Evidence map›Paper›PMID 17212830›Full record

ArticleBMC genomics2007

A multi-treatment experimental system to examine photosynthetic differentiation in the maize leaf.

Ruairidh J H Sawers, Peng Liu, Katya Anufrikova, J T Gene Hwang, Thomas P Brutnell

Abstract read
In one paragraph

Article in BMC genomics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

32 citing papers in PubMed.

  1. Article
  2. Review
  3. Plant engineering: advances, bottlenecks, and promise.The Plant journal : for cell and molecular biology · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Ruairidh J H SawersBoyce Thompson Institute, Cornell University, Tower Road, Ithaca, NY 14853, USA. Ruairidh.Sawers@unil.ch <Ruairidh.Sawers@unil.ch>
Peng Liu
Katya Anufrikova
J T Gene Hwang
Thomas P Brutnell

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe establishment of C4 photosynthesis in maize is associated with differential accumulation of gene transcripts and proteins between bundle sheath and mesophyll photosynthetic cell types. We have physically separated photosynthetic cell types in the leaf blade to characterize differences in gene expression by microarray analysis. Additional control treatments were used to account for transcriptional changes induced by cell preparation treatments. To analyse these data, we have developed a statistical model to compare gene expression values derived from multiple, partially confounded, treatment groups.

resultsDifferential gene expression in the leaves of wild-type maize seedlings was characterized using the latest release of a maize long-oligonucleotide microarray produced by the Maize Array Project consortium. The complete data set is available through the project web site. Data is also available at the NCBI GEO website, series record GSE3890. Data was analysed with and without consideration of cell preparation associated stress.

conclusionEmpirical comparison of the two analyses suggested that consideration of stress helped to reduce the false identification of stress responsive transcripts as cell-type enriched. Using our model including a stress term, we identified 8% of features as differentially expressed between bundle sheath and mesophyll cell types under control of false discovery rate of 5%. An estimate of the overall proportion of differentially accumulating transcripts (1-pi0) suggested that as many as 18% of the genes may be differentially expressed between B and M. The analytical model presented here is generally applicable to gene expression data and demonstrates the use of statistical elimination of confounding effects such as stress in the context of microarray analysis. We discuss the implications of the high degree of differential transcript accumulation observed with regard to both the establishment and engineering of the C4 syndrome.

Indexed as

Gene Expression Regulation, PlantPhotosynthesisPlant Physiological PhenomenaBotanyModels, StatisticalOligonucleotide Array Sequence AnalysisPlant LeavesRibulose-Bisphosphate CarboxylaseRNAZea maysRibulose-Bisphosphate CarboxylaseRNA

Identifiers

PMID17212830
PMCPMC1790712

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.