Biology subjects

Thompson, A.

Publications and source records attributed to Thompson, A..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

DNA-free CRISPR Genome Editing in Raspberry (Rubus idaeus) through RNP-mediated Protoplast Transfection and Comparison of Indel Analysis Techniques

Protoplast-based systems have been utilised in a wide variety of plant species to enable genome editing without chromosomal introgression of foreign DNA into plant genomes. This allows elite cultivars to be edited without further genetic segregation, preserving their unique genetic composition and their regulatory status as non-transgenic. This can be achieved by DNA-free genome editing in protoplasts, followed by regeneration. However, protoplast isolation presents a barrier to the development of advanced breeding technologies in raspberry and no protocol has been published for DNA-free genome editing in the species. Pre-assembled ribonucleoprotein complexes (RNPs) do not require cellular processing and the commercial availability of Cas9 proteins and synthetic guide RNAs has streamlined genome editing protocols. This study presents a novel high-yielding protoplast isolation protocol from raspberry stem cultures and RNP-mediated transfection of protoplast with CRISPR-Cas9. Targeted mutagenesis of the phytoene desaturase gene at two intragenic loci resulted in an editing efficiency of 19%, though estimated efficiency varied depending on the indel analysis technique. Only amplicon sequencing was sensitive enough to confirm genome editing in a low efficiency sample. To our knowledge, this study constitutes the first use of DNA-free genome editing in raspberry. This protocol provides a valuable platform for understanding gene function and facilitates the development of precision breeding in this important soft fruit crop.

plant biology↗

bioRxiv2024

Immune History Modifies Disease Severity to HPAI H5N1 Clade 2.3.4.4b Viral Challenge

The most recent outbreak of highly pathogenic avian H5 influenza (HPAI) virus in cattle is now widespread across the U.S. with spillover events happening to other mammals, including humans. Several human cases have been reported with clinical signs ranging from conjunctivitis to respiratory illness. However, most of those infected report mild to moderate symptoms, while previously reported HPAI H5Nx infections in humans have had mortality rates upwards of 50%. We recently reported that mice with pre-existing immunity to A/Puerto Rico/08/1934 H1N1 virus were protected from lethal challenge from highly pathogenic clade 2.3.4.4b H5N1 influenza virus. Here, we demonstrate that mice infected with the 2009 pandemic H1N1 virus strain A/California/04/2009 (Cal09) or vaccinated with a live-attenuated influenza vaccine (LAIV) were moderately-to-highly protected against a lethal A/bovine/Ohio/B24OSU-439/2024 H5N1 virus challenge. We also observed that ferrets with mixed pre-existing immunity--either from LAIV vaccination and/or from Cal09 infection--showed protection against a HPAI H5N1 clade 2.3.4.4b virus isolated from a cat. Notably, this protection occurred independently of any detectable hemagglutination inhibition titers (HAIs) against the H5N1 virus. To explore factors that may contribute to protection, we conducted detailed T cell epitope mapping using previously published sequences from H1N1 strains. This analysis revealed a high conservation of amino acid sequences within the internal proteins of our bovine HPAI H5N1 virus strain. These data highlight the necessity to explore additional factors that contribute to protection against HPAI H5N1 viruses, such as memory T cell responses, in addition to HA-inhibition or neutralizing antibodies.

microbiology↗

bioRxiv2024

Quantifying transcriptome turnover on phylogenies bymodeling gene expression as a binary trait

Changes in gene expression are a key driver of phenotypic evolution, leading to a persistent interest in the evolution of transcriptomes. Traditionally, gene expression is modeled as a continuous trait, leaving qualitative transitions largely unexplored. In this paper, we detail the development of new Bayesian inference techniques to study the evolutionary turnover of organ-specific transcriptomes, which we define as instances where orthologous genes gain or lose expression in a particular organ. To test these techniques, we analyze the transcriptomes of two male reproductive organs, testes and accessory glands, across 11 species of the Drosophila melanogaster species group. We first discretize gene expression states by estimating the probability that each gene is expressed in each organ and species. We then define a phylogenetic model of correlated transcriptome evolution in two or more organs and fit it to the expression state data. Inferences under this model show that many genes have gained and lost expression in each organ, and that the two organs experienced accelerated transcriptome turnover on different branches of the Drosophila phylogeny.

evolutionary biology↗

bioRxiv2024

Single cell genome and epigenome co-profiling reveals hardwiring and plasticity in breast cancer

