Question about Gene ID with different Transcription ID

Question

[jeonsangjun]

Hi I am new to the field and I am currently stuck on deciding how to deal with different Transcription ID of a given Gene ID.

I have a data sheet containing FPKM values from RNAseq analysis of mouse cancer cell line grown in different conditions (4 samples) and I want to compare the gene expression values across the samples.

In the data file I have, most genes have several different transcript Ids and from my understanding is that a given gene can be transcribed into several different proteins due to alternative splicing, and the resulting proteins may or may not have the same function from one another.

If I want to compare the expression level of a gene across the 4 samples, would it be logical to add all the FPKM values of each different transcription ID of a given gene and compare the sum value to different samples or would it be a better choice to leave the FPKM values separately for each transcriptions?

I'm not sure if I explained my situation clearly enough but I would appreciate any input on the matter

Thank you in advance!

Answer 1

[ashish]

Do not add FPKM values from each transcripts, leave them as they are. Look at individual transcripts and their annotations, many genes code for different transcripts which will have different functions. Also, you will do real time PCR on transcripts not on the gene, so stick to the transcripts. When a gene can be called differentially expressed is actually a debatable topic. There can be two cases: 1. All transcripts of a gene are differentially expressed. 2. Only one out of say three transcripts is differentially expressed.

In which case would you call the gene differentially expressed, both of them, but better resolution is achieved when you look at individual transcripts instead of genes. That's why the newer and faster tools such as salmon map reads to the transcriptome instead of the genome.