Expanding the Profile of Short Term Vacation Rental (STVR) Hosts in Savannah, GA

Expanding the Profile of Short Term Vacation Rental (STVR) Hosts in Savannah, GA Abstract This research explores the complex identities of STVR hosts through their roles as entrepreneurs and residents in the communities that they host and live. Additionally, this research studies how hosts’ fluid identity uniquely positions them as potential sustainable entrepreneurs in their community. A total of 26 in-depth interviews were conducted with hosts or STVR managers that were once hosts. As entrepreneurs, extrinsic motivations are often initial drivers for hosting but intrinsic benefits become integral to the enjoyment of hosting and an important motivator for continued participation. As residents, hosts were mixed in their sense of community but many voiced concerns over STVR impacts on their community. Lastly, many hosts already exhibit elements of sustainable entrepreneurship through listing specific efforts to reduce waste i.e. advertising compost bins to guests or promoting minority-owned businesses to guests

Diversity in the Glucose Transporter-4 Gene (SLC2A4) in Humans Reflects the Action of Natural Selection along the Old-World Primates Evolution

BACKGROUND: Glucose is an important source of energy for living organisms. In vertebrates it is ingested with the diet and transported into the cells by conserved mechanisms and molecules, such as the trans-membrane Glucose Transporters (GLUTs). Members of this family have tissue specific expression, biochemical properties and physiologic functions that together regulate glucose levels and distribution. GLUT4 -coded by SLC2A4 (17p13) is an insulin-sensitive transporter with a critical role in glucose homeostasis and diabetes pathogenesis, preferentially expressed in the adipose tissue, heart muscle and skeletal muscle. We tested the hypothesis that natural selection acted on SLC2A4. METHODOLOGY/PRINCIPAL FINDINGS: We re-sequenced SLC2A4 and genotyped 104 SNPs along a approximately 1 Mb region flanking this gene in 102 ethnically diverse individuals. Across the studied populations (African, European, Asian and Latin-American), all the eight common SNPs are concentrated in the N-terminal region upstream of exon 7 ( approximately 3700 bp), while the C-terminal region downstream of intron 6 ( approximately 2600 bp) harbors only 6 singletons, a pattern that is not compatible with neutrality for this part of the gene. Tests of neutrality based on comparative genomics suggest that: (1) episodes of natural selection (likely a selective sweep) predating the coalescent of human lineages, within the last 25 million years, account for the observed reduced diversity downstream of intron 6 and, (2) the target of natural selection may not be in the SLC2A4 coding sequence. CONCLUSIONS: We propose that the contrast in the pattern of genetic variation between the N-terminal and C-terminal regions are signatures of the action of natural selection and thus follow-up studies should investigate the functional importance of different regions of the SLC2A4 gene

Evaluation of TypeSeq, a Novel High-Throughput, Low-Cost, Next-Generation Sequencing-Based Assay for Detection of 51 Human Papillomavirus Genotypes.

BackgroundHuman papillomaviruses (HPV) cause over 500 000 cervical cancers each year, most of which occur in low-resource settings. Human papillomavirus genotyping is important to study natural history and vaccine efficacy. We evaluated TypeSeq, a novel, next-generation, sequencing-based assay that detects 51 HPV genotypes, in 2 large international epidemiologic studies.MethodsTypeSeq was evaluated in 2804 cervical specimens from the Study to Understand Cervical Cancer Endpoints and Early Determinants (SUCCEED) and in 2357 specimens from the Costa Rica Vaccine Trial (CVT). Positive agreement and risks of precancer for individual genotypes were calculated for TypeSeq in comparison to Linear Array (SUCCEED). In CVT, positive agreement and vaccine efficacy were calculated for TypeSeq and SPF10-LiPA.ResultsWe observed high overall and positive agreement for most genotypes between TypeSeq and Linear Array in SUCCEED and SPF10-LiPA in CVT. There was no significant difference in risk of precancer between TypeSeq and Linear Array in SUCCEED or in estimates of vaccine efficacy between TypeSeq and SPF10-LiPA in CVT.ConclusionsThe agreement of TypeSeq with Linear Array and SPF10-LiPA, 2 well established standards for HPV genotyping, demonstrates its high accuracy. TypeSeq provides high-throughput, affordable HPV genotyping for world-wide studies of cervical precancer risk and of HPV vaccine efficacy

δ-Aminolevulinic Acid Dehydratase Polymorphism and Risk of Brain Tumors in Adults

The enzyme δ -aminolevulinic acid dehydratase (ALAD), which catalyzes the second step of heme synthesis, can be inhibited by several chemicals, including lead, a potential risk factor for brain tumors, particularly meningioma. In this study we examined whether the ALAD G177C polymorphism in the gene coding for ALAD is associated with risk of intracranial tumors of the brain and nervous system. We use data from a case–control study with 782 incident brain tumor cases and 799 controls frequency matched on hospital, age, sex, race/ethnicity, and residential proximity to the hospital. Blood samples were drawn and DNA subsequently sent for genotyping for 73% of subjects. ALAD genotype was determined for 94% of these samples (355 glioma, 151 meningioma, 67 acoustic neuroma, and 505 controls). Having one or more copy of the ALAD2 allele was associated with increased risk for meningioma [odds ratio (OR) = 1.6; 95% confidence interval (CI), 1.0–2.6], with the association appearing stronger in males (OR = 3.5; 95% CI, 1.3–9.2) than in females (OR = 1.2; 95% CI, 0.7–2.2). No increased risk associated with the ALAD2 variant was observed for glioma or acoustic neuroma. These findings suggest that the ALAD2 allele may increase genetic susceptibility to meningioma

