Biomedical subjects

Jan O Korbel

Publications and source records attributed to Jan O Korbel.

10 recordsLinked to original sources

PubMed2026

Hypertranscription caused by p53 deficiency triggers nucleotide insufficiency that induces replication stress and genomic instability.

p53 plays a central role in the DNA damage response, inducing repair, cell-cycle arrest or apoptosis. Its loss is associated with replication stress and genomic instability. While several underlying mechanisms were suggested, the primary triggers of catastrophic genomic events like chromothripsis, a known driver of tumorigenesis linked with p53 loss, are still unclear. Using p53-depleted epithelial cells and fibroblasts, as well as patient-derived fibroblasts with germline p53 variants that spontaneously undergo chromothripsis, we found that p53 loss causes hypertranscription and increased nucleotide consumption. The resulting nucleotide shortage induces replication stress, causing telomere dysfunction, micronuclei formation, and chromothripsis. These effects were rescued by nucleoside supplementation or normalization of transcription levels, demonstrating a causal link between transcriptional activity, nucleotide availability, and genome stability. Emerging chromothriptic clones displayed restored DNA replication, telomere stabilization, and extrachromosomal DNA, suggesting key features that support clonal selection. We identify nucleotide pool homeostasis as a critical p53 function that suppresses replication stress, prevents chromothripsis, and protects against early tumorigenesis.

Genomic Instability↗

PubMed2024

Inverted triplications formed by iterative template switches generate structural variant diversity at genomic disorder loci.

The duplication-triplication/inverted-duplication (DUP-TRP/INV-DUP) structure is a complex genomic rearrangement (CGR). Although it has been identified as an important pathogenic DNA mutation signature in genomic disorders and cancer genomes, its architecture remains unresolved. Here, we studied the genomic architecture of DUP-TRP/INV-DUP by investigating the DNA of 24 patients identified by array comparative genomic hybridization (aCGH) on whom we found evidence for the existence of 4 out of 4 predicted structural variant (SV) haplotypes. Using a combination of short-read genome sequencing (GS), long-read GS, optical genome mapping, and single-cell DNA template strand sequencing (strand-seq), the haplotype structure was resolved in 18 samples. The point of template switching in 4 samples was shown to be a segment of ∼2.2-5.5 kb of 100% nucleotide similarity within inverted repeat pairs. These data provide experimental evidence that inverted low-copy repeats act as recombinant substrates. This type of CGR can result in multiple conformers generating diverse SV haplotypes in susceptible dosage-sensitive loci.

Humans↗

PubMed2007

Prediction of effective genome size in metagenomic samples.

We introduce a novel computational approach to predict effective genome size (EGS; a measure that includes multiple plasmid copies, inserted sequences, and associated phages and viruses) from short sequencing reads of environmental genomics (or metagenomics) projects. We observe considerable EGS differences between environments and link this with ecologic complexity as well as species composition (for instance, the presence of eukaryotes). For example, we estimate EGS in a complex, organism-dense farm soil sample at about 6.3 megabases (Mb) whereas that of the bacteria therein is only 4.7 Mb; for bacteria in a nutrient-poor, organism-sparse ocean surface water sample, EGS is as low as 1.6 Mb. The method also permits evaluation of completion status and assembly bias in single-genome sequencing projects.

Artifacts↗

PubMed2006

A supervised hidden markov model framework for efficiently segmenting tiling array data in transcriptional and chIP-chip experiments: systematically incorporating validated biological knowledge.

MOTIVATION: Large-scale tiling array experiments are becoming increasingly common in genomics. In particular, the ENCODE project requires the consistent segmentation of many different tiling array datasets into 'active regions' (e.g. finding transfrags from transcriptional data and putative binding sites from ChIP-chip experiments). Previously, such segmentation was done in an unsupervised fashion mainly based on characteristics of the signal distribution in the tiling array data itself. Here we propose a supervised framework for doing this. It has the advantage of explicitly incorporating validated biological knowledge into the model and allowing for formal training and testing. METHODOLOGY: In particular, we use a hidden Markov model (HMM) framework, which is capable of explicitly modeling the dependency between neighboring probes and whose extended version (the generalized HMM) also allows explicit description of state duration density. We introduce a formal definition of the tiling-array analysis problem, and explain how we can use this to describe sampling small genomic regions for experimental validation to build up a gold-standard set for training and testing. We then describe various ideal and practical sampling strategies (e.g. maximizing signal entropy within a selected region versus using gene annotation or known promoters as positives for transcription or ChIP-chip data, respectively). RESULTS: For the practical sampling and training strategies, we show how the size and noise in the validated training data affects the performance of an HMM applied to the ENCODE transcriptional and ChIP-chip experiments. In particular, we show that the HMM framework is able to efficiently process tiling array data as well as or better than previous approaches. For the idealized sampling strategies, we show how we can assess their performance in a simulation framework and how a maximum entropy approach, which samples sub-regions with very different signal intensities, gives the maximally performing gold-standard. This latter result has strong implications for the optimum way medium-scale validation experiments should be carried out to verify the results of the genome-scale tiling array experiments.

Artificial Intelligence↗

PubMed2006

High-resolution mapping of DNA copy alterations in human chromosome 22 using high-density tiling oligonucleotide arrays.

