Sequence Alignments Hemochromatosis

From Bioinformatikpedia
Revision as of 22:05, 31 August 2012 by Joerdensv (talk | contribs) (Multiple Sequence Alignments)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)

Hemochromatosis>>Task 2: Sequence alignments

Short Task Description

  • Apply and compare different sequence search algorithms.
  • Use the results for MSAs

Detailed description: Task_alignments

Protocol

We've made a protocol with the commands and scripts we used to create our results: Protocol

Reference Sequence

Sequence from Uniprot: Q30201

>sp|Q30201|HFE_HUMAN Hereditary hemochromatosis protein OS=Homo sapiens GN=HFE PE=1 SV=1
MGPRARPALLLLMLLQTAVLQGRLLRSHSLHYLFMGASEQDLGLSLFEALGYVDDQLFVF
YDHESRRVEPRTPWVSSRISSQMWLQLSQSLKGWDHMFTVDFWTIMENHNHSKESHTLQV
ILGCEMQEDNSTEGYWKYGYDGQDHLEFCPDTLDWRAAEPRAWPTKLEWERHKIRARQNR
AYLERDCPAQLQQLLELGRGVLDQQVPPLVKVTHHVTSSVTTLRCRALNYYPQNITMKWL
KDKQPMDAKEFEPKDVLPNGDGTYQGWITLAVPPGEEQRYTCQVEHPGLDQPLIVIWEPS
PSGTLVIGVISGIAVFVVILFIGILFIILRKRQGSRGAMGHYVLAERE

Sequence Searches

In this task we've tested three different sequence search algorithms against each other. We also used three different databases:

  • Big80 for BLAST and PSI-BLAST
  • Big for PSI-BLAST
  • Uniprot20 for HHblits

The results for each search run were filtered for unique hits and an e-Value cutoff of 2e-3. The cutoff was chosen to be in accordance with the given minimum cutoff (2-e3) for the PSI-BLAST profiles. For the evaluation of the hits we used two methods:

  • GO term analysis: We compared each hit's GO term with the GO terms of HFE (Q30201; 27 GO terms). Then we computed two percentages. The first one is the percentage of GO terms the hit has in common with HFE, the second one is the percentage of GO terms HFE has in common with the hit.
  • COPS classification: For each hit that could be mapped to a PDB ID we checked if it was within the same COPS cluster (L30-L99,S30,S90) as HFE.


BLAST

<figtable id="blastdist">

Hemo eval blast 80.png
Hemo ident blast 80.png
Table 1: E-Value and identity distributions of the BLAST search against Big80.

</figtable>

The first BLAST search against the Big80 database reached the hit limit of 250 sequences with an e-Value of e-30 for the worst hit. So we did it again with a new limit of 1500 reported hits. These hits were then filtered for unique IDs and an e-Value cutoff of 2e-3. After the filtering 1159 hits were left.

The distributions for the e-Values and identities of these hits are shown in <xr id="blastdist"/>. Most of the e-Values are between 1e-50 and 2e-3 (cutoff). Only few hits have a better e-Value. The identities are piled between 20% and 40% with two peaks at around 27% and 34% respectively.

For the evaluation of the results we compared the hits' GO terms and COPS classifications. <xr id="blastgo"/> shows that the majority of the hits share almost all of their GO terms with the HFE protein. In contrast, only about 10% to 15% of HFE's GO terms are shared by most of the hits. This might be caused by the fact that most of the hit proteins didn't have as much GO terms as HFE (27 GO terms). The COPS classification (see <xr id="blastcops"/>) shows that most (59) of the 69 PDB entries share at least 80% structure similarity with HFE, but only a few have a high sequence similarity (which is in accordance with the previous identity statistic). Overall BLAST shows the best performance for finding proteins of similar structure (see <xr id="allcops"/>).

<figtable id="blastgo">

Percentage of shared GO terms with HFE in relation to hit's GO terms.
Percentage of shared GO terms with HFE in relation to HFE's GO terms.
Table 2: Common GO terms within BLAST hits.

</figtable>

<figure id="blastcops">

Figure 1: COPS classification of BLAST hits. The figure shows the number of PDB IDs that are within the different similarity clusters with HFE.

</figure>


PSI-BLAST

<figtable id="psiblastdist">

Hemo eval psi 80.png
Hemo ident psi 80.png
Table 3: E-Value and identity distributions of the PSI-BLast search against Big80.

