Genomewide architecture of adaptation in experimentally evolved Drosophila characterized by widespread pleiotropy.

Dissecting the molecular basis of adaptation remains elusive despite our ability to sequence genomes and transcriptomes. At present, most genomic research on selection focusses on signatures of selective sweeps in patterns of heterozygosity. Other research has studied changes in patterns of gene expression in evolving populations but has not usually identified the genetic changes causing these shifts in expression. Here we attempt to go beyond these approaches by using machine learning tools to explore interactions between the genome, transcriptome, and life-history phenotypes in two groups of 10 experimentally evolved Drosophila populations subjected to selection for opposing life history patterns. Our findings indicate that genomic and transcriptomic data have comparable power for predicting phenotypic characters. Looking at the relationships between the genome and the transcriptome, we find that the expression of individual transcripts is influenced by many sites across the genome that are differentiated between the two types of populations. We find that single-nucleotide polymorphisms (SNPs), transposable elements, and indels are powerful predictors of gene expression. Collectively, our results suggest that the genomic architecture of adaptation is highly polygenic with extensive pleiotropy.

Human Heart Failure Alters Mitochondria and Fiber 3D Structure Triggering Metabolic Shifts.

This study, utilizing SBF-SEM, reveals structural alterations in mitochondria and myofibrils in human heart failure (HF). Mitochondria in HF show changes in structure, while myofibrils exhibit increased cross-sectional area and branching. Metabolomic and lipidomic analyses indicate concomitant dysregulation in key pathways. The findings underscore the need for personalized treatments considering individualized structural changes in HF.

3D reconstruction of murine mitochondria reveals changes in structure during aging linked to the MICOS complex.

During aging, muscle gradually undergoes sarcopenia, the loss of function associated with loss of mass, strength, endurance, and oxidative capacity. However, the 3D structural alterations of mitochondria associated with aging in skeletal muscle and cardiac tissues are not well described. Although mitochondrial aging is associated with decreased mitochondrial capacity, the genes responsible for the morphological changes in mitochondria during aging are poorly characterized. We measured changes in mitochondrial morphology in aged murine gastrocnemius, soleus, and cardiac tissues using serial block-face scanning electron microscopy and 3D reconstructions. We also used reverse transcriptase-quantitative PCR, transmission electron microscopy quantification, Seahorse analysis, and metabolomics and lipidomics to measure changes in mitochondrial morphology and function after loss of mitochondria contact site and cristae organizing system (MICOS) complex genes, Chchd3, Chchd6, and Mitofilin. We identified significant changes in mitochondrial size in aged murine gastrocnemius, soleus, and cardiac tissues. We found that both age-related loss of the MICOS complex and knockouts of MICOS genes in mice altered mitochondrial morphology. Given the critical role of mitochondria in maintaining cellular metabolism, we characterized the metabolomes and lipidomes of young and aged mouse tissues, which showed profound alterations consistent with changes in membrane integrity, supporting our observations of age-related changes in muscle tissues. We found a relationship between changes in the MICOS complex and aging. Thus, it is important to understand the mechanisms that underlie the tissue-dependent 3D mitochondrial phenotypic changes that occur in aging and the evolutionary conservation of these mechanisms between Drosophila and mammals.

Three-dimensional mitochondria reconstructions of murine cardiac muscle changes in size across aging.

With sparse treatment options, cardiac disease remains a significant cause of death among humans. As a person ages, mitochondria breakdown and the heart becomes less efficient. Heart failure is linked to many mitochondria-associated processes, including endoplasmic reticulum stress, mitochondrial bioenergetics, insulin signaling, autophagy, and oxidative stress. The roles of key mitochondrial complexes that dictate the ultrastructure, such as the mitochondrial contact site and cristae organizing system (MICOS), in aging cardiac muscle are poorly understood. To better understand the cause of age-related alteration in mitochondrial structure in cardiac muscle, we used transmission electron microscopy (TEM) and serial block facing-scanning electron microscopy (SBF-SEM) to quantitatively analyze the three-dimensional (3-D) networks in cardiac muscle samples of male mice at aging intervals of 3 mo, 1 yr, and 2 yr. Here, we present the loss of cristae morphology, the inner folds of the mitochondria, across age. In conjunction with this, the three-dimensional (3-D) volume of mitochondria decreased. These findings mimicked observed phenotypes in murine cardiac fibroblasts with CRISPR/Cas9 knockout of Mitofilin, Chchd3, Chchd6 (some members of the MICOS complex), and Opa1, which showed poorer oxidative consumption rate and mitochondria with decreased mitochondrial length and volume. In combination, these data show the need to explore if loss of the MICOS complex in the heart may be involved in age-associated mitochondrial and cristae structural changes.NEW & NOTEWORTHY This article shows how mitochondria in murine cardiac changes, importantly elucidating age-related changes. It also is the first to show that the MICOS complex may play a role in outer membrane mitochondrial structure.

