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Human Molecular Genetics Advance Access originally published online on July 13, 2005
Human Molecular Genetics 2005 14(16):2415-2419; doi:10.1093/hmg/ddi243
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© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oupjournals.org

Prediction of pathogenic mutations in mitochondrially encoded human tRNAs

Fyodor A. Kondrashov1,2,*

1Section on Ecology, Behavior and Evolution, Division of Biological Sciences, University of California at San Diego, 2218 Muir Biology Building, La Jolla, CA 92093, USA and 2Engelhardt Institute of Molecular Biology, Vavilova 32, 119991 Moscow, Russia

* To whom correspondence should be addressed. Tel: +1 7916 2566774; Fax: +1 858 534718; Email: kondrashov{at}ucdavis.edu

Received May 30, 2005; Revised June 24, 2005; Accepted July 1, 2005


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 SUPPLEMENTARY MATERIAL
 REFERENCES
 
Some mutations in human mitochondrial tRNAs are severely pathogenic. The available computational methods have a poor record of predicting the impact of a tRNA mutation on the phenotype and fitness. Here patterns of evolution at tRNA sites that harbor pathogenic mutations and at sites that harbor phenotypically cryptic polymorphisms were compared. Mutations that are pathogenic to humans occupy more conservative sites, are only rarely fixed in closely related species, and, when located in stem structures, often disrupt Watson–Crick pairing and display signs of compensatory evolution. These observations make it possible to classify ~90% of all known pathogenic mutations as deleterious together with only ~30% of polymorphisms. These polymorphisms segregate at frequencies that are more than two times lower than frequencies of polymorphisms classified as benign, indicating that at least ~30% of known polymorphisms in mitochondrial tRNAs affect fitness negatively.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 SUPPLEMENTARY MATERIAL
 REFERENCES
 
A variety of often severe genetic disorders, mostly neuromuscular and neurodegenerative, are caused by mutations in mitochondrial (mt) DNA (1Go–4Go). These mutations may be located in mitochondrially encoded proteins, rRNAs, tRNAs and even in regulatory regions (5Go). However, mutations of the 22 mt tRNAs are of particular interest because these tRNAs span only 10% of the human mitochondrial genome yet they harbor more than half of all known mitochondrial pathogenic mutations (5Go) and, as tRNAs have a specific, cloverleaf secondary structure, such mutations may be studied from the perspective of the secondary structure of the tRNAs (6Go).

It is thought that the accurate identification of pathogenic mutations would enable researchers to describe their molecular and biochemical characteristics (7Go,8Go), which may lead to more successful treatment of the resulting pathologies (8Go,9Go). Currently, a mutation can be identified as pathogenic by a variety of different criteria (10Go), one of which is the preference for the mutation to be found at an evolutionarily conserved site, which by itself is a poor predictor of pathogenic nature of a variant (11Go–13Go). The other criteria, such as the requirement for the pathogenic mitochondria to be heteroplasmic, are not computational and often require extensive work in the laboratory (10Go). Thus, the availability of an accurate computational approach should aid rapid and inexpensive identification of novel pathogenic mutations.

Previous comparisons of pathogenic mutations and phenotypically cryptic polymorphisms in human mt tRNAs showed that pathogenic mutations are more often located at conservative sites (11Go–14Go) and stem structures (14Go) and tend to disrupt Watson–Crick (WC) nucleotide pairing in stems (11Go,14Go). However, these observations turned out to be insufficient to predict the impact of a nucleotide substitution in an mt tRNA on the phenotype and fitness (11Go,14Go). Here, an evolutionarily based computational analysis of the differences between pathogenic and non-pathogenic substitutions is described.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
DISCUSSION
 MATERIALS AND METHODS
 SUPPLEMENTARY MATERIAL
 REFERENCES
 
Pathogenic mutations and cryptic polymorphisms were mapped on multiple alignments of the 22 mt tRNAs from 138 different mammals. Both nucleotides which act as mutations and as polymorphisms in humans may be found at orthologous sites of closely related species (15Go). However, compensatory substitutions, usually restoring WC pairing (not including GU pairs), often accompany fixations of pathogenic mutations (11Go), but not of cryptic polymorphisms, in a non-human mammal. For example, a human pathogenic mutation in tRNAGly that is a part of the normal sequence of its non-human orthologs appears to be subject to WC compensation (Fig. 1A). In contrast, the WC correspondence between sites that harbor human polymorphisms and the interacting sites is less than perfect (Fig. 1B). The tendency of mt tRNA stem sites harboring pathogenic mutations to co-evolve with their complementary stems sites was used to distinguish pathogenic mutations from polymorphisms. On the basis of the criteria of conservation and compensatory co-evolution, a human variant can be classified as either benign or deleterious.




