欢迎访问作物学报，今天是
作物学报

作物学报 ›› 2010, Vol. 36 ›› Issue (06): 918-931.doi: 10.3724/SP.J.1006.2010.00918

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

数量性状基因定位研究中若干常见问题的分析与解答

李慧慧,张鲁燕,王建康*   

  1. 中国农业科学院作物科学研究所/农作物基因资源与基因改良国家重大科学工程/CIMMYT中国办事处，北京100081
  • 收稿日期:2010-01-18 修回日期:2010-02-28 出版日期:2010-06-12 网络出版日期:2010-04-20
  • 通讯作者: 王建康,E-mail:wangjk@caas.net.cn;jkwang@cgiar.org;Tel:010-82105846
  • 基金资助:

    本研究由国家自然科学基金项目（30771351）资助。

Analysis and Answers to Frequently Asked Questions in Quantitative Trait Locus Mapping

LI Hui-Hui,ZHANG Lu-Yan,WANG Jian-Kang*   

  1. Institute of Crop Sciences/National Key Facility for Crop Gene Resources and genetic Improvement/CIMMYT China Office,Chinese Academy of Agricultural Sciences,Beijing 100081,China
  • Received:2010-01-18 Revised:2010-02-28 Published:2010-06-12 Published online:2010-04-20
  • Contact: WANG Jian-Kang,E-mail:wangjk@caas.net.cn;jkwang@cgiar.org;Tel:010-82105846

PDF

3490

被引次数

182

摘要：

QTL作图是基因精细定位、克隆以及有效开展分子育种的基础，在利用QTL作图开展数量性状基因定位研究的过程中经常会碰到一些问题，与统计方法有关的一些问题包括LOD的统计学意义是什么？检测QTL的可信度和LOD临界值的关系是什么？如何评价不同的QTL作图方法？提高QTL检测效率的途径有哪些？与遗传参数估计有关的一些问题包括QTL的贡献率是如何计算出来的？如何确定QTL有利等位基因的来源？选择基因型分析的有效性如何？复合性状是否适宜于QTL作图？与作图群体及遗传图谱有关的一些问题包括QTL作图群体中表型数据是否要求服从正态分布？加密标记是否可以显著提高QTL检测功效？缺失分子标记对QTL作图有什么影响？奇异分离标记对QTL作图有什么影响？文章试图结合笔者多年研究工作对这12个有共性的常见问题做出分析和解答，以供科研工作者参考。

关键词: 数量性状, QTL作图, 完备区间作图, 似然比检验, 功效分析

Abstract:

QTL mapping is an important step in gene fine mapping, map-based cloning, and the efficient use of gene information in molecular breeding. Questions are frequently met and asked in the application of QTL mapping in practical genetic populations. Questions related to statistical method of QTL mapping are: what does LOD score mean? What is the relationship between the reliability of detected QTL and the LOD threshold? How to evaluate different QTL mapping methods? How to improve the QTL detection power? Questions related to genetic parameter estimation are: how to calculate the phenotypic variance explained by each detected QTL? How to determine the source of favorable alleles at detected QTL? How efficient is the selective genotyping? Can composite traits be used in QTL mapping? Questions related to linkage map and mapping populations are: does the phenotype of a trait in interest have to follow a normal distribution? Does the increase in marker density greatly improve QTL mapping power? What effects will missing markers have in QTL mapping? What effects will segregation distortion have in QTL mapping? Our objective in this paper was to give an analysis and answer to each of the 12 frequently asked questions, based on our studies in past several years.

