MBE Advance Access originally published online on March 22, 2007
Molecular Biology and Evolution 2007 24(6):1347-1354; doi:10.1093/molbev/msm057
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Research Articles |
Adaptive Evolution of Metabolic Pathways in Drosophila
Department of Ecology and Evolution, Stony Brook University
E-mail: jmflower{at}life.bio.sunysb.edu.
| Abstract |
|---|
|
|
|---|
The adaptive significance of enzyme variation has been of central interest in population genetics. Yet, how natural selection operates on enzymes in the larger context of biochemical pathways has not been broadly explored. A basic expectation is that natural selection on metabolic phenotypes will target enzymes that control metabolic flux, but how adaptive variation is distributed among enzymes in metabolic networks is poorly understood. Here, we use population genetic methods to identify enzymes responding to adaptive selection in the pathways of central metabolism in Drosophila melanogaster and Drosophila simulans. We report polymorphism and divergence data for 17 genes that encode enzymes of 5 metabolic pathways that converge at glucose-6-phosphate (G6P). Deviations from neutral expectations were observed at five loci. Of the 10 genes that encode the enzymes of glycolysis, only aldolase (Ald) deviated from neutrality. The other 4 genes that were inconsistent with neutral evolution (glucose-6-phosphate dehydrogenase [G6pd]), phosphoglucomutase [Pgm], trehalose-6-phosphate synthetase [Tps1], and glucose-6phosphatase [G6pase] encode G6P branch point enzymes that catalyze reactions at the entry point to the pentose-phosphate, glycogenic, trehalose synthesis, and gluconeogenic pathways. We reconcile these results with population genetics theory and existing arguments on metabolic regulation and propose that the incidence of adaptive selection in this system is related to the distribution of flux control. The data suggest that adaptive evolution of G6P branch point enzymes may have special significance in metabolic adaptation.
Key Words: positive selection network evolution population genomics adaptation systems biology
| Introduction |
|---|
|
|
|---|
The adaptive significance of enzyme variation has been a central topic of interest in population genetics since the earliest surveys of allozyme polymorphism (Lewontin and Hubby 1966
An important step toward developing a systems-level view is to identify features of metabolic networks that influence the evolution of individual genes. Large-scale studies have reported correlations between network properties and rates of protein evolution. In yeast, highly connected enzymes have a slower rate of amino acid substitution (Vitkup et al. 2006
). This correlation suggests that selective constraints on molecular evolution depend on a system property and that the strength of "purifying" selection is contingent on how connected an enzyme is to other enzymes in the network. Unfortunately, the comparative methods frequently used to estimate evolutionary rates in biological networks can only rarely detect "adaptive" protein evolution (Kreitman and Akashi 1995
; Yang and Bielawski 2000
). As a consequence, very little is known about how adaptive variation is distributed among enzymes in metabolic networks or what structural and/or functional properties of these systems cause some enzymes to evolve adaptively, whereas others are subject to evolutionary constraints. This gap in current understanding of metabolic pathway evolution can be addressed with population-based approaches that contrast nucleotide polymorphism within species with interspecific divergence.
In biochemical pathways, natural selection is expected to target enzymes that control flux (Hartl et al. 1985
; Eanes 1999
; Watt and Dean 2000
). Consequently, where adaptive selection operates in a pathway will depend on the distribution of flux control among steps. Metabolic control analysis proposes that the regulation of flux through a linear biochemical pathway is distributed among enzymes throughout the pathway (Kacser and Burns 1981
). In branching pathways, flux allocation may be controlled primarily by enzymes at the intersections of competing pathways (LaPorte et al. 1984
; Stephanopoulos and Vallino 1991
). Therefore, branch point enzymes may disproportionately regulate, or control, the expression of biochemical phenotypes, such as the energy pools of glycogen or triglycerides that are important for adaptation in natural populations (Eanes 1999
).
