Sivan Bercovici

African ancestry allelic variation at the MYH9 gene contributes to increased susceptibility to non-diabetic end-stage kidney disease in Hispanic Americans

Recent studies identified MYH9 as a major susceptibility gene for common forms of non-diabetic end-stage kidney disease (ESKD). A set of African ancestry DNA sequence variants comprising the E-1 haplotype, was significantly associated with ESKD. In order to determine whether African ancestry variants are also associated with disease susceptibility in admixed populations with differing genomic backgrounds, we genotyped a total of 1425 African and Hispanic American subjects comprising dialysis patients with diabetic and non-diabetic ESKD and controls, using 42 single nucleotide polymorphisms (SNPs) within the MYH9 gene and 40 genome-wide and 38 chromosome 22 ancestry informative markers. Following ancestry correction, logistic regression demonstrated that three of the E-1 SNPs are also associated with non-diabetic ESKD in the new sample sets of both African and Hispanic Americans, with a stronger association in Hispanic Americans. We also identified MYH9 SNPs that are even more powerfully associated with the disease phenotype than the E-1 SNPs. These newly associated SNPs, could be divided into those comprising a haplotype termed S-1 whose association was significant under a recessive or additive inheritance mode (rs5750248, OR 4.21, P < 0.01, Hispanic Americans, recessive), and those comprising a haplotype termed F-1 whose association was significant under a dominant or additive inheritance mode (rs11912763, OR 4.59, P < 0.01, Hispanic Americans, dominant). These findings strengthen the contention that a sequence variant of MYH9, common in populations with varying degrees of African ancestry admixture, and in strong linkage disequilibrium with the associated SNPs and haplotypes reported herein, strongly predisposes to non-diabetic ESKD.

Alopecia, Neurological Defects, and Endocrinopathy Syndrome Caused by Decreased Expression of RBM28, a Nucleolar Protein Associated with Ribosome Biogenesis

Single-gene disorders offer unique opportunities to shed light upon fundamental physiological processes in humans. We investigated an autosomal-recessive phenotype characterized by alopecia, progressive neurological defects, and endocrinopathy (ANE syndrome). By using homozygosity mapping and candidate-gene analysis, we identified a loss-of-function mutation in RBM28, encoding a nucleolar protein. RBM28 yeast ortholog, Nop4p, was previously found to regulate ribosome biogenesis. Accordingly, electron microscopy revealed marked ribosome depletion and structural abnormalities of the rough endoplasmic reticulum in patient cells, ascribing ANE syndrome to the restricted group of inherited disorders associated with ribosomal dysfunction.

Population-Specific Association between a Polymorphic Variant in ST18, Encoding a Pro-Apoptotic Molecule, and Pemphigus Vulgaris

Pemphigus vulgaris (PV) is a severe autoimmune blistering disease caused by anti-epithelial antibodies, leading to disruption of cell-cell adhesion. Although the disease is exceedingly rare worldwide, it is known to be relatively prevalent in Jewish populations. The low prevalence of the disease represents a significant obstacle to a genome-wide approach to the mapping of susceptibility genes. We reasoned that the study of a genetically homogeneous cohort characterized by a high prevalence of PV may help exposing associated signals while reducing spurious results due to population sub-structure. We performed a genome-wide association study using 300K single-nucleotide polymorphisms (SNPs) in a case-control study of 100 PV patients of Jewish descent and 397 matched control individuals, followed by replication of significantly associated SNPs in three additional cohorts of Jewish, Egyptian, and German origin. In addition to the major histocompatibility complex locus, a genomic segment on 8q11.23 that spans the ST18 gene was also found to be significantly associated with PV. This association was confirmed in the Jewish and Egyptian replication sets but not in the German sample, suggesting that ST18-associated variants may predispose to PV in a population-specific manner. ST18 regulates apoptosis and inflammation, two processes of direct relevance to the pathogenesis of PV. Further supporting the relevance of ST18 to PV, we found this gene to be overexpressed in the skin of PV patients as compared with healthy individuals.

Pathway-based functional analysis of metagenomes.

Metagenomic data enables the study of microbes and viruses through their DNA as retrieved directly from the environment in which they live. Functional analysis of metagenomes explores the abundance of gene families, pathways, and systems, rather than their taxonomy. Through such analysis, researchers are able to identify those functional capabilities most important to organisms in the examined environment. Recently, a statistical framework for the functional analysis of metagenomes was described that focuses on gene families. Here we describe two pathway level computational models for functional analysis that take into account important, yet unaddressed issues such as pathway size, gene length, and overlap in gene content among pathways. We test our models over carefully designed simulated data and propose novel approaches for performance evaluation. Our models significantly improve over the current approach with respect to pathway ranking and the computations of relative abundance of pathways in environments.

