Difference between revisions of "Two Eel Scaffolds"
| Line 21: | Line 21: | ||
augustus --species=lamprey eelScaffold320.fa >aug_s320_lp.gtf | augustus --species=lamprey eelScaffold320.fa >aug_s320_lp.gtf | ||
| − | Augustus outputs in the GTF format, for visual browsing on JBrowse, we need to convert to the related format, GFF: | + | Augustus outputs in the GTF format, for future visual browsing on JBrowse, we need to convert to the related format, GFF: |
gtf2gff.pl --printExon --gff3 < aug_s32_lp.gtf --out=aug_s32_lp.gff | gtf2gff.pl --printExon --gff3 < aug_s32_lp.gtf --out=aug_s32_lp.gff | ||
| + | |||
| + | We are also probably interested in the CDS and proteins sequences of the predicted genes, we can use the following Augustus-supplied script: | ||
| + | |||
| + | getAnnoFasta.pl --seqfile=eelScaffold32.fa aug_s32_lp.gtf | ||
| + | |||
| + | In order to visually navigate the results of these annotations, they can be viewed on a browser [http://stab.st-andrews.ac.uk/JBrowse-1.12.1 here]. | ||
Against zebrafish, EelScaffold320 gives 19 predicted genes while EelScaffold32 give 39. An exhaustive search through each of these would require more time, but we can certainly undertake a quick blast with very stringent matching targets against the '''tilapia'' CDS to see if any of these stand out. | Against zebrafish, EelScaffold320 gives 19 predicted genes while EelScaffold32 give 39. An exhaustive search through each of these would require more time, but we can certainly undertake a quick blast with very stringent matching targets against the '''tilapia'' CDS to see if any of these stand out. | ||
| Line 43: | Line 49: | ||
And for EelScaffold320, we get: | And for EelScaffold320, we get: | ||
| − | + | g7.t1 ENSONIT00000001474.1 81.57 510 90 4 134 641 611 1118 7e-116 418 | |
| − | + | g8.t1 ENSONIT00000005855.1 82.95 651 105 5 51 698 21 668 1e-165 582 | |
| − | + | g10.t1 ENSONIT00000005827.1 88.51 522 60 0 3 524 27 548 0.0 632 | |
| − | |||
= Detecting presence of '''pdcd10b''' and '''nrd1a''' = | = Detecting presence of '''pdcd10b''' and '''nrd1a''' = | ||
Revision as of 21:09, 15 May 2016
Contents
Introduction
Two DNA scaffolds are presented:
- eelScaffold32. 679 422 bp and 42.25% GC.
- eelScaffold320. 246 433 bp and 43.47% GC.
We take tilapia (Oreochromis niloticus, Ensembl abbreviation ONI) to be the reference.
There are two genes expected to be around about the regions covered by these scaffolds:
- eelScaffold32 contains any part of PDCD10b (Programmed cell death 10b).
- eelScaffold320 contains any part of nrd1a (Nardilysin, N-arginine dibasic convertase)
Gene Predictor
One of the most up-to-date (2016) gene predictors is Augustus. It uses HMM profiles based on a related organism. In terms of eel, there are two given organisms: Zebra fish (zb) and Lamprey (lp) which Augustus makes available. Though tilapia is not available, it is possible - given time - to train and establish HMM profile for this organism.
An example Augustus command line is as follows:
augustus --species=lamprey eelScaffold320.fa >aug_s320_lp.gtf
Augustus outputs in the GTF format, for future visual browsing on JBrowse, we need to convert to the related format, GFF:
gtf2gff.pl --printExon --gff3 < aug_s32_lp.gtf --out=aug_s32_lp.gff
We are also probably interested in the CDS and proteins sequences of the predicted genes, we can use the following Augustus-supplied script:
getAnnoFasta.pl --seqfile=eelScaffold32.fa aug_s32_lp.gtf
In order to visually navigate the results of these annotations, they can be viewed on a browser here.
Against zebrafish, EelScaffold320 gives 19 predicted genes while EelScaffold32 give 39. An exhaustive search through each of these would require more time, but we can certainly undertake a quick blast with very stringent matching targets against the 'tilapia CDS to see if any of these stand out.
