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Unformatted text preview: Chapter 1 Cells and Genomes 1 THE UNIVERSAL FEATURES OF CELLS ON EARTH In This Chapter A1 DEFINITIONS THE UNIVERSAL FEATURES OF CELLS ON EARTH THE DIVERSITY OF GENOMES AND THE TREE OF LIFE A5 GENETIC INFORMATION IN EUCARYOTES A9 1–1 Plasma membrane 1–2 Enzyme 1–3 Transcription 1–4 Translation 1–5 Gene 1–6 Messenger RNA (mRNA) 1–7 Amino acid 1–8 Genome TRUE/FALSE 1–9 True. Even in eucaryotes where the coding regions of a gene are often interrupted by noncoding segments, the order of codons in the DNA is still the same as the order of amino acids in the protein. 1–10 False. The nucleotide subunits of RNA and DNA differ in two key ways. First, the backbone in RNA uses the sugar ribose instead of deoxyribose, which is used in DNA. Second, RNA uses the base uracil in place of the base thymine, which is used in DNA. Three of the four bases—A, C, and G—are the same in RNA and DNA. THOUGHT PROBLEMS 1–11 Trying to define life in terms of properties is an elusive business, as suggested by this scoring exercise (Table 1–2). Cars are highly organized objects, take energy from the environment and transform gasoline into motion, responding to stimuli from the driver as they do so. However, they cannot reproduce themselves, or grow and develop—but then neither can old animals. Cacti are not particularly responsive to stimuli, but they display other ‘life’ attributes. It is curious that standard definitions of life usually do not mention that living organisms on Earth are largely made of organic molecules, that life is carbon based. The first few pages of MBoC emphasize this point and discuss the properties of living cells mainly in terms of their ‘informational macromolecules’—DNA, RNA, and protein. Reference: Pace NR (2001) The universal nature of biochemistry. Proc. Natl Acad. Sci. U.S.A. 98, 805–808. A1 A2 Chapter 1: Cells and Genomes Table 1–2 Plausible ‘life’ scores for car, cactus, and humans (Answer 1–11). CHARACTERISTIC CAR CACTUS HUMAN 1. Organization 2. Homeostasis 3. Reproduction 4. Development 5. Energy 6. Responsiveness 7. Adaptation Yes Yes No No Yes Yes No Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes 1–12 Such modules are generally designed to look for organic molecules characteristic of life. The first Mars probe analyzed soil samples for amino acids; none were found. 1–13 It is extremely unlikely that you created a new organism in this experiment. Far more probably, a spore from the air landed in your broth, germinated, and gave rise to the cells you observed. In the middle of the nineteenth century, Louis Pasteur invented a clever apparatus to disprove the then widely accepted belief that life could arise spontaneously. He showed that sealed flasks never grew anything if properly heat sterilized first. He overcame the objections of those who pointed out the lack of oxygen or who suggested that his heat sterilization killed the life-generating principle, by using a special flask with a slender ‘swan’s neck,’ which was designed to allow in oxygen but to prevent spores carried in the air from contaminating the culture (Figure 1–4). The cultures in these flasks never showed any signs of life; however, they were capable of supporting life, as could be demonstrated by washing some of the ‘dust’ from the neck into the culture. 1–14 On the surface, the extraordinary mutation resistance of the genetic code argues that it was subjected to the forces of natural selection. An underlying assumption, which seems reasonable, is that resistance to mutation is a valuable feature of a genetic code, one that would allow organisms to maintain sufficient information to specify complex phenotypes. This reasoning suggests that it would have been a lucky accident indeed—roughly a one-ina-million chance—to stumble on a code as error proof as our own. But all is not so simple. If resistance to mutation is an essential feature of any code that can support the complexity of organisms such as humans, then the only codes we could observe are ones that are error resistant. A less favorable frozen accident, giving rise to a more error-prone code, might limit the complexity of life to organisms that would never be able to contemplate their genetic code. This is akin to the anthropic principle of cosmology: many universes may be possible, but few are compatible with life that can ponder the nature of the universe. Beyond these considerations, there is ample evidence that the code is not static, and thus could respond to the forces of natural selection. Deviant versions of the standard genetic code have been identified in the mitochondrial and nuclear genomes of several organisms. In each case one or a few codons have taken on a new meaning. original flask Reference: Freeland SJ & Hurst LD (1998) The genetic code is one in a million. J. Mol. Evol. 47, 238–248. 