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Single same cell RNAseq/ATACseq multiome data provide unparalleled potential to develop high resolution maps of the cell-type specific transcriptional regulatory circuitry underlying gene expression. We present CREMA, a framework that recovers the full cis-regulatory circuitry by modeling gene expression and chromatin activity in individual cells without peak-calling or cell type labeling constraints. We demonstrate that CREMA overcomes the limitations of existing methods that fail to identify about half of functional regulatory elements which are outside the called chromatin 'peaks'. These circuit sites outside called peaks are shown to be important cell type specific functional regulatory loci, sufficient to distinguish individual cell types. Analysis of mouse pituitary data identifies a Gata2-circuit for the gonadotrope-enriched disease-associated Pcsk1 gene, which is experimentally validated by reduced gonadotrope expression in a gonadotrope conditional Gata2-knockout model. We present a web accessible human immune cell regulatory circuit resource, and provide CREMA as an R package., (© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Follicle-stimulating hormone (FSH), a dimeric glycoprotein produced by pituitary gonadotrope cells, regulates spermatogenesis in males and ovarian follicle growth in females. Hypothalamic gonadotropin-releasing hormone (GnRH) stimulates FSHβ subunit gene (Fshb) transcription, though the underlying mechanisms are poorly understood. To address this gap in knowledge, we examined changes in pituitary gene expression in GnRH-deficient mice (hpg) treated with a regimen of exogenous GnRH that increases pituitary Fshb but not luteinizing hormone β (Lhb) messenger RNA levels. Activating transcription factor 3 (Atf3) was among the most upregulated genes. Activating transcription factor 3 (ATF3) can heterodimerize with members of the activator protein 1 family to regulate gene transcription. Co-expression of ATF3 with JunB stimulated murine Fshb, but not Lhb, promoter-reporter activity in homologous LβT2b cells. ATF3 also synergized with a constitutively active activin type I receptor to increase endogenous Fshb expression in these cells. Nevertheless, FSH production was intact in gonadotrope-specific Atf3 knockout [conditional knockout (cKO)] mice. Ovarian follicle development, ovulation, and litter sizes were equivalent between cKOs and controls. Testis weights and sperm counts did not differ between genotypes. Following gonadectomy, increases in LH secretion were enhanced in cKO animals. Though FSH levels did not differ between genotypes, post-gonadectomy increases in pituitary Fshb and gonadotropin α subunit expression were more pronounced in cKO than control mice. These data indicate that ATF3 can selectively stimulate Fshb expression in vitro but is not required for FSH production in vivo., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: The development of memory B cells after asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is not well understood., Methods: We compared spike antibody titers, pseudovirus neutralizing antibody titers, and memory B-cell responses among SARS-CoV-2 PCR-positive Marine recruits who either reported asymptomatic or symptomatic infection., Results: Thirty-six asymptomatic participants exhibited similar spike IgG titers, spike IgA titers, and pseudovirus neutralization titers compared to 30 symptomatic participants. Pseudovirus neutralization and spike IgG titers showed significant positive correlations with frequency of memory B cells., Conclusions: Among young adults, asymptomatic SARS-CoV-2 infection induced antibody and memory B-cell responses comparable to mild symptomatic infection., Competing Interests: Potential conflicts of interest. S. C. has consulted for GSK, JP Morgan, Citi, Morgan Stanley, Avalia NZ, Nutcracker Therapeutics, University of California, California State Universities, United Airlines, Adagio, and Roche. All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (Published by Oxford University Press on behalf of Infectious Diseases Society of America 2022.)

The inhibins control reproduction by suppressing follicle-stimulating hormone synthesis in pituitary gonadotrope cells. The newly discovered inhibin B coreceptor, TGFBR3L, is selectively and highly expressed in gonadotropes in both mice and humans. Here, we describe our initial characterization of mechanisms controlling cell-specific Tgfbr3l/TGFBR3L transcription. We identified two steroidogenic factor 1 (SF-1 or NR5A1) cis-elements in the proximal Tgfbr3l promoter in mice. SF-1 induction of murine Tgfbr3l promoter-reporter activity was inhibited by mutations in one or both sites in heterologous cells. In homologous cells, mutation of these cis-elements or depletion of endogenous SF-1 similarly decreased reporter activity. We observed nearly identical results when using a human TGFBR3L promoter-reporter. The Tgfbr3l gene was tightly compacted and Tgfbr3l mRNA expression was essentially absent in gonadotropes of SF-1 (Nr5a1) conditional knockout mice. During murine embryonic development, Tgfbr3l precedes Nr5a1 expression, though the two transcripts are fully colocalized by embryonic day 18.5 and thereafter. Collectively, these data indicate that SF-1 directly regulates Tgfbr3l/TGFBR3L transcription and is required for postnatal expression of the gene in gonadotropes., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Immediate-early response genes (IEGs) are rapidly and transiently induced following an extracellular signal. Elucidating the IEG response patterns in single cells (SCs) requires assaying large numbers of timed samples at high accuracy while minimizing handling effects. To achieve this, we developed and validated RNA stabilization Buffer for Examination of Single-cell Transcriptomes (RNA-Best), a versatile single-step cell and tissue preservation protocol that stabilizes RNA in intact SCs without perturbing transcription patterns. We characterize for the first time SC heterogeneity in IEG responses to pulsatile gonadotropin-releasing hormone (GnRH) stimuli in pituitary gonadotrope cells. Our study identifies a gene-specific hierarchical pattern of all-or-none transcript induction elicited by increasing concentrations of GnRH. This quantal pattern of gene activation raises the possibility that IEG activation, when accurately resolved at the SC level, may be mediated by gene bits that behave as pure binary switches.

