大豆叶绿素含量QTL定位及候选基因预测

叶绿素是调节光合作用的关键色素,对籽粒形成有着重要作用。本研究以美国半矮秆大豆Charleston为母本,东北地区主栽品种东农594为父本杂交衍生的147个重组自交系群体为材料,基于经SLAF测序获得的大豆高密度遗传图谱,利用复合区间作图法(CIM)、多重区间作图法(MIM)和完备区间作图法(ICIM)对大豆叶绿素含量进行QTL联合定位分析,并结合大豆基因组基因注释信息对QTL区段内的候选基因进行预测。利用CIM算法定位出2个QTL,表型遗传贡献率分别为6%和9.3%。利用MIM算法定位到了1个QTL,表型遗传贡献率为8.1%。利用ICIM算法定位到了1个QTL,表型遗传贡献率为7.76%。其中qchl-G-1被CIM和MIM两种算法同时检测到。在上述3个QTL区段内共含有151个基因,根据大豆基因组基因注释信息,筛选到了3个与叶绿素相关的候选基因,这些结果为叶绿素含量的遗传剖析和标记辅助育种提供理论基础,有利于分子辅助育种的发展。     

基于Meta分析的大豆倒伏性相关QTL的整合

倒伏性是大豆高产、稳产和优质的主要限制因子之一,是控制大豆产量性状的主要数量性状。本研究共搜集整理了16年来已经报道的与大豆倒伏性有关的59个QTL,以2004年发布的大豆公共遗传连锁图谱soymap2为参考图谱,通过软件BioMercator2.1的映射,将大豆倒伏性QTL整合到soymap2上,并利用Meta进行元分析进而推断QTL位置,计算提取真正有效的QTL位点,共得到11个与大豆倒伏性相关的真实主效QTL位点,分布于5个连锁群上。本研究结果为倒伏性相关基因的精细定位和克隆奠定了基础。     

利用选择性基因分型方法定位大豆分枝数QTL

分枝数是大豆重要的农艺性状之一。对控制大豆分枝数的基因位点进行定位具有重要的理论和应用价值。本研究以寡分枝栽培大豆冀黄13为母本,多分枝地方品种小黑豆为父本配制杂交组合,分别在2012年以F2:3群体为定位群体利用寡分枝单尾法和在2014以F2:4群体为定位群体,利用双尾法选择性基因分型方法对大豆分枝数进行QTL定位研究。研究表明,2012年,在寡分枝单尾群体检测到一个L连锁群上BARC19-1222(71.32 c M)位点与分枝数QTL位点连锁,该位点与已经报道的q Br2和q BN24-1位点较近,可能为同一个位点;2014年,在F2:4分离群体中的双尾群体中共检测到2个与分枝数QTL位点连锁的位点,分别是F连锁群上的BARC13-1845位点和B2连锁群上的BARC14-1214位点。在其附近尚未有分枝数相关QTL位点的报道,这两个位点可能为新位点。本研究将为进一步进行分枝数QTL位点的精细定位和分子标记辅助选择育种奠定基础。     

应用BXD小鼠鉴定肾脏发育相关QTLs

[目的]利用BXD小鼠群体定位肾脏发育相关QTLs及筛选QTLs区段内的候选功能基因。[方法]高脂饲喂BXD小鼠29w龄后,获取各品系小鼠肾脏重量和体重,结合该小鼠群体基因型信息,利用web QTL定位肾重比相关QTLs。为进一步筛选QTLs区段内的功能基因,首先,通过皮尔逊相关性分析,鉴定肾脏mRNA表达水平与肾重比显著相关(P 0. 05)的基因;其次,通过比较C57BL/6J和DBA/2J亲本品系的DNA序列信息,鉴定含有非同义突变的蛋白编码基因;最后,将上述基因导入到Phenolyzer在线分析数据库,并以"kidney"为表型关键词进行检索,优选QTLs区段内的候选功能基因。[结果]BXD小鼠肾重比存在显著差异。经QTL作图,在基因组上共鉴定3个与肾重比相关的QTLs,分别位于四号和X染色体上。在QTLs区段内,共发现45个基因的肾脏mRNA表达水平与肾重比显著相关(P 0. 05),65个基因含有非同义突变,经Phenolyzer在线数据库分析,发现51个基因可能与肾脏发育或肾脏疾病相关。[结论]通过QTL作图,在小鼠基因组上鉴定了3个影响肾脏发育的QTLs,筛选了部分候选基因,后续可做进一步的功能验证来阐明其参与肾脏发育的调控机制。     

