METHOD FOR ESTIMATING ADDITIVE AND DOMINANT GENETIC EFFECTS OF SINGLE METHYLATION POLYMORPHISMS (SMPS) ON QUANTITATIVE TRAITS

Information

  • Patent Application
  • 20200216916
  • Publication Number
    20200216916
  • Date Filed
    September 27, 2019
    5 years ago
  • Date Published
    July 09, 2020
    4 years ago
Abstract
The present invention relates to the field of plant molecular breeding, and provides methods for estimating additive and dominant genetic effects of single methylation polymorphisms (SMPs) on quantitative traits. The method comprises the following steps: 1) collecting samples and measuring phenotype in a natural population, and extracting genomic DNA from the samples; 2) constructing MethylC-seq libraries using the sample genomic DNA, and sequencing; 3) identifying the SMPs from the DNA methylation sequencing reads, and performing genotyping; and 4) performing epigenome-wide association study on the SMPs and the phenotypic data using a Mixed Linear Model (MLM), identifying SMPs that are significantly associated with the phenotype, and estimating the additive and dominant genetic effects. The method can provide a new technical guidance for gene marker-assisted breeding, and has important theoretical and breeding values.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS AND CLAIM TO PRIORITY

This application claims priority to Chinese application number 201910005389.1, filed Jan. 3, 2019, entitled METHOD FOR DETECTING ADDITIVE AND DOMINANT GENETIC EFFECTS OF DNA METHYLATION SITES ON QUANTITATIVE TRAITS AND USE THEREOF, which is incorporated herein by reference in its entirety.


FIELD OF THE INVENTION

The present invention relates to the field of plant molecular breeding, and in particular, to methods for estimating additive and dominant genetic effects of single methylation polymorphisms (SMPs) on quantitative traits.


BACKGROUND OF THE INVENTION

DNA methylation is a covalent base modification of nuclear genomes that is accurately inherited through both mitosis and meiosis, which is present in the CG, CHG and CHH contexts (where H=A, C or T). Similar to the SNP generated by spontaneous mutations in DNA sequence, due to the low fidelity of DNA methyltransferase in the genome, errors in the maintenance of the methylation status result in the accumulation of single methylation polymorphisms (SMPs) over an evolutionary timescale, and about 6-25% of cytosines are methylated in higher plant genomes. The natural SMPs with different epialleles can exhibit distinct phenotypes. For example, due to increasing methylation density of Lcyc genes in Linaria vulgaris, the fundamental symmetry of the flower has changed from bilateral to radial, indicating that DNA methylation may play a significant role in that phenotypic variation, and SMPs can be as an important marker to explore the epigenetic mechanism of complex traits.


Many traits that are important for adaptability and growth of plants are complex quantitative traits, affected by multiple genes in different biological pathways. In addition, dissection of genetic architecture reveals the importance of additive and dominant effects of gene in complex traits. The additive effect represents the breeding value of the traits and is the main component of the phenotypic value of the traits. The dominant effect is the effect produced by the interaction between allelic loci, i.e., the difference of a genotype value (G) and an additive effect value (D). Although previous studies have demonstrated the regulatory role of SMPs in plant complex traits, the additive and dominant genetic effects of SMPs, which indicate the breeding value, have not been estimated.


SUMMARY OF THE INVENTION

In view of the above, an objective of the present invention is to provide methods for estimating additive and dominant genetic effects of single methylation polymorphisms (SMPs) on quantitative traits. The methods can scientifically and accurately detect the additive and dominant genetic effects on quantitative traits, and provide new marker resources for marker-assisted breeding, which has important theoretical and breeding values.


To achieve the above purpose, the present invention provides the following technical solutions.


A method for estimating additive and dominant genetic effects of single methylation polymorphisms (SMPs) on quantitative traits includes the following steps:


1) collecting the samples of different individuals in a natural population at the same stage and in the same tissue, and isolating the genomic DNA of each sample; measuring the phenotypic data from the individuals in the natural population;


2) constructing MethylC-seq libraries using the genomic DNA of each sample in step 1), and performing paired-end sequence to obtain DNA methylation sequencing reads;


3) identifying single methylation polymorphisms (SMPs) from the DNA methylation sequencing reads, and performing genotyping according to the methylation support rate (MSR) of the DNA methylation sites in each individual, which is calculated by the formula:







DNA





methylation





support





rate






(
MSR
)


=


methylated





reads



methylated





reads

+

unmethylated





reads







if MSR of the site is >0.7, the genotyping is homozygous methylated site (M:M); if MSR of the site is between 0.3 and 0.7, the genotyping is heterozygous site (U:M); and if MSR of the site is <0.3, the genotyping is homozygous unmethylated site (U:U);


4) performing epigenome-wide association study on SMPs obtained in step 3) and the phenotypic data in step 1) by Mixed Linear Model (MLM), and identifying SMPs that are significantly associated with the phenotype;


5) estimating the additive and dominant genetic effects of the significantly associated SMPs using the Tassel 5.0 software package.