Unlabelled: MATLAB is popular in biological research for creating and simulating models that use ordinary differential equations (ODEs). However, sharing or using these models outside of MATLAB is often problematic. A community standard such as Systems Biology Markup Language (SBML) can serve as a neutral exchange format, but translating models from MATLAB to SBML can be challenging-especially for legacy models not written with translation in mind. We developed MOCCASIN (Model ODE Converter for Creating Automated SBML INteroperability) to help. MOCCASIN can convert ODE-based MATLAB models of biochemical reaction networks into the SBML format., Availability and Implementation: MOCCASIN is available under the terms of the LGPL 2.1 license (http://www.gnu.org/licenses/lgpl-2.1.html). Source code, binaries and test cases can be freely obtained from https://github.com/sbmlteam/moccasin, Contact: : mhucka@caltech.edu, Supplementary Information: More information is available at https://github.com/sbmlteam/moccasin., (© The Author 2016. Published by Oxford University Press.)

Motivation: Identifying alterations in gene expression associated with different clinical states is important for the study of human biology. However, clinical samples used in gene expression studies are often derived from heterogeneous mixtures with variable cell-type composition, complicating statistical analysis. Considerable effort has been devoted to modeling sample heterogeneity, and presently, there are many methods that can estimate cell proportions or pure cell-type expression from mixture data. However, there is no method that comprehensively addresses mixture analysis in the context of differential expression without relying on additional proportion information, which can be inaccurate and is frequently unavailable., Results: In this study, we consider a clinically relevant situation where neither accurate proportion estimates nor pure cell expression is of direct interest, but where we are rather interested in detecting and interpreting relevant differential expression in mixture samples. We develop a method, Cell-type COmputational Differential Estimation (CellCODE), that addresses the specific statistical question directly, without requiring a physical model for mixture components. Our approach is based on latent variable analysis and is computationally transparent; it requires no additional experimental data, yet outperforms existing methods that use independent proportion measurements. CellCODE has few parameters that are robust and easy to interpret. The method can be used to track changes in proportion, improve power to detect differential expression and assign the differentially expressed genes to the correct cell type., (© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Motivation: Modern molecular technologies allow the collection of large amounts of high-throughput data on the functional attributes of genes. Often multiple technologies and study designs are used to address the same biological question such as which genes are overexpressed in a specific disease state. Consequently, there is considerable interest in methods that can integrate across datasets to present a unified set of predictions., Results: An important aspect of data integration is being able to account for the fact that datasets may differ in how accurately they capture the biological signal of interest. While many methods to address this problem exist, they always rely either on dataset internal statistics, which reflect data structure and not necessarily biological relevance, or external gold standards, which may not always be available. We present a new rank aggregation method for data integration that requires neither external standards nor internal statistics but relies on Bayesian reasoning to assess dataset relevance. We demonstrate that our method outperforms established techniques and significantly improves the predictive power of rank-based aggregations. We show that our method, which does not require an external gold standard, provides reliable estimates of dataset relevance and allows the same set of data to be integrated differently depending on the specific signal of interest., Availability: The method is implemented in R and is freely available at http://www.pitt.edu/~mchikina/BIRRA/., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Motivation: For flow cytometry data, there are two common approaches to the unsupervised clustering problem: one is based on the finite mixture model and the other on spatial exploration of the histograms. The former is computationally slow and has difficulty to identify clusters of irregular shapes. The latter approach cannot be applied directly to high-dimensional data as the computational time and memory become unmanageable and the estimated histogram is unreliable. An algorithm without these two problems would be very useful., Results: In this article, we combine ideas from the finite mixture model and histogram spatial exploration. This new algorithm, which we call flowPeaks, can be applied directly to high-dimensional data and identify irregular shape clusters. The algorithm first uses K-means algorithm with a large K to partition the cell population into many small clusters. These partitioned data allow the generation of a smoothed density function using the finite mixture model. All local peaks are exhaustively searched by exploring the density function and the cells are clustered by the associated local peak. The algorithm flowPeaks is automatic, fast and reliable and robust to cluster shape and outliers. This algorithm has been applied to flow cytometry data and it has been compared with state of the art algorithms, including Misty Mountain, FLOCK, flowMeans, flowMerge and FLAME., Availability: The R package flowPeaks is available at https://github.com/yongchao/flowPeaks., Contact: yongchao.ge@mssm.edu, Supplementary Information: Supplementary data are available at Bioinformatics online.