1–15 There are several approaches you might try. 1. Analysis of the amino acids in the proteins would indicate whether the set of amino acids used in your organism differs from the set used in Earth organisms. But even Earthly organisms contain more amino acids than the standard set of 20, for example hydroxyproline, phosphoserine, and phosphotyrosine, which all result from modifications after a protein has been synthesized. Absence of one or more of the common set might be a more significant result. swan’s neck flask Figure 1–4 Flasks used in Pasteur’s tests of spontaneous generation (Answer 1–13). THE UNIVERSAL FEATURES OF CELLS ON EARTH 2. Sequencing DNA from the ‘Europan’ organism would allow a direct comparison with the database of sequences that are already known for Earth organisms. Matches to the database would argue for contamination. Absences of matches would constitute a less strong argument for a novel organism; it is a typical observation that about 15% to 20% of the genes identified in complete genome sequences of microorganisms do not appear to be homologous to genes in the database. Sufficiently extensive sequence comparison should resolve the issue. 3. Another approach might be to analyze the organism’s genetic code. We have no reason to expect that a novel organism based on DNA, RNA, and protein would have a genetic code identical to Earth’s universal genetic code. 1–16 In double-stranded DNA, which forms the genomes in all cellular life, G pairs with C, and A pairs with T. It is this requirement for base-pairing that necessitates that the number of Gs will equal the number of Cs, and that the numbers of As and Ts will be the same. In bulk samples of DNA this translates into equivalent mole percents of G and C and of A and T. The virus fX174 does not obey the ‘rules’ because its genome is singlestranded DNA. In the absence of a requirement for systematic base pairing there is no constraint on the relative amounts of G and C or of A and T. 1–17 Schrödinger answered his rhetorical question as follows: “The obvious inability of present-day physics and chemistry to account for such events is no reason at all for doubting that they can be accounted for by those sciences.” It is remarkable how much progress has been made since 1944, when the structure of DNA was completely unknown (its role was just beginning to come into focus), no protein had yet been sequenced, and the secret of the catalytic power of enzymes was very mysterious. Simple tests had already shown that plants and animals obeyed the laws of thermodynamics; neither cells nor organisms can create energy from nothing. All organisms require an input of energy from the environment to grow and reproduce— even to stay alive. Physicists have improved x-ray crystallography to the point where the structures of large proteins can be determined in weeks, and chemists can sequence whole bacterial genomes in a similar time. Organic chemists now understand enzyme-catalyzed reactions as well as any they study. The details of the metabolism of obscure bacteria living at extreme ocean depths on a diet of sulfur and carbon monoxide are well understood. The genes that control the intricate body plans of insects are mapped and sequenced. Yet many mysteries remain, of which one of the deepest is reflected by the enduring truth of Rudolph Virchow’s famous (1859) aphorism, “Omnis cellula e cellula” (All cells come from cells). One cannot yet mix a defined brew of DNA, RNA, and proteins together with some lipids and expect to generate a cell from its constituents. Will the next 50 years see this overturned? 1–18 A. During replication, parental DNA serves as a template for synthesis of new DNA. B. During transcription, DNA serves as a template for synthesis of RNA. F. During translation, RNA (mRNA) serves as the template for synthesis of protein. Two other processes, D. RNA Æ DNA, called reverse transcription, and E. RNA Æ RNA, called RNA replication, occur in the life cycles of RNA viruses such as HIV and poliovirus. CALCULATIONS 1–19 A. The number (n) of generations of cell divisions required to produce 1013 cells is A3 A4 Chapter 1: Cells and Genomes 2n = 1013 It is useful to remember that 210 ≅ 103 (2n produces the series: 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024; thus, 210 = 1024 ≅ 103). If 103 cells result from ten generations of dividing, 1012 cells will result from 4 ¥ 10 = 40 generations. Thus, you can estimate quickly that it will take a little over 40 generations to reach 1013 cells. You can get a more accurate answer, 