Biology subjects

Gordon, D. M.

Publications and source records attributed to Gordon, D. M..

7 recordsLinked to original sources

bioRxiv2026

Large-scale genomic rearrangements are a potential explanation for reproductive isolation in the Pogonomyrmex dependent-lineage system

Genetic variation is the raw material for evolution. One source of variation is chromosomal rearrangements, which can bring genes together and form genetic linkage. Rearrangements can also suppress recombination and gene flow, as in the case of sex chromosome evolution. We conducted the first population genomic study of the red harvester ant Pogonomyrmex barbatus to investigate genomic rearrangements that differentiate the lineages J1 and J2 in the "dependent-lineage system" (also known as "social hybridogenesis"). In this unusual reproductive system, males and females from different lineages mate to create hybrids, yet these hybrids develop into sterile offspring (workers), and so the two lineages remain reproductively isolated. We sequenced high-quality reference genomes for the two lineages to search for a potential explanation of the suppression of gene flow between them. Comparison of the two genome assemblies revealed multiple large-scale genomic rearrangements, all of which occurred in the J1 lineage. The rearrangements formed some of the largest J1 chromosomes, including the largest scaffold in the assembly that was formed by at least two translocation events and additional intra-chromosomal rearrangements. The translocations brought together 118 odorant receptor (OR) genes on this rearranged chromosome, 44 of which are 9-exon ORs, which are implicated in chemical communication in ants. We also identified an enrichment of transposable elements in a large synteny gap between the translocated segments. The discovery of multiple translocations that formed large rearranged chromosomes provides a potential explanation for the reproductive isolation between the pair of dependent lineages in this system, and opens the way for the study of the molecular genetic basis of an intriguing evolutionary phenomenon in these and in other ant lineages.

evolutionary biology↗

bioRxiv2026

Rhythmic gene expression and behavioral plasticity in harvester and carpenter ants

We examined the overlap in the genes associated with daily rhythms and with behavioral plasticity in ants. We first investigated the daily rhythms of gene expression in the harvester ant, Pogonomyrmex barbatus, and how the rhythmic genes overlap with others previously shown to be associated with plasticity of foraging behavior. Then, to consider whether the overlap is conserved across ant species, we compared rhythms of gene expression in the diurnal, desert harvester ants with those previously reported for a distantly related nocturnal, subtropical carpenter ant, Camponotus floridanus. First, daily transcriptomes in P. barbatus showed that most genes were expressed in light-dark (LD) and constantly dark (DD) conditions at about the same levels; only 11 genes showed at least a two-fold change in expression. Network analysis identified eleven modules of P. barbatus genes under LD conditions. Of these 11 clusters, modules C1 and C2 seem to be central nodes of the gene expression network, because they are the most highly connected in LD, and show the strongest preservation in DD vs. LD, and contain core clock gene Period. Only one module, C2, showed significant overlap with P. barbatus genes that have 24h-rhythmic expression in both LD and DD. There was significant overlap between modules C1, C2, C10, C11, and P. barbatus genes found previously to be associated with plasticity in the regulation of foraging activity to manage water loss. A comparison of the daily transcriptome of P. barbatus with that of C. floridanus showed significant overlap of 24h-rhythmic genes in LD. Modules C1 and C2 of P. barbatus also overlap with C. floridanus genes previously shown to differ in expression rhythms in nurses and foragers. In combination, these results indicate that genes linking plasticity of the circadian clock and of behavior may be broadly conserved in ants.

systems biology↗

bioRxiv2026

Shifts in demography in changing ecological conditions in a dependent-lineage population of harvester ant colonies