Asian Americans in STEM are not a monolith.

Despite tremendous diversity, Asian Americans in STEM are grouped and viewed as a homogeneous monolith, facing stereotypes and disparities. We propose solutions that include disaggregating the Asian American grouping and recognizing the diverse individual ethnic subgroups that comprise Americans of Asian ancestry to implement change within the STEM field.

Building Bridges from Genome to Physiology Using Machine Learning and Drosophila Experimental Evolution.

Drosophila experimental evolution, with its well-defined selection protocols, has long supplied useful genetic material for the analysis of functional physiology. While there is a long tradition of interpreting the effects of large-effect mutants physiologically, identifying and interpreting gene-to-phenotype relationships has been challenging in the genomic era, with many labs not resolving how physiological traits are affected by multiple genes throughout the genome. Drosophila experimental evolution has demonstrated that multiple phenotypes change because of the evolution of many loci across the genome, creating the scientific challenge of sifting out differentiated but noncausal loci for individual characters. The fused lasso additive model method allows us to infer some of the differentiated loci that have relatively greater causal effects on the differentiation of specific phenotypes. The experimental material that we use in the present study comes from 50 populations that have been selected for different life histories and levels of stress resistance. Differentiation of cardiac robustness, starvation resistance, desiccation resistance, lipid content, glycogen content, water content, and body masses was assayed among 40-50 of these experimentally evolved populations. Through the fused lasso additive model, we combined physiological analyses from eight parameters with whole-body pooled-seq genomic data to identify potentially causally linked genomic regions. We have identified approximately 2,176 significantly differentiated 50-kb genomic windows among our 50 populations, with 142 of those identified genomic regions that are highly likely to have a causal effect connecting specific genome sites to specific physiological characters.

How do DEI initiatives impact STEMM, and why do we still need them?

The number of diversity, equity, and inclusion (DEI) initiatives in science, technology, engineering, mathematics, and medicine (STEMM) have grown over the last few years. We asked several Black scientists what impact they have and why STEMM still needs them. They answer these questions and describe how DEI initiatives should evolve.

3D Mitochondrial Structure in Aging Human Skeletal Muscle: Insights into MFN-2 Mediated Changes.

Sarcopenia is an age-related loss of skeletal muscle, characterized by loss of mass, strength, endurance, and oxidative capacity during aging. Notably, bioenergetics and protein turnover studies have shown that mitochondria mediate this decline in function. Although mitochondrial aging is associated with decreased mitochondrial capacity, the three-dimensional (3D) mitochondrial structure associated with morphological changes in skeletal muscle during aging still requires further elucidation. Although exercise has been the only therapy to mitigate sarcopenia, the mechanisms that govern these changes remain unclear. We hypothesized that aging causes structural remodeling of mitochondrial 3D architecture representative of dysfunction, and this effect is mitigated by exercise. We used serial block-face scanning electron microscopy to image human skeletal tissue samples, followed by manual contour tracing using Amira software for 3D reconstruction and subsequent analysis of mitochondria. We then applied a rigorous in vitro and in vivo exercise regimen during aging. We found that mitochondria became less complex with age. Specifically, mitochondria lost surface area, complexity, and perimeter, indicating age-related declines in ATP synthesis and interaction capacity. Concomitantly, muscle area, exercise capacity, and mitochondrial dynamic proteins showed age-related losses. Exercise stimulation restored mitofusin 2 (MFN2), which we show is required for mitochondrial structure. Furthermore, we show that this pathway is evolutionarily conserved with Marf, the MFN2 ortholog in Drosophila, as Marf knockdown alters mitochondrial morphology and leads to the downregulation of genes regulating mitochondrial processes. Our results define age-related structural changes in mitochondria and further suggest that exercise may mitigate age-related structural decline through modulation of mitofusins.

Combining Metabolomics and Experimental Evolution Reveals Key Mechanisms Underlying Longevity Differences in Laboratory Evolved Drosophila melanogaster Populations.

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 to 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 provide 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 such as aging.

Crossing design shapes patterns of genetic variation in synthetic recombinant populations of Saccharomyces cerevisiae.

