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      Genome-wide transcriptomics of aging in the rotifer Brachionus manjavacas, an emerging model system

      research-article
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      BMC Genomics
      BioMed Central
      Aging, Rotifer, Monogonont, RNA-Seq, Transcriptome

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          Abstract

          Background

          Understanding gene expression changes over lifespan in diverse animal species will lead to insights to conserved processes in the biology of aging and allow development of interventions to improve health. Rotifers are small aquatic invertebrates that have been used in aging studies for nearly 100 years and are now re-emerging as a modern model system. To provide a baseline to evaluate genetic responses to interventions that change health throughout lifespan and a framework for new hypotheses about the molecular genetic mechanisms of aging, we examined the transcriptome of an asexual female lineage of the rotifer Brachionus manjavacas at five life stages: eggs, neonates, and early-, late-, and post-reproductive adults.

          Results

          There are widespread shifts in gene expression over the lifespan of B. manjavacas; the largest change occurs between neonates and early reproductive adults and is characterized by down-regulation of developmental genes and up-regulation of genes involved in reproduction. The expression profile of post-reproductive adults was distinct from that of other life stages. While few genes were significantly differentially expressed in the late- to post-reproductive transition, gene set enrichment analysis revealed multiple down-regulated pathways in metabolism, maintenance and repair, and proteostasis, united by genes involved in mitochondrial function and oxidative phosphorylation.

          Conclusions

          This study provides the first examination of changes in gene expression over lifespan in rotifers. We detected differential expression of many genes with human orthologs that are absent in Drosophila and C. elegans, highlighting the potential of the rotifer model in aging studies. Our findings suggest that small but coordinated changes in expression of many genes in pathways that integrate diverse functions drive the aging process. The observation of simultaneous declines in expression of genes in multiple pathways may have consequences for health and longevity not detected by single- or multi-gene knockdown in otherwise healthy animals. Investigation of subtle but genome-wide change in these pathways during aging is an important area for future study.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12864-017-3540-x) contains supplementary material, which is available to authorized users.

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          Most cited references52

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          Epigenetic Mechanisms of Longevity and Aging.

          Aging is an inevitable outcome of life, characterized by progressive decline in tissue and organ function and increased risk of mortality. Accumulating evidence links aging to genetic and epigenetic alterations. Given the reversible nature of epigenetic mechanisms, these pathways provide promising avenues for therapeutics against age-related decline and disease. In this review, we provide a comprehensive overview of epigenetic studies from invertebrate organisms, vertebrate models, tissues, and in vitro systems. We establish links between common operative aging pathways and hallmark chromatin signatures that can be used to identify "druggable" targets to counter human aging and age-related disease.
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            Meta-analysis of age-related gene expression profiles identifies common signatures of aging.

            Numerous microarray studies of aging have been conducted, yet given the noisy nature of gene expression changes with age, elucidating the transcriptional features of aging and how these relate to physiological, biochemical and pathological changes remains a critical problem. We performed a meta-analysis of age-related gene expression profiles using 27 datasets from mice, rats and humans. Our results reveal several common signatures of aging, including 56 genes consistently overexpressed with age, the most significant of which was APOD, and 17 genes underexpressed with age. We characterized the biological processes associated with these signatures and found that age-related gene expression changes most notably involve an overexpression of inflammation and immune response genes and of genes associated with the lysosome. An underexpression of collagen genes and of genes associated with energy metabolism, particularly mitochondrial genes, as well as alterations in the expression of genes related to apoptosis, cell cycle and cellular senescence biomarkers, were also observed. By employing a new method that emphasizes sensitivity, our work further reveals previously unknown transcriptional changes with age in many genes, processes and functions. We suggest these molecular signatures reflect a combination of degenerative processes but also transcriptional responses to the process of aging. Overall, our results help to understand how transcriptional changes relate to the process of aging and could serve as targets for future studies. http://genomics.senescence.info/uarrays/signatures.html. Supplementary data are available at Bioinformatics online.
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              Evaluation of genomic high-throughput sequencing data generated on Illumina HiSeq and Genome Analyzer systems

              Background The generation and analysis of high-throughput sequencing data are becoming a major component of many studies in molecular biology and medical research. Illumina's Genome Analyzer (GA) and HiSeq instruments are currently the most widely used sequencing devices. Here, we comprehensively evaluate properties of genomic HiSeq and GAIIx data derived from two plant genomes and one virus, with read lengths of 95 to 150 bases. Results We provide quantifications and evidence for GC bias, error rates, error sequence context, effects of quality filtering, and the reliability of quality values. By combining different filtering criteria we reduced error rates 7-fold at the expense of discarding 12.5% of alignable bases. While overall error rates are low in HiSeq data we observed regions of accumulated wrong base calls. Only 3% of all error positions accounted for 24.7% of all substitution errors. Analyzing the forward and reverse strands separately revealed error rates of up to 18.7%. Insertions and deletions occurred at very low rates on average but increased to up to 2% in homopolymers. A positive correlation between read coverage and GC content was found depending on the GC content range. Conclusions The errors and biases we report have implications for the use and the interpretation of Illumina sequencing data. GAIIx and HiSeq data sets show slightly different error profiles. Quality filtering is essential to minimize downstream analysis artifacts. Supporting previous recommendations, the strand-specificity provides a criterion to distinguish sequencing errors from low abundance polymorphisms.
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                Author and article information

                Contributors
                kgribble@mbl.edu
                dmarkwelch@mbl.edu
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                1 March 2017
                1 March 2017
                2017
                : 18
                : 217
                Affiliations
                ISNI 000000012169920X, GRID grid.144532.5, , Josephine Bay Paul Center for Comparative Molecular Biology and Evolution, Marine Biological Laboratory, ; Woods Hole, MA 02543 USA
                Article
                3540
                10.1186/s12864-017-3540-x
                5333405
                28249563
                b09b3bb2-aa76-483b-b3d8-8080c605f274
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 28 September 2016
                : 2 February 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000049, National Institute on Aging;
                Award ID: R01 AG037960-01
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2017

                Genetics
                aging,rotifer,monogonont,rna-seq,transcriptome
                Genetics
                aging, rotifer, monogonont, rna-seq, transcriptome

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