43.2, by plugging different values of n into your calculator. Alternatively, you can solve the equation for n, which tests your familiarity with logarithms. Remember that 2 = 10log2 and 2n = 10nlog2 Substituting, 10nlog2 = 1013 Taking the log of both sides, nlog2 = 13 n = 13/log2 = 13/0.301 n = 43.2 B. If cells divided once per day and all cells continued to divide, it would take 43.2 days to generate the number of cells in an adult human. C. Obviously we don’t become adults in 43 days. The simple answer is that all cells don’t continue to divide once per day and some cells are programmed to die. As cells differentiate, they generally slow their rate of division, ultimately in the adult dividing just often enough to replace cells that are lost or die. Of course, the real answer is much more complex, involving time for cell movements, for local environments to be established, for extracellular matrices to be laid down, for cells to differentiate, for global patterns to develop, and so on. 1–20 For calculations such as these, it is useful for purposes of estimation to remember that 45 ≅103 (4n produces the series: 4, 16, 64, 256, 1024; thus, 45 = 1024 ≅ 103) and that (1/4)5 ≅ (1/10)3. Hence, 4 different nucleotides can generate 1024 different DNA sequences, each 5 nucleotides long. Similarly, an 8nucleotide DNA sequence can provide enough diversity to tag 25,000 genes, there being 48 or 65,536 possible 8-nucleotide sequences. However, one would expect that most of these sequences would be present more than once in the 3.2 ¥ 109 nucleotides of the human genome. Indeed, for a sequence tag to be rare enough to be expected to be present only once, it would have to be at least 16 nucleotides long. A 16-nucleotide sequence would be expected to be present about 0.7 times in the haploid human genome [(1/4)16 ¥ (3.2 ¥ 109) = 0.75]. A probability calculation should properly be used to assess the likelihood that a tag is sufficiently long to be unique in the genome. For a sequence that is present in one gene, what is the probability that it is also present elsewhere in the genome? The probability of a match (PM) in any one comparison is the chance of a match at every nucleotide (1/4)n. Thus, for one comparison PM = (1/4)n Since the probability of all events is 1, the probability of not matching (PN) in one comparison is PN = 1 – PM = 1 – (1/4)n And the probability of not matching in any number of comparisons (c) is PN = {1 – (1/4)n}c THE DIVERSITY OF GENOMES AND THE TREE OF LIFE For a 16-nucleotide sequence and 3.2 ¥ 109 comparisons (imagine sliding the 16-nucleotide segment one nucleotide at a time along the sequence of the human genome), the probability of not matching elsewhere is PN = 0.53 Or, since PN + PM = 1, PM = 0.47 Thus, for a 16-nucleotide sequence there is about a 1 in 2 chance that it will be present elsewhere in the human genome. As you can calculate, a 19nucleotide sequence, for example, reduces the probability of a match to 1 in 100. 1–21 The surface-to-volume ratio for a sphere is 4pr 2/[(4/3)pr 3] = 3/r; thus, the ratio is inversely proportional to radius. Consequently, relative to a human cell a bacterium has 10 times more surface per volume of cytoplasm to allow the passage of nutrients in and waste products out. The bacteria, however, grow 72 times faster than human cells, which suggests that something besides the available surface limits the rate of growth. THE DIVERSITY OF GENOMES AND THE TREE OF LIFE DEFINITIONS 1–22 Virus 1–23 Model organism 1–24 Archaea 1–25 Homolog 1–26 Eucaryote 1–27 Procaryote TRUE/FALSE 1–28 True. Phototrophs provide the major pathway by which carbon in CO2 is incorporated into the biosphere; however, it is not the sole mechanism. Most lithotrophs can also fix carbon, but the amounts are tiny in comparison to the carbon fixed by phototrophs. 1–29 False. The clusters of human hemoglobin genes arose during evolution by duplication from an ancient ancestral globin gene; thus, they are examples of paralogous genes. The human hemoglobin a gene is orthologous to the chimpanzee hemoglobin a gene, as are the human and chimpanzee hemoglobin b genes, etc. All the globin genes, including the more distantly related gene for myoglobin, are homologous to one another. THOUGHT PROBLEMS 1–30 Whether it’s sunlight or inorganic chemicals, ‘to feed’ means ‘to obtain freeenergy and building materials from.’ In the case of photosynthesis, photons in sunlight are used to raise electrons of certain molecules to a high-energy, unstable state. When they return to their normal, ground state, the released A5 A6 Chapter 1: Cells and Genomes energy is captured by mechanisms that use it to drive the synthesis of ATP. Similarly, lithotrophs at a hydrothermal vent obtain free energy by oxidizing one or more of the reduced components from the vent (for example, H2S Æ S + 2 H+), using some common molecule in the environment to accept the electrons (for example, (2 H+ + © O2 Æ H2O). Lithotrophs harvest the energy released in such oxidation–reduction (electron-transfer) reactions to drive the synthesis of ATP. For both lithotrophs and phototrophs, the key to success is the evolution of a molecular mechanism to capture the available energy and couple it to ATP synthesis. For all organisms, be they phototrophs, organotrophs, or lithotrophs, their ability to obtain the free energy needed to support life depends on the exploitation of some nonequilibrium condition. Phototrophs depend on the continual flux of radiation from the sun; organotrophs depend on a supply of organic molecules, provided ultimately by phototrophs, that can be oxidized for energy; and lithotrophs depend on a supply of reduced inorganic molecules, provided, for example, by hydrothermal vents, that can be oxidized to produce free energy. 1–31 The hemoglobin of the giant tube worms binds O2 and H2S and transports them to the symbiotic bacteria, which use the H2S as an electron donor and the O2 as an electron acceptor to generate ATP and reducing power to meet their energy needs. The resulting growth of the bacteria benefits the worms by providing increased waste products and dead bodies to live on. Moreover, in the process the toxic H2S is rendered harmless by oxidation to elemental sulfur, thereby preventing it from poisoning the worms. 1–32 The balanced equation for oxygenic photosynthesis, derived from experiments using water with isotopically labeled oxygen, is 6 CO2 + 12 H2O + light Æ C6H12O6 + 6 H2O + 6 O2 In this form of the equation it is apparent that the O2 derives from H2O, and that all the oxygen in glucose derives from CO2. 1–33 Four (Figure 1–5). All could have split from the common ancestor at the same time. Eubacteria–archaea could have split from eucaryotes, followed by the separation of eubacteria from archaea. Eubacteria–eucaryotes could have split from archaea, followed by the separation of eubacteria from eucaryotes. Archaea–eucaryotes could have split from eubacteria, followed by the separation of archaea from eucaryotes. Although horizontal transfers across these divisions make interpretations problematic, it is thought that archaea–eucaryotes first split from eubacteria, and then archaea split from eucaryotes. 1–34 It is unlikely that any gene came into existence perfectly optimized for its function. It is thought that highly conserved genes such as ribosomal RNA genes were optimized by more rapid evolutionary change during the evolution of the common ancestor to archaea, eubacteria, and eucaryotes. Since ribosomal RNAs (and the products of most highly conserved genes) participate in fundamental processes that were optimized early, there has been no evolutionary pressure (and little leeway) for change. By contrast, less conserved—more rapidly evolving—genes have been continually presented with opportunities to fill new functional niches. Consider, for example, the evolution of distinct globin genes that are optimized for oxygen delivery to embryos, fetuses, and adult tissues in placental mammals. A B E A B E A B E A E B Figure 1–5 The four possible relationships for the evolution of archaea (A), eubacteria (B), and eucaryotes (E) (Answer 1–33). THE DIVERSITY OF GENOMES AND THE TREE OF LIFE 1–35 It would be impossible to identify genes in a vast stretch of Ts, As, Cs, and Gs if genes did not have some identifying characteristics. In the absence of any knowledge of gene structure in procaryotes, you might imagine that the sites where gene transcription begins and ends might be special and thus recognizable. Similarly, you might imagine that sequences where protein synthesis begins and ends might be distinctive and thus recognizable. In reality, it is the signals for protein synthesis that have proven most valuable for identifying procaryotic genes. Genes that encode proteins, which are the vast majority, start with ATG (corresponding to the start codon AUG in the mRNA) and end with TAA, TAG, or TGA (corresponding to the three stop codons UAA, UAG, and UGA in mRNA). One searches for an ATG and then proceeds three nucleotides at a time (codon-by-codon) until a stop codon is reached. This procedure defines an open reading frame, or ORF. Nearly all ORFs greater than 100 codons correspond to genes. Some smaller ORFs also encode proteins and are therefore genes; however, many small ORFs occur by chance and do not correspond to genes. In some cases real genes can be identified among the smaller ORFs by virtue of other typical signal sequences that characterize genes in procaryotes. Nevertheless, in gene counts derived from genomic sequences an arbitrary cut-off is used so that the smallest ORFs are not included in the count. Gene identification in eucaryotic genome sequences is much more problematical. The protein-coding regions of eucaryotic genes are often split into segments that are not finally united until the initial RNA transcript is processed to remove the noncoding RNA. Thus, the procedure used to count genes in procaryotes is not useful for eucaryotes. Computer algorithms to identify eucaryotic genes are still in their infancy and are not yet reliable. 