The crop QTLome comes of age

Current Opinion in Biotechnology

Volumn 32, Issue , 2015, Pages 179-185

  Salvi, Silvio ^a   Tuberosa, Roberto ^a  

^a UNIVERSITY OF BOLOGNA   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

GENES; PLANTS (BOTANY);

BREEDING PROGRAM; GENOMICS; GENOTYPING; MARKER-ASSISTED BREEDING; META ANALYSIS; QTL EFFECTS; QUANTITATIVE TRAIT LOCUS; RECENT PROGRESS;

CROPS;

CHICKPEA; DROUGHT TOLERANCE; FUSARIUM; GENE IDENTIFICATION; GENETIC ASSOCIATION; GENETIC LINKAGE; GENETIC VARIABILITY; GENOTYPE; INFECTION RESISTANCE; MAIZE; MARKER ASSISTED BREEDING; NONHUMAN; PLANT BREEDING; PLANT GENETICS; PLANT HEIGHT; QUANTITATIVE TRAIT LOCUS; QUANTITATIVE TRAIT LOCUS MAPPING; REVIEW; RICE; SALT TOLERANCE; SINGLE NUCLEOTIDE POLYMORPHISM; SORGHUM; SOYBEAN; TOMATO; WHEAT; ANIMAL; BREEDING; CROP; GENETICS; GENOMICS; HUMAN; PLANT GENOME;

ANIMALS; BREEDING; CROPS, AGRICULTURAL; GENOME, PLANT; GENOMICS; GENOTYPE; HUMANS; QUANTITATIVE TRAIT LOCI;

EID: 84921261557     PISSN: 09581669     EISSN: 18790429     Source Type: Journal    
DOI: 10.1016/j.copbio.2015.01.001     Document Type: Review

References (79)

