SNP Markers Identification by Genome Wide Association Study for Chemical Quality Traits of Coffee (Coffea Spp.) Germplasm

Overview

Journal Mol Biol Rep

Specialty Molecular Biology

Date 2022 Apr 27

PMID 35474051

Authors

Spinoso-Castillo Jose Luis

Perez-Rodriguez Paulino

Jerico Jabin Bello-Bello

Escamilla-Prado Esteban

Aguilar-Rincon Victor Heber

Corona-Torres Tarsicio

Garcia-de Los Santos Gabino

Morales-Ramos Victorino

Affiliations

Soon will be listed here.

Abstract

Background: Coffee quality is an important selection criterion for coffee breeding. Metabolite profiling and Genome-Wide Association Studies (GWAS) effectively dissect the genetic background of complex traits such as metabolites content (caffeine, trigonelline, and 5-caffeoylquinic acid (5-CQA)) in coffee that affect quality. Therefore, it is important to determine the metabolic profiles of Coffea spp. genotypes. This study aimed to identify Single Nucleotide Polymorphisms (SNPs) within Coffea spp. genotypes through GWAS and associate these significant SNPs to the metabolic profiles of the different genotypes.

Methods And Results: A total of 1,739 SNP markers were obtained from 80 genotypes using the DArTseq™ method. Caffeine, trigonelline, and 5-CQA content were determined in coffee leaves using Ultra-Performance Liquid Chromatography/tandem mass spectrometry (UPLC-MS/MS) analyses. The GWAS was carried out using the Genome Association and Prediction Integrated Tool (GAPIT) software and a compressed mixed linear model. Finally, a total of three significant SNP markers out of ten were identified. One SNP, located in the coffee chromosome (Chr) 8, was significantly associated with caffeine. The two remaining SNPs, located in Chr 4 and 5, were significantly associated with trigonelline and six SNPs markers were associated with 5-CQA in Chr 1, 5 and 10, but these six markers were not significant.

Conclusions: These significant SNP sequences were associated with protein ubiquitination, assimilation, and wall receptor kinases. Therefore, these SNPs might be useful hits in subsequent quality coffee breeding programs.

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References

Morales-Ramos V, Escamilla-Prado E, Ruiz-Carbajal R, Perez-Sato J, Velazquez-Morales J, Servin-Juarez R . On the soil-bean-cup relationships in Coffea arabica L. J Sci Food Agric. 2020; 100(15):5434-5441. DOI: 10.1002/jsfa.10594. View

SantAna G, Pereira L, Pot D, Ivamoto S, Domingues D, Ferreira R . Genome-wide association study reveals candidate genes influencing lipids and diterpenes contents in Coffea arabica L. Sci Rep. 2018; 8(1):465. PMC: 5764960. DOI: 10.1038/s41598-017-18800-1. View

Tran H, Ramaraj T, Furtado A, Lee L, Henry R . Use of a draft genome of coffee (Coffea arabica) to identify SNPs associated with caffeine content. Plant Biotechnol J. 2018; 16(10):1756-1766. PMC: 6131422. DOI: 10.1111/pbi.12912. View

Merot-Lanthoene V, Tournebize R, Darracq O, Rattina V, Lepelley M, Bellanger L . Development and evaluation of a genome-wide Coffee 8.5K SNP array and its application for high-density genetic mapping and for investigating the origin of Coffea arabica L. Plant Biotechnol J. 2018; 17(7):1418-1430. PMC: 6576098. DOI: 10.1111/pbi.13066. View

VanRaden P . Efficient methods to compute genomic predictions. J Dairy Sci. 2008; 91(11):4414-23. DOI: 10.3168/jds.2007-0980. View

Bo K, Wei S, Wang W, Miao H, Dong S, Zhang S . QTL mapping and genome-wide association study reveal two novel loci associated with green flesh color in cucumber. BMC Plant Biol. 2019; 19(1):243. PMC: 6556036. DOI: 10.1186/s12870-019-1835-6. View

Gao L, Turner M, Chao S, Kolmer J, Anderson J . Genome Wide Association Study of Seedling and Adult Plant Leaf Rust Resistance in Elite Spring Wheat Breeding Lines. PLoS One. 2016; 11(2):e0148671. PMC: 4744023. DOI: 10.1371/journal.pone.0148671. View

