分子系统发育树构建的简易方法

以系统发育树构建的原有距离方法为基础,吸取了NJ法和FM法中的部分理论,提出了以节点引入为手段的新的简易方法,通过该方法构建了分子系统发育树,结果表明这种方法更加快捷,而且所得结果与FM法完全一致。     

基于DTW距离的DNA序列相似性分析

在DNA序列相似性的研究中,通常采用的动态规划算法对空位罚分函数缺乏理论依据而带有主观性,从而取得不同的结果,本文提出了一种基于DTW（Dynamic Time Warping,动态时间弯曲）距离的DNA序列相似性度量方法可以解决这一问题．通过DNA序列的图形表示把DNA序列转化为时间序列,然后计算DTW距离来度量序列相似度以表征DNA序列属性,得到能够比较DNA序列相似性度量方法,并用这个方法比较分析了七种东亚钳蝎神经毒素（Buthusmartensi Karsch neurotoxin）基因序列的相似性,验证了该度量方法的有效性和准确性．     

木霉属补充DNA条形码筛选

木霉属真菌是一类重要的生物资源,在工农业、环境保护等方面具有较高经济价值,对其进行快速、准确的物种鉴定兼具理论意义和应用前景。以木霉属35个概念清晰的种为材料,选择ITS、rpb2和 tef1作为候选基因序列,利用TaxonGap对231个序列片段进行分析,将种内与种间序列差异以及序列获取难易程度作为评价指标,筛选该属的补充条形码片段。结果表明,rpb2具有适宜的种内与种间序列差异,其最小的种间差异（2.48%）,大于最大种内差异（1.8%）,种内、种间遗传距离存在明显的间隔区,并且该基因序列具有较高的PCR扩增与测序成功率（94.4%）;ITS和tef1基因序列的种内与种间序列差异之间存在交叉重叠。因此建议rpb2作为木霉属的补充DNA条形码序列。     

尖唇散白蚁的孤雌生殖行为及初建群体研究

为了证明尖唇散白蚁Reticulitermes aculabialis Tsai et Hwang是否存在孤雌生殖行为和探讨其初建群体的发育特征,本文对尖唇散白蚁分飞成虫进行雌雌配对（FF）和雌雄配对（FM）人工饲养对比研究。结果显示：FM和FF组的筑巢时间和筑巢活动相似;在建巢初期（配对第5天）FF配对组和FM配对组死亡率分别为11．33％和2．67％,FF配对组死亡率显著高于FM组;产卵前FM组的2只雌性个体和FF组的雌性个体卵巢发育程度一致,都有已经完成卵黄积累的成熟卵母细胞。6个月后,FF配对组有7组产生后代,FM配对组有17组产生后代;FF组子代数目显著低于FM组,分别平均为（7．00±1．58）个和（10．33±1．21）个;FF子代全为2～3龄工蚁,而FM组有由3-4龄工蚁分化的低龄兵蚁。最后,我们对新建群体分化出的第一只兵蚁与成熟巢群中的兵蚁进行了形态学比较。我们的结果表明,尖唇散白蚁具有孤雌生殖行为,并且分飞成虫通过雌雌配对和雌雄配对初建群体在发育模式上有显著差异,雌雌成虫配对采用孤雌生殖方式繁殖有可能是野外尖唇散白蚁建群的另一种方式。     

马铁菊头蝠(Rhinolophus ferrumequinum)回声定位声波与生境类型和环境因子的关系

2007年在吉林省罗通山自然保护区,利用超声波探测仪（Avisoft-SASLAB PRO）录制并分析不同生境中马铁菊头蝠的回声定位声波。结果显示马铁菊头蝠在不同类型生境中活动;各生境中回声定位声波参数存在显著差异（one-way ANOVA,P〈0.05）。从环境因子中通过主成分分析筛选出与其回声定位声波相关的植被、气候和地形因子,探讨回声定位声波与这些因子的相关性。结果显示FM1和FM2带宽与乔木高（r=-0.948,-0.825;P〈0.05）、FM1起始频率和FM2终止频率与林冠面积（r=-0.967,-0.958;P〈0.05）、FM1起始频率、FM2终止频率和峰频与湿度（r=-0.776、-0.875和-0.794,P〈0.05）、脉冲持续时间和脉冲间隔与平均灌木高均呈显著负相关（r=-0.911,-0.990;P〈0.05）,峰频与植被株数（r=0.756,P〈0.05）、脉冲持续时间与冠下高呈显著正相关（r=0.870,P〈0.05）。表明各种环境因子（植被因子、气候因子和地形因子）都在一定程度上影响回声定位声波,回声定位声波具有表型可塑性和生境适应性,这些特性决定了马铁菊头蝠生境利用的程度和可利用的资源。     

