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Results for “comparative transcriptomics”

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PubMed2001

The contributions of sex, genotype and age to transcriptional variance in Drosophila melanogaster.

Here we present a statistically rigorous approach to quantifying microarray expression data that allows the relative effects of multiple classes of treatment to be compared and incorporates analytical methods that are common to quantitative genetics. From the magnitude of gene effects and contributions of variance components, we find that gene expression in adult flies is affected most strongly by sex, less so by genotype and only weakly by age (for 1- and 6-wk flies); in addition, sex x genotype interactions may be present for as much as 10% of the Drosophila transcriptome. This interpretation is compromised to some extent by statistical issues relating to power and experimental design. Nevertheless, we show that changes in expression as small as 1.2-fold can be highly significant. Genotypic contributions to transcriptional variance may be of a similar magnitude to those relating to some quantitative phenotypes and should be considered when assessing the significance of experimental treatments.

Aging↗

PubMed2026

Benchmarking urinary cell transcriptomes for noninvasive differentiation of BK polyomavirus-associated nephropathy from T cell-mediated rejection.

BK polyomavirus-associated nephropathy (BKVN) adversely impacts kidney allograft survival and often mimics acute T cell-mediated rejection (TCMR), confounding diagnosis and management. To address this conundrum, we performed unbiased RNA sequencing of urinary cells matched to biopsies classified as BKVN with intragraft inflammation (BKVN-P), BKVN without inflammation (BKVN-N), TCMR, or no rejection (NR). BKVN-N displayed dominant host DNA replication, cell cycle, and repair programs, while BKVN-P samples exhibited expansive innate immune activation, antigen presentation, chemokine upregulation, and epithelial injury. Both BKVN subtypes shared signatures of T cell exhaustion and mature and tolerogenic dendritic cell activation but differed in immune orientation - Th1 predominance in BKVN-N versus Treg and CD8 enrichment in BKVN-P. Compared with TCMR samples, BKVN-P lacked robust TCR/CD28 signaling and was enriched for viral and innate modules; BKVN-N lacked alloimmune activation. B cell exhaustion characterized BKVN-N, while BKVN-P displayed robust B cell activation with metabolic downregulation. A ratiometric urinary cell biomarker, CXCL10 mRNA/CD3E mRNA, distinguished both BKVN subtypes from TCMR with diagnostic accuracy, replicated by quantitative reverse transcription PCR for clinical translation, and confirmed in an independent cohort. These findings demonstrate the utility of urinary cell transcriptomics for resolving viral injury from alloimmunity, enabling precision diagnostics and targeted immunomodulation in kidney transplantation.

Humans↗

PubMed2026

CAGNet: a structure-aware clustering-alternated graph network for cell-cell interaction inference in spatial transcriptomics.

MOTIVATION: Understanding cell-cell interactions (CCIs) in spatial transcriptomics is crucial for uncovering the spatial organization and functional heterogeneity of tissues. However, existing graph-based models typically rely on static clustering or fixed adjacency structures, which limits their ability to capture dynamic cellular relationships. RESULTS: We propose CAGNet, a two-stage framework for CCI inference from spatial transcriptomics data. In Stage 1, a Graph Attention Network encoder with joint feature and graph reconstruction learns structure-aware node embeddings from spatial gene expression profiles. In Stage 2, an alternating optimization mechanism iteratively updates cluster centers via KL-guided soft assignment and refines node embeddings through spatial graph reconstruction, establishing a closed-loop between representation learning and clustering. Experiments on three 10x Genomics Visium datasets demonstrate that CAGNet consistently outperforms six CCI inference baselines across ACC, AUC, AP, Precision, Recall, and F1. CAGNet also achieves the highest Adjusted Rand Index on all three datasets against six spatial domain identification methods, confirming that the learned embeddings capture biologically relevant spatial organization. Information-theoretic analysis further shows that CAGNet retains the highest mutual information between input features and learned embeddings among all compared methods. Ablation studies and 5-fold cross-validation confirm the contribution of each component and the reproducibility of the results. AVAILABILITY: The proposed method is implemented in the CAGNet package available at http://github.com/mahan1233333-maker/CAGNet .

