发掘大豆资源中灰斑病1号生理小种抗性优异等位变异

通过发掘大豆资源中抗灰斑病1号生理小种的优异等位变异和载体材料,为开展抗灰斑病品种分子设计育种提供理论基础。以205份大豆资源构建的自然群体为试验材料,对其进行灰斑病1号生理小种的抗性鉴定;利用117对SSR标记进行全基因组扫描,分析群体的遗传多样性和群体结构,应用GLM和MLM程序对标记与大豆灰斑病抗性开展关联分析。结果表明：205份大豆资源对灰斑病1号生理小种抗性遗传变异系数为20.90%;2个模型共检测到与灰斑病1号生理小种抗性关联的位点7个,表型变异解释率在7.58%~16.06%;发掘到增效等位变异36个,其中效应值较大的等位变异为Satt244-230（26.16）、Satt142-154（21.94）和Satt244-186（20.19）,携带上述3个等位变异的载体材料均为野生资源,3个典型材料分别为12C8646、12C8670和12C6175;育成品种中具有最大增效值的等位变异为Satt142-189（8.94）,有7个品种携带该等位片段,均为黑龙江品种,典型载体材料为东农43。 上述信息可用于分子标记辅助选择育种和抗源筛选。     

寒地水稻直链淀粉含量关联分析

直链淀粉含量是衡量水稻蒸煮食味品质的重要指标之一,寒地水稻直链淀粉含量适中,口感较好,广受消费者喜爱。本研究利用267对SSR标记对158份寒地水稻种质资源材料进行多态性扫描,分析群体遗传结构与位点间连锁不平衡,并使用TASSEL软件的MLM(mixed linear model)方法对直链淀粉含量进行标记与性状的关联分析。结果表明:群体结构分析将参试材料分为3个群体;关联分析结果在水稻的第1、第3、第6、第7、第8染色体上共检测到10个与水稻直链淀粉含量显著关联(p0.01)的位点,分别为RM2615、RM1152、RM148、RM570、RM1164、RM1377、RM276、RM25、RM141和RM1360,贡献率最高的位点是位于第6染色体上的RM2615(32.07%);10个显著关联位点的27个等位变异中仅包括1个减效位点(RM2615-482 bp),其余均为增效位点,增效表型效应值最大的等位变异为RM1152-296 bp(0.050 1)。研究得到的与寒地水稻直链淀粉含量相关的SSR位点及其表型效应可为改良寒地水稻直链淀粉含量、培育优质寒地水稻品种的分子辅助育种工作提供理论依据。     

1092份水稻材料稻瘟病抗性鉴定及抗性标记分析

在福建省沙县稻瘟病重发区,对1092份水稻材料进行连续3年的田间苗叶瘟和穗茎瘟的自然鉴定,供试材料中高抗、抗、中抗、中感、感和高感材料分别为124、99、121、545、156和47份。利用14个与抗性基因紧密连锁的SSR标记及3个源于抗病基因序列的显性标记,对其中130份抗性较好的材料进行了遗传背景分析,14个SSR标记引物共扩增到87个等位位点,每一标记的等位位点变幅为2～13个,平均为6.2个,每个SSR位点的多态性信息含量(PIC)变化范围为0.379～0.9,平均为0.695;不同抗性亲本材料出现抗性基因的标记为2～9个,其中与抗病基因Pi35、Pi-yt及Pi-ta相对应的标记RM1003、RM202和YL155/YL87的概率较高。     

