中国芒（Miscanthus sinensis）种质资源SSR标记遗传多样性分析

利用33对SSR引物对来自中国16个省的46份野生芒(Miscanthus sinensis)种质进行遗传多样性分析。结果显示:(1)33对SSR引物共扩增出87条DNA条带,75条为多态性条带,占86.21%,条带大小范围80～310 bp;(2)遗传多样性参数分析结果:Shannon’s信息指数(I)变幅为0.020～1.522,平均为0.745,引物多态性信息含量(PIC)变幅为0.040～0.738,平均为0.445,遗传相似系数(GS)的变幅为0.315～0.933,平均为0.569,说明我国芒种质资源遗传基础宽,遗传多样性丰富;(3)相似系数UMPGA聚类结果与主成分分析(PCA)结果一致,可将46份种质分为3大类群,类群Ⅰ主要由中部芒组成,类群Ⅱ主要由北方芒组成,类群Ⅲ主要由南方芒组成,西南芒在每个类群中均有渗透,这一结果说明芒种质资源的遗传分化与其种源的地理分布有一定的相关性,但与地理起源不能完全吻合。     

基于表型性状和SSR分子标记的云南省水稻主要育成品种(系)的遗传相似性分析

利用株高等17个表型性状和48个SSR标记,对云南省18个育种部门(或课题组)自20世纪60年代以来选育的40个品种(系)进行遗传相似性分析.结果显示,基于17个表型性状,40个品种(系)间的遗传相似性系数值平均为0.244,籼型品种间为0.289,粳型为0.309,籼粳亚种间为0.162;基于48个SSR分子标记,40个品种(系)间的遗传相似性系数值平均为0.383,籼型为0.318,粳型为0.478,籼粳亚种间为0.267;表明表型遗传相似性低于DNA水平.48个SSR分子标记共检测到214个等位基因(Na),每个标记平均为4.458个,变幅为2～8个;有效等位基因数(Ne)平均值为2.8336,变幅为1.1515～5.2981;多态性信息含量(PIC)平均值为0.6058,变幅为0.2118～0.8816;基因型多样性指数(H’)平均值为1.1328,变幅为0.3768～1.8087;其中RM84、RM249、RM152、RM222和RM528是评价云南省水稻选育品种(系)遗传相似性比较理想的SSR标记.聚类分析显示,云南省水稻主要选育品种(系)表现为亚种间遗传差异明显,亚种内遗传差异较小,粳型品种间遗传相似性高于籼型,表明云南省选育的粳型品种(系)遗传多样性低,尤其是同一育种部门(或课题组)选育的品种间遗传相似度较高.     

基于表型性状和SSR分子标记的云南省水稻主要育成品种（系）的遗传相似性分析

为了揭示云南省水稻主要育成品种（系）的遗传相似性。本文利用株高等17个表型性状和48个微卫星（SSR）分子标记,对云南省18个育种部门（或课题组）60年代以来选育的40个品种（系）进行遗传相似性评价。结果显示表型遗传相似性低于DNA水平。40个品种（系）基于17个表型性状的平均遗传相似系数为0.244,籼型为0.289,粳型为0.309,籼粳亚种间为0.162;基于48个SSR分子标记的平均遗传相似系数为0.383,籼型为0.318,粳型为0.478,籼粳亚种间为0.267。48个SSR分子标记共检测到等位基因214个,每个标记2～8,平均4.458个;平均有效等位基因数为2.8336,变幅为1.1515～5.2981;多态性信息含量（PIC）平均值为0.6058,变幅为0.2118～0.8816;基因型多样性指数（H′）平均值为1.1328,变幅为0.3768～1.8087。RM84、RM249、RM152、RM222和RM528是评价云南省水稻选育品种（系）遗传相似性比较理想的SSR分子标记。聚类分析显示,云南省水稻主要选育品种（系）表现为亚种间遗传差异明显,亚种内遗传差异较小,粳型遗传相似性高于籼型。表明云南省选育的粳型品种（系）遗传多样性低,且同一育种部门（或育种人）选育的品种遗传相似度高。     

