Sequence-based mutation analysis Gaucher Disease

The aim of this task was to carry out a thorough analysis of ten mutations and to classify them as disease-causing and non-disease causing. The mutations have been selected by another group from our set of mutations such that their impact had been unknown for us prior to this task. We investigated the provided mutations with respect to their physicochemical properties, structural features, as well as their conservation and employed the tools, SIFT, Polyphen2, as well as SNAP for predicting their impact on the phenotype. For quantifying to which extend the mutations are disease causing, we assigend a disease score where -1 means non-disease causing, 0 ambiguous, and 1 disease causing. We averaged the disease scores to obtain a final prediction which we compared with the true impact of the mutation on the phenotype. Technical details are reported in our protocol.

Mutations

<xr id="tab:mutations"/> contains five randomly chosen Gaucher disease-causing and five non-disease-causing mutations. Disease causing mutations were sampled from the HGMD whereas non-disease causing mutations were sampled from a set of mutations which were present in the dbSNP but not in the HGMD. Reference sequence was P04062 which has a 39 residue signal peptide. The ten mutations listed in <xr id="tab:mutations"/> were investigated in the following.

<figtable id="tab:mutations">

Nr	Position	From	To
1	99	H	R
2	211	V	I
3	150	E	K
4	236	L	P
5	248	W	R
6	509	L	P
7	351	W	C
8	423	A	D
9	482	D	N
10	83	R	S

Randomly selected mutations from HGMD and dbSNP which were used for the sequence-based mutation analysis. </figtable>

Physicochemical properties

We compared the charge, polarity, size, and the aromatic character of the wild-type and mutant amino-acid and assigned a disease-score of 1 to those mutations, which have a severe impact on the physicochemical properties (cf. <xr id="tab:props"/>). Mutations number 3 changes the polarity since glutamate is acidic but lysine basic. We also considered mutation number 5 and 7 disease-causing as tryptophan is aromatic and unpolar, in contrast to the target residues. Substituting alanine, which is small and unpolar, by the long and acidic aspartate might also impact the structure and function of the protein.

<figtable id="tab:props">

Nr	Wildtype					Mutant					Disease score
	AA	Charge	Polarity	Size	Aromatic	AA	Charge	Polarity	Size	Aromatic
1	H	negative	polar	large	no	R	negative	polar	large	no	-1
2	V	neutral	unpolar	medium	no	I	neutral	unpolar	medium	no	-1
3	E	positive	polar	large	no	K	negative	polar	large	no	1
4	L	neutral	unpolar	medium	no	P	neutral	unpolar	medium	no	-1
5	W	neutral	unpolar	large	yes	R	negative	polar	large	no	1
6	L	neutral	unpolar	medium	no	P	neutral	unpolar	medium	no	-1
7	W	neutral	unpolar	large	yes	C	neutral	polar	small	no	1
8	A	neutral	unpolar	small	no	D	positive	polar	medium	no	1
9	D	positive	polar	medium	no	N	neutral	polar	medium	no	-1
10	R	negative	polar	large	no	S	neutral	polar	small	no	0

Physicochemical properiets of the wildtype and mutatant amino acid which were used to classify the mutation as severe or non-severe. </figtable>

Structural analysis

We used the HHsearch alignment for mapping the mutations of <xr id="tab:mutations"/> onto 2nt0_Aand investigated for each mutated site its solvent accessibility (buried or exposed), secondary structure (H=Helix, S=Sheet, C=coil), and whether it takes places in a domain region. Based-upon these features, we estimated a disease score (cf. <xr id="tab:structure"/>, <xr id="fig:structure_all"/>).

<figtable id="tab:structure">

Nr	Mutation	Acc	2nd structure	Domain region	Mutation	Disease score
1	H99R	exposed	C	no		-1
2	V211I	exposed	C	no		-1
3	E150K	exposed	C	no		-1
4	L236P	exposed	C	no		0
5	W248R	buried	H	yes		1
6	L509P	exposed	S	yes		1
7	W351C	exposed	S	yes		0
8	A423D	buried	C	yes		1
9	D482N	exposed	C	yes		-1
10	R83S	exposed	C	yes		-1

Location of mutations in 2nt0_A. Blue: wildtype; Red: mutant; Acc: Solvent accessibility. </figtable>

<figure id="fig:structure_all">

2nt0_A along with the selected wildtype residues from <xr id="tab:mutations"/> in blue.