1. He J., Zhao X., Laroche A., Lu Z.X., Liu H., Li Z. Genotyping-by-sequencing (GBS), an ultimate marker-assisted selection (MAS) tool to accelerate plant breeding. Front Plant Sci 2014, 5:484.
2. Varshney R.K., Terauchi R., McCouch S.R. Harvesting the promising fruits of genomics: applying genome sequencing technologies to crop breeding. PLoS Biol 2014, 12:e1001883.
3. Granier C., Vile D. Phenotyping and beyond: modelling the relationships between traits. Curr Opin Plant Biol 2014, 18:96-102.
4. Houle D., Govindaraju D.R., Omholt S. Phenomics: the next challenge. Nat Rev Genet 2010, 11:855-866.
5. Zamir D. Where have all the crop phenotypes gone?. PLoS Biol 2013, 11:e1001595.
6. Drinkwater N.R., Gould M.N. The long path from QTL to gene. PLoS Genet 2012, 8:e1002975.
7. Bernardo R. Molecular markers and selection for complex traits in plants: learning from the last 20 years. Crop Sci 2008, 48:1649-1664.
8. Wurschum T. Mapping QTL for agronomic traits in breeding populations. Theor Appl Genet 2012, 125:201-210.
9. Korte A., Farlow A. The advantages and limitations of trait analysis with GWAS: a review. Plant Methods 2013, 9:29.
10. Jannink J.L., Lorenz A.J., Iwata H. Genomic selection in plant breeding: from theory to practice. Brief Funct Genom 2010, 9:166-177.
11. Nakaya A., Isobe SN: Will genomic selection be a practical method for plant breeding?. Ann Bot 2012, 110:1303-1316.
12. Cooper L., Walls R.L., Elser J., Gandolfo M.A., Stevenson D.W., Smith B., Preece J., Athreya B., Mungall C.J., Rensing S. The plant ontology as a tool for comparative plant anatomy and genomic analyses. Plant Cell Physiol 2013, 54:e1-e1.
13. Mano Y., Omori F., Takeda K. Construction of intraspecific linkage maps, detection of a chromosome inversion, and mapping of QTL for constitutive root aerenchyma formation in the teosinte Zea nicaraguensis. Mol Breed 2012, 29:137-146.
14. Ron M., Dorrity M.W., de Lucas M., Toal T., Hernandez R.I., Little S.A., Maloof J.N., Kliebenstein D.J., Brady S.M. Identification of novel loci regulating interspecific variation in root morphology and cellular development in tomato. Plant Physiol 2013, 162:755-768.
15. Wu R., Lin M. Functional mapping - how to map and study the genetic architecture of dynamic complex traits. Nat Rev Genet 2006, 7:229-237.
16. Würschum T., Liu W., Alheit K.V., Tucker M.R., Gowda M., Weissmann E.A., Hahn V., Maurer H.P. Adult plant development in triticale (× triticosecale wittmack) is controlled by dynamic genetic patterns of regulation. G3 2014, 4:1585-1591.
17. Horvatovich P., Franke L., Bischoff R. Proteomic studies related to genetic determinants of variability in protein concentrations. J Proteome Res 2014, 13:5-14.
18. Feltus F.A. Systems genetics: a paradigm to improve discovery of candidate genes and mechanisms underlying complex traits. Plant Sci 2014, 223:45-48.
19. Riedelsheimer C., Lisec J., Czedik-Eysenberg A., Sulpice R., Flis A., Grieder C., Altmann T., Stitt M., Willmitzer L., Melchinger A.E. Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize. Proc Natl Acad Sci USA 2012, 109:8872-8877.
20. Chen W., Gao Y., Xie W., Gong L., Lu K., Wang W., Li Y., Liu X., Zhang H., Dong H., et al. Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism. Nat Genet 2014, 46:714-721.
21. Esch E., Szymaniak J.M., Yates H., Pawlowski W.P., Buckler E.S. Using crossover breakpoints in recombinant inbred lines to identify quantitative trait loci controlling the global recombination frequency. Genetics 2007, 177:1851-1858.
22. Lacaze X., Hayes P.M., Korol A. Genetics of phenotypic plasticity: QTL analysis in barley, Hordeum vulgare. Heredity (Edinb) 2009, 102:163-173.
23. Goffinet B., Gerber S. Quantitative trait loci: a meta-analysis. Genetics 2000, 155:463-473.
24. Veyrieras J.B., Goffinet B., Charcosset A. MetaQTL: a package of new computational methods for the meta-analysis of QTL mapping experiments. BMC Bioinform 2007, 8:49.
