利用RFLP,SSR,AFLP和RAPD标记分析玉米自效系遗传多样性的比较研究

利用ＲＦＬＰ、ＳＳＲ、ＡＦＬＰ和ＲＡＰＤ４种分子标记方法研究了１５个玉米（Ｚｅａ ｍａｙｓ Ｌ．）自交系的遗传多样性,同时对４种标记系统进行比较。在供试材料中筛选到具多态性的ＲＦＬＰ探针酶组合５６个,６７６对ＳＳＲ引物,２０个ＲＡＰＤ引物和９个ＡＦＬＰ引物组合,分别检测到多态性带１６７、２０１、８７和１０８条。ＳＳＲ标记位点的平均多态性检测效率（Ａｉ,３２．２）。４种分子标记所得遗传相似自交系划分     

玉米CMS材料线粒体DNA遗传多型性的研究

选用１１×４＝４４个探针／酶组合,５０个（１０ｍｅｒ）随机序列引物对２５种不同胞质来源的ＣＭＳ玉米,５种正常胞质玉米线粒体ＤＮＡ进行ＲＦＬＰ和ＲＡＰＤ研究。研究结果表明：（１）４５％的探针／酶组合可检测到玉米线粒体ＤＮＡ的多型性,共表现１５种ＲＦＬＰ类型,其中Ｓ组ＣＭＳ材料内有７种,正常胞质材料内有２种;８０％的随机引物可检测到ＲＡＰＤ。（２）基于ＲＦＬＰ资料的聚类分析结果,可将３０种胞质明确地划分为Ｔ、Ｃ、Ｓ、Ｎ４组,其结果与恢复专效性测定结果一致。其中ｐＨＪ２－７－１／ＢａｍＨＩ的ＲＦＬＰ类型可成为利用ＲＦＬＰ技术进行胞质分组的鉴定体系。（３）“双”型胞质线粒体ＤＮＡ常表现Ｓ＋Ｃ胞质的ＲＦＬＰ图谱。     

应用RAPD技术对不同基因组组合生物型遗传多态性的研究(英文)

利用ＲＡＰＤ技术对不同基因组合的鱼类进行了基因组指纹图谱构建,在ＤＮＡ水平上对基因组成分进行了分析,探讨了其遗传多态性。ＲＡＰＤ结果发现,在２６个随机引物扩增的产物中,平均每个个体观察到约１４２个ＲＡＰＤ标记,单个引物获得的标记平均为５．４。其中４个引物扩增的图谱可将不同的生物型区分开：Ｓ－２６引物的扩增图谱（Ｆｉｇ．１）可将红鲫（ＲＡ）与其它组合区分开,还可将鲤鲫杂种一倍体（ＣＡ）与鲫鲤杂种三倍体（ＣＡＡ）和人工复合三倍体鲤（ＣＣＡ）区分开;Ｓ－８引物（Ｆｉｇ．２）可区分开红鲤（ＲＣ）和镜鲤（ＭＣ）;Ｓ－４５引物（Ｆｉｇ．３）可区分开ＲＣ和ＣＡ;Ｓ－２２引物则可区分开ＣＡＡ和ＣＣＡ。六种生物型均存在基因组特异性的图谱即各自独特的“诊断性”图谱,作者由此建立了详细的分子标记检索表（Ｔａｂｌｅ１）。通过对ＲＡＰＤ图谱的量化分析,利用ＵＰＧＭＡ构建了不同生物型的遗传关系树图;反映了鲤鲫及各种组合生物型之间的遗传相似关系：ＲＣ和ＭＣ属同一种系,聚为一族;ＣＡＡ和ＣＡ基因组类型相同,聚为一族;ＣＣＡ虽自成一体,但可与ＣＡＡ和ＣＡ聚为一族;而ＲＡ与其它组合遗传距离较远,自成一族。ＲＡＰＤ的结果也表明各种生物型内个体间     