"Synthetic recombinant" populations have emerged as a useful tool for dissecting the genetics of complex traits. They can be used to derive inbred lines for fine QTL mapping, or the populations themselves can be sampled for experimental evolution. In the latter application, investigators generally value maximizing genetic variation in constructed populations. This is because in evolution experiments initiated from such populations, adaptation is primarily fueled by standing genetic variation. Despite this reality, little has been done to systematically evaluate how different methods of constructing synthetic populations shape initial patterns of variation. Here we seek to address this issue by comparing outcomes in synthetic recombinant Saccharomyces cerevisiae populations created using one of two strategies: pairwise crossing of isogenic strains or simple mixing of strains in equal proportion. We also explore the impact of the varying the number of parental strains. We find that more genetic variation is initially present and maintained when population construction includes a round of pairwise crossing. As perhaps expected, we also observe that increasing the number of parental strains typically increases genetic diversity. In summary, we suggest that when constructing populations for use in evolution experiments, simply mixing founder strains in equal proportion may limit the adaptive potential.

Can laboratory evolution experiments teach us about natural populations?

The ability to predict how natural populations will evolve and adapt to major changes in environmental conditions has long been of interest to evolutionary biologists and ecologists alike. The reality of global climate change has also created a pressing need for advancement in this particular area of research, as species are increasingly faced with rapid shifts in abiotic and biotic conditions. Evolutionary genomics has the potential to be incredibly useful as we move forward in addressing this need and in particular, evolve and resequence (E&R) studies-where researchers combine experimental evolution with whole-genome sequencing-have an important role to play. However, while E&R studies have shown a great deal of promise in tackling fundamental questions regarding the genetics of adaptation (Long et al., 2015; Schlötterer et al., 2014), it is unclear whether results from laboratory experiments can be directly translated to natural populations. In a From the Cover article in this issue of Molecular Ecology, Hsu et al. (Mol Ecol, 29, 2020) explicitly contend with this issue by examining the overlap between genes implicated in thermal adaptation in a Drosophila melanogaster E&R study and genes identified by comparing natural populations from different latitudinal clines. They report significant correlations between the two sets of temperature-adaptive genes and ultimately conclude that E&R studies can indeed generate insights applicable to populations inhabiting complex natural environments. While more work is needed to assess the generality of these conclusions, Hsu and Belmouaden (Mol Ecol, 29, 2020) contribute an important precedent.

Increased time sampling in an evolve-and-resequence experiment with outcrossing Saccharomyces cerevisiae reveals multiple paths of adaptive change.

"Evolve and resequence" (E&R) studies combine experimental evolution and whole-genome sequencing to interrogate the genetics underlying adaptation. Due to ease of handling, E&R work with asexual organisms such as bacteria can employ optimized experimental design, with large experiments and many generations of selection. By contrast, E&R experiments with sexually reproducing organisms are more difficult to implement, and design parameters vary dramatically among studies. Thus, efforts have been made to assess how these differences, such as number of independent replicates, or size of experimental populations, impact inference. We add to this work by investigating the role of time sampling-the number of discrete time points sequence data are collected from evolving populations. Using data from an E&R experiment with outcrossing Saccharomyces cerevisiae in which populations were sequenced 17 times over ~540 generations, we address the following questions: (a) Do more time points improve the ability to identify candidate regions underlying selection? And (b) does high-resolution sampling provide unique insight into evolutionary processes driving adaptation? We find that while time sampling does not improve the ability to identify candidate regions, high-resolution sampling does provide valuable opportunities to characterize evolutionary dynamics. Increased time sampling reveals three distinct trajectories for adaptive alleles: one consistent with classic population genetic theory (i.e., models assuming constant selection coefficients), and two where trajectories suggest more context-dependent responses (i.e., models involving dynamic selection coefficients). We conclude that while time sampling has limited impact on candidate region identification, sampling eight or more time points has clear benefits for studying complex evolutionary dynamics.

Consequences of Cryopreservation in Diverse Natural Isolates of Saccharomyces cerevisiae.

