Search PubMed⌕ Search

Biomedical subjects

Eli Eisenberg

Publications and source records attributed to Eli Eisenberg.

16 recordsLinked to original sources
PubMed2024

Global quantification of off-target activity by base editors.

Base editors are engineered deaminases combined with CRISPR components. These engineered deaminases are designed to target specific sites within DNA or RNA to make a precise change in the molecule. In therapeutics, they hold promise for correcting mutations associated with genetic diseases. However, a key challenge is minimizing unintended edits at off-target sites, which could lead to harmful mutations. Researchers are actively addressing this concern through a variety of optimization efforts that aim to improve the precision of base editors and minimize off-target activity. Here, we examine the various types of off-target activity, and the methods used to evaluate them. Current methods for finding off-target activity focus on identifying similar sequences in the genome or in the transcriptome, assuming the guide RNA misdirects the editor. The main method presented here, that was originally developed to quantify editing levels mediated by the ADAR enzyme, takes a different approach, investigating the inherent activity of base editors themselves, which might lead to off-target edits beyond sequence similarity. The editing index tool quantifies global off-target editing, eliminates the need to detect individual off-target sites, and allows for assessment of the global load of mutations.

Gene Editing↗
PubMed2024

Bioinformatic approaches for accurate assessment of A-to-I editing in complete transcriptomes.

A-to-I RNA editing is an RNA modification that alters the RNA sequence relative to the its genomic blueprint. It is catalyzed by double-stranded RNA-specific adenosine deaminase (ADAR) enzymes, and contributes to the complexity and diversification of the proteome. Advancement in the study of A-to-I RNA editing has been facilitated by computational approaches for accurate mapping and quantification of A-to-I RNA editing based on sequencing data. In this chapter we review some of the main computational approaches currently used, describe potential hurdles, challenges and pitfalls, and discuss possible ways to mitigate them.

RNA Editing↗
PubMed2006

RNA editing level in the mouse is determined by the genomic repeat repertoire.

A-to-I RNA editing is the conversion of adenosine to inosine in double-stranded cellular and viral RNAs. Recently, abundant editing of human transcripts affecting thousands of genes has been reported. Most editing sites are confined to the primate-specific Alu repeats. Notably, the editing level in mouse was shown to be much lower. In order to find the reason for this dramatic difference, here we identify editing sites within mouse repeats and analyze the sequence properties required for RNA editing. Our results show that the overall rate of RNA editing is determined by specific properties of different repeat families such as abundance, length, and divergence. We show that the striking difference in editing levels between human and mouse is mostly due to the higher divergence of the different mouse repeats.

Animals↗
PubMed2006

Connectivity and expression in protein networks: proteins in a complex are uniformly expressed.

We explore the interplay between the protein-protein interactions network and the expression of the interacting proteins. It is shown that interacting proteins are expressed in significantly more similar cellular concentrations. This is largely due to interacting pairs which are part of protein complexes. We solve a generic model of complex formation and show explicitly that complexes form most efficiently when their members have roughly the same concentrations. Therefore, the observed similarity in interacting protein concentrations could be attributed to optimization for efficiency of complex formation.

Computer Simulation↗
PubMed2006

Algorithmic approaches for identification of RNA editing sites.

Recently a number of groups have introduced computational methods for the detection of A-to-I RNA editing sites. These approaches have resulted in finding thousands of editing sites within the genomic repeats, as well as a few novel genetic recoding sites. We review these recent advancements, emphasizing the principles underlying the various methods used. Possible directions for extending these methods are discussed.

Algorithms↗
PubMed2005

Identification of RNA editing sites in the SNP database.

The relationship between human inherited genomic variations and phenotypic differences has been the focus of much research effort in recent years. These studies benefit from millions of single-nucleotide polymorphism (SNP) records available in public databases, such as dbSNP. The importance of identifying false dbSNP records increases with the growing role played by SNPs in linkage analysis for disease traits. In particular, the emerging understanding of the abundance of DNA and RNA editing calls for a careful distinction between inherited SNPs and somatic DNA and RNA modifications. In order to demonstrate that some of the SNP database records are actually somatic modification, we focus on one type of these modifications, namely A-to-I RNA editing, and present evidence for hundreds of dbSNP records that are actually editing sites. We provide a list of 102 RNA editing sites previously annotated in dbSNP database as SNPs, and experimentally validate seven of these. Interestingly, we show how dbSNP can serve as a starting point to look for new editing sites. Our results, for this particular type of RNA editing, demonstrate the need for a careful analysis of SNP databases in light of the increasing recognition of the significance of somatic sequence modifications.

Base Sequence↗
PubMed2005

Evidence for abundant transcription of non-coding regions in the Saccharomyces cerevisiae genome.

BACKGROUND: Recent studies in a growing number of organisms have yielded accumulating evidence that a significant portion of the non-coding region in the genome is transcribed. We address this issue in the yeast Saccharomyces cerevisiae. RESULTS: Taking into account the absence of a significantly large yeast EST database, we use microarray expression data collected for genomic regions erroneously believed to be coding to study the expression pattern of non-coding regions in the Saccharomyces cerevisiae genome. We find that at least 164 out of 589 (28%) such regions are expressed under specific biological conditions. In particular, looking at the probes that are located opposing other known genes at the same genomic locus, we find that 88 out of 341 (26%) of these genes support antisense transcription. The expression patterns of these antisense genes are positively correlated. We validate these results using RT-PCR on a sample of 6 non-coding transcripts. CONCLUSION: 1. The yeast genome is transcribed on a scale larger than previously assumed. 2. Correlated transcription of antisense genes is abundant in the yeast genome. 3. Antisense genes in yeast are non-coding.

