Actually i have to check for effect of methylation on expression of each gene and i have rna seq and bs seq data
can i do like:
1.download gene ids from UCSC browser and then intersectBed with methylated sequence. this will give me methylated sites in each gene
2. then compare fpkm values of RNA seq data after mapping it by tophat
Am I thinking in the right path or not?
I need ur guidence. if not right plz let me knw
You have the correct idea:
1. Map WGBS -- I'd recommend methylpy https://bitbucket.org/schultzmattd/methylpy/wiki/Home
2. Filter the annotation file -- if you have one -- to only include CDS or exon coordinates
3. Use bedtools intersect to parse out regions from vcf (mapped WGBS) using modified annotation file
4. Calculate weighted methylation for each gene. Weighted methylation is the sum of the methylated reads divided by the number of total reads (methylated and un-methylated) for a certain cytosine sequence context. See below for more details on calculating methylation levels.
5. Map RNA-seq
6. Correlate methylation level and expression
There are lots of ways to look at methylation levels, and weighted methylation is the common one. Another common method is to bin genes by what type of methylation is enriched in the gene-body. For example, in plants genes are usually separated into gene-body (gbM; enrichment of CG methylation), CHG, CHH methylated, and un-methylated genes. This is done because of the difference mechanisms that methylate these sequence contexts. Usually binomial statistics are used to bin genes.
Each sequence context (in plants) shows very different relationships with gene expression. For example, gbM genes tend to be constitutively expressed, while CHH methylated genes tend to be silenced or active at very specific times/tissues during development.
Some helpful papers:
http://www.ncbi.nlm.nih.gov/pubmed/20395474
http://www.ncbi.nlm.nih.gov/pubmed/20395551
http://www.ncbi.nlm.nih.gov/pubmed/21813466
http://www.ncbi.nlm.nih.gov/pubmed/23467092
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