Identification of AFLP Makers Linked to Early-Bearing Gene in Walnut

Amplified fragment length polymorphism （AFLP）, a novel DNA fmgerprinting technique based on polymerase chain reaction （PCR） with high discriminatory power, has the advantages of high efficiency, rapidness, reliability, and rich polymorphism et. It has been widely used for screening molecular markers, constructing genetic linkage map, analyzing relationship and locating genes （Vos et al., 1995）. However, due to high price of reagents involved in AFLP and requirement of high technology, its potential use has been limited. For walnuts, there are two groups characterized with early-bearing and late-bearing trait, respectively. Early-bearing walnuts ramify early with short intemodes, and begin to blossom and bear fruits in the first or second year or so. Studies show that the gene associated with the early-bearing character is a kind of precious genetic resource in nature and has very high hereditable ability （Zheng et al., 2003; Yamamo et al., 1998; Fang et al., 1999）. Research and employment of this has important meaning not only for the varieties improvement of walnuts, controlling and realizing of earlybearing quality, but also for the studies of flower bud differentiation in fruit trees. This research, combined AFLP technology with bulked segregant analysis （BSA） to screen AFLP markers linked to early-bearing character in walnut, can be applied to early screening of walnut hybrids, constructing genetic linkage map, locating genes and improving varieties.     

Construction of Genetic Linkage Map and QTL Mapping for Fiber Quality in Upland Cotton

A comprehensive genetic linkage map was constructed using 270 F2:7 recombinant inbred lines from a cross between two upland cotton cultivars Yumian 1 and T586.The linkage map comprised of 604 loci and 57 linkage groups ordered into 25 chromosomes,spanning 3106.9 cM,and approximately accounting for the 69.87～ of the whole cotton genome with an average genetic distance of 5.15 cM between two markers.Based on interval mapping,29 QTLs affecting fiber quality were identified,including 5 QTLs for fiber length,7 QTLs for fiber uniformity,10 QTLs for fiber strength,2 QTLs for fiber elongation,and 5 QTLs for fiber fineness.Seventeen QTLs were mapped on A sub-genome chromosomes,and 12 on D sub-genome.     

Identification of QTLs for Drought Resistance of Maize Germination and Seedling Development

In most maize-growing areas yield reductions due to drought have been observed （Frova et al., 1999; Li et al., 2003; Ribaut et al., 1997; Sari-Gorla et al., 1999）. Seed germination and early seedling growth is the primary stage for maize development. The ability of seeds to germinate rapidly and uniformly under water stress is desirable for maize production. In this study, a F9 RIL （recombinant inbred line） population was developed by crossing a drought-tolerant inbred line with a drought-susceptible one （Huangzaosi/Mol7）. Using this population, SSR linkage map was constructed with a total of 101 SSR markers covered 1 422.7 cM and average SSR marker density 15.6 cM. The map was in high consistence with published IBM map（www.maizedb.org）. QTLs analysis was conducted for germination drought tolerance index （GDTI） measured as germination index （GI） under water stress （WS）/GI under well watered（WW） condition using hydroponics method, and seedling drought tolerance index （SDTI） measured as water content of seedling under WS/water content of seedling under WW（Tuberosa et al.     

Genetic Diversity of Peanut Core Collection from US Using Simple Sequence Repeats

Groundnut is a member of genus Arachis and the crop is divided into two subspecies and six botanical varieties based on morphological characteristics （Krapovickas and Gregory, 1994）. The International Crops Research Institute for the Semi-Arid Tropics （ICRISAT） holds more than 14 000 groundnut accessions from which a core collection of 1 704 have been developed （Upadhyaya et al., 2003）. Holdbrook et al. （1993） developed a groundnut core collection of 831 accessions from a total of 7 432 US groundnut accessions based on morphological characteristics. The large number and variability of accessions in GenBanks create problems in knowing which germplasm to select for breeding purpose. Only a few established cultivars and elite breeding lines have been utilised in breeding programmes. A core collection is a fraction of accessions from the entire collection which represent most of the available genetic diversity of the species. A core collection can extensively be evaluated and information derived from them can be applied to the whole collection. Identification of DNA markers associated with the botanical varieties of groundnut would be useful in genotyping, germplasm management and evolutionary studies.     

