Dataset Information

Growth of Heterostegina depressa under natural and laboratory conditions.

ABSTRACT: The use of micro-computed tomography (?CT) provides a unique opportunity to look inside the shells of larger benthic foraminifera to investigate their structure by measuring linear and volumetric parameters. For this study, gamonts/schizonts and agamonts of the species Heterostegina depressa d'Orbigny were examined by ?CT; each single chamber's volume was digitally measured. This approach enables cell growth to be recognised in terms of chamber volume sequence, which progressively increases until reproduction occurs. This sequence represents the ontogeny of the foraminiferal cell and has been used here to investigate controlling factors potentially affecting the process of chamber formation. This is manifested as instantaneous or periodic deviations of the realised chamber volumes derived from modelled growth functions. The results obtained on naturally grown specimens show oscillations in chamber volumes which can be modelled by sums of sinusoidal functions. A set of functions with similar periods in all investigated specimens points to lunar and tidal cycles. To determine whether such cyclic signals are genuine and not the effects of a theoretical model, the same analysis was conducted on specimens held in a closed laboratory facility, as they should not be affected by natural environmental effects. Surprisingly, similar cyclicities were observed in such samples. However, a solely genetic origin of these cycles couldn't be verified either. Therefore, detailed analysis on the phase equality of these growth oscillations have been done. This approach is pivotal for proving that the oscillatory patterns discovered in LBF are indeed genuine signals, and on how chamber growth might be influenced by tidal currents or lunar months.

SUBMITTER: Eder W

PROVIDER: S-EPMC5238945 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature

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Growth of <i>Heterostegina depressa</i> under natural and laboratory conditions.

Eder Wolfgang W Briguglio Antonino A Hohenegger Johann J

Marine micropaleontology 20151115

The use of micro-computed tomography (μCT) provides a unique opportunity to look inside the shells of larger benthic foraminifera to investigate their structure by measuring linear and volumetric parameters. For this study, gamonts/schizonts and agamonts of the species <i>Heterostegina depressa</i> d'Orbigny were examined by μCT; each single chamber's volume was digitally measured. This approach enables cell growth to be recognised in terms of chamber volume sequence, which progressively increas ...[more]

PMID: 28100933

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Project description:BACKGROUND: The transcript levels of many genes exhibit significant variation in tissue samples from inbred laboratory mice. A microarray experiment was designed to separate transcript abundance variation across samples from adipose, heart, kidney, and liver tissues of C57BL/6J mice into within-mouse and between-mouse components. Within-mouse variance captures variation due to heterogeneity of gene expression within tissues, RNA-extraction, and array processing. Between-mouse variance reflects differences in transcript levels between these genetically identical mice. Many biological sources can contribute to heterogeneous transcript levels within a tissue sample including inherent stochasticity of biochemical processes such as intrinsic and extrinsic noise within cells and differences in cell-type composition which can result from heterogeneity of stem and progenitor cell populations. Differences in global signaling patterns between individuals and micro-environmental influences such as interactions with pathogens and cage mates can also contribute to variation, but are likely to contribute more to the between-mouse variance component. RESULTS: The nature and extent of transcript abundance variation differs across tissues. Adipose has the largest total variance and the largest within-mouse variance. Liver has the smallest total variance, but it has the most between-mouse variation. Genes with high variability can be classified into groups with correlated patterns of expression that are enriched for specific biological functions. Variation between mice is associated with circadian rhythm, growth hormone signaling, immune response, androgen regulation, lipid metabolism, and the extracellular matrix. Genes showing correlated patterns of within mouse variation were also associated with biological functions, spatial connectivity of stochastic variation and heterogeneity of cell types within tissues. CONCLUSIONS: Genetically identical mice are individuals and they can experience different outcomes for medically important traits. This is reflected in the stochastic variation in gene expression observed between genetically identical mice. Much of the stochasticity has organismal, tissue, or spatial connectivity. Prior knowledge of the genes and functional classes of genes that are likely to vary in the absence of experimental perturbations, whether these are genetic or environmental, can inform experimental design decisions and the interpretation of gene expression data. Variation in gene expression in genetically identical mice sheds light on the impact of stochastic and micro-environmental factors and their phenotypic consequences.

Dataset Information

Growth of Heterostegina depressa under natural and laboratory conditions.

Publications

Growth of <i>Heterostegina depressa</i> under natural and laboratory conditions.

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