-
Notifications
You must be signed in to change notification settings - Fork 1
/
V2R_Finder_large_genomes.sh
2331 lines (1486 loc) · 130 KB
/
V2R_Finder_large_genomes.sh
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
#!/bin/bash
#SBATCH --job-name=V2R_Large_genomes # Job name
eval "$(conda shell.bash hook)"
conda activate olfactory
LMOD_DISABLE_SAME_NAME_AUTOSWAP=no
module purge
module load R/4.2.0-foss-2021a
module load BLAST/2.12.0-Linux_x86_64
module load EMBOSS/6.2.0-goolf-1.7.20
module load SAMtools/1.15-GCC-10.3.0
module load MAFFT/7.467-GCCcore-7.3.0-with-extensions
module load IQ-TREE/2.0-rc1-foss-2018b
module load Python/3.9.5-GCCcore-10.3.0
module load FASTX-Toolkit/0.0.14-goolf-1.7.20
dt=$(date '+%d/%m/%Y %H:%M:%S');
echo "$dt"
#Put the genome as first argument
genome=$1
V2R_database=$2
blast_database=$3
scripts_folder_location=$4 ; scripts_location=`echo "$scripts_folder_location" | sed 's/\/$//'`
maximum_intron_length=$5
number_of_thread=$6
tm_filter=$7
maximum_intron_length_half=$((maximum_intron_length / 2))
#genome=../Splitted_genome/Combined_genome_subparts.fna
#V2R_database=/scicore/home/salzburg/polica0000/Mammals_firsts_tests/Databases/Database_V2R_lungfish_newstrategy/Database_2022_V2R_vertebrates_cdhit_80.prot
#blast_database=/scicore/home/salzburg/polica0000/Mammals_firsts_tests/Databases/GPCR_plus_Olfactory_plus_Taste_receptors_vertebrates_rodentV2R.prot
#scripts_location=/scicore/home/salzburg/polica0000/Mammals_firsts_tests/Databases/Database_V2R_lungfish_newstrategy/Scripts_2022
#maximum_intron_length=30000
#number_of_thread=10
#tm_filter=TRUE
#maximum_intron_length_half=$((maximum_intron_length / 2))
# Becareful this script does not perform the blast ! This should be run before
#Lets launch a Rscript that will merge all blast hits
Rscript $scripts_location/Rscript_merge_blast_hits_7avril.R
xargs samtools faidx $genome < Blast_nonoverlapping.tsv > Blast_nonoverlapping.fasta
#Retain only besthit that best match to a V2R gene
blastx -query Blast_nonoverlapping.fasta -db $blast_database -max_target_seqs 1 -outfmt '6 qseqid sseqid' -out blastx_blast_regions.tsv -num_threads $number_of_thread
grep "V2R-Receptor" blastx_blast_regions.tsv | cut -f1 | sort | uniq > V2R_best_hits.txt
[ -e V2R_Regions.tsv ] && rm V2R_Regions.tsv
for i in `cat V2R_best_hits.txt` ; do grep "$i" Blast_nonoverlapping.tsv >> V2R_Regions.tsv ; done
#Extend all best hits by 5000bp upstream and downstream . Result file : Potential_V2R_regions.tsv
Rscript $scripts_location/Rscript_merge_filter_extend_blast_hit_lungfish.R
#Now for each scaffold, extract only the corresponding regions and merge them, and create what I call a "V2R subgenome"
sed 's/:.*//g' Potential_V2R_regions.tsv | sort | uniq > scaffold_list
rm V2R_subgenome.fa ; rm V2R_subgenome.fa.fai
for scaff in `cat scaffold_list` ; do
grep "$scaff:" Potential_V2R_regions.tsv > to_extract.tsv
xargs samtools faidx ../Splitted_genome/Combined_genome_subparts.fna < to_extract.tsv > to_extract.fa
grep -v ">" to_extract.fa > to_extract.txt
sed -i "1 i\>$scaff" to_extract.txt
fasta_formatter -i to_extract.txt -o to_extract.fa -w 60
cat to_extract.fa >> V2R_subgenome.fa
done
#Split the V2R database and launch exonerate with these sequences against potential V2R regions
mkdir Splitted_db
$scripts_location/exonerate-2.2.0-x86_64/bin/fastasplit -f $V2R_database -c 40 --output Splitted_db
################################################################################################################################################
################################################################################################################################################
################################################################################################################################################
################################################################################################################################################
################################################################################################################################################
################## Search for V2R genes in a loop #############################################################################################
################################################################################################################################################
################################################################################################################################################
################################################################################################################################################
################################################################################################################################################
################################################################################################################################################
cp V2R_subgenome.fa Initial_V2R_subgenome.fa
#re-initialize files
[ -e Potential_multiple_exon_CDS.fa ] && rm Potential_multiple_exon_CDS.fa
[ -e Pseudogenes_multiple_exon.fa ] && rm Pseudogenes_multiple_exon.fa
[ -e No_V2R_genes_coordinates.txt ] && rm No_V2R_genes_coordinates.txt
[ -e Frameshift_less_Pseudogenes.fa ] && rm Frameshift_less_Pseudogenes.fa
#Start the loop to search for V2R genes
current_nb_sequences=1
previous_iteration_nb_sequences=`if test -f "Potential_multiple_exon_CDS.fa" ; then grep -c ">" Potential_multiple_exon_CDS.fa ; else echo "0" ; fi`
number_regions_blast=`grep "[0-9]" Potential_V2R_regions.tsv | wc -l`
while [ "$current_nb_sequences" -gt "$previous_iteration_nb_sequences" ] && [ "$number_regions_blast" -gt "0" ] ; do
previous_iteration_nb_sequences=`if test -f "Potential_multiple_exon_CDS.fa" ; then grep -c ">" Potential_multiple_exon_CDS.fa ; else echo "0" ; fi`
#Extract identified regions in a fasta file
if test -f "V2R_subgenome.tsv" ; then xargs samtools faidx Initial_V2R_subgenome.fa < V2R_subgenome.tsv > V2R_subgenome.fa ; fi
rm *.fai ; sed -i 's/:/-/g' V2R_subgenome.fa
mkdir Exonerate_raw_results_folder
