Performance of gene expression analyses using de novo assembled transcripts in polyploid species

Homoeologs in Allopolyploids: Navigating Redundancy as Both an Evolutionary Opportunity and a Technical Challenge-A Transcriptomics Perspective

Allopolyploidy in plants involves the merging of two or more distinct parental genomes into a single nucleus, a significant evolutionary process in the plant kingdom. Transcriptomic analysis provides invaluable insights into allopolyploid plants by elucidating the fate of duplicated genes, revealing evolutionary novelties and uncovering their environmental adaptations. By examining gene expression profiles, scientists can discern how duplicated genes have evolved to acquire new functions or regulatory roles. This process often leads to the development of novel traits and adaptive strategies that allopolyploid plants leverage to thrive in diverse ecological niches. Understanding these molecular mechanisms not only enhances our appreciation of the genetic complexity underlying allopolyploidy but also underscores their importance in agriculture and ecosystem resilience. However, transcriptome profiling is challenging due to genomic redundancy, which is further complicated by the presence of multiple chromosomes sets and the variations among homoeologs and allelic genes. Prior to transcriptome analysis, sub-genome phasing and homoeology inference are essential for obtaining a comprehensive view of gene expression. This review aims to clarify the terminology in this field, identify the most challenging aspects of transcriptome analysis, explain their inherent difficulties, and suggest reliable analytic strategies. Furthermore, bulk RNA-seq is highlighted as a primary method for studying allopolyploid gene expression, focusing on critical steps like read mapping and normalization in differential gene expression analysis. This approach effectively captures gene expression from both parental genomes, facilitating a comprehensive analysis of their combined profiles. Its sensitivity in detecting low-abundance transcripts allows for subtle differences between parental genomes to be identified, crucial for understanding regulatory dynamics and gene expression balance in allopolyploids.

Heterochronic shift in gene expression leads to ontogenetic morphological divergence between two closely related polyploid species

Heterochrony-alteration to the rate or timing of development-is an important mechanism of trait differentiation associated with speciation. Heterochrony may explain the morphological divergence between two polyploid species, June sucker (Chasmistes liorus) and Utah sucker (Catostomus ardens). The larvae of both species have terminal mouths; however, as adults, June sucker and Utah sucker develop subterminal and ventral mouths, respectively. We document a difference in the timing of shape development and a corresponding change in the timing of gene expression, suggesting the distinctive mouth morphology in June suckers may result from paedomorphosis. Specifically, adult June suckers exhibit an intermediate mouth morphology between the larval (terminal) and ancestral (ventral) states. Endemic and sympatric Chasmistes/Catostomus pairs in two other lakes also are morphologically divergent, but genetically similar. These species pairs could have resulted from the differential expression of genes and corresponding divergence in trait development. Paedomorphosis may lead to adaptive diversification in Catostomids.

Chromosome-level genome and high nitrogen stress response of the widespread and ecologically important wetland plant Typha angustifolia

Typha angustifolia L., known as narrowleaf cattail, is widely distributed in Eurasia but has been introduced to North America. Typha angustifolia is a semi-aquatic, wetland obligate plant that is widely distributed in Eurasia and North America. It is ecologically important for nutrient cycling in wetlands where it occurs and is used in phytoremediation and traditional medicine. In order to construct a high-quality genome for Typha angustifolia and investigate genes in response to high nitrogen stress, we carried out complete genome sequencing and high-nitrogen-stress experiments. We generated a chromosomal-level genome of T. angustifolia, which had 15 pseudochromosomes, a size of 207 Mb, and a contig N50 length of 13.57 Mb. Genome duplication analyses detected no recent whole-genome duplication (WGD) event for T. angustifolia. An analysis of gene family expansion and contraction showed that T. angustifolia gained 1,310 genes and lost 1,426 genes. High-nitrogen-stress experiments showed that a high nitrogen level had a significant inhibitory effect on root growth and differential gene expression analyses using 24 samples found 128 differentially expressed genes (DEGs) between the nitrogen-treated and control groups. DEGs in the roots and leaves were enriched in alanines, aspartate, and glutamate metabolism, nitrogen metabolism, photosynthesis, phenylpropanoid biosynthesis, plant-pathogen interaction, and mitogen-activated protein kinase pathways, among others. This study provides genomic data for a medicinal and ecologically important herb and lays a theoretical foundation for plant-assisted water pollution remediation.

Inference of Ancient Polyploidy Using Transcriptome Data

Polyploidizations, or whole-genome duplications (WGDs), in plants have increased biological complexity, facilitated evolutionary innovation, and likely enabled adaptation under harsh conditions. Besides genomic data, transcriptome data have been widely employed to detect WGDs, due to their efficient accessibility to the gene space of a species. Age distributions based on synonymous substitutions (so-called K_S age distributions) for paralogs assembled from transcriptome data have identified numerous WGDs in plants, paving the way for further studies on the importance of WGDs for the evolution of seed and flowering plants. However, it is still unclear how transcriptome-based age distributions compare to those based on genomic data. In this chapter, we implemented three different de novo transcriptome assembly pipelines with two popular assemblers, i.e., Trinity and SOAPdenovo-Trans. We selected six plant species with published genomes and transcriptomes to evaluate how assembled transcripts from different pipelines perform when using K_S distributions to detect previously documented WGDs in the six species. Further, using genes predicted in each genome as references, we evaluated the effects of missing genes, gene family clustering, and de novo assembled transcripts on the transcriptome-based K_S distributions. Our results show that, although the transcriptome-based K_S distributions differ from the genome-based ones with respect to their shapes and scales, they are still reasonably reliable for unveiling WGDs, except in species where most duplicates originated from a recent WGD. We also discuss how to overcome some possible pitfalls when using transcriptome data to identify WGDs.

Disentangling Sources of Gene Tree Discordance in Phylogenomic Data Sets: Testing Ancient Hybridizations in Amaranthaceae s.l

Gene tree discordance in large genomic data sets can be caused by evolutionary processes such as incomplete lineage sorting and hybridization, as well as model violation, and errors in data processing, orthology inference, and gene tree estimation. Species tree methods that identify and accommodate all sources of conflict are not available, but a combination of multiple approaches can help tease apart alternative sources of conflict. Here, using a phylotranscriptomic analysis in combination with reference genomes, we test a hypothesis of ancient hybridization events within the plant family Amaranthaceae s.l. that was previously supported by morphological, ecological, and Sanger-based molecular data. The data set included seven genomes and 88 transcriptomes, 17 generated for this study. We examined gene-tree discordance using coalescent-based species trees and network inference, gene tree discordance analyses, site pattern tests of introgression, topology tests, synteny analyses, and simulations. We found that a combination of processes might have generated the high levels of gene tree discordance in the backbone of Amaranthaceae s.l. Furthermore, we found evidence that three consecutive short internal branches produce anomalous trees contributing to the discordance. Overall, our results suggest that Amaranthaceae s.l. might be a product of an ancient and rapid lineage diversification, and remains, and probably will remain, unresolved. This work highlights the potential problems of identifiability associated with the sources of gene tree discordance including, in particular, phylogenetic network methods. Our results also demonstrate the importance of thoroughly testing for multiple sources of conflict in phylogenomic analyses, especially in the context of ancient, rapid radiations. We provide several recommendations for exploring conflicting signals in such situations. [Amaranthaceae; gene tree discordance; hybridization; incomplete lineage sorting; phylogenomics; species network; species tree; transcriptomics.]

Homoeologous gene expression and co-expression network analyses and evolutionary inference in allopolyploids

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.