The induction of interferon beta (IFNB1) is a key event in the antiviral immune response. We studied the role of transcriptional noise in the regulation of the IFNB1 locus in primary cultures of human dendritic cells (DCs), which are important 'first responders' to viral infection. In single cell assays, IFNB1 mRNA expression in virus-infected DCs showed much greater cell-to-cell variation than that of a housekeeping gene, another induced transcript and viral RNA. We determined the contribution of intrinsic noise by measuring the allelic origin of transcripts in each cell and found that intrinsic noise is a very significant part of total noise. We developed a stochastic model to investigate the underlying mechanisms. We propose that the surprisingly high levels of IFNB1 transcript noise originate from the complexity of IFNB1 enhanceosome formation, which leads to a range up to many minutes in the differences within each cell in the time of activation of each allele.

The photostability and narrow emission spectra of non-organic quantum dot fluorophores (QDs) make them desirable candidates for fluorescent in situ hybridization (FISH) to study the expression of specific mRNA transcripts. We developed a novel method for direct QD labeling of modified oligonucleotide probes through streptavidin and biotin interactions, as well as protocols for their use in multiple-label FISH. We validated this technique in mouse brainstem sections. The subcellular localization of the vesicular monoamine transporter (Vmat2) mRNA corresponds when using probes labeled with two different QDs in the same hybridization. We developed protocols for combined direct QD FISH and QD immunohistochemical labeling within the same neurons as well as for simultaneous study of the subcellular distribution of multiple mRNA targets. We demonstrated increased sensitivity of FISH using QDs in comparison with organic fluorophores. These techniques gave excellent histological results both for multiplex FISH and combined FISH and immunohistochemistry. This approach can facilitate the ultrasensitive simultaneous study of multiple mRNA and protein markers in tissue culture and histological section.

Subsequent to demyelination in multiple sclerosis, myelin repair occurs but, as lesions age, the ability to remyelinate diminishes. Molecular pathways underlying oligodendrocyte behaviour during CNS remyelination remain to be elucidated. In this study, we report for the first time constitutive expression of the CXC/alpha chemokine receptors, CXCR1, CXCR2 and CXCR3, on oligodendrocytes in normal adult human CNS tissue, the levels of which were upregulated in multiple sclerosis and other neurological diseases (OND). In addition, both immature (A2B5+/O4+) and more mature (CNPase+) human oligodendrocytes in vitro expressed the same three receptors. The respective ligands to CXCR1, CXCR2 and CXCR3 [i.e. CXCL8/IL-8, CXCL1/GRO-alpha and CXCL10/IP-10), were absent in CNS tissue from normals and subjects with OND, but were present at high levels on hypertrophic (reactive) astrocytes at the edge of active (but not silent) multiple sclerosis lesions. Astrocytes in vitro could be induced to express chemokines following stimulation with pro-inflammatory cytokines. CXCL8 and CXCL1 production by human astrocytes at both the RNA and protein levels could be induced by interleukin (IL)-1beta, while CXCL10 was induced by both IL-1beta and interferon-gamma. Since these cytokines are integral to inflammatory events occurring at the margins of active multiple sclerosis lesions, their upregulation in these regions may underlie the dynamics of chemokine expression observed herein. The simultaneous expression of different CXC chemokine receptors on oligodendrocytes, and their ligands on astrocytes around multiple sclerosis lesions, may bespeak novel functional roles for these immune system molecules in the recruitment of oligodendrocytes and remyelination.