for i in Splitted_db/* ; do
file_name=`echo $i | sed 's/Splitted_db\///g'`
sbatch -W -c 4 --qos=6hours --wrap="$scripts_location/exonerate-2.2.0-x86_64/bin/exonerate -E True --showtargetgff TRUE --model protein2genome --minintron 50 --maxintron $maximum_intron_length --ryo '%tcs' Splitted_db/$file_name V2R_subgenome.fa > Exonerate_raw_results_folder/$file_name.exo.rslt ; sleep 10" &
done
echo "Exonerate running -- Wait"
wait
echo "Exonerate research done"
#Merge exonerate results
cat Exonerate_raw_results_folder/*.exo.rslt > Exonerate_results.txt
#extract vulgar lines
grep "vulgar" Exonerate_results.txt > vulgar_lines.txt
#extract interesting columns of vulgar lines
#query, query_start, query_end, scaffold, scaffold_start, scaffold_end, strand, exonerate_score
sed 's/vulgar: //g' vulgar_lines.txt | cut -f1,2,3,5,6,7,8,9 -d " " > vulgar_lines_parsed.txt
#count the number of introns using vulgar lines
IFS=$'\n'
awk -F'|' 'BEGIN{print "count", "lineNum"}{print gsub(/ I /,"") "\t" NR}' vulgar_lines.txt > number_introns_per_line.txt
grep -v "count" number_introns_per_line.txt | cut -f1 > intron_numbers.txt
#add the intron number to vulgar lines
paste -d " " vulgar_lines_parsed.txt intron_numbers.txt > vulgar_lines_intron_numbers.txt
##Add informations about the best blastp results of each exonerate predicted genes
sed -n '/^# --- END OF GFF DUMP ---/,/^C4 Alignment:/p' Exonerate_results.txt | sed 's/C4 Alignment:.*//g' | sed 's/Hostname:.*//g' | sed 's/Command line:.*//g' | sed 's/^--$//g' | sed 's/-- completed exonerate analysis.*//g' | sed 's/# --- END OF GFF DUMP ---//g' | sed 's/^#$/>seq_to_rename/g' > List_exonerate_cds.fasta #extract all predicted genes sequences
transeq List_exonerate_cds.fasta List_exonerate_cds.prot #translate sequences
sed 's/ /_/g' vulgar_lines_intron_numbers.txt > sequences_names.txt #extract exonerate vulgar line to rename sequences
awk '/^>/ { printf("%s_%s\n",$0,i++);next;} { print $0;}' List_exonerate_cds.prot > List_exonerate_cds_renamed.prot #first round of rename
grep ">" List_exonerate_cds_renamed.prot | sed 's/>//g' > old_names.txt #extract names
paste -d "\t" old_names.txt sequences_names.txt > renaming_file #crate a file for rename_fasta.pl
perl $scripts_location/rename_fasta.pl renaming_file List_exonerate_cds_renamed.prot > List_exonerate_cds.prot #completely rename sequences with the exonerate vulgar line
#Perform the blastp
blastp -query List_exonerate_cds.prot -db $scripts_location/Database_2022_V2R_vertebrates.prot -outfmt '6 qseqid sseqid evalue' -out all_blastp.txt -max_target_seqs 1 -num_threads $number_of_thread
#Extract the information
[ -e all_blastp_parsed.txt ] && rm all_blastp_parsed.txt
for i in `cat sequences_names.txt` ; do if grep -q "$i" all_blastp.txt ; then grep -m1 "$i" all_blastp.txt | cut -f2,3 >> all_blastp_parsed.txt ; else echo "NoQuery 99999" >> all_blastp_parsed.txt ; fi ; done
sed -i 's/ / /g' all_blastp_parsed.txt
paste -d " " vulgar_lines_intron_numbers.txt all_blastp_parsed.txt > vulgar_lines_intron_numbers_blastrslt.txt
#Parse exonerate results. Find the best exonerate results that are most likely complete genes or pseudoogenes, and not overlapping
Rscript $scripts_location/Parse_exonerate_results.R #result file : Parsed_exonerate_gene_regions.tsv
nb_row_parsed_exonerate=`wc -l < Parsed_exonerate_gene_regions.tsv`
if [ "$nb_row_parsed_exonerate" -gt "0" ] ; then
IFS=$'\n'
for line in `cat Parsed_exonerate_gene_regions.tsv` ; do
query=`echo "$line" | cut -f7`
scaffold=`echo "$line" | cut -f1`
scaff_start=`echo "$line" | cut -f2`
scaff_end=`echo "$line" | cut -f3`
echo "$scaffold:$scaff_start-$scaff_end $query"
done > Correct_coordinates_for_exonerate.tsv
#Let's now predict genes on these regions !
IFS=$'\n'
mkdir Genes_predictions
for line in `cat Correct_coordinates_for_exonerate.tsv` ; do
scaffold_s_e=`echo "$line" | cut -f1`
best_query=`echo "$line" | cut -f2`
scaffold_s_e_n=`echo "$line" | cut -f1 | sed 's/:/-/g'`
samtools faidx V2R_subgenome.fa $scaffold_s_e > scaffold.fa
sed -i 's/:/-/g' scaffold.fa
samtools faidx $scripts_location/Database_2022_V2R_vertebrates.prot $best_query > query.prot
$scripts_location/exonerate-2.2.0-x86_64/bin/exonerate -E True --showtargetgff TRUE --model protein2genome --minintron 50 --maxintron $maximum_intron_length --ryo "%tcs" --bestn 1 query.prot scaffold.fa > Genes_predictions/$scaffold_s_e_n.exonerate
cp scaffold.fa Genes_predictions/$scaffold_s_e_n.fasta
#extract only the best result if there are two with the same score
if [ `grep -c "Query: " Genes_predictions/$scaffold_s_e_n.exonerate` -ge 2 ] ; then
sed '/^C4 Alignment:/,/^# --- END OF GFF DUMP ---/!d;/^# --- END OF GFF DUMP ---/q' Genes_predictions/$scaffold_s_e_n.exonerate > first_result_infos
sed '/^# --- END OF GFF DUMP ---/,/^C4 Alignment:/!d;/^C4 Alignment:/q' Genes_predictions/$scaffold_s_e_n.exonerate > first_result_sequence
cat first_result_infos first_result_sequence > Genes_predictions/$scaffold_s_e_n.exonerate
fi
done
### Now we will extract coding sequences from exonerate files. We will define if predicted genes are functionnal or pseudogene ###
#Result folder
mkdir Filtered_predictions
for file in Genes_predictions/*.exonerate ; do
#extract some infos from file name
file_name=`echo "$file" | sed 's/.*\///g'`
file_name_reduced=`echo "$file" | sed 's/.*\///g' | sed 's/.exonerate//g'`
fasta_file_name=`echo "$file_name" | sed 's/exonerate/fasta/g'`
initial_header=`grep ">" Genes_predictions/$fasta_file_name | sed 's/>//g'`
#Test if the predicted gene is a V2R gene or not
awk '/# --- END OF GFF DUMP ---/ {p=1}; p; /C4 Alignment:/ {p=0}' $file | grep -v "^-- completed" | grep -v "C4 Align" | grep -v "END OF GFF" | sed "s/#/>predicted_cds/g" > predicted_cds.fa
transeq predicted_cds.fa predicted_cds.prot
blastp -query predicted_cds.prot -db $blast_database -evalue 1e-5 -outfmt "6 qseqid sseqid sscinames scomnames pident length mismatch gapopen qstart qend sstart send evalue stitle sblastnames sgi sacc" -out blastp_result -max_target_seqs 1 -num_threads 10
#Lets continue only if the best match is an OR
#if grep -q -i "olfactory\|odorant" blastp_result ; then
if grep -q -i "V2R-Receptor" blastp_result ; then
