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PubMed2024

The Genetic Determinants and Genomic Consequences of Non-Leukemogenic Somatic Point Mutations.

Clonal hematopoiesis (CH) is defined by the expansion of a lineage of genetically identical cells in blood. Genetic lesions that confer a fitness advantage, such as point mutations or mosaic chromosomal alterations (mCAs) in genes associated with hematologic malignancy, are frequent mediators of CH. However, recent analyses of both single cell-derived colonies of hematopoietic cells and population sequencing cohorts have revealed CH frequently occurs in the absence of known driver genetic lesions. To characterize CH without known driver genetic lesions, we used 51,399 deeply sequenced whole genomes from the NHLBI TOPMed sequencing initiative to perform simultaneous germline and somatic mutation analyses among individuals without leukemogenic point mutations (LPM), which we term CH-LPMneg. We quantified CH by estimating the total mutation burden. Because estimating somatic mutation burden without a paired-tissue sample is challenging, we developed a novel statistical method, the Genomic and Epigenomic informed Mutation (GEM) rate, that uses external genomic and epigenomic data sources to distinguish artifactual signals from true somatic mutations. We performed a genome-wide association study of GEM to discover the germline determinants of CH-LPMneg. After fine-mapping and variant-to-gene analyses, we identified seven genes associated with CH-LPMneg (TCL1A, TERT, SMC4, NRIP1, PRDM16, MSRA, SCARB1), and one locus associated with a sex-associated mutation pathway (SRGAP2C). We performed a secondary analysis excluding individuals with mCAs, finding that the genetic architecture was largely unaffected by their inclusion. Functional analyses of SMC4 and NRIP1 implicated altered HSC self-renewal and proliferation as the primary mediator of mutation burden in blood. We then performed comprehensive multi-tissue transcriptomic analyses, finding that the expression levels of 404 genes are associated with GEM. Finally, we performed phenotypic association meta-analyses across four cohorts, finding that GEM is associated with increased white blood cell count and increased risk for incident peripheral artery disease, but is not significantly associated with incident stroke or coronary disease events. Overall, we develop GEM for quantifying mutation burden from WGS without a paired-tissue sample and use GEM to discover the genetic, genomic, and phenotypic correlates of CH-LPMneg.

Journal Article↗
PubMed2006

Regional copy number-independent deregulation of transcription in cancer.

Genetic and epigenetic alterations have been identified that lead to transcriptional deregulation in cancers. Genetic mechanisms may affect single genes or regions containing several neighboring genes, as has been shown for DNA copy number changes. It was recently reported that epigenetic suppression of gene expression can also extend to a whole region; this is known as long-range epigenetic silencing. Various techniques are available for identifying regional genetic alterations, but no large-scale analysis has yet been carried out to obtain an overview of regional epigenetic alterations. We carried out an exhaustive search for regions susceptible to such mechanisms using a combination of transcriptome correlation map analysis and array CGH data for a series of bladder carcinomas. We validated one candidate region experimentally, demonstrating histone methylation leading to the loss of expression of neighboring genes without DNA methylation.

Cell Line, Tumor↗
PubMed2006

EST analysis of cDNA libraries from the entomopathogenic fungus Beauveria (Cordyceps) bassiana. I. Evidence for stage-specific gene expression in aerial conidia, in vitro blastospores and submerged conidia.

