大豆11S/7S球蛋白比值QTL定位及相关基因分析

11S球蛋白与7S球蛋白是大豆贮藏蛋白主要成分,对大豆营养品质及加工特性有显著影响,且11S球蛋白对大豆营养品质及加工特性影响优于7S球蛋白,两者蛋白含量呈负相关.因此,大豆11S/7S球蛋白比值性状相关QTL位点与候选基因挖掘尤为重要.研究选用181个株系染色体片段代换系群体(Chromosome segment substitution lines,CSSL),采用完备区间作图法(Inclusive composite interval mapping)作11S球蛋白与7S球蛋白比值QTL定位,获得3个与大豆11S/7S球蛋白比值相关QTL.在两个共识QTL区间内,获得6个候选基因,通过实时荧光定量PCR验证,Glyma.09G015100在低、高表型材料中相对表达量均高于对照材料,表明该基因在球蛋白表达过程中有促进作用.研究结果为大豆11S球蛋白与7S球蛋白比值QTL精细定位及适用于加工品种选育提供理论依据.     

大豆异黄酮与脂肪、蛋白质含量基因定位分析

 【目的】研究大豆异黄酮与脂肪、蛋白质含量基因定位及相关性,为大豆品质改良、分子育种及基因克隆等应用提供理论依据。【方法】利用SSR技术,对晋豆23号和灰布支杂交构建的F13代大豆重组自交系群体的474个家系进行了连锁图谱的构建。在此基础上,利用 WinQTLCart2.0 软件分析了影响大豆异黄酮含量、脂肪含量和蛋白质含量3个重要品质性状的QTL,通过复合区间作图分析,检测QTL;同时,对异黄酮与脂肪、蛋白质的含量相关性分析。【结果】检测到23个QTL,其中控制异黄酮含量QTL有6个,分别定位在J、N、D2和G染色体的连锁群上;控制脂肪含量的QTL有11个,分别定位在第A1、A2、B2、C2和D2染色体的连锁群上;控制蛋白质含量的QTL有6个,分别定位在B2、C2、G和H1染色体的连锁群上。相关性分析结果表明：异黄酮与蛋白质含量呈极显著负相关;蛋白质和脂肪含量呈极显著负相关;蛋白质和蛋白质脂肪总量呈极显著正相关。【结论】3个重要品质性状的部分基因定位结果与其相关性分析是一致的,其结果对大豆品质育种应用有重要利用价值。     

基于RIL和CSSL群体定位大豆脂肪酸组分QTL

【目的】 大豆（Glycine max）原产于中国,高品质的大豆在食品、饲料、纺织品等多种加工业中广泛应用,因此,选育高品质大豆已成为育种者和生产者的聚焦问题。通过对大豆脂肪酸各组分进行QTL定位及候选基因的筛选,为大豆品质改良奠定分子基础。【方法】 以美国大豆品种Charleston和东农594为亲本构建重组自交系（RILs）、以栽培大豆绥农14与野生大豆ZYD00006为亲本构建染色体片段代换系（CSSLs）为试验材料。利用气相色谱法测定2个群体的脂肪酸含量,根据东北农业大学农学院大豆遗传改良实验室已构建的遗传图谱,通过Windows QTL Cartographer 2.5和ICIMapping软件对2017—2018年RIL群体与CSSL群体中的大豆脂肪酸组分进行QTL定位研究,并对所获得的QTL置信区间进行候选基因的挖掘。【结果】 2017—2018年,RIL群体和CSSL群体分别定位到34和20个与脂肪酸组分相关的QTL,分布在除B2、C1、G、H、J、M和O以外的13个连锁群上。比较2个群体的QTL定位结果,发现在2个群体中重复检测到10对QTL,其中,分布在A1、C2、D1a、F、K和N连锁群上的QTL与多种脂肪酸含量相关,在A1连锁群上检测到亚油酸和油分含量重叠的QTL;在C2连锁群上检测到硬脂酸和油分含量重叠的QTL;在D1a连锁群上检测到硬脂酸和油分含量重叠的QTL;在F连锁群上检测到棕榈酸、硬脂酸和油分含量重叠的QTL;在K连锁群上检测到亚油酸和亚麻酸含量重叠的QTL;在N连锁群上检测到棕榈酸和油分含量重叠的QTL、油酸和亚油酸含量重叠的QTL。对QTL定位获得的所有置信区间进行候选基因的挖掘,从基因注释数据集中共筛选出485个候选基因,其中,271个候选基因具有GO注释,进一步进行GO富集数据分析,共有15个候选基因与脂肪酸相关。主要通过编码植物酰基-酰基载体蛋白（ACP）硫酯酶、脂肪酸去饱和酶、磷脂酶D1、脂肪酸-羟化酶、丙酮酸激酶和参与酰基辅酶A生物合成、调节脂肪酸链的延伸,从而影响脂肪酸的合成。【结论】 共检测到54个与大豆脂肪酸各组分相关的QTL,在2个群体中重复检测到10对QTL,对QTL定位获得的置信区间进行候选基因的筛选,共有15个候选基因与脂肪酸相关。这些稳定的脂肪酸相关的QTL和脂肪酸相关的候选基因可用于大豆脂肪酸改良的分子标记辅助选择。     

