Genome-wide Association Study of Stems Sucrose Accumulation and Translocation in Wheat

doi:10.7668/hbnxb.20193849

Abstract

Abstract:

Sucrose is the main form of water-soluble carbohydrates transported in wheat stems,and plays a key role in the regulation of wheat growth and grain filling,which is a typical quantitative trait with a complex genetic basis.The SNP loci and candidate genes significantly associated with sucrose accumulation and translocation in wheat stems were explored at the genome-wide level to provide a theoretical basis for gene cloning and molecular marker-assisted selection.Seven traits of 117 domestic wheat varieties were measured, such as the sucrose content of flowering, filling, and maturity, the translocation rate and contribution rate to grain filling of sucrose at the pre-anthesis and post-anthesis, under different environmental conditions. Based on 35K SNP microarray genotyping, a mixed linear model MLM (Q + K) was used for genome-wide association study (GWAS) and candidate gene prediction.The overall phenotypic variation ranged from 9.53% to 45.70% with rich phenotypic diversity;the heritability of seven traits ranged from 0.32 to 0.49;the genotyping results showed that the polymorphism information content (PIC) of SNP markers ranged from 0.10 to 0.38;the population structure analysis divided the tested materials into four subgroups.The MLM(Q+K)model detected 146 significantly associated loci for traits related to sucrose accumulation and transport,among them,three SNP loci were detected repeatedly in two environments,and 13 candidate genes related to sucrose accumulation and transport related traits were screened based on the 200 kb physical location interval upstream and downstream of the 3 SNP loci that were stably and significantly associated.Among them, TraesCS1B02G324100 (Nucleotide-diphospho-suger transferase gene),TraesCS1B02G324200(Cellulose synthase-like protein gene),and TraesCS1B02G324300 (β-1,3-glucanase gene) were associated with sugar metabolism.

Key words: Wheat, Sucrose, SNP, GWAS, Candidate gene

DOU Jiaxin, TIAN Tian, WANG Peng, LIU Yuan, CHEN Tao, ZHANG Peipei, YANG Delong. Genome-wide Association Study of Stems Sucrose Accumulation and Translocation in Wheat[J]. Acta Agriculturae Boreali-Sinica, 2023, 38(5): 39-50. doi: 10.7668/hbnxb.20193849.

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URL: http://www.hbnxb.net/EN/10.7668/hbnxb.20193849

http://www.hbnxb.net/EN/Y2023/V38/I5/39

Figures/Tables 10

Tab.1 Wheat varieties used in this study

来源 Origin	品种(系) Variety(line)
甘肃 Gansu	白齐麦、兰天13、兰天15、兰天8号、兰天9号、兰选1号、陇鉴103、陇鉴104、陇鉴108、陇鉴110、陇鉴111、陇鉴127、陇鉴169、陇鉴196、陇鉴294、陇鉴301、陇鉴385、陇鉴386、陇鉴387、陇鉴3号、陇麦079、陇麦838、陇麦844、陇麦847、陇育218、陇育4号、陇育5号、陇原031、陇原937、陇原961、陇原964、陇塬036、陇中1号、陇中2号、陇紫麦1号、宁麦5号、普冰151、青山782、青山821、清农3、清农4、清山843、清山851、洮157、西峰16、西峰20、西峰27、西峰28、西平1号
山西 Shanxi	晋2148-7、晋麦47、晋麦63、晋麦68、晋麦72、晋麦79、晋农207、晋太170、临丰3号、临丰615、临旱234、临旱51241、临旱538、临旱6号、运旱2028、运旱20410、运旱2129、运旱21-30、运旱22-33、运旱23-35、运旱618、运旱719、长4640、长4738、长6154、长6359、长6452、长6878、长8744
北京 Beijing	北京8686、旱选10号、京411、京东17号、京东22号、京冬8号、京双2号、轮选987、中麦175、中麦553、中优9507
河北 Hebei	沧麦6001、邯4589、衡7228、衡95观26、衡优18、冀麦32、石4185、石家庄8号、石麦12号、石麦13、四棱红葫芦头
山东 Shandong	昌乐5号、济麦21、鲁德1号、鲁麦14、鲁麦15、鲁麦1号、山农24
陕西 Shaanxi	西农688、西农797、西农979、咸农4号、长旱4738、长武521
天津 Tianjin	科遗29、轮抗7号
河南 Henan	豫麦18
新疆 Xinjiang	新冬18

Tab.2 Statistical analysis among stems sucrose accumulation and translocation related traits in the natural population of wheat

