Dear all,
We have recently generated RRBS libraries and sequenced them. Although the CpG site coverage is acceptable (~1M with coverage > 10), we are puzzled by the alignment result. Enclosed figure shows the alignment results from two of our samples covering one fragment with MspI sites at both ends. However, we only detect reads deriving from positive strand for the first sample (coverage = 186 reads) and reads from negative strand for the second sample (coverage = 58reads). My understanding is that the positive and negative strand should be more or less equally amplified and we should be able to detect reads from both strands in each sample. The second figure shows the methylation value density for the CpG sites. It looks like the methylation levels are either 0% or 100%. Our concern is that reads mapped to each MspI digested fragment might all come from one template. Does it mean that we do not have sufficient representation due to sample loss during library preparation? I will be grateful for your help.
Best,
Jason
We have recently generated RRBS libraries and sequenced them. Although the CpG site coverage is acceptable (~1M with coverage > 10), we are puzzled by the alignment result. Enclosed figure shows the alignment results from two of our samples covering one fragment with MspI sites at both ends. However, we only detect reads deriving from positive strand for the first sample (coverage = 186 reads) and reads from negative strand for the second sample (coverage = 58reads). My understanding is that the positive and negative strand should be more or less equally amplified and we should be able to detect reads from both strands in each sample. The second figure shows the methylation value density for the CpG sites. It looks like the methylation levels are either 0% or 100%. Our concern is that reads mapped to each MspI digested fragment might all come from one template. Does it mean that we do not have sufficient representation due to sample loss during library preparation? I will be grateful for your help.
Best,
Jason
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