小麦株高相关性状与SNP标记全基因组关联分析

株高是影响小麦产量和控制倒伏的重要因素,研究小麦株高相关性状的遗传机制对高产育种具有指导意义。以205份中国冬麦区小麦品种(系)为材料,利用分布于小麦全基因组的24 355个单核苷酸多态性(SNP)标记对株高相关性状进行关联分析。共发现38个与株高相关性状显著关联(P0.0001)的SNP,分布在1B、2A、2B、3A、3B、3D、4A、4B、5A和6D染色体上。其中,11个位点至少在2个环境中稳定表达,可用于开发CAPS标记。同时,发掘了一批株高性状相关基因的优异等位变异,如降低株高的等位变异Bob White_c48009_52,平均降低株高12.9 cm;控制穗下节间长的等位变异BS00039422_51-C和IAAV1698-A,分别调控穗下节间长5.9 cm和6.6 cm。本研究发掘的控制小麦株高基因位点为在分子水平上研究小麦株高复杂性状提供了有价值的参考。     

野生二粒小麦主要农艺特性融入普通小麦的全基因组关联分析

野生二粒小麦(Triticum turgidum ssp.dicoccoides)是普通小麦的四倍体祖先种,具有广泛的基因型变异,是改良普通小麦的重要种质资源。本研究对不同年份和地点四个环境下的161份野生二粒小麦渗入系材料的株高、分蘖数、小穗数、抽穗期、开花期和千粒重进行表型鉴定,并利用覆盖全基因组的13,116个DArT标记对各农艺性状进行全基因组关联分析,以期发掘性状显著关联标记及相关候选基因。本研究共检测到147个与6个农艺性状相关的稳定标记。其中,一些关联标记与抽穗期和开花期同时相关,并且在2B染色体上聚集成簇。在野生二粒小麦渗入系群体中共推定了21个与农艺性状相关的候选基因,其中位于7A染色体与千粒重显著相关的候选基因与细胞周期蛋白有关。这些标记和候选基因可为克隆优异农艺性状相关基因提供重要信息,从而为野生二粒小麦在普通小麦背景中的遗传改良综合利用提供依据与指导。     

玉米棒三叶叶型性状的全基因组关联分析

玉米棒三叶(穗上叶,穗叶及穗下叶)对玉米单产的形成起着至关重要的作用,为了深入剖析玉米各性状的遗传基础及挖掘相关性状的基因,本研究以253份玉米自交系为关联群体,利用分布于玉米全基因组上的558 529个单核苷酸多态性标记(SNPs)对玉米棒三叶的叶长、叶宽及叶面积进行全基因组关联分析。结果表明,通过对关联群体性状进行统计可知,不同性状变异系数在17.00%～31.00%,变异丰富;且各性状的峰度和偏度都在-1～1之间,呈典型的数量性状遗传;方差分析也表明,各性状在基因型间都达到极显著差异;相关性分析及层次聚类分析发现,关联群体的各性状间均呈现显著或极显著(P<0.05或P<0.01)正相关关系,且各性状间共同影响着玉米干物质的积累。由主成分分析(principal component analysis, PCA)可知,在棒三叶叶长、叶宽及叶面积间可筛选出对总体方差累计贡献率达89.436%的两个主成分,表明这两个主成可以代表棒三叶叶型性状的绝大多数信息。以P≤3.99×10^-6为显著阙值,利用Q模型对供试群体进行关联分析,在玉米叶长、叶宽及叶面积间共...     

小麦茎秆断裂强度相关性状QTL的连锁和关联分析

小麦茎秆断裂强度与倒伏特性关系密切,并对产量有很大影响。本研究旨在解析茎秆断裂强度的遗传机制,开发与该性状紧密连锁/关联的分子标记。利用山农01-35′藁城9411重组自交系(RIL)群体(含173个F8:9株系)和由205个品种(系)构成的自然群体,借助90 k小麦SNP基因芯片、DArT芯片及传统分子标记技术,在2个环境中对两群体的茎秆断裂强度相关性状进行连锁分析和全基因组关联分析。利用已构建的高密度连锁图谱,在4B染色体的TDURUM_CONTIG63670_287–IACX557和EX_C101685–RAC875_C27536等区段上,检测到9个控制小麦茎秆断裂强度、株高、茎秆第2节间充实度、茎秆第2节壁厚相关性状的加性QTL,可解释表型变异9.40%~36.30%。同时,利用包含24 355个SNP位点的复合遗传图谱,在自然群体中检测到37个与茎秆断裂强度相关性状(P0.0001)的标记,分别位于1A、1B、2B、2D、3A、3B、4A、4B、5A、5B、5D、6B、7A、7B和7D染色体,可解释表型变异7.76%~36.36%。在4B染色体上,以连锁分析检测到控制茎秆断裂强度的RAC875_C27536与关联分析检测到的Tdurum_contig4974_355标记,在复合遗传图谱上的距离为6.7 cM,说明该区段存在控制小麦茎秆断裂强度的重要基因。     

