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QTL mapping of stalk bending strength in a recombinant inbred line maize population |
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| Authors: | Haixiao Hu Wenxin Liu Zhiyi Fu Linda Homann Frank Technow Hongwu Wang Chengliang Song Shitu Li Albrecht E Melchinger Shaojiang Chen |
| Institution: | 1. National Maize Improvement Center of China, China Agricultural University (West Campus), 2# Yuanmingyuan West Road, Beijing, 100193, China 4. Institute of Plant Breeding, Seed Science, and Population Genetics, University of Hohenheim, 70599, Stuttgart, Germany 2. Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University (West Campus), 2# Yuanmingyuan West Road, Beijing, 100193, China 3. Applicational Mechanics Department, College of Science, China Agricultural University (East Campus), 17# Qinghua East Road, Beijing, 100083, China 5. Institute of Crop Science, Chinese Academy of Agricultural Sciences, 12# Zhongguancun South Street, Beijing, 100081, China |
| Abstract: | Stalk bending strength (SBS) is a reliable indicator for evaluating stalk lodging resistance of maize plants. Based on biomechanical considerations, the maximum load exerted to breaking (F max), the breaking moment (M max) and critical stress (σ max) are three important parameters to characterize SBS. We investigated the genetic architecture of SBS by phenotyping F max, M max and σ max of the fourth internode of maize plants in a population of 216 recombinant inbred lines derived from the cross B73 × Ce03005 evaluated in four environments. Heritability of F max, M max and σ max was 0.81, 0.79 and 0.75, respectively. F max and σ max were positively correlated with several other stalk characters. By using a linkage map with 129 SSR markers, we detected two, three and two quantitative trait loci (QTL) explaining 22.4, 26.1 and 17.2 % of the genotypic variance for F max, M max and σ max, respectively. The QTL for F max, M max and σ max located in adjacent bins 5.02 and 5.03 as well as in bin 10.04 for F max were detected with high frequencies in cross-validation. As our QTL mapping results suggested a complex polygenic inheritance for SBS-related traits, we also evaluated the prediction accuracy of two genomic prediction methods (GBLUP and BayesB). In general, we found that both explained considerably higher proportions of the genetic variance than the values obtained in QTL mapping with cross-validation. Nevertheless, the identified QTL regions could be used as a starting point for fine mapping and gene cloning. |
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