Spatial Transcriptomics↗

PubMed2006

Differential expression profiling of the hepatic proteome in a rat model of dioxin resistance: correlation with genomic and transcriptomic analyses.

One characteristic feature of acute 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) toxicity is dramatic interspecies and interstrain variability in sensitivity. This complicates dioxin risk assessment for humans. However, this variability also provides a means of characterizing mechanisms of dioxin toxicity. Long-Evans (Turku/AB) rats are orders of magnitude more susceptible to TCDD lethality than Han/Wistar (Kuopio) rats, and this difference constitutes a very useful model for identifying mechanisms of dioxin toxicity. We adopted a proteomic approach to identify the differential effects of TCDD exposure on liver protein expression in Han/Wistar rats as compared with Long-Evans rats. This allows determination of which, if any, protein markers are indicative of differences in dioxin susceptibility and/or responsible for conferring resistance. Differential protein expression in total liver protein was assessed using two-dimensional gel electrophoresis, computerized gel image analysis, in-gel digestion, and mass spectrometry. We observed significant changes in the abundance of several proteins, which fall into three general classes: (i) TCDD-independent and exclusively strain-specific (e.g. isoforms of the protein-disulfide isomerase A3, regucalcin, and agmatine ureohydrolase); (ii) strain-independent and only dependent on TCDD exposure (e.g. aldehyde dehydrogenase 3A1 and rat selenium-binding protein 2); (iii) dependent on both TCDD exposure and strain (e.g. oxidative stress-related proteins, apoptosis-inducing factor, and MAWD-binding protein). By integrating transcriptomic (microarray) data and genomic data (computational search of regulatory elements), we found that protein expression levels were mainly controlled at the level of transcription. These results reveal, for the first time, a subset of hepatic proteins that are differentially regulated in response to TCDD in a strain-specific manner. Some of these differential responses may play a role in establishing the major differences in TCDD response between these two strains of rats. As such, our work is expected to lead to new insights into the mechanism of TCDD toxicity and resistance.

Animals↗

PubMed2001

Correlation between Bacillus subtilis scoC phenotype and gene expression determined using microarrays for transcriptome analysis.

The availability of the complete sequence of the Bacillus subtilis chromosome (F. Kunst et al., Nature 390:249-256, 1997) makes possible the construction of genome-wide DNA arrays and the study of this organism on a global scale. Because we have a long-standing interest in the effects of scoC on late-stage developmental phenomena as they relate to aprE expression, we studied the genome-wide effects of a scoC null mutant with the goal of furthering the understanding of the role of scoC in growth and developmental processes. In the present work we compared the expression patterns of isogenic B. subtilis strains, one of which carries a null mutation in the scoC locus (scoC4). The results obtained indicate that scoC regulates, either directly or indirectly, the expression of at least 560 genes in the B. subtilis genome. ScoC appeared to repress as well as activate gene expression. Changes in expression were observed in genes encoding transport and binding proteins, those involved in amino acid, carbohydrate, and nucleotide and/or nucleoside metabolism, and those associated with motility, sporulation, and adaptation to atypical conditions. Changes in gene expression were also observed for transcriptional regulators, along with sigma factors, regulatory phosphatases and kinases, and members of sensor regulator systems. In this report, we discuss some of the phenotypes associated with the scoC mutant in light of the transcriptome changes observed.

Bacillus subtilis↗

PubMed2025

Integrative analysis of gene expression and histone modifications for DES, DSP, GJA1 and SMOC2 in adipose tissue reveals potential relationship to cardiometabolic health.

