Histone-fold domain protein NF-Y promotes chromatin accessibility for cell type-specific master transcription factors.

Cell type-specific master transcription factors (TFs) play vital roles in defining cell identity and function. However, the roles ubiquitous factors play in the specification of cell identity remain underappreciated. Here we show that the ubiquitous CCAAT-binding NF-Y complex is required for the maintenance of embryonic stem cell (ESC) identity and is an essential component of the core pluripotency network. Genome-wide studies in ESCs and neurons reveal that NF-Y regulates not only genes with housekeeping functions through cell type-invariant promoter-proximal binding, but also genes required for cell identity by binding to cell type-specific enhancers with master TFs. Mechanistically, NF-Y's distinct DNA-binding mode promotes master/pioneer TF binding at enhancers by facilitating a permissive chromatin conformation. Our studies unearth a conceptually unique function for histone-fold domain (HFD) protein NF-Y in promoting chromatin accessibility and suggest that other HFD proteins with analogous structural and DNA-binding properties may function in similar ways.

Metagenomic Insights into the Gut Microbiota of Eudrilus eugeniae (Kinberg) and Its Potential Roles in Agroecosystem.

Gut microbiomes, a consortium of microorganisms that live in the animal gut, are highly engineered microbial communities. It makes a major contribution to digestive health, metabolism management, and the development of a strong immune system in the host. The present study was taken up to answer the long-running question about the existence of truly indigenous microflora of the epigeic earthworm gut. This is due to the general difficulties of culturing many of the microorganisms found in soil or earthworms' gut. Keeping this fact in a view, the metagenomics approach using 16S rRNA marker gene incorporated with amplicon-based sequencing was used to explore microbiota of commercially overriding, diversely fed epigeic earthworm Eudrilus eugeniae (Kinberg) in three varied habitats viz., artificial soil (AS), organic agricultural farm soil (OAFS) and conventional agriculture farm soil (CAFS). There are predominant bacteria that belong to different phyla such as Proteobacteria (29.72-76.81%), Actinobacteria (11.06-34.42%), Firmicutes (6.02-19.81%), and Bacteroidetes (2.40-9.22%) present in the gut of E. eugeniae. The alpha diversity (Observed species, Chao1, ACE, Shannon, Simpson, and Fisher alpha) indices showed that OAFS had significantly higher alpha diversity than AS and CAFS groups. The core microbiota analysis showed that OAFS and AS groups had a relatively similar bacterial panel in comparison to the CAFS group. Various statistical tools i.e. MetagenomeSeq, LEfSe, and Random Forest analysis were performed and the findings demonstrated prevalence of the most significant bacterial genera; Aeromonas, Gaiella, and Burkholderia in CAFS group. Nonetheless, in AS and OAFS groups, the common existence of Anaerosporobacter and Aquihabitans were found respectively. Metagenomic functional prediction revealed that earthworms' gut microbial communities were actively involved in multiple organic and xenobiotics compound degradation-related pathways. This is the first research to use high-throughput 16S rRNA gene amplicon sequencing to show the gut microbiota of E. eugeniae in diverse agricultural systems. The findings suggest the configuration of the gut microbiota of earthworms and its potential role in the soil ecosystem depends on the microbial communities of the soil.

Integrative framework for identification of key cell identity genes uncovers determinants of ES cell identity and homeostasis.

Identification of genes associated with specific biological phenotypes is a fundamental step toward understanding the molecular basis underlying development and pathogenesis. Although RNAi-based high-throughput screens are routinely used for this task, false discovery and sensitivity remain a challenge. Here we describe a computational framework for systematic integration of published gene expression data to identify genes defining a phenotype of interest. We applied our approach to rank-order all genes based on their likelihood of determining ES cell (ESC) identity. RNAi-mediated loss-of-function experiments on top-ranked genes unearthed many novel determinants of ESC identity, thus validating the derived gene ranks to serve as a rich and valuable resource for those working to uncover novel ESC regulators. Underscoring the value of our gene ranks, functional studies of our top-hit Nucleolin (Ncl), abundant in stem and cancer cells, revealed Ncl's essential role in the maintenance of ESC homeostasis by shielding against differentiation-inducing redox imbalance-induced oxidative stress. Notably, we report a conceptually novel mechanism involving a Nucleolin-dependent Nanog-p53 bistable switch regulating the homeostatic balance between self-renewal and differentiation in ESCs. Our findings connect the dots on a previously unknown regulatory circuitry involving genes associated with traits in both ESCs and cancer and might have profound implications for understanding cell fate decisions in cancer stem cells. The proposed computational framework, by helping to prioritize and preselect candidate genes for tests using complex and expensive genetic screens, provides a powerful yet inexpensive means for identification of key cell identity genes.