水稻耐盐碱胁迫优异等位变异的发掘

本研究以281个水稻品种构成的自然群体为试验材料,调查了盐、碱胁迫下水稻种子萌发能力相关性状,选择260对SSR标记对基因组进行扫描,采用Structure软件进行群体分析,利用GLM（General Linear Model）方法对标记与幼苗耐盐碱能力进行关联分析;并以试验材料表型均值为对照,鉴别出携带优异等位变异及载体材料。检测到15个与盐胁迫下种子萌发能力关联的SSR位点,其中第10条染色体上分别与标记RM184和RM171连锁位点的贡献率较大,达到29.51%和31.67%,优异等位变异RM184-211表型效应值最大为0.31,载体材料为‘滇屯502选早’。检测到与碱胁迫下种子萌发能力相关联的20个SSR位点,其中第3染色体与RM168和第4染色体与RM6314连锁位点的贡献率较大,分别达到39.17%和50.02%,优异等位变异RM6314-179表型效应值最大为0.58,载体材料为‘越6(N202)’。     

利用关联分析发掘小麦自然群体旗叶叶绿素含量的优异等位变异

为揭示小麦自然群体干旱胁迫条件下旗叶叶绿素含量的变化, 筛选相关标记的优异等位变异, 以262份小麦种质资源组成的自然群体为材料, 分别种植在北京的2个试验地点, 均设雨养和灌溉处理, 于开花期和灌浆期检测旗叶叶绿素含量。以分布于21条染色体的169个SSR标记检测所有材料的基因型, 利用STRUCTURE 2.3.2软件分析群体结构, 用TASSEL软件的MLM (mixed linear model)方法对小麦自然群体的旗叶叶绿素含量进行关联分析。在此基础上, 将携带某等位变异的所有材料表型均值与携带无效等位基因(null allele)材料表型均值比较, 估计等位变异的表型效应, 鉴别优异等位变异。共检测到2048个等位变异, 每位点2~37个等位变异, 平均12个。每位点的标记多态性信息量(PIC)为0.008~0.936, 平均0.628。在22个标记位点共检测出40个(次)与旗叶叶绿素含量极显著的关联, 其中11个标记位点有2次以上的关联, Xwmc419-1B和Xgwm501-2B分别有3次关联。在Xcfa2123-7A、Xgwm232- 1D和Xgwm429-2B位点分别检测到效应值大于4.0的等位变异。     

粳稻育成品种种子耐贮性的SSR关联分析

旨在发掘粳稻育成品种中与种子耐贮性相关联的优异等位变异和携带优异等位变异的载体材料。利用太湖流域和黑龙江省粳稻育成品种构成的群体为实验材料,调查了100 个品种种子耐贮性指数,利用259 对SSR标记对基因组进行扫描,采用Structure 软件进行群体分析,根据GLM(general linear model)方法对标记与耐贮藏性状进行关联分析;并以携带无效等位基因(null allele)材料的表型均值作为对照,鉴别出携带优异等位变异的载体材料。（1）太湖流域粳稻育成品种的耐贮藏能力、遗传多样性高于黑龙江省;（2）与种子耐贮性关联的标记总计有71 个,与苗高关联的SSR标记有17 个,贡献率最大的是RM6811(50.54%),增加表型效应值最大的等位变异是RM5753-215,载体材料为‘台粳16 号选紫’;与根长关联的SSR 标记有26 个,贡献率最大的是RM5753(49.3%),增加表型效应值最大的等位变异是RM5753-207,载体材料为‘垦稻12 号’;与干重关联的SSR 标记有28 个,贡献率最大的是RM5340(50.49%)和M24481 (50.51%),增加表型效应值最大的等位变异是RM180-101,载体材料为‘连粳4号’。     

