Identification of conserved transcriptome features between humans and Drosophila in the aging brain utilizing machine learning on combined data from the NIH Sequence Read Archive.

J L Webb ,Simon M Moe,Andrew Bolstad ,Elizabeth Mcneill

doi:10.1371/journal.pone.0255085

Abstract

Aging is universal, yet characterizing the molecular changes that occur in aging which lead to an increased risk for neurological disease remains a challenging problem. Aging affects the prefrontal cortex (PFC), which governs executive function, learning, and memory. Previous sequencing studies have demonstrated that aging alters gene expression in the PFC, however the extent to which these changes are conserved across species and are meaningful in neurodegeneration is unknown. Identifying conserved, age-related genetic and morphological changes in the brain allows application of the wealth of tools available to study underlying mechanisms in model organisms such as Drosophila melanogaster. RNA sequencing data from human PFC and fly heads were analyzed to determine conserved transcriptome signatures of age. Our analysis revealed that expression of 50 conserved genes can accurately determine age in Drosophila (R2 = 0.85) and humans (R2 = 0.46). These transcriptome signatures were also able to classify Drosophila into three age groups with a mean accuracy of 88% and classify human samples with a mean accuracy of 69%. Overall, this work identifies 50 highly conserved aging-associated genetic changes in the brain that can be further studied in model organisms and demonstrates a novel approach to uncovering genetic changes conserved across species from multi-study public databases.

Highlights

Employing a comparative approach to study conserved aging phenotypes across multiple species provides a deeper insight into molecular aging signatures than studying aging within a single organism
From a comparative biology perspective, such conserved genes should play an important role in age-related physiological changes in the prefrontal cortex (PFC) and comprise a promising target set for future mechanistic analysis in Drosophila, a model organism with a short lifespan and well-established genetic tools
To obtain a higher analytical power than typically feasible from a single experiment in human prefrontal cortex and Drosophila head, we explored methods and constraints for combining data from the National Institutes of Health Sequence Read Archive

Summary

Introduction

Employing a comparative approach to study conserved aging phenotypes across multiple species provides a deeper insight into molecular aging signatures than studying aging within a single organism. Identifying conserved age-related transcriptome changes across model organisms allows for more efficient mechanistic study and may uncover novel therapeutic pathways for preventing age-related cognitive decline or vulnerability to neurodegeneration. We demonstrate the utility of previously published, publicly available RNA sequencing datasets from humans and Drosophila to increase statistical power through combining samples across multiple laboratories This facilitates the identification of conserved aging genes in the human PFC/fly head in a unique approach that circumvents the prohibitive cost of collecting hundreds of cross-species samples in a single laboratory. From a comparative biology perspective, such conserved genes should play an important role in age-related physiological changes in the PFC and comprise a promising target set for future mechanistic analysis in Drosophila, a model organism with a short lifespan and well-established genetic tools. Similar techniques could be used to identify target orthologs in other model organisms and tissues in future analyses

Materials and methods

Ethics approval and consent to participate

Results

Discussion