Biomedical subjects

J L Thorne

Publications and source records attributed to J L Thorne.

15 recordsLinked to original sources

PubMed1998

PASSML: combining evolutionary inference and protein secondary structure prediction.

MOTIVATION: Evolutionary models of amino acid sequences can be adapted to incorporate structure information; protein structure biologists can use phylogenetic relationships among species to improve prediction accuracy. Results : A computer program called PASSML ('Phylogeny and Secondary Structure using Maximum Likelihood') has been developed to implement an evolutionary model that combines protein secondary structure and amino acid replacement. The model is related to that of Dayhoff and co-workers, but we distinguish eight categories of structural environment: alpha helix, beta sheet, turn and coil, each further classified according to solvent accessibility, i.e. buried or exposed. The model of sequence evolution for each of the eight categories is a Markov process with discrete states in continuous time, and the organization of structure along protein sequences is described by a hidden Markov model. This paper describes the PASSML software and illustrates how it allows both the reconstruction of phylogenies and prediction of secondary structure from aligned amino acid sequences. AVAILABILITY: PASSML 'ANSI C' source code and the example data sets described here are available at http://ng-dec1.gen.cam.ac.uk/hmm/Passml.html and 'downstream' Web pages. CONTACT: P.Lio@gen.cam.ac.uk

Adenylate Kinase↗

PubMed1998

Assessing the impact of secondary structure and solvent accessibility on protein evolution.

Empirically derived models of amino acid replacement are employed to study the association between various physical features of proteins and evolution. The strengths of these associations are statistically evaluated by applying the models of protein evolution to 11 diverse sets of protein sequences. Parametric bootstrap tests indicate that the solvent accessibility status of a site has a particularly strong association with the process of amino acid replacement that it experiences. Significant association between secondary structure environment and the amino acid replacement process is also observed. Careful description of the length distribution of secondary structure elements and of the organization of secondary structure and solvent accessibility along a protein did not always significantly improve the fit of the evolutionary models to the data sets that were analyzed. As indicated by the strength of the association of both solvent accessibility and secondary structure with amino acid replacement, the process of protein evolution-both above and below the species level-will not be well understood until the physical constraints that affect protein evolution are identified and characterized.

Databases, Factual↗

PubMed1996

Using evolutionary trees in protein secondary structure prediction and other comparative sequence analyses.

Previously proposed methods for protein secondary structure prediction from multiple sequence alignments do not efficiently extract the evolutionary information that these alignments contain. The predictions of these methods are less accurate than they could be, because of their failure to consider explicitly the phylogenetic tree that relates aligned protein sequences. As an alternative, we present a hidden Markov model approach to secondary structure prediction that more fully uses the evolutionary information contained in protein sequence alignments. A representative example is presented, and three experiments are performed that illustrate how the appropriate representation of evolutionary relatedness can improve inferences. We explain why similar improvement can be expected in other secondary structure prediction methods and indeed any comparative sequence analysis method.

Amino Acid Sequence↗

PubMed1996

Combining protein evolution and secondary structure.

An evolutionary model that combines protein secondary structure and amino acid replacement is introduced. It allows likelihood analysis of aligned protein sequences and does not require the underlying secondary (or tertiary) structures of these sequences to be known. One component of the model describes the organization of secondary structure along a protein sequence and another specifies the evolutionary process for each category of secondary structure. A database of proteins with known secondary structures is used to estimate model parameters representing these two components. Phylogeny, the third component of the model, can be estimated from the data set of interest. As an example, we employ our model to analyze a set of sucrose synthase sequences. For the evolution of sucrose synthase, a parametric bootstrap approach indicates that our model is statistically preferable to one that ignores secondary structure.

Amino Acid Sequence↗

PubMed1995

Estimation and reliability of molecular sequence alignments.

The problem of estimating the relatedness of a pair of biological sequences is addressed. A stochastic model of sequence evolution is described that allows insertion and deletion as well as replacement of amino acid residues (or substitution of nucleotides) over time. An expectation-maximization (EM) algorithm that obtains maximum likelihood estimates of the model parameters is introduced. The method assumes that the sequences are related by descent from a common ancestor but the alignment (i.e., the precise evolutionary correspondence between residues in each sequence) is unknown. Results from the E-step of the EM algorithm are used to assess the likelihood that any two residues are related by direct descent from a common ancestor.

Algorithms↗

PubMed1992

Inching toward reality: an improved likelihood model of sequence evolution.

Our previous evolutionary model is generalized to permit approximate treatment of multiple-base insertions and deletions as well as regional heterogeneity of substitution rates. Parameter estimation and alignment procedures that incorporate these generalizations are developed. Simulations are used to assess the accuracy of the parameter estimation procedure and an example of an inferred alignment is included.

Animals↗

PubMed1992

Freeing phylogenies from artifacts of alignment.

Widely used methods for phylogenetic inference, both those that require and those that produce alignments, share certain weaknesses. These weaknesses are discussed, and a method that lacks them is introduced. For each pair of sequences in the data set, the method utilizes both insertion-deletion and amino acid replacement information to estimate a pairwise evolutionary distance. It is also possible to allow regional heterogeneity of replacement rates. Because a likelihood framework is adopted, the standard deviation of each pairwise distance can be estimated. The distance matrix and standard error estimates are used to infer a phylogenetic tree. As an example, this method is used on 10 widely diverged sequences of the second largest RNA polymerase subunit. A pseudo-bootstrap technique is devised to assess the validity of the inferred phylogenetic tree.

Base Sequence↗

PubMed1991

An evolutionary model for maximum likelihood alignment of DNA sequences.

Most algorithms for the alignment of biological sequences are not derived from an evolutionary model. Consequently, these alignment algorithms lack a strong statistical basis. A maximum likelihood method for the alignment of two DNA sequences is presented. This method is based upon a statistical model of DNA sequence evolution for which we have obtained explicit transition probabilities. The evolutionary model can also be used as the basis of procedures that estimate the evolutionary parameters relevant to a pair of unaligned DNA sequences. A parameter-estimation approach which takes into account all possible alignments between two sequences is introduced; the danger of estimating evolutionary parameters from a single alignment is discussed.

Algorithms↗

PubMed1990

Two progenitor cells for human oogonia inferred from pedigree data and the X-inactivation imprinting model of the fragile-X syndrome.

Laird has proposed that the human fragile-X syndrome is caused by abnormal chromosome imprinting. The analysis presented here supports and extends this proposal. Using published pedigrees that include DNA polymorphism (RFLP) data, we establish that the states of the fragile-X mutation termed "imprinted" and "nonimprinted" usually can be distinguished by the level of cytogenetic expression of the fragile-X chromosome. This information is then used to assess the state of the fragile-X allele in carrier progeny of individual women who inherited a nonimprinted fragile-X chromosome. From this assessment, an estimate is made of the frequency, in individual women, of primary oocytes with an imprinted fragile-X chromosome. The results of this analysis provide additional support for the specific model in which chromosome imprinting occurs in a female in, on average, half of her primary oocytes. This is the expected frequency if X-chromosome inactivation is the initial step in the imprinting of the mutant fragile-X allele. Moreover, this analysis suggests a biological explanation for peculiarities of fragile-X inheritance described by others as "clustering" and the "Sherman paradox." We interpret these peculiarities as consequences of a very small number of oogonial progenitor cells. Two progenitor cells for oogonia is the best integer estimate of the number of such cells at the time of the initial event that leads to chromosome imprinting.

Alleles↗

PubMed1970