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Why AI Isn’t Ready to Tackle Our Convoluted Genomes

Since its molecular structure was deduced in the 1950s, DNA has been hailed by many biologists as the secret of life. They’ve read and studied the information stored in the DNA found in the cells of living organisms, known as their genomes, and claimed that this genetic database must be some kind of blueprint, code script, or computer. But if DNA really does harbor some greater secret about how life works, biologists have yet to find it.

自 20 世纪 50 年代推导出 DNA 的分子结构以来，许多生物学家一直将其誉为生命的奥秘。他们阅读并研究了储存在生物体细胞内（即基因组）的 DNA 信息，并声称这种遗传数据库必然是某种蓝图、代码脚本或计算机。然而，如果 DNA 真的隐藏着关于生命运作的某种更深层的秘密，生物学家至今尚未发现。

In fact, the human genome is less a script than a puzzle that gets harder the closer they look. Knowing the entire sequence—the order of all 3 billion or so of our DNA’s chemical building blocks, nearly fully deduced by the international Human Genome Project between 1990 and 2003—hasn’t helped much. That investigation showed that barely 2 percent of the human genome consists of actual genes, the information-coding sequences of DNA.

事实上，人类基因组与其说是一个脚本，不如说是一个越深入研究就越复杂的谜题。了解整个序列——即我们 DNA 中约 30 亿个化学构件的排列顺序，这在 1990 年至 2003 年间由国际人类基因组计划几乎完全推导出来——并没有提供太大的帮助。那项调查显示，人类基因组中只有不到 2% 是真正的基因，即 DNA 中编码信息的序列。

It’s now clear that understanding the human genome is no longer a matter of figuring out what each gene does. The deeper and much harder question is how those genes are used, or regulated, a question that seems to involve some and perhaps much of the rest of the genome. By switching suites of genes on and off, the many different cell types in our bodies can all be created from the same material. Cells also regulate their genes from moment to moment in response to a constant inflow of signals from their neighbors and surroundings.

现在很清楚，理解人类基因组不再仅仅是弄清楚每个基因的功能。更深层且更困难的问题是这些基因是如何被使用或调控的，这个问题似乎涉及基因组其余部分的一部分，甚至大部分。通过开启或关闭不同的基因组合，我们体内许多不同的细胞类型都可以由相同的材料生成。细胞还会根据来自邻居和周围环境的持续信号输入，时刻调节其基因。

But the processes that govern gene regulation are proving so complex that some biologists wonder whether a full understanding of it—of how the genome really works—will ever be within the grasp of our puny minds.

然而，控制基因调控的过程被证明极其复杂，以至于一些生物学家怀疑，我们渺小的大脑是否真的能够完全理解它，即理解基因组是如何真正运作的。

Some are counting on outsourcing the analysis to artificial intelligence. Genomic “foundation models” such as Evo 2, Genos, and Google DeepMind’s AlphaGenome are trained on vast quantities of genomic data, which biologists use to make predictions about how differences in DNA sequence affect biological processes and ultimately the traits (including disease risk) of a whole organism. These algorithms don’t worry about the complicated regulatory stuff going on. All of that is supposedly subsumed by the algorithm’s “training,” through which it deduces correlations from cases we already know about.

有些人寄希望于将分析外包给人工智能。诸如 Evo 2、Genos 和 Google DeepMind 的 AlphaGenome 等基因组“基础模型”通过海量基因组数据进行训练，生物学家利用这些模型来预测 DNA 序列的差异如何影响生物过程，并最终影响整个生物体的性状（包括疾病风险）。这些算法并不关心正在发生的复杂调控机制。所有这些都被认为包含在算法的“训练”中，通过这种训练，算法从我们已知的案例中推导出相关性。

This approach is likely to be useful, but for those who crave real understanding of how the genome, and ultimately life itself, works, a computational black box will never suffice. And perhaps more to the point, the genome might not submit to the kind of straightforward input-output approach that such AI models ultimately assume.

这种方法可能会有用，但对于那些渴望真正理解基因组乃至生命本身如何运作的人来说，计算黑箱永远是不够的。更重要的是，基因组可能并不遵循这类人工智能模型所预设的那种简单的输入-输出逻辑。

That’s because the genome is no blueprint or algorithm. It’s something else.

这是因为基因组既不是蓝图也不是算法。它是别的东西。

Given that it’s the product of around 4 billion years of evolution, perhaps it’s not surprising that our genome is complicated. The surprise has been what those complications are. “Our genome is not what we might make it if we sat down at the drawing board,” said the biologist Karen Adelman, who studies gene regulation at Harvard Medical School.

