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| title: "如何获取基因的转录起始/终止位点(TSS/TES)?" | ||
| date: 2023-10-22T09:19:01Z | ||
| draft: ["false"] | ||
| tags: [ | ||
| "fetched", | ||
| "老俊俊的生信笔记" | ||
| ] | ||
| categories: ["Acdemic"] | ||
| --- | ||
| 如何获取基因的转录起始/终止位点(TSS/TES)? by 老俊俊的生信笔记 | ||
| ------ | ||
| <div><section data-tool="mdnice编辑器" data-website="https://www.mdnice.com" data-mpa-powered-by="yiban.io"><h4 data-tool="mdnice编辑器"><span></span></h4><section><mp-common-profile data-pluginname="mpprofile" data-id="MzkyMTI1MTYxNA==" data-headimg="http://mmbiz.qpic.cn/mmbiz_png/G5jjcE4usey42oX5qyLTVibLRO9dz8ic5G4TpEHQc9rICYlpS4MHg6Et8cgXrQDqibvibXombicTro8t9cekJRlDBcw/0?wx_fmt=png" data-nickname="老俊俊的生信笔记" data-alias="JunJunLab" data-signature="老俊俊的生信技能和知识分享,我不是巨人,但你可以站在我的肩膀上更进一步!" data-from="0" data-is_biz_ban="0"></mp-common-profile></section><h4 data-tool="mdnice编辑器"><span></span></h4><h2 data-tool="mdnice编辑器"><span><span>1</span></span><span>引言</span><span></span></h2><blockquote data-tool="mdnice编辑器"><p>群里看到有粉丝卡在了怎么获取基因的转录起始位点 <strong>TSS</strong>数据上,导致后续画图发生错误。下面介绍一下如何获取基因的转录起始位点 <strong>TSS</strong>数据 以及转录终止位点 <strong>TES</strong> 数据。</p></blockquote><h2 data-tool="mdnice编辑器"><span><span>2</span></span><span>示例</span><span></span></h2><h3 data-tool="mdnice编辑器"><span></span><span>从 <strong>TXDB</strong> 注释文件获取</span><span></span></h3><p data-tool="mdnice编辑器"><strong>Bioconductor</strong> 上面有很多模式物种的注释包,你可以下载直接使用:</p><blockquote data-tool="mdnice编辑器"><p><strong>https://www.bioconductor.org/packages/release/BiocViews.html#___TxDb</strong></p></blockquote><figure data-tool="mdnice编辑器"><img data-ratio="0.5722108145106092" data-src="https://mmbiz.qpic.cn/sz_mmbiz_png/G5jjcE4usexmLWZ8rn8G1x7mp8MMyTIAId0zbRmicyZuicnJJ6z9AibUMg0Gqx1CQ9nAY3uVFpibfZ9FicbZic4dFalw/640?wx_fmt=png" data-type="png" data-w="1461" src="https://mmbiz.qpic.cn/sz_mmbiz_png/G5jjcE4usexmLWZ8rn8G1x7mp8MMyTIAId0zbRmicyZuicnJJ6z9AibUMg0Gqx1CQ9nAY3uVFpibfZ9FicbZic4dFalw/640?wx_fmt=png"></figure><p data-tool="mdnice编辑器">我们用小鼠的测试,首先获取基因位置信息:</p><blockquote data-tool="mdnice编辑器"><p>如果你要画整个基因上信号富集的信号的话,下面这个就可以直接给 <strong>normalizedMatrix/getTagMatrix</strong> 作为输入了。<strong>此外要注意的是你的 bigwig 文件的染色体前缀 chr 和你的 TSS 文件的 chr 保持一致,要么都有,要么都没有。不然后面做的也还是错的,一定要仔细!</strong></p></blockquote><pre data-tool="mdnice编辑器"><span></span><code><span>library</span>(tidyverse)<br><span>library</span>(rtracklayer)<br><span>library</span>(IRanges)<br><span>library</span>(TxDb.Mmusculus.UCSC.mm10.knownGene)<br><br>gene <- genes(TxDb.Mmusculus.UCSC.mm10.knownGene)<br>gene<br><span># GRanges object with 24528 ranges and 1 metadata column:</span><br><span># seqnames ranges strand | gene_id</span><br><span># <Rle> <IRanges> <Rle> | <character></span><br><span># 100009600 chr9 21062393-21073096 - | 100009600</span><br><span># 100009609 chr7 84935565-84964115 - | 100009609</span><br><span># 100009614 chr10 77711457-77712009 + | 100009614</span><br><span># ...</span><br><span># -------</span><br><span># seqinfo: 66 sequences (1 circular) from mm10 genome</span><br></code></pre><blockquote data-tool="mdnice编辑器"><p>基因相对于双链 DNA 是区分正负链的,所以 <strong>TSS/TES</strong> 位点就是基因位置的两边位置,只不过正负链基因相反而已。