 3033 (stem rot resistant) and Tifrunner (stem rot susceptible) that consists of 156 lines was genotyped by using 58 K peanut single nucleotide polymorphism (SNP) array and phenotyped for stem rot resistance at multiple locations and in multiple years. A linkage map consisting of 1451 SNPs and 73 simple sequence repeat (SSR) markers was constructed. A total of 33 additive quantitative trait loci (QTLs) for stem rot resistance were detected, and six of them with phenotypic variance explained of over 10% (qSR.A01-2, qSR.A01-5, qSR.A05/B05-1, qSR.A05/B05-2, qSR.A07/B07-1 and qSR.B05-1) can be consistently detected in multiple years or locations. Besides, 12 pairs of QTLs with epistatic (additive × additive) interaction were identified. An additive QTL qSR.A01-2 also with an epistatic effect interacted with a novel locus qSR.B07_1-1 to affect the percentage of asymptomatic plants in a row. A total of 193 candidate genes within 38 stem rot QTLs intervals were annotated with functions of biotic stress resistance such as chitinase, ethylene-responsive transcription factors and pathogenesis-related proteins. The identified stem rot resistance QTLs, candidate genes, along with the associated SNP markers in this study, will benefit peanut molecular breeding programs for improving stem rot resistance.

The genetic control of leaf allometry in the common bean, Phaseolus vulgaris

BACKGROUND

To maximize photosynthetic efficiency, plants have evolved a capacity by which leaf area scales allometrically with leaf mass through interactions with the environment. However, our understanding of genetic control of this allometric relationship remains limited.

RESULTS

We integrated allometric scaling laws expressed at static and ontogenetic levels into genetic mapping to identify the quantitative trait loci (QTLs) that mediate how leaf area scales with leaf mass and how such leaf allometry, under the control of these QTLs, varies as a response to environment change. A major QTL detected by the static model constantly affects the allometric growth of leaf area vs. leaf mass for the common bean (Phaseolus vulgaris) in two different environments. The ontogenetic model identified this QTL plus a few other QTLs that determine developmental trajectories of leaf allometry, whose expression is contingent heavily upon the environment.

CONCLUSIONS

Our results gain new insight into the genetic mechanisms of how plants program their leaf morphogenesis to adapt to environmental perturbations.

Recent Advances in Mechanisms of Plant Defense to Sclerotinia sclerotiorum

Sclerotinia sclerotiorum (Lib.) de Bary is an unusual pathogen which has the broad host range, diverse infection modes, and potential double feeding lifestyles of both biotroph and necrotroph. It is capable of infecting over 400 plant species found worldwide and more than 60 names have agriculturally been used to refer to diseases caused by this pathogen. Plant defense to S. sclerotiorum is a complex biological process and exhibits a typical quantitative disease resistance (QDR) response. Recent studies using Arabidopsis thaliana and crop plants have obtained new advances in mechanisms used by plants to cope with S. sclerotiorum infection. In this review, we focused on our current understanding on plant defense mechanisms against this pathogen, and set up a model for the defense process including three stages: recognition of this pathogen, signal transduction and defense response. We also have a particular interest in defense signaling mediated by diverse signaling molecules. We highlight the current challenges and unanswered questions in both the defense process and defense signaling. Essentially, we discussed candidate resistance genes newly mapped by using high-throughput experiments in important crops, and classified these potential gene targets into different stages of the defense process, which will broaden our understanding of the genetic architecture underlying quantitative resistance to S. sclerotiorum. We proposed that more powerful mapping population(s) will be required for accurate and reliable QDR gene identification.

Meta-QTL analysis of seed iron and zinc concentration and content in common bean (Phaseolus vulgaris L.)

Twelve meta-QTL for seed Fe and Zn concentration and/or content were identified from 87 QTL originating from seven population grown in sixteen field trials. These meta-QTL include 2 specific to iron, 2 specific to zinc and 8 that co-localize for iron and zinc concentrations and/or content. Common bean (Phaseolus vulgaris L.) is the most important legume for human consumption worldwide and it is an important source of microelements, especially iron and zinc. Bean biofortification breeding programs develop new varieties with high levels of Fe and Zn targeted for countries with human micronutrient deficiencies. Biofortification efforts thus far have relied on phenotypic selection of raw seed mineral concentrations in advanced generations. While numerous quantitative trait loci (QTL) studies have been conducted to identify genomic regions associated with increased Fe and Zn concentration in seeds, these results have yet to be employed for marker-assisted breeding. The objective of this study was to conduct a meta-analysis from seven QTL studies in Andean and Middle American intra- and inter-gene pool populations to identify the regions in the genome that control the Fe and Zn levels in seeds. Two meta-QTL specific to Fe and two meta-QTL specific to Zn were identified. Additionally, eight Meta QTL that co-localized for Fe and Zn concentration and/or content were identified across seven chromosomes. The Fe and Zn shared meta-QTL could be useful candidates for marker-assisted breeding to simultaneously increase seed Fe and Zn. The physical positions for 12 individual meta-QTL were identified and within five of the meta-QTL, candidate genes were identified from six gene families that have been associated with transport of iron and zinc in plants.

Integration of sudden death syndrome resistance loci in the soybean genome

KEY MESSAGE

Complexity and inconsistencies in resistance mapping publications of soybean sudden death syndrome (SDS) result in interpretation difficulty. This review integrates SDS mapping literature and proposes a new nomenclature system for reproducible SDS resistance loci. Soybean resistance to sudden death syndrome (SDS) is composed of foliar resistance to phytotoxins and root resistance to pathogen invasion. There are more than 80 quantitative trait loci (QTL) and dozens of single nucleotide polymorphisms (SNPs) associated with soybean resistance to SDS. The validity of these QTL and SNPs is questionable because of the complexity in phenotyping methodologies, the disease synergism between SDS and soybean cyst nematode (SCN), the variability from the interactions between soybean genotypes and environments, and the inconsistencies in the QTL nomenclature. This review organizes SDS mapping results and proposes the Rfv (resistance to Fusarium virguliforme) nomenclature based on supporting criteria described in the text. Among ten reproducible loci receiving our Rfv nomenclature, Rfv18-01 is mostly supported by field studies and it co-localizes to the SCN resistance locus rhg1. The possibility that Rfv18-01 is a pleiotropic resistance locus and the concern about Rfv18-01 being confounded with Rhg1 is discussed. On the other hand, Rfv06-01, Rfv06-02, Rfv09-01, Rfv13-01, and Rfv16-01 were identified both by screening soybean leaves against phytotoxic culture filtrates and by evaluating SDS severity in fields. Future phenotyping using leaf- and root-specific resistance screening methodologies may improve the precision of SDS resistance, and advanced genetic studies may further clarify the interactions among soybean genotypes, F. virguliforme, SCN, and environments. The review provides a summary of the SDS resistance literature and proposes a framework for communicating SDS resistance loci for future research considering molecular interactions and genetic breeding for soybean SDS resistance.