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Results for “Comprehensive genomic profiling”

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PubMed2005

Comprehensive analysis of heterochromatin- and RNAi-mediated epigenetic control of the fission yeast genome.

The organization of eukaryotic genomes into distinct structural and functional domains is important for the regulation and transduction of genetic information. Here, we investigated heterochromatin and euchromatin profiles of the entire fission yeast genome and explored the role of RNA interference (RNAi) in genome organization. Histone H3 methylated at Lys4, which defines euchromatin, was not only distributed across most of the chromosomal landscape but was also present at the centromere core, the site of kinetochore assembly. In contrast, histone H3 methylated at Lys9 and its interacting protein Swi6/HP1, which define heterochromatin, coated extended domains associated with a variety of repeat elements and small islands corresponding to meiotic genes. Notably, RNAi components were distributed throughout all these heterochromatin domains, and their localization depended on Clr4/Suv39h histone methyltransferase. Sequencing of small interfering RNAs (siRNAs) associated with the RITS RNAi effector complex identified hot spots of siRNAs, which mapped to a diverse array of elements in these RNAi-heterochromatin domains. We found that Clr4/Suv39h predominantly silenced repeat elements whose derived transcripts, transcribed mainly by RNA polymerase II, serve as a source for siRNAs. Our analyses also uncover an important role for the RNAi machinery in maintaining genomic integrity.

DNA Methylation↗

PubMed2026

nf-core/pacsomatic: a scalable somatic analytic pipeline using PacBio HiFi data.

MOTIVATION: Pacific Biosciences (PacBio) HiFi long-read sequencing enables robust characterization of complex genomic regions, repetitive elements, and structural variants (SVs) that are often inaccessible to short-read technologies. To fully leverage HiFi reads to advance cancer genomics and epigenetics, researchers require an end-to-end, scalable and optimized bioinformatics workflow. The nf-core framework meets this need by providing rigorously tested, community-curated pipelines that ensure reproducibility, transparency, and broad compatibility across computational environments. RESULTS: We present nf-core/pacsomatic, an automated Nextflow DSL2 pipeline designed for comprehensive paired tumor-normal somatic analysis using PacBio HiFi data. The workflow includes steps for read alignments against reference genome, somatic SNV/indel, SV, and CNV calling, CpG methylation profiling and differential methylation region (DMR) detection. Additional downstream modules support functional annotation, mutational signature analysis, tumor purity and ploidy estimation, and homologous recombination deficiency (HRD) assessment. Utilizing nf-core's modular design and containerized execution, nf-core/pacsomatic provides a stable framework for the reproducible discovery of biological insights. AVAILABILITY: nf-core/pacsomatic is available under the MIT License at nf-core (https://nf-co.re/pacsomatic) and github (https://github.com/nf-core/pacsomatic).

Software↗

PubMed2005

CoGenT++: an extensive and extensible data environment for computational genomics.

MOTIVATION: CoGenT++ is a data environment for computational research in comparative and functional genomics, designed to address issues of consistency, reproducibility, scalability and accessibility. DESCRIPTION: CoGenT++ facilitates the re-distribution of all fully sequenced and published genomes, storing information about species, gene names and protein sequences. We describe our scalable implementation of ProXSim, a continually updated all-against-all similarity database, which stores pairwise relationships between all genome sequences. Based on these similarities, derived databases are generated for gene fusions--AllFuse, putative orthologs--OFAM, protein families--TRIBES, phylogenetic profiles--ProfUse and phylogenetic trees. Extensions based on the CoGenT++ environment include disease gene prediction, pattern discovery, automated domain detection, genome annotation and ancestral reconstruction. CONCLUSION: CoGenT++ provides a comprehensive environment for computational genomics, accessible primarily for large-scale analyses as well as manual browsing.

Chromosome Mapping↗

PubMed2002

High-throughput SELEX SAGE method for quantitative modeling of transcription-factor binding sites.

The ability to determine the location and relative strength of all transcription-factor binding sites in a genome is important both for a comprehensive understanding of gene regulation and for effective promoter engineering in biotechnological applications. Here we present a bioinformatically driven experimental method to accurately define the DNA-binding sequence specificity of transcription factors. A generalized profile was used as a predictive quantitative model for binding sites, and its parameters were estimated from in vitro-selected ligands using standard hidden Markov model training algorithms. Computer simulations showed that several thousand low- to medium-affinity sequences are required to generate a profile of desired accuracy. To produce data on this scale, we applied high-throughput genomics methods to the biochemical problem addressed here. A method combining systematic evolution of ligands by exponential enrichment (SELEX) and serial analysis of gene expression (SAGE) protocols was coupled to an automated quality-controlled sequence extraction procedure based on Phred quality scores. This allowed the sequencing of a database of more than 10,000 potential DNA ligands for the CTF/NFI transcription factor. The resulting binding-site model defines the sequence specificity of this protein with a high degree of accuracy not achieved earlier and thereby makes it possible to identify previously unknown regulatory sequences in genomic DNA. A covariance analysis of the selected sites revealed non-independent base preferences at different nucleotide positions, providing insight into the binding mechanism.

