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Article(id=1256536356533166416, tenantId=1146029695717560320, journalId=1256314692575182859, issueId=1256536349243523385, articleNumber=null, orderNo=null, doi=10.16035/j.issn.1001-7283.2026.02.007, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1755532800000, receivedDateStr=2025-08-19, revisedDate=1757001600000, revisedDateStr=2025-09-05, acceptedDate=null, acceptedDateStr=null, onlineDate=1777511212714, onlineDateStr=2026-04-30, pubDate=1776182400000, pubDateStr=2026-04-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1777511212714, onlineIssueDateStr=2026-04-30, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1777511212714, creator=13701087609, updateTime=1777511212714, updator=13701087609, issue=Issue{id=1256536349243523385, tenantId=1146029695717560320, journalId=1256314692575182859, year='2026', volume='42', issue='2', pageStart='1', pageEnd='264', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=0, createTime=1777511210976, creator=13701087609, updateTime=1777511532015, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1256537695891874281, tenantId=1146029695717560320, journalId=1256314692575182859, issueId=1256536349243523385, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1256537695891874282, tenantId=1146029695717560320, journalId=1256314692575182859, issueId=1256536349243523385, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=59, endPage=67, ext={EN=ArticleExt(id=1256536358370271587, articleId=1256536356533166416, tenantId=1146029695717560320, journalId=1256314692575182859, language=EN, title=Genetic Diversity Analysis of Newly Developed Wheat Germplasm Based on HMW-GS in Southern Huang-Huai Wheat Region, columnId=null, journalTitle=Crops, columnName=null, runingTitle=null, highlight=null, articleAbstract=

To clarify the relationship between high-molecular-weight glutenin subunits (HMW-GS) composition and quality traits in newly developed wheat varieties (lines) in the Southern Huang-Huai Wheat Region, a total of 93 newly developed wheat varieties (lines) from this region were used as materials. The HMW-GS composition was identified using SDS-PAGE, and their distribution and quality characteristics were systematically analyzed in conjunction with grain quality traits. The results showed that nine subunit types were detected across the three Glu-1 loci, specifically, subunits 1 (72.04%) and Null (27.96%) at the Glu-A1 locus; subunits 7+9 (64.52%), 7+8 (30.11%), and 14+15 (5.38%) at the Glu-B1 locus; and subunits 2+12 (37.63%), 5+12 (32.26%), 5+10 (29.03%), and 2+10 (1.08%) at the Glu-D1 locus. Among the 15 identified subunit combinations, the most frequent combination was 1/7+9/2+12 (19.35%), while the frequency of the combination 1/7+8/5+10 was 8.60%. Based on quality traits, the tested materials were clustered into three groups, with Group I, Group II, and Group III accounting for 47.3%, 17.2%, and 35.5%, respectively. Group III exhibited the best performance across all quality indicators such as protein content, water absorption rate, and wet gluten content; the frequencies of subunits 14+15, 7+8, and 5+10 in group III were 6.06%, 36.36%, and 30.30%, respectively. Varieties (lines) carrying the pedigree of two founder parents, Yumai 2 and Zhou 8425B, accounted for 70.96% of the tested materials. Eight varieties such as Zhengmai 366, Xinmai 26, Jimai 44, and Fumai 916, were screened for carrying high-quality subunits and combinations. These results provide a theoretical basis for parent selection in wheat quality breeding in the Southern Huang-Huai Wheat Region and serve as an important reference for further optimizing HMW-GS composition and improving wheat quality.

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为明确黄淮南片麦区新育小麦品种（系）高分子量麦谷蛋白亚基（HMW-GS）的组成与品质性状的关系，以该区近年育成的93份小麦品种（系）为材料，采用SDS-PAGE方法鉴定HMW-GS组成，并结合籽粒品质性状系统分析其HMW-GS分布及品质特征。结果表明，共检测到Glu-1 3个位点上共9种亚基类型，分别为Glu-A1位点的1（72.04%）和Null（27.96%）亚基，Glu-B1位点的7+9（64.52%）、7+8（30.11%）和14+15（5.38%）亚基，以及Glu-D1位点的2+12（37.63%）、5+12（32.26%）、5+10（29.03%）和2+10（1.08%）亚基。15种亚基组合类型中出现频率最高的是1/7+9/2+12（19.35%），组合1/7+8/5+10的分布频率为8.60%。依据品质性状将参试材料聚类为3个类群，类群Ⅰ、类群Ⅱ和类群Ⅲ分别占比47.3%、17.2%和35.5%。类群Ⅲ材料的蛋白质含量、吸水率和湿面筋含量等品质指标均表现最优，该类群中14+15、7+8和5+10亚基出现的频率分别为6.06%、36.36%和30.30%。参试材料中含有豫麦2号和周8425B两个骨干亲本血缘的品种（系）占比达70.96%。筛选出郑麦366、新麦26、济麦44和富麦916等8个品种携带优质亚基及组合。研究结果为黄淮南片麦区小麦品质育种的亲本选配提供了理论依据，对进一步优化HMW-GS组成和改良小麦品质具有重要参考价值。

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宋全昊，主要从事小麦育种和栽培技术研究，E-mail：
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金艳，主要从事小麦育种和栽培技术研究，E-mail：