Vega F, Ziska L, Simpkins A, Infante F, Davis A, Rivera J . Early growth phase and caffeine content response to recent and projected increases in atmospheric carbon dioxide in coffee (Coffea arabica and C. canephora). Sci Rep. 2020; 10(1):5875. PMC: 7125137. DOI: 10.1038/s41598-020-62818-x. View

Hassani S, Talebi R, Pourdad S, Naji A, Fayaz F . In-depth genome diversity, population structure and linkage disequilibrium analysis of worldwide diverse safflower (Carthamus tinctorius L.) accessions using NGS data generated by DArTseq technology. Mol Biol Rep. 2020; 47(3):2123-2135. DOI: 10.1007/s11033-020-05312-x. View

10.

Mahboubi M, Mehrabi R, Naji A, Talebi R . Whole-genome diversity, population structure and linkage disequilibrium analysis of globally diverse wheat genotypes using genotyping-by-sequencing DArTseq platform. 3 Biotech. 2020; 10(2):48. PMC: 6960278. DOI: 10.1007/s13205-019-2014-z. View

11.

Nyine M, Uwimana B, Akech V, Brown A, Ortiz R, Dolezel J . Association genetics of bunch weight and its component traits in East African highland banana (Musa spp. AAA group). Theor Appl Genet. 2019; 132(12):3295-3308. PMC: 6820618. DOI: 10.1007/s00122-019-03425-x. View

12.

Bush W, Moore J . Chapter 11: Genome-wide association studies. PLoS Comput Biol. 2013; 8(12):e1002822. PMC: 3531285. DOI: 10.1371/journal.pcbi.1002822. View

13.

Mogga M, Sibiya J, Shimelis H, Lamo J, Yao N . Diversity analysis and genome-wide association studies of grain shape and eating quality traits in rice (Oryza sativa L.) using DArT markers. PLoS One. 2018; 13(6):e0198012. PMC: 5983461. DOI: 10.1371/journal.pone.0198012. View

14.

He Y, Wu D, Wei D, Fu Y, Cui Y, Dong H . GWAS, QTL mapping and gene expression analyses in Brassica napus reveal genetic control of branching morphogenesis. Sci Rep. 2017; 7(1):15971. PMC: 5698412. DOI: 10.1038/s41598-017-15976-4. View

15.

Wang J, Yao W, Wang L, Ma F, Tong W, Wang C . Overexpression of VpEIFP1, a novel F-box/Kelch-repeat protein from wild Chinese Vitis pseudoreticulata, confers higher tolerance to powdery mildew by inducing thioredoxin z proteolysis. Plant Sci. 2017; 263:142-155. DOI: 10.1016/j.plantsci.2017.07.004. View

16.

Zhang D, Song Y, Dai R, Lee T, Kim J . Aldoxime Metabolism Is Linked to Phenylpropanoid Production in . Front Plant Sci. 2020; 11:17. PMC: 7025560. DOI: 10.3389/fpls.2020.00017. View

17.

Ajeesh Krishna T, Maharajan T, Roch G, Ignacimuthu S, Ceasar S . Structure, Function, Regulation and Phylogenetic Relationship of ZIP Family Transporters of Plants. Front Plant Sci. 2020; 11:662. PMC: 7267038. DOI: 10.3389/fpls.2020.00662. View

18.

Sun X, Yu Q, Tang L, Ji W, Bai X, Cai H . GsSRK, a G-type lectin S-receptor-like serine/threonine protein kinase, is a positive regulator of plant tolerance to salt stress. J Plant Physiol. 2013; 170(5):505-15. DOI: 10.1016/j.jplph.2012.11.017. View

19.

Sabzehzari M, Zeinali M, Naghavi M . Alternative sources and metabolic engineering of Taxol: Advances and future perspectives. Biotechnol Adv. 2020; 43:107569. DOI: 10.1016/j.biotechadv.2020.107569. View

20.

Lallemand L, Zubieta C, Lee S, Wang Y, Acajjaoui S, Timmins J . A structural basis for the biosynthesis of the major chlorogenic acids found in coffee. Plant Physiol. 2012; 160(1):249-60. PMC: 3440203. DOI: 10.1104/pp.112.202051. View