1–36 B. It is not thought that formation of genes de novo from the vast amount of unused, noncoding DNA typical of eucaryotic genomes is a significant process in evolution. Mutation to generate a coding sequence complete with regulatory elements is too slow a process to account for the observed rates of evolutionary change. 1–37 A. Since it appears that genes involved in informational processes are less subject to horizontal transfer, evolutionary trees derived from such genes should provide a more reliable estimate of evolutionary relationships. Thus, archaea most likely separated from eucaryotes after the archaea–eucaryote lineage separated from eubacteria. B. Complexity is a logical explanation for the difference in rates of horizontal gene transfer (and it may even be right, although there are other possibilities). Successful transfer of an ‘informational’ gene would require that the new gene product fit into a preexisting, functional complex, perhaps supplanting the original related protein. For a new protein to fit into a complex with other proteins, it would need to have binding surfaces that would allow it to interact with the right proteins in the appropriate geometry. If a new protein had one good binding surface, but not others, it would most likely disrupt the complex and put the recipient at a selective disadvantage. By contrast, a gene product that carries out a metabolic reaction on its own would be able to function in any organism. So long as the metabolic reaction conferred some advantage on the recipient (or at least no disadvantage) the gene transfer could be accommodated. Reference: Jain R, Rivera MC & Lake JA (1999) Horizontal gene transfer among genomes: The complexity hypothesis. Proc. Natl Acad. Sci. U.S.A. 96, 3801–3806. 1–38 In single-celled organisms the genome is the germline and any modification is passed on to the next generation. By contrast, in multicellular organisms most of the cells are somatic cells and make no contribution to the A7 A8 Chapter 1: Cells and Genomes next generation; thus, modification of those cells by horizontal gene transfer would have no consequence for the next generation. The germline cells are usually sequestered into the interior of multicellular organisms, minimizing their contact with foreign cells, viruses, and DNA, thereby insulating the species from the effects of horizontal gene transfer. 1–39 It is not a simple matter to determine the function of a gene from scratch, nor is there a universal recipe for how to do it. Nevertheless, there are a variety of standard questions that help narrow down the possibilities. Below we list some of these questions. In what tissues is the gene expressed? If the gene is expressed in all tissues, it is likely to have a general function. If it is expressed in one or a few tissues, its function is likely to be more specialized, perhaps related to the specialized functions of the tissues. If the gene is expressed in the embryo, but not the adult, it may function in development. In what compartment of the cell is the gene expressed? Knowing the subcellular localization of the protein—nucleus, plasma membrane, mitochondria, etc.—can also help to suggest categories of potential function. For example, a protein that is localized to the plasma membrane is likely to be a transporter, a receptor or other component of a signaling pathway, a celladhesion molecule, etc. What are the effects of mutations in the gene? Mutations that eliminate or modify the function of the gene product can also provide clues to function. For example, if the gene product is critical at a certain time during development, the embryo will often die at that stage or develop obvious abnormalities. Unless the abnormality is very specific, it is usually difficult to deduce the function or category of function. And often the links are very indirect, becoming apparent only after the gene’s function is known. With what other proteins does the encoded protein interact? In carrying out their function, proteins often interact with other proteins involved in the same