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  		Figure 1. Multiple alignment of (A) mt tRNAGly and (B) mt tRNAThr. Pathogenic mutations are labeled in red and their compensatory substitutions in blue. Polymorphic states are in green and their compensatory states in yellow. Sequences are, top to bottom, from Homo sapiens, Pan troglodytes, Pan paniscus, Gorilla gorilla, Pongo pygmaeus, Pongo pygmaeus abelii, Papio hamadryas, Macaca sylvanus, Macaca mulatto, Colobus guereza, Trachypithecus obscurus, Hylobates lar, Cebus albifrons, Lemur catta, Nycticebus coucang, Tarsius bancanus, Tupaia belangeri.

 
There are 94 known variants (47 pathogenic mutations and 47 polymorphisms) in mt tRNA stems that disrupt WC pairing. For each variant, the number of species was counted in which a variant was found without the compensatory substitution, and the number of species in which a potentially WC pairing-restoring compensatory substitution was found without the variant. For example, in Figure 1A, both of these numbers are equal to 0 (variant A is always found opposite a T) and in Figure 1B, these values are 1 and 2 for variant G, and 4 and 0 for variant A. The sum of these two numbers, obtained separately for primates only and for all mammals, was used as a gauge of evolutionary independence of the interacting sites. A variant was classified as benign if this sum was greater than two for primates (four pathogenic mutations; 15 polymorphisms) or if this sum was greater than nine for all mammals, and the site was conserved in less than 100 of the 138 (80 out of 119 for tRNALys variants, see Materials and Methods) available mammals (one pathogenic mutation; five polymorphisms). All other variants were classified as deleterious (42 pathogenic mutations; 27 polymorphisms).

If a variant within an mt tRNA stem that does not disrupt a WC pair (two pathogenic mutation and 38 polymorphisms total) affects a site that is conserved in more than 128 of the 138 available mammals (108 out of 119 for tRNALys variants, see Materials and Methods), and the variable nucleotide was found in fewer than five mammals, it was classified as deleterious (two pathogenic mutation; four polymorphisms) and other variants (34 polymorphisms) were classified as benign. Together, these criteria place 94% pathogenic mutations localized in the stems, and 36% of such cryptic polymorphisms, into the deleterious category.

Without tertiary structure information, the only available data on tRNA loops are sequence conservation. Previous attempts to distinguish pathogenic mutations from polymorphisms relied on sequence conservation in all the available mammalian orthologs (11Go). However, this dataset is too diverse, because mt tRNA loops are often not conserved even within primates (Fig. 1), and the use of non-primate mammals may obscure the pattern of conservation. In general, the use of closely related species is preferred, because of the possibility of functional or compensatory changes in more distant orthologs.

Two criteria were applied to 18 pathogenic mutations and 98 polymorphisms located outside of stems: (i) whether a variant is found in one of the five non-human Greater Ape species and (ii) the level of conservation in all of the 17 primate species of the site of a variant. A variant was classified as benign if it was present in at least one Greater Ape species (one pathogenic mutation; 42 polymorphisms) or if its site was not conservative, in the sense that its most common nucleotide was found in less than 15 out of 17 primate species (one pathogenic mutation; 35 polymorphisms). Otherwise, a variant was classified as deleterious (16 pathogenic mutations; 21 polymorphisms). This simple approach classifies as deleterious 89% of pathogenic mutations and only 21% of polymorphisms located outside of stem structures.

Among all the known variants within all human mt tRNAs, ~70% of polymorphisms were classified as benign, whereas the rate of false negative predictions was low: only ~10% of all known pathogenic mutations were classified as benign (Fig. 2). The classification of ~90% of all pathogenic mutation as deleterious is a substantial improvement over previous results (11Go,14Go). Still, classification of ~30% of phenotypically cryptic polymorphisms as deleterious may appear as a deficiency of the proposed analysis, should it represent the rate of false positive prediction. Previous analyses assumed that all segregating polymorphisms are selectively neutral (11Go,14Go). However, owing to a very high mutation rate of the mitochondrial DNA (16Go), many segregating variants may be deleterious (17Go). In addition, some polymorphisms may be sequencing errors or heteroplasmic variants.



