Gene Expression Data Explorer
Info Gene counts are sourced from ARCHS4, which provides uniform alignment of GEO samples. You can learn more about ARCHS4 and its pipeline here.
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GROUP CONDITION SAMPLES
C57BL/6 NIA male mice; age 12 months
GSM2711611 GSM2711612 GSM2711613 GSM2711614 GSM2711615 GSM2711616
GSM2711606 GSM2711607 GSM2711608 GSM2711609 GSM2711610
GSM2711593 GSM2711594 GSM2711595 GSM2711596 GSM2711597 GSM2711598
GSM2711599 GSM2711600 GSM2711601 GSM2711602 GSM2711603 GSM2711604 GSM2711605
GSM2711617 GSM2711618 GSM2711619 GSM2711620 GSM2711621 GSM2711622 GSM2711623
GSM2711588 GSM2711589 GSM2711590 GSM2711591 GSM2711592
Description

Submission Date: Jul 19, 2017

Summary: The ketone body β-hydroxybutyrate (BHB) is produced during dietary restriction, fasting, and exercise. A ketogenic diet (KD) results in long-term production of BHB outside of these contexts. We sought to determine a protein-matched, non-obese ketogenic diet (KD) would affect the longevity and healthspan of C57BL/6 male mice. We find that feeding KD every-other-week to prevent obesity (cyclic KD) reduces mid-life mortality but does not affect maximum lifespan. Similar feeding of a non-ketogenic high-fat/low-carbohydrate (HF) diet may have an intermediate effect on mortality. Cyclic KD improves memory performance in old age, while modestly improving composite measures of healthspan. RNAseq gene expression analysis identifies down-regulation of insulin, TOR, and fatty acid synthesis pathways as possible longevity mechanisms common to KD and HF. However, up-regulation of fasting-related PPARα target genes is unique to KD, consistent across tissues, and preserved in old age, suggesting a mechanism for an incremental benefit from KD. In all, we show that a non-obese ketogenic diet improves survival, memory, and healthspan into old age. These gene expression studies were carried out on 12 month-old male C56BL/6 mice from the NIA Aged Rodent Colony, habituated to AIN-93M control diet and then either maintained on this diet or switched for one week to a 75% kcal fat non-ketogenic high-fat diet or a 90% kcal fat ketogenic diet (all diets with 10% kcal from carbohydrates). Tissues were harvested in the middle of the nighttime feeding period (MN-3am).

GEO Accession ID: GSE101657

PMID: No Pubmed ID

Description

Submission Date: Jul 19, 2017

Summary: The ketone body β-hydroxybutyrate (BHB) is produced during dietary restriction, fasting, and exercise. A ketogenic diet (KD) results in long-term production of BHB outside of these contexts. We sought to determine a protein-matched, non-obese ketogenic diet (KD) would affect the longevity and healthspan of C57BL/6 male mice. We find that feeding KD every-other-week to prevent obesity (cyclic KD) reduces mid-life mortality but does not affect maximum lifespan. Similar feeding of a non-ketogenic high-fat/low-carbohydrate (HF) diet may have an intermediate effect on mortality. Cyclic KD improves memory performance in old age, while modestly improving composite measures of healthspan. RNAseq gene expression analysis identifies down-regulation of insulin, TOR, and fatty acid synthesis pathways as possible longevity mechanisms common to KD and HF. However, up-regulation of fasting-related PPARα target genes is unique to KD, consistent across tissues, and preserved in old age, suggesting a mechanism for an incremental benefit from KD. In all, we show that a non-obese ketogenic diet improves survival, memory, and healthspan into old age. These gene expression studies were carried out on 12 month-old male C56BL/6 mice from the NIA Aged Rodent Colony, habituated to AIN-93M control diet and then either maintained on this diet or switched for one week to a 75% kcal fat non-ketogenic high-fat diet or a 90% kcal fat ketogenic diet (all diets with 10% kcal from carbohydrates). Tissues were harvested in the middle of the nighttime feeding period (MN-3am).

GEO Accession ID: GSE101657

PMID: No Pubmed ID

Visualize Samples

Info Visualizations are precomputed using the Python package scanpy on the top 5000 most variable genes.

Precomputed Differential Gene Expression

Info Differential expression signatures are automatically computed using the limma R package. More options for differential expression are available to compute below.

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Perturbation Condition

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Differential Gene Expression Analysis
Info Differential expression signatures can be computed using DESeq2 or characteristic direction.
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Bulk RNA-seq Appyter

This pipeline enables you to analyze and visualize your bulk RNA sequencing datasets with an array of downstream analysis and visualization tools. The pipeline includes: PCA analysis, Clustergrammer interactive heatmap, library size analysis, differential gene expression analysis, enrichment analysis, and L1000 small molecule search.