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Record W7161935798 · doi:10.82308/34265

The genetic basis of phenotypic differentiation in Python regius and Gasterosteus aculeatus

2023· dissertation· en· W7161935798 on OpenAlexaboutno aff
Alan García‐Elfring

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicmelanin and skin pigmentation
Canadian institutionsnot available
Fundersnot available
KeywordsGasterosteusPhenotypePopulationNatural selectionTraitGenetic architectureHuman evolutionary geneticsPhenotypic trait

Abstract

fetched live from OpenAlex

"Knowledge of the underlying genetic mechanisms responsible for phenotypic evolution is central for understanding the process of adaptation. In my dissertation I use two complementary study systems to generate insight into distinct parts of this process. I first use captive ball pythons (Python regius) from the pet trade to identify causal links between genetic variation and phenotypic diversity. Next, to understand real-world fitness consequences of genetic variation, I use natural populations of threespine stickleback (Gasterosteus aculeatus) experiencing rapid environmental change. The first section of my research takes advantage of artificial selection on colour and patterning imposed in captive breeding programs to understand genotype-phenotype connections. Most pigmentation studies lack the functional validation needed to make a causal link between genotype and phenotype. Those that do are usually based on a few model species, like the mouse and zebrafish. This raises the question of whether the knowledge gained from these classic model species is generalizable across vertebrates. Furthermore, by far the most intensely studied colour trait is melanin pigmentation, with relatively little known of the genetics of pteridine pigmentation and iridophore structural colouration in non-mammal vertebrates, particularly reptiles. Captive ball pythons display an extraordinary degree of colour variation, making them an excellent model species for the study of the genetics of phenotypic diversification. I use whole-genome sequencing, population genetics, gene-editing, and electron microscopy methods to uncover the genetic basis of a recessive colour phenotype characterized by blotches of white skin. This research led to the discovery of a transcription factor not previously linked to reptile colouration or white spotting in general. Functional validation confirmed the role of this transcription factor in reptile pigmentation and showed it is required for iridophore development in a lizard model. A genomic analysis of additional Mendelian colour morphs identified genes not only in the melanin pathway but also pteridine pigmentation. I next used threespine stickleback fish to study the effects of selection acting on genetic variation within natural populations. Stickleback are a classic system in evolutionary genetics for showing evidence of natural selection through parallel evolution of freshwater-adapted ecomorphs from marine ancestors. However, studies on parallel adaptation in stickleback tend to be restricted in time and space. Most have been focused on populations in which the ecological shift (e.g., colonization of freshwater habitats by marine populations), and thus natural selection, occurred thousands of years prior, and they have been confined to a few geographic regions where certain derived phenotypes are repeatedly observed. This leaves open questions of how quickly genomic responses to selection can be detected – months, years, thousands of years - and what alternative evolutionary pathways to freshwater adaptation have been taken in populations outside of the extensively studied locations. My research shows that parallel genomic changes in estuary stickleback can be detected within a single year near to genes linked to osmoregulation, largely mirroring the longer-term patterns observed in post-glacial populations. In addition, lake populations of stickleback from eastern Canada show different genotypic targets of selection to those that have been repeatedly identified in the more well-studied regions on the Pacific coast of North America, suggesting alternative pathways can be used for adaptation. This is likely due to differences in standing genetic variation among populations from different geographic regions as a result of range expansion. Collectively, this research is helping expand our knowledge of the functional connections between genotype, phenotype, and fitness, and the ways in which they interact to govern the trajectory of evolutionary change."@eng

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.251
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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