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Improvement of marker-based predictability of Apparent Amylose Content in japonica rice through GBSSI allele mining

BACKGROUND: Apparent Amylose Content (AAC), regulated by the Waxy gene, represents the key determinant of rice cooking properties. In occidental countries high AAC rice represents the most requested market class but the availability of molecular markers allowing specific selection of high AAC variet...

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Autores principales: Biselli, Chiara, Cavalluzzo, Daniela, Perrini, Rosaria, Gianinetti, Alberto, Bagnaresi, Paolo, Urso, Simona, Orasen, Gabriele, Desiderio, Francesca, Lupotto, Elisabetta, Cattivelli, Luigi, Valè, Giampiero
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3904453/
https://www.ncbi.nlm.nih.gov/pubmed/24383761
http://dx.doi.org/10.1186/1939-8433-7-1
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author Biselli, Chiara
Cavalluzzo, Daniela
Perrini, Rosaria
Gianinetti, Alberto
Bagnaresi, Paolo
Urso, Simona
Orasen, Gabriele
Desiderio, Francesca
Lupotto, Elisabetta
Cattivelli, Luigi
Valè, Giampiero
author_facet Biselli, Chiara
Cavalluzzo, Daniela
Perrini, Rosaria
Gianinetti, Alberto
Bagnaresi, Paolo
Urso, Simona
Orasen, Gabriele
Desiderio, Francesca
Lupotto, Elisabetta
Cattivelli, Luigi
Valè, Giampiero
author_sort Biselli, Chiara
collection PubMed
description BACKGROUND: Apparent Amylose Content (AAC), regulated by the Waxy gene, represents the key determinant of rice cooking properties. In occidental countries high AAC rice represents the most requested market class but the availability of molecular markers allowing specific selection of high AAC varieties is limited. RESULTS: In this study, the effectiveness of available molecular markers in predicting AAC was evaluated in a collection of 127 rice accessions (125 japonica ssp. and 2 indica ssp.) characterized by AAC values from glutinous to 26%. The analyses highlighted the presence of several different allelic patterns identifiable by a few molecular markers, and two of them, i.e., the SNPs at intron1 and exon 6, were able to explain a maximum of 79.5% of AAC variation. However, the available molecular markers haplotypes did not provide tools for predicting accessions with AAC higher than 24.5%. To identify additional polymorphisms, the re-sequencing of the Waxy gene and 1kbp of the putative upstream regulatory region was performed in 21 genotypes representing all the AAC classes identified. Several previously un-characterized SNPs were identified and four of them were used to develop dCAPS markers. CONCLUSIONS: The addition of the SNPs newly identified slightly increased the AAC explained variation and allowed the identification of a haplotype almost unequivocally associated to AAC higher than 24.5%. Haplotypes at the waxy locus were also associated to grain length and length/width (L/W) ratio. In particular, the SNP at the first intron, which identifies the Wx( a ) and Wx( b ) alleles, was associated with differences in the width of the grain, the L/W ratio and the length of the kernel, most likely as a result of human selection.
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spelling pubmed-39044532014-01-29 Improvement of marker-based predictability of Apparent Amylose Content in japonica rice through GBSSI allele mining Biselli, Chiara Cavalluzzo, Daniela Perrini, Rosaria Gianinetti, Alberto Bagnaresi, Paolo Urso, Simona Orasen, Gabriele Desiderio, Francesca Lupotto, Elisabetta Cattivelli, Luigi Valè, Giampiero Rice (N Y) Research BACKGROUND: Apparent Amylose Content (AAC), regulated by the Waxy gene, represents the key determinant of rice cooking properties. In occidental countries high AAC rice represents the most requested market class but the availability of molecular markers allowing specific selection of high AAC varieties is limited. RESULTS: In this study, the effectiveness of available molecular markers in predicting AAC was evaluated in a collection of 127 rice accessions (125 japonica ssp. and 2 indica ssp.) characterized by AAC values from glutinous to 26%. The analyses highlighted the presence of several different allelic patterns identifiable by a few molecular markers, and two of them, i.e., the SNPs at intron1 and exon 6, were able to explain a maximum of 79.5% of AAC variation. However, the available molecular markers haplotypes did not provide tools for predicting accessions with AAC higher than 24.5%. To identify additional polymorphisms, the re-sequencing of the Waxy gene and 1kbp of the putative upstream regulatory region was performed in 21 genotypes representing all the AAC classes identified. Several previously un-characterized SNPs were identified and four of them were used to develop dCAPS markers. CONCLUSIONS: The addition of the SNPs newly identified slightly increased the AAC explained variation and allowed the identification of a haplotype almost unequivocally associated to AAC higher than 24.5%. Haplotypes at the waxy locus were also associated to grain length and length/width (L/W) ratio. In particular, the SNP at the first intron, which identifies the Wx( a ) and Wx( b ) alleles, was associated with differences in the width of the grain, the L/W ratio and the length of the kernel, most likely as a result of human selection. Springer 2014-01-02 /pmc/articles/PMC3904453/ /pubmed/24383761 http://dx.doi.org/10.1186/1939-8433-7-1 Text en Copyright © 2014 Biselli et al.; licensee Springer. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Biselli, Chiara
Cavalluzzo, Daniela
Perrini, Rosaria
Gianinetti, Alberto
Bagnaresi, Paolo
Urso, Simona
Orasen, Gabriele
Desiderio, Francesca
Lupotto, Elisabetta
Cattivelli, Luigi
Valè, Giampiero
Improvement of marker-based predictability of Apparent Amylose Content in japonica rice through GBSSI allele mining
title Improvement of marker-based predictability of Apparent Amylose Content in japonica rice through GBSSI allele mining
title_full Improvement of marker-based predictability of Apparent Amylose Content in japonica rice through GBSSI allele mining
title_fullStr Improvement of marker-based predictability of Apparent Amylose Content in japonica rice through GBSSI allele mining
title_full_unstemmed Improvement of marker-based predictability of Apparent Amylose Content in japonica rice through GBSSI allele mining
title_short Improvement of marker-based predictability of Apparent Amylose Content in japonica rice through GBSSI allele mining
title_sort improvement of marker-based predictability of apparent amylose content in japonica rice through gbssi allele mining
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3904453/
https://www.ncbi.nlm.nih.gov/pubmed/24383761
http://dx.doi.org/10.1186/1939-8433-7-1
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