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金艳，主要从事小麦育种和栽培技术研究，E-mail：

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journalName=中国农业科技导报(中英文), refType=null, unstructuredReference=刘一凡, 刘少帅, 臧瑞, 等. 168份小麦种质资源品质性状分析. 中国农业科技导报(中英文), 2025, 27(9):44-57., articleTitle=168份小麦种质资源品质性状分析, refAbstract=null), Reference(id=1256536450472992993, tenantId=1146029695717560320, journalId=1256314692575182859, articleId=1256536356533166416, doi=null, pmid=null, pmcid=null, year=2006, volume=26, issue=2, pageStart=68, pageEnd=71, url=null, language=null, rfNumber=[21], rfOrder=20, authorNames=冯毅, 闵东红, 孙道杰, journalName=麦类作物学报, refType=null, unstructuredReference=冯毅, 闵东红, 孙道杰, 等. 黄淮麦区部分推广小麦品种高分子量麦谷蛋白亚基组成分析. 麦类作物学报, 2006, 26(2):68-71., articleTitle=黄淮麦区部分推广小麦品种高分子量麦谷蛋白亚基组成分析, refAbstract=null), Reference(id=1256536450661736680, tenantId=1146029695717560320, journalId=1256314692575182859, articleId=1256536356533166416, doi=null, pmid=null, pmcid=null, year=2015, volume=24, issue=2, pageStart=27, pageEnd=32, url=null, language=null, rfNumber=[22], rfOrder=21, authorNames=王静, 刘东涛, 陈荣振, journalName=西北农业学报, refType=null, unstructuredReference=王静, 刘东涛, 陈荣振, 等. 黄淮麦区部分小麦品种(系)高分子量麦谷蛋白亚基的SDS-PAGE和分子标记分析. 西北农业学报, 2015, 24(2):27-32., articleTitle=黄淮麦区部分小麦品种(系)高分子量麦谷蛋白亚基的SDS-PAGE和分子标记分析, refAbstract=null), Reference(id=1256536450812731629, tenantId=1146029695717560320, journalId=1256314692575182859, articleId=1256536356533166416, doi=null, pmid=null, pmcid=null, year=2007, volume=27, issue=3, pageStart=483, pageEnd=487, url=null, language=null, rfNumber=[23], rfOrder=22, authorNames=李博, 张荣琦, 王亚娟, journalName=麦类作物学报, refType=null, unstructuredReference=李博, 张荣琦, 王亚娟, 等. 黄淮麦区部分小麦地方品种高分子量麦谷蛋白亚基组成分析. 麦类作物学报, 2007, 27(3):483-487., articleTitle=黄淮麦区部分小麦地方品种高分子量麦谷蛋白亚基组成分析, refAbstract=null), Reference(id=1256536451211190517, tenantId=1146029695717560320, journalId=1256314692575182859, articleId=1256536356533166416, doi=null, pmid=null, pmcid=null, year=2022, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[24], rfOrder=23, authorNames=韩文蕾, journalName=山西省小麦品种(系)HMW-GS组成分析, refType=null, unstructuredReference=韩文蕾. 山西省小麦品种(系)HMW-GS组成分析. 晋中: 山西农业大学, 2022., articleTitle=null, refAbstract=null), Reference(id=1256536451488014585, tenantId=1146029695717560320, journalId=1256314692575182859, articleId=1256536356533166416, doi=null, pmid=null, pmcid=null, year=2021, volume=41, issue=5, pageStart=544, pageEnd=552, url=null, language=null, rfNumber=[25], rfOrder=24, authorNames=范家霖, 陈晓杰, 张建伟, journalName=麦类作物学报, refType=null, unstructuredReference=范家霖, 陈晓杰, 张建伟, 等. 高分子量麦谷蛋白亚基组成及其与小麦品质性状的关系分析. 麦类作物学报, 2021, 41(5):544-552, articleTitle=高分子量麦谷蛋白亚基组成及其与小麦品质性状的关系分析, refAbstract=null), Reference(id=1256536451785810176, tenantId=1146029695717560320, journalId=1256314692575182859, articleId=1256536356533166416, doi=null, pmid=null, pmcid=null, year=2012, volume=32, issue=1, pageStart=79, pageEnd=82, url=null, language=null, rfNumber=[26], rfOrder=25, authorNames=张丽琴, 刘春雷, 杨雪, journalName=麦类作物学报, refType=null, unstructuredReference=张丽琴, 刘春雷, 杨雪, 等. 黄淮麦区小麦新品种(系)高分子量谷蛋白亚基多态性分析. 麦类作物学报, 2012, 32(1):79-82., articleTitle=黄淮麦区小麦新品种(系)高分子量谷蛋白亚基多态性分析, refAbstract=null), Reference(id=1256536452016496902, tenantId=1146029695717560320, journalId=1256314692575182859, articleId=1256536356533166416, doi=null, pmid=null, pmcid=null, year=2023, volume=null, issue=10, pageStart=62, pageEnd=65, url=null, language=null, rfNumber=[27], rfOrder=26, authorNames=耿惠敏, journalName=农业科技通讯, refType=null, unstructuredReference=耿惠敏. 714个黄淮麦区小麦新品种(系)HMW-GS组成的研究. 农业科技通讯, 2023(10):62-65,171., articleTitle=714个黄淮麦区小麦新品种(系)HMW-GS组成的研究, refAbstract=null), Reference(id=1256536452205240588, tenantId=1146029695717560320, journalId=1256314692575182859, articleId=1256536356533166416, doi=null, pmid=null, pmcid=null, year=2014, volume=15, issue=1, pageStart=18, pageEnd=23, url=null, language=null, rfNumber=[28], rfOrder=27, authorNames=李艳丽, 鲁敏, 麻姗姗, journalName=植物遗传资源学报, refType=null, unstructuredReference=李艳丽, 鲁敏, 麻姗姗, 等. 67份美国小麦种质资源的HMW-GS组成与品质分析. 植物遗传资源学报, 2014, 15(1):18-23,31., articleTitle=67份美国小麦种质资源的HMW-GS组成与品质分析, refAbstract=null), Reference(id=1256536452444315921, tenantId=1146029695717560320, journalId=1256314692575182859, articleId=1256536356533166416, doi=null, pmid=null, pmcid=null, year=2025, volume=51, issue=10, pageStart=2663, pageEnd=2680, url=null, language=null, rfNumber=[29], rfOrder=28, authorNames=田汉钊, 冯龙婷, 应开, journalName=作物学报, refType=null, unstructuredReference=田汉钊, 冯龙婷, 应开, 等. 外引小麦种质麦谷蛋白亚基组成及评价. 作物学报, 2025, 51(10):2663-2680., articleTitle=外引小麦种质麦谷蛋白亚基组成及评价, refAbstract=null), Reference(id=1256536452544979222, tenantId=1146029695717560320, journalId=1256314692575182859, articleId=1256536356533166416, doi=null, pmid=null, pmcid=null, year=2024, volume=26, issue=2, pageStart=33, pageEnd=45, url=null, language=null, rfNumber=[30], rfOrder=29, authorNames=金艳, 宋全昊, 宋佳静, journalName=中国农业科技导报, refType=null, unstructuredReference=金艳, 宋全昊, 宋佳静, 等. 69份小麦种质资源的综合性评价. 中国农业科技导报, 2024, 26(2):33-45., articleTitle=69份小麦种质资源的综合性评价, refAbstract=null), Reference(id=1256536452641448218, tenantId=1146029695717560320, journalId=1256314692575182859, articleId=1256536356533166416, doi=null, pmid=null, pmcid=null, year=2022, volume=50, issue=10, pageStart=25, pageEnd=27, url=null, language=null, rfNumber=[31], rfOrder=30, authorNames=王倩, 任文斌, 谢三刚, journalName=安徽农业科学, refType=null, unstructuredReference=王倩, 任文斌, 谢三刚. 山西省小麦品系HMW-GS的组成及品质分析. 安徽农业科学, 2022, 50(10):25-27., articleTitle=山西省小麦品系HMW-GS的组成及品质分析, refAbstract=null), Reference(id=1256536452834386207, tenantId=1146029695717560320, journalId=1256314692575182859, articleId=1256536356533166416, doi=null, pmid=null, pmcid=null, year=2018, volume=33, issue=2, pageStart=157, pageEnd=162, url=null, language=null, rfNumber=[32], rfOrder=31, authorNames=李立, 龚梦婕, 李锁平, journalName=华北农学报, refType=null, unstructuredReference=李立, 龚梦婕, 李锁平, 等. 黄淮麦区小麦新品系高分子量谷蛋白亚基的组成及结构变化分析. 华北农学报, 2018, 33(2):157-162., articleTitle=黄淮麦区小麦新品系高分子量谷蛋白亚基的组成及结构变化分析, refAbstract=null)], 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Parent information of test materials

