利用海岛棉染色体片段导入系定位衣分和籽指QTL

以染色体片段导入系IL-15-5和IL-15-5-1构建的F2和F2:3分离群体,利用SSR标记对数量性状衣分和籽指QTL进行了定位。应用复合区间作图法分析两个组合的774个F2单株和F2:3家系衣分和籽指,检测到2个衣分的QTL,1个籽指的QTL。衣分QTLqLP-15-1在两世代中都被检测到,位于相同的分子标记置信区间JESPR152～NAU3040,置信的遗传距离分别为5.40cM和3.20cM;qLP-15-2只在F2:3中被检测到,位于分子标记NAU5302～NAU2901之间,置信的遗传距离为0.08cM。籽指QTLqSI-15-1在F2和F2:3中都被检测到,分别位于分子标记NAU2814～NAU3040和JESPR152～NAU3040,置信的遗传距离分别为6.70cM和5.70cM。利用染色体片段导入系能准确地定位产量组分的QTL,为棉花产量的分子设计育种奠定基础。     

不同统计遗传模型QTL定位方法应用效果的模拟比较

分子遗传和数量遗传的结合,发展了QTL定位研究。随着定位方法与软件的建立和完善,QTL定位的研究越来越多。准确定位的QTL可用于分子标记辅助选择和图位克隆,而假阳性QTL将误导定位信息的应用。本文分析了迄今主要定位方法(软件)对于各种遗传模型数据的适用性。应用计算机模拟4类遗传模型不同的重组自交系群体(RIL),第一类只包含加性QTL;第二类包含加性和上位性互作QTL;第三类包含加性QTL和QTL与环境互作效应;第四类包含加性、上位性互作QTL和QTL与环境互作效应。每类按模拟QTL个数不同设两种情况,共分为8种数据模型(下称M-1～M-8)。选用WinQTLCart 2.5的复合区间作图(下称CIM)、多区间作图前进搜索(MIMF)、多区间作图回归前进选择(MIMR)、IciMapping 2.0的完备复合区间作图(ICIM)、MapQTL 5.0的多QTL模型(MQM)以及QTLnetwork 2.0的区间作图(MCIM)6种程序对8种不同遗传模型的RIL进行QTL检测。结果表明,不同程序适用的遗传模型范围不同。CIM和MQM只适于检测第一类模型;MIMR、MIMF和ICIM只适于检测第一类和第二类模型;只有MCIM适于检测所有4类遗传模型;因而不同遗传模型数据的最适合检测程序不同。由于未知实际数据的遗传模型,应采用在复杂模型程序,如QTLnetwork 2.0,扫描基础上的多模型QTL定位策略,对所获模型用相应模型软件进行验证。     

Identification of quantitative trait loci for seed traits and floral morphology in a field-grown Lolium perenne × Lolium multiflorum mapping population

Lolium perenne L. (perennial ryegrass), and Lolium multiflorum Lam. (annual or Italian ryegrass), differ in several traits related to seed yield. Generally, L. multiflorum spikes are larger than L. perenne spikes, and have more spikelets, more florets per spikelet, larger seeds and awns. The greater number of spikelets and florets and larger seeds are associated with higher seed yield in L. multiflorum . Ryegrass ( Lolium sp.) cultivars are produced by seed multiplication and understanding the genetics of seed production traits would aid in plant improvement. A total of 30 QTL for seed production related traits were identified in this study. The QTLs were primarily located on linkage groups 2 and 4 which appear to be the most important for distinguishing L.   multiflorum and L. perenne . These QTL will be used to develop molecular markers for marker-assisted breeding and screening of L. perenne seed lots to detect seed contamination with L. multiflorum .     

晋大52×晋大57 RIL群体重要农艺性状的QTL定位

以晋大52为母本、晋大57为父本及其176个RIL群体后代为材料,应用WinQTLCart V2.0软件采用复合区间作图法对所选取对象(LOD2.5)的生育期、开花日数、单株质量、单株粒重、单株粒数、单株荚数、百粒重、株高、茎粗、主茎节数、分枝数、结荚高度等12个农艺性状进行QTL定位分析。结果表明:效应最大的QTL可解释的遗传变异分别为md221.32%、fd248.11%、wp17.01%、swpp130.67%、nppp241.32%、spp18.56%、sw441.46%、ph152.51%、st135.14%、snn231.60%、bn225.43%、hp116.31%。检测到的30个QTL分布于山西农业大学大豆研究实验室建立的5个连锁群上,大多数性状聚集在c2(Dla)、c5(C2)、c7(M)等连锁群上,部分QTL在连锁群上的位置相同,即为同一位点,这类位点共有5个,除去重复计算部分,实际位点数为23个。     

大豆农艺性状的QTL分析(摘要)(英文)