大豆含硫氨基酸相关酶基因发掘

大豆(Glycine max)含硫氨基酸合成途径中的酶基因是含硫氨基酸组分的重要调控基因,发掘相关酶基因对高含硫氨基酸分子育种具有重要意义。文章采用大豆物理与遗传整合图谱,通过BioMercator2.1将113个含硫氨基酸合成途径酶基因及33个控制含硫氨基酸含量的QTL整合到遗传图谱Consensus Map 4.0上,依据酶基因位点与QTL的一致性以及QTL的效应值,初步筛选到16个与含硫氨基酸合成相关的候选基因。通过生物信息学方法对候选基因进行拷贝数、SNP、表达谱等分析,鉴定到12个相关酶基因,分别位于D1a、M、A2、K和G等8个连锁群上。生物信息学分析显示这些基因所在QTL可解释含硫氨基酸遗传变异的6.0%~38.5%,其中9个基因的间接效应值超过10%。12个相关酶基因参与含硫氨基酸代谢的重要途径,且多在子叶、花中高丰度表达,存在丰富的SNP。这些基因可作为候选基因进行功能标记开发,将为大豆分子设计育种奠定基础。     

大豆耐盐相关QTLs鉴定和功能基因研究进展

大豆(Glycine max (L.) Merill)是重要的粮食作物和经济作物,盐胁迫能造成大豆产量的大幅度降低。本文综述了通过正向遗传学手段获得的大豆耐盐数量性状位点(Quantitative trait locus, QTL)以及通过反向遗传学方法获得的大豆耐盐功能基因方面的研究进展。目前,正向遗传学发掘基因主要有图位克隆(Map-based cloning)和全基因组关联分析(Genome-wide association study, GWAS)两种方案,其中通过图位克隆在大豆中已经获得了6个耐盐QTL位点并且定位了1个重要的耐盐基因;利用GWAS在大豆中获得了1个耐盐功能基因。利用反向遗传学在大豆中获得了大量的耐盐相关功能基因并在模式植物中验证了其功能,主要包括离子转运蛋白基因和转录因子基因。这些研究为揭示大豆耐盐分子机制以及通过分子标记辅助育种或转基因技术创制耐盐大豆奠定了基础。     

大豆高蛋白种质中引1106蛋白质含量的QTL分析

大豆籽粒蛋白质含量由多基因控制且易受环境条件的影响,发掘高蛋白基因是促进大豆优质分子育种的重要手段。本研究选用综合性状优良、蛋白质含量较低的黑河50为轮回亲本,以引进的高蛋白种质中引1106为供体亲本,构建了由384个家系组成的回交高代群体。利用近红外光谱仪测定回交群体的蛋白质含量,使用SSR分子标记技术鉴定回交群体BC1F6基因型,通过QTL ICIMapping4.1的区间作图法(IM-ADD)和完备区间作图法(ICIM-ADD)定位蛋白含量QTL,共获得9个蛋白含量QTL,其中IM定位到7个蛋白含量QTL,而ICIM定位到3个蛋白含量QTL,两种方法同时在8号染色体上定位到一个QTL(q Pro-8-1),该QTL两侧的分子标记是SSR_50和SSR_51,可解释表型变异分别是2.26%和7.85%,定位区间物理距离大小为218.71 kb,该QTL尚未见报道,是一个与蛋白质含量相关的新QTL位点,为高蛋白大豆品种选育提供了材料和理论依据。     