25. Sosnowski O., Charcosset A., Joets J. BioMercator V3: an upgrade of genetic map compilation and quantitative trait loci meta-analysis algorithms. Bioinformatics 2012, 28:2082-2083.
26. Salvi S., Castelletti S., Tuberosa R. An updated consensus map for flowering time QTLs in maize. Maydica 2009, 54:501.
27. Griffiths S., Simmonds J., Leverington M., Wang Y., Fish L., Sayers L., Alibert L., Orford S., Wingen L., Snape J. Meta-QTL analysis of the genetic control of crop height in elite European winter wheat germplasm. Mol Breed 2012, 29:159-171.
28. Semagn K., Beyene Y., Warburton M.L., Tarekegne A., Mugo S., Meisel B., Sehabiague P., Prasanna B.M. Meta-analyses of QTL for grain yield and anthesis silking interval in 18 maize populations evaluated under water-stressed and well-watered environments. BMC Genomics 2013, 14:313.
29. Said J.I., Lin Z., Zhang X., Song M., Zhang J. A comprehensive meta QTL analysis for fiber quality, yield, yield related and morphological traits, drought tolerance, and disease resistance in tetraploid cotton. BMC Genomics 2013, 14:776.
30. Trijatmiko K.R., Prasetiyono J., Thomson M.J., Cruz C.M.V., Moeljopawiro S., Pereira A. Meta-analysis of quantitative trait loci for grain yield and component traits under reproductive-stage drought stress in an upland rice population. Mol Breed 2014, 34:283-295.
31. Landi P., Giuliani S., Salvi S., Ferri M., Tuberosa R., Sanguineti M.C. Characterization of root-yield-1.06, a major constitutive QTL for root and agronomic traits in maize across water regimes. J Exp Bot 2010, 61:3553-3562.
32. Zhang H., Uddin M.S., Zou C., Xie C., Xu Y., Li W.X. Meta-analysis and candidate gene mining of low-phosphorus tolerance in maize. J Integr Plant Biol 2014, 56:262-270.
33. Blanc G., Charcosset A., Mangin B., Gallais A., Moreau L. Connected populations for detecting quantitative trait loci and testing for epistasis: an application in maize. Theor Appl Genet 2006, 113:206-224.
34. Bardol N., Ventelon M., Mangin B., Jasson S., Loywick V., Couton F., Derue C., Blanchard P., Charcosset A., Moreau L. Combined linkage and linkage disequilibrium QTL mapping in multiple families of maize (Zea mays L.) line crosses highlights complementarities between models based on parental haplotype and single locus polymorphism. Theor Appl Genet 2013, 126:2717-2736.
35. Leroux D., Rahmani A., Jasson S., Ventelon M., Louis F., Moreau L., Mangin B. Clusthaplo: a plug-in for MCQTL to enhance QTL detection using ancestral alleles in multi-cross design. Theor Appl Genet 2014, 127:921-933.
36. Bink M.C., Jansen J., Madduri M., Voorrips R.E., Durel C.E., Kouassi A.B., Laurens F., Mathis F., Gessler C., Gobbin D., et al. Bayesian QTL analyses using pedigreed families of an outcrossing species, with application to fruit firmness in apple. Theor Appl Genet 2014, 127:1073-1090.
37. Rockman M.V. Reverse engineering the genotype-phenotype map with natural genetic variation. Nature 2008, 456:738-744.
38. Flint J., Mackay T.F. Genetic architecture of quantitative traits in mice, flies, and humans. Genome Res 2009, 19:723-733.
39. Wilson-Sanchez D., Rubio-Diaz S., Munoz-Viana R., Perez-Perez J.M., Jover-Gil S., Ponce M.R., Micol J.L. Leaf phenomics: a systematic reverse genetic screen for Arabidopsis leaf mutants. Plant J 2014, 79:878-891.
40. Kellis M., Wold B., Snyder M.P., Bernstein B.E., Kundaje A., Marinov G.K., Ward L.D., Birney E., Crawford G.E., Dekker J., et al. Defining functional DNA elements in the human genome. Proc Natl Acad Sci USA 2014, 111:6131-6138.
41. Otto S.P., Jones C.D. Detecting the undetected: estimating the total number of loci underlying a quantitative trait. Genetics 2000, 156:2093-2107.
42. Beavis W.D. The power and deceit of QTL experiments: lessons from comparative QTL studies. Proceedings of the Forty-Ninth Annual Corn and Sorghum Industry Research Conference 1994, 250-266.
