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M2 group-based candidate causal mutation site gene localization method

A mutation site and gene positioning technology, applied in the field of bioinformatics and biology, can solve time-consuming and labor-intensive problems, save time, help locate causal mutations, and remove background mutations

Active Publication Date: 2021-07-16
NORTHEAST INST OF GEOGRAPHY & AGRIECOLOGY C A S
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  • Abstract
  • Description
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  • Application Information

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Problems solved by technology

Third, it requires mutants to be crossed with wild-type lines to generate segregating populations, which is time-consuming and laborious work
Nevertheless, the second shortcoming has not been fully resolved in Mutmap+, which still requires at least two generations of selfing to produce the M3 generation

Method used

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  • M2 group-based candidate causal mutation site gene localization method
  • M2 group-based candidate causal mutation site gene localization method
  • M2 group-based candidate causal mutation site gene localization method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0037] Soybean was used as the plant material for the experiment below.

[0038] figure 1 The principle of M2-seq is illustrated. figure 1 A overview of the mutation filtering process. In the present invention, two DNA pools (wild-type pool and mutant-type pool) were respectively constructed in each M2 population, and DNAs from 15 individuals with wild-type and mutant phenotypes were respectively mixed in equal amounts. High-depth (>30X) whole-genome sequencing was performed on each DNA pool. M2-seq consists of two key processes: (i) removal of interfering variants; (ii) mapping of genomic regions harboring causal mutations.

[0039] In order to eliminate the false positive variation that represents the genetic polymorphism or sequencing / alignment error between the wild-type ancestor of the mutant and the reference genome sequence, the present invention designs a variation filtering process with the data of multiple M2 populations, as shown below ( figure 1A). In step 1,...

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Abstract

The invention belongs to the technical field of bioinformatics and biology, and particularly relates to a candidate causal mutation site gene localization method based on an M2 group. According to the method provided by the invention, positioning of candidate causal mutation sites is accelerated by only researching the M2 generation, and background variation can be effectively removed through mutual comparison among M2 groups in the M2-seq under the condition that wild type variation information of a mutant plant is not known. In addition, signal interference caused by rejection linkage of adjacent mutant alleles can be effectively removed by using the absolute value of the [delta]SNP index, so that causal mutation in a target gene can be identified favorably.

Description

technical field [0001] The invention belongs to the field of bioinformatics and biotechnology, in particular to a method for gene positioning of candidate causal mutation sites based on M2 population. Background technique [0002] With the development of next-generation sequencing technology and the continuous decline in the cost of whole genome sequencing (WGS), BSA based on WGS has become a routine tool for rapid location of candidate genes. At present, various WGS-based BSA methods have been developed to locate major QTLs. However, in such WGS-based BSA methods, due to the large number of segregation sites between parents, a large number of QTLs can still be detected in candidate regions. Mutations. To conclusively identify key causal mutations (where causal mutations specifically refer to mutagen-induced functional mutations that lead to target phenotypes), fine mapping of a large segregating population is required. [0003] To avoid reliance on time-consuming fine-map...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16B20/30G16B20/50G16B20/20C12Q1/6895
CPCG16B20/30G16B20/50G16B20/20C12Q1/6895C12Q2600/156
Inventor 冯献忠周煌凯杨素欣于慧唐宽强李广
Owner NORTHEAST INST OF GEOGRAPHY & AGRIECOLOGY C A S
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