Table Of ContentBIOINFORMATICS AND THE CELL
Modern Computational Approaches in Genomics,
Proteomics and Transcriptomics
BIOINFORMATICS AND THE CELL
Modern Computational Approaches in Genomics,
Proteomics and Transcriptomics
by
Xuhua Xia
University of Ottawa, Ontario, Canada
Xuhua Xia
CAREG and Biology Department
University of Ottawa
30 Marie Curie, P.O. Box 450
Ottawa, Ontario K1N 6N5
Canada
Library of Congress Control Number: 2007922341
ISBN-10: 0-387-71336-0 e-ISBN-10: 0-387-71337-9
ISBN-13: 978-0-387-71336-6 e-ISBN-13: 978-0-387-71337-3
Printed on acid-free paper.
©2007 Springer Science+Business Media, LLC
All rights reserved. This work may not be translated or copied in whole or in part without the written
permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York,
NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in
connection with any form of information storage and retrieval, electronic adaptation, computer soft-
ware, or by similar or dissimilar methodology now known or hereafter developed is forbidden.
The use in this publication of trade names, trademarks, service marks, and similar terms, even if they
are not identified as such, is not to be taken as an expression of opinion as to whether or not they are
subject to proprietary rights.
9 8 7 6 5 4 3 2 1
springer.com
CONTENTS
Contents....................................................................................................v
Preface.......................................................................................................x
Acknowledgement.................................................................................xiv
Chapter 1 BLAST and FASTA.................................................................1
1. Introduction....................................................................................1
2. Mathematics of string matching.....................................................4
2.1 Basic concepts.......................................................................4
3. String-matching algorithms in FASTA and BLAST....................11
3.1 FASTA................................................................................11
3.2 BLAST................................................................................16
4. Homology search and sequence annotation.................................20
5. Postscript......................................................................................21
Chapter 2 Sequence alignment................................................................23
1. Introduction..................................................................................23
2. Pairwise alignment.......................................................................24
2.1 Pairwise alignment with constant gap penalty.....................25
2.1.1 Global alignment............................................................25
2.1.2 Local alignment..............................................................29
2.1.3 The simple scoring scheme needs extension..................30
2.2 Pairwise alignment with a similarity matrix........................30
2.2.1 DNA matrices.................................................................30
2.2.2 Protein matrix.................................................................32
2.3 Pairwise alignment with gap penalty specified by the
affine function.....................................................................34
3. Multiple sequence alignment.......................................................38
3.1 Profile alignment.................................................................38
3.2 Multiple alignment with a guide tree...................................41
4. Sequence alignment with secondary structure.............................43
vi
5. Align nucleotide sequences against amino acid sequences..........44
6. Postscript......................................................................................47
Chapter 3 Contig assembly.....................................................................49
1. Introduction..................................................................................49
2. Skeletal output of contig assembly..............................................51
3. string matching of two sequence ends.........................................56
4. New development in contig assembly..........................................59
5. Postscript......................................................................................60
Chapter 4 DNA replication and viral evolution......................................62
1. Introduction..................................................................................62
2. Fundamentals of viruses...............................................................63
2.1 The virion and the viral genome..........................................64
2.2 Variation in viral genome size can be explained by
variation in mutation rate.....................................................65
2.3 A representative virus: Phage λ...........................................66
3. Fundamentals of bacterial species................................................67
4. genomic AT% of bacterial species is indicative of cellular
AT availability.............................................................................68
5. Formulating the hypothesis and predictions.................................70
6. Are our predictions supported?....................................................71
7. A short play featuring phages and bacteria..................................77
Chapter 5 Gene and motif prediction......................................................78
1. Introduction..................................................................................78
2. Bayes’ theorem and odds ratios...................................................79
3. Characterizing features of Signal sensor......................................83
3.1 Position weight matrix.........................................................83
3.2 Perceptron............................................................................93
4. Characterizing features of Content sensors................................100
4.1 Indices of content sensors related to DNA
methylation and spontaneous deamination........................101
4.2 Are these indices useful in discriminating between
coding and non-coding sequences?...................................104
Chapter 6 Hidden Markov Models........................................................109
1. Introduction................................................................................109
2. Markov models..........................................................................110
3. Hidden Markov Models.............................................................115
3.1 The Essential Elements in a Hidden Markov Model.........115
3.2 Training HMM..................................................................117
3.3 The Viterbi algorithm........................................................120
3.4 Forward algorithm.............................................................127
3.5 HMM and gene prediction.................................................130
4. Postscript....................................................................................131
Contents vii
Chapter 7 Gibbs Sampler......................................................................133
1. Introduction................................................................................133
2. A numerical illustration of the computational details of
Gibbs sampler............................................................................135
2.1 Initialization.......................................................................136
2.2 Predictive update...............................................................137
3. Motif sampler.............................................................................146
Chapter 8. Bioinformatics and vertebrate mitochondria.......................148
1. Introduction................................................................................148
1.1 Mitochondria and mitochondrial genomes........................149
1.2 DNA-Replication and Strand-biased mutation
spectrum............................................................................150
1.3 The effect of strand-biased mutation on codon usage.......152
2. Three hypotheses on tRNA anticodon.......................................156
2.1 The mutation hypothesis....................................................157
2.2 The codon-anticodon adaptation hypothesis.....................157
2.3 The wobble versatility hypothesis.....................................158
3. Empirical evaluation of the three alternative hypotheses...........160
3.1 Evaluation of the mutation hypothesis against the
