Difference between revisions of "Fabry:Sequence alignments (sequence searches and multiple alignments)"

From Bioinformatikpedia
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id eVal identity coverage alignment_length
  
id eVal identity coverage alignment_length
 
 
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#whole range
 +
# whole range = Set100
 
tr|C7PCU7|C7PCU7_CHIPD 5e-63 21 0.9933 474
  
tr|C7PCU7|C7PCU7_CHIPD 5e-63 21 0.9933 474
 
tr|B3RSE1|B3RSE1_TRIAD 2e-93 49 0.8415 362
  
tr|B3RSE1|B3RSE1_TRIAD 2e-93 49 0.8415 362
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tr|F8FLU8|F8FLU8_PAEMK 1e-76 10 0.6091 474
  
tr|F8FLU8|F8FLU8_PAEMK 1e-76 10 0.6091 474
 
 
−
#<40% sequence identity
 +
# <40% sequence identity = Set40
 
tr|B8P149|B8P149_POSPM 3e-80 28 0.9425 432
  
tr|B8P149|B8P149_POSPM 3e-80 28 0.9425 432
 
tr|G2TQE8|G2TQE8_BACCO 7e-68 8 0.5795 452
  
tr|G2TQE8|G2TQE8_BACCO 7e-68 8 0.5795 452
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tr|F2USV1|F2USV1_SALS5 1e-88 35 1 467
  
tr|F2USV1|F2USV1_SALS5 1e-88 35 1 467
 
 
−
#>60%
+
# >60% sequence identity = Set60
 
tr|G1P280|G1P280_MYOLU 1e-108 78 0.9699 420
  
tr|G1P280|G1P280_MYOLU 1e-108 78 0.9699 420
 
tr|Q4RTE7|Q4RTE7_TETNG 7e-89 71 0.7319 314
  
tr|Q4RTE7|Q4RTE7_TETNG 7e-89 71 0.7319 314

Revision as of 22:44, 6 May 2012

Introduction

This page contains our results and discussions. The lab journal can be found here.

Reference sequence

The reference sequence of α-Galactosidase A that will be used in this task was obtained from Swissprot P06280. 

>gi|4504009|ref|NP_000160.1| alpha-galactosidase A precursor [Homo sapiens]
MQLRNPELHLGCALALRFLALVSWDIPGARALDNGLARTPTMGWLHWERFMCNLDCQEEPDSCISEKLFM
EMAELMVSEGWKDAGYEYLCIDDCWMAPQRDSEGRLQADPQRFPHGIRQLANYVHSKGLKLGIYADVGNK
TCAGFPGSFGYYDIDAQTFADWGVDLLKFDGCYCDSLENLADGYKHMSLALNRTGRSIVYSCEWPLYMWP
FQKPNYTEIRQYCNHWRNFADIDDSWKSIKSILDWTSFNQERIVDVAGPGGWNDPDMLVIGNFGLSWNQQ
VTQMALWAIMAAPLFMSNDLRHISPQAKALLQDKDVIAINQDPLGKQGYQLRQGDNFEVWERPLSGLAWA
VAMINRQEIGGPRSYTIAVASLGKGVACNPACFITQLLPVKRKLGFYEWTSRLRSHINPTGTVLLQLENT
MQMSLKDLL

Sequence searches

Blast

GO terms of P06280 and each BLAST hit (with Evalue <= 0.003) compared. Percentage terms shared, in relation to number of GO terms of P06280 (AGAL_HUMAN) in the upper picture, in the secon picture in relation to number of each hit

First we performed a BLAST search with the default parameter. Since all hits were significant we raised the number of shown one line descriptions (-v) as well as the number of database sequences to show alignments for (-b). This led to 663 hits with an E-value smaller or equal to 0.003, which we declared as significant in our search. For these proteins we extracted the E-value and the number of positive and also of identical amino acids of the pairwise alignments, as well as the length of each hit. You can see a histogram of each of these features on the left.

For the comparison of the GO terms, we obtained the set of terms for each hit and analyzed the number of those in common with the GO terms of the search protein α-Galactosidase A . We devided the number of common terms by the number of GO terms of P06280 (49). Since these proportions are very small, we thought it would also make sense to explore the fraction of the hits GO terms shared with the reference terms. Thus we devided the number if common terms by the number of terms of the hit. The histogram of the second rate show that in average over 80% of the GO terms of each hit are common with those of AGAL. The small amount of average accordance of the Galactosidase terms to the hit terms may be due to the fact that humans are a lot more complex than the species the homologous hits belong to. So the protein has to fullfill more needs in a more complex organism and thus has more GO terms assigned.

