This site displays annotation on version 6.0 (July 2014) of the rat (mixed female BN/SsNHsdMCW and male SHR) genome assembly, known as 'Rnor_6.0', submitted from the Rat Genome Sequencing Consortium.
This assembly is based on a 6X WGS sequence approach (as used for the mouse genome), 10X PacBio data set and the hierarchical (BAC clone) approach used for the human genome. It is composed of 2738 toplevel sequences, of which 22 are chromosomes, 354 are unlocalized scaffolds and 578 are unplaced scaffolds. There are 75,697 contigs with an N50 length of 100.5kb, and 1,395 scaffolds with an N50 length of 14.99Mb. The Y chromosome is now present in the assembly.
The Rat Rnor_6.0 assembly was annotated using a mixed approach, with the standard Ensembl gene annotation system and the Ensembl RNASeq pipeline. The RNASeq data set contains 12 samples: liver, muscle, brain, heart, thymus, blood, testis, ovary, kidney, skin, spleen and lung. The HAVANA manual annotation team at the Sanger Institute provided a high quality gene set on gene clusters which are hard to annotate in an automated pipeline.
In addition to the main set, we have predicted gene models for each tissue type using the RNASeq pipeline. We did a BLASTp of these models against UniProt proteins of protein existence level 1 and 2, in order to confirm the open reading frame (ORF). The best BLAST hit is displayed as a transcript supporting evidence.
The tissue-specific sets of transcript models built using our RNAseq pipeline are as follows:
|Tissue||Number of gene models|
General information about this species can be found in Wikipedia.
|Assembly||Rnor_6.0, INSDC Assembly GCA_000001895.4, Jul 2014|
|Golden Path Length||2,870,184,193|
|Annotation method||Mixed strategy build|
|Genebuild started||Sep 2014|
|Genebuild released||Jun 2015|
|Genebuild last updated/patched||Jan 2017|
|Coding genes||22,250 (incl 12 ) readthrough|
|Non coding genes||8,934|
|Small non coding genes||5,122|
|Long non coding genes||3,288 (incl 6 ) readthrough|
|Misc non coding genes||524|
|Genscan gene predictions||59,821|