Preferably, a threshold for the identifying the significantly associated SMPs in step 4) is P<1/n (Bonferroni correction), where n is the number of SMPs.


Preferably, software for the identifying SMPs, and performing genotyping according to the methylation support rate of the DNA methylation sites in step 3) is the Bismark software.


Preferably, the DNA methylation sequencing in step 2) is paired-end sequencing with a read length of 125 bp and a depth of 30×; and the sequencing is performed by the Illumina Hiseq 2000/2500 platform.


Preferably, the samples are from perennial woody plants.


Preferably, the phenotypic data includes leaf area and stomatal conductance.


The present invention provides a method for plant molecular breeding.


The advantageous effects of the present invention: the methods provided by the present invention first considers the additive and dominant genetic effects of SMPs, while analyzing the epigenetic variation mechanism of DNA methylation on complex quantitative traits. The methods provide a scientific theoretical basis for the efficient analysis of the epigenetic variation mechanism of complex quantitative traits of perennial woody plants, and a new technical guidance for gene marker-assisted breeding, which has important theoretical and technical values.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 is a Manhattan plot showing the results of the epigenome-wide association study of the leaf area trait in Example 1; and



FIG. 2 is a Manhattan plot showing the results of the epigenome-wide association study of the stomatal conductance trait in Example 2.





DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The present invention provides methods for detecting additive and dominant genetic effects of SMPs on quantitative traits, including the following steps:


1) collecting samples of different individuals in natural population at the same stage and in same tissue, isolating the genomic DNA of each sample, and measuring the phenotypic data from the individuals the natural population;


2) constructing MethylC-seq libraries using the genomic DNA of each sample in step 1), and performing paired-end sequence to obtain DNA methylation sequencing reads;


3) identifying genome-wide single methylation polymorphisms (SMPs) from the DNA methylation sequencing reads, and performing genotyping according to the methylation support rate (MSR) of the DNA methylation sites in each individual, which is calculated by the formula:







DNA





methylation





support





rate






(
MSR
)


=


methylated





reads



methylated





reads

+

unmethylated





reads







if MSR of the site is >0.7, the genotyping is homozygous methylated site (M:M); if MSR of the site is between 0.3 and 0.7, the genotyping is heterozygous site (U:M); and if MSR of the site is <0.3, the genotyping is homozygous unmethylated site (U:U);


4) performing epigenome-wide association study on the SMPs obtained in step 3) and the phenotypic data in step 1) by Mixed Linear Model (MLM), and identifying SMPs that are significantly associated with the phenotype;


5) analyzing the additive and dominant genetic effects of the significantly associated SMPs by the Tassel 5.0 software package.


In the present invention, the samples of different individuals in the natural population are collecting at the same stage and in same tissue; and the phenotypic data are measured from the natural population. The present invention has no particular limitation on the species of the sample. The sample is preferably a plant, and more preferably, a perennial woody plant. In the specific implementation of the present invention, the sample is preferably from Populus tomentosa. In the present invention, the tissue is preferably a leaf. The present invention preferably collects the leaf tissues of different individuals at the same time in the same growth environment, so as to eliminate the influence of environmental effects, growth states and tissue-specificity on DNA methylation sites, thereby identifying SMPs to resolve the additive and dominant genetic effects of SMPs. The present invention has no particular limitation on the phenotypic traits, but a phenotype having practical application significance is preferred. In the specific implementation of the present invention, the phenotype is preferably leaf area and/or stomatal conductance. The present invention has no particular limitation on the phenotypic trait detection method; and a conventional phenotypic trait detection method may be employed.


