瘿螨染色体核型分析及其亲缘关系

本文采用玻璃纸压片法测定了瘿螨总科中分属于３科１０种瘿螨的染色体,其数目均为ｎ＝３或４。同时,选取染色体相对长度和形态特征数值两因子进行聚类分析,计算出欧氏距离并绘制谱系图。结果表明同科种的欧氏距离都较近,不同科间的欧氏距离都超过同科内的距离,其中瘿螨科和羽爪瘿螨科的亲缘关系较近,归并科间亲缘关系为：纳氏瘿螨科→瘿螨科→羽爪瘿螨科。     

中国叶刺瘿螨亚科四新种记述(蜱螨亚纲：瘿螨科)

记述了叶刺瘿螨亚科(Phyllocoptinae)四新种：茅莓上三脊瘿螨Calepitrimerus rubi sp.nov.,槐顶冠瘿螨Tegolophus sophorae sp.nov.,丁香四刺瘿螨Tetraspinus syringae sp.nov.和柳副四瘿螨Paratetra sallicis sp.nov.。     

中国瘿螨科三新种记述(蜱螨亚纲:瘿螨总科)

记述瘿螨科Ｅｒｉｏｐｈｙｉｄａｅ３新种：瘿螨亚科Ｅｒｉｏｐｈｙｉｄａｅ的相瘤瘿螨Ａｃｅｒｉａ ｃｅｌｔｉｄｉｓ Ｚｈａｏ ｅｔ Ｋｕａｎｇ,ｓｐ．ｎｏｖ．;叶刺瘿螨亚科Ｐｈｙｌｌｏｃｏｐｔｉｎａｅ的无花果中瘿螨Ｓｉｎａｃｕｓ ｃａｒｉｃａｅＺｈａｏ ｅｔ Ｋｕａｎｇ,ｓｐ．ｎｏｖ．和柳顶冠瘿螨Ｔ ｅｇｏｌｏｐｈｕｓ ｓａｌｉｃｉｓ Ｋｕａｎｇ ｅｔ Ｚｈａｏ,ｓｐ．ｎｏｖ．。display structure     

中国瘿螨科一新属二新种记述（蜱螨亚纲：瘿螨总科）

记述瘿螨科1新－长胫毛瘿螨属Longitibisetacus及2新种：竹长胫毛瘿螨Longitibisetaws bambusae,spl.nov。和榆顶冠瘿螨Tegolophus ulmi,sp.nov。模式标本保存在南京农业大学植物保护系。     

羽爪瘿螨科一新属三新种记述（蜱螨亚纲;真螨目）

记述了羽爪瘿螨科一新属,即新兰瘿螨属Ｎｅｏｌａｍｂｅｌｌａ ｇｅｎ。ｎｏｖ。三新种是女贞新兰瘿螨Ｎｅｏｌａｍｂｅｌｌａ ｌｉｇｕｓｔｒｉ ｓｐ．ｎｏｖ。,麻栎 蜡皮瘿螨Ａｐｏｄｉｐｔａｃｕｓ ａｃｕｔｉｓｓｉｍａｅ ｓｐ．ｎｏｖ。和榆畸刺瘿螨Ａｂａｃｏｐｔｅｓ ｕｌｍｉ ｓｐ．ｎｏｖ。对其形态进行了描述并与近缘种作了比较,模式标本保存在南京农业大学。     

中国南方叶刺瘿螨亚科3新种记述（蜱螨亚纲，瘿螨总科）

本文记述了叶刺瘿螨亚科Phyllocoptinae3新种：菝葜离子瘿螨Leipothrix smilaxsp．nov．,白饭树顶冠瘿螨Tegolophus virosae sp．nov．,鸡爪簕顶冠瘿螨Tegolophus randiae sp．nov．。本文所用量度单位均为微米（μm）。模式标本保存在广西大学农学院。     

中国大嘴瘿螨科三种新种记述：（蜱螨亚纲：瘿螨总科）

本文记述大嘴瘿螨科Ｒｈｙｎｃａｐｈｙｔｏｐｔｉｄａｅ３新种：大嘴瘿螨亚科Ｒｈｙｎｃａｐｈｙｔｏｐｔｉｎａｅ的无花果大嘴瘿螨Ｒｈｙｎｃａｐｈｙｔｏｐｔｕｓ ｃａｒｉｃａｅ Ｚｈａｏ ｅｔ Ｋｕａｎｇ,ｓｐ．ｎｏｖ．和中山大嘴瘿螨Ｒｈｙｎｃａｐｈｙｔｏｐｔｕｓ ｚｈｏｎｇｓｈａｎｉ ＺＨａｏ ｅｔ Ｋｕａｎｇ,ｓｐ．ｎｏｖ．;羽爪瘿螨亚科Ｄｉｐｔｉｌｏｍｉｏｐｉｎａｅ的竹尖嘴瘿螨Ａｃａｒｈｙｎｃｈｕｓ     

