DOI: 10.5281/zenodo.6778429
title: On taming the effect of transcript level intra-condition count variation during differential expression analysis: a story of dogs, foxes and wolves: Bowtie2 counts and kallisto abundances

description: Intra [1] and inter [2-5] study RNA-seq read datasets representing the varying brain compartments of foxes (n=24), as well as dogs (n=14) and wolves (n=6), as described in Lobo <em>et al.</em>, (2022) (under review), were mapped to the dog reference transcriptome [6], which contained 26,107 annotated transcripts (Ensembl CanFam3.1, release 92) [7], using Bowtie2 v.2.3.4.1 [8] and using kallisto v0.46.1 [9]. Count data obtained following each mapping approach for each dataset had high correlations (Lobo <em>et al.</em>, Figure S2). Bowtie2 counts were subsequently used in multiple differential analysis experiments in order to explore the effects of intra-condition count variation on the detection of differentially expressed transcripts. The individual count and abundance datasets for each corresponding RNA-seq dataset are available here. A preprint of Lobo et al., 2022, currently under review for PLOS ONE, is available [10]. The preprint however does not contain reviewer requested information on simulations as this, along with other additions including an additional author RL, has been subsequently added during the review process. These additions will be made available following review via a link to the final paper. Related software to this project are:<br> 1. CStone <br> 2. CSReadGen<br> 3. CView <br> 4. ChimSim<br> 5. TVScript &lt; General details of the projects involved are available: dog-wolf and chimerism. <strong>References</strong> 1. Wang X, Pipes L, Trut L, Herbeck Y, Vladimirova A, Gulevich R, et al. Genomic responses to selection for tame/aggressive behaviors in the silver fox (Vulpes vulpes). Proc Natl Acad Sci. 2018;115: 10398–10403. doi:10.1073/pnas.1800889115 2. Roy M, Kim N, Kim K, Chung WH, Achawanantakun R, Sun Y, et al. Analysis of the canine brain transcriptome with an emphasis on the hypothalamus and cerebral cortex. Mamm Genome. 2013;24: 484–499. doi:10.1007/s00335-013-9480-0 3. Fushan AA, Turanov AA, Lee SG, Kim EB, Lobanov A V, Yim SH, et al. Gene expression defines natural changes in mammalian lifespan. Aging Cell. 2015;14: 352–365. doi:10.1111/acel.12283 4. Hoeppner MP, Lundquist A, Pirun M, Meadows JRS, Zamani N, Johnson J, et al. An improved canine genome and a comprehensive catalogue of coding genes and non-coding transcripts. PLoS One. 2014;9(3):91172. doi:10.1371/journal.pone.0091172 5. Albert FW, Somel M, Carneiro M, Aximu-Petri A, Halbwax M, Thalmann O, et al. A Comparison of Brain Gene Expression Levels in Domesticated and Wild Animals. Akey JM, editor. PLoS Genet. 2012;8:e1002962. doi:10.1371/journal.pgen.1002962 6. Hoeppner MP, Lundquist A, Pirun M, Meadows JRS, Zamani N, Johnson J, et al. An improved canine genome and a comprehensive catalogue of coding genes and non-coding transcripts. PLoS One. 2014;9(3):91172. doi:10.1371/journal.pone.0091172 7. Yates AD, Achuthan P, Akanni W, Allen J, Allen J, Alvarez-Jarreta J, et al. Ensembl 2020. Nucleic Acids Res. 2020;48: D682–D688. doi:10.1093/NAR/GKZ966 8. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012. doi:10.1038/nmeth.1923 9. Bray NL, Pimentel H, Melsted P, Pachter L. Near-optimal probabilistic RNA-seq quantification. Nat Biotechnol 2016 345. 2016;34: 525–527. doi:10.1038/nbt.3519 10. Lobo D, Godinho R, Archer JP. On taming the effect of transcript level intra-condition count variation during differential expression analysis: a story of dogs, foxes and wolves. bioRxiv. 2022; 2022.01.24.477470. doi:10.1101/2022.01.24.477470
description: This work was funded by the project NORTE-01-0246-FEDER-000063, supported by Norte Portugal Regional Operational Programme (NORTE2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF), and by research funding from the projects under the references PTDC/BIA-EVF/29115/2017, PTDC/BIA-EVF/2460/2014 and POCI-01-0145-FEDER-029115 co-funded by Operational Competitiveness and Internationalization Program, Portugal 2020 and the European Union via the European Regional Development Fund (ERDF) and by National Funds through FCT. DL, RG were supported by FCT (PD/BD/132403/2017 to DL, contract under DL57/2016 to RG) and JA was supported by Funds through FCT under the references POCI-01-0145-FEDER-029115 and PTDC/BIA-EVL/29115/2017. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. FCT URL: https://www.fct.pt/.