BACKGROUND: Adipose tissue influences cardiometabolic health through its endocrine activity and its role in regulating inflammation, lipid metabolism, and cardiovascular function. The expression of cardiac-associated genes within adipose tissue may reflect or contribute to cardiometabolic risk, yet this relationship remains poorly understood. This study investigates the expression profiles of the cardiac function associated genes GJA1, DES, DSP and SMOC2 in human adipose tissue, and analyses their associations with cardiometabolic traits. Additionally, we explore epigenomic mechanisms that may underlie their differential gene expression. METHODS: Expression profiling and functional enrichment analyses were conducted to identify depot-specific cardiac gene expression patterns. Quantitative PCR validated gene expression in paired subcutaneous (SAT) and omental visceral adipose tissue (OVAT) samples from 78 individuals with obesity. Gene expression was further validated in three independent cohorts (N = 1,548 total). Associations with clinical traits were assessed using Spearman correlations and multivariate linear regression, adjusted for age, sex, and BMI. Integration with transcriptomic and proteomic datasets publicly available from the Adipose Tissue Knowledge Portal was performed to strengthen clinical relevance. Epigenomic profiling using genome-wide ChIP-seq for histone marks (H3K4me3, H3K4me1, H3K27ac, H3K27me3) was conducted in paired SAT and OVAT samples from five individuals. RESULTS: DES, DSP, GJA1, and SMOC2 were significantly upregulated in OVAT compared to SAT. DES, DSP, and SMOC2 showed consistent expression patterns across all cohorts, while GJA1 exhibited context-dependent regulation. Gene expression in SAT was negatively correlated with cardiometabolic traits, including blood pressure, insulin resistance, and liver function markers. These associations were confirmed by regression analysis and supported by publicly available multi-omics data. Epigenetic analyses revealed OVAT-specific enrichment of active histone marks and reduced repressive marks, supporting higher differential transcriptional activity in OVAT. CONCLUSIONS: Depot-specific gene expression of DES, DSP, and SMOC2 in adipose tissue is robustly linked to cardiometabolic traits and supported by distinct epigenetic landscapes in OVAT vs SAT, highlighting their potential as novel biomarkers for cardiometabolic health.

Humans↗

PubMed2004

Microdissection and SAGE as a combined tool to reveal gene expression in ductal carcinoma in situ of the breast.

The interplay between cancer cells and the normal surrounding tissue is believed to influence the biological behavior of the tumor. However, the presence of multiple cell types within the prelevated tumor specimen may attenuate changes that occur specifically in the malignant cells within their microenvironment. To study gene expression of the malignant cells in situ, we used a new microdissection method to separate ductal carcinoma in situ (DCIS) cells from the surrounding stroma, immunological infiltrates, and endothelial cells. We applied an adapted microSAGE protocol, without total mRNA amplification, to study their gene expression profile. Three thousand two hundred one different transcripts were identified in a total of 29 534 observed tags. Of these unique tags, 88.3% matched known GenBank sequences and 11.7% represented unknown transcripts. As compared to a total DCIS SAGE library, microdissection combined with SAGE revealed additional genes expressed only in normal surrounding, probably stromal, cells and not or significantly less in DCIS tumor cells. This study demonstrates that microdissection can be combined with SAGE as a tool to study transcriptomes. This approach provides important new information on differential gene expression both in tumor cells and normal surrounding tissue. Several of the observed differences indeed disappear when the total tumor mass is analyzed.

Adult↗

PubMed2004

Over-representation of exonic splicing enhancers in human intronless genes suggests multiple functions in mRNA processing.

The human transcriptome is constituted of a great majority of intron-containing and a minority of intron-lacking mRNAs; given the different processing these transcripts undergo, they are expected to carry, intermingled with coding properties, very different editing information. Here we applied a computational approach to compare intronless and intron-containing coding sequences. Hexamer composition comparison allowed the definition of over- and under-represented motifs in intronless genes; surprisingly, experimental testing revealed that intron-lacking coding sequences are enriched rather than depleted in elements with splicing enhancement ability. Similarly, we show evidence that intronless transcripts display a significantly higher frequency of both shuttling and non-shuttling SR protein binding sites compared to intron-containing sequences. These observations suggest that SR proteins (and possibly other splicing factors) play a role in cellular processes distinct from splicing.

Base Sequence↗

PubMed2026

SpliceHarmonization: an integrated method for identifying RNA splicing events in therapeutics for splicing modulation.

