Qu Yanzhi, Liu Zonghua, Zhang Yazhou, Yang Jiwei, Li Haochuan
College of Agronomy, National Key Laboratory of Wheat and Maize Crop Science, Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou, China.
Plant Methods. 2021 Jan 6;17(1):2. doi: 10.1186/s13007-020-00703-4.
Maize haploid breeding technology can be used to rapidly develop homozygous lines, significantly shorten the breeding cycle and improve breeding efficiency. Rapid and accurate sorting haploid kernels is a prerequisite for the large-scale application of this technology. At present, the automatic haploid sorting based on nuclear magnetic resonance (NMR) using a single threshold method has been realized. However, embryo-aborted (EmA) kernels are usually produced during in vivo haploid induction, and both haploids and EmA kernels have lower oil content and are separated together using a single threshold method based on NMR. This leads to a higher haploid false discrimination rate (FDR) and requires secondary manual sorting to select the haploid kernels from the mixtures, which increases the sorting cost and decreases the haploid sorting efficiency. In order to improve the correct discrimination rate (CDR) in sorting haploids, a method to distinguish EmA kernels is required.
Single kernel weight and oil content were measured for the diploid, haploid, and EmA kernels derived from three maize hybrids and nine inbred lines by in vivo induction. The results showed that the distribution of oil content showed defined boundaries between the three types of kernels, while the single kernel weight didn't. According to the distribution of oil content in the three types of kernels, a double-threshold method was proposed to distinguish the embryo-aborted kernels, haploid and diploid kernels based on NMR and their oil content. The double thresholds were set based on the minimum oil content of diploid kernels and the maximum content of EmA kernels as the upper and lower boundary values, respectively. The CDR of EmA kernels in different maize materials was > 97.8%, and the average FDR was reduced by 27.9 percent.
The oil content is an appropriate indicator to discriminate diploid, haploid and EmA kernels. An oil content double-threshold method based on NMR was first developed in this study to identify the three types of kernels. This methodology could reduce the FDR of haploids and improve the sorting efficiency of automated sorting system. Thus, this technique represents a potentially efficient method for haploid sorting and provides a reference for the process of automated sorting of haploid kernels with high efficiency using NMR.
玉米单倍体育种技术可用于快速培育纯合系，显著缩短育种周期并提高育种效率。快速准确地分选单倍体籽粒是该技术大规模应用的前提。目前，基于核磁共振（NMR）采用单阈值法已实现单倍体籽粒的自动分选。然而，在体内单倍体诱导过程中通常会产生胚败育（EmA）籽粒，单倍体籽粒和EmA籽粒的含油量均较低，基于NMR的单阈值法会将它们一起分离。这导致单倍体误判率（FDR）较高，需要二次人工分选以从混合物中挑选出单倍体籽粒，这增加了分选成本并降低了单倍体分选效率。为了提高单倍体分选的正确判别率（CDR），需要一种区分EmA籽粒的方法。
通过体内诱导测量了源自三个玉米杂交种和九个自交系的二倍体、单倍体和EmA籽粒的单粒重和含油量。结果表明，含油量分布在三种类型的籽粒之间呈现明确界限，而单粒重则不然。根据三种类型籽粒的含油量分布，提出了一种基于NMR及其含油量区分胚败育籽粒、单倍体和二倍体籽粒的双阈值法。分别以二倍体籽粒的最低含油量和EmA籽粒的最高含油量作为上下边界值设置双阈值。不同玉米材料中EmA籽粒的CDR>97.8%，平均FDR降低了27.9%。
含油量是区分二倍体、单倍体和EmA籽粒的合适指标。本研究首次开发了基于NMR的含油量双阈值法来鉴别这三种类型的籽粒。该方法可以降低单倍体的FDR并提高自动分选系统的分选效率。因此，该技术是一种潜在的高效单倍体分选方法，为利用NMR高效自动分选单倍体籽粒的过程提供了参考。
