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Record W4210596410 · doi:10.1038/s41598-022-05248-1

Population transcriptomics reveals the effect of gene flow on the evolution of range limits

2022· article· en· W4210596410 on OpenAlexfundno aff
Katsunori Tamagawa, Kotone Yoshida, Shiori Ohrui, Yuma Takahashi

Bibliographic record

VenueScientific Reports · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsnot available
FundersInstitute of GeneticsJapan Society for the Promotion of ScienceFujiwara Natural History Foundation
KeywordsLocal adaptationPopulationEcologyGene flowRange (aeronautics)Biological dispersalHabitatSpecies distributionBiologyEnvironmental scienceGenetic variation

Abstract

fetched live from OpenAlex

One of the most important questions in evolutionary biology is how the spatial distribution of species is limited. Asymmetric gene flow from core populations is suggested to increase the number of poorly adapted immigrants in the populations at the range edge. Genetic load due to migration, i.e., migration load, should prevent adaptation to the local habitat, leading to decreases in distribution range via local extinction or the limiting range expansion. However, few experimental studies have examined the effects of immigration on fitness and natural selection within recipient populations. To investigate the influence of migration load on the evolution of distribution range, we performed field and laboratory observations as well as population transcriptomics for the common river snail, Semisulcospira reiniana. This species meets the conditions that migration from source populations can prevent local adaptation in a sink population because they inhabit the broader range of environments, including middle/upper reaches of a river and estuaries within a single river and they may be more vulnerable to being swept away by water currents due to lowered spontaneous (upward) locomotion activity. We found that river steepness was related to the lower distribution limit of S. reiniana, with a narrower distribution range in the steeper river. Population transcriptomic analysis showed that gene flow was heavily asymmetric from the upstream populations to downstream ones in the steep river, suggesting a greater migration load in the steep river. The number of genes putatively involved in adaptation to the local habitat was lower in the steep river than in the gentle river. Gene expression profiles suggested that individuals achieve better local adaptation in the gentle river. Laboratory experiments suggested that evolutionary differences in salinity tolerance among local populations were only found in the gentle river. Our results consistent with the hypothesis that migration load owing to asymmetric gene flow disturbs local adaptation and restricts the distribution range of river snails.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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

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 head0.010
GPT teacher head0.217
Teacher spread0.207 · 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 designObservational
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

Citations5
Published2022
Admission routes1
Has abstractyes

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