--- OA_place: publisher _id: '20991' abstract: - lang: eng text: "Rapid local adaptation to new environments is critical for species persistence, especially in introduced populations. The evolutionary success of these populations is fundamentally dictated by the organization of genetic variation—the genomic architecture—in the face of severe demographic constraints, such as the founder effects and genetic bottlenecks that frequently accompany colonization. A central question in evolutionary biology is whether rapid adaptation relies on major-effect loci, such as chromosomal inversions, or on many small-effect loci dispersed across the genome. Furthermore, the genomic architecture strongly influences the extent to which evolutionary outcomes are predictable. Using introduced populations of the marine snail, Littorina saxatilis, as a model, this thesis investigates how genetic variation and genomic structure drive adaptation following introduction. We employed a population genomics approach on experimentally and accidentally introduced populations to dissect the specific genomic features that underpin divergence in newly colonized environments.\r\n\r\nIn Chapter 2, we tested the predictability of local adaptation through an uncommon 30-year transplant experiment in nature. By distinguishing allele and chromosomal inversion frequency changes from neutral expectations, we found that evolutionary change was highly predictable at the macro-scale (phenotypes and chromosomal inversions), but less robust at the level of individual collinear loci. This result demonstrates that evolution can be predictable when a population possesses sufficient standing genetic variation (SGV), with chromosomal inversions acting as key integrated units that facilitate a rapid response to selection. Building on this, Chapter 3 applied whole-genome sequencing to three accidentally introduced populations (Venice, San Francisco, and Redwood City) to investigate their likely source and genomic patterns of divergence. We identified genomic regions of remarkable divergence potentially associated with local adaptation, and likely fuelled by SGV, while explicitly acknowledging the difficulty in disentangling selection signals from the genome-wide effects of demographic processes. Furthermore, we found that the divergence patterns relied extensively on the collinear genome in these introduced populations, and less clearly on the chromosomal inversions. This observation contrasts with local adaptation observed in the experimental system that relied on both collinear loci and highly selected chromosomal inversions, highlighting how demographic history and genomic architecture influence the detectable signature of local adaptation.\r\n\r\nA major limitation to conducting large-scale comparative evolutionary studies is the lack of data standardization, which prevents the integration of community knowledge and high-resolution environmental and genetic data. Chapter 4 addresses this by developing a community database for the Littorina system. This platform implements standardized protocols for the integration of diverse phenotypic and environmental data from multiple Littorina species. Likewise, the platform also centralizes the availability of associated genomic data through links to external repositories. This database represents a crucial tool to test complex, large-scale evolutionary hypotheses.\r\n\r\nCollectively, this thesis strongly reinforces the fundamental importance of SGV as the raw material for successful local adaptation, a conclusion supported by evidence in both experimental and accidental introductions. Furthermore, this work highlights the critical role of the genomic architecture—specifically chromosomal inversions—in driving the predictability and effectiveness of adaptive responses. Our findings underscore how the interplay between SGV and genomic architecture dictates the trajectory and detectability of evolution in colonizing populations, while simultaneously providing a necessary tool to advance comparative evolutionary genomics in emerging model organisms." acknowledgement: "I acknowledge the funding agencies 1Norwegian Research Council RCN project 315287.\r\n2The FIASCO project \"Illuminating range shifts through evolutionary FIASCO: contrasting\r\nFaIling And Successful ColOnizations in replicated wild populations\", funded by the\r\nEuropean Union - Next Generation EU (Piano Nazionale di Ripresa e Resilienza - MUR\r\ncode: P202229JBC, CUP: C53D23007100001). 