, figureFileSmall=null, figureFileBig=null, tableContent=
编号
Code		 品种（系）
Variety (line)		 亲本
Parents		 编号
Code		 品种（系）
Variety (line)		 亲本
Parents
1 中育1051 04中36/周麦16 34 中农867 中育9307/漯6082
2 郑麦163 偃9998/百农AK58//郑麦366 35 04中36 百农64/周11
3 济麦44 954072/济南17 36 中农539 许科1018/周麦22号
4 新农23 （周麦16/济麦22）F1//西农979 37 中农031 （04中36/百农AK58）F5/周98165
5 周麦16 周麦9号/周8425B 38 郑大181 冀麦4号/郑农17
6 周麦22 周麦12/豫麦49//周麦13 39 安农1928 丰德存麦1号/徐麦9074
7 周麦32 百农AK58/周麦24 40 漯丰7011 S1012/郑麦366//漯6073
8 周麦52 周麦32号/周麦36号 41 豫农905 DH（新麦26/周麦28）
9 洛麦45 周麦22/洛麦07450 42 中植麦16 许科316/百农AK58//周麦22
10 洛麦44 周麦22//周麦22/洛麦07450 43 瑞华519 烟农19/瑞华麦516
11 徐麦17106 百农AK58/徐麦8083 44 陕禾1029 西农979/西农9718
12 新农9799 周麦32/郑麦366 45 泛麦26 新麦26/西农979/百农AK58
13 中麦698 中麦895/周麦22//中麦895 46 西农1125 西农20/郑麦7698
14 瑞华麦513 瑞华麦516/泛麦8号//瑞华麦518 47 富麦916 新麦26/周麦32
15 漯丰1905 L103/漯麦18 48 安科1704 淮麦25/07ELT203
16 郑麦136 百农AK58/济麦22 49 良科6号 西农979×泛麦8号
17 郑麦618 周麦16/选04115-8//周麦16 50 西农1155 丰德存麦1号/03011
18 郑麦22 周麦22/百农AK58//偃展4110 51 西农162 西农519/陕麦159
19 洛麦28 洛麦21/百农AK58 52 连麦12 刘虎98/西农4711//生选6号/漯38
20 洛麦26 百农AK58/开麦18 53 淮麦404 徐农029/淮麦44
21 矮抗58 周麦11/温麦6号/郑州8960 54 安农859 瑞华麦520/亿麦11
22 中原丰1号 温麦6/周麦12号//周麦13号/商麦008 55 郑研麦182 周麦16/郑豫麦9987
23 西农979 西农2611/(918×95选F1) 56 许科108 郑麦9023/兰考906//丰德存麦1号
24 郑品麦25 周麦16/淮麦20 57 百农207 周麦16/豫麦54
25 存麦35 兰考198/存1425//苏赖麦 58 周麦18 内乡185/周麦9号
26 西农20 郑麦366/陕农981//郑麦366 59 郑麦113 百农AK58/偃展4110
27 赛德麦5号 豫农982/周麦22 60 周麦36 百农AK58/周麦19//周麦22
28 中育1702 周麦26号/08漯33 61 西农579 2001121-31/西农822
29 中金13 周麦16/7979 62 新麦65 新麦26//济麦20/新麦26
30 中植麦13 周22/百农AK58 63 西农586 JY08S2-1-1-1/JY0752
31 驻麦4号 89中170/汴8539-2 64 天民360 小偃784/矮特早1-5//周麦18///百农AK58////扬麦20
32 新麦38 周麦32/新麦28 65 阜麦16 宿553/淮麦21
33 郑麦366 豫麦47/PH82-2-2 66 科大116 济麦3号/科大28
67 驻麦562 驻0204-721/良星66 81 郑麦21 兰考198/周麦22
68 天益科麦11 中麦895/华成麦1688 82 扬麦15 扬89-40/川育21526
69 洛麦49 周麦22/洛麦07420 83 驻麦328 百农AK58/济95519
70 豫州136 豫州109/扬麦15 84 驻麦305 周麦16/04中36
71 豫农917 DH（豫农904/豫农910）F2 85 驻麦762 04中36/百农AK58
72 郑麦827 百农AK58/洛麦22 86 驻麦256 04中36//周麦16/04中36
73 郑麦828 郑麦158辐射诱变 87 驻麦586 周麦26/泛麦08206
74 豫州121 科兴404/扬麦15//永川白麦子 88 驻麦726 周麦16/04中36
75 郑麦825 （偃展4110/周麦16）F0辐射诱变 89 驻麦591 濮育1号/洛麦23
76 郑麦826 （郑03876/兰考198）F0辐射诱变 90 驻麦592 洛麦23/许农7号
77 郑麦823 开麦26/咨4 91 驻麦596 04中36/周麦13
78 郑麦518 观35/新9944 92 驻麦598 洛麦23/周麦22
79 豫农911 DH（周麦26/冀糯200） 93 新麦26 新麦18/济南17
80 豫农914 DH（百农AK58/扬糯麦1号）
), ArticleFig(id=1256536425965675472, tenantId=1146029695717560320, journalId=1256314692575182859, articleId=1256536356533166416, language=CN, label=表1, caption=

试验材料的亲本信息

, figureFileSmall=null, figureFileBig=null, tableContent=
编号
Code		 品种（系）
Variety (line)		 亲本
Parents		 编号
Code		 品种（系）
Variety (line)		 亲本
Parents
1 中育1051 04中36/周麦16 34 中农867 中育9307/漯6082
2 郑麦163 偃9998/百农AK58//郑麦366 35 04中36 百农64/周11
3 济麦44 954072/济南17 36 中农539 许科1018/周麦22号
4 新农23 （周麦16/济麦22）F1//西农979 37 中农031 （04中36/百农AK58）F5/周98165
5 周麦16 周麦9号/周8425B 38 郑大181 冀麦4号/郑农17
6 周麦22 周麦12/豫麦49//周麦13 39 安农1928 丰德存麦1号/徐麦9074
7 周麦32 百农AK58/周麦24 40 漯丰7011 S1012/郑麦366//漯6073
8 周麦52 周麦32号/周麦36号 41 豫农905 DH（新麦26/周麦28）
9 洛麦45 周麦22/洛麦07450 42 中植麦16 许科316/百农AK58//周麦22
10 洛麦44 周麦22//周麦22/洛麦07450 43 瑞华519 烟农19/瑞华麦516
11 徐麦17106 百农AK58/徐麦8083 44 陕禾1029 西农979/西农9718
12 新农9799 周麦32/郑麦366 45 泛麦26 新麦26/西农979/百农AK58
13 中麦698 中麦895/周麦22//中麦895 46 西农1125 西农20/郑麦7698
14 瑞华麦513 瑞华麦516/泛麦8号//瑞华麦518 47 富麦916 新麦26/周麦32
15 漯丰1905 L103/漯麦18 48 安科1704 淮麦25/07ELT203
16 郑麦136 百农AK58/济麦22 49 良科6号 西农979×泛麦8号
17 郑麦618 周麦16/选04115-8//周麦16 50 西农1155 丰德存麦1号/03011
18 郑麦22 周麦22/百农AK58//偃展4110 51 西农162 西农519/陕麦159
19 洛麦28 洛麦21/百农AK58 52 连麦12 刘虎98/西农4711//生选6号/漯38
20 洛麦26 百农AK58/开麦18 53 淮麦404 徐农029/淮麦44
21 矮抗58 周麦11/温麦6号/郑州8960 54 安农859 瑞华麦520/亿麦11
22 中原丰1号 温麦6/周麦12号//周麦13号/商麦008 55 郑研麦182 周麦16/郑豫麦9987
23 西农979 西农2611/(918×95选F1) 56 许科108 郑麦9023/兰考906//丰德存麦1号
24 郑品麦25 周麦16/淮麦20 57 百农207 周麦16/豫麦54
25 存麦35 兰考198/存1425//苏赖麦 58 周麦18 内乡185/周麦9号
26 西农20 郑麦366/陕农981//郑麦366 59 郑麦113 百农AK58/偃展4110
27 赛德麦5号 豫农982/周麦22 60 周麦36 百农AK58/周麦19//周麦22
28 中育1702 周麦26号/08漯33 61 西农579 2001121-31/西农822
29 中金13 周麦16/7979 62 新麦65 新麦26//济麦20/新麦26
30 中植麦13 周22/百农AK58 63 西农586 JY08S2-1-1-1/JY0752
31 驻麦4号 89中170/汴8539-2 64 天民360 小偃784/矮特早1-5//周麦18///百农AK58////扬麦20
32 新麦38 周麦32/新麦28 65 阜麦16 宿553/淮麦21
33 郑麦366 豫麦47/PH82-2-2 66 科大116 济麦3号/科大28
67 驻麦562 驻0204-721/良星66 81 郑麦21 兰考198/周麦22
68 天益科麦11 中麦895/华成麦1688 82 扬麦15 扬89-40/川育21526
69 洛麦49 周麦22/洛麦07420 83 驻麦328 百农AK58/济95519
70 豫州136 豫州109/扬麦15 84 驻麦305 周麦16/04中36
71 豫农917 DH（豫农904/豫农910）F2 85 驻麦762 04中36/百农AK58
72 郑麦827 百农AK58/洛麦22 86 驻麦256 04中36//周麦16/04中36
73 郑麦828 郑麦158辐射诱变 87 驻麦586 周麦26/泛麦08206
74 豫州121 科兴404/扬麦15//永川白麦子 88 驻麦726 周麦16/04中36
75 郑麦825 （偃展4110/周麦16）F0辐射诱变 89 驻麦591 濮育1号/洛麦23
76 郑麦826 （郑03876/兰考198）F0辐射诱变 90 驻麦592 洛麦23/许农7号
77 郑麦823 开麦26/咨4 91 驻麦596 04中36/周麦13
78 郑麦518 观35/新9944 92 驻麦598 洛麦23/周麦22
79 豫农911 DH（周麦26/冀糯200） 93 新麦26 新麦18/济南17
80 豫农914 DH（百农AK58/扬糯麦1号）
), ArticleFig(id=1256536426632569818, tenantId=1146029695717560320, journalId=1256314692575182859, articleId=1256536356533166416, language=EN, label=Table 2, caption=

