Method for selecting statistically validated candidate genes

一种基因型、辅因子的技术，应用在分子遗传学领域，能够解决研究人员引入歧途、没有鉴定出基因等问题

Active Publication Date: 2015-03-18
SYNGENTA PARTICIPATIONS AG
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

As a result, researchers are often led astray and do not identify the gene that affects the trait

Method used

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  • Method for selecting statistically validated candidate genes
  • Method for selecting statistically validated candidate genes
  • Method for selecting statistically validated candidate genes

Examples

Experimental program
Comparison scheme
Effect test

example 1

[0152] Example 1. QTL detection in nested populations

[0153] NAM was performed using SMR and MMR in combination with the permutation method described below to determine the LOD threshold for NAM.

[0154] Single Marker Regression (SMR):

[0155] The linear model used to describe the relationship between trait values ​​and marker genotypes is:

[0156] the y ij =μ+x ij a+g i u i +e ij (Model 1)

[0157] where y ij is the phenotype value of individual j in subpopulation i; μ is the overall mean; a is the additive effect of QTL; g i is the indicator variable of subpopulation i; u i is the effect of subpopulation i; e ij is the residual; and where x if individual j carries an allele from a common parent ij is defined as 1, and if individual j carries alleles from other parents when x ij is defined as -1.

[0158] This definition is based on the fact that there are only two different alleles for each marker. To take advantage of the simplicity of regression, t...

example 2

[0172] Example 2. Method for selecting lead candidates for further validation after genome-wide joint mapping Law

[0173] With the advent of omics, the identification of key candidate genes (those that function in phenotypes or complex biological processes) among the thousands of genes in the genome has paradoxically become one of the major hurdles. Indeed, contrary to some early concerns (that the lack of sufficient comprehensive data will remain a limiting factor), it is the exact opposite that scientists are now challenged by the deluge of information. This has translated into the need for sophisticated tools to mine, integrate, and prioritize vast amounts of information. The present invention will help to prioritize candidate leads identified through genome-wide joint mapping (for example using sequences from Solexa technology) for further validation and implementation in marker assisted breeding.

[0174] QTL mapping for traits of interest was performed using nested...

example 3

[0176] Example 3. QTL detection using NAM SMR and MMR

[0177] Experimental design and preparation of phenotypic and genotypic data

[0178] These NAM RIL lines were grown across five locations over a two-year period. Traits of interest, including primarily starch and protein in the corn ethanol project, were assessed across the locations and years. The phenotypic data from each location was unbalanced. These unbalanced data structures suggest that it is necessary to obtain corresponding genotype data for these lines. To do so, genotype data (www.panzea.org / lit / data sets.html) were downloaded for all these markers and genotype information was extracted for the NAM lines evaluated. Also, to perform SMR and MMR, consensus linkage maps were found from the same website and downloaded for further use.

[0179] Methods of Data Analysis

[0180] QTLs responsible for starch and protein in maize were detected using NAM SMRs as well as MMRs. Details of these methods are describe...

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Abstract

Provided herein are methods for evaluating associations between candidate genes and a trait of interest in a population. The methods include a combination of genome-wide association analysis and one or more of nested association mapping (NAM), expression QTL analysis (eQTL), and allele epistastic analysis (AEA). Markers are selected or prioritized if they are shown to be positively-correlated with a trait of interest using GWA and a combination of one or both of NAM and eQTL. Also provided are models for evaluating the association between a candidate marker and a trait in a nested population of organisms. These methods include single marker regression and multiple marker regression models. Markers identified using the methods of the invention can be used in marker assisted breeding and selection, as genetic markers for constructing linkage maps, for gene discovery, for identifying genes contributing to a trait of interest, and for generating transgenic organisms having a desired trait.

Description

field of invention [0001] The present invention relates to molecular genetics, and in particular to methods for assessing associations between genetic markers and phenotypes in a population. Background of the invention [0002] Multiplexed experimental paradigms have been developed to identify and analyze quantitative trait loci (QTLs) (see eg, Jansen (1996) Trends Plant Sci 1:89). A quantitative trait locus (QTL) is a region of the genome that encodes one or more proteins and accounts for a significant proportion of the variability of a given phenotype that can be controlled by multiple genes. Most published reports on QTL mapping in crop species are based on the use of biparental crosses. Typically, these paradigms involve crossing one or more parental pairs, which may be, for example, a single pair derived from two inbred strains, or multiple related or Unrelated parents that each exhibit distinct characteristics relative to the phenotypic trait of interest. Typically,...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F19/18G16B20/20G16B20/40G16B40/00
CPCG06F19/24G06F19/18G16B20/00G16B20/40G16B40/00G16B20/20A01H1/02A01H1/045
Inventor V.K.基肖尔郭志刚李珉王道龙L.A.谷迪尔莱兹罗贾斯J.D.V.克拉克J.拜勒姆
Owner SYNGENTA PARTICIPATIONS AG
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