Base Sequence↗

PubMed2006

Comparative gene expression profiling reveals partially overlapping but distinct genomic actions of different antiestrogens in human breast cancer cells.

Antiestrogens used for breast cancer (BC) treatment differ among each other for the ability to affect estrogen receptor (ER) activity and thereby inhibit hormone-responsive cell functions and viability. We used high-density cDNA microarrays for a comprehensive definition of the gene pathways affected by 17beta-estradiol (E2), ICI 182,780 (ICI), 4OH-tamoxifen (Tamoxifen), and raloxifene (RAL) in ER-positive ZR-75.1 cells, a suitable model to investigate estrogen and antiestrogen actions in hormone-responsive BC. The expression of 601 genes was significantly affected by E2 in these cells; in silico analysis reveals that 86 among them include one or more potential ER binding site within or near the promoter and that the binding site signatures for E2F-1, NF-Y, and NRF-1 transcription factors are significantly enriched in the promoters of genes induced by estrogen treatment, while those for CAC-binding protein and LF-A1 in those repressed by the hormone, pointing to novel transcriptional effectors of secondary responses to estrogen in BC cells. Interestingly, expression of 176 E2-regulated mRNAs was unaffected by any of the antiestrogens tested, despite the fact that under the same conditions the transcriptional and cell cycle stimulatory activities of ER were inhibited. On the other hand, of 373 antiestrogen-responsive genes identified here, 52 were unresponsive to estrogen and 25% responded specifically to only one of the compounds tested, revealing non-overlapping and clearly distinguishable effects of the different antiestrogens in BC cells. As some of these differences reflect specificities of the mechanism of action of the antiestrogens tested, we propose to exploit this gene set for characterization of novel hormonal antagonists and selective estrogen receptor modulators (SERMs) and as a tool for testing new associations of antiestrogens, more effective against BC.

Breast Neoplasms↗

PubMed2025

The Mycobacterium tuberculosis Transposon Sequencing Database (MtbTnDB): A Large-Scale Guide to Genetic Conditional Essentiality.

Characterizing genetic essentiality across various conditions is fundamental for understanding gene function. Transposon sequencing (TnSeq) is a powerful technique to generate genome-wide essentiality profiles in bacteria and has been extensively applied to Mycobacterium tuberculosis (Mtb). Dozens of TnSeq screens have yielded valuable insights into the biology of Mtb in vitro, inside macrophages, and in model host organisms. Despite their value, these Mtb TnSeq profiles have not been standardized or collated into a single, easily searchable database. This results in significant challenges when attempting to query and compare these resources, limiting our ability to obtain a comprehensive and consistent understanding of genetic conditional essentiality in Mtb. We address this problem by building a central repository of publicly available Mtb TnSeq screens, the Mtb transposon sequencing database (MtbTnDB). The MtbTnDB is a living resource that encompasses to date ≈150 standardized TnSeq screens, enabling open access to data, visualizations, and functional predictions through an interactive web app (www.mtbtndb.app). We conduct several statistical analyses on the complete database, such as demonstrating that (i) genes in the same genomic neighborhood have similar TnSeq profiles, and (ii) clusters of genes with similar TnSeq profiles are enriched for genes from similar functional categories. We further analyze the performance of machine learning models trained on TnSeq profiles to predict the functional annotation of orphan genes in Mtb. By facilitating the comparison of TnSeq screens across conditions, the MtbTnDB will accelerate the exploration of conditional genetic essentiality, provide insights into the functional organization of Mtb genes, and help predict gene function in this important human pathogen.

DNA Transposable Elements↗

PubMed2001

Gene expression physiology and pathophysiology of the immune system.

Genomic-scale gene expression profiling can reveal cellular physiology with unprecedented richness. This technology is being used to define the gene expression targets of individual regulatory proteins and signaling pathways. Comprehensive databases of gene expression measurements can be used to understand the pathological mechanisms underlying disease processes.

Animals↗

PubMed2003

Gene expression profiles of I3C- and DIM-treated PC3 human prostate cancer cells determined by cDNA microarray analysis.

