Biology subjects

Ng'oma, E.

Publications and source records attributed to Ng'oma, E..

9 recordsLinked to original sources

bioRxiv2026

Hierarchical divergence across genomic, phenotypic, and microbiome dimensions in two annual killifish species from Malawi

Divergence among populations and species commonly occurs across multiple biological levels, yet the extent to which genomic, phenotypic, and ecological dimensions are coupled remains poorly understood. We integrated whole-genome sequencing, multivariate morphology, population-level phylogenetic structure, and gut microbiome composition to evaluate divergence in two allopatric annual killifish species across spatially structured populations in Malawi. Geographic and hydrological structure emerged as the primary axis of divergence, with strong differentiation between species and among populations. Genome-wide analyses revealed consistent clustering among populations in ordination and phylogenetic analyses, indicating pronounced spatial structuring of genomic variation. Although genomic divergence was widespread, exon-level enrichment analyses revealed distinct signatures across evolutionary scales. Divergence within N. kirki was associated primarily with translation-related functions, whereas divergence within N. wattersi involved ATP biosynthesis and physiological homeostasis. Interspecific divergence was enriched for transcription factor activity and transcription factor binding, implicating regulatory evolution as a major component of species differentiation. Morphological variation was likewise strongly structured among populations and aligned with drainage systems and geographic regions but was not correlated with genome-wide genetic differentiation, indicating partial decoupling between genotype and multivariate phenotype. Gut microbiome composition represented a more environmentally responsive layer of divergence, broadly reflecting host species and drainage structure while exhibiting greater overlap among populations. These results support a hierarchical model in which geographic and hydrological structure organize stable genomic divergence, whereas phenotypic and microbiome variation represent increasingly context-dependent and only partially aligned biological layers. Our findings highlight the value of integrating multiple biological levels to understand how evolutionary processes shape divergence in natural populations.

evolutionary biology↗

bioRxiv2026

Population divergence in growth allometry of annual killifishes across ephemeral habitats in Malawi floodplain systems

Body size is a fundamental determinant of ecological performance, and variation in length- weight relationships can provide insight into how populations respond to local environmental conditions. Annual killifishes inhabit highly seasonal wetlands characterized by substantial environmental heterogeneity, yet population-level variation in growth allometry remains poorly understood. We investigated growth allometry in 18 populations of two annual killifish species, Nothobranchius kirki and N. wattersi, distributed across ephemeral habitats in Malawi. Length- weight relationships were analyzed separately for each species using linear mixed-effects models, with locality incorporated as a random effect. Environmental variation among localities was summarized using principal component analysis of water quality variables, and population- specific allometric coefficients were subsequently related to environmental gradients. Significant population-level variation in growth trajectories was detected in both species, indicating divergence in allometric scaling among localities. Divergence was more pronounced in N. wattersi, which exhibited a broader range of population-specific allometric coefficients than N. kirki. Populations also differed significantly in relative body condition after accounting for body length and sex. Environmental gradients explained a significant proportion of variation in allometric slopes in N. kirki, whereas no significant relationship was detected in N. wattersi. Thus, the species exhibiting weaker allometric divergence showed stronger environmental associations, while the species exhibiting greater divergence showed little correspondence with measured environmental variables. These results demonstrate substantial spatial heterogeneity in growth allometry among populations of annual killifishes inhabiting seasonal wetlands. Furthermore, the contrasting environmental associations observed between species suggest that population divergence in growth trajectories may arise through different ecological and evolutionary processes, even among closely related taxa occupying similar habitats.

ecology↗

bioRxiv2025

Nutritional stress adaptation shapes host microbiome stability and life history dynamics