Deletions and amplifications of the human genomic sequence (copy number polymorphisms) are the cause of numerous diseases and a potential cause of phenotypic variation in the normal population. Comparative genomic hybridization (CGH) has been developed as a useful tool for detecting alterations in DNA copy number that involve blocks of DNA several kilobases or larger in size. We have developed high-resolution CGH (HR-CGH) to detect accurately and with relatively little bias the presence and extent of chromosomal aberrations in human DNA. Maskless array synthesis was used to construct arrays containing 385,000 oligonucleotides with isothermal probes of 45-85 bp in length; arrays tiling the beta-globin locus and chromosome 22q were prepared. Arrays with a 9-bp tiling path were used to map a 622-bp heterozygous deletion in the beta-globin locus. Arrays with an 85-bp tiling path were used to analyze DNA from patients with copy number changes in the pericentromeric region of chromosome 22q. Heterozygous deletions and duplications as well as partial triploidies and partial tetraploidies of portions of chromosome 22q were mapped with high resolution (typically up to 200 bp) in each patient, and the precise breakpoints of two deletions were confirmed by DNA sequencing. Additional peaks potentially corresponding to known and novel additional CNPs were also observed. Our results demonstrate that HR-CGH allows the detection of copy number changes in the human genome at an unprecedented level of resolution.

Base Sequence↗

PubMed2006

Similar gene expression profiles do not imply similar tissue functions.

Although similarities in gene expression among tissues are commonly inferred to reflect functional constraints, this has never been formally tested. Furthermore, it is unclear which evolutionary processes are responsible for the observed similarities. When examining genome-wide expression data in mouse, we found that patterns of expression similarity between tissues extend to genes that are unlikely to function in the tissues. Thus, ectopic expression can seem coordinated across tissues. This indicates that knowledge of gene expression patterns per se is insufficient to infer gene function. Ectopic expression is possibly explained as expression leakage, caused by spreading of chromatin modifications or the transcription apparatus into neighboring genes.

Animals↗

PubMed2005

Systematic association of genes to phenotypes by genome and literature mining.

One of the major challenges of functional genomics is to unravel the connection between genotype and phenotype. So far no global analysis has attempted to explore those connections in the light of the large phenotypic variability seen in nature. Here, we use an unsupervised, systematic approach for associating genes and phenotypic characteristics that combines literature mining with comparative genome analysis. We first mine the MEDLINE literature database for terms that reflect phenotypic similarities of species. Subsequently we predict the likely genomic determinants: genes specifically present in the respective genomes. In a global analysis involving 92 prokaryotic genomes we retrieve 323 clusters containing a total of 2,700 significant gene-phenotype associations. Some clusters contain mostly known relationships, such as genes involved in motility or plant degradation, often with additional hypothetical proteins associated with those phenotypes. Other clusters comprise unexpected associations; for example, a group of terms related to food and spoilage is linked to genes predicted to be involved in bacterial food poisoning. Among the clusters, we observe an enrichment of pathogenicity-related associations, suggesting that the approach reveals many novel genes likely to play a role in infectious diseases.

Bacteria↗

PubMed2004

Analysis of genomic context: prediction of functional associations from conserved bidirectionally transcribed gene pairs.

Several widely used methods for predicting functional associations between proteins are based on the systematic analysis of genomic context. Efforts are ongoing to improve these methods and to search for novel aspects in genomes that could be exploited for function prediction. Here, we use gene expression data to demonstrate two functional implications of genome organization: first, chromosomal proximity indicates gene coregulation in prokaryotes independent of relative gene orientation; and second, adjacent bidirectionally transcribed genes (that is,'divergently' organized coding regions) with conserved gene orientation are strongly coregulated. We further demonstrate that such bidirectionally transcribed gene pairs are functionally associated and derive from this a novel genomic context method that reliably predicts links between >2,500 pairs of genes in approximately 100 species. Around 650 of these functional associations are supported by other genomic context methods. In most instances, one gene encodes a transcriptional regulator, and the other a nonregulatory protein. In-depth analysis in Escherichia coli shows that the vast majority of these regulators both control transcription of the divergently transcribed target gene/operon and auto-regulate their own biosynthesis. The method thus enables the prediction of target processes and regulatory features for several hundred transcriptional regulators.

Amino Acid Sequence↗

PubMed2003

Systematic discovery of analogous enzymes in thiamin biosynthesis.

In all genome-sequencing projects completed to date, a considerable number of 'gaps' have been found in the biochemical pathways of the respective species. In many instances, missing enzymes are displaced by analogs, functionally equivalent proteins that have evolved independently and lack sequence and structural similarity. Here we fill such gaps by analyzing anticorrelating occurrences of genes across species. Our approach, applied to the thiamin biosynthesis pathway comprising approximately 15 catalytic steps, predicts seven instances in which known enzymes have been displaced by analogous proteins. So far we have verified four predictions by genetic complementation, including three proteins for which there was no previous experimental evidence of a role in the thiamin biosynthesis pathway. For one hypothetical protein, biochemical characterization confirmed the predicted thiamin phosphate synthase (ThiE) activity. The results demonstrate the ability of our computational approach to predict specific functions without taking into account sequence similarity.

Alkyl and Aryl Transferases↗

PubMed2002

SHOT: a web server for the construction of genome phylogenies.

With the increasing availability of genome sequences, new methods are being proposed that exploit information from complete genomes to classify species in a phylogeny. Here we present SHOT, a web server for the classification of genomes on the basis of shared gene content or the conservation of gene order that reflects the dominant, phylogenetic signal in these genomic properties. In general, the genome trees are consistent with classical gene-based phylogenies, although some interesting exceptions indicate massive horizontal gene transfer. SHOT is a useful tool for analysing the tree of life from a genomic point of view. It is available at http://www.Bork.EMBL-Heidelberg.de/SHOT.

Animals↗