鈥淥NE giant leap for humility鈥�. 鈥淲e鈥檙e nothing special鈥�. 鈥溈烀ǘ淌悠祍 find only
half as many genes as expected鈥�. These are some of the headlines that appeared
after papers on the draft genome were published in February. Both the public and
private projects estimated we had just 30,000 to 40,000 genes, far fewer than
most previous figures suggested鈥攁nd barely more than worms.
But the low estimates have ignited a firestorm of controversy. William
Haseltine, head of biotech company Human Genome Sciences (HGS) in Rockville,
Maryland, has been the most outspoken critic, attacking both the quality of the
draft sequences and the gene-finding efforts of those who compiled them.
鈥淭hey鈥檙e reading smudged text through foggy glasses,鈥� he recently snarled.
Haseltine claims to have found more than 90,000 genes, while companies such as
Affymetrix sell gene chips based on more than 60,000 genes and DoubleTwist puts
the number above 65,000.
But Craig Venter, head of Celera Genomics, the private rival to the public
genome consortium, is standing by the lower estimate. He calls it a 鈥渢ruth
serum鈥� for his competitors. So are these companies wasting hundreds of millions
of dollars on a wild goose chase? Or could the public consortium and Celera end
up delaying the development of medical tests and treatments by denying the
existence of large numbers of genes?
Advertisement
The accuracy of the draft genome is not the issue. The controversy is about
how you find the fragmented parts of the genome that actually code for proteins.
There are 26,000 genes that researchers more or less agree on. In the papers in
Nature and Science
(快猫短视频, 17 February, p 4),
the public consortium and Celera estimated that there are about another 10,000,
based on computer programs that search raw sequences for stretches that resemble
known genes.
But the programs tend to throw up lots of genes that don鈥檛 really exist. To
avoid counting these, Celera and the consortium demanded evidence that gene
candidates really are transcribed to make the messenger RNAs that cells use to
make proteins. 鈥淏ut we only have transcription evidence for half the genes in
the body,鈥� admits geneticist Michael Zhang at Cold Spring Harbor Laboratory in
New York.
That鈥檚 where HGS and similar genome companies come in. Instead of looking at
the raw sequence, they find genes by combing thousands of different cells for
bits of mRNA. These are then turned into bits of DNA called expressed sequence
tags, or ESTs. Haseltine claims his ESTs provide evidence for more than 10,000
genes that aren鈥檛 in the consortium鈥檚 database. 鈥淲e have made functional
proteins, some of which we are developing as drugs, that are not annotated as
even existing in that text,鈥� he says. But Celera and the consortium claim their
estimates include these proteins.
Another problem with gene-finding programs is that they can only look for
code that resembles known genes. So they not only turn up candidate genes that
don鈥檛 really exist, they also miss lots of real genes. 鈥淗istorically,
gene-prediction programs have tended to miss over 50 per cent of genes,鈥� says
geneticist Michael Snyder of Yale University. A group at Ohio State University
in Columbus has analysed the same data that the consortium looked at and
estimates there are actually about 80,000 genes. In an as yet unpublished paper,
it claims that the consortium鈥檚 software has missed nearly 850,000 gene segments
for which there is protein or RNA evidence.
While the debate should be settled eventually, the uncertainty could have
far-ranging implications. Some fear that undiscovered genes鈥攁nd thus
potential drug targets鈥攃ould fall through the cracks. While many labs
continue to mine the genome for new genes, some are finding it difficult to get
funding. The head of one biomedical research lab, who preferred not to be named,
says his funders recently asked him why he was continuing to look for genes when
the 鈥済enome was finished鈥�. 鈥淧eople should not give up the gene count,鈥� warns
Haseltine.
Meanwhile, the rival parties are heading for a showdown. 鈥淭here鈥檚 a simple
way to settle the question,鈥� says Eric Lander of the Whitehead Institute, one of
the leaders of the consortium. 鈥淟et鈥檚 randomly select 3 per cent of the genome,
have everyone declare the genes that they believe to be in that region, and test
the proposed genes.鈥� Let the games begin.