Estimating genome-wide IBD sharing from SNP data via an efficient hidden Markov model of LD with application to gene mapping

Motivation: Association analysis is the method of choice for studying complex multifactorial diseases. The premise of this method is that affected persons contain some common genomic regions with similar SNP alleles and such areas will be found in this analysis. An important disadvantage of GWA studies is that it does not distinguish between genomic areas that are inherited from a common ancestor [identical by descent (IBD)] and areas that are identical merely by state [identical by state (IBS)]. Clearly, areas that can be marked with higher probability as IBD and have the same correlation with the disease status of identical areas that are more probably only IBS, are better candidates to be causative, and yet this distinction is not encoded in standard association analysis. Results: We develop a factorial hidden Markov model-based algorithm for computing genome-wide IBD sharing. The algorithm accepts as input SNP data of measured individuals and estimates the probability of IBD at each locus for every pair of individuals. For two g-degree relatives, when g≥8, the computation yields a precision of IBD tagging of over 50% higher than previous methods for 95% recall. Our algorithm uses a first-order Markovian model for the linkage disequilibrium process and employs a reduction of the state space of the inheritance vector from being exponential in g to quadratic. The higher accuracy along with the reduced time complexity marks our method as a feasible means for IBD mapping in practical scenarios. Availability: A software implementation, called IBDMAP, is freely available at http://bioinfo.cs.technion.ac.il/IBDmap. Contact: sberco@gmail.com

Ancestry Inference in Complex Admixtures via Variable-length Markov Chain Linkage Models

Inferring the ancestral origin of chromosomal segments in admixed individuals is key for genetic applications, ranging from analyzing population demographics and history, to mapping disease genes. Previous methods addressed ancestry inference by using either weak models of linkage disequilibrium, or large models that make explicit use of ancestral haplotypes. In this paper we introduce ALLOY, an efficient method that incorporates generalized, but highly expressive, linkage disequilibrium models. ALLOY applies a factorial hidden Markov model to capture the parallel process producing the maternal and paternal admixed haplotypes, and models the background linkage disequilibrium in the ancestral populations via an inhomogeneous variable-length Markov chain. We test ALLOY in a broad range of scenarios ranging from recent to ancient admixtures with up to four ancestral populations. We show that ALLOY outperforms the previous state of the art, and is robust to uncertainties in model parameters.

Panel construction for mapping in admixed populations via expected mutual information.

Mapping by admixture linkage disequilibrium (MALD) is an economical and powerful approach for the identification of genomic regions harboring disease susceptibility genes in recently admixed populations. We develop an information-theory-based measure, called expected mutual information (EMI), which computes the impact of a set of markers on the ability to infer ancestry at each chromosomal location. We then present a simple and effective algorithm for the selection of panels that strives to maximize the EMI score. Finally, we demonstrate via well-established simulation tools that our panels provide more power and accuracy for inferring disease gene loci via the MALD method in comparison to previous methods.

Inferring Ancestries Efficiently in Admixed Populations with Linkage Disequilibrium

Much effort has recently been invested in developing methods for determining the ancestral origin of chromosomal segments in admixed individuals. Motivations for this task are the study of population history such as bottleneck effects and migration, the assessment of population stratification for adequate adjustment of association studies, and the enhancement of mapping by admixture linkage disequilibrium (MALD). In this article, we present a novel framework for the inference of ancestry at each chromosomal location. The uniqueness of our method stems from the ability to incorporate complex probability models that account for linkage-disequilibrium in the ancestral populations. We provide an inference algorithm that is polynomial in the number of markers even though the underlying problem seems to be inherently exponential in nature. We demonstrate the validity of our model and conclude that, with sufficient ancestral haplotypes, this framework can provide higher accuracy in inferring ancestral origin.

Decentralized Electronic Mail

E-mail is one of the most popular Internet applications. Unfortunately, the server-centric architecture of today’s commercial solutions inherently limits availability, efficiency, and scalability. The single point of failure as well as the increasing processing and storage stress on the server drives the 35 year old architecture to the limits of its abilities. This paper proposes decentralized electronic mail (DEM), a novel e-mail architecture that overcomes existing systems’ shortcomings. Following the mobile-object paradigm, DEM offers a decentralized approach, which breaks the dependency between a mail user and a single service provider, while relying entirely on participants’ resources.

Admixture aberration analysis: application to mapping in admixed population using pooled DNA.

Abstract Admixture mapping is a gene mapping approach used for the identification of genomic regions harboring disease susceptibility genes in the case of recently admixed populations such as African Americans. We present a novel method for admixture mapping, called admixture aberration analysis (AAA) that uses a DNA pool of affected admixed individuals. We demonstrate through simulations that AAA is a powerful and economical mapping method under a range of scenarios, capturing complex human diseases such as hypertension and end-stage kidney disease. The method has a low false-positive rate and is robust to deviation from model assumptions. Finally, we apply AAA on 600 prostate cancer-affected African Americans, replicating a known risk locus. Simulation results indicate that the method can yield over 96% reduction in genotyping. Our method is implemented as a Java program called AAAmap and is freely available at http://bioinfo.cs.technion.ac.il/AAAmap.