大豆倒伏性相关QTL的整合及Overview分析

倒伏性是影响大豆产量的重要因素,发掘与大豆倒伏相关的基因对于培育抗倒伏优良高产大豆品种具有重要意义。目前利用不同群体所构建的遗传图谱已经定位了大量与大豆倒伏性相关的QTLs。本研究在对已报道的QTLs进行物理整合的基础上,选择元分析方法将这些倒伏性相关的QTLs进一步整合,鉴定出位于C2(6号染色体)、F(13号染色体)、L(19号染色体)这3个连锁群上重复次数较多的QTL区间6个。选用基于统计学原理的Overview方法进行优化,获得了这些QTL在各个连锁群上的有效遗传位置,这些QTL的置信区间长度最小可缩至0.2 cM。通过在这些区间内进一步筛选,获得一个稳定性较好的标记Satt277。本研究可为大豆抗倒伏基因发掘及分子标记辅助选择育种提供理论依据。     

基于元分析的抗玉米丝黑穗病QTL比较定位

以玉米遗传连锁图谱IBM2 2005 Neighbors为参考图谱,通过映射整合不同试验中的抗玉米丝黑穗病QTL,构建QTL综合图谱。在国内外种质中,共发现22个抗病QTL,分布在除第7染色体外的9条玉米染色体上。采用元分析技术,获得2个“一致性”抗病QTL,图距分别为8.79 cM和18.92cM。从MaizeGDB网站下载“一致性”QTL区间内基因和标记的原始序列;采用NCBI网站在线软件BLASTx通过同源比对在2个“一致性”QTL区间内初步获得4个抗病位置候选基因。借助比较基因电子定位策略,将69个水稻和玉米抗性基因定位于玉米IBM2图谱上,在2个“一致性”QTL区间内分别发现1个水稻抗性基因,初步推断为抗病位置候选基因。本文结果为抗玉米丝黑穗病QTL精细定位和分子育种提供了基础。     

大豆株高QTL的“整合”及Overview分析

株高是作物株型的重要组成因子,与作物种植密度、抗倒伏性及产量等密切相关。文章利用Soybase数据库和文献报道的201个与大豆株高相关的QTL信息,在物理整合的基础上,采用软件BioMercator2.1进行元分析,得到15个株高的"通用"QTL,分别位于大豆的6号、7号、11号、13号和18号染色体。同时,利用基于统计学原理的Overview方法进行优化,将这些QTL位点的置信区间最小缩至0.1 cM,从而明确了QTL位点在染色体上的遗传位置。对重演性较好的QTL位点所对应的区段内的基因进行分析,初步筛选出可能与株高相关的候选基因17个。文章为大豆株高相关QTL位点的精细定位及分子标记辅助育种奠定了基础。     

Combining QTL and candidate gene analysis with phenotypic model to unravel the relationship between lodging and related traits in soybean

Lodging is one of the major influencing factors of yield and quality in soybean [Glycine max (L.) Merr.] and other crops. To dissect the genetic basis of lodging in soybean, a recombinant inbred line population consisting of 165 lines was used to evaluate lodging percentage and eight related traits (branch number, internode length, number of nodes, plant height, stem diameter, stem strength, root length, and root weight) in three environments. Regression analysis indicated that plant height and root weight, which explain more than 55% of the variation in lodging percentage, might be the key factors influencing lodging in soybean. Nine consensus quantitative trait locus (QTLs) of lodging percentage were detected in one to three environments. Of which, eight consensus QTLs were colocated with 16 consensus QTLs of lodging-related traits by meta-analysis. In addition, seven candidate genes with the biological functions of shoot branching, root development, internode elongation, and lignin biosynthesis were identified on four pleiotropic QTL regions (oq.13-1, oq.13-2, oq.19-2, and oq.19-3) for lodging percentage and related traits. These findings showed that the consensus QTLs of lodging percentage might result from the pleiotropic QTLs affecting the lodging-related traits. Soybean lodging is determined by the cumulative effect of many traits/processes of growth and development. The combination of MAS, statistical model, and phenotypic selection will provide a powerful breeding strategy for lodging resistance in soybean.     

