DOI: 10.5061/dryad.zpc866tmz
title: Engineered probiotic restores glp-1 signaling to ameliorate fiber-deficiency-exacerbated colitis

description: Raw sequencing data were first processed through Novogene’s quality
 control (QC) pipeline, in which raw reads were filtered to remove adapter
 sequences, ambiguous bases (N &gt; 10%), and low-quality reads (reads
 with &gt;50% bases having a quality score ≤ 5). Clean reads obtained
 from this step were then aligned to the reference genome using HISAT2,
 allowing precise mapping of splice junction reads and comprehensive
 detection of differential gene expression, alternative splicing events,
 genetic variants, and gene fusions. Post-mapping analyses included
 quantification and annotation of gene expression levels, normalized as
 fragments per kilobase of transcript per million mapped reads
 (FPKM). Genes were annotated with detailed genomic attributes
 such as chromosome location, strand orientation, gene length, biotype,
 transcription factor families, and functional descriptions. All QC
 information, stats and analysis including reads count and FPKM used for
 further analysis are uploaded here.
description: # Engineered probiotic restores glp-1 signaling to ameliorate
 fiber-deficiency-exacerbated colitis ### Transcriptomics_data_and_QC.zip
 **SupFile** 1 Directory tree SupFile |--all_compare.xls [gene expression
 and annotation information] |--gene.fa [fasta sequence file of gene]
 |--Upstream_Geneseq.fa [fasta sequence file of upstream]
 |--Downstream_Geneseq.fa [fastq sequence file of downstream] |--CDS.fa
 [fasta sequence file of cds] |--gene.xls [gene-related information file]
 |--go.xls [go information about related gene] |--kegg.xls [kegg
 information about related gene] |--ko.xls [KO annotation about related
 gene] |--ppi.xls [ppi information about related gene]
 |--SupFile/GOclassification |--1.GO_classification_bar.png [the figure of
 classification statistics by the GO annotation, all genes annotated to the
 second level are mapped, png] |--2.GO_classification_bar.pdf [the figure
 of classification statistics by the GO annotation, all genes annotated to
 the second level are mapped, pdf] |--3.GO_classification.xls [the
 classified statistical results of GO annotations]
 |--4.GO_classification_count.txt [the input data of the figure for
 classification statistics by the GO annotation] |--5.GO_classification.dat
 [the corresponding files of go id and gene id] 2 File Formats
 Specification 2.1 all_compare.xls Tab-delimited text file can be opened in
 Excel. The file format definition is as follows: | column | names |
 description | | ------ | ----------------------- |
 -------------------------------------------------------- | | 1 | gene\_id
 | Gene ID | | 2 | sample\_count | The readcount of genes of sample | | 3 |
 sample\_fpkm | The FPKM of genes of sample | | 4 | compare\_treat | The
 mean value of normalised readcounts in treat group | | 5 |
 compare\_control | The mean value of normalised readcounts in control
 group | | 6 | compare\_log2FoldChange | log2FoldChange value of a
 comparison group | | 7 | compare\_pvalue | pvalue value of a comparison
 group | | 8 | compare\_padj | padj value of a comparison group | | 9 |
 gene\_name | Gene symbol | | 10 | gene\_chr | The chromosome of gene | |
 11 | gene\_start | The start site of gene | | 12 | gene\_end | The end
 site of gene | | 13 | gene\_strand | The direction of the gene chain | |
 14 | gene\_length | The length of the gene | | 15 | gene\_biotype | The
 biotype of gene | | 16 | gene\_description | The description of gene | |
 17 | tf\_family | The transcription factor of gene | 2.2 gene.xls
 Tab-delimited text file can be opened in Excel. The file format definition
 is as follows: | column | names | description | | ------ |
 ----------------- | -------------------------------- | | 1 | gene\_id |
 Gene ID | | 2 | gene\_name | Gene symbol | | 3 | gene\_chr | The
 chromosome of gene | | 4 | gene\_start | The start site of gene | | 5 |
 gene\_end | The end site of gene | | 6 | gene\_strand | The direction of
 the gene chain | | 7 | gene\_length | The length of the gene | | 8 |
 gene\_biotype | The biotype of gene | | 9 | gene\_description | The
 description of gene | | 10 | tf\_family | The transcription factor of gene
 | 2.3 go.xls Tab-delimited text file can be opened in Excel. The file
 format definition is as follows: | column | names | description | | ------
 | ------------ | -------------------------------- | | 1 | gene\_id | Gene
 ID | | 2 | go\_id | Id of gene ontology | | 3 | go\_ontology | The gene
 ontology | | 4 | go\_term | The information of gene ontology | 2.4
 kegg.xls Tab-delimited text file can be opened in Excel. The file format
 definition is as follows: | column | names | description | | ------ |
 ----------------- | -------------------------------- | | 1 | gene\_id |
 Gene ID | | 2 | pathway\_gene\_id | Gene id in kegg pathway database | | 3
 | pathway\_id | Id of kegg pathway | | 4 | pathway\_name | The information
 of gene pathway | 2.5 ko.xls Tab-delimited text file can be opened in
 Excel. The file format definition is as follows: | column | names |
 Description | | ------ | --------------- | -------------------------------
 | | 1 | gene\_id | Gene ID | | 2 | ko\_id | Kegg pathway id | | 3 |
 ko\_name | Kegg pathway name | | 4 | ko\_description | The description of
 kegg pathway | 2.6 ppi.xls Tab-delimited text file can be opened in Excel.
