The BMP signaling gradient is interpreted through concentration thresholds in dorsal-ventral axial patterning.

Bone Morphogenetic Protein (BMP) patterns the dorsal-ventral (DV) embryonic axis in all vertebrates, but it is unknown how cells along the DV axis interpret and translate the gradient of BMP signaling into differential gene activation that will give rise to distinct cell fates. To determine the mechanism of BMP morphogen interpretation in the zebrafish gastrula, we identified 57 genes that are directly activated by BMP signaling. By using Seurat analysis of single-cell RNA sequencing (scRNA-seq) data, we found that these genes are expressed in at least 3 distinct DV domains of the embryo. We distinguished between 3 models of BMP signal interpretation in which cells activate distinct gene expression through interpretation of thresholds of (1) the BMP signaling gradient slope; (2) the BMP signal duration; or (3) the level of BMP signal activation. We tested these 3 models using quantitative measurements of phosphorylated Smad5 (pSmad5) and by examining the spatial relationship between BMP signaling and activation of different target genes at single-cell resolution across the embryo. We found that BMP signaling gradient slope or BMP exposure duration did not account for the differential target gene expression domains. Instead, we show that cells respond to 3 distinct levels of BMP signaling activity to activate and position target gene expression. Together, we demonstrate that distinct pSmad5 threshold levels activate spatially distinct target genes to pattern the DV axis.

A meta-analysis of genome-wide association studies of asthma in Puerto Ricans.

Puerto Ricans are disproportionately affected with asthma in the USA. In this study, we aim to identify genetic variants that confer susceptibility to asthma in Puerto Ricans.We conducted a meta-analysis of genome-wide association studies (GWAS) of asthma in Puerto Ricans, including participants from: the Genetics of Asthma in Latino Americans (GALA) I-II, the Hartford-Puerto Rico Study and the Hispanic Community Health Study. Moreover, we examined whether susceptibility loci identified in previous meta-analyses of GWAS are associated with asthma in Puerto Ricans.The only locus to achieve genome-wide significance was chromosome 17q21, as evidenced by our top single nucleotide polymorphism (SNP), rs907092 (OR 0.71, p=1.2×10-12) at IKZF3 Similar to results in non-Puerto Ricans, SNPs in genes in the same linkage disequilibrium block as IKZF3 (e.g. ZPBP2, ORMDL3 and GSDMB) were significantly associated with asthma in Puerto Ricans. With regard to results from a meta-analysis in Europeans, we replicated findings for rs2305480 at GSDMB, but not for SNPs in any other genes. On the other hand, we replicated results from a meta-analysis of North American populations for SNPs at IL1RL1, TSLP and GSDMB but not for IL33Our findings suggest that common variants on chromosome 17q21 have the greatest effects on asthma in Puerto Ricans.

LAIT: a local ancestry inference toolkit.

BACKGROUND: Inferring local ancestry in individuals of mixed ancestry has many applications, most notably in identifying disease-susceptible loci that vary among different ethnic groups. Many software packages are available for inferring local ancestry in admixed individuals. However, most of these existing software packages require specific formatted input files and generate output files in various types, yielding practical inconvenience. RESULTS: We developed a tool set, Local Ancestry Inference Toolkit (LAIT), which can convert standardized files into software-specific input file formats as well as standardize and summarize inference results for four popular local ancestry inference software: HAPMIX, LAMP, LAMP-LD, and ELAI. We tested LAIT using both simulated and real data sets and demonstrated that LAIT provides convenience to run multiple local ancestry inference software. In addition, we evaluated the performance of local ancestry software among different supported software packages, mainly focusing on inference accuracy and computational resources used. CONCLUSION: We provided a toolkit to facilitate the use of local ancestry inference software, especially for users with limited bioinformatics background.

iStable: off-the-shelf predictor integration for predicting protein stability changes.