作物分枝的分子调控研究进展

分枝的数量及角度是决定作物株型的重要农艺性状。有效分枝数决定着作物的穗数或荚果数,进而决定着作物的产量;而分枝角度与光合效率、种植密度和抗病性密切相关,不仅影响作物的产量,也会影响作物的品质。由于分枝在作物生产中具有十分重要的作用,吸引了越来越多的研究者的注意,多个与分枝性状相关的关键基因被鉴定,分枝数目调控的分子机制研究取得了重要进展。过去的研究表明作物分枝受严格的遗传调控,同时也受环境条件的影响。综述了与作物分枝性状相关的基因克隆、表达、功能和分子调控机理方面的研究进展,以及环境因素对分枝的影响,探讨分枝调控在作物品种改良中的应用。     

Mapping QTLs for seed yield and drought susceptibility index in soy-bean（Glycine max L.） across different environments

Drought stress has long been a major constraint in maintaining yield stability of soybean （Glycine max （L.） Merr.） in rainfed ecosystems. The identification of consistent quantitative trait loci （QTL） involving seed yield per plant （YP） and drought susceptibility index （DSI） in a population across different environments would therefore be important in molecular marker-assisted breeding of soybean cultivars suitable for rainfed regions. The YP of a recombinant line population of 184 F2：7：11 lines from a cross of Kefengl and Nannong1138-2 was studied under water-stressed （WS） and well-watered （WW） conditions in field （F） and greenhouse （G） trials, and DSI for yield was calculated in two trials. Nineteen QTLs associated with YP-WS and YP-WW, and 10 QTLs associated with DSI, were identi- fied. Comparison of these QTL locations with previous findings showed that the majority of these regions control one or more traits re- lated to yield and other agronomic traits. One QTL on molecular linkage group （MLG） K for YP-F, and two QTLs on MLG C2 for YP-G, remained constant across different water regimes. The regions on MLG C2 for YP-WW-F and MLG H for YP-WS-F had a pleiotropic effect on DSI-F, and MLG A1 for YP-WS-G had a pleiotropic effect on DSI-G. The identification of consistent QTLs for YP and DSI across different environments will significantly improve the efficiency of selecting for drought tolerance in soybean.     

Mapping of putative quantitative trait loci controlling the total oligosaccharide and sucrose content of Glycine max seeds

Although oligosaccharides and sucrose are very important nutritional components of soybean seeds, little information is available about inheritance of oligosaccharide and sucrose content. The objective of this study was to identify quantitative trait loci (QTLs) that determine the oligosaccharide and sucrose content of soybean. The 117 F_2:10 recombinant inbred lines developed from a cross of “Keunolkong” and “Shinpaldalkong” were used. Narrow-sense heritability estimates, on a plot mean basis, of oligosaccharide and sucrose content were 79.07 and 74.84%, respectively. Four QTLs for oligosaccharide content were located on linkage groups (LG) C2, H, J, and L. Sucrose content was related with two QTLs located on LG H and J. Total oligosaccharide and sucrose content have two common QTLs on LG H and J.     

Molecular mapping of soybean aphid resistance genes in PI 567541B

The soybean aphid (Aphis glycines Matsumura) is an important pest of soybean [Glycine max (L.) Merr.] in North America since it was first reported in 2000. PI 567541B is a newly discovered aphid resistance germplasm with early maturity characteristics. The objectives of this study were to map and validate the aphid resistance genes in PI 567541B using molecular markers. A mapping population of 228 F₃ derived lines was investigated for the aphid resistance in both field and greenhouse trials. Two quantitative trait loci (QTLs) controlling the aphid resistance were found using the composite interval mapping method. These two QTLs were localized on linkage groups (LGs) F and M. PI 567541B conferred resistant alleles at both loci. An additive × additive interaction between these two QTLs was identified using the multiple interval mapping method. These two QTLs combined with their interaction explained most of the phenotypic variation in both field and greenhouse trials. In general, the QTL on LG F had less effect than the one on LG M, especially in the greenhouse trial. These two QTLs were further validated using an independent population. The effects of these two QTLs were also confirmed using 50 advanced breeding lines, which were all derived from PI 567541B and had various genetic backgrounds. Hence, these two QTLs identified and validated in this study could be useful in improving soybean aphid resistance by marker-assisted selection.     