大豆抗大豆花叶病毒病基因研究进展

大豆花叶病毒(soybean mosaic virus,SMV)病是严重危害世界大豆(Glycine max(L.)Merr.)生产的主要病害之一。近十年来,国内外关于大豆对SMV抗病基因的遗传标记定位、候选抗病基因的分析及大豆抗SMV的调控网络等研究取得许多新进展。大豆对SMV的抗性遗传主要分为数量抗性和质量抗性,其中数量抗性的遗传主要由1对加性主基因+加性-显性多基因共同控制;对不同SMV株系的质量抗性遗传分别由1对不同的显性基因控制。标记定位研究发现,大豆对SMV数量抗性位点主要分布在大豆的第6、10和13等染色体上。22个对SMV具有单显性质量抗性的基因位点已被标记定位在大豆的第2、6、13和14染色体上,且定位的多数抗病基因位点两侧标记间的物理距离都在1 Mb以内。其中第13染色体上的基因位点数最多,有Rsv1、Rsv5、RSC3Q、RSC11和RSC12等10个,定位在第2染色体上的基因位点有8个,如Rsv4、RSC5、RSC6、RSC7和RSC8等,第6和14染色体上各有2个基因位点,分别为RSC15、RSC18和Rsv3、RSC4。参考大豆全基因组序列(http://www.phytozome.net/soybean),利用生物信息学方法、表达谱分析及克隆测序技术等进一步缩小了大豆抗SMV候选基因的筛选范围。目前,在大豆第2染色体上确定的抗SMV候选基因主要有8个:Glyma.02G121400、Glyma.02G121500、Glyma.02G121600、Glyma.02G121800、Glyma.02G121900、Glyma.02G122000、Glyma.02G122100和Glyma.02G122200,在第6染色体上的是Glyma.06G182600,在第13和14染色体上的抗SMV候选基因分别有9个和6个:Glyma.13G184800、Glyma.13G184900、Glyma.13G187900、Glyma.13G190000、Glyma.13G190300、Glyma.13G190400、Glyma.13G190800、Glyma.13G194700、Glyma.13G195100和Glyma.14G204500、Glyma.14G204600、Glyma.14G204700、Glyma.14G205000、Glyma.14G205200、Glyma.14G205300。基于病毒诱导的基因沉默VIGS(virus induced gene silencing,VIGS)和转基因操作等技术,研究发现抗SMV相关基因Gm HSP40、Gm PP2C3a、Gm AKT2、Gm Cnx1、Gm SN1、Glyma.14G204500、Glyma.14G204600、Glyma.14G204700等参与大豆对SMV的抗性,属于正调控因子;而Gm EF1A和Gme IF5A等则增加大豆对SMV的易感性,为负调控因子。在综合SMV抗病基因的相关研究基础上,构建了基于Rsv1和Rsv3介导对SMV极端抗性的调控网络模型。Rsv1介导的大豆对SMV极端抗性调控模型的建立为大豆抗SMV信号网络的研究提供了新的方向。Rsv3介导的大豆对SMV极端抗性的主要机制是通过ABA信号的传导,从而使胞间连丝处的胼胝质沉积以抑制病毒从最初侵染的细胞向健康细胞的转移。本文系统综述了SMV抗病基因方面的最新研究成果并对该领域未来的研究方向进行了展望,以期为大豆抗SMV分子设计育种和抗病基因的机理研究提供参考。     

