Evidence map›Paper›PMID 31527784›Full record

ArticleHeredity2020

Adaptive signals of flowering time pathways in wild barley from Israel over 28 generations.

Chaoju Qian, Xia Yan, Yong Shi, Hengxia Yin, Yuxiao Chang, Jun Chen, Pär K Ingvarsson, Eviatar Nevo, Xiao-Fei Ma

Abstract read
In one paragraph

Article in Heredity, 2020. 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
–field-weighted citation impact
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.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Review
  6. Genomic Adaptive Evolution of Sand Rice (Frontiers in genetics · 2021
    Article
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

9 authors.

Chaoju QianDepartment of Ecology and Agriculture Research, Key Laboratory of Stress Physiology and Ecology in Cold and Arid Regions, Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, Gansu, China.
Xia YanSchool of Life Sciences, Nantong University, Nantong, 226019, Jiangsu, China.
Yong ShiGermplasm Bank of Wild Species in Southwest China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, 650201, Yunnan, China.
Hengxia YinState Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining, 810016, Qinghai, China.
Yuxiao ChangAgricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 450002, China.ORCID http://orcid.org/0000-0002-0703-3732
Jun ChenCollege of Life Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China.
Pär K IngvarssonDepartment of Plant Biology, Swedish University of Agricultural Sciences, Uppsala BioCenter, SE-750 07, Uppsala, Sweden.ORCID http://orcid.org/0000-0001-9225-7521
Eviatar NevoInstitute of Evolution, University of Haifa, Haifa, 3498838, Israel. nevo@research.haifa.ac.il.
Xiao-Fei MaDepartment of Ecology and Agriculture Research, Key Laboratory of Stress Physiology and Ecology in Cold and Arid Regions, Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, Gansu, China. maxiaofei@lzb.ac.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Flowering time is one of the most critical traits for plants' life cycles, which is influenced by various environment changes, such as global warming. Previous studies have suggested that to guarantee reproductive success, plants have shifted flowering times to adapt to global warming. Although many studies focused on the molecular mechanisms of early flowering, little was supported by the repeated sampling at different time points through the changing climate. To fully dissect the temporal and spatial evolutionary genetics of flowering time, we investigated nucleotide variation in ten flowering time candidate genes and nine reference genes for the same ten wild-barley populations sampled 28 years apart (1980-2008). The overall genetic differentiation was significantly greater in the descendant populations (2008) compared with the ancestral populations (1980); however, local adaptation tests failed to detect any single-nucleotide polymorphism (SNP)/indel under spatial-diversifying selection at either time point. By contrast, the WFABC (Wright-Fisher ABC-based approach) that detected 54 SNPs/indels was under strong selection during the past 28 generations. Moreover, all these 54 alleles were segregated in the ancestral populations, but fixed in the descendent populations. Among the top ten SNPs/indels, seven were located in genes of FT1 (FLOWERING TIME LOCUS T 1), CO1 (CONSTANS-LIKE PROTEIN 1), and VRN-H2 (VERNALIZATION-H2), which have been documented to be associated with flowering time regulation in barley cultivars. This study might suggest that all ten populations have undergone parallel evolution over the past few decades in response to global warming, and even an overwhelming local adaptation and ecological differentiation.

Indexed as

Selection, GeneticAdaptation, PhysiologicalAllelesFlowersGene Expression Regulation, PlantGenes, PlantGenetics, PopulationHordeumINDEL MutationIsraelPolymorphism, Single Nucleotide

Identifiers

PMID31527784
PMCPMC6906298

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Registered trials

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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 OpenQuestion graph.