Biology subjects

Tittes, S.

Publications and source records attributed to Tittes, S..

11 recordsLinked to original sources

bioRxiv2026

This must be the place: deep learning local adaptation

Climate change is increasingly disrupting the relationship between locally adapted populations and the environments in which they evolved, creating an urgent need for tools that connect genomic variation to climate. Common-garden and provenance trials remain the gold standard for characterizing local adaptation, but their time and resource requirements limit how broadly they can be applied. Genomic approaches provide a complementary path. Genotype--environment association (GEA) methods identify environmentally associated loci. Machine-learning models have also shown that geographic origin can be predicted directly from genotypes. Here we introduce EcoLocator, a supervised deep neural network that jointly predicts geographic location and climate of origin from genotypes. Through extensive simulations we demonstrate that EcoLocator accurately recovers geographic location and environment of origin from genotype data, and, with SHAP-based feature attribution, identifies adaptive loci more reliably than benchmark GEA methods. We apply our method to coastal Douglas-fir (Pseudotsuga menziesii var. menziesii), where EcoLocator predicts geographic origin (R2=0.75--0.83) and climate of origin (R2=0.52--0.72) under leave-one-out cross-validation. Notably, we find that climate predicted directly from genotypes outperforms climate inferred by first predicting geographic origin, showing that EcoLocator captures genotype--climate signal that cannot be recovered from geography alone. Our prediction errors fall within the tolerances used in existing seed-transfer guidelines, demonstrating that EcoLocator's predictions are ready for practical application, and our approach is readily extendable to other species and conservation contexts.

evolutionary biology↗

bioRxiv2026

Diversity and divergence of two sympatric, sibling octopus species

Coleoid cephalopods have convergently evolved many traits shared with vertebrates, including camera-type eyes, large brain-to-body size ratios, and complex behaviors. Most evolutionary studies of cephalopods have compared individual genomes of taxa that diverged tens to hundreds of millions of years ago, yet very few have examined more recent evolution from a population genetics perspective. Here we present a comparative population genomic analysis of the sympatric sister species Octopus bimaculatus and Octopus bimaculoides using whole-genome resequencing. Despite similar morphologies, these species differ substantially in their life histories, ecologies, and geographic distributions. Using demographic inference, we estimated that the two species diverged approximately one million years ago and that O. bimaculatus has maintained a consistently larger effective population size since divergence. Consistent with these demographic histories, we found stronger signatures of positive selection in O. bimaculatus, including a positive correlation between recombination rate and nucleotide diversity, more selective sweeps, and a higher proportion of mutations fixed by adaptation--all consistent with more efficient natural selection in larger populations. Protein-coding genes overlapping with selective sweeps were enriched for various functions that included many related to brain and eye development, suggesting that traits characteristic of coleoid cephalopods continue to be shaped by positive selection on recent timescales in these species. Comparing coding-sequence divergence on the Z chromosome to the autosomes, we also find evidence for a female-biased mutation rate, consistent with an independent estimate from a deeper-timescale cephalopod comparison.

evolutionary biology↗

bioRxiv2025

Accessible, realistic genome simulation with selection using stdpopsim

Selection is a fundamental evolutionary force that shapes patterns of genetic variation across species. However, simulations incorporating realistic selection along heterogeneous genomes in complex demographic histories are challenging, limiting our ability to benchmark statistical methods aimed at detecting selection and to explore theoretical predictions. stdpopsim is a community-maintained simulation library that already provides an extensive catalog of species-specific population genetic models. Here we present a major extension to the stdpopsim framework that enables simulation of various modes of selection, including background selection, selective sweeps, and arbitrary distributions of fitness effects (DFE) acting on annotated subsets of the genome (for instance, exons). This extension maintains stdpopsims core principles of reproducibility and accessibility while adding support for species-specific genomic annotations and published DFE estimates. We demonstrate the utility of this framework by comparing methods for demographic inference, DFE estimation, and selective sweep detection across several species and scenarios. Our results demonstrate the robustness of demographic inference methods to selection on linked sites, reveal the sensitivity of DFE-inference methods to model assumptions, and show how genomic features, like recombination rate and functional sequence density, influence power to detect selective sweeps. This extension to stdpopsim provides a powerful new resource for the population genetics community to explore the interplay between selection and other evolutionary forces in a reproducible, user-friendly framework.

evolutionary biology↗

bioRxiv2024

Population genetics meets ecology: a guide to individual-based simulations in continuous landscapes

