Extracellular vesicle budding is inhibited by redundant regulators of TAT-5 flippase localization and phospholipid asymmetry.

Cells release extracellular vesicles (EVs) that mediate intercellular communication and repair damaged membranes. Despite the pleiotropic functions of EVs in vitro, their in vivo function is debated, largely because it is unclear how to induce or inhibit their formation. In particular, the mechanisms of EV release by plasma membrane budding or ectocytosis are poorly understood. We previously showed that TAT-5 phospholipid flippase activity maintains the asymmetric localization of the lipid phosphatidylethanolamine (PE) in the plasma membrane and inhibits EV budding by ectocytosis in Caenorhabditis elegans However, no proteins that inhibit ectocytosis upstream of TAT-5 were known. Here, we identify TAT-5 regulators associated with retrograde endosomal recycling: PI3Kinase VPS-34, Beclin1 homolog BEC-1, DnaJ protein RME-8, and the uncharacterized Dopey homolog PAD-1. PI3Kinase, RME-8, and semiredundant sorting nexins are required for the plasma membrane localization of TAT-5, which is important to maintain PE asymmetry and inhibit EV release. PAD-1 does not directly regulate TAT-5 localization, but is required for the lipid flipping activity of TAT-5. PAD-1 also has roles in endosomal trafficking with the GEF-like protein MON-2, which regulates PE asymmetry and EV release redundantly with sorting nexins independent of the core retromer. Thus, in addition to uncovering redundant intracellular trafficking pathways, our study identifies additional proteins that regulate EV release. This work pinpoints TAT-5 and PE as key regulators of plasma membrane budding, further supporting the model that PE externalization drives ectocytosis.

Power to detect risk alleles using genome-wide tag SNP panels.

Advances in high-throughput genotyping and the International HapMap Project have enabled association studies at the whole-genome level. We have constructed whole-genome genotyping panels of over 550,000 (HumanHap550) and 650,000 (HumanHap650Y) SNP loci by choosing tag SNPs from all populations genotyped by the International HapMap Project. These panels also contain additional SNP content in regions that have historically been overrepresented in diseases, such as nonsynonymous sites, the MHC region, copy number variant regions and mitochondrial DNA. We estimate that the tag SNP loci in these panels cover the majority of all common variation in the genome as measured by coverage of both all common HapMap SNPs and an independent set of SNPs derived from complete resequencing of genes obtained from SeattleSNPs. We also estimate that, given a sample size of 1,000 cases and 1,000 controls, these panels have the power to detect single disease loci of moderate risk (lambda approximately 1.8-2.0). Relative risks as low as lambda approximately 1.1-1.3 can be detected using 10,000 cases and 10,000 controls depending on the sample population and disease model. If multiple loci are involved, the power increases significantly to detect at least one locus such that relative risks 20%-35% lower can be detected with 80% power if between two and four independent loci are involved. Although our SNP selection was based on HapMap data, which is a subset of all common SNPs, these panels effectively capture the majority of all common variation and provide high power to detect risk alleles that are not represented in the HapMap data.

Cis sequence effects on gene expression.

BACKGROUND: 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 cis on gene expression (cis sequence effects) in a group of genes commonly studied in cancer research in lymphoblastoid cell lines. We estimated the proportion of genes exhibiting cis sequence effects and the proportion of gene expression variation explained by cis sequence effects using three different analytical approaches, and compared our results to the literature. RESULTS: 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 cis 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 cis sequence effects in our study, respectively. CONCLUSION: Based on analysis of our results and the extant literature, one in four genes exhibits significant cis sequence effects, and for these genes, about 30% of gene expression variation is accounted for by cis sequence variation. Despite diverse experimental approaches, the presence or absence of significant cis sequence effects is largely supported by previously published studies.

Whole-genome genotyping.

We have developed an array-based whole-genome genotyping (WGG) assay (Infinium) using our BeadChip platform that effectively enables unlimited multiplexing and unconstrained single nucleotide polymorphism (SNP) selection. A single tube whole-genome amplification reaction is used to amplify the genome, and loci of interest are captured by specific hybridization of amplified gDNA to 50-mer probe arrays. After target capture, SNPs are genotyped on the array by a primer extension reaction in the presence of hapten-labeled nucleotides. The resultant signal is amplified during staining and the array is read out on a high-resolution confocal scanner. We have employed our high-density BeadChips supporting up to 288,000 bead types to create an array that can query over 100,000 SNPs using the Infinium assay. In addition, we have developed an automated BeadChip processing platform using Tecan's GenePaint slide processing system. Hybridization, washing, array-based primer extension, and staining are performed directly in Tecan's capillary gap Te-Flow chambers. This automation process increases assay robustness and throughput greatly while enabling laboratory information management system control of sample tracking.

Whole-genome genotyping of haplotype tag single nucleotide polymorphisms.

The International HapMap Consortium recently completed genotyping over 3.8 million single nucleotide polymorphisms (SNPs) in three major populations, and the results of studying patterns of linkage disequilibrium indicate that characterization of 300,000-500,000 tag SNPs is sufficient to provide good genomic coverage for linkage-disequilibrium-based association studies in many populations. These whole-genome association studies will be used to dissect the genetics of complex diseases and pharmacogenomic drug responses. As such, the development of a cost-effective genotyping platform that can assay hundred of thousands of SNPs across thousands of samples is essential. In this review, we describe the development of a whole-genome genotyping (WGG) assay that enables unconstrained SNP selection and effectively unlimited multiplexing from a single sample preparation. The development of WGG in concert with high-density BeadChips has enabled the creation of three different high-density SNP genotyping BeadChips: the Sentrix Human-1 Genotyping BeadChip containing over 109,000 exon-centric SNPs; the HumanHap300 BeadChip containing over 317,000 tag SNPs, and the HumanHap550 Beadchip containing over 550,000 tag SNPs.

A novel, high-performance random array platform for quantitative gene expression profiling.

We have developed a new microarray technology for quantitative gene-expression profiling on the basis of randomly assembled arrays of beads. Each bead carries a gene-specific probe sequence. There are multiple copies of each sequence-specific bead in an array, which contributes to measurement precision and reliability. We optimized the system for specific and sensitive analysis of mammalian RNA, and using RNA controls of defined concentration, obtained the following estimates of system performance: specificity of 1:250,000 in mammalian poly(A(+)) mRNA; limit of detection 0.13 pM; dynamic range 3.2 logs; and sufficient precision to detect 1.3-fold differences with 95% confidence within the dynamic range. Measurements of expression differences between human brain and liver were validated by concordance with quantitative real-time PCR (R(2) = 0.98 for log-transformed ratios, and slope of the best-fit line = 1.04, for 20 genes). Quantitative performance was further verified using a mouse B- and T-cell model system. We found published reports of B- or T-cell-specific expression for 42 of 59 genes that showed the greatest differential expression between B- and T-cells in our system. All of the literature observations were concordant with our results. Our experiments were carried out on a 96-array matrix system that requires only 100 ng of input RNA and uses standard microtiter plates to process samples in parallel. Our technology has advantages for analyzing multiple samples, is scalable to all known genes in a genome, and is flexible, allowing the use of standard or custom probes in an array.