MOTIVATION: Splicing, a critical co-transcriptional process in eukaryotes, enhances transcriptome diversity by generating isoforms specific to cell types, tissues, or developmental stages. Recent advancements in splicing modulators have opened new avenues for targeting previously undruggable genes by inducing significant perturbations in splicing events. These developments underscore the need for comprehensive methods to accurately identify and compare splicing events. While several tools have been developed to detect local splice variants, inconsistencies across methods remain a significant challenge. To address this, we present SpliceHarmonization, an integrated approach that combines the strengths of rMATS, LeafCutter, and MAJIQ, enabling robust and reliable splicing analysis with event type annotations. RESULTS: In a comprehensive evaluation using diverse simulated datasets, SpliceHarmonization streamlined and standardized the outputs from three detection methods into a unified format, thereby improving splicing detection with event type annotation and outperforming individual methods. By integrating the outputs from rMATS, LeafCutter, and MAJIQ, our approach not only enhanced identification of a wide range of splicing events but also effectively mitigated method-specific discrepancies. This integration led to an accuracy exceeding 0.8 and a recall of up to 0.5, with an observed increase in AUC of up to 10%. Furthermore, SpliceHarmonization demonstrated high sensitivity in detecting low-abundance and complex splicing events, providing annotations including genomic coordinates and event type. AVAILABILITY AND IMPLEMENTATION: SpliceHarmonization is available at https://github.com/interactivereport/SpliceHarmonization.

RNA Splicing↗

PubMed2005

Evolving gene/transcript definitions significantly alter the interpretation of GeneChip data.

Genome-wide expression profiling is a powerful tool for implicating novel gene ensembles in cellular mechanisms of health and disease. The most popular platform for genome-wide expression profiling is the Affymetrix GeneChip. However, its selection of probes relied on earlier genome and transcriptome annotation which is significantly different from current knowledge. The resultant informatics problems have a profound impact on analysis and interpretation the data. Here, we address these critical issues and offer a solution. We identified several classes of problems at the individual probe level in the existing annotation, under the assumption that current genome and transcriptome databases are more accurate than those used for GeneChip design. We then reorganized probes on more than a dozen popular GeneChips into gene-, transcript- and exon-specific probe sets in light of up-to-date genome, cDNA/EST clustering and single nucleotide polymorphism information. Comparing analysis results between the original and the redefined probe sets reveals approximately 30-50% discrepancy in the genes previously identified as differentially expressed, regardless of analysis method. Our results demonstrate that the original Affymetrix probe set definitions are inaccurate, and many conclusions derived from past GeneChip analyses may be significantly flawed. It will be beneficial to re-analyze existing GeneChip data with updated probe set definitions.

Alleles↗

PubMed2026

Genomic and epigenomic diversity of breast cancer across Western and MENA populations: implications for precision oncology.

Breast cancer is the most common malignancy in women worldwide and is increasingly recognized as a biologically diverse disease shaped by both molecular and ancestral context. Women from the Middle East and North Africa (MENA) populations, including Saudi Arabia, often present at a younger age and with more aggressive subtypes such as HER2-positive and triple-negative breast cancer (TNBC) compared with Western cohorts. These clinical patterns reflect a distinctive genomic background marked by high consanguinity, founder mutations in key susceptibility genes, and population-specific somatic alterations that are not fully captured in global reference datasets. This review brings together current evidence on somatic, germline, transcriptomic, and epigenomic diversity in breast cancer across Western and MENA populations, with a focus on Saudi cohorts. Drawing on a previously published systematic review of more than 2,500 MENA breast cancer cases, TP53 accounted for approximately 24% and PIK3CA for roughly 10% of curated somatic mutation records pooled across 44 studies (proportions of mutation calls, not per-patient prevalence); in a separate single-center Saudi cohort, only 3.7% of patients underwent BRCA testing, and 37.5% of this clinically selected, testing-referred subgroup carried a pathogenic variant, a figure that should not be read as general-population BRCA prevalence. Variants of uncertain significance exceeded 20% across several regional genomic studies. We summarize conserved driver events, such as recurrent TP53 and PIK3CA mutations, while highlighting regional features, including unique stop-gain and loss-of-function variants, a high copy-number burden, and early-onset disease linked to ancestral architecture. We also discuss emerging data on MENA-specific regulatory signatures, including immune-enriched and basal-myo transcriptomic clusters, CIMP-like methylation patterns, and non-coding RNA networks; these associations are numerically suggestive in available cohorts but have not reached statistical significance in existing studies and warrant validation in larger, dedicated MENA/Saudi cohorts before being considered established determinants of treatment response and resistance. Finally, we examine the clinical implications of this diversity for biomarker development, pharmacogenomics, and access to targeted therapies, and outline practical steps toward ancestry-aware precision oncology in the region.

