不同生长环境下水稻氮、磷、钾利用相关性状的QTL定位分析

【目的】鉴定影响水稻氮、磷、钾利用相关性状的QTL,为开展水稻养分高效利用分子标记辅助选择育种和肥高效基因的图位克隆提供依据。【方法】以云南强耐冷(2级)粳稻地方品种丽江新团黑谷与十和田杂交、回交获包含105个株系的孕穗期耐冷性近等基因系BC4F8及双亲为材料,在云南白邑(冷水胁迫)、寻甸(自然低温胁迫)和玉溪(正常生长环境)3种生长环境下进行水稻氮、磷、钾养分吸收相关性状的鉴定,并利用构建的含有180个SSR标记,全长为1820.6 c M,标记间平均距离为15.67 c M的遗传图谱,用基于完备区间作图法的QTL Ici Mapping V3.2软件对16个性状进行QTL定位分析。【结果】3种环境下共检测到56个QTL,分布在第1、2、3、4、5、6、7、9和10染色体上,单个性状QTL数为1~10个,单个QTL可解释的各自性状表型贡献率为8.88%~35.30%。其中,氮、磷、钾利用效率QTLs数分别为12个、27个和17个。而q TNA-1a、q TPA-1、q PHI-1、q PHI-6、q PHI-7b和q KHI-6共6个QTL在冷害和正常环境下均能检测到,稳定性较高,其贡献率变幅为10.63%~31.57%。在第1、3、4、5、6、7和10染色体上有13个标记区域存在QTL成族分布,单个QTL位点控制的性状数为2~5个,其中共同控制磷总吸收量、磷素干物质生产效率、磷素收获指数、每100 kg籽粒需钾量和钾素收获指数等性状的位点数最多。【结论】获得56个影响氮、磷、钾利用相关性状的QTL,且发现的13个QTL富集区可作为水稻氮、磷、钾高效利用分子育种的重要候选区域。     

不同水分条件下水稻苗期根系性状的QTL分析

以超级杂交稻协优9308(协青早B/中恢9308)衍生的234个重组自交系(RIL)为材料,在正常水分和20%聚乙二醇(PEG-6000)模拟水分胁迫处理下对水稻苗期最长根长、总根长、根表面积、根体积、根平均直径、根尖数、根鲜重和根冠比进行QTL定位分析。采用复合区间作图法,共检测到影响8个根部性状的21个QTL,单个QTL可解释的表型变异介于4.80%～11.35%。其中,正常水分条件下检测到7个QTL,分布在第2、3、9、10、11染色体上;水分胁迫条件下检测到14个QTL,分布在第2、3、5、6、9染色体上。不同水分条件下检测到的QTL位点差异很大,表明不同水分条件下的遗传机制不同。在第3和第6染色体上各检测到1个根部性状的QTL簇,尤其在第3染色体RM6283-RM7370区间发现苗期根系性状与抗旱性及产量相关性状之间存在连锁关系,利用这些QTL紧密连锁的分子标记进行辅助选择,可望同时对多个相关性状进行遗传改良。     

协青早B//协青早B/东乡野生稻BC1F5群体产量性状QTL分析

两年同地种植协青早B//协青早B/东乡野生稻BC1F5群体的202个株系,利用含149个DNA标记的连锁图谱,检测到23个产量性状QTLs,包括每株穗数2个、每穗实粒数4个、每穗总粒数6个、结实率5个、千粒重4个和单株产量2个;有9个QTLs的增效等位基因来自东乡野生稻,包括每株穗数2个、每穗实粒数1个、每穗总粒数5个和千粒重1个,其中6个与前人应用野栽群体检测到的产量性状QTLs位于相似区间。这23个QTLs分布于除第11染色体外的所有水稻染色体中,其中18个形成8个QTL簇,含增效等位基因来自野生稻的2个、来自协青早B的4个,以及效应方向发生变化的2个。这些结果为东乡野生稻增产等位基因的发掘提供了基础。     

