Advertisement

Tree Genetics & Genomes

, 14:24 | Cite as

Genome-wide association mapping of fruit-quality traits using genotyping-by-sequencing approach in citrus landraces, modern cultivars, and breeding lines in Japan

  • A. Imai
  • K. Nonaka
  • T. Kuniga
  • T. Yoshioka
  • T. Hayashi
Original Article
Part of the following topical collections:
  1. Complex Traits

Abstract

Association mapping is an attractive method to identify QTLs in perennial horticultural crops such as citrus, as it does not need a designed cross between parental genotypes and can save time and labor to construct a segregating population. It usually requires more genetic markers than linkage-based QTL mapping owing to a lower degree of linkage disequilibrium (LD). However, recent advances in next-generation sequencing offer high-throughput, cost-effective methods, including genotyping-by-sequencing (GBS), for genotyping massive amounts of single nucleotide polymorphisms (SNPs). In this study, we performed a genome-wide association study (GWAS) of fruit-quality traits in citrus using SNPs obtained by GBS. We evaluated 110 citrus accessions, including landraces, modern cultivars, and breeding lines, for eight fruit-quality traits (fruit weight, fruit skin color, fruit surface texture, peelability, pulp firmness, segment firmness, sugar content, and acid content) during 2005 to 2012 (except 2007). GBS found 2309 SNPs, which we anchored to the clementine reference genome. We evaluated LD in the 110 accessions and confirmed that GBS gave enough SNPs to conduct GWAS. We identified seven QTLs, including four novel ones, comprising four significant QTLs for fruit weight and one QTL each for fruit skin color, pulp firmness, and segment firmness. These QTLs offer promise for use in citrus crossbreeding.

Keywords

Citrus breeding Fruit quality Single nucleotide polymorphism (SNP) Marker-assisted selection (MAS) 

Notes

Acknowledgements

We would like to thank Y. Yamamura, H. Hira, and other staff members of agricultural field in Kuchinotsu Citrus Research Station, NARO for careful management of plant materials used in this study.

Data Archiving Statement

All relevant data are presented in the main paper and in the Supplementary Materials.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

11295_2018_1238_MOESM1_ESM.pptx (513 kb)
Supplementary Fig. S1 Manhattan plot (left) and quantile–quantile plot (right) for (a) fruit skin color, (b) fruit surface texture, (c) peelability, (d) pulp firmness, (e) segment firmness, (f) sugar content, and (g) acid content. The y-axes of Manhattan plots show the –log10 (P-values) of SNP association. The horizontal lines show the threshold value of significant association. The threshold value was calculated by the Wald test with Bonferroni correction based on the tested number of SNP markers (P < 0.05/2309). (PPTX 512 kb)
11295_2018_1238_MOESM2_ESM.pptx (303 kb)
Supplementary Fig. S2 Distribution of fruit weight according to genotypes of significant SNPs. Box edges represent the upper and lower quantiles, with the median value shown as a bold line in the middle of the box. (a) ccsc2_11899695, (b) ccsc3_48681070, and (c) ccsc7_3228616. (PPTX 302 kb)
11295_2018_1238_MOESM3_ESM.pptx (150 kb)
Supplementary Fig. S3 Stacked bar graph of fruit skin color (a), pulp firmness (b), and segment firmness (c) according to genotypes of significant SNPs. The y-axes show the number of observations for each SNP genotype: (a) ccsc3_1745277, (b) ccsc3_4027526, and (c) ccsc7_2890075. (PPTX 149 kb)
11295_2018_1238_MOESM4_ESM.pptx (276 kb)
Supplementary Fig. S4 Gel images (left) and electropherogram traces (right) of GBS libraries made by digesting mixed genomic DNA of satsuma mandarin and sweet orange with methylation-sensitive restriction enzymes (a) ApeKI, (b) EcoT22I, and (c) PstI. Discrete peaks or bands (15 bp and 1500 bp) indicate the presence of repetitive DNAs. Most fragments in all three GBS libraries were <500 bp, and were thus appropriate for Illumina short-read sequencing. ApeKI (essentially a 4-base cutter) produced a larger fragment pool than did EcoT22I and PstI (6-base cutters). Therefore, an ApeKI GBS library could produce more SNPs than the other two restriction enzymes. In contrast, EcoT22I and PstI GBS libraries could increase sequence coverage per locus relative to an ApeKI GBS library. (PPTX 275 kb)
11295_2018_1238_MOESM5_ESM.xlsx (114 kb)
Supplementary Table S1 (XLSX 113 kb)

