Comparative proteomics analysis by DIGE and iTRAQ provides insight into the regulation of phenylpropanoids in maize

Robbins, Michael L.; Roy, Ansuman; Wang, Po Hao; Gaffoor, Iffa; Sekhon, Rajandeep S.; Buanafina, Marcia M. de O.; Rohila, Jai S.; Chopra, Surinder

doi:10.1016/j.jprot.2013.06.018

Cited by 32 publications

(28 citation statements)

References 77 publications

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“…The pericarp color1 (p1) gene encoding an R2R3 Myb-like transcription factor (Grotewold et al 1994) regulates flavonoid biosynthesis by promoting a suite of structural genes, and conditions pigment in several floral organs (Coe Jr et al 1988) including the seed coat, cob glumes, tassel glumes, and silk under both genetic and epigenetic regulation mechanisms (Grotewold et Robbins et al 2013). In this study, the quantification of 39 flavonoid metabolites together with cob color were used for GWAS, and results indicated the ePAV pattern of the p1 gene was highly associated with cob color (P=1.33E-19), and was correlated with six different flavonoid metabolites (P<2.34E-05; Fig 2a).…”

Section: Maize Pan-transcriptome Plays An Important Role In Regulatinmentioning

confidence: 99%

Maize pan-transcriptome provides novel insights into genome complexity and quantitative trait variation

Jin

Liu

et al. 2015

Preprint

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Variation in gene expression contributes to the diversity of phenotype. The construction of the pan-transcriptome is especially necessary for species with complex genomes, such as maize. However, knowledge of the regulation mechanisms and functional consequences of the pan-transcriptome is limited. In this study, we identified 13,382 nuclear expression presence and absence variation candidates (ePAVs, expressed in 5%~95% lines; based on the reference genome) by re-analyzing the RNA sequencing data from the kernels (15 days after pollination) of 368 maize diverse inbreds. It was estimated that only ~1% of the ePAVs are explained by DNA sequence presence and absence variations (PAV). The ePAV genes tend to be regulated by distant eQTLs when compared with non-ePAV genes (called here core expression genes, expressed in more than 95% lines). When the expression presence/absence status was used as the "genotype" to perform genome-wide association study, 56 (0.42%) ePAVs were significantly associated with 15 agronomic traits and 1,967 (14.74%) with 526 metabolic traits, measured from the mature kernels. While the above was majorly based on the reference genome, by using a modified 'assemble-then-align' strategy, 2,355 high confidence novel sequences with a total length of 1.9Mb were found absent in the current B73 reference genome (v2). Ten randomly selected novel sequences were validated with genomic PCR. A simulation analysis suggested that the pan-transcriptome of the maize whole kernel is approaching a maximum value of 63,000 genes. Two novel validated sequences annotated as NBS_LRR like genes were found to associate with flavonoid content and their homologs in rice were also found to affect flavonoids and disease-resistance. Novel sequences absent in the present reference genome might be functionally important and deserve more attentions. This study provides novel perspectives and resources to discover maize quantitative trait variations and help us to better understand the kernel regulation networks, thus enhancing maize breeding.

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Section: Maize Pan-transcriptome Plays An Important Role In Regulatinmentioning

confidence: 99%

Maize pan-transcriptome provides novel insights into genome complexity and quantitative trait variation

Jin

Liu

et al. 2015

Preprint

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“…We observed several defects in the form of plant stunting, leaf rolling, and reduced plant height. We previously showed that plant bending could be due to reduced lignin accumulation in Ufo1-1 plants (Robbins et al, 2013). Ufo1-1 plants were ;10 inches shorter on average than their wild-type siblings in a backcross population ( Figure 1C).…”

Section: Ufo1-1 Plants Are Stunted Exhibit Delayed Flowering and Shmentioning

confidence: 84%

“…Additionally, Ufo1-1 plants can display a range of pleiotropic defects, such as short stature and bent plants (Chopra et al, 2003). Robbins et al (2013) demonstrated that some of the bending defects of Ufo1-1 plants could be due to reduced lignin content in the plant body. It has been suggested that the excess pigments may have a deleterious effect on plant growth, causing defects (Chopra et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