水稻QTL定位研究进展

水稻的许多重要农艺性状均属于数量性状,研究水稻数量性状遗传对水稻育种具有十分重要的意义。近年来大量的研究揭示了水稻QTL的基本特征,剖析了重要农艺性状的遗传基础,给水稻遗传改良带来了新策略,不断深入的研究已经完成了水稻特定数量基因的精细定位和克隆,到目前为止已经有一万多个水稻QTL进行了定位,其中有19个进行了克隆,这对水稻育种具有十分重要的意义。本文主要综述了QTL定位的理论基础,水稻QTL定位的研究进展,并对水稻QTL研究的趋势进行了展望。     

非洲栽培稻基因渗入系粒形和剑叶形态性状的QTL定位

非洲栽培稻作为重要的水稻种质资源,其基因渗入系可以为普通栽培稻的遗传背景提供新的有利基因,如果能将这些优良基因引入普通栽培稻中,可为水稻分子设计育种提供新的基因资源。本研究以非洲栽培稻基因渗入系YIL60与轮回亲本中9B(Z9B)杂交衍生的包含188个株系的F₂和F_2:3群体为材料,对粒形性状包括粒长、粒宽、籽粒长宽比、千粒重,剑叶形态性状包括剑叶长、剑叶宽进行数量性状点位(QTL)检测。结果共检测到16个QTL,包括2个粒长QTL、3个粒宽QTL、2个籽粒长宽比QTL、2个千粒重QTL、1个剑叶长QTL、6个剑叶宽QTL,分布于第1、第6、第7、第10和第11号染色体上,贡献率为2.25%~25.64%;有4个多效性QTL区间,有4个QTL qGW7-1、qFLL10、qFLW10、qTGW7在F₂和F_2:3群体中被重复检测到,其中在第7号染色体RM3859-RM3394区间检测到同时控制粒长、粒宽、籽粒长宽比和千粒重的QTL,贡献率最高达17.10%,是一个来源于非洲栽培稻的新粒形QTL。本研究为进一步开展粒形、剑叶形态性状基因的精细定位、克隆和分子标记辅助育种工作奠定了一定的理论基础。     

小麦耐低钾性状的全基因组关联分析

  【目的】  筛选与小麦耐低钾性状相关的标记，为揭示小麦耐低钾性状的遗传机理奠定基础。  【方法】  本研究以198份中国黄淮南片麦区的小麦品种 (系) 作为供试群体。小麦种子发芽后，幼苗在正常钾营养液中生长4天，然后在低钾 (0.01 mmol/L) 和正常钾 (2 mmol/L) 营养液中生长25天。调查生物量，分析地上部和根部钾含量，计算小麦7个性状的相对值，利用小麦35K SNP芯片结合Q + K混合线性模型 (mixed linear model，MLM) 对7个耐低钾性状进行全基因组关联 (genome-wide association study，GWAS) 分析，筛选位于显著关联位点上的候选基因并进行功能注释，对显著关联位点进行等位变异分析，发掘优异等位变异。  【结果】  低钾胁迫条件下，地上部、根部、全株钾累积量和钾累积量根冠比显著降低，地上部、根部、全株钾利用指数显著升高。群体结构分析和PCA分析均将供试群体分为2个亚群。通过GWAS分析，共检测到75个显著关联单核苷酸多态性 (single nucleotide polymorphism，SNP) 标记 (P < 0.001)，分布在除1A、3B、3D、4D和6A染色体外的16条染色体上。通过候选基因搜寻及注释，共筛选出13个可能与小麦耐低钾胁迫相关的候选基因。等位变异分析共挖掘了 14 个优异等位变异，其中 6 个优异等位变异在供试群体中出现的频率较大。  【结论】  7个耐低钾性状均具有明显的数量性状特征，变异系数范围为20.66%～30.44%。40%的SNP标记分布在2B、5B和6B染色体上，21个SNP位点与多个耐低钾性状显著关联，单个SNP标记解释的表型贡献率的变异范围为5.78%～11.22%。TraesCS4A02G335400、TraesCS2B02G306000、TraesCS5B02G260000可能参与物质转运过程，TraesCS1D02G350600和TraesCSU02G105300可能参与逆境胁迫响应等生理过程，TraesCS2A02G000200可能参与逆境胁迫下的信号转导过程。     