The average length fits the length of the α-Galactosidase A protein very well. This can be seen in the left picture Histogram of the length of the BLAST hits for P06280. On average over 51% of the residues are positive and almost 36% are identical hits. Thus on average 87% of the residues in each alignment are similar to the protein sequence of AGAL.

<figtable id="blastidev">

Histogram of the logarithmic E-values of the BLAST hits for P06280
Histogram of the positive amino acids of the pairwise alignments of the BLAST hits for P06280
Histogram of the identical amino acids of the pairwise alignments of the BLAST hits for P06280
Histogram of the length of the BLAST hits for P06280

</figtable>


Psi-Blast

HHblits

We searched the "big80" database with HHblits using the default settings and also with the maximum number of possible iterations (8).

The HHBlits search was performed with the maximum E-value in the summary and alignment list set to 0.003 (-E) and the minimum number of lines in the summary hit list had to be 700 (-z). From this search we obtained only 326 significant hits.

We also compared the GO terms in a similar manner as in the BLAST section. Here we discovered that on average only 14% of the AGAL_HUMAN protein's GO terms are included in the hits' terms. The "reverse" calculation revealed that around 70% of the hits' GO classes are in common with the search protein. This is rather low in comparison to the BLAST results.

The mean E-value in contrast is almost equal to the average E-value of the BLAST search. The same applies to the number of identical amino acids.

<figtable id="blastidev">

2 iterations - default
GO terms of P06280 and each HHblits hit (with Evalue < 0.003) compared. Percentageterms shared, in relation to number of GO terms of P06280 (AGAL_HUMAN) in the upper picture, in the secon picture in relation to number of each hit
Histogram of the logarithmic E-values of the HHblits hits for P06280
Histogram of the similarity of the HHblits hits to P06280
Histogram of the identical amino acids of the pairwise alignments of the HHblits hits for P06280

</figtable>

Since we thought that the number of significant hits was too low, we performed another HHBlits search with 8 iterations. Doing so, we gained 729 hits with E-value smaller or equal to 0.003.

The similarity in GO terms got better, but all other comparative values, like average E-value, similarity and identical residues got worse.

Thus increasing the number of iterations might be better to obtain more homologous proteins, but since the similarity is smaller, the conservation might also be not as high as for proteins detected with less iterations.

<figtable id="blastidev">

8 iterations
GO terms of P06280 and each HHblits hit (with Evalue < 0.003 and 8 iterations) compared. Percentage terms shared, in relation to number of GO terms of P06280 (AGAL_HUMAN) in the upper picture, in the secon picture in relation to number of each hit
Histogram of the logarithmic E-values of the HHblits search with 8 iterations for P06280
Histogram of the similarity of the BLAST hits (search with 8 iterations) to P06280
Histogram of the identical amino acids of the pairwise alignments of the BLAST hits (search with 8 iterations) for P06280

</figtable>

The first HHblits run took about 2.5 minutes, the second one about 16 minutes (see section Time).

Comparison sequence searches

Comparing the hits

Venn diagram of proteins found by BLAST, HHBlits and HHBlits with 8 iterations
Venn diagram of the proteins found by BLAST, Psi-BLAST (10 iterations and E-value cutoff 10e-10 ) and HHBlits with 8 iterations
Venn diagram of the first 100 proteins found by BLAST, HHBlits and HHBlits with 8 iterations
Venn diagram of the first 100 proteins found by BLAST, Psi-BLAST and HHBlits with 8 iterations

Venn diagrams created with Oliveros, J.C. (2007) VENNY. An interactive tool for comparing lists with Venn Diagrams. In the Venn diagrams one realises, that only a small portion of the found hits is shared by all three methods. Each method seems to have a very unique set of findings. The biggest overlap is between the BLAST and Psi-BLAST hits, which is according to our expectations, since these two use similar approaches, while HHBlits searches by using iterative HMM-HMM comparison. These facts become most obvious in the last picture, where only the 100 best hits of all three methods are compared. Only 6 hits are common among all methods. In the remaining 94, about half are shared by BLAST and Psi-BLAST, the other half is unique in BLAST and Psi-BLAST. HHBlits has 84 unique hits and shares 5 hits solely with each of the BLAST algorithms. The comparison of all hits with E-value smaller or equal to 0.03 in all methods looks similar. It is noteworthy that here even a small number of hits is even shared only by HHBlits and BLAST (52), as well as Psi-BLAST and HHBlits (2). The shared hits of the two different HHBlits searches with 2 and 8 iterations shows also a great amount of overlap.

