LoQAtE--Localization and Quantitation ATlas of the yeast proteomE. A new tool for multiparametric dissection of single-protein behavior in response to biological perturbations in yeast.

Living organisms change their proteome dramatically to sustain a stable internal milieu in fluctuating environments. To study the dynamics of proteins during stress, we measured the localization and abundance of the Saccharomyces cerevisiae proteome under various growth conditions and genetic backgrounds using the GFP collection. We created a database (DB) called 'LoQAtE' (Localizaiton and Quantitation Atlas of the yeast proteomE), available online at http://www.weizmann.ac.il/molgen/loqate/, to provide easy access to these data. Using LoQAtE DB, users can get a profile of changes for proteins of interest as well as querying advanced intersections by either abundance changes, primary localization or localization shifts over the tested conditions. Currently, the DB hosts information on 5330 yeast proteins under three external perturbations (DTT, H₂O₂ and nitrogen starvation) and two genetic mutations [in the chaperonin containing TCP1 (CCT) complex and in the proteasome]. Additional conditions will be uploaded regularly. The data demonstrate hundreds of localization and abundance changes, many of which were not detected at the level of mRNA. LoQAtE is designed to allow easy navigation for non-experts in high-content microscopy and data are available for download. These data should open up new perspectives on the significant role of proteins while combating external and internal fluctuations

Back to the family: a renewed approach to rare variant studies

A report on the 62nd Annual Meeting of the American Society of Human Genetics, San Francisco, California, USA, 6-10 November 2012

A reference haplotype panel for genome-wide imputation of short tandem repeats.

Short tandem repeats (STRs) are involved in dozens of Mendelian disorders and have been implicated in complex traits. However, genotyping arrays used in genome-wide association studies focus on single nucleotide polymorphisms (SNPs) and do not readily allow identification of STR associations. We leverage next-generation sequencing (NGS) from 479 families to create a SNP + STR reference haplotype panel. Our panel enables imputing STR genotypes into SNP array data when NGS is not available for directly genotyping STRs. Imputed genotypes achieve mean concordance of 97% with observed genotypes in an external dataset compared to 71% expected under a naive model. Performance varies widely across STRs, with near perfect concordance at bi-allelic STRs vs. 70% at highly polymorphic repeats. Imputation increases power over individual SNPs to detect STR associations with gene expression. Imputing STRs into existing SNP datasets will enable the first large-scale STR association studies across a range of complex traits

The impact of short tandem repeat variation on gene expression.

Short tandem repeats (STRs) have been implicated in a variety of complex traits in humans. However, genome-wide studies of the effects of STRs on gene expression thus far have had limited power to detect associations and provide insights into putative mechanisms. Here, we leverage whole-genome sequencing and expression data for 17 tissues from the Genotype-Tissue Expression Project to identify more than 28,000 STRs for which repeat number is associated with expression of nearby genes (eSTRs). We use fine-mapping to quantify the probability that each eSTR is causal and characterize the top 1,400 fine-mapped eSTRs. We identify hundreds of eSTRs linked with published genome-wide association study signals and implicate specific eSTRs in complex traits, including height, schizophrenia, inflammatory bowel disease and intelligence. Overall, our results support the hypothesis that eSTRs contribute to a range of human phenotypes, and our data should serve as a valuable resource for future studies of complex traits

WebSTR: a population-wide database of short tandem repeat variation in humans.

Short tandem repeats (STRs) are consecutive repetitions of one to six nucleotide motifs. They are hypervariable due to the high prevalence of repeat unit insertions or deletions primarily caused by polymerase slippage during replication. Genetic variation at STRs has been shown to influence a range of traits in humans, including gene expression, cancer risk, and autism. Until recently STRs have been poorly studied since they pose significant challenges to bioinformatics analyses. Moreover, genome-wide analysis of STR variation in population-scale cohorts requires large amounts of data and computational resources. However, the recent advent of genome-wide analysis tools has resulted in multiple large genome-wide datasets of STR variation spanning nearly two million genomic loci in thousands of individuals from diverse populations. Here we present WebSTR, a database of genetic variation and other characteristics of genome-wide STRs across human populations. WebSTR is based on reference panels of more than 1.7 million human STRs created with state of the art repeat annotation methods and can easily be extended to include additional cohorts or species. It currently contains data based on STR genotypes for individuals from the 1000 Genomes Project, H3Africa, the Genotype-Tissue Expression (GTEx) Project and colorectal cancer patients from the TCGA dataset. WebSTR is implemented as a relational database with programmatic access available through an API and a web portal for browsing data. The web portal is publicly available at http://webstr.ucsd.edu

