中国棉花审定品种SSR指纹库的构建与综合评价

doi:10.3864/j.issn.0578-1752.2024.08.002

Abstract

Abstract:

【Objective】Cotton, a heterotetraploid crop with a complex genome structure, faces challenges in achieving high homozygosity due to frequent cross-pollination. The absence of effective technical supervision in the cotton seed market and the persistence of disordered varieties have a negative impact on the consistency of fiber quality. The objectives of this study are threefold: to establish a DNA fingerprint database for approved cotton varieties in China over the past 20 years, to explore a high-throughput SSR identification model for cotton varieties, and to provide a basis for the authentication of existing varieties and the specific identification of new cotton varieties. Additionally, we aim to analyze the genetic diversity and population differentiation among approved varieties. Ultimately, our goal is to provide a theoretical framework for identifying cotton varieties that are well-suited to different ecological regions and for developing varieties that can adapt to new environments. 【Method】Based on multiplex PCR technology and capillary electrophoresis detection method, using 60 SSR markers screened to construct a DNA fingerprint library of 1 015 standard samples of cotton approved varieties. Through the plant variety DNA fingerprint library management system, the SSR fingerprints of approved varieties were compared pairwise to analyze the genetic differences of approved varieties and screen the core SSR loci for variety identification. Cluster analysis and population structure analysis were used to analyze the genetic diversity of 1 015 cotton approved varieties and calculate the genetic differentiation index between populations. 【Result】60 SSR markers amplified 216 allelic variations in 1 015 approved varieties, with an average of 3.6 allelic variations and a mean PIC value of 0.37. When the SSR fingerprints of the 1 015 approved varieties were compared, a total of 513 591 pairwise results were generated, with a maximum of 58 different loci between samples. The percentage of different loci was mainly concentrated at 41%-70%, involving 428 115 groups, accounting for 83.36%. Among them, when the percentage of different loci was at 51%-60%, the largest number of groups was involved, accounting for 197 829 groups, accounting for 38.52%. When the percentage of different loci between varieties was greater than 20%, it accounted for more than 99% of all pairwise comparison groups, and the pairwise comparison results with a percentage of different loci lower than 20% only accounted for 0.58%. Based on the combination identification method, a set of cores SSR loci containing 10 SSR loci was selected, and the discrimination ability among the 1 015 varieties reached 99%. Clustering results and population structure analysis showed that the 1 015 varieties were clearly divided into five subpopulations. G1 (n=240) was an early-maturing cotton subpopulation, mainly distributed in northern and inland regions of China. This subpopulation had the most abundant genetic diversity among varieties, with an average genetic distance of 0.419 between varieties. G2 (n=277) was a medium-maturing cotton subpopulation, distributed in the Yangtze River Basin. This subpopulation had more hybrids, with an average genetic distance of 0.309 within the subpopulation. G3 (n=109) belonged to early-maturing and medium-maturing cotton subpopulations, distributed in Hebei'sHeilonggang region. This subpopulation had relatively simple genetic components, with the smallest average genetic distance among upland cotton subpopulations at only 0.150. G4 (n=254) belonged to a medium-early maturing cotton subpopulation, mainly distributed in the Yellow River Basin. The average genetic distance within this subpopulation was 0.307. G5 (n=37) consisted of 37 sea island cotton samples, with the smallest average genetic distance within the population at only 0.149. The genetic differentiation level between sea island cotton and upland cotton was the highest, with an average F_ST value of 0.503. Among upland cotton populations, the genetic differentiation level between G3 and other subpopulations was the highest, with F_ST values ranging from 0.193 to 0.242. The genetic differentiation level between the Yangtze River Basin and the Yellow River Basin was the lowest, with an F_ST value of 0.112. 【Conclusion】A DNA fingerprint library of standard samples of 1 015 approved varieties in China over the past 20 years was constructed. A set of cores SSR loci containing 10 SSR loci was selected to clearly identify more than 99% of the varieties. A high-throughput cotton identification model of "core loci + extended loci" was created. The 1 015 varieties were divided into five subpopulations, and upland cotton had obvious geographical distribution characteristics.

Key words: cotton, standard samples, SSR markers, DNA fingerprint database, comprehensive evaluation

WU YuZhen, HUANG LongYu, ZHOU DaYun, HUANG YiWen, FU ShouYang, PENG Jun, KUANG Meng. Construction of SSR Fingerprint Library and Comprehensive Evaluation for Approved Cotton Varieties in China[J].Scientia Agricultura Sinica, 2024, 57(8): 1430-1443.

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Figures/Tables 7

Table 1

Table 2

Results of amplification with 60 SSR primers"