Comparing the Evalues

Fabry animation.gif

Above you can see an animated histogram of the distribution of the E-values, for the search performed with different methods. The R Script is based on Andrea's R Script psiBlast.evalueHist.Rscript

The most obvious fact is, that the E-value distribution of the Psi-BLAST hits is very different from the other two methods' hits. The Psi-BLAST histogram has its maximum around -60, while the histograms of the BLAST and the HHBlits search do not, but rather tend towards the zero point. Comparing especially the BLAST and Psi-BLAST results the advantage of refining steps and more iterations becomes clear, since the quality, in respect to the E-value, increases. Thus in respect to the E-values I would prefer using Psi-Blast.

Time

We evaluated the time the programs ran with the command "time"


Method Parameter Time
Blast v = 700 b = 700, v = 700 1m53.944s
HHBlits default 2m19.519s
HHBlits n = 8 16m7.754s


Multiple sequence alignments

Dataset

The dataset was generated from the result set of the Psi-Blast run with 10 iterations and an E-value cut-off of 1e-9. We used the following 30 proteins to create multiple sequence alignments with the different methods. Since there were no sequences with a sequence identity of more than 90%, we created three datasets. One with 10 sequences spanning the whole range of sequence identity, one with sequences having an sequence identity <40% and the last one with sequence identity >60%. 

id                     eVal  identity coverage alignment_length

# whole range = Set100
tr|C7PCU7|C7PCU7_CHIPD	5e-63	21	0.9933	474
tr|B3RSE1|B3RSE1_TRIAD	2e-93	49	0.8415	362
tr|G2PG26|G2PG26_STRVO	1e-105	33	0.5854	427
tr|Q8RX86|Q8RX86_ARATH	1e-105	35	0.9814	422
tr|G8NYA7|G8NYA7_GRAMM	4e-61	22	0.6186	470
tr|H1Q7I8|H1Q7I8_9ACTO	1e-97	37	0.5409	396
tr|E1ZHK5|E1ZHK5_CHLVA	8e-80	38	0.8485	368
sp|Q0CEF5|AGALG_ASPTN	4e-63	12	0.611	478
tr|F5BFS9|F5BFS9_TOBAC	1e-106	36	0.9534	410
tr|F8FLU8|F8FLU8_PAEMK	1e-76	10	0.6091	474

# <40% sequence identity = Set40
tr|B8P149|B8P149_POSPM	3e-80	28	0.9425	432
tr|G2TQE8|G2TQE8_BACCO	7e-68	8	0.5795	452
tr|F9HJT9|F9HJT9_9STRE	3e-70	11	0.5709	452
tr|H2JN17|H2JN17_STRHY	3e-69	23	0.774	504
tr|C5AKH4|C5AKH4_BURGB	2e-67	26	0.5488	403
sp|Q0CEF5|AGALG_ASPTN	4e-63	12	0.611	478
tr|B3CFN7|B3CFN7_9BACE	1e-78	26	0.5828	412
tr|D4KDQ2|D4KDQ2_9FIRM	8e-76	10	0.611	483
tr|D4W2N5|D4W2N5_9FIRM	1e-67	10	0.5478	435
tr|F2USV1|F2USV1_SALS5	1e-88	35	1	467
 
# >60% sequence identity = Set60
tr|G1P280|G1P280_MYOLU	1e-108	78	0.9699	420
tr|Q4RTE7|Q4RTE7_TETNG	7e-89	71	0.7319	314
tr|F1Q5G5|F1Q5G5_DANRE	1e-106	67	0.9138	392
tr|E1B725|E1B725_BOVIN	1e-111	76	0.9727	428
tr|H2U095|H2U095_TAKRU	1e-101	65	0.9424	412
tr|G1T044|G1T044_RABIT	1e-109	82	0.9698	417
tr|C0HA45|C0HA45_SALSA	1e-102	63	0.9534	409
tr|H0WQ54|H0WQ54_OTOGA	4e-87	71	0.9953	428
tr|G3WK18|G3WK18_SARHA	1e-108	72	0.9388	414
tr|H2L5H7|H2L5H7_ORYLA	1e-100	61	0.9534	411

