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GFF3 files are in tabular format with 9 fields per line, separated by tabs. The first 8 fields share almost same data structure, but the 9th field varies a lot depending on feature type and gene prediction algorithm.
Presently I am trying to build my own GFF module that will parse a GFF file and return one structured data object (a python dictionary structure). For that, I need a good understanding of the 9th field of the GFF format.
So can any one please help me by providing various GFF files?
The first place to start is the GFF3 specification. This is the official word on what is and is not allowed in a GFF3 file. For example, users can define arbitrary attribute keys, so long as they do not begin with an uppercase letter (these are reserved for "official" use).
But your question doesn't seem to be about what is allowed, but what is commonly used. I have a question for you: which gene predictors are YOU using? Or are you using gene annotations produced by others?
Here are a few examples.
If you're using GFF3 from NCBI, chances are it looks something like this.
NC_007070.3 Gnomon gene 329235 331223 . + . ID=gene14;Dbxref=BEEBASE:GB42168,GeneID:551678;Name=LOC551678;gbkey=Gene;gene=LOC551678;gene_biotype=protein_coding
NC_007070.3 Gnomon mRNA 329235 331223 . + . ID=rna27;Parent=gene14;Dbxref=GeneID:551678,Genbank:XM_624067.4,BEEBASE:GB42168;Name=XM_624067.4;gbkey=mRNA;gene=LOC551678;model_evidence=Supporting evidence includes similarity to: 66 ESTs%2C 24 Proteins%2C and 99%25 coverage of the annotated genomic feature by RNAseq alignments%2C including 113 samples with support for all annotated introns;product=receptor expression-enhancing protein 5-like%2C transcript variant X1;transcript_id=XM_624067.4
NC_007070.3 Gnomon exon 329235 329459 . + . ID=id117;Parent=rna27;Dbxref=GeneID:551678,Genbank:XM_624067.4,BEEBASE:GB42168;gbkey=mRNA;gene=LOC551678;product=receptor expression-enhancing protein 5-like%2C transcript variant X1;transcript_id=XM_624067.4
NC_007070.3 Gnomon exon 329850 330082 . + . ID=id118;Parent=rna27;Dbxref=GeneID:551678,Genbank:XM_624067.4,BEEBASE:GB42168;gbkey=mRNA;gene=LOC551678;product=receptor expression-enhancing protein 5-like%2C transcript variant X1;transcript_id=XM_624067.4
NC_007070.3 Gnomon exon 330166 330301 . + . ID=id119;Parent=rna27;Dbxref=GeneID:551678,Genbank:XM_624067.4,BEEBASE:GB42168;gbkey=mRNA;gene=LOC551678;product=receptor expression-enhancing protein 5-like%2C transcript variant X1;transcript_id=XM_624067.4
NC_007070.3 Gnomon exon 330376 331223 . + . ID=id120;Parent=rna27;Dbxref=GeneID:551678,Genbank:XM_624067.4,BEEBASE:GB42168;gbkey=mRNA;gene=LOC551678;product=receptor expression-enhancing protein 5-like%2C transcript variant X1;transcript_id=XM_624067.4
NC_007070.3 Gnomon CDS 329333 329459 . + 0 ID=cds8;Parent=rna27;Dbxref=GeneID:551678,Genbank:XP_624070.1,BEEBASE:GB42168;Name=XP_624070.1;gbkey=CDS;gene=LOC551678;product=receptor expression-enhancing protein 5-like isoform X1;protein_id=XP_624070.1
NC_007070.3 Gnomon CDS 329850 330082 . + 2 ID=cds8;Parent=rna27;Dbxref=GeneID:551678,Genbank:XP_624070.1,BEEBASE:GB42168;Name=XP_624070.1;gbkey=CDS;gene=LOC551678;product=receptor expression-enhancing protein 5-like isoform X1;protein_id=XP_624070.1
NC_007070.3 Gnomon CDS 330166 330301 . + 0 ID=cds8;Parent=rna27;Dbxref=GeneID:551678,Genbank:XP_624070.1,BEEBASE:GB42168;Name=XP_624070.1;gbkey=CDS;gene=LOC551678;product=receptor expression-enhancing protein 5-like isoform X1;protein_id=XP_624070.1
NC_007070.3 Gnomon CDS 330376 330416 . + 2 ID=cds8;Parent=rna27;Dbxref=GeneID:551678,Genbank:XP_624070.1,BEEBASE:GB42168;Name=XP_624070.1;gbkey=CDS;gene=LOC551678;product=receptor expression-enhancing protein 5-like isoform X1;protein_id=XP_624070.1
The MAKER annotation workflow (paper, software) is a pretty commonly used gene annotation tool, and produces GFF3 output like this.