QTL Mapping of Isoflavone,Oil and Protein Contents in Soybean （Glycine max L. Merr.）

Soybean （Glycine max L. Merr.） is the world＇s foremost source of edible plant oil and proteins, meantime, the biologically active secondary metabolites such as saponins and isoflavones are benefit to human health. The objective of this study was to identify quantitative trait loci （QTL） and epistatic interactions associated with isoflavone, protein, and oil contents in soybean seeds. An F13 recombinant inbred line （RIL） comprising 474 lines was derived from a cross between Jindou 23 and Huibuzhi cultivars. SSR technique was employed for mapping of the QTLs. The QTLs for isoflavone, protein, and oil contents were analyzed and 23 QTLs were detected based on the constructed linkage map. Six QTLs for isoflavone content were localized in linkage groups J, N, D2, and G, eleven QTLs for oil content were localized in the linkage groups A1, A2, B2, C2, and D2, and six QTLs for protein content were localized in linkage groups B2, C2, G, and H1. The correlative analysis demonstrated that the isoflavone content had significant correlation with protein content, while significantly negative correlations was existed between oil and protein content, and significantly positive correlations was existed between protein and oil content. All these findings have laid an important basis for the marker assisted breeding in soybean. The phenotypic correlations of quantitative traits may be resulted from the correlation of the QTL controlling those traits.     

大豆产量相关性状的多年多点QTL分析

目前大豆和其他高产作物相比,相对产量偏低,提高大豆产量潜力是大豆育种的重要任务。产量是一个综合性状,受多个形态、生理以及农艺性状的影响。定位大豆产量性状QTL,具有重要的研究和应用价值。以美国大豆品种Charleston为母本,东北农业大学大豆品系东农594为父本及其F2:14代重组自交系的154个株系为试验材料,164个SSR引物经亲本筛选后用于群体扩增,并构建遗传图谱。在两年同一地点下对亲本间表现多态的12个与产量相关的农艺性状进行了调查及QTL分析。产量相关性状包括荚数、荚长、荚宽、百粒重等。QTL检测结果表明,在两年的种植环境下,12个产量相关性状共检测到QTL 33个。每个性状的QTLs在两种环境下共检出个数1~9个不等,其中6个QTLs在2个环境下被检测到,它们受环境的影响较小,为较稳定的QTLs。其他产量QTLs只在单一环境下被检测到,说明产量相关QTLs与环境之间存在明显的互作。与国内外对应农艺性状QTLs检测结果相比,多个性状的QTLs位点均一致,说明QTLs检测准确率较高。利用分子标记遗传图谱,定位控制产量相关性状的QTL,为利用分子标记改良大豆产量潜力提供了有力手段。     

Meta-analysis of soybean amino acid QTLs and candidate gene mining

The composition and quantity of amino acids influence the protein content and nutritional value of soybeans and also have an important impact upon soybean quality. After integrating and proofreading 140 original QTLs associated with amino acid contentfrom soybase (http://www.soybase.org/), 138 QTLs were further analyzed to determine high-confidence QTL regions. Meta-analysis was first carried out using the BioMercator ver. 2.1 software, yielding 33 consensus QTLs. The consensus QTL confidence intervals (CIs) ranged from 0.07 to 19.85 Mb. Next, the overview method was used to optimize the CIs, and 57 “real” QTLs were mapped. Candidate genes in the consensus QTL regions were obtained from Phytozome and were annotated using the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Swissprot, and gene annotation databases. Finally, 16 unpublished candidate genes controlling the content of five types of amino acids were identified with Blast. These results laid the foundation for fine mapping of soybean amino acid-related QTLs and marker-assisted selection.     

