Rice genetic resources: history,conservation, investigative characterization and use in Japan

Rice has been grown in Japan for about 3000 years. Although both japonica and indica varieties have been grown in Japan, now japonica rices are grown. Japanese rice breeding has used an ecological breeding approach. While emphasis in rice breeding in the 1940's and 1950's focussed on yield in recent decades quality has been of major importance. Consumer preference and name recognition of high quality varieties, such as Koshihikari, has resulted in slow acceptance of new varieties.Rice germplasm was systematically collected throughout Japan between 1962 and 1963. Subsequent acquisition and collecting, in Japan and other countries, has resulted in 28,000 accessions being conserved in the National Genebank, based at the National institute of Agrobiological Resources (NIAR).Research on genetic diversity of rice using a range of techniques, for example esterase isozymes, has revealed clinal variation in rice radiating from the center of diversity of rice in and around southwest China. Newly found genes in traditional rice germplasm, such as genes for non-elongating mesocotyl, are now routinely identified on the rice genome. Pioneering studies on eco-genetic differentiation of species in the genus Oryza in Japan has revealed much about the complex genepool for which rice evolved.Pest and disease resistance sources, particularly to blast, bacterial blight and brown plant hopper, from many countries have been incorporated into Japanese varieties. Cold tolerance at the booting stage was found in the Indonesian variety Silewah. In the future in characterisation of rice germplasm and interaction between rice germplasm specialists and rice molecular scientists, both in Japan and internationally, will be corner stones to securing rice genetic diversity and rice improvement in the next century.     

Covering chemical diversity of genetically-modified tomatoes using metabolomics for objective substantial equivalence assessment

As metabolomics can provide a biochemical snapshot of an organism's phenotype it is a promising approach for charting the unintended effects of genetic modification. A critical obstacle for this application is the inherently limited metabolomic coverage of any single analytical platform. We propose using multiple analytical platforms for the direct acquisition of an interpretable data set of estimable chemical diversity. As an example, we report an application of our multi-platform approach that assesses the substantial equivalence of tomatoes over-expressing the taste-modifying protein miraculin. In combination, the chosen platforms detected compounds that represent 86% of the estimated chemical diversity of the metabolites listed in the LycoCyc database. Following a proof-of-safety approach, we show that % had an acceptable range of variation while simultaneously indicating a reproducible transformation-related metabolic signature. We conclude that multi-platform metabolomics is an approach that is both sensitive and robust and that it constitutes a good starting point for characterizing genetically modified organisms.     

Genetic Influences on Metabolite Levels: A Comparison across Metabolomic Platforms

Metabolomic profiling is a powerful approach to characterize human metabolism and help understand common disease risk. Although multiple high-throughput technologies have been developed to assay the human metabolome, no technique is capable of capturing the entire human metabolism. Large-scale metabolomics data are being generated in multiple cohorts, but the datasets are typically profiled using different metabolomics platforms. Here, we compared analyses across two of the most frequently used metabolomic platforms, Biocrates and Metabolon, with the aim of assessing how complimentary metabolite profiles are across platforms. We profiled serum samples from 1,001 twins using both targeted (Biocrates, n = 160 metabolites) and non-targeted (Metabolon, n = 488 metabolites) mass spectrometry platforms. We compared metabolite distributions and performed genome-wide association analyses to identify shared genetic influences on metabolites across platforms. Comparison of 43 metabolites named for the same compound on both platforms indicated strong positive correlations, with few exceptions. Genome-wide association scans with high-throughput metabolic profiles were performed for each dataset and identified genetic variants at 7 loci associated with 16 unique metabolites on both platforms. The 16 metabolites showed consistent genetic associations and appear to be robustly measured across platforms. These included both metabolites named for the same compound across platforms as well as unique metabolites, of which 2 (nonanoylcarnitine (C9) [Biocrates]/Unknown metabolite X-13431 [Metabolon] and PC aa C28:1 [Biocrates]/1-stearoylglycerol [Metabolon]) are likely to represent the same or related biochemical entities. The results demonstrate the complementary nature of both platforms, and can be informative for future studies of comparative and integrative metabolomics analyses in samples profiled on different platforms.     

