GTF: Gene Annotation Files

After aligning short sequences, or reads, from RNA-seq to a genome, you need a table of gene locations to count which gene each read belongs to. That table is usually a GTF (Gene Transfer Format) file. GTF is a tab-delimited annotation format based on the GFF version 2 family with conventions added for gene and transcript information.

In one line:

GTF = an annotation file marking the locations of genes, transcripts, and exons on genome coordinates

Where is it used?

GTF is not read data. It is a reference annotation. A typical analysis pipeline uses it like this:

FASTQ → alignment (STAR/HISAT2) → BAM
                                  ↓
                             GTF annotation
                                  ↓
                       read count / TPM by gene

Common uses:

Stage	Role of GTF
Building a genome index	Lets an aligner such as STAR know splice-junction information in advance
Counting reads	Lets featureCounts and HTSeq-count assign reads to genes or exons
Quantifying transcripts	Lets RSEM, StringTie, and similar tools interpret transcript structure
Interpreting results	Links gene IDs, gene names, and transcript IDs to coordinates

Structure of one GTF line

GTF is a tab-delimited text file. Each line represents one feature and always contains nine columns.

chr1  HAVANA  exon  11869  12227  .  +  .  gene_id "ENSG00000223972"; transcript_id "ENST00000456328"; gene_name "DDX11L1";

Column	Name	Meaning
1	seqname	Chromosome or contig name, such as chr1, 1, or GL000...
2	source	Annotation source, such as HAVANA or ENSEMBL
3	feature	Feature type, such as gene, transcript, exon, CDS, or UTR
4	start	Start coordinate
5	end	End coordinate
6	score	Score, or . if absent
7	strand	Strand: +, -, or .
8	frame / phase	CDS frame, or phase. Usually . outside protein-coding regions
9	attributes	Additional information separated by semicolons

Coordinate rules

GTF coordinates are 1-based inclusive.

start = 11869
end   = 12227

This means the region includes both endpoints, from base 11869 through base 12227.

Take care with these differences:

Format	Coordinate rule
GTF / GFF / VCF	1-based
BED	0-based, half-open

Mixing BED and GTF files commonly produces one-base coordinate errors.

attributes: the most important ninth column

The ninth column is the part of GTF that analysis tools read most often.

gene_id "ENSG00000141510";
transcript_id "ENST00000269305";
gene_name "TP53";
gene_biotype "protein_coding";

Key attributes:

Attribute	Meaning
gene_id	Unique gene ID, usually the most stable analytical unit
transcript_id	Transcript isoform ID. Often absent from gene lines and present on transcript, exon, and CDS lines
gene_name	Human-readable gene symbol, such as TP53 or MDM2
gene_biotype / gene_type	Gene type such as protein_coding, lncRNA, or pseudogene. Ensembl mainly uses gene_biotype; GENCODE mainly uses gene_type
exon_number	Order of the exon within the transcript

Where possible, storing data by gene_id rather than gene_name is safer. Gene symbols can change or be duplicated, while identifiers such as Ensembl gene IDs are more stable.

Attribute names differ slightly by source

Columns 1 through 8 of GTF are fairly consistent, but detailed keys in the ninth-column attributes can differ among annotation providers. For example, GENCODE uses gene_type and transcript_type, while Ensembl dumps use names such as gene_biotype. Check which attribute your tool option uses for grouping.

Feature types

Common features include:

feature	Meaning
gene	Entire gene region
transcript	One transcript isoform
exon	An exon forming part of a transcript
CDS	Coding sequence translated into protein
UTR	Untranslated 5’ or 3’ region
start_codon, stop_codon	Start and stop codons

RNA-seq read counting usually aggregates exon features at the gene level. That is why featureCounts is often used with -t exon -g gene_id.

featureCounts \
  -a annotation.gtf \
  -t exon \
  -g gene_id \
  -o counts.txt \
  aligned.bam

Meaning:

Option	Meaning
-a annotation.gtf	GTF annotation to use
-t exon	Count only exon lines
-g gene_id	Group exons with the same gene_id to produce counts by gene

Differences between GTF and GFF3

GTF and GFF3 are both gene-annotation formats. They look similar, but the syntax of the ninth column differs.