性状 Trait	环境 Environment	平均值 Mean	最小值 Minimum	最大值 Maximum	标准差 s	变异系数/% CV	偏度 Ske.	峰度 Kur.	遗传力 $h 2 B$
SCf/(mg/g)	E1	27.37	21.18	33.76	2.87	10.47	0.06	-0.55	0.32
	E2	27.79	19.01	35.65	3.26	11.71	-0.17	-0.07
	E3	26.12	14.00	40.68	6.38	24.43	0.15	-0.77
	E4	28.92	10.53	48.32	8.11	28.06	0.12	-0.41
	BLUE	27.55	19.96	34.53	3.02	10.97	0.15	-0.52
SCg/(mg/g)	E1	29.58	24.13	36.03	2.84	9.65	0.15	-0.71	0.49
	E2	38.28	24.84	49.66	5.93	15.55	-0.27	-0.73
	E3	31.54	19.89	43.69	6.21	19.77	0.06	-0.91
	E4	37.29	16.56	59.40	8.50	22.90	0.27	-0.28
	BLUE	34.17	25.86	41.20	3.24	9.53	-0.10	-0.05
SCm/(mg/g)	E1	20.49	14.16	27.50	3.36	16.46	0.07	-0.92	0.40
	E2	20.46	6.37	33.56	6.24	30.64	-0.22	-0.58
	E3	20.31	8.82	30.69	4.97	24.58	0.12	-0.73
	E4	20.95	10.07	34.92	5.72	27.44	0.11	-0.61
	BLUE	20.55	12.70	26.15	2.81	13.73	-0.33	-0.42
RRSpr/%	E1	34.44	16.88	53.63	8.59	25.06	0.20	-0.76	0.33
	E2	29.04	10.97	56.65	10.06	34.80	0.38	-0.32
	E3	32.92	10.64	61.75	12.44	37.95	0.24	-0.78
	E4	29.88	9.80	61.14	12.33	41.45	0.45	-0.49
	BLUE	31.57	18.62	47.08	5.69	18.11	0.13	-0.24
RRSps/%	E1	21.76	10.54	33.82	5.63	25.98	-0.04	-0.99	0.41
	E2	23.41	11.55	35.94	6.04	25.89	0.01	-0.77
	E3	25.24	10.35	48.05	8.96	35.64	0.37	-0.60
	E4	26.99	9.39	49.82	10.12	37.64	0.26	-0.87
	BLUE	24.35	16.23	36.72	3.98	16.41	0.61	0.39
CRSpr/%	E1	30.39	10.35	57.93	11.34	37.49	0.23	-0.73	0.35
	E2	34.93	10.82	63.17	12.43	35.72	0.11	-0.80
	E3	34.68	10.34	60.71	13.71	39.72	0.19	-0.52
	E4	30.68	10.07	65.73	13.96	45.70	0.52	-0.67
	BLUE	32.67	15.09	46.36	6.33	19.46	-0.08	-0.06
CRSps/%	E1	26.94	10.43	49.58	9.97	37.16	0.30	-0.97	0.42
	E2	26.43	10.81	50.08	9.18	34.87	0.33	-0.46
	E3	28.80	10.07	54.18	10.80	37.65	0.23	-0.79
	E4	26.27	10.06	55.34	10.33	39.48	0.60	-0.08
	BLUE	27.11	15.03	43.23	5.58	20.66	0.31	-0.09

Tab.2 Statistical analysis among stems sucrose accumulation and translocation related traits in the natural population of wheat

性状 Trait	环境 Environment	平均值 Mean	最小值 Minimum	最大值 Maximum	标准差 s	变异系数/% CV	偏度 Ske.	峰度 Kur.	遗传力 $h 2 B$
SCf/(mg/g)	E1	27.37	21.18	33.76	2.87	10.47	0.06	-0.55	0.32
	E2	27.79	19.01	35.65	3.26	11.71	-0.17	-0.07
	E3	26.12	14.00	40.68	6.38	24.43	0.15	-0.77
	E4	28.92	10.53	48.32	8.11	28.06	0.12	-0.41
	BLUE	27.55	19.96	34.53	3.02	10.97	0.15	-0.52
SCg/(mg/g)	E1	29.58	24.13	36.03	2.84	9.65	0.15	-0.71	0.49
	E2	38.28	24.84	49.66	5.93	15.55	-0.27	-0.73
	E3	31.54	19.89	43.69	6.21	19.77	0.06	-0.91
	E4	37.29	16.56	59.40	8.50	22.90	0.27	-0.28
	BLUE	34.17	25.86	41.20	3.24	9.53	-0.10	-0.05
SCm/(mg/g)	E1	20.49	14.16	27.50	3.36	16.46	0.07	-0.92	0.40
	E2	20.46	6.37	33.56	6.24	30.64	-0.22	-0.58
	E3	20.31	8.82	30.69	4.97	24.58	0.12	-0.73
	E4	20.95	10.07	34.92	5.72	27.44	0.11	-0.61
	BLUE	20.55	12.70	26.15	2.81	13.73	-0.33	-0.42
RRSpr/%	E1	34.44	16.88	53.63	8.59	25.06	0.20	-0.76	0.33
	E2	29.04	10.97	56.65	10.06	34.80	0.38	-0.32
	E3	32.92	10.64	61.75	12.44	37.95	0.24	-0.78
	E4	29.88	9.80	61.14	12.33	41.45	0.45	-0.49
	BLUE	31.57	18.62	47.08	5.69	18.11	0.13	-0.24
RRSps/%	E1	21.76	10.54	33.82	5.63	25.98	-0.04	-0.99	0.41
	E2	23.41	11.55	35.94	6.04	25.89	0.01	-0.77
	E3	25.24	10.35	48.05	8.96	35.64	0.37	-0.60
	E4	26.99	9.39	49.82	10.12	37.64	0.26	-0.87
	BLUE	24.35	16.23	36.72	3.98	16.41	0.61	0.39
CRSpr/%	E1	30.39	10.35	57.93	11.34	37.49	0.23	-0.73	0.35
	E2	34.93	10.82	63.17	12.43	35.72	0.11	-0.80
	E3	34.68	10.34	60.71	13.71	39.72	0.19	-0.52
	E4	30.68	10.07	65.73	13.96	45.70	0.52	-0.67
	BLUE	32.67	15.09	46.36	6.33	19.46	-0.08	-0.06
CRSps/%	E1	26.94	10.43	49.58	9.97	37.16	0.30	-0.97	0.42
	E2	26.43	10.81	50.08	9.18	34.87	0.33	-0.46
	E3	28.80	10.07	54.18	10.80	37.65	0.23	-0.79
	E4	26.27	10.06	55.34	10.33	39.48	0.60	-0.08
	BLUE	27.11	15.03	43.23	5.58	20.66	0.31	-0.09

