XXIII EUCARPIA MAIZE AND SORGHUM CONFERENCE. - GENOMICS AND PHENOMICS FOR MODEL-BASED MAIZE AND SORGHUM BREEDING, Montpellier, 10-12 giugno 2015 Mapping QTLs for root architecture and yield in maize using a field-grown introgression library Silvia Giuliani1; Carlos Busanello2; Pierluigi Meriggi3; Ana K. Martinez A.1; Roberto Tuberosa1; Antonio Lopez4, Silvio Salvi1 1 Department of Agricultural Sciences, University of Bologna, Viale Fanin 44, 40127 Bologna, Italy (silvio.salvi@unibo.it) 2 Faculdade de Agronomia Eliseu Maciel, Universidade Federal de Pelotas, Pelotas-RS, CEP 96001-970, Brasil 3 Horta srl Via Egidio Gorra 55, 29122 Piacenza, Italy 4 National Research Council (CNR), Water Research Institute (IRSA), Via Salaria km 29,300 C.P. 10 00015 Monterotondo Stazione, Rome, Italy In crops, the genetic control of root architecture variation in the field and its relationship with yield are incompletely known. A 75 introgression-line (IL) collection from the maize cross B73 x Gaspé Flint was previously shown to segregate for several agronomically important traits (Salvi et al. 2011, BMC Plant Biology). The aim of our study was to investigate the presence of genetic variation for root traits at the adult stage in the field, and its effect on grain yield. For this purpose, the IL collection was grown in a replicated field trial at two water regimes (well-watered, WW, and water-stressed, WS). Forty-four traits covering phenology, plant architecture, yield, and root architecture were analyzed. Root architecture was investigated by means of shovelomics (Trachsel et al. 2011, Plant and Soil) coupled with software-assisted digital image analysis (REST, Colombi et al. 2015, Plant and Soil), for a total of c. 1,400 analyzed root images. The stress imposed in the WS experiment resulted in significantly lower yield (-42%) and longer anthesis-silking interval (+9%) when compared with WW. In WS, statistically significant lower root dry weight and higher number of brace roots were also observed. Relatively high correlation values (up to r = 0.66) were observed between visually or manually scored root traits and corresponding traits based on software-based analysis. QTL analysis showed a complex genetic control for most root traits, and only limited overlap between root and yield or yield components QTLs. Together with root and drought-related QTL information based on hydroponics and pot experiments for the same population, these results should contribute to unveil the role of root architecture variation on maize yield. (The financial support of EU FP7 Water4Crops, grant agreement#311933 is gratefully acknowledged). Colombi T, Kirchgessner N, Le Marié CA, York LM, Lynch JP, Hund A (2015) Next generation shovelomics: set up a tent and REST. Plant and Soil 388:1-20. Salvi S, Corneti S, Bellotti M, Carraro N, Sanguineti MC, Castelletti S, Tuberosa R (2011). Genetic dissection of maize phenology using an intraspecific introgression library. BMC Plant Biology 11:4. Trachsel S, Kaeppler SM, Brown KM, Lynch JP (2011) Shovelomics: high throughput phenotyping of maize (Zea mays L.) root architecture in the field. Plant and Soil 341:75-87.
Mapping QTLs for root architecture and yield in maize using a field-grown introgression library / Giuliani, S; Busanello, C; Meriggi, P; Martinez Ascanio, A k; Tuberosa, R; Lopez, A; Salvi, S. - STAMPA. - (2015), pp. 38-38. (Intervento presentato al convegno XXXIIIrd EUCARPIA Maize and Sorghum Conference tenutosi a Montpellier, France nel 10-12/06/2015).
Mapping QTLs for root architecture and yield in maize using a field-grown introgression library.
GIULIANI, SILVIA;MARTINEZ ASCANIO, ANA KARINE;TUBEROSA, ROBERTO;SALVI, SILVIO
2015
Abstract
XXIII EUCARPIA MAIZE AND SORGHUM CONFERENCE. - GENOMICS AND PHENOMICS FOR MODEL-BASED MAIZE AND SORGHUM BREEDING, Montpellier, 10-12 giugno 2015 Mapping QTLs for root architecture and yield in maize using a field-grown introgression library Silvia Giuliani1; Carlos Busanello2; Pierluigi Meriggi3; Ana K. Martinez A.1; Roberto Tuberosa1; Antonio Lopez4, Silvio Salvi1 1 Department of Agricultural Sciences, University of Bologna, Viale Fanin 44, 40127 Bologna, Italy (silvio.salvi@unibo.it) 2 Faculdade de Agronomia Eliseu Maciel, Universidade Federal de Pelotas, Pelotas-RS, CEP 96001-970, Brasil 3 Horta srl Via Egidio Gorra 55, 29122 Piacenza, Italy 4 National Research Council (CNR), Water Research Institute (IRSA), Via Salaria km 29,300 C.P. 10 00015 Monterotondo Stazione, Rome, Italy In crops, the genetic control of root architecture variation in the field and its relationship with yield are incompletely known. A 75 introgression-line (IL) collection from the maize cross B73 x Gaspé Flint was previously shown to segregate for several agronomically important traits (Salvi et al. 2011, BMC Plant Biology). The aim of our study was to investigate the presence of genetic variation for root traits at the adult stage in the field, and its effect on grain yield. For this purpose, the IL collection was grown in a replicated field trial at two water regimes (well-watered, WW, and water-stressed, WS). Forty-four traits covering phenology, plant architecture, yield, and root architecture were analyzed. Root architecture was investigated by means of shovelomics (Trachsel et al. 2011, Plant and Soil) coupled with software-assisted digital image analysis (REST, Colombi et al. 2015, Plant and Soil), for a total of c. 1,400 analyzed root images. The stress imposed in the WS experiment resulted in significantly lower yield (-42%) and longer anthesis-silking interval (+9%) when compared with WW. In WS, statistically significant lower root dry weight and higher number of brace roots were also observed. Relatively high correlation values (up to r = 0.66) were observed between visually or manually scored root traits and corresponding traits based on software-based analysis. QTL analysis showed a complex genetic control for most root traits, and only limited overlap between root and yield or yield components QTLs. Together with root and drought-related QTL information based on hydroponics and pot experiments for the same population, these results should contribute to unveil the role of root architecture variation on maize yield. (The financial support of EU FP7 Water4Crops, grant agreement#311933 is gratefully acknowledged). Colombi T, Kirchgessner N, Le Marié CA, York LM, Lynch JP, Hund A (2015) Next generation shovelomics: set up a tent and REST. Plant and Soil 388:1-20. Salvi S, Corneti S, Bellotti M, Carraro N, Sanguineti MC, Castelletti S, Tuberosa R (2011). Genetic dissection of maize phenology using an intraspecific introgression library. BMC Plant Biology 11:4. Trachsel S, Kaeppler SM, Brown KM, Lynch JP (2011) Shovelomics: high throughput phenotyping of maize (Zea mays L.) root architecture in the field. Plant and Soil 341:75-87.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
