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作物学报

作物学报 ›› 2026, Vol. 52 ›› Issue (4): 993-1005.doi: 10.3724/SP.J.1006.2026.53084

所属专题： 玉米：遗传育种·种质资源·分子遗传学

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

适于玉米品种鉴定的一套三等位变异SNP新型标记组合

田红丽(), 杨扬(), 范亚明(), 易红梅, 郭丹丹, 王凤格*(), 赵久然*()   

  1. 北京市农林科学院玉米研究所 / 农业农村部农作物DNA指纹创新利用重点实验室(部省共建) / 玉米DNA指纹及分子育种北京市重点实验室, 北京100097
  • 收稿日期:2025-10-29 接受日期:2026-01-22 出版日期:2026-04-12 网络出版日期:2026-02-06
  • 通讯作者: *赵久然, E-mail: maizezhao@126.com; 王凤格, E-mail: gege0106@163.com
  • 作者简介:田红丽, E-mail: tianhongli9963@163.com;
    杨扬, E-mail: caurwx@163.com;
    范亚明, E-mail: 13718078547@163.com
    **同等贡献
  • 基金资助:
    国家科技重大专项(2022ZD04019);北京市农林科学院科技创新能力建设专项(KJCX20230303)

A novel set of tri-allelic variant SNP loci suitable for maize variety identification

Tian Hong-Li(), Yang Yang(), Fan Ya-Ming(), Yi Hong-Mei, Guo Dan-Dan, Wang Feng-Ge*(), Zhao Jiu-Ran*()   

  1. Maize Research Institute, Beijing Academy of Agriculture and Forestry Sciences / Key Laboratory of Crop DNA Fingerprinting Innovation and Utilization of the Ministry of Agriculture and Rural Affairs (Co-construction by Ministry and Province) / Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Beijing 100097, China
  • Received:2025-10-29 Accepted:2026-01-22 Published:2026-04-12 Published online:2026-02-06
  • Contact: *E-mail: maizezhao@126.com; E-mail: gege0106@163.com
  • About author:First author contact:**Contributed equally to this work
  • Supported by:
    National Scientific and Technological Innovation-Major Projects(2022ZD04019);Science and Technology Innovation Capacity Building Project of BAAFS(KJCX20230303)

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摘要：

高通量测序、生物信息学以及基因型分型技术的快速发展, 为农作物品种的精准鉴定开辟了新的方法路径。本文基于全基因组水平挖掘的78万个初始多等位变异SNP位点, 利用生物信息、统计分析、靶向测序验证以及最优遗传算法等方法评估确定了一套三等位变异SNP新型标记组合。该组合包含的40个位点均匀分布于玉米的10对染色体上, 每对染色体为4个位点。利用200个杂交种和270个自交系的基因型数据对40个SNP位点进行多角度评估, 结果显示: (1) 对于杂交种和自交系, 所有位点的PIC值均高于二等位变异SNP位点的最高值0.375, 平均值为0.470和0.480, DP平均值为0.68和0.57。(2) 利用40个三等位和96个二等位变异SNP标记的杂交种数据进行品种的两两成对比较, 显示差异位点百分比分别集中在50%~85%和50%~70%; 自交系数据分析显示, 品种间差异分别集中在35%~75%和35%~60%; 三等位与二等位变异SNP标记相比, 品种间差异位点百分比平均值提高了10%。(3) 对于杂交种和自交系, 40个SNP位点的第一等位变异频率平均值分别为0.58和0.57, 第二等位变异平均值均为0.31, 第三等位变异平均值分别为0.11和0.12。(4) 聚类结果显示, 40个位点将270个自交系精准划分为10个杂种优势类群, 与高密度芯片划分结果一致。综上所述, 本研究报道了一套高质量、高鉴别力的三等位变异核心SNP标记位点组合, 为玉米品种鉴定提供了一种新型标记类型; 凭借其更高的变异解析能力, 有望与现有标记类型形成互补, 推动农作物分子鉴定技术的发展。