云南医学革螨数值分类研究

以云南省57种医学革螨作为分类单元,以形态特征为主列出60项分类性状特征来探讨云南省医学革螨不同属和种的亲缘关系。运用SPSS 11.5 统计软件中的系统聚类分析和主成分分析,对57种医学革螨进行了数值分类分析。结果显示：57种医学革螨划分为厉螨科（La elapidae）、寄螨科（Parasitidae）、皮刺螨科（Dermanyssidae）、赫刺螨科（Hirstionyssidae）和裂胸螨科（Aceosejidae）5个类群。赫刺螨属和棘刺螨属从厉螨科中分离出来另立为赫刺螨科,柏氏禽刺螨归入了皮刺螨科而不是巨刺螨科。分类结果与传统形态分类结果基本一致,因而认为数值分类能比较客观地反映医学革螨各分类阶元的分类地位与亲缘关系。     

中国大嘴瘿螨科三新种记述(蜱螨亚纲:瘿螨总科)

本文记述大嘴瘿螨科Ｒｈｙｎｃａｐｈｙｔｏｐｔｉｄａｅ３新种：大嘴瘿螨亚科Ｒｈｙｎｃａｐｈｙｔｏｐ－ｔｉｎａｅ的无花果大嘴瘿螨ＲｈｙｎｃａｐｈｙｔｏｐｔｕｓｃａｒｉｃａｅＺｈａｏｅｔＫｕａｎｇ,ｓｐ．ｎｏｖ．和中山大嘴瘿螨ＲｈｙｎｃａｐｈｙｔｏｐｔｕｓｚｈｏｎｇｓｈａｎｉＺｈａｏｅｔＫｕａｎｇ,ｓｐ．ｎｏｖ．;羽爪瘿螨亚科Ｄｉｐｔｉｌｏｍｉｏｐｉｎａｅ的竹尖嘴瘿螨ＡｃａｒｈｙｎｃｈｕｓｂａｍｂｕｓａｅＫｕａｎｇｅｔＺｈａｏ,ｓｐ．ｎｏｖ．。模式标本保存在南京农业大学植物保护系。     

中国林木瘿螨四新种记述(蜱螨亚纲：瘿螨总科)

本文记述瘿螨四个新种：纳瘿螨科Ｎａｌｅｐｅｌｉｄａｅ的五针松针羽瘿螨,瘿螨科Ｅｒｉｏｐｈｙｉ－ｄａｅ的黄连木刺瘿螨和楝五脊瘿螨,以及羽爪瘿螨科Ｄｉｐｔｉｌｏｍｉｏｐｉｄａｅ的复盆子蜡皮瘿螨。文内量度为μｍ。模式标本保存在南京农业大学植保系。１五针松针...     

Taxonomic review of the tribe Anthocoptini (Acari: Eriophyidae) from Korea

Tribe Anthocoptini (Prostigmata: Eriophyidae) from Korea was reviewed. A total of eight species in the tribe were presented, among them, four species, Abacarus hystrix (Nalepa), Aculus fockeui (Nalepa and Trouessart), Aculus schlechtendali (Nalepa) and Tegolophus zizyphagus (Keifer) were newly recorded to the fauna. All the Korean species of the tribe were redescribed and illustrated. Keys to the Korean species of the tribe and distributions were also presented with the biological information such as host plants and damage symptoms.     

Application of latent semantic indexing to evaluate the similarity of sets of sequences without multiple alignments character-by-character

Most molecular analyses, including phylogenetic inference, are based on sequence alignments. We present an algorithm that estimates relatedness between biomolecules without the requirement of sequence alignment by using a protein frequency matrix that is reduced by singular value decomposition (SVD), in a latent semantic index information retrieval system. Two databases were used: one with 832 proteins from 13 mitochondrial gene families and another composed of 1000 sequences from nine types of proteins retrieved from GenBank. Firstly, 208 sequences from the first database and 200 from the second were randomly selected and compared using edit distance between each pair of sequences and respective cosines and Euclidean distances from SVD. Correlation between cosine and edit distance was -0.32 (P < 0.01) and between Euclidean distance and edit distance was +0.70 (P < 0.01). In order to check the ability of SVD in classifying sequences according to their categories, we used a sample of 202 sequences from the 13 gene families as queries (test set), and the other proteins (630) were used to generate the frequency matrix (training set). The classification algorithm applies a voting scheme based on the five most similar sequences with each query. With a 3-peptide frequency matrix, all 202 queries were correctly classified (accuracy = 100%). This algorithm is very attractive, because sequence alignments are neither generated nor required. In order to achieve results similar to those obtained with edit distance analysis, we recommend that Euclidean distance be used as a similarity measure for protein sequences in latent semantic indexing methods.     