Studies from our laboratory and others have shown that indole-3-carbinol (I3C) and its in vivo dimeric product, 3,3'-diindolylmethane (DIM), inhibit the growth of PC3 prostate cancer cells and induce apoptosis by inhibiting nuclear factor (NF)-kappaB and Akt pathways. To obtain comprehensive gene expression profiles altered by I3C- and DIM-treated PC3 cells, we utilized cDNA microarray to interrogate the expression of 22,215 known genes using the Affymetrix Human Genome U133A Array. We found a total of 738 genes that showed a greater than twofold change after 24 h of DIM treatment. Among these genes, 677 genes were down-regulated and 61 were up-regulated. Similarly, 727 genes showed a greater than twofold change in expression, with down-regulation of 685 genes and up-regulation of 42 genes in I3C-treated cells. The altered expressions of genes were observed as early as 6 h and were more evident with longer treatment. Upon cluster analysis, we found that both I3C and DIM up-regulated the expression of genes that are related to the Phase I and Phase II enzymes, suggesting their increased capacity for detoxification of carcinogens or chemicals. We also found that I3C and DIM down-regulated the expression of genes that are critically involved in the regulation of cell growth, cell cycle, apoptosis, signal transduction, Pol II transcription factor and oncogenesis. Real-time reverse transcription-polymerase chain reaction analysis was conducted to confirm the cDNA microarray data, and the results were consistent. We conclude that I3C and DIM affected the expression of a large number of genes that are related to the control of carcinogenesis, cell survival and physiologic behaviors. This may help determine the molecular mechanism(s) by which I3C and DIM exert their pleiotropic effects on PC3 prostate cancer cells; in addition, this information could be further exploited for devising chemopreventive and/or therapeutic strategies for prostate cancer.

Cell Division↗

PubMed2026

High-variance phenome database reveals important roles of WD40 proteins in the plant pathogenic fungus Fusarium graminearum.

WD40 is a highly conserved protein domain in eukaryotes that functions as a versatile platform for protein-protein interactions and participates in diverse biological processes. We performed a genome-wide functional analysis of WD40 domain-containing proteins in Fusarium graminearum, a phytopathogenic fungus that causes severe yield losses and mycotoxin contamination in major cereal crops. Comprehensive phenotypic profiling of 119 WD40 gene deletion mutants across 22 phenotypic traits established a systematic WD40 phenome dataset, revealing the broad functional involvement of WD40 proteins and a strong correlation between sexual reproduction and virulence. Protein interaction analyses of selected WD40 proteins revealed diverse WD40-mediated interaction patterns and provided further insights into WD40-mediated protein interactions and their roles in protein complex formation. This study provides a foundation for further characterization of WD40 proteins in filamentous fungi.

Fusarium graminearum↗

PubMed2001

Using Serial Analysis of Gene Expression to identify tumor markers and antigens.

Tumor markers and antigens are normally highly expressed in malignant tissue, but not in the surrounding normal tissue. Serial Analysis of Gene Expression (SAGE) is a technology that counts mRNA transcripts and can be used to find those genes most highly induced in malignant tissues. SAGE produces a comprehensive profile of gene expression and can be used to search for tumor biomarkers in a limited number of samples. Public sources of SAGE data, in particular through the Cancer Genome Anatomy Project, increase the value of this technology by making a large source of information on many tumors and normal tissues available for comparison. Although the perfect tumor-specific gene does not exist, the differences in gene expression between tumor and normal can be exploited for therapeutic or diagnostic purposes.

Antigens, Neoplasm↗

PubMed2006

OncoDB.HCC: an integrated oncogenomic database of hepatocellular carcinoma revealed aberrant cancer target genes and loci.

The OncoDB.HCC (http://oncodb.hcc.ibms.sinica.edu.tw) is based on physical maps of rodent and human genomes containing quantitative trait loci of rodent HCC models and various human HCC somatic aberrations including chromosomal data from loss of heterozygosity and comparative genome hybridization analyses, altered expression of genes from microarray and proteomic studies, and finally experimental data of published HCC genes. Comprehensive integration of HCC genomic aberration data avoids potential pitfalls of data inconsistency from single genomic approach and provides lines of evidence to reveal somatic aberrations from levels of DNA, RNA to protein. Twenty-nine of 30 (96.7%) novel HCC genes with significant altered expressions in compared between tumor and adjacent normal tissues were validated by RT-PCR in 45 pairs of HCC tissues and by matching expression profiles in 57 HCC patients of re-analyzed Stanford HCC microarray data. Comparative mapping of HCC loci in between human aberrant chromosomal regions and QTLs of rodent HCC models revealed 12 syntenic HCC regions with 2 loci effectively narrowed down to 2 Mb. Together, OncoDB.HCC graphically presents comprehensive HCC data integration, reveals important HCC genes and loci for positional cloning and functional studies, and discloses potential molecular targets for improving HCC diagnosis and therapy.

