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Dynamic and non-additive gene regulation shapes maize responses to simultaneous salt and cold stress.

Salt and cold stresses often occur together in nature and severely impact crop productivity, yet their transcriptional regulation remains poorly understood. Here, we conducted a time-series transcriptomic analysis of maize under salt, cold, and their combination at 0, 6, 12, and 24 h. Differential expression analysis revealed dynamic, condition-specific gene responses grouped into eight distinct temporal patterns. Promoter motif analysis of genes within each pattern identified 5-39 significantly enriched motifs, with over 40% lacking known counterparts, suggesting the involvement of previously uncharacterized cis-regulatory elements in stress-responsive transcriptional regulation. By comparing combined stress responses to the sum of single-stress effects, we found that about 74% of DEGs showed non-additive patterns, suggesting that combined stress triggers a distinct transcriptional program. Evolutionary analysis showed that additive DEGs tend to be more recently evolved, subject to weaker purifying selection, and enriched in transposed duplications, contrasting with the stronger constraint observed in non-additive DEGs. WGCNA identified 24 co-expression modules, among which 65 hub DEGs were detected in modules significantly correlated with specific stress conditions. Furthermore, we reconstructed 228, 20, and 200 sequential transcription factor cascades spanning 6 h, 12 h, and 24 h under cold, salt, and combined stress, respectively, with no cascade shared across all three conditions. Together, these results reveal that maize responses to combined salt and cold stress are largely non-additive and temporally dynamic, with distinct evolutionary patterns underlying different response types, offering insights and candidate regulators for enhancing crop stress resilience.

Zea mays↗

Integrating explainable AI with multiomics systems biology and EHR data mining for personalized drug repurposing in Alzheimer's disease.

Alzheimer's disease (AD) is characterized by region- and patient-specific molecular heterogeneity, which hinders therapeutic design. In this study, we introduce PRISM-ML (PRecision-medicine using Interpretable Systems and Multiomics with Machine Learning), an open-source integrated analysis pipeline that combines interpretable machine learning with systems biology and electronic health record (EHR) data mining to elucidate the molecular diversity of AD and predict promising drug repurposing opportunities. First, we integrated and harmonized transcriptomic (bulk RNA-seq) and genomic (genome-wide association study) data from 2105 brain samples, each with matched data from the same individual (1363 AD patients, 742 controls; nine tissues), sourced from three independent studies. Random forest classifiers with SHapley Additive exPlanations (SHAP) identified patient-specific biomarkers; unsupervised clustering resolved 36 molecularly distinct "subtissues" (clusters of samples); and gene-gene co-expression networks prioritized 262 high-centrality bottleneck genes as putative regulators of dysregulated pathways. Next, knowledge graph-based drug repurposing predicted six FDA-approved drugs that simultaneously target multiple bottleneck genes and multiple AD-relevant pathways. Notably, in a large U.S. de-identified insurance-claims database (n = 364733), exposure to promethazine, one of the candidate drugs, was associated with a 57-62 % lower incidence of AD versus an active antihistamine comparator (adjusted hazard ratio 0.38; inverse-probability weighted 0.43; both p < 0.001), providing real-world support for its repurposing potential. In summary, PRISM-ML, as an explainable multi-omics analysis pipeline, is readily transferable to other complex diseases, advancing precision medicine.

Computational Biology↗

Gene microarray study corroborates proteomic findings in rodent islet cells.

As reported in an issue of Journal of Proteome Research, mass spectrometry has been used to identify numerous proteins in pancreatic islets. Our group studies beta cell gene expression, and we were interested in whether proteins described in this study could be found at the level of the transcriptome. Microarray analysis is a powerful technique for quantitative measurements of the expression of thousand genes in parallel. However, in crude tumor biopsies, only a subset of transcripts correlate with protein levels, and it is still unknown how frequently mRNA expression correlates with amount of protein in well-differentiated cells. To address this issue, we presently compared data from mouse primary islet proteins obtained by proteomic analysis with RNA data from FACS purified primary rat beta cells obtained by microarray analysis (Rasschaert J, Liu D, Cardozo AK, Kutlu B, Eizirik DL, manuscript in preparation).

Animals↗

Genome-Wide Association Analyses Identify Distinct Genetic Architectures for Extreme Early-Onset and Late-Onset T2D.