References

  1. Abecasis GR, Cherny SS, Cookson WO, Cardon LR (2002) Merlin–rapid analysis of dense genetic maps using sparse gene flow trees. Nat Genet 30:97–101CrossRefPubMedGoogle Scholar
  2. Baird NA, Etter PD, Atwood TS, Currey MC, Shiver AL, Lewis ZA, Selker EU, Cresko WA, Johnson EA (2008) Rapid SNP discovery and genetic mapping using sequenced RAD markers. PLoS One 3:e3376CrossRefPubMedPubMedCentralGoogle Scholar
  3. Bradbury PJ, Zhang Z, Kroon DE, Casstevens TM, Ramdoss Y, Buckler ES (2007) TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics 23:2633–2635CrossRefPubMedGoogle Scholar
  4. Chanock SJ, Manolio T, Boehnke M, Boerwinkle E, Hunter DJ, Thomas G, Hirschhorn JN, Abecasis G, Altshuler D, Bailey-Wilson JE, Brooks LD, Cardon LR, Daly M, Donnelly P, Fraumeni JF, Freimer NB, Gerhard DS, Gunter C, Guttmacher AE, Guyer MS, Harris EL, Hoh J, Hoover R, Kong CA, Merikangas KA, Morton CC, Palmer LJ, Phimister EG, Rice JP, Roberts J, Rotimi C, Tucker MA, Vogan KJ, Wacholder S, Wijsman EM, Winn DM, Collins FS (2007) Replicating genotype–phenotype associations. Nature 447:655–660CrossRefPubMedGoogle Scholar
  5. Curtolo M, Cristofani-Yaly M, Gazaffi R, Takita MA, Figueira A, Machado MA (2017) QTL mapping for fruit quality in Citrus using DArTseq markers. BMC Genomics 18:289CrossRefPubMedPubMedCentralGoogle Scholar
  6. Deng Z, Xu J (2011) Breeding for fruit quality in citrus. In: Jenks MA, Bebeli PJ (eds) Breeding for fruit quality. Wiley, New York, pp 349–371CrossRefGoogle Scholar
  7. Elshire RJ, Glaubitz JC, Sun Q, Poland JA, Kawamoto K, Buckler ES, Mitchell SE (2011) A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PLoS One 6:e19379CrossRefPubMedPubMedCentralGoogle Scholar
  8. Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14:2611–2620CrossRefPubMedGoogle Scholar
  9. FAO (2016) FAOSTAT. http://www.fao.org/economic/ess/en/. Accessed 29 Nov 2016
  10. Flint-Garcia SA, Thornsberry JM, Buckler ES IV (2003) Structure of linkage disequilibrium in plants. Annu Rev Plant Biol 54:357–374CrossRefPubMedGoogle Scholar
  11. Furr JR (1969) Citrus breeding for the arid southwestern United States. In: Chapman HD (ed) Proceedings of 1st international citrus symposium, vol 1. University of California, Riverside, CA, USA, pp 191–197Google Scholar
  12. Gianola D, Foulley JL (1983) Sire evaluation for ordered categorical data with a threshold model. Genet Sel Evol 15:201–224CrossRefPubMedPubMedCentralGoogle Scholar
  13. Gilmour AR, Gogel BJ, Cullis BR, Thompson R (2015) ASReml user guide release 4.1. VSN International Ltd., Hemel HempsteadGoogle Scholar
  14. Glaubitz JC, Casstevens TM, Lu F, Harriman J, Elshire RJ, Sun Q, Buckler ES (2014) TASSEL-GBS: a high capacity genotyping by sequencing analysis pipeline. PLoS One 9:e90346CrossRefPubMedPubMedCentralGoogle Scholar
  15. Gmitter FG, Chen C, Nagesware R, Soneji JR (2007) 14 Citrus fruits. In: Kole C (ed) Genome mapping and molecular breeding in plants, volume 4: Fruits and nuts. Springer-Verlag, Berlin Heidelberg, pp 265–279Google Scholar
  16. Gois IB, Borém A, Cristofani-Yaly M, de Resende MDV, Azevedo CF, Bastianel M, Novelli VM, Machado MA (2016) Genome wide selection in Citrus breeding. Genet Mol Res 15:gmr15048863CrossRefGoogle Scholar
  17. Goldenberg L, Yaniv Y, Porat R, Carmi N (2018) Mandarin fruit quality: a review. J Sci Food Agric 98:18–26CrossRefPubMedGoogle Scholar