举个例子: 上面 <strong>100009600</strong> 这个基因在负链上,所以 <strong>TSS/TES</strong> 分别是 <strong>21073096/21062393</strong>。而 <strong>100009614</strong> 基因在正链上, 所以 <strong>TSS/TES</strong> 分别是 <strong>77711457/77712009</strong>。</p></blockquote><p data-tool="mdnice编辑器">我们使用 <strong>promoters</strong> 函数可以获取 TSS:</p><pre data-tool="mdnice编辑器"><span></span><code>tss <- promoters(gene,upstream = <span>0</span>,downstream = <span>1</span>)<br>tss<br><span># GRanges object with 24528 ranges and 1 metadata column:</span><br><span># seqnames ranges strand | gene_id</span><br><span># <Rle> <IRanges> <Rle> | <character></span><br><span># 100009600 chr9 21073096 - | 100009600</span><br><span># 100009609 chr7 84964115 - | 100009609</span><br><span># 100009614 chr10 77711457 + | 100009614</span><br><span># ...</span><br></code></pre><p data-tool="mdnice编辑器">我们也可以手动来算一下,很简单,思路就是正链取 <strong>start</strong>,负链取 <strong>end</strong> 即可, 可以看到结果和上面一致:</p><pre data-tool="mdnice编辑器"><span></span><code>gene_df <- data.frame(gene)<br><br><span># check</span><br>head(gene_df,<span>3</span>)<br><span># seqnames start end width strand gene_id</span><br><span># 1 chr9 21062393 21073096 10704 - 100009600</span><br><span># 2 chr7 84935565 84964115 28551 - 100009609</span><br><span># 3 chr10 77711457 77712009 553 + 100009614</span><br><br>tss2 <- gene_df |><br> mutate(start = ifelse(strand == <span>"+"</span>,start,end),<br> end = start) |><br> GRanges()<br>tss2<br><span># GRanges object with 24528 ranges and 1 metadata column:</span><br><span># seqnames ranges strand | gene_id</span><br><span># <Rle> <IRanges> <Rle> | <character></span><br><span># 100009600 chr9 21073096 - | 100009600</span><br><span># 100009609 chr7 84964115 - | 100009609</span><br><span># 100009614 chr10 77711457 + | 100009614</span><br><span># ...</span><br></code></pre><hr data-tool="mdnice编辑器"><p data-tool="mdnice编辑器">思路反过来,我们就可以获取 <strong>TES</strong> 的信息了:</p><pre data-tool="mdnice编辑器"><span></span><code>tes <- gene_df |><br> mutate(start = ifelse(strand == <span>"+"</span>,end,start),<br> end = start) |><br> GRanges()<br>tes<br><span># GRanges object with 24528 ranges and 1 metadata column:</span><br><span># seqnames ranges strand | gene_id</span><br><span># <Rle> <IRanges> <Rle> | <character></span><br><span># [1] chr9 21062393 - | 100009600</span><br><span># [2] chr7 84935565 - | 100009609</span><br><span># [3] chr10 77712009 + | 100009614</span><br><span># ...</span><br></code></pre><h3 data-tool="mdnice编辑器"><span></span><span>从 GTF 文件获取</span><span></span></h3><p data-tool="mdnice编辑器">有时候可能没有你的物种注释好的包,你可能只有注释 <strong>GTF</strong> 注释文件,根据上面的思路,我们也可以从 <strong>GTF</strong> 文件来准备。