Evidence map›Paper›PMID 30590436›Full record

ReviewBriefings in bioinformatics2020

Homeolog expression quantification methods for allopolyploids.

Tony C Y Kuo, Masaomi Hatakeyama, Toshiaki Tameshige, Kentaro K Shimizu, Jun Sese

Open access · hybridAbstract readReview
In one paragraph

Review in Briefings in bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
5.1field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 50 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 2 countries.

Tony C Y KuoArtificial Intelligence Research Center, AIST, 2-3-26 Aomi, Koto-ku, Tokyo 135-0064, Japan.
Masaomi HatakeyamaDepartment of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, Zurich CH-8057, Switzerland.
Toshiaki TameshigeKihara Institute for Biological Research, Yokohama City University, 641-12, Maioka, Totsuka-ku, Yokohama 244-0813, Japan.
Kentaro K ShimizuDepartment of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, Zurich CH-8057, Switzerland.
Jun SeseArtificial Intelligence Research Center, AIST, 2-3-26 Aomi, Koto-ku, Tokyo 135-0064, Japan.
Tokyo Institute of Technology · JPUniversity of Zurich · CHYokohama City University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genome duplication with hybridization, or allopolyploidization, occurs in animals, fungi and plants, and is especially common in crop plants. There is an increasing interest in the study of allopolyploids because of advances in polyploid genome assembly; however, the high level of sequence similarity in duplicated gene copies (homeologs) poses 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 wheat. 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.

Indexed as

PolyploidyChromosomes, PlantGene Expression Regulation, PlantSequence Analysis, RNATriticumallopolyploidexpression quantificationhomeologRNA-seqsubgenome classification

Identifiers

PMID30590436
PMCPMC7299288
OpenAlexW2952615573

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.