NUCLEIC ACID STRUCTURE AND FUNCTION
`
`Lead Editor:  Bob Moss
`
`Eukaryotic Genome Complexity
`By: Leslie A. Pray, Ph.D. © 2008 Nature Education 
`Citation: Pray, L. (2008) Eukaryotic genome complexity. Nature Education 1(1):96
`
`Figure 1: Chromatin has highly complex structure with several levels of organization.
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`How many genes are there? This question is surprisingly not very important, and
`has nothing to do with the organism's complexity. There is more to genomes than
`protein-coding genes alone.
`Consider these fundamental facts about the eukaryotic nuclear genome. It is linear, as opposed to the typically circular DNA of bacterial
`cells. It conforms to the Watson-Crick double-helix structural model. Furthermore, it is embedded in nucleosomes—complex DNA-
`protein structures that pack together to form chromosomes. Beyond these basic, universal features, eukaryotic genomes vary dramatically
`in terms of size and gene counts. Even so, genome size and the number of genes present in an organism reveal little about that
`organism's complexity (Figure 1).
`The simplest level is the double-helical structure of DNA.
`

`

`Nature Education
`
`Does Size Matter?
`
`How Many Protein-Coding Genes Are in That Genome?
`
`Figure 2
`
`Table 1: Genome Size and Number of Protein-Coding Genes for a Select Handful of 
`
`Species and Common Name
`
`Estimated Total Size of Genome
`(bp)*
`
`Estimated Number of Protein-
`Encoding Genes*
`
`00002
`
`© 2013 
` Adapted from Pierce, Benjamin. Genetics: A Conceptual Approach, 2nd ed. All rights
`reserved. 
`Thirty-six horizontal
`lines on a graph
`represent the genomes
`of 36 taxa, including
`bacteria, plants, insects,
`fish, reptiles, birds, and
`mammals. The graph's
`x-axis is labeled from
`negative one to positive
`six and represents
`genome size as a log-
`ten-C value in millions
`of base pairs (MB). A
`circle in the middle of
`each line represents the
`average genome size,
`and the length of the
`lines represents the
`range of genome sizes
`for the specified taxa.
`How big is it? That is usually the first question asked about an organism's genome. Over the past 60 years,
`scientists have estimated the genome sizes of more than 10,000 plants, animals, and fungi. However, while
`information about an organism's genome size might seem like a good starting point for attempting to
`understand the genetic content, or "complexity," of the organism, this approach often belies the tremendous
`complexity of the eukaryotic genome. As Van Straalen and Roelofs (2006) explain, "There is a remarkable
`lack of correspondence between genome size and organism complexity, especially among eukaryotes. For
`example, the marbled lungfish, 
`Protopterus aethiopicus, has more than 40 times the amount of DNA
`per cell than humans!" (Figure 2). Indeed, the marbled lungfish has the largest recorded genome of
`any eukaryote. One haploid copy of this fish's genome is composed of a whopping 132.8 billion base pairs,
`while one copy of a human haploid genome has only 3.5 billion. (Genome size is usually measured in
`picograms [pg] and then converted to nucleotide number. One pg is equivalent to approximately 1 billion
`base pairs.) Therefore, genome size is clearly not an indicator of the genomic or biological complexity of an
`organism. Otherwise, humans would have at least as much DNA as the marbled lungfish, although probably
`much more.
`As further clarification, when scientists talk about the eukaryotic genome, they are usually referring to the
`haploid genome—this is the complete set of DNA in a single haploid nucleus, such as in a sperm or egg. So,
`saying that the human genome is approximately 3 billion base pairs (bp) long is the same as saying that
`each set of chromosomes is 3 billion bp long. In fact, each of our diploid cells contains twice that amount of
`base pairs. Moreover, scientists are usually referring only to the DNA in a cell's nucleus, unless they state
`otherwise. All eukaryotic cells, however, also have mitochondrial genomes, and many additionally
`contain chloroplast genomes. In humans, the mitochondrial genome has only about 16,500 nucleotide base
`pairs, a mere fraction of the length of the 3 billion bp nuclear genome (Anderson 
`et al., 1981).
`Interestingly, the same "remarkable lack of correspondence" can be noted when discussing the relationship between the number of
`protein-coding genes and organism complexity. Scientists estimate that the human genome, for example, has about 20,000 to 25,000
`protein-coding genes. Before completion of the draft sequence of the Human Genome Project in 2001, scientists made bets as to how
`many genes were in the human genome. Most predictions were between about 30,000 and 100,000. Nobody expected a figure as low as
`20,000, especially when compared to the number of protein-coding genes in an organism like 
`Trichomonas vaginalis. T. vaginalis is a
`single-celled parasitic organism responsible for an estimated 180 million urogenital tract infections in humans every year. This tiny
`organism features the largest number of protein-coding genes of any eukaryotic genome sequenced to date: approximately 60,000.
