NESDB 2015-Talk-Functional Annotation of the Preimplantation Transcriptome
1.
2. Abstracts Selected for Talks
Functional Annotation of the Preimplantation Transcriptome
Wei Cui, Chelsea Marcho, Kun Zhang, Jesse Mager
University of Massachusetts Amherst, USA
With genome sequencing complete and transcriptome dynamics being illustrated quickly by
microarrays/RNA-seqs, understanding the roles of expressed genes is the next research frontier.
Although recent advances in RNA interference (RNAi) technologies allow for knockdown
screens in tissue culture cells, these in vitro approaches cannot replace strategies for discovery in
vivo. Here we present for the first time a large-scale double-stranded RNA (dsRNA) mediated
knockdown screen using mouse preimplantation embryos as an in vivo model system, as many
key events occur during this dynamic and clinically relevant developmental window. Candidate
genes comprise two classes, genes with dynamic changes of expression patterns during this
period and genes differentially expressed among epiblast, primitive endoderm and trophectoderm
lineages of blastocysts. To perform a high-throughput screen, we adopt a pooling strategy that 5
different dsRNAs are pooled for microinjection to knock down 5 distinct genes within the same
embryo. Subsequent embryos are cultured and assessed for A) morphological development to
blastocysts B) epigenetic regulation of genome imprinting and C) hatching from the zona
pellucida and embryonic stem cell derivation. After identification of pooled dsRNAs resulting in
phenotype, each individual dsRNA is microinjected to confirm which one in the pool is
responsible and the related functional role of the targeted gene. Our approach provides a robust
and efficient in vivo knockdown strategy towards identification of novel phenotypes as well as
functional requirements during mouse preimplantation development. We have screened 824
genes and identified 52 genes with preimplantation phenotypes most of which have not been
documented in early embryo development other than large-scale cDNA annotation projects.