Molecular characterization of some Indian <Emphasis Type="Italic">Basmati</Emphasis> and other elite rice genotypes using fluorescent-AFLP

Cultivated rice is a high-volume, low-value cereal crop providing staple food to more than 50% of the world populace. A small group of rice cultivars, traditionally produced on the Indo-Gangetic plains and popularly known as Basmati, have exquisite quality grain characteristics and are a prized commercial commodity. Efforts to improve the yield potential of Basmati have led to the development of several crossbred Basmati-like cultivars. In this study we have analysed the genetic diversity and interrelationships among 33 rice genotypes consisting of the traditional Basmati, improved Basmati-like genotypes developed in India and elsewhere, American long-grain rice and a few non-aromatic rice using a DNA marker-based approach - fluorescent-amplified fragment length polymorphism (f-AFLP). Using a set of nine primer-pairs we scored a total of 10,672 data points over all of the genotypes in the size range of 75-500 bp. The scored data points corresponded to a total of 501 AFLP markers (putative loci/genome landmarks) of which 327 markers (65%) were polymorphic. The f-AFLP marker data, which were analysed using different clustering algorithms and principal component analysis, indicate that: (1) considerable genetic variability exists in the analysed genotypes; (2) traditional Basmati cultivars could be distinctly separated from the crossbred Basmati-like genotypes as well as from the non-aromatic rice; (3) the crossbred Basmati-like cultivars from the subcontinent and elsewhere are genetically very distinct; (4) f-AFLP-based clustering, in general, conforms to the putative pedigree of the improved genotypes. Moreover, analysis to ascertain the scope of AFLP as a technique suggests that the polymorphism revealed by three selective primer-pair combinations is sufficient to obtain reliable estimates of genetic diversity for the type of material used in this study. However, its utility to identify group-specific DNA markers was discounted due to a low frequency of observed group-specific discrete markers.     

Domestication, genomics and the future for banana

BACKGROUND: Cultivated bananas and plantains are giant herbaceous plants within the genus Musa. They are both sterile and parthenocarpic so the fruit develops without seed. The cultivated hybrids and species are mostly triploid (2n = 3x = 33; a few are diploid or tetraploid), and most have been propagated from mutants found in the wild. With a production of 100 million tons annually, banana is a staple food across the Asian, African and American tropics, with the 15 % that is exported being important to many economies. SCOPE: There are well over a thousand domesticated Musa cultivars and their genetic diversity is high, indicating multiple origins from different wild hybrids between two principle ancestral species. However, the difficulty of genetics and sterility of the crop has meant that the development of new varieties through hybridization, mutation or transformation was not very successful in the 20th century. Knowledge of structural and functional genomics and genes, reproductive physiology, cytogenetics, and comparative genomics with rice, Arabidopsis and other model species has increased our understanding of Musa and its diversity enormously. CONCLUSIONS: There are major challenges to banana production from virulent diseases, abiotic stresses and new demands for sustainability, quality, transport and yield. Within the genepool of cultivars and wild species there are genetic resistances to many stresses. Genomic approaches are now rapidly advancing in Musa and have the prospect of helping enable banana to maintain and increase its importance as a staple food and cash crop through integration of genetical, evolutionary and structural data, allowing targeted breeding, transformation and efficient use of Musa biodiversity in the future.     

Genomics-based precision breeding approaches to improve drought tolerance in rice

Rice (Oryza sativa L.), the major staple food crop of the world, faces a severe threat from widespread drought. The development of drought-tolerant rice varieties is considered a feasible option to counteract drought stress. The screening of rice germplasm under drought and its characterization at the morphological, genetic, and molecular levels revealed the existence of genetic variation for drought tolerance within the rice gene pool. The improvements made in managed drought screening and selection for grain yield under drought have significantly contributed to progress in drought breeding programs. The availability of rice genome sequence information, genome-wide molecular markers, and low-cost genotyping platforms now makes it possible to routinely apply marker-assisted breeding approaches to improve grain yield under drought. Grain yield QTLs with a large and consistent effect under drought have been indentified and successfully pyramided in popular rice mega-varieties. Various rice functional genomics resources, databases, tools, and recent advances in “-omics” are facilitating the characterization of genes and pathways involved in drought tolerance, providing the basis for candidate gene identification and allele mining. The transgenic approach is successful in generating drought tolerance in rice under controlled conditions, but field-level testing is necessary. Genomics-assisted drought breeding approaches hold great promise, but a well-planned integration with standardized phenotyping is highly essential to exploit their full potential.     

Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry

Metabolism has an essential role in biological systems. Identification and quantitation of the compounds in the metabolome is defined as metabolic profiling, and it is applied to define metabolic changes related to genetic differences, environmental influences and disease or drug perturbations. Chromatography-mass spectrometry (MS) platforms are frequently used to provide the sensitive and reproducible detection of hundreds to thousands of metabolites in a single biofluid or tissue sample. Here we describe the experimental workflow for long-term and large-scale metabolomic studies involving thousands of human samples with data acquired for multiple analytical batches over many months and years. Protocols for serum- and plasma-based metabolic profiling applying gas chromatography-MS (GC-MS) and ultraperformance liquid chromatography-MS (UPLC-MS) are described. These include biofluid collection, sample preparation, data acquisition, data pre-processing and quality assurance. Methods for quality control-based robust LOESS signal correction to provide signal correction and integration of data from multiple analytical batches are also described.     

Drought‐related secondary metabolites of barley (Hordeum vulgare L.) leaves and their metabolomic quantitative trait loci

Determining the role of plant secondary metabolites in stress conditions is problematic due to the diversity of their structures and the complexity of their interdependence with different biological pathways. Correlation of metabolomic data with the genetic background provides essential information about the features of metabolites. LC‐MS analysis of leaf metabolites from 100 barley recombinant inbred lines (RILs) revealed that 98 traits among 135 detected phenolic and terpenoid compounds significantly changed their level as a result of drought stress. Metabolites with similar patterns of change were grouped in modules, revealing differences among RILs and parental varieties at early and late stages of drought. The most significant changes in stress were observed for ferulic and sinapic acid derivatives as well as acylated glycosides of flavones. The tendency to accumulate methylated compounds was a major phenomenon in this set of samples. In addition, the polyamine derivatives hordatines as well as terpenoid blumenol C derivatives were observed to be drought related. The correlation of drought‐related compounds with molecular marker polymorphisms resulted in the definition of metabolomic quantitative trait loci in the genomic regions of single‐nucleotide polymorphism 3101‐111 and simple sequence repeat Bmag0692 with multiple linkages to metabolites. The associations pointed to genes related to the defence response and response to cold, heat and oxidative stress, but not to genes related to biosynthesis of the compounds. We postulate that the significant metabolites have a role as antioxidants, regulators of gene expression and modulators of protein function in barley during drought.     

Metabolomic Profiling of 13 Diatom Cultures and Their Adaptation to Nitrate-Limited Growth Conditions

Diatoms are very efficient in their use of available nutrients. Changes in nutrient availability influence the metabolism and the composition of the cell constituents. Since diatoms are valuable candidates to search for oil producing algae, measurements of diatom-produced compounds can be very useful for biotechnology. In order to explore the diversity of lipophilic compounds produced by diatoms, we describe the results from an analysis of 13 diatom strains. With the help of a lipidomics platform, which combines an UPLC separation with a high resolution/high mass accuracy mass spectrometer, we were able to measure and annotate 142 lipid species. Out of these, 32 were present in all 13 cultures. The annotated lipid features belong to six classes of glycerolipids. The data obtained from the measurements were used to create lipidomic profiles. The metabolomic overview of analysed cultures is amended by the measurement of 96 polar compounds. To further increase the lipid diversity and gain insight into metabolomic adaptation to nitrogen limitation, diatoms were cultured in media with high and low concentrations of nitrate. The growth in nitrogen-deplete or nitrogen-replete conditions affects metabolite accumulation but has no major influence on the species-specific metabolomic profile. Thus, the genetic component is stronger in determining metabolic patterns than nitrogen levels. Therefore, lipid profiling is powerful enough to be used as a molecular fingerprint for diatom cultures. Furthermore, an increase of triacylglycerol (TAG) accumulation was observed in low nitrogen samples, although this trend was not consistent across all 13 diatom strains. Overall, our results expand the current understanding of metabolomics diversity in diatoms and confirm their potential value for producing lipids for either bioenergy or as feed stock.     