</p><pre data-tool="mdnice编辑器"><span></span><code>gtf <- import.gff(<span>"../Mus_musculus.GRCm38.102.gtf.gz"</span>,format = <span>"gtf"</span>) |><br> data.frame()<br></code></pre><figure data-tool="mdnice编辑器"><img data-ratio="0.2681734880879658" data-src="https://mmbiz.qpic.cn/sz_mmbiz_png/G5jjcE4usexmLWZ8rn8G1x7mp8MMyTIABFheibibuUUy8H7ibNc1vPNaB50clTdk8Riasbd0oichhEnNczaibIqVficog/640?wx_fmt=png" data-type="png" data-w="1637" src="https://mmbiz.qpic.cn/sz_mmbiz_png/G5jjcE4usexmLWZ8rn8G1x7mp8MMyTIABFheibibuUUy8H7ibNc1vPNaB50clTdk8Riasbd0oichhEnNczaibIqVficog/640?wx_fmt=png"></figure><p data-tool="mdnice编辑器">信息很多,提取我们需要的即可:</p><pre data-tool="mdnice编辑器"><span></span><code>df_gene <- gtf |><br> dplyr::filter(type == <span>"gene"</span>) |><br> dplyr::select(seqnames,start,end,gene_id,gene_name,strand)<br><br><span># check</span><br>head(df_gene,<span>3</span>)<br><span># seqnames start end gene_id gene_name strand</span><br><span># 1 1 3073253 3074322 ENSMUSG00000102693 4933401J01Rik +</span><br><span># 2 1 3102016 3102125 ENSMUSG00000064842 Gm26206 +</span><br><span># 3 1 3205901 3671498 ENSMUSG00000051951 Xkr4 -</span><br></code></pre><p data-tool="mdnice编辑器">到这里了方法就和上面提取的一样了,这里就不再写了。这里你可以看到染色体名称是没有 <strong>chr</strong> 前缀的,你需要检查和你的 <strong>bigwig</strong> 文件是否保持一致,才好做后面的分析!</p><h2 data-tool="mdnice编辑器"><span><span>3</span></span><span>嫌麻烦? 打包成函数</span><span></span></h2><blockquote data-tool="mdnice编辑器"><p>如果你还嫌麻烦,那就把上面代码打包成一个小函数,这样方便快捷。</p></blockquote><p data-tool="mdnice编辑器">示例:</p><pre data-tool="mdnice编辑器"><span></span><code>getSite(object = TxDb.Mmusculus.UCSC.mm10.knownGene,type = <span>"tss"</span>)<br><br>getSite(object = TxDb.Mmusculus.UCSC.mm10.knownGene,type = <span>"tss"</span>,<br> upstream = <span>10</span>,downstream = <span>5</span>)<br> <br>getSite(object = TxDb.Mmusculus.UCSC.mm10.knownGene,type = <span>"tes"</span>)<br><br>getSite(object = TxDb.Mmusculus.UCSC.mm10.knownGene,type = <span>"body"</span>)<br><br>getSite(object = <span>"../Mus_musculus.GRCm38.102.gtf.gz"</span>,type = <span>"tss"</span>)<br></code></pre><p data-tool="mdnice编辑器">函数代码:</p><pre data-tool="mdnice编辑器"><span></span><code>getSite <- <span>function</span>(object = <span>NULL</span>,<br> upstream = <span>0</span>,<br> downstream = <span>0</span>,<br> type = c(<span>"tss"</span>,<span>"tes"</span>,<span>"body"</span>)){<br> type <- match.arg(type,c(<span>"tss"</span>,<span>"tes"</span>,<span>"body"</span>))<br><br> <span># ============================================================================</span><br> <span># define func</span><br> <span># ============================================================================</span><br> getfun <- <span>function</span>(data = <span>NULL</span>,type = <span>NULL</span>,upstream = <span>0</span>,downstream = <span>0</span>){<br> <span># check type to extract</span><br> <span>if</span>(type == <span>"tss"</span>){<br> ts <- data |><br> dplyr::mutate(start = ifelse(strand == <span>"+"</span>,start,end),end = start)<br><br> }<span>else</span> <span>if</span>(type == <span>"tes"</span>){<br> ts <- data |><br> dplyr::mutate(start = ifelse(strand == <span>"+"</span>,end,start),end = start)<br> }<span>else</span>{<br> ts <- data<br> }<br><br> <span># extend</span><br> ts_ed <- ts |><br> dplyr::mutate(start1 = ifelse(strand == <span>"+"</span>,start - upstream,start - downstream),<br> end1 = ifelse(strand == <span>"+"</span>,end + downstream,end + upstream)) |><br> dplyr::select(-start,-end) |><br> dplyr::rename(start = start1,end = end1) |><br> GRanges()<br><br> <span>return</span>(ts_ed)<br> }<br><br> <span># ============================================================================</span><br> <span># extract from file</span><br> <span># ============================================================================</span><br> <span>if</span>(<span>"TxDb"</span> %<span>in</span>% class(object)){<br> gene <- GenomicFeatures::genes(object)<br> gene_df <- data.frame(gene)<br><br> res <- getfun(data = gene_df,type = type,<br> upstream = upstream,downstream = downstream)<br><br> }<span>else</span> <span>if</span>(is.character(object)){<br> gtf <-rtracklayer::import.gff(object,format = <span>"gtf"</span>) |><br> data.frame()<br><br> ctype <- ifelse(<span>"gene"</span> %<span>in</span>% unique(gtf$type),<span>"gene"</span>,<span>"transcript"</span>)<br><br> gene_df <- gtf |><br> dplyr::filter(type == ctype) |><br> dplyr::select(seqnames,start,end,gene_id,gene_name,strand)<br><br> res <- getfun(data = gene_df,type = type,<br> upstream = upstream,downstream = downstream)<br> }<br><br> <span>return</span>(res)<br>}<br></code></pre><h2 data-tool="mdnice编辑器"><span><span>4</span></span><span>结尾</span><span></span></h2><blockquote data-tool="mdnice编辑器"><p><strong>路漫漫其修远兮,吾将上下而求索。</strong></p></blockquote><hr data-tool="mdnice编辑器"><p data-tool="mdnice编辑器">欢迎加入生信交流群。加我微信我也拉你进 <strong>微信群聊</strong> <strong>老俊俊生信交流群</strong> <strong>(微信交流群需收取 20 元入群费用,一旦交费,拒不退还!(防止骗子和便于管理))</strong> 。QQ 群可免费加入, 记得进群按格式修改备注哦。</p><section data-tool="mdnice编辑器"><section><p><strong>老俊俊微信：</strong></p><figure><img data-ratio="1" data-src="https://mmbiz.qpic.cn/sz_mmbiz_png/G5jjcE4usexmLWZ8rn8G1x7mp8MMyTIAMAjv4WFN2yRnVzHa5Aq4xl3bRce9aXyvsC3giaL6iaHg5eI18gJsjSWg/640?wx_fmt=png" data-type="png" data-w="430" src="https://mmbiz.qpic.cn/sz_mmbiz_png/G5jjcE4usexmLWZ8rn8G1x7mp8MMyTIAMAjv4WFN2yRnVzHa5Aq4xl3bRce9aXyvsC3giaL6iaHg5eI18gJsjSWg/640?wx_fmt=png"></figure><figure><img data-ratio="1.3668430335097002" data-src="https://mmbiz.qpic.cn/sz_mmbiz_png/G5jjcE4usexmLWZ8rn8G1x7mp8MMyTIAbM7l2cmGQkXgMtBLLU5ODHWzBo0pgfoOMhkmzStHONIukPbxgEyLSA/640?wx_fmt=png" data-type="png" data-w="567" src="https://mmbiz.qpic.cn/sz_mmbiz_png/G5jjcE4usexmLWZ8rn8G1x7mp8MMyTIAbM7l2cmGQkXgMtBLLU5ODHWzBo0pgfoOMhkmzStHONIukPbxgEyLSA/640?wx_fmt=png"></figure></section><section><p><strong>知识星球：</strong></p><figure><img data-ratio="1.5896226415094339" data-src="https://mmbiz.qpic.cn/sz_mmbiz_jpg/G5jjcE4usexmLWZ8rn8G1x7mp8MMyTIANerIBOfCR2fMuicyY73ZcD5QLUW1J6ticzdlWsZvv5wM3c5MroIHu6sA/640?wx_fmt=jpeg" data-type="jpeg" data-w="1060" src="https://mmbiz.qpic.cn/sz_mmbiz_jpg/G5jjcE4usexmLWZ8rn8G1x7mp8MMyTIANerIBOfCR2fMuicyY73ZcD5QLUW1J6ticzdlWsZvv5wM3c5MroIHu6sA/640?wx_fmt=jpeg"></figure></section></section><hr data-tool="mdnice编辑器"><p data-tool="mdnice编辑器"><br></p><center data-tool="mdnice编辑器"><strong> 往期回顾目录</strong></center><blockquote data-tool="mdnice编辑器"><p><br></p><center><strong><a href="https://mp.weixin.qq.com/s?__biz=MzkyMTI1MTYxNA==&mid=2247510151&idx=1&sn=de70b667d6eb7f581a68fd3fc231b1fc&chksm=c18492f6f6f31be05a57cb681d802fb813e36ac67f3d70fb05d26a6ea1aeee14bd17a91844e7&token=1624839730&lang=zh_CN&scene=21#wechat_redirect" data-linktype="2">ChIP-seq 绘图设计</a></strong></center><strong><center><a href="https://mp.weixin.qq.com/s?