水稻的AFLP研究初报——反应条件的优化及对温敏核不育等位突变系的分析

通过对５４６０Ｓ和５４６０Ｆ这一对水稻等位突变系的ＡＦＬＰ分析,比较了ＡＦＬＰ与ＲＡＰＤ及ＲＦＬＰ检测ＤＮＡ多态性的相对效率。结果表明,这３种分子标记的ＤＮＡ多态性检出效率依次为ＡＦＬＰ＞ＲＡＰＤ＞ＲＦＬＰ;找出了水稻ＡＦＬＰ分析的最适反应条件;在这对等位突变系之间找到了一些多态性ＡＦＬＰ产物,已完成了对４个多态性ＡＦＬＰ产物的克隆,其中３个为单拷贝顺序;用这３个单拷贝克隆的混合物为探针,对作者自己构建的５４６０Ｓ水稻的ＢＡＣ库进行了筛选,获得了１２个阳性克隆,为今后ＢＡＣ库的筛选打下了基础。此外,对上述３种分子标记各自的优缺点及它们在ＤＮＡ多态性检测中的适用之处进行了分析探讨。     

RAPD标记构建水稻分子连锁图

利用随机扩增多态性ＤＮＡ（ＲＡＰＤ）,在一个水稻（Ｏｒｙｚａ ｓａｔｉｖａ Ｌ．）的双单倍体（ＤＨ）群体中发展分子标记,仅用５２ 个ＲＡＰＤ标记建成了一个水稻ＲＡＰＤ分子连锁图。该图覆盖基因组的总长度为８９８．４ ｃＭ （ｃｅｎｔｉｍ ｏｒｇａｎ）,标记间的平均间距为１７．３ ｃＭ,它能与用同一群体构成的ＲＦＬＰ图谱互相补充     

RFLP、RAPD、AFLP在水稻农垦58S和1514中多态性比较

本文用ＲＦＬＰ、ＲＡＰＤ和ＡＦＬＰ三种分子标记技术对农垦５８ＳＸ１５１４组合及其Ｆ２极性集团进行了分析,比较了它们多成性和阳性的比率,结果显示,三种分子标记的多态性和与目的基因连锁的阳性比率分别为１９．９３％,５．２３％;１１．１７％,０．７６％和８６．４７％,７．５２％。ＡＦＬＰ的多态性比率和阳性比率均为最高。分析探讨了三种分子标记技术的优缺点及其在区间高分辩率作图和筛选与目的基因连锁标记中的运     

玉米自交系遗传变异的RFLP分析

利用ＲＦＬＰ标记研究了１３个玉米（Ｚｃａ ｎａｙｓ Ｌ．）自交系的遗传变异。从３０对探针／酶组合中筛选出杂交带型清晰、稳定、重复性好的２４对组合,在１３个自交系中获得８５个等位基因杂交片段,平均每个位点为３．３条,平均多态性指数为０．４９９。１３个自交系之间的遗传相似系数为０．５２３－０．８０２,平均为０．６４９。ＵＰＧＭＡ聚类分析表明,供试自交系共分为５个类群,分群结果与其系谱关系基本吻合;表明     

古代“太子莲”及现代红花中国莲种质资源的RAPD分析

采用４０个１０碱基随机引物及８个锚定ＳＳＲ引物,对寿命为（５８０±７０）年的古代“太子莲”以及哈尔滨、河北、江西、湖南等地区的红花中国莲（ＮｅｌｕｍｂｏｎｕｃｉｆｅｒａＧａｅｒｔｎ．）野生居群或农家栽培品种的基因组ＤＮＡ进行了ＲＡＰＤ及微卫星（ＳＳＲ）ＤＮＡ多态性检测,共筛选出能产生多态性标记的ＲＡＰＤ引物１３个、ＳＳＲ引物２个。这１５个引物共扩增出１３５个位点,其中多态性位点７１个,占５２６％。琼脂糖电泳表明“太子莲”与哈尔滨红花莲表现出高度的遗传一致性,上述１５个引物未能在两组样品内检测到任何遗传变异。来自河北、江西、湖南的红花莲皆表现出不同程度的居群内或品种内分化。根据ＭＥＧＡ程序中的ＵＰＧＭＡ聚类分析结果,“太子莲”与哈尔滨、河北两地区的红花莲聚为一支。“太子莲”与河北红花莲的遗传距离最近（００５）,它们拥有共同的祖先。古代“太子莲”与其它４个地区的红花莲比较起来只缺少ＯＰＭＯ６３００一条带,仍属于红花中国莲这个种。湖南红花莲与江西红花莲之间可能有基因交流,彼此亲缘关系密切,聚为另一支。它们与“太子莲”遗传距离较远（０６７）。     

