Evidence map›Paper›PMID 38983700›Full record

ArticleEcology and evolution2024

Landscape genomics reveals genetic signals of environmental adaptation of African wild eggplants.

Emmanuel O Omondi, Chen-Yu Lin, Shu-Mei Huang, Cheng-An Liao, Ya-Ping Lin, Ricardo Oliva, Maarten van Zonneveld

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Article in Ecology and evolution, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Emmanuel O OmondiGenetic Resources and Seed Unit World Vegetable Center Tainan Taiwan.ORCID https://orcid.org/0000-0001-5212-7685
Chen-Yu LinBiotechnology, World Vegetable Center Tainan Taiwan.
Shu-Mei HuangBiotechnology, World Vegetable Center Tainan Taiwan.
Cheng-An LiaoDepartment of Horticulture National Taiwan University Taipei Taiwan.
Ya-Ping LinBiotechnology, World Vegetable Center Tainan Taiwan.
Ricardo OlivaPlant Pathology World Vegetable Center Tainan Taiwan.
Maarten van ZonneveldGenetic Resources and Seed Unit World Vegetable Center Tainan Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Crop wild relatives (CWR) provide a valuable resource for improving crops. They possess desirable traits that confer resilience to various environmental stresses. To fully utilize crop wild relatives in breeding and conservation programs, it is important to understand the genetic basis of their adaptation. Landscape genomics associates environments with genomic variation and allows for examining the genetic basis of adaptation. Our study examined the differences in allele frequency of 15,416 single nucleotide polymorphisms (SNPs) generated through genotyping by sequencing approach among 153 accessions of 15 wild eggplant relatives and two cultivated species from Africa, the principal hotspot of these wild relatives. We also explored the correlation between these variations and the bioclimatic and soil conditions at their collection sites, providing a comprehensive understanding of the genetic signals of environmental adaptation in African wild eggplant. Redundancy analysis (RDA) results showed that the environmental variation explained 6% while the geographical distances among the collection sites explained 15% of the genomic variation in the eggplant wild relative populations when controlling for population structure. Our findings indicate that even though environmental factors are not the main driver of selection in eggplant wild relatives, it is influential in shaping the genomic variation over time. The selected environmental variables and candidate SNPs effectively revealed grouping patterns according to the environmental characteristics of sampling sites. Using four genotype-environment association methods, we detected 396 candidate SNPs (2.5% of the initial SNPs) associated with eight environmental factors. Some of these SNPs signal genes involved in pathways that help adapt to environmental stresses such as drought, heat, cold, salinity, pests, and diseases. These candidate SNPs will be useful for marker-assisted improvement and characterizing the germplasm of this crop for developing climate-resilient eggplant varieties. The study provides a model for applying landscape genomics to other crops' wild relatives.

Indexed as

climate‐resilientcrop wild relativesenvironmental stressgenotype–environment associationmarker‐assisted improvement

Identifiers

PMID38983700
PMCPMC11232056

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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.