Abstract

Triticum aestivum L., also known as common wheat, is affected by many biotic stresses. Root diseases are the most difficult to tackle due to the complexity of phenotypic evaluation and the lack of resistant sources compared to other biotic stress factors. Soil-borne pathogens such as the root-lesion nematodes caused by the Pratylenchus species and crown rot caused by various Fusarium species are major wheat root diseases, causing substantial yield losses globally. A set of 189 advanced spring bread wheat lines obtained from the International Maize and Wheat Improvement Center (CIMMYT) were genotyped with 4056 single nucleotide polymorphisms (SNP) markers and screened for root-lesion nematodes and crown rot resistance. Population structure revealed that the genotypes could be divided into five subpopulations. Genome-Wide Association Studies were carried out for both resistances to Pratylenchus and Fusarium species. Based on our results, 11 different SNPs on chromosomes 1A, 1B, 2A, 3A, 4A, 5B, and 5D were significantly associated with root-lesion nematode resistance. Seven markers demonstrated association with P. neglectus, while the remaining four were linked to P. thornei resistance. In the case of crown rot, eight different markers on chromosomes 1A, 2B, 3A, 4B, 5B, and 7D were associated with Fusarium crown rot resistance. Identification and screening of root diseases is a challenging task; therefore, the newly identified resistant sources/genotypes could be exploited by breeders to be incorporated in breeding programs. The use of the identified markers in marker-assisted selection could enhance the selection process and cultivar development with root-lesion nematode and crown rot resistance.

Highlights

  • Bread wheat (Triticum aestivum L.) is one of the most important cereal crops for human consumption around the world

  • In this study, we analyzed the association of single nucleotide polymorphism (SNP) markers with resistance responses of a panel of spring bread wheat accessions against root-lesion nematodes (RLN) (P. neglectus and P. thornei) and crown rot (CR) (F. culmorum) diseases to identify novel sources of resistance to soil-borne diseases

  • A decrease in wheat yields could result in global food security issues and may lead to hunger in some cases

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Summary

Introduction

Bread wheat (Triticum aestivum L.) is one of the most important cereal crops for human consumption around the world. These nematodes usually pierce the root cell walls, which limits the nutrient and water uptake This reduction in nutrient uptake, in turn, causes drought-like or nutrient deficiency symptoms, eventually resulting in yield loss and damaging grain quality [6,7]. The two Pratylenchus species are the most common RLN species in wheat and usually coexist in fields [8] They cause the most damage in temperate and dry regions of the U.S, Northern Canada, Latin America, Australia, the Middle East, etc. Another economically important wheat root disease is Fusarium crown rot (CR), which is caused by various Fusarium species [10–12] The occurrence of this disease has become more common with the application of minimum tillage because Fusarium species survives on crop residue and infect following seasons wheat crop [13]. In GWAS, a panel of genotypes is screened with a large number of genome-wide markers for detecting associations with important morphological, agronomic, or disease-resistance traits. In this study, we analyzed the association of single nucleotide polymorphism (SNP) markers with resistance responses of a panel of spring bread wheat accessions against RLN (P. neglectus and P. thornei) and CR (F. culmorum) diseases to identify novel sources of resistance to soil-borne diseases

Phenotypic Data Description for PT, PN, and CR
Genotypic Data and Population Structure
GWAS for PT, PN and CR
Discussion
Plant Material and Experimental Procedures
Growthroom Screening for Root-Lesion Nematodes
Inoculum Preparation
Growth Room Experiments
Greenhouse Experiment
Field Experiments
Disease Assessment
Data Analyses
DNA Extraction and Genotyping
Population Structure Analysis
Linkage Disequilibrium and GWAS
Full Text
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