水氮互作下直播稻群体质量与氮素利用特征的关系

探讨水氮耦合下直播稻群体质量和氮素利用特征可为直播水稻丰产高效生产提供理论基础和实践依据。以杂交稻‘F优498’为试验材料,设置淹水灌溉(W₁)、干湿交替灌溉(W₂)、旱种(W₃)3种灌水方式和基肥∶蘖肥∶穗肥分别为5∶3∶2(N₁)、3∶3∶4(N₂)、3∶1∶6(N₃)3种氮肥运筹模式,以不施氮处理(N₀)为对照,研究水氮互作对直播稻群体质量和氮素利用特征的影响,并探讨水氮互作下直播稻群体质量构建与氮素利用特征和产量的关系。结果表明:灌溉方式和氮肥运筹对直播稻各生育时期干物质积累、稻谷收获指数、抽穗及抽穗20 d高效叶(上3叶)干重、结实期群体透光率、氮素积累总量、氮肥表观利用率、氮肥偏生产力、氮肥生理利用率和产量均存在显著的互作效应。综合直播稻群体质量、产量和氮肥利用特征,各灌溉方式下,氮肥后移比例均以占总量的20%～40%(N₁～N₂)为宜,氮肥后移比例达到总量的60%(N₃)和W₃处理均会显著降低直播稻群体质量、产量、氮肥农学利用率和氮肥偏生产力。相关分析表明,水氮互作下直播稻产量和氮素利用特征与最终有效分蘖数、结实期干物质积累、其余叶(除上三叶以外叶片)干重减少量、总叶片干重减少量,以及群体中部和基部受光率均呈显著或极显著正相关。干湿交替灌溉(W₂)可以提高直播稻茎蘖成穗率、各时期干物质积累、稻谷收获指数、氮肥吸收总量、氮肥农学利用率和最终产量,配合N₂的氮肥运筹模式可优化调控直播稻群体质量,实现高产与氮肥高效利用的协调统一,为本试验最优组合。     

Genetic Diversity and Population Structure in Aromatic and Quality Rice (Oryza sativa L.) Landraces from North-Eastern India

The North-eastern (NE) India, comprising of Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim and Tripura, possess diverse array of locally adapted non-Basmati aromatic germplasm. The germplasm collections from this region could serve as valuable resources in breeding for abiotic stress tolerance, grain yield and cooking/eating quality. To utilize such collections, however, breeders need information about the extent and distribution of genetic diversity present within collections. In this study, we report the result of population genetic analysis of 107 aromatic and quality rice accessions collected from different parts of NE India, as well as classified these accessions in the context of a set of structured global rice cultivars. A total of 322 alleles were amplified by 40 simple sequence repeat (SSR) markers with an average of 8.03 alleles per locus. Average gene diversity was 0.67. Population structure analysis revealed that NE Indian aromatic rice can be subdivided into three genetically distinct population clusters: P1, joha rice accessions from Assam, tai rices from Mizoram and those from Sikkim; P2, chakhao rice germplasm from Manipur; and P3, aromatic rice accessions from Nagaland. Pair-wise F_ST between three groups varied from 0.223 (P1 vs P2) to 0.453 (P2 vs P3). With reference to the global classification of rice cultivars, two major groups (Indica and Japonica) were identified in NE Indian germplasm. The aromatic accessions from Assam, Manipur and Sikkim were assigned to the Indica group, while the accessions from Nagaland exhibited close association with Japonica. The tai accessions of Mizoram along with few chakhao accessions collected from the hill districts of Manipur were identified as admixed. The results highlight the importance of regional genetic studies for understanding diversification of aromatic rice in India. The data also suggest that there is scope for exploiting the genetic diversity of aromatic and quality rice germplasm of NE India for rice improvement.     