Understanding the impact of genetic alterations on epigenomic phenotypes during breast cancer progression is challenging with unimodal measurements. Here, we report wellDA-seq, the first high-genomic resolution, high-throughput method that can simultaneously measure the whole genome and chromatin accessibility profiles of thousands of single cells. Using wellDA-seq, we profiled 22,123 single cells from 2 normal and 9 tumors breast tissues. By directly mapping the epigenomic phenotypes to genetic lineages across cancer subclones, we found evidence of both genetic hardwiring and epigenetic plasticity. In 6 estrogen-receptor positive breast cancers, we directly identified the ancestral cancer cells, and found that their epithelial cell-of-origin was Luminal Hormone Responsive cells. We also identified cell types with copy number aberrations (CNA) in normal breast tissues and discovered non-epithelial cell types in the microenvironment with CNAs in breast cancers. These data provide insights into the complex relationship between genetic alterations and epigenomic phenotypes during breast tumor evolution.

genomics↗

bioRxiv2024

phyddle: software for phylogenetic model exploration with deep learning

Phylogenies contain a wealth of information about the evolutionary history and process that gave rise to the diversity of life. This information can be extracted by fitting phylogenetic models to trees. However, many realistic phylogenetic models lack tractable likelihood functions, prohibiting their use with standard inference methods. We present phyddle, pipeline-based software for performing phylogenetic modeling tasks on trees using likelihood-free deep learning approaches. phyddle has a flexible command-line interface, making it easy to integrate deep learning approaches for phylogenetics into research workflows. phyddle coordinates modeling tasks through five pipeline analysis steps (Simulate, Format, Train, Estimate, and Plot) that transform raw phylogenetic datasets as input into numerical and visual model-based output. We conduct three experiments to compare the accuracy of likelihood-based inferences against deep learning-based inferences obtained through phyddle. Benchmarks show that phyddle accurately performs the inference tasks for which it was designed, such as estimating macroevolutionary parameters, selecting among continuous trait evolution models, and passing coverage tests for epidemiological models, even for models that lack tractable likelihoods. Learn more about phyddle at https://phyddle.org.

evolutionary biology↗

bioRxiv2024

One Health in practice: Multi-season survey of ixodid tick species collected from domestic dogs in Chad

Ticks are medically important vectors of pathogens, many of which are zoonotic or impact domestic animal and/or wildlife health. Climate change, landscape use, and increasing interactions between domestic animals, wildlife, and humans have resulted in changes in tick-host dynamics and the emergence of novel pathogens worldwide. Therefore, it is crucial to describe the host and geographic ranges of vector species to assess disease risk, particularly in areas where research is lacking. This task necessitates adopting a One Health approach. In sub-Saharan Africa, previous work on ticks has focused primarily on those species most relevant to domestic livestock or humans, highlighting a significant knowledge gap concerning species of ticks that infest peri-domestic animals in rural areas. The objective of this study was to investigate the species diversity of ticks on peri-domestic dogs in rural areas of Chad, Africa. From 2019-2022, we collected 3,412 ixodid ticks from 435 peri-domestic dogs from 23 villages in Chad, Africa during both dry and wet seasons. Ticks were identified to species using morphological techniques and/or molecular analyses of the 16S rRNA, 12S rRNA, and cytochrome oxidase I gene regions. We identified 11 species of ticks from dogs including Amblyomma variegatum, Amblyomma marmoreum, Haemaphysalis leachi, a Haemaphysalis sp., Hyalomma impressum, Hyalomma truncatum, Rhipicephalus decoloratus, Rhipicephalus guilhoni, Rhipicephalus muhsamae, Rhipicephalus linnaei (=R. sanguineus tropical lineage), and a Rhipicephalus sp. Several of these tick species are known vectors for important canine and zoonotic pathogens and some are more commonly associated with cattle hosts. Our results show that sampling ticks from peri-domestic dogs provides an opportunity to examine vectors that may infest domestic animals, agricultural animals, wildlife, and humans as hosts in an understudied area. HighlightsO_LITick-borne diseases are significant concern across sub-Saharan Africa C_LIO_LILimited data on ticks of animals and people in Chad, Africa C_LIO_LIA high diversity of tick species infested domestic dogs in Chad C_LIO_LIMany detected tick species associated with important pathogens C_LI

zoology↗

bioRxiv2024

From birds to mammals: spillover of highly pathogenic avian influenza H5N1 virus to dairy cattle led to efficient intra- and interspecies transmission

