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Record W3201217934 · doi:10.1111/mec.16174

Phenotypic and genomic adaptations to the extremely high elevation in plateau zokor (<i>Myospalax baileyi</i>)

2021· article· en· W3201217934 on OpenAlexaff
Tao Zhang, Jie Chen, Jia Zhang, Yuan‐Ting Guo, Xin Zhou, Meng‐Wen Li, Zhizhong Zheng, Tongzuo Zhang, Robert W. Murphy, Eviatar Nevo, Peng Shi

Bibliographic record

VenueMolecular Ecology · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHigh Altitude and Hypoxia
Canadian institutionsRoyal Ontario Museum
FundersNational Natural Science Foundation of China
KeywordsBiologyAdaptation (eye)Evolutionary biologyLocal adaptationPhenotypePopulationPlateau (mathematics)Phenotypic traitGeneticsEcologyGeneDemography

Abstract

fetched live from OpenAlex

The evolutionary outcomes of high elevation adaptation have been extensively described. However, whether widely distributed high elevation endemic animals adopt uniform mechanisms during adaptation to different elevational environments remains unknown, especially with respect to extreme high elevation environments. To explore this, we analysed the phenotypic and genomic data of seven populations of plateau zokor (Myospalax baileyi) along elevations ranging from 2,700 to 4,300 m. Based on whole-genome sequencing data and demographic reconstruction of the evolutionary history, we show that two populations of plateau zokor living at elevations exceeding 3,700 m diverged from other populations nearly 10,000 years ago. Further, phenotypic comparisons reveal stress-dependent adaptation, as two populations living at elevations exceeding 3,700 m have elevated ratios of heart mass to body mass relative to other populations, and the highest population (4,300 m) displays alterations in erythrocytes. Correspondingly, genomic analysis of selective sweeps indicates that positive selection might contribute to the observed phenotypic alterations in these two extremely high elevation populations, with the adaptive cardiovascular phenotypes of both populations possibly evolving under the functional constrains of their common ancestral population. Taken together, phenotypic and genomic evidence demonstrates that heterogeneous stressors impact adaptations to extreme elevations and reveals stress-dependent and genetically constrained adaptation to hypoxia, collectively providing new insights into the high elevation adaptation.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.855
Threshold uncertainty score0.495

Codex and Gemma teacher scores by category

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 head0.008
GPT teacher head0.219
Teacher spread0.211 · 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 teacher head, 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

Citations32
Published2021
Admission routes1
Has abstractyes

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