Method for forecasting bacterial leaf blight of paddy rice by utilizing miRNA172b gene

Abstract

The invention discloses a method for forecasting bacterial leaf blight of paddy rice by utilizing miRNA172b gene, and belongs to the technical field of biology. The method comprises the following steps: selecting to-be tested paddy rice and control paddy rice, wherein the selected control paddy rice is paddy rice which is not infected by bacterial leaf blight and is cultivated under same conditions with the to-be tested paddy rice; respectively separating total miRNA gene of the to-be tested paddy rice and the control paddy rice; respectively detecting the expression level of miRNA172b gene in the total miRNA gene of the to-be tested paddy rice and the control paddy rice, wherein the sequence of the miRNA172b gene is shown as SEQ ID NO: 1; and determining whether the experiment is successful according to the expression level of miRNA172b gene in the to-be tested paddy rice and the control paddy rice, if successful, further determining whether the to-be tested plant is infected by bacterial leaf blight. The provided prediction method is successful, is capable of accurately performing forecast several days before paddy rice has symptoms of bacterial leaf blight, wins time for early prevention and early controlling, and helps to reduce loss of paddy rice caused by bacterial leaf blight.

Description

technical field [0001] The invention relates to the field of biotechnology, in particular to a method for predicting rice bacterial blight by using the expression of miRNA172b gene. Background technique [0002] Rice is the main food crop in my country. Bacterial blight is one of the two major diseases of rice. It is a worldwide disease, especially in Asian rice regions. The incidence of bacterial blight is high, the infection is fast, and the rice field with the disease is reduced by 20-30%, or even 50%. Like most diseases, the early control effect of bacterial blight is better. In the middle and late stages of the disease, the bacteria have multiplied in large numbers, which has caused damage to the rice, and the control effect is poor. It can be seen that early forecasting is the key to rice bacterial blight prevention. [0003] Traditional rice bacterial blight prediction is mainly based on climate, weather, variety resistance, nitrogen fertilizer application, and dis...

AI Technical Summary

Problems solved by technology

[0006] In order to solve the shortcomings of untimely and inaccurate prediction of rice bacterial blight in the prior art, the embodiment of the present invention provides a method for predicting rice bacterial blight by using the expression of miRNA172b gene

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