Soybean plant height QTL mapping and meta‐analysis for mining candidate genes

Plant height is closely related to seed yield of soybean. The goal of this study was to identify important loci affecting soybean plant height using meta‐analysis based on a reference physical map. Plant height related to QTLs was mapped across eight years with a RIL population by WinQTLCart v2.5. 182 QTLs related to plant height of soybean from database and our research were collected, and each QTL was projected onto the soybean physical map by software BioMercator v2.1. The confidence interval of meta‐QTL ranged from 0.09 to 5.07 Mb, and the mean phenotypic variance ranged from 4.9% to 73.0%. Furthermore, 4,259 candidate genes were located in these consensus QTLs, and 40 of them were involved in the plant growth and stem elongation and annotated as plant hormone signal transduction (pathway ID ko04075) in KEGG pathway. These results would lay a foundation for fine mapping of QTLs/genes related to plant height and marker‐assisted selection for breeding in soybean.     

Progress of genome wide association study in domestic animals

ABSTRACT: Domestic animals are invaluable resources for study of the molecular architecture of complex traits. Although the mapping of quantitative trait loci (QTL) responsible for economically important traits in domestic animals has achieved remarkable results in recent decades, not all of the genetic variation in the complex traits has been captured because of the low density of markers used in QTL mapping studies. The genome wide association study (GWAS), which utilizes high-density single-nucleotide polymorphism (SNP), provides a new way to tackle this issue. Encouraging achievements in dissection of the genetic mechanisms of complex diseases in humans have resulted from the use of GWAS. At present, GWAS has been applied to the field of domestic animal breeding and genetics, and some advances have been made. Many genes or markers that affect economic traits of interest in domestic animals have been identified. In this review, advances in the use of GWAS in domestic animals are described.     

低磷胁迫下大豆主要农艺性状的QTL定位

利用来自铁一7555(耐低磷种质)和凤59-15的重组自交系群体(110个家系),通过盆栽试验研究与耐低磷有关的性状,并进行耐低磷性状的QTL定位.对所调查的相对株高、相对根系干质量、相对叶中磷含量和相对根系磷含量4个性状进行分析,结果表明,在N和O两个连锁群上共检测到3个QTL与耐低磷有关.分别可解释所对应性状表型变异的4.84%～18.2%,其中2个QTL的增效基因来自亲本铁-7555,1个QTL的增效基因来自亲本凤59-15.     

辣椒分子连锁遗传图谱的构建及抗疫病QTL定位

以抗疫病材料perennial和感疫病材料83-60杂交得到的F2群体144个单株为试材,利用AFLP、RAPD、SSR等分子标记,采用JoinMap3.0构建辣椒分子连锁遗传图谱,该图谱包括12个连锁群,70个标记位点,其中AFLP标记54个,RAPD标记15个,SSR标记1个,覆盖长度为429.02cM,平均图距为6.13cM,连锁群长度在4.30～85.85cM之间。对F2群体进行辣椒疫病的室内人工接种,利用Windows QTL Cartographer2.0软件进行QTL分析,在第4连锁群上检测到两个QTL,解释表型差异的贡献率分别为9.5%和16.4%。     

爆裂玉米3个膨爆特性的非条件和条件QTL分析

膨化倍数(PF)、膨化体积(PV)和爆花率(PR)是爆裂玉米的主要品质指标。本研究以普通玉米自交系丹232和爆裂玉米自交系N04杂交构建的259个F2:3家系为定位群体,采用完全随机区组设计在郑州夏播条件下测定了3个膨爆特性指标。利用覆盖玉米10条染色体的183对多态性分子标记构建连锁图,采用复合区间作图(CIM)方法对各性状进行非条件QTL定位分析,采用条件遗传统计软件对PF进行条件QTL分析。3个膨爆特性指标非条件QTL定位共检测出31个QTL,单个QTL的贡献率为3.09%￣12.46%,累计贡献率为51.90%、77.37%和61.45%。在8个标记区间(占42.11%)同时检测到控制2￣3个性状的QTL。加性和部分显性在膨爆特性的遗传中起主要作用,同时存在显性和超显性基因效应。条件QTL定位结果表明,PV和PR以不同方式显著影响PF的QTL表达,PV比PR更重要。     

两个水稻DH群体发芽期和幼苗前期耐碱性状QTL定位比较

利用两个不同的加倍单倍体群体,在0.15%Na2CO3胁迫下,以发芽期和幼苗前期的发芽势（GE）等10个性状碱害相对值作为耐碱指标,进行耐碱性状QTL定位比较。碱害相对值相关分析表明,多个性状的碱害相对值存在显著或极显著相关。采用QTLMapper1.6统计软件对碱害相对值进行QTL分析。DH-1群体定位到10个主效QTL和15个上位性QTL,DH-2群体定位到14个主效QTL和15个上位性QTL。两群体定位列线比对发现：1个控制相对根长的QTL,qRRL3-1,两群体定位在第3染色体对应的区域（CT339-G62和RM7-RM3280）。其他性状两群体没有定位在相同的区域,但存在多个重要的数量基因座位,如CT158-CT550、RM3755-RM418和RM1349-RM1061等区域。在这些相同基因座位上两群体都检测到控制不同性状的主效QTL或上位性QTL,耐碱性QTL可能存在多效性、连锁性,在不同遗传背景下加性效应和上位性效应可以相互转化。多个QTL不仅与水稻耐碱性有关,还与多种抗逆性有关。这些结果将有利于耐碱性分子机制的剖析和强耐碱性水稻品种的选育。     