`In fact, compared to almost any other organism, humans' 25,000 protein-coding genes do not seem like many. The fruit fly Drosophila
`melanogaster, for example, has an estimated 13,000 protein-coding genes. Or consider the mustard plant 
`Arabidopsis thaliana, the "fruit
`fly" of the plant world, which scientists use as a model organism for studying plant genetics. 
`A. thaliana has just about the same number
`of protein-coding genes as humans—actually, it has slightly more, coming in at about 25,500. Moreover, 
`A. thaliana has one of the
`smallest genomes in the plant world! It would seem obvious that humans would have more protein-coding genes than plants, but that is
`not the case. These observations suggest that there is more to the genome than protein-coding genes alone.
`As shown in Table 1 (adapted from Van Straalen & Roelofs, 2006), there is no clear correspondence between genome size and number of
`protein-coding genes—another indication that the number of genes in a eukaryotic genome reveals little about organismal complexity.
`The number of protein-coding genes usually caps off at around 25,000 or so, even as genome size increases.
`Species
`Saccharomyces
`cerevisiae
` (unicellular budding yeast)
`12 million
`6,000
`Trichomonas vaginalis
`160 million
`60,000
`Plasmodium falciparum (unicellular
`malaria parasite)
`23 million
`5,000
`Caenorhabditis elegans (nematode)
`95.5 million
`18,000
`Drosophila melanogaster (fruit fly)
`170 million
`14,000
`Arabidopsis thaliana (mustard; thale
`cress)
`125 million
`25,000
`Oryza sativa (rice)
`470 million
`51,000
`Gallus gallus (chicken)
`1 billion
`20,000-23,000
`

`

`Beyond Estimating the Number of Protein-Coding Genes
`
`References and Recommended Reading
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`290
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`25
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`315
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`309
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`00003
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`Canis familiaris (domestic dog)
`2.4 billion
`19,000
`Mus musculus (laboratory mouse)
`2.5 billion
`30,000
`Homo sapiens (human)
`2.9 billion
`20,000-25,000
`* There may be other estimates in the literature, but most estimates approximate those listed here.
`While the majority of emphasis has been placed on protein-coding genes in particular, scientists have continued to refine their definition
`of what exactly a gene is, partly in response to the realization that DNA encodes more than just proteins. For instance, in a study of the
`mouse genome, scientists found that more than 60% of this 2.5 billion bp genome is transcribed, but less than 2% is actually translated
`into functional protein products (FANTOM Consortium 
`et al., 2005). Within this article, however, the discussion focuses on protein-coding
`genes, unless otherwise stated. Note, however, that much of the genome's transcription is dedicated to making tRNA, rRNA, and many
`RNAs involved in splicing and gene regulation.
`While scientists have been measuring genome size for decades, they have only recently had the technological capacity and know-how to
`count genes. To estimate the number of protein-coding genes in a genome, scientists often start by using what are known as gene-
`prediction programs: computational programs that align the sequence of interest with one or more known genome sequences. Other
`computer programs can predict gene location by looking for sequence characteristics of genes, such as open reading frames within exons
`and CpG islands within promoter regions.
`However, all of these computer programs only 
`predict the presence of genes. Each prediction must then be experimentally validated, such
`as by using microarray hybridization to confirm that the predicted genes are represented in RNA (Yandell 
`et al., 2005). As Michael Brent, a
`professor of computer engineering at Washington University, explained in 
`Nature Biotechnology, gene prediction has become much more
`accurate over the past several years (Brent, 2007). Its improved precision accounts for why estimates of the number of genes in the
`human genome have decreased from 45,000 about 10 years ago, to Venter 
`et al.'s estimate of 26,588 upon completion of the Human
`Genome Project (Venter 
`et al., 2001), to the current estimate of between 20,000 and 21,000. In short, the older computational methods
`generated a lot of false positives, meaning that they predicted the presence of protein-coding genes that weren't actually there.
`As with genome size, having more protein-coding genes does not necessarily translate into greater complexity. This is because the
`eukaryotic genome has evolved other ways to generate biological complexity. Much of this complexity derives from how the genome
`"behaves," or more precisely, how various genes are expressed.
`Alternative splicing was the first phenomenon scientists discovered that made them realize that genomic complexity cannot be judged by
`the number of protein-coding genes. During alternative splicing, which occurs after transcription and before translation, introns are
`removed and exons are spliced together to make an mRNA molecule. However, the exons are not necessarily all spliced back together in
`the same way. Thus, a single gene, or transcription unit, can code for multiple proteins or other gene products, depending on how the
`exons are spliced back together. In fact, scientists have estimated that there may be as many as 500,000 or more different human
`proteins, all coded by a mere 20,000 protein-coding genes.