Mutations that alter enzyme activity will have larger fitness consequences in enzymes with greater flux control (Hartl et al. 1985
). As a consequence, natural selection can redistribute flux most effectively by altering the activity of enzymes at branch points. This hypothesis predicts that networks evolve primarily through adaptive changes in enzymes at major pathway intersections and less frequently through mutational changes in remote enzymes.
Addressing hypotheses about adaptive evolution in metabolic networks requires that the enzymatic steps targeted by natural selection be identified. Previously, we used nucleotide polymorphism data from enzyme-coding loci to test for departures from neutrality at enzymatic steps in the central metabolic corridor of Drosophila. This work focused on branch point enzymes that metabolize glucose-6-phosphate (G6P). The first evidence for significant deviations from neutrality came from surveys of nucleotide variation at G6pd (i.e., Zw; Eanes et al. 1993
, 1996
) and Pgm (Verrelli and Eanes 2000
). In contrast, patterns of sequence variation at loci that encode the branch point enzymes, HEX-A and HEX-C (Duvernell and Eanes 2000
) and the downstream glycolytic enzyme TPI (Hasson et al. 1998
) were consistent with neutrality. These studies suggested that adaptive selection may be prevalent, but establishing the general significance of adaptive evolution of branch point enzymes requires an expanded study of enzymes in the pathways that converge at G6P.
In this report, we significantly expand our survey of nucleotide variation to include 17 enzymes of central metabolism. We collected sequence polymorphism and divergence data from Drosophila melanogaster and Drosophila simulans for 10 additional enzyme-coding loci and assembled all available nucleotide polymorphism data for enzymes of the 5 pathways that intersect at G6P (i.e., glycolytic, gluconeogenic, glycogenic, trehalose, and pentose shunt). We report 3 additional genes that deviate from neutrality in D. simulans and now find that 4 of 7 enzymes at the intersection of these pathways are inconsistent with the neutral model in one or both species. This pattern suggests that Darwinian selection on amino acid variation has been an important mechanism of metabolic network evolution in Drosophila. Furthermore, the added evidence of adaptive selection at the G6P branch point suggests that evolutionary change at this major pathway intersection may be a means by which the Drosophila metabolic network has adapted in response to natural selection.
| Materials and Methods |
|---|
|
|
|---|
Line Origins and DNA Sequencing
Drosophila melanogaster sequences new to this study were collected from flies homozygous for extracted 2nd, 3rd, or X chromosomes derived from North American populations (i.e., some combination of alleles from New York, Vermont, Florida, Massachusetts, South Carolina, and Virginia; see Duvernell and Eanes 2000
|
DNA sequences were collected for glyceraldehyde-3-phosphate dehydrogenase paralogs (Gapdh1, Gapdh2), aldolase (Ald), phosphoglyceromutase (Pglym78), phosphogluconate kinase (Pgk), enolase (Eno), UDP-glucose pyrophosphorylase (UGP), trehalase (Treh), trehalose-6-phosphate synthetase (Tps1), and CG15400 (hereafter, G6pase). This gene has been identified as the putative ortholog to the human gene (G6PC) encoding glucose-6-phosphatase (Hubbard et al. 2006
Data for triosephosphate isomerase (Tpi; Hasson et al. 1998
), the muscle- and fat body-specific hexokinases (Hex-A and Hex-C; Duvernell and Eanes 2000
), G6pd (Eanes et al. 1993
, 1996
), phosphoglucomutase (Pgm; Verrelli and Eanes 2000
), and 6-phosphogluconate dehydrogenase (Pgd; Begun and Aquadro 1994
; Begun and Whitley 2000
) have been reported previously. GenBank accession numbers for unpublished phosphoglucoisomerase (Pgi) sequences are L27539
[GenBank]
L27555 and U20556
[GenBank]
U20575. Central metabolic enzymes that are testes specific in their expression (Grumbling et al. 2006
) were not included in the analysis.