大豆叶型性状全基因组关联分析与候选基因鉴定

大豆叶片的形状和垂直分布影响群体冠层结构和光合效率并最终影响大豆的产量。植物叶片大小、形态因着生位置不同而产生差异的现象称为异形叶,虽然异形叶现象在被子植物中广泛存在,但目前关于大豆叶片发育过程中异形叶的调控的研究还很有限。本研究通过对283份大豆种质资源的叶长、叶宽、叶形指数和异形叶指数等叶型相关的性状在江苏南京进行连续2年的考察,利用全基因组关联分析检测到181个叶型性状相关位点,其中能够在2个环境或多个性状中重复检测到的位点18个。利用检测到的与叶型相关的SNP位点,结合基因的表达谱数据、拟南芥中同源基因的功能,鉴定与大豆叶片发育和异形叶形成相关的候选基因。其中在20号染色体的相关位点Chr20:36152820上游发现已知的大豆叶形调控基因Ln (Glyma.20G116200)。此外,在19号染色体的相关位点Chr19:45155943附近鉴定到2个候选基因Glyma.19G192700、Glyma.19G194100,分别被注释为Growth-regulating factor 4 (GRF4)和LITTLE ZIPPER 3 (ZPR3)基因的同源基因,为阐明大豆异形叶等...     

玉米种子萌发相关性状的全基因组关联分析

种子萌发是出苗的前提, 对玉米产量影响重大。为了解玉米种子萌发相关性状的遗传机制, 本研究对476份玉米自交系种子萌发相关的6个性状进行调查, 结合125万个(1.25M) SNP标记, 利用3种统计模型(Q, K, Q+K)进行全基因关联分析(GWAS)。结果表明K模型能够较好地评价吸胀前重量、吸胀前体积、吸胀后重量、吸胀后体积和吸胀体积5个性状; Q+K模型能更好地评价吸胀重量性状。基于这6个性状的最优模型的GWAS结果, 共检测到15个种子萌发相关性状的显著SNP, 15个SNP对应6个QTL, 集中分布在玉米第3、第6、第7和第10染色体上, QTL内单个SNP能解释的表型变异为5.09%~7.85%。其中5个QTL可在多个生物学重复中被检测到。以最显著SNP所在基因或附近基因作为QTL的候选基因, 共筛选到6个最可能的候选基因。GRMZM2G148411是吸胀后重量、吸胀重量和吸胀体积3个性状共同鉴定到的QTL候选基因, 根据基因的功能注释, 该基因编码一个包含TLD-domain的钙离子结合蛋白, 可能是一种调控种子休眠与萌发的信号分子。本研究鉴定的QTL为解析玉米种子萌发的遗传机制和相应功能标记的开发奠定了基础。     

全基因组关联分析在作物中的研究进展

全基因组关联分析(genome-wide association study, GWAS)是2005年左右出现的一种用于开展连锁标记开发和基因挖掘等研究的有效方法,并在多种作物中得到了广泛应用。本研究阐述了GWAS的原理、优点和主要研究方法以及在粮食作物、经济作物、糖料作物等作物中的研究进展,同时对作物GWAS研究的未来进行了展望,以期为进一步利用GWAS进行作物各种性状遗传基础的研究提供参考。     

玉米粒宽的全基因组关联分析及候选基因结构预测

粒宽与产量有显著正相关性,为了筛选与玉米粒宽紧密关联的SNP位点和控制粒宽的相关的候选基因,本实验采用全基因组关联分析的方法,以139份核心玉米自交系为关联群体,对其粒宽进行考种测量。同时利用6 973个高质量的SNP标记,结合表型数据进行全基因组关联分析。关联分析结果共检测到21个与玉米粒宽显著性相关的SNP位点,在LD衰退有效距离上下20 kb范围内挖掘到2个候选基因,与前人报道的完全一致,分别是主要编码叶绿体中钠代谢物共转运体BASS4 (GRMZM2G092475)、含SWIB复合BAF60b结构域的蛋白(GRMZM2G124502)。本研究为进一步了解粒宽的遗传结构和研发高产品种具有一定的理论基础。     