Key words: Quantitative trait, QTL mapping, Inclusive composite interval mapping, Likelihood ratio test, Power analysis

[1]Lynch M, Walsh B. Genetic and Analysis of Quantitative Traits. Sunderland, MA: Sinauer Associates, 1998
[2]Doerge R W. Mapping and analysis of quantitative trait loci in experiment populations. Nat Rev Genet, 2002, 3: 43-52
[3]Zhai H-Q (翟虎渠), Wang J-K (王建康). Applied Quantitative Genetics (应用数量遗传). Beijing: China Agricultural Science and Technology Press, 2007 (in Chinese)
[4]Wang J-K (王建康). Inclusive composite interval mapping of quantitative trait genes
[J].Acta Agron Sin(作物学报.2009, 35(2):239-245
[5]Lander E S, Botstein D. Mapping Mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics, 1989, 121: 185-199
[6]Zeng Z B. Precision mapping of quantitative trait loci. Genetics, 1994, 136: 1457-1468
[7]Li H, Ye G, Wang J. A modified algorithm for the improvement of composite interval mapping. Genetics, 2007, 175: 361-374
[8]Li H, Ribaut J M, Li Z, Wang J. Inclusive composite interval mapping (ICIM) for digenic epistasis of quantitative traits in biparental populations
[J].Theor Appl Genet
[9]Zhang L, Li H, Li Z, Wang J. Interactions between markers can be caused by the dominance effect of QTL
[J].Genetics
[10]Goffinet P, Loisel B, Lawrent B. Testing in normal mixture models when the proportions are known
[J].Biometrika
[11]Churchill G A, Doerge R W. Empirical threshold values for quantitative trait mapping. Genetics, 1994, 138: 963-971
[12]Chen L, Storey J D. Relaxed significance criteria for linkage analysis
[J].Genetics
[13]Li H.
[J].Hearne S, Bänziger M, Li Z, Wang J. Statistical properties of QTL linkage mapping in biparental genetic populations. Heredity
[14]Wang J, Wan X, Crossa J, Crouch J, Weng J, Zhai H, Wan J. QTL mapping of grain length in rice (Oryza sativa L.) using chromosome segment substitution lines. Genet Res, 2006, 88: 93-104
[15]Wang J, Wan X, Li H, Pfeiffer W, Crouch J, Wan J. Application of identified QTL-marker associations in rice quality improvement through a design breeding approach
[J].Theor Appl Genet
[16]Tinker N A, Mather D E, Rossnagel B G, Kasha K J, Kleinhofs A, Hayes P M, Falk D E, Ferguson T, Shugar L P, Legge W G, Irvine R B, Choo T M, Briggs K G, Ullrich S E, Franckowiak J D, Blake T K, Graf R J, Dofing S M, Saghai-Maroof M A, Scoles G J, Hoffman D, Dahleen L S, Kilian A, Chen F, Biyashev R M, Kudrna D A, Steffenson B J. Regions of the genome that affect agronomic performance in two-row barley
[J].Crop Sci
