大豆重组自交系群体荚粒性状的QTL分析

利用大豆重组自交系soy01群体中的255个家系进行2年田间试验，采用两种作图方法，寻找一粒荚、四粒荚、每荚粒数等5个荚粒性状稳定的QTL。结果表明，利用区间作图法，2年共找到24个荚粒性状QTL，解释的遗传变异为5%~80%；利用复合区间作图法，2年共找到27个荚粒性状QTL，解释的遗传变异为4%~73%。利用复合区间作图法，2年找到2个重复出现、稳定的四粒荚QTL和2个每荚粒数QTL，为大豆荚粒性状QTL的精细定位和分子标记辅助育种提供了基础和依据。     

大豆叶形分布与四粒荚

对64份遗传稳定材料和8l份F_1的分析发现,在下阔叶-上阔叶类型中没有四粒荚材料,在下阔叶-上窄叶类型中绝大部分材料有四粒荚;而在下窄叶-上窄叶类型中,全部材料都是四粒荚类型。通过对一个组合的F_2叶形分布型进行分析,初步明确叶形分布受一对基因控制,下阔叶-上窄叶类型对下窄叶-上窄叶类型为显性;中部叶形变化较大,下部叶片次之,顶部叶片的叶形变化最小。在F_1中有些没有阔叶的材料也有四粒荚出现,但并非所有有窄叶的F_l材料都有四粒荚。窄叶基因对四粒荚的产生固然起到十分重要的作用,却不是四粒荚形成的唯一原     

大豆多四粒荚创新种质‘汾豆96’选育及理想模型构建

旨在选育多四粒荚大豆品种,构建理想模型,为大豆高产超高产育种探索新途径。用spss 18分析‘汾豆96’生理生态特性,以椭圆叶形多四粒荚‘汾豆96’为主,结合34份披针叶形四粒荚材料,对其10项产量相关的农艺性状用逐步回归法构建理想模型。‘汾豆96’群体内四粒荚单株的存在率达85%以上,单株四粒荚最高达49个,占总荚数的30.25%,‘汾豆96’产量随四粒荚数的增加总体呈增加趋势。当R~2=0.939时,模型拟合最优:Y=-87.583+0.415X_1-5.155X_2+10.094X_3+13.459X_4。回归方程表明多四粒荚创新材料产量与生物产量(X_1)、株高(X_2)、百粒重(X_3)和主茎节数(X_4)呈显著线性回归关系。提升每荚粒数和选育多四粒荚品种,是高产超高产育种产量突破的新途径。大豆品种具备的理想模型是抗倒伏、多荚粒、适合机械化收获的短节间密荚类型。     

应用荚粒库容对大豆种质群的分类

应用荚粒库容,能够准确地描述大豆种质的单荚结实能力;能够更好地解释大豆荚粒数遗传与变异的现象;并能够将现有大豆种质群,按荚粒库容的不同进行分类。     

大豆单株荚数QTL定位及整合

大豆单株荚数是构成大豆产量的重要因素之一,同时在大豆种质资源中也是一个变异范围较广的性状,为了有助于大豆单株荚数分子选择育种,以大豆多荚材料C025和少荚材料JD18为亲本,以通过杂交构建的F2群体为材料,对亲本及遗传群体进行2 a(太原2017、太原2018)表型性状和基因型数据分析,同时结合利用已知的大豆SSR遗传图谱,结果显示,共定位大豆单株荚数QTLs 33个,解释的表型变异为0.2%～56. 4%;通过元分析整合最终共定位大豆单株荚数23个QTLs,其中有5个QTLs(q PN. C2-3、q PN. I、q PN. C2-4、q PN. C1和q PN. L)与前人的研究重叠,分别位于C2、N、C1这3条染色体上;其余18个QTLs是研究发现的控制大豆单株荚数新的QTLs(q PN. D1a、q PN. N、q PN. C2-1、q PN. C2-2、q PN. M、q PN. A2-1、q PN. A2-2、q PN. K、q PN. O-1、q PN. O-2、q PN. B1、q PN. F、q PN. B2、q PN. E、q PN. J、q PN. D2-1、q PN. D2-2、q PN. G)。q PN. A2-1、q PN. C2-4和q PN. C1(贡献率分别为56. 4%,29. 5%,35. 4%)这3个QTLs可被多环境重复检测且贡献率较高,因此,其可以作为主效QTL进行后续大豆单株荚数分子研究。由于大豆单株荚数是一个易受环境影响且由多位点控制的复杂数量性状,研究检测到一些新的QTLs,并且也验证了一些前人检测的大豆单株荚数QTLs,同时整合目前比较完善的大豆单株荚数QTLs。     

