{"id":1772,"date":"2018-09-20T11:06:28","date_gmt":"2018-09-20T02:06:28","guid":{"rendered":"http:\/\/163.180.4.222\/lab\/?p=1772"},"modified":"2023-07-05T15:16:00","modified_gmt":"2023-07-05T06:16:00","slug":"%ea%b2%8c%eb%86%88%ec%a7%80%eb%8f%84-%ec%99%84%ec%84%b1%ec%97%90%eb%8f%84-%ec%9d%b8%ea%b0%84%ec%9c%a0%ec%a0%84%ec%9e%90-90-%eb%b0%a9%ec%b9%98%c2%b7%c2%b7%c2%b7%ec%97%b0%ea%b5%ac-%ed%8e%b8%ec%8b%9d","status":"publish","type":"post","link":"https:\/\/biochemistry.khu.ac.kr\/lab\/?p=1772","title":{"rendered":"\uac8c\ub188\uc9c0\ub3c4 \uc644\uc131\uc5d0\ub3c4 \uc778\uac04\uc720\uc804\uc790 90% \ubc29\uce58\u00b7\u00b7\u00b7”\uc5f0\uad6c ‘\ud3b8\uc2dd’ \ud0d3”"},"content":{"rendered":"

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(\uc6d0\ubb38: \uc5ec\uae30<\/a>\ub97c \ud074\ub9ad\ud558\uc138\uc694~)<\/p>\n

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https:\/\/www.theatlantic.com\/science\/archive\/2018\/09\/the-popularity-contest-of-human-genes\/570586\/<\/p>\n

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The Genes That Never Go Out of Style<\/h5>\n
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Fifteen years after the Human Genome Project, scientists are still mostly studying genes that have already been well studied.<\/h6>\n<\/div>\n

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Back in 2000, a group of mildly inebriated geneticists set up a lighthearted sweepstakes to guess how many genes the human genome would turn out to contain once it was fully sequenced. More than 460 bets were placed, and\u00a0the lowest guess of 25,947<\/a>\u00a0eventually won when the Human Genome Project was completed in 2003. Fifteen years later, the exact number of human genes\u00a0is still being debated<\/a>, with estimates ranging from 19,000 to 22,000. And regardless of the true count, it\u2019s clear that many of these genes are largely unknown.<\/p>\n
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Since 2003, several researchers have noticed that scientists\u00a0tend to study genes<\/a>that are already well studied, and the genes that become popular\u00a0aren\u2019t necessarily the most biologically interesting ones<\/a>. Even among genes, it seems, the rich get richer. This trend hasn\u2019t changed in the past two decades, according to a new study from Thomas Stoeger from Northwestern University.\u00a0Through a massive analysis of existing biomedical data<\/a>, he found that he can predict how intensely a given gene is studied based on a small number of basic biochemical traits. Most of these, he says, reflect how easy a gene was to investigate in the 1980s and 1990s, rather than how important it is.<\/p>\n

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\u201cPeople said that knowing all the genes was going to change everything,\u201d says\u00a0Luis Amaral<\/a>, who led the new study. But the 16 percent of genes that were known in 1991 still accounted for half of all biomedical papers in 2015. By contrast, more recently discovered genes are more poorly known, and a quarter (27 percent) have\u00a0never<\/em>\u00a0been the focus of a scientific paper. Based on current trends, Stoeger estimates that it would take at least five decades before every gene was characterized at the most basic level, let alone fully understood. \u201cThere\u2019s a chance that we are missing out on a lot of interesting biology,\u201d he says.\u201cI find that very depressing,\u201d says\u00a0Jay Shendure<\/a>\u00a0from the University of Washington. \u201cIt is stunning that we sit here 15 years after the Human Genome Project, and still know little to nothing about so many genes. In a world of finite resources, it does not make sense to invest equal effort in every gene. But it\u2019s clear that something is amiss in the status quo of research allocation.\u201d<\/p>\n
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In what Amaral describes as a \u201cheroic effort,\u201d Stoeger spent years collating information from dozens of databases about every known gene. Using machine-learning tools, he then showed that he could accurately predict how many papers have been published about a given gene using just 15 traits.<\/p>\n

Some of these telltale traits\u2014how often the gene is mutated, or the negative consequences of losing it entirely\u2014certainly reflect the gene\u2019s importance and its relevance to human disease. They\u2019re the kind of characteristics scientists\u00a0should<\/em>\u00a0be paying attention to.<\/p>\n

But other traits\u2014how big the gene is, how active it is, how many tissues it is active in, whether it produces proteins that are secreted from cells, whether those proteins are soluble in water, and more\u2014reflect how amenable the genes are to experiments. Highly active genes, for example, are easier to detect using older methods. \u201cThat definitely had a substantial impact on whether you were even able to study a gene in [the 1980s and 1990s],\u201d says\u00a0Sharon Plon<\/a>\u00a0from Baylor College of Medicine. And those historical quirks are better at predicting how the National Institutes of Health currently allocates its money than thousands of other features that more directly reflect what we now know about the role of genes in disease.<\/p>\n

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It\u2019s possible, of course, that scientists have already identified all the really important genes, and are allocating their attention appropriately. There are good reasons, for example, why\u00a0p53 is the most popular human gene<\/a>: It protects our cells from cancer, and is itself mutated in half of all tumors. More broadly, Stoeger found that compared to the least popular genes, the most popular ones are three to five times more likely to have been linked to diseases in large studies, or to wreak havoc when they accrue incapacitating mutations. The problem is that those celebrity genes get over\u00a08000 times<\/em>\u00a0more attention than their neglected counterparts. Scientists do tend to study important genes, Stoeger says, but even then, they do so disproportionately.<\/p>\n<\/section>\n<\/div>\n