</figtable>

After the BLAST search, we also performed several searches with PSI-BLAST. This time we increased the number of reported hits and used a variety of parameter combinations to test their impact on the search results. The parameters to be changed were 'h' and 'j'. The first one, 'h', sets the e-Value cutoff for the inclusion of sequences into the PSI-BLAST-profile. The second one, 'j', is for the number of iterations for the PSI-BLAST search. For each of these parameters we used two different values: 2e-3 and 1e-10 for 'h', 2 and 10 for 'j'. This resulted in a total of 4 combinations.


The first 4 searches were against Big80 with a maximum of 10000 reported hits. We also saved the PSI-BLAST profiles for later (see bellow). The hits for each individual parameter combination were again filtered for unique IDs and an e-Value cutoff of 2e-3. This resulted in the following number of hits:

  • h=2e-3, j=2: 1892 (2786 prefiltered)
  • h=2e-3, j=10: 1704 (2734 prefiltered)
  • h=1e-10, j=2: 2058 (3574 prefiltered)
  • h=1e-10, j=10: 2035 (3458 prefiltered)

<xr id="psiblastdist"/> shows the e-Value and identity distributions for the Big80 results. In contrast to the previous BLAST search, we have more significant e-Values, but the identity shifts a bit to the left (lower identity). The differences between the parameter combinations are quite easy to spot. The lower e-Value cutoff (1-e10) also produces more significant hits (lower e-Values). This might be caused by the inclusion of fewer sequences into the profile and therefore a higher specificity for more closely related sequences (i.e. low e-Values). An increased number of iterations on the other hand reduces the number of significant hits and seems to slightly reduce the average identity.


After the searches against Big80 we also ran PSI-BLAST against the Big database. We reused the profiles from the Big80 runs and also increased the maximum of reported hits to 100000.

  • h=2e-3, j=2: 23840 (25934 prefiltered)
  • h=2e-3, j=10: 25756 (30616 prefiltered)
  • h=1e-10, j=2: 26483 (28766 prefiltered)
  • h=1e-10, j=10: 27535 (29609 prefiltered)

The two combinations with 10 iterations threw multiple error messages (but finished the process nevertheless). These errors were due to an internal code failure of PSI-BLAST and caused by too many possible hits[1].


The performances of the different PSI-BLAST runs (see <xr id="psiblastruntime"/>) show that the cutoff for the profiles ('h') doesn't really affect the runtime. The number of iteration on the other hand has a big impact on the runtime. The size of the database, of course, also affects the runtime. The exceptionally high runtime for the 10-iteration runs against Big might also be caused by the errors mentioned above.

<figtable id="psiblastruntime">

Iterations 2 2 10 10
E-Value 0.002 10E-10 0.002 10E-10
Big80 3m21 3m6 16m39 16m41
Big 28m17 26m43 367m15 64m4

Table 4: Runtime analysis of PSI-BLAST. </figtable>


The GO term and COPS classification analysis yields similar results to BLAST. The different parameter values have almost no effect on the GO terms. The only visible effect is that a higher iteration count seems to have a small negative effect on the GO term analysis. In the COPS analysis (see <xr id="psiblastcops"/>) the parameters seem to make almost no difference in the distribution of the different clusters (L30-L99,S30,S90), but a more strict e-Value cutoff and higher iteration count both have a negative effect on the overall percentages of hits within these clusters (see <xr id="allcops"/>).

<figtable id="psiblastgo">

Percentage of shared GO terms with HFE in relation to hit's GO terms (Big80).
Percentage of shared GO terms with HFE in relation to HFE's GO terms (Big80).
Percentage of shared GO terms with HFE in relation to hit's GO terms (Big).
Percentage of shared GO terms with HFE in relation to HFE's GO terms (Big).
Table 5: Common GO terms within PSI-BLAST hits.

</figtable>

<figtable id="psiblastcops">

Database: Big80
Database: Big
Table 6: COPS classification of PSI-BLAST hits.

</figtable>


HHblits

<figtable id="hhblitsdist">

Hemo eval hhblits 80.png
Hemo ident hhblits 80.png
Table 7: E-Value and identity distributions of the HHblits search against Uniprot20.

</figtable>

The final sequence search algorithm we apllied was HHblits. This time we searched against another database, Uniprot20. We set the number of reported hits (clusters) to 600 which corresponds to a worst e-Value of 0.0021. After filtering for unique clusters, we had 585 clusters left. Within these clusters we had 27588 unique Uniprot ACs. The most significant cluster with an e-Value of 2e-131 and an 40% identities accounted for 2771 (about 10% total) of these Uniprot ACs.