基于无人机高光谱影像的薇甘菊分布提取研究——以云南德宏州为例

为有效控制薇甘菊入侵,及时掌握其空间分布和动态变化,基于无人机高光谱数据,通过深度学习（DL）、支持向量机（SVM）、随机森林（RF）等方法提取云南省德宏州微甘菊分布情况。结果表明,DL、SVM和RF等3种方法均有效实现了薇甘菊的分布提取,以DL方法的提取效果最佳,制图精度和用户精度分别为96.61%和95.00%;其次为RF方法,制图精度和用户精度分别为94.83%和91.67%;SVM方法的制图精度和用户精度分别为92.45%和81.67%。这3种方法均能很好提取薇甘菊集中分布区域,且DL和RF方法对零散分布薇甘菊的识别效果优于SVM。因此,无人机高光谱影像为薇甘菊的监测、预警和精准防治提供了支撑和依据,对保护当地生态系统安全具有重要意义。     

大豆低聚糖对牙鲆营养效应的研究：I摄食、生长和代谢酶活性

本试验比较研究了不同蛋白源（鱼粉,FM;大豆分离蛋白,SPI）基础饲料中添加大豆低聚糖（SBOS）对牙鲆（Paralichthysolivaceus）摄食率、生长性能和代谢酶活性的影响。分别以FM、SPI作为主要蛋白源,配制了4种等氮等能饲料。其中,饲料FM、SP1分别以FM、SPI作为主要蛋白源;饲料FMO、SPIO分别在饲料FM、SPI基础上添加10％SBOS（水苏糖：2．61％;棉籽糖：0．61％）。试验表明：①饲料中添加SBOS对牙鲆前两周摄食丰无显著影响（P〉0．05）;而显著降低了整个养殖周期FMO组牙鲆总摄食率,提高了SPIO组牙鲆总摄食牢（P〈0．05）;②FM基础饲料中添加SBOS对牙鲆特定生长率（SGR）、饲料效率（FER）和蛋白质效率（PER）均无显著影响（P〉0．05）,但均呈明显下降趋势;SPI基础饲料中添加SBOS对FER和PER无显著影响,却显著提高了SGR（P〈0．05）;③FM基础饲料中添加SBOS提高了牙鲆血浆谷草转氨酶（AST）、谷丙转氨酶（ALT）、碱性磷酸酶（AKP）、乳酸脱氢酶（LDH）和γ-L-谷氨酰转肽酶（γ-GT）的活性,但仅AST差异显著（P〈0．05）,而对肝脏AST、ALT、AKP、LDH和1．GT活性无显著影响（P〉0．05）;SPI基础饲料中添加SBOS显著提高了血浆ALT和LDH活性,而对AST、AKP和γ-GT活性无显著影响;同时,SPI基础饲料中添加SBOS显著提高了肝脏AST和ALT活性,而对AKP、LDH和γ-GT活性无显著影响;④饲料巾添加SBOS对牙鲆血浆中尿素氮和游离氨基酸浓度均无显著影响。试验结果表明,不同蛋白源基础饲料中添加SBOS表现出不同的生长效应;其中,FM基础饲料中添加SBOS表现出一定的抑制生长效应,而SPI基础饲料中添加SBOS却表现出促生长效应。     