基于元分析的大豆成熟期单片段代换系鉴定与QTL定位

【目的】大豆成熟期是由多基因控制的数量性状,是影响大豆产量和适应性的重要性状。研究大豆成熟期单片段代换系遗传规律,鉴定分析大豆成熟期的主效QTL。【方法】以大豆红丰11为受体和回交亲本,以15个国内外大豆核心种质为供体亲本,构建回交导入系群体,基于元分析的大豆成熟期（R8）“真实QTL”SSR标记进行单片段代换系鉴定,利用“图示基因型法”计算导入片段和代换作图法鉴定大豆成熟期QTL,用单标记法鉴定成熟期重要QTL。【结果】在C2、L连锁群上检测到16种导入片段,C2连锁群检测到7种导入片段,导入片段总长度为9.8 cM。L连锁群检测到9种导入片段,导入片段总长度为37.212 cM;在C2和L连锁群上共检测出8个成熟期QTL,根据前人的研究,在L连锁群上有2个QTL即Sat_010、Satt156是E4/e4的特异SSR标记;在8个成熟期QTL中用单标记法鉴定了5个有关大豆成熟期重要SSR标记Sat_238、Satt460、Sct_010、Satt166、Sat_113;确定了单片段Satt460缩短大豆生育期,单片段Sat_238、Sct_010、Sat_113延迟大豆生育期。【结论】基于元分析的成熟期2个导入位点C2、L连锁群上检测到16种单片段,用代换作图法共检测出8个成熟期QTL,用单标记法鉴定了5个有关大豆成熟期重要SSR标记Sat_238、Satt460、Sct_010、Satt166、Sat_113。确定单片段Satt460与缩短大豆生育期有关,单片段Sat_238、Sct_010、Sat_113与延迟大豆生育期有关。     

大豆脂肪含量遗传分析及QTL定位研究

以高蛋白大豆品种吉育50和高油大豆品种吉农18杂交后获得的F2及其衍生群体为材料,采用主基因+多基因混合遗传模型和QTL IciMapping v2.2完备区间作图法研究大豆脂肪含量的遗传规律.结果表明:大豆脂肪含量表现为多基因遗传模型,主要受多基因控制,多基因遗传率为79.15%;对大豆脂肪含量进行QTL定位和分析,共检测到2个主效QTL和2个微效QTL,分布于12(G)、17(M)和22(F)3个连锁群上,其中包括了1个在2年间稳定存在的主效QTL.     

QTL analysis for plant height and fine mapping of two environmentally stable QTLs with major effects in soybean

Plant height is an important agronomic trait, which is governed by multiple genes with major or minor effects. Of numerous QTLs for plant height reported in soybean, most are in large genomic regions, which results in a still unknown molecular mechanism for plant height. Increasing the density of molecular markers in genetic maps will significantly improve the efficiency and accuracy of QTL mapping. This study constructed a high-density genetic map using 4 011 recombination bin markers developed from whole genome re-sequencing of 241 recombinant inbred lines (RILs) and their bi-parents, Zhonghuang 13 (ZH) and Zhongpin 03-5373 (ZP). The total genetic distance of this bin map was 3 139.15 cM, with an average interval of 0.78 cM between adjacent bin markers. Comparative genomic analysis indicated that this genetic map showed a high collinearity with the soybean reference genome. Based on this bin map, nine QTLs for plant height were detected across six environments, including three novel loci (qPH-b_11, qPH-b_17 and qPH-b_18). Of them, two environmentally stable QTLs qPH-b_13 and qPH-b_19-1 played a major role in plant height, which explained 10.56–32.7% of the phenotypic variance. They were fine-mapped to 440.12 and 237.06 kb region, covering 54 and 28 annotated genes, respectively. Via the function of homologous genes in Arabidopsis and expression analysis, two genes of them were preferentially predicted as candidate genes for further study.     