scaffold_12 maker gene 652527 655343 . + . ID=maker-scaffold_12-augustus-gene-0.959;Name=maker-scaffold_12-augustus-gene-0.959
scaffold_12 maker mRNA 652527 655343 . + . ID=maker-scaffold_12-augustus-gene-0.959-mRNA-1;Parent=maker-scaffold_12-augustus-gene-0.959;Name=maker-scaffold_12-augustus-gene-0.959-mRNA-1;_AED=0.24;_eAED=0.18;_QI=0|0|0|0.66|0.5|0.33|3|0|218
scaffold_12 maker exon 652527 652817 . + . ID=maker-scaffold_12-augustus-gene-0.959-mRNA-1:exon:1203;Parent=maker-scaffold_12-augustus-gene-0.959-mRNA-1
scaffold_12 maker exon 654877 655170 . + . ID=maker-scaffold_12-augustus-gene-0.959-mRNA-1:exon:1204;Parent=maker-scaffold_12-augustus-gene-0.959-mRNA-1
scaffold_12 maker exon 655272 655343 . + . ID=maker-scaffold_12-augustus-gene-0.959-mRNA-1:exon:1205;Parent=maker-scaffold_12-augustus-gene-0.959-mRNA-1
scaffold_12 maker CDS 652527 652817 . + 0 ID=maker-scaffold_12-augustus-gene-0.959-mRNA-1:cds;Parent=maker-scaffold_12-augustus-gene-0.959-mRNA-1
scaffold_12 maker CDS 654877 655170 . + 0 ID=maker-scaffold_12-augustus-gene-0.959-mRNA-1:cds;Parent=maker-scaffold_12-augustus-gene-0.959-mRNA-1
scaffold_12 maker CDS 655272 655343 . + 0 ID=maker-scaffold_12-augustus-gene-0.959-mRNA-1:cds;Parent=maker-scaffold_12-augustus-gene-0.959-mRNA-1
scaffold_12 maker gene 941547 943897 . + . ID=snap-scaffold_12-processed-gene-0.851;Name=snap-scaffold_12-processed-gene-0.851
scaffold_12 maker mRNA 941547 943897 . + . ID=snap-scaffold_12-processed-gene-0.851-mRNA-1;Parent=snap-scaffold_12-processed-gene-0.851;Name=snap-scaffold_12-processed-gene-0.851-mRNA-1;_AED=0.22;_eAED=0.22;_QI=0|0|0.25|0.25|1|1|4|661|95
scaffold_12 maker exon 941547 941631 . + . ID=snap-scaffold_12-processed-gene-0.851-mRNA-1:exon:1206;Parent=snap-scaffold_12-processed-gene-0.851-mRNA-1
scaffold_12 maker exon 942343 942367 . + . ID=snap-scaffold_12-processed-gene-0.851-mRNA-1:exon:1207;Parent=snap-scaffold_12-processed-gene-0.851-mRNA-1
scaffold_12 maker exon 942780 942920 . + . ID=snap-scaffold_12-processed-gene-0.851-mRNA-1:exon:1208;Parent=snap-scaffold_12-processed-gene-0.851-mRNA-1
scaffold_12 maker exon 943200 943897 . + . ID=snap-scaffold_12-processed-gene-0.851-mRNA-1:exon:1209;Parent=snap-scaffold_12-processed-gene-0.851-mRNA-1
scaffold_12 maker CDS 941547 941631 . + 0 ID=snap-scaffold_12-processed-gene-0.851-mRNA-1:cds;Parent=snap-scaffold_12-processed-gene-0.851-mRNA-1
scaffold_12 maker CDS 942343 942367 . + 2 ID=snap-scaffold_12-processed-gene-0.851-mRNA-1:cds;Parent=snap-scaffold_12-processed-gene-0.851-mRNA-1
scaffold_12 maker CDS 942780 942920 . + 1 ID=snap-scaffold_12-processed-gene-0.851-mRNA-1:cds;Parent=snap-scaffold_12-processed-gene-0.851-mRNA-1
scaffold_12 maker CDS 943200 943236 . + 1 ID=snap-scaffold_12-processed-gene-0.851-mRNA-1:cds;Parent=snap-scaffold_12-processed-gene-0.851-mRNA-1
scaffold_12 maker three_prime_UTR 943237 943897 . + . ID=snap-scaffold_12-processed-gene-0.851-mRNA-1:three_prime_utr;Parent=snap-scaffold_12-processed-gene-0.851-mRNA-1
If we look at the output of several common ab initio gene prediction tools, none of them actually produces GFF3 by default. Here is some output from GeneMark (paper, software).
543 1 + Initial 799051 799097 47 1 2 - -
543 2 + Terminal 799236 799266 31 3 3 - -
544 3 - Terminal 802357 802514 158 3 2 - -
544 2 - Internal 802607 802685 79 1 1 - -
544 1 - Initial 802829 802843 15 3 1 - -
Here is some output from SNAP (paper, software).