关键词: 玉米, 品种鉴定, SNP位点, 三等位变异, 核心位点组合

Abstract:

The rapid development of high-throughput sequencing, bioinformatics, and genotyping technologies has opened new avenues for the precise identification of crop varieties. In this study, based on 780,000 initially mined multi-allelic variant SNPs from the maize whole genome, a novel set of 40 tri-allelic SNP markers was evaluated and identified using bioinformatics approaches, statistical analysis, targeted sequencing validation, and optimal genetic algorithms. These 40 SNPs are evenly distributed across the 10 maize chromosome pairs, with four markers per chromosome. A comprehensive evaluation and comparison of the 40 SNPs were conducted using genotype data from 200 hybrids and 270 inbred lines. The results showed that: (1) For both hybrids and inbred lines, the PIC values of all loci exceeded the maximum value of 0.375 typical for bi-allelic SNP loci, with average values of 0.470 and 0.480, and average discrimination power (DP) values of 0.68 and 0.57, respectively. (2) Pairwise comparisons using the 40 tri-allelic and 96 bi-allelic SNP markers revealed that the percentage of differential loci among hybrids mainly ranged from 50% to 85% and 50% to 70%, respectively; for inbred lines, the ranges were 35% to 75% and 35% to 60%, respectively. The average percentage of differential loci among varieties increased by 10% for tri-allelic SNPs compared to bi-allelic SNPs. (3) For both hybrids and inbred lines, the average frequencies of the first, second, and third alleles at the 40 tri-allelic loci were 0.58 and 0.57, 0.31, and 0.11 and 0.12, respectively. (4) Clustering analysis showed that the 40 loci effectively classified the 270 inbred lines into 10 heterotic groups, consistent with classifications based on high-density SNP chip data. In summary, this study reports a high-quality, highly discriminative core set of tri-allelic SNP markers, providing a novel marker type for maize variety identification. With their enhanced ability to resolve genetic variation, these markers are expected to complement existing marker systems and contribute to the advancement of molecular identification technologies in crop breeding.

Key words: maize, variety identification, SNP loci, tri-allelic, core loci set

图1

最优位点集的品种识别率变化曲线图"

附表1

适于玉米品种鉴定的一套三等位变异SNP核心位点信息"