Animals↗

PubMed2005

The transcriptome's drugable frequenters.

Microarray studies are widely employed in the exploratory phase of the drug discovery process. Expectations raised by the genomics revolution led to the belief that they would rapidly lead to the identification of novel drug targets. However, a few basic questions were often overlooked. Are members of drugable gene families properly represented in the transcriptome? Or are they poorly expressed and below the detection limit of the microarray technology? This review explores the representation of drug targets and components of downstream cellular signaling pathways in the transcriptome. It appears that members of drugable gene families are underrepresented in the transcriptomes of non-pathological human tissues. But, they are represented at or above the expected frequency in the differential transcriptome (i.e. the set of genes that changes expression upon a change in cellular environment). Analysis of differential gene expression on a genome-wide scale will therefore give a comprehensive overview of cellular pathways and possible drug targets.

Drug Design↗

PubMed2002

Transformation of follicular lymphoma to diffuse large cell lymphoma is associated with a heterogeneous set of DNA copy number and gene expression alterations.

Genomic aberrations in a series of paired biopsy samples from patients who presented initially with follicle center lymphoma (FCL) and subsequently transformed to diffuse large B-cell lymphoma (DLBCL) were measured by array comparative genomic hybridization (CGH). The consequences of these aberrations on gene expression were determined by comparison with expression analysis on these specimens using cDNA microarrays. A heterogeneous pattern of acquired genomic abnormalities was observed upon transformation, some of which were recurrent in small subsets of patients. Some of the genomic aberration acquired upon transformation, such as gain/amplification of 1q21-q24, 2p16 (REL/BCL11A gene loci), 3q27-q29 (including the BCL6 locus), 7q11.2-q22.1, 12pter-q12, 18q21 (including the BCL2 locus) and Xq, and deletion of 6q22-q24, 13q14-q21 and 17p13 (P53 locus) have been previously implicated in the FCL/DLBCL pathogenesis. In addition, novel genomic imbalances not previously reported in association with FCL transformation, such as overrepresentation of 4p12-pter, 5p12-p15, 6p12.3-p21, 9p23, 9q13-q31, 16q, 17q21, and loss of 1p36.3, 4q21-q23, 5q21-q23, 9q31-qter, 11q24-q25, and 15q23, were identified. We observed a differential expression profile of many genes within regions of gain and deletion upon transformation, including novel target genes associated with FCL transformation. However, other genes did not show deregulated expression despite their location within these areas. In summary, the combination of array CGH and expression analysis provides a more comprehensive picture of the transformation of FCL to DLBCL. This process is associated with the acquisition of a variable spectrum of genomic imbalances affecting recurrent chromosomal areas that harbor overexpressed or underexpressed genes targeted upon transformation.

Allelic Imbalance↗

PubMed2025

Single-cell copy number calling and event history reconstruction.

MOTIVATION: Copy number alterations are driving forces of tumour development and the emergence of intra-tumour heterogeneity. A comprehensive picture of these genomic aberrations is therefore essential for the development of personalised and precise cancer diagnostics and therapies. Single-cell sequencing offers the highest resolution for copy number profiling down to the level of individual cells. Recent high-throughput protocols allow for the processing of hundreds of cells through shallow whole-genome DNA sequencing. The resulting low read-depth data poses substantial statistical and computational challenges to the identification of copy number alterations. RESULTS: We developed SCICoNE, a statistical model and MCMC algorithm tailored to single-cell copy number profiling from shallow whole-genome DNA sequencing data. SCICoNE reconstructs the history of copy number events in the tumour and uses these evolutionary relationships to identify the copy number profiles of the individual cells. We show the accuracy of this approach in evaluations on simulated data and demonstrate its practicability in applications to two breast cancer samples from different sequencing protocols. AVAILABILITY AND IMPLEMENTATION: SCICoNE is available at https://github.com/cbg-ethz/SCICoNE.

Single-Cell Analysis↗

PubMed2001

Blazing pathways through genetic mountains.

It is now widely accepted that high-throughput data sources will shed essential understanding on the inner workings of cellular and organism function. One key challenge is to distill the results of such experiments into an interpretable computational form that will be the basis of a predictive model. A predictive model represents the gold standard in understanding a biological system and will permit us to investigate the underlying cause of diseases and help us to develop therapeutics. Here I explore how discoveries can be based on high-throughput data sources and discuss how independent discoveries can be assembled into a comprehensive picture of cellular function.

