（好奇的音乐） (inquisitive music)
-[画外音]几十年来我们所学到的 - [Voiceover] What we've been taught for decades
关于正常组织的是31亿个碱基对 about normal tissues is that the 3.1 billion base pairs
细胞之间在遗传上是相同的。 are genetically identical between cells.
这根本是错误的。 And that's fundamentally wrong.
现在我们知道的是，每个单元格都是唯一的。 What we now know is that every cell is unique.
即使正常细胞分裂， Even when a normal cell divides,
它在每个单元划分中引入大约一个或多个错误。 it introduces about one or more errors per cell division.
所以现在的挑战变成了 So the challenge now becomes,
我们如何研究单个细胞之间的差异， how do we study the differences between individual cells,
在看RNA，DNA或表观基因组？ looking at RNA, or DNA or epigenomes?
那对生物学有何影响？ And what are the implications of that for biology?
（动感音乐） (dynamic music)
（欢快的音乐） (upbeat music)
-那是最大的惊喜之一 - So what was one of the biggest surprises
您开始进行单细胞测序时得到了什么？ you got when you started doing single cell sequencing?
-因此，最大的惊喜之一是， - So, one of the big surprises was,
当我们开始对副本编号配置文件进行排序时 as we started to sequence copy number profiles
在单细胞中，从肿瘤中，我们发现 in single cells, from tumors, we found that
有几个主要人口 there are a few major populations
共享相似的副本编号配置文件。 that share similar copy number profiles.
并利用系统发育推断， And using phylogenetic inference,
我们推断了一个标点基因组进化的模型。 we inferred a model of punctuated genome evolution.
在这些短暂的点滴声中， In these short punctuated bursts,
您获得了许多突变。 you acquired many many mutations.
然后爆发后，基因组 And then after that burst, the genome
长期稳定。 was stable for a long period of time.
然后在这种情况下，还有另一个标点爆裂 And then in this case, there's another punctuated burst
在其中您获得许多许多突变。 in which you acquire many many mutations.
再说一次，基因组是稳定的 And then, again, the genome is stable
在肿瘤的整个生命周期中 for most of the lifetime of the tumor.
-因此，单细胞测序不仅具有 - So, single cell sequencing has not only
帮助我们确定了 helped us identify the time at which
这些细胞吸收了这些突变。 these cells take up these take up the mutations,
而且还有哪些细胞具有突变。 But also which cells have the mutations.
-是的，所以我们可以利用这种肿瘤内异质性 - Right, so we can use this intratumor heterogeneity
在肿瘤内作为永久记录，这样我们就可以 within the tumor as a permanent record, so that we can
重建突变的顺序和时间顺序， reconstruct the order and the chronology of the mutations,
或副本号更改（随时间推移而发生）。 or copy number changes, that happened over time.
所以我们现在要在这里加入Marco So we're gonna join Marco now, here,
谁是实验室的研究生 who is a graduate student in the lab
他将向我们展示如何做 and he's going to show us how to do
通过移液器进行显微操作 micromanipulation by mouth pipetting to
分离单个细胞进行测序分析。 isolate single cells for sequencing analysis.
因此，首先，马可（Marco）将拿起其中一个玻璃移液管。 So first, Marco's going to take one of the glass pipettes.
他要放一个塑料管 He is going to place a plastic tubing
会连接到他的嘴，这样他 that will connect to his mouth so that he
可能会有一些输入和输出压力。 can have some input and output pressure.
然后他要拿玻璃毛细管去 And then he's going to take the glass capillary tube and go
到显微镜载玻片上的细胞溶液， to the solution of cells that's on a microscope slide,
然后他将找到一个牢房并保存在那里。 and he's going to find a single cell and hold it there.
通过毛细作用，该细胞 And by capillary action, that cell
会被吸进管子。 will get sucked into the tube.
之后，他将玻璃管转移到 After that, he'll transfer the glass tube over to a
96孔板，他将吹入以允许液体 96 well plate and he'll blow in to allow the liquid
出来并进入裂解缓冲液 to come out and go into a lysis buffer
用于随后的扩增反应。 for the subsequent amplification reactions.
所以第二步将把那个细胞 So step two will be taking that cell
然后进入整个基因组或 and going into a whole genome or
整个转录组的扩增反应 a whole transcriptome amplification reactions
这样就可以得到很多DNA和RNA so that you can get lots of DNA and RNA
然后我们用来制作测序库。 that we then use to make sequencing libraries.
然后，我们将这些库条形码化， We then barcode those libraries,
我们将它们拉在一起，我们做 we pull them together and the we do
下一代测序反应可获取数据。 the next generation sequencing reaction to get data.
这就是我们得到的数据 So this is the data that we get back
从典型的测序运行中 from a typical sequencing run and
我们将获取所有这些数据，并将其与 we'll take all of this data, we'll align it to
人类基因组，这样我们将 the human genome so that way we'll
确切知道这些序列在哪里 know exactly where these sequences
来自基因组。 are coming from in the genome.
