BioMicroCenter:RNA HTL: Difference between revisions
(New page: {{BioMicroCenter}} For users with large numbers of eukaryotic RNA samples, The BioMicro Center offers a high-throughput RNAseq methodology that minimizes cost. High-Throughput 3' Digital ...) |
No edit summary |
||
| Line 1: | Line 1: | ||
{{BioMicroCenter}} | {{BioMicroCenter}} | ||
For users with large numbers of eukaryotic RNA samples, The BioMicro Center offers a high-throughput RNAseq methodology that minimizes cost. High-Throughput 3' Digital Gene Expression (HT3DGE) uses a combination of molecular tagged indexes, SMARTseq chemistry and Nextera Tagmentation to produce libraries derived from the 3' ends of transcripts. In limiting the sequence space used by the samples, fewer reads should be required for a good transcriptome. | [[image:HT3DGE_method.png|right|400px]]For users with large numbers of eukaryotic RNA samples, The BioMicro Center offers a high-throughput RNAseq methodology that minimizes cost. High-Throughput 3' Digital Gene Expression (HT3DGE) uses a combination of molecular tagged indexes, SMARTseq chemistry and Nextera Tagmentation to produce libraries derived from the 3' ends of transcripts. The protocol is based on Soumillon et al.,doi: http://dx.doi.org/10.1101/003236 as part of a new collaboration with the KI High-Throughput Screening Core. In limiting the sequence space used by the samples, fewer reads should be required for a good transcriptome. | ||
{| | |||
| | |||
[[image:HT3DGE_gene_example.png|left|300px]]<BR><BR> | |||
{|border=1 | |||
!colspan=2|Plate setup | |||
|- | |||
| Batch Size || 24 | |||
|- | |||
| Sample Layout || Rows from top | |||
|- | |||
| Volume || 5ul exact | |||
|- | |||
| Concentration || 10ng-25ng* totalRNA/5ul | |||
|- | |||
| Buffer || H2O or 10mM Tris 8.0. <br> no organics! | |||
|- | |||
| Plate || Axygen 96well (CAT#) | |||
|- | |||
| Additional services available <BR> can be added if samples are not submitted as above | |||
| | |||
* Sample setup (per 48) | |||
* SPRI cleanup (if not clean in proper buffer) | |||
* Advanced Analytical (if not quantified) - 10ul minimim submission.. | |||
|- | |||
|colspan=2| *Lower input amounts may also work. | |||
|} | |||
<BR><BR> | |||
| | |||
HT3DGE uses a very early indexing step to tag each sample with a "well ID" and a molecular ID. Once tagged the samples are immediately pooled to minimize costs but failed samples cannot be easily reprepped and are not identifiable until sequencing. As such, the method is best suited for experiments where the NUMBER of samples is not limiting (material can be). The 3' nature of the protocol also limits the utility of this method in splicing applications but it should be more robust to using imperfect RNA ([[BioMicroCenter:RIN|RIN 7+]] instead of 9+ for standard RNAseq) <BR><BR> | |||
Analysis of HT3DGE is not a standard method supported by most open source platforms. We have built pipelines to work with this data, but working closely with the Bioinformatics team is highly recommended. | |||
|} | |||
Revision as of 09:13, 24 August 2016
| HOME -- | SEQUENCING -- | LIBRARY PREP -- | HIGH-THROUGHPUT -- | COMPUTING -- | OTHER TECHNOLOGY |
For users with large numbers of eukaryotic RNA samples, The BioMicro Center offers a high-throughput RNAseq methodology that minimizes cost. High-Throughput 3' Digital Gene Expression (HT3DGE) uses a combination of molecular tagged indexes, SMARTseq chemistry and Nextera Tagmentation to produce libraries derived from the 3' ends of transcripts. The protocol is based on Soumillon et al.,doi: http://dx.doi.org/10.1101/003236 as part of a new collaboration with the KI High-Throughput Screening Core. In limiting the sequence space used by the samples, fewer reads should be required for a good transcriptome.
|
HT3DGE uses a very early indexing step to tag each sample with a "well ID" and a molecular ID. Once tagged the samples are immediately pooled to minimize costs but failed samples cannot be easily reprepped and are not identifiable until sequencing. As such, the method is best suited for experiments where the NUMBER of samples is not limiting (material can be). The 3' nature of the protocol also limits the utility of this method in splicing applications but it should be more robust to using imperfect RNA (RIN 7+ instead of 9+ for standard RNAseq) Analysis of HT3DGE is not a standard method supported by most open source platforms. We have built pipelines to work with this data, but working closely with the Bioinformatics team is highly recommended. | ||||||||||||||||||