利用分子标记定位农垦58S的光敏核不育基因

对农垦５８Ｓ（Ｏｒｙｚａｓａｔｉｖａｓｐ．ｊａｐｏｎｉｃａ）／大黑矮生标记基因系ＦＬ２组合组建可育集团和不育集团,并以亲本为对照进行了ＲＦＬＰ、ＲＡＰＤ和双引物ＲＡＰＤ分析,结果第１２染色体上的一个单拷贝标记Ｇ２１４０与光敏核不育基因连锁遗传,二者间的遗传图距为１４．１ｃＭ（ｃｅｎｔｉｍｏｒｇａｎ）。在筛选过的１０４０个随机单引物和１９０个双引物中,仅引物ＯＰＡＵ１０扩增出与光敏核不育基因连锁的１．５ｋｂＤＮＡ片段,回收、克隆该ＤＮＡ片段并制备探针,将其转换成共显性的ＲＦＬＰ标记并命名为ＯＰＡＵ１０１５００。分离群体连锁分析表明该标记与标记Ｇ２１４０紧密连锁,将农垦５８Ｓ的一对光敏核不育基因定位于第１２染色体上。     

微卫星DNA和AFLP标记在水稻分子标记连锁图上的分布

以一个栽培稻（ＯｒｙｚａｓａｔｉｖａＬ．ｓｐ．ｉｎｄｉｃａ）和野生稻（Ｏ．ｒｕｆｉｐｏｇｏｎＧｒｉｆ）杂交的Ｆ２作图群体以及由该群体构建的ＲＦＬＰ标记连锁图,分析了微卫星ＤＮＡ和ＡＦＬＰ标记的多态性、遗传行为及其在染色体上的分布。共定位了２８个微卫星ＤＮＡ标记和１７２个ＡＦＬＰ标记。２８个微卫星ＤＮＡ标记中有６个为华中农业大学作物遗传改良国家重点实验室根据数据库中序列而设计,其余２２个来自美国Ｃｏｒｎｅｌ大学已发表的结果。１７２个ＡＦＬＰ标记出自２５对引物扩增得到的２２８个多态性带的片段。这些标记分布于水稻的１２条染色体。将此２００个ＰＣＲ标记与华中农业大学作物遗传改良国家重点实验室构建的ＲＦＬＰ连锁图整合,得到一张含６１２个分子标记位点的遗传连锁图。     

Comparative analysis of genetic similarity among maize inbred lines detected by RFLPs, RAPDs, SSRs, and AFLPs

 DNA-based fingerprinting technologies have proven useful in genetic similarity studies. RFLP is still most commonly used in the estimation of genetic diversity in plant species, but the recently developed PCR-based marker techniques, RAPDs, SSRs and AFLPs, are playing an increasingly important role in these investigations. Using a set of 33 maize inbred lines we report on a comparison of techniques to evaluate their informativeness and applicability for the study of genetic diversity. The four assays differed in the amount of polymorphism detected. The information content, measured by the expected heterozygosity and the average number of alleles, was higher for SSRs, while the lowest level of polymorphism was obtained with AFLPs. However, AFLPs were the most efficient marker system because of their capacity to reveal several bands in a single amplification. In fact, the assay efficiency index was more than ten-fold higher for AFLPs compared to the other methods. Except for RAPDs, the genetic similarity trees were highly correlated. SSR and AFLP technologies can replace RFLP marker in genetic similarity studies because of their comparable accuracy in genotyping inbred lines selected by pedigree. Bootstrap analysis revealed that, in the set of lines analysed, the number of markers used was sufficient for a reliable estimation of genetic similarity and for a meaningful comparison of marker technologies. Received: 11 April 1998 / Accepted: 19 May 1998     

Comparative analysis on the genetic relatedness of Sorghum bicolor accessions from Southern Africa by RAPDs,AFLPs and SSRs