The present invention isolates the genomic DNA from each sample to obtain genomic DNA. The present invention has no particular limitation on the genomic DNA isolation method; and a conventional genomic DNA extraction method may be used. Preferably, a plant genomic DNA extraction kit is used. Specifically, a DNeasy Plant Mini Kit (Qiagen China, Shanghai, China) is used for extraction. The QiAGEN DNeasy Plant Mini Kit provides rapid and easy purification of the genomic DNA via a gel membrane-based spin column. The genomic DNA isolated from the samples described in the present invention within a specific stage and specific tissue is used to facilitate genotyping of the DNA methylation sites. After extracting the sample genomic DNA, Nanodrop is used to detect an OD260/OD280 ratio of each DNA sample to determine the purity of the DNA sample. OD260/OD280≈1.8 indicates high DNA purity. OD260/OD280 >1.9 indicates RNA contamination. OD260/OD280<1.6 indicates contamination with protein and phenol. After the purity and integrity detection, the present invention preferably further includes: detecting the concentration of the genomic DNA by the Qubit 2.0 Flurometer (Life Technologies, CA, USA).


The present invention constructs MethylC-seq libraries using each genomic DNA of the sample. In the specific implementation of the present invention, the method for constructing the MethylC-seq libraries specifically includes the following steps: 2.1) randomly fragmenting the genomic DNA to 200-300 bp; 2.2) performing terminal modification on the DNA fragment by adding a tail A, and ligating a sequencing adapter; and 2.3) performing PCR amplification after twice treating the ligated DNA fragment with bisulfite. In the present invention, the all cytosines in the sequencing adapter are methylated, and the function of the ligated sequence adapter is to provide sequence information for primers required for the sequencing by amplification process. In the present invention, after the bisulfite treatment, the un-methylated C becomes U (which becomes T after PCR amplification), and the methylated C remains unchanged. In the present invention, the bisulfite treatment is preferably carried out using an EZ DNA Methylation Gold Kit (Zymo Research, Murphy Ave., Irvine, Calif., U.S.A.). The present invention has no particular limitation on the method for constructing the MethylC-seq library. A conventional method for constructing a MethylC-seq library in the art may be used; or the construction of the MethylC-seq library may be entrusted to a biological sequencing company.


After obtaining the MethylC-seq library, the present invention performs DNA methylation sequencing to obtain the DNA methylation sequencing data. In the present invention, the DNA methylation sequencing is preferably paired-end sequencing with a read length of 125 bp and a depth of 30×, and the sequencing is preferably performed using an Illumina Hiseq 2000/2500 platform. In the specific implementation of the present invention, the DNA methylation sequencing is preferably entrusted to Beijing Novogene Biological Information Technology Co., Ltd.


After DNA methylation sequencing, the present invention identifies genome-wide SMPs from the DNA methylation sequencing reads, and performs genotyping according to the methylation support rate (MSR) of the DNA methylation sites in each individual, which calculated by the formula:







DNA





methylation





support





rate






(
MSR
)


=


methylated





reads



methylated





reads

+

unmethylated





reads







if MSR of the site is >0.7, the genotyping is homozygous methylated site (M:M); if MSR of the site is between 0.3 and 0.7, the genotyping is heterozygous site (U:M); and if MSR of the site is <0.3, the genotyping is homozygous unmethylated site (U:U);


In the present invention, the foregoing operation is preferably performed using the Bismark software. The genotyping data of the SMPs obtained by the present invention can be used to perform epigenome-wide association study of SMPs-phenotype to explore the genetic effects of DNA methylation.


After obtaining the genotyping data of the SMPs, the present invention performs epigenome-wide association study on SMPs and the phenotypic data by using a Mixed Linear Model (MLM), and identifies the SMPs significantly associated with the phenotype. In the present invention, a threshold for the identifying the significantly associated DNA methylation sites is P<1/n (Bonferroni correction), where n is the number of SMPs. In the specific implementation of the present invention, the MLM module is preferably selected in the Tassel 5.0 software package, and the population structure and kinship matrix are set as covariates.


After obtaining the significantly associated SMPs, the present invention analyzes the additive and dominant genetic effects of the significantly associated SMPs by the Tassel 5.0 software package.


The present invention also provides use of the foregoing method in plant molecular breeding, and preferably used in plant molecular assisted breeding. The present invention has no particular limitation on the specific method of application.


The technical solution provided by the present invention are described below in detail with reference to examples. However, the examples should not be construed as limiting the protection scope of the present invention.


Example 1

Specific operation steps are as follows:


Step 1): The natural population is of 5-year-old, 300 Populus tomentosa genotypic individuals planted in Guanxian County, Shandong, China. The functional leaves (the fourth to sixth leaves from the top of the stem) are collected from 9:00 to 11:00 AM, and in order to prevent changes in its DNA methylation pattern, and are immediately frozen in liquid nitrogen (−196° C.) after collection.


Step 2): the genomic DNA of the leaf samples are isolated using DNeasy Plant Mini Kit (Qiagen China, Shanghai, China).