Einit 8230 8239 + 9.329 0 1 0 scaffold_12-snap.4
Exon 8848 8869 + 2.484 2 2 2 scaffold_12-snap.4
Exon 10121 10208 + 15.302 1 0 2 scaffold_12-snap.4
Exon 11361 11420 + 5.969 0 0 2 scaffold_12-snap.4
Exon 11471 11535 + 0.921 0 2 1 scaffold_12-snap.4
Eterm 12169 12187 + 18.163 1 0 1 scaffold_12-snap.4
Einit 14569 14668 + -6.918 0 1 0 scaffold_12-snap.5
Exon 15029 15203 + -1.023 2 2 0 scaffold_12-snap.5
Exon 16171 16307 + -9.230 1 1 1 scaffold_12-snap.5
Eterm 16667 16698 + 9.829 2 0 0 scaffold_12-snap.5
Einit 17809 17898 - -5.390 0 0 0 scaffold_12-snap.6
Exon 17299 17350 - 6.978 0 1 2 scaffold_12-snap.6
Eterm 17029 17129 - -2.857 2 0 0 scaffold_12-snap.6
Both of these formats appear to be tab-delimited, but that's where the similarity with GFF3 ends.
The output of Augustus (paper, software) looks like GTF (a variant of the GFF format) once you lose all the lines beginning with a # symbol, but Augustus also has a GFF3 output mode.
# Predicted genes for sequence number 1 on both strands
# start gene g1
scaffold_12 AUGUSTUS gene 2841 3400 1 + . g1
scaffold_12 AUGUSTUS transcript 2841 3400 1 + . g1.t1
scaffold_12 AUGUSTUS start_codon 2841 2843 . + 0 transcript_id "g1.t1"; gene_id "g1";
scaffold_12 AUGUSTUS intron 3027 3097 1 + . transcript_id "g1.t1"; gene_id "g1";
scaffold_12 AUGUSTUS CDS 2841 3026 1 + 0 transcript_id "g1.t1"; gene_id "g1";
scaffold_12 AUGUSTUS CDS 3098 3400 1 + 0 transcript_id "g1.t1"; gene_id "g1";
scaffold_12 AUGUSTUS stop_codon 3398 3400 . + 0 transcript_id "g1.t1"; gene_id "g1";
# protein sequence = [MAIKNAEHDLRVIVDAIEGLGLKVAPHKTEAMAFPASALCGRRGAAPPKIRLGGSSILVGSRSRWYISGHSENSSKSP
# RTEGKETTPLQQRDPLDAPLWVSGVVAHCCGGPEGQEGCPGLAAQGSDQGVLRIRDGLLCGYDGCGDHRPRPSDSSAGGGLCRP]
# end gene g1
###
# start gene g2
scaffold_12 AUGUSTUS gene 4712 15229 0.21 + . g2
scaffold_12 AUGUSTUS transcript 4712 15229 0.21 + . g2.t1
scaffold_12 AUGUSTUS start_codon 4712 4714 . + 0 transcript_id "g2.t1"; gene_id "g2";
scaffold_12 AUGUSTUS intron 4858 5591 0.74 + . transcript_id "g2.t1"; gene_id "g2";
scaffold_12 AUGUSTUS intron 5686 15028 0.23 + . transcript_id "g2.t1"; gene_id "g2";
scaffold_12 AUGUSTUS CDS 4712 4857 0.72 + 0 transcript_id "g2.t1"; gene_id "g2";
scaffold_12 AUGUSTUS CDS 5592 5685 0.42 + 1 transcript_id "g2.t1"; gene_id "g2";
scaffold_12 AUGUSTUS CDS 15029 15229 0.43 + 0 transcript_id "g2.t1"; gene_id "g2";
scaffold_12 AUGUSTUS stop_codon 15227 15229 . + 0 transcript_id "g2.t1"; gene_id "g2";
# protein sequence = [MGRNSHRSCCVVNCKITSAKSDCKFYKFPTAKWKINQRKMWVAAVKRQKYIKDEISHAETQTEITEVTGATKVNYANK
# KYICLLFVRTYVLRMLVDVALSNLRFSLFGIRKSLEIFGQSEKADQTRWRLPSCEMEWIESRKGKMRE]
# end gene g2
###
So...how should YOU handle attributes in GFF3's 9th column? That depends a lot on what you want to do with the data.
The most important attributes are ID and Parent, which are used to define relationships between features and subfeatures. (These relationships implicitly define a directed acyclic graph of features, although most GFF3 parsers don't directly support traversal of this graph.)
But not only do you have to handle the pre-defined attributes discussed in the GFF3 specification, you also have to be able to handle any number of arbitrary attributes whose keys you may not know beforehand.
The simplest way to handle this would be to parse the attribute column into a dictionary of key/value pairs. Once it's in this form, it's trivial to see what attributes are there and how to access them.
For example, if we have a feature with the following attributes...
ID=mRNA42;Parent=gene19;integrity=0.95;foo=bar
...we would want it in a dictionary like so.
attributes = {
'ID': 'mrna42',
'Parent': 'gene19',
'integrity': '0.95',
'foo': 'bar',
}
Python code to parse that might look something like this.
attributes = dict()
for keyvaluepair in attributestring.split(';'):
for key, value in keyvaluepair.split('='):
attributes[key] = value
One thing to consider is that it's possible for an attribute to have multiple values (separated by commas). It's not commonly used, but it is valid and something that should be handled or at least checked for.