然后我们经历了一系列 And then we go through a series of
处理步骤和过滤步骤 processing steps and filtering steps
消除可能存在的所有技术错误 to remove all the technical errors that might have
在单个细胞扩增期间发生。 occurred during the amplification of that single cell.
-现在问题变成了 - So the question now becomes,
您如何理解呢？ how do you make sense out of that?
-所以我们要把我们的单间 - So we're gonna take our single cell
大规模数据集，我们将要 large scale data sets and we're going to
将它们上传到MD Anderson的集群中。 upload them to the cluster here at MD Anderson.
（古典音乐） (classical music)
所以现在我们要离开 So now we're leaving
基础科学研究大楼， the basic science research building,
我们将进行一些公路旅行 and we're going to take a little road trip down
高性能计算集群。 to the high performance computing cluster.
-那么您要花多长时间， - So how long does it take for you to,
假设是从一个单元获取数据？ let's say, get data from one cell?
-在群集上，仅需20到30分钟。 - On the cluster, it'll only take about 20 to 30 minutes.
- 哇。 - Wow.
-因为您不能等很长时间才能获得 - Because you can't wait a very long time to get
患者诊断测试或预后的结果。 results from patient diagnostic tests or prognostics.
因此，一旦我们取回所有测序数据， So as soon as we get all of the sequencing data back,
在测序仪上，我们要做的第一件事是， from the sequencing machines, the first thing we do is,
我们接受了数以百万计的读取， we take those millions and millions of reads,
然后将它们上传到集群中 and we upload them to the cluster, where we're going to
做我们的初始数据处理和分析。 do our initial data processing and analysis.
-通常情况下，有多少个细胞 - So typically, how many cells
您会一次分析吗？ would you analyze at one time?
-所以这取决于我们是否在做基因组 - So it depends on whether we're doing genomes
或外显子组，或者我们只是在看 or exomes, or we're just looking at
单细胞中的靶向基因板。 targeted gene panels in single cells.
对于基因组，通常只是 For genomes, it would usually just
最多几个，甚至几个。 be a few, maybe a dozen at most.
外显子要几十个，然后当我们做面板时， Exomes would be a few dozen, and then when we do panels,
我们正在做数百个单细胞。 we're doing hundreds and hundreds of single cells.
所以这是一个系统发育树 So this is a phylogenetic tree that was created
从单个单元格副本编号配置文件 from single cell copy number profiles
在三阴性乳腺癌中 in a triple negative breast cancer.
树的一个分支，您可以看到所有正常单元格 And one branch of the tree, you can see all the normal cells
他们有二倍体拷贝数谱 they have diploid copy number profiles
每个染色体两份。 and two copies of each chromosome.
在这里，您可以看到三种不同的肿瘤种群 Over here, you can see three different tumor populations
以蓝色，黄色和红色表示。 indicated in blue, in yellow and in red.
您会看到有一个很大的 What you can see is that there's a very large
这些亚群之间的遗传距离。 genetic distance between these subpopulations.
它支持副本数演变的标点模型。 Which supports a punctuated model of copy number evolution.
在这些突变中， In which you have these bursts of mutations,
并且您获得了大量的副本编号更改。 and you acquire lots of copy number changes.
随后随着时间的推移人口稳定增长。 Followed by a stable expansion of the population over time.
-我可以想象在那里 - I can just imagine that there
必须有很多其他应用程序 must be lots of other applications,
您可以在哪里实际应用这项技术。 where you can actually apply this technology.
-在过去五年中，我们已经看到了很多 - Over the last five years, we've seen a lot
单细胞测序的广泛应用 of broad applications of single cell sequencing,
在生物学的许多不同领域。 in many diverse fields of biology.
包括微生物学和免疫学， Including things like microbiology and immunology,
神经生物学，组织镶嵌术，产前遗传学诊断， neurobiology, tissue mosaicism, prenatal genetic diagnosis,
具有很好的临床应用。 which has great clinical applications.
胚胎学研究早期发展， Embryology to study early development,
诸如器官发生，器官发育之类的东西。 and things like organogenesis, the development of organs.
还有癌症，那是非常大的 And cancer, which is a really big one,
有很多应用的地方 where there are many applications,
在癌症研究方面， both in the cancer research side,
而且还有潜在的翻译应用。 but also potential translational applications.
-这真是很棒的一天，不是吗？ - This was an amazing day, wasn't it?
-很棒的设施。 - Amazing facility.
-单细胞测序实际上会产生影响 - A single cell sequencing actually impacts
您能想到的每个应用程序。 every application you can think of.
-是的，绝对可以，我们终于有办法 - Yeah, absolutely, and we finally have a way to
测量生活的最基本单位。 measure the very basic unit of life.
（古典音乐） (classical music)