← 返回分析流程中心创建时间 2026/6/3 分析难度 高级 推荐场景 翻译组 预计耗时 3-5 天
Pipeline Detail
Translatomics长读长、翻译组与非模式物种
Ribo-seq 翻译组分析
面向 ribosome profiling 的翻译组分析流程，覆盖 RPF 质控、rRNA/tRNA 去除、比对、P-site 校正、三核苷酸周期性、ORF 检测和翻译效率分析。
Metadata
流程元数据
先看应用场景、输入输出和工具依赖，再进入正文命令细节。
Difficulty
高级
Scenario
翻译组
Estimated Time
3-5 天
Tools
DESeq2STARRiboCode
Inputs
FASTQBAMGTFcount matrix
Outputs
report
Workflow DAG
流程图
用步骤节点快速理解这个分析从原始数据到结果报告的流转关系。
STEP 1
→建立 Ribo-seq 项目
STEP 2
→adapter trimming
STEP 3
→rRNA/tRNA 过滤
STEP 4
→基因组/转录组比对
STEP 5
→三核苷酸周期性
STEP 6
→P-site 校正
STEP 7
→ORF 检测
STEP 8
→翻译效率 TE
STEP 9
翻译组报告
Protocol
流程文档
正文保留 Markdown 排版、代码语言标识和表格样式，适合边学边复现。
Ribo-seq 翻译组分析
一、项目目录
mkdir -p riboseq_project/{00_metadata,01_fastq,02_trimmed,03_filter_rrna,04_alignment,05_qc,06_counts,07_te,08_orf,report}
二、示例数据
sample_id,assay,condition,fastq
Ctrl_Ribo_1,Ribo-seq,Ctrl,01_fastq/Ctrl_Ribo_1.fq.gz
Treat_Ribo_1,Ribo-seq,Treat,01_fastq/Treat_Ribo_1.fq.gz
Ctrl_RNA_1,RNA-seq,Ctrl,01_fastq/Ctrl_RNA_1_R1.fq.gz
Treat_RNA_1,RNA-seq,Treat,01_fastq/Treat_RNA_1_R1.fq.gz
三、整体流程图
flowchart TD
A[Ribo-seq FASTQ] --> B[adapter trimming]
B --> C[length filtering 26-34 nt]
C --> D[remove rRNA/tRNA reads]
D --> E[align to genome/transcriptome]
E --> F[read length distribution and periodicity]
F --> G[P-site offset correction]
G --> H[RPF count matrix]
H --> I[ORF detection]
J[matched RNA-seq count] --> K[translation efficiency]
H --> K
I --> L[translation report]
K --> L
四、接头过滤和长度筛选
cutadapt -a CTGTAGGCACCATCAAT -m 26 -M 34 -o 02_trimmed/Ctrl_Ribo_1.trimmed.fq.gz 01_fastq/Ctrl_Ribo_1.fq.gz
Ribo-seq footprints 通常集中在 28-32 nt 左右，不同物种和实验可能略有变化。
五、去除 rRNA/tRNA
bowtie -p 8 -v 2 --un 03_filter_rrna/Ctrl_Ribo_1.no_rrna.fq ref/rrna_trna_index 02_trimmed/Ctrl_Ribo_1.trimmed.fq.gz > 03_filter_rrna/Ctrl_Ribo_1.rrna.sam
六、比对
STAR --runThreadN 12 --genomeDir ref/star_index --readFilesIn 03_filter_rrna/Ctrl_Ribo_1.no_rrna.fq --outSAMtype BAM SortedByCoordinate --outFilterMultimapNmax 1 --outFileNamePrefix 04_alignment/Ctrl_Ribo_1_
samtools index 04_alignment/Ctrl_Ribo_1_Aligned.sortedByCoord.out.bam
七、周期性和 P-site QC
library(riboWaltz)
annotation_dt <- create_annotation(gtfpath = "ref/genes.gtf")
bam_list <- bamtolist(
bamfolder = "04_alignment",
annotation = annotation_dt
)
psite_offset <- psite(bam_list)
rlength_distr(bam_list, sample = "Ctrl_Ribo_1")
frame_psite_length(bam_list, sample = "Ctrl_Ribo_1")
图例解释：
| QC | 理想表现 |
|---|---|
| read length distribution | 28-32 nt 有明显峰 |
| trinucleotide periodicity | CDS 中 0 frame 富集 |
| metagene plot | start/stop codon 附近有合理分布 |
八、RPF count 和翻译效率 TE
library(DESeq2)
ribo_counts <- read.csv("06_counts/ribo_counts.csv", row.names = 1)
rna_counts <- read.csv("06_counts/rna_counts.csv", row.names = 1)
combined <- cbind(ribo_counts, rna_counts)
sample_info <- data.frame(
sample = colnames(combined),
condition = rep(c("Ctrl", "Treat"), times = 2),
assay = c(rep("Ribo", ncol(ribo_counts)), rep("RNA", ncol(rna_counts)))
)
rownames(sample_info) <- sample_info$sample
dds <- DESeqDataSetFromMatrix(
countData = combined,
colData = sample_info,
design = ~ assay + condition + assay:condition
)
dds <- DESeq(dds, test = "LRT", reduced = ~ assay + condition)
res_te <- results(dds)
write.csv(as.data.frame(res_te), "07_te/translation_efficiency_DESeq2.csv")
解释：
RNA-seq 上调 + Ribo-seq 上调：转录和翻译同步增强。
RNA-seq 不变 + Ribo-seq 上调：可能存在翻译效率增强。
RNA-seq 上调 + Ribo-seq 不变：转录变化未传递到翻译层面。
九、ORF 检测
常用工具包括 RiboTaper、RiboCode、ORFquant。
RiboCode -a ref/transcripts.gtf -c 04_alignment/config.txt -l no -g -o 08_orf/ribocode_ORFs
十、交付物
- trimmed RPF reads
- rRNA/tRNA 过滤统计
- Ribo-seq BAM
- read length distribution
- 三核苷酸周期性图
- P-site offset 表
- RPF count matrix
- translation efficiency 结果
- ORF/uORF 候选表
- 翻译调控机制报告