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All protein_only mRNAs are single-exon #69
Description
Hello,
I annotated a plant genome using EviAnn with combined RNA-seq and homologous protein evidence. I noticed an obvious biased pattern in the output GFF3:
- Every mRNA tagged with
Evidence=protein_onlybelongs to single-exon genes (Num_exons=1). - But for transcripts marked
Evidence=complete, the most abundant category is two-exon models (Num_exons=2).
$ les ref.fa.pseudo_label.gff |grep protein_only | grep 'Num_exons=\d+' -Po | sort | uniq -c
3410 Num_exons=1
$ les ref.fa.pseudo_label.gff |grep complete | grep 'Num_exons=\d+' -Po | sort -V | uniq -c
7663 Num_exons=1
8035 Num_exons=2
7290 Num_exons=3
5870 Num_exons=4
4953 Num_exons=5
4188 Num_exons=6
3506 Num_exons=7
2938 Num_exons=8
2478 Num_exons=9
1972 Num_exons=10
1501 Num_exons=11
1229 Num_exons=12
1056 Num_exons=13
900 Num_exons=14
609 Num_exons=15
446 Num_exons=16
264 Num_exons=17
303 Num_exons=18
277 Num_exons=19
204 Num_exons=20
148 Num_exons=21
138 Num_exons=22
120 Num_exons=23
115 Num_exons=24
36 Num_exons=25
46 Num_exons=26
42 Num_exons=27
29 Num_exons=28
26 Num_exons=29
30 Num_exons=30
14 Num_exons=31
17 Num_exons=32
11 Num_exons=33
8 Num_exons=34
9 Num_exons=35
5 Num_exons=36
3 Num_exons=37
4 Num_exons=38
7 Num_exons=39
1 Num_exons=40
2 Num_exons=41
6 Num_exons=42
1 Num_exons=44
1 Num_exons=46
1 Num_exons=47
1 Num_exons=49
1 Num_exons=50
2 Num_exons=52
1 Num_exons=64
Is this biased distribution an inherent design of EviAnn? Or is it caused by certain parameter settings or input evidence bias? Could you explain the underlying logic and suggest possible adjustments if needed?
Thanks a lot for your help.
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alekseyzimin commentedon Jul 9, 2026
Hello, there is nothing in the design of EviAnn to cause that, and there are no parameters to adjust. The protein-only transcripts are in minority in your assembly as they should be. Most protein coding transcripts are annotated from RNA-seq data. You can use more proteins from related species, I suggest using at least 500000 unique proteins.