引进海岛棉种质的SSR遗传多样性分析

利用95对SSR分子标记对56份海岛棉种质进行遗传多样性分析,其中33份来自于俄罗斯,5份来自埃及,2份来自美国,1份来自阿尔巴尼亚,8份来自我国新疆,7份来自我国云南、江苏等地。结果表明,95对SSR引物在56个海岛棉品种中共测出了384个等位基因,其中多态性等位基因296个,占77.1%。每对引物等位基因变幅是2~9个,平均为4.1个。基因多样性指数(H)在0.035~2.931之间,平均为0.879。Shannon信息指数(I)在0.090~4.417之间,平均为1.363。各指数的趋势一致。95对SSR引物的多态性信息含量PIC变幅为0.035~0.926,平均为0.698。56份海岛棉品种两两间的相似系数在0.585~0.952之间,主要集中在0.6~0.8之间,占整个数据的97%,平均遗传相似系数为0.7。从整体上来看,56份海岛棉的遗传相似系数较高,从聚类图上可以看出,以遗传距离为0.69为标准,56份海岛棉品种可分为4类。第1类主要是前苏联海岛棉为主的27份品种,其中来自埃及的吉扎77和来自美国的派字棉以及中239都归到了这一类。第2类较复杂,但主要是以来自新疆的6份海岛棉和来自埃及的吉扎系列的4份为主。第3类包括8个品种,主要是来自于前苏联的6个品种、来自于新疆的巴3116和河北的冀B91-45。第4类只有来自于前苏联的L-8007,独自成一类。研究结果表明SSR作为一种共显性标记,尤为适用于海岛棉及其亲本的系谱分析及鉴定。因而,SSR标记技术可以为海岛棉育种实践工作中的亲本选配,提供可靠的分子水平上的依据。     

江西野生大豆遗传多样性分析

利用48个SSR分子标记分析了192份采集于江西49个县（区）的野生大豆遗传多样性。结果表明,共扩增出等位基因343个,平均每对引物扩增出7.2个等位基因,平均基因遗传多样性指数0.7369,平均多态性信息含量（PIC）0.7060,表明江西野生大豆具有较为丰富的遗传多样性。不同纬度和不同海拔的野生大豆其遗传多样性不同,高纬度及低海拔地区野生大豆遗传多样性要高。192份野生大豆可聚类成三大类,聚类结果与地理来源较为一致。     

基于SSR标记的132份甘薯种质指纹图谱的构建及遗传多样性分析

利用SSR分子标记技术,构建132份甘薯种质的DNA指纹图谱,并进行遗传多样性分析,旨在为甘薯种质资源亲缘关系鉴定、分类提供理论依据。利用筛选的核心引物进行PCR扩增,通过聚丙烯酰胺凝胶电泳检测显示,19对引物共扩增出232个条带,其中多态性条带165条,多态性比率为71.1%,平均每对引物扩增出8.68个条带,多态性信息含量变化范围在0.6706~0.9331之间,平均为0.8158;其中引物SSR9和引物C33可将132份种质完全区分开,并构建供试材料的DNA指纹图谱,供试材料遗传距离在0.0363~0.5939之间,平均为0.4087,表明种质资源间遗传多样性丰富。基于SSR标记对供试材料进行聚类分析,将供试材料分为2个类群,第Ⅰ类群分为两个亚类,第Ⅰ-1亚类包括济薯25和3份日本引进品种日本金千贯、安納芋、日本薯;第Ⅰ-2亚类包括济徐薯23、苏丹、济薯09281。第Ⅱ类群分为两个亚类,第Ⅱ-1亚类由S07甘薯品系和与其亲缘关系较近的20份甘薯种质组成;第Ⅱ-2亚类由剩余的70份甘薯种质组成,为甘薯分子辅助育种中亲本的选择提供理论依据。     