Genetic Diversity and Population Differentiation of Liaoning Weedy Rice Detected by RAPD and SSR Markers

Weedy rice refers to populations of usually annual Oryza species that diminish farmer income through reduction of grain yield and lowered commodity value at harvest. The genetic diversity and population genetic structure of weedy rice in Liaoning Province were studied by RAPD and SSR markers. The results indicate that the level of genetic diversity of Liaoning weedy rice is very low, with polymorphic loci being only 3.70% (RAPDs) and 47.62% (SSRs). On the other hand, high genetic differentiation was found among populations, in particular between two regions (Shenyang and Dandong), with Fst values of 0.746 (RAPDs) and 0.656 (SSRs), suggesting that more than two thirds of the genetic variation resides among regions. Combined with our investigations of cultural traditions, the low level of genetic diversity in Liaoning Province is attributed to its narrow genetic background enhanced by exchanges of cultivar seeds, whereas the high genetic differentiation between the two regions is most likely the result of different founding parents and gene flow from local rice varieties to weedy rice. The rice cultivars in the two regions are all local varieties and are different genetically. A comparison of the two marker systems demonstrates that SSR is more informative and powerful in terms of the assessment of genetic variability, although both RAPD and SSR provide useful genetic information on weedy rice.     

Plant metabolomics and its potential application for human nutrition

With the growing interest in the use of metabolomic technologies for a wide range of biological targets, food applications related to nutrition and quality are rapidly emerging. Metabolomics offers us the opportunity to gain deeper insights into, and have better control of, the fundamental biochemical basis of the things we eat. So doing will help us to design modified breeding programmes aimed at better quality produce; optimised food processing strategies and ultimately, improved (micro)nutrient bioavailability and bioefficacy. A better understanding of the pathways responsible for the biosynthesis of nutritionally relevant metabolites is key to gaining more effective control of the absence/level of presence of such components in our food. Applications of metabolomic technologies in both applied and fundamental science strategies are therefore growing rapidly in popularity. Currently, the world has two highly contrasting nutrition-related problems--over-consumption and under-nourishment. Dramatic increases in the occurrence of overweight individuals and obesity in developed countries are in staggering contrast to the still-familiar images of extreme malnutrition in many parts of the developing world. Both problems require a modified food supply, achieved through highly contrasting routes. For each, metabolomics has a future role to play and this review shall deal with this key dichotomy and illustrate where metabolomics may have a future part to play. In this short overview, attention is given to how the various technologies have already been exploited in a plant-based food context related to key issues such as biofortification, bioprotectants and the general link between food composition and human health. Research on key crops such as rice and tomato are used as illustration of potentially broader application across crop species. Although the focus is clearly on food supply, some attention is given to the complementary field of research, nutrigenomics, where similar technologies are being applied to understand nutrition better from the human side.     

Using minimum DNA marker loci for accurate population classification in rice (Oryza sativa L.)

Because of the rich diversity among rice accessions grown around the world in distinct environments, traditional methods using morphology, cross compatibility and geography for classifying rice accessions according to different sub-populations have given way to use of molecular markers. Having a few robust markers that can quickly assign population structure to germplasm will facilitate making more informed choices about genetic diversity within seedbanks and breeding genepools. WHICHLOCI is a computer program that selects the best combination of loci for population assignment through empirical analysis of molecular marker data. This program has been used in surveys of plant species, for fish population assignment, and in human ancestry analysis. Using WHICHLOCI, we ranked the discriminatory power of 72 DNA markers used to genotype 1,604 accessions of the USDA rice core collection, and developed panels with a minimum number of markers for population assignment with 99% or higher accuracy. A total of 14 markers with high discriminatory power, genetic diversity, allelic frequency, and polymorphic information content were identified. A panel of just four markers, RM551, RM11, RM224 and RM44, was effective in assigning germplasm accessions to any of five sub-populations with 99.4% accuracy. Panels using only three markers were effective for assignment of rice germplasm to specific sub-populations, tropical japonica, temperate japonica, indica, aus, and aromatic. Assignment to tropical japonica, temperate japonica, or indica sub-populations was highly reliable using 3–4 markers, demonstrated by the high correlation with assignment using 72 markers. However, population assignment to aus and aromatic groups was less reliable, possibly due to the smaller representation of this material in the USDA core collection. More reference cultivars may be needed to improve population assignment to these two groups. This study demonstrated that a small number of DNA markers is effective for classification of germplasm into five sub-populations in rice. This will facilitate rapid screening of large rice germplasm banks for population assignment at a modest cost. The resulting information will be valuable to researchers to verify population classification of germplasm prior to initiating genetic studies, maximizing genetic diversity between sub-populations, or minimizing cross incompatibility while maximizing allelic diversity within specific sub-populations.     