In order to get an overview on the genetic relatedness of sorghum (Sorghum bicolor) landraces and cultivars grown in low-input conditions of small-scale farming systems, 46 sorghum accessions derived from Southern Africa were evaluated on the basis of amplified fragment length polymorphism (AFLPs), random amplified polymorphic DNAs (RAPDs) and simple sequence repeats (SSRs). By this approach all sorghum accessions were uniquely fingerprinted by all marker systems. Mean genetic similarity was estimated at 0.88 based on RAPDs, 0.85 using AFLPs and 0.31 based on SSRs. In addition to this, genetic distance based on SSR data was estimated at 57 according to a stepwise mutation model (Deltamu-SSR). All UPGMA-clusters showed a good fit to the similarity estimates (AFLPs: r = 0.92; RAPDs: r = 0.88; SSRs: r = 0.87; Deltamu-SSRs: r = 0.85). By UPGMA-clustering two main clusters were built on all marker systems comprising landraces on the one hand and newly developed varieties on the other hand. Further sub-groupings were not unequivocal. Genetic diversity (H, DI) was estimated on a similar level within landraces and breeding varieties. Comparing the three approaches to each other, RAPD and AFLP similarity indices were highly correlated (r = 0.81), while the Spearman's rank correlation coefficient between SSRs and AFLPs was r = 0.57 and r = 0.51 between RAPDs and SSRs. Applying a stepwise mutation model on the SSR data resulted in an intermediate correlation coefficient between Deltamu-SSRs and AFLPs (r = 0.66) and RAPDs ( r = 0.67), respectively, while SSRs and Deltamu-SSRs showed a lower correlation coefficient (r = 0.52). The highest bootstrap probabilities were found using AFLPs (56% on average) while SSR, Deltamu-SSR and RAPD-based similarity estimates had low mean bootstrap probabilities (24%, 27%, 30%, respectively). The coefficient of variation (CV) of the estimated genetic similarity decreased with an increasing number of bands and was lowest using AFLPs.     

Construction of a combined sorghum linkage map from two recombinant inbred populations using AFLP,SSR, RFLP,and RAPD markers,and comparison with other sorghum maps

Sorghum [Sorghum bicolor (L.) Moench] is an important crop in the semi-arid tropics that also receives growing attention in genetic research. A comprehensive reference map of the sorghum genome would be an essential research tool. Here, a combined sorghum linkage map from two recombinant inbred populations was constructed using AFLP, SSR, RFLP and RAPD markers. The map was aligned with other published sorghum maps which are briefly reviewed. The two recombinant inbred populations (RIPs) analyzed in this study consisted of 225 (RIP 1) and 226 (RIP 2) F_3:5 lines, developed from the crosses IS 9830 2 E 36-1 (RIP 1) and N 13 2 E 36-1 (RIP 2), respectively. The genetic map of RIP 1 had a total length of 1,265 cM (Haldane), with 187 markers (125 AFLPs, 45 SSRs, 14 RFLPs, 3 RAPDs) distributed over ten linkage groups. The map of RIP 2 spanned 1,410 cM and contained 228 markers (158 AFLPs, 54 SSRs, 16 RFLPs) in 12 linkage groups. The combined map of the two RIPs contained 339 markers (249 AFLPs, 63 SSRs, 24 RFLPs, 3 RAPDs) on 11 linkage groups and had a length of 1,424 cM. It was in good agreement with other sorghum linkage maps, from which it deviated by a few apparent inversions, deletions, and additional distal regions.     

The comparison of RFLP,RAPD, AFLP and SSR (microsatellite) markers for germplasm analysis

The utility of RFLP (restriction fragment length polymorphism), RAPD (random-amplified polymorphic DNA), AFLP (amplified fragment length polymorphism) and SSR (simple sequence repeat, microsatellite) markers in soybean germplasm analysis was determined by evaluating information content (expected heterozygosity), number of loci simultaneously analyzed per experiment (multiplex ratio) and effectiveness in assessing relationships between accessions. SSR markers have the highest expected heterozygosity (0.60), while AFLP markers have the highest effective multiplex ratio (19). A single parameter, defined as the marker index, which is the product of expected heterozygosity and multiplex ratio, may be used to evaluate overall utility of a marker system. A comparison of genetic similarity matrices revealed that, if the comparison involved both cultivated (Glycine max) and wild soybean (Glycine soja) accessions, estimates based on RFLPs, AFLPs and SSRs are highly correlated, indicating congruence between these assays. However, correlations of RAPD marker data with those obtained using other marker systems were lower. This is because RAPDs produce higher estimates of interspecific similarities. If the comparisons involvedG. max only, then overall correlations between marker systems are significantly lower. WithinG. max, RAPD and AFLP similarity estimates are more closely correlated than those involving other marker systems.Abbreviations RFLP restriction fragment length plymorphism - RAPD random-amplified polymorphic DNA - AFLP amplified fragment length polymorphism - SSR simple sequence repeat - PCR polymerase chain reaction - TBE Tris-borate-EDTA buffer - MI marker index - SENA sum of effective numbers of alleles     