</figure>

W248R takes place in the hydrophobic core region of the TIM beta/alpha-barrel domain and inserting a hydrophilic, arginine is likely to impair the catalytic activity of the enzyme, although it does no change the secondary structure according to the PSI-PRED prediction. Same holds true for A423D. We though L509P as disease-causing as Proline turned the sheet into a loop region at this site. W351C might change the protein structure due to the formation of disulide bonds.

Conservation

The conservation of an amino acid indicates its importance for the structure and function of the protein. The log-odds substitution score is used to quantify the likelihood of a substitution where a negative score indicates that the substitution is observed less frequently than expected by chance. This is primarily due to different physicochemical properties which cause severe structural changes such that the resulting protein is negatively selected. Hence, substitutions with a negative score a likely to be disease-causing whereas a positive score indicates that the mutation does not affect the protein.

BLOSUM62 scores

The BLOSUM62 matrix substitution matrix was derived by clustering sequences of the Blocks database with a minimal identity of 62% and counting inter-cluster substitutions. The evolutionary distance underlying the BLOSUM62 matrix turned out to be suitable for many applications. We labeled substitutions with a score close to the minimal score as disease-causing (cf. <xr id="tab:subst_blosum"/>).

<figtable id="tab:subst_blosum">

Nr	Mutation	Score mutation	Score min	Score max	Disease score
1	H99R	0	-3	8	0
2	V211I	3	-3	4	-1
3	E150K	1	-4	5	0
4	L236P	-3	-4	4	1
5	W248R	-3	-4	11	1
6	L509P	-3	-4	4	1
7	W351C	-2	-4	11	1
8	A423D	-2	-3	4	1
9	D482N	1	-4	6	0
10	R83S	-1	-3	5	0

BLOSUM62 scores of the selected mutations. </figtable>

PSSM of all hits

A Position Specific Scoring Matrix (PSSM) or profile is a matrix which stores the probability P(a|i) to an observed amino acid a at position i. It is derived from a sequence alignment and the position specific substitution scores S(a,b)=log P(a|i)/ P(a) are more precise than the general BLOSUM62 scores. We therefore computed an alignment (cf. <xr id="fig:subst_pssm_all_ali"/>) from all significant sequences found by performing five rounds PSI-BLAST, computed a PSSM (cf. <xr id="fig:subst_pssm_all"/>) and used the position specific substitution scores to assign a disease score for each mutation (cf. <xr id="tab:subst_pssm_all"/>). Mutations 5-7 were though of as disease-causing since their substitution score were close to the minimum and the sites were highly conserved.

</figure> </figure>

Sequence alignment of P04062 derived from all significant hits after 5 rounds PSI-BLAST

PSSM of P04062 derived from all significant hits after 5 rounds PSI-BLAST.

<figure id="fig:subst_pssm_all_ali">

<figure id="fig:subst_pssm_all">

<figtable id="tab:subst_pssm_all">

Nr	Mutation	Score mutation	Score min	Score max	Conservation	Disease score
1	H99R	0	-4	2		0
2	V211I	4	-4	4		-1
3	E150K	0	-4	5		0
4	L236P	0	-3	1		0
5	W248R	-2	-3	4		1
6	L509P	-6	-6	4		1
7	W351C	-3	-6	9		1
8	A423D	-3	-3	3		1
9	D482N	4	-4	4		-1
10	R83S	0	-3	2		0

Position specific substitution scores derived from all significant hits after 5 rounds PSI-BLAST. The respective profile column is shown on the right. </figtable>

PSSM of close homologous sequences

By performing five rounds PSI-BLAST, also distant homologous sequences are recognised whose function is not conversed, i.e. proteins with different functions are incorporated into the alignment. We therefore built an alignment using only the closest homologous sequences which probably exhibit the same catalytic activity than the query sequence. For this, we used HHfilter and the option -qsc 1.0 for filtering the alignment depicted in <xr id="fig:subst_pssm_all_ali"/> from 1050 sequences to only 60 sequences. The resulting alignment is shown in <xr id="fig:subst_pssm_best_ali"/> and the corresponding profile in <xr id="fig:subst_pssm_best"/> which is clearly less diverse than the profile shown in <xr id="fig:subst_pssm_all"/>. Since less sequences entered the alignment, also the substitution scores became more extreme (cf. <xr id="tab:subst_pssm_best"/>). However, we assigned the same disease scores, expect for L236P, as the lysine was more conserved.

