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Map** QTL for agronomic traits under two levels of salt stress in a new constructed RIL wheat population

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Abstract

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QTL for 15 agronomic traits under two levels of salt stress in dry salinity field were mapped in a new constructed RIL population utilizing a Wheat55K SNP array. Furthermore, eight QTL were validated in a collected natural population.

Abstract

Soil salinity is one of the major abiotic stresses causing serious impact on crop growth, development and yield. As one of the three most important crops in the world, bread wheat (Triticum aestivum L.) is severely affected by salinity, too. In this study, an F7 recombinant inbred line (RIL) population derived from a cross between high-yield wheat cultivar Zhongmai 175 and salt-tolerant cultivar ** showed that 90 stable QTL for 15 traits were detected, and they were distributed on all wheat chromosomes except 4D, 6B and 7D. These QTL individually explained 2.34–32.43% of the phenotypic variation with LOD values ranging from 2.68 to 47.15. It was found that four QTL clusters were located on chromosomes 2D, 3D, 4B and 6A, respectively. Notably, eight QTL from the QTL clusters were validated in a collected natural population. Among them, QPh-4B was deduced to be an allele of Rht-B1. In addition, three kompetitive allele-specific PCR (KASP) markers derived from SNPs were successfully designed for three QTL clusters. This study provides an important base for salt-tolerant QTL (gene) cloning in wheat, and the markers, especially the KASP markers, will be useful for marker-assisted selection in salt-tolerant wheat breeding.

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Acknowledgements

We particularly thank Dr. Yunfeng Xu for his generous help in genetic linkage map construction. This study was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (No. XDA24030302 and XDA08030105).

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Authors and Affiliations

  1. State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, The Innovative Academy of Seed Design, Chinese Academy of Sciences, Bei**g, 100101, China

    Qiaoling Luo, Qi Zheng, Pan Hu, Liqin Liu, Guotang Yang, Hongwei Li, Bin Li & Zhensheng Li

  2. University of Chinese Academy of Sciences, Bei**g, 100049, China

    Guotang Yang

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  1. Qiaoling Luo
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Contributions

ZSL and QZ supervised the research. QLL and QZ designed the experiment. QLL, QZ and PH performed the phenotypes of the RIL population. QLL created the RIL population, performed data analyses and QTL map**, confirmed the QTL effects and wrote the manuscript. QZ also put forward many constructive suggestions and revised the manuscript. LQL, GTY, HWL and BL provided a lot of help in the materials preparation and experiments performance. All authors read and approved the final manuscript.

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Correspondence to Qi Zheng.

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Fig. S1

The frequency distribution histogram for all 15 traits and the parents positions among RILs under HS and LS in three years. All data were derived from the averages of three years. The first three rows were under HS, and the last three rows were under LS. (PDF 640 kb)

Fig. S2

Comparison of the genetic and physical positions of the SNPs on the genetic map. The bars in green indicate the percentage of markers whose physical and genetic positions are coincident (identical chromosome); yellow indicates the percentage of markers whose physical and genetic chromosomes are homoeologous; red indicates the percentage of markers whose physical and genetic positions are inconsistent (in disorder); and purple indicates the percentage of markers whose physical positions are unknown. The physical positions are from the Chinese Spring contigs which were the best hits for the corresponding markers. (PDF 345 kb)

Fig. S3

Syntenic relationships between the genetic and physical maps of a total of 16,008 SNP markers used in this study. Gen-1A to Gen-7D represent the 21 wheat chromosomal genetics maps released in this paper; Phy-1A to Phy-7D represent the 21 wheat chromosomal physical maps (IWGSC RefSeq v1.0). (TIF 7451 kb)

Fig. S4

Confirmation of the QTL effect in the RIL population. Comparison of the QTL corresponding traits between two groups with different alleles derived from RIL parents ZM175 and XY60. SNP markers used in validation were shown as chart titles. Y-axis titles were the corresponding traits for the validated QTL. Error bars indicate the standard deviation. *, significant difference determined by the Student’s t test (P <0.05); **, significant difference determined by the Student’s t test (P <0.01). (PDF 548 kb)

Fig. S5

Genoty** of 24 RILs with the KASP markers developed in this study. The genotypes obtained using KASP markers were coincided with the genoty** results on the Wheat55K SNP array. (PDF 379 kb)

Fig. S6

QSl-7A was detected in both RIL and natural populations. (a) QSl-7A involved SNP markers and the LOD curves in the RIL population. SNPs tightly linked to QSl-7A in purple were near to the significantly associated SNPs by GWAS. (b) Quantile–quantile (Q-Q) plot of SL in the natural population. (C) Manhattan plot for SL on chromosome 7A under LS with mixed linear model (MLM) by TASSEL 5.0 (Bradbury et al. 2007). Two vertical black lines showed the position of the SNP markers which were significantly associated with QSl-7A in the natural population. (PDF 361 kb)

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Luo, Q., Zheng, Q., Hu, P. et al. Map** QTL for agronomic traits under two levels of salt stress in a new constructed RIL wheat population. Theor Appl Genet 134, 171–189 (2021). https://doi.org/10.1007/s00122-020-03689-8

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