水稻产量性状一般配合力QTL定位

为了定位与发掘水稻产量性状高配合力数量性状座位(QTL),本研究按照不完全双列杂交(NCⅡ)设计,以泸恢8285与扬恢34杂交构建的重组自交系群体(RIL),分别与泸98A、Ⅱ-32A、冈46A杂交构建的双列杂交群体作为试验材料,在德阳、遂宁和泸州3种环境下对单株生物量、收获指数、单株产量、有效穗数、每穗颖花数、每穗实粒数、结实率和千粒重等性状的一般配合力进行QTL定位。结果表明,3种环境下共检测到50个QTL,单个QTL对表型的贡献率变幅在3.26%～34.26%之间,其中qEP2-2、qSP2-2、qFGP2-2、qTGW1和qTGW2 5个QTL在3种环境下均有检出,qHI3、qEP7、qSP7、qSSR12-1和qTGW3-2 5个QTL在2种环境下检出,其他的QTL仅在其中1种环境下检出。此外,有27个QTL增效等位基因来自泸恢8258。本研究结果为进一步开展相关基因的精细定位、克隆和分子辅助选择育种奠定了基础。     

施氮与不施氮条件下玉米开花期相关性状的 QTL 定位

【目的】 探究施氮与不施氮对玉米开花期相关性状变异的影响,并定位相关 QTLs。 【方法】 以玉米的骨干自交系综 3 为供体亲本,许 178 为受体亲本,通过杂交、回交和分子标记辅助选择的方法,构建了一套以许 178 为遗传背景的综 3 染色体单片段代换系 (SSSLs) 群体,其中包含 160 个单片段代换系。以这套 SSSLs 以及许 178 为材料,采用裂区试验设计,在施氮 (N+) 和不施氮 (N–) 条件下,通过一年三点 (贵州贵阳、德江和云南罗平) 的表型评价,利用复合区间作图法对玉米散粉期、吐丝期和散粉–吐丝间隔期 (ASI) 3 个开花期相关性状进行 QTL 定位。 【结果】 在基因组范围内,2 种氮处理条件下共定位到 54 个开花期相关性状 QTLs,主要定位在第 1、3、6、9 和 10 染色体上。其中 5 个 QTLs 在 3 个环境中均被检测到。施氮条件下,吐丝期 (DTS) 相关位点qDTS9a,位于第 9 染色体,可解释表型变异的 3.05%;吐丝散粉间隔期 (ASI) 相关位点qASI10a,位于第 10 染色体,可解释表型变异的 30.74%。不施氮条件下,散粉期 (DTP) 相关位点qDTP9,可解释表型变异的 3.43%;吐丝期相关位点qDTS9a,位于第 9 染色体,可解释表型变异的 4.08%;ASI 相关位点qASI10,位于第 10 染色体,可解释表型变异的 50.28%。对不同处理条件下的定位结果比较发现,不施氮条件下检测到的 QTLs 数目显著高于施氮条件下的检测数量。 【结论】 不同氮素处理下存在一些共有的控制玉米开花期相关的遗传区段,分别位于 Bin9.02 (umc1170-umc1636-bnlg1401-umc1271) 和 Bin10.04 (umc1077-umc1053-umc2350),这些区段可能在玉米氮素吸收、转运和利用过程中起重要作用,可作为下一步精细定位和图位克隆玉米开花期相关基因的重要候选区域。      