#Define the scaffold name
scaffold=`echo "$file" | sed 's/.*\///g' | sed 's/-.*//g'`
#Define the strand on which the predicted gene is
strand=`grep " similarity " $file | cut -f7`
#Define the first position of the query on the target sequence
first_hit_range=`grep -m1 "Target range:" $file | sed 's/^ *//g' | sed 's/Target range://g' | sed 's/ //g' | sed 's/->/ /g' | cut -f1 -d " "`
#Define the last position of the query on the target sequence
second_hit_range=`grep -m1 "Target range:" $file | sed 's/^ *//g' | sed 's/Target range://g' | sed 's/ //g' | sed 's/->/ /g' | cut -f2 -d " "`
#Lets extract CDS if the gene is on the negative strand
if [ $strand == "-" ] ; then
#file=Genes_predictions/NC_019879.2-28438421-28440954.exonerate
#If strand is minus, then the first position is:
target_end=$((first_hit_range + 1))
#And we will went to extend this by 500bp to be sure to have the potentiel start codon
target_extanded_end=$((first_hit_range + 500))
#Extract 500bp downstream and extract the whole current scaffold fasta file untill the start
samtools faidx Genes_predictions/$fasta_file_name $initial_header:$target_end-$target_extanded_end > Extend_three_prime.fa
samtools faidx Genes_predictions/$fasta_file_name $initial_header:1-$second_hit_range > Extend_five_prime.fa
#remove fasta header of extanded region files
grep -v ">" Extend_three_prime.fa | tr -d '\n' | sed 's/NNN//g' > Extend_three_prime.txt
grep -v ">" Extend_five_prime.fa | tr -d '\n' | sed 's/NNN//g' > Extend_five_prime.txt
#Extract the target sequence corresponding to the CDS predicted by exonerate and revseq, and remove fasta header
grep " exon " $file | cut -f3,4,5 | sort -n -k2 > target_seq.tsv
for exons in `cat target_seq.tsv` ; do begin_exon=`echo "$exons" | cut -f2` ; end_exon=`echo "$exons" | cut -f3` ; samtools faidx Genes_predictions/$fasta_file_name $initial_header:$begin_exon-$end_exon >> Correct_cds.fa ; done
grep -v ">" Correct_cds.fa > predicted_cds_rev.txt ; rm Correct_cds.fa
#Merge the three regions files, add a fasta header and then search for an ORF with the same parameters we used for single exon genes
cat Extend_five_prime.txt predicted_cds_rev.txt Extend_three_prime.txt > Complete_extanded_sequence.fa
sed -i '1 i\>Complete_seq' Complete_extanded_sequence.fa
getorf -sequence Complete_extanded_sequence.fa -outseq Filtered_predictions/$file_name_reduced.ORF -minsize 2100 -find 3
if grep -q -i "reverse" Filtered_predictions/$file_name_reduced.ORF ; then sequence_to_grep=`grep -i "reverse" Filtered_predictions/$file_name_reduced.ORF | sed 's/>//g' | sed 's/ .*//g'` ; samtools faidx Filtered_predictions/$file_name_reduced.ORF $sequence_to_grep > temporary ; mv temporary Filtered_predictions/$file_name_reduced.ORF ; rm Filtered_predictions/$file_name_reduced.ORF.fai ; else rm Filtered_predictions/$file_name_reduced.ORF ; echo "bad strand" > Filtered_predictions/$file_name_reduced.ORF ; fi
#Rename the fasta file (might also be usefull to generate a gff3 file using exonerate ? )
if [ `grep -c ">" Filtered_predictions/$file_name_reduced.ORF` -ge 1 ] ; then
extracted_scaffold_start=`echo "$file" | sed 's/.*\///g' | sed 's/.exonerate//g' | sed 's/-/ /g' | cut -f2`
nb_tiret=`echo "$file" | sed 's/.*\///g' | sed 's/.exonerate//g' | grep -o "-" | wc -l`
if [ $nb_tiret -ge 4 ] ; then extracted_scaffold_start=`echo "$file" | sed 's/.*\///g' | sed 's/.exonerate//g' | cut -f2,4 -d "-" | tr - '\n' | awk -F',' '{sum+=$1;} END{print sum;}'` ; fi
cds_end_extract=`grep -m1 "Target range:" $file | sed 's/^ *//g' | sed 's/Target range://g' | sed 's/ //g' | sed 's/->/ /g' | cut -f1 -d " "`
cds_start_extract=`grep -m1 "Target range:" $file | sed 's/^ *//g' | sed 's/Target range://g' | sed 's/ //g' | sed 's/->/ /g' | cut -f2 -d " "`
cds_coord_start=$((extracted_scaffold_start + cds_start_extract))
cds_coord_end=$((extracted_scaffold_start + cds_end_extract - 1))
exon_number=`grep " exon " $file | wc -l`
sed -i "s/>.*/>$scaffold-$cds_coord_start-$cds_coord_end---$exon_number\_exons/g" Filtered_predictions/$file_name_reduced.ORF
#check that there were no merge between two genes with a tblastn (number of tblastn hits should be inferior or equal to the number of exon)
samtools faidx Initial_V2R_subgenome.fa $scaffold:$cds_coord_start-$cds_coord_end > Verification_scaffold.fa
makeblastdb -in Verification_scaffold.fa -dbtype nucl
number_blast_hit=`tblastn -query Filtered_predictions/$file_name_reduced.ORFP -db Verification_scaffold.fa -evalue 1e-10 -outfmt 6 | awk '{ if ($4 >= 60) { print } }' | wc -l`
if [ "$number_blast_hit" -gt "$exon_number" ] ; then rm Filtered_predictions/$file_name_reduced.ORF ; fi
#If not ORF found, then determinate the gene state
elif [ `grep -c ">" Filtered_predictions/$file_name_reduced.ORF` -lt 1 ] ; then
stop_codon_state="FALSE"
edge_state="FALSE"
frameshift_state="FALSE"
##Stop codon checking
#lets check for the presence of premature stop codons. We will count the number of predicted stop 5percent before the true end position of the query
transeq predicted_cds.fa predicted_cds.prot
#Estimate the interval on which we wil search stop codons.
query_name=`grep "Query: " $file | sed 's/.*Query: //g'`
query_total_length=`grep -m1 "$query_name" $scripts_location/Database_2022_V2R_vertebrates.prot.fai | cut -f2`
query_start_position=`grep "Query range: " $file | sed 's/^ *//g' | sed 's/Query range://g' | sed 's/ //g' | sed 's/->/ /g' | cut -f1 -d " "`
five_percent_position=$((query_total_length * 95 / 100 - query_start_position))
#Lets see if we find stop codon before the five_percent_position
stop_codon_nb=`grep -v ">" predicted_cds.prot | fold -c1 | grep -n "\*" | sed 's/:.*//g' | awk -v myvar=$five_percent_position 'BEGIN{FS="\t";OFS="\t"}($1<=myvar){print $1}' | wc -l` #number of stop codons before the ten percent pos
if [ "$stop_codon_nb" -ge '1' ] ; then stop_codon_state="TRUE" ; fi
##Frameshift checking
#To search for frameshifts, start by removing spurious exons at the border. They are most probably true for functionnal genes, and most of the time bad for pseudogenes
#We remove border exons if there are less than 60nt in length. Run as iteration.