[17]Zhang L P, Lin G Y, Niño-Liu D, Foolad M R. Mapping QTLs conferring early blight (Alternaria solani) resistance in a Lycopersicon esculentum × L. hirsutum cross by selective genotyping. Mol Breed, 2003, 12: 3-19
[18]Wingbermuehle W J, Gustus C, Smith K P. Exploiting selective genotyping to study genetic diversity of resistance to Fusarium head blight in barley
[J].Theor Appl Genet
[19]Docherty S J, Butcher L M, Schalkwyk L C, Plomin R. Applicability of DNA pools on 500 K SNP microarrays for cost-effective initial screens in genome wide association studies
[J].BMC Genomics
[20]Sun Y, Wang J, Crouch J H, Xu Y. Efficiency of selective genotyping for genetic analysis and crop improvement of complex traits. Mol Breed, 2010 (in press)Wang Y.
[J].Li H, Zhang L, Lü W, Wang J. On the use of composite traits in quantitative trait locus mapping. GeneticsZhang L, Wang S, Li H, Deng Q, Zheng A, Li S, Li P, Li Z, Wang J. Effects of missing markers and segregation distortion on QTL mapping in F2 populations. Theor Appl Genet, 2010 (submitted)
[1] 王靖天, 张亚雯, 杜应雯, 任文龙, 李宏福, 孙文献, 葛超, 章元明. 数量性状主基因+多基因混合遗传分析R软件包SEA v2.0[J]. 作物学报, 2022, 48(6): 1416-1424.
[2] 王小雷, 李炜星, 欧阳林娟, 徐杰, 陈小荣, 边建民, 胡丽芳, 彭小松, 贺晓鹏, 傅军如, 周大虎, 贺浩华, 孙晓棠, 朱昌兰. 基于染色体片段置换系群体检测水稻株型性状QTL[J]. 作物学报, 2022, 48(5): 1141-1151.
[3] 黄莉, 陈玉宁, 罗怀勇, 周小静, 刘念, 陈伟刚, 雷永, 廖伯寿, 姜慧芳. 花生种子大小相关性状QTL定位研究进展[J]. 作物学报, 2022, 48(2): 280-291.
[4] 王吴彬, 童飞, KHAN Mueen Alam, 张雅轩, 贺建波, 郝晓帅, 邢光南, 赵团结, 盖钧镒. 大豆根部水压胁迫耐逆指数遗传体系解析[J]. 作物学报, 2021, 47(5): 847-859.
[5] 李书宇, 黄杨, 熊洁, 丁戈, 陈伦林, 宋来强. 甘蓝型油菜早熟性状QTL定位及候选基因筛选[J]. 作物学报, 2021, 47(4): 626-637.
[6] 蒙姜宇, 梁光伟, 贺亚军, 钱伟. 甘蓝型油菜耐盐和耐旱相关性状的QTL分析[J]. 作物学报, 2021, 47(3): 462-471.
[7] 孙志广, 王宝祥, 周振玲, 方磊, 迟铭, 李景芳, 刘金波, Bello Babatunde Kazeem, 徐大勇. 水稻萌发耐淹性种质资源筛选及QTL定位[J]. 作物学报, 2021, 47(1): 61-70.
[8] 姜树坤,王立志,杨贤莉,李波,母伟杰,董世晨,车韦才,李忠杰,迟力勇,李明贤,张喜娟,姜辉,李锐,赵茜,李文华. 基于高密度SNP遗传图谱的粳稻芽期耐低温QTL鉴定[J]. 作物学报, 2020, 46(8): 1174-1184.
[9] 王小雷, 李炜星, 曾博虹, 孙晓棠, 欧阳林娟, 陈小荣, 贺浩华, 朱昌兰. 基于染色体片段置换系对水稻粒形及千粒重QTL检测与稳定性分析[J]. 作物学报, 2020, 46(10): 1517-1525.
[10] 蒙姜宇,傅鹰,贺亚军,钱伟. 利用DH和IF2群体检测油菜籽粒油酸、亚油酸、亚麻酸含量QTL[J]. 作物学报, 2019, 45(9): 1338-1348.
[11] 童治军,张谊寒,陈学军,曾建敏,方敦煌,肖炳光. 雪茄烟品种Beinhart1000-1赤星病抗性基因的QTL定位[J]. 作物学报, 2019, 45(3): 477-482.
[12] 李英双,胡丹,聂蛟,黄科慧,张玉珂,张园莉,佘恒志,方小梅,阮仁武,易泽林. 甜荞株高和茎粗的遗传分析[J]. 作物学报, 2018, 44(8): 1185-1195.
[13] 郭海平, 孙高阳, 张晓祥, 闫鹏帅, 刘坤, 谢惠玲, 汤继华, 丁冬, 李卫华. 基于SSSL群体的玉米穗下节间长QTL分析[J]. 作物学报, 2018, 44(04): 522-532.
[14] 贺亚军, 吴道明, 傅鹰, 钱伟. 利用DH和IF2群体检测甘蓝型油菜株高相关性状QTL[J]. 作物学报, 2018, 44(04): 533-541.
[15] 方雅洁，朱亚军，吴志超，陈凯，申聪聪，石英尧，徐建龙. 全基因组关联定位籼稻种质资源外观和加工品质QTL[J]. 作物学报, 2018, 44(01): 32-42.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
京ICP备15008789号-2