Results

TODO: Add pictures of MSA and find a way to present them, since they are _very_ wide --Rackersederj 07:06, 5 May 2012 (UTC)
Maybe only interesting parts or the active site...? --Rackersederj 13:07, 5 May 2012 (UTC) ... Active site (D179 and D231) and partly the surrounding parts are highly conserved! Functional sites... maybe also Glycosylation site (139,192,215,408) and Disulfide bonds (52 ↔ 94, 56 ↔ 63, 142 ↔ 172, 202 ↔ 223, 378 ↔ 382)

ClustalW

msa/clustalw_fabry_dataset_0.msa

Sequence ID Number of gaps
tr|G2PG26|G2PG26_STRVO 144
tr|C7PCU7|C7PCU7_CHIPD 383
tr|G8NYA7|G8NYA7_GRAMM 108
sp|Q0CEF5|AGALG_ASPTN 104
tr|E1ZHK5|E1ZHK5_CHLVA 463
tr|Q8RX86|Q8RX86_ARATH 433
tr|F5BFS9|F5BFS9_TOBAC 416
tr|B3RSE1|B3RSE1_TRIAD 464
tr|F8FLU8|F8FLU8_PAEMK 100
tr|H1Q7I8|H1Q7I8_9ACTO 145
conserved 2

msa/clustalw_fabry_dataset_40.msa

Sequence ID Number of gaps
tr|C5AKH4|C5AKH4_BURGB 187
tr|G2TQE8|G2TQE8_BACCO 164
tr|H2JN17|H2JN17_STRHJ 270
tr|F9HJT9|F9HJT9_9STRE 153
sp|Q0CEF5|AGALG_ASPTN 169
tr|D4W2N5|D4W2N5_9FIRM 151
tr|B3CFN7|B3CFN7_9BACE 230
tr|B8P149|B8P149_POSPM 459
tr|D4KDQ2|D4KDQ2_9FIRM 151
tr|F2USV1|F2USV1_SALS5 431
conserved 2

msa/clustalw_fabry_dataset_61.msa

Sequence ID Number of gaps
tr|H2U095|H2U095_TAKRU 23
tr|H0WQ54|H0WQ54_OTOGA 33
tr|F1Q5G5|F1Q5G5_DANRE 48
tr|G1P280|G1P280_MYOLU 25
tr|G3WK18|G3WK18_SARHA 16
tr|E1B725|E1B725_BOVIN 18
tr|Q4RTE7|Q4RTE7_TETNG 80
tr|H2L5H7|H2L5H7_ORYLA 29
tr|G1T044|G1T044_RABIT 27
tr|C0HA45|C0HA45_SALSA 49
conserved 154


Muscle

msa/muscle_fabry_dataset_0.msa

Sequence ID Number of gaps
sp|Q0CEF5|AGALG_ASPTN 187
tr|F8FLU8|F8FLU8_PAEMK 183
tr|C7PCU7|C7PCU7_CHIPD 466
tr|G8NYA7|G8NYA7_GRAMM 191
tr|B3RSE1|B3RSE1_TRIAD 547
tr|G2PG26|G2PG26_STRVO 227
tr|H1Q7I8|H1Q7I8_9ACTO 228
tr|E1ZHK5|E1ZHK5_CHLVA 546
tr|Q8RX86|Q8RX86_ARATH 516
tr|F5BFS9|F5BFS9_TOBAC 499
conserved 6

msa/muscle_fabry_dataset_40.msa

Sequence ID Number of gaps
tr|H2JN17|H2JN17_STRHJ 305
tr|C5AKH4|C5AKH4_BURGB 222
tr|B8P149|B8P149_POSPM 494
tr|F2USV1|F2USV1_SALS5 466
tr|B3CFN7|B3CFN7_9BACE 265
sp|Q0CEF5|AGALG_ASPTN 204
tr|G2TQE8|G2TQE8_BACCO 199
tr|F9HJT9|F9HJT9_9STRE 188
tr|D4KDQ2|D4KDQ2_9FIRM 186
tr|D4W2N5|D4W2N5_9FIRM 186
conserved 2

msa/muscle_fabry_dataset_61.msa

Sequence ID Number of gaps
tr|H2L5H7|H2L5H7_ORYLA 39
tr|C0HA45|C0HA45_SALSA 59
tr|F1Q5G5|F1Q5G5_DANRE 58
tr|Q4RTE7|Q4RTE7_TETNG 90
tr|H2U095|H2U095_TAKRU 33
tr|H0WQ54|H0WQ54_OTOGA 43
tr|G3WK18|G3WK18_SARHA 26
tr|E1B725|E1B725_BOVIN 28
tr|G1T044|G1T044_RABIT 37
tr|G1P280|G1P280_MYOLU 35
conserved 157

