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Publications - Molecular Signal Processing

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Dekkers, B.J.W.; Pearce, S.; van Bolderen-Veldkamp, R.P.; Marshall, A.; Widera, P.; Gilbert, J.; Drost, H.-G.; Basseli, G.W.; Müller, K.; King, J.R.; Wood, A.T.A.; Grosse, I.; Quint, M.; Krasnogor, N.; Leubner-Metzger, G.; Holdsworth, M.J. & Bentsink, L. Transcriptional Dynamics of Two Seed Compartments with Opposing Roles in Arabidopsis Seed Germination Plant Physiol 163, 205-215, (2013) DOI: 10.1104/pp.113.223511

Seed germination is a critical stage in the plant life cycle and the first step toward successful plant establishment. Therefore, understandinggermination is of important ecological and agronomical relevance. Previous research revealed that different seed compartments (testa,endosperm, and embryo) control germination, but little is known about the underlying spatial and temporal transcriptome changes thatlead to seed germination. We analyzed genome-wide expression in germinating Arabidopsis (Arabidopsis thaliana) seedswith both temporaland spatial detail and provide Web-accessible visualizations of the data reported (vseed.nottingham.ac.uk). We show the potential of this highresolutiondata set for the construction ofmeaningful coexpression networks, which provide insight into the genetic control of germination.The data set reveals two transcriptional phases during germination that are separated by testa rupture. The first phase is marked by largetranscriptome changes as the seed switches from a dry, quiescent state to a hydrated and active state. At the end of this first transcriptionalphase, the number of differentially expressed genes between consecutive time points drops. This increases again at testa rupture, the start ofthe second transcriptional phase. Transcriptome data indicate a role for mechano-induced signaling at this stage and subsequently highlightthe fates of the endosperm and radicle: senescence and growth, respectively. Finally, using a phylotranscriptomic approach, we show thatexpression levels of evolutionarily young genes drop during the first transcriptional phase and increase during the second phase.Evolutionarily old genes show an opposite pattern, suggesting a more conserved transcriptome prior to the completion of germination.

Poeschl, Y.; Delker, C.; Trenner, J.; Ullrich, K.; Quint, M. & Grosse, I. Optimized Probe Masking for Comparative Transcriptomics of Closely Related Species PLOS ONE 8, e78497, (2013) DOI: 10.1371/journal.pone.0078497

Microarrays are commonly applied to study the transcriptome of specific species. However, many available microarrays arerestricted to model organisms, and the design of custom microarrays for other species is often not feasible. Hence,transcriptomics approaches of non-model organisms as well as comparative transcriptomics studies among two or morespecies often make use of cost-intensive RNAseq studies or, alternatively, by hybridizing transcripts of a query species to amicroarray of a closely related species. When analyzing these cross-species microarray expression data, differences in thetranscriptome of the query species can cause problems, such as the following: (i) lower hybridization accuracy of probes dueto mismatches or deletions, (ii) probes binding multiple transcripts of different genes, and (iii) probes binding transcripts ofnon-orthologous genes. So far, methods for (i) exist, but these neglect (ii) and (iii). Here, we propose an approach forcomparative transcriptomics addressing problems (i) to (iii), which retains only transcript-specific probes binding transcriptsof orthologous genes. We apply this approach to an Arabidopsis lyrata expression data set measured on a microarraydesigned for Arabidopsis thaliana, and compare it to two alternative approaches, a sequence-based approach and a genomicDNA hybridization-based approach. We investigate the number of retained probe sets, and we validate the resultingexpression responses by qRT-PCR. We find that the proposed approach combines the benefit of sequence-based stringencyand accuracy while allowing the expression analysis of much more genes than the alternative sequence-based approach. Asan added benefit, the proposed approach requires probes to detect transcripts of orthologous genes only, which provides asuperior base for biological interpretation of the measured expression responses.
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