Direct comparison of levels of genetic variation among barley accessions detected by RFLPs, AFLPs, SSRs and RAPDs

 RFLPs, AFLPs, RAPDs and SSRs were used to determine the genetic relationships among 18 cultivated barley accessions and the results compared to pedigree relationships where these were available. All of the approaches were able to uniquely fingerprint each of the accessions. The four assays differed in the amount of polymorphism detected. For example, all 13 SSR primers were polymorphic, with an average of 5.7 alleles per primer set, while nearly 54% of the fragments generated using AFLPs were monomorphic. The highest diversity index was observed for AFLPs (0.937) and the lowest for RFLP (0.322). Principal co-ordinate analysis (PCoA) clearly separated the spring types from the winter types using RFLP and AFLP data with the two-row winter types forming an intermediate group. Only a small group of spring types clustered together using SSR data with the two-row and six-row winter varieties more widely dispersed. Direct comparisons between genetic similarity (GS) estimates revealed by each of the assays were measured by a number of approaches. Spearman rank correlation ranked over 70% of the pairwise comparisons between AFLPs and RFLPs in the same order. SSRs had the lowest values when compared to the other three assays. These results are discussed in terms of the choice of appropriate technology for different aspects of germplasm evaluation.     

Variation of DNA fingerprints among accessions within maize inbred lines and implications for identification of essentially derived varieties: II. Genetic and technical sources of variation in AFLP data and comparison with SSR data

Accuracy and reproducibility of genetic distances (GDs) based on molecular markers are crucial issues for identification of essentially derived varieties (EDVs). Our objectives were to investigate (1) the amount of variation for amplified fragment length polymorphism (AFLP) markers found among different accessions within maize inbreds and doubled haploid (DH) lines, (2) the proportion attributable to genetic and technical components and marker system specific sources, (3) its effect on GDs between maize lines and implications for identification of EDVs, and (4) the comparison to published SSR data from the same plant materials. Two to five accessions from nine inbred lines and five DH lines were taken from different sources of maintenance breeding or drawn as independent samples from the same seed lot. Each of the 41 accessions was genotyped with 20 AFLP primer combinations revealing 988 AFLP markers. Map positions were available for 605 AFLPs covering all maize chromosomes. On average, six (0.6%) AFLP bands were polymorphic between different accessions of the same line. GDs between two accessions of the same line averaged 0.013 for inbreds and 0.006 for DH lines. The correlation of GDs based on AFLPs and SSRs was tight (r = 0.97**) across all 946 pairs of accessions but decreased (r = 0.55**) for 43 pairs of accessions originating from the same line. On the basis of our results, we recommend specific EDV thresholds for marker systems with different degree of polymorphism. In addition, precautions should be taken to warrant a high level of homogeneity for DNA markers within maize lines before applying for plant variety protection.     

Tropical maize germplasm: what can we say about its genetic diversity in the light of molecular markers?

Knowledge about genetic variability of a crop allows for more efficient and effective use of resources in plant improvement programs. The genetic variation within temperate maize has been studied extensively, but the levels and patterns of diversity in tropical maize are still not well understood. Brazilian maize germplasm represents a very important pool of genetic diversity due to many past introductions of exotic material. To improve our knowledge of the genetic diversity in tropical maize inbred lines, we fingerprinted 85 lines with 569 AFLP bands and 50 microsatellite loci. These markers revealed substantial variability among lines, with high rates of polymorphism. Cluster analysis was used to identify groups of related lines. Well-defined groups were not observed, indicating that the tropical maize studied is not as well organized as temperate maize. Three types of genetic distance measurements were applied (Jaccard’s coefficient, Modified Rogers’ distance and molecular coefficient of coancestry), and the values obtained with all of them indicated that the genetic similarities were small among the lines. The different coefficients did not substantially affect the results of cluster analysis, but marker types had a large effect on genetic similarity estimates. Regardless of genetic similarity coefficient used, estimates based on AFLPs were poorly correlated with those based on SSRs. Analyses using AFLP and SSR data together do not seem to be the most efficient manner of assessing variability in highly diverse materials because the result was similar to using AFLPs alone. It was seen that molecular markers can help to organize the genetic variability and expose useful diversity for breeding purposes.     