UV-B辐射增强下水稻苗期硅营养性状的QTL定位及其与环境互作效应分析

以"Lemont"和"Dular"杂交建立的包含123个家系的水稻重组自交系(RILs)群体为材料,选用水稻根系硅吸收能力和叶片硅利用率为指标,进行水稻硅营养遗传性状QTL定位,并分析其与UV-B辐射增强的互作效应。结果表明,控制水稻叶片硅利用率的4个加性QTL分别在第2、3、10染色体上,而控制根系硅吸收能力的1个加性QTL位于第11染色体上。QTL与UV-B辐射互作分析发现2对控制根系硅吸收能力和3对控制叶片硅利用率的基因×环境上位性QTL,其中只有1对控制根系硅吸收能力的QTL效应值较大。说明水稻这两种硅营养性状中,根系硅吸收能力较叶片硅利用率受UV-B辐射影响大,在抗UV-B辐射育种中以叶片硅利用率为水稻硅营养遗传选择的指标具有较高效率。     

利用双向导入系和重组自交系解析水稻加工品质的遗传基础

水稻加工品质直接影响水稻的商品价值。为解析水稻加工品质的遗传基础,以粳稻秀水09和籼稻IR2061构建的2套双向导入系和1套重组自交系为材料,在温州和三亚环境下考察了稻米加工品质,并进行了加工品质性状的数量性状位点(QTL)定位。本研究构建了一张包含145个简单重复序列(SSR)分子标记的遗传连锁图,该连锁图总长1 567.8 cM,秀水09和IR2061背景导入系的平均背景回复率分别为90.15%和85.82%。双亲的糙米率和精米率无显著差异,秀水09整精米率显著高于IR2061。3套群体的加工品质均表现为连续分布,且糙米率、精米率和整精米率3个性状间彼此均呈显著正相关。在两个环境下共定位到影响糙米率、精米率和整精米率的29个主效QTL和20对上位性QTL,其中6个QTL在其中的两套群体中被重复定位到,2个QTL在两个环境下稳定表达,10个QTL与环境互作,说明遗传背景和环境显著影响加工品质QTL的表达。此外,在第7号染色体RM432~RM11区间、第8号染色体RM80~RM458区间和第9号染色体RM257~RM278区间均同时定位到影响糙米率、精米率和整精米率的QTL,秀水09等位基因在这些QTL处均提高加工品质。研究结果可为分子改良水稻加工品质提供重要基因资源的参考依据。     

Genetic diversity analysis of common bean (Phaseolus vulgaris L.) genotypes for resistance to Mexican bean weevil (Zabrotes subfasciatus), using single nucleotide polymorphism and phenotypic markers

ABSTRACT

The objective of this study was to examine the genetic diversity present among 297 common bean genotypes using 2554 SNPs and 12 insects and seed-related traits. The phenotyping was done under laboratory condition while the genotyping was conducted by using the Illumina SNP BeadChip. High phenotypic diversity among traits were recorded, ranging from 0.87 to 0.96, with a mean of 0.92. Principal component and discriminant analyses identi?ed four PCs and three discriminant functions, which explained 82% and 100% of the total phenotypic variations among genotypes, respectively. Polymorphic Information Content ranged from 0.21 to 0.38, with a mean of 0.34. The mean gene diversity among genotypes ranged from 0.24 to 0.50, with a mean of 0.44. Genetic distance ranged from 0.19 to 0.82, with a mean of 0.62, while the phenotypic distance ranged from 0.00 to 1.00, with a mean of 0.64 were observed aamong genotypes. The analysis of molecular variance revealed highly signi?cant differences (p<0.001) among and within individuals and among populations. Both the SNP and the phenotypic markers grouped the 297 genotypes into two major distinct clusters and three sub-clusters. This information is useful for identi?cation and development of common bean germplasm with economically valuable traits and the conservation and utilization of genotypes.     

