Trait diversity and potential for selection indices based on variation among regionally adapted processing Tomato Germplasm

Journal of the American Society for Horticultural Science

Volumn 137, Issue 6, 2012, Pages 427-437

  Merk, Heather L ^a,i   Yarnes, Shawn C ^b,j   Van Deynze, Allen ^b   Tong, Nankui ^c   Menda, Naama ^d   Mueller, Lukas A ^d   Mutschler, Martha A ^e   Loewen, Steven A ^f   Myers, James R ^g   Francis, David M ^h  

^a OHIO STATE UNIVERSITY   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c Campbell Soup R and D   (United States)

^d Boyce Thompson Institute for Plant Research   (United States)

^e Cornell University ^*  (United States)

^f UNIVERSITY OF GUELPH   (Canada)

^g OREGON STATE UNIVERSITY   (United States)

^h OHIO STATE UNIVERSITY   (United States)

ⁱ BHN Research of Gargiulo Inc ^*  (United States)

^j BHN Research   (United States)

more..

Author keywords

Best linear unbiased predictor; BLUP; Digital phenotyping; MTI; Multitrait selection indices; Plant genetic resources; Solanum lycopersicum; Standardized phenotyping; Variance components

Indexed keywords

EID: 84866719001     PISSN: 00031062     EISSN: None     Source Type: Journal    
DOI: 10.21273/jashs.137.6.427     Document Type: Article

References (54)