cis sequence effects on gene expression

<p>Abstract</p> <p>Background</p> <p>Sequence and transcriptional variability within and between individuals are typically studied independently. The joint analysis of sequence and gene expression variation (genetical genomics) provides insight into the role of linked sequence variation in the regulation of gene expression. We investigated the role of sequence variation in <it>cis </it>on gene expression (<it>cis </it>sequence effects) in a group of genes commonly studied in cancer research in lymphoblastoid cell lines. We estimated the proportion of genes exhibiting <it>cis </it>sequence effects and the proportion of gene expression variation explained by <it>cis </it>sequence effects using three different analytical approaches, and compared our results to the literature.</p> <p>Results</p> <p>We generated gene expression profiling data at N = 697 candidate genes from N = 30 lymphoblastoid cell lines for this study and used available candidate gene resequencing data at N = 552 candidate genes to identify N = 30 candidate genes with sufficient variance in both datasets for the investigation of <it>cis </it>sequence effects. We used two additive models and the haplotype phylogeny scanning approach of Templeton (Tree Scanning) to evaluate association between individual SNPs, all SNPs at a gene, and diplotypes, with log-transformed gene expression. SNPs and diplotypes at eight candidate genes exhibited statistically significant (p < 0.05) association with gene expression. Using the literature as a "gold standard" to compare 14 genes with data from both this study and the literature, we observed 80% and 85% concordance for genes exhibiting and not exhibiting significant <it>cis </it>sequence effects in our study, respectively.</p> <p>Conclusion</p> <p>Based on analysis of our results and the extant literature, one in four genes exhibits significant <it>cis </it>sequence effects, and for these genes, about 30% of gene expression variation is accounted for by <it>cis </it>sequence variation. Despite diverse experimental approaches, the presence or absence of significant <it>cis </it>sequence effects is largely supported by previously published studies.</p

Improved Imputation of Common and Uncommon Single Nucleotide Polymorphisms (SNPs) with a New Reference Set

Statistical imputation of genotype data is an important technique for analysis of genome-wide association studies (GWAS). We have built a reference dataset to improve imputation accuracy for studies of individuals of primarily European descent using genotype data from the Hap1, Omni1, and Omni2.5 human SNP arrays (Illumina). Our dataset contains 2.5-3.1 million variants for 930 European, 157 Asian, and 162 African/African-American individuals. Imputation accuracy of European data from Hap660 or OmniExpress array content, measured by the proportion of variants imputed with R^2^&#x3e;0.8, improved by 34%, 23% and 12% for variants with MAF of 3%, 5% and 10%, respectively, compared to imputation using publicly available data from 1,000 Genomes and International HapMap projects. The improved accuracy with the use of the new dataset could increase the power for GWAS by as much as 8% relative to genotyping all variants. This reference dataset is available to the scientific community through the NCBI dbGaP portal. Future versions will include additional genotype data as well as non-European populations

Viral coinfection analysis using a MinHash toolkit

Abstract: Background: Human papillomavirus (HPV) is a common sexually transmitted infection associated with cervical cancer that frequently occurs as a coinfection of types and subtypes. Highly similar sublineages that show over 100-fold differences in cancer risk are not distinguishable in coinfections with current typing methods. Results: We describe an efficient set of computational tools, rkmh, for analyzing complex mixed infections of related viruses based on sequence data. rkmh makes extensive use of MinHash similarity measures, and includes utilities for removing host DNA and classifying reads by type, lineage, and sublineage. We show that rkmh is capable of assigning reads to their HPV type as well as HPV16 lineage and sublineages. Conclusions: Accurate read classification enables estimates of percent composition when there are multiple infecting lineages or sublineages. While we demonstrate rkmh for HPV with multiple sequencing technologies, it is also applicable to other mixtures of related sequences

Common single nucleotide polymorphisms in genes related to immune function and risk of papillary thyroid cancer

Accumulating evidence suggests that alterations in immune function may be important in the etiology of papillary thyroid cancer (PTC). To identify genetic markers in immune-related pathways, we evaluated 3,985 tag single nucleotide polymorphisms (SNPs) in 230 candidate gene regions (adhesion-extravasation-migration, arachidonic acid metabolism/eicosanoid signaling, complement and coagulation cascade, cytokine signaling, innate pathogen detection and antimicrobials, leukocyte signaling, TNF/NF-kB pathway or other) in a case-control study of 344 PTC cases and 452 controls. We used logistic regression models to estimate odds ratios (OR) and calculate one degree of freedom P values of linear trend (P(SNP-trend)) for the association between genotype (common homozygous, heterozygous, variant homozygous) and risk of PTC. To correct for multiple comparisons, we applied the false discovery rate method (FDR). Gene region- and pathway-level associations (P(Region) and P(Pathway)) were assessed by combining individual P(SNP-trend) values using the adaptive rank truncated product method. Two SNPs (rs6115, rs6112) in the SERPINA5 gene were significantly associated with risk of PTC (P(SNP-FDR)/P(SNP-trend) = 0.02/6×10(−6) and P(SNP-FDR)/P(SNP-trend) = 0.04/2×10(−5), respectively). These associations were independent of a history of autoimmune thyroiditis (OR = 6.4; 95% confidence interval: 3.0–13.4). At the gene region level, SERPINA5 was suggestively associated with risk of PTC (P(Region-FDR)/P(Region = )0.07/0.0003). Overall, the complement and coagulation cascade pathway was the most significant pathway (P(Pathway) = 0.02) associated with PTC risk largely due to the strong effect of SERPINA5. Our results require replication but suggest that the SERPINA5 gene, which codes for the protein C inhibitor involved in many biological processes including inflammation, may be a new susceptibility locus for PTC