Infections with the highly pathogenic avian influenza (HPAI) H5N1 clade 2.3.4.4b virus have resulted in the death of millions of domestic birds and thousands of wild birds in the U.S. since January, 20221-4 Throughout this outbreak, spillovers of the virus to mammals have been frequently documented5-12. Here, we report the detection of HPAI H5N1 virus in dairy cattle herds across several states in the U.S. The affected cows displayed clinical signs encompassing decreased feed intake, altered fecal consistency, respiratory distress, and decreased milk production with abnormal milk. Infectious virus and RNA were consistently detected in milk collected from affected cows. Viral staining in tissues revealed a distinct tropism of the virus for the epithelial cells lining the alveoli of the mammary gland in cows. Analysis of whole genome sequences obtained from dairy cows, birds, domestic cats, and a racoon from affected farms indicated multidirectional interspecies transmissions. Epidemiologic and genomic data revealed efficient cow-to-cow transmission after healthy cows from an affected farm were transported to a premise in a different state. These results demonstrate the transmission of HPAI H5N1 clade 2.3.4.4b virus at a non-traditional interface and to a new and highly relevant livestock species, underscoring the ability of the virus to cross species barriers.

microbiology↗

bioRxiv2024

Climate resilience conserved in global germplasm repositories: Picking the most promising parents for agile plant breeding

Crop diversity is an essential resource for national and international breeding programs aimed at preparing global agriculture for a changing climate to ensure global food security. To do this there are related risks that need to be evaluated (1) does the genetic diversity needed for climate adaptation exist somewhere? And (2) is such genetic diversity accessible? To evaluate these risks, we consider the test case of publicly available genotyped and georeferenced sorghum landraces (n = 1,937) to ask if diversity is sufficient to support breeding for climate change adaptation. Answering these questions allows for characterization of the best potential parents and the geographies that harbor the most potentially promising genetypes for crop improvement. We subset this data into national, regional, and global geographic regions, and complete/mini core collections to understand the potential for climate adaptation in regional germplasm. Study accessions were given a future climate resilience score based on future climatic projections and a genomic adaptive capacity score using genomic estimated adaptive values (GEAVs) generated from environmental genomic selection - EGS) to ask whether this accessible diversity stored in germplasm repositories is potentially sufficient to meet forecasted changes in growing environments under climate change. We find that genomic resilience capacity is highly variable among countries and regions. High geographical variability was also found for climate resilience. To equitably adapt agriculture to future climate conditions, increased accessibility to plant genetic resources is essential.

genomics↗

bioRxiv2023

Post-GWAS Prioritization of Genome-Phenome Associations in Sorghum

Genome-Wide Association Studies (GWAS) are widely used to infer the genetic basis of traits in organisms, yet selecting appropriate thresholds for analysis remains a significant challenge. In this study, we developed the Sequential SNP Prioritization Algorithm (SSPA) to elucidate the genetic underpinnings of two key phenotypes in Sorghum bicolor: maximum canopy height and maximum growth rate. Utilizing a subset of the Sorghum Bioenergy Association Panel cultivated at the Maricopa Agricultural Center in Arizona, our objective was to employ GWAS with specific permissive-filtered thresholds to identify the genetic markers associated with these traits, allowing for a broader collection of explanatory candidate genes. Following this, our proposed method incorporates a feature engineering approach based on statistical correlation coefficient to reveal patterns between phenotypic similarity and genetic proximity across 274 accessions. This approach helps prioritize Single Nucleotide Polymorphisms (SNPs) likely to be associated with the studied phenotype. Additionally, we evaluated the impact of SSPA by considering all variants (SNPs) as inputs, without any GWAS filtering, as a complementary analysis. Empirical evidence including ontology- based gene function, spatial and temporal expression, and similarity to known homologs, demonstrated that SSPA effectively prioritizes SNPs and genes influencing the phenotype of interest, providing valuable insights for functional genetics research.

genomics↗

bioRxiv2023

A chromosome-level genome assembly of Solanum chilense, a tomato wild relative associated with resistance to salinity and drought