In <xr id="hhblitsdist"/> you can see the distribution of the clusters' e-Values and identities. Like in the BLAST results, most e-Values are between 1e-50 and 2e-3. The majority of the identities are again between 20% and 40%, with a peak at around 26%.

The runtime was 13m 13s. This means that HHblits' is more or less between BLAST's and PSI-BLAST's runtime.


HHblits shows about the same results for the GO term analysis (<xr id="hhblitsgo"/>) regarding the percentage of HFE's GO terms. In contrast to the previous results, HHblits also has a high peak for the hit's GO terms at around 65% to 70%. This means that HHblits finds more proteins with a more distant related function than the other algorithms. The COPS classification (<xr id="hhblitscops"/> and <xr id="allcops"/>) is similar to PSI-BLAST (database: Big) in the L99 and L80 clusters, but HHblits has a better performance to find proteins in the L30, L40, and L60 clusters than PSI-BLAST (database: Big).

<figtable id="hhblitsgo">

Percentage of shared GO terms with HFE in relation to hit's GO terms.
Percentage of shared GO terms with HFE in relation to HFE's GO terms.
Table 8: Common GO terms within HHblits hits.

</figtable>

<figure id="hhblitscops">

Figure 2: COPS classification of HHblits hits. The figure shows the number of PDB IDs that are within the different similarity clusters with HFE.

</figure>


Comparison

To compare the different search algorithms and PSI-BLAST combinations we collected the unique hits and created several Venn diagrams (Oliveros, J.C. (2007) VENNY. An interactive tool for comparing lists with Venn Diagrams.). In order to compare PSI-BLAST and HHblits we took the runs of PSI-BLAST against the Big database. BLAST was never run against Big, so all of BLAST's hits are based on the Big80 database.

<figtable id="psiblastoverlap">

Database: Big80.
Database: Big.
Table 9: Overlap between the different PSI-BLAST runs.

</figtable>

First we compared the different variations of PSI-BLAST runs. <xr id="psiblastoverlap"/> shows that the different parameters have only a small effect on the results as most of them are shared between all combinations. Only the adjustment of the inclusion e-Value cutoff produces some hits unique to these configurations. This is true for both databases: Big80 and Big.

<figtable id="alloverlap">

Databases: Big80, Big, Uniprot20.
Databases: Big, Uniprot20.
Database: Big80.
Table 10: Overlap between the different search algorithms. BLAST results are always against the Big80 database, HHblits against Uniprot20, and

PSI-BLAST against Big (left and middle figure) or Big80 (right figure).

</figtable>

When comparing all three algorithms (<xr id="alloverlap"/>), we can see that PSI-BLAST and BLAST have the most hits in common. This is not surprising as both algorithms use a similar approach to collect thier hits. HHblits and PSI-BLAST share about half of their hits. This seems also to be true for HHblits and BLAST, but the number of BLAST hits is too small to be sure.

<figure id="allcops">

Figure 3: COPS classification statistics for all algorithms.

</figure>

Last we compared the COPS analysis for all algorithms and PSI-BLAST combinations (see <xr id="allcops"/>). BLAST shows the best performance among all of them in the L99 and L80 cluster, though it is equal to PSI-BLAST (database: Big80) in the L30 to L60 clusters. When comparing the results for HHblits and PSI-BLAST (database: Big), HHblits yields slightly better results in the L30 to L60 range.


Multiple Sequence Alignments


Dataset

We created three groups of sequences for the MSAs. One group with only 40% (or lower) sequence identity to HFE, one with 60% identity or higher (max 99%), and a last one with 20% to 99% identity. We tried to get several sequences with PDB entries into the lists, but the only sequence with a identity higher than 40% was Q30201 (HFE) itself. In contrast, the whole 40% or lower group consists only of Uniprot ACs that can be mapped to PDB entries. Of course, every group also includes the HFE protein which means that there are really 3 groups with 11 sequences each.