or closely related processes. If an interacting protein can be identified, and if its function is already known (through previous research or the searching of databases), the range of possible functions can be narrowed dramatically. Mutations in what other genes can suppress effects of mutation in the unknown gene? Looking for suppressor genes can be a very powerful approach to investigating gene function in organisms such as bacteria and yeast, which have well-developed genetic systems, but this approach is not readily applicable to mouse or most higher eucaryotes at present. The rationale for this approach is analogous to that of looking for interacting proteins: genes that interact genetically are often involved in the same or a closely related process. Identification of such an interacting gene (and knowledge of its function) would provide an important clue to the function of the unknown gene. Addressing each of these questions requires specialized experimental expertise and a substantial time commitment from the investigator. It is no wonder that progress is made so much more rapidly when a clue to a gene’s function can be found simply by identifying a similar gene of known function in the database. CALCULATIONS 1–40 It takes only 20 hours—less than a day—before the mutant cells become more abundant in the culture. From the equation provided in the question, the number of the original (‘wild-type’) bacterial cells at time t minutes after the mutation occurred is 106 ¥ 2t/20. The number of mutant cells at time t is 1 ¥ 2t/15. At the time when the mutant cells ‘overtake’ the wild-type cells, these two numbers are equal. 106 ¥ 2t/20 = 2t/15 GENETIC INFORMATION IN EUCARYOTES Converting to base 10 (see Answer 1–19), 106 ¥ 10(t/20) log2 = 10(t/15) log2 Taking the log of both sides and substituting for log2 (0.301), 6 + (t/20)(0.301) = (t/15)(0.301) Solving for t, 6 + 0.015t = 0.020t 0.005t = 6 t = 1200 minutes, or 20 hours Note that it is also possible to solve this problem quickly, using the useful relationship 210 ≅ 103, by realizing that after 1 hour the mutant cells have doubled one more time than the wild-type cells. Thus, the mutant cells double relative to the wild-type cells once per hour. After 10 hours (210) the mutant cells would have gained a factor of a thousand (103), and after 20 hours (220), a factor of a million (106), at which time they would be equal in number to the wild-type cells. Incidentally, when the two populations of cells are equal, the culture contains 2 ¥ 1024 cells [(106 ¥ 260) + (1 ¥ 280) = (106 ¥ 1018) + 1024 = 2 ¥ 1024], which at 10–12 g per cell, would weigh 2 ¥ 1012 g, or two million tons! This can only have been a thought experiment. GENETIC INFORMATION IN EUCARYOTES TRUE/FALSE 1–41 False. Plant cells contain both mitochondria and chloroplasts. 1–42 True. Bacterial genomes seem to be pared down to the essentials: most of the DNA sequences encode proteins, a small amount of DNA is devoted to regulating gene expression, and there are very few extraneous, nonfunctional sequences. By contrast, only about 1.5% of the DNA sequences in the human genome is thought to code for proteins. Even allowing for large amounts of regulatory DNA, much of the human genome is composed of DNA with no apparent function. 1–43 False. In addition to transfers from the mitochondrial genome, there are many examples of transfers of viral genomes; for example, some 1% of the mouse genome arose from copies of a sequence that originated as the genome of the mouse mammary tumor virus. What is rare is the transfer of genes from other species. THOUGHT PROBLEMS 1–44 Like most questions about evolutionary relationships this one was decided by comparing sequences of genes such as those for ribosomal RNA. These comparisons showed that fungi are more similar in gene sequence to animals than to plants, and probably split from the animal–plant lineage after plants separated from animals. Thus, fungi are thought never to have had chloroplasts, and fungi and plants are thought to have invented cell walls independently, as is suggested by the use of cellulose in plant cell walls and chitin in fungal cell walls. 