Dissection of genetically complex traits with extremely large pools of yeast segregants.

Most heritable traits, including many human diseases, are caused by multiple loci. Studies in both humans and model organisms, such as yeast, have failed to detect a large fraction of the loci that underlie such complex traits. A lack of statistical power to identify multiple loci with small effects is undoubtedly one of the primary reasons for this problem. We have developed a method in yeast that allows the use of much larger sample sizes than previously possible and hence permits the detection of multiple loci with small effects. The method involves generating very large numbers of progeny from a cross between two Saccharomyces cerevisiae strains and then phenotyping and genotyping pools of these offspring. We applied the method to 17 chemical resistance traits and mitochondrial function, and identified loci for each of these phenotypes. We show that the level of genetic complexity underlying these quantitative traits is highly variable, with some traits influenced by one major locus and others by at least 20 loci. Our results provide an empirical demonstration of the genetic complexity of a number of traits and show that it is possible to identify many of the underlying factors using straightforward techniques. Our method should have broad applications in yeast and can be extended to other organisms.

Genetic basis of hidden phenotypic variation revealed by increased translational readthrough in yeast.

Eukaryotic release factors 1 and 3, encoded by SUP45 and SUP35, respectively, in Saccharomyces cerevisiae, are required for translation termination. Recent studies have shown that, besides these two key factors, several genetic and epigenetic mechanisms modulate the efficiency of translation termination. These mechanisms, through modifying translation termination fidelity, were shown to affect various cellular processes, such as mRNA degradation, and in some cases could confer a beneficial phenotype to the cell. The most studied example of such a mechanism is [PSI+], the prion conformation of Sup35p, which can have pleiotropic effects on growth that vary among different yeast strains. However, genetic loci underlying such readthrough-dependent, background-specific phenotypes have yet to be identified. Here, we used sup35(C653R), a partial loss-of-function allele of the SUP35 previously shown to increase readthrough of stop codons and recapitulate some [PSI+]-dependent phenotypes, to study the genetic basis of phenotypes revealed by increased translational readthrough in two divergent yeast strains: BY4724 (a laboratory strain) and RM11_1a (a wine strain). We first identified growth conditions in which increased readthrough of stop codons by sup35(C653R) resulted in different growth responses between these two strains. We then used a recently developed linkage mapping technique, extreme QTL mapping (X-QTL), to identify readthrough-dependent loci for the observed growth differences. We further showed that variation in SKY1, an SR protein kinase, underlies a readthrough-dependent locus observed for growth on diamide and hydrogen peroxide. We found that the allelic state of SKY1 interacts with readthrough level and the genetic background to determine growth rate in these two conditions.

Genetic architecture of highly complex chemical resistance traits across four yeast strains.

Many questions about the genetic basis of complex traits remain unanswered. This is in part due to the low statistical power of traditional genetic mapping studies. We used a statistically powerful approach, extreme QTL mapping (X-QTL), to identify the genetic basis of resistance to 13 chemicals in all 6 pairwise crosses of four ecologically and genetically diverse yeast strains, and we detected a total of more than 800 loci. We found that the number of loci detected in each experiment was primarily a function of the trait (explaining 46% of the variance) rather than the cross (11%), suggesting that the level of genetic complexity is a consistent property of a trait across different genetic backgrounds. Further, we observed that most loci had trait-specific effects, although a small number of loci with effects in many conditions were identified. We used the patterns of resistance and susceptibility alleles in the four parent strains to make inferences about the allele frequency spectrum of functional variants. We also observed evidence of more complex allelic series at a number of loci, as well as strain-specific signatures of selection. These results improve our understanding of complex traits in yeast and have implications for study design in other organisms.

Variants in SUP45 and TRM10 underlie natural variation in translation termination efficiency in Saccharomyces cerevisiae.