普通菜豆根系相关性状的关联分析

幼苗期根系发育对作物的生长发育具有重要作用。利用生长袋纸培系统对324份普通菜豆种质的主根长、根干重、根体积、根表面积等9个根系相关性状进行表型鉴定,并结合覆盖全基因组、有多态性的116对SSR标记,利用MLM（Q+K）模型进行表型和标记的关联分析。表型分析表明,324份材料的9个根系相关性状表型变异丰富,平均变异系数的变动范围是10.09%~37.03%;基因型分析表明,116个多态性SSR标记共检测到919个等位变异位点,每个标记的平均基因多样性指数为0.59,多态性信息含量（PIC）平均值为0.54,显示这些标记具有较高的基因多样性;群体结构分析表明,供试材料分为两个亚群,与普通菜豆起源于两个基因库对应;关联分析结果显示,以P<0.01作为显著条件,共检测到48个显著标记位点,其中有10个位点同时与2个以上性状相关联,有5个位点与前人研究结果一致。研究结果为进一步理解普通菜豆根系的遗传机理提供了理论参考,也为分子标记辅助选择改良普通菜豆根系奠定了基础。     

Genetic variation for nitrogen use efficiency in winter wheat (Triticum aestivum L.)

Summary The new European Common Agricultural Policy and environmental considerations are certainly to change agricultural practices toward low input cultivation systems. Nitrogen is one of the main inputs of winter wheat in northern France and it contributes highly to phreatic water pollution. A research programme has then been set up in order to study whether it is possible to breed for winter wheat cultivars using more efficiently N fertilisers. Less nitrogen would be applied, decreasing pollution risks and operational costs. It has been shown that a large variation exists for N related traits and for the resistance against N deficiency. On the one hand the cv Arche is very resistant to N deficiency, its yield on low N conditions (with no N fertiliser) is on average 89% of its yield on high N conditions (with a high N application). On the other hand, cv Récital is very susceptible to N deficiency as this same percentage is only 61%. A study on 10 hybrids showed that heterosis for grain yield was higher at low N level than at high N level. This was due to a higher number of grains per m².     

Genetic control of boron efficiency in wheat (Triticum aestivum L.)

The genetic control of boron (B) efficiencyin wheat (Triticum aestivum L.) wasstudied for three genotypes representing Binefficient (I, Bonza), moderately Binefficient (MI, SW 41) and B efficient (E,Fang 60) categories. Boron efficiency wasexpressed as a partially dominant characterbut the phenotypes of F₁ hybrids,relative to parents, indicated geneticcontrol varying from recessive to additiveto completely dominant with different crosscombinations and B levels. Major geneswere identified from the evaluation ofF₂-derived F₃ populations derivedfrom intercrosses between the threeparents. Monogenic segregation was foundin Bonza × SW 41 and SW 41 × Fang 60crosses and digenic segregation resultedin Bonza × Fang 60. Among thethree wheat genotypes with widely differentB efficiency, genetic variation forresponse to B could be accounted for by twogenes, Bo _d 1 and Bo _d 2.     

Genome-wide association study reveals loci associated with seed longevity in common wheat (Triticum aestivum L.)

Seed longevity could significantly determine seed regeneration cycle and greatly affect wheat production. With the 90 K chip assays, a genome-wide association study was performed to identify seed longevity-related markers and loci in common wheat. Seed germination ratios (GR) under artificially ageing of 166 wheat accessions across three environments were evaluated to assess seed longevity. Totally, 23 longevity-related loci were identified in the study, explaining 6.7%–11.4% of the phenotypic variations. Of these, QlgGR.cas-1A and QlgGR.cas-2B.2 were deemed as stable loci associated with wheat seed longevity. Fifteen loci were found overlapped with known quantitative trait loci or genes. Besides, QlgGR.cas-1A, QlgGR.cas-2B.2, QlgGR.cas-3D.1, QlgGR.cas-3D.2, QlgGR.cas-4A.2, QlgGR.cas-5A.1, QlgGR.cas-5A.2 and QlgGR.cas-6A.1 were colocated with seed dormancy-related loci. Significant additive effects were obtained for seed longevity by pyramiding favourable alleles. Several candidate genes were found involved in signal transduction and stress resistance pathways by sequencing analysis of significantly longevity-related molecular markers. These results might provide new sights into the genetic architecture of seed longevity.     