3Ecotypic formation in Littorina saxatilis\r\nin the Western Atlantic and comparisons across the North Atlantic. University of\r\nGothenburg Research Travel Grant, Tjarno Marine Laboratory, Sweden. $3023 (2018).\r\n4JIN project (Young Researchers, Spanish Ministry of Science, RTI2018-101274-J-I00)" alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Diego Fernando full_name: Garcia Castillo, Diego Fernando id: ae681a14-dc74-11ea-a0a7-c6ef18161701 last_name: Garcia Castillo citation: ama: Garcia Castillo DF. The genomic architecture of local adaptation in introduced populations. 2026. doi:10.15479/AT-ISTA-20991 apa: Garcia Castillo, D. F. (2026). The genomic architecture of local adaptation in introduced populations. Institute of Science and Technology Austria. https://doi.org/10.15479/AT-ISTA-20991 chicago: Garcia Castillo, Diego Fernando. “The Genomic Architecture of Local Adaptation in Introduced Populations.” Institute of Science and Technology Austria, 2026. https://doi.org/10.15479/AT-ISTA-20991. ieee: D. F. Garcia Castillo, “The genomic architecture of local adaptation in introduced populations,” Institute of Science and Technology Austria, 2026. ista: Garcia Castillo DF. 2026. The genomic architecture of local adaptation in introduced populations. Institute of Science and Technology Austria. mla: Garcia Castillo, Diego Fernando. The Genomic Architecture of Local Adaptation in Introduced Populations. Institute of Science and Technology Austria, 2026, doi:10.15479/AT-ISTA-20991. short: D.F. Garcia Castillo, The Genomic Architecture of Local Adaptation in Introduced Populations, Institute of Science and Technology Austria, 2026. corr_author: '1' date_created: 2026-01-16T09:47:59Z date_published: 2026-01-16T00:00:00Z date_updated: 2026-04-16T12:20:37Z day: '16' ddc: - '576' degree_awarded: PhD department: - _id: GradSch - _id: NiBa doi: 10.15479/AT-ISTA-20991 file: - access_level: closed checksum: 841f1bc073d667125729b2a017f8c37a content_type: application/vnd.openxmlformats-officedocument.wordprocessingml.document creator: dgarciac date_created: 2026-01-16T12:25:13Z date_updated: 2026-01-16T12:25:13Z file_id: '20996' file_name: 2026_Garcia_Diego_Thesis.docx file_size: 22456421 relation: source_file - access_level: open_access checksum: a1f33d4f183ce7072eee42a6ccf5340b content_type: application/pdf creator: dgarciac date_created: 2026-01-16T12:25:13Z date_updated: 2026-01-16T12:25:13Z file_id: '20997' file_name: 2026_Garcia_Diego_Thesis.pdf file_size: 9556719 relation: main_file success: 1 - access_level: closed checksum: 98a80691067174c30fe53f38ce7344e6 content_type: application/x-compressed creator: dgarciac date_created: 2026-01-16T13:08:14Z date_updated: 2026-01-16T13:08:14Z description: Source code of the PostgreSQL database, front-end and back-end of the LittorinaDB web application developed as a product of the 4th chapter of the thesis. file_id: '20998' file_name: 2026_DiegoGarcia_LittorinaDB Source Code and Protocols.rar file_size: 54491433 relation: supplementary_material - access_level: open_access checksum: 99a3cab2fa36666b9a92eefc27d586da content_type: application/x-compressed creator: dgarciac date_created: 2026-01-16T13:08:14Z date_updated: 2026-01-16T13:08:14Z file_id: '20999' file_name: 2026_DiegoGarcia_Thesis-Supplementary_Material.rar file_size: 7982811 relation: supplementary_material - access_level: open_access checksum: 255fdf56b2932c46bf27c63aa6106a4f content_type: text/plain creator: dgarciac date_created: 2026-01-16T13:08:59Z date_updated: 2026-01-16T13:08:59Z file_id: '21000' file_name: README.txt file_size: 732 relation: supplementary_material file_date_updated: 2026-01-16T13:08:59Z has_accepted_license: '1' language: - iso: eng license: https://creativecommons.org/licenses/by-nc-sa/4.0/ month: '01' oa: 1 oa_version: Published Version page: '199' publication_identifier: isbn: - 978-3-99078-077-0 issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '18498' relation: research_data status: public - id: '18491' relation: part_of_dissertation status: public status: public supervisor: - first_name: Nicholas H full_name: Barton, Nicholas H id: 4880FE40-F248-11E8-B48F-1D18A9856A87 last_name: Barton orcid: 0000-0002-8548-5240 - first_name: Anja M full_name: Westram, Anja M id: 3C147470-F248-11E8-B48F-1D18A9856A87 last_name: Westram orcid: 0000-0003-1050-4969 title: The genomic architecture of local adaptation in introduced populations tmp: image: /images/cc_by_nc_sa.png legal_code_url: https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode name: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) short: CC BY-NC-SA (4.0) type: dissertation user_id: ba8df636-2132-11f1-aed0-ed93e2281fdd year: '2026' ...