Animals↗

PubMed2002

Integrated genomic and proteomic analysis of signaling pathways in dendritic cell differentiation and maturation.

Dendritic cells (DCs) are antigen-presenting cells that play a major role in initiating primary immune responses. Their phenotypic and functional characteristics are intimately linked to their stage of maturation. The specific biochemical pathways and genes whose expression mediates differentiation of progenitors to DCs and their maturation are largely undefined. We recently utilized two approaches, DNA microarrays and proteomics, to analyze the expression profile of human CD14(+) blood monocytes and their derived DCs. Approximately 4% of the genes or proteins expressed were found to be regulated during DC differentiation. Most of these genes were not previously associated with DCs and included genes highly relevant to DC functions (genes involved in antigen presentation, cell adhesion and motility, lipid metabolism). Genes involved in specific signaling pathways, including IkappaBalpha, PPAR-gamma and C/EBPalpha as well as two members of the family of transcription factors, interferon regulatory factors (IRFs), were also modified. Modulation of IRF gene expression is of particular interest because of their functional roles in innate and adaptive immune responses. IRF-family members control the expression of proteins that include type-1 interferons, interleukin-12, interleukin-15, MHC molecules and adhesion molecules. They have also been found to play an important role in lymphocyte development. In contrast to DC differentiation, very few genes were modified at the transcript level during DC maturation as determined by microarray experiments. Further analysis suggested that DC maturation is largely controlled by posttranscriptional and posttranslational modifications. The use of proteomics is therefore necessary for a full comprehension of DC maturation process.

Animals↗

PubMed2026

Case Report: Immune-driven clonal selection underlying lineage switch from B-Precursor acute lymphoblastic leukemia to acute myeloid leukemia following inotuzumab ozogamicin.

Lineage switch (LS), defined as a change in leukemic lineage during the disease course, is a rare but clinically significant event in acute leukemia and is typically associated with poor prognosis. Although LS has been increasingly reported following targeted immunotherapies, the clonal mechanisms underlying this phenomenon remain incompletely understood, particularly in cases without KMT2A rearrangement. We report a case of LS from B-precursor acute lymphoblastic leukemia (BCP-ALL) to acute myeloid leukemia (AML) following treatment with the CD22-targeted antibody-drug conjugate inotuzumab ozogamicin. To elucidate the clonal architecture underlying LS, targeted next-generation sequencing was performed on bone marrow samples obtained at multiple time points throughout the disease course. Genomic analysis demonstrated that the lymphoid and myeloid disease phases shared ancestral genetic alterations but displayed distinct mutational profiles. At the time of LS, TP53 and SMC1A mutations newly emerged, whereas only a subset of mutations detected at ALL relapse was retained. These findings suggest that the AML phase most likely resulted from the selective expansion of a genetically distinct subclone derived from a common progenitor, rather than the direct transdifferentiation of the dominant ALL clone, consistent with immunotherapy-driven clonal selection. Longitudinal genomic profiling revealed stepwise clonal evolution during disease progression, supporting a model of immunotherapy-driven clonal selection leading to LS. This case provides molecular evidence suggesting that immune-targeted therapy can promote expansion of minor pre-existing subclones with alternative lineage potential within a common progenitor even in non-KMT2A-rearranged leukemia. Our findings highlight the importance of comprehensive genomic monitoring during immunotherapy to identify therapy-resistant subclones and better understand mechanisms of lineage plasticity in acute leukemia.

Humans↗

PubMed2005

Genome-assisted analysis of dissimilatory metal-reducing bacteria.

The availability of whole genome sequences for Shewanella oneidensis and Geobacter sulfurreducens has provided numerous new biological insights into the function of these model dissimilatory metal-reducing bacteria. Many of these findings, including the identification of a high number of c-type cytochromes in both organisms, have resulted from comparative genomic analyses, and several have been experimentally confirmed. These genome sequences have also aided the identification of genes important for the reduction of metal ions and other electron acceptors utilized during anaerobic growth, by facilitating the identification of genes disrupted by random insertions. Technologies for assaying global expression patterns for genes and proteins have also been employed, but their application has been limited mainly to the analysis of the role of global regulatory genes and to identifying genes expressed or repressed in response to specific electron acceptors. It is anticipated that details of the mechanisms of metal ion respiration, and metabolism in general, will eventually be revealed by comprehensive, systems-level analyses enabled by functional genomics data.

Bacterial Proteins↗