Additional file 1: of Weighted-SAMGSR: combining significance analysis of microarray-gene set reduction algorithm with pathway topology-based weights to select relevant genes

R codes for the weighted-SAMGSR algorithm. (DOCX 76 kb

Additional file 1: of A simulation study to quantify the impacts of exposure measurement error on air pollution health risk estimates in copollutant time-series models

Supplemental materials including supplemental text, figures, and tables, are available as an additional file. (PDF 392 kb

Additional file 1: of A novel ATAC-seq approach reveals lineage-specific reinforcement of the open chromatin landscape via cooperation between BAF and p63

Includes the supplementary Figures S1–4. Figure S1. BAF is essential for epidermal gene induction. (a) Quantitative RT-PCR analysis demonstrating the knockdown efficiency of BRG1/BRM siRNAs and the suppression of differentiation gene expression in BAF loss compared to control. (b) GO analysis of the significant changed genes (fold change > 3, FDR < 0.01) with BAF knockdown in RNA-seq. (c) Western blot analysis showing the time course of 4-day differentiation induction in primary human keratinocytes, comparing BRG1/BRM loss with control. BRG1/BRM siRNA efficiently knocked down BRG1 and BRM protein levels. The induction of Keratin 1 is significantly impaired with BAF loss, although no significant changes were detected with p63 and p53 protein level relative to tubulin loading control. (d–f) Distribution of total ATAC-seq peaks, and the BAF-dependent ATAC-seq peaks relative to gene promoter, exon, intron and distal regulatory regions. Figure S2. BAF maintains open chromatin regions with p63 binding sites. (a) Scatter plot demonstrating correlation between BAF binding and open chromatin across the genome. (b) RNA expression levels (RPKM) of p53 family transcription factors in human keratinocytes. (c) Pie chart demonstrating the percentage of p63 motif sites at p63 binding sites that became inaccessible with BAF knockdown. (d) RNA expression levels of all expressed TFs in keratinocytes. Gray dots indicate the expression levels of 809 TFs (RPKM > 1 in differentiating human keratinocytes) listed in GO. Representative TFs known to be functional in epidermal differentiation along with CTCF are highlighted in brown and red. (e) ATAC-seq accessibility in KLF4 motif sites in KLF4 binding sites comparing control vs BAF loss conditions. (f) Heatmap showing the fold changes of the shared 236 genes (fold change > 3, FDR < 0.01) controlled by both BAF and p63. (g) Representative RNA-seq data tracks of BAFi, p63i, and CTRLi replicates. Figure S3. BAF loss does not affect nucleosome positioning or genome accessibility at CTCF binding regions. (a) ATAC-seq fragment size distribution. Gray shaded area represents nucleosome-free fragments (<100 bp), and blue shaded area represents mononucleosome fragments (180–247 bp). Schematic illustration of these ATAC-seq fragments is shown on the right. (b, c) V-plot analysis demonstrating the nucleosome positioning at CTCF motif regions comparing control versus BAF loss. (d) Average diagram of nucleosome-free ATAC-seq fragments at CTCF motif regions comparing control and BAF loss. (e) Average diagram of mononucleosome ATAC-seq fragments at CTCF motif regions comparing control and BAF loss. (f) Average diagram of predicted nucleosome binding probability based on DNA sequences using same number of shuffled genomic regions as in p63 motif nucleosome probability analysis. Figure S4. BAF loss impairs p63 binding to its target sites. (a, b) Single nucleotide ATAC accessibility analysis with 1-bp resolution at p63 and CTCF motif regions in their ChIP-seq binding sites, comparing control and BAF loss. (c) Summit-centered heatmap comparing p63 ChIP-seq peaks in control and BAF loss. (d, e) Average diagram of p63 ChIP-seq signal enrichment in the peaks that are overlapped or unique in control. (f) Average diagram of BAF ChIP-seq signal at CTCF sites comparing p63 loss with control conditions. (PDF 3349 kb

Additional file 2: Table S1. of A novel ATAC-seq approach reveals lineage-specific reinforcement of the open chromatin landscape via cooperation between BAF and p63

Genes changed >3-fold with BRG1/BRM knockdown. Table S2 Shared genes controlled by both BAF and p63 with fold change > 3. Table S3 Sequencing depth of the ATAC-seq, RNA-seq, and ChIP-seq data generated for this study. (XLSX 78 kb

A <i>cis</i>-regulatory antisense RNA represses translation in <i>Vibrio cholerae</i> through extensive complementarity and proximity to the target locus