T-Coffee

msa/tcoffe_fabry_dataset_0.msa

Sequence ID Number of gaps
tr|G2PG26|G2PG26_STRVO 491
tr|C7PCU7|C7PCU7_CHIPD 730
sp|Q0CEF5|AGALG_ASPTN 451
tr|E1ZHK5|E1ZHK5_CHLVA 810
tr|G8NYA7|G8NYA7_GRAMM 455
tr|Q8RX86|Q8RX86_ARATH 780
tr|F8FLU8|F8FLU8_PAEMK 447
tr|F5BFS9|F5BFS9_TOBAC 763
tr|B3RSE1|B3RSE1_TRIAD 811
tr|H1Q7I8|H1Q7I8_9ACTO 492
conserved 8

msa/tcoffe_fabry_dataset_40.msa

Sequence ID Number of gaps
tr|B3CFN7|B3CFN7_9BACE 540
tr|C5AKH4|C5AKH4_BURGB 497
tr|G2TQE8|G2TQE8_BACCO 474
tr|H2JN17|H2JN17_STRHJ 580
tr|B8P149|B8P149_POSPM 769
tr|F9HJT9|F9HJT9_9STRE 463
sp|Q0CEF5|AGALG_ASPTN 479
tr|D4W2N5|D4W2N5_9FIRM 461
tr|D4KDQ2|D4KDQ2_9FIRM 461
tr|F2USV1|F2USV1_SALS5 741
conserved 11

msa/tcoffe_fabry_dataset_61.msa

Sequence ID Number of gaps
tr|H2U095|H2U095_TAKRU 44
tr|H0WQ54|H0WQ54_OTOGA 54
tr|F1Q5G5|F1Q5G5_DANRE 69
tr|G1P280|G1P280_MYOLU 46
tr|G3WK18|G3WK18_SARHA 37
tr|Q4RTE7|Q4RTE7_TETNG 101
tr|E1B725|E1B725_BOVIN 39
tr|H2L5H7|H2L5H7_ORYLA 50
tr|G1T044|G1T044_RABIT 48
tr|C0HA45|C0HA45_SALSA 70
conserved 156


3D-Coffee

msa/3Dcoffee_fabry_dataset_0.msa

Sequence ID Number of gaps
tr|G2PG26|G2PG26_STRVO 491
tr|C7PCU7|C7PCU7_CHIPD 730
sp|Q0CEF5|AGALG_ASPTN 451
tr|E1ZHK5|E1ZHK5_CHLVA 810
tr|G8NYA7|G8NYA7_GRAMM 455
tr|Q8RX86|Q8RX86_ARATH 780
tr|F8FLU8|F8FLU8_PAEMK 447
tr|F5BFS9|F5BFS9_TOBAC 763
tr|B3RSE1|B3RSE1_TRIAD 811
tr|H1Q7I8|H1Q7I8_9ACTO 492
conserved 8

msa/3Dcoffee_fabry_dataset_40.msa

Sequence ID Number of gaps
tr|B3CFN7|B3CFN7_9BACE 540
tr|C5AKH4|C5AKH4_BURGB 497
tr|G2TQE8|G2TQE8_BACCO 474
tr|H2JN17|H2JN17_STRHJ 580
tr|B8P149|B8P149_POSPM 769
tr|F9HJT9|F9HJT9_9STRE 463
sp|Q0CEF5|AGALG_ASPTN 479
tr|D4W2N5|D4W2N5_9FIRM 461
tr|D4KDQ2|D4KDQ2_9FIRM 461
tr|F2USV1|F2USV1_SALS5 741
conserved 11

msa/3Dcoffee_fabry_dataset_61.msa

Sequence ID Number of gaps
tr|H2U095|H2U095_TAKRU 44
tr|H0WQ54|H0WQ54_OTOGA 54
tr|F1Q5G5|F1Q5G5_DANRE 69
tr|G1P280|G1P280_MYOLU 46
tr|G3WK18|G3WK18_SARHA 37
tr|Q4RTE7|Q4RTE7_TETNG 101
tr|E1B725|E1B725_BOVIN 39
tr|H2L5H7|H2L5H7_ORYLA 50
tr|G1T044|G1T044_RABIT 48
tr|C0HA45|C0HA45_SALSA 70
conserved 156
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