Breeding for increased nitrogen‐use efficiency: a review for wheat (T. aestivum L.)

Nitrogen fertilizer is the most used nutrient source in modern agriculture and represents significant environmental and production costs. In the meantime, the demand for grain increases and production per area has to increase as new cultivated areas are scarce. In this context, breeding for an efficient use of nitrogen became a major objective. In wheat, nitrogen is required to maintain a photosynthetically active canopy ensuring grain yield and to produce grain storage proteins that are generally needed to maintain a high end‐use quality. This review presents current knowledge of physiological, metabolic and genetic factors influencing nitrogen uptake and utilization in the context of different nitrogen management systems. This includes the role of root system and its interactions with microorganisms, nitrate assimilation and its relationship with photosynthesis as postanthesis remobilization and nitrogen partitioning. Regarding nitrogen‐use efficiency complexity, several physiological avenues for increasing it were discussed and their phenotyping methods were reviewed. Phenotypic and molecular breeding strategies were also reviewed and discussed regarding nitrogen regimes and genetic diversity.     

Genetic improvement of bread wheat (Triticum aestivum L.) in Argentina: relationships between nitrogen and dry matter

Summary Changes in nitrogen (N) economy and N to dry matter (DM) relationships were studied for six cultivars of bread wheat (Triticum aestivum L.) released in Argentina at different times between 1912 and 1980. Experiments were performed on two successive years.N partitioning to reproductive organs was changed both at anthesis and at maturity. Grain N yield (GNY) was associated to both total N accumulated and N partitioning. Most of the changes produced by genetic improvement on N economy at maturity could be explained by parallel changes at anthesis. Neither biological N yield (BNY) at anthesis nor BNY at maturity showed any trend with the year of release of the cultivars.Grain N concentration (GNC) showed a negative trend with the year of release, and was inversely correlated to both grain yield (GY) and harvest index (HI). However, GNC was positively and significantly associated with NHI to HI ratio, indicating that the main reason for its behaviour along this century was the dilution of N on non N compounds.The N utilization efficiencies (NUE) for both GY and grain number were positively affected by breeding. Moreover, modern Argentinian cultivars are as efficient as the best cultivars showed by other authors.It is suggested that to increase GNC together with GY, breeders should improve N accumulation at anthesis maintaining high remobilization of vegetative N.     

Several stably expressed QTL for spike density of common wheat (Triticum aestivum) in multiple environments

Spike density (SD), an important spike morphological trait associated with wheat yield, is the spikelet number per spike (SNS) divided by spike length (SL). In this study, phenotypic data from eight environments were collected and a recombinant inbred line population (RIL) constructed by the wheat line 20828 and the cultivar 'Chuannong16' and a Wheat55K SNP array-based constructed genetic linkage map were used to identify SD quantitative trait locus (QTL). Correlation between SD and other agronomic traits was calculated. Genes associated with plant growth and development for major loci were predicted. The results showed that 24 QTLs associated with SD were detected in eight environments. Among them, three major QTL, namely QSd.sicau-5B.2, QSd.sicau-2D.3 and QSd.sicau-4B.1, explained up to 35.62%, 14.21% and 11.23% of phenotypic variation, respectively. The positive alleles of them were all derived from 'Chuannong16'. The significant relationships between SD and other agronomic traits were detected and discussed. Taken together, the stably expressed SD QTL under different environments identified in this study provided theoretical guidance for further fine mapping and germplasm improvement.     

甘蓝型油菜角果长度性状的全基因组关联分析

角果长度是油菜重要的农艺性状,适度增加角果长度有利于扩大角果库容量,增加光合面积,提高油菜的籽粒产量。本研究利用Illumina60KSNP芯片对496份具有代表性的油菜资源进行基因型分析,考察群体在4个环境中的角果长度表型,利用MLM和GLM模型进行全基因组关联分析。结果表明, MLM模型检测到7个位点,联合解释25.01%的表型变异; GLM模型检测到25个位点,联合解释41.77%的表型变异。合并共同位点后得到27个位点,其中7个与前人报道的QTL重叠,其余20个是新鉴定的位点。效应最大的位点Bn-A09-p29991443位于A09染色体,在MLM和GLM模型中分别解释13.89%和12.86%的表型变异,携带其优异等位基因的材料平均角果长度增加0.89cm。同时,在该位点附近找到已克隆的油菜角果长度基因ARF18和BnaA9.CYP78A9。此外,在5个位点附近发现拟南芥已知角果长度基因GID1b、FUL、EOD3、DOF4.4和GA20ox1的同源拷贝。本研究结果有助于解析角果长度的遗传基础,为研究角果长度的调控机理,指导角果长度的遗传改良打下基础。     

