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Failure of tumor FFPE samples sequencing
Dear all,
I am a PhD student in Belgium, Brussels, working on RNA sequencing of ~130 tumoral FFPE samples. My samples date from 2005 to 2017. I am new to RNA sequencing and ask you in advance to forgive me for potential simple questions.
I extracted RNA + DNA with AllPrep FFPE kit from Qiagen, for all samples.
We wanted to look for whole transcriptome analysis
From there, we began with a run of 36 samples to test libraries and sequencing.
RiboZero libraries were prepared (use of RNA clean XP beads+AMPure XP Beads)
and NovaSeq was performed for 25M reads.
The results are disappointing. Duplicate mapping attain 98% for some samples, and unique mapping is often no higher than 3%. I don't have the DV200 values here but the profiles are flat.
Here are some clues given by colleagues :
-Ribozero is still dependent on samples quality. If it didn't work on the sample and too many reads are taken by ribosomal RNA, we should change the library method, for example for a polyA library, which is said to be better for extremely degraded RNA. But this would restrict the whole transcriptome objective.
-Pass to panel-methods such as Nanostring, said to be better for highly degraded FFPE samples. Though I was told about sequencing error rate that is higher ?
I would hihly appreciate any feedback or advice on this ! Thank you very much
I am a PhD student in Belgium, Brussels, working on RNA sequencing of ~130 tumoral FFPE samples. My samples date from 2005 to 2017. I am new to RNA sequencing and ask you in advance to forgive me for potential simple questions.
I extracted RNA + DNA with AllPrep FFPE kit from Qiagen, for all samples.
We wanted to look for whole transcriptome analysis
From there, we began with a run of 36 samples to test libraries and sequencing.
RiboZero libraries were prepared (use of RNA clean XP beads+AMPure XP Beads)
and NovaSeq was performed for 25M reads.
The results are disappointing. Duplicate mapping attain 98% for some samples, and unique mapping is often no higher than 3%. I don't have the DV200 values here but the profiles are flat.
Here are some clues given by colleagues :
-Ribozero is still dependent on samples quality. If it didn't work on the sample and too many reads are taken by ribosomal RNA, we should change the library method, for example for a polyA library, which is said to be better for extremely degraded RNA. But this would restrict the whole transcriptome objective.
-Pass to panel-methods such as Nanostring, said to be better for highly degraded FFPE samples. Though I was told about sequencing error rate that is higher ?
I would hihly appreciate any feedback or advice on this ! Thank you very much
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