Acute depletion of Tet1-dependent 5-hydroxymethylcytosine levels impairs LIF/Stat3 signaling and results in loss of embryonic stem cell identity.

The TET family of FE(II) and 2-oxoglutarate-dependent enzymes (Tet1/2/3) promote DNA demethylation by converting 5-methylcytosine to 5-hydroxymethylcytosine (5hmC), which they further oxidize into 5-formylcytosine and 5-carboxylcytosine. Tet1 is robustly expressed in mouse embryonic stem cells (mESCs) and has been implicated in mESC maintenance. Here we demonstrate that, unlike genetic deletion, RNAi-mediated depletion of Tet1 in mESCs led to a significant reduction in 5hmC and loss of mESC identity. The differentiation phenotype due to Tet1 depletion positively correlated with the extent of 5hmC loss. Meta-analyses of genomic data sets suggested interaction between Tet1 and leukemia inhibitory factor (LIF) signaling. LIF signaling is known to promote self-renewal and pluripotency in mESCs partly by opposing MAPK/ERK-mediated differentiation. Withdrawal of LIF leads to differentiation of mESCs. We discovered that Tet1 depletion impaired LIF-dependent Stat3-mediated gene activation by affecting Stat3's ability to bind to its target sites on chromatin. Nanog overexpression or inhibition of MAPK/ERK signaling, both known to maintain mESCs in the absence of LIF, rescued Tet1 depletion, further supporting the dependence of LIF/Stat3 signaling on Tet1. These data support the conclusion that analysis of mESCs in the hours/days immediately following efficient Tet1 depletion reveals Tet1's normal physiological role in maintaining the pluripotent state that may be subject to homeostatic compensation in genetic models.

Systems-wide view of host-pathogen interactions across COVID-19 severities using integrated omics analysis.

The mechanisms explaining the variability in COVID-19 clinical manifestations (mild, moderate, and severe) are not fully understood. To identify key gene expression markers linked to disease severity, we employed an integrated approach, combining host-pathogen protein-protein interaction data and viral-induced host gene expression data. We analyzed an RNA-seq dataset from peripheral blood mononuclear cells across 12 projects representing the spectrum of disease severity. We identified genes showing differential expression across mild, moderate, and severe conditions. Enrichment analysis of the pathways in host proteins targeted by each of the SARS-CoV-2 proteins revealed a strong association with processes related to ribosomal biogenesis, translation, and translocation. Interestingly, most of these pathways and associated cellular machinery, including ribosomal biogenesis, ribosomal proteins, and translation, were upregulated in mild conditions but downregulated in severe cases. This suggests that COVID-19 exhibits a paradoxical host response, boosting host/viral translation in mild cases but slowing it in severe cases.

DOMINE: a comprehensive collection of known and predicted domain-domain interactions.

DOMINE is a comprehensive collection of known and predicted domain-domain interactions (DDIs) compiled from 15 different sources. The updated DOMINE includes 2285 new domain-domain interactions (DDIs) inferred from experimentally characterized high-resolution three-dimensional structures, and about 3500 novel predictions by five computational approaches published over the last 3 years. These additions bring the total number of unique DDIs in the updated version to 26,219 among 5140 unique Pfam domains, a 23% increase compared to 20,513 unique DDIs among 4346 unique domains in the previous version. The updated version now contains 6634 known DDIs, and features a new classification scheme to assign confidence levels to predicted DDIs. DOMINE will serve as a valuable resource to those studying protein and domain interactions. Most importantly, DOMINE will not only serve as an excellent reference to bench scientists testing for new interactions but also to bioinformaticans seeking to predict novel protein-protein interactions based on the DDIs. The contents of the DOMINE are available at http://domine.utdallas.edu.

Metabolic remodeling in Escherichia coli MG1655. A prophage e14-encoded small RNA, co293, post-transcriptionally regulates transcription factors HcaR and FadR.

