Genome-wide architecture of prolonged starvation adaptation in experimentally evolved Drosophila and comparative enrichment in human orthologs

  1. Gaurav Yadav
  2. Prachi Mishra
  3. Ranjan Kumar Sahu
  4. Vijendra Sharma
  5. Pawel Michalak
  6. Dau Dayal Aggarwal

  • Curated by eLife

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    eLife Assessment

    This study offers valuable insights into the genetic and evolutionary basis of the starvation response by confirming the hypothesis about the mito-nuclear etiology of this trait. The level of evidence is currently incomplete but could be improved if controls were designed better, particularly by including analysis of variation in the initial, common population prior to all treatments. Overall, this work would be interesting to a broad audience, beyond the Drosophila community, if the analysis of the candidate genes against Human ortholog loci were to be conducted with more careful controls.

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Abstract

Long-term starvation stress represents a strong evolutionary constraint across taxa, yet the genetic architecture underlying adaptation to sustained nutrient deprivation remains poorly resolved. We experimentally evolved Drosophila melanogaster under starvation stress for 60 generations, maintaining four starvation-selected populations and four matched controls, and then performed whole-genome resequencing. Starvation-selected populations exhibited extended survival and pronounced genome-wide restructuring, including the expansion of low-heterozygosity regions, reduced nucleotide diversity, and recurrent sweep signatures across replicates. Drift-aware allele-frequency modeling identified 3,578 single-nucleotide polymorphisms (SNPs) whose shifts exceeded neutral expectations, indicating widespread, parallel responses to sustained starvation. Mitochondrial pathways emerged as prominent targets: nuclear-encoded mitochondrial genes were significantly enriched among low-diversity, sweep-associated, and drift-exceeding loci, and the mitochondrial origin of replication harbored a sharply differentiated variant, suggesting a mito–nuclear component of starvation adaptation. Comparative analyses further showed that human orthologs of starvation-responsive fly genes were enriched for highly differentiated variants in selected 1000 Genomes populations, with regulators of TOR/S6K signaling recurring among loci in the extreme tails of population differentiation. Together, these results define a replicate-convergent and functionally coherent genomic response to prolonged starvation in Drosophila, comprising regional signatures of linked selection and distributed allele-frequency shifts exceeding neutral expectations, and connect laboratory selection in flies to population differentiation in human orthologs.

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  1. eLife

    eLife Assessment

    This study offers valuable insights into the genetic and evolutionary basis of the starvation response by confirming the hypothesis about the mito-nuclear etiology of this trait. The level of evidence is currently incomplete but could be improved if controls were designed better, particularly by including analysis of variation in the initial, common population prior to all treatments. Overall, this work would be interesting to a broad audience, beyond the Drosophila community, if the analysis of the candidate genes against Human ortholog loci were to be conducted with more careful controls.

  2. eLife

    Reviewer #1 (Public review):

    Summary:

    This manuscript presents a genome-wide investigation of the genetic architecture underlying adaptation to prolonged starvation in Drosophila melanogaster, using an E&R experimental design maintained across 60 generations. Four starvation-selected (SS) and four matched control (C) populations were whole-genome resequenced, and two complementary analytical frameworks, selective sweep inference combined with low-heterozygosity mapping, and a diffusion-based drift-filtering approach, were applied to identify genomic regions under selection. As a result, the authors report (1) 62 high-confidence sweep-low-heterozygosity regions encompassing 255 genes, and (2) 3,578 SNPs with allele-frequency shifts exceeding neutral drift expectations shared across all four SS replicates, mapping to 578 genes. Mitochondrial pathways are identified as prominent targets, with a 13.9-fold enrichment of nuclear-encoded mitochondrial genes among candidates and differentiation at the mitochondrial origin of replication. Finally, the authors demonstrate that human orthologs of starvation-responsive fly genes are enriched for highly differentiated variants in four human populations from the 1000 Genomes Project.

    Strengths:

    (1) The experimental design with four evolution replicates provides proper control for false discovery.

    (2) The phenotypic characterisation is thorough. The approximately 3-fold increase in starvation survival and 1.5-fold increase in TAG content provide a clear physiological basis for interpreting the genomic findings, and the observation of increased adult longevity adds a meaningful life-history dimension to the results.

    (3) The mito-nuclear analysis is one of the more novel contributions of this paper. The implicated picture of coordinated mito-nuclear remodelling under sustained nutrient deprivation is compelling.

    (4) The comparative analysis connecting fly selection candidates to human population differentiation is ambitious and adds evolutionary breadth to the study.