The entomopathogenic fungus Beauveria (Cordyceps) bassiana holds much promise as a pest biological control agent. B. bassiana produces at least three in vitro single cell infectious propagules, including aerial conidia, vegetative cells termed blastospores and submerged conidia, that display different morphological, biochemical and virulence properties. Populations of aerial conidia, blastospores and submerged conidia were produced on agar plates, rich liquid broth cultures and under conditions of nutrient limitation in submerged cultures, respectively. cDNA libraries were generated from mRNA isolated from each B. bassiana cell type and approximately 2,500 5' end sequences were determined from each library. Sequences derived from aerial conidia clustered into 284 contigs and 963 singlets, with those derived from blastospores and submerged conidia forming 327 contigs with 788 singlets, and 303 contigs and 1,079 contigs, respectively. Almost half (40-45 %) of the sequences in each library displayed either no significant similarity (e value >10(-4)) or similarity to hypothetical proteins found in the NCBI database. The expressed sequence tag dataset also included sequences representing a significant portion of proteins in cellular metabolism, information storage and processing, transport and cell processes, including cell division and posttranslational modifications. Transcripts encoding a diverse array of pathogenicity-related genes, including proteases, lipases, esterases, phosphatases and enzymes producing toxic secondary metabolites, were also identified. Comparative analysis between the libraries identified 2,416 unique sequences, of which 20-30 % were unique to each library, and only approximately 6 % of the sequences were shared between all three libraries. The unique and divergent representation of the B. bassiana transcriptome in the cDNA libraries from each cell type suggests robust differential gene expression profiles in response to environmental conditions.

Animals↗
PubMed2025

Altered ruminal microbiome tryptophan metabolism and their derived 3-indoleacetic acid inhibit ruminal inflammation in subacute ruminal acidosis goats.

BACKGROUND: Subacute ruminal acidosis (SARA) is a digestive disorder that often severely jeopardizes the health and lactation performance of ruminants fed a high-energy diet. Different dairy ruminants exhibit varying degrees of inflammation accompanied by variations in the rumen microbiota when SARA occurs. Our understanding of the occurrence of SARA and varying degrees of rumen epithelial inflammation is lacking. Hence, we performed rumen metagenomic, metagenome-assembled genome and metabolomic analyses, with transcriptome and single-nucleus RNA sequence analyses, to explore the microbial mechanism of SARA occurrence and different degrees of inflammation. RESULTS: A total of 36 goats fed two diets with gradually increasing levels of rumen-degradable starch (RDS) were included in this study, and SARA goats fed 70% concentrate diets supplemented with whole corn (HGW-SARA) and SARA goats fed 70% concentrate diets supplemented with crushed corn (HGC-SARA) were identified. Moreover, 11 goats fed a control basal diet, named LGW-CON, were also included. Compared with those in the LGW-CON group, the rumen fermentation capacity was enhanced, accompanied by ruminal epithelial and systemic inflammation, in goats from HGW-SARA and HGC-SARA. Between them, HGC-SARA goats presented less inflammation. Notably, the ruminal inflammation-related pathways were increased only in the HGW-SARA group but not in the HGC-SARA group. Metagenomic analysis revealed that the β diversity of SARA goats was significantly different from that of LGW-CON goats. Ruminococcus significantly increased in both SARA groups, whereas Prevotella and Bacteroidales significantly decreased, which was accompanied by a decrease in cellulose and hemicellulose enzymes and an increase in lysozymes and lipopolysaccharide synthesis enzymes. Multi-omics analysis of the ruminal contents and tissues suggested that epithelial inflammation was caused by disturbed ruminal microbiome-induced Th17 cell differentiation and IL-17 signalling pathway activation. Comparative analyses between the HGW-SARA and HGC-SARA groups highlighted the importance of Selenomonas and Bifidobacterium, as well as bacterial tryptophan metabolism, in the production of 3-indoleacetic acid, which mitigated ruminal epithelial inflammation by modulating Th17 cells and inhibiting IL-17 signalling. Ruminal microbiota transplantation from HGW-SARA goats to healthy dairy goats and mice revealed the role of microbes in epithelial inflammation. Additionally, 3-indoleacetic acid supplementation reduced rumen inflammation and the IL-17 concentration in the serum, improved VFAs absorption, and enhanced milk production. CONCLUSIONS: This study unveiled that after SARA was induced by high-concentrate feeding, the rumen homeostasis was disrupted, and rumen fiber degradation capacity of dairy goats decreased, but the LPS synthesis capacity increased, and inflammation of the rumen epithelium was observed. However, the ruminal microbial species from the Bifidobacterium and Selenomonas genera and bacterial 3-indole acetic acid are pivotal in mitigating ruminal epithelial inflammation during SARA in dairy goats. This could potentially be attributed to the modulation of ruminal Th17 cell proportions and the inhibition of IL-17 signalling pathways. Video Abstract.

