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

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Abstract

Key message

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.

Abstract

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.

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Funding

This study was funded by the Florida Peanut Producers Association, the National Peanut Foundation and USDA National Institute of Food and Agriculture, Hatch Project 1011664.

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Author notes

  1. Ziliang Luo and Renjie Cui contributed equally to this work.

Authors and Affiliations

  1. Agronomy Department, University of Florida, Gainesville, FL, USA

    Ziliang Luo, Yu-Chien Tseng, Hai Zhou, Ze Peng, Xiping Yang, Yolanda Lopez, Barry Tillman & Jianping Wang

  2. Department of Plant Pathology, University of Georgia, Tifton, GA, USA

    Renjie Cui & Timothy Brenneman

  3. Center for Applied Genetic Technologies, Institute of Plant Breeding, Genetics and Genomics, The University of Georgia, Athens, GA, USA

    Carolina Chavarro

  4. Department of Agronomy, National Chiayi University, Chiayi, Taiwan

    Yu-Chien Tseng

  5. Department of Horticulture, Institute for Plant Breeding, Genetics and Genomics, University of Georgia Tifton Campus, Tifton, GA, USA

    Ye Chu & Peggy Ozias-Akins

  6. North Florida Research and Education Center, Marianna, FL, USA

    Barry Tillman

  7. Department of Plant Pathology, University of Florida, Gainesville, FL, USA

    Nicholas Dufault

  8. Department of Crop and Soil Sciences, North Carolina State University, Raleigh, NC, USA

    Thomas G. Isleib

  9. Crop Genetics and Breeding Research Unit, USDA-ARS, Tifton, GA, USA

    Corley Holbrook

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  1. Ziliang Luo
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  2. Renjie Cui
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  3. Carolina Chavarro
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  4. Yu-Chien Tseng
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  5. Hai Zhou
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  6. Ze Peng
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  7. Ye Chu
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  16. Jianping Wang
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Contributions

JW coordinated the research. YC, TGI, POA and CH developed the RIL population. ND and TB provided the inoculum and advised on the inoculation procedure. BT and JW supervised the phenotyping in Florida. YCT, HZ, ZP, XY, YL and JW conducted the experiments and collected the phenotypic data in Florida. TB and POA supervised the research in Georgia. RC and TB conducted the experiments and collected the phenotypic data in Georgia. CC and POA conducted the linkage map analysis. ZL analyzed the whole data sets and prepared the manuscript draft. All authors revised the manuscript and read and approved the final manuscript.

Corresponding author

Correspondence to Jianping Wang.

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Availability of data and material

Data supporting the results are provided in the additional files and analyzed/organized in tables. The original data and the materials are available upon reasonable request to the corresponding author at wangjp@ufl.edu.

Conflict of interest

The authors declare that they have no competing interests.

Additional information

Communicated by Albrecht E. Melchinger.

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Fig. S1

The distributions of phenotypic data from all datasets (TIFF 44237 kb)

Table S1

Description of experiments in this study (XLSX 10 kb)

Table S2

Kruskal-Wallis ANOVA test for different datasets (XLSX 11 kb)

Table S3

The correlation of phenotypic data from all experiments (XLSX 12 kb)

Table S4

Information of the linkage groups used for stem rot QTL mapping (XLSX 10 kb)

Table S5

The original additive QTLs detected for stem rot resistance by three types of software (XLSX 19 kb)

Table S6

Summary of original additive QTLs’ contribution to phenotype variations (XLSX 10 kb)

Table S7

The consensus additive QTLs detected for stem rot resistance after QTL meta-analysis (XLSX 15 kb)

Table S8

The epistatic QTLs for stem rot resistance detected by QTL IciMapping and QTLNetwork (XLSX 17 kb)

Table S9

The candidate genes identified within all stem rot QTL intervals (XLSX 27 kb)

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Luo, Z., Cui, R., Chavarro, C. et al. Mapping quantitative trait loci (QTLs) and estimating the epistasis controlling stem rot resistance in cultivated peanut (Arachis hypogaea). Theor Appl Genet 133, 1201–1212 (2020). https://doi.org/10.1007/s00122-020-03542-y

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