43. Romay M.C., Millard M.J., Glaubitz J.C., Peiffer J.A., Swarts K.L., Casstevens T.M., Elshire R.J., Acharya C.B., Mitchell S.E., Flint-Garcia S.A., et al. Comprehensive genotyping of the USA national maize inbred seed bank. Genome Biol 2013, 14:R55.
44. Peiffer J.A., Romay M.C., Gore M.A., Flint-Garcia S.A., Zhang Z., Millard M.J., Gardner C.A., McMullen M.D., Holland J.B., Bradbury P.J., et al. The genetic architecture of maize height. Genetics 2014, 196:1337-1356.
45. Huang X., Wei X., Sang T., Zhao Q., Feng Q., Zhao Y., Li C., Zhu C., Lu T., Zhang Z., et al. Genome-wide association studies of 14 agronomic traits in rice landraces. Nat Genet 2010, 42:961-967.
46. Zhao K., Tung C.W., Eizenga G.C., Wright M.H., Ali M.L., Price A.H., Norton G.J., Islam M.R., Reynolds A., Mezey J., et al. Genome-wide association mapping reveals a rich genetic architecture of complex traits in Oryza sativa. Nat Commun 2011, 2:467.
47. Joseph B., Atwell S., Corwin J.A., Li B., Kliebenstein DJ: Meta-analysis of metabolome QTLs in Arabidopsis: trying to estimate the network size controlling genetic variation of the metabolome. Front Plant Sci 2014, 5:461.
48. Kliebenstein D.J. Systems biology uncovers the foundation of natural genetic diversity. Plant Physiol 2010, 152:480-486.
49. Orr H.A. The genetic theory of adaptation: a brief history. Nat Rev Genet 2005, 6:119-127.
50. Wallace J.G., Larsson S.J., Buckler E.S. Entering the second century of maize quantitative genetics. Heredity 2014, 112:30-38.
51. Xing Y., Zhang Q. Genetic and molecular bases of rice yield. Annu Rev Plant Biol 2010, 61:421-442.
52. Maccaferri M., Sanguineti M.C., Demontis A., El-Ahmed A., Garcia del Moral L., Maalouf F., Nachit M., Nserallah N., Ouabbou H., Rhouma S., et al. Association mapping in durum wheat grown across a broad range of water regimes. J Exp Bot 2011, 62:409-438.
53. Zanke C.D., Ling J., Plieske J., Kollers S., Ebmeyer E., Korzun V., Argillier O., Stiewe G., Hinze M., Neumann K., et al. Whole genome association mapping of plant height in winter wheat (Triticum aestivum L.). PLoS One 2014, 9:113287.
54. McMullen M.D., Kresovich S., Villeda H.S., Bradbury P., Li H., Sun Q., Flint-Garcia S., Thornsberry J., Acharya C., Bottoms C., et al. Genetic properties of the maize nested association mapping population. Science 2009, 325:737-740.
55. Maccaferri M., Sanguineti M.C., Corneti S., Ortega J.L., Salem M.B., Bort J., DeAmbrogio E., del Moral L.F., Demontis A., El-Ahmed A., et al. Quantitative trait loci for grain yield and adaptation of durum wheat (Triticum durum Desf.) across a wide range of water availability. Genetics 2008, 178:489-511.
56. Wurschum T., Maurer H.P., Schulz B., Mohring J., Reif J.C. Genome-wide association mapping reveals epistasis and genetic interaction networks in sugar beet. Theor Appl Genet 2011, 123:109-118.
57. Quarrie S.A., Steed A., Calestani C., Semikhodskii A., Lebreton C., Chinoy C., Steele N., Pljevljakusic D., Waterman E., Weyen J., et al. A high-density genetic map of hexaploid wheat (Triticum aestivum L.) from the cross Chinese Spring×SQ1 and its use to compare QTLs for grain yield across a range of environments. Theor Appl Genet 2005, 110:865-880.
58. Huang A., Xu S., Cai X. Whole-genome quantitative trait locus mapping reveals major role of epistasis on yield of rice. PLoS One 2014, 9:e87330.
59. Mackay T.F. Epistasis and quantitative traits: using model organisms to study gene-gene interactions. Nat Rev Genet 2014, 15:22-33.
60. Canè M.A., Maccaferri M., Nazemi G., Salvi S., Francia R., Colalongo C., Tuberosa R: Association mapping for root architectural traits in durum wheat seedlings as related to agronomic performance. Mol Breed 2014, 34:1629-1645.
61. Peleman J.D., van der Voort J.R. Breeding by design. Trends Plant Sci 2003, 8:330-334.