Development and field performance of nitrogen use efficient rice lines for Africa

Nitrogen (N) fertilizers are a major input cost in rice production, and its excess application leads to major environmental pollution. Development of rice varieties with improved nitrogen use efficiency (NUE) is essential for sustainable agriculture. Here, we report the results of field evaluations of marker‐free transgenic NERICA4 (New Rice for Africa 4) rice lines overexpressing barley alanine amino transferase (HvAlaAT) under the control of a rice stress‐inducible promoter (pOsAnt1). Field evaluations over three growing seasons and two rice growing ecologies (lowland and upland) revealed that grain yield of pOsAnt1:HvAlaAT transgenic events was significantly higher than sibling nulls and wild‐type controls under different N application rates. Our field results clearly demonstrated that this genetic modification can significantly increase the dry biomass and grain yield compared to controls under limited N supply. Increased yield in transgenic events was correlated with increased tiller and panicle number in the field, and evidence of early establishment of a vigorous root system in hydroponic growth. Our results suggest that expression of the HvAlaAT gene can improve NUE in rice without causing undesirable growth phenotypes. The NUE technology described in this article has the potential to significantly reduce the need for N fertilizer and simultaneously improve food security, augment farm economics and mitigate greenhouse gas emissions from the rice ecosystem.     

Enhanced genetic diversity of weedy rice populations associated with latitude decreases revealed by simple sequence repeat fingerprints

Weedy rice (WR, Oryza sativa L. f. spontanea) is a noxious agricultural weed, infesting rice fields worldwide and causing tremendous yield losses of cultivated rice. However, little is known about the relationship between genetic diversity and distribution of WR populations across a wide latitudinal gradient, in addition to its reasons for genetic differentiation. To determine the distribution of genetic diversity and differentiation, we analyzed 20 WR populations collected from wide geographic ranges of rice-planting regions across Northeast, Jiangsu and Guangdong provinces of China, and Sri Lanka, based on 20 simple sequence repeat loci. Our results indicated a significant negative correlation (R = 0.84, P < 0.01) between genetic diversity and latitudinal locations of WR populations. The Mantel test (R² = 0.49, P < 0.01) showed distinct groupings of WR populations from different rice-planting regions, fitting an isolation-by-distance pattern. In addition, the STRUCTURE analysis and principal coordinates (PCoA) analysis indicated considerable genetic differentiation of WR from different rice-planting regions, which was associated with the types of co-occurring rice cultivars. We conclude based on the above results that WR genetic diversity is affected by the latitudes where WR populations are located. The genetic differentiation of WR populations is determined by their spatial distances and co-occurring rice cultivars. Such a pattern of genetic diversity and differentiation across different regions may facilitate the design of effective WR control, in addition to understanding adaptive evolution of this weed.     

水稻轮回选择群体XTBG-HP1表型遗传多样性分析

该研究基于4个陆稻群体及172个水稻品种或杂交组合,构建了水稻多亲本隐性核不育轮回选择群体XTBG-HP1,并经过4次轮回重组,采用16个表型性状对其进行了遗传多样性分析。结果表明:(1)该群体14个数量性状符合正态分布,各表型均存在极端性状个体。(2)数量性状变异系数范围为0.08～0.41,均值为0.20; Shannon-Wiener多样性指数范围为0.72～1.92,均值为1.50。(3)群体在株型与产量构成因子性状方面有显著的相关性,对株型的选择可以实现产量性状的改良。(4)剑叶长、每穗粒总数、千粒重、穗长、粒长、一次枝梗数、有效穗数、剑叶宽、二次枝梗数、抽穗期10个性状可作为群体综合评价指标。(5)剑叶长、二次枝梗数、每穗粒总数3个表型性状具有较高的遗传变异、丰富的遗传多样性及与综合得分F值相关系数较高。综合以上结果发现,后期群体进行基因挖掘、品种改良以及优良育种材料的选育可以基于剑叶长、二次枝梗数及每穗粒总数3个表型性状,同时要充分利用群体株型与产量构成因子性状间的显著相关性。此外,该研究群体中极端单性状或综合得分F值较高的个体,可进一步用于品种选育。     