基于SSR标记的六倍体小黑麦遗传多样性分析

采用已筛选出的多态性较好的分布于六倍体小黑麦21对染色体上的100对SSR引物对从国际玉米小麦改良中心(CIMMYT)引进的339份六倍体小黑麦进行了遗传多样性分析。结果显示,100对引物共检测出323个等位变异,变幅是1~6个,平均等位变异丰富度为3.23;多态信息含量(PIC)的变幅为0~0.748,平均多态信息含量为0.465;平均遗传多样性指数(H')为0.1439,说明供试的339份六倍体小黑麦品种的SSR遗传多样性较为丰富。同时基于Nei's遗传距离对339份材料进行聚类分析,可以将供试材料分为6个类群。其中,第Ⅵ类群与其他类群的遗传距离较大、遗传差异较明显。研究结果为将六倍体小黑麦的优良基因应用于普通小麦的遗传改良提供了理论依据。     

16 个蝴蝶兰品种 EST-SSR 遗传多样性分析

利用 NCBI 上提供的8 188 条蝴蝶兰 EST 序列开发 EST-SSR 引物,用来分析市场上较常见的 16 个蝴蝶兰栽培品种的遗传多样性。结果成功开发出了 9 对多态性引物,这 9 对引物在 16 个蝴蝶兰品种上共检测出 45 个等位基因,每对引物可检测等位基因2 ~ 12 个,平均为 5 个;SSR 引物多态性信息量 (PIC) 变化范围为 0.527 ~ 0.981,平均为 0.755;16 个蝴蝶兰品种间的遗传相似系数在 0.550 ~ 0.875 之间,平均值为 0.728,表明供试品种间的亲缘关系较近。UPGMA 聚类分析结果表明,在遗传相似系数为 0.73 处可将 16 个蝴蝶兰品种分为四大类,第Ⅰ类包括满天红、巨宝红玫瑰等 10 个品种,第Ⅱ类包括夕阳红、富乐夕阳、昌新皇后和新原美人 4 个品种,第Ⅲ类包括萨拉黄金 1 个品种,第Ⅳ类包括台湾阿妈 1 个品种,聚类结果与花色特征比较一致。该研究结果对蝴蝶兰品种选育有一定参考价值。     

设施用厚皮甜瓜品种SSR标记遗传多样性分析

使用分布于甜瓜12条染色体上的72对SSR引物,对我国中东部设施内栽培的30个厚皮甜瓜品种进行分析;56对SSR引物在30个品种间表现为多态性。共检测到138个等位变异,每对引物的等位变异数变幅为2～6个,平均为2.6个。有效等位变异为86.16个,平均为2.25。每个SSR位点的多态性信息量(PIC)变化范围为0.045～0.725,平均为0.390。30个品种间遗传相似系数变幅为0.274～0.974之间,平均值为0.665,且90.4%的供试品种其遗传相似系数在0.474～0.824之间,亲缘关系较近;以遗传相似系数为原始数据,按UPGMA方法将30个品种划分为3大类群,结合系谱分析结果表明,我国中东部设施适宜种植的甜瓜品种遗传多样性不够丰富,多数品种间的亲缘关系较近,欲进一步提高中东部地区设施甜瓜产量和品质还需要拓宽亲本选择范围,扩大遗传背景。     

黄淮麦区小麦品种(系)的ISSR位点遗传多样性分析

选用11个ISSR引物,对黄淮麦区96个小麦推广品种（系）进行遗传多样性分析。共检测到96个多态性位点,每个引物多态性位点数平均为8．7个,变幅为3～23个;ISSR引物的多态性信息含量PIC变幅为0．601～0．941,平均0．791,表明ISSR具有较强的品种间区分能力,是研究小麦种质资源遗传多样性的有效分子标记技术之一。96个品种（系）间,Nei’s遗传相似系数变化范围为0．53～0．91,平均为0．60,品种间遗传相似性变幅较大,表明黄淮麦区不同小麦品种（系）间存在着不同程度的遗传多样性差异。根据品种间遗传相似系数聚类,96份材料被聚成8大类群,共14个亚类,类群与系谱和原产地无关。     