Environmental stress can influence population dynamics and shift selection pressures. We considered the demographic effects since 2011 of intensifying drought in a J1/J2 dependent-lineage population, monitored since 1988, of the red harvester ant, Pogonomyrmex barbatus. A queen must mate with males of both dependent lineages to found a viable colony; mating with the same lineage results in a gyne, while mating with the other lineage results in a worker. We used reduced representation genomic sequencing of workers from 407 colonies, ages 1-3, mostly sampled in 2021-23, to determine colony lineage, identify sets of colonies with the same mitotype, and estimate kinship between mother-daughter pairs. We found that the rare lineage J1 became even more rare, from 39% in 2011 to 25% in 2023. This creates pressure on J1 to produce more sperm or more males to allow the population to persist. We compared survival and numbers of offspring produced in the two lineages and in sets of colonies with the same mitotypes, using census data. Survival and fecundity were similar among 5 J1 and 6 J2 mitotype groups, showing no evidence for selection favoring any mitotype. We identified 62 mother-daughter colony pairs. These included 14 grandmother-triplets, with most grandmothers found in J2, suggesting that some families dominate each mitotype group. Within the 62 mother-daughter pairs, those from J1 tended to live longer than J2 colonies, maintaining a low but constant fecundity rate, while J2 colonies showed the highest fecundity at ages 11-17. Our results suggest that increasingly harsh ecological conditions are shaping population dynamics more rapidly than selection for phenotypic traits that could facilitate adaptation.

evolutionary biology↗

bioRxiv2019

Better tired than lost: turtle ant trail networks favor coherence over shortest paths

Creating a routing backbone is a fundamental problem in both biology and engineering. The routing backbone of the trail networks of arboreal turtle ants (Cephalotes goniodontus) connects many nests and food sources using trail pheromone deposited by ants as they walk. Unlike species that forage on the ground, the trail networks of arboreal ants are constrained by the vegetation. We examined what objectives the trail networks meet by comparing the observed ant trail networks with networks of random, hypothetical trail networks in the same surrounding vegetation and with trails optimized for four objectives: minimizing path length, minimizing average edge length, minimizing number of nodes, and minimizing opportunities to get lost. The ants trails minimized path length by minimizing the number of nodes traversed rather than choosing short edges. In addition, the ants trails reduced the opportunity for ants to get lost at each node, favoring nodes with 3D configurations most likely to be reinforced by pheromone. Thus, rather than finding the shortest edges, turtle ant trail networks take advantage of natural variation in the environment to favor coherence, keeping the ants together on the trails. Author SummaryWe investigated the trail networks of arboreal turtle ants in the canopy of the tropical forest, to ask what characterizes the colonys choice of foraging paths within the vegetation. We monitored day to day changes in the junctions and edges of trail networks of colonies in the dry forest of western Mexico. We compared the paths used by the ants to simulated random paths in the surrounding vegetation. We found that the paths of turtle ants prioritize coherence, keeping ants together on the trail, over minimizing the average edge length. The choice of paths reduces the number of junctions in the trail where ants could get lost, and favors junctions with a physical configuration that makes it likely that successive ants will reinforce the same path. Our work suggests that design principles that emphasize keeping information flow constrained to streamlined, coherent trails may be useful in human-designed distributed routing and transport networks or robot swarms.

ecology↗

bioRxiv2019

Global Analysis of Human mRNA Folding Disruptions in Synonymous Variants Demonstrates Significant Population Constraint

BackgroundIn most organisms the structure of an mRNA molecule is crucial in determining speed of translation, half-life, splicing propensities and final protein configuration. Synonymous variants which distort this wildtype mRNA structure may be pathogenic as a consequence. However, current clinical guidelines classify synonymous or "silent" single nucleotide variants (sSNVs) as largely benign unless a role in RNA splicing can be demonstrated. ResultsWe developed novel software to conduct a global transcriptome study in which RNA folding statistics were computed for 469 million SNVs in 45,800 transcripts using an Apache Spark implementation of ViennaRNA in the cloud. Focusing our analysis on the subset of 17.9 million sSNVs, we discover that variants predicted to disrupt mRNA structure have lower rates of incidence in the human population. Given that the community lacks tools to evaluate the potential pathogenic impact of sSNVs, we introduce a "Structural Predictivity Index" (SPI) to quantify this constraint due to mRNA structure. ConclusionsOur findings support the hypothesis that sSNVs may play a role in genetic disorders due to their effects on mRNA structure. Our RNA-folding scores provide a means of gauging the structural constraint operating on any sSNV in the human genome. Given that the majority of patients with rare or as yet to be diagnosed disease lack a molecular diagnosis, these scores have the potential to enable discovery of novel genetic etiologies. Our RNA Stability Pipeline as well as ViennaRNA structural metrics and SPI scores for all human synonymous variants can be downloaded from GitHub https://github.com/nch-igm/rna-stability.