位点
Locus		 染色体
Chr.		 物理位置
Physical
location		 等位
变异1
Allele 1		 等位
变异2
Allele 2		 等位
变异3
Allele 3		 上游侧翼序列(60 bp)
Upstream flanking sequence (60 bp)
(5′-3′)		 下游侧翼序列(60 bp)
Downstream flanking sequence (60 bp)
(5′-3′)
TaSNP01 1 26,694,070 A C G CCAGCCAGTCTGCTTCAACCTTTGCCGGTGCCCTCGGCCATTTGGAATGACATCTCCATA ATATCATTGGGGGTTTCCTCGAGTTGCTGGCAAATCTGTGATTTTGACTGTGGTGAACAT
TaSNP02 1 70,264,325 C A G CCTCGATCCTTGAGAGATTTTCCATATCCATTTGACCAATAAGCATTCATTCATCACCTG GTGTCAATAAAACCTAGAGCCCCTAGTCTTTTGGCCTAGTTAGCATCTCCCACCTCGCCA
TaSNP03 1 70,370,458 C T G CGGAACCCTCTGGAACGGAGCCTCGAACAAAAAAAAAGAATATAGAACAATATAAGCACA GTTAGCAGATGCGATGACGACTAGAAGGGAATGGGAACCGGGACCACGGCAAGCAGACAC
TaSNP04 1 268,027,869 T C A TTCTTGTGAATTGTGATAGAGCCTTGTGAGAGTGCTAAAGAGAAGAGTGTGTGCTGCGTT TTGTGATCTTGATGCAAGACACCCATCCATTGTAAAGCTAGCATTAGCCTTCAACGTGTG
TaSNP05 2 56,077,965 T A G TGCCAACCAGTAAACACCAAGTTCTACAGGCAAGGCAGCATACAAGACTTTCCTTTTGAG ATAGAATTTGCGAAAGATAGCGCATATGGCGTGCAAAATTGGCTGTGATAAAGCAATTAC
TaSNP06 2 191,937,511 T A C AATATGTTCCATAGAATTACCTTAGGTTTGTTCTCTCTTCACGCAGCAGTTCTAATGATC TGTACTTCTTGACTGTTGCCATTCTTAATAAGAAACCGTCCAGTCATTTGATAATGCTTA
TaSNP07 2 192,091,927 A T C ACTATCTACACAGAGACGGATAGCATTAGTTACAGCAGAACATGTACTGCAATATACTGT TGGAGAGAAGGGGGCATCAGCGCGCGGAGTGGCAACAGATAAACGGCATCCACGGCTGCT
TaSNP08 2 237,697,548 G T C GTTGATATTCTATTACGGATGTGGTCACCACAACCGAATCTTTAGGCATGAACTCTTCCA GCTTCTTACTATGCCAGATCACACACTAGATGATAATCGGTTATAACCATTCATCTATAA
TaSNP09 3 47,899,705 G A C GAAGAGCAAGTAGCCATATTTTTGCATGTCATAGGAAACAATGAGCGATTTCGTGTCATT CAATGTCCTTTCGCCGCTCTACCGAGACAATTAGTCATTATTTCCAAGAGGTCCTAGCAG
TaSNP10 3 129,111,971 A G T AGTGCTGTTTCCTCACCTCAGCCAGTCCACAAGTAGCAAGTAGCAACTATAGTCCTAAAG CTAAAGGTACTAACTACTAGCCAGACATAACTAATTCCATATGCTTTGGGAGACAATGCA
TaSNP11 3 222,001,675 C A T CCAACATTTGAGTGGGGGCCTAAATAGAGGCTAAATGACTACTAGACCTTTGTAGCTACA TAAAATGTCCACTGAAACTAGAAAATTGAGTGGGGGCCTGTGCCCCCGCTAAGCCCAACG
TaSNP12 3 224,178,922 T G A TTGCACCTCCTCAATTTTGTTATAGCTTCGTCATTTACTAGCACCGACGTGTCGTGCCCG TGACAAAAGAAATAGTGGAAGAAGACCAGGAGCACGCTTGCGGTGGTGGCCAGGTGCAAC
TaSNP13 4 3,788,094 G A T AAATAGAAATTCTTGACCTTCAGCATCATGCTAAACAGGTGAACCATGAACACTGTTAGA ACTTTATGCACATTTTTATTGTACATATATTTTTTTCCTAATTAACTTCTGCCAGAGCCC
TaSNP14 4 10,076,723 G C T GCATCCTCTCCTAGATGCTCTCTTATGTTACTAGTATCAAGTTTCTAGCCAAAATGATGC GGTCTTATTTCCTACAATACATAGTGATGGCCACACTATAAATGCAGGTGATGTGCTCTC