<div><p>As with all facultative pathogens, <i>Vibrio cholerae</i> must optimize its cellular processes to adapt to different environments with varying carbon sources and to environmental stresses. More specifically, in order to metabolize mannitol, <i>V. cholerae</i> must regulate the synthesis of MtlA, a mannitol transporter protein produced exclusively in the presence of mannitol. We previously showed that a <i>cis</i>-acting small RNA (sRNA) expressed by <i>V. cholerae,</i> MtlS, appears to post-transcriptionally downregulate the expression of <i>mtlA</i> and is produced in the absence of mannitol. We hypothesized that since it is complementary to the 5′ untranslated region (UTR) of <i>mtlA</i> mRNA, MtlS may affect synthesis of MtlA by forming an <i>mtlA</i>-MtlS complex that blocks translation of the mRNA through occlusion of its ribosome binding site. To test this hypothesis, we used in vitro translation assays in order to examine the role MtlS plays in <i>mtlA</i> regulation and found that MtlS is sufficient to suppress translation of transcripts harboring the 5′ UTR of <i>mtlA</i>. However, in a cellular context, the 5′ UTR of <i>mtlA</i> is not sufficient for targeted repression by endogenous MtlS; additional segments from the coding region of <i>mtlA</i> play a role in the ability of the sRNA to regulate translation of <i>mtlA</i> mRNA. Additionally, proximity of transcription sites between the sRNA and mRNA significantly affects the efficacy of MtlS.</p></div

Additional file 1: Figure S1. of Ozone and childhood respiratory disease in three US cities: evaluation of effect measure modification by neighborhood socioeconomic status using a Bayesian hierarchical approach

Distribution and summary statistics for indicators of neighborhood SES in each city. Table S1. Number of ED visits and ZCTAs in high and low SES neighborhoods. Figure S2. Effect modification of ozone-respiratory disease by continuous values of neighborhood SES in city-specific analyses (PDF 1175 kb

Additional file 1: Figure S1. of Single-cell epigenomic variability reveals functional cancer heterogeneity

Molecular characteristics of identified subpopulations. a Left: QRT-PCR of GATA1 and GATA2 in K562 cells measured relative to ACTIN. Error bars represent standard error. Right: Representative FACS analysis of K562 cells stained for GATA1 and GATA2. b Histograms showing expression (fluorescent intensity) of CD44 (light blue) and CD52 (dark blue) in K562 cells. c Dot plots displaying the gating strategy for sorting CD24hi and CD24lo expressing K562 cells. d Expression analysis of GATA1 and GATA2 in CD24 sorted K562 cells measured by qRT-PCR relative to ACTIN. *P value <0.05 (t-test), error bars represent standard error. e Representative FACS analysis of CD24hi and CD24lo sorted K562 cells, stained after sort for pJUN. Mean fluorescent intensity (MFI) was 152 (high), and 137 (low). (PDF 616 kb

Genetic Evidence of Contemporary Dispersal of the Intermediate Snail Host of <i>Schistosoma japonicum</i>: Movement of an NTD Host Is Facilitated by Land Use and Landscape Connectivity

<div><p>Background</p><p>While the dispersal of hosts and vectors—through active or passive movement—is known to facilitate the spread and re-emergence of certain infectious diseases, little is known about the movement ecology of <i>Oncomelania</i> spp., intermediate snail host of the parasite <i>Schistosoma japonicum</i>, and its consequences for the spread of schistosomiasis in East and Southeast Asia. In China, despite intense control programs aimed at preventing schistosomiasis transmission, there is evidence in recent years of re-emergence and persistence of infection in some areas, as well as an increase in the spatial extent of the snail host. A quantitative understanding of the dispersal characteristics of the intermediate host can provide new insights into the spatial dynamics of transmission, and can assist public health officials in limiting the geographic spread of infection.</p><p>Methodology/Principal findings</p><p><i>Oncomelania hupensis robertsoni</i> snails (n = 833) were sampled from 29 sites in Sichuan, China, genotyped, and analyzed using Bayesian assignment to estimate the rate of recent snail migration across sites. Landscape connectivity between each site pair was estimated using the geographic distance distributions derived from nine environmental models: Euclidean, topography, incline, wetness, land use, watershed, stream use, streams and channels, and stream velocity. Among sites, 14.4% to 32.8% of sampled snails were identified as recent migrants, with 20 sites comprising >20% migrants. Migration rates were generally low between sites, but at 8 sites, over 10% of the overall host population originated from one proximal site. Greater landscape connectivity was significantly associated with increased odds of migration, with the minimum path distance (as opposed to median or first quartile) emerging as the strongest predictor across all environmental models. Models accounting for land use explained the largest proportion of the variance in migration rates between sites. A greater number of irrigation channels leading into a site was associated with an increase in the site’s propensity to both attract and retain snails.</p><p>Conclusions/Significance</p><p>Our findings have important implications for controlling the geographic spread of schistosomiasis in China, through improved understanding of the dispersal capacity of the parasite’s intermediate host.</p></div

Map of study sites showing proportion of recent migrant individuals (denoted by symbol size) estimated by BayesAss at each site, propensity of the site to attract or retain migrants (denoted by symbol color; note two sites with split color symbology indicate simultaneous high attractivity and low/high retentivity), and inter-village migration rates (denoted by arrows).

<p>To improve clarity, inter-village migration rates less than 0.02 are not shown.</p

Relative coefficient of determinations from random-effects models for migration rate and geographic distance restricting sites to within specified distance, in meters.

<p>Highlighted boxes indicate superiority of fit, based on relative R², where Euclidean model is used as the reference model. Higher numbers of R² indicate superiority of fit.</p