62. Yamamoto T., Nagasaki H., Yonemaru J., Ebana K., Nakajima M., Shibaya T., Yano M. Fine definition of the pedigree haplotypes of closely related rice cultivars by means of genome-wide discovery of single-nucleotide polymorphisms. BMC Genomics 2010, 11:267.
63. Yonemaru J., Mizobuchi R., Kato H., Yamamoto T., Yamamoto E., Matsubara K., Hirabayashi H., Takeuchi Y., Tsunematsu H., Ishii T., et al. Genomic regions involved in yield potential detected by genome-wide association analysis in Japanese high-yielding rice cultivars. BMC Genomics 2014, 15:346.
64. Chen H., He H., Zhou F., Yu H., Deng X.W. Development of genomics-based genotyping platforms and their applications in rice breeding. Curr Opin Plant Biol 2013, 16:247-254.
65. Varshney R.K., Gaur P.M., Chamarthi S.K., Krishnamurthy L., Tripathi S., Kashiwagi J., Samineni S., Singh V.K., Thudi M., Jaganathan D. Fast-Track introgression of "QTL hotspot" for root traits and other drought tolerance traits in JG 11, an elite and leading variety of chickpea. Plant Genome 2013, 6.
66. Borrell A.K., Mullet J.E., George-Jaeggli B., van Oosterom E.J., Hammer G.L., Klein P.E., Jordan D.R. Drought adaptation of stay-green sorghum is associated with canopy development, leaf anatomy, root growth, and water uptake. J Exp Bot 2014, 65:6251-6263.
67. Concibido V.C., Diers B.W., Arelli P.R. A decade of QTL mapping for cyst nematode resistance in soybean. Crop Sci 2004, 44:1121-1131.
68. Anderson J.A., Chao S., Liu S. Molecular breeding using a major QTL for Fusarium head blight resistance in wheat. Crop Sci 2007, 47:S-112-S-119.
69. James R.A., Blake C., Byrt C.S., Munns R. Major genes for Na+ exclusion, Nax1 and Nax2 (wheat HKT1;4 and HKT1;5), decrease Na+ accumulation in bread wheat leaves under saline and waterlogged conditions. J Exp Bot 2011, 62:2939-2947.
70. Salvi S., Sponza G., Morgante M., Tomes D., Niu X., Fengler K.A., Meeley R., Ananiev E.V., Svitashev S., Bruggemann E., et al. Conserved noncoding genomic sequences associated with a flowering-time quantitative trait locus in maize. Proc Natl Acad Sci USA 2007, 104:11376-11381.
71. Septiningsih E.M., Pamplona A.M., Sanchez D.L., Neeraja C.N., Vergara G.V., Heuer S., Ismail A.M., Mackill D.J. Development of submergence-tolerant rice cultivars: the Sub1 locus and beyond. Ann Bot 2009, 103:151-160.
72. Famoso A.N., Zhao K., Clark R.T., Tung C.W., Wright M.H., Bustamante C., Kochian L.V., McCouch S.R. Genetic architecture of aluminum tolerance in rice (Oryza sativa) determined through genome-wide association analysis and QTL mapping. PLoS Genet 2011, 7:e1002221.
73. Gamuyao R., Chin J.H., Pariasca-Tanaka J., Pesaresi P., Catausan S., Dalid C., Slamet-Loedin I., Tecson-Mendoza E.M., Wissuwa M., Heuer S. The protein kinase Pstol1 from traditional rice confers tolerance of phosphorus deficiency. Nature 2012, 488:535-539.
74. Steele K.A., Price A.H., Witcombe J.R., Shrestha R., Singh B.N., Gibbons J.M., Virk D.S. QTLs associated with root traits increase yield in upland rice when transferred through marker-assisted selection. Theor Appl Genet 2013, 126:101-108.
75. Pallotta M., Schnurbusch T., Hayes J., Hay A., Baumann U., Paull J., Langridge P., Sutton T: Molecular basis of adaptation to high soil boron in wheat landraces and elite cultivars. Nature 2014, 514:88-91.
76. Tardieu F., Tuberosa R: Dissection and modelling of abiotic stress tolerance in plants. Curr Opin Plant Biol 2010, 13:206-212.
77. Cooper M., van Eeuwijk F.A., Hammer G.L., Podlich D.W., Messina C.Q.T.L. Modeling for complex traits: detection and context for plant breeding. Curr Opin Plant Biol 2009, 12:231-240.
78. Harrison M.T., Tardieu F., Dong Z., Messina C.D., Hammer G.L. Characterizing drought stress and trait influence on maize yield under current and future conditions. Glob Chang Biol 2014, 20:867-878.
79. Tanksley S.D., Medina-Filho H., Rick C.M. Use of naturally-occurring enzyme variation to detect and map genes controlling quantitative traits in an interspecific backcross of tomato. Heredity 1982, 49:11-25.