大豆籽粒蛋白与脂肪含量上位性QTLs分析

大豆籽粒富含蛋白与脂肪,是人类植物蛋白与食用油重要来源;然而,蛋白、脂肪含量属多基因控制数量性状,尽管已有相关QTLs报道,但多是针对单个QTL进行分析,而很少有关于上位性QTLs的报道。鉴于此,利用大豆RIL群体,在4种环境条件下评价其籽粒蛋白与脂肪含量,结合SNP基因型进行上位性QTLs分析发现,定位到48对控制籽粒蛋白、55对控制籽粒脂肪含量上位性QTLs,涉及大豆所有染色体;进一步分析发现,有19对上位性QTLs同时与籽粒蛋白和脂肪含量相关,具体包括12对定位区间完全相同的QTLs、2对定位区间含共同标记的QTLs以及5对定位区间距离不超过5 c M的QTLs;同时发现,19对上位性QTLs分布在除11号染色体以外的19条染色体,其中以13号染色体分布数量最多,其次为1号染色体。上述结果不仅增添了控制大豆蛋白与脂肪含量上位性QTLs,而且为揭示二者之间的负相关关系提供了QTL间/基因间互作方面的分子证据。     

Identification and validation of stable and novel quantitative trait loci for pod shattering in soybean [Glycinemax (L.) Merr.]

Pod shattering is an important domesticated trait which can cause great economic loss of crop yield in cultivated soybean. In this study, we utilized two recombinant inbred line populations (RILs, CY, Huachun 2×Wayao; GB, Guizao 1× B13) to identify quantitative trait loci (QTLs) associated with pod shattering in soybean across multiple environments. A total of 14 QTLs for pod shattering were identified in the two RIL populations, which had LOD scores ranging from 2.64 to 44.33 with phenotypic variance explanation (PVE) ranging from 1.33 to 50.85%. One QTL qPS16-1, located on chromosome 16, included a well-known functional gene Poddehiscence1 (Pdh1) that was reported previously. Ten new putative QTLs were validated in two RIL populations, and their LOD scores were between 2.55 and 4.24, explaining 1.33 to 2.60% of the phenotypic variation. Of which four novel QTLs (qPS01-1, qPS03-2, qPS05-1, and qPS07-1) could be detected in two environments where nine genes had specific changes in gene expression. Although the nine genes may have significant effects on pod shattering of soybean, their detailed functions still need to be further explored in the future. The results of this study will facilitate a better understanding of the genetic basis of the pod shattering-resistant trait and benefit soybean molecular breeding for improving pod shattering resistance.     

Identification of quantitative trait loci and candidate genes associated with ABA sensitivity in common wild rice(Oryza rufipogon Griff.)

Abscisic acid(ABA),as one of the foremost signaling molecules in plants,is an important hormone which plays versatile functions in regulating developmental process and adaptive stress process.A set of introgression lines were previously generated via a backcrossing program using an elite indica cultivar rice Teqing(O.sativa L.) as recipient and an accession of Yuanjiang common wild rice(O.rufipogon Griff.) as donor.In this study,the previously developed introgression lines were evaluated for ABA sensitivity.Here we reported that a total of 14 quantitative trait loci(QTLs) associated with ABA sensitivity were identified.An ABA sensitive introgression line,YIL53,was identified and characterized.Physiological characterization,including chlorophyll content,malondialdehyde content,soluble sugar content,and stomata movement,demonstrated that YIL53 exhibited the characteristics associated with ABA sensitivity.Genotypic analysis revealed that YIL53 harbored one QTL related to ABA sensitivity,q ASS1-2,which was located on chromosome 1 within one introgressed segment derived from the Yuanjiang common wild rice.Furthermore,the qASS1-2 was finally narrowed down to a 441-kb region between simple sequence repeats(SSR) marker RM212 and single nucleotide polymorphism(SNP) marker M3 using the segregation population derived from the cross between Teqing and YIL53,and three candidate genes associated with ABA sensitivity were identified using a strategy combined gene expression analysis with QTL mapping.Identification of the QTLs related to ABA sensitivity and characterization of the ABA sensitive line YIL53 would provide a helpful basis for isolating novel genes related to ABA sensitivity.     

