Dataset Information

Accurate measurements of dynamics and reproducibility in small genetic networks.

ABSTRACT: Quantification of gene expression has become a central tool for understanding genetic networks. In many systems, the only viable way to measure protein levels is by immunofluorescence, which is notorious for its limited accuracy. Using the early Drosophila embryo as an example, we show that careful identification and control of experimental error allows for highly accurate gene expression measurements. We generated antibodies in different host species, allowing for simultaneous staining of four Drosophila gap genes in individual embryos. Careful error analysis of hundreds of expression profiles reveals that less than ?20% of the observed embryo-to-embryo fluctuations stem from experimental error. These measurements make it possible to extract not only very accurate mean gene expression profiles but also their naturally occurring fluctuations of biological origin and corresponding cross-correlations. We use this analysis to extract gap gene profile dynamics with ?1?min accuracy. The combination of these new measurements and analysis techniques reveals a twofold increase in profile reproducibility owing to a collective network dynamics that relays positional accuracy from the maternal gradients to the pair-rule genes.

SUBMITTER: Dubuis JO

PROVIDER: S-EPMC3564256 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Accurate measurements of dynamics and reproducibility in small genetic networks.

Dubuis Julien O JO Samanta Reba R Gregor Thomas T

Molecular systems biology 20130101

Quantification of gene expression has become a central tool for understanding genetic networks. In many systems, the only viable way to measure protein levels is by immunofluorescence, which is notorious for its limited accuracy. Using the early Drosophila embryo as an example, we show that careful identification and control of experimental error allows for highly accurate gene expression measurements. We generated antibodies in different host species, allowing for simultaneous staining of four ...[more]

PMID: 23340845

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Project description:INTRODUCTION:Quantitative longitudinal magnetic resonance imaging and spectroscopy (MRI/S) is used to assess progress of brain disorders and treatment effects. Understanding the significance of MRI/S changes requires knowledge of the inherent technical and physiological consistency of these measurements. This longitudinal study examined the variance and reproducibility of commonly used quantitative MRI/S measurements in healthy subjects while controlling physiological and technical parameters. METHODS:Twenty-five subjects were imaged three times over 5 days on a Siemens 3T Verio scanner equipped with a 32-channel phase array coil. Structural (T1, T2-weighted, and diffusion-weighted imaging) and physiological (pseudocontinuous arterial spin labeling, proton magnetic resonance spectroscopy) data were collected. Consistency of repeated images was evaluated with mean relative difference, mean coefficient of variation, and intraclass correlation (ICC). Finally, a "reproducibility rating" was calculated based on the number of subjects needed for a 3% and 10% difference. RESULTS:Structural measurements generally demonstrated excellent reproducibility (ICCs 0.872-0.998) with a few exceptions. Moderate-to-low reproducibility was observed for fractional anisotropy measurements in fornix and corticospinal tracts, for cortical gray matter thickness in the entorhinal, insula, and medial orbitofrontal regions, and for the count of the periependymal hyperintensive white matter regions. The reproducibility of physiological measurements ranged from excellent for most of the magnetic resonance spectroscopy measurements to moderate for permeability-diffusivity coefficients in cingulate gray matter to low for regional blood flow in gray and white matter. DISCUSSION:This study demonstrates a high degree of longitudinal consistency across structural and physiological measurements in healthy subjects, defining the inherent variability in these commonly used sequences. Additionally, this study identifies those areas where caution should be exercised in interpretation. Understanding this variability can serve as the basis for interpretation of MRI/S data in the assessment of neurological disorders and treatment effects.

Dataset Information

Accurate measurements of dynamics and reproducibility in small genetic networks.

Publications

Accurate measurements of dynamics and reproducibility in small genetic networks.

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