Whole genome re-sequencing of sweet cherry (Prunus avium L.) yields insights into genomic diversity of a fruit species

Abstract

Sweet cherries, Prunus avium L. (Rosaceae), are gaining importance due to their perenniallity and nutritional attributes beneficial for human health. Interestingly, sweet cherry cultivars exhibit a wide range of phenotypic diversity in important agronomic traits, such as flowering time and defense reactions against pathogens. In this study, whole-genome resequencing (WGRS) was employed to characterize genetic variation, population structure and allelic variants in a panel of 20 sweet cherry and one wild cherry genotypes, embodying the majority of cultivated Greek germplasm and a representative of a local wild cherry elite phenotype. The 21 genotypes were sequenced in an average depth of coverage of 33.91×. and effective mapping depth, to the genomic reference sequence of ‘Satonishiki’ cultivar, between 22.21× to 36.62×. Discriminant analysis of principal components (DAPC) with SNPs revealed two clusters of genotypes. There was a rapid linkage disequilibrium decay, as the majority of SNP pairs with r² in near complete disequilibrium (>0.8) were found at physical distances less than 10 kb. Functional analysis of the variants showed that the genomic ratio of non-synonymous/synonymous (dN/dS) changes was 1.78. The higher dN frequency in the Greek cohort of sweet cherry could be the result of artificial selection pressure imposed by breeding, in combination with the vegetative propagation of domesticated cultivars through grafting. The majority of SNPs with high impact (e.g., stop codon gaining, frameshift), were identified in genes involved in flowering time, dormancy and defense reactions against pathogens, providing promising resources for future breeding programs. Our study has established the foundation for further large scale characterization of sweet cherry germplasm, enabling breeders to incorporate diverse germplasm and allelic variants to fine tune flowering and maturity time and disease resistance in sweet cherry cultivars.

References

[1] McCune, L. M., Kubota, C., Stendell-Hollis, N. R. & Thomson, C. A. Cherries and health: a review. Crit. Rev. Food Sci. Nutr. 51, 1-12 (2010).

[2] Ganopoulos, I. V., Kazantzis, K., Chatzicharisis, I., Karayiannis, I. & Tsaftaris, A. S. Genetic diversity, structure and fruit trait associations in Greek sweet cherry cultivars using microsatellite based (SSR/ISSR) and morpho-physiological markers. Euphytica 181, 237-251 (2011).

[3] Zambounis, A. et al. Evidence of extensive positive selection acting on cherry (‘Prunus avium’L.) resistance gene analogs (RGAs). Aust. J. Crop Sci. 10, 1324 (2016).

[4] Campoy, J. A. et al. Genetic diversity, linkage disequilibrium, population structure and construction of a core collection of Prunus avium L. landraces and bred cultivars. BMC Plant Biol. 16, 49 (2016).

[5] Ganopoulos, I. et al. A mini review on morphological and genetic diversity of sweet (Prunus avium L.) and sour cherry (Prunus cerasus L.) cultivars. (Nova Science Publishers, 2016).

[6] Peace, C. et al. Development and evaluation of a genome-wide 6K SNP array for diploid sweet cherry and tetraploid sour cherry. PLoS ONE 7, e48305 (2012).

[7] Rawat, N. et al. Genome resequencing and transcriptome profiling reveal structural diversity and expression patterns of constitutive disease resistance genes in Huanglongbing-tolerant Poncirus trifoliata and its hybrids. Hortic. Res. 4, 17064 (2017).

[8] Fernandez i Marti, A., Saski, C. A., Manganaris, G. A., Gasic, K. & Crisosto, C. H. Genomic sequencing of Japanese plum (Prunus salicina Lindl.) mutants provides a new model for Rosaceae fruit ripening studies. Front. Plant Sci. 9, 21 (2018).

[9] Zhang, J. et al. Genome-Wide Discovery of DNA Polymorphisms in Mei (Prunus mume Sieb. et Zucc.), an ornamental woody plant, with contrasting tree architecture and their functional relevance for weeping trait. Plant Mol. Biol. Report. 35, 37-46 (2017).

[10] Cao, K. et al. Comparative population genomics reveals the domestication history of the peach, Prunus persica, and human influences on perennial fruit crops. Genome Biol. 15, 415 (2014).