Traits-related QTLs and genes and their potential applications in rice improvement under low phosphorus condition

The genetic improvement of rice over past decades has led to the loss of several genes which are responsible for nutrient acquisition and soil-related stresses. Phosphorus (P) is a non-renewable resource and inevitable element of metabolic functions in plants. By pedogenesis process, organic matter contributes to renewing soil P in lesser extent. Therefore, improvement of the P use efficiency is one of the most imperative traits in rice breeding program, which is governed by quantitative trait loci (QTLs). QTLs controlling low P associated morphological and physiological traits in rice were investigated mostly during last one and half decade by using diverse mapping populations. Comprehensive and meticulous survey from literature, we found that to date 133 P associated QTLs of morpho-physiological traits were reported to be distributed on twelve chromosomes and majority of these QTLs localized on chromosome 1, 2 and 12. For the first time, a complete figure is presented in this review on chromosome wise with respective QTLs associated with low P for easy understanding and selecting markers for future prospect. Further, it is necessary to understand the molecular mechanisms and regulation of genes and traits associated with low P to develop tolerant rice cultivars using functional marker-assisted selection.     

Quantitative Trait Loci for Brown Rice Color,Phenolics, Flavonoid Contents,and Antioxidant Capacity in Rice Grain

Phytochemicals such as phenolics and flavonoids, which are present in rice grains, are associated with reduced risk of developing chronic diseases such as cardiovascular disease, type 2 diabetes, and certain cancers. The phenolic and flavonoid compounds in rice grains also contribute to the antioxidant activity. Biofortification of rice grain by conventional breeding is one way to improve nutritional quality to combat nutritional deficiency. For improvement of the phenolics, flavonoids, and antioxidant capacity, we must understand the genetic bases of the related traits. In the present study, mapping of quantitative trait locus (QTL) for five color parameters, phenolics, flavonoids, and antioxidant capacity was completed using a composite interval mapping approach using a doubled haploid (DH) population. Correlation analysis showed that the five color parameters lightness (L*), redness (a*), yellowness (b*), chroma (C), and hue angle (H°) were intercorrelated. The phenolic content was positively correlated with the flavonoid content and antioxidant capacity (P < 0.001), whereas the flavonoid content had no relationship with antioxidant capacity, but it was positively correlated with color parameters L* and H° (P < 0.05). A total of 21 putative QTL were detected for the eight traits with at least one QTL and as many as four QTL for different traits. Three QTL at the same interval of GA285 and CT580 on chromosome 2 were significant for color parameters L*, b*, and C; the latter two traits also shared another QTL region on chromosome 8. Two QTL on chromosome 2, qPH‐2 and qFL‐2‐1, flanked by CT87 and G1234, were identified for phenolic and flavonoid content with large additive effects, explaining 16.91 and 12.71%, respectively, of the total phenotypic variation. Three QTL located at the same interval of G379A and CT360 on chromosome 7 were detected for color parameters a* and H°, and antioxidant capacity, which might be allelic to the Rd gene that is responsible for the production of the pigment in brown rice. The results of the present study may provide new opportunities for rice breeders with potential markers to improve nutritional quality by marker‐assisted selection approach.     

