Schema for RT-PCR Primers - RT-PCR Detection Kit Primer Sets
  Database: wuhCor1    Primary Table: primers    Row Count: 55   Data last updated: 2020-04-14
Format description: Summary info about a patSpace alignment
On download server: MariaDB table dump directory
fieldexampleSQL type info description
bin 585smallint(5) unsigned range Indexing field to speed chromosome range queries.
matches 21int(10) unsigned range Number of bases that match that aren't repeats
misMatches 0int(10) unsigned range Number of bases that don't match
repMatches 0int(10) unsigned range Number of bases that match but are part of repeats
nCount 0int(10) unsigned range Number of 'N' bases
qNumInsert 0int(10) unsigned range Number of inserts in query
qBaseInsert 0int(10) unsigned range Number of bases inserted in query
tNumInsert 0int(10) unsigned range Number of inserts in target
tBaseInsert 0int(10) unsigned range Number of bases inserted in target
strand +char(2) values + or - for strand. First character query, second target (optional)
qName Seq1_NIID_WH-1_F501varchar(255) values Query sequence name
qSize 21int(10) unsigned range Query sequence size
qStart 0int(10) unsigned range Alignment start position in query
qEnd 21int(10) unsigned range Alignment end position in query
tName NC_045512v2varchar(255) values Target sequence name
tSize 29903int(10) unsigned range Target sequence size
tStart 483int(10) unsigned range Alignment start position in target
tEnd 504int(10) unsigned range Alignment end position in target
blockCount 1int(10) unsigned range Number of blocks in alignment
blockSizes 21,longblob   Size of each block
qStarts 0,longblob   Start of each block in query.
tStarts 483,longblob   Start of each block in target.

Sample Rows

Note: all start coordinates in our database are 0-based, not 1-based. See explanation here.

RT-PCR Primers (primers) Track Description


This track shows the locations of those primers in detection kits that match the reference sequence. The primers were copied from a spreadsheet created by the project OpenCovid19. The initial version of the track used the FASTA file from Design Flaws in COVID-19 Primers from Multiple International Labs.

Most are RT-qPCR primer sets, sequencing primers have the prefix Seq1- or Seq2-. RT-qPCR sets consists of one forward, one reverse and one internal probe, as indicated by the names.

As expected, the three control primers were not found at all: US-CDC-Control_RP-P, US-CDC-Control_RP-R, US-CDC-Control_RP-F.

Here is a quick overview of the origin of the primers, please see the website and spreadsheet linked above for more details:

Prefix Institution Overview Manual
NIID- Nat. Inst. of Infect. Dis., Japan
WH- National Inst. of Health (Thailand)
HKU- The University of Hong King Detects N gene and Orf1b. Not specific for SARS-Cov2, but other Sarbecovirus species are not in circulation WHO Peiris Protocol
US-CDC- CDC, USA Three reactions, target: N gene. One primer/probe set detects all betacoronaviruses, two sets are specific for SARS-CoV-2. All 3 assays must be positive Instructions
EU-Drosten Drosten Lab, Charite Berlin, Germany Set 1: run E and RdRp primers (designed for SARS-CoV, SARS-CoV-2, and bat-associated betacoronaviruses), if Set 1 is positive, use SARS-Cov-2 specific detection primer Instructions

The sequences and the identifiers for these primers were obtained from the following sources, among others:

More details can be found in the spreadsheet linked above.


The primers were mapped with the following command:
blat ../../wuhCor1.2bit primers.fa stdout -stepSize=3 -tileSize=6 -minScore=10 -oneOff=1 -noHead -fine | pslReps stdin stdout /dev/null -minNearTopSize=10 -minCover=0.8 -nohead > primers.psl

Data Access

You can download the PSL file underlying this track (primers) from our Download Server. The data can be explored interactively with the Table Browser or the Data Integrator. The data can also be accessed from scripts through our API.


This data annotation track was made by Maximilian Haeussler, with assistance from Daniel Schmelter. Fasta data collected by Tomer Altman (Biome Bioinformatics), prepared by Jason Fernandes (UCSC), updated by Darach Miller (Stanford) and the OpenCovid19 project.