<figtable id="msagroup60">

Uniprot AC (Group 60-99) Identity Comment
G3QU39 99.14 Uncharacterized protein OS=Gorilla gorilla gorilla
H2PI54 97.41 Uncharacterized protein OS=Pongo abelii
Q6B0J5 95.98 HFE protein OS=Homo sapiens
G7P2L8 94.54 Putative uncharacterized protein OS=Macaca fascicularis
F7GRH8 90.52 Uncharacterized protein OS=Callithrix jacchus
F7DKE9 86.18 Uncharacterized protein OS=Callithrix jacchus
Q9GL42 79.89 Hereditary hemochromatosis protein homolog OS=Dicerorhinus sumatrensis
F6RUG7 78.16 Uncharacterized protein OS=Equus caballus
G3THV5 75.21 Uncharacterized protein (Fragment) OS=Loxodonta africana
G5BQE5 67.66 Hereditary hemochromatosis protein-like protein OS=Heterocephalus glaber

</figtable>

<figtable id="msagroup40">

Uniprot AC (Group 00-40) Identity Comment
P16391 36.03 RT1 class I histocompatibility antigen, AA alpha chain OS=Rattus norvegicus
P05534 35.13 HLA class I histocompatibility antigen, A-24 alpha chain OS=Homo sapiens
Q30597 33.72 MHC class I Mamu-A*02 (Fragment) OS=Macaca mulatta
P01900 32.11 H-2 class I histocompatibility antigen, D-D alpha chain OS=Mus musculus
Q31093 31.74 Histocompatibility 2, M region locus 3 OS=Mus musculus
P14432 29.14 H-2 class I histocompatibility antigen, TLA(B) alpha chain OS=Mus musculus
Q860W6 27.74 Major histocompatibility complex class Ib M10.5 (Fragment) OS=Mus musculus
Q31615 26.38 MHC class I H2-TL-27-129 mRNA (b haplotype), complete cds OS=Mus musculus
Q31206 25.87 MHC class I H2-TL-T10-129 mRNA (b haplotype), complete cds OS=Mus musculus
P01921 21.10 H-2 class II histocompatibility antigen, A-D beta chain OS=Mus musculus

</figtable>

<figtable id="msagroup00">

Uniprot AC (Group 00-99) Identity Comment
Q6B0J5 95.98 HFE protein OS=Homo sapiens
F7GRH8 90.52 Uncharacterized protein OS=Callithrix jacchus
F7DKE9 86.18 Uncharacterized protein OS=Callithrix jacchus
Q9GL42 79.89 Hereditary hemochromatosis protein homolog OS=Dicerorhinus sumatrensis
G5BQE5 67.66 Hereditary hemochromatosis protein-like protein OS=Heterocephalus glaber
G1PHG2 57.43 Uncharacterized protein (Fragment) OS=Myotis lucifugus
F7C3B3 40.11 Uncharacterized protein OS=Macaca mulatta
Q30597 33.72 MHC class I Mamu-A*02 (Fragment) OS=Macaca mulatta
Q860W6 27.74 Major histocompatibility complex class Ib M10.5 (Fragment) OS=Mus musculus
P01921 21.10 H-2 class II histocompatibility antigen, A-D beta chain OS=Mus musculus

</figtable>


ClustalW

ClustalW 0-40

<figure id="clustal040">

View of the alignment of the 0-40 group aligned by ClustalW

</figure>

Sequence Gap
Q30597 79
P01900 71
Q860W6 109
Q31093 100
Q31615 57
P05534 71
P01921 171
Q30201 88
P16391 65
P14432 52
Q31206 30
Conserved
23

ClustalW 0-99

<figure id="clustal099">

View of the alignment of the 0-99 group aligned by ClustalW

</figure>

Sequence Gap
Q30597 42
Q860W6 72
G5BQE5 32
Q9GL42 51
G1PHG2 61
Q6B0J5 54
P01921 134
Q30201 51
F7C3B3 146
F7DKE9 62
F7GRH8 51
Conserved
21

ClustalW 60-99

<figure id="clustal6099">

View of the alignment of the 60-99 group aligned by ClustalW

</figure>

Sequence Gap
G3THV5 12
H2PI54 25
F6RUG7 25
G5BQE5 6
Q9GL42 25
Q6B0J5 28
Q30201 25
G3QU39 25
F7GRH8 25
F7DKE9 36
G7P2L8 25
Conserved
175



Muscle

Muscle Group 0-40

<figure id="muscle040">

View of the alignment of the 0-40 group aligned by Muscle

</figure>

Sequence Gap
P01900 82
Q30597 90
Q31093 111
Q860W6 120
Q31615 68
P05534 82
Q30201 99
P01921 182
P16391 76
P14432 63
Q31206 41
Conserved
22