Field	GTF	GFF3
Ninth column	gene_id "X"; transcript_id "Y";	ID=exon1;Parent=transcript1
Representing hierarchy	Linked through gene_id and transcript_id attributes	Explicit parent-child relationships through ID and Parent

GFF3 uses reserved attributes such as ID and Parent to represent the gene → transcript → exon hierarchy more explicitly. GTF usually groups features belonging to the same gene or transcript through repeated gene_id and transcript_id values on each line.

Tools expect different formats. Even tools such as featureCounts that support multiple annotation formats need explicit instructions for which feature to count (-t) and which attribute to group by (-g).

Where to obtain GTF files

Human-genome analyses mainly use these annotations.

Source	Characteristics
GENCODE	High-quality annotation used very widely for human and mouse RNA-seq
Ensembl	Supports many species and matches Ensembl gene and transcript IDs well
RefSeq	NCBI-based annotation, common in clinical and legacy pipelines

The important requirement is that the FASTA genome and GTF annotation use the same build.

Good:       GRCh38 genome FASTA + GRCh38 GTF
Dangerous:  GRCh37 genome FASTA + GRCh38 GTF

Practical cautions

1. Chromosome names must match

If the genome FASTA uses chr1 but the GTF uses 1, a tool may not recognize them as the same chromosome.

FASTA: >chr1
GTF:   1  HAVANA  exon ...

This can produce nearly zero counts or warnings while building an index. Always check whether the chr prefix is present.

2. Record the annotation version

Even within GRCh38, gene models can differ among annotation versions such as GENCODE v39, v44, and v46. Record the version with the results for reproducibility.

genome: GRCh38
annotation: GENCODE v46

GENCODE and Ensembl continue to update, so saying only “we used GRCh38” is insufficient. Where possible, record genome build, annotation source, and release number together in papers, notebooks, and result tables.

3. Handle gene_id version suffixes

Ensembl IDs can include a version.

ENSG00000141510.18

Other databases often store the same ID without the suffix, as ENSG00000141510. When joining external data, decide whether to retain or remove version suffixes such as .18.

4. Do not rely only on gene_name

gene_name is easy for people to read but weak as an analytical key.

• Historical names can change
• The same symbol can appear at multiple locations
• Duplicates become more likely when pseudogenes and lncRNAs are included

A safer pattern is to key internal analysis tables by gene_id and attach gene_name only at the final interpretation stage.

Small example

This example shows one gene with one transcript and two exons.

chr1  source  gene        1000  5000  .  +  .  gene_id "GENE1"; gene_name "ABC1";
chr1  source  transcript  1000  5000  .  +  .  gene_id "GENE1"; transcript_id "TX1";
chr1  source  exon        1000  1200  .  +  .  gene_id "GENE1"; transcript_id "TX1"; exon_number "1";
chr1  source  exon        3000  5000  .  +  .  gene_id "GENE1"; transcript_id "TX1"; exon_number "2";

When counting against this GTF, reads that overlap exon 1 or exon 2 are added to the count for GENE1.

One-line cheat sheet

GTF is a "gene map on a genome."
RNA-seq uses it to assign BAM reads to genes and exons.
Coordinates are 1-based inclusive; key attributes are gene_id and transcript_id.
The genome FASTA and GTF must use the same build and chromosome names.

See the Data Formats Reference and Turning Raw Counts into Comparable Values for related material.

References

• Ensembl: GFF/GTF File Format: the nine GFF/GTF columns, 1-based inclusive coordinates, and the attribute column.
• GENCODE: Data format: GENCODE GTF column definitions and attributes including gene_id, transcript_id, gene_type, and exon_number.
• Sequence Ontology: GFF3 specification: GFF3 ID, Parent, and tag=value attribute syntax and hierarchy representation.
• Subread/featureCounts User Guide: read-summarization options for featureCounts -a annotation.gtf -t exon -g gene_id.
• Liao Y, Smyth GK, Shi W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics (2014). DOI: 10.1093/bioinformatics/btt656