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Even before the discovery of the structure of DNA, it was clear that the fertilized mammalian egg could contain only a finite amount of genetic information, and that this information was all that was needed to define something as complicated as a whole mouse or human being. However, with the demonstration of the double helix and the unraveling of the relationships that exist between basepairs, codons, genes, and polypeptides, it became possible to determine just how finite the total sum of genetic information actually is. But the problem that still looms large is an understanding of the essential genetic information needed to make a mammal. Is it the total amount of DNA in a haploid set of chromosomes, just that portion of DNA that does not include repeated sequence copies, transcription units, coding and regulatory regions, or only those genes required for viability? In some cases, it seems possible to distinguish among what is essential, what is nice to have but not essential, and that which serves no useful function at all. However, in many cases, the distinctions are still not yet clear. This section addresses the quantitation of the genome at various levels of analysis.

5.1.1 How large is the genome?

Quantitative DNA-specific staining can be achieved with the use of the Feulgen reagent. Through microphotometric measurements of the staining intensity in individual sperm nuclei, it is possible to determine the total amount of DNA present in the haploid mouse genome (Laird, 1971). These measurements indicated a total haploid genome content of 3 pg, which translates into a molecular weight of 1.8 x 1012 daltons (Da).

The smallest unit of genetic information is the basepair (bp) which has a molecular weight of ~600 Da. By dividing this number into the total haploid DNA mass, one arrives at an approximate value for the total information content in the haploid genome: three billion bp, which can also be written as three million kilobasepairs (kb) or 3,000 megabasepairs (mb). All eutherian mammals have genomes of essentially the same size.

It is instructive to consider the size of the mammalian genome in terms of the amount of computer-based memory that it would occupy. Each basepair can have one of only four values (G, C, A, or T) and is thus equivalent to two bits of binary code information (with potential values of 00, 01, 10, 11). Computer information is usually measured in terms of bytes that typically contain 8 bits. Thus, each byte can record the information present in 4 bp. A simple calculation indicates that a complete haploid genome could be encoded within 750 megabytes of computer storage space. Incredibly, small lightweight storage devices with such a capacity are now available for desktop computers. Of course, the computer capacity required to actually interpret this information will be many orders of magnitude larger.

5.1.2 How complex is the genome?

Another method for determining genome size relies upon the kinetics of DNA renaturation as an indication of the total content of different DNA sequences in a sample. When a solution of double stranded DNA is denatured into single strands which are then allowed to renature, the time required for renaturation is directly proportional to the complexity of the DNA in the solution, if all other parameters are held constant. Single-stranded and double-stranded molecules are easily distinguished by various physical, chemical, and enzymatic procedures.

Complexity is a measure of the information contained within the DNA. The maximal information possible in a solution of genomic DNA purified from one animal or tissue culture line is equivalent to the total number of basepairs present in the haploid genome. 24 The information content of a DNA solution is independent of the actual amount or concentration of DNA present. DNA obtained from one million cells of a single animal or cell line contains no more information than the DNA present in one cell. Furthermore, if sequences within the haploid genome are duplicates of one another — repeated sequences — the complexity will drop accordingly.

The effect of complexity on the kinetics of renaturation can be understood by viewing the system through the eyes of a single strand of DNA, randomly diffusing through a solution, looking for its complementary partner. For example, imagine two DNA solutions, both 2 micrograms/ml in concentration, but one from a genome having a complexity of 3x109 bp, and the second from a genome having a complexity of only 3x108 bp. In the second solution, with the same quantity of DNA but ten-fold less complexity, each segment of DNA sequence will be represented ten times as often as any particular segment of DNA sequence in the first solution. Thus, a single strand will be able to find its partner ten times more quickly in the second solution as compared to the first solution. The speed with which a DNA sample renatures can be expressed in the form of a Cot curve, which is a graphic representation of the fraction of a sample that has renatured (along the Y axis) as a function of the single stranded DNA concentration at time zero (C0) multiplied by the time allowed for renaturation (t) shown on the X axis. The C0t value attained at the midpoint of renaturation — when half of the molecules have become double-stranded — is called C0t1/2 and is used as a indicator of the complexity of the sample being measured. Different C0t1/2 values can be compared directly to allow a determination of complexity in a new sample relative to a calibrated control.