In the case of EelScaffold32 against zebrafish we get:
g16.t1 ENSONIT00000001464.1 84.98 293 44 0 152 444 266 558 6e-80 298
And for EelScaffold320, we get:
g10.t1 ENSONIT00000001474.1 82.78 395 64 4 206 598 545 937 5e-95 350 g11.t1 ENSONIT00000005855.1 82.95 651 105 5 42 689 21 668 1e-165 582 g19.t1 ENSONIT00000005827.1 88.66 494 56 0 1 494 55 548 6e-172 603
Against lamprey, we suspect that the best hits will be the same. For EelScaffold32:
g6.t1 ENSONIT00000001464.1 84.88 291 44 0 199 489 268 558 4e-79 294
And for EelScaffold320, we get:
g7.t1 ENSONIT00000001474.1 81.57 510 90 4 134 641 611 1118 7e-116 418 g8.t1 ENSONIT00000005855.1 82.95 651 105 5 51 698 21 668 1e-165 582 g10.t1 ENSONIT00000005827.1 88.51 522 60 0 3 524 27 548 0.0 632
Detecting presence of pdcd10b and nrd1a
We obtain these genes from the tilapia and then their exons and apply Smith-Waterman alignment (via the Emboss program, wrapped in this script with the scaffolds to them. We order via scaffold starting site (reverse strand end site).
pdcd10b's 7 exons against eelScaffold32
Output of script:
5 89 125.5 56 62.9 56 15 16.9 92493 92577 0.0 1 78 79 98.7 7 80 112.0 52 65.0 52 16 20.0 153839 153911 0.0 1 71 82 86.6 6 97 113.0 59 60.8 59 20 20.6 222386 222481 0.0 4 81 83 94.0 2 54 105.0 37 68.5 37 7 13.0 270271 270324 0.0 2 48 54 87.0 1 91 134.0 58 63.7 58 9 9.9 305491 305572 0.0 6 96 96 94.8 4 149 161.5 91 61.1 91 29 19.5 337277 337419 0.0 2 127 127 99.2 3 112 129.5 69 61.6 69 16 14.3 607211 607313 0.0 7 111 118 89.0 Score for 7 query sequences (total 639 bp) against forward-sense target (679422 bp) = 880.50 Exon separation string: << e00:92493-92577 >> 61262 << e01:153839-153911 >> 68475 << e02:222386-222481 >> 47790 << e03:270271-270324 >> 35167 << e04:305491-305572 >> 31705 << e05:337277-337419 >> 269792 << e06:607211-607313 >>
7 82 320.0 72 87.8 72 0 0.0 441200 441281 0.0 1 82 82 100.0
6 83 334.0 74 89.2 74 0 0.0 442739 442821 0.0 1 83 83 100.0
5 78 282.0 66 84.6 66 0 0.0 442964 443041 0.0 1 78 79 98.7
4 127 437.0 105 82.7 105 0 0.0 443355 443481 0.0 1 127 127 100.0
3 51 183.0 43 84.3 43 0 0.0 445730 445780 0.0 1 51 118 43.2
2 54 198.0 46 85.2 46 0 0.0 446360 446413 0.0 1 54 54 100.0
1 94 380.0 84 89.4 84 0 0.0 448216 448309 0.0 3 96 96 97.9
Score for 7 query sequences (total 639 bp) against reverse-sense target (679422 bp) = 2134.00
Key: SFI src file idx, ALEN aln length, SCORE aln score, IDEN identical bases, IPT percent iden, SIM similar bases, GAPS num gaps, GPT gap percent
TSC target start query, TEC target end coord, PET percent of target, QSC Query start coord, QEC query end coord, QLN query aln length, PEQ percent of query
Exon separation string:
<< e00:441200-441281 >> 1458 << e01:442739-442821 >> 143 << e02:442964-443041 >> 314 << e03:443355-443481 >> 2249 << e04:445730-445780 >> 580 << e05:446360-446413 >> 1803 << e06:448216-448309 >>
We can clearly see good alignment on the reverse strand, and so can verify pdcd10b presence in eelScaffold32. Note how localized the exons are on target string.