Rumen↗
PubMed2026

Evaluation of the clinical and mechanistic role of MCM2 expression in the prediction of meningioma recurrence after radiotherapy.

OBJECTIVE: Postoperative radiotherapy is an effective treatment for meningiomas; however, treatment response varies among patients. In addition, practical methods for predicting tumor recurrence after radiotherapy have not been well established. Minichromosome maintenance protein 2 (MCM2), a key regulator of DNA replication licensing, was recently implicated in highly proliferative molecular subtypes of meningioma. In this study, the authors evaluated whether MCM2 immunohistochemical expression predicts response to radiotherapy in patients with meningiomas. METHODS: The authors retrospectively analyzed the records of patients with WHO grade 1-3 meningiomas treated with resection followed by radiotherapy at a single institution between July 2003 and November 2023. The MCM2 labeling index was assessed immunohistochemically, and patients were stratified into MCM2-high and -low groups using a cutoff of 35%. Progression-free survival (PFS) was defined as the interval from the completion of radiation therapy to postoperative radiological tumor recurrence or regrowth. Patients who showed no progression were censored at their last follow-up. PFS was estimated using Kaplan-Meier analysis and subsequently evaluated with Cox proportional hazards models. To further investigate the biological mechanisms associated with MCM2 expression, comprehensive transcriptomic analyses, including gene set enrichment analysis, was performed to elucidate the molecular processes that occur within MCM2-high tumors. RESULTS: The study population included 15 men (42%) and 21 women (58%), with a mean age of 63 years. Ten tumors (28%) were classified as MCM2-high meningiomas and 26 (72%) as MCM2-low meningiomas. High MCM2 expression was significantly associated with WHO grades 2-3 histology and higher Ki-67 labeling indices. During a median follow-up of 2.52 years, tumor progression after radiotherapy occurred in 47% of the patients. High MCM2 expression (HR 8.34, p = 0.03) was significantly associated with shorter PFS and remained an independent predictor of recurrence after adjustment for WHO grade, tumor size, and Ki-67 labeling index. Transcriptomic analyses of MCM2-high tumors revealed upregulation of cell proliferation-related pathways, accompanied by increased signaling through the E2F8-CHEK1 axis associated with radiation resistance and suppression of the TNF-α signaling pathway implicated in radiosensitivity. CONCLUSIONS: In meningiomas, high MCM2 expression is associated with early recurrence following radiotherapy. The study findings suggest that this association is driven by diverse biological mechanisms related to cell cycle regulation and radioresistance. Immunohistochemical assessment of MCM2 expression may serve as a practical and accessible biomarker for risk stratification and may support the future development of individualized postoperative radiotherapy strategies.

Humans↗
PubMed2004

EST and microarray analyses of pathogen-responsive genes in hot pepper (Capsicum annuum L.) non-host resistance against soybean pustule pathogen (Xanthomonas axonopodis pv. glycines).

Large-scale single-pass sequencing of cDNA libraries and microarray analysis have proven to be useful tools for discovering new genes and studying gene expression. As a first step in elucidating the defense mechanisms in hot pepper plants, a total of 8,525 expressed sequence tags (ESTs) were generated and analyzed in silico. The cDNA microarray analysis identified 613 hot pepper genes that were transcriptionally responsive to the non-host soybean pustule pathogen Xanthomonas axonopodis pv. glycines ( Xag). Several functional types of genes, including those involved in cell wall modification/biosynthesis, transport, signaling pathways and divergent defense reactions, were induced at the early stage of Xag infiltration. In contrast, genes encoding proteins that are involved in photosynthesis, carbohydrate metabolism and the synthesis of chloroplast biogenetic proteins were down-regulated at the late stage of Xag infiltration. These expression profiles share common features with the expression profiles elicited by other stresses, such as fungal challenge, wounding, cold, drought and high salinity. However, we also identified several novel transcription factors that may be specifically involved in the defense reaction of the hot pepper. We also found that the defense reaction of the hot pepper may involve the deactivation of gibberellin. Furthermore, many genes encoding proteins with unknown function were identified. Functional analysis of these genes may broaden our understanding of non-host resistance. This study is the first report of large-scale sequencing and non-host defense transcriptome analysis of the hot pepper plant species. (The sequence data in this paper have been submitted to the dbEST and GenBank database under the codes 10227604-10236595 and BM059564-BM068555, respectively. Additional information is available at http://plant.pdrc.re.kr/ks200201/pepper.html).