In previous studies, we have shown the existence of metabolic remodeling in glucose-grown Escherichia coli MG1655 cells expressing the esterase Orf306 from the opd island of Sphingobium fuliginis. We now show that Orf306-dependent metabolic remodeling is due to regulation of a novel small RNA (sRNA). Endogenous propionate, produced due to the esterase/lipase activity of Orf306, repressed expression of a novel E. coli sRNA, co293. This sRNA post-transcriptionally regulates expression of the transcription factors HcaR and FadR either by inhibiting translation or by destabilizing their transcripts. Hence, repression of co293 expression elevates the levels of HcaR and FadR with consequent activation of alternative carbon catabolic pathways. HcaR activates the hca and MHP operons leading to upregulation of the phenyl propionate and hydroxy phenyl propionate (HPP) degradation pathways. Similarly, FadR stimulates the expression of the transcription factor IclR which negatively regulates the glyoxylate bypass pathway genes, aceBAK.

Comparative transcriptome profiling of pomegranate genotypes having resistance and susceptible reaction to Xanthomonas axonopodis pv. punicae.

Pomegranate (Punica granatum L.) is an important fruit crop, rich in fiber, vitamins, antioxidants, minerals and source of different biologically active compounds. The bacterial blight caused by Xanthomonas axonopodispv. punicae is a serious threat to the crop leading to 60-80% yield loss under epiphytotic conditions. In this work, we have generated comparative transcriptome profile to mark the gene expression signatures during resistance and susceptible interactions. We analyzed leaf and fruits samples of moderately resistant genotype (IC 524207) and susceptible variety (Bhagawa) of pomegranate at three progressive infection stages upon inoculation with the pathogen. RNA-Seq with the Illumina HiSeq 2500 platform revealed 1,88,337 non-redundant (nr) transcript sequences from raw sequencing data, for a total of 34,626 unigenes with size >2 kb. Moreover, 85.3% unigenes were annotated in at least one of the seven databases examined. Comparative analysis of gene-expression signatures in resistant and susceptible varieties showed that the genes known to be involved in defense mechanism in plants were up-regulated in resistant variety. Gene Ontology (GO) analysis successfully annotated 90,485 pomegranate unigenes, of which 68,464 were assigned to biological, 78,107 unigenes molecular function and 44,414 to cellular components. Significantly enriched GO terms in DEGs were related to oxidations reduction biological process, protein binding and oxidoreductase activity. This transcriptome data on pomegranate could help in understanding resistance and susceptibility nature of cultivars and further detailed fine mapping and functional validation of identified candidate gene would provide scope for resistance breeding programme in pomegranate.

Prediction of evolutionarily conserved interologs in Mus musculus.

BACKGROUND: Identification of protein-protein interactions is an important first step to understand living systems. High-throughput experimental approaches have accumulated large amount of information on protein-protein interactions in human and other model organisms. Such interaction information has been successfully transferred to other species, in which the experimental data are limited. However, the annotation transfer method could yield false positive interologs due to the lack of conservation of interactions when applied to phylogenetically distant organisms. RESULTS: To address this issue, we used phylogenetic profile method to filter false positives in interologs based on the notion that evolutionary conserved interactions show similar patterns of occurrence along the genomes. The approach was applied to Mus musculus, in which the experimentally identified interactions are limited. We first inferred the protein-protein interactions in Mus musculus by using two approaches: i) identifying mouse orthologs of interacting proteins (interologs) based on the experimental protein-protein interaction data from other organisms; and ii) analyzing frequency of mouse ortholog co-occurrence in predicted operons of bacteria. We then filtered possible false-positives in the predicted interactions using the phylogenetic profiles. We found that this filtering method significantly increased the frequency of interacting protein-pairs coexpressed in the same cells/tissues in gene expression omnibus (GEO) database as well as the frequency of interacting protein-pairs shared the similar Gene Ontology (GO) terms for biological processes and cellular localizations. The data supports the notion that phylogenetic profile helps to reduce the number of false positives in interologs. CONCLUSION: We have developed protein-protein interaction database in mouse, which contains 41109 interologs. We have also developed a web interface to facilitate the use of database http://lgsun.grc.nia.nih.gov/mppi/.