大豆单株荚数与主要农艺性状关系的分析

本试验采用适合黑龙江省第四积温带种植的21个大豆品种（系）,通过田间调查、室内考种,进行关联度分析、相关和通径分析,得出单株英数与百粒重、每英粒数、主茎节数、生育前期、生育后期、茎粗等农艺性状关系密切,因此对单株荚数进行选择时,应突出百粒重、每英粒数、主茎节数、生育前期、生育后期、茎粗等农艺性状的选择。     

不同熟期大豆品种花荚形成及垂直分布比较

以早熟品种垦18号、中熟品种黑农41号、晚熟品种吉育60号为试材,对其开花和成荚进程及垂直分布进行比较分析,结果表明,早熟品种开花成荚速率快,花荚重叠期时间长,中熟及晚熟品种荚期后移,荚生长期长,花荚重叠期明显缩短。     

水稻穗粒数相关基因研究进展

穗粒数作为影响水稻产量的主要因素之一,一直深受育种家的广泛关注。穗粒数形成受小穗分生组织分化率、小穗分化持续时间及穗型等多因素控制,是个十分复杂的生物学过程。随着植物功能基因组学研究技术的飞速发展,目前水稻穗粒数基因克隆及机理研究等方面已取得了一些进展。本研究从穗分生组织发育、穗型等方面阐述了调控水稻穗粒数发育基因的研究进展,探讨了当前水稻穗粒数研究所存在的问题和未来的研究方向,以期待为水稻高产育种提供理论依据。     

Identification and validation of number of pod ‐ and seed ‐ related traits QTLs in soybean

Traits related to the number of pods and seeds are important yield factors on soybean. The relationships between phenotype and quantitative trait loci (QTLs) of these traits may reveal the mechanisms underlying productivity. Our study objectives were to analyse phenotypic correlations, detect stable QTLs and identify candidate genes useful for marker‐assisted selection. Phenotypic analyses revealed that NThSP (number of three‐seeded pods) was positively correlated with NPPP (number of pods per plant) and SNPP (number of seeds per plant). Seventy‐five QTLs were identified based on the mean phenotypic data for at least 2 years. We detected two to 15 and one to three significant QTLs identified at the same location, respectively. Six consensus QTLs associated with at least two NPS‐related (number of pods and seeds related) traits were identified. Two of these were verified in another population. The QTLs for NPPP, SNPP and NThSP formed a consensus QTL cluster on GM02. Another 27 QTLs also formed clusters in five regions. Fifteen candidate genes were mined and discussed. The results will provide more information to soybean breeding.     

甘蓝型油菜每角粒数的全基因组关联分析

每角粒数是油菜重要的产量构成因子,增加每角粒数有助于提高油菜的籽粒产量。利用Illumina 60K SNP芯片对496份具有代表性的油菜资源进行基因型分析,考察该群体在2个环境中的每角粒数,利用MLM和GLM模型进行全基因组关联分析。结果表明,本群体在2个环境中每角粒数的广义遗传力为57.7%。利用MLM和GLM模型分别检测到9个和20个位点,所有MLM位点均得到GLM结果的验证。6个位点与前人定位的QTL重叠,其中2个位点得到2次验证,其余14个是新位点。在7个位点附近找到了候选基因,其中在C09染色体的位点Bn-scaff155761-p74980附近找到已克隆的油菜每角粒数基因BnaC9.SMG7b,在其余6个位点附近找到GRDP1、SPATULA、HVA22D、DA2等已知的拟南芥每角粒数基因的同源基因。本研究结果有助于解析油菜每角粒数的遗传基础及其调控机制,为每角粒数的遗传改良奠定了基础。     

Optimum number of crosses and progeny per cross in breeding self-fertilizing crops. I. General approach and first numerical results