  18. Guo F, Yu H, Tang Z, Jiang X, Wang L, Wang X, Xu Q, Deng X (2015) Construction of a SNP-based high-density genetic map for pummelo using RAD sequencing. Tree Genet Genomes 11:1–11CrossRefGoogle Scholar
  19. Harville DA, Mee RW (1984) A mixed model procedure for analyzing ordered categorical data. Biometrics 40:393–408CrossRefGoogle Scholar
  20. He J, Zhao X, Laroche A, Lu ZX, Liu HK, Li Z (2014) Genotyping-by-sequencing (GBS), an ultimate marker-assisted selection (MAS) tool to accelarate plant breeding. Front Plant Sci 5:484CrossRefPubMedPubMedCentralGoogle Scholar
  21. Hearn CJ, Bai J, Baldwin E, McCollum TG, Hall DG, Stover E, Driggers R (2014) Breeding “sweet oranges” at the USDA US Horticultural Research Laboratory. In XXIX International Horticultural Congress on Horticulture: sustaining lives, livelihoods and landscapes (IHC2014): 1127 (pp. 41–44)Google Scholar
  22. Heffner EL, Jannink JL, Sorrells ME (2011) Genomic selection accuracy using multifamily prediction models in a wheat breeding program. Plant Genome 4:65–75CrossRefGoogle Scholar
  23. Imai A, Kuniga T, Yoshioka T, Nonaka K, Mitani N, Fukamachi H, Hiehata N, Yamamoto M, Hayashi T (2017a) Genetic background, inbreeding, and genetic uniformity in the national citrus breeding program, Japan. Hortic J 86:200–207CrossRefGoogle Scholar
  24. Imai A, Yoshioka T, Hayashi T (2017b) Quantitative trait locus (QTL) analysis of fruit-quality traits for mandarin breeding in Japan. Tree Genet Genomes 13:79CrossRefGoogle Scholar
  25. Iwata H, Hayashi T, Terakami S, Takada N, Sawamura Y, Yamamoto T (2013) Potential assessment of genome-wide association study and genomic selection in Japanese pear Pyrus pyrifolia. Breed Sci 63:125–140CrossRefPubMedPubMedCentralGoogle Scholar
  26. Khan IA, Kender WJ (2007) Citrus breeding: introduction and objectives. In: Khan IA (ed) Citrus genetics, breeding and biotechnology. CAB International, Wallingford, pp 1–8CrossRefGoogle Scholar
  27. Kouassi AB, Durel CE, Costa F, Tartarini S, van de Weg E, Evans K, Fernandez-Fernandez F, Govan C, Boudichevskaja A, Dunemann F, Antofie A, Lateur M, Stankiewicz-Kosyl M, Soska A, Tomala K, Lewandowski M, Rutkovski K, Zurawicz E, Guerra W, Laurens F (2009) Estimation of genetic parameters and prediction of breeding values for apple fruit-quality traits using pedigreed plant material in Europe. Tree Genet Genomes 5:659–672CrossRefGoogle Scholar
  28. Kumar S, Chagné D, Bink MCAM, Volz RK, Whitworth C, Carlisle C (2012) Genomic selection for fruit quality traits in apple (Malus× domestica Borkh.) PLoS One 7:e36674CrossRefPubMedPubMedCentralGoogle Scholar
  29. Kumar S, Garrick DJ, Bink M, Whitworth C, Chagne D, Volz RK (2013) Novel genomic approaches 145 unravel genetic architecture of complex traits in apple. BMC Genomics 14:393CrossRefPubMedPubMedCentralGoogle Scholar
  30. Kunihisa M, Moriya S, Abe K, Okada K, Haji T, Hayashi T, Kim H, Nishitani C, Terakami S, Yamamoto T (2014) Identification of QTLs for fruit quality traits in Japanese apples: QTLs for early ripening are tightly related to preharvest fruit drop. Breeding Sci 64:240–251CrossRefGoogle Scholar
  31. Langmead B, Trapnell C, Pop M, Salzberg SL (2009) Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Bio l10:R25CrossRefGoogle Scholar