Distribution of HMW-GS subunits and their impact on wheat quality

, figureFileSmall=null, figureFileBig=null, tableContent=
位点
Locus		 亚基
Subunit		 数量
Number		 频率
Frequency
(%)		 蛋白质含量
Protein
content (%)		 湿面筋含量
Wet gluten
content (%)		 沉降值
Zeleny sedimentation
value (mL)		 吸水率
Water absorption
rate (%)		 含水量
Moisture
content (%)		 容重
Test weight
(g/L)
Glu-A1 1 67 72.04 14.75 30.53 27.07 57.77 12.06 772.80
N 26 27.96 14.72 30.65 28.41 58.82 12.10 780.14
Glu-B1 14+15 5 5.38 15.01 30.65 27.36 54.18 12.14 772.81
7+8 28 30.11 14.48 30.17 27.80 58.97 12.46 779.02
7+9 60 64.52 14.84 30.74 27.29 57.97 11.88 773.07
Glu-D1 5+12 30 32.26 14.66 30.26 26.54 57.11 12.10 774.85
5+10 27 29.03 14.86 30.94 28.22 58.72 12.03 775.06
2+12 35 37.63 14.64 30.41 27.28 58.28 12.05 774.34
2+10 1 1.08 17.60 34.82 39.44 61.66 12.76 786.75
), ArticleFig(id=1256536428335457248, tenantId=1146029695717560320, journalId=1256314692575182859, articleId=1256536356533166416, language=CN, label=表2, caption=

HMW-GS亚基分布及其对小麦品质的影响

, figureFileSmall=null, figureFileBig=null, tableContent=
位点
Locus		 亚基
Subunit		 数量
Number		 频率
Frequency
(%)		 蛋白质含量
Protein
content (%)		 湿面筋含量
Wet gluten
content (%)		 沉降值
Zeleny sedimentation
value (mL)		 吸水率
Water absorption
rate (%)		 含水量
Moisture
content (%)		 容重
Test weight
(g/L)
Glu-A1 1 67 72.04 14.75 30.53 27.07 57.77 12.06 772.80
N 26 27.96 14.72 30.65 28.41 58.82 12.10 780.14
Glu-B1 14+15 5 5.38 15.01 30.65 27.36 54.18 12.14 772.81
7+8 28 30.11 14.48 30.17 27.80 58.97 12.46 779.02
7+9 60 64.52 14.84 30.74 27.29 57.97 11.88 773.07
Glu-D1 5+12 30 32.26 14.66 30.26 26.54 57.11 12.10 774.85
5+10 27 29.03 14.86 30.94 28.22 58.72 12.03 775.06
2+12 35 37.63 14.64 30.41 27.28 58.28 12.05 774.34
2+10 1 1.08 17.60 34.82 39.44 61.66 12.76 786.75
), ArticleFig(id=1256536428675195877, tenantId=1146029695717560320, journalId=1256314692575182859, articleId=1256536356533166416, language=EN, label=Table 3, caption=

HMW-GS composition types, frequencies and scores in 93 wheat varieties (lines)

, figureFileSmall=null, figureFileBig=null, tableContent=
编号
Code		 HMW-GS 品种（系）编号
Codes of varieties (lines)		 份数
Number of samples		 频率
Frequency (%)		 评分
Score
Glu-A1 Glu-B1 Glu-D1
1 1 14+15 5+12 64，72，73 3 3.23 11
2 1 14+15 5+10 77 1 1.08 10
3 1 7+8 2+12 23，39，82 3 3.23 8
4 1 7+8 5+10 2，3，33，47，54，59，84，93 8 8.60 10
5 1 7+8 5+12 16，21，25，45，48，50，56，79，85 9 9.68 11
6
 1
 7+9
 2+12
 4，6，7，8，9，13，22，29，30，35，42，58，60，69，71，78，86，88 18
 19.35
 7
7 1 7+9 5+10 12，19，20，26，32，40，49，51，62，74，89，90 12 12.90 9
8 1 7+9 5+12 15，18，27，28，36，37，57，67，76，80，87，91，92 13 13.98 8
9 N 14+15 2+12 75 1 1.08 6
10 N 7+8 2+12 1，31，52，53，66，68 6 6.45 6
11 N 7+8 5+10 44，46 2 2.15 8
12 N 7+9 2+10 43 1 1.08 <6
13 N 7+9 2+12 5，10，14，17，24，61，83 7 7.53 5
14 N 7+9 5+10 11，41，63，65 4 4.30 7
15 N 7+9 5+12 34，38，55，70，81 5 5.38 8
), ArticleFig(id=1256536429136569325, tenantId=1146029695717560320, journalId=1256314692575182859, articleId=1256536356533166416, language=CN, label=表3, caption=

93份小麦品种（系）HMW-GS组合类型、频率及得分

, figureFileSmall=null, figureFileBig=null, tableContent=
编号
Code		 HMW-GS 品种（系）编号
Codes of varieties (lines)		 份数
Number of samples		 频率
Frequency (%)		 评分
Score
Glu-A1 Glu-B1 Glu-D1
1 1 14+15 5+12 64，72，73 3 3.23 11
2 1 14+15 5+10 77 1 1.08 10
3 1 7+8 2+12 23，39，82 3 3.23 8
4 1 7+8 5+10 2，3，33，47，54，59，84，93 8 8.60 10
5 1 7+8 5+12 16，21，25，45，48，50，56，79，85 9 9.68 11
6
 1
 7+9
 2+12
 4，6，7，8，9，13，22，29，30，35，42，58，60，69，71，78，86，88 18
 19.35
 7
7 1 7+9 5+10 12，19，20，26，32，40，49，51，62，74，89，90 12 12.90 9
8 1 7+9 5+12 15，18，27，28，36，37，57，67，76，80，87，91，92 13 13.98 8
9 N 14+15 2+12 75 1 1.08 6
10 N 7+8 2+12 1，31，52，53，66，68 6 6.45 6
11 N 7+8 5+10 44，46 2 2.15 8
12 N 7+9 2+10 43 1 1.08 <6
13 N 7+9 2+12 5，10，14，17，24，61，83 7 7.53 5
14 N 7+9 5+10 11，41，63，65 4 4.30 7
15 N 7+9 5+12 34，38，55，70，81 5 5.38 8
), ArticleFig(id=1256536429627302900, tenantId=1146029695717560320, journalId=1256314692575182859, articleId=1256536356533166416, language=EN, label=Table 4, caption=

Statistical analysis of wheat quality traits of different groups

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项目
Item		 平均值
Mean		 标准差
SD		 变异系数
CV (%)		 类群Group
Ⅰ Ⅱ Ⅲ
蛋白质含量Protein content (%) 14.74 1.19 8.07 14.88ab 14.35b 15.22a
含水量Moisture content (%) 12.07 0.73 6.04 12.02ab 11.72b 12.33a
沉降值Sedimentation value (mL) 27.45 3.83 13.95 27.54a 26.97a 27.57a
湿面筋含量Wet gluten content (%) 30.56 2.29 7.49 30.59a 30.23a 31.17a
吸水率Water absorption rate (%) 58.06 3.44 5.92 57.84a 57.57a 58.62a
容重Test weight (g) 774.85 11.70 1.50 757.46c 771.97b 787.13a
类群内材料个数Number of materials within group 44.00 16.00 33.00
占总材料数的比例Proportion in total materials (%) 47.31 17.20 35.48
), ArticleFig(id=1256536430403249146, tenantId=1146029695717560320, journalId=1256314692575182859, articleId=1256536356533166416, language=CN, label=表4, caption=