[11] Xu, X. et al. Resequencing 50 accessions of cultivated and wild rice yields markers for identifying agronomically important genes. Nat. Biotechnol. 30, 105 (2012).

[12] McClure, K. A., Sawler, J., Gardner, K. M., Money, D. & Myles, S. Genomics: a potential panacea for the perennial problem. Am. J. Bot. 101, 1780-1790 (2014).

[13] Shirasawa, K. et al. The genome sequence of sweet cherry (Prunus avium) for use in genomics-assisted breeding. DNA Res. 24, 499-508 (2017).

[14] Yan, M., Zhang, X., Zhao, X. & Yuan, Z. The complete mitochondrial genome sequence of sweet cherry (Prunus avium cv.‘summit’). Mitochondrial DNA 4, 1996-1997 (2019).

[15] Chen, T. et al. Characterization of complete chloroplast genome and phylo-genetic analysis of sweet cherry Cerasus avium (L.) Moench (Prunoideae, Rosaceae). Mitochondrial DNA 3, 1274-1275 (2018).

[16] Ono, K., Akagi, T., Morimoto, T., Wünsch, A. & Tao, R. Genome re-sequencing of diverse sweet cherry (Prunus avium) individuals reveals a modifier gene mutation conferring pollen-part self-compatibility. Plant Cell Physiol. 59, 1265-1275 (2018).

[17] Ganopoulos, I. et al. Towards sweet cherry (Prunus avium L.) breeding: phe-notyping evaluation of newly developed hybrids. Euphytica 214, 99 (2018).

[18] Li, H. & Durbin, R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics 26, 589-595 (2010).

[19] DePristo, M. A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43, 491 (2011).

[20] Cingolani, P. et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly 6, 80-92 (2012).

[21] Pembleton, L. W., Cogan, N. O. I. & Forster, J. W. St AMPP: an R package for calculation of genetic differentiation and structure of mixed‐ploidy level populations. Mol. Ecol. Resour. 13, 946-952 (2013).

[22] Paradis, E., Claude, J. & Strimmer, K. APE: analyses of phylogenetics and evo-lution in R language. Bioinformatics 20, 289-290 (2004).

[23] Jombart, T., Devillard, S. & Balloux, F. Discriminant analysis of principal com-ponents: a new method for the analysis of genetically structured populations. BMC Genet. 11, 94 (2010).

[24] Murtagh, F. & Legendre, P. Ward’s hierarchical agglomerative clustering method: which algorithms implement Ward’s criterion? J. Classif. 31, 274-295 (2014).

[25] Zheng, L.-Y. et al. Genome-wide patterns of genetic variation in sweet and grain sorghum (Sorghum bicolor). Genome Biol. 12, R114 (2011).

[26] Rausch, T. et al. DELLY: structural variant discovery by integrated paired-end and split-read analysis. Bioinformatics 28, i333-i339 (2012).

[27] Layer, R. M., Chiang, C., Quinlan, A. R. & Hall, I. M. LUMPY: a probabilistic framework for structural variant discovery. Genome Biol. 15, R84 (2014).

[28] Danecek, P. et al. The variant call format and VCFtools. Bioinformatics 27, 2156-2158 (2011).

[29] Yao, W. intansv: Integrative analysis of structural variations. R package version 1.9 2 (2015).

[30] Sánchez-Pérez, R., Del Cueto, J., Dicenta, F. & Martínez-Gómez, P. Recent advancements to study flowering time in almond and other Prunus species. Front. Plant Sci. 5, 334 (2014).

[31] Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841-842 (2010).

[32] Liang, Z. et al. Whole-genome resequencing of 472 Vitis accessions for grapevine diversity and demographic history analyses. Nat. Commun. 10, 1190 (2019).

[33] Hazzouri, K. M. et al. Whole genome re-sequencing of date palms yields insights into diversification of a fruit tree crop. Nat. Commun. 6, 8824 (2015).

[34] Tomato Genome Sequencing, C. et al. Exploring genetic variation in the tomato (Solanum section Lycopersicon) clade by whole‐genome sequencing. Plant J. 80, 136-148 (2014).