Genome scale portrait of cAMP-receptor protein (CRP) regulons in mycobacteria points to their role in pathogenesis.

cAMP Receptor Protein (CRP)/Fumarate Nitrate Reductase Regulator (FNR) family proteins are ubiquitous regulators of cell stress in eubacteria. These proteins are commonly associated with maintenance of intracellular oxygen levels, redox-state, oxidative and nitrosative stresses, and extreme temperature conditions by regulating expression of target genes that contain regulatory cognate DNA elements. We describe the use of informatics enabled comparative genomics to identify novel genes under the control of CRP regulator in Mycobacterium tuberculosis (M.tb). An inventory of CRP regulated genes and their operon context in important mycobacterial species such as M. leprae, M. avium subsp. paratuberculosis and M. smegmatis and several common genes within this genus including the important cellular functions, mainly, cell-wall biogenesis, cAMP signaling and metabolism associated with such regulons were identified. Our results provide a possible theoretical framework for better understanding of the stress response in mycobacteria. The conservation of the CRP regulated genes in pathogenic mycobacteria, as opposed to non-pathogenic ones, highlights the importance of CRP-regulated genes in pathogenesis.

iCR: a web tool to identify conserved targets of a regulatory protein across the multiple related prokaryotic species.

Gene regulatory circuits are often commonly shared between two closely related organisms. Our web tool iCR (identify Conserved target of a Regulon) makes use of this fact and identify conserved targets of a regulatory protein. iCR is a special refined extension of our previous tool PredictRegulon- that predicts genome wide, the potential binding sites and target operons of a regulatory protein in a single user selected genome. Like PredictRegulon, the iCR accepts known binding sites of a regulatory protein as ungapped multiple sequence alignment and provides the potential binding sites. However important differences are that the user can select more than one genome at a time and the output reports the genes that are common in two or more species. In order to achieve this, iCR makes use of Cluster of Orthologous Group (COG) indices for the genes. This tool analyses the upstream region of all user-selected prokaryote genome and gives the output based on conservation target orthologs. iCR also reports the Functional class codes based on COG classification for the encoded proteins of downstream genes which helps user understand the nature of the co-regulated genes at the result page itself. iCR is freely accessible at http://www.cdfd.org.in/icr/.

System-wide coordinates of higher order functions in host-pathogen environment upon Mycobacterium tuberculosis infection.

Molecular signatures and their interactions behind the successful establishment of infection of Mycobacterium tuberculosis (Mtb) inside macrophage are largely unknown. In this work, we present an inter-system scale atlas of the gene expression signatures, their interactions and higher order gene functions of macrophage-Mtb environment at the time of infection. We have carried out large-scale meta-analysis of previously published gene expression microarray studies andhave identified a ranked list of differentially expressed genes and their higher order functions in intracellular Mtb as well as the infected macrophage. Comparative analysis of gene expression signatures of intracellular Mtb with the in vitro dormant Mtb at different hypoxic and oxidative stress conditions led to the identification of the large number of Mtb functional groups, namely operons, regulons and pathways that were common and unique to the intracellular environment and dormancy state. Some of the functions that are specific to intracellular Mtb are cholesterol degradation and biosynthesis of immunomodulatory phenolic compounds. The molecular signatures we have identified to be involved in adaptation to different stress conditions in macrophage environment may be critical for designing therapeutic interventions against tuberculosis. And, our approach may be broadly applicable for investigating other host-pathogen interactions.

RNA sequencing of murine mammary epithelial stem-like cells (HC11) undergoing lactogenic differentiation and its comparison with embryonic stem cells.

OBJECTIVES: Understanding of transcriptional networks specifying HC11 murine mammary epithelial stem cell-like cells (MEC) in comparison with embryonic stem cells (ESCs) and their rewiring, under the influence of glucocorticoids (GC) and prolactin (PRL) hormones, is critical for elucidating the mechanism of lactogenesis. In this data note, we provide RNA sequencing data from murine MECs and ESCs, MECs treated with steroid hormone alone and in combination with PRL. This data could help in understanding temporal dynamics of mRNA transcription that impact the process of lactogenesis associated with mammary gland development. Further integration of these data sets with existing datasets of cells derived from various stages of mammary gland development and different types of breast tumors, should pave the way for effective prognosis and to develop therapies for breast cancer. DATA DESCRIPTION: We have generated RNA-sequencing data representing steady-state levels of mRNAs from murine ESCs, normal MECs (N), MECs primed (P) with hydrocortisone (HC) alone and in combination with PRL hormone by using Illumina sequencing platform. We have generated ~ 58 million reads for ESCs with an average length of ~ 100 nt and an average 115 million good quality mapped reads with an average length of ~ 150 nt for different stages of MECs differentiation.

Comprehensive profiling of transcriptional networks specific for lactogenic differentiation of HC11 mammary epithelial stem-like cells.