中国东北地区水稻主要栽培品种的遗传多样性分析

利用68对SSR引物对91份粳稻品种进行了遗传多样性分析。研究结果共检测到293个等位基因,平均4．3个;平均多态信息含量（PIC）为0．313,变动范围为0．022～0．825。RM333和RM206的等住基因数最多,分别为14、10;且PIC也最高,分别为0．825、0．805。聚类和群体差异分析结果表明,东北三省水稻品种的遗传基础狭窄。黑龙江省和吉林省、黑龙江省和日本、吉林省和日本的水稻品种间遗传距离都很小．分别为0．083、0．084、0．090,而辽宁省与吉林省、黑龙江省的水稻品种遗传基础有一些差异。9个地理来源的品种聚类结果,可分为5个大类群,黑龙江省、吉林省、日本和韩国形成第Ⅰ类群;北京和辽宁省归为第Ⅱ类群;中国台湾、云南省、美国分别为第Ⅲ、第Ⅳ和第Ⅴ类群。东北三省是重要的粳稻生产基地,但遗传基础非常狭窄,要克服遗传脆弱性应从地理位置较远的国家或地区收集更丰富的遗传资源。     

SSR based genetic diversity of pigmented and aromatic rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.) genotypes of the western Himalayan region of India

A set of 24 of SSR markers were used to estimate the genetic diversity in 16 rice genotypes found in Western Himalayas of Kashmir and Himachal Pradesh, India. The level of polymorphism among the genotypes of rice was evaluated from the number of alleles and PIC value for each of the 24 SSR loci. A total of 68 alleles were detected across the 16 genotypes through the use of these 24 SSR markers The number of alleles per locus generated varied from 2 (RM 338, RM 452, RM 171) to 6 (RM 585, RM 249, RM 481, RM 162). The PIC values varied from 0.36 (RM 1) to 0.86 (RM 249) with an average of 0.62 per locus. Based on information generated, the genotypes got separated in six different clusters. Cluster 1 comprised of 4 genotypes viz; Zag 1, Zag 13, Pusa sugandh 3, and Zag 14, separated from each other at a similarity value of 0.40. Cluster second comprised of 3 landraces viz; Zag 2. Zag 4 and Zag10 separated from each other at a similarity value of 0.45. Cluster third comprised of 3 genotypes viz; Grey rice, Mushk budji and Kamad separated from each other at a similarity value of 0.46. Cluster fourth had 2 landraces viz; Kawa kreed and Loual anzul, and was not sub clustered. Fifth cluster had 3 genotypes viz; Zag 12, Purple rice and Jhelum separated from each other at a similarity value of 0.28. Cluster 6 comprised of a single popular variety i.e. Shalimar rice 1 with independent lineage.     

Population structure and genetic diversity analysis of Indian and exotic rice (Oryza sativa L.) accessions using SSR markers

In order to understand the population structure and genetic diversity among a set of 82 rice genotypes collected from different parts of the Asian countries including India were characterized using 39 microsatellite loci. The Population structure analysis suggested that the optimum number of subpopulations was four (K = 4) among the rice genotypes, whereas phylogenetic analysis grouped them into three populations. The results obtained from phylogenetic and STRUCTURE analysis proved to be very powerful for the differentiation of rice genotypes based on their place of origin. The genetic diversity analysis using 39 SSR loci yielded 183 scorable alleles, out of which 182 alleles were observed to be polymorphic with an average of 4.8 alleles per locus. The Polymorphism Information Content (PIC) values for all the polymorphic primers across 82 rice genotypes varied from 0.02 to 0.77, with an average of 0.50. Gene diversity (He) was found to be in the range of 0.02 (RM484) to 0.80 (OSR13) with an average value of 0.55, while heterozygosity (Ho) was observed with an average of 0.07, ranging from 0.01 (RM334) to 0.31 (RM316). The present study resulted in identification of seven highly polymorphic SSR loci viz., OSR13, RM152, RM144, RM536, RM489, RM259 and RM271 based on the parameters like PIC value (≥0.70), gene diversity (≥0.71), and polymorphic alleles (≥6). These seven polymorphic primers can effectively be used in further molecular breeding programs and QTL mapping studies of rice since they exhibited very high polymorphism over other loci. SSR analysis resulted in a more definitive separation of clustering of genotypes indicating a higher level of efficiency of SSR markers for the accurate determination of relationships between accessions.     