Individual-based simulation has become an increasingly crucial tool for many fields of population biology. However, continuous geography is important to many applications, and implementing realistic and stable simulations in continuous space presents a variety of difficulties, from modeling choices to computational efficiency. This paper aims to be a practical guide to spatial simulation, helping researchers to implement individual-based simulations and avoid common pitfalls. To do this, we delve into mechanisms of mating, reproduction, density-dependent feedback, and dispersal, all of which may vary across the landscape, discuss how these affect population dynamics, and describe how to parameterize simulations in convenient ways (for instance, to achieve a desired population density). We also demonstrate how to implement these models using the current version of the individual-based simulator, SLiM. We additionally discuss natural selection - in particular, how genetic variation can affect demographic processes. Finally, we provide four short vignettes: simulations of pikas that shift their range up a mountain as temperatures rise; mosquitoes that live in rivers as juveniles and experience seasonally changing habitat; cane toads that expand across Australia, reaching 120 million individuals; and monarch butterflies whose populations are regulated by an explicitly modeled resource (milkweed).

evolutionary biology↗

bioRxiv2024

Cephalopod Sex Determination and its AncientEvolutionary Origin Revealed by Chromosome-levelAssembly of the California two-spot Octopus

Octopuses, squids, and cuttlefishes - the coleoid cephalopods - are a remarkable branch in the tree of life whose members exhibit a repertoire of sophisticated behaviors (Hanlon and Messenger, 2018). As a clade, coleoids harbor an incredible variety of novel traits including the most complex nervous system among invertebrates, derived camera-type eyes, and rapid adaptive camouflage abilities (Young, 1971; Hanlon, 2007). The burst of evolutionary novelty that distinguishes cephalopods is even more striking in a phylogenetic context; cephalopods are a deeply diverged lineage that last share a common ancestor with other extant molluscs in the Cambrian period, roughly 550 million years ago (Ponder and Lindberg, 2008; Huang et al., 2022). With recent advances in genome sequencing technologies, we have the capability to explore the genomic foundations of cephalopod novelties. Here, using PacBio long-read sequencing of genomic DNA and IsoSeq full-length mRNA sequencing, we provide a novel chromosome-scale reference genome and annotation for a female California two-spot octopus (O. bimaculoides). Our assembly reveals that the female octopus has just one sex chromosome, consistent with a ZO karyotype, while the male has two (ZZ), providing the first evidence of genetic sex determination in cephalopods. We use our assembly and annotation in combination with existing genomic information from other cephalopods to create the first whole genome alignments from this group and demonstrate that the sex chromosome is of an ancient origin, before the radiation of extant cephalopods approximately 480 million years ago (Huang et al., 2022), and has been conserved to the present day in all cephalopod genomes available.

evolutionary biology↗

bioRxiv2022

Expanding the stdpopsim species catalog, and lessons learned forrealistic genome simulations

Simulation is a key tool in population genetics for both methods development and empirical research, but producing simulations that recapitulate the main features of genomic data sets remains a major obstacle. Today, more realistic simulations are possible thanks to large increases in the quantity and quality of available genetic data, and to the sophistication of inference and simulation software. However, implementing these simulations still requires substantial time and specialized knowledge. These challenges are especially pronounced for simulating genomes for species that are not well-studied, since it is not always clear what information is required to produce simulations with a level of realism sufficient to confidently answer a given question. The community-developed framework stdpopsim seeks to lower this barrier by facilitating the simulation of complex population genetic models using up-to-date information. The initial version of stdpopsim focused on establishing this framework using six well-characterized model species (Adrion et al., 2020). Here, we report on major improvements made in the new release of stdpopsim (version 0.2), which includes a significant expansion of the species catalog and substantial additions to simulation capabilities. Features added to improve the realism of the simulated genomes include non-crossover recombination and provision of species-specific genomic annotations. Through community-driven efforts, we expanded the number of species in the catalog more than three-fold and broadened coverage across the tree of life. During the process of expanding the catalog, we have identified common sticking points and developed best practices for setting up genome-scale simulations. We describe the input data required for generating a realistic simulation, suggest good practices for obtaining the relevant information from the literature, and discuss common pitfalls and major considerations. These improvements to stdpopsim aim to further promote the use of realistic whole-genome population genetic simulations, especially in non-model organisms, making them available, transparent, and accessible to everyone.

bioinformatics↗

bioRxiv2022

Dispersal inference from population genetic variation using a convolutional neural network

