花生含油量全基因组选择及近红外光谱筛选的育种技术探究

doi:10.3724/SP.J.1006.2024.34115

Abstract

Abstract:

Oil content is a crucial trait for the yield of oil per unit area in peanut. This trait is controlled by multiple minor genes, and its avaliable tightly linked markers are very limited, resulting in low breeding accuracy in traditional molecular marker assisted selection. Genomic selection (GS), as a new breeding method, could achieve early prediction of quantitative traits. Near infrared ray (NIR) technology can non-destructively detect seed quality traits, such as oil content. By combining the advantages of the two breeding technologies, we have established a breeding technology that combined GS and NIR for breeding peanut oil content, and explored the factors that affected the accuracy of GS for peanut oil content. This study lays a theoretical foundation for peanut molecular breeding. Here, a total of 216 recombinant inbred lines were used as a training population. The F₂ (139), F₃ (464), and F₄ (505) were used to construct the breeding populations. Genotyping was carried out using the self-developed “PeanutGBTS40K” liquid chip. The breeding application of oil content was conducted using a GS and NIR jointed breeding technology, and evaluated its breeding effects. The results showed that after genotyping the training population, a total of 30,355 high-quality SNPs were obtained, and used for 11 GS models selection analyses. The rrBLUP model showed the highest accuracy, followed by randomforest and svmrbf. The GS prediction accuracy of F₂, F₃, and F₄ was 0.116, 0.128, and 0.119, respectively, using recombinant inbred lines as the training population. Accordingly, the prediction accuracy was 0.116, 0.131, and 0.160, respectively, using a superimposed training population. Compared with the GS, the GS-NIR can improve oil content by 1.8%, 2.7%, and 3.4% for each generation. Compared with the NIR, there was no significant difference (0.1%, 0.06%, and 0.07%). Compared with the GS, the NIR can significantly improve oil content by 1.7%, 2.6%, and 3.3% for each generation. Through the combined technologies, compared to F₂, the oil content of F₃ and F₄ increased by 1.2% and 1.0%, respectively. Finally, a total of 16 improved lines were obtained in F₄, of which 10 lines had oil content ≥ 55.0%. Among them, two lines (SF4_201 and SF4_379) had a theoretical yield increase of 7.0% and 11.1%, respectively, compared to the control variety. This study suggested that oil content could be effectively improved through GS combined with NIR in peanut.

Key words: peanut (Arachis hypogaea L.), oil content, genomic selection, near infrared ray, genomic breeding value

LU Qing, LIU Hao, LI Hai-Fen, WANG Run-Feng, HUANG Lu, LIANG Xuan-Qiang, CHEN Xiao-Ping, HONG Yan-Bin, LIU Hai-Yan, LI Shao-Xiong. Research on oil content screen with genomic selection and near infrared ray in peanut (Arachis hypogaea L.)[J].Acta Agronomica Sinica, 2024, 50(4): 969-980.

Figures/Tables 5

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Research on oil content screen with genomic selection and near infrared ray in peanut (Arachis hypogaea L.)

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