Muscle Group 0-99

<figure id="muscle099">

View of the alignment of the 0-99 group aligned by Muscle

</figure>

Sequence Gap
Q30597 44
Q860W6 74
G5BQE5 34
Q9GL42 53
Q6B0J5 56
G1PHG2 63
Q30201 53
P01921 136
F7C3B3 148
F7DKE9 64
F7GRH8 53
Conserved
22

Muscle Group 60-99

<figure id="muscle06099">

View of the alignment of the 60-99 group aligned by Muscle

</figure>

Sequence Gap
G3THV5 12
H2PI54 25
F6RUG7 25
G5BQE5 6
Q9GL42 25
Q6B0J5 28
Q30201 25
G3QU39 25
F7GRH8 25
F7DKE9 36
G7P2L8 25
Conserved
175



T-Coffee

T-Coffee Group 0-40

<figure id="tcoffee040">

View of the alignment of the 0-40 group aligned by T-Coffee

</figure>

Sequence Gap
Q30597 92
P01900 84
Q31093 113
Q860W6 122
Q31615 70
P05534 84
P01921 184
Q30201 101
P14432 65
P16391 78
Q31206 43
Conserved
22

T-Coffee Group 0-99

<figure id="tcoffee099">

View of the alignment of the 0-99 group aligned by T-Coffee

</figure>

Sequence Gap
Q30597 51
Q860W6 81
G5BQE5 41
Q9GL42 60
Q6B0J5 63
G1PHG2 70
P01921 143
Q30201 60
F7C3B3 155
F7DKE9 71
F7GRH8 60
Conserved
22

T-Coffee Group 60-99

<figure id="tcoffee6099">

View of the alignment of the 60-99 group aligned by T-Coffee

</figure>

Sequence Gap
G3THV5 12
H2PI54 25
F6RUG7 25
G5BQE5 6
Q9GL42 25
Q6B0J5 28
Q30201 25
G3QU39 25
G7P2L8 25
F7GRH8 25
F7DKE9 25
Conserved
175



3D-Coffee

T-Coffee Group 0-40

<figure id="3dcoffee040">

View of the alignment of the 0-40 group aligned by 3D-Coffee

</figure>

Sequence Gap
Q30597 92
P01900 84
Q31093 113
Q860W6 122
Q31615 70
P05534 84
P01921 184
Q30201 101
P14432 65
P16391 78
Q31206 43
Conserved
22



Conservation of important positions

Position 3DCoffee0-40 T-Coffee0-40 T-Coffee0-99 T-Coffee60-99 Muscle0-40 Muscle0-99 Muscle60-99 ClustalW0-40 ClustalW0-99 ClustalW60-99
110 9/10(Gap) 9/10(Gap) 8/10(Gap) 10/10 9/10(Gap) 8/10(Gap) 10/10 9/10(Mismatch) 8/10(Gap/Mismatch) 10/10
130 X X X 10/10 X X 10/10 X X 10/10
234 X X X 10/10 X X 10/10 X X 10/10
124 9/10(Gap) 9/10(Gap) 10/10 10/10 9/10(Gap) 10/10 10/10 10/10 10/10 10/10
187 10/10 10/10 10/10 10/10 10/10 10/10 10/10 10/10 10/10 10/10
225 10/10 10/10 10/10 10/10 10/10 9/10(Mismatch) 10/10 10/10 10/10 10/10
282 10/10 10/10 10/10 10/10 10/10 10/10 10/10 10/10 10/10 10/10

All positions are some at which the protein is modified.


The positions are not ordered by their appearance because of their type of modification. The first three noted positions (110, 130, 234) are positions which are modified via glycosylation. The last four are responsible for disulfide-bonds (as they're grouped together, position 124 builds a disulfide bond with position 187, the same goes for positions 225 and 282).

A X represents a non-conserved position within the alignment, meaning that 5 or less sequences have the same amino acid as the HFE sequence at that position.

One can see that in nearly all groups and in all alignments the disulfide positions are conserved. This may show that the disulfide bond is crucial for the 3d structure of the protein and therefore its function. Of the Glycosylation positions only position 110 seems to be quite conserved, meaning it has a higher probability to be important than the other glycolysation positions.

The conservation of all these positions when looking at the 60-99 groups can be explained by the high similarity of the proteins.

Also one should keep in mind that these statistics are withdrawn from 10 proteins, and due to random selection of these errors may have occured.

When looking at the domain region(positions 207-298) one can see in the MSAs that this region in all groups seems to be highly conserved. Even in the group with 20-40% identity. This is what we expected because the methods should find similar proteins and as we know mutations that last occur less often in functional domains.