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  		Figure 2. Frequency of 184 polymorphisms (white) and 68 pathogenic mutations (grey) classified as benign (131 polymorphisms; seven pathogenic mutations) and deleterious (52 polymorphisms; 60 pathogenic mutations). Error bars represent the standard deviation.

 
Indeed, the average frequency of polymorphisms classified as deleterious (0.0014) is more than two times lower than that of the polymorphisms classified as benign (0.0032), which is highly significant (n1=131, n2=52, U=4401.0, P<0.0018, two-tailed Mann Whitney U-test). Most of the polymorphisms that were classified as deleterious are singletons, i.e. they are present in only one of the 2064 individuals from which the data on segregating variants have been obtained (18Go) and few were found in more than two individuals (Fig. 3). The 52 different polymorphisms that were classified as deleterious were found 340 times in the sample of 2064 individuals from the human population, although all the 183 polymorphisms were found 1415 times. Thus, ~30% of all polymorphisms in human tRNAs classified as deleterious (52/183), indeed, reduce fitness, despite the lack of obvious phenotypic manifestation. The probability that a polymorphism drawn at random from the human population is deleterious is ~25% (340/1415). The high estimate is not surprising because some of the polymorphisms found in the human population used in this study are known to contribute to the progression of mitochondrial disease (17Go). However, these estimates were made using a highly non-random sample of the human population (18Go) and more accurate measurements are needed to make a more reliable qualitative estimate.



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  		Figure 3. Frequency distribution of polymorphisms classified as benign (white) and deleterious (grey). Error bars represent the standard deviation.

 
Taken together, these observations suggest that the described method has a high rate of accuracy for distinguishing benign variants from severely and slightly pathogenic ones. To aid the identification of new pathogenic variants, this method was applied to all possible mutations of the 22 mt tRNAs (Supplementary Material). As expected, the mutations disrupting WC pairing in stems were predicted to have the highest probability of being deleterious (2218 deleterious mutations out of 2346 mutations total), whereas mutations in stems that to do not disrupt WC pairs have the lowest (104 out of 354). Mutations that are not located in stems have an intermediate probability of being deleterious (1095 out of 1767), most likely due to the inclusion of the highly conserved anticodon loop. Obviously, most lethal mutations should also be classified as deleterious by this approach.


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
MATERIALS AND METHODS
 SUPPLEMENTARY MATERIAL
 REFERENCES
 
Polymorphisms classified here as deleterious are not necessarily overtly pathogenic, because even a slight decrease in fitness is enough to reduce the frequency of a variant (19Go). However, the identification of a relatively high proportion of slightly deleterious polymorphisms is not necessarily a disadvantage of the proposed method even from a medical perspective. It is likely that many of the identified deleterious polymorphisms either contribute epistatically to the progression of many mitochondrial disorders (17Go) or slightly reduce life expectancy (20Go,21Go). Investigation of the impact of such polymorphisms on fitness may lead to more accurate description of the impact of these polymorphisms on morbidity and mortality.

Similar attempts to discriminate pathogenic mutations from polymorphisms were made for amino acid replacements in nuclear encoded proteins (22Go,23Go). However, the described analysis of pathogenic mutations in mt tRNAs is slightly more successful than that in proteins, possibly because of the difficulty of predicting patterns of compensatory evolution in proteins (24Go), relative to tRNAs (15Go). Many polymorphisms found in nuclear encoded proteins are deleterious (22Go,23Go); future application of the method described here for the identification of deleterious variants in the two rRNA genes encoded in the mitochondria and the application of protein-based methods (25Go) for the identification of deleterious variants in 13 mitochondrially encoded proteins should lead to an estimate of the genetic load (26Go) of the mitochondrial genome.