甘蓝型油菜千粒重全基因组关联分析

千粒重是油菜产量构成的重要因素之一。本研究利用高通量SNP芯片对496份具有代表性的油菜种质资源进行基因型分析,考察群体在3个环境(14NJ、15TZ、16TZ)中的千粒重表型,利用混合线性模型(mixed linear model,MLM)和一般线性模型(general linear model,GLM)进行全基因组关联分析。结果表明,本群体在3个环境中千粒重的广义遗传力为63.12%。MLM模型检测到6个显著位点,解释28.92%的表型变异;GLM模型检测到61个显著位点,解释47.08%的表型变异。合并共同位点后得到62个显著位点,联合解释47.31%的表型变异。这些位点分布在基因组所有染色体上,在A07、A03和C06染色体上分别检测到数目最多的9、8和7个位点。其中效应最大的位点Bn-scaff_17526_1-p1066214位于C09染色体,在MLM和GLM模型中表型贡献值分别为5.55%和15.26%。21个位点与前人报道的QTL重叠,其中8个位点得到至少2个群体的验证。其余41个位点为新鉴定的位点,其中多个位点效应高且在多环境中被检测到,如位点Bn-A03-p560769、Bn-scaff_15743_1-p599416和Bn-scaff_15743_1-p590955等。在11个位点附近找到DGAT、EOD3、AGL61、WRI1、DA2、RAV1等拟南芥已报道千粒重基因的同源基因。本研究结果有助于解析甘蓝型油菜千粒重的遗传基础,为研究千粒重的调控机制、指导千粒重的遗传改良奠定基础。     

Limited but specific variations of seed storage proteins in Japanese common wheat (Triticum aestivum L.)

The electrophoretic banding patterns ofgliadin in common wheat lines derived fromJapan were determined byacid-polyacrylamide gel electrophoresis. For the 107 wheat lines used in our study,27 different patterns were identified, 13corresponding to the -gliadin, 8 tothe , -gliadin and 6 to the-gliadin. The gliadin patterns ofJapanese wheat cultivars and landracesgreatly differed from the patterns of wheatlines from other countries, and thevariation seen in wheat lines from Japanwas limited to 46 patterns. Sevencollection or breeding areas in Japanshowed different frequencies in theirgliadin patterns. Combining the gliadinpatterns with high molecular weightglutenin subunit compositions, 67combinations were observed. One gliadinpattern consisting of -gliadinpattern F, , -gliadinpattern H and -gliadin pattern Dwas frequently found in many Japanese wheatlines, though the other patterns werelimited to only one or two wheat lines.     

普通小麦主要农艺性状的全基因组关联分析

为解析小麦复杂农艺性状的遗传机制,本研究以150份小麦品种(系)为自然群体,在4个环境条件下测定了9个主要农艺性状,利用小麦35K SNP芯片,结合5种关联模型(Q、PCA、K、PCA+K、Q+K),进行全基因组关联分析。结果表明,全基因组多态性信息量PIC的范围为0.0950～0.5000,最小等位基因频率MAF值为0.0500～0.5000;群体结构分析和PCA分析均表明参试材料可分为两个亚群;连锁不平衡分析发现A基因组、B基因组、D基因组和全基因组的LD衰减距离分别为4.7、8、11和6 Mb。9个性状共检测到652个显著的关联位点(P≤0.001),其中21个SNP在2个或2个以上的环境中被重复检测到,分布在1A(1)、1B(4)、2A(3)、2D(2)、3A(1)、5A(1)、5B(5)、6A(1)、6B(2)和7D(3)染色体上; 1个SNP标记的物理位置未知, 3个SNP标记同时与2个性状显著关联;单个SNP的表型贡献率为7.67%～18.79%。8个优势等位变异在供试群体中所占比例较低,筛选出14个可能与小麦农艺性状相关的候选基因,其中TraesCS5B02G237200、TraesCS7D02G129700和TraesCS1B02G426300可能在植物抵御生物与非生物胁迫中起作用,TraesCS5B02G010800和TraesCS7D02G436800可能与植物激素的合成和响应有关,TraesCS2A02G092200可能与植物细胞壁的增强有关, TraesCS5A02G438800可能参与叶绿体发育,另外7个候选基因的功能未知。