BackgroundDietary environments can shape host-microbe co-evolution by imposing selection pressures that favor host and microbial genotypes with enhanced fitness under specific nutritional conditions. However, the long-term evolutionary dynamics of these interactions after selection pressures are relaxed remain poorly understood. Here, we investigated the microbiome of Drosophila melanogaster populations that underwent long-term experimental evolution under three temporally variable nutritional regimes (constant high sugar, progressively decreasing protein, and fluctuating protein), and compared them to unselected controls. Following inbreeding of evolved populations, we examined how persistent evolutionary effects interact with aging to shape host-microbe relationships and survival. ResultsAll selected regimes exhibited reduced survival relative to controls, indicating lasting physiological costs associated with historical selection and inbreeding. Survival differed among regimes: the deteriorating-protein regime was closest to controls, the fluctuating-protein regime was intermediate, and the high-sugar regime showed the shortest lifespan. Survival effects were sex-specific: relative to control females, those from the fluctuating-protein regime exhibited reduced early-life survival, whereas females from the deteriorating-protein regime experienced greater late-life mortality. Microbiome composition varied with both selection regime and age. Although Firmicutes and Proteobacteria dominated across groups, selected lines showed increased Firmicutes and reduced Proteobacteria, especially early in life, suggesting early-life taxonomic restructuring. The decreasing-protein regime maintained more stable microbial diversity over time, whereas high-sugar and fluctuating-protein diets were associated with progressive microbiome instability with age. Core Acetobacter species (A. aceti, A. oryzifermentans) declined in abundance in selected flies, indicating persistent disruption of microbiome integrity. A random forest model predicted fly age from microbiome composition with 78.8% accuracy, reinforcing links between microbial dynamics and host aging. ConclusionHistorical dietary selection and inbreeding can leave lasting signatures on survival and microbiome composition in Drosophila. Protein restriction promoted late-life longevity and microbial stability, whereas high-sugar and fluctuating diets were associated with early-life effects followed by later-life shifts in dominant taxa. Together, these findings illustrate how nutritional history and its microbial legacies influence lifespan and aging through persistent host-microbe interactions.

evolutionary biology↗

bioRxiv2024

Larval protein restriction interacts with adult diet to increase fitness in an outbred multiparent population.

Developmental conditions including temperature, diet, and parasites can shape adult fitness phenotypes in many species. Studies typically focus on the additive effects of early-life and adult life conditions on life history response in the context of competing models of developmental plasticity (i.e. environmental matching and silver spoon). These models continue to yield mixed results in the same or different species. Here, we characterize interaction effects of larval vs adult diet on lifespan and fecundity in a high diversity outbred population of Drosophila melanogaster. We compare fitness proxies of matched vs mismatched early-to-late nutritional conditions differing in protein content. Diet interactions significantly affected both traits, albeit differently. We find no consistent evidence for either model. Rather, several patterns emerged including age and sex effects, survival differences in the post-median life phase, regime-specific timing of peak fecundity, and substantial fecundities in older post-median flies. Surprisingly, lower adult protein delayed egg-laying by about 2 weeks, compared to treatments with higher protein in adult diet. Our results underscore the extent to which adult life history expression depends significantly on developmental conditions. Results further highlight the need for assessing possible adult life phase patterns which might potentially reveal trade-offs between adult life stages than traits.

developmental biology↗

bioRxiv2019

Diverse biological processes coordinate the transcriptional response to nutritional changes in a Drosophila melanogaster multiparent population

BackgroundEnvironmental variation in the amount of resources available to populations challenge individuals to optimize the allocation of those resources to key fitness functions. This coordination of resource allocation relative to resource availability is commonly attributed to key nutrient sensing gene pathways in laboratory model organisms, chiefly the insulin/TOR signaling pathway. However, the genetic basis of diet-induced variation in gene expression is less clear.\n\nResultsTo describe the natural genetic variation underlying nutrient-dependent differences, we used an outbred panel derived from a multiparental population, the Drosophila Synthetic Population Resource. We analyzed RNA sequence data from multiple female tissue samples dissected from flies reared in three nutritional conditions: high sugar (HS), dietary restriction (DR), and control (C) diets. A large proportion of genes in the experiment (19.6% or 2,471 genes) were significantly differentially expressed for the effect of diet, 7.8% (978 genes) for the effect of the interaction between diet and tissue type (LRT, Padj. < 0.05). Interestingly, we observed similar patterns of gene expression relative to the C diet, in the DR and HS treated flies, a response likely reflecting diet component ratios. Hierarchical clustering identified 21 robust gene modules showing intra-modularly similar patterns of expression across diets, all of which were highly significant for diet or diet-tissue interaction effects (false discovery rate, FDR Padj. < 0.05). Gene set enrichment analysis for different diet-tissue combinations revealed a diverse set of pathways and gene ontology (GO) terms (two-sample t-test, FDR < 0.05). GO analysis on individual co-expressed modules likewise showed a large number of terms encompassing a large number of cellular and nuclear processes (Fisher exact test, Padj. < 0.01). Although a handful of genes in the IIS/TOR pathway including Ilp5, Rheb, and Sirt2 showed significant elevation in expression, known key genes such as InR, chico, insulin peptide genes, and the nutrient-sensing pathways were not observed.\n\nConclusionsOur results suggest that a more diverse network of pathways and gene networks mediate the diet response in our population. These results have important implications for future studies focusing on diet responses in natural populations.