基于SSR标记的荔枝种质遗传多样性分析

从53对本课题组自主开发设计的SSR特异引物对中筛选出22对多态性引物,对46份荔枝材料的基因组DNA进行扩增,共得到54个等位基因,其中每对引物的平均等位基因数为2.4,共获得23个特异性标记,各标记的平均观察杂合度值、平均期望杂合度和PIC值分别为0.451、0.355和0.507。其中L it6位点各数值最高,是最理想的选择标记。利用22对多态性引物对46份荔枝种质进行聚类分析,构建树状图,结果表明:大多数种质相似系数在0.63～0.95之间,说明它们之间的亲缘关系较近,并发现淮枝(广东)与淮枝(海南)两者可能为同名异物品种。     

Comparison of SSR and SNP Markers in Estimation of Genetic Diversity and Population Structure of Indian Rice Varieties

Simple sequence repeat (SSR) and Single Nucleotide Polymorphic (SNP), the two most robust markers for identifying rice varieties were compared for assessment of genetic diversity and population structure. Total 375 varieties of rice from various regions of India archived at the Indian National GeneBank, NBPGR, New Delhi, were analyzed using thirty six genetic markers, each of hypervariable SSR (HvSSR) and SNP which were distributed across 12 rice chromosomes. A total of 80 alleles were amplified with the SSR markers with an average of 2.22 alleles per locus whereas, 72 alleles were amplified with SNP markers. Polymorphic information content (PIC) values for HvSSR ranged from 0.04 to 0.5 with an average of 0.25. In the case of SNP markers, PIC values ranged from 0.03 to 0.37 with an average of 0.23. Genetic relatedness among the varieties was studied; utilizing an unrooted tree all the genotypes were grouped into three major clusters with both SSR and SNP markers. Analysis of molecular variance (AMOVA) indicated that maximum diversity was partitioned between and within individual level but not between populations. Principal coordinate analysis (PCoA) with SSR markers showed that genotypes were uniformly distributed across the two axes with 13.33% of cumulative variation whereas, in case of SNP markers varieties were grouped into three broad groups across two axes with 45.20% of cumulative variation. Population structure were tested using K values from 1 to 20, but there was no clear population structure, therefore Ln(PD) derived Δk was plotted against the K to determine the number of populations. In case of SSR maximum Δk was at K=5 whereas, in case of SNP maximum Δk was found at K=15, suggesting that resolution of population was higher with SNP markers, but SSR were more efficient for diversity analysis.     

405份CIMMYT引进小麦种质的遗传多样性分析

为了明确国际玉米改良中心(CIMMYT)引进普通小麦种质材料的遗传多样性特点,为其利用提供参考依据,本研究从均匀分布于小麦基因组的420对SSR引物中选择出条带清晰、多态性较好的62对引物对引自CIMMYT的405份普通小麦种质系进行遗传多样性检测。结果表明,62对SSR引物在405份CIMMYT材料中共检测到198个等位变异,每对引物检测到等位变异的数目为2~8个,平均每对SSR引物能够检测到3.19个等位变异。单个SSR引物的PIC值介于0.03~0.79之间,平均值0.48。405份CIMMYT材料A、B、D基因组之间多态性位点数和等位变异数相差不大,PIC平均值B基因组(0.53)A基因组(0.52)D基因组(0.39)。聚类分析结果显示,62对SSR引物能够将405份CIMMYT材料区分开来,在0.1285遗传距离处将供试材料分为24个类群,类型较为丰富,不同类群的材料在农艺性状和品质性状上存在差异。     