Summary Based on maximization of selection response, Peek (1986) proposed methodology for determining the optimum number of crosses and progeny per cross in breeding self-fertilizing crops. By this method the total selection response is obtained by adding the individual responses from the two steps of selection: selection between crosses and selection within crosses. In this paper, Peek's approach has been generalized for finite or nonnormal populations. Optimum numbers of crosses are determined by testing capacity, number of selected crosses, number of selected lines from each selected cross, and heritability.In the case selection of the best line from the best cross, the optimum number of crosses increases monotonically with increasing testing capacity (for any given fixed heritability). For increasing heritabilities, however, the optimum number of crosses exhibits relatively flat maxima (for any given fixed testing capacity). These maxima are located at intermediate or sub-intermediate heritabilities.For varying numbers of selected crosses and selected lines from each selected cross the main results are: The optimum number of crosses i) increases with increasing testing capacity, ii) increases with increasing number of selected crosses and iii) decreases with increasing number of selected lines from each selected cross.     

授粉方式与蜂群群势对杂交大豆授粉效果的影响

为提高大豆不育系的异交结实率,研究了授粉方式与蜂群群势对杂交大豆产量与品质的影响。采用人工授粉、自然授粉和蜜蜂授粉3 种方式,小蜂箱蜂脾1 脾、2 脾、3 脾3 种蜂群的群势对网室杂交大豆进行授粉。统计分析大豆花期采集蜂数量、采集蜂出勤规律、不同节位的结荚率、父母本大豆产量性状,比较3 个处理方式的授粉效果。随着网室内蜜蜂脾数的增加,出勤采集蜜蜂数量也随之增加,蜜蜂访花最活跃的时间均集中在9:00—13:00。不论是自然授粉还是蜜蜂授粉,都表现为母本中上部节位的结荚率高于下部。与自然授粉相比,蜜蜂授粉杂交大豆母本的单株结荚率、单株粒数、十株产量显著提高(P＜0.01),百粒重有所减少。蜜蜂授粉方式优于自然授粉和人工授粉方式,1 脾蜜蜂授粉区内单株荚数为49.4 个,单株粒数为96.1 个,百粒重为20.8 g,十株产量为196.6 g。蜜蜂授粉提高了母本的大豆结籽产量,小蜂箱1脾（即标准脾0.5脾）蜜蜂即可满足20 m2网室杂交大豆的授粉。     

大豆分枝数相关分子标记开发及qBN-18位点精细定位

The branch number is one of the important factors influencing soybean yield, which is directly related to pod setting rate. At the same time, it is also an important component of soybean plant type, and further affects the yield by adjusting the population structure and planting density. At present, there is few report related to map-based cloning of genes related to branch number. Therefore, the discovery of genes/QTL involved in the regulation of soybean branching is of great significance for the basic research on the establishment of plant type and the applied research on the development of high-yielding varieties. In this study, based on the F₂ of crossing low-branched variety Kenfeng 19 (KF19) and high-branched variety Kennong 24 (KN24), we developed the F_7:8 recombinant inbred line (RIL) population, consisting of 606 lines, and two backcrossing populations consisting of 1486 individuals for KF19-BC₃F₂ and 1150 individuals for KN24-BC₂F₂. Within the localization interval of the new QTL of the branch number of chromosome 18 (qBN-18), 11 polymorphism SSR markers were screened out to identify the RIL population, and region of qBN-18 was reduced from 1.6 Mb to 113 kb. After developing two InDel markers BR69 and BR77 in the mapping region, the backcross population was used to screen the exchange individuals, the interval of qBN-18 was further reduced to 63.7 kb, including 9 genes. Those results provide the information for gene map-based cloning and molecular marker assisted breeding of branch number in soybean.     

