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Genetic Diversity of Coffea arabica L.: A Genomic Approach

Authors: José Luis Spinoso-Castillo; Tarsicio Corona-Torres; Esteban Escamilla-Prado; Victorino Morales-Ramos; Víctor Heber Aguilar-Rincón; Gabino García-de los Santos;

Genetic Diversity of Coffea arabica L.: A Genomic Approach

Abstract

Coffea arabica L. produces a high-quality beverage, with pleasant aroma and flavor, but diseases, pests and abiotic stresses often affect its yield. Therefore, improving important agronomic traits of this commercial specie remains a target for most coffee improvement programs. With advances in genomic and sequencing technology, it is feasible to understand the coffee genome and the molecular inheritance underlying coffee traits, thereby helping improve the efficiency of breeding programs. Thanks to the rapid development of genomic resources and the publication of the C. canephora reference genome, third-generation markers based on single-nucleotide polymorphisms (SNPs) have gradually been identified and assayed in Coffea, particularly in C. arabica. However, high-throughput genotyping assays are still needed in order to rapidly characterize the coffee genetic diversity and to evaluate the introgression of different cultivars in a cost-effective way. The DArTseq™ platform, developed by Diversity Arrays Technology, is one of these approaches that has experienced an increasing interest worldwide since it is able to generate thousands of high quality SNPs in a timely and cost-effective manner. These validated SNP markers will be useful to molecular genetics and for innovative approaches in coffee breeding.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
hybrid