ReviewBriefings in bioinformatics2021
Homoeologous gene expression and co-expression network analyses and evolutionary inference in allopolyploids.
Review in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed.
- The promise of long-read RNA-seq: reducing bias in analyses of allele imbalance.NAR genomics and bioinformatics · 2026Article
- Systems-level proteomic models of cotton fiber development: a high-resolution data resource to analyze cell dynamics and trait engineering.Plant physiology · 2026Article
- Diploid- and tetraploid wall barley exhibit alternative molecular responses but comparable reproductive performance in response to different ambient temperature regimes.The Plant journal : for cell and molecular biology · 2026Article
- Radiogenomics deciphers tumor heterogeneity in hepatocellular carcinoma and combined hepatocellular-cholangiocarcinoma.Discover oncology · 2026Article
- Article
- A likelihood ratio test for detecting shifts in homeolog expression ratios in allopolyploids.The New phytologist · 2026Article
- Comparative multi "omics" profiling ofFrontiers in plant science · 2026Article
- Genome wide identification and analysis of inositol tetrakisphosphate kinase (ITPK) gene family in Triticum aestivum L.PloS one · 2026Article
- Individualized co-expression-like index (iCKI) enables gene-gene interactions as individual biomarkers for complex disease.BMC bioinformatics · 2025Article
- Long-read genomics reveal extensive nuclear-specific evolution and allele-specific expression in a dikaryotic fungus.Genome research · 2025Article
- Structure-based virtual screening aids the identification of glycosyltransferases in the biosynthesis of salidroside.Plant biotechnology journal · 2025Article
- A high-resolution model of gene expression during Gossypium hirsutum (cotton) fiber development.BMC genomics · 2025Article
- Daily glycome and transcriptome profiling reveals polysaccharide structures and correlated glycosyltransferases critical for cotton fiber growth.The Plant journal : for cell and molecular biology · 2024Article
- A Quantitative Computational Framework for Allopolyploid Single-Cell Data Integration and Core Gene Ranking in Development.Molecular biology and evolution · 2024Article
- Comparative Metabolome and Transcriptome Analysis of Rapeseed (Plants (Basel, Switzerland) · 2024Article
- Review
- Evaluating deep learning techniques for identifying tongue features in subthreshold depression: a prospective observational study.Frontiers in psychiatry · 2024Article
- Peanut allergen characterization and allergenicity throughout development.Frontiers in allergy · 2024Article
- A low-coverage 3' RNA-seq to detect homeolog expression in polyploid wheat.NAR genomics and bioinformatics · 2023Article
- Homoeologous evolution of the allotetraploid genome of Poa annua L.BMC genomics · 2023Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Polyploidy is a widespread phenomenon throughout eukaryotes. Due to the coexistence of duplicated genomes, polyploids offer unique challenges for estimating gene expression levels, which is essential for understanding the massive and various forms of transcriptomic responses accompanying polyploidy. Although previous studies have explored the bioinformatics of polyploid transcriptomic profiling, the causes and consequences of inaccurate quantification of transcripts from duplicated gene copies have not been addressed. Using transcriptomic data from the cotton genus (Gossypium) as an example, we present an analytical workflow to evaluate a variety of bioinformatic method choices at different stages of RNA-seq analysis, from homoeolog expression quantification to downstream analysis used to infer key phenomena of polyploid expression evolution. In general, EAGLE-RC and GSNAP-PolyCat outperform other quantification pipelines tested, and their derived expression dataset best represents the expected homoeolog expression and co-expression divergence. The performance of co-expression network analysis was less affected by homoeolog quantification than by network construction methods, where weighted networks outperformed binary networks. By examining the extent and consequences of homoeolog read ambiguity, we illuminate the potential artifacts that may affect our understanding of duplicate gene expression, including an overestimation of homoeolog co-regulation and the incorrect inference of subgenome asymmetry in network topology. Taken together, our work points to a set of reasonable practices that we hope are broadly applicable to the evolutionary exploration of polyploids.
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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.