BACKGROUND: Mutation of a single amino acid residue can cause changes in a protein, which could then lead to a loss of protein function. Predicting the protein stability changes can provide several possible candidates for the novel protein designing. Although many prediction tools are available, the conflicting prediction results from different tools could cause confusion to users. RESULTS: We proposed an integrated predictor, iStable, with grid computing architecture constructed by using sequence information and prediction results from different element predictors. In the learning model, several machine learning methods were evaluated and adopted the support vector machine as an integrator, while not just choosing the majority answer given by element predictors. Furthermore, the role of the sequence information played was analyzed in our model, and an 11-window size was determined. On the other hand, iStable is available with two different input types: structural and sequential. After training and cross-validation, iStable has better performance than all of the element predictors on several datasets. Under different classifications and conditions for validation, this study has also shown better overall performance in different types of secondary structures, relative solvent accessibility circumstances, protein memberships in different superfamilies, and experimental conditions. CONCLUSIONS: The trained and validated version of iStable provides an accurate approach for prediction of protein stability changes. iStable is freely available online at: http://predictor.nchu.edu.tw/iStable.

Dimeric p53 Mutant Elicits Unique Tumor-Suppressive Activities through an Altered Metabolic Program.

Cancer-related alterations of the p53 tetramerization domain (TD) abrogate wild-type (WT) p53 function. They result in a protein that preferentially forms monomers or dimers, which are also normal p53 states under basal cellular conditions. However, their physiologic relevance is not well understood. We have established in vivo models for monomeric and dimeric p53, which model Li-Fraumeni syndrome patients with germline p53 TD alterations. p53 monomers are inactive forms of the protein. Unexpectedly, p53 dimers conferred some tumor suppression that is not mediated by canonical WT p53 activities. p53 dimers upregulate the PPAR pathway. These activities are associated with lower prevalence of thymic lymphomas and increased CD8+ T-cell differentiation. Lymphomas derived from dimeric p53 mice show cooperating alterations in the PPAR pathway, further implicating a role for these activities in tumor suppression. Our data reveal novel functions for p53 dimers and support the exploration of PPAR agonists as therapies. SIGNIFICANCE: New mouse models with TP53R342P (monomer) or TP53A347D (dimer) mutations mimic Li-Fraumeni syndrome. Although p53 monomers lack function, p53 dimers conferred noncanonical tumor-suppressive activities. We describe novel activities for p53 dimers facilitated by PPARs and propose these are "basal" p53 activities. See related commentary by Stieg et al., p. 1046. See related article by Choe et al., p. 1250. This article is highlighted in the In This Issue feature, p. 1027.

Mapping the Lineage Relationship between CXCR5+ and CXCR5- CD4+ T Cells in HIV-Infected Human Lymph Nodes.

CXCR5 is a key marker of follicular helper T (TFH) cells. Using primary lymph nodes (LNs) from HIV-infected patients, we identified a population of CXCR5- CD4+ T cells with TFH-cell-like features. This CXCR5- subset becomes expanded in severe HIV infection and is characterized by the upregulation of activation markers and high PD-1 and ICOS surface expression. Integrated analyses on the phenotypic heterogeneity, functional capacity, T cell receptor (TCR) repertoire, transcriptional profile, and epigenetic state of CXCR5-PD-1+ICOS+ T cells revealed a shared clonal relationship with TFH cells. CXCR5-PD-1+ICOS+ T cells retained a poised state for CXCR5 expression and exhibited a migratory transcriptional program. TCR sequence overlap revealed a contribution of LN-derived CXCR5-PD-1+ICOS+ T cells to circulating CXCR5- CD4+ T cells with B cell help function. These data link LN pathology to circulating T cells and expand the current understanding on the diversity of T cells that regulate B cell responses during chronic inflammation.

A thrifty variant in CREBRF strongly influences body mass index in Samoans.