  32. Marchini J, Cardon LR, Phillips MS, Donnelly P (2004) The effects of human population structure on large genetic association studies. Nat Genet 36(5):512–517CrossRefPubMedGoogle Scholar
  33. Meuwissen TH, Hayes B, Goddard M (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics 157:1819–1829PubMedPubMedCentralGoogle Scholar
  34. Minamikawa MF, Nonaka K, Kaminuma E, Kajiya-Kanegae H, Onogi A, Goto S, Yoshioka T, Imai A, Hamada H, Hayashi T, Matsumoto S, Katayose Y, Toyoda A, Fujiyama A, Nakamura Y, Shimizu T, Iwata H (2017) Genome-wide association study and genomic prediction in citrus: potential of genomics-assisted breeding for fruit quality traits. Sci Rep 7:4721CrossRefPubMedPubMedCentralGoogle Scholar
  35. Moriya S, Kunihisa M, Okada K, Iwanami H, Iwata H, Minamikawa M, Katayose Y, Matsumoto T, Mori S, Sasaki H, Matsumoto T, Nishitani C, Terakami S, Yamamoto T, Abe K (2017) Identification of QTLs for flesh mealiness in apple (Malus × domestica Borkh.) Hortic J 86:159–170CrossRefGoogle Scholar
  36. Ninomiya T, Shimada T, Endo T, Nonaka K, Omura M, Fujii H (2015) Development of citrus cultivar identification by CAPS markers and parentage analysis. Hort Res 14:127–133CrossRefGoogle Scholar
  37. Nishio S, Norio T, Saito T, Yamamoto T, Iketani H (2016) Estimation of loss of genetic diversity in modern Japanese cultivars by comparison of diverse genetic resources in Asian pear (Pyrus spp.) BMC Genet 17:81CrossRefPubMedPubMedCentralGoogle Scholar
  38. Ollitrault P, Terol J, Chen CX, Federici CT, Lotfy S, Hippolyte I, Ollitrault F, Bérard A, Chauveau A, Cuenca J, Costantino G, Kacar Y, Mu L, Garcia-Lor A, Froelicher Y, Aleza P, Boland A, Billot C, Navarro L, Luro F, Roose ML, Gmitter FG, Talon M, Brunel D (2012) A reference genetic map of C. clementina hort. ex Tan.; citrus evolution inferences from comparative mapping. BMC Genomics 13:593CrossRefPubMedPubMedCentralGoogle Scholar
  39. Omura M, Shimada T (2016) Citrus breeding, genetics and genomics in Japan. Breeding Sci 66:3–17CrossRefGoogle Scholar
  40. Oueslati A, Salhi-Hannachi A, Luro F, Vignes H, Mournet P, Ollitrault P (2017) Genotyping by sequencing reveals the interspecific C. maxima / C. reticulata admixture along the genomes of modern citrus varieties of mandarins, tangors, tangelos, orangelos and grapefruits. PLoS One 12:e0185618CrossRefPubMedPubMedCentralGoogle Scholar
  41. Peterson BK, Weber JN, Kay EH, Fisher HS, Hoekstra HE (2012) Double digest RADseq: an inexpensive method for de novo SNP discovery and genotyping in model and non-model species. PLoS One 7:e37135CrossRefPubMedPubMedCentralGoogle Scholar
  42. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959PubMedPubMedCentralGoogle Scholar
  43. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira M, Bender D, Maller J, Sklar P, de Bakker P, Daly M, Sham P (2007) PLINK: a toolset for whole-genome association and population-based linkage analysis. Am J Hum Genet 81:559–575CrossRefPubMedPubMedCentralGoogle Scholar
  44. Rafalski A, Morgante M (2004) Corn and humans: recombination and linkage disequilibrium in two genomes of similar size. Trends Genet 20:103–111CrossRefPubMedGoogle Scholar
  45. Sargolzaei M, Chesnais JP, Schenkel FS (2014) A new approach for efficient genotype imputation using information from relatives. BMC Genomics 15:478CrossRefPubMedPubMedCentralGoogle Scholar