Solanum chilense is a wild relative of tomato reported to exhibit resistance to biotic and abiotic stresses. There is potential to improve tomato cultivars via breeding with wild relatives, a process greatly accelerated by suitable genomic and genetic resources. In this study we generated a high-quality, chromosome-level, de novo assembly for the S. chilense accession LA1972 using a hybrid assembly strategy with [~]180 Gbp of Illumina short reads and [~]50 Gbp long PacBio reads. Further scaffolding was performed using Bionano optical maps and 10x Chromium(R) reads. The resulting sequences were arranged into 12 pseudomolecules using Hi-C sequencing. This resulted in a 901 Mbp assembly, with a completeness of 95%, as determined by Benchmarking with Universal Single-Copy Orthologs (BUSCO). Sequencing of RNA from multiple tissues resulting in [~]219 Gbp of reads was used to annotate the genome assembly with an RNA-Seq guided gene prediction, and for a de novo transcriptome assembly. This chromosome-level, high-quality reference genome for S. chilense accession LA1972 will support future breeding efforts for more sustainable tomato production. Gene sequences related to drought and salt resistance were compared between S. chilense and S. lycopersicum to identify amino acid variations with high potential for functional impact. These variants were subsequently analysed in 84 resequenced tomato lines across 12 different related species to explore the variant distributions. We identified a set of 7 putative impactful amino acid variants some of which may also impact on fruit development for example the ethylene-responsive transcription factor WIN1 and ethylene-insensitive protein 2. These variants could be tested for their ability to confer functional phenotypes to cultivars that have lost these variants.

bioinformatics↗

bioRxiv2023

Structural and functional analysis of the minimal orthomyxovirus-like polymerase of Tilapia Lake Virus from the highly diverged Amnoonviridae family

Tilapia Lake Virus (TiLV), a recently discovered pathogen of tilapia fish, belongs to the Amnoonviridae family from the Articulavirales order. Its ten genome segments have characteristic conserved ends and encode proteins with no known homologues, apart from the segment 1, which encodes an orthomyxo-like RNA-dependent-RNA polymerase core subunit. Here we show that segments 1-3 encode respectively the PB1, PB2 and PA-like subunits of an active heterotrimeric polymerase that maintains all domains found in the distantly related influenza polymerase, despite an unprecedented overall size reduction of 40%. Multiple high-resolution cryo-EM structures of TiLV polymerase in pre-initiation, initiation and active elongation states, show how it binds the vRNA and cRNA promoters and performs RNA synthesis, with both transcriptase and replicase configurations being characterised. However, the highly truncated endonuclease-like domain appears inactive and the putative cap-binding domain is autoinhibited, emphasising that many functional aspects of TiLV polymerase remain to be elucidated.

microbiology↗

bioRxiv2023

Decoupled evolution of the Sex Peptide gene family and Sex Peptide Receptor in Drosophilidae

Across internally fertilising species, males transfer ejaculate proteins that trigger wide-ranging changes in female behaviour and physiology. Much theory has been developed to explore the drivers of ejaculate protein evolution. The accelerating availability of high-quality genomes now allows us to test how these proteins are evolving at fine taxonomic scales. Here, we use genomes from 264 species to chart the evolutionary history of Sex Peptide (SP), a potent regulator of female post-mating responses in Drosophila melanogaster. We infer that SP first evolved in the Drosophilinae subfamily and has followed markedly different evolutionary trajectories in different lineages. Outside of the Sophophora-Lordiphosa, SP exists largely as a single-copy gene with independent losses in several lineages. Within the Sophophora-Lordiphosa, the SP gene family has repeatedly and independently expanded. Up to seven copies, collectively displaying extensive sequence variation, are present in some species. Despite these changes, SP expression remains restricted to the male reproductive tract. Alongside, we document considerable interspecific variation in the presence and morphology of seminal microcarriers that, despite the critical role SP plays in microcarrier assembly in D. melanogaster, appear to be independent of changes in the presence/absence or sequence of SP. We end by providing evidence that SPs evolution is decoupled from that of its receptor, SPR, in which we detect no evidence of correlated diversifying selection. Collectively, our work describes the divergent evolutionary trajectories that a novel gene has taken following its origin and finds a surprisingly weak coevolutionary signal between a supposedly sexually antagonistic protein and its receptor. SignificanceIn insects, seminal fluid proteins (SFPs) induce dramatic changes in female behaviour and physiology. How this degree of male influence evolves remains a central question in sexual selection research. Here, we map the origin and diversification of the posterchild insect SFP, the Drosophila Sex Peptide (SP), across 264 Diptera species. We show that SP first evolved at the base of the subfamily Drosophilinae and followed markedly different evolutionary trajectories in different lineages, including accelerated change in sequence, copy number, and genomic position in the lineage leading to D. melanogaster. By contrast, we find only limited, uncorrelated change in the sequence of its receptor, SPR, arguing against a sexually antagonistic coevolutionary arms race between these loci on macroevolutionary time scales.

