--- title: "Combining Transcriptomes with TAMA Merge" canonical: "https://help.biobam.com/space/OED0324/3676962822/Combining%20Transcriptomes%20with%20TAMA%20Merge" format: markdown --- # Introduction Combining FLAIR transcriptomes from 3 different tissues in *[Ursus arctos horribilis](https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=116960)**.* ### Dataset Description This dataset contains long reads sequenced by PacBio Sequel technology, representing adipose, skeletal muscle, and liver tissue of brown bears, once in active phase and once in hibernation phase. For each of these tissues, we have created a tissue-specific transcriptome with FLAIR in order to capture tissue-specific isoforms. Now, we can use TAMA Merge to create a combined brown bear transcriptome. - Organism: *[Ursus arctos horribilis](https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=116960)**.* - Instrument: PacBio Sequel - Previous analysis: FLAIR ### Publication [Tseng, E., Underwood, J. G., Evans Hutzenbiler, B. D., Trojahn, S., Kingham, B., Shevchenko, O., ... & Kelley, J. L. (2022). Long-read isoform sequencing reveals tissue-specific isoform expression between active and hibernating brown bears (Ursus arctos). ](https://academic.oup.com/g3journal/article/12/3/jkab422/6472356)*[G3](https://academic.oup.com/g3journal/article/12/3/jkab422/6472356)*[, ](https://academic.oup.com/g3journal/article/12/3/jkab422/6472356)*[12](https://academic.oup.com/g3journal/article/12/3/jkab422/6472356)*[(3), jkab422.](https://academic.oup.com/g3journal/article/12/3/jkab422/6472356)
Abstract Understanding hibernation in brown bears (Ursus arctos) can provide insight into some human diseases. During hibernation, brown bears experience periods of insulin resistance, physical inactivity, extreme bradycardia, obesity, and the absence of urine production. These states closely mimic aspects of human diseases such as type 2 diabetes, muscle atrophy, as well as renal and heart failure. The reversibility of these states from hibernation to active season enables the identification of mediators with possible therapeutic value for humans. Recent studies have identified genes and pathways that are differentially expressed between active and hibernation seasons in bears. However, little is known about the role of differential expression of gene isoforms on hibernation physiology. To identify both distinct and novel mRNA isoforms, full-length RNA-sequencing (Iso-Seq) was performed on adipose, skeletal muscle, and liver from three individual bears sampled during both active and hibernation seasons. The existing reference genome annotation was improved by combining it with the Iso-Seq data. Short-read RNA-sequencing data from six individuals were mapped to the new reference annotation to quantify differential isoform usage (DIU) between tissues and seasons. We identified differentially expressed isoforms in all three tissues, to varying degrees. Adipose had a high level of DIU with isoform switching, regardless of whether the genes were differentially expressed. Our analyses revealed that DIU, even in the absence of differential gene expression, is an important mechanism for modulating genes during hibernation. These findings demonstrate the value of isoform expression studies and will serve as the basis for deeper exploration into hibernation biology.
### Original Data - PacBio NCBI Project: [PRJNA727613](https://www.ncbi.nlm.nih.gov/bioproject/PRJNA727613) - NCBI Genome and Annotation: [Ursus arctos](https://www.ncbi.nlm.nih.gov/datasets/taxonomy/9644/) # Bioinformatic Analysis ## Combining Transcriptomes with TAMA Merge ### Input - Tissue-specific transcriptomes created with FLAIR, in .gtf format: [liver](https://drive.google.com/file/d/1MRka2t0OwpmPensJ3uJZb0wQFFIFK-48/view?usp=sharing), [fat](https://drive.google.com/file/d/1D7xNcBxFrImdrl71-dlyxnkpWSxejM3g/view?usp=sharing), [muscle](https://drive.google.com/file/d/1Aoot8wOi0qi0pchyr94-QwQvbZfiScap/view?usp=sharing) - [NCBI annotation](https://drive.google.com/file/d/1IFPfwI0RsZ9rK3UsXmOqbHM7Ey_MG6Gi/view?usp=sharing) in .gtf format (or in .db format using gtftools) ### Parameters #### Input Transcriptomes: [genomic.gtf](https://drive.google.com/file/d/1IFPfwI0RsZ9rK3UsXmOqbHM7Ey_MG6Gi/view?usp=sharing), [liver.transcriptome.gtf](https://drive.google.com/file/d/1MRka2t0OwpmPensJ3uJZb0wQFFIFK-48/view?usp=sharing), [fat.transcriptome.gtf](https://drive.google.com/file/d/1D7xNcBxFrImdrl71-dlyxnkpWSxejM3g/view?usp=sharing), [muscle.transcriptome.gtf](https://drive.google.com/file/d/1Aoot8wOi0qi0pchyr94-QwQvbZfiScap/view?usp=sharing) #### Algorithm Options Reference transcriptome: genomic.gtf Transcript start sites: All capped Exon ends: Most common exon 5' threshold: 50 Splice junction threshold: 0 3' threshold: 50 #### Output Output File Prefix: TAMA Output Directory: path/to/result Save Merged Transcriptome as .bed: True Save Merged Transcriptome as .gtf: True ### Execution Time 2m48s ### Output - [TAMA.bed](https://drive.google.com/file/d/1XWvbE8dsMAVPRn6Rnm7vEESIQ2ovtKRP/view?usp=sharing): merged transcriptome in .bed format - [TAMA.gtf](https://drive.google.com/file/d/13cjBkEAdi-hnOoslp4NxVIQrMf6VQ9Ti/view?usp=sharing): merged transcriptome in .gtf format - [TAMA_gene_report.txt](https://drive.google.com/file/d/1jXmeYh39hFCXE6OcWUlwcdnhe1V4FWyV/view?usp=sharing): gene report showing e.g. number of transcripts per gene before and after merge - [TAMA_trans_report.txt](https://drive.google.com/file/d/1pmZ1rB45NW0AGyb5EouQQ5Oj65225KMN/view?usp=sharing): transcript report showing e.g. in which input files transcripts were present - [TAMA_merge.txt](https://drive.google.com/file/d/1aZUY5pA4iN1EaCoAhmBwRTLXEQMMCdpz/view?usp=sharing): bed-format file attributing source to final transcripts