黔东南香禾糯AFLP遗传多样性分析与评价

香禾糯是我国侗族人民数百年来的传统主食,也是传统农业生态系统的重要组成部分。本文通过民族植物学调查与现代分子生物学试验相结合的方法,对黔东南侗族地区传统分类的香禾糯农家品种进行了评价,以便探讨香禾糯种质资源的遗传多样性变化。通过8对AFLP引物并基于遗传距离和遗传相似系数,对从黔东南侗族地区收集的95个香禾糯农家品种进行了分析。共检测到707个位点,其中多态性位点为619个,占87.55%,Shannon-Weiner多样性指数为0.3738,基因多样性指数为0.2446,遗传相似系数为0.7121~0.9958。当遗传相似系数为0.7546时,可划分为Ⅰ、Ⅱ两大类,外加1个特殊品种,其中Ⅰ类群有88个品种,Ⅱ类群有6个品种,来自相同和相邻侗寨或者形态性状相近的品种并没有完全聚在一起。结果表明黔东南地区香禾糯农家品种遗传多样性总体水平较高,特别是传统耕作文化保护较好的侗寨内,其遗传背景差异较大。香禾糯种质资源的多样性形成,在很大程度上与黔东南地区复杂多变的自然环境有关,还与该地区少数民族的传统耕作制度和民族传统文化延续密切相关。     

广东省地方稻种品质性状表型多样性及其形成的生态因子分析

（广东省农业科学院水稻研究所,广州 510640） 摘要 为了进一步完善广东地方稻种资源的鉴定评价,并为该资源在水稻品质育种中的有效利用提供科学依据,我们以国家作物种质库编目的2974份广东地方稻种为研究对象,其9个品质性状数据为基础,研究了广东地方稻种品质性状的区域分布特点,并对总体和不同稻作区品质性状多样性进行了比较分析.同时对部分生态因子与品质性状的相关性进行了初探。结果显示,广东地方稻种资源品质性状具有丰富的多样性。其糙、精米率较高,蛋白质含量丰富多样,胶稠度的变异幅度大,直链淀粉含量适中达国标的材料偏少;中南稻作区为广东优质地方稻种的主要集中地;不同稻作区的品质性状多样性表现各异;直链淀粉含量、碱消值及胶稠度是影响广东地方稻种品质形成的主要指标;湿度和温度的地域差异是广东地方稻种稻米品质多样性的主要成因。本研究结果充分说明,广东地方稻种中具有优异品质性状资源的利用对改良现有品质的稻米品质和拓宽遗传基础具有十分重要的意义。     

Metabolic diversity in the grains of Indian varieties of rice

The aim of the present work was to analyze metabolic diversity in 26 different indica varieties of rice grains. Seventy-six metabolites could be identified in the methanol extracts of each of the rice varieties analyzed by gas chromatography-mass spectrometry. These metabolites included 9 sugars/sugar alcohols, 17 amino acids/derivatives, 18 fatty acids, 5 free phenolic acids and 19 other organic acids, 3 phytosterols, 5 other constituents. Cluster analyses to extract information for similarity and differences in metabolites unveiled diversity in metabolite profile. Two hierarchical clusters were generated based on the metabolite contents of the rice varieties. The first cluster (cluster I) consisted of one variety only. The second cluster again segregated into four clusters (clusters II, III, IV and V). Very distinct differences were visible amongst the clusters with respect to their sugars/sugar alcohols, organic acid, amino acid and fatty acid, phenol, and sterol profiles. Metabolites determine nutritional quality, taste, aroma. This and future efforts on the metabolomic information would help biochemists and nutritionists to better understand the nutritional quality of such grains at varietal level and correlating metabolites and long term human health related issues.