大豆低聚糖对牙鲆营养效应的研究：II消化率和消化生理

本试验比较研究了不同蛋白源（鱼粉,FM;大豆分离蛋白,SPI）基础饲料中添加大豆低聚糖（SBOS）对牙鲆（Paralichthys olivaceus）消化道（胃、幽门盲囊、前肠、中肠和后肠）和肝脏消化酶活性、饲料表观消化率和消化道（胃、小肠）组织结构的影响。分别以FM、SPI作为主要蛋白源,配制了4种等氮等能饲料。其中,饲料FM、SP1分别以FM、SPI作为主要蛋白源;饲料FMO、SPIO分别在饲料FM、SPI基础上添加10％SBOS（水苏糖：2．61％;棉籽糖：0．61％）。试验表明：①饲料中添加SBOS普遍降低了牙鲆消化道和肝脏蛋白酶活性,但差异均不显著（P〉O．05）。FM基础饲料中添加SBOS显著降低了肝脏脂肪酶活性（P〈0．05）,而对消化道脂肪酶活性无显著影响;SPI基础饲料中添加SBOS显著提高了前肠脂肪酶活性,降低了胃和中肠脂肪酶的活性,而对幽门盲囊、后肠和肝脏脂肪酶活性均无显著影响。FM基础饲料中添加SBOS显著降低了中肠淀粉酶活性,提高了胃淀粉酶活性（P〈0．05）,而对幽门盲囊、前肠、后肠和肝脏淀粉酶活性无显著影响;SPI基础饲料中添加SBOS显著提高了胃和前肠淀粉酶活性,降低了中肠脂肪酶活性（P〈0．05）,而对幽门盲囊、后肠和肝脏淀粉酶活性无显著影响;②FM基础饲料中添加SBOS显著降低了饲料干物质表观消化率（P〈0．05）,而对粗蛋白、粗脂肪和能量表观消化率均无显著影响（P〉0．05）。SPI基础饲料中添加SBOS对干物质、粗蛋白、粗脂肪和能量表观消化率均无显著影响;③饲料中添加SBOS对牙鲆胃和小肠组织结构均无明显负面影响。试验结果表明,饲料中添加SBOS对牙鲆消化道和肝脏消化酶活性、饲料表观消化率和消化道组织结构均没有表现出明显的负面效应;大豆蛋白源中含有的SBOS不是影响牙鲆对其利用率差的主要因素。     

新疆克孜勒苏柯尔克孜地区帕米尔牦牛mtDNA COⅠ 的遗传多样性分析

为了更好地保护和开发我国新疆的牦牛遗传资源,对新疆克孜勒苏柯尔克孜地区帕米尔牦牛的遗传多样性及群体遗传结构进行了分析。对3个帕米尔牦牛类群的线粒体COⅠ基因序列进行测定,分析其多态性,构建系统进化树。研究结果显示,帕米尔牦牛COⅠ基因序列全长为1 048 bp,共检测到13个变异位点,其中单态突变位点9个,简约信息位点4个。在帕米尔牦牛类群中共检测出10种单倍型,平均单倍型多样性（haplotype diversity,H_d）、平均核苷酸多样性（nucleotide diversity,P_i）分别为0.762和0.001 64。3个类群间平均遗传距离为0.004 30,且苏木塔什牦牛与布伦口牦牛的遗传距离最小（0.003 72）。结果表明,帕米尔牦牛具有丰富的遗传多样性,但各类群之间遗传分化不明显,且经人工或自然选择后群体发生了扩张和基因交流的情况。研究结果为新疆帕米尔牦牛的遗传改良及新疆优良畜禽遗传资源的保护和开发提供了科学依据。     

Reconstructing an ultrametric galled phylogenetic network from a distance matrix

Given a distance matrix M that specifies the pairwise evolutionary distances between n species, the phylogenetic tree reconstruction problem asks for an edge-weighted phylogenetic tree that satisfies M, if one exists. We study some extensions of this problem to rooted phylogenetic networks. Our main result is an O(n(2) log n)-time algorithm for determining whether there is an ultrametric galled network that satisfies M, and if so, constructing one. In fact, if such an ultrametric galled network exists, our algorithm is guaranteed to construct one containing the minimum possible number of nodes with more than one parent (hybrid nodes). We also prove that finding a largest possible submatrix M' of M such that there exists an ultrametric galled network that satisfies M' is NP-hard. Furthermore, we show that given an incomplete distance matrix (i.e. where some matrix entries are missing), it is also NP-hard to determine whether there exists an ultrametric galled network which satisfies it.     

FastJoin, an improved neighbor-joining algorithm

Reconstructing the evolutionary history of a set of species is an elementary problem in biology, and methods for solving this problem are evaluated based on two characteristics: accuracy and efficiency. Neighbor-joining reconstructs phylogenetic trees by iteratively picking a pair of nodes to merge as a new node until only one node remains; due to its good accuracy and speed, it has been embraced by the phylogeny research community. With the advent of large amounts of data, improved fast and precise methods for reconstructing evolutionary trees have become necessary. We improved the neighbor-joining algorithm by iteratively picking two pairs of nodes and merging as two new nodes, until only one node remains. We found that another pair of true neighbors could be chosen to merge as a new node besides the pair of true neighbors chosen by the criterion of the neighbor-joining method, in each iteration of the clustering procedure for the purely additive tree. These new neighbors will be selected by another iteration of the neighbor-joining method, so that they provide an improved neighbor-joining algorithm, by iteratively picking two pairs of nodes to merge as two new nodes until only one node remains, constructing the same phylogenetic tree as the neighbor-joining algorithm for the same input data. By combining the improved neighbor-joining algorithm with styles upper bound computation optimization of RapidNJ and external storage of ERapidNJ methods, a new method of reconstructing phylogenetic trees, FastJoin, was proposed. Experiments with sets of data showed that this new neighbor-joining algorithm yields a significant speed-up compared to classic neighbor-joining, showing empirically that FastJoin is superior to almost all other neighbor-joining implementations.     

