Skip to main content Accessibility help
×
Hostname: page-component-7c8c6479df-94d59 Total loading time: 0 Render date: 2024-03-28T15:06:33.837Z Has data issue: false hasContentIssue false

21 - Analysis of Point Mutations in Vertebrate Genomes

from Part II - Studies on the four themes

Published online by Cambridge University Press:  04 August 2010

L. Pachter
Affiliation:
University of California, Berkeley
B. Sturmfels
Affiliation:
University of California, Berkeley
Get access

Summary

Using homologous sequences from eight vertebrates, we present a concrete example of the estimation of mutation rates in the models of evolution introduced in Chapter 4. We detail the process of data selection from a multiple alignment of the ENCODE regions, and compare rate estimates for each of the models in the Felsenstein hierarchy of Figure 4.7. We also address a standing problem in vertebrate evolution, namely the resolution of the phylogeny of the Eutherian orders, and discuss several challenges of molecular sequence analysis in inferring the phylogeny of this subclass. In particular, we consider the question of the position of the rodents relative to the primates, carnivores and artiodactyls; we affectionately dub this question the rodent problem.

Estimating mutation rates

Given an alignment of sequence homologs from various taxa, and an evolutionary model from Section 4.5, we are naturally led to ask the question, “what tree (with what branch lengths) and what values of the parameters in the rate matrix for that model are suggested by the alignment?” One answer to this question, the so-called maximum-likelihood solution, is, “the tree and rate parameters which maximize the probability that the given alignment would be generated by the given model.” (See also Sections 1.3 and 3.3.)

There are a number of available software packages which attempt to find, to varying degrees, this maximum-likelihood solution. For example, for a few of the most restrictive models in the Felsenstein hierarchy, the package PHYLIP [Felsenstein, 2004] will very efficiently search the tree space for the maximum-likelihood tree and rate parameters.

Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2005

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×