</figure> </figure>

Sequence alignment of P04062 derived from the 60 closest homologous sequences after 5 rounds PSI-BLAST

PSSM of P04062 derived from the 60 closest homologous sequences after 5 rounds PSI-BLAST.

<figure id="fig:subst_pssm_best_ali">

<figure id="fig:subst_pssm_best">

<figtable id="tab:subst_pssm_best">

Nr	Mutation	Score mutation	Score min	Score max	Conservation	Disease score
1	H99R	0	-3	8		0
2	V211I	3	-3	4		-1
3	E150K	1	-4	5		0
4	L236P	-3	-4	4		1
5	W248R	-3	-4	11		1
6	L509P	-3	-4	4		1
7	W351C	-2	-4	11		1
8	A423D	-2	-3	4		1
9	D482N	1	-4	6		-1
10	R83S	-1	-3	6		0

Position specific substitution scores derived from the 60 closest homologous sequences after 5 rounds PSI-BLAST. The respective profile column is shown on the right. </figtable>

Scoring Mutants

SIFT

SIFT (Sorting Intolerant From Tolerant) is a sequence homology-based tool that predicts whether an amino acid substitution in a protein will effect its function or not. SIFT is based on the thought that the functional related amino acids should be conserved and the mutations at such positions will lead to the change of protein function. protein evolution is correlated with protein function. On the contrary, the unimportant position will show much more amino acids variation.

The predicted results from SIFT is shown in <xr id="tab:subst_sift"/>, where the substitutions with a score less than 0.05 are predicted to affect the protein function, otherwise should be tolerated:

<figtable id="tab:subst_sift">

Nr	Mutation	Prediction	Score	Sequence conservation	Disease score
1	H99R	TOLERATED	0.74	3.11	-1
2	V211I	TOLERATED	1.0	3.10	-1
3	E150K	TOLERATED	0.44	3.10	-1
4	L236P	AFFECT PROTEIN FUNCTION	0.00	3.10	1
5	W248R	AFFECT PROTEIN FUNCTION	0.00	3.10	1
6	L509P	AFFECT PROTEIN FUNCTION	0.01	3.11	1
7	W351C	AFFECT PROTEIN FUNCTION	0.00	3.10	1
8	A423D	AFFECT PROTEIN FUNCTION	0.01	3.10	1
9	D482N	TOLERATED	0.77	3.10	-1
10	R83S	AFFECT PROTEIN FUNCTION	0.05	3.10	1

SIFT prediction results of the selected mutations. </figtable>

Polyphen2

PolyPhen-2 (Polymorphism Phenotyping v2) predicts whether an amino acid substitution will effect the protein function by using straightforward physical and comparative considerations. There are two pairs of datasets used to train and test PolyPhen-2 prediction models. HumDiv uses all damaging alleles with known effects on the molecular function causing human Mendelian diseases from UniProtKB database. The differences between human proteins and their closely related mammalian homologs are assumed to be non-damaging. HumVar uses all human disease-causing mutations from UniProtKB. The common human nsSNPs (MAF>1%) without annotated involvement in disease are assumed to be as non-damaging.

The predicted results from Polyphen2 is shown in <xr id="tab:subst_polyphen2"/>. Mutations with score near to 0 are predicted as "benign" and those with score near to 1 are predicted as "probably damaging":

<figtable id="tab:subst_polyphen2">

Nr	Mutation	HumDiv				HumVar				Disease score
		Prediction	Score	Sensitivity	Specificity	Prediction	Score	Sensitivity	Specificity
1	H99R	benign	0.000	1.00	0.00	benign	0.000	1.00	0.00	-1
2	V211I	benign	0.000	1.00	0.00	benign	0.001	0.99	0.09	-1
3	E150K	benign	0.000	1.00	0.00	benign	0.001	0.99	0.09	-1
4	L236P	probably damaging	1.000	0.00	1.00	probably damaging	1.000	0.00	1.00	1
5	W248R	probably damaging	1.000	0.00	1.00	probably damaging	0.999	0.09	0.99	1
6	L509P	probably damaging	0.992	0.70	0.97	probably damaging	0.988	0.53	0.95	1
7	W351C	probably damaging	1.000	0.00	1.00	probably damaging	1.000	0.00	1.00	1
8	A423D	probably damaging	1.000	0.00	1.00	probably damaging	0.996	0.36	0.97	1
9	D482N	benign	0.000	1.00	0.00	benign	0.002	0.99	0.18	-1
10	R83S	benign	0.007	0.96	0.75	benign	0.019	0.95	0.55	-1

PolyPhen2 prediction results of the selected mutations. </figtable>

SNAP

SNAP(screening for non-acceptable polymorphisms) is a tool for evaluating effects of single amino acid substitutions on protein function. It was developed by Yana Bromberg in Rost Lab, at Columbia University, New York.