利用BSA法发掘野生大豆种子硬实性相关QTL

【目的】野生大豆的硬实性是大豆遗传改良利用中的重要限制因素。利用BSA法发掘与大豆种子硬实性相关的QTL,为野生大豆在大豆遗传改良中的合理利用奠定基础。【方法】利用栽培大豆中黄39与野生大豆NY27-38杂交构建F₂和F₇分离群体,从每个单株选取整齐一致的种子,取30粒种子置于铺有一层滤纸的培养皿中,加入30 mL蒸馏水,25℃培养箱中暗处理4 h,设3次重复,分别统计每个培养皿中正常吸胀和硬实种子数。在F₂群体中,选取22个正常吸胀单株（吸胀率＞90%）和16个硬实单株（吸胀率＜10%）;在F₇群体中,选取20个完全吸胀单株（吸胀率=100%）和20个完全硬实单株（吸胀率=0%）,单株DNA等量混合,分别构建2个吸胀和2个硬实DNA池。利用259对在亲本间有多态性的SSR标记对吸胀和硬实DNA池进行检测,筛选在吸胀和硬实DNA池间表现多态性的SSR标记;用192个SSR标记检测F₇分离群体,构建遗传图谱,利用复合区间作图法定位大豆硬实相关QTL。【结果】利用F₂个体构建的吸胀和硬实DNA池,在第2染色体16.3 Mb区间和第6染色体23.4 Mb区间分别检测到10个和8个在两池间有差异的SSR标记。利用这些标记检测F₂群体,将第2染色体的QTL定位于Satt274与Sat_198间的276.0 kb区间,该区间包括已克隆的大豆硬实基因GmHs1-1,解释17.2%的表型变异。第6染色体的QTL位于标记BARCSOYSSR_06_0993与BARCSOYSSR_06_1068间,可解释17.8%的表型变异。利用F₇株系构建的吸胀和硬实DNA池,在第2（27.4 Mb区间）、6（27.8 Mb 区间）和3染色体（18.2 Mb区间）分别检测到11个、9个和4个在两池间有多态性的SSR标记。利用F₇群体构建包括192个SSR标记、覆盖2 390.2 cM的遗传图谱,共检测到3个硬实相关QTL,其中第2染色体定位到的QTL位于标记Satt274与Sat_198间,可解释23.3%的遗传变异。第6染色体定位到的QTL位于标记Sat_402与Satt557之间,可解释20.4%的表型变异。在第3染色体标记Sat_266与Sat_236间发现一个可以解释4.9%表型变异的QTL,与BSA法检测的结果相符。【结论】利用BSA法可以检测到传统遗传作图定位的所有与硬实性相关的QTL,证明BSA法发掘大豆种子硬实性主要QTL的高效性。     

基于Meta分析的大豆百粒重的QTLs定位

 【目的】百粒重是控制大豆产量性状的主要数量性状,对大豆产量性状进行基因定位具有重要的研究和应用价值。现有百粒重QTL定位结果分散,需选择合适的公共图谱,整合前人的研究结果,使其真正应用到实践中。【方法】以2004年发布大豆公共遗传连锁图谱soymap2为参考图谱,将近20年不同试验中的大豆百粒重的QTLs进行映射整合,构建百粒重QTL综合图谱。利用BioMercator2.1的映射功能将国内外常用的大豆图谱上的百粒重QTLs通过公共标记映射整合到大豆公共遗传连锁图谱soymap2上,并利用Meta分析,通过对比已经报道的QTLs的95%的置信区间来推断QTL位置,从而提取真正有效的QTL标记。【结果】在已经发表的文献中共找到65个百粒重QTLs定位信息,其中有53个QTLs定位区间与公共图谱有共有标记,包括36个增效效应的QTLs和17个减效效应的百粒重QTLs,共得到12个QTL簇,通过Meta分析,发掘出6个增效效应和6个减效效应的百粒重“通用QTLs”及其连锁标记。【结论】本研究得到的“通用QTLs”其置信区间最小可达到1.52 cM,为辅助选择分子标记、QTL精细定位以及数量性状基因的克隆奠定基础。     

