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High-throughput identification method for pathogenic differentiation of bipolaria maydis

A technology of corn spot disease and identification method, applied in the field of high-throughput identification of corn spot spot pathogenicity differentiation, can solve the problem of affecting pathogenicity, single infection observation time point, and inability to comprehensively analyze corn spot spot fungus Pathogenicity differentiation and other issues, to achieve the effect of high reliability and simple operation

Inactive Publication Date: 2019-09-10
SHANGHAI JIAO TONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, it is time-consuming and labor-intensive to identify the pathogenicity of corn leaf spot by this system, and when the corn leaves are reattached, the variety and singleness of the corn variety will affect the judgment of the pathogenicity. The corn leaves are counted at 3 days, and the infection observation time point is relatively single, lacking the measurement of the infection process
Therefore, this system cannot comprehensively analyze the differentiation of pathogenicity of P. maize

Method used

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  • High-throughput identification method for pathogenic differentiation of bipolaria maydis
  • High-throughput identification method for pathogenic differentiation of bipolaria maydis
  • High-throughput identification method for pathogenic differentiation of bipolaria maydis

Examples

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Embodiment 1

[0048] This embodiment relates to the construction of a high-throughput identification method for pathogenicity differentiation of P. maize spot, specifically as follows:

[0049] The inventor has selected the different virulence types of the lesser pathogenicity of maize spot bacterium that the virulence difference is more significant from the bacterial strain isolated in the field: DY, strong pathogenic strain; WF, weak pathogenic strain (wherein, DY is from Zhejiang Province The fungus was isolated and purified from the diseased corn leaves in the field of Dongyang City, and the strain was identified as a strong pathogenic strain by counting the size of the lesion after being reattached to the corn leaves; WF was obtained from the field of Weifang City, Shandong Province. The method of observing the size of the lesion spot after collecting and single spore isolation and purification on the sick leaves of corn and then returning to the corn leaves, identified that the bacteri...

Embodiment 2

[0064] This example relates to the verification of the effect of the high-throughput identification method for pathogenicity differentiation of P. maize spot of the present invention.

[0065] According to the identification standard of strong and weak pathogenic strains, the corn leaf spot fungus collected and purified in 2018 (specifically, collected diseased leaves from all over the country, disinfected the surface of the diseased leaves with sodium hypochlorite and then cultured them in PDA medium for 2 days, Then pick the tip of mycelia and cultivate it in a new PDA medium for 5-7 days. After the spores of the spot bacterium to be purified, carry out the isolation and purification of single spores to obtain the purified spot bacterium). Randomly select 10 strains for verification. The pathogenicity of the isolated and purified bacterial strains was identified by the traditional leaf reconnection method and the high-throughput detection method of the present invention, resp...

Embodiment 3

[0079] This embodiment relates to the application case of the high-throughput identification method of the pathogenicity differentiation of corn leaf spot bacterium of the present invention:

[0080] Henan Province

[0081] A total of 36 strains of Phytophthora spp. were identified in Henan Province, among which 12 strains were strongly pathogenic and 24 strains were weakly pathogenic, accounting for 33.3% and 66.7% respectively.

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Abstract

The invention discloses a high-throughput identification method for pathogenic differentiation of bipolaria maydis. The method screens out molecular marker genes related to the pathogenic differentiation mainly according to differences of strains with strong and weak pathogenicity in gene level and transcription level, and the degree of pathogenicity of the strain can be judged by detecting the molecular marker genes of small spot strains. Compared with the prior art, the high-throughput identification method of the invention can identify the degree of the pathogenicity of the bipolaria maydisat a molecular level and on a large sample size, and time and labor are saved.

Description

technical field [0001] The invention relates to an identification method, in particular to a high-throughput identification method for the differentiation of pathogenicity of corn leaf spot fungus. Background technique [0002] Corn is one of the main food crops in my country, and it is also a very important feed crop. The serious occurrence of leaf diseases is the main factor restricting the production of corn, which not only causes great economic losses to the corn planting industry, but also affects the breeding industry. have a greater impact. [0003] Maize leaf diseases mainly refer to pathogenic bacteria or fungi colonizing and infecting maize leaf tissues, causing disease in some or even whole plant leaves of maize, which can lead to partial or complete death of maize, seriously reducing maize yield or even crop failure. Corn spot disease is caused by the infection of Cochliobolus heterostrophus (C.heterostrophus), and it is a widespread worldwide disease. In the 197...

Claims

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Application Information

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IPC IPC(8): C12Q1/6895C12Q1/686C12Q1/04C12R1/645
CPCC12Q1/686C12Q1/6895C12Q2565/125
Inventor 王少青王猛陈捷王新华李雅乾
Owner SHANGHAI JIAO TONG UNIV
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