Translation termination is a highly controlled process in the cell. In Saccharomyces cerevisiae, various regulatory factors employ genetic and epigenetic mechanisms to control this process. We used a quantitative dual luciferase reporter assay to demonstrate a difference in translation termination efficiency between two different yeast strains, BY4724 and RM11-1a. We then used a recently developed linkage mapping technique, extreme QTL mapping (X-QTL), to show that this difference is largely explained by a coding polymorphism in TRM10 (which encodes a tRNA-methylating enzyme) and a regulatory polymorphism in SUP45 (which encodes one of the yeast translation termination factors). BY and RM carry variants of TRM10 and SUP45 with opposite effects on translation termination efficiency. These variants are common among 63 diverse S. cerevisiae strains and are in strong linkage disequilibrium with each other. This observation suggests that selection may have favored allelic combinations of the two genes that maintain an intermediate level of translation termination efficiency. Our results also provide genetic evidence for a new role of Trm10p in translation termination efficiency.

Designing multiple degenerate primers via consecutive pairwise alignments.

BACKGROUND: Different algorithms have been proposed to solve various versions of degenerate primer design problem. For one of the most general cases, multiple degenerate primer design problem, very few algorithms exist, none of them satisfying the criterion of designing low number of primers that cover high number of sequences. Besides, the present algorithms require high computation capacity and running time. RESULTS: PAMPS, the method presented in this work, usually results in a 30% reduction in the number of degenerate primers required to cover all sequences, compared to the previous algorithms. In addition, PAMPS runs up to 3500 times faster. CONCLUSION: Due to small running time, using PAMPS allows designing degenerate primers for huge numbers of sequences. In addition, it results in fewer primers which reduces the synthesis costs and improves the amplification sensitivity.

Amino acid and codon usage profiles: adaptive changes in the frequency of amino acids and codons.

In the work presented, the changes in codon and amino acid contents have been studied as a function of environmental conditions by comparing pairs of homologs in a group of extremophilic/non-extremophilic genomes. Our results obtained based on such analysis highlights a number of notable observations: (i) the overall preference of amino acid usages in the proteins of a given organism is significantly affected by major environmental factors. The changes in amino acid preferences (amino acid usage profiles) in an extremophile compared to its non-extremophile relative recurs in the organisms of similar extreme habitats. (ii) On the other hand, changes in codon usage preferences in these extremophilic/non-extremophilic pairs, lack such persistency not only in different genome-pairs but also in the individual genes of a specific pair. (iii) We have noted a correlation between cellular function and codon usage profiles of the genes in the studied pairs. (iv) Based on this correlation, we could obtain a decent prediction of cellular functions solely based on codon usage profile data. (v) Comparisons made between two sets of randomly generated genomes suggest that different patterns of codon usage changes in genes of different functional categories result in a partial resistance towards the changes in the concentration of a given amino acid. This buffering capacity might explain the observed differences in codon usage trends in genes of different functions. In the end, we suggest codon usage and amino acid profiles as powerful tools that can be utilized to improve function predictions and genome-environment mappings.

MAD-DPD: designing highly degenerate primers with maximum amplification specificity.

This work introduces minimum accumulative degeneracy, a variant of the degenerate primer design problem, which is particularly useful when a large number of sequences are to be covered by a set of restricted number of primers. A primer set, which is designed on a minimum accumulative degeneracy basis, especially helps to reduce nonspecific PCR amplification of undesired DNA fragments, as fewer primer species are present in PCR. A Boltzmann machine is designed to solve the minimum accumulative degeneracy degenerate primer design problem, called the MAD-DPD Boltzmann machine. This algorithm shows great flexibility, as it can be determined either to solve the problem with strict fidelity to covering all input sequences or to exclude some input sequences if it results in less degenerate primers. This Boltzmann machine is successfully implemented in designing a new set of primers for amplification of antibody variable fragments from mouse spleen cells, which theoretically covers more diverse antibody sequences than currently available primers. The MAD-DPD Boltzmann machine is available online at bioinf.cs.ipm.ir/download/MAD_DPD08172007.zip.

Homozygous missense mutation in fibulin-5 in an Iranian autosomal recessive cutis laxa pedigree and associated haplotype.

