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Highly efficient genotyping of rice biparental populations by GoldenGate assays based on parental resequencing

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A new time- and cost-effective strategy was developed for medium-density SNP genotyping of rice biparental populations, using GoldenGate assays based on parental resequencing.

Abstract

Since the advent of molecular markers, crop researchers and breeders have dedicated huge amounts of effort to detecting quantitative trait loci (QTL) in biparental populations for genetic analysis and marker-assisted selection (MAS). In this study, we developed a new time- and cost-effective strategy for genotyping a population of progeny from a rice cross using medium-density single nucleotide polymorphisms (SNPs). Using this strategy, 728,362 “high quality” SNPs were identified by resequencing Teqing and Lemont, the parents of the population. We selected 384 informative SNPs that were evenly distributed across the genome for genotyping the biparental population using the Illumina GoldenGate assay. 335 (87.2 %) validated SNPs were used for further genetic analyses. After removing segregation distortion markers, 321 SNPs were used for linkage map construction and QTL mapping. This strategy generated SNP markers distributed more evenly across the genome than previous SSR assays. Taking the GW5 gene that controls grain shape as an example, our strategy provided higher accuracy (0.8 Mb) and significance (LOD 5.5 and 10.1) in QTL mapping than SSR analysis. Our study thus provides a rapid and efficient strategy for genetic studies and QTL mapping using SNP genotyping assays.

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Acknowledgments

This work was supported by grants from the National Program on Key Basic Research Project of China (973 Program: 2011CB100101), Ministry of Agriculture of China (948 Program: 2011-G2B), National High Technology Research and Development Program of China (863 Program: 2012AA10A304), National Natural Science Foundation of China (U1031001) and the Program of International Science and Technology Cooperation (2012DFB32280).

Conflict of interest

The authors declare that they have no conflict of interest.

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Correspondence to Jianlong Xu or Hang He.

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W. Chen, H. Chen and T. Zheng equally contributed to this work.

Communicated by T. Sasaki.

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Fig. S1

Supplementary material 1 (EPS 1774 kb) Workflow for the high-efficiency genotyping of a biparental population derived from a cross between Teqing and Lemont

Fig. S2

Supplementary material 2 (TIFF 3412 kb) Sequencing data of the parents of introgression lines. (a) Mapping bases (b) Genome coverage

Fig. S3

Supplementary material 3 (TIFF 478 kb). Three separate clusters of the 143 introgression lines revealed by a representative SNP. This figure was generated by the Illumina GenomeStudio Analysis Module software. The middle cluster represents heterozygous lines, while the other two clusters represent homozygous lines

Fig. S4

Supplementary material 4 (EPS 12404 kb) Genotyping of 143 introgression lines (ILs) derived from Teqing and Lemont by medium-density SNPs. (a) Red indicates genotypes consistent with Lemont, while green indicates genotypes consistent with Teqing. Yellow indicates heterozygous loci and gray means missing loci. (b) Y axis represents number of lines containing introgression fragments at each SNP locus

Fig. S5

Supplementary material 5 (TIFF 6046 kb) Comparative genotyping of IL1 (a) and IL2 (b) on the 12 chromosomes with different markers

Fig. S6

Supplementary material 6 (EPS 906 kb) Linkage map constructed by 321 SNP markers for 143 introgression lines derived from Teqing and Lemont

Fig. S7

Supplementary material 7 (TIFF 1391 kb) Comparison of QTL mapping using SNP and SSR markers of BR, MR, and HR. (a) LOD curves of QTL mapping of the brown rice ratio on chromosome 4 using 160 SSR markers. Short bars on X axis indicate the position of SSR markers. (b) LOD curves of QTL mapping of the brown rice ratio on chromosome 4 using 321 SNP markers. (c) LOD curves of QTL mapping of the milled rice rate on chromosome 4 using 160 SSR markers. (d) LOD curves of QTL mapping of the milled rice rate on chromosome 4 using all 321 SNP markers. (e) LOD curves of QTL mapping of the head rice rate on chromosome 2 using160 SSR markers. Short bars on Xaxis indicate the position of SNP markers. (f) LOD curves of QTL mapping of the head rice rate on chromosome 2 using 321 SNP markers

Fig. S8

Supplementary material 8 (TIFF 1455 kb) (a) Genotyping of progeny homozygous for GW5 delimited the locus to an ~ 0.8-Mb stretch flanked by Os05-04578273-LT and Os05-05389716-LT. Grain thickness (mean ± standard error (SE)) of 3 types of ILs. (b) Genotyping of progeny homozygous for GW5 delimited the locus to an ~ 4.4-Mb stretch flanked by RM574 and RM289

Fig. S9

Supplementary material 9 (EPS 2475 kb) Linkage map constructed by 160 genome-wide evenly selected SNP markers for 143 introgression lines derived from Teqing and Lemont

Fig. S10

Supplementary material 10 (EPS 4284 kb) QTL mapping with 160 SNP markers in comparison with 160 SSR markers. (a) LOD curves of QTL mapping of grain thickness on chromosome 5 using SSR. Short bars on X axis indicate the position of 160 SSR markers. (b) LOD curves of QTL mapping of the grain length to thickness ratio on chromosome 5 using 160 SSR markers. (c) LOD curves of QTL mapping of grain thickness on chromosome 5 using 160 SNP markers. Short bars on X axis indicate the position of 160 SNP markers. (d) LOD curves of QTL mapping of the grain length to thickness ratio on chromosome 5 using 160 SNP markers

Supplementary material 11 (DOCX 19 kb) The number of SNPs detected at each sequencing depth in Teqing and Lemont.

Supplementary material 12 (XLSX 14 kb) Primer sequences for PCR validation of 56 SNP loci

122_2013_2218_MOESM13_ESM.xlsx

Supplementary material 13 (XLSX 170 kb) Genotyping data for Teqing-Lemont derived introgression lines.(2 means TQ,0 means Lemont,1 means heterozygous,-1 means missing)

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Chen, W., Chen, H., Zheng, T. et al. Highly efficient genotyping of rice biparental populations by GoldenGate assays based on parental resequencing. Theor Appl Genet 127, 297–307 (2014). https://doi.org/10.1007/s00122-013-2218-2

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