不同类群小麦的品质性状差异分析

, figureFileSmall=null, figureFileBig=null, tableContent=
项目
Item		 平均值
Mean		 标准差
SD		 变异系数
CV (%)		 类群Group
Ⅰ Ⅱ Ⅲ
蛋白质含量Protein content (%) 14.74 1.19 8.07 14.88ab 14.35b 15.22a
含水量Moisture content (%) 12.07 0.73 6.04 12.02ab 11.72b 12.33a
沉降值Sedimentation value (mL) 27.45 3.83 13.95 27.54a 26.97a 27.57a
湿面筋含量Wet gluten content (%) 30.56 2.29 7.49 30.59a 30.23a 31.17a
吸水率Water absorption rate (%) 58.06 3.44 5.92 57.84a 57.57a 58.62a
容重Test weight (g) 774.85 11.70 1.50 757.46c 771.97b 787.13a
类群内材料个数Number of materials within group 44.00 16.00 33.00
占总材料数的比例Proportion in total materials (%) 47.31 17.20 35.48
), ArticleFig(id=1256536431200165892, tenantId=1146029695717560320, journalId=1256314692575182859, articleId=1256536356533166416, language=EN, label=Table 5, caption=

Variance analysis of wheat HMW-GS subunit variations among different groups

, figureFileSmall=null, figureFileBig=null, tableContent=
亚基类型
HMW-GS		 类群Ⅰ Group Ⅰ 类群Ⅱ Group Ⅱ 类群Ⅲ Group Ⅲ
材料数量
Number of materials		 频率
Frequency (%)		 材料数量
Number of materials		 频率
Frequency (%)		 材料数量
Number of materials		 频率
Frequency (%)
Glu-A1 1 33 75.00 14 87.50 20 60.61
Null 11 25.00 2 12.50 13 39.39
Glu-B1 14+15 2 4.55 1 6.25 2 6.06
7+8 16 36.36 0 0.00 12 36.36
7+9 26 59.09 15 93.75 19 57.58
Glu-D1 5+12 15 34.09 5 31.25 10 30.30
5+10 11 25.00 6 37.50 10 30.30
2+12 18 40.91 5 31.25 12 36.36
2+10 0 0.00 0 0.00 1 3.03
), ArticleFig(id=1256536432978550793, tenantId=1146029695717560320, journalId=1256314692575182859, articleId=1256536356533166416, language=CN, label=表5, caption=

不同类群小麦的HMW-GS亚基类型差异分析

, figureFileSmall=null, figureFileBig=null, tableContent=
亚基类型
HMW-GS		 类群Ⅰ Group Ⅰ 类群Ⅱ Group Ⅱ 类群Ⅲ Group Ⅲ
材料数量
Number of materials		 频率
Frequency (%)		 材料数量
Number of materials		 频率
Frequency (%)		 材料数量
Number of materials		 频率
Frequency (%)
Glu-A1 1 33 75.00 14 87.50 20 60.61
Null 11 25.00 2 12.50 13 39.39
Glu-B1 14+15 2 4.55 1 6.25 2 6.06
7+8 16 36.36 0 0.00 12 36.36
7+9 26 59.09 15 93.75 19 57.58
Glu-D1 5+12 15 34.09 5 31.25 10 30.30
5+10 11 25.00 6 37.50 10 30.30
2+12 18 40.91 5 31.25 12 36.36
2+10 0 0.00 0 0.00 1 3.03
), ArticleFig(id=1256536433817411606, tenantId=1146029695717560320, journalId=1256314692575182859, articleId=1256536356533166416, language=EN, label=Table 6, caption=

Parental pedigree analysis of 93 wheat varieties (lines)

, figureFileSmall=null, figureFileBig=null, tableContent=
编号
Code		 血缘
Genetic origin		 衍生品种（系）
Progeny varieties (lines)		 以衍生品种为亲本的品种（系）数量
Number of bred varieties (lines)
using progeny cultivars as parents		 占比
Percentage
(%)
1 周8425B 百农AK58 18 19.35
周麦11号、周麦12号等 4 4.30
2 豫麦2号 周麦22号 13 13.98
周麦9号、周麦13号、周麦17号、周麦28号等 7 7.53
3 豫麦2号+周8425B 周麦16号 14 15.05
周麦32、周麦26、周麦24等 9 9.68
4 优质血缘 郑麦366 4 4.30
新麦26号 4 4.30
西农979 4 4.30
其他Other 济麦、扬麦等其他材料 27 29.03
), ArticleFig(id=1256536434975039517, tenantId=1146029695717560320, journalId=1256314692575182859, articleId=1256536356533166416, language=CN, label=表6, caption=

93份小麦品种（系）的系谱分析

, figureFileSmall=null, figureFileBig=null, tableContent=
编号
Code		 血缘
Genetic origin		 衍生品种（系）
Progeny varieties (lines)		 以衍生品种为亲本的品种（系）数量
Number of bred varieties (lines)
using progeny cultivars as parents		 占比
Percentage
(%)
1 周8425B 百农AK58 18 19.35
周麦11号、周麦12号等 4 4.30
2 豫麦2号 周麦22号 13 13.98
周麦9号、周麦13号、周麦17号、周麦28号等 7 7.53
3 豫麦2号+周8425B 周麦16号 14 15.05
周麦32、周麦26、周麦24等 9 9.68
4 优质血缘 郑麦366 4 4.30
新麦26号 4 4.30
西农979 4 4.30
其他Other 济麦、扬麦等其他材料 27 29.03
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黄淮南片麦区新育成小麦品种（系）高分子量麦谷蛋白遗传多样性分析
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金艳 1 , 宋全昊 1 , 宋佳静 1 , 郜战宁 1 , 马红珍 1 , 陈亮 2 , 朱统泉 1
作物杂志 | 遗传育种·种质资源·生物技术 2026,42(2): 59-67
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作物杂志 | 遗传育种·种质资源·生物技术 2026, 42(2): 59-67
黄淮南片麦区新育成小麦品种（系）高分子量麦谷蛋白遗传多样性分析
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金艳1 , 宋全昊1 , 宋佳静1, 郜战宁1, 马红珍1, 陈亮2, 朱统泉1
作者信息
  • 1驻马店市农业科学院， 463000， 河南驻马店
  • 2西北农林科技大学农学院， 712100， 陕西杨凌

    • 金艳，主要从事小麦育种和栽培技术研究，E-mail：

通讯作者:

宋全昊，主要从事小麦育种和栽培技术研究，E-mail：
Genetic Diversity Analysis of Newly Developed Wheat Germplasm Based on HMW-GS in Southern Huang-Huai Wheat Region
Yan Jin1 , Quanhao Song1 , Jiajing Song1, Zhanning Gao1, Hongzhen Ma1, Liang Chen2, Tongquan Zhu1
Affiliations
  • 1Zhumadian Academy of Agricultural Sciences, Zhumadian 463000, Henan, China
  • 2College of Agronomy, Northwest A & F University, Yangling 712100, Shaanxi, China
出版时间: 2026-04-15 doi: 10.16035/j.issn.1001-7283.2026.02.007
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摘要
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为明确黄淮南片麦区新育小麦品种（系）高分子量麦谷蛋白亚基（HMW-GS）的组成与品质性状的关系，以该区近年育成的93份小麦品种（系）为材料，采用SDS-PAGE方法鉴定HMW-GS组成，并结合籽粒品质性状系统分析其HMW-GS分布及品质特征。结果表明，共检测到Glu-1 3个位点上共9种亚基类型，分别为Glu-A1位点的1（72.04%）和Null（27.96%）亚基，Glu-B1位点的7+9（64.52%）、7+8（30.11%）和14+15（5.38%）亚基，以及Glu-D1位点的2+12（37.63%）、5+12（32.26%）、5+10（29.03%）和2+10（1.08%）亚基。15种亚基组合类型中出现频率最高的是1/7+9/2+12（19.35%），组合1/7+8/5+10的分布频率为8.60%。依据品质性状将参试材料聚类为3个类群，类群Ⅰ、类群Ⅱ和类群Ⅲ分别占比47.3%、17.2%和35.5%。类群Ⅲ材料的蛋白质含量、吸水率和湿面筋含量等品质指标均表现最优，该类群中14+15、7+8和5+10亚基出现的频率分别为6.06%、36.36%和30.30%。参试材料中含有豫麦2号和周8425B两个骨干亲本血缘的品种（系）占比达70.96%。筛选出郑麦366、新麦26、济麦44和富麦916等8个品种携带优质亚基及组合。研究结果为黄淮南片麦区小麦品质育种的亲本选配提供了理论依据，对进一步优化HMW-GS组成和改良小麦品质具有重要参考价值。