SSR标记与陆地棉田间黄萎病抗性的关联分析

通过关联分析挖掘与陆地棉黄萎病抗性关联的分子标记,为陆地棉抗黄萎病性状的分子检测及标记辅助选择育种提供有益参考。选用在棉花基因组上均匀分布多态性较好的237个SSR标记对214份陆地棉材料的基因组变异进行了扫描,并使用Power Marker v3. 25分析群体的遗传多样性,Structure 2. 2分析群体结构,在此基础上结合3年黄萎病抗性鉴定数据,采用Tassel 2. 1中的GLM(Q)方法挖掘与黄萎病抗性相关的QTLs。结果表明,不同陆地棉材料黄萎病发病情况差异显著; 237个标记共检测到280个多态性位点,共计695个等位变异,变异范围2～6个,平均等位变异数2. 479 0;按照基因型数据可将该群体划分为2个亚群;通过关联分析,在不同年份中发掘与黄萎病抗性显著关联(P 0. 01)的SSR位点27个,其中有2个位点(BNL3442和BNL1064)在3年均被重复检测到,表型变异解释率最高分别为12. 10%和8. 02%。这些在不同年份中稳定存在的SSR标记位点有可能与抗病基因紧密连锁,有望用于棉花黄萎病抗性材料筛选和抗病基因挖掘。     

基于大豆胞囊线虫病抗性候选基因rhg1的InDel标记开发与鉴定

大豆胞囊线虫病是严重危害大豆生产的重要病害之一,根据抗病候选基因开发标记可为分子标记辅助选择抗病材料提供标记资源.本研究通过对大豆胞囊线虫抗性候选基因rhg1的序列比对分析,发现4个插入/删除位点,针对其中3个多碱基插入/缺失位点开发了InDel标记.应用开发的3个InDel标记对33份栽培大豆进行基因型鉴定,共检测到等位变异11个,平均每个位点3.67个.其中rhg1-I1位点有等位变异5个,rhg1-I2位点有等位变异2个;rhg1-I4位点有等位变异4个.各等位变异发生频率范围为0.8%～77.3%.InDel标记与大豆胞囊线虫抗性间的关联分析表明,rhg1-14为抗性相关标记,对抗病资源的检出效率为88.2%,对感病资源的检出效率为100%.该标记的288 bp等位变异和294 bp等位变异为抗病相关等位变异,269 bp等位变异和272 bp等位变异为感病相关等位变异.此标记与常用于标记辅助选择的Satt309配合鉴定可以提高SCN抗病资源的检测效率.     

以关联分析发掘小麦整穗发芽抗性基因分子标记

利用分布于小麦全基因组的181对分子标记,分析264份自然群体的基因型,采用TASSLE软件的GLM和MLM模型检测与整穗发芽抗性紧密关联的标记位点,发掘相关位点内的优异等位变异。在2012年和2013年室内整穗发芽率、2013年田间自然降雨整穗发芽率3个环境中,共关联到20个显著位点(P<0.05),分布于小麦染色体1AS、2DS、3AS、3BL、4AL、5AS、5BL、6BS、6DS、7AL和7BL上。分别位于2DS和7BL上的分子标记gwm102和barc340同时在3个环境下关联到,属于稳定的抗性位点; 另有6个标记位点同时在2个环境下关联到; 其余12个标记位点仅在1个环境下关联到。位于7BL上的barc340标记位点为一新报道位点。从重复关联的8个标记位点内共检测出10种优异等位变异。barc28-229bp和barc28-217bp对提高整穗发芽抗性效应最显著,主要分布在地方品种中(如遂宁坨坨麦等),而gwm102-142bp和barc186-199bp效应虽然相对较小,但多分布在推广品种中(如扬麦158等),有利于穗发芽抗性分子育种的直接应用。     

青稞遗传多样性及其农艺性状与SSR标记的关联分析

利用92个SSR标记对108份青稞亲本材料进行多态性扫描,分析其遗传多样性,旨在寻找与农艺性状相关联的分子标记,为青稞杂交组合的配制及分子标记辅助育种提供依据。挑选48个多态性标记进行群体遗传结构分析,在此基础上采用Tassel 2.1 GLM (general linear model)和MLM (mixed linear model)方法进行标记与农艺性状的关联分析。共检测出156个等位变异,每个位点2~6个等位变异。供试群体的Shannon指数为0.6727~1.1368,材料间遗传相似系数为0.2250~1.0000,平均0.7585。通过群体遗传结构分析将供试材料划分成4个亚群。以GLM分析,发现12个与株高、穗长、穗粒数和分蘖数相关联的标记,对表型变异的解释率分别为11.5%~17.6%、19.4%~45.4%、15.4%~22.1%和29.2%;以MLM分析,发现8个与株高、分蘖数和小穗数相关的标记,各标记对表型变异的解释率分别为31.7%~49.8%、28.1%~37.2%、22.7%~32.7%。关联标记分布在基因组全部6个连锁群上。     