QTL Mapping of Hard Seededness in Wild Soybean Using BSA Method

【Objective】 Hard seededness of wild soybean is an important effector that limits the utilization of wild resources in soybean genetic improvement. Bulked segregant analysis (BSA) was employed to identify major quantitative trait loci (QTLs) related with hard seededness in soybean, which laid a foundation for effective utilization of wild soybean germplasm in cultivated soybean improvement. 【Method】 F₂ and F₇ segregation populations were constructed from a cross between cultivated soybean Zhonghuang39 and wild soybean NY27-38. Uniformly sized seeds were selected from each line, and 30 seeds were soaked in a petri dish with 30 mL distilled water for 4 hours at 25℃. The assay was replicated 3 times. The number of permeable and impermeable seeds were counted. In F₂ population, the first DNA pool was constructed from 22 individuals with permeable seeds (imbibition rate ＞90%), and second DNA pool was constructed from 16 individuals with impermeable seeds (imbibition rate ＜10%). In F₇ population, 20 lines with permeable seeds (100% imbibition) and 20 lines with impermeable seeds (no imbibition) were used to construct two DNA pools, respectively. To detect genomic regions associated with hard seededness, these DNA bulks were genotyped with 259 polymorphic SSR markers to identify markers linked to QTL. A linkage map was constructed with 192 SSR markers, QTLs related with hard seededness were identified by composite interval mapping in F₇ segregation population. 【Result】 Out of 259 SSR loci polymorphic between Zhonghuang39 and NY27-38, 10 and eight polymorphic SSR markers between the permeable and impermeable pools were detected in 16.3 Mb interval on chromosome 2 and 23.4 Mb interval on chromosome 6, respectively, in F₂ population. The QTL region (276.0 kb) located between Satt274 and Sat_198 on chromosome 2 contained previously cloned gene GmHs1-1, the QTL explained 17.2% of the total genetic variation. The other QTL was mapped on chromosome 6 flanked by BARCSOYSSR_06_0993 and BARCSOYSSR_06_1068, accounting for 17.8% of the total genetic variation. In F₇ population, eleven, nine and four SSR polymorphic markers between the permeable and impermeable pools were detected in 27.4 Mb interval on chromosome 2, 27.8 Mb interval on chromosome 6, 18.2 Mb interval on chromosome 3, respectively. A linkage map of 192 SSR markers and covering 2 390.2 cM was constructed through composite interval mapping in F₇ population. Three QTLs related with hard seededness were detected. The QTL on chromosome 2 located between Satt274 and Sat_198, explained 23.3% of the total genetic variation; the QTL on chromosome 6 flanked by Sat_402 and Satt557, explained 20.4% of the total genetic variation; the QTL on chromosome 3 flanked by Sat_266 and Sat_236 accounted for 4.9% of the total genetic variation. 【Conclusion】 In this study, three QTLs related to soybean hard seededness were identified by both BSA and traditional linkage mapping, indicating that BSA is an effective strategy for identifying QTLs in soybean.     