1–45 Nucleotide sequence comparisons with other species would allow you to decide whether Giardia represented an ancient lineage or a more recent A9 A10 Chapter 1: Cells and Genomes one. Such sequence comparisons have been done; they show that Giardia represents an ancient lineage (or one that has evolved very rapidly) that is almost as closely related to bacteria as it is to other eucaryotes. If Giardia were a stripped-down eucaryote, sequence comparisons would have revealed a closer kinship with the eucaryotic species from which it diverged. Standard sorts of sequence comparisons, of ribosomal RNA genes, for example, cannot decide the more fundamental—and more interesting—question of whether the Giardia lineage traces back to a time before mitochondria and internal membranes became permanent fixtures in eucaryotic cell organization. Additional sequence comparisons can be used to address this fundamental question. The hypothesis that Giardia lost its mitochondria as an adaptation to its current anaerobic lifestyle in the intestinal tract implies that its ancestors once lived in aerobic environments and depended on mitochondria for energy. If that were so, then mitochondrial genes might have been transferred to the nuclear genome, and the sequence of the Giardia genome might reveal genes that originated from mitochondria. Sequencing targeted to genes that are likely mitochondrial markers suggests that Giardia at one time did indeed possess mitochondria or some related endosymbiont. Reference: Roger AJ, Svard SG, Tovar J, Clark CG, Smith MW, Gillin FD & Sogin ML (1998) A mitochondrial-like chaperonin 60 gene in Giardia lamblia: Evidence that diplomonads once harbored an endosymbiont related to the progenitor of mitochondria. Proc. Natl Acad. Sci. U.S.A. 95, 229–234. 1–46 Three general hypotheses have been proposed to account for the differences in rate of evolutionary change in different lineages. The individual hypotheses discussed below are not mutually exclusive and may all contribute to some extent. The generation-time hypothesis proposes that rate differences are a consequence of different generation times. Species such as rat with short generation times will go through more generations and more rounds of germ-cell division, and hence more rounds of DNA replication. This hypothesis assumes that errors during DNA replication are the major source of mutations. Tests of this hypothesis in rat versus human tend to support its validity. The metabolic-rate hypothesis postulates a higher rate of evolution for species with a higher metabolic rate. Species with high metabolic rates use more oxygen; hence, they generate more oxygen free radicals, a major source of damage to DNA. This is especially relevant for mitochondrial genomes, because mitochondria are the major cellular site for oxygen utilization and free radical production. The efficiency-of-repair hypothesis proposes that the efficiency of repair of DNA damage differs in different lineages. Species with highly efficient repair of DNA damage would reduce the fraction of damage events that lead to mutation. There is evidence in cultured human and rat cells that such differences in repair exist, in the expected direction, but it is unclear whether such differences exist in the germlines of these organisms. Reference: Li WH (1997) Molecular Evolution, pp 228–230. Sinauer Associates, Inc.: Sunderland MA. DATA HANDLING 1–47 A. The simplest hypothesis is that gene transfer occurred at the point indicated in Figure 1–6. Genera in many of the lineages beyond this point have a nuclear Cox2 gene, whereas lineages that branched off prior to this point do not. B. Five genera (Lespedeza, Dumasia, Pseudeminia, Neonotonia, and Amphicarpa) apparently have functional copies of both the mitochondrial and the nuclear genes, as indicated by shaded boxes in Figure 1–6. A11 GENETIC INFORMATION IN EUCARYOTES GENE RNA mt nuc mt nuc Pisum + + Clitoria + + Tephrosia Galactia Canavalia + + + + + + Lespedeza + + + + Eriosema Atylosia Erythrina gene transfer and activation + + + + + + Ramirezella Vigna Phaseolus + + + + + + + + + Calopogonium + Pachyrhizus + + + + + + + + + + + Dumasia Cologania Pueraria Pseudeminia Pseudovigna + + + + + + + Ortholobium Psoralea Cullen Glycine + + + + + + + + + + + Neonotonia Teramnus Amphicarpa + + + + + + + C. Ten genera (Eriosema, Atylosia, Erythrina, Ramirezella, Vigna, Phaseolus, Ortholobium, Psoralea, Cullen, and Glycine) no longer have a functional mitochondrial gene. The minimum number of inactivation events that could account for the observed data is four, as shown by squares on the tree in Figure 1–6. D. Six genera no longer have a functional nuclear gene. The minimum number of inactivation events that could account for this is five, as shown by circles on the tree in Figure 1–6. E. These data argue strongly that transfer of genes from mitochondria to the nucleus is not a one-step process; that is, simultaneous loss of the gene from mitochondria and its appearance in the nucleus. This is an unlikely scenario a priori since nuclear versions of mitochondrial genes must acquire a special targeting sequence that allows the encoded proteins to be delivered to mitochondria (see MBoC Chapter 12). The data in Figure 1–6 argue that the transfer process