__biz=MzkyMTI1MTYxNA==&mid=2247510122&idx=1&sn=f06cfbecb15ee4f133c9b3d49791743a&chksm=c184921bf6f31b0d471e37ef63fdc4c7caf63df2a6598bd1f3c04d9b1505e2e103ef4f60eb66&token=1598639854&lang=zh_CN&scene=21#wechat_redirect" data-linktype="2">ggChIPvis 可视化基因组富集信号</a></center></strong><strong><center><a href="https://mp.weixin.qq.com/s?__biz=MzkyMTI1MTYxNA==&mid=2247510122&idx=1&sn=f06cfbecb15ee4f133c9b3d49791743a&chksm=c184921bf6f31b0d471e37ef63fdc4c7caf63df2a6598bd1f3c04d9b1505e2e103ef4f60eb66&token=1598639854&lang=zh_CN&scene=21#wechat_redirect" data-linktype="2">ggChIPvis 可视化基因组富集信号</a></center></strong><strong><center><a href="https://mp.weixin.qq.com/s?__biz=MzkyMTI1MTYxNA==&mid=2247510110&idx=1&sn=5b8a12b864509d65c243b61d080350a9&chksm=c184922ff6f31b3943a3681def268998388a3a930b2c384f3d8ea33ff17a437cc4513fc1b286&token=819162780&lang=zh_CN&scene=21#wechat_redirect" data-linktype="2">ChIP-seq 可视化探索</a></center></strong><strong><center><a href="https://mp.weixin.qq.com/s?__biz=MzkyMTI1MTYxNA==&mid=2247510080&idx=1&sn=d296de1de6d26ca85c724c392fe9959b&chksm=c1849231f6f31b272f3826f9a8f5277a1272f44443a5553513c0ffe3d82ca48d3c518ad49d0f&token=1127717108&lang=zh_CN&poc_token=HItqJWWjkYgH0feCwRqHpggUnZg-boP69onpft9F&scene=21#wechat_redirect" data-linktype="2">自定义基因集 GseaVis 绘图</a></center></strong><strong><center><a href="https://mp.weixin.qq.com/s?__biz=MzkyMTI1MTYxNA==&mid=2247510066&idx=1&sn=19c713554cd00a6d444e098145f3d286&chksm=c1849243f6f31b5582896d837ce91f6655d7029fc6c95bfc98c622787d4a9dfe57a74152fd75&token=1127717108&lang=zh_CN&scene=21#wechat_redirect" data-linktype="2">批量下载 starbase 数据</a></center></strong><strong><center><a href="https://mp.weixin.qq.com/s?__biz=MzkyMTI1MTYxNA==&mid=2247510050&idx=1&sn=9b1a5fb1cc6ecf52844847f4aba6bfb8&chksm=c1849253f6f31b450c12a6748a188e734f92c16be1abc51d75afabb33f404f45d60d1d616191&token=100163832&lang=zh_CN&scene=21#wechat_redirect" data-linktype="2">听说你想在 python 中对 kegg 可视化?</a></center></strong><strong><center><a href="https://mp.weixin.qq.com/s?__biz=MzkyMTI1MTYxNA==&mid=2247510034&idx=1&sn=e43a22b9de87e7e4500d3e2f52bc50c5&chksm=c1849263f6f31b75338900b88e5abfe2747e7cd980706c8348e23078d65ca28273cbcbf2ff84&token=203556469&lang=zh_CN&scene=21#wechat_redirect" data-linktype="2">优雅的使用 lattice 可视化单细胞</a></center></strong><strong><center><a href="https://mp.weixin.qq.com/s?__biz=MzkyMTI1MTYxNA==&mid=2247510008&idx=1&sn=86892dd2412183414ed984d5279848fc&chksm=c1849d89f6f3149f5771e1b74a7e9ad1e72c619c203e227f25bd895712c981c2f9d8230e91b6&token=203556469&lang=zh_CN&scene=21#wechat_redirect" data-linktype="2">听说你想在 circlize 的环形热图里添加显著性?</a></center></strong><strong><center><a href="https://mp.weixin.qq.com/s?__biz=MzkyMTI1MTYxNA==&mid=2247509978&idx=1&sn=7af95b9220830dfc92a31ef64092e72e&chksm=c1849dabf6f314bd5d28fee0a1467696de2c157d506ea1d19a43c2319811514fcc76515469bf&token=1162368673&lang=zh_CN&scene=21#wechat_redirect" data-linktype="2">听说表达趋势你想分面展示?</a></center></strong><p><br></p></blockquote></section><p><mp-style-type data-value="3"></mp-style-type></p></div> | ||
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