Scientia Agricultura Sinica ›› 2023, Vol. 56 ›› Issue (8): 1561-1573.doi: 10.3864/j.issn.0578-1752.2023.08.011

• HORTICULTURE • Previous Articles     Next Articles

Genome-Wide Association Studies for Grape Berry Weight Related Traits

WANG HuiLing1(), YAN AiLing2, WANG XiaoYue3, LIU ZhenHua1, REN JianCheng1, XU HaiYing1(), SUN Lei1()   

  1. 1 Institute of Forestry and Pomology, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100093
    2 Beijing Engineering Research Center for Deciduous Fruit Trees, Beijing 100093
    3 Key Laboratory of Biology and Genetic Improvement of Horticultural Crops (North China), Ministry of Agriculture and Rural Affairs, Beijing 100093
  • Received:2022-06-08 Accepted:2022-08-24 Online:2023-04-16 Published:2023-04-23

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Abstract:

【Objective】Grape berry size is one of important factors affecting grape appearance and the final productivity. It is a complex quantitative trait regulated by multiple genes. Mining the key genetic regulatory loci and the underlying genes for berry size related traits would help to improve grape yield. 【Method】In this study, 150 diverse grapevine varieties were selected as materials. The berry weight, seed number per berry, and seed weight were measured in 2019 and 2020, respectively. Based on high-density genotype data obtained by resequencing, the genome-wide association studies (GWAS) were carried out to detect significantly associated SNPs and to predict important candidate genes.【Result】The three measured traits exhibited extensive phenotypic variation with 39.55%-68.89% of phenotypic variation coefficients; the phenotypic distribution of the observed three traits in the population showed continuous quantitative genetic characteristics; a significant positive correlation between each trait were observed in two years; based on the phenotypic data collected in two years, a total of 150 significant SNPs were detected for berry weight. In 2019, 99 SNPs were detected, each of which contributed the phenotypic variation from 14.48% to 25.59%; in 2020, 73 SNPs were detected, explaining 16.08%-26.83% of phenotypic variation; among these SNPs, 24 were detected repeatedly in both two years, mainly located on chromosome 1, 5, 11 and 16. Compared with the trait of berry weight, less SNPs significantly associated with the seed number were detected. A significant SNP was detected in 2019, and the phenotypic explanation value was 24.29%; in 2020, 17 significant SNPs were detected, which all located on chromosome 18; 1 and 2 SNPs located on chromosome 18 significantly associated with seed weight were detected in 2019 and 2020, respectively, accounting for 23.59%-48.29% of phenotypic variation. Within the genomic region of SNPs detected repeatedly for two years, 11 candidate genes related to berry weight were screened out based on the functional annotation, including ethylene signal pathway genes (VIT_05s0049g00490, VIT_05s0049g00500, VIT_05s0049g00510 and VIT_16s0100g00400), gibberellin signal pathway genes (VIT_11s0016g04630 and VIT_16s0022g02310), auxin responsive protein gene (VIT_11s0016g05640) and some important transcription factor genes (VIT_05s0049g00460, VIT_11s0016g05660 and VIT_16s0022g02330). A candidate gene VIT_18s0041g01880 (encoding a MADS box protein VviAGL11) associated with seed content was identified on chromosome 18, and different SNP genotypes on this gene significantly affected the grape berry seed number and weight. 【Conclusion】A total of 150 SNPs significantly associated with berry weight were detected in two years, mainly located on chromosomes 1, 5, 11 and 16; A total of 19 significant SNPs associated with seed content were detected, mainly located on chromosome 18. Based on the results of gene annotation and genotype analysis, 11 candidate genes that might be involved in the regulation of grape berry weight including VIT_11s0016g04630 and VIT_16s0022g02310 were selected; the candidate gene VIT_18s0041g01880 was determined significantly correlated with seed content.

Key words: grape, berry size, genome-wide association studies, candidate gene

Table 1

Statistics of grape berry size related traits"

性状
Trait		 年份
Year		 变异范围
Variation range		 均值±标准差
Mean±SD		 偏度
Skewness		 峰度
Kurtosis		 变异系数
CV (%)
果实单粒重
Berry weight (BW, g)		 2019 0.91-11.91 5.62±2.37 -0.02 -0.71 42.17
2020 1.5-11.7 5.92±2.44 -0.004 -0.72 41.22
种子数
Seed number (SN)		 2019 0-4.75 2.23±1.15 -0.69 -0.17 51.57
2020 0-4 2.20±0.87 -0.52 0.15 39.55
种子质量
Seed weight (SW, g)		 2019 0-1.00 0.34±0.22 -0.13 -0.66 64.71
2020 0-1.32 0.45±0.31 0.11 -0.97 68.89

Fig. 1

Frequency distribution of grape berry size related traits"

Table 2

Correlation coefficient for grape berry size related traits"

性状Trait 2019BW 2019SN 2019SW 2020BW 2020SN 2020SW
2019BW 1 0.442** 0.561** 0.858** 0.166 0.526**
2019SN 1 0.584** 0.407** 0.550** 0.561**
2019SW 1 0.494** 0.360** 0.823**
2020BW 1 0.212* 0.529**
2020SN 1 0.537**
2020SW 1

Fig. 2

Population linkage disequilibrium (LD) and population genetic structure"

Fig. 3

The Manhattan diagram of GWAS results for grape berry size related traits A-B: The GWAS results for berry weight in 2019 and 2020, respectively; C-D: The GWAS results for seed number in 2019 and 2020, respectively; E-F: The GWAS results for seed weight in 2019 and 2020, respectively. The X-axis shows the SNPs along each chromosome, a dot represents a SNP loci, the Y-axis is the -log10 P for the association, The red dotted line is the negative logarithm of 0.05/all SNPs, and the blue dotted line is the negative logarithm of 0.1/all SNPs. Scattered dots (or lines) above the threshold line are candidate sites"