The development of mammary gland as a lactogenic tissue is a highly coordinated multistep process. The epithelial cells of lactiferous tubules undergo profound changes during the developmental window of puberty, pregnancy, and lactation. Several hormones including estrogen, progesterone, glucocorticoids and prolactin act in concert, and orchestrate the development of mammary gland. Understanding the gene regulatory networks that coordinate proliferation and differentiation of HC11 Mammary Epithelial stem-like Cells (MEC) under the influence of lactogenic hormones is critical for elucidating the mechanism of lactogenesis in detail. In this study, we analyzed transcriptome profiles of undifferentiated MEC (normal) and compared them with Murine Embryonic Stem Cells (ESC) using next-generation mRNA sequencing. Further, we analyzed the transcriptome output during lactogenic differentiation of MEC following treatment with glucocorticoids (primed state) and both glucocorticoids and prolactin together (prolactin state). We established stage-specific gene regulatory networks in ESC and MEC (normal, priming and prolactin states). We validated the top up-and downregulated genes in each stage of differentiation of MEC by RT-PCR and found that they are comparable with that of RNA-seq data. HC11 MEC display decreased expression of Pou5f1 and Sox2, which is crucial for the differentiation of MEC, which otherwise ensure pluripotency to ESC. Cited4 is induced during priming and is involved in milk secretion. MEC upon exposure to both glucocorticoids and prolactin undergo terminal differentiation, which is associated with the expression of several genes, including Xbp1 and Cbp that are required for cell growth and differentiation. Our study also identified differential expression of transcription factors and epigenetic regulators in each stage of lactogenic differentiation. We also analyzed the transcriptome data for the pathways that are selectively activated during lactogenic differentiation. Further, we found that selective expression of chromatin modulators (Dnmt3l, Chd9) in response to glucocorticoids suggests a highly coordinated stage-specific lactogenic differentiation of MEC.

Inhibitors of Apoptosis Protein Antagonists (Smac Mimetic Compounds) Control Polarization of Macrophages during Microbial Challenge and Sterile Inflammatory Responses.

Apoptosis is a physiological cell death process essential for development, tissue homeostasis, and for immune defense of multicellular animals. Inhibitors of apoptosis proteins (IAPs) regulate apoptosis in response to various cellular assaults. Using both genetic and pharmacological approaches we demonstrate here that the IAPs not only support opportunistic survival of intracellular human pathogens like Chlamydia pneumoniae but also control plasticity of iNOS+ M1 macrophage during the course of infection and render them refractory for immune stimulation. Treatment of Th1 primed macrophages with birinapant (IAP-specific antagonist) inhibited NO generation and relevant proteins involved in innate immune signaling. Accordingly, birinapant promoted hypoxia, angiogenesis, and tumor-induced M2 polarization of iNOS+ M1 macrophages. Interestingly, birinapant-driven changes in immune signaling were accompanied with changes in the expression of various proteins involved in the metabolism, and thus revealing the new role of IAPs in immune metabolic reprogramming in committed macrophages. Taken together, our study reveals the significance of IAP targeting approaches (Smac mimetic compounds) for the management of infectious and inflammatory diseases relying on macrophage plasticity.

Comparative analysis of iron regulated genes in mycobacteria.

Iron dependent regulator, IdeR, regulates the expression of genes in response to intracellular iron levels in M. tuberculosis. Orthologs of IdeR are present in all the sequenced genomes of mycobacteria. We have used a computational approach to identify conserved IdeR regulated genes across the mycobacteria and the genes that are specific to each of the mycobacteria. Novel iron regulated genes that code for a predicted 4-hydroxy benzoyl coA hydrolase (Rv1847) and a protease dependent antibiotic regulatory system (Rv1846c, Rv0185c) are conserved across the mycobacteria. Although Mycobacterium natural-resistance-associated macrophage protein (Mramp) is present in all mycobacteria, it is, as predicted, an iron-regulated gene in only one species, M. avium subsp. paratuberculosis. We also observed an additional iron-regulated exochelin biosynthetic operon, which is present only in non-pathogenic Mycobacterium, M. smegmatis.

PredictRegulon: a web server for the prediction of the regulatory protein binding sites and operons in prokaryote genomes.

An interactive web server is developed for predicting the potential binding sites and its target operons for a given regulatory protein in prokaryotic genomes. The program allows users to submit known or experimentally determined binding sites of a regulatory protein as ungapped multiple sequence alignments. It analyses the upstream regions of all genes in a user-selected prokaryote genome and returns the potential binding sites along with the downstream co-regulated genes (operons). The known binding sites of a regulatory protein can also be used to identify its orthologue binding sites in phylogeneticaly related genomes where the trans-acting regulator protein and cognate cis-acting DNA sequences could be conserved. PredictRegulon can be freely accessed from a link on our world wide web server: http://www.cdfd.org.in/predictregulon/.