grep " exon " $file | cut -f4,5,9 | awk 'BEGIN{FS="\t";OFS="\t"}{{$4=$2-$1} print; }' > Exons_length.txt
awk 'BEGIN{FS="\t";OFS="\t"}($4>60){print;}' Exons_length.txt > Correct_exons.txt
#Check for the presence of frameshift
frameshift_nb=`grep -o "frameshifts [0-9]*" Correct_exons.txt | cut -f2 -d " " | awk '{ sum+=$1} END {print sum}'`
if [[ $frameshift_nb == "" ]] ; then frameshift_nb=0 ; fi
if [ "$frameshift_nb" -ge '1' ] ; then frameshift_state="TRUE" ; fi
##Edge checking
#Check if the gene is at a conting border
#These borders are either scaffold end or a repeat of "N", usually more than 50 (100 in zebrafish assembly for example)
gene_start_coord=`cut -f1 Correct_exons.txt | sort -n | head -1`
gene_end_coord=`cut -f2 Correct_exons.txt | sort -n | tail -1`
extracted_scaffold_start=`echo "$file" | sed 's/.*\///g' | sed 's/.exonerate//g' | sed 's/-/ /g' | cut -f2`
nb_tiret=`echo "$file" | sed 's/.*\///g' | sed 's/.exonerate//g' | grep -o "-" | wc -l`
if [ $nb_tiret -ge 4 ] ; then extracted_scaffold_start=`echo "$file" | sed 's/.*\///g' | sed 's/.exonerate//g' | cut -f2,4 -d "-" | tr - '\n' | awk -F',' '{sum+=$1;} END{print sum;}'` ; fi
true_start_coord=$((extracted_scaffold_start + gene_start_coord))
true_end_coord=$((extracted_scaffold_start + gene_end_coord))
#First check if these coordinates are near the end of scaffolds (<5000 bp)
if [ "$true_start_coord" -le '5000' ] ; then edge_state="TRUE" ; fi #check if its near the start of scaffold
scaffold_length=`grep -m1 "^$scaffold " Initial_V2R_subgenome.fa.fai | cut -f2` #extract scaffold length from .fai file
diff_lengths=$((scaffold_length - true_end_coord))
if [ "$diff_lengths" -le '5000' ] ; then edge_state="TRUE" ; fi #check if its near the end of scaffold
#Now check if there are consecutive N near the gene that could indicate conting end
extanded_start_coord=$((true_start_coord - 200))
extanded_end_coord=$((true_end_coord + 200))
#Command below extract the region, put in a single line and count the consecutive number of N (only take the greatest number)
consecutive_N_nb=`samtools faidx Initial_V2R_subgenome.fa $scaffold:$extanded_start_coord-$extanded_end_coord | sed 's/n/N/g' | grep -v ">" | awk '/^>/ {printf("\n%s\n",$0);next; } { printf("%s",$0);} END {printf("\n");}' | grep N | awk -F '[^N]+' '{for (i=1; i<=NF; i++) if ($i != "") print length($i)}' | sort -n | tail -1`
if [[ $consecutive_N_nb == "" ]] ; then consecutive_N_nb=0 ; fi
if [ "$consecutive_N_nb" -ge '50' ] ; then edge_state="TRUE" ; fi
##Extract the sequence
[ -e Current_exon_rev.txt ] && rm Current_exon_rev.txt
#Extract the corresponding sequence
for line in `cat Correct_exons.txt` ; do
start_pos=`echo "$line" | cut -f1`
end_pos=`echo "$line" | cut -f2`
samtools faidx Genes_predictions/$fasta_file_name $initial_header:$start_pos-$end_pos > Current_exon.fa
revseq Current_exon.fa Current_exon_rev.fa
#add the reversed sequence to a text file
grep -v ">" Current_exon_rev.fa >> Current_exon_rev.txt
done
#add a header to the text file containing our sequence with the number of exon + frameshift/stopcodon/truncated/edge
exon_nb=`wc -l Exons_length.txt | sed 's/ .*//g'`
header_name=`echo "$scaffold-$true_start_coord-$true_end_coord---$exon_nb exons-$edge_state-$stop_codon_state-$frameshift_state" | sed 's/ /_/g'`
sed -e "1i>$header_name\\" Current_exon_rev.txt > Filtered_predictions/$file_name_reduced.PSEU
sed -i '/^[[:space:]]*$/d' Filtered_predictions/$file_name_reduced.PSEU
cat predicted_cds.prot > Filtered_predictions/$file_name_reduced.CDSP
sed -i "s/>.*/>$header_name/g" Filtered_predictions/$file_name_reduced.CDSP
#check that there were no merge between two genes with a tblastn (number of tblastn hits should be inferior or equal to the number of exon)
samtools faidx Initial_V2R_subgenome.fa $scaffold:$true_start_coord-$true_end_coord > Verification_scaffold.fa
makeblastdb -in Verification_scaffold.fa -dbtype nucl
number_blast_hit=`tblastn -query predicted_cds.prot -db Verification_scaffold.fa -evalue 1e-10 -outfmt 6 | awk '{ if ($4 >= 60) { print } }' | wc -l`
if [ "$number_blast_hit" -gt "$exon_nb" ] ; then rm Filtered_predictions/$file_name_reduced.PSEU ; fi
if [ "$number_blast_hit" -gt "$exon_nb" ] ; then rm Filtered_predictions/$file_name_reduced.CDSP ; fi
fi
#Lets make the same steps with slight modifications for the + strand
elif [ $strand == "+" ] ; then
#If strand is minus, then the first position is:
target_end=$((second_hit_range + 1))
#And we will went to extend this by 500bp to be sure to have the potentiel start codon
target_extanded_end=$((second_hit_range + 500))
#Extract 500bp downstream and extract the whole current scaffold fasta file untill the start
samtools faidx Genes_predictions/$fasta_file_name $initial_header:1-$first_hit_range > Extend_three_prime.fa
samtools faidx Genes_predictions/$fasta_file_name $initial_header:$target_end-$target_extanded_end > Extend_five_prime.fa
#remove fasta header of extanded region files
grep -v ">" Extend_three_prime.fa | tr -d '\n' | sed 's/NNN//g' > Extend_three_prime.txt
grep -v ">" Extend_five_prime.fa | tr -d '\n' | sed 's/NNN//g' > Extend_five_prime.txt
#Extract the CDS sequence predicted by exonerate and remove fasta header
grep " exon " $file | cut -f3,4,5 | sort -n -k2 > target_seq.tsv
for exons in `cat target_seq.tsv` ; do begin_exon=`echo "$exons" | cut -f2` ; end_exon=`echo "$exons" | cut -f3` ; samtools faidx Genes_predictions/$fasta_file_name $initial_header:$begin_exon-$end_exon >> Correct_cds.fa ; done
grep -v ">" Correct_cds.fa > predicted_cds.txt ; rm Correct_cds.fa
#Merge the three regions files, add a fasta header and then search for an ORF with the same parameters we used for single exon genes
cat Extend_three_prime.txt predicted_cds.txt Extend_five_prime.txt > Complete_extanded_sequence.fa
sed -i '1 i\>Complete_seq' Complete_extanded_sequence.fa
getorf -sequence Complete_extanded_sequence.fa -outseq Filtered_predictions/$file_name_reduced.ORF -minsize 2100 -find 3 -reverse FALSE
#Rename the fasta file (might also be usefull to generate a gff3 file using exonerate ? )
if [ `grep -c ">" Filtered_predictions/$file_name_reduced.ORF` -ge 1 ] ; then
extracted_scaffold_start=`echo "$file" | sed 's/.*\///g' | sed 's/.exonerate//g' | sed 's/-/ /g' | cut -f2`
nb_tiret=`echo "$file" | sed 's/.*\///g' | sed 's/.exonerate//g' | grep -o "-" | wc -l`
if [ $nb_tiret -ge 4 ] ; then extracted_scaffold_start=`echo "$file" | sed 's/.*\///g' | sed 's/.exonerate//g' | cut -f2,4 -d "-" | tr - '\n' | awk -F',' '{sum+=$1;} END{print sum;}'` ; fi
cds_start_extract=`grep -m1 "Target range:" $file | sed 's/^ *//g' | sed 's/Target range://g' | sed 's/ //g' | sed 's/->/ /g' | cut -f1 -d " "`
cds_end_extract=`grep -m1 "Target range:" $file | sed 's/^ *//g' | sed 's/Target range://g' | sed 's/ //g' | sed 's/->/ /g' | cut -f2 -d " "`
cds_coord_start=$((extracted_scaffold_start + cds_start_extract))
cds_coord_end=$((extracted_scaffold_start + cds_end_extract - 1))
exon_number=`grep " exon " $file | wc -l`
sed -i "s/>.*/>$scaffold-$cds_coord_start-$cds_coord_end---$exon_number\_exons/g" Filtered_predictions/$file_name_reduced.ORF
transeq Filtered_predictions/$file_name_reduced.ORF Filtered_predictions/$file_name_reduced.ORFP
#check that there were no merge between two genes with a tblastn (number of tblastn hits should be inferior or equal to the number of exon)
samtools faidx Initial_V2R_subgenome.fa $scaffold:$cds_coord_start-$cds_coord_end > Verification_scaffold.fa
makeblastdb -in Verification_scaffold.fa -dbtype nucl
number_blast_hit=`tblastn -query Filtered_predictions/$file_name_reduced.ORFP -db Verification_scaffold.fa -evalue 1e-10 -outfmt 6 | awk '{ if ($4 >= 60) { print } }' | wc -l`
if [ "$number_blast_hit" -gt "$exon_number" ] ; then rm Filtered_predictions/$file_name_reduced.ORF ; fi
#If not ORF found, then determinate the gene state
elif [ `grep -c ">" Filtered_predictions/$file_name_reduced.ORF` -lt 1 ] ; then
stop_codon_state="FALSE"
edge_state="FALSE"
frameshift_state="FALSE"
##Stop codon checking
#lets check for the presence of premature stop codons. We will count the number of predicted stop 5percent before the true end position of the query
transeq predicted_cds.fa predicted_cds.prot
#Estimate the interval on which we wil search stop codons.