evolutionary biology↗

bioRxiv2023

A spatially resolved single cell genomic atlas of the adult human breast

The adult human breast comprises an intricate network of epithelial ducts and lobules that are embedded in connective and adipose tissue. While previous studies have mainly focused on the breast epithelial system, many of the non-epithelial cell types remain understudied. Here, we constructed a comprehensive Human Breast Cell Atlas (HBCA) at single-cell and spatial resolution. Our single-cell transcriptomics data profiled 535,941 cells from 62 women, and 120,024 nuclei from 20 women, identifying 11 major cell types and 53 cell states. These data revealed abundant pericyte, endothelial and immune cell populations, and highly diverse luminal epithelial cell states. Our spatial mapping using three technologies revealed an unexpectedly rich ecosystem of tissue-resident immune cells in the ducts and lobules, as well as distinct molecular differences between ductal and lobular regions. Collectively, these data provide an unprecedented reference of adult normal breast tissue for studying mammary biology and disease states such as breast cancer.

genomics↗

bioRxiv2023

Drug discovery for heart failure targeting myosin-binding protein C

Cardiac MyBP-C (cMyBP-C) interacts with actin-myosin to fine-tune cardiac muscle contractility. Phosphorylation of cMyBP-C, which reduces binding of cMyBP-C to actin or myosin, is often decreased in heart failure (HF) patients, and is cardioprotective in model systems for HF. Therefore, cMyBP-C is a potential target for HF drugs that mimic phosphorylation and/or perturb its interactions with actin or myosin. We labeled actin with fluorescein-5-maleimide (FMAL), and the C0-C2 fragment of cMyBP-C (cC0-C2) with tetramethyl rhodamine (TMR). We performed two complementary high-throughput screens (HTS) on an FDA-approved drug library, to discover small molecules that specifically bind to cMyBP-C and affect its interactions with actin or myosin, using fluorescence lifetime (FLT) detection. We first excited FMAL and detected its FLT, to measure changes in fluorescence resonance energy transfer (FRET) from FMAL (donor) to TMR (acceptor), indicating binding and/or structural changes in the protein complex. Using the same samples, we then excited TMR directly, using a longer wavelength laser, to detect the effects of compounds on the environmentally sensitive FLT of TMR, to identify compounds that bind directly to cC0-C2. Secondary assays, performed on selected modulators with the most promising effects in the primary HTS assays, characterized specificity of these compounds for phosphorylated versus unphosphorylated cC0-C2 and for cC0-C2 versus C1-C2 of fast skeletal muscle (fskC1-C2). A subset of identified compounds modulated ATPase activity in cardiac and/or skeletal myofibrils. These assays establish feasibility for discovery of small-molecule modulators of the cMyBP-C-actin/myosin interaction, with the ultimate goal of developing therapies for HF.

biophysics↗

bioRxiv2023

The Primacy of Temporal Dynamics in Driving Spatial Self-organization of Soil Redox Patterns

In this study, we investigate mechanisms that generate regularly-spaced, iron banding in upland soils. These redoximorphic features appear in soils worldwide, but their genesis has been heretofore unresolved. Upland soils are highly redox dynamic, with significant redox fluctuations driven by rainfall, groundwater changes, or irrigation. Pattern formation in these highly dynamic systems provides an opportunity to investigate the temporal dimension of spatial self-organization, which is not often explored. By comparing multiple alternative mechanisms, we find that regular redox patterns in upland soils are formed by coupling two sets of scale-dependent feedbacks (SDF), the general framework underlying Turing instability. The first set of SDF is based on clay aggregation and disaggregation. The second set is realized by threshold-dependent, negative root responses to aggregated crystalline Fe(III). The former SDF amplifies Fe(III) aggregation and crystallinity to trigger the latter SDF. Neither set of SDF alone is sufficient to reproduce observed patterns. Redox oscillations driven by environmental variability play an indispensable role in pattern formation. Environmental variability creates a range of conditions at the same site for various processes in SDF to occur, albeit in different temporal windows of differing durations. In effect, environmental variability determines mean rates of pattern-forming processes over the timescale relevant to pattern formation and modifies the likelihood that pattern formation will occur. As such, projected climate change might significantly alter many self-organized systems, as well as the ecological consequences associated with the striking patterns they present. This temporal dimension of pattern formation is previously unreported and merits close attention. Statement of SignificanceIron reactions create redox features in soils around the world. This study investigates mechanisms forming regularly-spaced iron stripes in upland soils. Upland soil redox conditions, driven by environmental variability, are highly dynamic. We show that two sets of scale-dependent feedbacks are coupled to form redox patterns and environmental variability plays a critical role in both. Significantly, environmental variability creates opportunities for various pattern-forming processes to occur at the same site in different temporal windows and determines mean process rates over the timescale relevant to pattern formation. Hence, environmental variability dictates the likelihood of pattern formation. Such a critical role of the temporal dimension in spatial self-organization has rarely been reported and has great potential for application in other self-organized ecosystems.