The Dominant and Poorly Penetrant Phenotypes of Maize Unstable factor for orange1 Are Caused by DNA Methylation Changes at a Linked Transposon

et al. 2018

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The maize (Zea mays) mutant Unstable factor for orange1 (Ufo1) has been implicated in the epigenetic modifications of pericarp color1 (p1), which regulates the production of the flavonoid pigments phlobaphenes. Here, we show that the ufo1 gene maps to a genetically recalcitrant region near the centromere of chromosome 10. Transcriptome analysis of Ufo1-1 mutant and wild-type plants identified a candidate gene in the mapping region using a comparative sequence-based approach. The candidate gene, GRMZM2G053177, is overexpressed by >45-fold in multiple tissues of Ufo1-1, explaining the dominance of Ufo1-1 and its phenotypes. In the mutant stock, GRMZM2G053177 has a unique transcript originating within a CACTA transposon inserted in its first intron, and it is missing the first four codons of the wild-type transcript. GRMZM2G053177 expression is regulated by the DNA methylation status of the CACTA transposon, explaining the incomplete penetrance and poor expressivity of Ufo1-1. Transgenic overexpression lines of GRMZM2G053177 (Ufo1-1) phenocopy the p1-induced pigmentation in coleoptiles, tassels, leaf sheaths, husks, pericarps, and cob glumes. Transcriptome analysis of Ufo1 versus wild-type tissues revealed changes in several pathways related to abiotic and biotic stress. Thus, this study addresses the enigma of Ufo1 identity in maize, which had gone unsolved for more than 50 years.

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“…Differential proteomics methods that better perform than single staining 2-DE have also been applied to conduct discovery studies in plant SM. These include differential in gel electrophoresis (DIGE), as a top-down protein-centric approach ( Martínez-Esteso et al, 2011c ; Champagne et al, 2012 ; Corchete and Bru, 2013 ), and isobaric tags for relative and absolute quantitation (iTRAQ) ( Martínez-Esteso et al, 2011b , 2013 ; Robbins et al, 2013 ) and label-free ( Oldham et al, 2010 ), as bottom-up peptide-centric approaches. DIGE has allowed the identification of three TIA biosynthetic enzymes in Catharanthus roseus cell cultures and five others that are putatively involved in the pathway among the 172 identified deregulated proteins ( Champagne et al, 2012 ).…”

Section: Proteomic Strategies and Approaches In Secondary Metabolismmentioning

confidence: 99%

The role of proteomics in progressing insights into plant secondary metabolism

et al. 2015

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The development of omics has enabled the genome-wide exploration of all kinds of biological processes at the molecular level. Almost every field of plant biology has been analyzed at the genomic, transcriptomic and proteomic level. Here we focus on the particular contribution that proteomic technologies have made in progressing knowledge and characterising plant secondary metabolism (SM) pathways since early expectations were created 15 years ago. We analyzed how three major issues in the proteomic analysis of plant SM have been implemented in various research studies. These issues are: (i) the selection of a suitable plant material rich in secondary metabolites of interest, such as specialized tissues and organs, and in vitro cell cultures; (ii) the proteomic strategy to access target proteins, either a comprehensive or a differential analysis; (iii) the proteomic approach, represented by the hypothesis-free discovery proteomics and the hypothesis-driven targeted proteomics. We also examine to what extent the most-advanced technologies have been incorporated into proteomic research in plant SM and highlight some cutting edge techniques that would strongly benefit the progress made in this field.

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Comparative proteomics analysis by DIGE and iTRAQ provides insight into the regulation of phenylpropanoids in maize

Cited by 32 publications

References 77 publications

Maize pan-transcriptome provides novel insights into genome complexity and quantitative trait variation

Maize pan-transcriptome provides novel insights into genome complexity and quantitative trait variation

The Dominant and Poorly Penetrant Phenotypes of Maize Unstable factor for orange1 Are Caused by DNA Methylation Changes at a Linked Transposon

The role of proteomics in progressing insights into plant secondary metabolism

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