Capsicum↗
PubMed2026

Identifying causal genetic variants for high-altitude adaptation through blood eQTL analysis in plateau populations.

A substantial number of genetic variants have been associated with high-altitude adaptation (HAA), yet most of them are located in non-coding genomic regions, leaving their specific functions and underlying mechanisms largely unknown. In this study, we analyze whole-genome and transcriptome sequencing data from a self-established cohort comprising 61 native highlanders (NHs) and 164 acclimatized newcomers (ANs), identifying 6,586 cis- and 34,203 trans-expression quantitative trait loci (eQTLs), along with 130 cell type-specific eQTLs. By further combining these data with a large East Asia (~30% Tibetan) genome-wide association study (GWAS) cohort, we employ colocalization and causal inference analyses to prioritize 85 cis-eQTLs associated with HAA and identify several novel candidate causal genes, including EXOC8, which is experimentally confirmed to regulate erythroid differentiation. Additionally, network analysis of these causal genes uncovers multiple regulatory pathways, mainly involving energy metabolism, autophagy, ubiquitination and inflammation. Our study offers a comprehensive eQTL map and reveals causal chains of "variant-gene-phenotype" for HAA-related traits, which provides new insights into potential regulatory mechanisms and targets for prevention and treatment of altitude sickness.

Quantitative Trait Loci↗
PubMed2005

Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes.

BACKGROUND: The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer studies. Although similar questions for the same type of cancer are addressed in these different studies, a comparative analysis of their results is hampered by the use of heterogeneous microarray platforms and analysis methods. RESULTS: In contrast to a meta-analysis approach where results of different studies are combined on an interpretative level, we investigate here how to directly integrate raw microarray data from different studies for the purpose of supervised classification analysis. We use median rank scores and quantile discretization to derive numerically comparable measures of gene expression from different platforms. These transformed data are then used for training of classifiers based on support vector machines. We apply this approach to six publicly available cancer microarray gene expression data sets, which consist of three pairs of studies, each examining the same type of cancer, i.e. breast cancer, prostate cancer or acute myeloid leukemia. For each pair, one study was performed by means of cDNA microarrays and the other by means of oligonucleotide microarrays. In each pair, high classification accuracies (> 85%) were achieved with training and testing on data instances randomly chosen from both data sets in a cross-validation analysis. To exemplify the potential of this cross-platform classification analysis, we use two leukemia microarray data sets to show that important genes with regard to the biology of leukemia are selected in an integrated analysis, which are missed in either single-set analysis. CONCLUSION: Cross-platform classification of multiple cancer microarray data sets yields discriminative gene expression signatures that are found and validated on a large number of microarray samples, generated by different laboratories and microarray technologies. Predictive models generated by this approach are better validated than those generated on a single data set, while showing high predictive power and improved generalization performance.

Animals↗
PubMed2006

Transcriptome changes in the phenylpropanoid pathway of Glycine max in response to Pseudomonas syringae infection.