 The file format definition is as follows: | column | names | description |
 | ------ | ----------- | ------------- | | 1 | gene\_id | Gene ID | | 2 |
 protein\_id | Id of protein | 2.7 GO_classification.xls Tab-delimited text
 file can be opened in Excel. The file format definition is as follows: |
 column | names | description | | ------ | ------------- |
 -------------------------------- | | 1 | GO ID(Lev1) | GO id of level 1 |
 | 2 | GO Term(Lev1) | GO term of level 1 | | 3 | GO ID(Lev2) | GO id of
 level 2 | | 4 | GO Term(Lev2) | GO term of level 2 | | 5 | GO ID (Lev3) |
 GO id of level 3 | | 6 | GO Term(Lev3) | GO term of level 3 | | 7 | GO ID
 (Lev4) | GO id of level 4 | | 8 | GO Term(Lev4) | GO term of level 4 | | 9
 | Gene Number | Gene number related to GO (Lev4) | | 10 | Gene List | Gene
 id related to GO (Lev4) | **QC** 1 Introduction The Sequenced Reads/raw
 reads often contain low quality reads or reads with adapters, which will
 affect the analysis quality and reliability.To avoid this, it's
 necessary to fiIter the raw reads and get the clean reads. The procedure
 of raw reads filtering is as follows: (1) Remove reads containing
 adapters; (2)Remove reads containing $\mathrm {N}&gt;10%$ (N represents
 base that could not be determined); (3) Remove low quality reads: The
 Qscore (Quality value) of over 50% bases of the read $is&lt;=5.$ 2
 Directory tree QC/ QC/1.Error [Error Rate Distribution] |--
 sampleID_Error.pdf [figure of error rate distribution, pdf format]
 |--sampleID_Error.pdf [figure of error rate distribution, png format]
 |--sampleID_Error.svg [figure of error rate distribution, svg format]
 QC/2.GC [GC Content Distribution] |--sampleID_GC.pdf [figure of GC
 distribution diagram, pdf format] |--sampleID_GC.pdf [figure of GC
 distribution diagram, png format] |--sampleID_GC.svg [figure of GC
 distribution diagram,svg format] QC/3.Filter [Data Filtering]
 |--sampleID_Filter.pdf [figure of raw reads classification
 distribution,pdf format] |--sampleID_Filter.pdf [figure of raw reads
 classification distribution, png format] |--sampleID_Filter.png [figure of
 raw reads classification distribution, png format] QC/4.Stat [Data Quality
 Summary] |--data_table.xls [Summary table of sample data quality] 3 File
 Formats Specification 3.1 data_table.xls The data quality of all samples
 are summaried in this table, which contains: | column | names |
 description | | ------ | ----------- |
 --------------------------------------------------------------------------------------------------------------------------------------------------- | | 1 | sample | SampleID | | 2 | library | LibraryID | | 3 | raw\_reads | Reads count from the raw data, four rows as an unit, with statistics of reads count for every sequencing | | 4 | raw bases | Base number of raw data. (number of raw reads) \* (sequence length), converting unit to G | | 5 | clean reads | Clean data is reads count filtered from raw data. Statistics method is similar with raw reads.All the following<br>analysis is based on clean data | | 6 | clean bases | Base number of raw data after filtering. (number of clean reads) \* (sequence length), converting unit to G | | 7 | error\_rate | Base error rate of whole sequencing | | 8 | Q20 | Phred values greater than 20 base number contain the percentage of total bases. (Base number of Phred valu $\text {u}&gt;2)/$ $(Totalbasenumber)\*100$ | | 9 | Q30 | Phred values greater than 30 base number contain the percentage of total bases. (Base number of Phred valu $\text {u}&gt;3)/$ $(Totalbasenumber)\*100$ | | 10 | $GC\_pct$ | The percentage of G\&C base numbers of total bases.(G\&C base number) / (Total base numbe $\text {r}\*100$ | **Mapping** 1 Introduction Mapping the clean reads to the reference genome or the transcriptome is the basis for the next following analysis. We use HISAT2 to accomplish the mapping. If only the differential expression significant genes are needed, we map reads to the transcriptome directly. If the study of alternative splicing, variation, the fusion gene are needed, the alignment are carried out at the genome level. In order to avoid losing a lot of effective junction reads, we use HISAT2 software to alignment for RNA-seq sequencing data analysis and the junction reads can be positioned precisely. 