不同磷、钾处理小麦苗期氮营养性状的QTL分析

【目的】 对不同浓度磷、钾处理下小麦苗期氮养分效率相关性状进行QTL分析,以深入理解磷、钾与氮养分效率的相互关系,为氮营养相关性状的图位克隆及分子标记辅助选择育种奠定基础。 【方法】 采用苗期液培试验,以“川35050 ×山农483”组合衍生的小麦重组自交系群体(131个株系)为研究材料,设置了中磷中钾(MPMK)、高磷(HP)、低磷1 (LP1)、低磷2 (LP2)、低磷3 (LP3),高钾(HK)、低钾1 (LK1)、低钾2 (LK2)、低钾3 (LK3)共9个处理,对不同磷、钾处理下的氮养分效率相关性状进行研究,并结合分子标记遗传图谱,从整个基因组水平对与小麦苗期氮养分效率相关的10个性状进行QTL定位及遗传分析。 【结果】 不同处理下的10个性状共检测到137个QTL,位于除3D外的20条染色体上,大部分QTL (89.05%)仅在单一处理下被定位到,有3个QTL (QRnue-1A.2、QSnue-1A.1和QTnue-1A.1)可在至少4个处理中被检测到,有5个QTL (QRnue-1A.1、QTnue-1A.1、QSnc-4A、QRnc-6A.3和QSnue-6B)可同时在低磷和低钾环境中被检测到。本研究还检测到至少包含3个以上QTL的QTL簇17个,分别位于1A、1B、2B、2D、3A、3B、4A、4B、5D、6A、6B、6D和7A染色体上,共涉及66个QTL,占QTL总数的48.18%。其中,有5个QTL簇仅与特定磷、钾处理有关,大多数QTL簇均同时定位了不同磷、钾处理的不同性状,许多QTL簇位点还与前人定位的生物量、产量及其他养分有关。 【结论】 磷、钾的供应能够显著影响小麦苗期对氮素的吸收利用及其相关QTL的表达。影响苗期小麦氮养分效率相关性状的QTL大多数仅在特定处理下被检测到,但大多数QTL会形成QTL簇,构成了控制氮养分效率的QTL热点,许多热点区域也与前人定位的许多成株期性状如生物量、产量及其他养分效率有关,这些QTL/基因密集区域及其特点的发现,为我们深入理解小麦氮养分效率的遗传控制特点及其与磷、钾养分供应的关系提供了新的视角,也为这些重要位点的克隆及其应用提供数据支持。     

水稻第6染色体短臂每穗实粒数和每穗颖花数QTL的精细定位

对水稻第6染色体短臂上一个控制每穗实粒数和每穗颖花数的QTL进行精细定位研究。针对前期定位的RM587-RM6119区域,应用在目标区间内杂合片段呈交叉排列的3个剩余杂合体,自交后获得3套F2∶3群体,对每穗实粒数、每穗颖花数和单株产量进行QTL分析。在3套群体中均检测到控制每穗实粒数、每穗颖花数和单株产量的QTL,其遗传作用均以加性作用为主,增效等位基因来自母本珍汕97B,且QTL的效应在各群体间相近。因此,该目标区间存在一个共同的QTL,通过控制每穗粒数来调控单株产量。通过比较3个剩余杂合体共有的杂合区间,最终将控制每穗实粒数和每穗颖花数的QTL定位于RM3414-RM19417之间约96.4kb的区域内。     

Selenium effects and quantitative trait locus (QTL) mapping for mineral nutrient efficiency traits in wheat at the seedling stage

A nutrient solution culture experiment was conducted in the greenhouse to investigate the effects of selenium (Se) on biomass and the mineral nutrient efficiency of macroelements phosphorus, potassium, calcium and magnesium (P, K, Ca and Mg) and microelements iron, manganese, copper and zinc (Fe, Mn, Cu and Zn) in wheat at the seedling stage using a set of recombinant inbred lines (RILs). Quantitative trait locus (QTL) analysis was also performed for all 60 traits. The results showed that 0.1 μmol/L Se can significantly affect the phenotypic traits relation to biomass and nutrient efficiency and the corresponding QTLs. A total of 260 QTLs were located on 19 chromosomes, and 96.54% of these QTLs were only detected in one treatment. A total of 23 important QTL clusters and 31 cooperative uptake and utilization (CUU) loci that colocalized with QTLs for nutrient uptake and/or utilization of at least two elements were also identified. These CUU loci involved 190 out of the 248 QTLs (76.66%) for nutrient efficiency traits, indicating that CUU-QTLs were common for macroelements (P, K, Ca and Mg) and microelements (Fe, Mn, Cu and Zn). Additionally, these loci may be hot spots for genetic control of mineral nutrient efficiency traits.     