Relationship between 17 Venezuelan counties estimated through communality of surnames

The coefficients of relationship and the Euclidean distances between 17 Venezuelan counties were estimated based on the frequency distribution of surnames obtained from the 1984 Venezuelan register of electors. In general, the coefficients of relationship between counties within the same state were higher than those between counties from different states. Euclidean distances exhibited the opposite relationship. Spearman's correlation coefficients for 136 pairs of counties were estimated between geographic and Euclidean distances (r = 0.41), geographic distance and coefficient of relationship (r = -0.44) and between Euclidean distance and coefficient of relationship (r = -0.48). The effect of partial geographic isolation on the frequency distribution of surnames is shown in the State of Falcón, where an isthmus separates two counties of the peninsula from two others on the mainland, and in Mérida, where the Venezuelan Andes separates three counties from the rest of the country. Our results suggest that Euclidean distances are less influenced by common surnames than the coefficients of relationship. They also indicate that in Venezuela a high proportion of the population has remained sedentary until recently, and this gives rise to the focal distribution of some surnames.     

Sequence ordinations: a multivariate analysis approach to analysing large sequence data sets

Ordination is a powerful method for analysing complex data setsbut has been largely ignored in sequence analysis. This papershows how to use principal coordinates analysis to find low–dimensionalrepresentations of distance matrices derived from aligned setsof sequences. The method takes a matrix of Euclidean distancesbetween all pairs of sequence and finds a coordinate space wherethe distances are exactly preserved The main problem is to finda measure of distance between aligned sequences that is Euclidean.The simplest distance function is the square root of the percentagedifference (as measured by identities) between two sequences,where one ignores any positions in the alignment where thereis a gap in any sequence. If one does not ignore positions witha gap, the distances cannot be guaranteed to be Euclidean butthe deleterious effects are trivial. Two examples of using themethod are shown. A set of 226 aligned globins were analysedand the resulting ordination very successfully represents theknown patterns of relationship between the sequences. In theother example, a set of 610 aligned 5S rRNA sequences were analysed.Sequence ordinations complement phylogenetic analyses. Theyshould not be viewed as a complete alternative.     

Statistical Measures of DNA Sequence Dissimilarity under Markov Chain Models of Base Composition

In molecular biology, the issue of quantifying the similarity between two biological sequences is very important. Past research has shown that word-based search tools are computationally efficient and can find some new functional similarities or dissimilarities invisible to other algorithms like FASTA. Recently, under the independent model of base composition, Wu, Burke, and Davison (1997, Biometrics 53, 1431 1439) characterized a family of word-based dissimilarity measures that defined distance between two sequences by simultaneously comparing the frequencies of all subsequences of n adjacent letters (i.e., n-words) in the two sequences. Specifically, they introduced the use of Mahalanobis distance and standardized Euclidean distance into the study of DNA sequence dissimilarity. They showed that both distances had better sensitivity and selectivity than the commonly used Euclidean distance. The purpose of this article is to extend Mahalanobis and standardized Euclidean distances to Markov chain models of base composition. In addition, a new dissimilarity measure based on Kullback-Leibler discrepancy between frequencies of all n-words in the two sequences is introduced. Applications to real data demonstrate that Kullback-Leibler discrepancy gives a better performance than Euclidean distance. Moreover, under a Markov chain model of order kQ for base composition, where kQ is the estimated order based on the query sequence, standardized Euclidean distance performs very well. Under such a model, it performs as well as Mahalanobis distance and better than Kullback-Leibler discrepancy and Euclidean distance. Since standardized Euclidean distance is drastically faster to compute than Mahalanobis distance, in a usual workstation/PC computing environment, the use of standardized Euclidean distance under the Markov chain model of order kQ of base composition is generally recommended. However, if the user is very concerned with computational efficiency, then the use of Kullback-Leibler discrepancy, which can be computed as fast as Euclidean distance, is recommended. This can significantly enhance the current technology in comparing large datasets of DNA sequences.     