The predicted results from SNAP is shown in <xr id="tab:subst_sift"/>, where Reliability indices are indicative of confidence in prediction and Expected Accuracy illustrate the likelihood that a given prediction is correct.

<figtable id="tab:subst_sift">

Nr	Mutation	Prediction	Reliability Index	Expected Accuracy	Disease score
1	H99R	Neutral	7	94%	-1
2	V211I	Neutral	7	94%	-1
3	E150K	Neutral	6	92%	-1
4	L236P	Non-neutral	0	58%	1
5	W248R	Non-neutral	2	70%	1
6	L509P	Neutral	0	53%	-1
7	W351C	Non-neutral	3	78%	1
8	A423D	Non-neutral	1	63%	1
9	D482N	Neutral	4	85%	-1
10	R83S	Neutral	3	78%	-1

SNAP prediction results of the selected mutations. </figtable>

Discussion

Summary

In <xr id="tab:discussion"/> we see a summary of the sequence-based mutation analysis. The prediction results by using different properties/methods listed above are presented here again, and with a predicted disease score which is defined as:

• -1 = non-disease causing
• 1 = disease causing
• 0 = ambiguous

A final disease score is obtained by computing the weighted average of all individual disease scores. i.e.:

final disease score = sum (weights f each methods * its predicted disease score)/sum (weight of each method)

And the final prediction is made following this rule:

• "non-disease causing" if the final disease score <= 0.0

• "disease causing" if the final disease score > 0.0

<figtable id="tab:discussion">

Property		1	2	3	4	5	6	7	8	9	10	Prediction
Name	Weight	H99R	V211I	E150K	L236P	W248R	L509P	W351C	A423D	D482N	R83S	Accuracy
Physicochemical	1.0	-1	-1	1	0	1	-1	1	1	-1	0	80%
Structure	1.0	-1	-1	-1	-1	1	1	0	1	-1	-1	60%
BLOSUM62	0.2	0	-1	0	1	1	1	1	1	0	0	50%
PSSM all	0.4	0	-1	0	0	1	1	1	1	-1	0	50%
PSSM close	0.4	0	-1	0	1	1	1	1	1	-1	0	60%
SIFT	1.0	-1	-1	-1	1	1	1	1	1	-1	1	70%
Polyphen2	1.0	-1	-1	-1	1	1	1	1	1	-1	-1	80%
SNAP	1.0	-1	-1	-1	1	1	-1	1	1	-1	-1	90%
Average disease score		-0.83	-1.00	-0.50	0.43	1.00	0.33	0.83	1.00	-1.00	-0.33
Prediction		!Disease	!Disease	!Disease	Disease	Disease	Disease	Disease	Disease	!Disease	!Disease	80%
Verification		!Disease	!Disease	Disease	Disease	Disease	!Disease	Disease	Disease	!Disease	!Disease

Summary of the sequence-based mutation analysis. A final disease score is obtained by computing the weighted average of all individual disease scores. Mutations with an average disease score above 0.0 are considered as disease-causing and non-disease causing otherwise. green: "non-disease causing", red: "disease causing", yellow: "ambiguous". </figtable>

Here we can see the individual properties/methods that we used to predict the effect of the mutations show variant prediction performance. Simply Using the physicochemical analysis returned 80% prediction accuracy. It suggests that the mutation causing physicochemical change will tend to affect significantly the protein function.

Other property analysis, like the structural analysis, conservation analysis using BLOSUM and PSSM, do not perform well (with around 50% prediction accuracy). Since such analysis was done manually and could be very subjective. Therefore the prediction results vary from person to person. Still, the quite low prediction accuracy from these analysis maybe suggest that only considering the structure change or sequence conservation lonely is not sufficient to make a good prediction. Combining these methods might improve the prediction accuracy.

All the prediction tools, SIFT, PolyPhen-2 and SNAP, have returned satisfied prediction results. Among them, SNAP shows the best prediction accuracy, 90%.