BRCA↗

PubMed2005

Analysis of the epidermal growth factor receptor specific transcriptome: effect of receptor expression level and an activating mutation.

Overexpression or expression of activating mutations of the epidermal growth factor receptor (EGFR) is common in cancer and correlates with neoplastic progression. The present study employed Affymetrix oligonucleotide arrays to profile genes induced by ligand-activated EGFR with the receptor either moderately expressed or overexpressed at an in-itself transforming level. These changes were compared to those induced by the naturally occurring constitutively active variant EGFRvIII. This study provides novel insight on the activities and mechanisms of EGFRvIII and EGFR mediated transformation, as genes encoding proteins with functions in promoting cell proliferation, invasion, antiapoptosis, and angiogenesis featured prominently in the EGFRvIII- and EGFR-expressing cells. Surprisingly, it was found that ligand-activated EGFR induced the expression of a large group of genes known to be inducible by interferons. Expression of this module was absent in the EGFRvIII-expressing cell line and the parental cell line. Treatment with the specific EGFR inhibitor AG1478 indicated that the regulations were primary, receptor-mediated events. Furthermore, activation of this module correlated with activation of STAT1 and STAT3. The results thus demonstrate that ligand-activated EGFR at different expression levels results in different kinetics of signaling and induction of gene expression. In addition, the constitutively active variant EGFRvIII seems to activate only a subset of signal pathways and induce a subset of genes as compared to the ligand-activated EGFR.

Animals↗

PubMed2005

Comparative analysis of transcriptional responses to saline stress in the laboratory and brewing strains of Saccharomyces cerevisiae with DNA microarray.

To construct yeast strains showing tolerance to high salt concentration stress, we analyzed the transcriptional response to high NaCl concentration stress in the yeast Saccharomyces cerevisiae using DNA microarray and compared between two yeast strains, a laboratory strain and a brewing one, which is known as a stress-tolerant strain. Gene expression dynamically changed following the addition of NaCl in both yeast strains, but the degree of change in the gene expression level in the laboratory strain was larger than that in the brewing strain. The response of gene expression to the low NaCl concentration stress was faster than that to the high NaCl concentration stress in both strains. Expressions of the genes encoding enzymes involved in carbohydrate metabolism and energy production in both strains or amino acid metabolism in the brewing strain were increased under high NaCl concentration conditions. Moreover, the genes encoding sodium ion efflux pump and copper metallothionein proteins were more highly expressed in the brewing strain than in the laboratory strain. According to the results of transcriptome analysis, candidate genes for the creation of stress-tolerant strain were selected, and the effect of overexpression of candidate genes on the tolerance to high NaCl concentration stress was evaluated. Overexpression of the GPD1 gene encoding glycerol-3-phosphate dehydrogenase, ENA1 encoding sodium ion efflux protein, and CUP1 encoding copper metallothionein conferred high salt stress tolerance to yeast cells, and our selection of candidate genes for the creation of stress-tolerant yeast strains based on the transcriptome data was validated.

Gene Expression Regulation, Fungal↗

PubMed2026

Transcriptomic Changes Associated with Electroacupuncture in a DMCAO Model of Delayed Cognitive Impairment.