query_name=`grep "Query: " $file | sed 's/.*Query: //g'`
query_total_length=`grep -m1 "$query_name" $scripts_location/Database_2022_V2R_vertebrates.prot.fai | cut -f2`
query_start_position=`grep "Query range: " $file | sed 's/^ *//g' | sed 's/Query range://g' | sed 's/ //g' | sed 's/->/ /g' | cut -f1 -d " "`
five_percent_position=$((query_total_length * 95 / 100 - query_start_position))
#Lets see if we find stop codon before the five_percent_position
stop_codon_nb=`grep -v ">" predicted_cds.prot | fold -c1 | grep -n "\*" | sed 's/:.*//g' | awk -v myvar=$five_percent_position 'BEGIN{FS="\t";OFS="\t"}($1<=myvar){print $1}' | wc -l` #number of stop codons before the ten percent pos
if [ "$stop_codon_nb" -ge '1' ] ; then stop_codon_state="TRUE" ; fi
##Frameshift checking
#To search for frameshifts, start by removing spurious exons at the border. They are most probably true for functionnal genes, and most of the time bad for pseudogenes
#We remove border exons if there are less than 60nt in length. Run as iteration.
grep " exon " $file | cut -f4,5,9 | awk 'BEGIN{FS="\t";OFS="\t"}{{$4=$2-$1} print; }' > Exons_length.txt
awk 'BEGIN{FS="\t";OFS="\t"}($4>60){print;}' Exons_length.txt > Correct_exons.txt
#Check for the presence of frameshift
frameshift_nb=`grep -o "frameshifts [0-9]*" Correct_exons.txt | cut -f2 -d " " | awk '{ sum+=$1} END {print sum}'`
if [[ $frameshift_nb == "" ]] ; then frameshift_nb=0 ; fi
if [ "$frameshift_nb" -ge '1' ] ; then frameshift_state="TRUE" ; fi
##Edge checking
#Check if the gene is at a conting border
#These borders are either scaffold end or a repeat of "N", usually more than 50 (100 in zebrafish assembly for example)
gene_start_coord=`cut -f1 Correct_exons.txt | sort -n | head -1`
gene_end_coord=`cut -f2 Correct_exons.txt | sort -n | tail -1`
extracted_scaffold_start=`echo "$file" | sed 's/.*\///g' | sed 's/.exonerate//g' | sed 's/-/ /g' | cut -f2`
nb_tiret=`echo "$file" | sed 's/.*\///g' | sed 's/.exonerate//g' | grep -o "-" | wc -l`
if [ $nb_tiret -ge 4 ] ; then extracted_scaffold_start=`echo "$file" | sed 's/.*\///g' | sed 's/.exonerate//g' | cut -f2,4 -d "-" | tr - '\n' | awk -F',' '{sum+=$1;} END{print sum;}'` ; fi
true_start_coord=$((extracted_scaffold_start + gene_start_coord))
true_end_coord=$((extracted_scaffold_start + gene_end_coord))
#First check if these coordinates are near the end of scaffolds (<5000 bp)
if [ "$true_start_coord" -le '5000' ] ; then edge_state="TRUE" ; fi #check if its near the start of scaffold
scaffold_length=`grep -m1 "^$scaffold " Initial_V2R_subgenome.fa.fai | cut -f2` #extract scaffold length from .fai file
diff_lengths=$((scaffold_length - true_end_coord))
if [ "$diff_lengths" -le '5000' ] ; then edge_state="TRUE" ; fi #check if its near the end of scaffold
#Now check if there are consecutive N near the gene that could indicate conting end
extanded_start_coord=$((true_start_coord - 200))
extanded_end_coord=$((true_end_coord + 200))
#Command below extract the region, put in a single line and count the consecutive number of N (only take the greatest number)
consecutive_N_nb=`samtools faidx Initial_V2R_subgenome.fa $scaffold:$extanded_start_coord-$extanded_end_coord | sed 's/n/N/g' | grep -v ">" | awk '/^>/ {printf("\n%s\n",$0);next; } { printf("%s",$0);} END {printf("\n");}' | grep N | awk -F '[^N]+' '{for (i=1; i<=NF; i++) if ($i != "") print length($i)}' | sort -n | tail -1`
if [[ $consecutive_N_nb == "" ]] ; then consecutive_N_nb=0 ; fi
if [ "$consecutive_N_nb" -ge '50' ] ; then edge_state="TRUE" ; fi
##Extract the sequence
[ -e Current_exon.txt ] && rm Current_exon.txt
#Extract the corresponding sequence
for line in `cat Correct_exons.txt` ; do
start_pos=`echo "$line" | cut -f1`
end_pos=`echo "$line" | cut -f2`
samtools faidx Genes_predictions/$fasta_file_name $initial_header:$start_pos-$end_pos > Current_exon.fa
#add the reversed sequence to a text file
grep -v ">" Current_exon.fa >> Current_exon.txt
done
#add a header to the text file containing our sequence with the number of exon + frameshift/stopcodon/truncated/edge
exon_nb=`wc -l Exons_length.txt | sed 's/ .*//g'`
header_name=`echo "$scaffold-$true_start_coord-$true_end_coord---$exon_nb exons-$edge_state-$stop_codon_state-$frameshift_state" | sed 's/ /_/g'`
sed -e "1i>$header_name\\" Current_exon.txt > Filtered_predictions/$file_name_reduced.PSEU
sed -i '/^[[:space:]]*$/d' Filtered_predictions/$file_name_reduced.PSEU
cat predicted_cds.prot > Filtered_predictions/$file_name_reduced.CDSP
sed -i "s/>.*/>$header_name/g" Filtered_predictions/$file_name_reduced.CDSP
#check that there were no merge between two genes with a tblastn (number of tblastn hits should be inferior or equal to the number of exon)
samtools faidx Initial_V2R_subgenome.fa $scaffold:$true_start_coord-$true_end_coord > Verification_scaffold.fa
makeblastdb -in Verification_scaffold.fa -dbtype nucl
number_blast_hit=`tblastn -query predicted_cds.prot -db Verification_scaffold.fa -evalue 1e-10 -outfmt 6 | awk '{ if ($4 >= 60) { print } }' | wc -l`
if [ "$number_blast_hit" -gt "$exon_nb" ] ; then rm Filtered_predictions/$file_name_reduced.PSEU ; fi
if [ "$number_blast_hit" -gt "$exon_nb" ] ; then rm Filtered_predictions/$file_name_reduced.CDSP ; fi
fi
fi
else echo "$initial_header" >> No_V2R_genes_coordinates.txt
fi
done
fi
#Now that we have filtered all our results, we can concatenate the results
for file in Filtered_predictions/*.ORF ; do if grep -q ">" $file ; then i=1 ; else rm $file ; fi ; done #supress files not containg cds
cat Filtered_predictions/*.ORF >> Potential_multiple_exon_CDS.fa #concatenate results of proper CDS
cat Filtered_predictions/*.PSEU >> Pseudogenes_multiple_exon.fa #concatenate results of pseudo/edge...