黄淮南片麦区  /  小麦  /  高分子量麦谷蛋白亚基（HMW-GS）  /  籽粒品质

To clarify the relationship between high-molecular-weight glutenin subunits (HMW-GS) composition and quality traits in newly developed wheat varieties (lines) in the Southern Huang-Huai Wheat Region, a total of 93 newly developed wheat varieties (lines) from this region were used as materials. The HMW-GS composition was identified using SDS-PAGE, and their distribution and quality characteristics were systematically analyzed in conjunction with grain quality traits. The results showed that nine subunit types were detected across the three Glu-1 loci, specifically, subunits 1 (72.04%) and Null (27.96%) at the Glu-A1 locus; subunits 7+9 (64.52%), 7+8 (30.11%), and 14+15 (5.38%) at the Glu-B1 locus; and subunits 2+12 (37.63%), 5+12 (32.26%), 5+10 (29.03%), and 2+10 (1.08%) at the Glu-D1 locus. Among the 15 identified subunit combinations, the most frequent combination was 1/7+9/2+12 (19.35%), while the frequency of the combination 1/7+8/5+10 was 8.60%. Based on quality traits, the tested materials were clustered into three groups, with Group I, Group II, and Group III accounting for 47.3%, 17.2%, and 35.5%, respectively. Group III exhibited the best performance across all quality indicators such as protein content, water absorption rate, and wet gluten content; the frequencies of subunits 14+15, 7+8, and 5+10 in group III were 6.06%, 36.36%, and 30.30%, respectively. Varieties (lines) carrying the pedigree of two founder parents, Yumai 2 and Zhou 8425B, accounted for 70.96% of the tested materials. Eight varieties such as Zhengmai 366, Xinmai 26, Jimai 44, and Fumai 916, were screened for carrying high-quality subunits and combinations. These results provide a theoretical basis for parent selection in wheat quality breeding in the Southern Huang-Huai Wheat Region and serve as an important reference for further optimizing HMW-GS composition and improving wheat quality.

