Detection of the local adaptive and genome-wide associated loci in southeast Nigerian taro (Colocasia esculenta (L.) Schott) populations

Tilahun Wondimu Fufa; Temesgen Matiwos Menamo; Wosene Gebreselassie Abtew; Charles Okechukwu Amadi; Happiness Ogba Oselebe

doi:10.1186/s12864-023-09134-6

Detection of the local adaptive and genome-wide associated loci in southeast Nigerian taro (Colocasia esculenta (L.) Schott) populations

BMC Genomics. 2023 Jan 24;24(1):39. doi: 10.1186/s12864-023-09134-6.

Authors

Tilahun Wondimu Fufa^{1

2}, Temesgen Matiwos Menamo³, Wosene Gebreselassie Abtew⁴, Charles Okechukwu Amadi⁵, Happiness Ogba Oselebe²

Affiliations

¹ Department of Horticulture, Oromia Agricultural Research Institute, Addis Ababa, Ethiopia.
² Department of Crop Production and Landscape Management, Ebonyi State University, Abakaliki, Nigeria.
³ Department of Plant Science and Horticulture, Jimma University, Jimma, Ethiopia. temesgen2008@hotmail.com.
⁴ Department of Plant Science and Horticulture, Jimma University, Jimma, Ethiopia.
⁵ Cocoyam Improvement Programme, National Root Crops Research Institute, Umudike, Nigeria.

Abstract

Background: Taro has a long history of being consumed and remains orphan and on the hand Nigeria farmers. The role of farmer-driven artificial selection is not negligible to fit landraces to a particular ecological condition. Limited study has been conducted on genome-wide association and no study has been conducted on genome-environment association for clinal adaptation for taro. Therefore, the objective of this study was to detect loci that are associated with environmental variables and phenotype traits and forward input to breeders. The study used 92 geographical referred taro landraces collected from Southeast (SE) Nigeria.

Results: The result indicates that SE Nigerian taro has untapped phenotype and genetic variability with low admixture. Redundancy analysis indicated that collinear explained SNP variation more than single climatic variable. Overall, the results indicated that no single method exclusively was able to capture population confounding effects better than the others for all six traits. Nevertheless, based on overall model performance, Blink seemed to provide slight advantage over other models and was selected for all subsequent assessment of genome-environment association (GEA) and genome-wide association study (GWAS) models. Genome scan and GEA identified local adapted loci and co-located genes. A total of nine SNP markers associated with environmental variables. Some of the SNP markers (such as S_101024366) co-located with genes which previously reported for climatic adaptation such as astringency, diaminopimelate decarboxylase and MYB transcription factor. Genome-wide association also identified 45, 40 and 34 significant SNP markers associated with studied traits in combined, year 1 and year 2 data sets, respectively. Out of these, five SNP markers (S1_18891752 S3_100795476, S1_100584471 S1_100896936 and S2_10058799) were consistent in two different data sets.

Conclusions: The findings from this study improve our understanding of the genetic control of adaptive and phenotypic traits in Nigerian taro. However, the study suggests further study on identification of local adaptive loci and GWAS through collection of more landraces throughout the country, and across different agro-ecologies.

Keywords: Genome-environment association; Genome-traits association; Nigerian taro.

MeSH terms

Colocasia* / genetics
Genome-Wide Association Study
Nigeria
Phenotype