The Power of Integrative Approaches to Develop Markers for Maize Molecular Breeding

Recent advances in genomics and bioinformatics now offer real opportunities for dissecting complex Waits into their component sub-traits, which will simplify the process of developing the tools necessary to manipulate the underlying genes （Varshney et al., 2005）. The value of molecular markers as a complement to phenotyping under several breeding scenarios is largely unquestioned, as demonstrated by the increasing number of successful studies published （Varshney et al., 2006）. However most experiments have targeted crop improvement for disease resistance, morphological waits or quality waits （Franca et al., 2005） and there is still some way to go before markers can be used routinely and ubiquitously to breed for complex waits, such as tolerance to abiotic stress （Ribaut and Ragot, 2007）. The combination of genetic mapping and association studies has considerable potential to generate a catalogue of genetic variation, and thereby present novel opportunities for selection based on genome-wide scans （Biswas and Akey, 2006）. Nevertheless, it remains to be seen whether the outcome of gene interactions, particularly where significant gene networks are involved,     

Molecular Breeding in an Industrial Setting

To develop better varieties for farmers and to increase overall agricultural productivity, Monsanto Company has continued to lead innovations in plant biotech, breeding and molecular breeding. In Molecular breeding, nongel based SNP markers have replaced traditional gel-based markers. Our advanced SNP discovery pipeline enabled us to rapidly identify thousands of single nucleotide polymorphisms （SNP） for use as markers in any crops of choice. High-density SNP maps have been successfully constructed for major crops and these maps have provided a useful tool for QTL identification, Marker-Assisted Breeding, Association Study as well as biotech trait integration. Our high level of automation, in conjunction with accurate data tracking and analytical systems, has made it possible to achieve high throughput and unattended 24-hour operations for reliable and cost-effective large volume genotyping and data analysis. As genetic information continues to accumulate, confirmed associations between markers and traits grow. Such information will allow breeders to gain insight into the genetic determinants underlying complex agronomic traits. Furthermore,     

Comparative Genomics for Gene Isolation in Legumes

The similarity in gene order between closely related taxa suggests that genomic information from model systems should facilitate gene isolation and characterization in target crops. If this is the case, a great deal of effort and investment can be saved by focusing attention on a few model systems that have appropriate applicability. Pea （Pisura sativum） provides a good test case： its genome is large and the insertion sites for repetitive elements, which comprise the bulk of its genome, are highly polymorphic （Jing et al., 2005; Vershinin et al., 2003）, so we expect a great deal of structural polymorphism between the genomes of Pisum lines. Yet the genetic map of Pisum is essentially coUinear with Medicago （Choi et al., 2004; Kalo et al., 2004）.     

Comparative Mapping of Cotton and Arabidopsis

A high-density inferred consensus map for 13homoeologous groups of cotton was constructedthrough the integration of three genetic maps(At,Dt and D)of homoeologous chromosomes.The consensus map included 2843 markers andspanned about 2242 cM in 13 linkage groups.1777 mapped probes were sequenced andcompared to the Arabidopsis using the BLAST     

Comparison of QTL for Grain Number per Panicle in Three Populations Sharing 3 Parents and Fine Mapping of Gnlc

Complex traits, such as yield components, are inherited in a quantitative manner and typically controlled by quantitative trait loci （QTL）. Grain number per panicle （GN） is an important component of yield in rice and has been studied for QTL mapping in our lab （Yu et al., 1997; Xing et al., 2002）. Further discovery of QTL for GN and fine mapping will provide rich of gene resources for high yield breeding by marker assistant selection. Gene cloning is helpful to understand the biological mechanism underlying GN and instruct the application of gene engineering in rice yield breeding. In recent years, near-isogenic lines （NILs） for grain number have been reported for gene fine mapping （Tian et al., 2006; Zhang et al., 2006） and gene cloning （Ashikari et al., 2005）. However, so far, this kind of research is insufficiency for systematically elucidating the genetic bases and regulatory mechanism involved in GN. In this study, we compare the locations and genetic effects of QTL for GN detected in three sets of recombinant inbred line populations （RILs） sharing three parents, and fine map a new major QTL, Gnlc, commonly detected in the 3 populations.     

Genetic Dissection, Marker-assisted Introgression, and Pyramiding of Agronomic Traits in Rice

Through the efforts of the International Rice Genome Sequencing Project, the whole genome sequence office has been decoded （International Rice Genome Sequencing Project, 2005）. This sequence information has provided new tools for genetics and has created a new paradigm of plant breeding. Many phenotypic traits of economic interest are controlled by multiple genes and often show complex and quantitative inheritance： Recent progress in rice genomics has had a great impact in the genetic dissection of such traits into single genetic factors. Such genetic factors can subsequently be identified at the molecular level by map-based strategies （Yano, 2001）. So far, we have identified several genes involved in heading date （Yano et al., 2001）, field resistance to rice blast, cool temperature tolerance （Takeuchi et al., 2001） and pre-harvest sprouting （Takeuchi et al., 2003）, and genetic dissection of root morphology and yield-related traits is progressing. Working from the current status of genetic dissection, we have begun marker-assisted introgression of particular genes of interest into elite rice cultivars in Japan. Exploitation of economically important genes in natural variants will be essential to enhance the potential of new breeding strategies.     