Fig.1 Pearson correlation analysis among stems sucrose accumulation and translocation related traits in the natural population of wheat ^*,^**and^***indicate significance at P<0.05,P<0.01 and P<0.001 levels,respectively.

Tab.3 Basic statistics of the SNP markers used in GWAS

染色体 Chr	标记数目 Number of markers	物理长度/Mb Physical distance	标记密度/ (Mb/标记) Density of marker	最小等位基因频率 Minimum allele frequency(MAF)		遗传多样性 Genetic diversity		多态性信息含量 Polymorphic information content(PIC)
染色体 Chr	标记数目 Number of markers	物理长度/Mb Physical distance	标记密度/ (Mb/标记) Density of marker	均值 Average	范围 Range	均值 Average	范围 Range	均值 Average	范围 Range
1A	809	592.86	0.73	0.25	0.05~0.50	0.34	0.10~0.50	0.28	0.10~0.38
1B	919	688.60	0.75	0.27	0.05~0.50	0.36	0.10~0.50	0.29	0.10~0.38
1D	613	495.13	0.81	0.25	0.05~0.50	0.34	0.10~0.50	0.27	0.10~0.38
2A	846	780.32	0.92	0.24	0.05~0.50	0.33	0.10~0.50	0.26	0.10~0.38
2B	975	799.42	0.82	0.26	0.05~0.50	0.34	0.10~0.50	0.28	0.10~0.38
2D	705	651.40	0.92	0.25	0.05~0.50	0.34	0.10~0.50	0.27	0.10~0.38
3A	621	749.26	1.21	0.25	0.05~0.50	0.34	0.10~0.50	0.28	0.10~0.38
3B	878	829.07	0.94	0.26	0.05~0.50	0.35	0.10~0.50	0.28	0.10~0.38
3D	390	613.59	1.57	0.26	0.05~0.50	0.35	0.10~0.50	0.28	0.10~0.38
4A	460	742.10	1.61	0.25	0.05~0.50	0.34	0.10~0.50	0.27	0.10~0.38
4B	444	672.67	1.52	0.23	0.05~0.50	0.32	0.10~0.50	0.26	0.10~0.38
4D	178	508.05	2.85	0.23	0.05~0.50	0.31	0.10~0.50	0.25	0.10~0.37
5A	680	798.54	1.17	0.26	0.05~0.50	0.35	0.10~0.50	0.28	0.10~0.38
5B	908	712.88	0.79	0.27	0.05~0.50	0.36	0.10~0.50	0.29	0.10~0.38
5D	466	565.85	1.21	0.26	0.05~0.50	0.35	0.10~0.50	0.28	0.10~0.38
6A	629	617.28	0.98	0.27	0.05~0.50	0.35	0.10~0.50	0.28	0.10~0.38
6B	719	720.60	1.00	0.27	0.05~0.50	0.35	0.10~0.50	0.28	0.10~0.38
6D	381	473.37	1.24	0.26	0.05~0.50	0.35	0.10~0.50	0.28	0.10~0.38
7A	681	736.45	1.08	0.24	0.05~0.50	0.33	0.10~0.50	0.27	0.10~0.38
7B	546	750.49	1.37	0.23	0.05~0.50	0.32	0.10~0.50	0.26	0.10~0.37
7D	384	634.71	1.65	0.23	0.05~0.50	0.31	0.10~0.50	0.25	0.10~0.38
A基因组 A genome	4 726	5 016.81	1.06	0.25	0.05~0.50	0.34	0.10~0.50	0.28	0.10~0.38
B基因组 B genome	5 389	5 173.73	0.96	0.26	0.05~0.50	0.34	0.10~0.50	0.28	0.10~0.38
D基因组 D genome	3 117	3 942.10	1.26	0.25	0.05~0.50	0.34	0.10~0.50	0.27	0.10~0.38
总计 Total	13 232	14 132.64	1.07	0.25	0.05~0.50	0.34	0.10~0.50	0.28	0.10~0.38