The final prediction has 80% prediction accuracy which satisfied us. However, a little worse than that from SNAP. The reason is clear: since the final prediction was made by combining all the individual properties/methods prediction, relative worse prediction results from structure and sequence conservation analysis brought a negative influence.

H99R

• H99R is not disease causing, since it is not listed in the HGMD.
• The final prediction is correct.
• The estimated disease-scores are correct expect for the conservation-based approaches. Here, we decided to assign a disease score of 0 (ambiguous), since the mutation happens just as often as expected by random and is not positively selected. Since the score is not negative, i.e. the mutation is not negatively selected, we might have also defined the mutation as non-disease-causing.
• The fact that H99R is non-disease-causing can be accounted primarily by the similar physicochemical properties of histidine and arginine (both basic) and the fact that the mutation does no affect the core region of the enzyme.

• All three conservation analysis returned intermediate score "0" which suggest a neither close nor distant conservation relationship between two residuese. It can not lead to a clear prediction. Therefore, we gave an "ambiguous" effect for that mutation.

• All three scoring tools predicted it as non-disease mutation which confirmed the above analyses again.

V211I

• V211I is not disease causing, since it is not listed in the HGMD.
• The final prediction is correct.
• All the individual property/methods returned correct prediction.
• Valine and isoleucine are both hydrophobic and are thus interchangeable without changing the structure/function of the enzyme. This is also indicated by the positive substitution score.
• The structural analysis showed that the mutated site is exposed and is not part of a helix or sheet which makes the mutation less likely to impair the structure/function of the protein.

E150K

• Gaucher disease type 1 <ref name="E150K">Rozenberg R, Fox DC, Sobreira E, Pereira LV. (2006). Detection of 12 new mutations in Gaucher disease Brazilian patients. Blood Cells Mol Dis. [1]</ref>
• The final prediction was wrong.
• Only the physicochemical analysis was correct.
• Changing the acidic glutamate into a basic lysine probably impairs the enzymatic activity although the mutated site is not in the core region of the enzyme. This suggests that also mutation outside of the core region can effect the protein function.
• Both SIFT, Polypen2, and SNAP considered the mutation as non-disease-causing despite the different physicochemical properties of the residues.

L236P

• Gaucher disease type 1 <ref name="L236P">Beutler E, Gelbart T, Scott CR. (2005). Hematologically important mutations: Gaucher disease. Blood Cells Mol Dis. [2]</ref>
• The final prediction was wrong.
• The physicochemical and structural analysis was wrong. The prediction of SIFT, Polypen2, and SNAP as correct.
• We defined the mutation from leucine to proline as ambiguous, since (1) both amino acids are hydrophobic, (2) the mutated site is not part of a helix which would be broken by proline, and (3) the mutated site is not part of one of the two domains. However, the mutated site is in the vicinity of the core region which might account the detrimental effect of the mutation.

W248R

• Gaucher disease [3]
• The final prediction is correct.
• All the individual property/methods returned correct prediction.

• This mutation is from tryptophan to arginine showing a change from a large sized unpolar residue with neutral charge to another large sized polar residue with negative charge. tryptophan is aromatic but arginine not. These two residues have obviously different physicochemical properties. Losing a ring structure might change the structure of the protein. Therefore, notable effect on the protein function is expected.

• The structural analysis shows that the mutated site is buried and has a alpha helix secondary structure on the domain region. Observation shows that it takes place in the hydrophobic core region of the TIM beta/alpha-barrel domain and inserting a hydrophilic, arginine is likely to impair the catalytic activity of the enzyme, although it does no change the secondary structure according to the PSI-PRED prediction. Therefore, it is predicted as a harmful mutation.

L509P

• L509P is not disease causing, since it is not listed in the HGMD.
• The final prediction is correct.
• However, only physicochemical analysis and SNAP returned correct prediction.

• This mutation is from leucine to proline showing a change from a medium sized nonpolar residue with neutral charge to another medium sized nonpolar residue with neutral charge. Both are not aromatic. These two residues share similar phisicochemical properties.

• The structural analysis shows that the mutated site is exposed and has a beta sheet secondary structure on the domain region. Observation shows that the mutation to proline tends to turn the sheet into a loop region at this site. Therefore, it is predicted as a harmful mutation which is not confirmed by verification from HGMD.

