Evidence map›Paper›PMID 37919677›Full record

ArticleBMC plant biology2023

Genomic signals of local adaptation in Picea crassifolia.

Shuo Feng, Erning Xi, Wei Wan, Dafu Ru

Open access · goldAbstract read
In one paragraph

Article in BMC plant biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.9field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 6 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 1 country.

Shuo Feng *State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining, 810016, People's Republic of China. fengshuo8894@126.com.
Erning Xi *State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining, 810016, People's Republic of China.
Wei WanState Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining, 810016, People's Republic of China.
Dafu RuState Key Laboratory of Herbage Improvement and Grassland Agro-Ecosystem, College of Ecology, Lanzhou University, Lanzhou, 730000, People's Republic of China. rudf@lzu.edu.cn.
Qinghai University · CNLanzhou University · CNState Key Laboratory of Plateau Ecology and Agriculture

Funding

National Natural Science Foundation of China 32001085Project of Qinghai Science & Technology Department 2020-ZJ-944Q
6 · The paper itself

Abstract

backgroundGlobal climate change poses a grave threat to biodiversity and underscores the importance of identifying the genes and corresponding environmental factors involved in the adaptation of tree species for the purposes of conservation and forestry. This holds particularly true for spruce species, given their pivotal role as key constituents of the montane, boreal, and sub-alpine forests in the Northern Hemisphere.

resultsHere, we used transcriptomes, species occurrence records, and environmental data to investigate the spatial genetic distribution of and the climate-associated genetic variation in Picea crassifolia. Our comprehensive analysis employing ADMIXTURE, principal component analysis (PCA) and phylogenetic methodologies showed that the species has a complex population structure with obvious differentiation among populations in different regions. Concurrently, our investigations into isolation by distance (IBD), isolation by environment (IBE), and niche differentiation among populations collectively suggests that local adaptations are driven by environmental heterogeneity. By integrating population genomics and environmental data using redundancy analysis (RDA), we identified a set of climate-associated single-nucleotide polymorphisms (SNPs) and showed that environmental isolation had a more significant impact than geographic isolation in promoting genetic differentiation. We also found that the candidate genes associated with altitude, temperature seasonality (Bio4) and precipitation in the wettest month (Bio13) may be useful for forest tree breeding.

conclusionsOur findings deepen our understanding of how species respond to climate change and highlight the importance of integrating genomic and environmental data in untangling local adaptations.

Indexed as

PiceaForestsGenomicsPhylogenyPlant BreedingGenetic structureGlobal climate changeRedundancy analysisTranscriptome

Identifiers

PMID37919677
PMCPMC10623705
OpenAlexW4388302641

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.