基于SNP遗传图谱对甘蓝型油菜部分脂肪酸 组成性状的QTL定位

目的 菜籽油在烹饪、食品加工及工业生产中广泛应用,因此,根据生产需要改善菜籽油脂肪酸组分是油菜育种的重要目标。通过对2种环境下甘蓝型油菜主要脂肪酸组成进行QTL定位分析,寻找甘蓝型油菜脂肪酸组分的QTL及影响本群体脂肪酸组分的候选基因。方法以人工合成甘蓝型油菜10D130和甘蓝型油菜常规品种中双11构建高世代重组自交系（RIL）为研究材料,分别于2016-2017年和2017-2018年2个年度在重庆市北碚区2个不同的环境中设置田间试验,收获自交种子,采用气相色谱法3次重复对种子的脂肪酸组分进行分析。利用油菜6K SNP芯片对该RIL群体进行基因分型,DNA样品预处理及芯片处理严格按照Illumina Inc 公司Infinium HD Assay Ultra操作说明进行。取最小阈值LOD 2.0利用JoinMap4.0软件构建高密度遗传连锁图谱。通过QTL IciMapping V4.1完备区间作图法对油菜主要脂肪酸组成进行QTL定位。结果 2种环境中,两亲本各性状间差异及RIL群体各性状在株系间差异均达到显著或极显著水平,且6种脂肪酸含量在2个环境中均表现为连续分布,适合进行QTL检测。构建用于QTL定位的遗传图谱包含1 897个多态性SNP标记,覆盖甘蓝型油菜基因组3 214.19 cM,平均图距1.69 cM。利用此图谱,在2个环境共检测到位于8条染色体上的23个控制脂肪酸组分QTL位点,与硬脂酸、油酸、亚油酸、亚麻酸、廿碳烯酸和芥酸含量相关的QTL位点分别为6、3、4、5、2和3个,其中在A05、A08和C03染色体上发现多种脂肪酸含量的QTL“富集区”。在A05染色体上检测到亚油酸和亚麻酸含量重叠的主效QTL,亚油酸与亚麻酸表现加性效应相同;在A08和C03上都检测到油酸、廿碳烯酸和芥酸含量重叠的主效QTL,油酸与廿碳烯酸及芥酸表现加性效应相反。与拟南芥脂肪酸代谢基因进行同源性比对分析,在17个QTL置信区间内筛选到22个候选基因,主要通过编码脂肪酸去饱和酶、全羧化酶合酶、碳链延长酶和参与酰基辅酶A生物合成等途径调控脂质的生物合成和代谢。结论 利用甘蓝型油菜6K SNP芯片准确定位了2种环境条件脂肪酸组成的QTL位点,筛选到位于A05、A08和C03染色体上多种脂肪酸QTL的“富集区”,并与拟南芥脂肪酸代谢基因比对出该群体油菜脂肪酸代谢基因,可作为改善油菜籽脂肪酸组成的重要区段及候选基因。     

RTM-GWAS方法应用于大豆RIL群体百粒重QTL检测的功效

【目的】为全面解析大豆重组自交系群体中调控百粒重性状的QTL体系,将限制性两阶段多位点全基因组关联分析方法（RTM-GWAS）和不同定位方法进行比较、优选,为后续候选基因体系探索及分子标记辅助育种设计提供依据。【方法】利用以科丰1号和南农1138-2为亲本衍生的重组自交系群体NJRIKY的427个家系,通过由全基因组39 353个SNP构建的3 683个SNPLDB标记及3个环境下的百粒重表型数据,选用复合区间作图法（CIM）、基于混合线性模型的全基因组关联分析方法（MLM-GWAS）和RTM-GWAS3种方法检测百粒重QTL,通过QTL数目和总的表型变异解释率比较检测功效,挑选最佳定位结果进行NJRIKY群体中的百粒重遗传体系解析。通过候选基因体系的功能注释,挖掘调控大豆百粒重的生物学途径。【结果】科丰1号与南农1138-2的百粒重差异较大,多环境平均数分别为9.0和17.9 g,遗传变异系数为12.4%,遗传率为85.4%,适用于百粒重性状的遗传解析。比较3种方法定位结果表明RTM-GWAS方法表现最佳,检测QTL数目最多（57个）,解释表型变异最多（70.78%）。而CIM仅检测到14个QTL,解释了56.47%的表型变异,MLM-GWAS仅定位到6个QTL,解释了18.47%的表型变异。RTM-GWAS共检测到57个QTL,分布在19条染色体上,表型变异解释率为0.03%—7.57%,其中41个QTL覆盖了已报道的来自30个双亲群体的81个百粒重QTL,16个QTL为新发现位点,包含一个表型变异解释率大于3%的大效应位点Sw-09-2。此外,检测的57个QTL中有20个位点与环境存在互作效应。这57个QTL构成了影响NJRIKY群体百粒重性状的遗传体系。通过SNPLDB标记与预测基因内的SNP进行χ²检验,共筛选到36个候选基因,其中4个候选基因来自大效应QTL,剩余32个候选基因来自小效应QTL。通过GO注释发现这些候选基因功能注释丰富,其中13个候选基因与籽粒发育直接相关,剩余的候选基因功能丰富,包含转运、转录调节因子等,表明不同生物学途径的基因共同调控NJRIKY群体中百粒重性状的表达。【结论】3种定位方法中,高效的RTM-GWAS方法检测到较为全面的NJRIKY群体的百粒重QTL,更适用于双亲RIL群体的QTL定位。不同功能的候选基因共同调控了复杂的百粒重性状的表达。