1. Asoro, F.G., M.A. Newell, W.D. Beavis, M.P. Scott, and J.-L. JanninkAccuracy and training population design for genomic selection on quantitative traits in elite North American oatsPlant Genome 4:132-144.
2. Azanza, F., T.E. Young, D. Kim, S.D. Tanksley, and J.A. Juvik. 1994title type="contributor">. Characterization of the effect of introgressed segments of chromosome 7 and chromosome 10 from Lycopersicon chmielewskii on tomato soluble solids, pH, and yieldTheor. Appl. Genet. 87:965-972.
3. Barringer, S.A., M.A. Bennett, and W.D. Bash. 1999. Effect of fruit maturity and nitrogen fertilizer on tomato peeling efficiency. J. Veg. Crop Production 5:3-11.
4. Bates, D., M. Maechler, and B. Bolker. 2011. Lme4: Linear mixed-effects models using s4 classes. 1 Sept. 2011. http://cran.r-project.org/web/packages/lme4/index.html.
5. Bernardo, R. 2008. Molecular markers and selection for complex traits in plants: Learning from the last 20 years. Crop Sci. 48:1649-1664.
6. Bernardo, R. 2009. Genomewide selection for rapid introgression of exotic germplasm in maize. Crop Sci. 49:419-425.
7. Bernardo, R. and J. Yu. 2007. Prospects for genomewide selection for quantitative traits in maize. Crop Sci. 47:1082-1090.
8. Brewer, M.T., L.X. Lang, K. Fujimura, N. Dujmovic, S. Gray, and E. van der Knaap. 2006. Development of a controlled vocabulary and software application to analyze fruit shape variation in tomato and otherplant species. Plant Physiol. 141:15-25.
9. Brewer, M.T., J.B. Moyseenko, A.J. Monforte, and E. van der Knaap. 2007. Morphological variation in tomato: A comprehensive study of quantitative trait loci controlling fruit shape and development. J. Expt. Bot. 58:1339-1349.
10. California Tomato Research Institute. 2002. CTRI 2002 annual report. California Tomato Research Institute, Escalon, CA.
11. California Tomato Research Institute. 2011. CTRI 2011 annual report. California Tomato Research Institute, Escalon, CA.
12. Chen, F.Q., M.R. Foolad, J. Hyman, D.A. St Clair, and R.B. Beelaman. 1999. Mapping of QTLs for lycopene and other fruit traits in a Lycopersicon esculentum X l-pimpinellifolium cross and comparison of QTLs across tomato species. Mol. Breed. 5:283-299.
13. Commission Internationale de l'Eclairage. 1978. Recommendations on uniform color spaces: Color-difference equations, psychometric color terms. Commission Internationale de l'Eclairage, Paris, France.
14. Crossa, J., G. de los Campos, P. Perez, D. Gianola, J. Burgueno, J.L. Araus, D. Makumbi, R.P. Singh, S. Dreisigacker, J.B. Yan, V. Arief, M. Banziger, and H.J. Braun. 2010. Prediction of genetic values of quantitative traits in plant breeding using pedigree and molecular markers. Genetics 186:713-U406.
15. Darrigues, A., J. Hall, E. van der Knaap, D.M. Francis, N. Dujmovic, and S. Gray. 2008. Tomato analyzer-color test: A new tool for efficient digital phenotyping. J. Amer. Soc. Hort. Sci. 133:579-586.
16. de los Campos, G., H. Naya, D. Gianola, J. Crossa, A. Legarra, E. Manfredi, K. Weigel, and J.M. Cotes. 2009. Predicting quantitative traits with regression models for dense molecular markers and pedigree. Genetics 182:375-385.
17. de Mendiburu, F. 2010. Agricolae: Statistical procedures for agricultural research. 1 Sept. 2011. http://cran.r-project.org/web/packages/agricolae/index.html.
18. Federer, W.T. and D. Raghavarao. 1975. Augmented designs. Biometrics 31:29-35.
19. Friedrich, J.E. 2001. Titratable activity of acid tastants. Current Protocols Food Anal. Chem. G2.1.1-G2.1.7.
20. Garcia, E. and D.M. Barrett. 2006. Peelability and yield of processing tomatoes by steam or lye. J. Food Processing Preservation 30:3-14.
21. Gonzalo, M.J., M.T. Brewer, C. Anderson, D. Sullivan, S. Gray, and E. van der Knaap. 2009. Tomato fruit shape analysis using morpho-metric and morphology attributes implemented in tomato analyzer software program. J. Amer. Soc. Hort. Sci. 134:77-87.
22. Gonzalo, M.J. and E. van der Knaap. 2008. A comparative analysis into the genetic bases of morphology in tomato varieties exhibiting elongated fruit shape. Theor. Appl. Genet. 116:647-656.
23. Grandillo, S., D. Zamir, and S.D. Tanksley. 1999. Genetic improvement of processing tomatoes: A 20 years perspective. Euphytica 110:85-97.
24. Hartmann, A., T. Czauderna, R. Hoffmann, N. Stein, and F. Schreiber. Htpheno: An image analysis pipeline for high-throughput plant phenotyping. BMC Bioinformatics 12:148.
25. Hazel, L.N. 1943. The genetic basis for constructing selection indices. Genetics 28:476-490.
26. Heffner, E.L., J.-L. Jannink, and M.E. Sorrells. 2011. Genomic selection accuracy using multifamily prediction models in a wheat breeding program. Plant Genome 4:65-75.
27. Heffner, E.L., M.E. Sorrells, and J.L. Jannink. 2009. Genomic selection for crop improvement. Crop Sci. 49:1-12.
28. Hothorn, T., F. Bretz, and P. Westfal. 2008. Simultaneous inference in general parametric models. Biometrical J. 50:346-363.
29. International Plant Genetic Resources Institute. 1996. Descriptors for tomato (Lycopersicon spp.). Intl. Plant Genet. Resources Inst., Rome, Italy.
30. International Union for the Protection of New Varieties and Plants. 2001. Guidelines for the conduct of tests for distinctness, homogeneity and stability (tomato). UPoV, Geneva, Switzerland.