小麦苗期钾、钠吸收相关性状及其QTL分析

为进一步了解小麦苗期钾、钠吸收的相关性和遗传特征,本试验在温室环境下,以RIL（Recombinant Inbred Lines, RIL）群体为试验材料,采用营养液培养法对不同K+、Na+浓度处理条件下小麦苗期生长及钾、钠的积累、分配及利用等相关的20个性状进行了鉴定,探讨了K+和Na+的关系及其对小麦苗期生长的影响;并对所有相关性状进行了QTL（Quantitative trait loci,QTL）分析。结果表明,缺钾条件下,供应钠能够显著提高小麦体内的Na/K比,但对小麦的生物量没有显著影响,表明钠替代钾的能力较差。而正常钾条件下,供钠可显著促进钾、钠的吸收,提高了Na/K比,但地上部的生物量反而显著下降,表明大量的钾和钠的累积对小麦地上部生物量的形成不利。小麦苗期对钾、钠离子的吸收与累积呈显著正相关。本试验在小麦全部的21条染色体上共检测到与生物量及钾、钠相关性状有关的QTLs 141个。其中的103个QTLs 组成了14个重要的QTL簇,有11个QTL簇同时定位了钾、钠相关性状位点。另外,试验还发现了8个在多个养分环境条件下均可检测到的QTL位点高频表达的QTL位点（RHF-QTLs）,其中4个是新发现的位点。这些重要的QTL位点为K+、Na+关系及其遗传控制的深入研究提供了重要参考。     

Variation in flowering time in sorghum core collection and mapping of QTLs controlling flowering time by association analysis

A wide range of variation in flowering time was observed within a diversity research set of 107 sorghum accessions ranging from 56 to 133 days. Accessions were classified into early medium and late flowering groups. 45 accessions were grown under three different environments of photoperiod (11, 12 and 15 h). Sorghum accessions gradually responded to the decreasing of day-length. The 12 h of photoperiod could be considered as a threshold above which day-length delays the flowering time in sorghum. Association analysis was performed to identify the QTLs controlling flowering time and photoperiod sensitivity using 107 accessions of sorghum grown under natural condition and 45 accessions grown under controlled conditions. Four QTLs controlling flowering time were detected under natural condition of day-length at threshold 2.5 using K model. A total of seven flowering time loci were detected under controlled conditions of day-length. One QTL controlling photoperiod sensitivity was detected on chromosome 1 and one QTL controlling photoperiod insensitivity was detected on chromosome 4.     

排除主效作用下水稻产量性状QTL的检测

本研究旨在排除主效QTL效应的基础上检测控制水稻产量性状的微效QTL。前期应用中156/谷梅2号重组自交系（RIL）群体在第7染色体RM2-RM214区间上检测到控制抽穗期和产量性状的主效QTL,本研究挑选在此区间呈谷梅2号基因型的两个株系,配组衍生新的RIL群体,检测控制水稻产量性状的QTL。共检测到25个产量性状Q...     

LOWLAND RICE GENOTYPES EVALUATION FOR PHOSPHORUS USE EFFICIENCY

ABSTRACT

Phosphorus (P) deficiency is the most yield-limiting factor in lowland rice production in Inceptisols of Brazil. A greenhouse experiment was conducted to evaluate 12 genotypes of lowland rice (Oryza sativa L.) using an Inceptisol (Typic Haplaquepts). The P treatments were: low (0?mg?P?kg^?1), medium (100?mg?P?kg^?1), and high (400?mg?P?kg^?1). Significant (P<0.01) genotypes differences in P-use efficiency were found. On the basis of P-use efficiency, genotypes were classified as efficient and responsive, efficient and non-responsive, non-efficient and responsive, and non-efficient and non-responsive. From a practical point of view, efficient and responsive and efficient and non-responsive genotypes are the most desirable ones. Among the 12 genotypes tested, none were found to be efficient and responsive and genotypes CNA7553, CNA7591, CNA7601, and Aliança were found to be efficient and non-responsive. Among the yield components, panicle length and harvest index were significantly affected by P levels and genotypes and P and genotypes interactions were significant for these two parameters. However, panicle number was significantly influenced only by P treatment. Among the yield components, panicle number, harvest index, and panicle length were significantly (P<0.01) related to grain yield.