Detecting the signature of natural selection with microsatellites

Natural selection is one of the major factors in the evolution of all organisms. Detecting the signature of natural selection has been a central theme in evolutionary genetics. With the availability of microsatellite data, it is of interest to study how natural selection can be detected with microsatellites. ^ The overall aim of this research is to detect signatures of natural selection with data on genetic variation at microsatellite loci. The null hypothesis to be tested is the neutral mutation theory of molecular evolution, which states that different alleles at a locus have equivalent effects on fitness. Currently used tests of this hypothesis based on data on genetic polymorphism in natural populations presume that mutations at the loci follow the infinite allele/site models (IAM, ISM), in the sense that at each site at most only one mutation event is recorded, and each mutation leads to an allele not seen before in the population. Microsatellite loci, which are abundant in the genome, do not obey these mutation models, since the new alleles at such loci can be created either by contraction or expansion of tandem repeat sizes of core motifs. Since the current genome map is mainly composed of microsatellite loci and this class of loci is still most commonly studied in the context of human genome diversity, this research explores how the current test procedures for testing the neutral mutation hypothesis should be modified to take into account a generalized model of forward-backward stepwise mutations. In addition, recent literature also suggested that past demographic history of populations, presence of population substructure, and varying rates of mutations across loci all have confounding effects for detecting signatures of natural selection. ^ The effects of the stepwise mutation model and other confounding factors on detecting signature of natural selection are the main results of the research. ^

Clinical relevance of polymorphic DNA copy number variation (CNV) in African American women with stage I-II breast cancer

Objectives. The chief goal of this study was to analyze copy number variation (CNV) in breast cancer tumors from 25 African American women with early stage breast cancer (BC) using molecular inversion probes (MIP) in order to: (1) compare the degree of CNV in tumors compared to normal lymph nodes, and (2) determine whether gains and/or losses of genes in specific chromosomes differ between pathologic subtypes of breast cancer defined by known prognostic markers, (3) determine whether gains/losses in CN are associated with known oncogenes or tumor suppressor genes, and (4) determine whether increased gains/losses in CN for specific chromosomes were associated with differences in breast cancer recurrence. ^ Methods. Twenty to 37 nanograms of DNA extracted from 25 formalin-fixed paraffin embedded (FFPE) tumor samples and matched normal lymph nodes were added to individual tubes. Oligonucleotide probes with recognition sequences at each terminus were hybridized with a genomic target sequence to form a circular structure. Probes are released from genomic DNA obtained from FFPE samples, and those which have been correctly "circularized" in the proper allele/nucleotide reaction combination are amplified using polymerase chain reaction (PCR) primers. Amplicons were fluorescently labeled and the tag sequences released from the genome homology regions by treatment with uracil-N-glycosylase to cleave the probe at the site where uracils are present, and detected using a complementary tag array developed by Affymetrix. ^ Results. Analysis of CN gains and losses from tumors and normal tissues showed marked differences in tumors with numerous chromosomes affected. Similar changes were not observed in normal lymph nodes. When tumors were stratified into four groups based on expression or lack of expression of the estrogen receptor and HER2/neu, distinct patterns of CNV for different chromosomes were observed. Gains or losses in CN for specific chromosomes correlated with amplifications/deletions of particular oncogenes or tumor suppressor genes (i.e. such as found on chromosome 17) known to be associated with aggressive tumor phenotype and poor prognosis. There was a trend for increases in CN observed for chromosome 17 to correlate inversely with time to recurrence of BC (p=0.14 for trend). CNV was also observed for chromosomes 5, 8, 10, 11, and 16, which are known sites for several breast cancer susceptibility alleles. ^ Conclusions. This study is the first to validate the MIP technique, to correlate differences in gene expression with known prognostic tumor markers, and to correlate significant increases/decreases in CN with known tumor markers associated with prognosis. The results of this study may have far reaching public health implications towards identifying new high-risk groups based on genomic differences in CNP, both with respect to prognosis and response to therapy, and to eventually identify new therapeutic targets for prevention and treatment of this disease. ^