2 Directory tree Mapping/ Mapping/1.Region [Reads distribution on genome] |--sampleID_Region.pdf [figures of Reads distribution on genome, pdf format] |--sampleID_Region.png [figures of Reads distribution on genome, png format] |--sampleID_Region.svg [figures of Reads distribution on genome, svg format] Mapping/2.Stat [the summary of mapping result] |--align_pct.xls [Statistical table of sample comparison rate] |--align_region.xls [Statistical table of sample comparison area] 3 File Formats Specification 3.1 align_pct.xls Tab-delimited text file can be opened in Excel. The file format definition is as follows: | row | names | description | | --- | ------------- | ----------------------------------------------------------------------------------------- | | 1 | sample | sampleID. | | 2 | total\_reads | total clean reads using for analysis. | | 3 | total\_map | numbers of reads being mapped to the genome. | | 5 | unique\_map | numbers of reads being mapped to unique position of the genome. | | 6 | multi\_map | numbers of reads being mapped to multiple positions of the genome. | | 7 | read1\_map | number of left read that can be mapped tothe reference genome. | | 8 | read2\_map | number of right read that can be mapped to the reference genome. | | 9 | positive\_map | number of reads that can be mapped to the positive strand (+). | | 10 | negative\_map | number of reads that can be mapped to the minus strand (-). | | 11 | splice\_map | number of reads that can be segmented and mapped to two exons (alsonamed junction reads). | | 12 | unsplice\_map | number of reads thatcan be mapped entirely to a single exon. | | 13 | proper\_map | number of reads that can be mapped to the genome by paired readl and read2 | 3.2 align_region.xls Tab-delimited text file can be opened in Excel. The file format definition is as follows: | row | names | description | | --- | ---------- | ----------------------------------------------------- | | 1 | sample | sampleID. | | 2 | exon | numbers of reads being mapped on the exon area. | | 3 | intron | numbers of reads being mapped on the intron area. | | 4 | intergenic | numbers of reads being mapped on the intergenic area. | 3.3 MappingRegion Mapped regions can be classified as exon, intron, or intergenic region. Exon-mapped reads should be the most abundant type of read when the reference genome is well-annotated. Intron-reads may be derived from pre-mRNA contamination or intron-retention events from alternative splicing. Reads mapped to intergenic regions are mainly because of weak annotation of the reference genome. **Quant** 1 Introduction The abundance of transcript reflects the gene expression level directly. In RNA-seq experiment, we estimate gene expression level by the abundance of transcripts(count of sequencing) that mapped to genome or exon. Reads count is proportional to gene expression level, gene length and sequencing depth. FPKM (short for the expected number of Fragments Per Kilobase of transcript sequence per Millions base pairs sequenced)is the most common method of estimating gene expression levels, which takes the effects into consideration of both sequencing depth and gene length on counting of fragments. 2 Directory tree Quant/1.Count [gene expression level list] |--gene_count.xls [the readcount list with the annotation of each gene] |--gene_fpkm.xls [the FPKM list with the annotation of each gene] |--gene_fpkm_group.xls [list of FPKM values for all groups. FPKM value: the adjusted readcount.(for biological replicates experiment)] Quantification/2.Correlation [RNA-Seq Correlation] |--correlation.xls [the list of pearson coefficients between samples] Quantification/ 3.Distribution |--fpkm_interval.xls [statistics list of expression level for all genes.The first column is the **FPKM** Interval, the other column is the gene number(proportion) of different samples.] **3 File Formats Specification** 3.1 gene_count.xls Tab-delimited xls file can be opened in Excel. The file format definition is as follows: | column | names | description | | ------------- | ----------------- | -------------------------------- | | 1 | gene\_id | Gene ID | | 2 | sample | The readcount of genes of sample | | 3 | gene\_name | Gene symbol | | 4 | gene\_chr | Chromosome/scaffold ID | | 5 | gene\_start | Start coordinate | | 6 | gene\_end | End coordinate | | 7 | gene\_strand | Strand specificity | | 8 | gene\_length | Novel gene length | | 9 | gene\_biotype | The type of novel gene | | 10 | gene\_description | Description from PFAM Annotation | | 11 tf\_family | 11 tf\_family | TheTFfamilyofnovelgene | 3.2 gene_fpkm.xls Tab-delimited xls file can be opened in Excel. The file format definition is as follows: | column | names | description | | ------ | ----------------- | -------------------------------- | | 1 | gene\_id | Gene ID | | 2 | sample | The FPKM of genesofsample | | 3 | gene\_name | Gene symbol | | 4 | gene\_chr | Chromosome/scaffold ID | | 5 | gene\_start | Start coordinate | | 6 | gene\_end | End coordinate | | 7 | gene\_strand | Strand specificity | | 8 | gene\_length | Novel gene length | | 9 | gene\_biotype | Thetypeofnovelgene | | 10 | gene\_description | Description from PFAM Annotation | | 11 | tf\_family | The TF family of novel gene | | 1 | gene\_id | Gene ID | | 2 | group | The FPKM of genes of group | | 3 | gene\_name | Gene symbol | | 4 | gene\_chr | Chromosome/scaffold ID | | 5 | gene\_start | Start coordinate | | 6 | gene\_end | End coordinate | | 7 | gene\_strand | Strand specificity | | 8 | gene\_length | Novel gene length | | 9 | gene\_biotype | The type of novel gene | | 10 | gene\_description | Description from PFAM Annotation | | 11 | tf\_family | The TF family of novel gene |