Single Oocyte Genomics
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Advancements in high throughput sequencing and mRNA linear amplification have facilitated the ability to measure full transcriptome from low amounts of RNA. This technological advancement now enables the evaluation of the expression of every gene in a single cell. Yet, although these tools revolutionized studies in many systems, it has been impossible to use them in some biological tissues. The nuclei in the C. elegans gonad are arranged in a perfect temporal manner yet they all share the same cytoplasm (syncytium). Thus, although it is possible to find all the meiotic stages in a single gonad arm, it has so far been impossible to analyze the transcriptome in a single nucleus.
Together with colleagues, we developed a method to overcome this hurdle and we now have full transcriptome data for every stage of oocyte development. We are mining these datasets and have found surprising results. We intend to continue using this method to find changes in transcription under different conditions and genetic backgrounds.
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Open questions and current work:
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Repeat the collection of gonads of aging worms
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Measure the level of expression of every gene in different meiotic and aging stages
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Find the gene expression changes that occur in human oocytes
Students with strong background in computational biology and data mining are encouraged to join us to work on this exciting project.
Spatial transcriptomics: Illustration of the C. elegans gonad and the 10 consecutive sections we captured using Laser Capture Microdissection. Following RNASeq the stdandardized expression (y axis) was color coded for each gene in the autosomes and the X chromosome along the 10 sections (x axis)
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