    Weaknesses:

    (1) Ne estimation is derived from controls only, not from selected populations

    The entire drift-filtering framework rests on estimates of effective population size obtained from allele-frequency variance among the four control replicates (Ne = 530 for autosomes, Ne = 461 for the X chromosome). This is justified by assuming that divergence among control populations reflects neutral drift alone, a reasonable assumption for C populations maintained on standard food.

    However, the starvation-selected populations experienced 75-80% mortality per generation as an explicit design feature of the selection regime. This severe, recurrent demographic bottleneck would substantially reduce the effective population size within SS lines relative to controls. The authors do not acknowledge this discrepancy, nor do they attempt to estimate Ne within SS replicates or assess the sensitivity of their drift thresholds to plausible reductions in Ne. If Ne in SS populations is appreciably lower than in controls, the drift thresholds derived from the control-based Ne will underestimate the amount of neutral drift occurring in SS lines. Consequently, some allele-frequency shifts that are driven by the repeated bottleneck could be misclassified as candidate loci, inflating the apparent number of selection targets. This is the most consequential methodological concern in the paper. The authors should either estimate Ne separately for SS populations, implement a sensitivity analysis varying Ne over a biologically plausible range, or, at a minimum, provide a thorough discussion of how downward bias in SS Ne would affect their results and conclusions.

    (2) Lack of consideration about binomial sampling noise due to the pool size in the modeling

    With only 100 individuals pooled per population, binomial sampling from the pool contributes a non-trivial additional source of variance to allele-frequency estimates, on top of genetic drift and sequencing error. This is a well-documented issue in Pool-seq data. Critically, the Kimura diffusion framework used for drift modeling does not appear to explicitly incorporate this binomial sampling noise component, an omission that could affect the calibration of drift thresholds, particularly for low-frequency alleles. The authors should discuss whether and how pool-size-induced sampling variance is accounted for in their drift model.

    (3) No benchmarking against established Pool-seq analysis tools

    The authors use Pool-HMM for sweep detection and a custom diffusion-based drift framework for allele-frequency analysis, with PoPoolation (v1) used only for Tajima's D calculations. However, the study does not benchmark its candidate SNP sets or sweep regions against well-established Pool-seq analysis frameworks such as PoPoolation2, which provides CMH tests and FST estimation specifically designed for replicated Pool-seq E&R data, or R/poolSeq, which implements drift-aware testing purpose-built for this experimental design. The authors should either benchmark their approach against at least one established alternative or provide explicit justification for why their custom framework is preferable and how it compares in sensitivity and specificity.

    (4) Absence of negative controls in the human PBS comparative analysis

    A critical missing element in this comparative analysis is a negative control: the authors do not test whether equivalent enrichment is observed in populations with no particular history of famine or nutritional stress, such as European or East Asian populations from the 1000 Genomes Project. The inclusion of at least one negative-control population triplet is necessary to support the cross-species interpretation as stated.

  3. eLife

    Reviewer #2 (Public review):

    Summary:

    The authors use an Evolve-and-Resequence approach in Drosophila to study the genomic basis of adaptation to long-term starvation. Replicated selection lines and control populations are sequenced and analyzed to identify signals of selection, which are then related to starvation-related phenotypes. The general experimental design is appropriate, and the combination of genomic and phenotypic data is a clear strength of the study.

    Strengths:

    The strongest aspect of the work is the experimental evolution framework combined with population genomic inference across replicate populations. The observed parallelism across replicates supports the robustness of at least a subset of the detected selection signals. However, several key methodological details are either unclear or insufficiently justified. In particular, both the maintenance of control populations and demographic assumptions are not fully described, and the treatment of structural variation (e.g., segregating inversions) is not sufficiently addressed. The phenotypic analyses are broadly appropriate and replicated but would benefit from access to raw data.

    Weaknesses:

    The human ortholog enrichment analysis is an interesting component of the study, but it should be interpreted more cautiously. As currently presented, it is based on correlational signals of differentiation and is therefore sensitive to potential confounding factors. While the analysis may point to intriguing patterns consistent with conserved genetic architecture, the evidence is not sufficient to support strong claims of conserved starvation/malnutrition-related polygenic adaptation in humans. Framing this component more explicitly as exploratory would strengthen the manuscript. In its current form, this analysis is somewhat less conclusive than the experimental evolution results in flies.