Assessment of genetic diversity of <Emphasis Type="Italic">Saltol</Emphasis> QTL among the rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.) genotypes

Eight Saltol quantitative trait locus (QTL) linked simple sequence repeat (SSR) markers of rice (Oryza sativa L.) were used to study the polymorphism of this QTL in 142 diverse rice genotypes that comprised salt tolerant as well as sensitive genotypes. The SSR profiles of the eight markers generated 99 alleles including 20rare alleles and 16 null alleles. RM8094 showed the highest number (13) of alleles followed by RM3412 (12), RM562 (11), RM493 (9) and RM1287 (8) while as, RM10764 and RM10745 showed the lowest number (6) of alleles. Based on the highest number of alleles and PIC value (0.991), we identified RM8094 as suitable marker for discerning salt tolerant genotypes from the sensitive ones. Based upon the haplotype analysis using FL478 as a reference (salt tolerant genotypes containing Saltol QTL), we short listed 68 rice genotypes that may have at least one allele of FL478 haplotype. Further study may confirm that some of these genotypes might have Saltol QTL and can be used as alternative donors in salt tolerant rice breeding programmes.     

不同国家水稻品种的遗传多样性分析

探讨世界不同国家水稻品种的遗传多样性,旨在为各国品种资源的有效利用提供理论依据。本研究利用63对引物对36份来源于不同国家的水稻品种进行遗传多样性分析。共检测到269个等位基因,每个位点的等位基因数(Na)平均为4.54个,有效等位基因数(Ne)平均为3.22,基因多样性指数(H)平均为0.64,Shannon’s信息指数(I)平均为1.21,引物RM206、RM257、RM410、RM235、RM266的等位基因数较多在7条以上。所处纬度相近的国家或地区的水稻品种之间的遗传距离较近,被聚为同一类群,而所处纬度较远的国家或地区的水稻品种被分到了不同类群。结果表明,水稻品种之间的遗传差异与纬度和地理距离有很大的关系。     

SSR analysis of 38 genotypes of soybean (Glycine Max (L.) Merr.) genetic diversity in India

Sixteen polymorphic Simple sequence repeat (SSR) markers were used to determine the genetic diversity and varietal identification among 38 soybean (Glycine max (L.) Merr.) genotypes which are at present under seed multiplication chain in India. A total of 51 alleles with an average of 2.22 alleles per locus were detected. The polymorphic information content (PIC) among genotypes varied from 0.049 (Sat_243 and Satt337) to 0.526 (Satt431) with an average of 0.199. The pair wise genetic similarity between soybean varieties varied from 0.56 to 0.97 with an average of 0.761. These 16 SSR markers successfully distinguished 12 of the 38 soybean genotypes. These results suggest that used SSR markers are efficient for measuring genetic diversity and relatedness as well as identifying varieties of soybeans. Diverse genetic materials may be used for genetic improvements of soybean genotypes.     

基于SSR标记的谷子遗传多样性研究

用21个分布在谷子9条染色体上的SSR标记,对120份来自于核心种质的谷子材料进行遗传多样性研究。21个标记共检查出305个等位变异,各标记检测出的等位变异数在3～26个之间,平均每个位点检测出的等位变异数为14.5个;21个位点的平均多态信息量(PIC)为0.809。基于21个SSR标记的分子鉴定,计算了120份材料间的遗传相似系数,其变化范围为0.8393～0.9672,平均值为0.8906。根据计算的遗传距离,对120份谷子材料进行UPGMA聚类,在遗传相似系数0.8865处这些材料被划分为4个类群,分类结果与这些谷子来源地生态类型总体上表现一致,分别为西北内陆类群、黄土高原内蒙古高原类群、华北平原类群以及华北平原近年育成种类群。