Tab.3 Basic statistics of the SNP markers used in GWAS

染色体 Chr	标记数目 Number of markers	物理长度/Mb Physical distance	标记密度/ (Mb/标记) Density of marker	最小等位基因频率 Minimum allele frequency(MAF)		遗传多样性 Genetic diversity		多态性信息含量 Polymorphic information content(PIC)
染色体 Chr	标记数目 Number of markers	物理长度/Mb Physical distance	标记密度/ (Mb/标记) Density of marker	均值 Average	范围 Range	均值 Average	范围 Range	均值 Average	范围 Range
1A	809	592.86	0.73	0.25	0.05~0.50	0.34	0.10~0.50	0.28	0.10~0.38
1B	919	688.60	0.75	0.27	0.05~0.50	0.36	0.10~0.50	0.29	0.10~0.38
1D	613	495.13	0.81	0.25	0.05~0.50	0.34	0.10~0.50	0.27	0.10~0.38
2A	846	780.32	0.92	0.24	0.05~0.50	0.33	0.10~0.50	0.26	0.10~0.38
2B	975	799.42	0.82	0.26	0.05~0.50	0.34	0.10~0.50	0.28	0.10~0.38
2D	705	651.40	0.92	0.25	0.05~0.50	0.34	0.10~0.50	0.27	0.10~0.38
3A	621	749.26	1.21	0.25	0.05~0.50	0.34	0.10~0.50	0.28	0.10~0.38
3B	878	829.07	0.94	0.26	0.05~0.50	0.35	0.10~0.50	0.28	0.10~0.38
3D	390	613.59	1.57	0.26	0.05~0.50	0.35	0.10~0.50	0.28	0.10~0.38
4A	460	742.10	1.61	0.25	0.05~0.50	0.34	0.10~0.50	0.27	0.10~0.38
4B	444	672.67	1.52	0.23	0.05~0.50	0.32	0.10~0.50	0.26	0.10~0.38
4D	178	508.05	2.85	0.23	0.05~0.50	0.31	0.10~0.50	0.25	0.10~0.37
5A	680	798.54	1.17	0.26	0.05~0.50	0.35	0.10~0.50	0.28	0.10~0.38
5B	908	712.88	0.79	0.27	0.05~0.50	0.36	0.10~0.50	0.29	0.10~0.38
5D	466	565.85	1.21	0.26	0.05~0.50	0.35	0.10~0.50	0.28	0.10~0.38
6A	629	617.28	0.98	0.27	0.05~0.50	0.35	0.10~0.50	0.28	0.10~0.38
6B	719	720.60	1.00	0.27	0.05~0.50	0.35	0.10~0.50	0.28	0.10~0.38
6D	381	473.37	1.24	0.26	0.05~0.50	0.35	0.10~0.50	0.28	0.10~0.38
7A	681	736.45	1.08	0.24	0.05~0.50	0.33	0.10~0.50	0.27	0.10~0.38
7B	546	750.49	1.37	0.23	0.05~0.50	0.32	0.10~0.50	0.26	0.10~0.37
7D	384	634.71	1.65	0.23	0.05~0.50	0.31	0.10~0.50	0.25	0.10~0.38
A基因组 A genome	4 726	5 016.81	1.06	0.25	0.05~0.50	0.34	0.10~0.50	0.28	0.10~0.38
B基因组 B genome	5 389	5 173.73	0.96	0.26	0.05~0.50	0.34	0.10~0.50	0.28	0.10~0.38
D基因组 D genome	3 117	3 942.10	1.26	0.25	0.05~0.50	0.34	0.10~0.50	0.27	0.10~0.38
总计 Total	13 232	14 132.64	1.07	0.25	0.05~0.50	0.34	0.10~0.50	0.28	0.10~0.38

Fig.2 Marker-distribution on the genome for the 13 228 SNPs used in the present study

Fig.4 Kinships among the 117 natural population wheat accessions used in this study

Fig.3 Population structure of the 117 natural population wheat accessions used in this study A.Trend of estimated K in population structure analysis;B.Population structure analysis diagram in admixture software.