AIMS: Type 2 diabetes (T2D) is a heterogeneous disorder with substantial variation in age at onset (AAO). This study aimed to characterize the distinct genetic architectures and biological mechanisms underlying extreme AAO-defined T2D subtypes. MATERIALS AND METHODS: Using 74&#x2009;795 European-ancestry participants from the UK Biobank, we performed genome-wide association studies (GWAS) of relatively early-onset T2D (eoT2D; AAO <&#x2009;55&#x2009;years) and late-onset T2D (loT2D; AAO &#x2265;&#x2009;70&#x2009;years). We investigated subtype-specific genetic loci, SNP-based heritability, genetic correlations, Mendelian randomization (MR)-based relationships, polygenic risk scores (PRS) and phenome-wide association studies (PheWAS). Single-cell transcriptomic data from human pancreatic tissues were further used to evaluate cell-type-specific expression patterns of candidate genes. RESULTS: SNP-based heritability was substantially higher for eoT2D than loT2D (11.2% vs. 6.4%), with eoT2D displaying distinct genetic loci related to &#x3b2;-cell function and insulin regulation, including SLC30A8 and IRS1. By contrast, loT2D showed a comparatively lipid-related genetic profile, featuring APOE-associated signals and expression patterns in immune-related cell populations. Linkage disequilibrium score regression (LDSC) and MR analyses further underscored this divergence: eoT2D exhibited broader genetic overlap with cardiometabolic traits, whereas loT2D showed stronger relationships with traditional metabolic risk factors. Finally, subtype-specific PRSs improved risk discrimination beyond conventional covariates, although their clinical utility warrants further evaluation. CONCLUSIONS: Extreme AAO-defined T2D subtypes exhibit partially distinct genetic architectures, highlighting AAO as an important dimension of T2D heterogeneity and providing a framework for future age-stratified genetic risk assessment.

Type 2 diabetes↗

Sex-specific expression of alternative transcripts in Drosophila.

BACKGROUND: Many genes produce multiple transcripts due to alternative splicing or utilization of alternative transcription initiation/termination sites. This 'transcriptome expansion' is thought to increase phenotypic complexity by allowing a single locus to produce several functionally distinct proteins. However, sex, genetic and developmental variation in the representation of alternative transcripts has never been examined systematically. Here, we describe a genome-wide analysis of sex-specific expression of alternative transcripts in Drosophila melanogaster. RESULTS: We compared transcript profiles in males and females from eight Drosophila lines (OregonR and 2b, and 6 RIL) using a newly designed 60-mer oligonucleotide microarray that allows us to distinguish a large proportion of alternative transcripts. The new microarray incorporates 7,207 oligonucleotides, satisfying stringent binding and specificity criteria that target both the common and the unique regions of 2,768 multi-transcript genes, as well as 12,912 oligonucleotides that target genes with a single known transcript. We estimate that up to 22% of genes that produce multiple transcripts show a sex-specific bias in the representation of alternative transcripts. Sexual dimorphism in overall transcript abundance was evident for 53% of genes. The X chromosome contains a significantly higher proportion of genes with female-biased transcription than the autosomes. However, genes on the X chromosome are no more likely to have a sexual bias in alternative transcript representation than autosomal genes. CONCLUSION: Widespread sex-specific expression of alternative transcripts in Drosophila suggests that a new level of sexual dimorphism at the molecular level exists.

Alternative Splicing↗

A defective NF-kappa B/RelB pathway in autoimmune-prone New Zealand black mice is associated with inefficient expansion of thymocyte and dendritic cells.

New Zeland Black (NZB) mice develop an autoimmune disease involving an abnormal B cell response to peripheral self Ags. This disease is associated with defects in other cell types and thymic stromal organization. We present evidence that NZB cells of various lineages, including thymocytes, fibroblasts, and dendritic precursor cells, show impaired proliferation and enhanced cell death in culture upon stimulation compared with non-autoimmune-prone mice such as C57BL/6. This phenotype explains the reduced efficiency of maturation of bone marrow-derived dendritic cells and the loss of TNF- or IL-1-dependent thymocyte costimulation. Upon TNF-induced activation of NZB thymocytes, nuclear translocation and DNA binding of RelA- and RelB-dependent NF-kappaB heterodimers are significantly reduced. This phenotype has a transcriptional signature, since the NZB, but not the nonobese diabetic, thymic transcriptome shows striking similarities with that of RelB-deficient thymuses. This partial NF-kappaB deficiency detected upon activation by proinflammatory cytokines could explain the disorganization of thymic microenvironments in NZB mice. These combined effects might reduce the efficiency of central tolerance and expose apoptotic debris generated during inflammatory processes to self recognition.

Active Transport, Cell Nucleus↗

Integrated transcriptomic, transcriptional factors, and protein interaction reveal the regulatory mechanisms of flowering time in rice (Oryza sativa L.).

Appropriate flowering time is important for rice regional adaptation and optimum rice production, but little is known about the omics of heading date in rice. Here, we studied omics including transcriptome, proteome and transcriptional factors to identify regulatory genes related to flowering time. A total of 1402 differentially expressed genes (DEGs, 721 up-regulated and 681 down-regulated) were detected in wild and mutant. These transcripts are classified according to biological processes, cellular components, and molecular functions. Among these differentially expressed genes, many transcription factor genes demonstrated multiple regulatory pathways involved in flowering time. Gene expression analysis showed that Os03g0122600 (OsMADS50), Os08g0105000 (Ehd3), Os06g0275000 (Hd1) were expressed higher and Os06g0199500 (OsHAL3), Os06g0498800 (OsMFT1), Os08g0105000 (Ehd3), Os06g0157700 (Hd3a), and Os02g0731700 (Ghd2), were expressed lower in wild compared to mutant, which are the key genes that regulate the flowering in rice. In addition, Ghd7 interacted with Os10g30860 and Os12g08260 using yeast two-hybrid assay. We identified 28 potential Ghd7 transcriptional regulators using the transcription factor-centered yeast one hybrid (TF-Centered Y1H) assay. Taken together, this study developed a new set of genomic resources to identify and characterize genes, proteins, and motifs associated with flowering time.

