scholarly journals Population structure in the Neisseria , and the biological significance of fuzzy species

2011 ◽  
Vol 9 (71) ◽  
pp. 1208-1215 ◽  
Author(s):  
Jukka Corander ◽  
Thomas R. Connor ◽  
Clíona A. O'Dwyer ◽  
J. Simon Kroll ◽  
William P. Hanage
Keyword(s):  
Population Structure ◽  
Genetic Analysis ◽  
Population Genetic ◽  
Vaccine Development ◽  
Sequence Data ◽  
Genetic Material ◽  
Biological Significance ◽  
Population Genetic Analysis ◽  
Uniform Manner ◽  
Complex Forms

Phenotypic and genetic variation in bacteria can take bewilderingly complex forms even within a single genus. One of the most intriguing examples of this is the genus Neisseria , which comprises both pathogens and commensals colonizing a variety of body sites and host species, and causing a range of disease. Complex relatedness among both named species and previously identified lineages of Neisseria makes it challenging to study their evolution. Using the largest publicly available collection of bacterial sequence data in combination with a population genetic analysis and experiment, we probe the contribution of inter-species recombination to neisserial population structure, and specifically whether it is more common in some strains than others. We identify hybrid groups of strains containing sequences typical of more than one species. These groups of strains, typical of a fuzzy species, appear to have experienced elevated rates of inter-species recombination estimated by population genetic analysis and further supported by transformation experiments. In particular, strains of the pathogen Neisseria meningitidis in the fuzzy species boundary appear to follow a different lifestyle, which may have considerable biological implications concerning distribution of novel resistance elements and meningococcal vaccine development. Despite the strong evidence for negligible geographical barriers to gene flow within the population, exchange of genetic material still shows directionality among named species in a non-uniform manner.

POPULATION GENETIC ANALYSIS OF MOUNTAIN PLOVER USING MITOCHONDRIAL DNA SEQUENCE DATA

The Condor ◽  
10.1650/7594 ◽  
2005 ◽  
Vol 107 (2) ◽  
pp. 353 ◽  
Author(s):  
Sara J. Oyler-McCance ◽  
Judy St. John ◽  
Fritz L. Knopf ◽  
Tom W. Quinn
Keyword(s):  
Mitochondrial Dna ◽  
Genetic Analysis ◽  
Dna Sequence ◽  
Population Genetic ◽  
Sequence Data ◽  
Population Genetic Analysis ◽  
Dna Sequence Data ◽  
Mitochondrial Dna Sequence

scholarly journals Evaluation of Whole Exome Sequencing as an Alternative of BeadChip and Whole Genome Sequencing in Human Population Genetic Analysis

2018 ◽  
Author(s):  
Zoltán Maróti ◽  
Zsolt Boldogkői ◽  
Dóra Tombácz ◽  
Michael Snyder ◽  
Tibor Kalmár
Keyword(s):  
Genetic Analysis ◽  
Whole Genome Sequencing ◽  
Exome Sequencing ◽  
Genome Sequencing ◽  
Population Genetic ◽  
Genomic Sequence ◽  
Sequence Data ◽  
Human Populations ◽  
Whole Genome ◽  
Population Genetic Analysis

ABSTRACTUnderstanding the underlying genetic structure of human populations is of fundamental interest to both biological and social sciences. Advances in high-throughput genotyping technology have markedly improved our understanding of global patterns of human genetic variation. The most widely used methods for collecting variant information at the DNA-level include whole genome sequencing, which continues to remain costly, and the more economical solution of array-based techniques, as these are capable of simultaneously genotyping a pre-selected set of variable DNA sites in the human genome. The largest publicly accessible set of human genomic sequence data available today originates from exome sequencing that comprises around 1.2% of the whole genome (approximately 30 million base pairs). In this study, we compared the application of the exome dataset to the array-based dataset and to the gold standard whole genome dataset using the same population genetic analysis methods. Our results draw attention to some of the inherent problems that arise from using pre-selected SNP sets for population genetic analysis. Additionally, we demonstrate that exome sequencing provides a better alternative to the array-based methods for population genetic analysis. In this study, we propose a strategy for unbiased variant collection from exome data and offer a bioinformatics protocol for proper data processing.

scholarly journals Adaptive Evolution of Relish, a Drosophila NF-κB/IκB Protein

Genetics ◽  
2000 ◽  
Vol 154 (3) ◽  
pp. 1231-1238 ◽  
Author(s):  
David J Begun ◽  
Penn Whitley
Keyword(s):  
Immune Response ◽  
Innate Immunity ◽  
Genetic Analysis ◽  
Adaptive Evolution ◽  
Strong Evidence ◽  
Population Genetic ◽  
Microbial Pathogens ◽  
Population Genetic Analysis ◽  
Evolutionary Conflict ◽  
A Site

Abstract NF-κB and IκB proteins have central roles in regulation of inflammation and innate immunity in mammals. Homologues of these proteins also play an important role in regulation of the Drosophila immune response. Here we present a molecular population genetic analysis of Relish, a Drosophila NF-κB/IκB protein, in Drosophila simulans and D. melanogaster. We find strong evidence for adaptive protein evolution in D. simulans, but not in D. melanogaster. The adaptive evolution appears to be restricted to the IκB domain. A possible explanation for these results is that Relish is a site of evolutionary conflict between flies and their microbial pathogens.

Population genetic analysis of Enterocytozoon bieneusi in humans

2012 ◽  
Vol 42 (3) ◽  
pp. 287-293 ◽  
Author(s):  
Wei Li ◽  
Vitaliano Cama ◽  
Yaoyu Feng ◽  
Robert H. Gilman ◽  
Caryn Bern ◽  
...  
Keyword(s):  
Genetic Analysis ◽  
Population Genetic ◽  
Enterocytozoon Bieneusi ◽  
Population Genetic Analysis

scholarly journals Population genetic analysis and phylogeny reconstruction in Eucalyptus (Myrtaceae) using high-throughput, genome-wide genotyping

2011 ◽  
Vol 59 (1) ◽  
pp. 206-224 ◽  
Author(s):  
Dorothy A. Steane ◽  
Dean Nicolle ◽  
Carolina P. Sansaloni ◽  
César D. Petroli ◽  
Jason Carling ◽  
...  
Keyword(s):  
Genetic Analysis ◽  
High Throughput ◽  
Population Genetic ◽  
Phylogeny Reconstruction ◽  
Population Genetic Analysis ◽  
Genome Wide
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