Computational Biology↗
PubMed2005

Evolutionarily conserved human targets of adenosine to inosine RNA editing.

A-to-I RNA editing by ADARs is a post-transcriptional mechanism for expanding the proteomic repertoire. Genetic recoding by editing was so far observed for only a few mammalian RNAs that are predominantly expressed in nervous tissues. However, as these editing targets fail to explain the broad and severe phenotypes of ADAR1 knockout mice, additional targets for editing by ADARs were always expected. Using comparative genomics and expressed sequence analysis, we identified and experimentally verified four additional candidate human substrates for ADAR-mediated editing: FLNA, BLCAP, CYFIP2 and IGFBP7. Additionally, editing of three of these substrates was verified in the mouse while two of them were validated in chicken. Interestingly, none of these substrates encodes a receptor protein but two of them are strongly expressed in the CNS and seem important for proper nervous system function. The editing pattern observed suggests that some of the affected proteins might have altered physiological properties leaving the possibility that they can be related to the phenotypes of ADAR1 knockout mice.

Adenosine↗
PubMed2005

Is abundant A-to-I RNA editing primate-specific?

A-to-I RNA editing is common in all eukaryotes, and is associated with various neurological functions. Recently, A-to-I editing was found to occur frequently in the human transcriptome. In this article, we show that the frequency of A-to-I editing in humans is at least an order of magnitude higher than in the mouse, rat, chicken or fly genomes. The extraordinary frequency of RNA editing in human is explained by the dominance of the primate-specific Alu element in the human transcriptome, which increases the number of double-stranded RNA substrates.

3' Untranslated Regions↗
PubMed2005

Is there any sense in antisense editing?

Several recent studies have hypothesized that sense-antisense RNA-transcript pairs create dsRNA duplexes that undergo extensive A-to-I RNA editing. We studied human and mouse genomic antisense regions and found that the editing level in these areas is negligible. This observation questions the scope of sense-antisense duplexes formation in-vivo, which is the basis for several proposed regulatory mechanisms.

Alu Elements↗
PubMed2005

Letter from the editor: Adenosine-to-inosine RNA editing in Alu repeats in the human genome.

Adenosine-to-inosine (A-to-I) RNA editing increases the complexity of the human transcriptome and is essential for maintenance of normal life in mammals. Most A-to-I substitutions occur within repetitive elements in the genome, mainly in Alu repeats. The phenomenon of A-to-I editing is far less abundant in mice, rats, chickens and flies than in humans, which correlates with the relative under-representation of Alu repeats in these non-primate genomes. Here, we review the recent results of bioinformatic and laboratory approaches that have estimated the extent of the editing phenomenon. We discuss the possible biological relevance of the editing pathway, its possible interaction with other cellular pathways that respond to double-stranded RNA and its possible contribution to the accelerated evolution of primates.

Adenosine↗
PubMed2004

Systematic identification of abundant A-to-I editing sites in the human transcriptome.

RNA editing by members of the ADAR (adenosine deaminases acting on RNA) family leads to site-specific conversion of adenosine to inosine (A-to-I) in precursor messenger RNAs. Editing by ADARs is believed to occur in all metazoa, and is essential for mammalian development. Currently, only a limited number of human ADAR substrates are known, whereas indirect evidence suggests a substantial fraction of all pre-mRNAs being affected. Here we describe a computational search for ADAR editing sites in the human transcriptome, using millions of available expressed sequences. We mapped 12,723 A-to-I editing sites in 1,637 different genes, with an estimated accuracy of 95%, raising the number of known editing sites by two orders of magnitude. We experimentally validated our method by verifying the occurrence of editing in 26 novel substrates. A-to-I editing in humans primarily occurs in noncoding regions of the RNA, typically in Alu repeats. Analysis of the large set of editing sites indicates the role of editing in controlling dsRNA stability.

Adenosine↗
PubMed2003

Preferential attachment in the protein network evolution.

The Saccharomyces cerevisiae protein-protein interaction map, as well as many natural and man-made networks, shares the scale-free topology. The preferential attachment model was suggested as a generic network evolution model that yields this universal topology. However, it is not clear that the model assumptions hold for the protein interaction network. Using a cross-genome comparison, we show that (a) the older a protein, the better connected it is, and (b) the number of interactions a protein gains during its evolution is proportional to its connectivity. Therefore, preferential attachment governs the protein network evolution. Evolutionary mechanisms leading to such preference and some implications are discussed.

Evolution, Molecular↗
PubMed2002

Polarization of interacting bosons with spin.

We prove that in the absence of explicit spin-dependent forces one of the ground states of interacting bosons with spin is always fully polarized. Generally, this state is degenerate with other states, but one can specify the exact degeneracy. For T>0, the magnetization and zero-field susceptibility exceed that of a pure paramagnet. The results are relevant to experimental work on triplet superconductivity and condensation of atoms with spin. They eliminate the possibility, raised in some theoretical speculations, that the ground state or positive temperature state might be antiferromagnetic.

Journal Article↗
PubMed2002

Dephasing times in closed quantum dots.

Dephasing of one-particle states in closed quantum dots is analyzed within the framework of random matrix theory and the master equation. The combination of this analysis with recent experiments on the magnetoconductance allows, for the first time, the evaluation of the dephasing times of closed quantum dots. These dephasing times turn out to be dependent on the mean level spacing and significantly enhanced as compared with the case of open dots. Moreover, the experimental data available are consistent with the prediction that the dephasing of one-particle states in finite closed systems disappears at low enough energies and temperatures.

Journal Article↗