INTRODUCTION: Delayed Cognitive Impairment (DCIS) occurs in approximately 31% to 77% of individuals following stroke. Clinical findings have indicated that electroacupuncture may alleviate post-stroke DCIS. However, insights derived from animal models remain limited. The present study utilized a Distal Middle Cerebral Artery Occlusion (DMCAO) mouse model to investigate the potential mechanisms of electroacupuncture through hippocampal transcriptomic analysis. MATERIALS AND METHODS: Adult male BALB/c mice were subjected to DMCAO and received electroacupuncture treatment. High-throughput RNA sequencing of hippocampal tissue was performed to identify Differentially Expressed Genes (DEGs). Enrichment analyses, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, hierarchical clustering, and Protein-Protein Interaction (PPI) network analysis, were performed to elucidate potential biological mechanisms. RESULTS: The DMCAO model exhibited features consistent with DCIS. Electroacupuncture treatment was associated with improved cognitive performance and enhanced hippocampal neuroplasticity. A total of 116 DEGs were identified in the DMCAO group compared with the sham group, while 69 DEGs were identified in the DMCAO + electroacupuncture group compared with the untreated DMCAO group. DISCUSSION: GO enrichment analysis indicated that electroacupuncture modulated biological processes related to nerve fibers, axonal development, neuronal regulation, cellular processes, and cardiovascular protection. KEGG pathway analysis indicated involvement in pathways associated with neuronal recovery and axonal function. The PPI network comprised 28 nodes and 33 interactions, with hub genes such as Gna13, Hipk2, and Stambp playing key roles. Quantitative Reverse Transcription Polymerase Chain Reaction (qRT-PCR) results were consistent with RNA sequencing findings. CONCLUSION: Electroacupuncture improved DCIS in the DMCAO mouse model. Transcriptomic analysis of the hippocampus provided preliminary evidence of the potential mechanisms underlying the therapeutic effects of electroacupuncture treatment following ischemic stroke.

Animals↗

PubMed2006

Differentially profiling the low-expression transcriptomes of human hepatoma using a novel SSH/microarray approach.

BACKGROUND: The main limitation in performing genome-wide gene-expression profiling is the assay of low-expression genes. Approaches with high throughput and high sensitivity for assaying low-expression transcripts are urgently needed for functional genomic studies. Combination of the suppressive subtractive hybridization (SSH) and cDNA microarray techniques using the subtracted cDNA clones as probes printed on chips has greatly improved the efficiency for fishing out the differentially expressed clones and has been used before. However, it remains tedious and inefficient sequencing works for identifying genes including the great number of redundancy in the subtracted amplicons, and sacrifices the original advantages of high sensitivity of SSH in profiling low-expression transcriptomes. RESULTS: We modified the previous combination of SSH and microarray methods by directly using the subtracted amplicons as targets to hybridize the pre-made cDNA microarrays (named as "SSH/microarray"). mRNA prepared from three pairs of hepatoma and non-hepatoma liver tissues was subjected to the SSH/microarray assays, as well as directly to regular cDNA microarray assays for comparison. As compared to the original SSH and microarray combination assays, the modified SSH/microarray assays allowed for much easier inspection of the subtraction efficiency and identification of genes in the subtracted amplicons without tedious and inefficient sequencing work. On the other hand, 5015 of the 9376 genes originally filtered out by the regular cDNA microarray assays because of low expression became analyzable by the SSH/microarray assays. Moreover, the SSH/microarray assays detected about ten times more (701 vs. 69) HCC differentially expressed genes (at least a two-fold difference and P < 0.01), particularly for those with rare transcripts, than did the regular cDNA microarray assays. The differential expression was validated in 9 randomly selected genes in 18 pairs of hepatoma/non-hepatoma liver tissues using quantitative RT-PCR. The SSH/microarray approaches resulted in identifying many differentially expressed genes implicated in the regulation of cell cycle, cell death, signal transduction and cell morphogenesis, suggesting the involvement of multi-biological processes in hepato-carcinogenesis. CONCLUSION: The modified SSH/microarray approach is a simple but high-sensitive and high-efficient tool for differentially profiling the low-expression transcriptomes. It is most adequate for applying to functional genomic studies.

Carcinoma, Hepatocellular↗

PubMed2005

Exploring the plant transcriptome through phylogenetic profiling.