DNA Sequence Analysis
McDonaldKreitman (MK) tests were conducted in DnaSP v. 4.10 (Rozas et al. 2003
). Fixations were inferred from comparison of D. melanogaster and D. simulans sequences only. Fixations occurring along the branch to D. yakuba were excluded to minimize the effects of multiple hits and to reduce the effect of mutations segregating within yakuba on divergence estimates. In lineage-specific MK tests, fixations were assigned to the melanogaster or simulans lineages by parsimony with a script written in Perl by J.M.F. and S.K. All MK tests were conducted on combined African and North American alleles, where applicable. Ancestral codons were reconstructed base-by-base using D. yakuba as an outgroup. The parsimony criterion utilized all mutations in the 3 species alignment (i.e., mutations segregating in melanogaster and simulans were considered when inferring the most parsimonious ancestral states). Codons with multiple substitutions in the same lineage were treated using the method of Pamilo and Bianchi (1993)
when equal number of mutations defined alternative pathways, the pathway with fewer nonsynonymous changes was accepted. Preferred and unpreferred codons were defined according to Sharp and Lloyd (1993)
and polarized by the same parsimony criterion. Statistical significance of 2 x 2 contingency tables was assessed with 2-tailed Fisher's exact tests. Rates of nucleotide substitution were estimated from pairwise alignments of D. melanogaster and D. simulans sequences. Alignments were generated with MUSCLE (Edgar 2004
) using sequences from the whole genome (Grumbling et al. 2006
) or by haphazardly selecting an allele from our polymorphism data sets. Rates were estimated by the approximate method of Comeron (1995)
using K-estimator v. 6.1 (Comeron 1999
). This allowed for comparison with substitution rates reported for 419 genes by Shapiro et al. (2007)
.
Entries from table 1 were used to estimate the scaled selection parameter, 2Nes, by the Poisson random field method of Bustamante et al. (2002)
. The analysis was conducted using mkprf and implemented by the Cornell Computational Biology Service Unit at http://cbsuapps.tc.cornell.edu/mkprf.aspx. Markov Chain Monte Carlo sampling of the posterior distribution was performed by retaining 5,000 draws from each of 10 chains. The initial burn-in was 1,000 steps. The mkprf analysis was run without specifying a class structure by using the fixed variance option. Pgd was excluded from this analysis because polymorphism data were only available for one species.
| Results and Discussion |
|---|
|
|
|---|
Under the neutral model of molecular evolution (Kimura 1983
|
|
Analysis of the average strength of selection on amino acid replacement mutations supports our assertion that natural selection has operated on Pgm, G6pd, Tps1, G6pase, and Ald. The Bayesian method we employed to determine the strength of selection uses the joint nucleotide configurations of the MK table to estimate the posterior probability distribution of the scaled selection coefficient, 2Nes (Bustamante et al. 2002
|
Because most metabolic genes in Drosophila show exceptionally high levels of codon bias (Duvernell and Eanes 2000
|
Consequently, a deficit of synonymous fixations due to selection on silent sites could provide an alternative explanation for what we interpret to be an excess of replacement fixations at Ald, G6pd, Tps1, and G6pase in D. simulans. This explanation seems unlikely for 3 of the genes. First, G6pase shows the lowest codon bias (ENC = 50.32, table 3; the median for D. melanogaster is 49.57, Hey and Kliman 2002
|
It is conceivable that deviations from neutrality reflect the fixation of slightly deleterious replacement mutations. If D. simulans historically had a small population size that recently expanded, the excess of amino acid divergence could be attributed to the fixation of slightly deleterious variants in the smaller ancestral population (McDonald and Kreitman 1991
Deviations from neutral expectations at loci that encode G6P branch point enzymes suggest that adaptive evolution at this intersection may be important for metabolic adaptation in Drosophila. A possible explanation for adaptive selection on branch point enzymes is the localization of flux control at this junction. G6P is an allosteric effector that lies at a common entry point to pathways functioning in the storage, mobilization, transport, and breakdown of carbohydrate. In D. melanogaster, there is evidence that G6P branch point enzymes are capable of controlling flux allocation. Flux apportionment to the pentose shunt is extremely sensitive to allozyme variation at G6pd (Labate and Eanes 1992
), and glycogen storage levels have been reported to depend on Pgm genotype (Verrelli and Eanes 2001b
). In addition, overexpression of Tps1 increases trehalose content (Chen et al. 2001
), suggesting that this enzyme may control flux in the trehalose pathway.
