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Advances in Molecular Breeding for Pest and Disease Resistance in Legume Crops

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Dr. Eleonora Barilli

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Guest Editor

Institute for Sustainable Agriculture, CSIC, Avenida Menendez Pidal s/n, 14004 Cordoba, Spain
Interests: crop protection; molecular; cell biology and genetics; plant disease; legumes; biotic stress

Dr. Nicolas Rispail

E-Mail Website
Guest Editor

Institute for Sustainable Agriculture, CSIC, Avenida Menendez Pidal s/n, 14004 Cordoba, Spain
Interests: plant-pathogen interaction; plant disease; plant breeding for resistance; genome-wide association mapping; resistance mechanism; legumes; pea; fusarium oxysporum; oat; crop adaptation

Dr. Diego Rubiales

E-Mail Website
Guest Editor

Institute for Sustainable Agriculture, CSIC, Avenida Menendez Pidal s/n, 14004 Cordoba, Spain
Interests: identification, characterization and use of genetic resistance in legume breeding
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Special Issue Information

Dear Colleagues,

Legume crops are relevant globally due to both their high protein content and ability to fix atmospheric nitrogen thanks to their symbiosis with rhizobia. In spite of the globally accepted nutritional, economic, and environmental benefits of legumes, legume breeding has received relatively less attention than other crops such as cereals. However, after decades of slow progress, techniques of legume cultivation have now rapidly entered into the genomics era due to the recently completed genome sequencing of many species. A wealth of genomic tools has now become available and these allow researchers to improve legume genetics more substantially.

The aim of the Special Issue is to compile research and review articles on advances in legume breeding for pest and disease resistance. We are especially interested in research with a focus on molecular approaches, and submissions can cover:

Molecular characterization of plant/pathogen interactions;
Marker-assisted selection;
Genomics-assisted breeding.

Dr. Eleonora Barilli
Dr. Nicolas Rispail
Dr. Diego Rubiales
Guest Editors

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Keywords

legume crops
genetic resistance
molecular breeding
diseases
plant–pathogen interaction
genomic selection
marker-assisted breeding

Published Papers (2 papers)

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Research

18 pages, 2808 KiB

Open AccessArticle

Genome-Wide Association Study and Genomic Prediction of Fusarium Wilt Resistance in Common Bean Core Collection

by Kenani Chiwina, Haizheng Xiong, Gehendra Bhattarai, Ryan William Dickson, Theresa Makawa Phiri, Yilin Chen, Ibtisam Alatawi, Derek Dean, Neelendra K. Joshi, Yuyan Chen, Awais Riaz, Paul Gepts, Mark Brick, Patrick F. Byrne, Howard Schwartz, James B. Ogg, Kristin Otto, Amy Fall, Jeremy Gilbert and Ainong Shi

Int. J. Mol. Sci. 2023, 24(20), 15300; https://doi.org/10.3390/ijms242015300 - 18 Oct 2023

Cited by 2 | Viewed by 1207

Abstract

The common bean (Phaseolus vulgaris L.) is a globally cultivated leguminous crop. Fusarium wilt (FW), caused by Fusarium oxysporum f. sp. phaseoli (Fop), is a significant disease leading to substantial yield loss in common beans. Disease-resistant cultivars are recommended to counteract this. The objective of this investigation was to identify single nucleotide polymorphism (SNP) markers associated with FW resistance and to pinpoint potential resistant common bean accessions within a core collection, utilizing a panel of 157 accessions through the Genome-wide association study (GWAS) approach with TASSEL 5 and GAPIT 3. Phenotypes for Fop race 1 and race 4 were matched with genotypic data from 4740 SNPs of BARCBean6K_3 Infinium Bea Chips. After ranking the 157-accession panel and revealing 21 Fusarium wilt-resistant accessions, the GWAS pinpointed 16 SNPs on chromosomes Pv04, Pv05, Pv07, Pv8, and Pv09 linked to Fop race 1 resistance, 23 SNPs on chromosomes Pv03, Pv04, Pv05, Pv07, Pv09, Pv10, and Pv11 associated with Fop race 4 resistance, and 7 SNPs on chromosomes Pv04 and Pv09 correlated with both Fop race 1 and race 4 resistances. Furthermore, within a 30 kb flanking region of these associated SNPs, a total of 17 candidate genes were identified. Some of these genes were annotated as classical disease resistance protein/enzymes, including NB-ARC domain proteins, Leucine-rich repeat protein kinase family proteins, zinc finger family proteins, P-loopcontaining nucleoside triphosphate hydrolase superfamily, etc. Genomic prediction (GP) accuracy for Fop race resistances ranged from 0.26 to 0.55. This study advanced common bean genetic enhancement through marker-assisted selection (MAS) and genomic selection (GS) strategies, paving the way for improved Fop resistance. Full article

(This article belongs to the Special Issue Advances in Molecular Breeding for Pest and Disease Resistance in Legume Crops)

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22 pages, 5428 KiB

Open AccessArticle

RNA-Seq and Comparative Transcriptomic Analyses of Asian Soybean Rust Resistant and Susceptible Soybean Genotypes Provide Insights into Identifying Disease Resistance Genes

by Qingnan Hao, Hongli Yang, Shuilian Chen, Yanhui Qu, Chanjuan Zhang, Limiao Chen, Dong Cao, Songli Yuan, Wei Guo, Zhonglu Yang, Yi Huang, Zhihui Shan, Haifeng Chen and Xinan Zhou

Int. J. Mol. Sci. 2023, 24(17), 13450; https://doi.org/10.3390/ijms241713450 - 30 Aug 2023

Cited by 1 | Viewed by 1004

Abstract

Asian soybean rust (ASR), caused by Phakopsora pachyrhizi, is one of the most destructive foliar diseases that affect soybeans. Developing resistant cultivars is the most cost-effective, environmentally friendly, and easy strategy for controlling the disease. However, the current understanding of the mechanisms underlying soybean resistance to P. pachyrhizi remains limited, which poses a significant challenge in devising effective control strategies. In this study, comparative transcriptomic profiling using one resistant genotype and one susceptible genotype was performed under infected and control conditions to understand the regulatory network operating between soybean and P. pachyrhizi. RNA-Seq analysis identified a total of 6540 differentially expressed genes (DEGs), which were shared by all four genotypes. The DEGs are involved in defense responses, stress responses, stimulus responses, flavonoid metabolism, and biosynthesis after infection with P. pachyrhizi. A total of 25,377 genes were divided into 33 modules using weighted gene co-expression network analysis (WGCNA). Two modules were significantly associated with pathogen defense. The DEGs were mainly enriched in RNA processing, plant-type hypersensitive response, negative regulation of cell growth, and a programmed cell death process. In conclusion, these results will provide an important resource for mining resistant genes to P. pachyrhizi infection and valuable resources to potentially pyramid quantitative resistance loci for improving soybean germplasm. Full article

(This article belongs to the Special Issue Advances in Molecular Breeding for Pest and Disease Resistance in Legume Crops)

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