Fig.5 Manhattan plot for stems sucrose accumulation and translocation related traits analyzed by mixed linear model in TASSEL

Tab.4 Summary of significant associated SNP markers

标记 Marker	性状 Trait	染色体 Chromosome	物理位置 Position	环境 Enviroment	P value	Marker R²/%
AX-94453107	RRSps	1D	407 916 367	BLUE	3.79E-04	16.27
				E4	4.40E-04	16.15
AX-94526541	CRSps	1B	549 710 285	E3	4.54E-04	17.11
				BLUE	4.74E-04	16.61
AX-94853813	SCf	5D	361 664 925	BLUE	1.57E-04	18.27
				E3	7.33E-04	14.75

Tab.5 Information of candidate genes for stems sucrose accumulation and translocation in the natural population of wheat

基因 Gene	染色体 Chromosome	物理位置 Position
TraesCS1B02G324100	1B	549765444~549766742	Nucleotide-diphospho-sugar transferase family protein
TraesCS1B02G324200	1B	549782044~549784997	Cellulose synthase-like protein
TraesCS1B02G324300	1B	549790711~549794806	Putative beta-1,3-glucanase
TraesCS1B02G324400	1B	549888828~549889436	GRF zinc finger family protein, expressed
TraesCS1B02G559400LC	1B	549517888~549521248	Glycerol-3-phosphate dehydrogenase [NAD(+)]
TraesCS1D02G311900	1D	407823302~407824296	RING/U-box superfamily protein
TraesCS1D02G312000	1D	407862708~407863290	VQ motif-containing protein
TraesCS5D02G255200	5D	361649578~361651275	Ring finger protein, putative
TraesCS5D02G255300	5D	361659153~361661404	F-box family protein
TraesCS5D02G331300LC	5D	361584500~361585507	Serine protease/ABC transporter B family protein tagC
TraesCS5D02G331500LC	5D	361613707~361614859	XH/XS domain-containing family protein
TraesCS5D02G331700LC	5D	361639333~361641088	Protein FAR1-RELATED SEQUENCE 5
TraesCS5D02G331800LC	5D	361641153~361642408	FAR1