BACKGROUND: Reports of plant molecular responses to pathogenic infections have pinpointed increases in activity of several genes of the phenylpropanoid pathway leading to the synthesis of lignin and flavonoids. The majority of those findings were derived from single gene studies and more recently from several global gene expression analyses. We undertook a global transcriptional analysis focused on the response of genes of the multiple branches of the phenylpropanoid pathway to infection by the Pseudomonas syringae pv. glycinea with or without the avirulence gene avrB to characterize more broadly the contribution of the multiple branches of the pathway to the resistance response in soybean. Transcript abundance in leaves was determined from analysis of soybean cDNA microarray data and hybridizations to RNA blots with specific gene probes. RESULTS: The majority of the genes surveyed presented patterns of increased transcript accumulation. Some increased rapidly, 2 and 4 hours after inoculation, while others started to accumulate slowly by 8-12 hours. In contrast, transcripts of a few genes decreased in abundance 2 hours post inoculation. Most interestingly was the opposite temporal fluctuation in transcript abundance between early responsive genes in defense (CHS and IFS1) and F3H, the gene encoding a pivotal enzyme in the synthesis of anthocyanins, proanthocyanidins and flavonols. F3H transcripts decreased rapidly 2 hours post inoculation and increased during periods when CHS and IFS transcripts decreased. It was also determined that all but one (CHS4) family member genes (CHS1, CHS2, CHS3, CHS5, CHS6 and CHS7/8) accumulated higher transcript levels during the defense response provoked by the avirulent pathogen challenge. CONCLUSION: Based on the mRNA profiles, these results show the strong bias that soybean has towards increasing the synthesis of isoflavonoid phytoalexins concomitant with the down regulation of genes required for the synthesis of anthocyanins and proanthocyanins. Although proanthocyanins are known to be toxic compounds, the cells in the soybean leaves seem to be programmed to prioritize the synthesis and accumulation of isoflavonoid and pterocarpan phytoalexins during the resistance response. It was known that CHS transcripts accumulate in great abundance rapidly after inoculation of the soybean plants but our results have demonstrated that all but one (CHS4) member of the gene family member genes accumulated higher transcript levels during the defense response.

Bacterial Proteins↗
PubMed2003

Comprehensive sampling of gene expression in human cell lines with massively parallel signature sequencing.

Whereas information is rapidly accumulating about the structure and position of genes encoded in the human genome, less is known about the complexity and relative abundance of their expression in individual human cells and tissues. Here, we describe the characteristics of the transcriptomes of two cultured cell lines, HB4a (normal breast epithelium) and HCT-116 (colon adenocarcinoma), using massively parallel signature sequencing (MPSS). We generated in excess of 10(7) short signature sequences per cell line, thus providing a comprehensive snapshot of gene expression, within the technical limitations of the method. The number of genes expressed at one copy per cell or more in either of the lines was estimated to be between 10,000 and 15,000. The vast majority of the transcripts found in these cells can be mapped to known genes and their polyadenylation variants. Among the genes that could be identified from their signature sequences, approximately 8,500 were expressed by both cell lines, whereas 6,000 showed cellular specificity. Taking into account sequence tags that map uniquely to the genome but not to known transcripts, overall the data are consistent with an upper limit of 17,000 for the total number of genes expressed at more than one copy per cell in one or both of the two cell lines examined.

Adenocarcinoma↗
PubMed2006

A comprehensive proteomics and genomics analysis reveals novel transmembrane proteins in human platelets and mouse megakaryocytes including G6b-B, a novel immunoreceptor tyrosine-based inhibitory motif protein.