Renaturation analysis of mouse DNA reveals an overall complexity of approximately 1.3-1.8 x 109 bp. This value is only 40-60% of the size of the complete haploid genome and it implies the existence of a large fraction of repeated sequences. In fact, a careful analysis of the renaturation curve indicates that 5% of the genome renatures almost one million times faster than the bulk of the DNA. This "low complexity class" of sequences represents the satellite DNA which is discussed in detail in Section 5.3.3. After renaturation of the satellite DNA class comes a very broad class of repeated sequences (whose copy number varies from several hundred thousand to less than ten) which merges into the final bulk class of "unique" sequences. With the advent of DNA cloning and sequencing, the "repeated sequence" class of mouse DNA has been divided into a number of functionally and structurally distinct subclasses which are also discussed more fully in Sections 5.3 and 5.4. It was originally assumed that nearly all of the protein-coding genes would be present in the final renaturation class of unique copy sequences. However, we now know that the situation is not that simple and that many genes are members of gene families that can have anywhere from two to 50 similar, but non-identical, cross-hybridizing members.

5.1.3 What is the size of the mouse linkage map?

The genome size of any sexually reproducing diploid organism can actually be measured according to two semi-independent parameters. There is the physical size measured in numbers of basepairs, as just discussed, and there is recombinational size measured in terms of the cumulative linkage distances that span each chromosome (discussed fully in Section 7.1). The size of the whole mouse linkage map can be arrived at by a number of different approaches. First, one can perform a statistical test on the frequency with which new loci are found to be linked to previously identified loci In 1954, Carter used this test on then-available data for 43 loci to estimate the size of the complete mouse linkage map at 1620 +/- 352 cM 25 (Carter, 1954).

A second estimate is based on counting the number of chiasmata that appear in spreads of chromosomes prepared from germ cells undergoing meiosis and viewed under the microscope. A chiasma (the singular of chiasmata) represents the cytological manifestation of crossing over; it is seen as a visible connection between non-sister chromatids at each site where a crossover event has occurred between the maternally and paternally derived chromosomes of the animal that provided the sample. 26 Chiasma formation occurs after the final round of DNA replication when each of the two homologs contains two identical sister chromatids — the genomic content of cells at this stage is represented by the notation "4N." Each crossover event involves only two of the four chromatids present. Thus, there is only a 50% chance that any one crossover event will be segregated to any one haploid (1N) gamete and so the total number of crossovers segregated into any one gamete genome will be approximately half the number of chiasmata present within 4N meiotic cells. Thus, one can derive an estimate of total linkage distance by multiplying the average number of chiasmata observed per meiotic cell by the expected interchiasmatic distance (100 cM) and dividing by two. This analysis provided the basis for a whole mouse genome linkage size of 1,954 cM (Slizynski, 1954).

With the generation of high-density whole genome linkage maps based on the segregation of hundreds of loci, it is now possible to determine map size directly from the distance spanned by the set of mapped loci. In two cases, this calculation was performed for data generated within the context of single crosses: the resulting map sizes were 1,424 cM for a B6 X M. spretus intercross-backcross (Copeland and Jenkins, 1991) and 1,447 cM for an F2 intercross between B6 and M. m. castaneus (Dietrich et al., 1992). Two other direct estimates of 1,468 cM and 1,476 cM are based on whole genome consensus maps formed by the incorporation of data from large numbers of different crosses that used overlapping sets of markers for mapping (Hillyard et al., 1992; Lyon and Kirby, 1992).

All of these estimates are remarkably consistent with each other and yield a simple average value of 1,453 cM. 27 This consistency is remarkable because, in isolated regions of the genome, linkage distances are highly strain-dependent with differences that vary by as much as a factor of two (see Section 7.2.3). Nevertheless, the accumulated data suggest that the overall level of recombination is pre-determined in the Mus genus and maintained from one cross to another through compensatory changes so that suppression of recombination in one region will be offset by an increase in recombination in another region of the genome.

One can derive an average equivalence value between the two metrics of genome measurement described in this section — kilobases and centimorgans — of approximately 2,000 kb per centimorgan. As mentioned above and discussed in Section, the actual relationship between linkage distance and physical distance can vary greatly in different parts of the genome as well as in crosses between different strains of mice.

5.1.4 What proportion of the genome is functional?

Bacterial species are remarkably efficient at packing the most genetic information into the smallest possible space. In one analysis of a completely sequenced 100 kb region of the E. coli chromosome, it was found that 84% of the total DNA content was actually used to encode polypeptides (Daniels et al., 1992). Most of the remaining DNA is used for regulatory purposes, and only 2% was found to have no recognizable function.