大豆昆虫抗性相关QTLs的元分析

大豆虫害严重危害大豆生产。虽然大豆抗虫相关QTLs研究增多, 但由于作图群体不同、同种昆虫抗性QTL的调查性状不同以及数据分析方法存在差异等原因, 使QTL精确性和有效性被降低。因此, 获得相对真实且有效的QTLs位点对于促进分子标记辅助选择有重要意义。文章通过搜集已报道的81个与大豆昆虫抗性相关的QTL, 提取相对有效且可靠的QTLs标记信息, 利用元分析软件BioMercator2.1将这些QTLs映射到大豆公共遗传连锁图谱Soymap2上, 通过单独与联合的两种元分析途径, 利用QTLs的95%的置信区间来推断“真实QTLs”的位置。文章不仅构建了一张大豆昆虫抗性一致性图谱, 而且通过两种元分析途径分别得到12个和14个QTLs位点, 且其中有6个位点QTL的位置一致。它们被定位在9个连锁群上, 主要成簇分布在E、F、H、M等4个连锁群上, 图距由原来平均15 cM缩减到平均3.67 cM。除了一个与大豆食心虫抗性相关的位点外, 其余QTLs都与多种昆虫抗性相关。研究结果明显缩短了原来已报道的QTL置信区间, 为大豆抗虫相关QTL的精细定位以及抗虫相关基因挖掘提供了依据。     

大豆种皮色相关基因研究进展

大豆种皮色在从野生大豆到栽培大豆的演变过程中逐渐从黑色变成黄色,是重要的形态标记,因此,大豆种皮色相关基因研究无论对进化理论还是育种实践都具有重要的意义。种皮颜色是通过各种花色苷的沉积而形成的。虽然很多植物色素沉积的分子调控机制比较明晰,但大豆中控制种皮颜色形成的基因尚未被完全了解。文章综述了控制大豆种皮色基因与位点的相关研究进展,主要有I、T、W1、R、O 5个经典遗传位点,其中I位点被定位在第8号染色体(A2连锁群)一个富含查尔酮合成酶(CHS)的区域,CHS基因在大豆中是多基因家族且同源性较高;定位于第6号染色体(C2连锁群)T位点的基因F3’H已被克隆和转基因验证,由于碱基缺失导致所编码的氨基酸缺少了保守域GGEK,从而不能与血红素结合而丧失功能;R位点定位在第9号染色体(K连锁群)A668-1与K387-1两标记之间,可能是R2R3类MYB转录因子,也可能是UDP类黄酮3-O糖基转移酶;O位点定位在第8号染色体(A2连锁群)Satt207与Satt493两标记之间,其分子特性尚不清楚;W1位点可能由F3’5’H基因控制遗传。     

Determination of the genetic architecture of seed size and shape via linkage and association analysis in soybean (Glycine max L. Merr.)

Seed-size traits, which are controlled by multiple genes in soybean, play an important role in determining seed yield, quality and appearance. However, the molecular mechanisms controlling the size of soybean seeds remain unclear, and little research has been done to investigate these mechanisms. In this study, we performed a genetic analysis to determine the genetic architecture of soybean seed size and shape via linkage and association analyses. We used 184 recombinant inbred lines (RILs) and 219 cultivated soybean accessions to evaluate seed length, seed width and seed height as seed-size traits, and their ratios of these values as seed-shape traits. Our results showed that all six traits had high heritability ranging from 92.46 to 98.47 %. Linkage analysis in the RILs identified 12 quantitative traits loci (QTLs), with five of these QTLs being associated with seed size, five with seed shape and two with the two first principal components of our principal component analysis (PCA). Association analysis in the 219 accessions detected 41 single nucleotide polymorphism (SNP)-trait associations, with 20 of these SNPs being associated with seed-size traits, seven with seed-shape traits and 14 with the two first principal components of our PCA. This analysis reveals that seed-size and seed-shape may be controlled by different genetic factors. Our results provide a greater understanding of phenotypic structure and genetic architecture of soybean seed, and the QTLs detected in this study form a basis for future fine mapping, quantitative trait gene cloning and molecular breeding in soybean.