Effective selection of informative SNPs and classification on the HapMap genotype data

Background  

Since the single nucleotide polymorphisms (SNPs) are genetic variations which determine the difference between any two unrelated individuals, the SNPs can be used to identify the correct source population of an individual. For efficient population identification with the HapMap genotype data, as few informative SNPs as possible are required from the original 4 million SNPs. Recently, Park et al. (2006) adopted the nearest shrunken centroid method to classify the three populations, i.e., Utah residents with ancestry from Northern and Western Europe (CEU), Yoruba in Ibadan, Nigeria in West Africa (YRI), and Han Chinese in Beijing together with Japanese in Tokyo (CHB+JPT), from which 100,736 SNPs were obtained and the top 82 SNPs could completely classify the three populations.     

A Modified T-test Feature Selection Method and Its Application on the HapMap Genotype Data

Single nucleotide polymorphisms (SNPs) are genetic variations that determine the differences between any two unrelated individuals. Various population groups can be distinguished from each other using SNPs. For instance, the HapMap dataset has four population groups with about ten million SNPs. For more insights on human evolution, ethnic variation, and population assignment, we propose to find out which SNPs are significant in determining the population groups and then to classify different populations using these relevant SNPs as input features. In this study, we developed a modified t-test ranking measure and applied it to the HapMap genotype data. Firstly, we rank all SNPs in comparison with other feature importance measures including F-statistics and the informativeness for assignment. Secondly, we select different numbers of the most highly ranked SNPs as the input to a classifier, such as the support vector machine, so as to find the best feature subset corresponding to the best classification accuracy. Experimental results showed that the proposed method is very effective in finding SNPs that are significant in determining the population groups, with reduced computational burden and better classification accuracy.     

Dissection of a metastatic gene expression signature into distinct components

Background  

Metastasis, the process whereby cancer cells spread, is in part caused by an incompletely understood interplay between cancer cells and the surrounding stroma. Gene expression studies typically analyze samples containing tumor cells and stroma. Samples with less than 50% tumor cells are generally excluded, thereby reducing the number of patients that can benefit from clinically relevant signatures.     

Localization of thyroglobulin antigenicity in rat thyroid sections using antibodies labled with peroxidase or (125)I-radioiodine

In the hope of localizing thyroglobulin within focullar cells of the thyroid gland, antibodies raised against rat thyroglobulin were labeled with the enzyme horseradish peroxidase or with (125)I-radioiodine. Sections of rat thyroids fixed in glutaraldehyde and embedded in glycol methacrylate or Araldite were placed in contact with the labeled antibodies. The sites of antibody binding were detected by diaminobenzidine staining in the case of peroxidase labeling, and radioautography in the case of 125(I) labeling. Peroxidase labeling revealed that the antibodies were bound by the luminal colloid of the thyroid follicles and, within focullar cells, by colloid droplets, condensing vacuoles, and apical vesicles. (125)I labeling confirmed these findings, and revealed some binding of antibodies within Golgi saccules and rough endoplasmic reticulum. This method provides a visually less distinct distribution than peroxidase labeling, but it allowed ready quantitation of the reactions by counts of silver grains in the radioautographs. The counts revealed that the concentration of label was similar in the luminal colloid of different follicles, but that it varied within the compartments of follicular cells. A moderate concentration was detected in rough endoplasmic reticulum and Golgi saccules, whereas a high concentration was found in condensing vacuoles, apical vesicles, and in the luminal colloid. Varying amounts of label were observed over the different types of colloid droplets, and this was attributed to various degrees of lysosomal degradation of thyroglobulin. It is concluded that the concentration of thyroglobulin antigenicity increases during transport from the ribosomal site of synthesis to the follicular colloid, and then decreases during the digestion of colloid droplets which leads to the release of the thyoid hormone.     

Molecular evolution of a repetitive region within the per gene of Drosophila

The clock gene period (per) controls a number of biological rhythms in Drosophila. In D. melanogaster, per has a repetitive region that encodes a number of alternating threonine-glycine residues. We sequenced and compared this region from several different Drosophila species belonging to various groups within the Drosophila and Sophophora subgenera. This part of per shows a great variability in both DNA sequence and length. Furthermore, analysis of the data suggests that changes in the length of this variable region might be associated with amino acid replacements in the more conserved flanking sequences.      

Comparative genomics of 274 Vibrio cholerae genomes reveals mobile functions structuring three niche dimensions

Background

Vibrio cholerae is a globally dispersed pathogen that has evolved with humans for centuries, but also includes non-pathogenic environmental strains. Here, we identify the genomic variability underlying this remarkable persistence across the three major niche dimensions space, time, and habitat.

Results

Taking an innovative approach of genome-wide association applicable to microbial genomes (GWAS-M), we classify 274 complete V. cholerae genomes by niche, including 39 newly sequenced for this study with the Ion Torrent DNA-sequencing platform. Niche metadata were collected for each strain and analyzed together with comprehensive annotations of genetic and genomic attributes, including point mutations (single-nucleotide polymorphisms, SNPs), protein families, functions and prophages.

Conclusions

Our analysis revealed that genomic variations, in particular mobile functions including phages, prophages, transposable elements, and plasmids underlie the metadata structuring in each of the three niche dimensions. This underscores the role of phages and mobile elements as the most rapidly evolving elements in bacterial genomes, creating local endemicity (space), leading to temporal divergence (time), and allowing the invasion of new habitats. Together, we take a data-driven approach for comparative functional genomics that exploits high-volume genome sequencing and annotation, in conjunction with novel statistical and machine learning analyses to identify connections between genotype and phenotype on a genome-wide scale.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-654) contains supplementary material, which is available to authorized users.     

Cell cycle population effects in perturbation studies

Growth condition perturbation or gene function disruption are commonly used strategies to study cellular systems. Although it is widely appreciated that such experiments may involve indirect effects, these frequently remain uncharacterized. Here, analysis of functionally unrelated Saccharyomyces cerevisiae deletion strains reveals a common gene expression signature. One property shared by these strains is slower growth, with increased presence of the signature in more slowly growing strains. The slow growth signature is highly similar to the environmental stress response (ESR), an expression response common to diverse environmental perturbations. Both environmental and genetic perturbations result in growth rate changes. These are accompanied by a change in the distribution of cells over different cell cycle phases. Rather than representing a direct expression response in single cells, both the slow growth signature and ESR mainly reflect a redistribution of cells over different cell cycle phases, primarily characterized by an increase in the G1 population. The findings have implications for any study of perturbation that is accompanied by growth rate changes. Strategies to counter these effects are presented and discussed.