31. Iwata, H. and J.-L. Jannink. 2011. Accuracy of genomic selection prediction in barley breeding programs: A simulation study based on the real single nucleotide polymorphism data of barley breeding lines. Crop Sci. 51:1915-1927.
32. Jung, S., N. Menda, S. Redmond, R.M. Buels, M. Friesen, Y. Bendana, L.A. Sanderson, H. Lapp, T. Lee, B. MacCallum, K.E. Bett, S. Cain, D. Clements, L.A. Mueller, and D. Main. 2011. The chado natural diversity module: A new generic database schema for large-scale phenotyping and genotyping data. Database 2011:bar051. 6 Aug. http://database.oxfordjournals.org/content/2011/bar051.full.
33. Kump, K.L., P.J. Bradbury, R.J. Wisser, E.S. Buckler, A.R. Belcher, M.A. Oropeza-Rosas, J.C. Zwonitzer, S. Kresovich, M.D. McMullen, D. Ware, P.J. Balint-Kurti, and J.B. Holland. 2011. Genome-wide association study of quantitative resistance to southern leaf blight in the maize nested association mapping population. Nat. Genet. 43:163-U120.
34. Lorenz, A.J., M.T. Hamblin, and J.L. Jannink. 2010. Performance of single nucleotide polymorphisms versus haplotypes for genome-wide association analysis in barley. PLoS One 5:e14079.
35. Menda, N., R.M. Buels, I. Tecle, and L.A. Mueller. 2008. A community-based annotation framework for linking Solanaceae genomes with phenomes. Plant Physiol. 147:1788-1799.
36. Meuwissen, T.H.E., B.J. Hayes, and M.E. Goddard. 2001. Prediction of total genetic value using genome-wide dense marker maps. Genetics 157:1819-1829.
37. Milc, J., A. Sala, S. Bergamaschi, and N. Pecchioni. 2011. A genotypic and phenotypic information source for marker-assisted selection of cereals: The cerealab database. Database 2011:baq038. 17 Aug. 2012. http://database.oxfordjournals.org/content/2011/baq038.full.
38. Ontario Processing Vegetable Growers. 2011. Agreement for marketing the 2011 crop of tomatoes for processing under the farm products marketing act. Ontario Processing Vegetable Growers, London, Ontario, Canada.
39. Osborn, T.C., D.C. Alexander, and J.F. Fobes. 1987. Identification of restriction-fragment-length-polymorphisms linked to genes-controlling soluble solids content in tomato fruit. Theor. Appl. Genet. 73:350-356.
40. R Development Core Team. 2011. R: A language and environment for statistical computing. 1 Sept. 2011. http://www.r-project.org/>.
41. Riedelsheimer, C., A. Czedik-Eysenberg, C. Grieder, J. Lisec, F. Technow, R. Sulpice, T. Altmann, M. Stitt, L. Willmitzer, and A.E. Melchinger. 2012. Genomic and metabolic prediction of complex heterotic traits in hybrid maize. Nat. Genet. 44:217-220.
42. Rodriguez, G.R., S. Munos, C. Anderson, S.C. Sim, A. Michel, M. Causse, B.B.M. Gardener, D. Francis, and E. van der Knaap. 2011. Distribution of sun, ovate, lc, and fas in the tomato germplasm and the relationship to fruit shape diversity. Plant Physiol. 156:275-285.
43. Saliba-Colombani, V., M. Causse, D. Langlois, J. Philouze, and M. Buret. 2001. Genetic analysis of organoleptic quality in fresh market tomato. 1. Mapping QTLs for physical and chemical traits. Theor. Appl. Genet. 102:259-272.
44. Sim, S.C., M.D. Robbins, A. Van Deynze, A.P. Michel, and D.M. Francis. 2011. Population structure and genetic differentiation associated with breeding history and selection in tomato (Solanum lycopersicum L.). Heredity 106:927-935.
45. Sol Genomics Network. 2012. Search SGN. 10 Apr. 2012. http://solgenomics.net/search/phenotypes.
46. Solanaceae Coordinated Agricultural Project. 2012. Tomato phenotype data. 10 Apr. 2012.
47. Souza, E.J., C. Sneller, M.J. Guttieri, A. Sturbaum, C. Griffey, M. Sorrells, H. Ohm, and D. Van Sanford. 2012. Basis for selecting soft wheat for end-use quality. Crop Sci. 52:21-31.
48. Tanksley, S.D., S. Grandillo, T.M. Fulton, D. Zamir, Y. Eshed, V. Petiard, J. Lopez, andT. BeckBunn. 1996. Advancedbackcross QTL analysis in a cross between an elite processing line of tomato and its wild relative l-pimpinellifolium. Theor. Appl. Genet. 92:213-224.
49. Tanksley, S.D. and J. Hewitt. 1988. Use of molecular markers in breeding for soluble solids content in tomato-A re-examination. Theor. Appl. Genet. 75:811-823.
50. Tian, F., P.J. Bradbury, P.J. Brown, H. Hung, Q. Sun, S. Flint-Garcia, T.R. Rocheford, M.D. McMullen, J.B. Holland, and E.S. Buckler. 2011. Genome-wide association study of leaf architecture in the maize nested association mapping population. Nat. Genet. 43:159-U113.
51. Wang, M.H., N. Jiang, T.Y. Jia, L. Leach, J. Cockram, R. Waugh, L. Ramsay, B. Thomas, and Z.W. Luo. 2012. Genome-wide association mapping of agronomic and morphologic traits in highly structured populations of barley cultivars. Theor. Appl. Genet. 124:233-246.
52. Weller, J.I. (ed.). 1994. Economic aspects of animal breeding. Kluwer, Chapman and Hall, London, UK.
53. Xu, Y.B. and J.H. Crouch. 2008. Marker-assisted selection in plant breeding: From publications to practice. Crop Sci. 48:391-407.
54. Zhao, Y.S., M. Gowda, W.X. Liu, T. Wurschum, H.P. Maurer, F.H. Longin, N. Ranc, and J. Reif. 2012. Accuracy of genomic selection in european maize elite breeding populations. Theor. Appl. Genet. 124:769-776.