The platelet surface is poorly characterized due to the low abundance of many membrane proteins and the lack of specialist tools for their investigation. In this study we identified novel human platelet and mouse megakaryocyte membrane proteins using specialist proteomics and genomics approaches. Three separate methods were used to enrich platelet surface proteins prior to identification by liquid chromatography and tandem mass spectrometry: lectin affinity chromatography, biotin/NeutrAvidin affinity chromatography, and free flow electrophoresis. Many known, abundant platelet surface transmembrane proteins and several novel proteins were identified using each receptor enrichment strategy. In total, two or more unique peptides were identified for 46, 68, and 22 surface membrane, intracellular membrane, and membrane proteins of unknown subcellular localization, respectively. The majority of these were single transmembrane proteins. To complement the proteomics studies, we analyzed the transcriptome of a highly purified preparation of mature primary mouse megakaryocytes using serial analysis of gene expression in view of the increasing importance of mutant mouse models in establishing protein function in platelets. This approach identified all of the major classes of platelet transmembrane receptors, including multitransmembrane proteins. Strikingly 17 of the 25 most megakaryocyte-specific genes (relative to 30 other serial analysis of gene expression libraries) were transmembrane proteins, illustrating the unique nature of the megakaryocyte/platelet surface. The list of novel plasma membrane proteins identified using proteomics includes the immunoglobulin superfamily member G6b, which undergoes extensive alternate splicing. Specific antibodies were used to demonstrate expression of the G6b-B isoform, which contains an immunoreceptor tyrosine-based inhibition motif. G6b-B undergoes tyrosine phosphorylation and association with the SH2 domain-containing phosphatase, SHP-1, in stimulated platelets suggesting that it may play a novel role in limiting platelet activation.

Animals↗
PubMed2026

Molecular and Genomic Mechanisms Linking Diabetes Mellitus and Periodontitis: From Pathogenesis to Translational Opportunities.

Diabetes mellitus and periodontitis are bidirectionally associated chronic disorders linked through metabolic dysregulation, host inflammation, microbial dysbiosis, and impaired tissue remodeling. This review summarizes clinical, molecular, cellular, genomic, epigenomic, transcriptomic, and microbial evidence concerning the mechanisms underlying this relationship and their potential translational relevance. Chronic hyperglycemia is associated with advanced glycation end product signaling through the receptor for advanced glycation end products, mitogen-activated protein kinase/nuclear factor-κB activation, reactive oxygen species production, oxidative stress, and NLR family pyrin domain-containing 3 inflammasome activation, which may contribute to enhanced cytokine responses and periodontal tissue injury. Diabetes is also associated with altered neutrophil and macrophage function, increased T helper 17/interleukin-17 signaling, and an elevated receptor activator of nuclear factor-κB ligand/osteoprotegerin ratio, thereby favoring osteoclastogenesis and alveolar bone loss. Conversely, periodontal inflammation and microbial products may contribute to systemic low-grade inflammation, insulin resistance, and metabolic dysregulation. Multi-omics studies have identified shared susceptibility loci, regulatory networks, and disease-associated cell states, although their causal and clinical significance remains incompletely defined. These findings suggest potential roles for integrated medical-dental care, glycemic screening in dental settings, periodontal inflammation control, host-modulatory therapies, and regenerative biomaterials. Further longitudinal and experimental studies are needed to determine their clinical applicability.

Humans↗
PubMed2004

Identitag, a relational database for SAGE tag identification and interspecies comparison of SAGE libraries.

BACKGROUND: Serial Analysis of Gene Expression (SAGE) is a method of large-scale gene expression analysis that has the potential to generate the full list of mRNAs present within a cell population at a given time and their frequency. An essential step in SAGE library analysis is the unambiguous assignment of each 14 bp tag to the transcript from which it was derived. This process, called tag-to-gene mapping, represents a step that has to be improved in the analysis of SAGE libraries. Indeed, the existing web sites providing correspondence between tags and transcripts do not concern all species for which numerous EST and cDNA have already been sequenced. RESULTS: This is the reason why we designed and implemented a freely available tool called Identitag for tag identification that can be used in any species for which transcript sequences are available. Identitag is based on a relational database structure in order to allow rapid and easy storage and updating of data and, most importantly, in order to be able to precisely define identification parameters. This structure can be seen like three interconnected modules : the first one stores virtual tags extracted from a given list of transcript sequences, the second stores experimental tags observed in SAGE experiments, and the third allows the annotation of the transcript sequences used for virtual tag extraction. It therefore connects an observed tag to a virtual tag and to the sequence it comes from, and then to its functional annotation when available. Databases made from different species can be connected according to orthology relationship thus allowing the comparison of SAGE libraries between species. We successfully used Identitag to identify tags from our chicken SAGE libraries and for chicken to human SAGE tags interspecies comparison. Identitag sources are freely available on http://pbil.univ-lyon1.fr/software/identitag/ web site. CONCLUSIONS: Identitag is a flexible and powerful tool for tag identification in any single species and for interspecies comparison of SAGE libraries. It opens the way to comparative transcriptomic analysis, an emerging branch of biology.