  46. Soetaert K (2013) plot3D: plotting multi-dimensional data. R package version 1.0Google Scholar
  47. Soost RK (1987) Breeding citrus-genetics and nucellar embryony. Improving vegetatively propagated crops. Academic Press, London, pp 83–110Google Scholar
  48. Turner SD (2014) qqman: an R package for visualizing GWAS results using Q-Q and manhattan plots. bioRxiv (2014): 005165Google Scholar
  49. Turner S, Armstrong LL, Bradford Y, Carlson CS, Crawford DC, Crenshaw AT, de Andrade M, Doheny KF, Haines JL, Hayes G, Jarvik G, Jiang L, Kullo IJ, Li R, Ling H, Manolio TA, Matsumoto M, McCarty CA, McDavid AN, Mirel DB, Paschall JE, Pugh EW, Rasmussen LV, Wilke RA, Zuvich RL, Ritchie MD (2011) Quality control procedures for genome-wide association studies. Curr Protoc Hum Genet Chapter 1: Unit1 19Google Scholar
  50. Viana AP, Resende MDV, Riaz S, Walker MA (2016) Genome selection in fruit breeding: application to table grapes. Sci Agric 73:142–149CrossRefGoogle Scholar
  51. Voorrips RE, Bink MCAM, van de Weg WE (2012) Pedimap: software for the visualization of genetic and phenotypic data in pedigrees. J Hered 103:903–907CrossRefPubMedPubMedCentralGoogle Scholar
  52. Wiggans GR, Sonstegard TS, Vanraden PM, Matukumalli LK, Schnabel RD, Taylor JF, Schenkel FS, Van Tassell CP (2009) Selection of single-nucleotide polymorphisms and quality of genotypes used in genomic evaluation of dairy cattle in the United States and Canada. J Dairy Sci 92:3431–3436CrossRefPubMedGoogle Scholar
  53. Wolak ME (2012) nadiv: an R package to create relatedness matrices for estimating non-additive genetic variances in animal models. Methods Ecol Evol 3(5):792–796CrossRefGoogle Scholar
  54. Wu GA, Prochnik S, Jenkins J, Salse J, Hellsten U, Murat F, Perrier X, Ruiz M, Scalabrin S, Terol J, Takita MA, Labadie K, Poulain J, Couloux A, Jabbari K, Cattonaro F, Del Fabbro C, Pinosio S, Zuccolo A, Chapman J, Grimwood J, Tadeo FR, Estornell LH, Muñoz-Sanz JV, Ibanez V, Herrero-Ortega A, Aleza P, Pérez-Pérez J, Ramón D, Brunel D, Luro F, Chen C, Farmerie WG, Desany B, Kodira C, Mohiuddin M, Harkins T, Fredrikson K, Burns P, Lomsadze A, Borodovsky M, Reforgiato G, Freitas-Astúa J, Quetier F, Navarro L, Roose M, Wincker P, Schmutz J, Morgante M, Machado MA, Talon M, Jaillon O, Ollitrault P, Gmitter F, Rokhsar D (2014) Sequencing of diverse mandarin, pummelo and orange genomes reveals complex history of admixture during citrus domestication. Nat Biotechnol 32:656–662CrossRefPubMedPubMedCentralGoogle Scholar
  55. Yu J, Pressoir G, Briggs WH, Bi IV, Yamsaki M, Doebley JF, McMullen MD, Gaut BS, Nielsen DM, Holland JB, Kresovich S, Buckler ES (2006) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat Genet 38:203–208CrossRefPubMedGoogle Scholar
  56. Yu Y, Chen C, Gmitter FG Jr (2016) QTL mapping of mandarin (Citrus reticulata) fruit characters using high-throughput SNP markers. Tree Genet Genomes 12:77CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.NARO Institute of Fruit Tree and Tea ScienceTsukubaJapan
  2. 2.Graduate School of Life and Environmental SciencesTsukuba UniversityTsukubaJapan
  3. 3.NARO Institute of Fruit Tree and Tea ScienceShimizuJapan
  4. 4.NARO Western Region Agricultural Research CenterZentsujiJapan
  5. 5.NARO Institute of Crop ScienceTsukubaJapan

Personalised recommendations