cat Filtered_predictions/*.CDSP >> Frameshift_less_Pseudogenes.fa
#Extract coordinates of found genes
grep ">" Potential_multiple_exon_CDS.fa | sed 's/>//g' | sed 's/-/ /g' | cut -f1,2,3 > Coordinates_already_examined.tsv
grep ">" Pseudogenes_multiple_exon.fa | sed 's/>//g' | sed 's/-/ /g' | cut -f1,2,3 >> Coordinates_already_examined.tsv
sed 's/-/ /g' No_V2R_genes_coordinates.txt >> Coordinates_already_examined.tsv
if [ `wc -l < Coordinates_already_examined.tsv` -lt 1 ] ; then echo "Simulated_scaffold 1 10" >> Coordinates_already_examined.tsv ; fi
current_nb_sequences=`if test -f "Potential_multiple_exon_CDS.fa" ; then grep -c ">" Potential_multiple_exon_CDS.fa ; else echo "0" ; fi`
#re-process blast result to find potential V2R regions exclusing already found genes
rm Initial_V2R_subgenome.fa.fai ; samtools faidx Initial_V2R_subgenome.fa
Rscript $scripts_location/Rscript_merge_filter_extend_blast_hit_Second_7avril_v2.R $maximum_intron_length
#sed 's/:.*//g' Potential_V2R_regions.tsv | sort | uniq > scaffold_list
rm -r Filtered_predictions/
rm -r Genes_predictions/
rm -r Exonerate_raw_results_folder/
rm Parsed_exonerate_gene_regions.tsv
if test -f "V2R_subgenome.tsv" ; then number_regions_blast=`grep "[0-9]" V2R_subgenome.tsv | wc -l` ; else number_regions_blast=0 ; fi
done
rm -r Filtered_predictions/
rm -r Genes_predictions/
rm Parsed_exonerate_gene_regions.tsv
################################################################################################################################################
################################################################################################################################################
################################################################################################################################################
################################################################################################################################################
################################################################################################################################################
################## Search for remaining V2R genes with size a bit below #######################################################################
################################################################################################################################################
################################################################################################################################################
################################################################################################################################################
################################################################################################################################################
################################################################################################################################################
Rscript $scripts_location/Parse_exonerate_results_second_3Avril.R
nb_row_parsed_exonerate=`wc -l < Parsed_exonerate_gene_regions.tsv`
if [ "$nb_row_parsed_exonerate" -gt "0" ] ; then
IFS=$'\n'
for line in `cat Parsed_exonerate_gene_regions.tsv` ; do
query=`echo "$line" | cut -f7`
scaffold=`echo "$line" | cut -f1`
scaff_start=`echo "$line" | cut -f2`
scaff_end=`echo "$line" | cut -f3`
echo "$scaffold:$scaff_start-$scaff_end $query"
done > Correct_coordinates_for_exonerate.tsv
#Let's now predict genes on these regions !
IFS=$'\n'
mkdir Genes_predictions
for line in `cat Correct_coordinates_for_exonerate.tsv` ; do
scaffold_s_e=`echo "$line" | cut -f1`
best_query=`echo "$line" | cut -f2`
scaffold_s_e_n=`echo "$line" | cut -f1 | sed 's/:/-/g'`
samtools faidx V2R_subgenome.fa $scaffold_s_e > scaffold.fa
sed -i 's/:/-/g' scaffold.fa
samtools faidx $scripts_location/Database_2022_V2R_vertebrates.prot $best_query > query.prot
$scripts_location/exonerate-2.2.0-x86_64/bin/exonerate -E True --showtargetgff TRUE --model protein2genome --minintron 50 --maxintron $maximum_intron_length --ryo "%tcs" --bestn 1 query.prot scaffold.fa > Genes_predictions/$scaffold_s_e_n.exonerate
cp scaffold.fa Genes_predictions/$scaffold_s_e_n.fasta
#extract only the best result if there are two with the same score
if [ `grep -c "Query: " Genes_predictions/$scaffold_s_e_n.exonerate` -ge 2 ] ; then
sed '/^C4 Alignment:/,/^# --- END OF GFF DUMP ---/!d;/^# --- END OF GFF DUMP ---/q' Genes_predictions/$scaffold_s_e_n.exonerate > first_result_infos
sed '/^# --- END OF GFF DUMP ---/,/^C4 Alignment:/!d;/^C4 Alignment:/q' Genes_predictions/$scaffold_s_e_n.exonerate > first_result_sequence
cat first_result_infos first_result_sequence > Genes_predictions/$scaffold_s_e_n.exonerate
fi
done
### Now we will extract coding sequences from exonerate files. We will define if predicted genes are functionnal or pseudogene ###
#Result folder
mkdir Filtered_predictions
for file in Genes_predictions/*.exonerate ; do
#extract some infos from file name
file_name=`echo "$file" | sed 's/.*\///g'`
file_name_reduced=`echo "$file" | sed 's/.*\///g' | sed 's/.exonerate//g'`
fasta_file_name=`echo "$file_name" | sed 's/exonerate/fasta/g'`
initial_header=`grep ">" Genes_predictions/$fasta_file_name | sed 's/>//g'`
#Test if the predicted gene is a V2R gene or not
awk '/# --- END OF GFF DUMP ---/ {p=1}; p; /C4 Alignment:/ {p=0}' $file | grep -v "^-- completed" | grep -v "C4 Align" | grep -v "END OF GFF" | sed "s/#/>predicted_cds/g" > predicted_cds.fa
transeq predicted_cds.fa predicted_cds.prot
blastp -query predicted_cds.prot -db $blast_database -evalue 1e-5 -outfmt "6 qseqid sseqid sscinames scomnames pident length mismatch gapopen qstart qend sstart send evalue stitle sblastnames sgi sacc" -out blastp_result -max_target_seqs 1 -num_threads 10
#Lets continue only if the best match is an OR
#if grep -q -i "olfactory\|odorant" blastp_result ; then
if grep -q -i "V2R-Receptor" blastp_result ; then
#Define the scaffold name
scaffold=`echo "$file" | sed 's/.*\///g' | sed 's/-.*//g'`