After the foregoing steps are completed, the genomic DNA can be further detected, specifically: 2.1: the degree of degradation of the DNA sample and the RNA contamination are determined by agarose gel electrophoresis; 2.2: the OD260/OD280 ratio of each DNA sample is detected using Nanodrop to determine the purity of the DNA sample; and 2.3: the concentration of each DNA sample is accurately quantified using Qubit2.0 Flurometer (Life Technologies, CA, USA).


Then, the methods of performing bisulfite sequencing on the extracted genomic DNA and constructing the bisulfite-treated DNA library based on the genomic DNA in step 3) uses a conventional technical method, and the specific implementation of the present invention is as follows:


Step 3.1: the genomic DNA is randomly fragment to 200-300 bp by using Covaris S220.


Step 3.2: end repairing and tail A addition are performed on the DNA fragments, using the sequencing adapters in which all cytosines are methylated, the purpose of which is to provide sequence information for the primers required for PCR amplification.


Step 3.3: the DNA fragments in step 3.2 are twice treat with bisulfite, and after the bisulfite treatment, the C which is not methylated becomes U (which becomes T after PCR amplification), and the methylated C remains unchanged. Specifically, the bisulfite treatment is carried out using an EZ DNA Methylation Gold Kit (Zymo Research, Murphy Ave., Irvine, Calif., U.S.A.).


Step 3.4: the bisulfite-treated DNA fragments in step 3.3 are subjected to PCR amplification to construct a MethylC-seq library.


Step 3.5: sequencing is performed on MethylC-seq library.


The DNA isolation, MethylC-seq library construction, and sequencing were performed on Beijing Novogene Biological Information Technology Co., Ltd.


Step 4): identifying DNA methylation sites according to a sequencing reads of each sample, and performing genotyping on the SMPs. The sequencing reads of each sample were aligned to the Populus tomentosa reference genome using the Bismark and the Bowtie2 software, with default parameters to identify the SMPs. The methylation support rate of each DNA methylation site is calculated for genotyping. Specifically, the methylation support rate (MSR) of the DNA methylation sites in each individual, which calculated by the formula:







DNA





methylation





support





rate






(
MSR
)


=


methylated





reads



methylated





reads

+

unmethylated





reads







if MSR of the site is >0.7, the genotyping is homozygous methylated site (M:M); if MSR of the site is between 0.3 and 0.7, the genotyping is heterozygous site (U:M); and if MSR of the site is <0.3, the genotyping is homozygous unmethylated site (U:U);


Step 5) Measurement of leaf area traits. The functional leaves (the fourth to sixth leaves from the top of the stem) are collected at the same time as the leaf samples for extracting the genomic DNA. Then, the functional leaves of each individuals were used to measure the leaf area by CI-202 portable laser leaf area meter (CID Bio-Science, Inc., Camas, Wash., USA). The leaf area phenotypic value is shown in Table 1.









TABLE 1







Leaf area of 300 genotypic individuals of a natural


population of Populus tomentosa (unit: cm2)