• All three conservation analysis returned scores which tend to be negative which suggest that such mutation might happen very rarely and might be disease causing.

• SIFT and PolyPhen-2 predicted it as disease causing mutation while SNAP reported it as non-disease causing.

• It is interesting to note that only physicochemical analysis and SNAP returned correct prediction. There could be two different explanation:

1. SNAP performances well with this mutation.
2. Or it suggests that this muatation might be a true disease causing mutation but is still not reported and is confirmed by HGMD.

W351C

• Gaucher disease type 1 [4]
• The final prediction is correct.
• All the individual property/methods but structural analysis returned correct prediction.

• This mutation is from tryptophan to cysteine showing a change from a large sized nonpolar residue with neutral charge to another small sized polar residue with neutral charge. tryptophan is aromatic but cysteine not. These two residues have obviously different physicochemical properties. Losing a ring structure might change the structure of the protein. Therefore, notable effect on the protein function is expected.

• The structural analysis shows that the mutated site is exposed and has a beta sheet secondary structure on the domain region. The mutation might change the protein structure due to the formation of disulfide bonds. However not for sure, therefore, it is predicted as "ambiguous".

• All three conservation analysis returned scores which tend to be negative which suggest that such mutation might happen very rarely and might be disease causing.

• All three scoring tools predicted it as disease mutation which confirmed the above analyses again.

A423D

• Gaucher disease [5]
• The final prediction is correct.
• All the individual property/methods returned correct prediction.

• This mutation is from alanine to aspartic acid showing a change from a small sized nonpolar residue with neutral charge to another medium sized polar residue with positive charge. Both are not aromatic. These two residues have obviously different physicochemical properties. Such mutation might change the structure of the protein. Therefore, notable effect on the protein function is expected.

• The structural analysis shows that the mutated site is buried and has a coil secondary structure on the domain region. Similar to the mutation W248R, this mutation occurs in the hydrophobic core region of the TIM beta/alpha-barrel domain. Insertion of an aspartic acid might influences the catalytic activity of the enzyme. Therefore, it is predicted as a harmful mutation.

• All three conservation analysis returned scores which tend to be negative which suggest that such mutation might happen very rarely and might be disease causing.

• All three scoring tools predicted it as disease mutation which confirmed the above analyses again.

D482N

• D482N is not disease causing, since it is not listed in the HGMD.
• The final prediction is correct.
• All the individual property/methods but structural analysis and BLOSUM62 returned correct prediction.

• This mutation is from aspartic acid to asparagine showing a change from a medium sized polar residue with positive charge to another medium sized polar residue with neutral charge. Both are not aromatic. These two residues share similar phisicochemical properties. Therefore, such change will probably lead to very minor effect on the protein function.
• The structural analysis shows that the mutated site is exposed and has a coil secondary structure on the domain region. It suggests that such mutation might not effect the protein function since the both residues have similar phisicochemical properties.
• All three conservation analysis returned scores which tend to be positive which suggest that such mutation might happen randomly and should be non disease causing.
• All three scoring tools predicted it as non-disease mutation which confirmed the above analyses again.

R83S

• R83S is not disease causing, since it is not listed in the HGMD.
• The final prediction is correct.
• However, only the structural analysis, PolyPhen-2 and SNAP returned correct prediction.

• This mutation is from arginine to serine showing a change from a large sized polar residue with negative charge to another small sized polar residue with neutral charge. Both are not aromatic. These two residues do not seem to share similar phisicochemical properties. however, the changes could be not very significant. Therefore, we predicted it as "ambiguous" since the effect of such mutation is not very clear only based on physicochemical analysis.
• The structural analysis shows that the mutated site is exposed and has a coil secondary structure on the domain region. It suggests that such mutation might not effect the protein function although the both residues do not share very close phisicochemical properties.

• All three conservation analysis returned intermediate score near to "0" which suggest a neither close nor distant conservation relationship between two residuese. It can not lead to a clear prediction. Therefore, we gave an "ambiguous" effect for that mutation.

• Polyphen-2 and SNAP predicted it as non-disease causing mutation which confirmed the above analyses. However, SIFT predicted it as disease mutation. Looking at the score from SIFT for this mutation "0.05", we can see it is just at the boundary. So such prediction is not very trustable. If we lowered that threshold, it will be also predicted as a disease causing mutation. Overall, the scoring tools have returned correct prediction.

References

<references/>