考虑到它是约 40 亿年进化的产物，我们的基因组如此复杂或许并不令人惊讶。令人惊讶的是这些复杂性究竟是什么。哈佛医学院研究基因调控的生物学家凯伦·阿德尔曼（Karen Adelman）说：“如果我们坐在绘图板前设计，我们的基因组绝不会是现在这个样子。”

The traditional view posits that a small proportion of our DNA holds the code for making the protein molecules that orchestrate our cells’ chemistry. Each instruction for a protein is held in a corresponding gene—we have around 20,000 of these—and gene sequences can range in length from a couple of dozen to almost 3 million DNA “letters” (representing molecules called nucleotides).

传统观点认为，我们 DNA 中只有一小部分包含制造蛋白质分子的代码，这些蛋白质分子负责协调我们细胞的化学反应。每个蛋白质的指令都包含在相应的基因中——我们大约有 2 万个这样的基因——基因序列的长度从几十个到近 300 万个 DNA“字母”（代表称为核苷酸的分子）不等。

Making a protein from its gene is a two-stage affair. First the DNA is read, letter by letter, by an enzyme called a polymerase, which creates a copy of that code in a related molecule called messenger RNA (mRNA). This is called transcription. The mRNA is then read by a piece of molecular machinery called the ribosome, which constructs the protein—a process called translation. The proteins made by the ribosome then go off to do their jobs in making and sustaining the organism.

从基因制造蛋白质是一个两阶段的过程。首先，一种称为聚合酶的酶逐个字母地读取 DNA，并在一种称为信使 RNA (mRNA) 的相关分子中创建该代码的副本。这被称为转录。然后，mRNA 被一种称为核糖体的分子机器读取，该机器构建蛋白质——这个过程称为翻译。由核糖体制造的蛋白质随后去执行它们在构建和维持生物体方面的任务。

This picture is still more or less correct. But it turns out that “the genes are probably not the most interesting part of the genome,” Adelman said.

这幅图景大体上仍然是正确的。但阿德尔曼说，事实证明，“基因可能并不是基因组中最有趣的部分。”

What matters more is how our genes, many of which we share with simpler organisms, are regulated—turned on and off. Which proteins a cell needs changes over time and according to cell type: muscle, brain, skin, and so on. How the genes that encode those proteins are regulated depends on some of the genome that doesn’t code for proteins.

更重要的是我们的基因（其中许多与更简单的生物体共有）是如何被调控——即开启和关闭的。细胞所需的蛋白质会随着时间和细胞类型（肌肉、大脑、皮肤等）的不同而变化。编码这些蛋白质的基因如何被调控，取决于基因组中不编码蛋白质的部分。

Biologists have known about gene regulation, and the involvement of “noncoding” DNA, since the 1960s. But for many years, most of what they understood about this came from studies of simple organisms like bacteria, where the principles are generally straightforward. It has gradually become clear, though, that in complex eukaryotic organisms like us, gene regulation is far more complicated, involving overlapping systems of oversight and control, each with its own intricacies.

自 20 世纪 60 年代以来，生物学家就已经了解基因调控以及“非编码”DNA 的参与。但多年来，他们对此的大部分理解来自于对细菌等简单生物的研究，在这些生物中，其原理通常很简单。然而，人们逐渐认识到，在我们这样复杂的真核生物中，基因调控要复杂得多，涉及重叠的监督和控制系统，每一个都有其自身的复杂性。

Transcription gets started by proteins called transcription factors, which are like the operations managers of gene regulation. These proteins stick to sections of DNA (typically close to the target gene) and recruit the polymerase enzyme to make an mRNA copy. In bacteria, transcription factors are rather like keys that fit the locks of unique binding sites on DNA. But that’s not how they work in complex organisms. In us, the logic of transcription factors is more difficult to parse.

转录由称为转录因子的蛋白质启动，它们就像基因调控的运营经理。这些蛋白质附着在 DNA 片段上（通常靠近目标基因），并招募聚合酶来制作 mRNA 副本。在细菌中，转录因子就像钥匙，可以插入 DNA 上独特结合位点的锁中。但在复杂生物体中，它们的工作方式并非如此。在我们体内，转录因子的逻辑更难解析。

For one thing, our transcription factors don’t show strong preferences for particular DNA binding sites. What’s more, they tend to work in pairs or groups. And a given transcription factor might have different effects in different contexts, such as activating gene transcription in one cell type in one cell type but suppressing it in another, depending on which other transcription factors are around.

首先，我们的转录因子对特定的 DNA 结合位点没有表现出强烈的偏好。此外，它们倾向于成对或成组工作。而且，特定的转录因子在不同的环境下可能会产生不同的影响，例如在一种细胞类型中激活基因转录，而在另一种细胞类型中抑制它，这取决于周围还有哪些其他转录因子。

In bacteria, regulation tends to have an “OR” logic, Adelman said, whereby a particular signal turns a gene on or off: It’s either this or that. But in the human genome the logic is more lik

阿德尔曼说，在细菌中，调控往往具有“或”逻辑，即特定的信号开启或关闭一个基因：要么是这个，要么是那个。但在人类基因组中，逻辑更像……