Individual
Leaf



No.
area














P1
49.083



P2
59.855



P3
49.930



P4
36.623



P5
40.853



P6
38.860



P7
40.840



P8
69.623



P9
50.240



P10
33.293



P11
65.273



P12
50.123



P13
68.125



P14
40.953



P15
45.693



P16
43.947



P17
40.073



P18
49.123



P19
61.123



P20
52.210



P21
31.343



P22
46.910



P23
37.695



P24
38.763



P25
48.915



P26
40.588



P27
41.583



P28
51.040



P29
40.373



P30
45.067



P31
37.533



P32
47.357



P33
60.853



P34
58.697



P35
48.353



P36
43.053



P37
49.500



P38
37.577



P39
47.467



P40
56.023



P41
52.110



P42
54.677



P43
51.950



P44
36.813



P45
53.353



P46
41.260



P47
79.670



P48
35.470



P49
53.010



P50
43.687



P51
44.827



P52
58.093



P53
35.393



P54
43.487



P55
61.603



P56
70.720



P57
35.943



P58
54.493



P59
61.335



P60
46.500



P61
39.470



P62
73.667



P63
37.892



P64
54.569



P65
71.414



P66
76.283



P67
34.955



P68
56.178



P69
34.529



P70
53.192



P71
52.071



P72
73.927



P73
42.210



P74
39.881



P75
54.557



P76
70.088



P77
54.795



P78
39.476



P79
55.622



P80
59.773



P81
66.672



P82
37.155



P83
38.168



P84
44.874



P85
64.770



P86
71.582



P87
66.887



P88
76.834



P89
45.763



P90
74.009



P91
48.508



P92
75.425



P93
34.930



P94
55.451



P95
40.035



P96
44.023



P97
35.823



P98
54.938



P99
68.346



P100
57.539



P101
28.577



P102
42.988



P103
46.291



P104
49.900



P105
62.410



P106
39.532



P107
70.836



P108
30.866



P109
31.078



P110
39.121



P111
61.967



P112
37.722



P113
29.301



P114
66.277



P115
54.727



P116
33.596



P117
73.800



P118
55.943



P119
34.167



P120
73.484



P121
38.289



P122
76.656



P123
75.219



P124
33.297



P125
49.464



P126
68.489



P127
66.641



P128
29.645



P129
74.485



P130
28.387



P131
54.633



P132
59.134



P133
62.161



P134
45.621



P135
41.156



P136
36.315



P137
50.044



P138
48.783



P139
57.555



P140
39.324



P141
69.668



P142
28.293



P143
55.258



P144
71.853



P145
29.790



P146
41.682



P147
63.049



P148
73.299



P149
44.750



P150
34.424



P151
49.343



P152
61.850



P153
48.575



P154
77.912



P155
43.120



P156
55.207



P157
61.314



P158
61.479



P159
41.501



P160
35.072



P161
45.791



P162
30.921



P163
32.816



P164
62.476



P165
75.361



P166
67.696



P167
30.662



P168
60.338



P169
53.910



P170
31.342



P171
67.656



P172
53.879



P173
51.972



P174
77.709



P175
53.074



P176
37.112



P177
77.032



P178
33.794



P179
58.133



P180
44.387



P181
32.296



P182
28.201



P183
59.196



P184
69.913



P185
34.461



P186
73.376



P187
36.657



P188
28.777



P189
45.385



P190
54.075



P191
73.212



P192
76.185



P193
31.726



P194
53.727



P195
68.299



P196
72.902



P197
34.605



P198
60.115



P199
28.971



P200
46.561



P201
39.706



P202
64.099



P203
58.639



P204
55.944



P205
67.451



P206
47.302



P207
39.418



P208
48.549



P209
58.114



P210
36.017



P211
48.257



P212
55.182



P213
74.486



P214
56.220



P215
28.831



P216
48.770



P217
44.003



P218
32.474



P219
28.426



P220
54.987



P221
51.716



P222
60.996



P223
45.842



P224
69.373



P225
70.203



P226
54.424



P227
54.551



P228
57.263



P229
31.684



P230
33.353



P231
59.161



P232
36.854



P233
71.878



P234
63.735



P235
72.703



P236
63.190



P237
43.626



P238
45.447



P239
63.674



P240
61.973



P241
49.860



P242
40.573



P243
47.432



P244
46.447



P245
37.605



P246
43.497



P247
29.440



P248
30.064



P249
47.393



P250
46.697



P251
31.023



P252
52.193



P253
63.787



P254
48.363



P255
37.305



P256
43.833



P257
59.904



P258
63.976



P259
75.217



P260
67.104



P261
48.533



P262
70.309



P263
36.488



P264
29.788



P265
32.623



P266
35.577



P267
47.400



P268
66.821



P269
30.767



P270
48.007



P271
34.967



P272
45.603



P273
41.774



P274
64.766



P275
61.117



P276
48.990



P277
35.583



P278
47.577



P279
70.887



P280
67.749



P281
30.258



P282
39.828



P283
59.357



P284
55.322



P285
40.718



P286
76.666



P287
44.021



P288
41.988



P289
59.963



P290
32.149



P291
65.665



P292
49.786



P293
69.942



P294
71.353



P295
69.399



P296
77.248



P297
40.207



P298
68.124



P299
55.493



P300
35.035










Step 6) the additive and dominant genetic effects of SMPs on leaf size trait are detected. The MLM model is used to perform epigenome-wide association study on the SMPs and leaf area trait under the population structure and kinship matrix. The significantly associated SMPs were identified under the threshold is P<1/n (n is the number of DNA methylation sites, Bonferroni correction). Then the additive and dominant genetic effects are analyzed by the Tassel 5.0 software. The results are shown in FIG. 1. FIG. 1 shows the results of genome-wide epigenetic association analysis of the leaf area (shown in the Manhattan plot), and a specific region on chromosome 1 of Populus tomentosa is shown, which significantly associated DNA methylation sites are shown above the horizontal line. Table 2 shows the additive and dominant genetic effects of the significantly associated SMPs of the leaf area.