大豆磷效率QTL定位及互作分析

磷效率是复杂的数量性状,有一系列基因参与其中.利用科丰1号×南农1138-2衍生的重组自交系群体NJRIKY,对影响大豆磷效率的加性和上位性QTL同时进行定位,比较在两种磷条件下的大豆磷效率QTL的表达差异.采用5个指标评估大豆的磷效率,包括:茎干重、根干重、根冠比、磷利用效率和磷吸收效率.结果表明:在高磷和低磷条件下在8个连锁群上分别检测到3个和12个加性的QTL,可解释4.0%～13.8%的表型变异;另外,在高磷和低磷条件下,分别检测到12对和7对互作的QTL,可解释3.3%～19.9%的表型变异.本研究的QTL定位结果为进一步了解大豆在不同磷条件下的磷效率遗传机制提供了重要的线索.     

油菜种子含油量GWAS分析及位点整合系统构建

含油量是油菜最重要的性状之一, 目前已有较多的油菜种子含油量定位研究, 然而各研究系统相对独立, 群体与标记的差别使得难以比较不同研究结果。本研究连续4年种植了一个含308份材料的油菜自然群体, 结合60K SNP芯片数据对种子含油量进行了全基因组关联分析(GWAS), 并将所鉴定的显著位点与早前2个自然群体及10个分离群体鉴定到的位点进行全基因组比较与整合。结果显示, 通过GWAS共检测到8个与种子含油量显著关联的位点, 单个位点解释的表型变异度为3.22%~5.13%; 结合其他12个群体的定位结果, 共获得193个油菜含油量整合位点, 分布于油菜的所有19条染色体, A亚基因组平均每条染色体有13个位点, 显著高于C亚基因组(7个)。对不同群体鉴定结果的比较发现, 7个整合区间能在至少3个群体中被检测到, 均位于A亚基因组染色体(A01、A02、A03、A06、A08、A09和A10)上, 其中有3个与C亚基因组上的区间存在同源性, 在这3个区间中共鉴定到26个已知的油脂代谢相关基因。本研究将193个位点锚定到法国公布的甘蓝型油菜参考基因组, 构建了一个可视的油菜种子含油量位点全基因组整合系统, 可为油菜种子含油量重要位点的确定提供帮助, 并为制定提高油菜种子含油量的育种方案提供参考。     

普通菜豆籽粒大小与形状的QTL定位

普通菜豆是世界上最重要的食用豆类作物之一,其籽粒大小和形状与产量及外观品质密切相关。本研究以来自安第斯基因库的大粒品种龙270709和来自中美基因库的小粒品种F5910配置杂交组合,获得的F2分离群体分别在哈尔滨大田与北京昌平温室种植,对百粒重、粒长、粒宽、粒厚、长宽比和长厚比6个籽粒性状进行了相关性分析和QTL定位。相关性分析表明,百粒重与粒长、粒宽、粒厚、长宽比、长厚比5个衡量籽粒大小和形状的性状均显著正相关。利用基于完备区间作图方法的Ici Mapping 4.1进行QTL定位,哈尔滨环境下定位到38个与百粒重、粒长、粒宽、粒厚、长宽比、长厚比相关的QTL,表型贡献率介于2.39%~17.37%之间,分布在除第1染色体外的其余10条染色体上;北京昌平环境下定位到21个上述性状的QTL,表型贡献率介于5.92%~22.53%之间,分布在第1、第3、第6、第7、第8、第9和第11染色体上。其中,百粒重QTLSW7与SW7’,SW6.1与SW6’,粒长QTLSL6.1与SL6.1’,粒厚QTLSH11与SH11’在2个环境下的标记区间重叠或者重合,SW7、SW6.1、SL6.1、SW6’和SL6.1’的表型贡献率在10%以上。     

Quantitative trait loci (QTL) affecting sugars, organic acids and other biochemical properties possibly contributing to flavor, identified in four advanced backcross populations of tomato

Although the Advanced Backcross strategy has proven very useful for QTL detection in tomato, it has been used mainly in identifying QTL for agronomic traits such as yield, color, etc. Tomato flavor is an important quality characteristic, yet it has been difficult to assess flavor or traits that affect it. In this study the AB-QTL strategy was applied to four advanced backcross populations to identify QTL for biochemical properties that may contribute to the flavor of processed tomatoes, such as sugars and organic acids. A total of 222 QTL were identified for 15 traits, including flavor as assessed by a taste panel. Correlations of certain biochemicals with flavor and possible methods of assessing and improving flavor are discussed. In particular, QTL with very significant effects associated with the ratio of sugars/glutamic acid, a trait highly correlated with improved flavor, have been identified as good targets for future work in improving the flavor of tomatoes. This revised version was published online in August 2006 with corrections to the Cover Date.