Mapping association of molecular markers and sheath blight (<Emphasis Type="Italic">Rhizoctonia solani</Emphasis>) disease resistance and identification of novel resistance sources and loci in rice

Sheath blight (ShB) disease caused by Rhizoctonia solani is one of the major threats to rice crop world-wide. Progress in breeding for resistant rice varieties is limited due to lack of highly resistant germplasm against sheath blight. In present study, diverse rice landrace were phenotyped against R. solani and resistant and moderately resistant sources were identified from the panel of 134 germplasm pool. Landrace Nizam shait showed resistance, where as Bidar local-2, Jigguvaratiga, NavaliSali, Jaddu and Tetep exhibited moderate resistance. Population structure was analysed by genotyping the accessions using 63 genome wide Rice Microsatellite markers which divided the mapping panel into two groups. Association mapping using GLM?+?Q model of TASSEL indicated significant association between twenty-one marker loci on nine chromosomes with ShB resistance with phenotypic variation (R²) ranging 3.02–22.71 per cent. We identified 13 new markers to be associated with ShB resistance. The present work validates previously identified eight markers flanking different shB QTLs. None of the allele from the tested markers was unique and common among resistant and moderately resistant landraces identified in this work except allele 420 bp of RM337 and allele 310 bp of RM5556 noticed only in Tetep. Our findings predict the possible presence of unreported QTL region in marker interval of RM337 and RM5556 on chromosome 8 for ShB resistance in Tetep which invites further investigation.     

Morphological and genetic diversity analysis of rice accessions (Oryza sativa L.) differing in iron toxicity tolerance

A major emphasis in breeding for iron toxicity tolerance in rice is to identify differences that are associated with resistance and harness them for genetic improvement. In this study, thirty accessions, including IRRI gene bank accessions, two varieties from Brazil, 8 cultivars from West Africa and 10 cultivars from Uganda were analyzed for sensitivity to iron toxicity, and genetic diversity using morphological and SSR markers. Two genotypes, IR61612-313-16-2-2-1 and Suakoko 8 showed significantly high resistance with an average score of ≤ 3.5 on 1–9 scale. The SRR markers were highly informative and showed mean polymorphism information content (pic) of 0.68. The PIC values revealed that RM10793, RM3412, RM333, RM562, RM13628, RM310, RM5749, and RM154 could be the best markers for genetic diversity estimation of these rice cultivars. Diversity at the gene level showed an average of 4.61 alleles ranging from 2 to 12 per locus. Mean gene diversity (H) value for all SSR loci for the 30 genotypes evaluated was 0.69 but was decreased to 0.53 when analysis was performed on Ugandan accessions. The low genetic diversity found among the Ugandan accessions is the evidence of a narrow genetic base, and such a scenario has a potential vulnerability for resistance break down. A low correlation was detected between the observed molecular and morphological datasets. This means that a combination of morphological traits and SSR analysis would be required when assessing genetic variation under iron toxic conditions, and could be a practical strategy for breeders when planning crosses. A distinction between the resistant and susceptible accessions in both phenotyping and SSR datasets suggests the presence of unique alleles that could be harnessed for improvement of rice against iron toxicity.     