    Overall, the study provides a useful dataset and a reasonably solid analysis of starvation adaptation in experimental Drosophila populations, but several methodological clarifications and a more balanced framing of the cross-species comparisons would strengthen the manuscript.

  4. eLife

    Reviewer #3 (Public review):

    Summary:

    This study tries to identify the genetic signatures of adaptation to starvation conditions. For this, outbred populations of Drosophila melanogaster were selected for starvation resistance by using the 20% surviving adults after starvation to start the next generation. This was done for 60 generations while parallel populations were kept under control conditions. At the end of the experiment, starvation-selected flies showed increased survival, longevity, and TGA storage. DNA poolseq data from control and starvation populations were compared to identify genomic regions with low heterozygosity and signatures of selective sweeps, and SNPs with differences in allele frequency. The candidate regions point to mitochondrial and metabolic pathways as the targets of selection for starvation resistance.

    The authors replicate the experimental design, selection approach, data collection, and analyses from Hardy et al 2018 (https://doi.org/10.1093/molbev/msx254), which also investigated adaptation to starvation conditions but used a different Drosophila melanogaster population. In this sense, the current study recapitulates most of the findings from Hardy et al. (2018). The analyses of the mitochondrial results, including the overlap with human data, are the novelty of this paper. However, those analyses are not very well justified. The fact that this study is almost identical to Hardy et al is not clearly stated nor discussed in the manuscript.

    Strengths:

    The authors made use of an experimental evolution approach to identify the genetic basis underlying adaptation. This is a powerful approach that has proven very successful in the past. They used a good number of replicates (four per condition), an appropriate depth of sequencing, and quantified higher-order phenotypes to validate the claim that the populations had evolved increased starvation resistance.

    Weaknesses :

    Although the findings of this study seem credible based on the known biology of starvation resistance, there are several aspects of the experimental design that weaken my confidence in the results. The points below should be clarified, and the limitations of the experimental design and analyses need to be included in the discussion.

    (1) Pooled genomic data were collected for the four replicates at the end of 60 generations of selection, and four replicates were kept under control conditions. No data were collected at the beginning of the experiment, which is the current standard in Evolve and Resequence experiments. To infer the genomic regions underlying adaptation to starvation, evolved control and starved cages are compared. Although this will identify regions that are possibly truly caused by adaptation to starvation stress, the available data doesn't allow to determine, for example: a) whether the differences between control and starvation regimes are due to changes in control cages relative to the starting population, combined with no changes in starvation cages relative to the starting population; b) whether the differences across replicates are due to different genomic composition at the start of the experiment that could have been amplified by drift.

    (2) Selection was applied by starving flies until ~80% of the population died. The 20% surviving flies were used to seed the next generation. The control populations, on the other hand, were propagated using the whole population. Given that only the starvation populations were subject to such a strong bottleneck, it is not possible to disentangle whether the genomic signatures at the end of the experiment are due to this, and not necessarily to starvation resistance. For example, the low heterozygosity blocks and the very great changes in allele frequency could be a natural result of such a bottleneck. A proper comparison would have been to select a random 20% of the control individuals to seed every generation.

    (3) The analyses that involve human populations are poorly justified, and the enrichment tests are not clearly explained. There is no evidence of signatures of selection for starvation resistance in human datasets (as mentioned in the text, line 112), and yet the authors claim that their analyses that identify branch-specific alleles for a set of four human populations serve as a dataset for it. I don't think the results of this analysis and further overlap with candidate genes identified in the Drosophila experiment support the conclusion that polygenic adaptation of metabolic pathways is conserved across species (line 303).

    (4) The conclusion that adaptation to starvation conditions is repeatable is not justified by the data. The overlap across replicates is very low in every metric.

    (5) The methods are poorly described. In most of the sections, there is not enough information to be able to replicate the experiments or the analyses. Several of the analyses presented in the results are not described in the methods. Without this information, it is very difficult to assess whether the analyses were correctly done or whether the results are robust.

  5. Version published to 10.7554/elife.111749.1 on eLife
  6. Version published to 10.7554/elife.111749 on eLife
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    Genome-wide architecture of prolonged starvation adaptation in experimentally evolved Drosophila and comparative enrichment in human orthologs https://www.biorxiv.org/content/10.64898/2026.05.01.722137v1

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    Genome-wide architecture of prolonged starvation adaptation in experimentally evolved Drosophila and comparative enrichment in human orthologs https://www.biorxiv.org/content/10.64898/2026.05.01.722137v1

  9. Version published to 10.64898/2026.05.01.722137v1 on bioRxiv