Cutis laxa is a rare group of inherited and acquired disorders characterized by loose and redundant skin with reduced elasticity. Mutations in the elastin coding gene have been shown to cause autosomal dominant cutis laxa in three families. A homozygous mutation in the fibulin-5 coding gene was discovered in a Turkish pedigree showing recessive inheritance, and a different mutation in this gene was found in the heterozygous state in a sporadic case of the disease. Here, we report the third case of a mutation in the fibulin-5 coding gene in a recessive Iranian cutis laxa pedigree. The mutation is the same as previously reported in the Turkish pedigree, further confirming that it is causative of disease. A haplotype consisting of seven intragenic sequence variations common to both pedigrees is described for the mutation-carrying fibulin-5 allele.

On the coevolution of genes and genetic code.

The canonical genetic code acts efficiently in minimizing the effects of mistranslations and point mutations. In the work presented we have also considered the effects of single nucleotide insertions and deletions on the optimality of the genetic code. Our results suggest that the canonical genetic code compensates for the ins/del mutations as well as mistranslations and point mutations. On the other hand, we highlighted the point that ins/del mutations have a lesser impact on the selected genes of Saccharomyces cerevisiae compared to randomly generated ones. We hypothesized that the codon usage preferences in S. cerevisiae genes are responsible for the higher efficiency of translation machinery in this organism. Our results support the conjecture that codon usage preferences render the genetic code more effective in minimizing the effects of ins/del mutations.

Designing a neural network for the constraint optimization of the fitness functions devised based on the load minimization of the genetic code.

Nonrandom patterns in codon assignments are supported by many statistical and biochemical studies in the last two decades. The canonical genetic code is known to be highly efficient in minimizing the effects of mistranslational errors and point mutations, an ability, which in term is designated "load minimization". Prior studies have included many attempts at quantitative estimation of the fraction of randomly generated codes, which in terms of load minimization, score higher than the canonical genetic code. In this study, a neural network, which estimates a highly optimized genetic code in a relatively short period of time has been devised. Several fitness functions were used throughout this text. Meanwhile, we have made use of two cost measure matrices, PAM74-100 and mutation matrix.

On the optimality of the genetic code, with the consideration of termination codons.

The existence of nonrandom patterns in codon assignments is supported by many statistical and biochemical studies. The canonical genetic code is known to be highly efficient in minimizing the effects of mistranslation errors and point mutations. For example, it is known that when an error induces the conversion of an amino acid to another, the biochemical properties of the resulting amino acid are usually very similar to that of the original. Prior studies include many attempts at quantitative estimation of the fraction of randomly generated codes which, based upon load minimization, score higher than the canonical genetic code. In this study, we took into consideration both the relative frequencies of amino acids and nonsense mistranslations, factors which had been previously ignored. Incorporation of these parameters, resulted in a fitness function (phi) which rendered the canonical genetic code to be highly optimized with respect to load minimization. Considering termination codons, we applied a biosynthetic version of the coevolution theory, however, with low significance. We employed a revised cost for the precursor-product pairs of amino acids and showed that the significance of this approach depends on the cost measure matrix used by the researcher. Thus, we have compared the two prominent matrices, point accepted mutations 74-100 (PAM(74-100)) and mutation matrix in our study.

The case for an error minimizing set of coding amino acids.

The fidelity of the translation machinery largely depends on the accuracy by which the tRNAs within the living cells are charged. Aminoacyl-tRNA synthetases (aaRSs) attach amino acids to their cognate tRNAs ensuring the fidelity of translation in coding sequences. Based on the sequence analysis and catalytic domain structure, these enzymes are classified into two major groups of 10 enzymes each. In this study, we have generally tackled the role of aaRSs in decreasing the effects of mistranslations and consequently the evolution of the translation machinery. To this end, a fitness function was introduced in order to measure the accuracy by which each tRNA is charged with its cognate amino acid. Our results suggest that the aaRSs are very well optimized in "load minimization" based on their classes and their mechanisms in distinguishing the correct amino acids. Besides, our results support the idea that from an evolutionary point, a selectional pressure on the translational fidelity seems to be responsible in the occurrence of the 20 coding amino acids.

Solvent accessibility, residue charge and residue volume, the three ingredients of a robust amino acid substitution matrix.