Mutations that modify activity of controlling enzymes are expected to be visible to natural selection, whereas comparable changes in activity at steps with little or no control are neutral (Hartl et al. 1985
). Because branch point enzymes PGM, TPS1, and G6PD exert some measure of control over flux allocation, activity-altering mutations in these enzymes can affect pathway fluxes, modify the phenotype, and are therefore subject to natural selection. Significant MK tests for Pgm, Tps1, and G6pd (Eanes et al. 1993
, 1996
; Verrelli and Eanes 2000
, table 1), latitudinal clines at G6pd and Pgm in D. melanogaster (Oakeshott et al. 1983
; Verrelli and Eanes 2001a
), and evidence that functional variation at these loci influences biochemical phenotypes supports this expectation. Although the distribution of control among enzymes in these pathways is not well understood, we propose that adaptive substitution at the G6P intersection reflects a greater capability of branch point enzymes to control flux allocation.
Several processes may drive gene-specific adaptive responses in metabolic pathways. First, environmentally driven changes in flux demands and resource partitioning may shift the distribution of control among steps or branches. As the level of control exercised by an enzyme diminishes, alleles with reduced activity become effectively neutral and have an increased probability of fixation (Hartl et al. 1985
). These accumulated nearly neutral changes can become deleterious should control return, but can be compensated by subsequent adaptive substitutions that restore activity. Therefore, excesses of allele fixation may reflect a continuous process of network adaptation in which control shifts and pathway fluxes are fine-tuned to match metabolic demands. Enzymes that lack metabolic control will not experience this process. Alternatively, if control remains static over time, adaptive substitution may occur in a pathway as a consequence of fluctuating population size and adaptive compensatory evolution (Hartl and Taubes 1996
). When population sizes contract, slightly deleterious alleles with reduced activity can fix at controlling steps because they are effectively neutral. Subsequent increases in population size promote the fixation of adaptive compensatory changes that restore activity. These compensatory cycles are not expected for enzymes possessing limited control.
In this study, we have reported that 5 of 17 genes surveyed in the central metabolic corridor deviated from neutrality in MK tests, and that 1 enzyme in each of the 5 intersecting pathways showed evidence of natural selection. In addition, our observation that 4 of the 5 genes for which neutrality could be rejected encode G6P branch point enzymes could indicate that natural selection at this major pathway intersection has special significance in metabolic adaptation. When the incidence of selection is compared between G6P branch point and nonbranch point enzymes, 4 of 7 branch point enzymes deviate from neutrality, whereas only 1 of 10 enzymes remote to this intersection show evidence of selection. This is not significant in a 2 x 2 test (P > 0.05, 2-tailed Fisher's exact test), but is marginally significant when departures from neutrality are inferred from Bonferroni-corrected MK tests (i.e., 3 of 7 and 0 of 10 branch point and nonbranch point enzymes reject neutrality; P = 0.051). This could suggest that adaptive substitutions are concentrated at the G6P branch point, but additional sampling of enzyme-coding loci will be required to address this question. A recent survey of nucleotide polymorphism in D. melanogaster included a 1.1 Kb fragment of PyK (Shapiro et al. 2007
), which encodes the enzyme pyruvate kinase at the end of the glycolytic pathway. Shapiro et al. (2007)
reported no replacement polymorphisms segregating in D. melanogaster and no amino acid fixations since the divergence with simulans suggesting that this enzyme may also be evolving neutrally. The emerging pattern from these observations and our previous work showing geographic clines in G6P branch point enzymes (Sezgin et al. 2004
) is intriguing and implicates enzymes at this intersection in the process of metabolic adaptation. This warrants an expanded survey of nucleotide polymorphism from genes in other pathways and in other species to evaluate the significance of adaptive evolution at the G6P branch point and other principal nodes in metabolic networks.
