Universal Journal of Agricultural Research Vol. 11(2), pp. 275 - 299
DOI: 10.13189/ujar.2023.110206
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Genetic Diversity and Population Structure Analysis of Arabica Coffee (Coffea arabica L.) Germplasm Collections in Burundi Based on DArTseq

Jean Marie Vianney Niyoyankunze ^1,2,*, Aggrey Bernard Nyende ¹, Martina Kyallo ³, Anaclet Nibasumba ⁴, Gilbert Nduwayo ², Oluwaseyi Shorinola ^3
1 Institute for Biotechnology Research, Jomo Kenyatta University of Agriculture and Technology, P.O. Box 62000,00200, Nairobi, Kenya
² Institut des Sciences Agronomiques du Burundi (ISABU), P.O. Box 795, Bujumbura, Burundi
³ International Livestock Research Institute, P.O. Box 30700, 00100, Nairobi, Kenya
⁴ Institut Supérieur de Formation Agricole (ISFA), Université du Burundi, P.O. Box 1550, Bujumbura, Burundi

ABSTRACT

Coffee is the most important export commodity that contributes significantly to the national economy and supports the livelihood of millions of people in Burundi. The lack of information on the diversity of the existing pool of advanced breeding materials and introduced accessions of Arabica coffee in Burundi has been a key limitation for coffee improvement and sustainable conservation. To address this limitation, DArTseq Genotyping by sequencing (GBS) was used to document the genetic diversity of the Arabica coffee collection in Burundi. We analyzed 255 Coffea arabica germplasm composed of hybrid, commercial varieties, and landraces. A total of 4036 SNPs were identified and 3488 of those were found to be anchored to the C. arabica chromosomes. After quality filtering, 3070 highly informative SNPs were used for Linkage Disequilibrium (LD) pruning leading to 1874 LD-pruned markers employed for further genetic diversity analyses. A complementary approach involving distance-based (hierarchical clustering and Principal Coordinate Analysis) and model-based (ADMIXTURE and Discriminant Analysis of Principal Component) methods congruently stratified these 255 Coffea arabica germplasm into four genetic clusters. The group membership of the clusters identified throughout the two methods was comparable. Admixture between coffee accessions was evaluated using ADMIXTURE, and the best-fit number of populations (clusters) based on cross-validation estimates was K = 4. Based on genetic diversity parameters including Polymorphism Information Content, heterozygosity, and overall minor allele frequency, a relatively low genetic diversity was observed between and within the genetics groups. The analysis of the coffee genetic variation through Principal Coordinate analysis indicated a low variation of 22.1% among the existing coffee genotypes. This study documents genetic diversity presented of the C. arabica genetic resources in Burundi. These findings can be used in selecting and introducing parents for breeding in this low-diversity collection to set up effective strategies for Arabica coffee improvement and conservation in Burundi.

KEYWORDS
Coffea Arabica, Genetic Diversity, Coffee Breeding, Dartseq Genotyping, Allotetraploid

Cite This Paper in IEEE or APA Citation Styles
(a). IEEE Format:
[1] Jean Marie Vianney Niyoyankunze , Aggrey Bernard Nyende , Martina Kyallo , Anaclet Nibasumba , Gilbert Nduwayo , Oluwaseyi Shorinola , "Genetic Diversity and Population Structure Analysis of Arabica Coffee (Coffea arabica L.) Germplasm Collections in Burundi Based on DArTseq," Universal Journal of Agricultural Research, Vol. 11, No. 2, pp. 275 - 299, 2023. DOI: 10.13189/ujar.2023.110206.

(b). APA Format:
Jean Marie Vianney Niyoyankunze , Aggrey Bernard Nyende , Martina Kyallo , Anaclet Nibasumba , Gilbert Nduwayo , Oluwaseyi Shorinola (2023). Genetic Diversity and Population Structure Analysis of Arabica Coffee (Coffea arabica L.) Germplasm Collections in Burundi Based on DArTseq. Universal Journal of Agricultural Research, 11(2), 275 - 299. DOI: 10.13189/ujar.2023.110206.