Maximum-likelihood models for combined analyses of multiple sequence data

被引:312
作者
Yang, ZH
机构
[1] PENN STATE UNIV,INST MOLEC EVOLUT GENET,UNIVERSITY PK,PA 16802
[2] PENN STATE UNIV,DEPT BIOL,MUELLER LAB 328,UNIVERSITY PK,PA 16802
[3] BEIJING AGR UNIV,COLL ANIM SCI & TECHNOL,BEIJING 100094,PEOPLES R CHINA
关键词
models; maximum likelihood; multiple gene data; molecular clock;
D O I
10.1007/BF02352289
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Models of nucleotide substitution were constructed for combined analyses of heterogeneous sequence data (such as those of multiple genes) from the same set of species. The models account for different aspects of the heterogeneity in the evolutionary process of different genes, such as differences in nucleotide frequencies, in substitution rate bias (for example, the transition/transversion rate bias), and in the extent of rate variation across sites. Model parameters were estimated by maximum likelihood and the likelihood ratio test was used to test hypotheses concerning sequence evolution, such as rate constancy among lineages (the assumption of a molecular clock) and proportionality of branch lengths for different genes. The example data from a segment of the mitochondrial genome of six hominoid species (human, common and pygmy chimpanzees, gorilla, orangutan, and siamang) were analyzed. Nucleotides at the three codon positions in the protein-coding regions and from the tRNA-coding regions were considered heterogeneous data sets. Statistical tests showed that the amount of evolution in the sequence data reflected in the estimated branch lengths can be explained by the codon-position effect and lineage effect of substitution rates. The assumption of a molecular clock could not be rejected when the data were analyzed separately or when the rate variation among sites was ignored. However, significant differences in substitution rate among lineages were found when the data sets were combined and when the rate variation among sites was accounted for in the models. Under the assumption that the orangutan and African apes diverged 13 million years ago, the combined analysis of the sequence data estimated the times for the human-chimpanzee separation and for the separation of the gorilla as 4.3 and 6.8 million years ago, respectively.
引用
收藏
页码:587 / 596
页数:10
相关论文
共 50 条
  • [21] MAXIMUM-LIKELIHOOD ADAPTIVE NEURAL CONTROLLER
    PERLOVSKY, LI
    JASKOLSKI, J
    NEURAL NETWORKS, 1994, 7 (04) : 671 - 680
  • [22] Maximum-Likelihood Inference of Population Size Contractions from Microsatellite Data
    Leblois, Raphael
    Pudlo, Pierre
    Neron, Joseph
    Bertaux, Francois
    Beeravolu, Champak Reddy
    Vitalis, Renaud
    Rousset, Francois
    MOLECULAR BIOLOGY AND EVOLUTION, 2014, 31 (10) : 2805 - 2823
  • [23] Maximum-likelihood DOA estimation by data-supported grid search
    Stoica, P
    Gershman, AB
    IEEE SIGNAL PROCESSING LETTERS, 1999, 6 (10) : 273 - 275
  • [24] QUADRATIC APPROXIMATION OF THE MAXIMUM-LIKELIHOOD CRITERION
    Afonine, P.
    Lunin, V. Y.
    Urzhumtsev, A.
    ACTA CRYSTALLOGRAPHICA A-FOUNDATION AND ADVANCES, 2002, 58 : C263 - C263
  • [25] A MAXIMUM-LIKELIHOOD APPROACH TO FEATURE SEGMENTATION
    BRILLAULTOMAHONY, B
    ELLIS, TJ
    PATTERN RECOGNITION, 1993, 26 (05) : 787 - 798
  • [26] The effect of taxon sampling on estimating rate heterogeneity parameters of maximum-likelihood models
    Sullivan, J
    Swofford, DL
    Naylor, GJP
    MOLECULAR BIOLOGY AND EVOLUTION, 1999, 16 (10) : 1347 - 1356
  • [27] Maximum-Likelihood Nonparametric Estimation of Smooth Spectra From Irregularly Sampled Data
    Stoica, Petre
    Babu, Prabhu
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2011, 59 (12) : 5746 - 5758
  • [28] Maximum-likelihood autoregressive estimation on incomplete spectra
    Weruaga, Luis
    Kepesi, Marian
    2007 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL III, PTS 1-3, PROCEEDINGS, 2007, : 1001 - +
  • [29] Testing for differentially-expressed genes by maximum-likelihood analysis of microarray data
    Ideker, T
    Thorsson, V
    Siegel, AF
    Hood, LE
    JOURNAL OF COMPUTATIONAL BIOLOGY, 2000, 7 (06) : 805 - 817
  • [30] Blind Maximum-Likelihood Identification of Wiener Systems
    Vanbeylen, Laurent
    Pintelon, Rik
    Schoukens, Johan
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2009, 57 (08) : 3017 - 3029