Refining transcriptional programs in kidney development by integration of deep RNA-sequencing and array-based spatial profiling

Thiagarajan, Rathi D., Cloonan, Nicole, Gardiner, Brooke B., Mercer, Tim R., Kolle, Gabriel, Nourbaksh, Ehsan, Wani, Shivangi, Tang, Dave, Krishnan, Keerthana, Georgas, Kylie M., Rumballe, Bree A., Chiu, Han S., Steen, Jason A., Mattick, John S., Little, Melissa H. and Grimmond, Sean M. (2011) Refining transcriptional programs in kidney development by integration of deep RNA-sequencing and array-based spatial profiling. BMC Genomics, 12 441-1-441-16. doi:10.1186/1471-2164-12-441

Author Thiagarajan, Rathi D.
Cloonan, Nicole
Gardiner, Brooke B.
Mercer, Tim R.
Kolle, Gabriel
Nourbaksh, Ehsan
Wani, Shivangi
Tang, Dave
Krishnan, Keerthana
Georgas, Kylie M.
Rumballe, Bree A.
Chiu, Han S.
Steen, Jason A.
Mattick, John S.
Little, Melissa H.
Grimmond, Sean M.
Title Refining transcriptional programs in kidney development by integration of deep RNA-sequencing and array-based spatial profiling
Journal name BMC Genomics   Check publisher's open access policy
ISSN 1471-2164
Publication date 2011-09-05
Sub-type Article (original research)
DOI 10.1186/1471-2164-12-441
Open Access Status DOI
Volume 12
Start page 441-1
End page 441-16
Total pages 16
Place of publication London, United Kingdom
Publisher BioMed Central
Collection year 2012
Language eng
Formatted abstract
Background: The developing mouse kidney is currently the best-characterized model of organogenesis at a transcriptional level. Detailed spatial maps have been generated for gene expression profiling combined with systematic in situ screening. These studies, however, fall short of capturing the transcriptional complexity arising from each locus due to the limited scope of microarray-based technology, which is largely based on "gene-centric" models.
Results: To address this, the polyadenylated RNA and microRNA transcriptomes of the 15.5 dpc mouse kidney were profiled using strand-specific RNA-sequencing (RNA-Seq) to a depth sufficient to complement spatial maps from pre-existing microarray datasets. The transcriptional complexity of RNAs arising from mouse RefSeq loci was catalogued; including 3568 alternatively spliced transcripts and 532 uncharacterized alternate 3' UTRs. Antisense expressions for 60% of RefSeq genes was also detected including uncharacterized non-coding transcripts overlapping kidney progenitor markers, Six2 and Sall1, and were validated by section in situ hybridization. Analysis of genes known to be involved in kidney development, particularly during mesenchymal-to-epithelial transition, showed an enrichment of non-coding antisense transcripts extended along protein-coding RNAs.
Conclusion: The resulting resource further refines the transcriptomic cartography of kidney organogenesis by integrating deep RNA sequencing data with locus-based information from previously published expression atlases. The added resolution of RNA-Seq has provided the basis for a transition from classical gene-centric models of kidney development towards more accurate and detailed "transcript-centric" representations, which highlights the extent of transcriptional complexity of genes that direct complex development events.
Keyword RNA-Seq
Kidney development
Sense-antisense transcripts
Alternative splicing
Mesenchymal-epthilial transition
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Article no. 441

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2012 Collection
Institute for Molecular Bioscience - Publications
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Citation counts: TR Web of Science Citation Count  Cited 15 times in Thomson Reuters Web of Science Article | Citations
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Created: Mon, 10 Oct 2011, 15:16:30 EST by Kylie Georgas on behalf of Institute for Molecular Bioscience