nrd1a's 37 exons against eelScaffold320
SFI ALEN SCORE IDEN IPT SIM GAPS GPT TSC TEC PET QSC QEC QLN PEQ
32 52 99.5 36 69.2 36 4 7.7 11214 11261 0.0 10 61 84 61.9
18 46 105.5 34 73.9 34 4 8.7 21678 21720 0.0 1 45 55 81.8
17 70 95.0 45 64.3 45 20 28.6 22625 22693 0.0 3 53 59 86.4
24 40 96.5 29 72.5 29 2 5.0 22849 22886 0.0 8 47 52 76.9
23 21 69.0 17 81.0 17 0 0.0 26374 26394 0.0 1 21 22 95.5
6 18 72.0 16 88.9 16 0 0.0 28762 28779 0.0 5 22 23 78.3
14 64 105.5 42 65.6 42 9 14.1 42560 42621 0.0 12 68 70 81.4
2 315 228.0 183 58.1 183 64 20.3 46282 46552 0.1 7 301 324 91.0
21 90 112.5 58 64.4 58 17 18.9 80763 80842 0.0 3 85 87 95.4
25 153 138.0 88 57.5 88 27 17.6 81195 81324 0.1 1 149 151 98.7
11 81 148.5 55 67.9 55 10 12.3 81550 81625 0.0 47 122 123 61.8
1 525 261.0 294 56.0 294 105 20.0 83281 83764 0.2 2 462 541 85.2
15 61 107.0 40 65.6 40 4 6.6 89643 89699 0.0 8 68 78 78.2
28 39 78.0 28 71.8 28 8 20.5 92398 92435 0.0 1 32 32 100.0
8 168 147.0 104 61.9 104 32 19.0 97584 97741 0.1 8 153 154 94.8
3 254 229.0 150 59.1 150 55 21.7 106270 106501 0.1 6 226 241 91.7
31 54 88.5 37 68.5 37 6 11.1 106293 106342 0.0 2 53 53 98.1
29 129 142.5 79 61.2 79 30 23.3 107213 107332 0.0 23 130 139 77.7
13 70 119.0 46 65.7 46 5 7.1 108538 108605 0.0 1 67 74 90.5
4 37 84.5 27 73.0 27 3 8.1 129499 129534 0.0 3 37 38 92.1
37 131 128.5 79 60.3 79 26 19.8 133637 133753 0.0 13 131 131 90.8
35 96 114.5 60 62.5 60 21 21.9 135814 135897 0.0 1 87 90 96.7
9 78 106.5 50 64.1 50 14 17.9 136915 136989 0.0 5 71 74 90.5
30 39 87.0 27 69.2 27 0 0.0 137258 137296 0.0 1 39 48 81.2
22 114 120.0 69 60.5 69 20 17.5 143789 143896 0.0 2 101 101 99.0
5 30 64.5 22 73.3 22 6 20.0 158927 158955 0.0 1 25 26 96.2
27 176 145.0 102 58.0 102 39 22.2 161163 161325 0.1 13 162 163 92.0
33 89 109.0 56 62.9 56 19 21.3 164489 164570 0.0 5 81 91 84.6
10 82 119.0 52 63.4 52 11 13.4 168702 168776 0.0 1 78 96 81.2
7 81 106.5 50 61.7 50 7 8.6 178661 178740 0.0 4 78 82 91.5
20 121 141.5 76 62.8 76 21 17.4 178727 178838 0.0 14 122 124 87.9
12 43 98.0 31 72.1 31 4 9.3 202832 202872 0.0 5 45 58 70.7
36 65 118.0 44 67.7 44 8 12.3 208219 208279 0.0 3 63 70 87.1
19 120 157.5 76 63.3 76 29 24.2 221343 221456 0.0 2 98 105 92.4
34 86 124.0 58 67.4 58 14 16.3 221411 221484 0.0 19 102 117 71.8
26 123 127.5 74 60.2 74 14 11.4 225229 225348 0.0 4 115 128 87.5
16 129 126.0 77 59.7 77 21 16.3 226946 227071 0.1 11 121 121 91.7
Score for 37 query sequences (total 4025 bp) against forward-sense target (246433 bp) = 4519.50
SFI ALEN SCORE IDEN IPT SIM GAPS GPT TSC TEC PET QSC QEC QLN PEQ
36 79 135.5 53 67.1 53 13 16.5 31868 31943 0.0 2 70 70 98.6
1 531 279.0 295 55.6 295 122 23.0 44814 45314 0.2 52 490 541 81.1