We compared the accuracy of microarray measurements obtained with oligonucleotide arrays (GeneChip, Affymetrix) with a laboratory-developed cDNA array by assaying test RNA samples from an experiment using a paradigm known to regulate many genes measured on both arrays. We selected 47 genes represented on both arrays, including both known regulated and unregulated transcripts, and established reference relative expression measurements for these genes in the test RNA samples using quantitative reverse transcriptase real-time PCR (QRTPCR) assays. The validity of the reproducible (average coefficient of variation = 11.8%) QRTPCR measurements were established through application of a new mathematical model. The performance of both array platforms in identifying regulated and non-regulated genes was identical. With either platform, 16 of 17 definitely regulated genes were correctly identified, and no definitely unregulated transcript was falsely identified as regulated. Accuracy of the fold-change measurements obtained with each platform was assessed by determining measurement bias. Both platforms consistently underestimate the relative changes in mRNA expression between experimental and control samples. The bias observed with cDNA arrays was predictable for fold-changes <250-fold by QRTPCR and could be corrected by the calibration function F(c) = F(a(cDNA))(q), where F(a(cDNA)) is the microarray-determined fold-change comparing experimental with control samples, q is the correction factor and F(c) is the calibrated value. The bias observed with the commercial oligonucleotide arrays was less predictable and calibration was unfeasible. Following calibration, fold-change measurements generated by custom cDNA arrays were more accurate than those obtained by commercial oligonucleotide arrays. Our study demonstrates systematic bias of microarray measurements and identifies a calibration function that improves the accuracy of cDNA array data.

Prolonged exposure of the GnRH receptor to high concentrations of GnRH leads to receptor down-regulation. The role of altered receptor biosynthesis in this agonist-induced receptor down-regulation was investigated in the mouse gonadotrope cell line, alpha T3-1 cells. After exposure to 1 microM GnRH for 24 h, the number of GnRH receptor-binding sites in alpha T3-1 cells decreased to 25 +/- 6% of the control levels. No corresponding changes were observed in GnRH receptor messenger RNA (mRNA) using either quantitative ribonuclease protection/solution hybridization assay or Northern blot analysis. However, when the ability of this RNA to direct the synthesis of functional GnRH receptors was examined by quantitative assessment of the voltage clamp response in Xenopus oocytes, GnRH-induced currents in oocytes injected with RNA isolated from down-regulated cells was reduced to 40 +/- 13% of the response obtained after the injection of RNA from control alpha T3-1 cells. Thus, although GnRH receptor mRNA levels were not altered, the ability of cellular RNA isolated from alpha T3-1 cells to direct the synthesis of functional GnRH receptors was regulated in concert with receptor binding. To investigate the possibility that GnRH receptor mRNA translational efficiency was reduced, the distribution of polyribosome-associated GnRH receptor mRNA was studied. Polyribosome-associated mRNA was separated by linear sucrose gradient, and GnRH receptor mRNA distribution was determined by ribonuclease protection assay. GnRH receptor mRNA distribution shifted from the largest to smaller polyribosome and monosome fractions in cells exposed to GnRH compared to controls. The weighted mean of GnRH receptor mRNA distribution among eight fractions shifted from fraction 5.924 +/- 0.06 in control polysomes to fraction 5.45 +/- 0.219 for polysomes from down-regulated cells (P < 0.05). These results demonstrate that GnRH receptor down-regulation is accompanied by decreased GnRH receptor mRNA translation in the absence of any change in GnRH receptor mRNA levels. These data suggest that decreased efficiency of GnRH receptor mRNA translation contributes to the down-regulation of this receptor in alpha T3-1 cells.

GnRH regulates the synthesis and secretion of pituitary gonadotropins. The number of receptors for GnRH (GnRH-rec) can vary from 500 to 15,000-20,000/gonadotrope in ovine pituitary cultures after treatment with physiologically relevant combinations of gonadal hormones. This large range suggests that regulation of GnRH-rec expression may be an important control point in GnRH action at the pituitary level. Reported here are the changes in GnRH-rec mRNA associated with pituitary treatments (48 h) of 17 beta-estradiol (E), progesterone (P), and an enriched preparation of porcine follicular inhibin (IN). Northern blot analysis was used to detect 3 species of GnRH-rec mRNA in primary ovine pituitary culture [5.5 kilobases (kb; 32%), 3.6 kb (51%), and 1.4 kb (17%)]; all were changed in parallel by E, P, and IN. GnRH-rec mRNAs were increased 190% over control levels after treatment with either E or IN, and 400% with E and IN combined; when E and IN were added along with P, the increase was only 50% (P caused an 87% inhibition of E plus IN induction). The addition of P in the absence of any other treatment reduced levels of GnRH-rec mRNA by 50%. Studies were also conducted with GnRH agonists (GnRH-A) due to their widespread clinical use for down-regulating reproductive function in men and women. The addition of GnRH-A to cultures was as effective as P in blocking E plus IN induction of GnRH-rec mRNA. In vivo studies in wethers showed that 7 days of chronic treatment with GnRH-A decreased all sizes of ovine GnRH-rec mRNA by 84-89%. These data indicate that E, P, and IN change GnRH-rec levels at least in part by changing levels of GnRH-rec mRNAs. They also show that GnRH-A can almost entirely block E plus IN induction of GnRH-rec mRNA in vitro and decrease levels of GnRH-rec mRNA in vivo in wethers.