[35] Varshney, R. K. et al. Whole-genome resequencing of 292 pigeonpea acces-sions identifies genomic regions associated with domestication and agro-nomic traits. Nat. Genet. 49, 1082 (2017).

[36] Li, Y. et al. Genomic analyses of an extensive collection of wild and cultivated accessions provide new insights into peach breeding history. Genome Biol. 20, 36 (2019).

[37] Zhang, Q. et al. The genetic architecture of floral traits in the woody plant Prunus mume. Nat. Commun. 9, 1702 (2018).

[38] Varshney, R. K. et al. Resequencing of 429 chickpea accessions from 45 countries provides insights into genome diversity, domestication and agro-nomic traits. Nat. Genet. 51, 857 (2019).

[39] Aranzana, M. J. et al. Prunus genetics and applications after de novo genome sequencing: achievements and prospects. Hortic. Res. 6, 58 (2019).

[40] Mariette, S. et al. Genome‐wide association links candidate genes to resistance to Plum Pox Virus in apricot (Prunus armeniaca). New Phytol. 209, 773-784 (2016).

[41] Micheletti, D. et al. Whole-genome analysis of diversity and SNP-major gene association in peach germplasm. PLoS ONE 10, e0136803 (2015).

[42] Zhou, Y., Massonnet, M., Sanjak, J. S., Cantu, D. & Gaut, B. S. Evolutionary genomics of grape (Vitis vinifera ssp. vinifera) domestication. Proc. Natl Acad. Sci. USA 114, 11715-11720 (2017).

[43] Duan, N. et al. Genome re-sequencing reveals the history of apple and sup-ports a two-stage model for fruit enlargement. Nat. Commun. 8, 249 (2017).

[44] Putterill, J., Laurie, R. & Macknight, R . It’s time to flower: the genetic control of flowering time. Bioessays 26, 363-373 (2004).

[45] Ehrenreich, I. M. et al. Candidate gene association mapping of Arabidopsis flowering time. Genetics 183, 325-335 (2009).

[46] Johanson, U. et al. Molecular analysis of FRIGIDA, a major determinant of natural variation in Arabidopsis flowering time. Science 290, 344-347 (2000).

[47] Jung, C. & Müller, A. E. Flowering time control and applications in plant breeding. Trends Plant Sci. 14, 563-573 (2009).

[48] Trainin, T., Bar-Ya’akov, I. & Holland, D. ParSOC1, a MADS-box gene closely related to Arabidopsis AGL20/SOC1, is expressed in apricot leaves in a diurnal manner and is linked with chilling requirements for dormancy break. Tree Genet. Genomes 9, 753-766 (2013).

[49] Yoshida, N. et al. EMBRYONIC FLOWER2, a novel polycomb group protein homolog, mediates shoot development and flowering in Arabidopsis. Plant Cell 13, 2471-2481 (2001).

[50] Rothkegel, K. et al. DNA methylation and small interference RNAs participate in the regulation of MADS-box genes involved in dormancy in sweet cherry (Prunus avium L.). Tree Physiol. 37, 1739-1751 (2017).

[51] Larkan, N. J. et al. Multi-environment QTL studies suggest a role for cysteine-rich protein kinase genes in quantitative resistance to blackleg disease in Brassica napus. BMC Plant Biol. 16, 183 (2016).

[52] Tornero, P., Chao, R. A., Luthin, W. N., Goff, S. A. & Dangl, J. L. Large-scale structure-function analysis of the Arabidopsis RPM1 disease resistance protein. Plant Cell 14, 435-450 (2002).

[53] El-Kereamy, A. et al. Prunus domestica pathogenesis-related protein-5 activates the defense response pathway and enhances the resistance to fungal infec-tion. PLoS ONE 6, e17973 (2011).

[54] Li, Z. et al. Overexpression of Arabidopsis nucleotide-binding and leucine-rich repeat genes RPS2 and RPM1 (D505V) confers broad-spectrum disease resistance in rice. Front. Plant Sci. 10, 417 (2019).

[55] Wang, R. et al. Immunity to rice blast disease by suppression of effector-triggered necrosis. Curr. Biol. 26, 2399-2411 (2016).