Abstract Background Jasmonates (JAs) are one of important phytohormones regulating potato tuber development. It is a complex process and the underlying molecular mechanism regulating tuber development by JAs is still limited. This study attempted to illuminate it through the potential proteomic dynamics information about tuber development in vitro regulated by exogenous JA. Results A combined analysis of physiological and iTRAQ (isobaric tags for relative and absolute quantification)-based proteomic approach was performed in tuber development in vitro under exogenous JA treatments (0, 0.5, 5 and 50 μΜ). Physiological results indicated that low JA concentration (especially 5 μM) promoted tuber development, whereas higher JA concentration (50 μM) showed inhibition effect. A total of 257 differentially expressed proteins (DEPs) were identified by iTRAQ, which provided a comprehensive overview on the functional protein profile changes of tuber development regulated by JA. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis indicated that low JA concentration (especially 5 μM) exhibited the promotion effects on tuber development in various cellular processes. Some cell wall polysaccharide synthesis and cytoskeleton formation-related proteins were up-regulated by JA to promote tuber cell expansion. Some primary carbon metabolism-related enzymes were up-regulated by JA to provide sufficient metabolism intermediates and energy for tuber development. And, a large number of protein biosynthesis, degradation and assembly-related were up-regulated by JA to promote tuber protein biosynthesis and maintain strict protein quality control during tuber development. Conclusions This study is the first to integrate physiological and proteomic data to provide useful information about the JA-signaling response mechanism of potato tuber development in vitro. The results revealed that the levels of a number of proteins involved in various cellular processes were regulated by JA during tuber development. The proposed hypothetical model would explain the interaction of these DEPs that associated with tuber development in vitro regulated by JA.

马铃薯块茎产量性状复杂,由多个产量组分构成.为探究马铃薯块茎不同顶端优势类型、植株主茎数和产量组分的相关性,本研究对国际马铃薯中心引进的102份高代品系块茎的发芽情况进行筛选,以12个顶端优势强弱程度不同的马铃薯品系为试验材料,在马铃薯植株盛花期测定主茎数;收获期统计小区产量、小区大薯产量、小区小薯产量、单株产量、单株大薯产量、单株小薯产量、单株结薯数、单株大薯数、单株小薯数;贮藏期测定芽眼个数、发芽个数、发芽长度等,分析马铃薯块茎不同顶端优势类型与植株主茎数及产量组分的相关性.结果表明,12个马铃薯品系根据块茎的发芽情况可分为四种顶端优势类型.对发芽率和发芽长度的分析结果表明,四种顶端优势类型马铃薯品系的发芽率存在显著差异,发芽长度在第90天时差异不显著.对主茎数、小区产量、小区大薯产量、小区小薯产量、单株产量、单株大薯产量、单株小薯产量、单株结薯数、单株大薯数、单株小薯数的分析表明,四种顶端优势类型马铃薯品系的主茎数、小区产量、小区大薯产量、单株产量、单株大薯产量、单株小薯产量、单株结薯数、单株大薯数、单株小薯数差异显著,小区小薯产量差异不显著.方差分析表明,马铃薯块茎顶端优势显著影响植株主茎数及产量组分中的单株小薯产量、单株结薯数、单株大薯数、单株小薯数.相关性分析表明,主茎数与单株结薯数等产量组分无显著相关性.本试验研究了马铃薯产量组分中不同性状之间的相关性,对于结薯特性不同的品种的选育,不同结薯类型品种在生产中采用不同的栽培模式,以及提高田间管理效率和促进产量增加均具有重要意义.

This study mainly focused on the application of GGE (genotype + genotypes and environment interactions) biplot in potato breeding, to evaluate the productivity, stability and adaptability of yield traits of potato lines in different environments comprehensively, and screen out the excellent lines adapted to different mage-environments.The representativeness and discriminating ability of each test-environment were also evaluated, providing a basis for the selection of test-environment.A total of 101 advanced lines from International Potato Center (CIP) and potato variety Qingshu 9 were planted in Neiguan Town, Lujiagou Town and Wuzhu Town of Gansu province in 2015 and 2016 to measure the plot yield, plot yield of large-sized tubers, plot yield of small-sized tubers, yield per plant, large-sized tuber yield per plant, small-sized tuber yield per plant, tuber number per plant, large-sized tuber number per plant and small-sized tuber number per plant.The genotype and environment interactions were analyzed by the combined analysis of variance and GGE biplot.Except the plot yield of small-sized tubers had no significant difference in genotype and environment interactions effect, all the other yield components had significant differences (P < 0.01) in genotype effect, environmental effect and genotype and environment interaction effect.The square sum of environmental effect on the plot yield, plot yield of large-sized tubers, plot yield of small-sized tubers, yield per plant, large-sized tuber yield per plant, tuber number per plant, and the square sum of genotype and environment interaction effect on the plot yield of small-sized tubers, the large-sized tuber number per plant, and the small-sized tuber number per plant were worth the largest in the square sum of total variance.The most adaptable lines in Lujiagou Town were G86, in Wuzhu Town G65, in Neiguan Town G86.The high-yield lines were G86, G116, and G124; the stable-yield lines were G124, G125, and G10; the high-yielding and stable lines were G86, G116, G124, and Qingshu 9.The lines with more large-sized tuber number per plant were G45, G86, and G67, and the lines with good stability were G67, G116, and G51.The variety Qingshu 9 did not have stable large-sized tuber yield per plant.According to the comprehensive discrimination and representativeness, the order of test-environments were Lujiagou Town in 2016, Lujiagou Town in 2015, Wuzhu Town in 2015, Wuzhu Town in 2016, Neiguan Town in 2015, and Neiguan Town in 2016.GGE model can intuitively display the results in the genotype-location-year framework, and objectively evaluate the productivity, stability and adaptability of tested lines, as well as the representativeness and discriminating ability of test-environment.According to the comprehensive evaluation of GGE model, the high-yielding and stable lines were G116, G124, G125, G122, and Qingshu 9, and the high-yielding and unstable lines were G86, G10, G121, G106, G107, and G72.The most ideal mage-environment is Lujiagou Town, and Wuzhu Town is the test-environment with the strongest discriminating ability for varieties identification.