| Acknowledgements |
|---|
|
|
|---|
We thank J. L. Lachance, C. S. Willett, J. R. True, D. W. Foltz, R. Geeta, J. H. McDonald, and 2 anonymous reviewers for helpful comments. The hierarchical Bayesian analysis was implemented with support from the Cornell Computational Biology Service Unit. This work was supported by US Public Health Service Grant GM-45247 to W.F.E. This is contribution number 1153 from the Graduate Program in Ecology and Evolution, Stony Brook University.
| Footnotes |
|---|
1 Present address: Laboratory of Genomic Diversity, National Cancer Institute, Frederick, Maryland
2 Present address: Department of Biological Sciences, Southern Illinois University, Edwardsville, Illinois ![]()
3 Present address: Department of Ecology and Evolutionary Biology, University of Arizona ![]()
4 Present address: Department of Biology, University of Pennsylvania ![]()
John H McDonald, Associate Editor
| References |
|---|
|
|
|---|
Akashi H. Inferring weak selection from patterns of polymorphism and divergence at silent sites in Drosophila DNA. Genetics (1995) 139:10671076.[Abstract]
Begun DJ. The frequency distribution of nucleotide variation in Drosophila simulans. Mol Biol Evol (2001) 18:13431352.
Begun DJ, Aquadro CF. Evolutionary inferences from DNA variation in the 6-Phosphogluconate dehydrogenase locus in natural populations of Drosophila: selection and geographic differentiation. Genetics (1994) 136:155171.[Abstract]
Begun DJ, Whitley P. Reduced X-linked nucleotide polymorphism in Drosophila simulans. Proc Natl Acad Sci USA (2000) 97:59605965.
Bustamante CD, Nielsen R, Sawyer SA, Olsen KM, Purugganan MD, Hartl DL. The cost of inbreeding in Arabidopsis. Nature (2002) 416:531534.[CrossRef][Medline]
Chen Q, Ma E, Behar KL, Xu T, Haddad G. Role of trehalose phosphate synthase in anoxia tolerance and development in Drosophila melanogaster. J Biol Chem (2001) 277:32743279.[CrossRef][Web of Science][Medline]
Comeron JM. A method for estimating the numbers of synonymous and nonsynonymous substitutions per site. J Mol Evol (1995) 41:11521159.[Web of Science][Medline]
Comeron JM. K-Estimator: calculation of the number of nucleotide substitutions per site and the confidence intervals. Bioinformatics (1999) 15:763764.
Cork JM, Purugganan MD. The evolution of molecular genetic pathways and networks. Bioessays (2004) 5:479484.
Crawford DL, Powers DA. Molecular basis of evolutionary adaptation at the lactate dehydrogenase B locus in the fish Fundulus heteroclitus. Proc Natl Acad Sci USA (1989) 86:93659369.
Duvernell DD, Eanes WF. Contrasting molecular population genetics of four hexokinases in Drosophila melanogaster, D. simulans and D. yakuba. Genetics (2000) 156:11911201.
Eanes WF. Analysis of selection on enzyme polymorphisms. Annu Rev Ecol Syst (1999) 30:301326.[CrossRef][Web of Science]
Eanes WF, Kirchner M, Yoon J. Evidence for adaptive evolution of the G6PD gene in the Drosophila melanogaster and Drosophila simulans lineages. Proc Natl Acad Sci USA (1993) 90:74757479.