TaSNP15 4 10,645,740 A C G TATAGAGGAGCATCAAACTGTACGATGGTCACTCGTGGACTATTCGACAGGCATCAAACC TGTGAATGATGCACGAGTCCTATCCAACAAGCTCAAATCATAGGCATTAGATAGTCCGAT
TaSNP16 4 86,481,785 C A T CAAATATGAGAAATCACTATATGTCATTCCTTATTTTGAGGCCTAGGATTTTAGCTCATT TGTGTAGCTACAACAAGTGTGACACAATAGCTGTAGAAGGGGTCAGTATGGATCATGATC
TaSNP17 5 1,487,478 T G A ACCCGCCCCCCTTCCGTGCGACGAATAGTTGGCGAACACTGCATCGAGTTACGAGACATT AGTCAAGACACGAGAAGGGGAAAGCATCGGTCGACGCTAAGAACATCAAACAGTTGGGAT
TaSNP18 5 60,276,448 G C T CTCTGTCTCTTTTAGTCTTTTTGGAGGAGGAACAAAGAACCAGTGGGGTTTCGAAAGGAG AGTAGGCCGACAAGTAGCATCGCATCACGTTCTCCTAATGAATGACTAGCATGAGTCAAA
TaSNP19 5 91,897,631 G A T CCCACCAATGATATCCCTTATGCTCAGCACTATACCCAAGAAAAAGCACACTCAACTGAC GAGCAATCAACTTAGTGCGCTCATGAGGTGGGAGCAGCACATATAAACACAACTAGACAT
TaSNP20 5 186,888,339 C T G TACTCAGCAGGTAATGATGCTATAAAAGCATCAGACTGCCTGGGCGCCATATCAGCCTTC ACTGGTGCATATCAGCCACTGCTTTCACCTCCCCCACCGTCTCACTCTCACCTGATATCT
TaSNP21 6 75,706,844 T G A GGAATACTTCGGTTGAAGTCGTGGAACTCGTTCCCTACGCGATGAATGGGTGGGGGAACA GTGGGACTTTTGGTTTTACATTCAAACAAAAGATAGTGAAGGGGTTCTGAGTCTGTCGTT
TaSNP22 6 149,861,566 T G C TAGGCAAGTTAGTAGAGGTGTATTTCAATGACATTGTATTGAAAACATGTGAGTCCAACA TCCCATTTGGGATCTTGAAACCGTTTTTACAGCCTCCCCCCAAAACTGCATCTTCAACAT
TaSNP23 6 151,920,452 G T A AATTAAGTGTTTTGTTCACCAAAACACATACATTCAAAGTGTAAGACCAAATACCACCAC GAATGGTTGAAGCTACCCAGGGACATCCATAATTTAAGAACCAAAAACAAATAAAAGTAG
TaSNP24 6 167,615,957 C A G GAATGAAGGAAACAATTAATTGGACCTTCTGAGCCTGGCCTAATTGCAGAGGTATGCAAT TGGACAGCAGTTGAGGCCATCAAACTCAGATTGAGAGGCCGGTTGGAAACCGGTATGACG
TaSNP25 7 20,793,475 A T G GCTCTAAGTTACCCTCATTCATAGTGAAAAACATTCTCATATTAAGAGCAACAGCTCCTG CTTGACAACGAGGAAGGGTGTGTGACCCGTGGCCTTTGTGGCTGACCTCAACTACGTAGA
TaSNP26 7 23,775,501 T G A CGACATACTCGTCGCTGGTCTACACCACATTTGTCCTCGAGTTCTTCGCCGACAAGTACC TCGTCGCGCTCCTCTGGCGCCATCGAGTCTCTTCATGTGTGTCGTAACTCTCACCGTTGC
TaSNP27 7 25,104,386 T A C ATTTAGTTTTAAATTCCATATCAATCCACGCTATAATAACACATGTATAAGGAGTATATC AAACAGGCCCACACATGGAATGTTTGAGATATGCATTCAAATGCATTCCTCCGCATCCTG
TaSNP28 7 91,528,461 G T A GATCCATTTTTTGAGGAACGGTGGGTTGCTTCATCGTTGGTCCCTATAGTGTGGAGATTC TGCTTTCCAAGGCAGTCAATTCATCCAACGGGAGTGACGACACATTTCATCGAGGTAGTC
TaSNP29 8 117,427,483 G T C GCTTGTTCGAAAAGGCGAATCCAAAGAAATGCTAACGTTGCAGAAGAATGAAGGCCAATT TGCCTTAGATTGCGTAAGCATGAGAAAAGCAAGTGGCTACAGAAACGACCGCTACAGATA
