Genome-level diversification of eight ancient tea populations in the Guizhou and Yunnan regions identifies candidate genes for core agronomic traits

Abstract

The ancient tea plant, as a precious natural resource and source of tea plant genetic diversity, is of great value for studying the evolutionary mechanism, diversification, and domestication of plants. The overall genetic diversity among ancient tea plants and the genetic changes that occurred during natural selection remain poorly understood. Here, we report the genome resequencing of eight different groups consisting of 120 ancient tea plants: six groups from Guizhou Province and two groups from Yunnan Province. Based on the 8,082,370 identified high-quality SNPs, we constructed phylogenetic relationships, assessed population structure, and performed genome-wide association studies (GWAS). Our phylogenetic analysis showed that the 120 ancient tea plants were mainly clustered into three groups and five single branches, which is consistent with the results of principal component analysis (PCA). Ancient tea plants were further divided into seven subpopulations based on genetic structure analysis. Moreover, it was found that the variation in ancient tea plants was not reduced by pressure from the external natural environment or artificial breeding (nonsynonymous/synonymous = 1.05). By integrating GWAS, selection signals, and gene function prediction, four candidate genes were significantly associated with three leaf traits, and two candidate genes were significantly associated with plant type. These candidate genes can be used for further functional characterization and genetic improvement of tea plants.

References

[1] Willson, K. C. & Clifford, M. N. Tea: cultivation to consumption. Ecol. Freshw. Fish. 5, 175-182 (1992).

[2] Mondal, T. K., Bhattacharya, A., Laxmikumaran, M. & Ahuja, P. S. Recent advances of tea (Camellia sinensis) biotechnology. Plant Cell Tiss. Org. 76, 195-254 (2004).

[3] Yamamoto, T., Juneja, L. R., Chu, S. & Kim, M. Chemistry and Applications of Green Tea (CRC Press, 1997).

[4] Cabrera, C., Artacho, R. & Giménez, R. Beneficial effects of green tea-a review. J. Am. Coll. Nutr. 25, 79-99 (2006).

[5] Rogers, P. J., Smith, J. E., Heatherley, S. V. & Pleydell-Pearce, C. W. Time for tea: mood, blood pressure and cognitive performance effects of caffeine and theanine administered alone and together. Psychopharmacology 195, 569-577 (2008).

[6] Chacko, S. M., Thambi, P. T., Kuttan, R. & Nishigaki, I. Beneficial effects of green tea: a literature review. Chin. Med. 5, 13 (2010).

[7] Hayat, K., Iqbal, H., Malik, U., Bilal, U. & Mushtaq, S. Tea and its consumption: benefits and risks. Crit. Rev. Food Sci. 55, 939-954 (2013).

[8] Xia, E. H. et al. The tea tree genome provides insights into tea flavor and independent evolution of caffeine biosynthesis. Mol. Plant. 10, 866-877 (2017).

[9] Xia, E. H. et al. Tea plant information archive: a comprehensive genomics and bioinformatics platform for tea plant. Plant Biotech. J. 17, 1938-1953 (2019).

[10] Hufford, M. B. et al. Comparative population genomics of maize domestication and improvement. Nat. Genet. 44, 808-811 (2012).

[11] Jiao, Y. P. et al. Genome-wide genetic changes during modern breeding of maize. Nat. Genet. 44, 812-815 (2012).

[12] Qi, J. J. et al. A genomic variation map provides insights into the genetic basis of cucumber domestication and diversity. Nat. Genet. 45, 1510-1515 (2013).

[13] Levy, D. et al. Genome-wide association study of blood pressure and hypertension. Nat. Genet. 41, 677-687 (2009).

[14] Su, J. et al. Genome-wide association study identified genetic variations and candidate genes for plant architecture component traits in Chinese upland cotton. Theor. Appl. Genet. 131, 1299-1314 (2018).

[15] Wang, M. et al. Genome-wide association study (GWAS) of resistance to head smut in maize. Plant Sci. 196, 125-131 (2012).

[16] Zhang, J. P. et al. Genome-wide association study for flowering time, maturity dates and plant height in early maturing soybean (Glycine max) germplasm. BMC Genomics 16, 217-228 (2015).

[17] Wu, J. et al. Genome-wide association study (GWAS) of mesocotyl elongation based on re-sequencing approach in rice. BMC Plant Biol. 15, 1-10 (2015).

[18] Wei, C. L. et al. Draft genome sequence of Camellia sinensis var. sinensis provides insights into the evolution of the tea genome and tea quality. Proc. Natl Acad. Sci. USA 115, 4151-4158 (2018).

[19] Chen, L., Yang, Y. J., Yu, F. L., Yao, M. Z. & Wang, X. C. Descriptors and data standard for tea (Camellia spp.). China Agriculture Press 1, 3-6 (2005).

[20] Wang, W. S. et al. Genomic variation in 3,010 diverse accessions of Asian cultivated rice. Nature 557, 43-49 (2018).

[21] Wu, J. et al. Diversification and independent domestication of Asian and European pears. Genome Biol. 19, 1-16 (2018).

[22] Duan, N. B. et al. Genome re-sequencing reveals the history of apple and supports a two-stage model for fruit enlargement. Nat. Commun. 8, 1-11 (2017).

[23] Lam, H. M. et al. Resequencing of 31 wild and cultivated soybean genomes identifies patterns of genetic diversity and selection. Nat. Genet. 42, 1053-1062 (2010).