[目的]分析大豆农艺性状的QTL,为探讨大豆的遗传机制及进行遗传育种提供参考。[方法]以栽培大豆"合丰25"为母本和半野生大豆"新民6号"为父本杂交得到的122个F8代重组自交系为试材,应用复合区间作图法对蛋白质含量、脂肪含量、产量、百粒重、生育期5个数量性状进行QTL定位和遗传效应分析。蛋白质、脂肪含量均使用近红外谷物分析仪测定。[结果]控制蛋白质含量、脂肪含量、产量、百粒重、生育期性状的4、4、1、2、5个共16个QTL位点,遗传贡献率在7.4%～33.7%。其中,遗传贡献率较大的主效QTL有分别位于I连锁群上Satt562-Sat_219、Sat_219-Satt496、Sat_219-Satt496区间的3个控制蛋白质含量的QTL位点,其遗传贡献率分别为29.15%、33.70%和31.67%,且均为来自母本合丰25的加效基因,还有位于O连锁群上Satt477-Satt331、Satt331-Satt153区间的2个控制生育期QTL位点,其遗传贡献率分别为24.69%和24.96%,也是来自母本合丰25的加效基因。另外,6个分别距M连锁群Satt175(蛋白质)、A1连锁群Satt684(油分)、F连锁群Satt348(油分)、J连锁群Sat_412(油分)、C1连锁群Sat_416(百粒重)、C1连锁群Sat_416(生育期)标记仅有0.01cm的QTL位点。[结论]定位了影响蛋白质含量、油分含量、产量、百粒重和生育期5个重要农艺性状的QTL位点。     

Stability of QTL Across Environments and QTL-by-Environment Interactions for Plant and Ear Height in Maize

Better understanding of genotype-by-environment interaction （GEI） is expected to provide a solid foundation for genetic improvement of crop productivity especially under drought-prone environments. To elucidate the genetic basis of the plant and ear height, 2 F2：3 populations were derived from the crosses of Qi 319 × Huangzaosi （Q/H） and Ye 478 × Huangzaosi （Y/H） with 230 and 235 families, respectively, and their parents were evaluated under 3 diverse environments in Henan, Beijing, and Xinjiang, China during the year of 2007 and 2008, and all the lines were also evaluated under water stress environment. The mapping results showed that a total of 21 and 12 QTLs were identified for plant height in the Q/H and Y/H population, respectively, and 24 and 13 QTLs for ear height, respectively. About 56 and 73% of the QTLs for 2 traits did not present significant QTL-by-environment interaction （QE1） in the normal joint analyses for Q/H and Y/H population, respectively, and about 73% of the QTLs detected did not show significant QEI according to joint analyses for stress condition in Q/H. Most of the detected major QTLs exhibited high stability across different environments. Besides, several major QTLs were detected with large and consistent effect under normal condition （Chr. 6 and 7 in Q/H; Chr. 1, 3 and 9 in Y/H）, or across 2 water regimes （Chr. 1, 8 and 10 for in Q/H）. There were several constitutive QTLs （3 for Q/H and 1 for Y/H） with no or minor QTL-by-environment for the 2 populations. Finally, we found several genomic regions （Chr. 1, 10, etc.） to be co-located across the populations, which could provide useful reference for genetic improvement of these traits in maize breeding programs. Comparative genomic analysis revealed that 3 genes/genetic segments associated with plant height in rice were orthologous to these 3 identified genomic regions carrying the major QTLs for plant and ear height on Chr. 1, 6, and 8, respectively.     

小麦株高发育动态QTL定位

【目的】检测小麦生长发育过程中控制株高的条件QTL和非条件QTL,揭示株高发育的分子遗传机理,获得更多调控株高的遗传信息。【方法】以两个主栽小麦品种花培3号和豫麦57的F1获得的含有168个株系的DH(双单倍体)群体为材料,自拔节至开花期,每隔7d取样测定株高(分蘖节至穗顶端)。根据3个环境下株高的表型数据和含有323个位点的分子遗传图谱,采用条件复合区间作图法进行小麦株高的发育动态QTL分析。【结果】共检测到18个非条件QTL和10个条件QTL。在18个非条件QTL中,Qph5D-1在前4个取样期(3月9日—4月23日)均能检测到,Qph4D-1在后3个取样期均能检测到,分别是挑旗前、后阶段影响株高的主效QTL,其它非条件QTL在少数几个取样期发现或效应很小。10个条件QTL中,Qph5D-1在两个阶段均能检测到,总贡献率为30.1%。Qph4B在5月1日—5月8日检测到,贡献率为20.3%,对后期株高的净增长量起主要作用。其它条件QTL只在一个阶段出现或效应较小。【结论】影响株高的QTL数目及其QTL表达效应在株高形成的过程中有很大的变化,说明控制株高生长的数量性状基因以一定的时空方式表达。在小麦育种中,本研究结果可为株高的分子标记辅助选择提供理论依据。     

猪肌内脂肪酸成分的研究进展

脂肪酸成分在猪的育种上是一个重要的经济性状,不仅影响猪肉品质,而且对人类的健康也有十分重要的作用。本文综述了近几年来国内外学者在猪肌内脂肪酸成分方面的研究进展。