Vadim K Khlestkin1,2, Irina V Rozanova3, Vadim M Efimov3,4, Elena K Khlestkina3,4,5. 1. Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Lavrentjeva Ave. 10, Novosibirsk, 630090, Russia. khlestkin@bionet.nsc.ru. 2. Russian Research Institute of Farm Animal Genetics and Breeding - Branch of the L.K. Ernst Federal Science Center for Animal Husbandry, St. Peterburg-Tyarlevo, Moskovskoe shosse, 55a, 196625, Russia. khlestkin@bionet.nsc.ru. 3. Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Lavrentjeva Ave. 10, Novosibirsk, 630090, Russia. 4. Novosibirsk State University, Pirogova Str., 1, Novosibirsk, 630090, Russia. 5. N.I. Vavilov All-Russian Research Institute of Plant Genetic Resources (VIR), Bolshaya Morskaya Str., 42-44, St. Petersburg, 190000, Russia.
Abstract
BACKGROUND: The natural variation of starch phosphate content in potatoes has been previously reported. It is known that, in contrast to raw starch, commercially phosphorylated starch is more stable at high temperatures and shear rates and has higher water capacity. The genetic improvement of phosphate content in potato starch by selection or engineering would allow the production of phosphorylated starch in a natural, environmentally friendly way without chemicals. The aim of the current research is to identify genomic SNPs associated with starch phosphorylation by carrying out a genome-wide association study in potatoes. RESULTS: A total of 90 S. tuberosum L. varieties were used for phenotyping and genotyping. The phosphorus content of starch in 90 potato cultivars was measured and then statistically analysed. Principal component analysis (PCA) revealed that the third and eighth principal components appeared to be sensitive to variation in phosphorus content (p = 0.0005 and p = 0.002, respectively). PC3 showed the correlation of starch phosphorus content with allelic variations responsible for higher phosphorylation levels, found in four varieties. Similarly, PC8 indicated that hybrid 785/8-5 carried an allele associated with high phosphorus content, while the Impala and Red Scarlet varieties carried alleles for low phosphorus content. Genotyping was carried out using an Illumina 22 K SNP potato array. A total of 15,214 scorable SNPs (71.7% success rate) was revealed. GWAS mapping plots were obtained using TASSEL based on several statistical models, including general linear models (GLMs), with and without accounting for population structure, as well as MLM. A total of 17 significant SNPs was identified for phosphorus content in potato starch, 14 of which are assigned to 8 genomic regions on chromosomes 1, 4, 5, 7, 8, 10, and 11. Most of the SNPs identified belong to protein coding regions; however, their allelic variation was not associated with changes in protein structure or function. CONCLUSIONS: A total of 8 novel genomic regions possibly associated with starch phosphorylation on potato chromosomes 1, 4, 5, 7, 8, 10, and 11 was revealed. Further validation of the SNPs identified and the analysis of the surrounding genomic regions for candidate genes will allow better understanding of starch phosphorylation biochemistry. The most indicative SNPs may be useful for developing diagnostic markers to accelerate the breeding of potatoes with predetermined levels of starch phosphorylation.
BACKGROUND: The natural variation of starch phosphate content in potatoes has been previously reported. It is known that, in contrast to raw starch, commercially phosphorylated starch is more stable at high temperatures and shear rates and has higher water capacity. The genetic improvement of phosphate content in potatostarch by selection or engineering would allow the production of phosphorylated starch in a natural, environmentally friendly way without chemicals. The aim of the current research is to identify genomic SNPs associated with starch phosphorylation by carrying out a genome-wide association study in potatoes. RESULTS: A total of 90 S. tuberosum L. varieties were used for phenotyping and genotyping. The phosphorus content of starch in 90 potato cultivars was measured and then statistically analysed. Principal component analysis (PCA) revealed that the third and eighth principal components appeared to be sensitive to variation in phosphorus content (p = 0.0005 and p = 0.002, respectively). PC3 showed the correlation of starch phosphorus content with allelic variations responsible for higher phosphorylation levels, found in four varieties. Similarly, PC8 indicated that hybrid 785/8-5 carried an allele associated with high phosphorus content, while the Impala and Red Scarlet varieties carried alleles for low phosphorus content. Genotyping was carried out using an Illumina 22 K SNP potato array. A total of 15,214 scorable SNPs (71.7% success rate) was revealed. GWAS mapping plots were obtained using TASSEL based on several statistical models, including general linear models (GLMs), with and without accounting for population structure, as well as MLM. A total of 17 significant SNPs was identified for phosphorus content in potatostarch, 14 of which are assigned to 8 genomic regions on chromosomes 1, 4, 5, 7, 8, 10, and 11. Most of the SNPs identified belong to protein coding regions; however, their allelic variation was not associated with changes in protein structure or function. CONCLUSIONS: A total of 8 novel genomic regions possibly associated with starch phosphorylation on potato chromosomes 1, 4, 5, 7, 8, 10, and 11 was revealed. Further validation of the SNPs identified and the analysis of the surrounding genomic regions for candidate genes will allow better understanding of starch phosphorylation biochemistry. The most indicative SNPs may be useful for developing diagnostic markers to accelerate the breeding of potatoes with predetermined levels of starch phosphorylation.
Authors: Peter J Bradbury; Zhiwu Zhang; Dallas E Kroon; Terry M Casstevens; Yogesh Ramdoss; Edward S Buckler Journal: Bioinformatics Date: 2007-06-22 Impact factor: 6.937
Authors: Xuan Xu; Dianka Dees; Annemarie Dechesne; Xing-Feng Huang; Richard G F Visser; Luisa M Trindade Journal: Carbohydr Polym Date: 2016-11-14 Impact factor: 9.381
Authors: Natalia Carreno-Quintero; Animesh Acharjee; Chris Maliepaard; Christian W B Bachem; Roland Mumm; Harro Bouwmeester; Richard G F Visser; Joost J B Keurentjes Journal: Plant Physiol Date: 2012-01-05 Impact factor: 8.340
Authors: Sebastian Mahlow; Mahdi Hejazi; Franziska Kuhnert; Andreas Garz; Henrike Brust; Otto Baumann; Joerg Fettke Journal: New Phytol Date: 2014-04-03 Impact factor: 10.151
Authors: Margaret A Carpenter; Nigel I Joyce; Russell A Genet; Rebecca D Cooper; Sarah R Murray; Alasdair D Noble; Ruth C Butler; Gail M Timmerman-Vaughan Journal: Front Plant Sci Date: 2015-03-10 Impact factor: 5.753
Authors: Peter G Vos; Jan G A M L Uitdewilligen; Roeland E Voorrips; Richard G F Visser; Herman J van Eck Journal: Theor Appl Genet Date: 2015-08-12 Impact factor: 5.699