References 45

[1]	钱薇, 刘媛, 栗孟飞, 杨德龙, 陈菁菁, 程宏波, 常磊, 柴守玺. 不同水分条件下小麦ILs群体花后不同器官蔗糖积累与转运的遗传特性[J]. 麦类作物学报, 2017, 37(10):1309-1317.doi:10.7606/j.issn.1009-1041.2017.10.06.
	Qian W, Liu Y, Li M F, Yang D L, Chen J J, Cheng H B, Chang L, Chai S X. Genetic analysis of accumulation and translocation of sucrose in different organs after flowering in wheat ILs population under different water conditions[J]. Journal of Triticeae Crops, 2017, 37(10):1309-1317.
[2]	Housley T L. Role of fructans redistributed from vegetative tissues in grain filling of wheat and barley[J]. Developments in Crop Science, 2000, 26:207-221.doi:10.1016/S0378-519X(00)80011-2.
[3]	Xue G P, McIntyre C L, Jenkins C L D, Glassop D, van Herwaarden A F, Shorter R. Molecular dissection of variation in carbohydrate metabolism related to water-soluble carbohydrate accumulation in stems of wheat[J]. Plant Physiology, 2008, 146(2):441-454.doi:10.1104/pp.107.113076.
[4]	Veenstra L D, Jannink J L, Sorrells M E. Wheat Fructans:A potential breeding target for nutritionally improved,climate-resilient varieties[J]. Crop Science, 2017, 57(3):1624-1640.doi:10.2135/cropsci2016.11.0955. URL
[5]	王振林, 贺明荣, 傅金民, 田奇卓, 尹燕枰, 曹鸿鸣. 源库调节对灌溉与旱地小麦开花后光合产物生产和分配的影响[J]. 作物学报, 1999, 25(2):162-168.doi:10.3321/j.issn:0496-3490.1999.02.005.
	Wang Z L, He M R, Fu J M, Tian Q Z, Yin Y P, Cao H M. Effects of source-sink regulation on irrigation and the production and distribution of photosynthetic products after flowering of dryland wheat[J]. Acta Agronomica Sinica, 1999, 25(2):162-168.
[6]	Joudi M, Ahmadi A, Mohamadi V, Abbasi A, Vergauwen R, Mohammadi H, Van den Ende W. Comparison of fructan dynamics in two wheat cultivars with different capacities of accumulation and remobilization under drought stress[J]. Physiologia Plantarum, 2012, 144(1):1-12.doi:10.1111/j.1399-3054.2011.01517.x. URL
[7]	杨德龙, 李唯, 景蕊莲, 昌小平. 小麦DH群体茎秆可溶性碳水化合物含量相关数量性状的遗传分析[J]. 作物学报, 2007, 33(9):1543-1547.doi:10.3321/j.issn:0496-3490.2007.09.023.
	Yang D L, Li W, Jing R L, Chang X P. Genetic analysis of quantitative traits associated with soluble carbohydrate content of doubled haploid population in wheat(Triticum aestivum L.) stem[J]. Acta Agronomica Sinica, 2007, 33(9):1543-1547.
[8]	Yang D L, Jing R L, Chang X P, Li W. Identification of quantitative trait loci and environmental interactions for accumulation and remobilization of water-soluble carbohydrates in wheat (Triticum aestivum L.) stems[J]. Genetics, 2007, 176(1):571-584.doi:10.1534/genetics.106.068361. URL
[9]	Rebetzke G J, Van Herwaarden A F, Jenkins C, Weiss M, Lewis D, Ruuska S, Tabe L, Fettell N A, Richards R A. Quantitative trait loci for water-soluble carbohydrates and associations with agronomic traits in wheat[J]. Australian Journal of Agricultural Research, 2008, 59(10):891.doi:10.1071/AR08067. URL
[10]	Li M F, Liu Y, Ma J F, Zhang P P, Wang C X, Su J J, Yang D L. Genetic dissection of stem WSC accumulation and remobilization in wheat (Triticum aestivum L.) under terminal drought stress[J]. BMC Genetics, 2020, 21(1):50.doi:10.1186/s12863-020-00855-1.
[11]	谭贤杰, 吴子恺, 程伟东, 王天宇, 黎裕. 关联分析及其在植物遗传学研究中的应用[J]. 植物学报, 2011, 46(1):108-118.doi:10.3724/SP.J.1259.2011.00108.
	Tan X J, Wu Z K, Cheng W D, Wang T Y, Li Y. Association analysis and its application in plant genetic research[J]. Bulletin of Botany, 2011, 46(1):108-118.
[12]	Ingvarsson P K, Street N R. Association genetics of complex traits in plants[J]. New Phytologist, 2011, 189(4):909-922.doi:10.1111/j.1469-8137.2010.03593.x. pmid: 21182529
[13]	Zhu C S, Gore M, Buckler E S, Yu J M. Status and prospects of association mapping in plants[J]. The Plant Genome, 2008, 1(1):5-20.doi:10.3835/plantgenome2008.02.0089.
[14]	Dong Y, Liu J D, Zhang Y, Geng H W, Rasheed A, Xiao Y G, Cao S H, Fu L P, Yan J, Wen W E, Zhang Y, Jing R L, Xia X C, He Z H. Genome-wide association of stem water soluble carbohydrates in bread wheat[J]. PLoS One, 2016, 11(11):e0164293.doi:10.1371/journal.pone.0164293. URL
[15]	Fu L P, Wu J C, Yang S R, Jin Y R, Liu J D, Yang M J, Rasheed A, Zhang Y, Xia X C, Jing R L, He Z H, Xiao Y G. Genome-wide association analysis of stem water-soluble carbohydrate content in bread wheat[J]. Theoretical and Applied Genetics, 2020, 133(10):2897-2914.doi:10.1007/s00122-020-03640-x. pmid: 32594265