There are four reasons why the method described here appears to have a higher accuracy than those that were published previously (11Go,14Go). First, sites in mt tRNAs were segregated into three, rather than two, structural categories. Secondly, this method allows for the possibility of having a variable site that excludes a particular nucleotide, i.e. it allows for the possibility that A, T and G are neutral equivalents and C is deleterious. Thirdly, use patterns of compensatory evolution were used in stem sites that disrupt WC pairs. Finally, sequence conservation information is used only in closely related species. Further improvement of this method may be based fine-tuning the cutoff values that were used, or on the addition of other ways to distinguish pathogenic and polymorphic variants. For example, the use of tertiary structure information improves the prediction of pathogenic mutations in proteins (23Go) and should help to improve the method of pathogenic mutation prediction for mt tRNAs as well. However, given that sequence similarity of closely related species is a good predictor of pathogenicity, the present method can be improved by the availability of mitochondrial sequences of other primate species, especially from Platyrrhini and Strepsirhini, of which only three species are currently available.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
SUPPLEMENTARY MATERIAL
 REFERENCES
 
A list of pathogenic mutations was taken from MitoMap (5Go) (http://www.mitomap.org/) and a list of polymorphisms from mtDB (18Go) (http://www.genpat.uu.se/mtDB/). Those pathogenic mutations whose status was listed as ‘unclear’ in MitoMap were excluded from the analysis. Data from the recent re-evaluation of the pathogenicity of mutations reported in MitoMap (14Go) were used with a slight modification: data on sequence conservation was excluded from the score of pathogenicity [see Supplemental Material from McFarland et al. (14Go)]. Those mutations that were listed in MitoMap and scored less than six on the scale of pathogenicity (minus the score from the conservation column from McFarland et al. (14Go)] were removed from the list of pathogenic mutations. In addition, the mutation 606(A->G) was excluded from the list of pathogenic mutations because of the raised doubts of its pathogenic nature (27Go). Finally, variants that were listed as pathogenic mutations and as polymorphisms were not included in either category. The final dataset included 67 pathogenic mutations and 183 polymorphisms. The cutoff values that were used to classify variants as pathogenic or benign were chosen according to the expected fraction of non-WC compensations among all observed compensatory events in primates and mammals, which were published previously (15Go). The fraction of non-WC compensations was ~5% for pathogenic compensations in WC pairs (11Go), and as there are two interacting nucleotides in a WC pair, it implies that 10% of the nucleotides involved in WC pairing may be subject to non-WC compensations. Thus, the cutoff values for WC compensations in WC pairs were two out of 17 (~12%) in primate species and 15 out of 138 (~11%) in all mammals. Sequence conservation cutoff values were taken as ~5% for non-WC pairs, as was done previously (11Go), and a more relaxed threshold of ~20% was chosen for sites located outside of stem structures because of a substantially higher fraction of compensatory evolution in such sites (15Go). Complete mitochondrial sequences from 138 different mammalian species were obtained from GenBank by using ‘mammal AND complete AND genome AND mitochondria’ as a keyword in the Entrez retrieval system (28Go). Only one mitochondrial sequence was used from each mammal, and the possibility that a polymorphism in humans randomly occurs at the same site as a polymorphism in another species was ignored. Alignments of tRNA genes were made with CLUSTALW (29Go) and manually corrected using secondary structure information published previously (6Go). Annotations of tRNA genes were manually corrected for several species using data on sequence similarity from closely related species. Different cutoff values were used for variants located in mt tRNALys when estimating the level of conservation in stem sites because this gene is missing in marsupial species (30Go). In calculating average frequencies of benign and deleterious polymorphisms, but not in the application of the Mann Whitney U-test, three outliers (polymorphisms with a frequency>0.05) were removed.


   SUPPLEMENTARY MATERIAL
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 SUPPLEMENTARY MATERIAL
REFERENCES
 
Supplementary Material is available at HMG Online.


   ACKNOWLEDGEMENTS
 
The author thanks P. Andolfatto, D. Bachtrog, N. Esipova, S. Makeev, A. Kondrashov, V. Ramensky, V. Tumanyan and P. Vlasov for a critical reading of the manuscript. The author is an NSF Graduate Research Fellow. This work was supported by a Contract of the Russian Ministry of Science and Education (02.434.11.1008 [EC] ) and a grant on Molecular and Cellular Biology from RAS.

Conflict of Interest statement. None declared.


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 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 SUPPLEMENTARY MATERIAL
 REFERENCES
 

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