中国普通野生稻与栽培稻种SSR多样性的比较分析

采用48对SSR引物对288份我国普通野生稻和栽培稻的遗传多样性进行比较分析。结果显示, 共检测到505个等位基因, 每个位点的等位基因数变幅为5~20, 平均10.5个; 平均Nei基因多样性指数(He)为0.731, 变幅为0.384(RM409)~0.905(RM206)。普通野生稻遗传多样性高于栽培稻种, 栽培稻等位基因数和平均Nei基因多样性指数分别为普通野生稻的70.2%和88.2%, 其中, 栽培稻地方品种和选育品种等位基因数分别为普通野生稻的65.4%和53.0%, 选育品种等位基因数仅为地方品种的81.1%。AMOVA分析表明, 总变异的10.3%是由于种间SSR遗传差异所引起的, 不同SSR位点种间的分化程度不同, 在0.7%~46.3%之间, 有43个位点种间遗传分化达到显著水平, 其中以RM427分化最为明显, 达46.3%。聚类分析表明, 中国普通野生稻总体偏粳, 极少数广东、海南材料偏籼。     

Mining of favorable marker alleles for flag leaf inclination in some rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.) accessions by association mapping

Flag leaf angle (FLA) in rice (Oryza sativa L.) is one of the important traits affecting F₁ seed production by mechanization. To elucidate the genetic mechanism of FLA and mine favorable marker alleles for F₁ seed production in rice, we performed a genome-wide association study using phenotypic data over 2 years and genotypic data of 262 pairs of simple sequence repeat (SSR) markers collected from 441 rice accessions. We detected seven SSR marker loci associated with FLA and four loci were novel. The four newly found loci were RM6266 on chromosome 3, RM348 on chromosome 4, RM258 on chromosome 10 and RM7303 on chromosome 11. We found a total of 27 favorable alleles, of which four, i.e., RM348-130 bp, RM7303-90 bp, RM258-180 bp, and RM4835-230 bp, had phenotypic effects larger than 10°. Nine combinations, which increased FLA by 45.7°–94.7° through pyramiding the favorable alleles contained in seven typical accessions, were predicted.     

Genetic structure and association mapping of cold tolerance in improved japonica rice germplasm at the booting stage

Cold tolerance at booting stage is one of the major determinants for a stable yield of rice (Oryza sativa L.) in many high elevation or high latitude regions. Understanding the genetic basis of cold tolerance is crucial for the improvement of cold tolerance through breeding. In this study, association mapping was performed in 347 rice accessions worldwide with different statistical models in order to identify the genetic marker loci/QTL associated with cold tolerance traits at the booting stage. The evaluation of cold tolerance for all the traits was conducted under natural low temperature in Yunnan and cold water irrigation in Jilin. The 148 SSRs were used for the genotyping. Population structure analysis identified three main subpopulations for the accessions that corresponded to major geographic origins. The relative kinship analysis revealed a weak or no relationship for most of the individual pairs. Model comparisons indicated that the Q+K model controlling both population structure (Q) and the relative kinship (K) was performed better than other models in association mapping. In total, 24 markers were identified that were significantly associated with cold tolerance, including five markers in Yunnan and 19 markers in Jilin. Moreover, RM282, RM252, RM335 and RM6824 were identified in multiple environments or years. Many of these identified markers were located either in or nearby the regions where the QTLs have been reported for cold tolerance at booting stage. These results highlighted the targeted regions for future studies and might be subsequently used in breeding programs to trace and select the useful alleles by MAS.     

Genetic loci responding to two cycles of divergent selection for grain yield under drought stress in a rice breeding population