[16]	Wang S C, Wong D, Forrest K, Allen A, Chao S, Huang B E, Maccaferri M, Salvi S, Milner S G, Cattivelli L, Mastrangelo A M, Whan A, Stephen S, Barker G, Wieseke R, Plieske J, International Wheat Genome Sequencing Consortium, Lillemo M, Mather D, Appels R, Dolferus R, Brown-Guedira G, Korol A, Akhunova A R, Feuillet C, Salse J, Morgante M, Pozniak C, Luo M C, Dvorak J, Morell M, Dubcovsky J, Ganal M, Tuberosa R, Lawley C, Mikoulitch I, Cavanagh C, Edwards K J, Hayden M, Akhunov E. Characterization of polyploid wheat genomic diversity using a high-density 90 000 single nucleotide polymorphism array[J]. Frontiers in Plant Science, 2014, 12(6):787-796.doi:10.1111/pbi.12183.
[17]	Cui F, Zhang N, Fan X L, Zhang W, Zhao C H, Yang L J, Pan R Q, Chen M, Han J, Zhao X Q, Ji J, Tong Y P, Zhang H X, Jia J Z, Zhao G Y, Li J M. Utilization of a Wheat660K SNP array-derived high-density genetic map for high-resolution mapping of a major QTL for kernel number[J]. Scientific Reports, 2017, 7(1):3788.doi:10.1038/s41598-017-04028-6. pmid: 28630475
[18]	Yemm E W, Willis A J. The estimation of carbohydrates in plant extracts by anthrone[J]. Scientific Reports, 1954, 57(3):508-514.doi:10.1042/bj0570508.
[19]	Toker C. Estimates of broad-sense heritability for seed yield and yield criteria in faba bean (Vicia faba L.)[J]. Hereditas, 2004, 140(3):222-225.doi:10.1111/j.1601-5223.2004.01780.x. URL
[20]	Porebski S, Bailey L G, Baum B R. Modification of a CTAB DNA extraction protocol for plants containing high polysaccharide and polyphenol components[J]. Plant Molecular Biology Reporter, 1997, 15(1):8-15.doi:10.1007/BF02772108. URL
[21]	Wang P, Tian T, Ma J F, Liu Y, Zhang P, Chen T, Shahinnia F, Yang D L. Genome-wide association study of kernel traits using a 35K SNP array in bread wheat (Triticum aestivum L.)[J]. Frontiers in Plant Science, 2022, 13:905660.doi:10.3389/fpls.2022.905660. URL
[22]	Liu K J, Muse S V. PowerMarker:An integrated analysis environment for genetic marker analysis[J]. Bioinformatics, 2005, 21(9):2128-2129.doi:10.1093/bioinformatics/bti282. URL
[23]	Bradbury P J, Zhang Z W, Kroon D E, Casstevens T M, Ramdoss Y, Buckler E S. TASSEL:Software for association mapping of complex traits in diverse samples[J]. Bioinformatics, 2007, 23(19):2633-2635.doi:10.1093/bioinformatics/btm308. pmid: 17586829
[24]	Yu J M, Pressoir G, Briggs W H, Vroh Bi I V, Yamasaki M, Doebley J F, McMullen M D, Gaut B S, Nielsen D M, Holland J B, Kresovich S, Buckler E S. A unified mixed-model method for association mapping that accounts for multiple levels of relatedness[J]. Nature Genetics, 2006, 38(2):203-208.doi:10.1038/ng1702. pmid: 16380716
[25]	Zhang Z M, Ersoz E, Lai C Q, Todhunter R J, Tiwari H K, Gore M A, Bradbury P J, Yu J M, Arnett D K, Ordovas J M, Buckler E S. Mixed linear model approach adapted for genome-wide association studies[J]. Nature Genetics, 2010, 42(4):355-360.doi:10.1038/ng.546. pmid: 20208535
[26]	Ma S W, Wang M, Wu J H, Guo W L, Chen Y M, Li G W, Wang Y P, Shi W M, Xia G M, Fu D L, Kang Z S, Ni F. WheatOmics:A platform combining multiple omics data to accelerate functional genomics studies in wheat[J]. Molecular Plant, 2021, 14(12):1965-1968.doi:10.1016/j.molp.2021.10.006. URL
[27]	Zhang L C, Dong C H, Chen Z X, Gui L X, Chen C, Li D P, Xie Z C, Zhang Q, Zhang X Y, Xia C, Liu X, Kong X Y, Wang J R. WheatGmap:A comprehensive platform for wheat gene mapping and genomic studies[J]. Molecular Plant, 2021, 14(2):187-190.doi:10.1016/j.molp.2020.11.018. URL
[28]	Chen H G, Zeng X L, Yang J, Cai X, Shi Y M, Zheng R R, Wang Z Q, Liu J Y, Yi X X, Xiao S W, Fu Q, Zou J J, Wang C Y. Whole-genome resequencing of Osmanthus fragrans provides insights into flower color evolution[J]. Horticulture Research, 2021, 8(1):98.doi:10.1038/s41438-021-00531-0.
[29]	Jiang Q Y, Hou J, Hao C Y, Wang L F, Ge H M, Dong Y S, Zhang X Y. The wheat (T.aestivum) sucrose synthase 2 gene (TaSus2) active in endosperm development is associated with yield traits[J]. Functional & Integrative Genomics, 2011, 11(1):49-61.doi:10.1007/s10142-010-0188-x.
[30]	景凡丽, 张沛沛, 苗永平, 陈涛, 刘媛, 杨德龙. 小麦TaSPP基因的克隆及表达分析[J]. 华北农学报, 2022, 37(2):28-34.doi:10.7668/hbnxb.20192653.
