An obvious place to start our comparison is the total number of genes in each species. Here is a real surprise: the human genome probably contains between 25,000 and 40,000 genes, only about twice the number needed to make a fruitfly³, worm⁴ or plant⁵. We know that there is a higher degree of 'alternative splicing' in humans than in other species. In other words, there are often many more ways in which a gene's protein-coding sections (exons) can be joined together to create a functional messenger RNA molecule, ready to be translated into protein. So more proteins are encoded per gene in humans than in other species.

Even so, we cannot escape the conclusion — drawn previously from comparisons of simpler genomes⁶ — that physical and behavioural differences between species are not related in any simple way to gene number. Many researchers, struck by the fact that there are four times as many genes in some gene families in the human genome compared with fruitflies⁷, extrapolated from these cases and suggested that the human genome might be the product of two doublings of the whole of a simpler genome found in the common ancestor of fruitflies and humans. But, as the analyses of the human genome show^{1, 2}, if such doublings did occur, the evidence for them has since been obscured by massive gene loss and amplification of particular gene families in the human genome.

Individual proteins often feature discrete structural units, called domains, that are conserved in evolution. More than 90% of the domains that can be identified in human proteins are also present in fruitfly and worm proteins, although they have been shuffled to create nearly twice as many different arrangements in humans^{1, 2}. Thus, vertebrate evolution has required the invention of few new domains. Of the human proteins that are predicted to exist, 60% have some sequence similarity to proteins from other species whose genomes have been sequenced. Just over 40% of the predicted human proteins share similarity with fruitfly or worm proteins. And 61% of fruitfly proteins, 43% of worm proteins and 46% of yeast proteins have sequence similarities to predicted human proteins.

But what about the proteins whose sequences show no strong similarity to known proteins from other species? Over a third of the yeast, fruitfly, worm and human proteins fall into this class. These proteins might retain similar functions, even though their sequences have diverged. Or they might have acquired species-specific functions.

Alternatively, we may need to entertain the possibility that the open reading frames that encode these proteins are maintained in a new way, one that is independent of the precise amino-acid sequence and thus is free to evolve rapidly. (An open reading frame is the part of a gene encoding the amino-acid sequence of its protein product.) After all, we know that cells have at least one mechanism, called nonsense-mediated decay of mRNA, for detecting imperfect open reading frames irrespective of the amino-acid sequence that they encode⁸.

It will be interesting to see the extent to which the number of human proteins in this rapidly evolving class decreases as the genomes of other vertebrates, such as mice, are sequenced. This will give us an indication of just how fast these proteins are changing. Indeed, there is already evidence from studies of flies⁹ and worms¹⁰ that these rapidly evolving proteins are less likely to have essential functions, consistent with their being less likely to be conserved during evolution.

Such comparisons of distantly related genomes are fascinating from an evolutionary point of view. But comparison of closely related genomes will be much more important in addressing the key problem now facing genomics — determining the function of individual DNA segments. The concept is simple: segments that have a function are more likely to retain their sequence during evolution than non-functional segments. So DNA segments that are conserved between species are likely to have important functions. The ideal species for comparison are those whose form, physiology and behaviour are as similar as possible, but whose genomes have evolved sufficiently that non-functional sequences have had time to diverge. In practice, there may be no one ideal species, because different genes and regulatory sites evolve at different rates. Nevertheless, this approach has a long history of success, and becomes progressively more efficient as the cost of DNA sequencing declines.

One use of such sequence comparisons is to determine the structure of genes — which parts (the exons) make their way into a functional mRNA molecule and which do not (the introns). The high degree of alternative splicing in vertebrates makes this comparative approach particularly important. Gene-finding computational algorithms cannot easily predict the existence of alternative forms of an mRNA without experimental information, but this information is difficult to come by in the case of rare mRNAs. For example, an exon that is used in only a few cells of the human brain might never be experimentally detected in an mRNA. But that exon's sequence would probably be conserved in the mouse genome.

Comparing the genomes of closely related species can also help in identifying gene-control regions. This approach has been used for over two decades¹¹, and has been validated by showing that the conserved sequences indeed correspond to functional control elements in individual genes¹². But this computational problem is more difficult than identifying exons, and it will be challenging to scale up to a genome-wide level. The proteins that control gene expression by recognizing regulatory regions often detect sequence features that elude the best computer algorithms, and may use information from contacts with other proteins that is difficult to model. Proteins are simply cleverer than computers.

That said, our knowledge of the DNA-binding properties of individual proteins, as well as the structural features of the DNA sites to which they bind, continues to increase. Moreover, we can use experimental evidence; for example, genes that are expressed together might be expected to share control elements. And, as methods for comparing sequences continue to improve, we can expect to learn more about elusive features of the genome, such as genes encoding RNAs that do not encode proteins¹³, start points of DNA replication, and genetic elements that control chromosome structure.