Publicly available protein sequences represent only a small fraction of the full catalog of genes encoded by the genomes of different plants, such as green algae, mosses, gymnosperms, and angiosperms. By contrast, an enormous amount of expressed sequence tags (ESTs) exists for a wide variety of plant species, representing a substantial part of all transcribed plant genes. Integrating protein and EST sequences in comparative and evolutionary analyses is not straightforward because of the heterogeneous nature of both types of sequence data. By combining information from publicly available EST and protein sequences for 32 different plant species, we identified more than 250,000 plant proteins organized in more than 12,000 gene families. Approximately 60% of the proteins are absent from current sequence databases but provide important new information about plant gene families. Analysis of the distribution of gene families over different plant species through phylogenetic profiling reveals interesting insights into plant gene evolution, and identifies species- and lineage-specific gene families, orphan genes, and conserved core genes across the green plant lineage. We counted a similar number of approximately 9,500 gene families in monocotyledonous and eudicotyledonous plants and found strong evidence for the existence of at least 33,700 genes in rice (Oryza sativa). Interestingly, the larger number of genes in rice compared to Arabidopsis (Arabidopsis thaliana) can partially be explained by a larger amount of species-specific single-copy genes and species-specific gene families. In addition, a majority of large gene families, typically containing more than 50 genes, are bigger in rice than Arabidopsis, whereas the opposite seems true for small gene families.

Arabidopsis↗

PubMed2006

Differential brain transcriptome of beta4 nAChR subunit-deficient mice: is it the effect of the null mutation or the background strain?

Studies using mice with beta4 nicotinic acetylcholine receptor (nAChR) subunit deficiency (beta4-/- mice) helped reveal the roles of this subunit in bradycardiac response to vagal stimulation, nicotine-induced seizure activity and anxiety. To identify genes that might be related to beta4-containing nAChRs activity, we compared the mRNA expression profiles of brains from beta4-/- and wild-type mice using Affymetrix U74Av2 microarray. Seventy-seven genes significantly differentiated between these two experimental groups. Of them, the two most downregulated were spastic paraplegia 21 (human) homolog (Spg21) and 6-pyruvoyl-tetrahydropterin synthase (Pts) genes. Since the targeted mutagenesis of the beta4 nAChR subunit was done by using two mouse strains, 129SvEv and C57BL/6J, it is possible that the genes closely linked to the mutated beta4 gene represent the 129SvEv allele and not the control C57BL/6J-driven allele. We examined this possibility by using public database and quantitative RT-PCR. The expression levels of Spg21 and Pts genes that, like the beta4 gene, are localized on mouse chromosome 9, as well as the expression levels of other genes located on this chromosome, were dependent on the mouse background strain. The 67 differentially expressed genes that are not located on chromosome 9 were further analyzed for overrepresented functional annotations and transcription regulatory elements compared with the entire microarray. Genes encoding for proteins involved in tyrosine phosphatase activity, calcium ion binding, cell growth and/or maintenance, and chromosome organization were overrepresented. Our data enhance the understanding of the molecular interactions involved in the beta4 nAChR subunit function. They also emphasize the need for careful interpretation of expression microarray studies done on genetically manipulated animals.

Animals↗

PubMed2004

First comprehensive mapping of cartilage transcripts to the human genome.

We present the first comprehensive transcriptome-to-genome mapping for human cartilage. First, we determined that the cartilage transcriptome represents between 13,200 and 15,800 unique genes. Next, a subset of approximately 10,000 of the best characterized cartilage-expressed transcripts (CETs) was selected and mapped to the human genome. The distribution of CETs across the genome was found to be significantly different compared to the expected distribution. Furthermore, clusters of adjacent coordinately transcribed genes, as well as numerous "hot spots" and "cold spots" for transcription in cartilage, were identified. We propose that transcriptional control in cartilage can be exerted over genomic domains containing as few as four neighboring genes. Our findings, which are consistent with recent "chromatin domain" models of transcription, are further supported by our identification of CETs that putatively encode components of the HDAC- and Swi/SNF-mediated chromatin remodeling pathways. Our study illustrates the value of comprehensive high-resolution scans to detect transcription patterns within the human genome.

Cartilage↗