Method for breeding good corn germplasm high in combining ability

A technology with excellent combining ability, applied in the field of breeding, can solve the problems of high testing and matching cost, low genetic gain, low efficiency, etc., and achieve the effect of broadening the genetic basis, speeding up the breeding process, and increasing the strength and effect of aggregation.

Inactive Publication Date: 2020-08-14
INST OF CROP SCI CHINESE ACAD OF AGRI SCI
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  • Abstract
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  • Application Information

AI Technical Summary

Problems solved by technology

[0007] Aiming at the problems of long cycle, high matching cost, low efficiency and low genetic gain in the breeding technology in the

Method used

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Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0036] In this embodiment, corn is taken as an example to provide a method for rapid and efficient breeding of excellent germplasm with high combining ability in corn, which includes the following steps:

[0037] 1. Collect high-quality corn inbred line materials, including the parents of large-scale promotion varieties, American declassified inbred lines and inbred lines selected by breeders, and divide heterotic groups based on pedigree and molecular markers. The collected germplasm was divided into two heterogenic groups, SS group: Ye 478, Tie 7922, Ye 107, Zheng 58, Liao 5114, etc., NSS group: Mo17, Jing 92, WK798-1, Chang 7-2, Ji 444 Wait. Taking the SS subpopulation as an example, the inbred line that has nothing to do with the initial population was selected to combine two hybrids as the test species for the test and mating work, so as to ensure that the test and mating results are more accurate and reliable. Here the 20K SNP chip is used for genotype identification of...

Embodiment 2

[0046] This example provides a method for rapid and efficient breeding of excellent maize germplasm with high combining ability. The difference from Example 1 is that the selected excellent individual plants in step 3 enter the subsequent recurrent selection program, and a total of 6 rounds of selection are carried out. Further accumulation of favorable alleles.

[0047] Results After 6 rounds of selection of superior plants for mixed pollination, the frequency of favorable alleles in the population could be increased, the dominant genes could be aggregated, and the probability of breeding superior maize inbred lines could be increased. Therefore, the improved population has better target traits than the original population, and the 58 selected DH lines all exhibit high combining ability, early maturity and density tolerance, and have excellent agronomic traits.

[0048] It can be seen from the results that, compared with the traditional repeated 1-2 rounds of selection, multi...

Embodiment 3

[0050] This example provides a method for rapid and efficient breeding of maize germplasm with high combining ability. The difference from Example 1 is that after two rounds of mixed pollination, a new germplasm of the same heterotic group as the initial population is added to expand the breeding population. Genetic basis, re-establish a genome-wide selection model for subsequent prediction of GCA effects in DH lines; then proceed to steps 2-6.

[0051] The new germplasms added in this example are European precocious durum and American Iodent. In actual operation, parents of other market-leading varieties can also be added to the method of the present invention as new germplasms.

[0052] As a result, the size of the initial population (that is, the training population) has been increased and historical data has been accumulated, which is conducive to improving the accuracy of genome-wide selection and prediction accuracy. Furthermore, the cross-validation prediction accuracy ...

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Abstract

The invention belongs to the field of breeding techniques, and particularly relate to a method for breeding good corn germplasm high in combining ability. The method comprises the steps of firstly collecting good selfing lines for constructing an initial group, performing genotype identification and heterotic group division, selecting specific hybrids as test hybrids for assessing the combining ability expression of each material in the initial group, and establishing a complete genome selection model; then in the heterotic group, according to the combining ability assessment result, performing breeding step by step to obtain good single plants, and further obtaining homozygosis selfing lines; and finally, performing genotype identification on the homozygosis selfing lines, forecasting thecombining ability according to the complete genome selection model, and reserving the homozygosis selfing lines having high combining ability estimated value namely obtaining the good germplasm highin combining ability. The method disclosed by the invention is high in breeding efficiency and short in breeding cycle, and can accelerate the breeding process of good germplasm.

Description

technical field [0001] The invention belongs to the technical field of breeding, and in particular relates to a method for breeding high-combining ability excellent germplasm of maize. Background technique [0002] As the world's largest grain and feed crop, maize has important application value and status in food, feed and bioenergy, and the selection of excellent commercial maize hybrids is very important to increase yield. [0003] Traditionally commonly used inbred breeding methods include methods such as recurrent selection, pedigree selection, and backcross breeding, but these methods often have the following problems: 1. The breeding cycle is long: the performance of the combining ability of the inbred line is based on the performance of its hybrid offspring. In addition, the selected line material needs multiple generations of self-crossing to form a pure line before it can be used to assemble hybrids, so it often requires a longer breeding cycle; 2. High cost in the...

Claims

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Application Information

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IPC IPC(8): A01H1/04A01H1/02
CPCA01H1/04A01H1/02
Inventor 刘小刚王红武胡小娇李坤黄长玲
Owner INST OF CROP SCI CHINESE ACAD OF AGRI SCI
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