Eanes WF, Kirchner M, Yoon J, Biermann CH, Wang I-N, McCartney MA, Verrelli BC. Historical selection, amino acid polymorphism and lineage-specific divergence at the G6pd locus in Drosophila melanogaster and D. simulans. Genetics (1996) 144:10271041.[Abstract]
Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res (2004) 32:17921797.
Eyre-Walker A. Changing effective population size and the McDonald-Kreitman test. Genetics (2002) 162:20172024.
Gillespie J. The causes of molecular evolution (1991) New York: Oxford University Press.
Grumbling G, Strelets V, The FlyBase Consortium. FlyBase: anatomical data, images and queries. Nucleic Acids Res (2006) 34:D484D488.
Hartl DL, Dykhuizen DE, Dean AM. Limits of adaptation: the evolution of selective neutrality. Genetics (1985) 111:655674.
Hartl DL, Taubes CH. Compensatory nearly neutral mutations: selection without adaptation. J Theor Biol (1996) 182:303309.[CrossRef][Web of Science][Medline]
Hasson E, Wang I-N, Zeng LW, Kreitman M, Eanes WF. Nucleotide variation in the triosephosphate isomerase (Tpi) locus of Drosophila melanogaster and Drosophila simulans. Mol Biol Evol (1998) 15:756769.[Abstract]
Hey J, Kliman RM. Interactions between natural selection, recombination and gene density in the genes of Drosophila. Genetics (2002) 160:595608.
Hubbard TJP, Aken BL, Beal K, et al, (58 co-authors). Ensembl 2007. Nucleic Acids Res (2006) 00:D1D8.
Kacser H, Burns JA. The molecular basis of dominance. Genetics (1981) 97:639666.
Kimura M. The neutral theory of molecular evolution (1983) Cambridge (UK): Cambridge University Press.
Kreitman M, Akashi H. Molecular evidence for natural selection. Annu Rev Ecol Syst (1995) 26:403422.[Web of Science]
Labate J, Eanes WF. Direct measurement of in vivo flux differences between electrophoretic variants of G6pd from Drosophila melanogaster. Genetics (1992) 132:783787.[Abstract]
LaPorte DC, Walsh K, Koshland DE. The branch point effect: ultrasensitivity and subsensitivity to metabolic control. J Biol Chem (1984) 259:40684075.[Web of Science]
Lewontin RC. The genetic basis of evolutionary change (1974) New York: Columbia University Press.
Lewontin RC, Hubby JL. A molecular approach to the study of genic heterozygosity in natural populations. II. Amount of variation and degree of heterozygosity in natural populations of Drosophila pseudoobscura. Genetics (1966) 54:595609.
McDonald JH, Kreitman M. Adaptive protein evolution at the Adh locus in Drosophila. Nature (1991) 351:652654.[CrossRef][Medline]
Mitton J. Selection in natural populations (1997) New York: Oxford University Press.
Moriyama EN, Powell JR. Intraspecific nuclear DNA variation in Drosophila. Mol Biol Evol (1996) 13:261277.[Abstract]
Oakeshott JG, Chambers GK, Gibson JB, Eanes WF, Willcocks DA. Geographic variation at G6pd and Pgd allele frequencies in Drosophila melanogaster. Heredity (1983) 50:6772.[Web of Science][Medline]
Pamilo P, Bianchi NO. Evolution of the Zfx and Zfy genes: rates and interdependence of the genes. Mol Biol Evol (1993) 10:271281.[Abstract]
Pierce VA, Crawford DL. Phylogenetic analysis of glycolytic enzyme expression. Science (1997) 276:256259.
Rausher MD, Miller RE, Tiffin P. Patterns of evolutionary rate variation among genes of the anthocyanin biosynthetic pathway. Mol Biol Evol (1999) 16:266274.[Abstract]
Rozas J, Sanchez-DelBarrio JC, Messeguer X, Rozas R. DnaSP, DNA polymorphism analyses by the coalescent and other methods. Bioinformatics (2003) 19:24962497.
