Transcriptional Milestones in Dictyostelium Development

Authors

Mariko Katoh-Kurasawa
Karin Hrovatin
Shigenori Hirose
Amanda Webb
Hsing-I Ho
Blaž Zupan
Gad Shaulsky

Publication Date

8-1-2021

Journal

Genome Research

DOI

10.1101/gr.275496.121

PMID

34183452

PMCID

PMC8327917

PubMedCentral® Posted Date

8-31-2021

PubMedCentral® Full Text Version

Post-print

Published Open-Access

yes

Keywords

Dictyostelium, Morphogenesis, RNA, Messenger, Regulon, Software

Abstract

Dictyostelium development begins with single-cell starvation and ends with multicellular fruiting bodies. Developmental morphogenesis is accompanied by sweeping transcriptional changes, encompassing nearly half of the 13,000 genes in the genome. We performed time-series RNA-sequencing analyses of the wild type and 20 mutants to explore the relationships between transcription and morphogenesis. These strains show developmental arrest at different stages, accelerated development, or atypical morphologies. Considering eight major morphological transitions, we identified 1371 milestone genes whose expression changes sharply between consecutive transitions. We also identified 1099 genes as members of 21 regulons, which are groups of genes that remain coordinately regulated despite the genetic, temporal, and developmental perturbations. The gene annotations in these groups validate known transitions and reveal new developmental events. For example, DNA replication genes are tightly coregulated with cell division genes, so they are expressed in mid-development although chromosomal DNA is not replicated. Our data set includes 486 transcriptional profiles that can help identify new relationships between transcription and development and improve gene annotations. We show its utility by showing that cycles of aggregation and disaggregation in allorecognition-defective mutants involve dedifferentiation. We also show sensitivity to genetic and developmental conditions in two commonly used actin genes, act6 and act15, and robustness of the coaA gene. Finally, we propose that gpdA is a better mRNA quantitation standard because it is less sensitive to external conditions than commonly used standards. The data set is available for democratized exploration through the web application dictyExpress and the data mining environment Orange.

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