ecology↗

bioRxiv2023

Deep learning approaches to viral phylogeography are fast and as robust as likelihood methods to model misspecification

Analysis of phylogenetic trees has become an essential tool in epidemiology. Likelihood-based methods fit models to phylogenies to draw inferences about the phylodynamics and history of viral transmission. However, these methods are computationally expensive, which limits the complexity and realism of phylodynamic models and makes them ill-suited for informing policy decisions in real-time during rapidly developing outbreaks. Likelihood-free methods using deep learning are pushing the boundaries of inference beyond these constraints. In this paper, we extend, compare and contrast a recently developed deep learning method for likelihood-free inference from trees. We trained multiple deep neural networks using phylogenies from simulated outbreaks that spread among five locations and found they achieve close to the same levels of accuracy as Bayesian inference under the true simulation model. We compared robustness to model misspecification of a trained neural network to that of a Bayesian method. We found that both models had comparable performance, converging on similar biases. We also implemented a method of uncertainty quantification called conformalized quantile regression which we demonstrate has similar patterns of sensitivity to model misspecification as Bayesian highest posterior intervals (HPI) and greatly overlap with HPIs, but have lower precision (more conservative). Finally, we trained and tested a neural network against phylogeographic data from a recent study of the SARS-Cov-2 pandemic in Europe and obtained similar estimates of region-specific epidemiological parameters and the location of the common ancestor in Europe. Along with being as accurate and robust as likelihood-based methods, our trained neural networks are on average over 3 orders of magnitude faster. Our results support the notion that neural networks can be trained with simulated data to accurately mimic the good and bad statistical properties of the likelihood functions of generative phylogenetic models.

evolutionary biology↗

bioRxiv2023

High quality genome and transcriptome data for two new species of Mantamonas, a deep-branching eukaryote clade

Mantamonads were long considered to represent an "orphan" lineage in the tree of eukaryotes, likely branching near the most frequently assumed position for the root of eukaryotes. Recent phylogenomic analyses have placed them as part of the "CRuMs" supergroup, along with collodictyonids and rigifilids. This supergroup appears to branch at the base of Amorphea, making it of special importance for understanding the deep evolutionary history of eukaryotes. However, the lack of representative species and complete genomic data associated with them has hampered the investigation of their biology and evolution. Here, we isolated and described two new species of mantamonads, Mantamonas vickermani sp. nov. and Mantamonas sphyraenae sp. nov., for each of which we generated transcriptomic sequence data, as well as a high-quality genome for the latter. The estimated size of the M. sphyraenae genome is 25 Mb; our de novo assembly appears to be highly contiguous and complete with 9,416 predicted protein-coding genes. This near-chromosome-scale genome assembly is the first described for the CRuMs supergroup.

genomics↗

bioRxiv2022

Some like it hotter: differential thermal preferences among lizard color morphs

Temperature rules the lives of ectotherms. To perform basic biological functions, ectotherms must make behavioral adjustments to keep their body temperatures near a preferred temperature (Tpref). Many color polymorphic lizards are active thermoregulators and exhibit morph differences in traits related to thermoregulation, such as color, body size, and microhabitat use. The Aegean wall lizard, Podarcis erhardii, is a heliothermic lizard with orange, white, and yellow color morphs that differ in size, behavior, and microhabitat use. Here, we tested whether P. erhardii color morphs from the same population from Naxos island, Greece, differ in Tpref. We hypothesized that orange morphs would prefer lower temperatures than white and yellow morphs because orange morphs are often found on cooler substrates and in microhabitats with more vegetation cover. We obtained Tpref for 95 individuals using laboratory thermal gradient experiments of wild-caught lizards and found that orange morphs do, indeed, prefer significantly cooler temperatures, regardless of body size differences. Average orange morph Tpref was 2.3 {o}C lower than average white and yellow morph Tpref. Our results add support to the idea that P. erhardii color morphs have multivariate alternative phenotypes and present the possibility that thermally heterogeneous environments play a role in the maintenance of color polymorphism in this species.

zoology↗