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Reassessing domain architecture evolution of metazoan proteins: major impact of errors caused by confusing paralogs and epaktologs.

Nagy A, Bányai L, Patthy L - Genes (Basel) (2011)

Bottom Line: Based on these findings, we suggest that earlier genome-scale studies based on comparison of predicted (frequently mispredicted) protein sequences may have led to some erroneous conclusions about the evolution of novel domain architectures of multidomain proteins.In this manuscript we examine the impact of confusing paralogous and epaktologous multidomain proteins (i.e., those that are related only through the independent acquisition of the same domain types) on conclusions drawn about DA evolution of multidomain proteins in Metazoa.Our findings caution that earlier studies based on analysis of datasets of protein families that were contaminated with epaktologs may have led to some erroneous conclusions about the evolution of novel domain architectures of multidomain proteins.

View Article: PubMed Central - PubMed

Affiliation: Institute of Enzymology, Biological Research Center, Hungarian Academy of Sciences, Budapest H-1113, Hungary. nagya@enzim.hu.

ABSTRACT
In the accompanying paper (Nagy, Szláma, Szarka, Trexler, Bányai, Patthy, Reassessing Domain Architecture Evolution of Metazoan Proteins: Major Impact of Gene Prediction Errors) we showed that in the case of UniProtKB/TrEMBL, RefSeq, EnsEMBL and NCBI's GNOMON predicted protein sequences of Metazoan species the contribution of erroneous (incomplete, abnormal, mispredicted) sequences to domain architecture (DA) differences of orthologous proteins might be greater than those of true gene rearrangements. Based on these findings, we suggest that earlier genome-scale studies based on comparison of predicted (frequently mispredicted) protein sequences may have led to some erroneous conclusions about the evolution of novel domain architectures of multidomain proteins. In this manuscript we examine the impact of confusing paralogous and epaktologous multidomain proteins (i.e., those that are related only through the independent acquisition of the same domain types) on conclusions drawn about DA evolution of multidomain proteins in Metazoa. To estimate the contribution of this type of error we have used as reference UniProtKB/Swiss-Prot sequences from protein families with well-characterized evolutionary histories. We have used two types of paralogy-group construction procedures and monitored the impact of various parameters on the separation of true paralogs from epaktologs on correctly annotated Swiss-Prot entries of multidomain proteins. Our studies have shown that, although public protein family databases are contaminated with epaktologs, analysis of the structure of sequence similarity networks of multidomain proteins provides an efficient means for the separation of epaktologs and paralogs. We have also demonstrated that contamination of protein families with epaktologs increases the apparent rate of DA change and introduces a bias in DA differences in as much as it increases the proportion of terminal over internal DA differences.We have shown that confusing paralogous and epaktologous multidomain proteins significantly increases the apparent rate of DA change in Metazoa and introduces a positional bias in favor of terminal over internal DA changes. Our findings caution that earlier studies based on analysis of datasets of protein families that were contaminated with epaktologs may have led to some erroneous conclusions about the evolution of novel domain architectures of multidomain proteins. A reassessment of the DA evolution of multidomain proteins is presented in an accompanying paper [1].

No MeSH data available.


Related in: MedlinePlus

Analysis of the DA of clusters defined by strong component analysis of sequence similarity networks of human Swiss-Prot sequences. The numbers on the abscissa indicate the number of top-scoring matches included in the analyses (TSS = 1, …. TSS = 7) used to define paralogous clusters. The values of the ordinate show the percent of DA comparisons within clusters where the pairs compared differ in DA. (Since the number of pair-wise comparisons and computational time increased exponentially with the increase of TSS values, the figure shows only data for TSS = 1−TSS = 7).
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f7-genes-02-00516: Analysis of the DA of clusters defined by strong component analysis of sequence similarity networks of human Swiss-Prot sequences. The numbers on the abscissa indicate the number of top-scoring matches included in the analyses (TSS = 1, …. TSS = 7) used to define paralogous clusters. The values of the ordinate show the percent of DA comparisons within clusters where the pairs compared differ in DA. (Since the number of pair-wise comparisons and computational time increased exponentially with the increase of TSS values, the figure shows only data for TSS = 1−TSS = 7).

Mentions: Since, in the above classification, the size of the clusters is hidden, no distinction is made between a cluster with just a pair of sequences with identical DA and a cluster with 50 sequences of identical DAs (they are both clusters with identical DAs). Similarly, a cluster with five sequences each of which differs in DA and a cluster with 50 members just one of which differs from the others in DA, will equally qualify as a cluster with different DA. To estimate the degree of DA heterogeneity within clusters, we have calculated the percent of all-against-all DA comparisons that show a difference in DA (Table S2 and Figure 7).