genomics↗

bioRxiv2018

Regulation of Harvester Ant Foraging as a Closed-Loop Excitable System

Ant colonies regulate activity in response to changing conditions without using centralized control. Harvester ant colonies forage in the desert for seeds, and their regulation of foraging manages a tradeoff between spending and obtaining water. Foragers lose water while outside in the dry air, but the colony obtains water by metabolizing the fats in the seeds they eat. Previous work shows that the rate at which an outgoing forager leaves the nest depends on its recent experience of brief antennal contact with returning foragers that carry a seed. We examine how this process can yield foraging rates that are robust to uncertainty and responsive to temperature and humidity across minutes to hour-long timescales. To explore possible mechanisms, we develop a low-dimensional analytical model with a small number of parameters that captures observed foraging behavior. The model uses excitability dynamics to represent response to interactions inside the nest and a random delay distribution to represent foraging time outside the nest. We show how feedback of outgoing foragers returning to the nest stabilizes the incoming and outgoing foraging rates to a common value determined by the \"volatility\" of available foragers. The model exhibits a critical volatility above which there is sustained foraging at a constant rate and below which there is cessation of foraging. To explain how the foraging rates of colonies adjust to temperature and humidity, we propose a mechanism that relies on foragers modifying their volatility after they leave the nest and get exposed to the environment. Our study highlights the importance of feedback in the regulation of foraging activity and points to modulation of volatility as a key to explaining differences in foraging activity in response to conditions and across colonies. Our results present opportunities for generalization to other contexts and systems with excitability and feedback across multiple timescales.\n\nAuthor SummaryWe investigate the collective behavior that allows colonies of desert harvester ants to regulate foraging activity in response to environmental conditions. We develop an analytical model connecting three processes: 1) the interactions between foragers returning to the nest and available foragers waiting inside the nest, 2) the effect of these interactions on the likelihood of available foragers to leave the nest to forage, and 3) the return of foragers to the nest after finding seeds. We propose a mechanism in which available foragers modify their response to interactions after their first exposure to the environment. We show how this leads to colony foraging rates that adjust to environmental conditions over time scales from minutes to hours. Our model may prove useful for studying resilience in other classes of systems with excitatory dynamics.

animal behavior and cognition↗

bioRxiv2017

A distributed algorithm to maintain and repair the trail networks of arboreal ants

We study how the arboreal turtle ant (Cephalotes goniodontus) solves a fundamental computing problem: maintaining a trail network and finding alternative paths to route around broken links in the network. Turtle ants form a routing backbone of foraging trails linking several nests and temporary food sources. This species travels only in the trees, so their foraging trails are constrained to lie on a natural graph formed by overlapping branches and vines in the tangled canopy. Links between branches, however, can be ephemeral, easily destroyed by wind, rain, or animal movements. Here we report a biologically feasible distributed algorithm, parameterized using field data, that can plausibly describe how turtle ants maintain the routing backbone and find alternative paths to circumvent broken links in the backbone. We validate the ability of this probabilistic algorithm to circumvent simulated breaks in synthetic and real-world networks, and we derive an analytic explanation for why certain features are crucial to improve the algorithms success. Our proposed algorithm uses fewer computational resources than common distributed graph search algorithms, and thus may be useful in other domains, such as for swarm computing or for coordinating molecular robots.

bioinformatics↗