葫芦科瓜类作物分子遗传图谱研究进展

黄瓜、甜瓜和西瓜是重要的葫芦科瓜类作物,构建高密度的葫芦科瓜类分子遗传图谱研究将有助于提高瓜类作物的育种水平。近年来,AFLP、RAPD和SSR等分子标记技术的运用,加速了瓜类作物分子遗传图谱的构建。然而,与番茄、拟南芥的图谱研究相比,目前瓜类作物的遗传图谱密度还不够饱和,不能覆盖整个基因组。今后需要增加更多种类的分子标记和进行图谱整合工作,以获得高密度的遗传图谱,加速标记辅助育种进程。     

苦荞SSR分子遗传图谱的构建及分析

构建苦荞遗传连锁图谱,为今后有关苦荞基因组结构、重要农艺性状QTL定位、分子标记辅助育种和基因克隆等研究工作奠定基础。以栽培苦荞‘滇宁一号’和苦荞野生近缘种杂交产生的119份F4代分离材料为作图群体,利用SSR分子标记来构建苦荞的分子遗传连锁图谱。本研究构建的连锁图谱包含15个连锁群,由89个标记组成,其中偏分离的标记有22个,占24.7%,每条连锁群上的标记在2~16之间。连锁群长度在6.9~165.8 cM的范围,覆盖基因组860.2 cM,总平均长度9.7 cM。本研究构建了首张苦荞SSR遗传连锁图谱,为苦荞QTL定位、基因克隆、遗传选育等研究奠定了基础。     

黄瓜遗传图谱研究进展

黄瓜是重要的蔬菜作物,其遗传、育种研究长期受到研究人员的关注。近20年来,黄瓜遗传图谱构建研究取得很大进展。最初的研究只包含了个别形态学性状的连锁关系分析,随着大量分子标记技术和稳定的构图群体的应用,国内外各个实验室已各自构建了基于不同遗传背景的黄瓜遗传连锁图谱。目前的黄瓜分子遗传图谱已经发展到整合图谱阶段,包含大量的通用标记和单核苷酸差异(SNPs),且黄瓜细菌染色体克隆载体技术也日益完善,这就为黄瓜重要基因的克隆分析、分子标记辅助选择育种和分子生物学的深入研究提供了更加完善的基础和工具。本文全面总结近年来黄瓜遗传图谱的研究进程,着重论述了基于分子标记构建的遗传图谱的现状及应用,提出了黄瓜遗传图谱构建中存在的问题,并探讨了其发展趋势。     

利用3个F_2群体整合高密度栽培种花生遗传连锁图

遗传图谱的构建及整合是开展花生分子育种研究的基础,利用多个作图群体整合遗传图谱是解决图谱标记密度低的有效途径。本研究采用基于锚定SSR标记的作图策略,构建3个F_2群体3张遗传连锁图,利用Join Map 3.0软件整合图谱,获得一张包含20个连锁群、792个位点、总遗传距离为2079.50 c M,标记间平均距离为2.63 c M的整合图谱,各连锁群标记数在20~66个之间,遗传距离在59.10~175.80 c M之间。将3个分离群体中检测到的与荚果及种子大小相关的QTL区段与整合连锁图的标记比较发现,各群体中检测到的位于各染色体上的QTL在整合图谱中都能出现,有些QTL标记区间在整合图谱中存在更多的标记,为今后利用这些标记进行精细定位奠定了基础。     

用SSR标记提高水稻分子连锁图谱密度

本课题组利用圭630／台湾粳的DH群体，建立了一个水稻RFLP连锁图。该图谱含175个标记，总长1224．6cM，相邻标记间平均距离为7．0cM。但该图标记分布不够均匀，存在较多空白区，且在第4和第8染色体上分别存在一个断点。本研究试图在原有RFLP图谱的基础上，添加一些SSR标记，以使该图谱标记更加密集和均匀，并消除两个断点。共筛选了361对RM引物，获得了183对多态标记，在12条染色体上共整合了57个RM标记，染色体连锁图总长度为1811．2cM，比原图谱增长了47．9％，相邻标记间平均距离为7．8cM，与原图谱相近。不过，两条染色体上的两个断点仍无法消除，暗示这两个断点区域多态性较低或重组率较高。     

玉米抗病基因一致性图谱的构建

发掘和精细定位玉米抗病基因是构建玉米抗病分子育种技术体系的重要基础。利用生物信息学手段,整理文献和玉米基因组数据库中已有的抗病基因定位的信息,借助高密度玉米分子标记连锁图谱IBM2 2005 neighbors,通过染色体映射的方法,绘制了玉米抗病基因的一致性图谱。结果显示,在试验涉及到的14种主要玉米病害的78个抗病主基因或QTL之中,抗病基因在各条染色体上呈不均匀分布,第3、第6、第10染色体上的主效抗病基因较多,第5和第7染色体上的抗病基因较少,且抗病基因呈簇集分布。研究结果为进一步发掘和鉴定玉米抗病基因和建立玉米抗病分子标记辅助育种技术体系奠定了基础。     