Reassessing domain architecture evolution of metazoan proteins: major impact of errors caused by confusing paralogs and epaktologs.

Nagy A, Bányai L, Patthy L - Genes (Basel) (2011)

Analysis of the DA of clusters defined by strong component analysis of sequence similarity networks of human Swiss-Prot sequences. The numbers on the abscissa indicate the number of top-scoring matches included in the analyses (TSS = 1, …. TSS = 7) used to define paralogous clusters. The values of the ordinate show the percent of DA comparisons within clusters where the pairs compared differ in DA. (Since the number of pair-wise comparisons and computational time increased exponentially with the increase of TSS values, the figure shows only data for TSS = 1−TSS = 7).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3927612&req=5

f7-genes-02-00516: Analysis of the DA of clusters defined by strong component analysis of sequence similarity networks of human Swiss-Prot sequences. The numbers on the abscissa indicate the number of top-scoring matches included in the analyses (TSS = 1, …. TSS = 7) used to define paralogous clusters. The values of the ordinate show the percent of DA comparisons within clusters where the pairs compared differ in DA. (Since the number of pair-wise comparisons and computational time increased exponentially with the increase of TSS values, the figure shows only data for TSS = 1−TSS = 7).
Mentions: Since, in the above classification, the size of the clusters is hidden, no distinction is made between a cluster with just a pair of sequences with identical DA and a cluster with 50 sequences of identical DAs (they are both clusters with identical DAs). Similarly, a cluster with five sequences each of which differs in DA and a cluster with 50 members just one of which differs from the others in DA, will equally qualify as a cluster with different DA. To estimate the degree of DA heterogeneity within clusters, we have calculated the percent of all-against-all DA comparisons that show a difference in DA (Table S2 and Figure 7).

Bottom Line: Based on these findings, we suggest that earlier genome-scale studies based on comparison of predicted (frequently mispredicted) protein sequences may have led to some erroneous conclusions about the evolution of novel domain architectures of multidomain proteins.In this manuscript we examine the impact of confusing paralogous and epaktologous multidomain proteins (i.e., those that are related only through the independent acquisition of the same domain types) on conclusions drawn about DA evolution of multidomain proteins in Metazoa.Our findings caution that earlier studies based on analysis of datasets of protein families that were contaminated with epaktologs may have led to some erroneous conclusions about the evolution of novel domain architectures of multidomain proteins.

View Article: PubMed Central - PubMed

Affiliation: Institute of Enzymology, Biological Research Center, Hungarian Academy of Sciences, Budapest H-1113, Hungary. nagya@enzim.hu.

ABSTRACT
In the accompanying paper (Nagy, Szláma, Szarka, Trexler, Bányai, Patthy, Reassessing Domain Architecture Evolution of Metazoan Proteins: Major Impact of Gene Prediction Errors) we showed that in the case of UniProtKB/TrEMBL, RefSeq, EnsEMBL and NCBI's GNOMON predicted protein sequences of Metazoan species the contribution of erroneous (incomplete, abnormal, mispredicted) sequences to domain architecture (DA) differences of orthologous proteins might be greater than those of true gene rearrangements. Based on these findings, we suggest that earlier genome-scale studies based on comparison of predicted (frequently mispredicted) protein sequences may have led to some erroneous conclusions about the evolution of novel domain architectures of multidomain proteins. In this manuscript we examine the impact of confusing paralogous and epaktologous multidomain proteins (i.e., those that are related only through the independent acquisition of the same domain types) on conclusions drawn about DA evolution of multidomain proteins in Metazoa. To estimate the contribution of this type of error we have used as reference UniProtKB/Swiss-Prot sequences from protein families with well-characterized evolutionary histories. We have used two types of paralogy-group construction procedures and monitored the impact of various parameters on the separation of true paralogs from epaktologs on correctly annotated Swiss-Prot entries of multidomain proteins. Our studies have shown that, although public protein family databases are contaminated with epaktologs, analysis of the structure of sequence similarity networks of multidomain proteins provides an efficient means for the separation of epaktologs and paralogs. We have also demonstrated that contamination of protein families with epaktologs increases the apparent rate of DA change and introduces a bias in DA differences in as much as it increases the proportion of terminal over internal DA differences.We have shown that confusing paralogous and epaktologous multidomain proteins significantly increases the apparent rate of DA change in Metazoa and introduces a positional bias in favor of terminal over internal DA changes. Our findings caution that earlier studies based on analysis of datasets of protein families that were contaminated with epaktologs may have led to some erroneous conclusions about the evolution of novel domain architectures of multidomain proteins. A reassessment of the DA evolution of multidomain proteins is presented in an accompanying paper [1].

No MeSH data available.


Related in: MedlinePlus