Identification and functional analysis of essential, conserved, housekeeping and duplicated genes.

Gene conservation, duplication and constitutive expression are intricately linked and strong predictors of essentiality. Here, we introduce metrics based on diversity indices to measure gene conservation, duplication and constitutive expression and validate them by measuring their performance in prediction of essential genes. Conservation and duplication were measured using the diversity indices on the bit score profile of Escherichia coli K12 orthologues, across the genomes, and paralogues, within the genome respectively. Constitutive expression was measured using expression diversity of E. coli K12 genes across different conditions. In addition, we developed a systematic method for enrichment analysis of gene-sets in a given ranked list of genes. The method was used to identify genome-wide functions of essential, conserved, constitutively expressed and duplicated genes. Furthermore, we also ranked various operons, complexes and pathways according to their essentiality, conservation, constitutive expression and duplication.

Prediction of DtxR regulon: identification of binding sites and operons controlled by Diphtheria toxin repressor in Corynebacterium diphtheriae.

BACKGROUND: The diphtheria toxin repressor, DtxR, of Corynebacterium diphtheriae has been shown to be an iron-activated transcription regulator that controls not only the expression of diphtheria toxin but also of iron uptake genes. This study aims to identify putative binding sites and operons controlled by DtxR to understand the role of DtxR in patho-physiology of Corynebacterium diphtheriae. RESULT: Positional Shannon relative entropy method was used to build the DtxR-binding site recognition profile and the later was used to identify putative regulatory sites of DtxR within C. diphtheriae genome. In addition, DtxR-regulated operons were also identified taking into account the predicted DtxR regulatory sites and genome annotation. Few of the predicted motifs were experimentally validated by electrophoretic mobility shift assay. The analysis identifies motifs upstream to the novel iron-regulated genes that code for Formamidopyrimidine-DNA glycosylase (FpG), an enzyme involved in DNA-repair and starvation inducible DNA-binding protein (Dps) which is involved in iron storage and oxidative stress defense. In addition, we have found the DtxR motifs upstream to the genes that code for sortase which catalyzes anchoring of host-interacting proteins to the cell wall of pathogenic bacteria and the proteins of secretory system which could be involved in translocation of various iron-regulated virulence factors including diphtheria toxin. CONCLUSIONS: We have used an in silico approach to identify the putative binding sites and genes controlled by DtxR in Corynebacterium diphtheriae. Our analysis shows that DtxR could provide a molecular link between Fe+2-induced Fenton's reaction and protection of DNA from oxidative damage. DtxR-regulated Dps prevents lethal combination of Fe+2 and H2O2 and also protects DNA by nonspecific DNA-binding. In addition DtxR could play an important role in host interaction and virulence by regulating the levels of sortase, a potential vaccine candidate and proteins of secretory system.

Comparing transcription rate and mRNA abundance as parameters for biochemical pathway and network analysis.

The cells adapt to extra- and intra-cellular signals by dynamic orchestration of activities of pathways in the biochemical networks. Dynamic control of the gene expression process represents a major mechanism for pathway activity regulation. Gene expression has thus been routinely measured, most frequently at steady-state mRNA abundance level using micro-array technology. The results are widely used in statistical inference of the structures of underlying biochemical networks, with the assumption that functionally related genes exhibit similar dynamic profiles. Steady-state mRNA abundance, however, is a composite of two factors: transcription rate and mRNA degradation rate. The question being asked here is therefore whether steady-state mRNA abundance or any of two factors is a more informative measurement target for studying network dynamics. The yeast S. cerevisiae was used as model organism and transcription rate was chosen out of the two factors in this study, because genome-wide determination of transcription rates has been reported for several physiological processes in this species. Our strategy is to test which one is a better measurement of functional relatedness between genes. The analysis was performed on those S. cerevisiae genes that have bacterial orthologs as identified by reciprocal BLAST analysis, so that functional relatedness of a gene pair can be measured by the frequency at which their bacterial orthologs co-occur in the same operon in the collection of bacterial genomes. It is found that transcription rate data is generally a better parameter for functional relatedness than steady state mRNA abundance, suggesting transcription rate data is more informative to use in deciphering the logics used by the cells in dynamic regulation of biochemical network behaviors. The significance of this finding for network and systems biology, as well as biomedical research in general, is discussed.