Sawyer SA, Hartl DL. Population genetics of polymorphism and divergence. Genetics (1992) 132:11611176.[Abstract]
Sezgin E, Duvernell DD, Matzkin LM, Duan YH, Zhu CT, Verrelli BC, Eanes WF. Single-locus latitudinal clines and their relationship to temperate adaptation in metabolic genes and derived alleles in Drosophila melanogaster. Genetics (2004) 168:923931.
Shapiro JA, Huang W, Zhang C, et al. Adaptive genic evolution in the Drosophila genomes. Proc Natl Acad Sci USA (2007) 104:22712276. (12 co-authors).
Sharp PM, Lloyd AT. Codon usage in Drosophila genes. In: An atlas of Drosophila genesMaroni G, ed. (1993) New York: Oxford University Press. 378397.
Stephanopoulos G, Vallino JJ. Network rigidity and metabolic engineering in metabolite overproduction. Science (1991) 252:16751681.
Verrelli BC, Eanes WF. Extensive amino acid polymorphism at the Pgm locus is consistent with adaptive protein evolution in Drosophila melanogaster. Genetics (2000) 156:17371752.
Verrelli BC, Eanes WF. Clinal variation for amino acid polymorphisms at the Pgm locus in Drosophila melanogaster. Genetics (2001a) 157:16491663.
Verrelli BC, Eanes WF. The functional impact of Pgm amino acid polymorphism on glycogen content in Drosophila melanogaster. Genetics (2001b) 159:201210.
Vitkup D, Kharchenko P, Wagner A. Influence of metabolic network structure and function on enzyme evolution. Genome Biol (2006) 7:R39.[CrossRef][Medline]
Watt WB, Dean AM. Molecular functional studies of adaptive genetic variation in prokaryotes and eukaryotes. Annu Rev Genet (2000) 34:593622.[CrossRef][Web of Science][Medline]
Wright F. The effective number of codons used in a gene. Gene (1990) 87:2329.[CrossRef][Web of Science][Medline]
Yang Z, Bielawski JP. Statistical methods for detecting molecular adaptation. Trends Ecol Evol (2000) 15:496505.[CrossRef][Medline]
![]()
CiteULike
Connotea
Del.icio.us What's this?
This article has been cited by other articles:
![]() |
K. Livingstone and S. Anderson Patterns of Variation in the Evolution of Carotenoid Biosynthetic Pathway Enzymes of Higher Plants J. Hered., June 11, 2009; (2009) esp026v1. [Abstract] [Full Text] [PDF] |
||||
![]() |
T. J. S. Merritt, C. Kuczynski, E. Sezgin, C.-T. Zhu, S. Kumagai, and W. F. Eanes Quantifying Interactions Within the NADP(H) Enzyme Network in Drosophila melanogaster Genetics, June 1, 2009; 182(2): 565 - 574. [Abstract] [Full Text] [PDF] |
||||
![]() |
D. Alvarez-Ponce, M. Aguade, and J. Rozas Network-level molecular evolutionary analysis of the insulin/TOR signal transduction pathway across 12 Drosophila genomes Genome Res., February 1, 2009; 19(2): 234 - 242. [Abstract] [Full Text] [PDF] |
||||
![]() |
A. J. Greenberg, S. R. Stockwell, and A. G. Clark Evolutionary Constraint and Adaptation in the Metabolic Network of Drosophila Mol. Biol. Evol., December 1, 2008; 25(12): 2537 - 2546. [Abstract] [Full Text] [PDF] |
||||
![]() |
D. C. S. G. Oliveira, R. Raychoudhury, D. V. Lavrov, and J. H. Werren Rapidly Evolving Mitochondrial Genome and Directional Selection in Mitochondrial Genes in the Parasitic Wasp Nasonia (Hymenoptera: Pteromalidae) Mol. Biol. Evol., October 1, 2008; 25(10): 2167 - 2180. [Abstract] [Full Text] [PDF] |
||||
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||





