New methods for inferring population dynamics from microbial sequences

Marcos Pérez-Losada, Megan L. Porter, Loubna Rothenburg, Keith A. Crandall

Research output: Contribution to journalArticle

16 Citations (Scopus)

Abstract

The reduced cost of high throughput sequencing, increasing automation, and the amenability of sequence data for evolutionary analysis are making DNA data (or the corresponding amino acid sequences) the molecular marker of choice for studying microbial population genetics and phylogenetics. Concomitantly, due to the ever-increasing computational power, new, more accurate (and sometimes faster), sequence-based analytical approaches are being developed and applied to these new data. Here we review some commonly used, recently improved, and newly developed methodologies for inferring population dynamics and evolutionary relationships using nucleotide and amino acid sequence data, including: alignment, model selection, bifurcating and network phylogenetic approaches, and methods for estimating demographic history, population structure, and population parameters (recombination, genetic diversity, growth, and natural selection). Because of the extensive literature published on these topics this review cannot be comprehensive in its scope. Instead, for all the methods discussed we introduce the approaches we think are particularly useful for analyses of microbial sequences and where possible, include references to recent and more inclusive reviews.

Original languageEnglish (US)
Pages (from-to)24-43
Number of pages20
JournalInfection, Genetics and Evolution
Volume7
Issue number1
DOIs
StatePublished - Jan 1 2007
Externally publishedYes

Fingerprint

Population Dynamics
Amino Acid Sequence
population dynamics
Microbial Genetics
Genetic Selection
Automation
Population Genetics
amino acid sequences
Genetic Recombination
Population
Sequence Analysis
microbial genetics
Nucleotides
amino acid
phylogeny
Demography
automation
phylogenetics
Costs and Cost Analysis
demographic history

Keywords

  • Alignment
  • Coalescent
  • Microorganisms
  • Phylogenetics
  • Population genetics
  • Sequences

ASJC Scopus subject areas

  • Microbiology
  • Ecology, Evolution, Behavior and Systematics
  • Molecular Biology
  • Genetics
  • Microbiology (medical)
  • Infectious Diseases

Cite this

New methods for inferring population dynamics from microbial sequences. / Pérez-Losada, Marcos; Porter, Megan L.; Rothenburg, Loubna; Crandall, Keith A.

In: Infection, Genetics and Evolution, Vol. 7, No. 1, 01.01.2007, p. 24-43.

Research output: Contribution to journalArticle

Pérez-Losada, Marcos ; Porter, Megan L. ; Rothenburg, Loubna ; Crandall, Keith A. / New methods for inferring population dynamics from microbial sequences. In: Infection, Genetics and Evolution. 2007 ; Vol. 7, No. 1. pp. 24-43.
@article{22ff370cb50d4f6ca5fbf3d072a464df,
title = "New methods for inferring population dynamics from microbial sequences",
abstract = "The reduced cost of high throughput sequencing, increasing automation, and the amenability of sequence data for evolutionary analysis are making DNA data (or the corresponding amino acid sequences) the molecular marker of choice for studying microbial population genetics and phylogenetics. Concomitantly, due to the ever-increasing computational power, new, more accurate (and sometimes faster), sequence-based analytical approaches are being developed and applied to these new data. Here we review some commonly used, recently improved, and newly developed methodologies for inferring population dynamics and evolutionary relationships using nucleotide and amino acid sequence data, including: alignment, model selection, bifurcating and network phylogenetic approaches, and methods for estimating demographic history, population structure, and population parameters (recombination, genetic diversity, growth, and natural selection). Because of the extensive literature published on these topics this review cannot be comprehensive in its scope. Instead, for all the methods discussed we introduce the approaches we think are particularly useful for analyses of microbial sequences and where possible, include references to recent and more inclusive reviews.",
keywords = "Alignment, Coalescent, Microorganisms, Phylogenetics, Population genetics, Sequences",
author = "Marcos P{\'e}rez-Losada and Porter, {Megan L.} and Loubna Rothenburg and Crandall, {Keith A.}",
year = "2007",
month = "1",
day = "1",
doi = "10.1016/j.meegid.2006.03.004",
language = "English (US)",
volume = "7",
pages = "24--43",
journal = "Infection, Genetics and Evolution",
issn = "1567-1348",
publisher = "Elsevier",
number = "1",

}

TY - JOUR

T1 - New methods for inferring population dynamics from microbial sequences

AU - Pérez-Losada, Marcos

AU - Porter, Megan L.

AU - Rothenburg, Loubna

AU - Crandall, Keith A.

PY - 2007/1/1

Y1 - 2007/1/1

N2 - The reduced cost of high throughput sequencing, increasing automation, and the amenability of sequence data for evolutionary analysis are making DNA data (or the corresponding amino acid sequences) the molecular marker of choice for studying microbial population genetics and phylogenetics. Concomitantly, due to the ever-increasing computational power, new, more accurate (and sometimes faster), sequence-based analytical approaches are being developed and applied to these new data. Here we review some commonly used, recently improved, and newly developed methodologies for inferring population dynamics and evolutionary relationships using nucleotide and amino acid sequence data, including: alignment, model selection, bifurcating and network phylogenetic approaches, and methods for estimating demographic history, population structure, and population parameters (recombination, genetic diversity, growth, and natural selection). Because of the extensive literature published on these topics this review cannot be comprehensive in its scope. Instead, for all the methods discussed we introduce the approaches we think are particularly useful for analyses of microbial sequences and where possible, include references to recent and more inclusive reviews.

AB - The reduced cost of high throughput sequencing, increasing automation, and the amenability of sequence data for evolutionary analysis are making DNA data (or the corresponding amino acid sequences) the molecular marker of choice for studying microbial population genetics and phylogenetics. Concomitantly, due to the ever-increasing computational power, new, more accurate (and sometimes faster), sequence-based analytical approaches are being developed and applied to these new data. Here we review some commonly used, recently improved, and newly developed methodologies for inferring population dynamics and evolutionary relationships using nucleotide and amino acid sequence data, including: alignment, model selection, bifurcating and network phylogenetic approaches, and methods for estimating demographic history, population structure, and population parameters (recombination, genetic diversity, growth, and natural selection). Because of the extensive literature published on these topics this review cannot be comprehensive in its scope. Instead, for all the methods discussed we introduce the approaches we think are particularly useful for analyses of microbial sequences and where possible, include references to recent and more inclusive reviews.

KW - Alignment

KW - Coalescent

KW - Microorganisms

KW - Phylogenetics

KW - Population genetics

KW - Sequences

UR - http://www.scopus.com/inward/record.url?scp=33845270141&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33845270141&partnerID=8YFLogxK

U2 - 10.1016/j.meegid.2006.03.004

DO - 10.1016/j.meegid.2006.03.004

M3 - Article

C2 - 16627010

AN - SCOPUS:33845270141

VL - 7

SP - 24

EP - 43

JO - Infection, Genetics and Evolution

JF - Infection, Genetics and Evolution

SN - 1567-1348

IS - 1

ER -