begins with the appearance of the gene in the nucleus (presumably followed at some point by its activation via acquisition of a targeting sequence). This first step is not accompanied by loss of the gene from the mitochondria. Once the nuclear gene is activated, there appears to be an intermediate stage in which both genes function. Subsequently, one or the other gene is inactivated. If the nuclear gene is inactivated, the transfer process is effectively aborted. If the mitochondrial gene is inactivated (often initially by point mutations), then the transfer can proceed. The final stage of transfer is deletion of the defective mitochondrial gene, a process favored by the economics of genome replication. Reference: Adams KL, Song K, Roessler PG, Nugent JM, Doyle JL, Doyle JJ & Palmer JD (1999) Intracellular gene transfer in action: Dual transcription and multiple silencings of nuclear and mitochondrial cox2 genes in legumes. Proc. Natl Acad. Sci. U.S.A. 96, 13863–13868. 1–48 If the intermediary in transfer were DNA, you would expect that the nuclear copy of the gene would have Cs at the sites of RNA editing. If the intermediary were RNA, you would expect Ts at the sites of RNA editing. Figure 1–6 Summary of Cox2 gene distribution and transcript data in a phylogenetic context, showing the most likely point of gene transfer and the minimal number of points for mitochondrial (squares) and nuclear (circles) gene inactivation (Answer 1–47). Boxes indicate genera with apparently functional copies of both the mitochondrial and nuclear genes. A12 Chapter 1: Cells and Genomes When sequences of nuclear Cox2 genes were examined, they were found to resemble the edited RNA transcript more closely. This observation suggests that RNA was an intermediary in the transfer process. At some point the RNA was presumably copied back into DNA by reverse transcription. Whether this is a general feature of transfer is unclear. Reference: Nugent JM & Palmer JD (1991) RNA-mediated transfer of the gene coxII from the mitochondrion to the nucleus during flowering plant evolution. Cell 66, 473–481. 1–49 A. Because synonymous changes do not alter the amino acid sequence of the protein, they are not subject to selection pressures, which operate at the level of the function of the protein (and how it affects the overall fitness of the organism). By contrast, nonsynonymous changes, which substitute a new amino acid in place of the original one, have the potential to alter the function of the encoded protein (and change the fitness of the organism). Since most amino acid substitutions are deleterious to the function of the protein, they are selected against. B. The histone H3 gene must be so exquisitely tuned to its function that virtually all amino acid substitutions are deleterious and, therefore, are selected against. The extreme conservation of histone H3 argues that its function is very tightly constrained, probably because of extensive interactions with other proteins and with its unchanging substrate, DNA. C. Histone H3 is clearly not in a ‘privileged’ site in the genome because it undergoes synonymous nucleotide changes at about the same rate as other genes. Reference: Li WH (1997) Molecular Evolution. Sinauer Associates, Inc.: Sunderland MA. 1–50 A. The data in the phylogenetic tree (see Figure 1–3) refute the hypothesis that plant hemoglobin genes arose by horizontal transfer. Looking at the more familiar parts of the tree, we see that the vertebrates (fish to human) cluster together as a closely related set of species. Moreover, the relationships in the unrooted tree shown in Figure 1–3 are compatible with the order of branching we know from the evolutionary relationships among these species: fish split off before amphibians, reptiles before birds, and mammals last of all in a tightly knit group. Plants also form a distinct group that displays accepted evolutionary relationships, with barley, a monocot, diverging before bean, alfalfa, and lotus, which are all dicots (and legumes). The sequences of the plant hemoglobins appear to have diverged long ago in evolution, at or before the time that mollusks, insects, and nematodes arose. The relationships in the tree indicate that the hemoglobin genes arose by descent from some common ancestor. B. Had the plant hemoglobin genes arisen by horizontal transfer from a parasitic nematode, then the plant sequences would have clustered with the nematode sequences in the phylogenetic tree in Figure 1–3. ...
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This note was uploaded on 04/07/2008 for the course BME 50A taught by Professor Botvinick during the Spring '08 term at UC Irvine.

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