The geographic nature of biological dispersal shapes patterns of genetic variation over landscapes, making it possible to infer properties of dispersal from genetic variation data. Here we present an inference tool that uses geographically distributed genotype data in combination with a convolutional neural network to estimate a critical population parameter: the mean per-generation dispersal distance. Using extensive simulation, we show that our deep learning approach is competitive with or outperforms state-of-the-art methods, particularly at small sample sizes. In addition, we evaluate varying nuisance parameters during training--including population density, demographic history, habitat size, and sampling area--and show that this strategy is effective for estimating dispersal distance when other model parameters are unknown. Whereas competing methods depend on information about local population density or accurate identification of identity-by-descent tracts, our method uses only single-nucleotide-polymorphism data and the spatial scale of sampling as input. Strikingly, and unlike other methods, our method does not use the geographic coordinates of the genotyped individuals. These features make our method, which we call "disperseNN", a potentially valuable new tool for estimating dispersal distance in non-model systems with whole genome data or reduced representation data. We apply disperseNN to 12 different species with publicly available data, yielding reasonable estimates for most species. Importantly, our method estimated consistently larger dispersal distances than mark-recapture calculations in the same species, which may be due to the limited geographic sampling area covered by some mark-recapture studies. Thus genetic tools like ours complement direct methods for improving our understanding of dispersal.

evolutionary biology↗

bioRxiv2021

Not so local: the population genetics of convergent adaptation in maize and teosinte.

What is the genetic architecture of local adaptation and what is the geographic scale over which it operates? We investigated patterns of local and convergent adaptation in five sympatric population pairs of traditionally cultivated maize and its wild relative teosinte (Zea mays subsp. parviglumis). We found that signatures of local adaptation based on the inference of adaptive fixations and selective sweeps are frequently exclusive to individual populations, more so in teosinte compared to maize. However, for both maize and teosinte, selective sweeps are also frequently shared by several populations, and often between subspecies. We were further able to infer that selective sweeps were shared among populations most often via migration, though sharing via standing variation was also common. Our analyses suggest that teosinte has been a continued source of beneficial alleles for maize, even after domestication, and that maize populations have facilitated adaptation in teosinte by moving beneficial alleles across the landscape. Taken together, our results suggest local adaptation in maize and teosinte has an intermediate geographic scale, one that is larger than individual populations but smaller than the species range.

evolutionary biology↗

bioRxiv2021

De novo assembly, annotation, and comparative analysis of 26 diverse maize genomes

We report de novo genome assemblies, transcriptomes, annotations, and methylomes for the 26 inbreds that serve as the founders for the maize nested association mapping population. The data indicate that the number of pan-genes exceeds 103,000 and that the ancient tetraploid character of maize continues to degrade by fractionation to the present day. Excellent contiguity over repeat arrays and complete annotation of centromeres further reveal the locations and internal structures of major cytological landmarks. We show that combining structural variation with SNPs can improve the power of quantitative mapping studies. Finally, we document variation at the level of DNA methylation, and demonstrate that unmethylated regions are enriched for cis-regulatory elements that overlap QTL and contribute to changes in gene expression. One sentence summaryA multi-genome analysis of maize reveals previously unknown variation in gene content, genome structure, and methylation.

genomics↗

bioRxiv2020

rdmc: an open source R package implementing convergent adaptation models of Lee and Coop (2017)

The availability of whole genome sequencing data from multiple related populations creates opportunities to test sophisticated population genetic models of convergent adaptation. Recent work by Lee and Coop (2017) developed models to infer modes of convergent adaption at local genomic scales, providing a rich framework for assessing how selection has acted across multiple populations at the tested locus. Here I present, rdmc, an R package that builds on the existing software implementation of Lee and Coop (2017) that prioritizes ease of use, portability, and scalability. I demonstrate installation and comprehensive overview of the packages current utilities.

evolutionary biology↗

bioRxiv2019

Genetic diversity and thermal performance in invasive and native populations of African fig flies

During biological invasions, alien populations can suffer losses of genetic diversity that are predicted to negatively impact their fitness/performance. Using genome sequences, we show that invasive populations of the African fig fly, Zaprionus indianus, have lower levels of genetic diversity compared to native populations, and that genetic diversity is lost more in regions of the genome with low recombination rates. However, genetic diversity remains as high or higher in invasive populations than in populations of non-invasive congeneric species. We then use parameter estimates from thermal performance curves measured for 13 species of Zaprionus to show that Z. indianus has the broadest thermal niche of measured species, and that performance does not differ between invasive and native populations. These results illustrate how aspects of genetic diversity in invasive species can be decoupled from measures of fitness, and that a broad thermal niche may have helped facilitate Z. indianuss range expansion.

evolutionary biology↗