Yield trade-off and the role of parental selection based on seed size when breeding for soybean seed protein

Alternative physiological strategies can increase protein concentration in soybean: (i) more-than-proportional increases in seed protein content (mg seed⁻¹) relative to increases in carbohydrate and oil content in large-seeded genotypes or (ii) more-than-proportional reductions in carbohydrate and/or oil content relative to protein content reductions in small-seeded genotypes. Because these strategies differentially affect crop growth and development, we hypothesized that populations developed from high-protein (HP) parents with contrasting seed sizes will present differences in how seed yield and protein concentration correlate. To test this, three breeding strategies were developed by mating high-yielding cultivars and HP ones that differ in seed sizes, reflecting the alternative strategies mentioned above. Neither tested crossing strategies showed differences in their correlation values between seed yield and protein concentration, as initially expected. Nevertheless, populations developed from crossing a HP-small-seeded parent to a HP-large-seeded one showed the highest number of transgressive segregants for protein yield. Our results showed that parent selection based on seed size has no beneficial effects on the development of high-yielding, HP soybean populations, but it might affect the number of transgressive segregants for protein yield.     

Stability Analysis of Winter-rape (Brassica napus L.) by Using Plant Density and Mean Yield per Plant

The yield F per area can be expressed multiplicatively by using yield components. For the most simple case of including only two yield components one obtains: F = X₁− X₂ with X₁= number of plants per area (= plant density) and X₂= mean yield per plant.
For normal variables X₁ and X₂ the phenotypic yield stability of F, which has been measured quantitatively by the variance V(F) of F, can be explicitly expressed dependent on 1) the component means, 2) the component variances and 3) the correlation between the two components. V(F), therefore, depends on 5 parameters.
For many applications the use of the coefficient of variation v of F instead of the variance itself may be advantageous, v can be explicitly expressed dependent on 1) the coefficients of variation of the yield components and 2) the correlation between the components, v, therefore, depends on 3 parameters.
The different conditions leading to the same phenotypic yield stability can be investigated by using these explicit expressions for V(F) and v.
The main purpose of the present paper is the application of these theoretical models and results to the data of an extensive field trial with winter-rape, which has been performed for 5 years with 4 plant densities and 3 row distances.
For the lowest plant density (40 plants/m²) there results a very good agreement between the theoretically expected and the experimentally obtained values for the phenotypic stability of yield per area. But, for the higher plant densities this result don't hold true. Possible causes and explanations are discussed in detail.     

Effects of high oleic acid soybean on seed yield,protein and oil contents,and seed germination revealed by near‐isogeneic lines

Typical soybean oil is composed of palmitic, stearic, oleic, linoleic and linolenic acids. High oleic acid content in soybean seed is a key compositional trait that improves oxidative stability and increases oil functionality and shelf life. Using a marker‐assisted selection method, near‐isogenic lines (NILs) of G00‐3213 for the high oleic trait were developed and yield tested. These NILs have various combinations of FAD2‐1A and FAD2‐1B alleles that were derived from the same backcrossing populations. The results indicated that G00‐3213 NILs with both homozygous mutant FAD2‐1A and FAD2‐1B alleles produced an average of 788 g/kg oleic acid content. The results also demonstrated that possessing these mutant alleles did not cause a yield reduction. Furthermore, seed germination tests across 12 temperatures (12.8–32.0°C) showed that modified seed composition for oleic acid in general did not have a major impact on seed germination. However, there was a possible reduction in seed germination vigour when high oleic seeds are planted in cold soil. The mutant FAD2‐1A and FAD2‐1B alleles did not hinder either seed or plant development.     

氮肥与密度互作对单粒精播花生根系形态、植株性状及产量的影响

为明确花生单粒精播适宜的氮肥水平和种植密度,本研究于2018年和2019年以‘花育22’为供试花生品种,设置3个氮肥水平(0 kg hm^–2, N0; 60 kg hm^–2, N1; 120 kg hm^–2, N2), 3个种植密度(7.93万株hm^–2, D1; 15.86万株hm^–2,D2; 23.79万株hm^–2, D3),采用二因素裂区试验设计,研究氮肥、密度及其互作对单粒精播花生根系形态、植株性状及产量的影响。氮肥对花生根长、根表面积、根体积、根干重的影响不显著,而密度的影响显著。单株根长、根表面积、根体积及根系干重随密度的增加而降低, D1显著高于D2和D3, D2、D3处理间差异不显著;单位面积根长、根表面积、根体积及根系干重随密度的增加而增加, D1显著低于D2和D3, D2、D3处理间差异不显著。氮肥和密度互作对2019年收获期单位面积根长、根表面积的影响显著,与D1相比, N1处理下D3的增幅显著高于N0和N2处理。氮肥及氮肥与密度互作...