Comparison of PCR-based marker systems for the analysis of genetic relationships in cultivated potato

The application of AFLPs, RAPDs and SSRs to examine genetic relationships in the primary northwestern European cultivated potato gene pool was investigated. Sixteen potato cultivars were genotyped using five AFLP primer combinations, 14 RAPD primers, and 17 database-derived SSR primer pairs. All three approaches successfully discriminated between the 16 cultivars using a minimum of one assay. Similarity matrices produced for each marker type on the basis of Nei and Li coefficients showed low correlations when compared with different statistical tests. Dendrograms were produced from these data for each marker system. The usefulness of each system was examined in terms of number of loci revealed (effective multiplex ratio, or EMR) and the amount of polymorphism detected (diversity index, or DI). AFLPs had the highest EMR, and SSRs the highest DI. A single parameter, marker index (MI), which is the product of DI and EMR, was used to evaluate the overall utility of each marker system. The use of these PCR-based marker systems in potato improvement and statutory applications is discussed.Abbreviations: PCR, polymerase chain reaction; AFLP, amplified fragment length polymorphism; RAPD, randomly amplified polymorphic DNA; DNA, deoxyribonucleic acid; EMR, effective multiplex ratio; DI, diversity index; MI, marker index; RFLP, restriction fragment length polymorphism.     

Molecular marker-based genetic diversity assessment of Striga-resistant maize inbred lines

Striga-resistant maize inbred lines are of interest to maize breeding programs in the savannas of Africa where the parasitic weed is endemic and causes severe yield losses in tropical maize. Assessment of the genetic diversity of such inbred lines is useful for their systematic and efficient use in a breeding program. Diversity analysis of 41 Striga-resistant maize inbred lines was conducted using amplified fragment length polymorphism (AFLP) and simple sequence repeat (SSR) markers to examine the genetic relationships among these lines and to determine the level of genetic diversity that exists within and between their source populations. The two marker systems generated 262 and 101 polymorphic fragments, respectively. Genetic similarity (GS) values among all possible pairs of inbred lines varied from 0.45 to 0.95, with a mean of 0.61±0.002 for AFLPs, and from 0.21 to 0.92, with a mean of 0.48±0.003, for SSRs. The inbred lines from each source population exhibited a broad range of GS values with the two types of markers. Both AFLPs and SSRs revealed similar levels of within population genetic variation for all source populations. Cluster and principal component analysis of GS estimates with the two markers revealed clear differentiation of the Striga-resistant inbred lines into groups according to their source populations. There was clear separation between early- and late-maturing Striga-resistant inbred lines. Considering the paucity of germplasm with good levels of resistance to Striga in maize, the broad genetic diversity detected within and among source populations demonstrates the genetic potential that exists to improve maize for resistance to Striga.     

Genetic diversity analysis in sorghum germplasm as estimated by AFLP, SSR and morpho-agronomical markers

A comparison of the different methods of the estimation of genetic diversity is important to evaluate their utility as a tool in germplasm conservation and plant breeding. Amplified fragment length polymorphism (AFLP), microsatellites or SSR and morphological traits markers were used to evaluate 45 sorghum germplasm for genetic diversity assessment and discrimination power. The mean polymorphism information content (PIC) values were 0.65 (AFLPs) and 0.46 (SSRs). The average pairwise genetic distance estimates were 0.57 (morphological traits), 0.62 (AFLPs) and 0.60 (SSRs) markers data sets. The Shannon diversity index was higher for morphological traits (0.678) than AFLP (0.487) and SSR (0.539). The correlation coefficients obtained by the Mantel matrix correspondence test, which was used to compare the cophenetic matrices for the different markers, showed that estimated values of genetic relationship given for AFLP and SSR markers, as well as for morphological and SSR markers were significantly related (p <0.001). However, morphological and AFLP data showed non-significant correlation (p >0.05). Both data sets from AFLP and SSR allowed all accessions to be uniquely identified; two accessions could not be distinguished by the morphological data. In summary, AFLP and SSR markers proved to be efficient tools in assessing the genetic variability among sorghum genotypes. The patterns of variation appeared to be consistent for the three marker systems, and they can be used for designing breeding programmes, conservation of germplasm and management of sorghum genetic resources.