Animals↗
PubMed2003

High-throughput classification of yeast mutants for functional genomics using metabolic footprinting.

Many technologies have been developed to help explain the function of genes discovered by systematic genome sequencing. At present, transcriptome and proteome studies dominate large-scale functional analysis strategies. Yet the metabolome, because it is 'downstream', should show greater effects of genetic or physiological changes and thus should be much closer to the phenotype of the organism. We earlier presented a functional analysis strategy that used metabolic fingerprinting to reveal the phenotype of silent mutations of yeast genes. However, this is difficult to scale up for high-throughput screening. Here we present an alternative that has the required throughput (2 min per sample). This 'metabolic footprinting' approach recognizes the significance of 'overflow metabolism' in appropriate media. Measuring intracellular metabolites is time-consuming and subject to technical difficulties caused by the rapid turnover of intracellular metabolites and the need to quench metabolism and separate metabolites from the extracellular space. We therefore focused instead on direct, noninvasive, mass spectrometric monitoring of extracellular metabolites in spent culture medium. Metabolic footprinting can distinguish between different physiological states of wild-type yeast and between yeast single-gene deletion mutants even from related areas of metabolism. By using appropriate clustering and machine learning techniques, the latter based on genetic programming, we show that metabolic footprinting is an effective method to classify 'unknown' mutants by genetic defect.

Cells, Cultured↗
PubMed2006

Group testing for pathway analysis improves comparability of different microarray datasets.

MOTIVATION: The wide use of DNA microarrays for the investigation of the cell transcriptome triggered the invention of numerous methods for the processing of microarray data and lead to a growing number of microarray studies that examine the same biological conditions. However, comparisons made on the level of gene lists obtained by different statistical methods or from different datasets hardly converge. We aimed at examining such discrepancies on the level of apparently affected biologically related groups of genes, e.g. metabolic or signalling pathways. This can be achieved by group testing procedures, e.g. over-representation analysis, functional class scoring (FCS), or global tests. RESULTS: Three public prostate cancer datasets obtained with the same microarray platform (HGU95A/HGU95Av2) were analyzed. Each dataset was subjected to normalization by either variance stabilizing normalization (vsn) or mixed model normalization (MMN). Then, statistical analysis of microarrays was applied to the vsn-normalized data and mixed model analysis to the data normalized by MMN. For multiple testing adjustment the false discovery rate was calculated and the threshold was set to 0.05. Gene lists from the same method applied to different datasets showed overlaps between 42 and 52%, while lists from different methods applied to the same dataset had between 63 and 85% of genes in common. A number of six gene lists obtained by the two statistical methods applied to the three datasets was then subjected to group testing by Fisher's exact test. Group testing by GSEA and global test was applied to the three datasets, as well. Fisher's exact test followed by global test showed more consistent results with respect to the concordance between analyses on gene lists obtained by different methods and different datasets than the GSEA. However, all group testing methods identified pathways that had already been described to be involved in the pathogenesis of prostate cancer. Moreover, pathways recurrently identified in these analyses are more likely to be reliable than those from a single analysis on a single dataset.

Biomarkers, Tumor↗
PubMed2026

Recent Advances in Multi-Omics of Systemic Lupus Erythematosus.

