Genomics of Early Cardiac Dysfunction and Mortality in Obese<i>Drosophila melanogaster</i>

Phillips, Mark; Thomas, Misty D.; Ewunkem, Akamu J.; Rutledge, Grant A.; Barter, Thomas T.; Santos, Marta A.; Wong, Brandon D.; Arnold, Kenneth R.; Humphrey, Laura A.; Yan, Albert C.; Nouzille, Chloe; Sanchez, Isaias; Cabral, Larry G.; Bradley, Timothy J.; Mueller, Laurence D.; Graves, Joseph L.; Rose, Michael R.

doi:10.1086/706099

Cited by 9 publications

(22 citation statements)

References 55 publications

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“…Unlike the A and C populations where selection is defined by shifting reproductive windows, the S populations have been subjected to selection for increased starvation resistance. A full description of the S populations and how they were created can be found in Kezos et al (2019) 15 . Briefly, the 10 S populations (SCO 1-5a and SCO 1-5b ) were derived from the CO 1-5 populations with two replicates derived from each CO population (e.g., SCO 1a and SCO 1b were derived from CO 1 ).…”

Section: Experimental Populationsmentioning

confidence: 99%

“…Here the goal was to identify patterns of SNP differentiation between the A, C, and S populations that best predict key patterns of metabolomic differentiation. For this analysis, efforts were focused on 15 for the S populations). Genomic data was reprocessed to since the original studies used different version of the D. melanogaster reference genome.…”

Section: Linking Genome To Metabolomementioning

confidence: 99%

“…For this analysis, efforts were focused on significantly differentiated metabolites associated with the top ten enriched pathways from our GC-MS and LC-MS metabolomic profiling (see Supplementary Table 1 for list of metabolites, and Figures 2C and 3C for enriched pathways). SNP data came from previously published pool-seq DNA data from the (see Graves et al 2017 26 for DNA extraction details for the A and C populations, and Kezos et al 2019 15 for the S populations). Genomic data was reprocessed to since the original studies used different version of the D. melanogaster reference genome.…”

Section: Linking Genome To Metabolomementioning

confidence: 99%

“…Many studies using experimental evolution to study physiological mechanisms underlying longevity differences have focused on the relationship between stress tolerance and life span. For instance, selection for decreased rates of senescence and increased longevity have repeatably been shown to associate with improved desiccation and starvation resistance and vice-versa [11][12][13][14][15] . Physiological assays have then shown that differences in longevity associated stress tolerances in these systems are tied to differences in lipid, glycogen, and water content [15][16][17][18][19] .…”

Section: Introductionmentioning

confidence: 99%

“…However, with respect to longevity, we find similar mean lifespans in the C and S populations while the A populations tend to die at much younger ages (Figure 1A). Additionally, all populations are ultimately derived from a single ancestral population, differences between groups are known to be the result of selection on standing genetic variation 15,26 , and populations cluster genetically based on treatment (Figure 1B). As such, comparisons across the three groups have the potential to isolate and identify mechanisms specifically associated with longevity (i.e.…”

Section: Introductionmentioning

confidence: 99%

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Combining metabolomics and experimental evolution reveals key mechanisms underlying longevity differences in laboratory evolved Drosophila melanogaster populations

Phillips

Arnold

Vue

et al. 2021

Preprint

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Experimental evolution with Drosophila melanogaster has been used extensively for decades to study aging and longevity. In recent years, the addition of DNA and RNA sequencing to this framework has allowed researchers to leverage the statistical power inherent to experimental evolution study the genetic basis of longevity itself. Here we incorporated metabolomic data into to this framework to generate even deeper insights into the physiological and genetic mechanisms underlying longevity differences in three groups of experimentally evolved D. melanogaster populations with different aging and longevity patterns. Our metabolomic analysis found that aging alters mitochondrial metabolism through increased consumption of NAD+ and increased usage of the TCA cycle. Combining our genomic and metabolomic data produced a list of biologically relevant candidate genes. Among these candidates, we found significant enrichment for genes and pathways associated with neurological development and function, and carbohydrate metabolism. While we do not explicitly find enrichment for aging canonical genes, neurological dysregulation and carbohydrate metabolism are both known to be associated with accelerated aging and reduced longevity. Taken together, our results in total provide very plausible genetic mechanisms for what might be driving longevity differences in this experimental system. More broadly, our findings demonstrate the value of combining multiple types of omic data with experimental evolution when attempting to dissect mechanisms underlying complex and highly polygenic traits like aging.

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Section: Experimental Populationsmentioning

confidence: 99%

Section: Linking Genome To Metabolomementioning

confidence: 99%