引物编号 Marker No.	等位基因数目 Allele No.	基因型数目 Genotype No.	遗传多样性 Gene diversity	杂合率 Heterozygosity	PIC	主要等位变异及频率 Major allele, frquency
PC01	5	11	0.59	0.33	0.53	313, 0.56
PC02	4	8	0.27	0.10	0.25	290, 0.85
PC03	5	12	0.62	0.51	0.55	182, 0.46
PC04	3	4	0.49	0.50	0.37	367, 0.59
PC05	3	5	0.52	0.48	0.41	268, 0.57
PC06	4	9	0.56	0.57	0.48	341, 0.53
PC07	9	17	0.55	0.45	0.47	264, 0.57
PC08	6	12	0.39	0.32	0.36	153, 0.76
PC09	3	5	0.29	0.36	0.26	216, 0.84
PC10	3	5	0.25	0.16	0.23	369, 0.86
PC11	4	9	0.48	0.46	0.40	392, 0.65
PC12	6	16	0.65	0.49	0.60	307, 0.50
PC13	5	13	0.64	0.52	0.58	217, 0.50
PC14	4	8	0.42	0.33	0.35	343, 0.71
PC15	5	15	0.65	0.56	0.60	239, 0.52
PC16	5	11	0.42	0.27	0.39	190, 0.74
PC17	7	15	0.61	0.51	0.54	196, 0.50
PC18	5	11	0.54	0.44	0.47	238, 0.61
PC19	3	6	0.46	0.37	0.38	235 0.67
PC20	3	5	0.54	0.38	0.43	306, 0.51
PC21	4	7	0.62	0.60	0.54	189, 0.44
PC22	3	5	0.40	0.36	0.32	218, 0.72
PC23	2	3	0.50	0.57	0.37	184, 0.54
PC24	3	6	0.52	0.52	0.43	199, 0.57
PC25	2	3	0.45	0.46	0.35	240, 0.66
PC26	3	4	0.42	0.28	0.33	172, 0.70
PC27	3	6	0.53	0.40	0.43	340, 0.52
PC28	4	6	0.47	0.42	0.38	258, 0.65
PC29	10	27	0.68	0.50	0.63	177, 0.45
PC30	3	6	0.46	0.41	0.39	224, 0.67
PC31	2	3	0.50	0.53	0.37	220, 0.52
PC32	2	3	0.49	0.49	0.37	218, 0.55
PC33	2	3	0.23	0.17	0.20	335, 0.87
PC34	2	3	0.28	0.17	0.24	307, 0.84
PC35	3	4	0.26	0.11	0.24	342, 0.85
PC36	6	11	0.39	0.40	0.36	271, 0.76
PC37	2	3	0.27	0.22	0.24	305, 0.84
PC38	3	5	0.49	0.40	0.40	297, 0.63
PC39	2	3	0.10	0.06	0.09	255, 0.95
PC40	2	3	0.23	0.23	0.20	226, 0.87
PC41	2	3	0.39	0.31	0.32	301, 0.73
PC42	2	3	0.50	0.50	0.37	172, 0.51
PC43	6	9	0.30	0.22	0.27	323, 0.83
PC44	2	3	0.31	0.22	0.26	384, 0.81
PC45	2	3	0.47	0.47	0.36	232, 0.62
PC46	2	3	0.30	0.26	0.25	192, 0.82
PC47	2	3	0.41	0.22	0.33	219, 0.71
PC48	3	6	0.39	0.36	0.32	324, 0.73
PC49	2	3	0.41	0.32	0.33	214, 0.71
PC50	4	8	0.37	0.15	0.33	331, 0.77
PC51	2	3	0.49	0.42	0.37	319, 0.57
PC52	3	6	0.45	0.37	0.37	255, 0.69
PC53	2	3	0.43	0.38	0.34	173, 0.68
PC54	7	12	0.22	0.03	0.21	240, 0.88
PC55	4	8	0.36	0.23	0.32	267, 0.77
PC56	2	3	0.40	0.40	0.32	266, 0.72
PC57	2	3	0.47	0.49	0.36	304, 0.62
PC58	4	9	0.42	0.33	0.39	223, 0.74
PC59	5	11	0.29	0.14	0.28	308, 0.84
PC60	3	6	0.34	0.14	0.30	230, 0.79
平均Mean	3.6	7	0.43	0.36	0.37	-

Table 2

Table 3

Fig. 1

Fig. 2

Table 4

Fig. 3

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组合 Group	PET荧光标记（红） PET (Red)	FAM荧光标记（蓝） FAM (Blue)	VIC荧光标记（绿） VIC (Green)	NED荧光标记（黑） NED (Black)
1	PC05、PC06、PC24	PC30、PC12	PC04、PC15、PC03	PC25、PC16
2	PC10、PC22、PC29	PC11、PC18、PC23	PC14、PC21	PC07、PC09
3	PC17、PC20、PC28	PC02、PC26、PC27	PC08、PC19	PC01、PC13
4	PC36、PC49、PC59	PC39、PC41、PC42	PC43、PC45	PC31、PC35
5	PC51、PC52、PC53	PC32、PC50、PC55	PC38、PC47	PC57、PC60
6	PC48、PC54	PC34、PC44、PC58	PC37、PC46	PC33、PC40、PC56

差异位点百分比 Percentage of different loci (%)	差异位点数 <BOLD>D</BOLD>ifferent loci No.	涉及组数 Group No.	所占比例 <BOLD>P</BOLD>roportion (%)	累计百分比 <BOLD>C</BOLD>umulative percentage (%)
91-100	55-60	772	0.15	0.15
81-90	49-54	16879	3.29	3.44
71-80	43-48	31906	6.21	9.65
61-70	37-42	117749	22.93	32.58
51-60	31-36	197829	38.52	71.10
41-50	25-30	112537	21.91	93.01
31-40	19-24	28200	5.49	98.50
21-30	13-18	4734	0.92	99.42
11-20	7-12	2367	0.46	99.88
6-10	4-6	412	0.08	99.96
0-5	0-3	206	0.04	100.00

Construction of SSR Fingerprint Library and Comprehensive Evaluation for Approved Cotton Varieties in China

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亚群名称 Subgroup name	分布地区 Area of distribution	材料数目 No. of materials	杂交种数目 No. of hybrids	群体内平均遗传距离 Average genetic distance within a subgroup
G1	中国北部和西北内陆North China and Northwest China	240	19	0.419
G2	长江流域Yangtze River region	277	191	0.309
G3	河北省黑龙港地区Heilonggang region, Hebei	109	35	0.150
G4	黄河流域Yellow River region	254	110	0.307
G5	新疆（海岛棉）Xinjiang (Island cotton)	37	0	0.149
H	/	98	43	/

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