TABLE 2







Additive and dominant genetic effects of the


significantly associated SMPs underlying the leaf area












Additive
Dominant


SMP_ID
P_value
effect
effect













chr01_35476367
0.000000565

18.61


chr01_35476368
0.000000367
−4.34



chr01_35477495
0.000000000536
5.54
−2.80


chr01_35478662
0.00000741
6.88










Example 2

Specific operation steps are as follows:


Step 1): The natural population is of 5-year-old, 300 Populus tomentosa genotypic individuals planted in Guanxian County, Shandong, China. The functional leaves (the fourth to sixth leaves from the top of the stem) are collected from 9:00 to 11:00 AM, and in order to prevent changes in its DNA methylation pattern, the functional leaves are immediately frozen in liquid nitrogen (−196° C.) after collection.


Step 2): the genomic DNA of the leaf samples are isolated using DNeasy Plant Mini Kit (Qiagen China, Shanghai, China).


After the foregoing steps are completed, the genomic DNA can be further detected, specifically: 2.1: the degree of degradation of the DNA sample and the RNA contamination are determined by agarose gel electrophoresis; 2.2: the OD260/OD280 ratio of each DNA sample is detected using Nanodrop to determine the purity of the DNA sample; and 2.3: the concentration of each DNA sample is accurately quantified using Qubit2.0 Flurometer (Life Technologies, CA, USA).


Then, the method of performing bisulfite sequencing on the extracted genomic DNA, and constructing the bisulfite-treated DNA library based on the genomic DNA in step 3) uses a conventional technical method. The specific implementation of the present invention is as follows:


Step 3.1: the genomic DNA is randomly fragment to 200-300 bp by using Covaris S220.


Step 3.2: end repairing and tail A addition are performed on the DNA fragments using sequencing adapters in which all cytosines are methylated, the purpose of which is to provide sequence information for the primers required for the PCR amplification.


Step 3.3: the DNA fragments in step 3.2 are twice treat with bisulfite. After the bisulfite treatment, C which is not methylated becomes U (which becomes T after PCR amplification), and the methylated C remains unchanged. Specifically, the bisulfite treatment is carried out using EZ DNA Methylation Gold Kit (Zymo Research, Murphy Ave., Irvine, Calif., U.S.A.).


Step 3.4: the bisulfite-treated DNA fragments in step 3.3 are subjected to PCR amplification to construct a MethylC-seq library.


Step 3.5: sequencing is performed on the MethylC-seq library.


The DNA isolation, MethylC-seq library construction, and sequencing were performed by Beijing Novogene Biological Information Technology Co., Ltd.


Step 4): identifying DNA methylation sites according to a sequencing reads of each sample, and performing genotyping on the SMPs. The sequencing reads of each sample are aligned to the Populus tomentosa reference genome using the Bismark and the Bowtie2 software with default parameters to identify the SMPs. The methylation support rate of each DNA methylation site is calculated for genotyping. Specifically, the methylation support rate (MSR) of the DNA methylation sites in each individual, which is calculated by the formula:







DNA





methylation





support





rate






(
MSR
)


=


methylated





reads



methylated





reads

+

unmethylated





reads







if MSR of the site is >0.7, the genotyping is homozygous methylated (M:M); if MSR of the site is between 0.3 and 0.7, the genotyping is heterozygous (U:M); and if MSR of the site is <0.3, the genotyping is homozygous unmethylated (U:U);


Step 5) Measurement of stomatal conductance traits. The functional leaves (the fourth to sixth leaves from the top of the stem) are collected at the same time as the leaf samples for extracting the genomic DNA. Then, the functional leaves of each individuals were used to measuring the stomatal conductance by the LI-6400 portable photosynthesis system (LI-COR Inc., Lincoln, Nebr., USA). The stomatal conductance phenotypic value is shown in Table 3.