The landscape of human STR variation

Short tandem repeats are among the most polymorphic loci in the human genome. These loci play a role in the etiology of a range of genetic diseases and have been frequently utilized in forensics, population genetics, and genetic genealogy. Despite this plethora of applications, little is known about the variation of most STRs in the human population. Here, we report the largest-scale analysis of human STR variation to date. We collected information for nearly 700,000 STR loci across more than 1000 individuals in Phase 1 of the 1000 Genomes Project. Extensive quality controls show that reliable allelic spectra can be obtained for close to 90% of the STR loci in the genome. We utilize this call set to analyze determinants of STR variation, assess the human reference genome’s representation of STR alleles, find STR loci with common loss-of-function alleles, and obtain initial estimates of the linkage disequilibrium between STRs and common SNPs. Overall, these analyses further elucidate the scale of genetic variation beyond classical point mutations.American Society for Engineering Education. National Defense Science and Engineering Graduate Fellowshi

OTX2 Duplication Is Implicated in Hemifacial Microsomia

Hemifacial microsomia (HFM) is the second most common facial anomaly after cleft lip and palate. The phenotype is highly variable and most cases are sporadic. We investigated the disorder in a large pedigree with five affected individuals spanning eight meioses. Whole-exome sequencing results indicated the absence of a pathogenic coding point mutation. A genome-wide survey of segmental variations identified a 1.3 Mb duplication of chromosome 14q22.3 in all affected individuals that was absent in more than 1000 chromosomes of ethnically matched controls. The duplication was absent in seven additional sporadic HFM cases, which is consistent with the known heterogeneity of the disorder. To find the critical gene in the duplicated region, we analyzed signatures of human craniofacial disease networks, mouse expression data, and predictions of dosage sensitivity. All of these approaches implicated OTX2 as the most likely causal gene. Moreover, OTX2 is a known oncogenic driver in medulloblastoma, a condition that was diagnosed in the proband during the course of the study. Our findings suggest a role for OTX2 dosage sensitivity in human craniofacial development and raise the possibility of a shared etiology between a subtype of hemifacial microsomia and medulloblastoma

Mechanisms underlying divergent responses of genetically distinct macrophages to IL-4

Mechanisms by which noncoding genetic variation influences gene expression remain only partially understood but are considered to be major determinants of phenotypic diversity and disease risk. Here, we evaluated effects of >50 million single-nucleotide polymorphisms and short insertions/deletions provided by five inbred strains of mice on the responses of macrophages to interleukin-4 (IL-4), a cytokine that plays pleiotropic roles in immunity and tissue homeostasis. Of >600 genes induced >2-fold by IL-4 across the five strains, only 26 genes reached this threshold in all strains. By applying deep learning and motif mutation analyses to epigenetic data for macrophages from each strain, we identified the dominant combinations of lineage-determining and signal-dependent transcription factors driving IL-4 enhancer activation. These studies further revealed mechanisms by which noncoding genetic variation influences absolute levels of enhancer activity and their dynamic responses to IL-4, thereby contributing to strain-differential patterns of gene expression and phenotypic diversity

Mutation and selection processes regulating short tandem repeats give rise to genetic and phenotypic diversity across species

Short tandem repeats (STRs) are units of 1-6 bp that repeat in a tandem fashion in DNA. Along with single nucleotide polymorphisms and large structural variations, they are among the major genomic variants underlying genetic, and likely phenotypic, divergence. STRs experience mutation rates that are orders of magnitude higher than other well-studied genotypic variants. Frequent copy number changes result in a wide range of alleles, and provide unique opportunities for modulating complex phenotypes through variation in repeat length. While classical studies have identified key roles of individual STR loci, the advent of improved sequencing technology, high-quality genome assemblies for diverse species, and bioinformatics methods for genome-wide STR analysis now enable more systematic study of STR variation across wide evolutionary ranges. In this review, we explore mutation and selection processes that affect STR copy number evolution, and how these processes give rise to varying STR patterns both within and across species. Finally, we review recent examples of functional and adaptive changes linked to STRs