This comprehensive narrative review examines recent advances in multi-omics research for Systemic Lupus Erythematosus (SLE), emphasizing integrated approaches over single-omics studies. The review critically evaluates technological advancements, methodological innovations, and clinical applications while identifying current limitations and future research directions. We conducted a comprehensive narrative review following SANRA guidelines, searching PubMed, Web of Science, Scopus, and Embase, covering publications from January 2018 to June 2025. The review focuses on studies integrating two or more omics layers in SLE research, with emphasis on computational methods, biomarker validation, and clinical applications. Multi-omics integration has revealed critical insights into SLE pathogenesis, including immune cell heterogeneity, gene-environment interactions, and metabolic dysregulation. However, significant challenges remain in data integration methodologies, small sample sizes, and biomarker reproducibility. Current computational approaches include early integration (concatenation), intermediate integration (joint dimensionality reduction), and late integration (ensemble methods). While multi-omics approaches offer unprecedented insights into SLE complexity, standardized integration protocols and robust validation frameworks are urgently needed. Small sample sizes and heterogeneity issues limit reproducibility, particularly affecting biomarker discovery and clinical translation. Multi-omics integration represents a paradigm shift toward precision medicine in SLE, but realizing this potential requires addressing current methodological limitations, standardizing validation processes, and developing robust computational frameworks for reliable clinical applications.

Humans↗
PubMed2006

High-protein and high-carbohydrate breakfasts differentially change the transcriptome of human blood cells.

BACKGROUND: Application of transcriptomics technology in human nutrition intervention studies would allow for genome-wide screening of the effects of specific diets or nutrients and result in biomarker profiles. OBJECTIVE: The aim was to evaluate the potential of gene expression profiling in blood cells collected in a human intervention study that investigated the effect of a high-carbohydrate (HC) or a high-protein (HP) breakfast on satiety. DESIGN: Blood samples were taken from 8 healthy men before and 2 h after consumption of an HP or an HC breakfast. Both breakfasts contained acetaminophen for measuring the gastric emptying rate. Analysis of the transcriptome data focused on the effects of the HP or HC breakfast and of acetaminophen on blood leukocyte gene expression profiles. RESULTS: Breakfast consumption resulted in differentially expressed genes, 317 for the HC breakfast and 919 for the HP breakfast. Immune response and signal transduction, specifically T cell receptor signaling and nuclear transcription factor kappaB signaling, were the overrepresented functional groups in the set of 141 genes that were differentially expressed in response to both breakfasts. Consumption of the HC breakfast resulted in differential expression of glycogen metabolism genes, and consumption of the HP breakfast resulted in differential expression of genes involved in protein biosynthesis. CONCLUSIONS: Gene expression changes in blood leukocytes corresponded with and may be related to the difference in macronutrient content of the breakfast, meal consumption as such, and acetaminophen exposure. This study illustrates the potential of gene expression profiling in blood to study the effects of dietary exposure in human intervention studies.

Acetaminophen↗
PubMed2006

Metabolic regulation in the lactating mammary gland: a lipid synthesizing machine.

The mammary gland of the lactating mouse synthesizes and secretes milk lipid equivalent to its entire body weight in a single 20-day lactation cycle, making it one of the most active lipid synthetic organs known. We test the hypothesis that multiple control points and potential regulatory mechanisms regulate milk lipid synthesis at the level of gene expression. The mammary transcriptome of 130 genes involved in glucose metabolism was examined at late pregnancy and early lactation, utilizing data obtained from microarray analysis of mammary glands from quadruplicate FVB mice at pregnancy day 17 and lactation day 2. To correlate changes with physiological parameters, the metabolome obtained from magnetic resonance spectroscopy of flash-frozen glands at day 17 of pregnancy was compared with that at day 2 of lactation. A significant increase in carbohydrates (glucose, lactose, sialic acid) and amino acids (alanine, aspartate, arginine, glutamate) with a moderate increase in important osmolytes (myo-inositol, betaine, choline derivatives) were observed in the lactating gland. In addition, diets containing 8% or 40% lipid were fed from lactation days 5-10 and mammary glands and livers of triplicate FVB mice prepared for microarray analysis. The results show that substantial regulation of lipid synthesis occurs at the level of mRNA expression and that some of the regulation points differ substantially from the liver. They also implicate the transcription factor SREBP-1c in regulation of part of the pathway.

Animals↗