`Scientists have since come across several other mechanisms that contribute to the eukaryotic genome's capacity to generate phenotypic
`complexity. These include RNA editing, trans-splicing, and tandem chimerism. RNA editing is the alteration of an mRNA molecule after
`transcription—for example, the modification of a cytosine to a uracil before an mRNA molecule is translated into a protein. The
`phenotypic consequences of RNA editing vary among genes and species. While sometimes detrimental (e.g., some RNA editing events
`have been associated with disease), those RNA editing events that lead to slight changes in protein structure could be selectively
`advantageous (Reenan, 2005). Trans-splicing is the splicing together of separate transcripts to form an mRNA molecule, as opposed to
`alternative splicing, which is the splicing together of exons from the same transcript. Tandem chimerism occurs when adjacent
`transcription units are transcribed together to form a single "chimeric" mRNA molecule (Parra 
`et al., 2005).
`Consider again those 60,000 protein-coding genes in 
`Trichomonas vaginalis. If all of those 60,000 genes operated at the same level of
`complexity as the 20,000 or so genes in 
`Homo sapiens, then shouldn't T. vaginalis be a much more complex organism than it is? As it
`turns out, its genes do not operate at that same level of complexity. For starters, few of the genes have any introns at all, which means
`that alternative splicing is not a major source of protein variation. Rather, scientists suspect the large number of genes—which,
`incidentally, is 10 times more than they expected they would find before they started the sequencing project—is due
`to duplication (Carlton 
`et al., 2007). In other words, many of the genes are simply copies of each other. Furthermore, about half are
`believed to be "pseudogenes," or DNA sequences that are similar to functional protein-coding genes but have lost their protein-encoding
`capacities. Scientists still don't know why the 
`T. vaginalis genome has so many genes, including so many defunct genes.
`Organismal complexity is thus the result of much more than the sheer number of nucleotides that compose a genome and the number of
`coding sequences in that genome. Not only may one coding sequence encode a large number of separate protein products via alternative
`splicing, but many genomes are also rich with noncoding RNA sequences that work to coordinate gene expression. When one combines
`these elements with other regulatory elements, such as enhancers and promoters, as well as with potential sequences that remain
`uncharacterized, it becomes clear that while size is one component of organismal complexity, its contribution to that complexity is small.
`Anderson, S. Sequence and organization of the human mitochondrial genome. 
`Nature 
`, 457–465 (1981) doi:10.1038/290457a0 (link
`to article)
`Brent, M. R. How does eukaryotic gene prediction work? 
`Nature Biotechnology 
`, 883–885 (2007) doi:10.1038/nbt0807-883 (link to
`article)
`Carlton, J. M., 
`et al. Draft genome sequence of the sexually transmitted pathogen Trichomonas vaginalis. Science 
`, 207–212 (2007)
`doi:10.1126/science.1132894
`FANTOM Consortium, 
`et al. The transcriptional landscape of the mammalian genome. Science 
`, 1559-1563 (2005)
`doi:10.1126/science.1112014
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`Outline  
`
`  Keywords  
`
`  Add Content to Group  
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`APPLICATIONS IN BIOTECHNOLOGY
`DNA REPLICATION
`JUMPING GENES
`TRANSCRIPTION & TRANSLATION
`Genetically Modified Organisms (GMOs):
`Transgenic Crops and Recombinant DNA
`Technology
`Recombinant DNA Technology and Transgenic
`Animals
`Restriction Enzymes
`The Biotechnology Revolution: PCR and the Use of
`Reverse Transcriptase to Clone Expressed Genes
`DNA Damage & Repair: Mechanisms for
`Maintaining DNA Integrity
`DNA Replication and Causes of Mutation
`Genetic Mutation
`Genetic Mutation
`Major Molecular Events of DNA Replication
`Semi-Conservative DNA Replication: Meselson and
`Stahl
`Barbara McClintock and the Discovery of Jumping
`Genes (Transposons)
`Functions and Utility of 
`Alu Jumping Genes
`Transposons, or Jumping Genes: Not Junk DNA?
`Transposons: The Jumping Genes
`DNA Transcription
`RNA Transcription by RNA Polymerase: Prokaryotes
`vs Eukaryotes
`Translation: DNA to mRNA to Protein
`What is a Gene? Colinearity and Transcription Units
`Gregory, T. R. Synergy between sequence and size in large-scale genomics. 
`Nature Reviews Genetics 
`, 699–708 (2005)
`doi:10.1038/nrg1674 link to article)
`Parra, G., 
`et al. Tandem chimerism as a means to increase protein complexity in the human genome. Genome Research 
`, 37–44
`(2005)
`Reenan, R. Molecular determinants and guided evolution of species-specific RNA editing. 
`Nature 
`, 409–413 (2005)
`doi:10.1038/nature03364 (link to article)
`Van Straalen, N. I., & Roelofs, D. 
`Introduction to Ecological Genetics (New York, Oxford University Press, 2006)
`Venter, J. C., 
`et al. The sequence of the human genome. Science 
`, 1304–1351 (2001) doi:10.1126/science.1058040
`Yandell, M., 
`et al. A computational and experimental approach to validating annotations and gene predictions in the Drosophila
`melanogaster
` genome. Proceedings of the National Academy of Sciences 
`, 1566–1571 (2005)
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