Experimental evolution allows the observation of change over time as laboratory populations evolve in response to novel, controlled environments. Microbial evolution experiments take advantage of cryopreservation to archive experimental populations in glycerol media, creating a frozen, living "fossil" record. Prior research with Escherichia coli has shown that cryopreservation conditions can affect cell viability and that allele frequencies across the genome can change in response to a freeze-thaw event. We expand on these observations by characterizing fitness and genomic consequences of multiple freeze-thaw cycles in diploid yeast populations. Our study system is a highly recombinant Saccharomyces cerevisiae population (SGRP-4X) that harbors standing genetic variation that cryopreservation may threaten. We also investigate the four parental isogenic strains crossed to create the SGRP-4X. We measure cell viability over five consecutive freeze-thaw cycles; whereas we find that viability increases over time in the evolved recombinant populations, we observe no such viability improvements in the parental strains. We also collect genome-wide sequence data from experimental populations initially, after one freeze-thaw, and after five freeze-thaw cycles. In the recombinant evolved populations, we find a region of significant allele frequency change on chromosome 15 containing the ALR1 gene. In the parental strains, we find little evidence for new mutations. We conclude that cryopreserving yeast populations with standing genetic variation may have both phenotypic and genomic consequences, though the same cryopreservation practices may have only small impacts on populations with little or no initial variation.

Genomics of Early Cardiac Dysfunction and Mortality in Obese Drosophila melanogaster.

In experimental evolution, we impose functional demands on laboratory populations of model organisms using selection. After enough generations of such selection, the resulting populations constitute excellent material for physiological research. An intense selection regime for increased starvation resistance was imposed on 10 large outbred Drosophila populations. We observed the selection responses of starvation and desiccation resistance, metabolic reserves, and heart robustness via electrical pacing. Furthermore, we sequenced the pooled genomes of these populations. As expected, significant increases in starvation resistance and lipid content were found in our 10 intensely selected SCO populations. The selection regime also improved desiccation resistance, water content, and glycogen content among these populations. Additionally, the average rate of cardiac arrests in our 10 obese SCO populations was double the rate of the 10 ancestral CO populations. Age-specific mortality rates were increased at early adult ages by selection. Genomic analysis revealed a large number of single nucleotide polymorphisms across the genome that changed in frequency as a result of selection. These genomic results were similar to those obtained in our laboratory from less direct selection procedures. The combination of extensive genomic and phenotypic differentiation between these 10 populations and their ancestors makes them a powerful system for the analysis of the physiological underpinnings of starvation resistance.

Drosophila transcriptomics with and without ageing.

The genomic basis of ageing still remains unknown despite being a topic of study for many years. Here, we present data from 20 experimentally evolved laboratory populations of Drosophila melanogaster that have undergone two different life-history selection regimes. One set of ten populations demonstrates early ageing whereas the other set of ten populations shows postponed ageing. Additionally, both types of populations consist of five long standing populations and five recently derived populations. Our primary goal was to determine which genes exhibit changes in expression levels by comparing the female transcriptome of the two population sets at two different time points. Using three different sets of increasingly restrictive criteria, we found that 2.1-15.7% (82-629 genes) of the expressed genes are associated with differential ageing between population sets. Conversely, a comparison of recently derived populations to long-standing populations reveals little to no transcriptome differentiation, suggesting that the recent selection regime has had a larger impact on the transcriptome than its more distant evolutionary history. In addition, we found very little evidence for significant enrichment for functional attributes regardless of the set of criteria used. Relative to previous ageing studies, we find little overlap with other lists of aging related genes. The disparity between our results and previously published results is likely due to the high replication used in this study coupled with our use of highly differentiated populations. Our results reinforce the notion that the use of genomic, transcriptomic, and phenotypic data to uncover the genetic basis of a complex trait like ageing can benefit from experimental designs that use highly replicated, experimentally-evolved populations.

Effects of evolutionary history on genome wide and phenotypic convergence in Drosophila populations.

BACKGROUND: Studies combining experimental evolution and next-generation sequencing have found that adaptation in sexually reproducing populations is primarily fueled by standing genetic variation. Consequently, the response to selection is rapid and highly repeatable across replicate populations. Some studies suggest that the response to selection is highly repeatable at both the phenotypic and genomic levels, and that evolutionary history has little impact. Other studies suggest that even when the response to selection is repeatable phenotypically, evolutionary history can have significant impacts at the genomic level. Here we test two hypotheses that may explain this discrepancy. Hypothesis 1: Past intense selection reduces evolutionary repeatability at the genomic and phenotypic levels when conditions change. Hypothesis 2: Previous intense selection does not reduce evolutionary repeatability, but other evolutionary mechanisms may. We test these hypotheses using D. melanogaster populations that were subjected to 260 generations of intense selection for desiccation resistance and have since been under relaxed selection for the past 230 generations. RESULTS: We find that, with the exception of longevity and to a lesser extent fecundity, 230 generations of relaxed selection has erased the extreme phenotypic differentiation previously found. We also find no signs of genetic fixation, and only limited evidence of genetic differentiation between previously desiccation resistance selected populations and their controls. CONCLUSION: Our findings suggest that evolution in our system is highly repeatable even when populations have been previously subjected to bouts of extreme selection. We therefore conclude that evolutionary repeatability can overcome past bouts of extreme selection in Drosophila experimental evolution, provided experiments are sufficiently long and populations are not inbred.