#Define the strand on which the predicted gene is
strand=`grep " similarity " $file | cut -f7`
#Define the first position of the query on the target sequence
first_hit_range=`grep -m1 "Target range:" $file | sed 's/^ *//g' | sed 's/Target range://g' | sed 's/ //g' | sed 's/->/ /g' | cut -f1 -d " "`
#Define the last position of the query on the target sequence
second_hit_range=`grep -m1 "Target range:" $file | sed 's/^ *//g' | sed 's/Target range://g' | sed 's/ //g' | sed 's/->/ /g' | cut -f2 -d " "`
#Lets extract CDS if the gene is on the negative strand
if [ $strand == "-" ] ; then
#file=Genes_predictions/NC_019879.2-28438421-28440954.exonerate
#If strand is minus, then the first position is:
target_end=$((first_hit_range + 1))
#And we will went to extend this by 500bp to be sure to have the potentiel start codon
target_extanded_end=$((first_hit_range + 500))
#Extract 500bp downstream and extract the whole current scaffold fasta file untill the start
samtools faidx Genes_predictions/$fasta_file_name $initial_header:$target_end-$target_extanded_end > Extend_three_prime.fa
samtools faidx Genes_predictions/$fasta_file_name $initial_header:1-$second_hit_range > Extend_five_prime.fa
#remove fasta header of extanded region files
grep -v ">" Extend_three_prime.fa | tr -d '\n' | sed 's/NNN//g' > Extend_three_prime.txt
grep -v ">" Extend_five_prime.fa | tr -d '\n' | sed 's/NNN//g' > Extend_five_prime.txt
#Extract the target sequence corresponding to the CDS predicted by exonerate and revseq, and remove fasta header
grep " exon " $file | cut -f3,4,5 | sort -n -k2 > target_seq.tsv
for exons in `cat target_seq.tsv` ; do begin_exon=`echo "$exons" | cut -f2` ; end_exon=`echo "$exons" | cut -f3` ; samtools faidx Genes_predictions/$fasta_file_name $initial_header:$begin_exon-$end_exon >> Correct_cds.fa ; done
grep -v ">" Correct_cds.fa > predicted_cds_rev.txt ; rm Correct_cds.fa
#Merge the three regions files, add a fasta header and then search for an ORF with the same parameters we used for single exon genes
cat Extend_five_prime.txt predicted_cds_rev.txt Extend_three_prime.txt > Complete_extanded_sequence.fa
sed -i '1 i\>Complete_seq' Complete_extanded_sequence.fa
getorf -sequence Complete_extanded_sequence.fa -outseq Filtered_predictions/$file_name_reduced.ORF -minsize 2100 -find 3
if grep -q -i "reverse" Filtered_predictions/$file_name_reduced.ORF ; then sequence_to_grep=`grep -i "reverse" Filtered_predictions/$file_name_reduced.ORF | sed 's/>//g' | sed 's/ .*//g'` ; samtools faidx Filtered_predictions/$file_name_reduced.ORF $sequence_to_grep > temporary ; mv temporary Filtered_predictions/$file_name_reduced.ORF ; rm Filtered_predictions/$file_name_reduced.ORF.fai ; else rm Filtered_predictions/$file_name_reduced.ORF ; echo "bad strand" > Filtered_predictions/$file_name_reduced.ORF ; fi
#Rename the fasta file (might also be usefull to generate a gff3 file using exonerate ? )
if [ `grep -c ">" Filtered_predictions/$file_name_reduced.ORF` -ge 1 ] ; then
extracted_scaffold_start=`echo "$file" | sed 's/.*\///g' | sed 's/.exonerate//g' | sed 's/-/ /g' | cut -f2`
nb_tiret=`echo "$file" | sed 's/.*\///g' | sed 's/.exonerate//g' | grep -o "-" | wc -l`
if [ $nb_tiret -ge 4 ] ; then extracted_scaffold_start=`echo "$file" | sed 's/.*\///g' | sed 's/.exonerate//g' | cut -f2,4 -d "-" | tr - '\n' | awk -F',' '{sum+=$1;} END{print sum;}'` ; fi
cds_end_extract=`grep -m1 "Target range:" $file | sed 's/^ *//g' | sed 's/Target range://g' | sed 's/ //g' | sed 's/->/ /g' | cut -f1 -d " "`
cds_start_extract=`grep -m1 "Target range:" $file | sed 's/^ *//g' | sed 's/Target range://g' | sed 's/ //g' | sed 's/->/ /g' | cut -f2 -d " "`
cds_coord_start=$((extracted_scaffold_start + cds_start_extract))
cds_coord_end=$((extracted_scaffold_start + cds_end_extract - 1))
exon_number=`grep " exon " $file | wc -l`
sed -i "s/>.*/>$scaffold-$cds_coord_start-$cds_coord_end---$exon_number\_exons/g" Filtered_predictions/$file_name_reduced.ORF
#check that there were no merge between two genes with a tblastn (number of tblastn hits should be inferior or equal to the number of exon)
samtools faidx Initial_V2R_subgenome.fa $scaffold:$cds_coord_start-$cds_coord_end > Verification_scaffold.fa
makeblastdb -in Verification_scaffold.fa -dbtype nucl
number_blast_hit=`tblastn -query Filtered_predictions/$file_name_reduced.ORFP -db Verification_scaffold.fa -evalue 1e-10 -outfmt 6 | awk '{ if ($4 >= 60) { print } }' | wc -l`
if [ "$number_blast_hit" -gt "$exon_number" ] ; then rm Filtered_predictions/$file_name_reduced.ORF ; fi
#If not ORF found, then determinate the gene state
elif [ `grep -c ">" Filtered_predictions/$file_name_reduced.ORF` -lt 1 ] ; then
stop_codon_state="FALSE"
edge_state="FALSE"
frameshift_state="FALSE"
##Stop codon checking
#lets check for the presence of premature stop codons. We will count the number of predicted stop 5percent before the true end position of the query
transeq predicted_cds.fa predicted_cds.prot
#Estimate the interval on which we wil search stop codons.
query_name=`grep "Query: " $file | sed 's/.*Query: //g'`
query_total_length=`grep -m1 "$query_name" $scripts_location/Database_2022_V2R_vertebrates.prot.fai | cut -f2`
query_start_position=`grep "Query range: " $file | sed 's/^ *//g' | sed 's/Query range://g' | sed 's/ //g' | sed 's/->/ /g' | cut -f1 -d " "`
five_percent_position=$((query_total_length * 95 / 100 - query_start_position))
#Lets see if we find stop codon before the five_percent_position
stop_codon_nb=`grep -v ">" predicted_cds.prot | fold -c1 | grep -n "\*" | sed 's/:.*//g' | awk -v myvar=$five_percent_position 'BEGIN{FS="\t";OFS="\t"}($1<=myvar){print $1}' | wc -l` #number of stop codons before the ten percent pos
if [ "$stop_codon_nb" -ge '1' ] ; then stop_codon_state="TRUE" ; fi
##Frameshift checking
#To search for frameshifts, start by removing spurious exons at the border. They are most probably true for functionnal genes, and most of the time bad for pseudogenes
#We remove border exons if there are less than 60nt in length. Run as iteration.