Bias in phylogenetic reconstruction of vertebrate rhodopsin sequences

Two spurious nodes were found in phylogenetic analyses of vertebrate rhodopsin sequences in comparison with well-established vertebrate relationships. These spurious reconstructions were well supported in bootstrap analyses and occurred independently of the method of phylogenetic analysis used (parsimony, distance, or likelihood). Use of this data set of vertebrate rhodopsin sequences allowed us to exploit established vertebrate relationships, as well as the considerable amount known about the molecular evolution of this gene, in order to identify important factors contributing to the spurious reconstructions. Simulation studies using parametric bootstrapping indicate that it is unlikely that the spurious nodes in the parsimony analyses are due to long branches or other topological effects. Rather, they appear to be due to base compositional bias at third positions, codon bias, and convergent evolution at nucleotide positions encoding the hydrophobic residues isoleucine, leucine, and valine. LogDet distance methods, as well as maximum-likelihood methods which allow for nonstationary changes in base composition, reduce but do not entirely eliminate support for the spurious resolutions. Inclusion of five additional rhodopsin sequences in the phylogenetic analyses largely corrected one of the spurious reconstructions while leaving the other unaffected. The additional sequences not only were more proximal to the corrected node, but were also found to have intermediate levels of base composition and codon bias as compared with neighboring sequences on the tree. This study shows that the spurious reconstructions can be corrected either by excluding third positions, as well as those encoding the amino acids Ile, Val, and Leu (which may not be ideal, as these sites can contain useful phylogenetic signal for other parts of the tree), or by the addition of sequences that reduce problems associated with convergent evolution.     

Clearcut: a fast implementation of relaxed neighbor joining

SUMMARY: Clearcut is an open source implementation for the relaxed neighbor joining (RNJ) algorithm. While traditional neighbor joining (NJ) remains a popular method for distance-based phylogenetic tree reconstruction, it suffers from a O(N(3)) time complexity, where N represents the number of taxa in the input. Due to this steep asymptotic time complexity, NJ cannot reasonably handle very large datasets. In contrast, RNJ realizes a typical-case time complexity on the order of N(2)logN without any significant qualitative difference in output. RNJ is particularly useful when inferring a very large tree or a large number of trees. In addition, RNJ retains the desirable property that it will always reconstruct the true tree given a matrix of additive pairwise distances. Clearcut implements RNJ as a C program, which takes either a set of aligned sequences or a pre-computed distance matrix as input and produces a phylogenetic tree. Alternatively, Clearcut can reconstruct phylogenies using an extremely fast standard NJ implementation. AVAILABILITY: Clearcut source code is available for download at: http://bioinformatics.hungry.com/clearcut     

Edge Principal Components and Squash Clustering: Using the Special Structure of Phylogenetic Placement Data for Sample Comparison

Principal components analysis (PCA) and hierarchical clustering are two of the most heavily used techniques for analyzing the differences between nucleic acid sequence samples taken from a given environment. They have led to many insights regarding the structure of microbial communities. We have developed two new complementary methods that leverage how this microbial community data sits on a phylogenetic tree. Edge principal components analysis enables the detection of important differences between samples that contain closely related taxa. Each principal component axis is a collection of signed weights on the edges of the phylogenetic tree, and these weights are easily visualized by a suitable thickening and coloring of the edges. Squash clustering outputs a (rooted) clustering tree in which each internal node corresponds to an appropriate “average” of the original samples at the leaves below the node. Moreover, the length of an edge is a suitably defined distance between the averaged samples associated with the two incident nodes, rather than the less interpretable average of distances produced by UPGMA, the most widely used hierarchical clustering method in this context. We present these methods and illustrate their use with data from the human microbiome.     