two selectionist hypotheses...............................................160
3.2 Evaluating the two selectionist hypotheses.......................161
4. Integrating the codon-anticodon adaptation hypothesis
(CAAH) and the wobble versatility hypothesis (WVH)............162
4.1 Four-fold NNN codons......................................................163
4.2 Two-fold NNY codon families..........................................164
4.3 Two-fold NNR codon families..........................................165
5. Conflict between translation initiation and elongation..............165
6. PostScript...................................................................................171
Chapter 9. Characterizing translation efficiency...................................173
1. Introduction................................................................................173
2. RSCU (Relative synonymous codon usage)..............................175
3. CAI (Codon adaptation index)...................................................176
3.1 Computation and basic properties of CAI.........................176
3.2 Problems with CAI and its current implementation..........178
3.2.1 Problem when w = 0.....................................................178
3.2.2 Problems with codon families containing a single codon
179
3.2.3 Problems with amino acids coded by two different codon
families.........................................................................180
3.2.4 Problems with initiation and termination codons.........181
3.2.5 The problem with the compilation of the reference set of
genes.............................................................................181
4. Indices of codon-anticodon adaptation......................................182
viii
4.1 CAI with a tRNA anticodon-derived codon usage
table...................................................................................185
4.2 Codon-anticodon adaptation index (CAAI).......................187
5. Why CAI or CAAI should not be taken as a measure of
gene expression?........................................................................192
6. Will AT-rich mRNA be translated inefficiently?.......................200
7. Codon adaptation index and proteomics: clarrification of
some misunderstandings............................................................201
Chapter 10 Protein isoelectric point......................................................207
1. Introduction................................................................................207
2. Amino acid and protein isoelectric point...................................209
3. Genomic profiling of protein isoelectric point: a case study
with Helicobacter pylori............................................................213
4. An alternative explanation of H. pylori data..............................217
Chapter 11 Bioinformatics and Two-Dimensional Protein Separation.220
1. Introduction................................................................................220
2. Scientific rationale behind the 2D-SDS-PAGE.........................221
3. Expected separation pattern of 2D-SDS-PAGE for the
genome-derived proteome.........................................................222
4. posttranslational modification....................................................227
4.1 Importance in studying posttranslational modification.....227
4.2 Posttranslational modification changes the migration
pattern of proteins on 2D-SDS-PAGE...............................227
Chapter 12 Self-Organizing Map and other clustering Algorithms......231
1. Introduction................................................................................231
1.1 Classification and clustering..............................................231
1.2 Clustering and gene expression.........................................233
1.3 Similarity and distance indices..........................................235
2. UPGMA.....................................................................................239
3. Self-organizing map (SOM).......................................................243
3.1 The SOM algorithm...........................................................244
3.2 Variations of the basic SOM algorithm.............................249
Chapter 13 Molecular Phylogenetics....................................................251
1. Introduction................................................................................251
2. Biodiversity, historical information, and phylogenetics............252
3. Substitution models....................................................................253
3.1 Nucleotide-based substitution models and genetic
distances............................................................................254
3.2 Amino acid-based and codon-based substitution
models................................................................................264
4. Tree-building methods...............................................................266
4.1 Distance-based methods....................................................266
Contents ix
4.2 Maximum parsimony methods..........................................272
4.2.1 The Fitch algorithm......................................................272
4.2.2 The uphill search and branch-and-bound search
algorithms.....................................................................275
4.2.3 The long-branch attraction problem.............................277
4.3 Maximum likelihood methods...........................................279
4.4 Bayesian inference.............................................................283
4.4.1 Bayes theorem for a continuous variable......................283
4.4.2 Alternative computational approaches in Bayesian
inference.......................................................................287
Chapter 14 Fundamentals of Proteomics..............................................293
1. Introduction................................................................................293
2. Protein Mass Spectrometry........................................................294
3. Charge deconvolution................................................................295
4. Peptide mass fingerprinting........................................................301
4.1 Peptide digestion...............................................................301
4.2 MS determination of peptide mass....................................304
4.3 Protein database and in silico digestion.............................305
4.4 Protein identification.........................................................305
References.............................................................................................309
Postscript...............................................................................................342
Index.....................................................................................................344
PREFACE
Biological and biomedical sciences are becoming more interdisciplinary,
and scientists of the future need interdisciplinary training instead of the
conventional disciplinary training. Just as Sean Eddy (2005) wisely pointed
out that sending monolingual diplomats to the United Nations may not
enhance international collaborations, combining strictly disciplinary
scientists trained in either mathematics, computational science or molecular
biology will not create a productive interdisciplinary team ready to solve
interdisciplinary problems.
Molecular biology is an interdisciplinary science back in its heyday, and
founders of molecular biology were often interdisciplinary scientists. Indeed,
Francis Crick considered himself as “a mixture of crystallographer,
biophysicist, biochemist, and geneticist” (Crick, 1965). Because it was too
cumbersome to explain to people that he was such a mixture, the term
“molecular biologist” came handy. To get the crystallographer, biophysicist,
biochemist, and geneticist within himself to collaborate with each other
probably worked better than a team with a crystallographer, a biophysicist, a
biochemist and a geneticist who may not even be interested in each other’s
problems.
Bioinformatics was born in response to the interdisciplinary demand of
modern biological and biomedical sciences as a joint effort by among
mathematicians, computational scientists and biologists of all colors and
shades. It is a peculiar branch of science. A conventional branch of science
such as quantum mechanics in physics or population genetics in biology will
typically have a few classic publications laying down its theoretical
foundation, delineating its boundary and interface with other related
sciences, formulating its central questions, and highlighting the spectacular
views within and beyond that particular mansion of science. Once the
mansion has been skeletally constructed, subsequent works will only serve to