Southern Huang-Huai Wheat Region  /  Wheat  /  High-molecular-weight glutenin subunits (HMW- GS)  /  Grain quality
金艳, 宋全昊, 宋佳静, 郜战宁, 马红珍, 陈亮, 朱统泉. 黄淮南片麦区新育成小麦品种（系）高分子量麦谷蛋白遗传多样性分析. 作物杂志, 2026 , 42 (2) : 59 -67 . DOI: 10.16035/j.issn.1001-7283.2026.02.007
Yan Jin, Quanhao Song, Jiajing Song, Zhanning Gao, Hongzhen Ma, Liang Chen, Tongquan Zhu. Genetic Diversity Analysis of Newly Developed Wheat Germplasm Based on HMW-GS in Southern Huang-Huai Wheat Region[J]. Crops, 2026 , 42 (2) : 59 -67 . DOI: 10.16035/j.issn.1001-7283.2026.02.007
正文
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小麦（Triticum aestivum L.）是全球主要的粮食作物，在人类膳食中提供近1/5的能量和蛋白质[1]。小麦的加工品质主要由贮藏蛋白组分决定，包括麦谷蛋白和醇溶蛋白，麦谷蛋白是影响面团弹性和强度的关键因素，依据分子量大小可分为高分子量谷蛋白亚基（HMW-GS，70~90 kDa）和低分子量谷蛋白亚基（LMW-GS，20~45 kDa）[1-3]。二者通过复杂的分子间和分子内二硫键网络构建谷蛋白聚合体[4]，HMW-GS虽然含量仅占谷蛋白总量的10%左右，但在决定小麦加工品质方面发挥着核心调控作用，特别是在面包烘焙品质方面具有40%~75%的贡献率[5]。
HMW-GS的基因由位于第一同源群染色体长臂上的Glu-1位点编码，该位点包含Glu-A1、Glu-B1和Glu-D1 3个基因座，每个位点均有x型和y型2个紧密连锁的基因[6-7]。研究[8]表明，不同HMW-GS亚基对小麦品质的贡献存在显著差异，其亚基组成与组合方式通过调控面团弹性和延展性影响面粉的加工品质[9-10]。Glu-A1位点的1和2亚基对面包烘烤品质具有正向贡献[11-12]；Glu-B1位点的7+8亚基对蛋白质含量和面包烘烤体积具有正效应[13]；Glu-D1位点的5+10亚基能显著提升面团弹性和稳定时间[12-15]。相反，Glu-A1的null亚基、Glu-B1的6+8亚基及Glu-D1的2+12亚基通常与面包烘烤品质呈负相关[16]。目前，因Glu-B1位点的等位变异较为复杂，7+9亚基对品质的贡献存在差异，需通过分子层面深入探究其机制[17]。在亚基组合上，已鉴定出多组对籽粒品质有显著正向影响的优势等位基因组合，如1/7+8/5+12能显著提升馒头品质，表现为更高的蛋白质含量、湿面筋含量、稳定时间和感官评分等[18]。HMW-GS的组成分析及其与品质性状的关联研究已成为现代小麦品质育种中不可或缺的分子标记手段，为亲本选配和后代筛选提供了坚实的理论依据。
黄淮南片麦区作为我国最重要的小麦生产基地，尽管近年来通过育种攻关培育出如郑麦366和新麦26等优质强筋小麦品种，但优质亚基的分布频率仍然偏低[19]。值得关注的是，由于育种过程中对骨干亲本的过度依赖与重复利用，限制了小麦品质的进一步提升[20]。当前针对黄淮南片麦区小麦HMW-GS组成的研究[21-23]虽有开展，但重心多集中于优质亚基的鉴定与分布频率统计层面，关于该区域新育成品种的HMW-GS组成与蛋白质含量和沉降值等关键品质性状的系统性关联、品种品质多样性的聚类分析以及结合血缘遗传基础开展的HMW-GS组成效应研究鲜见报道。
本研究选取黄淮南片麦区93个新育成小麦品种（系）作为研究对象，通过SDS-PAGE技术鉴定其HMW-GS组成，并测定蛋白质含量、湿面筋含量和沉降值等6项关键品质指标，分析亚基及其组成分布特征及其与品质性状的关系，并结合聚类分析探讨遗传血缘对品质的影响，以期为该区域HMW-GS组成结构的遗传改良提供理论依据，为优质小麦品种亲本选配及通过分子标记聚合特定亚基提供参考。
1 材料与方法
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1.1 供试材料
供试材料为93份近年黄淮南片麦区审定或正在参试的普通小麦品种（系），能较好地反映黄淮南片麦区小麦资源的遗传多样性特征，由国家现代农业产业技术体系驻马店综合试验站收集并提供（表1）。HMW-GS亚基鉴定对照材料为中国春（Null/7+8/2+12）和西农979（1/7+8/2+12），分别编号为CK1和CK2。
1.2 试验设计
试验于2023-2024年度在小麦生长季种植在国家小麦产业技术体系驻马店试验站（32.59° N，114.2° E）的试验田进行，该地海拔110 m，土壤类型为黄褐土，前茬作物为玉米，土壤肥力中等。随机区组设计，3次重复，各材料的每个重复种植3行，单粒点播种植，行长2.0 m，行距0.3 m，株距0.1 m，田间管理措施统一同大田生产。自然成熟后每份材料选择3行的中间行进行人工整行收获与脱粒。
1.3 籽粒品质性状
采用DA7200型多功能近红外分析仪（Perten，瑞典）测定样品品质参数，检测指标包括含水量、吸水率、蛋白质含量、湿面筋含量、容重和沉降值，所有样品均进行3次重复测定。
1.4 HMW-GS的提取与鉴定
选取单粒饱满种子研磨成粉，参照韩文蕾[24]的纯化方法提取麦谷蛋白，随后采用10% SDS- PAGE凝胶电泳进行分离；分离胶由11.90 mL蒸馏水、10.00 mL 30%单体胶、7.50 mL Tris-HCl分离缓冲液（pH 8.8）、0.30 mL 10%十二烷基硫酸钠、0.30 mL 10%过硫酸铵和0.01 mL四甲基乙二胺组成；浓缩胶由6.80 mL蒸馏水、1.70 mL 30%单体胶、1.25 mL Tris-HCl浓缩缓冲液（pH 6.8）、0.10 mL 10%十二烷基硫酸钠、0.10 mL 10%过硫酸铵和0.01mL四甲基乙二胺组成。制胶时按先分离胶后浓缩胶的顺序灌注。样品上样量为10~20 μL/孔，初始以100 V电压电泳，待样品进入分离胶后调整为160 V，直至溴酚蓝指示剂接近凝胶底部时停止电泳。电泳结束后，用考马斯亮蓝R-250溶液染色（10~12 h），经蒸馏水脱色至背景清晰后拍照记录，最后通过与标准样品比对完成HMW-GS亚基组成的鉴定。
1.5 数据处理
利用Excel 2019完成试验数据整理与初步统计分析；通过RStudio软件进行系统聚类分析；依据聚类分组结果，运用SPSS 26.0对不同类群的性状指标开展方差分析（ANOVA）和Duncan多重比较检验。
2 结果与分析
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2.1 HMW-GS等位变异类型及频率
93份参试品种（系）共检测到Glu-1 3个位点上9种亚基类型（图1，表2），Glu-A1位点上检出2种亚基类型，分别是1（频率72.04%）和Null（频率27.96%）。Glu-B1位点上3种亚基类型，分别为7+9、7+8和14+15，频率分别为64.52%、30.11%和5.38%，7+9亚基的频率最高，共计60份材料。Glu-D1位点上有4种亚基类型，分别为2+12、5+12、5+10和2+10，分别占比37.63%、32.26%、29.03%和1.08%。其中2+10亚基类型占比最低，仅有1份材料。
2.2 HMW-GS亚基分布及其对小麦品质的影响
由表2表明，在Glu-A1位点上，含1亚基材料的蛋白质含量为14.75%，略高于Null的品种（系）。在Glu-B1位点上，3种亚基中含14+15亚基的品种（系）蛋白质含量为15.01%，优于其他2种亚基类型；含有7+8优质亚基的材料在沉降值、吸水率、含水量和容重较优，但在蛋白质含量和湿面筋含量上并没有表现出优势。在Glu-D1位点上，含有5+10亚基材料的蛋白质含量、湿面筋含量、沉降值、吸水率、含水量和容重6个品质指标均优于含有5+12和2+12亚基的材料。2+10亚基仅有1份材料，虽然其品质指标较好，但不具有统计的意义，有待进一步验证。
2.3 HMW-GS组合类型及品质评分
供试材料共检出15种亚基组合（表3），比例较高的前3位的亚基组合为1/7+9/2+12、1/7+9/5+12号和1/7+9/5+10，分别占参试品种（系）的19.35%、13.98%和12.90%。占比较低的组合为1/14+15/5+ 10、N/14+15/2+12和N/7+9/2+10，每个组合仅有1份材料（占1.08%）；其他亚基组合各占有一定比例。亚基组合1/7+8/5+10的频率为8.6%，对应济麦44、郑麦366、富麦916、郑麦113、郑麦163、安农859、驻麦305和新麦26共8份材料。参考韩文蕾[24]的评分标准进行评分，15种亚基组合的评分变幅为5~11分，其中品质评分在10分以上的组合类型有4种，分别为1/7+8/5+12、1/7+8/5+10、1/14+15/5+10和1/14+15/5+12，对应组合频率分别为9.68%（9份）、8.60%（8份）、3.23%（3份）和1.08%（1份），共计21份材料，占供试材料总数的22.58%。
2.4 参试小麦品质性状的聚类分析及品质差异
根据品质性状的数据对93份试验材料进行聚类分析，可聚为3类（图2）。类群Ⅰ包含周麦16、周麦22、驻麦762、郑麦366和新麦26等44个品种（系），占比47.3%；类群Ⅱ包含周麦32、新农9799、瑞华麦513、洛麦26和西农20等16个品种（系），占比17.2%；类群Ⅲ包含郑麦136、矮抗58、百农207和周麦36等33个品种（系），占比35.5%。
6个品质性状的变异系数为1.50%~13.95%，平均7.16%，沉降值的变异系数最大（13.95%），其次是蛋白质含量（8.07%）和湿面筋含量（7.49%）；含水量、吸水率和容重的变异系数均低于平均值，分别为6.04%、5.92%和1.50%（表4）。对聚类结果分组进行多重比较，3个类群间在蛋白质含量、含水量和容重3个性状间达显著差异水平；沉降值、湿面筋含量和吸水率均无显著性差异。类群Ⅰ的容重显著低于类群Ⅱ和类群Ⅲ，其他各项品质指标介于类群Ⅱ和类群Ⅲ之间。类群Ⅱ的材料数最少，其容重（771.97 g）与其他2个类群达到显著性差异，介于类群Ⅰ和类群Ⅲ之间，其余指标如蛋白质和湿面筋含量等5个指标均为最低。类群Ⅲ材料的6项品质指标均最高，且蛋白质含量、含水量和容重显著高于其他2个类群。