In higher eukaryotes of all types, the situation has long been known to be quite different. The early finding that some primitive organisms had haploid genome sizes which were many-fold larger than that of mammals 28 led to the realization that large portions of higher eukaryotic genomes might be "non-functional". However, to answer the question posed in the title to this section, one must first define what is meant by functional. Are entire transcription units considered functional even though, in most cases, 80% or more of the transcript will be spliced away before translation begins? Are both copies of a perfectly duplicated gene considered functional even though the organism could function just as well without one. What about the twilight class of pseudogenes which, in some cases, may be functional in some individuals but not others, and may serve as a reservoir for the emergence of new genetic elements in a future generation? Finally, comparative sequence analysis over long regions of the mouse and human genomes shows evolutionary conservation over stretches of sequence that do not have coding potential or any obvious function (Hood, 1992). However, sequences can only be conserved when selective forces act to maintain their integrity for the benefit of the organism. Thus, conservation implies functionality, even though we may be too ignorant at the present time to understand exactly what that functionality might be in this case.

Taking all of these caveats into consideration, and defining functional sequences as those with coding potential or with potential roles in gene regulation or chromatin structure, one can come up with a broad answer to the question posed in this section based on a synthesis of the data described in the next section. The fraction of the mouse genome that is functional is likely to lie somewhere between 5% and 10% of the total DNA present.

5.1.5 How many genes are there? Gene density estimates

How many genes are in the genome? A truly accurate answer to this question will be a long time in coming. The complete sequence of the genome will almost certainly provide a means for uncovering most genes, however, an unknown percentage will probably still remain hidden from view. But, in the absence of a complete sequence, one is forced to make multiple assumptions in order to come up with just a broad estimate of the final number.

One approach to estimating gene number is to derive an average gene size and then determine how many average genes can fit into a 3,000 megabase pair space. Unfortunately, the sizes of the genes characterized to date do not form a nice discrete bell curve around some mean value. The first mammalian gene to be characterized — Hbb — encodes the beta-globin polypeptide; the Hbb gene has a length on the order of 2 kb. The alpha globin gene is even smaller with a length of less than 1 kb. At the opposite extreme is the mouse homolog of the human Duchene's muscular dystrophy gene (called mdx in the mouse); at 2,000 kb, the size of mdx is three orders of magnitude larger than Hbb. Nevertheless, a survey spanning all of the hundreds of mammalian genes characterized to date would seem to suggest that mdx is an extreme example, with most genes falling into the range of 10-80 kb, with an median size in the range of 20 kb. This estimate must be considered highly qualified, since size could play a role in determining which genes have been cloned and characterized.

Interestingly, a similar estimate of median gene size is obtained by viewing complete cellular polypeptide patterns on two-dimensional gels where the highest density of proteins appears in the 50-70,000 Mr window for all cell types. A "typical" polypeptide in this range will have an amino acid length of ~600, encoded within 1,800 nucleotides, that will "typically" be flanked by another 200 nucleotides of untranslated regions on the 3' and 5' ends of a 2 kb mRNA that has been "typically" spliced down from an original 20 kilobase transcript that included 18 kb of intronic sequences. 29 If one assumes an average inter-gene distance of 10 kb — including gene regulatory regions and various non-essential repetitive elements to be discussed later — one obtains an average density of one gene per 30 kb. When this number is divided into the whole 3,000 mb genome, one derives a total gene number of 100,000.

Actual validation of a gene density in the range just estimated has been obtained for the major histocompatibility (MHC) region of the human and mouse genomes. With intensive searches for all transcribed sequences present within portions of the 4 mb MHC region, a gene density of one per 20 kb has been found (Milner and Campbell, 1992). Direct extrapolation of this gene density to the whole genome would yield a total of 130,000 genes. However, such an extrapolation is probably not valid since the average gene size in the MHC appears to be significantly smaller than the average overall. Another problem is that a significant proportion of the "genes" in the MHC (and elsewhere as well) are non-functioning pseudogenes. If one assumes a pseudogene rate of 20%, the value of 130,000 is reduced down to near 100,000.