An optimal algorithm to reconstruct trees from additive distance data

In this article the question of reconstructing a phylogeny from additive distance data is addressed. Previous algorithms used the complete distance matrix of then OTUs (Operational Taxonomic Unit), that corresponds to the tips of the tree. This usedO(n ²) computing time. It is shown that this is wasteful for biologically reasonable trees. If the tree has internal nodes with degrees that are bounded onO(n*log(n)) algorithm is possible. It is also shown if the nodes can have unbounded degrees the problem hasn ² as lower bound.     

MODELING BRAIN EVOLUTION FROM BEHAVIOR: A PERMUTATIONAL REGRESSION APPROACH

This paper has two complementary purposes: first, to present a method to perform multiple regression on distance matrices, with permutation testing appropriate for path-length matrices representing evolutionary trees, and then, to apply this method to study the joint evolution of brain, behavior and other characteristics in marsupials. To understand the computation method, consider that the dependent matrix is unfolded as a vector y; similarly, consider X to be a table containing the independent matrices, also unfolded as vectors. A multiple regression is computed to express y as a function of X. The parameters of this regression (R² and partial regression coefficients) are tested by permutations, as follows. When the dependent matrix variable y represents a simple distance or similarity matrix, permutations are performed in the same manner as the Mantel permutational test. When it is an ultrametric matrix representing a dendrogram, we use the double-permutation method (Lapointe and Legendre 1990, 1991). When it is a path-length matrix representing an additive tree (cladogram), we use the triple-permutation method (Lapointe and Legendre 1992). The independent matrix variables in X are kept fixed with respect to one another during the permutations. Selection of predictors can be accomplished by forward selection, backward elimination, or a stepwise procedure. A phylogenetic tree, derived from marsupial brain morphology data (28 species), is compared to trees depicting the evolution of diet, sociability, locomotion, and habitat in these animals, as well as their taxonomy and geographical relationships. A model is derived in which brain evolution can be predicted from taxonomy, diet, sociability and locomotion (R² = 0.75). A new tree, derived from the “predicted” data, shows a lot of similarity to the brain evolution tree. The meaning of the taxonomy, diet, sociability, and locomotion predictors are discussed and conclusions are drawn about the evolution of brain and behavior in marsupials.     

Likelihood analysis of phylogenetic networks using directed graphical models

A method for computing the likelihood of a set of sequences assuming a phylogenetic network as an evolutionary hypothesis is presented. The approach applies directed graphical models to sequence evolution on networks and is a natural generalization of earlier work by Felsenstein on evolutionary trees, including it as a special case. The likelihood computation involves several steps. First, the phylogenetic network is rooted to form a directed acyclic graph (DAG). Then, applying standard models for nucleotide/amino acid substitution, the DAG is converted into a Bayesian network from which the joint probability distribution involving all nodes of the network can be directly read. The joint probability is explicitly dependent on branch lengths and on recombination parameters (prior probability of a parent sequence). The likelihood of the data assuming no knowledge of hidden nodes is obtained by marginalization, i.e., by summing over all combinations of unknown states. As the number of terms increases exponentially with the number of hidden nodes, a Markov chain Monte Carlo procedure (Gibbs sampling) is used to accurately approximate the likelihood by summing over the most important states only. Investigating a human T-cell lymphotropic virus (HTLV) data set and optimizing both branch lengths and recombination parameters, we find that the likelihood of a corresponding phylogenetic network outperforms a set of competing evolutionary trees. In general, except for the case of a tree, the likelihood of a network will be dependent on the choice of the root, even if a reversible model of substitution is applied. Thus, the method also provides a way in which to root a phylogenetic network by choosing a node that produces a most likely network.     

LZ complexity distance of DNA sequences and its application in phylogenetic tree reconstruction

DNA sequences can be treated as finite-length symbol strings over a four-letter alphabet （A, C, T, G）. As a universal and computable complexity measure, LZ complexity is valid to describe the complexity of DNA sequences. In this study, a concept of conditional LZ complexity between two sequences is proposed according to the principle of LZ complexity measure. An LZ complexity distance metric between two nonnull sequences is defined by utilizing conditional LZ complexity. Based on LZ complexity distance, a phylogenetic tree of 26 species of placental mammals （Eutheria） with three outgroup species was reconstructed from their complete mitochondrial genomes. On the debate that which two of the three main groups of placental mammals, namely Primates, Ferungulates, and Rodents, are more closely related, the phylogenetic tree reconstructed based on LZ complexity distance supports the suggestion that Primates and Ferungulates are more closely related.