TABLE 3







Stomatal conductance trait of 300 genotypic individuals


of a natural population of Populus tomentosa (unit: mol ·


m−2 · s−1)










Indiv.
Stomatal



No.
conductance














P1
0.258



P2
0.227



P3
0.152



P4
0.104



P5
0.260



P6
0.053



P7
0.078



P8
0.168



P9
0.054



P10
0.028



P11
0.265



P12
0.063



P13
0.298



P14
0.209



P15
0.047



P16
0.048



P17
0.171



P18
0.248



P19
0.159



P20
0.089



P21
0.015



P22
0.051



P23
0.015



P24
0.073



P25
0.042



P26
0.111



P27
0.080



P28
0.260



P29
0.150



P30
0.195



P31
0.090



P32
0.068



P33
0.209



P34
0.236



P35
0.251



P36
0.086



P37
0.107



P38
0.193



P39
0.063



P40
0.019



P41
0.062



P42
0.227



P43
0.189



P44
0.107



P45
0.050



P46
0.272



P47
0.220



P48
0.079



P49
0.121



P50
0.018



P51
0.094



P52
0.060



P53
0.024



P54
0.163



P55
0.238



P56
0.237



P57
0.051



P58
0.261



P59
7.702



P60
0.158



P61
4.552



P62
1.793



P63
5.242



P64
6.424



P65
6.288



P66
1.177



P67
3.511



P68
5.980



P69
0.191



P70
6.411



P71
2.399



P72
0.521



P73
0.502



P74
1.143



P75
4.796



P76
0.386



P77
0.892



P78
0.568



P79
1.258



P80
5.852



P81
6.810



P82
6.318



P83
2.317



P84
5.949



P85
2.036



P86
5.017



P87
0.795



P88
3.640



P89
5.191



P90
3.755



P91
3.596



P92
1.332



P93
3.900



P94
0.286



P95
6.846



P96
6.915



P97
4.113



P98
5.949



P99
2.541



P100
1.980



P101
5.108



P102
5.161



P103
4.002



P104
0.473



P105
6.714



P106
6.309



P107
6.605



P108
3.216



P109
1.740



P110
5.112



P111
1.790



P112
5.837



P113
4.768



P114
2.112



P115
2.105



P116
6.314



P117
2.738



P118
3.507



P119
4.875



P120
4.889



P121
3.012



P122
3.496



P123
4.900



P124
2.632



P125
5.616



P126
1.949



P127
4.334



P128
6.489



P129
3.417



P130
2.220



P131
4.948



P132
1.547



P133
6.973



P134
1.325



P135
4.926



P136
6.315



P137
2.451



P138
3.593



P139
2.761



P140
4.571



P141
6.337



P142
3.424



P143
5.204



P144
3.826



P145
6.532



P146
6.930



P147
4.321



P148
0.817



P149
2.754



P150
6.488



P151
0.003



P152
3.434



P153
6.168



P154
5.678



P155
2.431



P156
2.321



P157
6.207



P158
1.014



P159
5.414



P160
6.745



P161
0.203



P162
4.738



P163
2.823



P164
6.120



P165
1.387



P166
0.778



P167
3.501



P168
1.421



P169
3.389



P170
4.788



P171
2.939



P172
2.618



P173
1.863



P174
5.977



P175
0.407



P176
2.436



P177
2.843



P178
4.030



P179
6.926



P180
6.632



P181
5.677



P182
4.716



P183
6.456



P184
2.130



P185
0.821



P186
1.877



P187
6.165



P188
5.600



P189
5.216



P190
1.314



P191
4.615



P192
1.425



P193
1.206



P194
5.523



P195
1.097



P196
6.355



P197
5.797



P198
6.625



P199
5.087



P200
0.026



P201
2.113



P202
5.660



P203
5.908



P204
5.261



P205
2.198



P206
6.399



P207
0.378



P208
3.647



P209
6.803



P210
6.920



P211
1.002



P212
0.262



P213
4.849



P214
3.847



P215
0.589



P216
5.112



P217
1.893



P218
1.501



P219
4.583



P220
4.009



P221
2.806



P222
1.936



P223
4.493



P224
2.935



P225
6.782



P226
2.257



P227
2.267



P228
3.780



P229
4.908



P230
2.207



P231
3.356



P232
3.070



P233
0.634



P234
2.522



P235
3.062



P236
2.078



P237
1.747



P238
4.851



P239
1.332



P240
0.227



P241
0.251



P242
0.032



P243
0.094



P244
0.112



P245
0.081



P246
0.089



P247
0.139



P248
0.053



P249
0.257



P250
0.066



P251
0.276



P252
0.079



P253
0.260



P254
0.080



P255
0.040



P256
0.253



P257
0.048



P258
0.145



P259
0.059



P260
0.115



P261
0.063



P262
0.203



P263
0.298



P264
0.153



P265
0.311



P266
2.756



P267
1.188



P268
5.814



P269
6.607



P270
6.107



P271
0.873



P272
1.551



P273
5.731



P274
3.718



P275
6.090



P276
5.812



P277
2.363



P278
2.034



P279
5.149



P280
1.649



P281
4.447



P282
5.860



P283
0.544



P284
3.543



P285
5.083



P286
3.652



P287
1.283



P288
6.147



P289
3.518



P290
0.816



P291
6.110



P292
3.081



P293
3.481



P294
1.530



P295
3.403



P296
1.362



P297
0.321



P298
3.707



P299
6.424



P300
2.594