Molecular marker loci responding to selection under drought stress were monitored in a rice breeding population obtained by crossing a tolerant parent (Apo) to a susceptible parent (IR64). The 40 highest-yielding lines under stress and non-stress conditions obtained after two cycles of divergent selection under drought stress and non-stress conditions, respectively were genotyped using 72 polymorphic and widely distributed SSR markers. Ten loci (RM572, RM6703, RM71, RM3387, RM5686, RM520, RM510, RM256, RM269 and RM511) showing highly significant allele frequency differences between the two sets were identified. Favorable alleles at eight of these loci came from the tolerant parent, and at two (RM3387 and RM510) from the susceptible parent (IR64). Effects of these loci on grain yield were tested in five independent experiments covering a range in soil moisture levels. Results showed that at six loci (RM572, RM6703, RM520, RM256, RM269, and RM511), Apo alleles had highly significant effects on grain yield in at least three of the four stress trials but only two of these loci (RM572 and RM511) also affected grain yield under non-stress conditions. In all these cases, the effects of loci generally increased with stress level. Apo alleles at these loci seem to enhance yield under stress mainly by increasing harvest index and reducing flowering delay. Large-effect quantitative trait loci (QTLs) affecting grain yield under upland drought stress have already been found previously in other populations near RM6703, RM520, and RM511. Thus, these regions appear to be important in explaining genetic variation for upland drought tolerance in rice.     

大豆品种资源抗灰斑病7号生理小种优异等位变异的发掘

本文旨在发掘大豆品种资源中抗灰斑病7号生理小种优异等位变异,为培育抗灰斑病品种提供遗传信息和载体材料。以202份大豆品种为试验材料,鉴定材料抗灰斑病7号生理小种的抗病性。利用SSR标记进行全基因组扫描,采用TASSEL 3.0软件的GLM模型和MLM模型对大豆品种的灰斑病抗性与标记进行关联分析。结果表明,2种模型共同检测到12个与灰斑病7号生理小种抗性显著关联的位点,各标记对表型变异的解释率为2.00%~15.47%,共同检测到增效作用的等位变异共有20个,其中增效表型效应值最大的等位变异是Satt549-263(18.88),载体材料为‘合丰29’;其次为Satt372-291(17.92),载体材料为‘合丰34’。发掘到的等位变异信息和载体材料为培育抗灰斑病品种亲本选配和后代等位条带辅助选择提供了依据。     

Identification of a diverse mini‐core panel of Indian rice germplasm based on genotyping using microsatellite markers

Identification of a small core germplasm set representing the available genetic diversity is essential for its proper evaluation and subsequent utilization in rice improvement programmes. For constituting a small diverse mini‐core panel of Indian rice germplasm, a representative set of 6912 accessions drawn based on their geographic origin from the whole rice germplasm collection available in the National Gene Bank was genotyped using 36 microsatellite markers. Automated fragment analysis of amplicons yielded a total of 435 alleles, with an average 12.4 and range of 3–29 alleles per locus. Polymorphism information content (PIC) ranged from 0.08 (RGNMS190) to 0.86 (RM552) with an average of 0.528. Based on genotyping data, a mini‐core consisting of 98 genotypes was identified. Ninety‐four per cent of the alleles present in the core set were present in the mini‐core. The identified small but diverse panel will be useful for further intensive trait‐specific evaluation and utilization in allele mining.     

Resistance to rice sheath blight (<Emphasis Type="Italic">Rhizoctonia solani</Emphasis> Kühn) [(teleomorph: <Emphasis Type="Italic">Thanatephorus cucumeris</Emphasis> (A.B. Frank) Donk.] disease: current status and perspectives

Sheath blight (ShB) disease, caused by Rhizoctonia solani, is an economically important rice disease worldwide, especially in intensive production systems. Several studies have been conducted to identify sources for ShB resistance in different species of rice, including local accessions and landraces. To date, none of the genotypes screened are immune to ShB, although variation in levels of resistance have been reported. Several quantitative trait loci (QTL) for ShB resistance have been identified using mapping populations derived from indica or japonica rice. A total of 33 QTL associated with ShB resistance located on all 12 rice chromosomes have been reported, with ten of these co-localizing with QTL for morphological attributes, especially plant height, or for heading date. Sixteen QTL, from the same or differing genetic backgrounds, have been mapped at least twice. Of these, nine QTL were independent of morphological traits and heading date. We hypothesize that two main, distinct, mechanisms contribute to ShB resistance: physiological resistance and disease escape. Strategies to improve our understanding of the genetics of resistance to ShB are discussed.