[24] 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, 415-430 (2014).

[25] Zhang, X. Q. et al. Diversity analysis of agronomic and quality traits of tea plant resources in Guiding Bird King. Mol. Plant Breed. 13, 415-423 (2015).

[26] Wang, W. et al. Cassava genome from a wild ancestor to cultivated varieties. Nat. Commun. 5, 1-9 (2014).

[27] Hazzouri, K. M. et al. Whole genome re-sequencing of date palms yields insights into diversification of a fruit tree crop. Nat. Commun. 6, 1-11 (2015).

[28] Ge, J. X. in China’s Belt and Road Initiatives (ed. Liu, W.) 10-14 (Springer, 2018).

[29] Xia, E. H. et al. The reference genome of tea plant and resequencing of 81 diverse accessions provide insights into genome evolution and adaptation of tea plants. Mol. Plant. 13, 1013-1026 (2020).

[30] Xu, X. et al. Resequencing 50 accessions of cultivated and wildrice yields markers for identifying agronomically important genes. Nat. Biotechnol. 30, 105-111 (2011).

[31] Krisztina, N. et al. The balance between the MIR164A and CUC2 genes controls leaf margin serration in Arabidopsis. Plant Cell 18, 2929-2945 (2006).

[32] Zhang, X. Q., Zhou, F. Y., Yang, C., Zhang, Z. Q. & Hu, J. Q. Diversity of tea germplasm resource (Camellia sinensis ‘Guiding-niaowangzhong’) revealed based on agronomic and quality traits. Mol. Plant Breed. 13, 415-423 (2015).

[33] Yano, K. et al. Genome-wide association study using whole-genome sequencing rapidly identifies new genes influencing agronomic traits in rice. Nat. Gene. 48, 927-934 (2016).

[34] Woo, H. R. et al. ORE9, an F-Box protein that regulates leaf senescence in Arabidopsis. Plant Cell 13, 1779-1790 (2001).

[35] Joke, B. et al. F-Box protein FBX92 affects leaf size in Arabidopsis thaliana. Plant Cell Physiol. 5, 962-975 (2017).

[36] Lakhssassi, N. et al. Stearoyl-acyl carrier protein desaturase mutations uncover an impact of stearic acid in leaf and nodule structure. Plant Physiol. 174, 1531-1543 (2017).

[37] Gou, L. et al. Multigene synergism increases the isoflavone and proanthocyanidin contents of Medicago truncatula. Plant Biotech. J. 14, 915-925 (2016).

[38] Gagne, J. M. et al. Arabidopsis EIN3-binding F-box 1 and 2 form ubiquitin-protein ligases that repress ethylene action and promote growth by directing EIN3 degradation. Proc. Natl Acad. Sci. USA 101, 6803-6808 (2013).

[39] Takato, S. et al. Auxin signaling through SCFTIR1/AFBs mediates feedback regulation of IAA biosynthesis. Biosci. Biotech. Biochem. 81, 1-7 (2017).

[40] Murray, M. & Thompson, W. F. Rapid isolation of high molecular weight plant DNA. Nucleic Acids Res. 8, 4321-4326 (1980).

[41] Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754-1760 (2009).

[42] Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078-2079 (2009).

[43] Kim, J. E., Oh, S. K., Lee, J. H. & Jo, S. H. Genome-wide SNP calling using next generation sequencing data in tomato. Mol. Cells 37, 36-42 (2014).

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

[45] Megan, J. et al. Supercomputing for the parallelization of whole genome analysis. Bioinformatics 30, 1508-1513 (2014).

[46] Josh, C. et al. Single nucleotide polymorphism identification in polyploids: a review, example, and recommendations. Mol. Plant 8, 831-846 (2015).

[47] McKenna, A. et al. The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome 20, 1297-1303 (2010).

[48] Wang, K., Li, M. & Hakonarson, H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 38, 164 (2010).

[49] Sudhir, K., Glen, S. & Koichiro, T. MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol. Biol. Evol. 7, 1870-1874 (2016).

[50] Yang, J., Lee, S. H., Goddard, M. E. & Visscher, P. M. GCTA: a tool for genome-wide complex trait analysis. Am. J. Hum. Genet. 88, 76-82 (2011).

[51] Stephanie, M. G. et al. Genetic association testing using the GENESIS R/Bioconductor package. Bioinformatics 35, 5346-5348 (2019).

[52] Zhang, C., Dong, S. Shan, Xu, J. Y., He, W. M. & Yang, T. L. PopLDdecay: a fast and effective tool for linkage disequilibrium decay analysis based on variant call format files. Bioinformatics 35, 1786-1788 (2018).

[53] Browning, B. L. & Browning, S. R. Genotype imputation with millions of reference samples. Am. J. Hum. Genet. 98, 116-126 (2016).

[54] Lipka, A. E. et al. GAPIT: genome association and prediction integrated tool. Bioinformatics 15, 2397-2399 (2012).

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

[56] Durvasula, A. et al. ANGSD-wrapper: utilities for analyzing next generation sequencing data. Mol. Ecol. Resour. 16, 1449-1454 (2016).

[57] Wang, X. J. et al. Characterization and expression analysis of ERF genes in Fragaria vesca suggest different divergences of tandem ERF duplicates. Front. Genet. 10, 1-13 (2019).