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Homeolog expression quantification methods for allopolyploids


Kuo, Tony; Hatakeyama, Masaomi; Tameshige, Toshiaki; Shimizu, Kentaro K; Sese, Jun (2018). Homeolog expression quantification methods for allopolyploids. bioRxiv 426437, University of Zurich.

Abstract

Genome duplication with hybridization, or allopolyploidization, occurs in animals, fungi, and plants, and is especially common in crop plants. There is increasing interest in the study of allopolyploids due to advances in polyploid genome assembly, however the high level of sequence similarity in duplicated gene copies (homeologs) pose many challenges. Here we compared standard RNA-seq expression quantification approaches used currently for diploid species against subgenome-classification approaches which maps reads to each subgenome separately. We examined mapping error using our previous and new RNA-seq data in which a subgenome is experimentally added (synthetic allotetraploid Arabidopsis kamchatica) or reduced (allohexaploid wheat Triticum aestivum versus extracted allotetraploid) as ground truth. The error rates in the two species were very similar. The standard approaches showed higher error rates (>10% using pseudo-alignment with Kallisto) while subgenome-classification approaches showed much lower error rates (<1% using EAGLE-RC, <2% using HomeoRoq). Although downstream analysis may partly mitigate mapping errors, the difference in methods was substantial in hexaploid wheat, where Kallisto appeared to have systematic differences relative to other methods. Only approximately half of the differentially expressed homeologs detected using Kallisto overlapped with those by any other method. In general, disagreement in low expression genes was responsible for most of the discordance between methods, which is consistent with known biases in Kallisto. We also observed that there exist uncertainties in genome sequences and annotation which can affect each method differently. Overall, subgenome-classification approaches tend to perform better than standard approaches with EAGLE-RC having the highest precision.

Abstract

Genome duplication with hybridization, or allopolyploidization, occurs in animals, fungi, and plants, and is especially common in crop plants. There is increasing interest in the study of allopolyploids due to advances in polyploid genome assembly, however the high level of sequence similarity in duplicated gene copies (homeologs) pose many challenges. Here we compared standard RNA-seq expression quantification approaches used currently for diploid species against subgenome-classification approaches which maps reads to each subgenome separately. We examined mapping error using our previous and new RNA-seq data in which a subgenome is experimentally added (synthetic allotetraploid Arabidopsis kamchatica) or reduced (allohexaploid wheat Triticum aestivum versus extracted allotetraploid) as ground truth. The error rates in the two species were very similar. The standard approaches showed higher error rates (>10% using pseudo-alignment with Kallisto) while subgenome-classification approaches showed much lower error rates (<1% using EAGLE-RC, <2% using HomeoRoq). Although downstream analysis may partly mitigate mapping errors, the difference in methods was substantial in hexaploid wheat, where Kallisto appeared to have systematic differences relative to other methods. Only approximately half of the differentially expressed homeologs detected using Kallisto overlapped with those by any other method. In general, disagreement in low expression genes was responsible for most of the discordance between methods, which is consistent with known biases in Kallisto. We also observed that there exist uncertainties in genome sequences and annotation which can affect each method differently. Overall, subgenome-classification approaches tend to perform better than standard approaches with EAGLE-RC having the highest precision.

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Item Type:Working Paper
Communities & Collections:04 Faculty of Medicine > Functional Genomics Center Zurich
07 Faculty of Science > Institute of Evolutionary Biology and Environmental Studies
Dewey Decimal Classification:570 Life sciences; biology
610 Medicine & health
Language:English
Date:2018
Deposited On:22 Feb 2019 14:45
Last Modified:13 Mar 2019 16:31
Series Name:bioRxiv
OA Status:Green
Publisher DOI:https://doi.org/10.1101/426437
Related URLs:https://www.zora.uzh.ch/id/eprint/168479/

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