An introduction to markers, quantitative trait loci (QTL) mapping and marker-assisted selection for crop improvement: The basic concepts

Recognizing the enormous potential of DNA markers in plant breeding, many agricultural research centers and plant breeding institutes have adopted the capacity for marker development and marker-assisted selection (MAS). However, due to rapid developments in marker technology, statistical methodology for identifying quantitative trait loci (QTLs) and the jargon used by molecular biologists, the utility of DNA markers in plant breeding may not be clearly understood by non-molecular biologists. This review provides an introduction to DNA markers and the concept of polymorphism, linkage analysis and map construction, the principles of QTL analysis and how markers may be applied in breeding programs using MAS. This review has been specifically written for readers who have only a basic knowledge of molecular biology and/or plant genetics. Its format is therefore ideal for conventional plant breeders, physiologists, pathologists, other plant scientists and students.     

甘蔗SSR和AFLP分子遗传连锁图谱构建

采用甘蔗商业品种Co419与野生种割手密Y75/1/2杂交,获得269个单株,组成F1群体,用F102/356与商业品种ROC25回交获得266个单株,组成BC1群体。利用筛选的多态性条带丰富的36对SSR引物和12对AFLP引物,对两个群体进行PCR扩增和分子遗传连锁分析,构建甘蔗分子遗传连锁图谱。用F1群体获得630个分离标记,经χ2检测,298个标记为单双剂量标记,占总标记数的47%;用BC1群体获得571个分离标记,有264个标记为单双剂量标记,占总标记数的46%;4个亲本获得单双剂量标记的数量依次为Co41902/356Y75/1/2ROC25。在LOD≥5.0,相邻标记遗传距离≤40cM的条件下,F1群体有134个单双剂量标记被纳入55个连锁群,其中39个连锁群归属8个同源组,16个未列入,总遗传距离为1458.3cM,标记间平均图距为10.9cM;BC1群体有133个单双剂量标记被纳入47个连锁群,其中34个连锁群归属于8个同源组,13个连锁群未列入,总遗传距离为1059.6cM,标记间平均图距为8.0cM。从4个亲本单双剂量标记进入的连锁群数来看,Co419最多,归入34个连锁群,其次为Y75/1/2,归入20个连锁群,第3为02/356和ROC25,归入19个连锁群。研究结果表明,从单双剂量标记比例、形成连锁群数量、总遗传距离来看,F1群体构图质量要优于BC1群体。     

绿豆遗传连锁图谱的整合

利用绿豆及其近缘种的701对SSR引物,对现有绿豆遗传连锁图谱进行补充,结果在高感豆象绿豆栽培种Berken和高抗豆象绿豆野生种ACC41两亲本间筛选到多态性SSR引物104对。群体分析后,结合其他分子数据,使用作图软件Mapmaker/Exp 3.0b,获得一张含有179个遗传标记和12个连锁群,总长1831.8cM、平均图距10.2cM的新遗传连锁图谱,包括97个SSR标记,91个来自绿豆近缘种;RFLP标记76个;RAPD标记4个;STS标记2个。对32个绿豆、小豆共用SSR标记在遗传连锁图谱的分布分析发现,二个基因组间有一定程度的同源性,共用标记在连锁群上的排列顺序基本上一致,只有部分标记显示绿豆和小豆基因组在进化过程中发生了染色体重排;利用新图谱对ACC41的抗绿豆象主效基因重新定位,仍定位于I(9)连锁群,与其相邻分子标记的距离均小于8cM,其中与右翼SSR标记C220的距离约2.7cM。与原图谱比较,新定位的抗性基因与其相邻标记的连锁更加紧密。     

Breeding for boron tolerance in lentil (Lens culinaris Medik.) using a high‐throughput phenotypic assay and molecular markers

This study describes the identification of a quantitative trait locus (QTL) in the recombinant inbred line population of ILL2024 × ILL6788 and subsequent validation of associated molecular markers. A high‐quality genetic linkage map was constructed with 758 markers that cover 1,057 cM, with an average intermarker distance of 2 cM. QTL analysis revealed a single genomic region on Lc2 to be associated with B tolerance and accounted for up to 76% of phenotypic variation (Vp). The best markers for B tolerance were assessed for their utility in routine breeding applications using validation panels of diverse lentil germplasm and breeding material derived from ILL2024. A marker generated from the dense genetic map of this study was found to be the most accurate of all markers available for B tolerance in lentil, with a success rate of 93% within a large breeding pool derived from ILL2024. However, given the number of the unrelated lines for which the marker–trait association was not conserved, B tolerance screening is still required at later stages to confirm predicted phenotypes.