Step 6) the additive and dominant genetic effects of SMPs on stomatal conductance trait are detected. The MLM model is used to perform epigenome-wide association study on the SMPs and stomatal conductance trait under the population structure and kinship matrix. The significantly associated SMPs are identified under the threshold P<1/n (n is the number of DNA methylation sites, Bonferroni correction). Then the additive and dominant genetic effects are analyzed using the Tassel 5.0 software. The results are shown in FIG. 2. FIG. 2 shows the results of genome-wide epigenetic association analysis of the stomatal conductance (shown in the Manhattan plot), and a specific region on chromosome 1 of Populus tomentosa is shown, where significantly associated DNA methylation sites are shown above the horizontal line. Table 4 shows the additive and dominant genetic effects of the significantly associated SMPs of the stomatal conductance.









TABLE 4







Additive and dominant genetic effects of the


significantly associated SMPs underlying


the stomatal conductance










SMP_ID
P_value
Additive effect
Dominant effect













chr01_928366
0.00000000539
−3.778696064
−3.760257703


chr01_949225
0.0000000571

7.552436241


chr01_728260
0.000000393

0.094728243


chr01_928367
0.000000664

0.165908058


chr01_63116
0.00000136

0.150602667


chr01_680224
0.00000171
−0.13269173










As can be seen from the above experimental data, the method provided by the present invention has the advantage of providing the first estimation of the additive and dominant genetic effects of SMPs underlying complex quantitative traits. The present invention provides a scientific theoretical basis for the dissection of the epigenetic architectures of quantitative traits of perennial woody plants, and a new technical guidance for gene marker-assisted breeding, which has important theoretical and technical values.


The foregoing descriptions are only preferred implementation manners of the present invention. It should be noted that for a person of ordinary skill in the field, several improvements and modifications might further be made without departing from the principle of the present invention. These improvements and modifications should also be deemed as falling within the protection scope of the present invention.

Claims
  • 1. A method for estimating additive and dominant genetic effects of single methylation polymorphisms (SMPs) on quantitative traits, comprising the following steps: 1) collecting the samples of different individuals in natural population at the same stage and same tissue, and isolating the genomic DNA of each sample; measuring the phenotypic data from the individuals in natural population;2) constructing MethylC-seq libraries using the genomic DNA of each sample in step 1), and performing paired-end sequence to obtain DNA methylation sequencing reads;3) identifying single methylation polymorphisms (SMPs) from the DNA methylation sequencing reads, and performing genotyping according to the methylation support rate (MSR) of the DNA methylation sites in each individual, which calculated by the formula:
  • 2. The method according to claim 1, wherein a threshold for the identifying the significantly associated SMPs in step 4) is P<1/n (Bonferroni correction), where n is the number of SMPs.
  • 3. The method according to claim 1, wherein software for the identifying SMPs, and performing genotyping according to the methylation support rate of the DNA methylation sites in step 3) is Bismark software.
  • 4. The method according to claim 1, wherein the DNA methylation sequencing in step 2) is paired-end sequencing with a read length of 125 bp and a depth of 30×; and the sequencing is performed by Illumina Hiseq 2000/2500 platform.
  • 5. The method according to claim 1, wherein the samples are perennial woody plants.
  • 6. The method according to claim 2, wherein the samples are perennial woody plants.
  • 7. The method according to claim 3, wherein the samples are perennial woody plants.
  • 8. The method according to claim 4, wherein the samples are perennial woody plants.
  • 9. The method according to claim 1, wherein the phenotypic shape comprises leaf area and stomatal conductance.
  • 10. The method according to claim 2, wherein the phenotypic shape comprises leaf area and stomatal conductance.
  • 11. The method according to claim 3, wherein the phenotypic shape comprises leaf area and stomatal conductance.
  • 12. The method according to claim 4, wherein the phenotypic shape comprises leaf area and stomatal conductance.
  • 13. Use of the method according to claim 1 in plant molecular breeding.
  • 14. Use of the method according to claim 2 in plant molecular breeding.
  • 15. Use of the method according to claim 3 in plant molecular breeding.
  • 16. Use of the method according to claim 4 in plant molecular breeding.
Priority Claims (1)
Number Date Country Kind
201910005389.1 Jan 2019 CN national