基于形态学差异探讨秦岭细鳞鲑亚种有效性问题

秦岭细鳞鲑(Brachymystax lenok tsinlingensis Li)的亚种分类地位自命名以来一直饱受争议。研究运用单因素方差分析、主成分分析、判别分析、聚类分析及差异系数检验法, 对秦岭细鳞鲑和黑龙江流域的尖吻细鳞鲑(B. lenok lenok)和钝吻细鳞鲑(B. tumensis)的5项可数性状和34项标准化后的比例性状进行统计分析。单因素方差分析结果表明, 尖吻细鳞鲑、钝吻细鳞鲑和秦岭细鳞鲑在32项比例性状和5项可数性状上存在极显著差异(P<0.01); 主成分分析结果显示, 贡献率较大的前3个主成分的累计贡献率为92.779%; 以逐步判别分析方法选用14个判别效果较好的比例性状构建了3个细鳞鲑类群的判别函数, 综合判别率为99.4%。基于欧式距离矩阵法构建的形态学聚类图显示, 秦岭细鳞鲑和尖吻细鳞鲑距离较近, 而与钝吻细鳞鲑距离较远。据Mayr 75%亚种识别和划分规则, 34项比例性状和5项可数性状中, 尖吻细鳞鲑和秦岭细鳞鲑第一鳃弓外鳃耙数目的差异系数大于1.28, 而钝吻细鳞鲑和秦岭细鳞鲑有31项比例性状和2项可数性状的差异系数高于1.28。据分析结果, 结合秦岭细鳞鲑地理隔离的事实及其与尖吻细鳞鲑和钝吻细鳞鲑的形态差异, 推断秦岭细鳞鲑与黑龙江流域内的尖吻细鳞鲑的形态差异程度至少已达亚种水平。     

蒙古沙拐枣种群形态和同工酶变异的比较研究

调查和测定了中国西北荒漠地区的蒙古沙拐枣(Calligomum mongolicum Turcz)5个种群的形态学指标,应用方差分析(MANOVA)、主成分分析(PCA)和聚类分析,对种群间及种群内的形态性状进行研究。结果表明,种群间的形态变异差异显著。植株高度、种子刺毛长度和种子重量指标具有较强的形态差异性分析意义。形态差异(欧氏距离)与种群间基因流动(地理距离)间没有发现相关关系。聚类分析结果表明,种群M1与M2亲缘关系最近,种群M5与其他种群的亲缘关系相对较远;采用垂直板聚丙烯酰胺电泳技术对5个种群的3个酶系统进行了遗传多样性分析,结果表明,种群M5与其他种群的遗传一致度稍低(0．8197～0．8902)以外,其余各种群遗传一致度较高(0．8480～0．9505),体现其亲缘关系较近。依据Nei的遗传距离进行聚类,结果与形态聚类结果有一定的相似性。     

An integrated approach to the analysis and modeling of protein sequences and structures. II. On the relationship between sequence and structural similarity for proteins that are not obviously related in sequence

Here, we discuss the relationship between protein sequence and protein structural similarity. It is established that a protein structural distance (PSD) of 2.0 is a threshold above which two proteins are unlikely to have a detectable pairwise sequence relationship. A precise correlation is established between the level of sequence similarity, defined by a normalized Smith-Waterman score, and the probability that two proteins will have a similar structure (defined by pairwise PSD<2). This correlation can be used in evaluating the likelihood for success in a comparative modeling procedure. We establish the existence of a correlation between sequence and structural similarity for pairs of proteins that are related in structure but whose sequence relationship is not detectable using standard pairwise sequence alignments. Although it is well known that there is a close relationship between sequence and structural similarity for pairwise sequence identities greater than about 30 %, there has been little discussion as to the possible existence of such a relationship for pairs of proteins in or below the twilight zone of sequence similarity (<25 % pairwise sequence identity). Possible implications of our results for the evolution of protein structure are discussed.     

浙江省沿海地区南瓜地方品种的表型遗传多样性

利用表型性状探讨了浙江省沿海地区20份南瓜地方品种资源的遗传多样性。结果表明,36个数量性状的变异系数在7.33%~59.11%之间,46个质量性状Shannon-wiener遗传多样性指数在0~1.99之间,表明其丰富的遗传多样性。农艺性状聚类分析表明,20份资源分为2大类,其中19份资源归为一大类;在欧氏距离15.0处把这一大类又分成5个小类,小类的划分与花萼片大小、花梗刺毛、瓜形、老瓜皮色等质量性状具有一定的相关性,但划分依据相对独立。本研究结果进一步丰富了南瓜的评价体系,并为今后优异基因资源的挖掘与利用提供了重要依据。