	Jing F L, Zhang P P, Miao Y P, Chen T, Liu Y, Yang D L. Cloning and expression analysis of TaSPP gene in wheat[J]. Acta Agriculturae Boreali-Sinica, 2022, 37(2):28-34.
[31]	Jing F L, Miao Y P, Zhang P P, Chen T, Liu Y, Ma J F, Li M F, Yang D L. Characterization of TaSPP-5A gene associated with sucrose content in wheat (Triticum aestivum L.)[J]. BMC Plant Biology, 2022, 22(1):58.doi:10.1186/s12870-022-03442-x.
[32]	Keegstra K, Raikhel N. Plant glycosyltransferases[J]. Current Opinion in Plant Biology, 2001, 4(3):219-224.doi:10.1016/s1369-5266(00)00164-3. pmid: 11312132
[33]	Vrielink A, Rüger W, Driessen H P, Freemont P S. Crystal structure of the DNA modifying enzyme beta-glucosyltransferase in the presence and absence of the substrate uridine diphosphoglucose[J]. The EMBO Journal, 1994, 13(15):3413-3422.doi:10.1002/j.1460-2075.1994.tb06646.x.
[34]	Campbell J A, Davies G J, Bulone V, Henrissat B. A classification of nucleotide-diphospho-sugar glycosyltransferases based on amino acid sequence similarities[J]. The Biochemical Journal, 1997, 326 (Pt 3):929-939.doi:10.1042/bj3260929u. URL
[35]	Unligil U M, Rini J M. Glycosyltransferase structure and mechanism[J]. Current Opinion in Structural Biology, 2000, 10(5):510-517.doi:10.1016/s0959-440x(00)00124-x.
[36]	Ishikura N, Mato M. Partial purification and some properties of flavonol 3-O-glycosyltransferases from seedlings of Vigna mungo,with special reference to the formation of kaempferol 3-O-galactoside and 3-O-glucoside[J]. Plant and Cell Physiology, 1993, 34(2):329-335.doi:10.1093/oxfordjournals.pcp.a078424.
[37]	Bar-Peled M, Lewinsohn E, Fluhr R, Gressel J. UDP-rhamnose:Flavanone-7-O-glucoside-2″-O-rhamnosyltransferase.Purification and characterization of an enzyme catalyzing the production of bitter compounds in citrus[J]. The Journal of Biological Chemistry, 1991, 266(31):20953-20959.doi:10.1016/s0021-9258(18)54803-1.
[38]	Jones P, Messner B, Nakajima J I, Schäffner A R, Saito K. UGT73C6 and UGT78D1,glycosyltransferases involved in flavonol glycoside biosynthesis in Arabidopsis thaliana[J]. The Journal of Biological Chemistry, 2003, 278(45):43910-43918.doi:10.1074/jbc.m303523200. URL
[39]	Li H M, Chen H, Yang Z N, Gong J M. Cdi gene is required for pollen germination and tube growth in Arabidopsis[J]. FEBS Letters, 2012, 586(7):1027-1031.doi:10.1016/j.febslet.2012.02.046.
[40]	魏建华, 宋艳茹. 植物纤维素合酶基因研究进展[J]. 植物学通报, 2002, 19(6):641-649.doi:10.3969/j.issn.1674-3466.2002.06.001.
	Wei J H, Song Y R. Advances of studies on plant cellulose synthase[J]. Chinese Bulletin of Botany, 2002, 19(6):641-649.
[41]	李益, 胡尚连, 卢学琴, 蒋瑶, 黄胜雄, 李向前. 植物纤维素合成酶基因的进化分析[J]. 华北农学报, 2008, 23(2):101-105.doi:10.3321/j.issn:0253-9772.2007.01.021.
	Li Y, Hu S L, Lu X Q, Jiang Y, Huang S X, Li X Q. Evolution analysis of the plant cellulose synthase(CesA)gene family[J]. Acta Agriculturae Boreali-Sinica, 2008, 23(2):101-105. doi: 10.7668/hbnxb.2008.02.023
[42]	Hu H Z, Zhang R, Feng S Q, Wang Y M, Wang Y T, Fan C F, Li Y, Liu Z Y, Schneider R, Xia T, Ding S Y, Persson S, Peng L C. Three AtCesA6-like members enhance biomass production by distinctively promoting cell growth in Arabidopsis[J]. Plant Biotechnology Journal, 2018, 16(5):976-988.doi:10.1111/pbi.12842. URL
[43]	陈燕玲, 岑光莉, 孙婷婷, 尤垂淮, 阙友雄, 苏亚春. 植物几丁质酶和β-1,3-葡聚糖酶及其协同抗病性研究进展[J]. 农业生物技术学报, 2022, 30(7):1394-1411.doi:10.3969/j.issn.1674-7968.2022.07.016.
	Chen Y L, Cen G L, Sun T T, You C H, Que Y X, Su Y C. Progress on plant chitinase and β-1,3-glucanase and their synergistic function in disease resistance[J]. Journal of Agricultural Biotechnology, 2022, 30(7):1394-1411.
[44]	Wally O, Jayaraj J, Punja Z. Comparative resistance to foliar fungal pathogens in transgenic carrot plants expressing genes encoding for chitinase, β-1,3-glucanase and peroxidise[J]. European Journal of Plant Pathology, 2009, 123(3):331-342.doi:10.1007/s10658-008-9370-6. URL
[45]	Nookaraju A, Agrawal D C. Enhanced tolerance of transgenic grapevines expressing chitinase and β-1,3-glucanase genes to downy mildew[J]. The Plant Cell, Tissue and Organ Culture, 2012, 111(1):15-28.doi:10.1007/s11240-012-0166-1. URL

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