Add Genome annotation page

docs/source/genome-annotation.rst

@@ -0,0 +1,88 @@
+Genome annotation
+=================
+
+Annotating non-coding RNAs in complete genomes
+----------------------------------------------
+
+Before trying to annotate your own genome sequences on your local
+hardware or submitting lots of sequences to Rfam via the website, please
+check that the following resources do not provide the annotation for you:
+
+* `Ensembl <http://www.ensembl.org>`_
+* `Ensembl Genomes <http://ensemblgenomes.org/>`_
+* `UCSC Genome Browser <http://www.genome.ucsc.edu/>`_
+
+The Rfam library of covariance models can be used to search sequences
+(including whole genomes) for homologues to known non-coding RNAs, in
+conjunction with the `Infernal software <http://eddylab.org/infernal/>`_.
+
+Compute
+-------
+
+Covariance model searches are extremely computionally intensive. A small
+model (like tRNA) can search a sequence database at a rate of around
+300 bases/sec.
+
+The compute time scales roughly to the 4th power of the
+length of the RNA, so searching larger models quickly become infeasible
+without significant compute resources.
+
+Specificity
+-----------
+
+The Rfam/Infernal approach aims to be sufficiently generic to cope with
+**all types of RNAs**. A sequence can be searched using every model in
+exactly the same way.
+
+In contrast, several tools are available that search for specific types of
+RNA, such as
+
+* `tRNAscan-SE <http://lowelab.ucsc.edu/tRNAscan-SE/>`_ for tRNAs,
+* `RNAMMER <http://www.cbs.dtu.dk/services/RNAmmer/>`_ for rRNA,
+* `snoscan <http://lowelab.ucsc.edu/snoscan/>`_ for snoRNAs, and
+* `SRPscan <http://bio.lundberg.gu.se/srpscan/>`_ for SRP RNA.
+
+The generic Rfam approach has obvious advantages. However,
+the specialised programs are likely to incorporate heuristics and
+family-specific information, which ensure that they out-perform the
+general method, often requiring only a fraction of the compute time.
+
+Pseudogenes
+-----------
+
+ncRNA derived pseudogenes pose the biggest problem for eukaryotic
+genome annotation using Rfam/Infernal. Many genomes contain **repeat elements**
+that are derived from a non-coding RNA gene, sometimes in
+huge copy number. For example, `Alu repeats <https://en.wikipedia.org/wiki/Alu_element>`_
+in human are evolutionarily related to `SRP RNA <https://en.wikipedia.org/wiki/Signal_recognition_particle>`_,
+and the active `B2 SINE <http://lncrnadb.org/b2sinerna/>`_
+in mouse is recently derived from a tRNA.
+
+In addition, specific RNA genes appear to have
+undergone massive **pseudogene expansions** in certain genomes. For
+example, searching the human genome using the Rfam
+`U6 family <http://rfam.xfam.org/family/RF00026>`_
+yields over 1000 hits, all with very high score. These are not "false
+positives" in the sequence analysis sense, because they are closely
+related by sequence to the real U6 genes, but they completely
+overwhelm the small number (only 10s) of expected real U6 genes.
+
+At present we don't have computational methods to distinguish the real
+genes from the pseudogenes (of course the standard protein coding gene
+tricks - in frame stop codons and the like - are useless). The sensible
+and precedented method for ncRNA annotation in large vertebrate genomes
+is to annotate the easy-to-identify RNAs, such as tRNAs
+and rRNAs, and then trust only hits with very high sequence identity
+(>95% over >95% of the sequence length) to an experimentally
+verified real gene. `tRNAscan-SE <http://lowelab.ucsc.edu/tRNAscan-SE/>`_ has a
+very nice method for detecting tRNA pseudogenes.
+
+.. DANGER::
+  We recommend that you use Rfam/Infernal for vertebrate genome
+  annotation with **extreme caution**!
+
+Nevertheless, Rfam/Infernal does tell us about important
+sequence similarities that are effectively undetectable by other means.
+However, in complex eukaryotic genomes, it is important to treat hits as
+sequence similarity information (much as you might treat BLAST hits),
+rather than as evidence of bona fide ncRNA genes.

docs/source/index.rst

@@ -24,6 +24,7 @@ Contents
    about-rfam
    searching-rfam
    building-families
+   genome-annotation
    database
    website-updates