TaSNP30 8 141,530,330 A C G CTTCACCGCTCTCAAACTGACATCTATCTCCGAACAGAACATACAAATAATCAAACCAAT AGTTTACTGAATCAAGTGCAATTCGCCGTAAGAACAAACCTGTAAGGTACGATATTTGTG
TaSNP31 8 141,766,718 C G T TATAGCGAGGACAAGACATGAGCAACTTCTGGTCAGGTAGAAAAGTACGGTTGGACAGCA CATGAAGCACACAAAAAGGGATTAGATAAAAATCATGGCTGCAGTAGGTTGATTAGGTCT
TaSNP32 8 172,879,909 A G C TCCAATGCCAGTCTCTCGAGGGAACTAGAGTTTAGGCTAGCCTCTAGTTTCTATCTTGTT CACTATTCTATGGACCAATGGATTTATTCAGTGGTCCCTGGTTCCAAGCACGAGAGCAAA
TaSNP33 9 46,962,286 T C A CTTATATTTATCACATTGCTGTTTTTTTTACTGTTGTGCGGACCAATGTTTTTTTAATTT TTGAGAACAACAGTGCAACATGCGTAACTTAGAGAAGGAGCAGCAAGGTAATCCATGTCC
TaSNP34 9 88,827,030 T C A TGCAAAATTCTCACTCGCTAACCCTAATCCTCATTTCCTAAAATAATCGTTGAGAAAGCA CGGACATGTCTGGTGCAGAAAGTGGACGAGCACCGAACATGTCCAATGCACCCAACTGGG
TaSNP35 9 97,080,329 A T C ATGGGAAAATTCACAGCGAATCTGCTTTGCCCATAGGTAATGAACGAATGCCATCGATGG ACACCACTTAGATATGGAAACTGCCAGCCGACCAGCTGGGCTGGTTCTTTCTAACTTCGC
TaSNP36 9 149,325,574 A G C ACTGGACTTCGAATCCCTTCTTCTGCTCTGCAATAATTGCAAGCACAAAAGAAGGCTAAA CAAGGAATTGCTCCTTCCTTCTAGAGGTCTTTGCGCTGGGACGTTGACGAAATTATCTCG
TaSNP37 10 16,222,443 A T G ATGATAGGGCTCCAACATATGGGGTCCTATATTTAGGACCTGAGAGGCTGAGTATTATAA TATTCGATGATTTTTTGTGAAATAAGACCTCTGTTGGAGCAAGCTTTTAGTGTTAGAGTC
TaSNP38 10 113,185,518 T G C AAAAAAGGATCAGGCACTCTGATAAACTAATAGCAAGGTGATTGCAAATCAGTATGTCCA CCTACTAAATCTGTAGATCTGTACACAAAAATTGCAAAGGATGGCATCTTAACAACGCAG
TaSNP39 10 145,237,355 C G A TAGTTGATCTGATCCCTAACCTTCAATCTTTGCACAAATGGGTAATACAAACTTCTGACT ATTGTAGCTTTTAAGAGCCAACTCCAAGAATGACATGCAAAAGACCCGAAGAAGTGTTTT
TaSNP40 10 146,434,632 G C T TGGTTATGGGCCTAACGGGCAGAAGTATGTATATATAAAAATATTAGAATATGTTCATCA ACAGTACATATTAGACTCTCGCTGACTGTTGTTGTACCATATATTTGTAATATAGATCAT

图2

三等位变异位点TaSNP06及其侧翼序列"

图3

基于200个玉米杂交种和270个自交系评估40个SNP位点的PIC值和DP值 横坐标为SNP位点, 顺序为基于杂交种数据评估值由小到大。"

图4

利用96个二等位和40个三等位变异SNP标记评估玉米杂交种、自交系两两成对比较的差异位点百分比分布图"

图5

基于玉米200个杂交种和270个自交系评估40个SNP位点的3种等位变异频率 横坐标为40个SNP位点及其3种等位变异, 例如, TaSNP01:G/C/A指等位变异1为G, 等位变异2为C, 等位变异3为A。"

图6

基于玉米270个自交系的40个SNP位点数据构建的杂优类群聚类图 Tangsipingtou: 塘四平头群; Lvda red cob: 旅大红骨群; Iodent: 爱荷华黄马齿群; P group: P群; Reid: 瑞德群; Improved Reid: 改良瑞德群; X group: X群; Lancaster: 兰卡斯特群; Mixed 1: 混合1群; Mixed 2: 混合2群。"

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