A serious problem with all estimates made from the extrapolation of "average" genes is that genomic regions containing smaller, more densely packed genes will contribute disproportionately to the total number. As an example only, if 1% of the genome was occupied by (mostly uncharacterized) short genes that were only 500 bp in length and were packed at a density of one per kilobase, this class alone would account for 30,000 genes to be added onto the previous 100,000 estimate. Number of transcript estimates

A very different approach to placing boundaries on the total gene number is to estimate the number of different transcripts produced in various cell types. Estimates of this type can be made, in a manner similar to that described for Cot studies, by analyzing the kinetics of mRNA-cDNA renaturation for a determination of the "complexity" of transcript populations in single cell types or tissues. This approach allowed Hasties and Bishop (1976) to estimate the presence of 12,000 different transcripts (representing the products of 12,000 different genes) in each of the three tissues analyzed — liver, kidney, and brain. However, as these investigators indicate, the brain in particular is a very complex tissue with millions of cells that are likely to have different patterns of gene expression. Genes expressed at low levels in a small percentage of cells will go undetected in a broad-tissue analysis of the type described. Thus, the actual level of gene expression in the brain, and other complex "tissues" like the developing embryo, could be much greater than the number derived experimentally. A revised complexity estimate of 20-30,000 has been suggested for the brain.

The only way in which estimates of transcript number could provide an estimate of total gene number is if every tissue in the body was analyzed at every developmental stage, and the number of cell- or stage-specific transcripts was determined apart from the number that were expressed elsewhere. A comprehensive analysis of this type is impossible even today, but some simple estimates can be made. For example, by analysis of cross-hybridization between sequences from different tissues, an overlap in expression of 75-85% has been estimated (Hasties and Bishop, 1976). This would suggest that perhaps 3,000 genes may be uniquely expressed in any one tissue relative to any other. However, when the data from many tissues are brought together, the actual number of tissue-specific transcripts is likely to be further reduced. On the other hand, it is also the case that some genes are likely to function in some tissue types only during brief periods of development.

Interpretation of the accumulated data provides a means only for estimating the minimum number of transcribed genes that could be present in the genome. By adding the brain estimate of ~25,000 to ~1,000 unique genes for each of 25 different tissue types, one arrives at a minimum estimate of 50,000. Vital function estimates

Another independent, and very old, method for estimating gene number is to first saturate a region of known length with mutations that cause homozygous lethality, then count the number of lethal complementation groups and extrapolate from this number to the whole genome. The assumption one makes with an approach of this type is that the vast majority of genes in the genome will be essential to the viability of the organism. If one eliminates the expression of a "vital" gene through mutagenesis, the outcome will be a clear homozygous phenotype of prenatal or postnatal lethality.

It has long been clear that the early assumption of vitality associated with most genes is incorrect. Even genes thought to play critical roles in cell cycling and growth, such as p53, can be "knocked-out" and still allow the birth of normal-looking viable animals (Donehower et al., 1992). Whole genomic regions of 550 kb in length can be eliminated with a resulting phenotype not more severe than short ears and subtle changes in skeletal structures (Kingsley et al., 1992). Observations of this type can be interpreted in two ways. First, there is likely to be redundancy in various genetic pathways so that if the absence of one gene prevents one pathway from being followed, another series of unrelated genes may provide compensation (sufficient for viability) through the use of an alternative pathway. Second, genes need not be vital to be maintained in the genome. If a gene provides even the slightest selective advantage to an animal, it will be maintained throughout evolution.

Although vital genes will represent only a subset of the total in the genome, it is still of interest to determine the size of this particular subset. In two saturation mutagenesis experiments in regions from different chromosomes, estimates of 5,000-10,000 vital genes were derived (Shedlovsky et al., 1988; Rinchik et al., 1990b). This range of values is likely to represent only 5-10% of the total functional units in the mouse genome. However, it is interesting that the number of vital genes in mice is not very different from the number of vital genes in Drosophila melanogaster, where the genome size is an order of magnitude smaller. This suggests that genes added on to the genome later in evolutionary time are less likely to be vital to the organism and more likely to help the organism in more subtle ways. Overview

From the discussion presented in this section, it seems fair to say, with a high level of confidence, that the actual number of genes in the mammalian genome will be somewhere between 50,000 and 150,000. As of 1993, fewer than 10% of these genes have been characterized at any level from DNA to phenotype, and many fewer still are fully understood in terms of their effect on the organism and their interaction with other genes. Although the efforts to clone and sequence the entire human and mouse genomes will provide an entry point into many more genes, an understanding of the relationship between genotype and phenotype, in nearly every case, will still require much more work with the organism itself. Thus, the need to breed mice is likely to remain strong for many years to come.

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