Treatments which upregulate more genes than they downregulate?
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7.1 years ago
mbabic • 0

A slightly strange question, I know, but - can anyone suggest specific cell culture treatments which would result in many more genes (especially low expressing genes) being upregulated than downregulated?

I'm essentially looking for "I noticed significant increases in transcription when I treated cell line X with compound Y in manner Z."

RNA-Seq • 1.9k views
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For any cell-type and cell-line?

Sure, treat MCF7 breast cancer cells with estradiol (E2) and you'll see the 'entire' (or virtually entire, thereof) transcriptome up-regulated. This highlights the potency of oestrogen signalling in regulating transcription.

Other 'master' transcription up-regulators include MYC and p210.

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Thank you! Do you have any recommendations on which treatments would be best for hitting MYC or p210?

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For MYC and p210, you may want to look through the methods for our published work: Lineage-Specific Genes Are Prominent DNA Damage Hotspots during Leukemic Transformation of B Cell Precursors.

We (not me, as I was just one of the analysts) created cell models in which MYC and p210 were up-regulated. The downside of up-regulating these potent transcription factors, though, is that the increased transcription also results in increased DNA damage. For example, estradiol, MYC, and p210 increase rates of DNA double-strand breaks. In breast tissue and breast cancer, this highlights the importance of BRCA1, a DNA double-strand break repair protein, in breast tissue, which is responsive to estradiol and which is frequently dosed with high levels of estradiol in the menstrual cycle. I also wrote about this particular topic and area.

You may want to reach out to the lead author of our MYC and p210 study if you want specifics on how the MYC and p210 models were constructed. Mention my name and he'll know who I am.

Kevin

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Thank you, I will certainly look into it.

I greatly appreciate everyone's answers. This is a great community, I can't believe I just discovered its existence.

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Curious, how are you planning to measure the significant, global, increases in transcription? If using methods like RNA-Seq or arrays, standard ways of normalizing that data make an assumption that overall average gene expression levels remain constant, so may not be able to reliably quantify global increases, even if you can induce them. Using spike-in normalization standards is one way to address this. Good luck with your experiments.

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Hi Ahill - I will be using TempO-Seq, which skips all normalization steps (it uses straight cell lysate as input, and works on a huge dynamic range, down to single cell). However, the purpose of this is not measurement, it is production of signal >0 for as many genes as possible for a small side "sanity check" experiment.

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