Cost measure matrices or different amino acid indices have been widely used for studies in many fields of biology. One major criticism of these studies might be based on the unavailability of an unbiased and yet effective amino acid substitution matrix. Throughout this study we have devised a cost measure matrix based on the solvent accessibility, residue charge, and residue volume indices. Performed analyses on this novel substitution matrix (i.e. solvent accessibility charge volume (SCV) matrix) support the uncontaminated nature of this matrix regarding the genetic code. Although highly similar to a number of previously available cost measure matrices, the SCV matrix results in a more significant optimality in the error-buffering capacity of the genetic code when compared to many other amino acid substitution matrices. Besides, a method to compare an SCV-based scoring matrix with a number of widely used matrices has been devised, the results of which highlights the robustness of this matrix in protein family discrimination.

Applying a neural network to predict the thermodynamic parameters for an expanded nearest-neighbor model.

Predicting the secondary and tertiary structure of RNAs largely depends on our capabilities in estimating the thermodynamics of RNA duplexes. In this work, an expanded nearest-neighbor model, designated INN-48, is established. The thermodynamic parameters of this model are predicted using both multiple linear regression analysis and neural network analysis. It is suggested that due to the increase in the number of parameters and the insufficiency of the existing data, neural network analysis results in more reliable predictions. Furthermore, it is suggested that INN-48 can be used to estimate the thermodynamics of RNA duplex formation for longer sequences, whereas INN-HB, the previous model on which INN-48 is based, can be used for short sequences.

Optimality of codon usage in Escherichia coli due to load minimization.

The canonical genetic code is known to be highly efficient in minimizing the effects of mistranslational errors and point mutations, an ability which in term is designated "load minimization". One parameter involved in calculating the load minimizing property of the genetic code is codon usage. In most bacteria, synonymous codons are not used with equal frequencies. Different factors have been proposed to contribute to codon usage preference. It has been shown that the codon preference is correlated with the composition of the tRNA pool. Selection for translational efficiency and translational accuracy both result in such a correlation. In this work, it is shown that codon usage bias in Escherichia coli works so as to minimize the consequences of translational errors, i.e. optimized for load minimization.

On the optimality of the genetic code, with the consideration of coevolution theory by comparison of prominent cost measure matrices.

Statistical and biochemical studies have revealed non-random patterns in codon assignments. The canonical genetic code is known to be highly efficient in minimizing the effects of mistranslation errors and point mutations, since it is known that when an amino acid is converted to another due to error, the biochemical properties of the resulted amino acid are usually very similar to those of the original one. In this study, using altered forms of the fitness functions used in the prior studies, we have optimized the parameters involved in the calculation of the error minimizing property of the genetic code so that the genetic code outscores the random codes as much as possible. This work also compares two prominent matrices, the Mutation Matrix and Point Accepted Mutations 74-100 (PAM(74-100)). It has been resulted that the hypothetical properties of the coevolution theory of the genetic code are already considered in PAM(74-100), giving more evidence on the existence of bias towards the genetic code in this matrix. Furthermore, our results indicate that PAM(74-100) is biased towards the single base mistranslation occurrences in second codon position as well as the frequency of amino acids. Thus PAM(74-100) is not a suitable substitution matrix for the studies conducted on the evolution of the genetic code.

The impact of including tRNA content on the optimality of the genetic code.

Statistical and biochemical studies have revealed nonrandom patterns in codon assignments. The canonical genetic code is known to be highly efficient in minimizing the effects of mistranslational errors and point mutations, since it is known that, when an amino acid is converted to another due to error, the biochemical properties of the resulted amino acid are usually very similar to those of the original one. In this study, we have taken into consideration both relative frequencies of amino acids and relative gene copy frequencies of tRNAs in genomic sequences in order to introduce a fitness function which models the mistranslational probabilities more accurately in modern organisms. The relative gene copy frequencies of tRNAs are used as estimates of the tRNA content. We also altered the rule previously used for the calculation of the probabilities of single base mutation occurrences. Our model signifies higher optimality of the genetic code towards load minimization and suggests the presence of a coevolution of tRNA frequency and the genetic code.