Samoans are a unique founder population with a high prevalence of obesity, making them well suited for identifying new genetic contributors to obesity. We conducted a genome-wide association study (GWAS) in 3,072 Samoans, discovered a variant, rs12513649, strongly associated with body mass index (BMI) (P = 5.3 × 10(-14)), and replicated the association in 2,102 additional Samoans (P = 1.2 × 10(-9)). Targeted sequencing identified a strongly associated missense variant, rs373863828 (p.Arg457Gln), in CREBRF (meta P = 1.4 × 10(-20)). Although this variant is extremely rare in other populations, it is common in Samoans (frequency of 0.259), with an effect size much larger than that of any other known common BMI risk variant (1.36-1.45 kg/m(2) per copy of the risk-associated allele). In comparison to wild-type CREBRF, the Arg457Gln variant when overexpressed selectively decreased energy use and increased fat storage in an adipocyte cell model. These data, in combination with evidence of positive selection of the allele encoding p.Arg457Gln, support a 'thrifty' variant hypothesis as a factor in human obesity.

A systematic study of normalization methods for Infinium 450K methylation data using whole-genome bisulfite sequencing data.

DNA methylation plays an important role in disease etiology. The Illumina Infinium HumanMethylation450 (450K) BeadChip is a widely used platform in large-scale epidemiologic studies. This platform can efficiently and simultaneously measure methylation levels at ∼480,000 CpG sites in the human genome in multiple study samples. Due to the intrinsic chip design of 2 types of chemistry probes, data normalization or preprocessing is a critical step to consider before data analysis. To date, numerous methods and pipelines have been developed for this purpose, and some studies have been conducted to evaluate different methods. However, validation studies have often been limited to a small number of CpG sites to reduce the variability in technical replicates. In this study, we measured methylation on a set of samples using both whole-genome bisulfite sequencing (WGBS) and 450K chips. We used WGBS data as a gold standard of true methylation states in cells to compare the performances of 8 normalization methods for 450K data on a genome-wide scale. Analyses on our dataset indicate that the most effective methods are peak-based correction (PBC) and quantile normalization plus ß-mixture quantile normalization (QN.BMIQ). To our knowledge, this is the first study to systematically compare existing normalization methods for Illumina 450K data using novel WGBS data. Our results provide a benchmark reference for the analysis of DNA methylation chip data, particularly in white blood cells.

Expression quantitative trait loci (eQTL) mapping in Puerto Rican children.

BACKGROUND: Expression quantitative trait loci (eQTL) have been identified using tissue or cell samples from diverse human populations, thus enhancing our understanding of regulation of gene expression. However, few studies have attempted to identify eQTL in racially admixed populations such as Hispanics. METHODS: We performed a systematic eQTL study to identify regulatory variants of gene expression in whole blood from 121 Puerto Rican children with (n = 63) and without (n = 58) asthma. Genome-wide genotyping was conducted using the Illumina Omni2.5M Bead Chip, and gene expression was assessed using the Illumina HT-12 microarray. After completing quality control, we performed a pair-wise genome analysis of ~15 K transcripts and ~1.3 M SNPs for both local and distal effects. This analysis was conducted under a regression framework adjusting for age, gender and principal components derived from both genotypic and mRNA data. We used a false discovery rate (FDR) approach to identify significant eQTL signals, which were next compared to top eQTL signals from existing eQTL databases. We then performed a pathway analysis for our top genes. RESULTS: We identified 36,720 local pairs in 3,391 unique genes and 1,851 distal pairs in 446 unique genes at FDR <0.05, corresponding to unadjusted P values lower than 1.5x10-4 and 4.5x10-9, respectively. A significant proportion of genes identified in our study overlapped with those identified in previous studies. We also found an enrichment of disease-related genes in our eQTL list. CONCLUSIONS: We present results from the first eQTL study in Puerto Rican children, who are members of a unique Hispanic cohort disproportionately affected with asthma, prematurity, obesity and other common diseases. Our study confirmed eQTL signals identified in other ethnic groups, while also detecting additional eQTLs unique to our study population. The identified eQTLs will help prioritize findings from future genome-wide association studies in Puerto Ricans.