genomics↗

bioRxiv2019

Multiple genetic loci affect place learning and memory performance in Drosophila melanogaster

Learning and memory are critical functions for all animals, giving individuals the ability to respond to changes in their environment. Within populations, individuals vary, however the mechanisms underlying this variation in performance are largely unknown. Thus, it remains to be determined what genetic factors cause an individual to have high learning ability, and what factors determine how well an individual will remember what they have learned. To genetically dissect learning and memory performance, we used the DSPR, a multiparent mapping resource in the model system Drosophila melanogaster, consisting of a large set of recombinant inbred lines (RILs) that naturally vary in these and other traits. Fruit flies can be trained in a \"heat box\" to learn to remain on one side of a chamber (place learning), and can remember this (place memory) over short timescales. Using this paradigm, we measured place learning and memory for [~]49,000 individual flies from over 700 DSPR RILs. We identified 16 different loci across the genome that significantly affect place learning and/or memory performance, with 5 of these loci affecting both traits. To identify transcriptomic differences associated with performance, we performed RNA-Seq on pooled samples of 7 high performing and 7 low performing RILs for both learning and memory and identified hundreds of genes with differences in expression in the two sets. Integrating our transcriptomic results with the mapping results allowed us to identify nine promising candidate genes, advancing our understanding of the genetic basis underlying natural variation in learning and memory performance.

genetics↗

bioRxiv2018

A model-based high throughput method for fecundity estimation in fruit fly studies.

The ability to quantify fecundity is critically important to a wide range of experimental applications, particularly in widely-used model organisms such as Drosophila melanogaster. However, the standard method of manually counting eggs is time consuming and limits the feasibility of large-scale experiments. We develop a predictive model to automate the counting of eggs from images of eggs removed from the media surface and washed onto dark filter paper. A cross-validation approach demonstrates our method performs well, with a correlation between predicted and manually counted values of 0.88. We show how this method can be applied to a large data set where egg densities vary widely.

bioinformatics↗

bioRxiv2018

The evolutionary potential of diet-dependent effects on lifespan and fecundity in a multi-parental population of Drosophila melanogaster

The nutritional conditions experienced by a population play a major role in shaping trait evolution in many taxa. Constraints exerted by nutrient limitation or nutrient imbalance can influence the maximal value that fitness components such as reproduction and lifespan attains, and organisms may shift how resources are allocated to different structures and functions in response to changes in nutrition. Whether the phenotypic changes associated with changes in nutrition represent an adaptive response is largely unknown. Further, it is unclear whether the response of fitness components to diet even has the potential to evolve in most systems. In this study, we use an admixed multiparental population of Drosophila melanogaster reared in three different diet conditions to estimate quantitative genetic parameters for lifespan and fecundity. We find significant genetic variation for both traits in our population and show that lifespan has moderate to high heritabilities within diets. Genetic correlations for lifespan between diets were significantly less than one, demonstrating a strong genotype by diet interaction. These findings demonstrate substantial standing genetic variation in our population that is comparable to natural populations and highlights the potential for adaptation to changing nutritional environments.

evolutionary biology↗

bioRxiv2017

How to get the most bang for your buck: the evolution and physiology of nutrition-dependent resource allocation strategies

All organisms utilize resources to grow, survive, and reproduce. The supply of these resources varies widely across landscapes and time, imposing ultimate constraints on the maximal trait values for allocation-related traits. In this review, we address three key questions fundamental to our understanding of the evolution of allocation strategies and their underlying mechanisms. First, we ask: how diverse are flexible resource allocation strategies among different organisms? We find there are many, varied, examples of flexible strategies that depend on nutrition. However, this diversity is often ignored in some of the best-known cases of resource allocation shifts, such as the commonly observed pattern of lifespan extension under nutrient limitation. A greater appreciation of the wide variety of flexible allocation strategies leads directly to our second major question: what conditions select for different plastic allocation strategies? Here, we highlight the need for additional models that explicitly consider the evolution of phenotypically plastic allocation strategies and empirical tests of the predictions of those models in natural populations. Finally, we consider the question: what are the underlying mechanisms determining resource allocation strategies? Although evolutionary biologists assume differential allocation of resources is a major factor limiting trait evolution, few proximate mechanisms are known that specifically support the model. We argue that an integrated framework can reconcile evolutionary models with proximate mechanisms that appear at first glance to be in conflict with these models. Overall, we encourage future studies to 1) mimic ecological conditions in which those patterns evolve, and 2) take advantage of the omic opportunities to produce multi-level data and analytical models that effectively integrate across physiological and evolutionary theory.

evolutionary biology↗