37 130 317.0 93 71.5 93 0 0.0 88877 89006 0.1 1 130 131 99.2
35 91 213.5 66 72.5 66 4 4.4 89201 89289 0.0 1 89 90 98.9
34 117 360.0 92 78.6 92 0 0.0 89454 89570 0.0 1 117 117 100.0
33 93 249.0 70 75.3 70 4 4.3 89571 89661 0.0 1 91 91 100.0
32 82 275.0 67 81.7 67 0 0.0 90168 90249 0.0 2 83 84 97.6
31 53 211.0 47 88.7 47 0 0.0 90408 90460 0.0 1 53 53 100.0
30 48 123.0 35 72.9 35 0 0.0 91324 91371 0.0 1 48 48 100.0
29 140 422.5 111 79.3 111 4 2.9 91967 92104 0.1 2 139 139 99.3
28 32 97.0 25 78.1 25 0 0.0 92238 92269 0.0 1 32 32 100.0
26 118 365.0 93 78.8 93 0 0.0 93551 93668 0.0 11 128 128 92.2
25 150 408.0 113 75.3 113 4 2.7 93879 94026 0.1 3 150 151 98.0
24 52 107.0 35 67.3 35 0 0.0 94256 94307 0.0 1 52 52 100.0
22 101 253.0 73 72.3 73 0 0.0 94486 94586 0.0 1 101 101 100.0
21 89 185.5 62 69.7 62 4 4.5 94724 94810 0.0 1 87 87 100.0
20 124 359.0 95 76.6 95 0 0.0 94902 95025 0.1 1 124 124 100.0
19 101 289.0 77 76.2 77 0 0.0 95201 95301 0.0 4 104 105 96.2
18 53 202.0 46 86.8 46 0 0.0 96018 96070 0.0 2 54 55 96.4
17 59 214.0 50 84.7 50 0 0.0 96349 96407 0.0 1 59 59 100.0
16 123 426.0 103 83.7 103 4 3.3 96864 96984 0.0 1 121 121 100.0
15 77 286.0 66 85.7 66 0 0.0 97195 97271 0.0 1 77 78 98.7
14 67 200.0 52 77.6 52 0 0.0 97632 97698 0.0 4 70 70 95.7
13 74 181.0 53 71.6 53 0 0.0 98153 98226 0.0 1 74 74 100.0
12 58 227.0 51 87.9 51 0 0.0 98324 98381 0.0 1 58 58 100.0
11 124 284.0 88 71.0 88 2 1.6 98645 98767 0.0 1 123 123 100.0
10 96 336.0 80 83.3 80 0 0.0 99073 99168 0.0 1 96 96 100.0
9 73 239.0 59 80.8 59 0 0.0 99304 99376 0.0 2 74 74 98.6
8 155 583.0 135 87.1 135 2 1.3 99622 99775 0.1 1 154 154 100.0
7 83 205.0 61 73.5 61 2 2.4 99952 100033 0.0 1 82 82 100.0
3 255 397.5 169 66.3 169 31 12.2 100706 100943 0.1 1 241 241 100.0
2 331 330.5 196 59.2 196 57 17.2 101708 101996 0.1 9 324 324 97.5
6 21 63.0 17 81.0 17 1 4.8 113247 113266 0.0 2 22 23 91.3
5 25 71.0 21 84.0 21 3 12.0 141659 141681 0.0 2 25 26 92.3
27 171 165.0 104 60.8 104 37 21.6 142741 142906 0.1 18 156 163 85.3
23 22 78.5 19 86.4 19 2 9.1 213159 213180 0.0 2 21 22 90.9
4 46 92.0 31 67.4 31 8 17.4 228468 228513 0.0 1 38 38 100.0
Score for 37 query sequences (total 4025 bp) against reverse-sense target (246433 bp) = 9229.50
Key: SFI src file idx, ALEN aln length, SCORE aln score, IDEN identical bases, IPT percent iden, SIM similar bases, GAPS num gaps, GPT gap percent
TSC target start query, TEC target end coord, PET percent of target, QSC Query start coord, QEC query end coord, QLN query aln length, PEQ percent of query
This is a more complicated gene, so the alignment is less good, but there is clearly good identity so we can reasonably suspect the reverse strand harbours this second gene.
