第六章分子系统发生讲述.ppt

第六章 分子进化与系统发育分析 Ka/Ks：计算及含义 1. Ka：每个非同义位点的非同义替代数目； 2. Ks：每个同义位点的同义替代数目； 3. 一般计算公式：考虑序列上所有可能的同义位点(S)和非同义位点(N)，通过双序列比对发现存在的同义位点(Sd)和非同义位点(Nd)，存在： 第二节 系统发育树的构建 1. 系统发育树：分子进化树/分子进化分析… 2. 通过进化树的构建，分析分子之间的起源关系，预测分子的功能； 3. 建树方法： A.距离法(distance-based methods); B. 最大简约法(Maximum Parsimony)； C. 最大似然性法(Maximum Likelihood); 无根树，有根树，外群 系统发育树重建分析步骤 系统发育树重建的基本方法 1.距离法(distance) 2.最大简约法(maximum parsimony,MP) 3. 最大似然法(maximum likelihood,ML) 1. 距离法 又称距离矩阵法，首先通过各个物种之间的比较，根据一定的假设（进化距离模型）推导得出分类群之间的进化距离，构建一个进化距离矩阵。进化树的构建则是基于这个矩阵中的进化距离关系 。 通过距离矩阵建树的方法 由进化距离构建进化树的方法有很多，常见有： (1) Fitch-Margoliash Method（FM法）: 对短支长非常有效； (2) Unweighted Pair Group Method (UPGMA法) (3) Neighbor-Joining Method (NJ法/邻接法) ：求最短支长，最通用的距离方法 Fitch and Margoliash Algorithm (3 sequences) Distance table used Sequences combined in threes define the branches of the predicted tree calculate the branch lengths of the tree Fitch and Margoliash Algorithm (3 sequences) 1)?Draw unrooted tree with three branches originating from common node:(given the closer A and B) Fitch and Margoliash Algorithm (3 sequences) 2)?Calculate lengths of tree branches algebraically: distance from A to B = a + b = 22 (1) distance from A to C = a + c = 39 (2) distance from B to C = b + c = 41 (3) Fitch and Margoliash Algorithm (3 sequences) subtracting (3) from (2) yields: ? b + c = 41 -a – c = -39 __________ b – a = 2 (4) Fitch and Margoliash Algorithm (3 sequences) adding (1) and (4) yields 2b = 24; b = 12 so a + 12 = 22; a = 10 10 + c = 39; c = 29 Fitch and Margoliash Algorithm (3 sequences) 3)?Resulting tree: Fitch and Margoliash Algorithm (5 sequences) Algorithm can be extended to more sequences. Consider the distances: Fitch and Margoliash Algorithm (5 sequences) Locate most closely related sequences Fitch and Margoliash Algorithm (5 sequences) Create a new table by combining remaining sequences Distance from D to A,B,C: average distance of each of these to D ( (39 + 41 + 18) / 3 = 32.7) Fitch and Margoliash Algorithm (5 sequences) F