2.5 各类群小麦的HMW-GS亚基组成差异
不同类群间HMW-GS的亚基分布存在差异（表5）。在Glu-A1位点上，各类群携带1亚基的材料占比较Null亚基高，其中，类群Ⅰ、类群Ⅱ和类群Ⅲ分别为75.00%、87.50%和60.61%；Null亚基的出现频率则依次为25.00%、12.50%和39.39%。在Glu-B1位点上，类群Ⅰ和类群Ⅲ的亚基分布较为相似，14+15亚基占比分别为4.55%和6.06%，7+8亚基均为36.36%；7+9亚基占比分别为59.09%和57.58%。对比之下，类群Ⅱ的亚基组成高度单一，93.75%的材料携带7+9亚基，另有1份材料（6.25%）含有14+15亚基，7+8亚基完全缺失。结合品质分析数据，类群Ⅱ的蛋白质和湿面筋含量最低。在Glu-D1位点上，不同类群的亚基分布呈现多样性，类群Ⅰ以2+12亚基为主（40.91%），类群Ⅱ以5+10占比最高（37.50%），而类群Ⅲ中2+12亚基（36.36%）和5+10亚基（30.30%）分布均衡，2+10亚基低频出现（3.03%）。综合来看，品质较优的类群Ⅲ的单个亚基虽无明显优势，多介于类群Ⅰ和类群Ⅱ之间，但后两者在亚基组合上均存在不足。具体表现为，类群Ⅰ虽在7+8亚基上与类群Ⅲ相同，但其5+10亚基含量明显低于类群Ⅲ；类群Ⅱ的5+10亚基含量虽最高，却完全缺失7+8亚基。
2.6 参试小麦品种（系）的系谱来源分析
系谱分析结果见表6，部分材料的血缘有重叠（如泛麦26，其亲本来源有新麦26、西农979和百农AK58），因此频率占比统计值大于100%。93份参试材料的遗传基础主要来源于周8425B和豫麦2号。利用含周8425B血缘的百农AK58和周麦11号等衍生品种选育的后续品种（系）共22份，以含豫麦2号血缘的周麦22号和周麦13号等为亲本选育的品种（系）21份，利用同时含周8425B和豫麦2号血缘的周麦16、周麦26等衍生品种育成的有23份。总计含有这2个骨干亲本血缘的品种（系）66份，占比达70.96%，充分体现了其在育种体系中的核心地位。此外，直接以百农AK58（18份，19.35%）、周麦22号（13份，13.97%）和周麦16号（14份，15.05%）为亲本的材料占比最高。利用优质血缘品种（西农979、郑麦366和新麦26）作为亲本之一育成品种（系）12份，占比12.90%；以济麦系列和扬麦系列等其他血缘作为亲本之一的育成品种（系）共27份，占比29.03%。
3 讨论
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对黄淮南片麦区93份小麦材料的HMW-GS分析表明，Glu-1位点共鉴定出9种亚基类型和15种组合模式，与该麦区既往研究相比，本研究在亚基类型与组合数量分别与范家霖等[25]报道的8种类型、14种组合及张丽琴等[26]研究的10种类型、18种组合基本吻合，印证了本研究的可靠性；但显著低于耿惠敏[27]对714份材料的研究结果（13种类型、28种组合），可能是供试材料遗传广度或筛选标准的差异所致。在关键优质亚基1、7+8和5+10的频率分布方面，近20年来该麦区呈现显著演变趋势，李博等[23]研究显示，这3种亚基的频率分别为1.75%、77.13%和34.74%；张丽琴等[26]的研究结果中，频率分别为61.67%、21.59%和40.97%；而本研究进一步发现，其频率分别为72.04%、30.11%和29.03%。综合分析表明，该麦区优质亚基的演变规律如下：Glu-A1位点亚基1的频率持续逐步上升；Glu-B1位点7+8亚基的频率表现为先降后升；而Glu-D1位点5+10亚基的频率则呈先升后降的趋势。这一结果说明，5+10作为重要的优质亚基，其选育成效近期出现回落，在当前育种工作中亟待进一步加强。与亚基相对应的，亚基组合从李博等[23]报道的Null/7+8/2+12绝对主导（70.90%），转变为以优质亚基1为核心的类型。本研究与张丽琴等[26]的结果一致，1/7+9/2+12均为最高频组合，但理想组合1/7+8/5+10频率仍较低。与国外材料相比，黄淮南片麦区材料的HMW-GS多样性差距较为明显。李艳丽等[28]对67份美国小麦种质的研究鉴定出20种亚基和25种组合，优质亚基5+10频率达74.6%；田汉钊等[29]对外引270份小麦种质的研究发现19种亚基类型和72种组合，其中CIMMYT种质的2和5+10亚基频率分别为69.39%和44.90%，均远超黄淮南片麦区对应指标。这些差异为黄淮南片麦区小麦品质改良带来启示，可通过跨区域和国际种质交流，引入17+18和2等稀有优质亚基，提升5+10等关键亚基频率，为精准改良提供理论依据和资源支撑。
本研究系统分析了小麦HMW-GS亚基组合与品质性状的关系，发现93份材料中优质亚基组合（评分≥10分）占比达22.58%，其中1/7+8/5+10组合的出现频率（9.68%）与张丽琴等[26]的研究结果（9.69%）高度吻合，组合1/7+9/2+12（19.35%）和1/7+9/5+10（12.90%）的分布规律也与前人[25]研究一致，并验证了5+10亚基对品质的正向效应。值得注意的是，部分携带组合1/7+8/5+10的品种（如驻麦305），其实际品质性状表现却未达优质水平，显示出基因型与表型不一致的现象，揭示小麦品质形成除受HMW-GS影响外，还与LMW- GS、醇溶蛋白含量、环境因素及基因互作等多重因素密切相关，这一发现与相关研究[25]结论相互印证，深化了对小麦品质复杂调控机制的认识。
聚类分析在小麦品种分类中的应用具有重要意义[30]，本研究基于多个品质指标通过聚类将参试小麦分为3个类群。类群Ⅲ的蛋白质等各项指标均最高，但是黄淮南片麦区熟知和广泛应用的优质麦郑麦366和新麦26均在类群Ⅰ，一方面说明了类群划分的可行性，另一方面也说明了亚基组成与加工品质的优劣、蛋白质含量及蛋白质质量并不是简单的线性相关，而是存在着更为复杂的基因间互作和调控机理。5+12亚基在各类群中占比相近（30.30%~34.09%），但其他亚基及品质数据存在差异，进一步证实了优质亚基组合对品质的显著影响。王倩等[31]通过对49份山西小麦品种（系）的HMW-GS组成及其对品质的影响进行分析，也得到了相同结论。因此，在优质育种实践中，将优质亚基组合检测与品质性状鉴定早期相结合更具指导价值。本研究筛选出郑麦366、新麦26、济麦44和富麦916等8个品种携带优质亚基及组合，这些材料可作为优质亚基基因克隆的基础材料进行优质亚基的转育，也可直接作为杂交亲本用于小麦品种的品质改良。
亲本溯源发现93份供试材料中，含豫麦2号和周8425B 2个骨干亲本血缘的品种（系）达66份，占比高达70.96%。这一结果与李立等[32]对近10年黄淮麦区小麦新品系研究结果（70.1%）高度一致，表明近年来该麦区在小麦育种的亲本选择上仍高度依赖这2个骨干亲本，导致育成品种的遗传背景较为单一。虽然济麦、扬麦及其他未知血缘等也提供了部分遗传变异，但整体上仍难以突破骨干亲本带来的遗传限制。血缘结构的单一虽然保证了优良性状的稳定传递，但却严重限制了HMW-GS的多样性。因此，在保持骨干亲本优良农艺性状的同时，亟需通过分子标记辅助选择等手段，针对性地引入新的优质高分子量谷蛋白亚基类型，以丰富遗传基础，培育具有更优加工品质的新品种。
4 结论
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在Glu-1 3个位点共鉴定出9种亚基类型和15种组合，Glu-A1位点的1亚基出现频率显著较高（72.04%），Glu-B1位点7+8和14+15亚基分别占比30.11%和5.38%，Glu-D1位点5+10亚基占29.03%。亚基组合中比例较高的前3位是1/7+9/2+12（19.35%）、1/7+9/5+12（13.98%）和1/7+9/5+10（12.90%）。93份小麦材料的聚类分析将其分为3个类群，其中类群Ⅰ和Ⅲ的亚基分布相似（14+15：4.55%和6.06%；7+8：均为36.36%；7+9：59.09%和57.58%），而类群Ⅱ的亚基组成高度单一，93.75%的材料携带7+9亚基，2+10亚基仅1份材料，7+8亚基完全缺失。参试材料中含有豫麦2号和周8425B 2个骨干亲本血缘的品种（系）达66份，占比高达70.96%。
基金
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  • 河南省中央引导地方科技发展资金项目(Z20231811144)
  • 河南省科技攻关项目(242102111149)
  • 驻马店市科技创新青年专项(QNZX202320)
  • 国家现代农业产业技术体系建设专项(CARS-03)
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2026年第42卷第2期
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doi: 10.16035/j.issn.1001-7283.2026.02.007
  • 接收时间：2025-08-19
  • 首发时间：2026-04-30
  • 出版时间：2026-04-15
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  • 收稿日期：2025-08-19
  • 修回日期：2025-09-05
基金
河南省中央引导地方科技发展资金项目(Z20231811144)
河南省科技攻关项目(242102111149)
驻马店市科技创新青年专项(QNZX202320)
国家现代农业产业技术体系建设专项(CARS-03)
作者信息
    1驻马店市农业科学院， 463000， 河南驻马店
    2西北农林科技大学农学院， 712100， 陕西杨凌

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宋全昊，主要从事小麦育种和栽培技术研究，E-mail：
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2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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