Genome-Wide Mapping of Gene-Phenotype Relationships in Experimentally Evolved Populations.

Model organisms subjected to sustained experimental evolution often show levels of phenotypic differentiation that dramatically exceed the phenotypic differences observed in natural populations. Genome-wide sequencing of pooled populations then offers the opportunity to make inferences about the genes that are the cause of these phenotypic differences. We tested, through computer simulations, the efficacy of a statistical learning technique called the "fused lasso additive model" (FLAM). We focused on the ability of FLAM to distinguish between genes which are differentiated and directly affect a phenotype from differentiated genes which have no effect on the phenotype. FLAM can separate these two classes of genes even with relatively small samples (10 populations, in total). The efficacy of FLAM is improved with increased number of populations, reduced environmental phenotypic variation, and increased within-treatment among-replicate variation. FLAM was applied to SNP variation measured in both twenty-population and thirty-population studies of Drosophila subjected to selection for age-at-reproduction, to illustrate the application of the method.

Genome-wide analysis of long-term evolutionary domestication in Drosophila melanogaster.

Experimental evolutionary genomics now allows biologists to test fundamental theories concerning the genetic basis of adaptation. We have conducted one of the longest laboratory evolution experiments with any sexually-reproducing metazoan, Drosophila melanogaster. We used next-generation resequencing data from this experiment to examine genome-wide patterns of genetic variation over an evolutionary time-scale that approaches 1,000 generations. We also compared measures of variation within and differentiation between our populations to simulations based on a variety of evolutionary scenarios. Our analysis yielded no clear evidence of hard selective sweeps, whereby natural selection acts to increase the frequency of a newly-arising mutation in a population until it becomes fixed. We do find evidence for selection acting on standing genetic variation, as independent replicate populations exhibit similar population-genetic dynamics, without obvious fixation of candidate alleles under selection. A hidden-Markov model test for selection also found widespread evidence for selection. We found more genetic variation genome-wide, and less differentiation between replicate populations genome-wide, than arose in any of our simulated evolutionary scenarios.

Rapid divergence and convergence of life-history in experimentally evolved Drosophila melanogaster.

Laboratory selection experiments are alluring in their simplicity, power, and ability to inform us about how evolution works. A longstanding challenge facing evolution experiments with metazoans is that significant generational turnover takes a long time. In this work, we present data from a unique system of experimentally evolved laboratory populations of Drosophila melanogaster that have experienced three distinct life-history selection regimes. The goal of our study was to determine how quickly populations of a certain selection regime diverge phenotypically from their ancestors, and how quickly they converge with independently derived populations that share a selection regime. Our results indicate that phenotypic divergence from an ancestral population occurs rapidly, within dozens of generations, regardless of that population's evolutionary history. Similarly, populations sharing a selection treatment converge on common phenotypes in this same time frame, regardless of selection pressures those populations may have experienced in the past. These patterns of convergence and divergence emerged much faster than expected, suggesting that intermediate evolutionary history has transient effects in this system. The results we draw from this system are applicable to other experimental evolution projects, and suggest that many relevant questions can be sufficiently tested on shorter timescales than previously thought.

Four steps toward the control of aging: following the example of infectious disease.

The biotechnological task of controlling human aging will evidently be complex, given the failure of all simple strategies for accomplishing this task to date. In view of this complexity, a multi-step approach will be necessary. One precedent for a multi-step biotechnological success is the burgeoning control of human infectious diseases from 1840 to 2000. Here we break down progress toward the control of infectious disease into four key steps, each of which have analogs for the control of aging. (1) Agreement about the fundamental nature of the medical problem. (2) Public health measures to mitigate some of the factors that exacerbate the medical problem. (3) Early biotechnological interventions that ward off the more tractable disease etiologies. (4) Deep understanding of the underlying biology of the diseases involved, leading in turn to comprehensive control of the medical problems that they pose. Achievement of all four of these steps has allowed most people who live in Western countries to live largely free of imminent death due to infectious disease. Accomplishing the equivalent feat for aging over this century should lead to a similar outcome for aging-associated disease. Neither infection nor aging will ever be entirely abolished, but they can both be rendered minor causes of death and disability.