Table 3

The information of significant sites detected in two years by genome-wide association analysis for grape berry size related traits"

性状
Trait		 染色体
Chr		 位置
Position		 P值 P value 贡献率R2 (%) 基因型
Genotype
2019 2020 2019 2020
单粒重
Berry weight		 1 22639484 2.48E-10 1.94E-09 23.45 23.30 T/ A
5 7537999 6.37E-11 4.89E-10 21.59 22.03 G/A
5 9220655 6.91E-10 5.16E-10 22.19 23.47 A/G
11 3961705 1.44E-09 7.32E-10 21.88 24.67 T/C
11 4206358 1.97E-09 1.31E-10 17.40 21.14 T/G
11 4206905 1.88E-10 4.3E-11 23.35 26.73 T/A
11 4207208 1.03E-09 2.53E-10 22.20 25.79 G/A
11 4207295 8.32E-10 1.29E-10 21.32 25.17 A/G
11 4208224 1.47E-09 2.31E-10 22.27 26.51 G/A
11 4211568 6.47E-10 1.50E-10 22.79 26.40 A/G
11 4212068 3.21E-11 6.20E-12 23.95 27.69 T/C
11 4337558 1.61E-10 2.89E-11 22.81 26.83 G/A
11 4342720 8.80E-11 2.30E-10 24.01 25.40 A/T
11 4342872 3.19E-10 1.38E-09 22.30 22.73 G/C
11 4420462 1.43E-11 3.06E-10 21.97 21.28 A/G
11 4835190 1.76E-09 1.30E-10 19.10 24.69 T/G
11 4855046 1.86E-09 2.45E-10 18.67 22.55 G/A
11 4902154 1.96E-09 2.16E-10 19.77 24.39 G/A
11 5132979 4.75E-10 2.43E-09 16.23 16.08 G/A
11 5164917 2.34E-09 1.70E-09 16.03 17.85 A/T
11 5168340 4.44E-10 2.25E-10 16.72 19.05 A/G
11 5169147 1.64E-09 2.72E-09 18.08 18.47 C/T
16 14893081 1.17E-09 6.98E-10 17.83 18.70 G/A
16 15790424 1.03E-09 1.96E-09 18.55 18.45 T/C
种子数目 Seed number 18 27835284 2.44E-09 8.72E-10 24.29 25.67 G/A
种子质量 Seed weight 18 26889437 4.90E-11 1.53E-13 40.11 48.29 C/A

Table 4

Published functional candidate genes potentially involved in grapevine seed and/or berry development colocalized significant locus detected"

基因ID
Gene ID		 基因组位置
Physical position		 基因注释
NR annotation		 参考文献
Reference
VIT_01s0150g00260 1: 22675690-22682439 E3泛素蛋白连接酶At3g02290
E3 ubiquitin-protein ligase At3g02290 [Vitis vinifera]		 SONG等[18]
VIT_05s0049g00460 5: 7500113-7506717 转录因子bHLH104异构体X2
Transcription factor bHLH104 isoform X2 [Vitis vinifera]		 GU等[19]
VIT_05s0049g00490 5:7542707-7543164 乙烯响应转录因子ERF095
Ethylene-responsive transcription factor ERF095 [Vitis vinifera]		 YUSTE-LISBONA等[20]
VIT_05s0049g00500 5: 7549843-7550323 乙烯响应转录因子ERF098
Ethylene-responsive transcription factor ERF098 [Vitis vinifera]		 YUSTE-LISBONA等[20]
VIT_05s0049g00510 5: 7567335-7580633 乙烯响应转录因子1B
Ethylene-responsive transcription factor 1B [Vitis vinifera]		 YUSTE-LISBONA等[20]
VIT_11s0016g04630 11: 3959481-3961177 DELLA蛋白SLR1
DELLA protein SLR1 [Vitis vinifera]		 UPADHYAY等[21]
VIT_11s0016g05640 11: 生长素响应蛋白IAA9异构体X1
Auxin-responsive protein IAA9 isoform X1 [Vitis vinifera]		 SU等[22]
VIT_11s0016g05660 11: 5121267-5122148 转录因子MYB82
Transcription factor MYB82 [Vitis vinifera]		 MORI等[23]
VIT_16s0022g02310 16: 14861534-14863137 赤霉素-20-氧化酶
gibberellin 20-oxidase [Vitis vinifera]		 WANG等[24]
VIT_16s0022g02330 16: 14940190-14955349 MADS-box转录因子6异构体X1
MADS-box transcription factor 6 isoform X1 [Vitis vinifera]		 IRELAND等[25]
VIT_16s0100g00400 16: 15837953-15838931 乙烯响应转录因子ERF027
Ethylene-responsive transcription factor ERF027 [Vitis vinifera]		 YUSTE-LISBONA等[20]
VIT_18s0041g01880 18: 26888672-26896521 MADS-box蛋白5异构体X2 VviAGL11
MADS-box protein 5 isoform X2 VviAGL11 [Vitis vinifera]		 ROYO等[26]

Fig. 4

Genetic effect analysis of significant SNPs associated with candidate genes SNPs 1_22639484, 5_7537999, 11_39611705, 11_5164917, 16_14893081 and 16_15790424 were associated with candidate genes VIT_01s0150g00260, VIT_05s0049g00460-VIT_05s0049g00510, VIT_11s0016g05640-VIT_11s0016g05660, VIT_16s0022g02310-VIT_16s0022g02330, respectively; SNP 18_26889437 located within candidate gene VIT_18s0041g01880; ** and * indicate 0.01 and 0.05 significant level, respectively"

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