grep " exon " $file | cut -f4,5,9 | awk 'BEGIN{FS="\t";OFS="\t"}{{$4=$2-$1} print; }' > Exons_length.txt
awk 'BEGIN{FS="\t";OFS="\t"}($4>60){print;}' Exons_length.txt > Correct_exons.txt
#Check for the presence of frameshift
frameshift_nb=`grep -o "frameshifts [0-9]*" Correct_exons.txt | cut -f2 -d " " | awk '{ sum+=$1} END {print sum}'`
if [[ $frameshift_nb == "" ]] ; then frameshift_nb=0 ; fi
if [ "$frameshift_nb" -ge '1' ] ; then frameshift_state="TRUE" ; fi
##Edge checking
#Check if the gene is at a conting border
#These borders are either scaffold end or a repeat of "N", usually more than 50 (100 in zebrafish assembly for example)
gene_start_coord=`cut -f1 Correct_exons.txt | sort -n | head -1`
gene_end_coord=`cut -f2 Correct_exons.txt | sort -n | tail -1`
extracted_scaffold_start=`echo "$file" | sed 's/.*\///g' | sed 's/.exonerate//g' | sed 's/-/ /g' | cut -f2`
nb_tiret=`echo "$file" | sed 's/.*\///g' | sed 's/.exonerate//g' | grep -o "-" | wc -l`
if [ $nb_tiret -ge 4 ] ; then extracted_scaffold_start=`echo "$file" | sed 's/.*\///g' | sed 's/.exonerate//g' | cut -f2,4 -d "-" | tr - '\n' | awk -F',' '{sum+=$1;} END{print sum;}'` ; fi
true_start_coord=$((extracted_scaffold_start + gene_start_coord))
true_end_coord=$((extracted_scaffold_start + gene_end_coord))
#First check if these coordinates are near the end of scaffolds (<5000 bp)
if [ "$true_start_coord" -le '5000' ] ; then edge_state="TRUE" ; fi #check if its near the start of scaffold
scaffold_length=`grep -m1 "^$scaffold " Initial_V2R_subgenome.fa.fai | cut -f2` #extract scaffold length from .fai file
diff_lengths=$((scaffold_length - true_end_coord))
if [ "$diff_lengths" -le '5000' ] ; then edge_state="TRUE" ; fi #check if its near the end of scaffold
#Now check if there are consecutive N near the gene that could indicate conting end
extanded_start_coord=$((true_start_coord - 200))
extanded_end_coord=$((true_end_coord + 200))
#Command below extract the region, put in a single line and count the consecutive number of N (only take the greatest number)
consecutive_N_nb=`samtools faidx Initial_V2R_subgenome.fa $scaffold:$extanded_start_coord-$extanded_end_coord | sed 's/n/N/g' | grep -v ">" | awk '/^>/ {printf("\n%s\n",$0);next; } { printf("%s",$0);} END {printf("\n");}' | grep N | awk -F '[^N]+' '{for (i=1; i<=NF; i++) if ($i != "") print length($i)}' | sort -n | tail -1`
if [[ $consecutive_N_nb == "" ]] ; then consecutive_N_nb=0 ; fi
if [ "$consecutive_N_nb" -ge '50' ] ; then edge_state="TRUE" ; fi
##Extract the sequence
[ -e Current_exon_rev.txt ] && rm Current_exon_rev.txt
#Extract the corresponding sequence
for line in `cat Correct_exons.txt` ; do
start_pos=`echo "$line" | cut -f1`
end_pos=`echo "$line" | cut -f2`
samtools faidx Genes_predictions/$fasta_file_name $initial_header:$start_pos-$end_pos > Current_exon.fa
revseq Current_exon.fa Current_exon_rev.fa
#add the reversed sequence to a text file
grep -v ">" Current_exon_rev.fa >> Current_exon_rev.txt
done
#add a header to the text file containing our sequence with the number of exon + frameshift/stopcodon/truncated/edge
exon_nb=`wc -l Exons_length.txt | sed 's/ .*//g'`
header_name=`echo "$scaffold-$true_start_coord-$true_end_coord---$exon_nb exons-$edge_state-$stop_codon_state-$frameshift_state" | sed 's/ /_/g'`
sed -e "1i>$header_name\\" Current_exon_rev.txt > Filtered_predictions/$file_name_reduced.PSEU
sed -i '/^[[:space:]]*$/d' Filtered_predictions/$file_name_reduced.PSEU
cat predicted_cds.prot > Filtered_predictions/$file_name_reduced.CDSP
sed -i "s/>.*/>$header_name/g" Filtered_predictions/$file_name_reduced.CDSP
#check that there were no merge between two genes with a tblastn (number of tblastn hits should be inferior or equal to the number of exon)
samtools faidx Initial_V2R_subgenome.fa $scaffold:$true_start_coord-$true_end_coord > Verification_scaffold.fa
makeblastdb -in Verification_scaffold.fa -dbtype nucl
number_blast_hit=`tblastn -query predicted_cds.prot -db Verification_scaffold.fa -evalue 1e-10 -outfmt 6 | awk '{ if ($4 >= 60) { print } }' | wc -l`
if [ "$number_blast_hit" -gt "$exon_nb" ] ; then rm Filtered_predictions/$file_name_reduced.PSEU ; fi
if [ "$number_blast_hit" -gt "$exon_nb" ] ; then rm Filtered_predictions/$file_name_reduced.CDSP ; fi
fi
#Lets make the same steps with slight modifications for the + strand
elif [ $strand == "+" ] ; then
#If strand is minus, then the first position is:
target_end=$((second_hit_range + 1))
#And we will went to extend this by 500bp to be sure to have the potentiel start codon
target_extanded_end=$((second_hit_range + 500))
#Extract 500bp downstream and extract the whole current scaffold fasta file untill the start
samtools faidx Genes_predictions/$fasta_file_name $initial_header:1-$first_hit_range > Extend_three_prime.fa
samtools faidx Genes_predictions/$fasta_file_name $initial_header:$target_end-$target_extanded_end > Extend_five_prime.fa
#remove fasta header of extanded region files
grep -v ">" Extend_three_prime.fa | tr -d '\n' | sed 's/NNN//g' > Extend_three_prime.txt
grep -v ">" Extend_five_prime.fa | tr -d '\n' | sed 's/NNN//g' > Extend_five_prime.txt
#Extract the CDS sequence predicted by exonerate and remove fasta header
grep " exon " $file | cut -f3,4,5 | sort -n -k2 > target_seq.tsv
for exons in `cat target_seq.tsv` ; do begin_exon=`echo "$exons" | cut -f2` ; end_exon=`echo "$exons" | cut -f3` ; samtools faidx Genes_predictions/$fasta_file_name $initial_header:$begin_exon-$end_exon >> Correct_cds.fa ; done
grep -v ">" Correct_cds.fa > predicted_cds.txt ; rm Correct_cds.fa
#Merge the three regions files, add a fasta header and then search for an ORF with the same parameters we used for single exon genes
cat Extend_three_prime.txt predicted_cds.txt Extend_five_prime.txt > Complete_extanded_sequence.fa
sed -i '1 i\>Complete_seq' Complete_extanded_sequence.fa
getorf -sequence Complete_extanded_sequence.fa -outseq Filtered_predictions/$file_name_reduced.ORF -minsize 2100 -find 3 -reverse FALSE
#Rename the fasta file (might also be usefull to generate a gff3 file using exonerate ? )
if [ `grep -c ">" Filtered_predictions/$file_name_reduced.ORF` -ge 1 ] ; then
extracted_scaffold_start=`echo "$file" | sed 's/.*\///g' | sed 's/.exonerate//g' | sed 's/-/ /g' | cut -f2`
nb_tiret=`echo "$file" | sed 's/.*\///g' | sed 's/.exonerate//g' | grep -o "-" | wc -l`
if [ $nb_tiret -ge 4 ] ; then extracted_scaffold_start=`echo "$file" | sed 's/.*\///g' | sed 's/.exonerate//g' | cut -f2,4 -d "-" | tr - '\n' | awk -F',' '{sum+=$1;} END{print sum;}'` ; fi
cds_start_extract=`grep -m1 "Target range:" $file | sed 's/^ *//g' | sed 's/Target range://g' | sed 's/ //g' | sed 's/->/ /g' | cut -f1 -d " "`
cds_end_extract=`grep -m1 "Target range:" $file | sed 's/^ *//g' | sed 's/Target range://g' | sed 's/ //g' | sed 's/->/ /g' | cut -f2 -d " "`
cds_coord_start=$((extracted_scaffold_start + cds_start_extract))
cds_coord_end=$((extracted_scaffold_start + cds_end_extract - 1))
exon_number=`grep " exon " $file | wc -l`
sed -i "s/>.*/>$scaffold-$cds_coord_start-$cds_coord_end---$exon_number\_exons/g" Filtered_predictions/$file_name_reduced.ORF
transeq Filtered_predictions/$file_name_reduced.ORF Filtered_predictions/$file_name_reduced.ORFP
#check that there were no merge between two genes with a tblastn (number of tblastn hits should be inferior or equal to the number of exon)