Oryza↗

Mapping QTLs regulating morpho-physiological traits and yield: case studies, shortcomings and perspectives in drought-stressed maize.

Comparative analysis of a number of studies in drought-stressed maize (Zea mays L.) reporting quantitative trait loci (QTLs) for abscisic acid concentration, root characteristics, other morpho-physiological traits (MPTs) and grain yield (GY) reveals their complex genetic basis and the influence of the genetic background and the environment on QTL effects. Chromosome regions (e.g. near umc11 on chromosome 1 and near csu133 on chromosome 2) with QTLs controlling a number of MPTs and GY across populations and conditions of different water supply have been identified. Examples are presented on the use of QTL information to elucidate the genetic and physiological bases of the association among MPTs and GY. The QTL approach allows us to develop hypotheses accounting for these associations which can be further tested by developing near isogenic lines (NILs) differing for the QTL alleles. NILs also allow for a more accurate assessment of the breeding value of MPTs and, in some cases, may allow for the map-based cloning of the gene(s) underlying the QTL. Although QTL analysis is still time-consuming and resource-demanding, its integration with genomics and post-genomics approaches (e.g. transcriptome, proteome and metabolome analyses) will play an increasingly important role for the identification and validation of candidate genes affecting MPTs and GY.

Abscisic Acid↗

Predicting cellular responses to perturbation across diverse contexts with State.

While machine learning models offer potential for predicting transcriptomic effects of perturbation, they currently struggle to generalize across cellular contexts. Here, we introduce State, a machine learning model that predicts perturbation effects while accounting for cellular heterogeneity within and across experiments. State is trained using single-cell gene expression data to predict perturbation effects across sets of cells. State improved discrimination of effects on large datasets by more than 30% and identified differentially expressed genes across genetic, signaling, and chemical perturbations with significantly improved accuracy compared with baselines. Its cell embeddings trained on observational data from 167 million cells enable the identification of strong perturbations in cellular contexts where no perturbations were observed during training. We further introduce Cell-Eval, a comprehensive evaluation framework that can be used to evaluate future models. Overall, the performance and flexibility of State set the stage for scaling the development of AI models of cell state.

Machine Learning↗

Neurogenomics: at the intersection of neurobiology and genome sciences.

Neurogenomics is the study of how the genome as a whole contributes to the evolution, development, structure and function of the nervous system. It includes investigations of how genome products (transcriptomes and proteomes) vary in time and space. Neurogenomics differs markedly from the application of genome sciences to other systems, particularly in the spatial category, because anatomy and connectivity are paramount to our understanding of function in the nervous system. We focus here on some of the influences of genomics and its associated technologies on neuroscience. We discuss comparative genomics, gene expression atlases of the brain, network genetics and applications to behavioral phenotypes, and consider the culture, organization and funding of genome-scale projects.

Animals↗

Common features and differences in the transcriptome of large cell anaplastic lymphoma and classical Hodgkin's lymphoma.

BACKGROUND AND OBJECTIVES: Anaplastic large cell lymphoma (ALCL) and classical Hodgkin's lymphoma (HL) are derived from different cell types, namely T cells and B cells, respectively. However, both lymphomas share a similar cytological and immunohistochemical tumor cell phenotype with little resemblance to their cells of origin. DESIGN AND METHODS: In this study, the transcriptional profiles of ALCL cell lines, primary ALCL tumor cells from peripheral blood and HL cell lines were compared to each other and to normal B-cell subsets, B non-Hodgkin's lymphomas (NHL) and B NHL- and Epstein-Barr virus (EBV)-transformed B-cell lines in order to establish their relationship at the transcriptional level and to identify genes with possible pathobiological impact. Expression of some of the genes identified was confirmed in microdissected primary tumor cells by reverse transcriptase polymerase chain reaction (RT-PCR) and immunohistochemistry. RESULTS: HL samples clustered separately from ALCL samples, but HL and ALCL were found to be more closely related to each other than to any normal or malignant B-cell sample in the dataset. Their relationship was determined to a large extent, but not exclusively, by lack of expression of B-cell antigens and by the over-expression of mRNA encoding activation markers and structural proteins. Apart from established differences between HL and ALCL, further genes of interest could be identified that distinguish both entities from each other and from the other samples. The differential expression of PRAME, DDR2, SOCS3 and CEBPD in HL and ALCL was confirmed in primary tumor tissue by immunohistochemistry and/or RT-PCR. INTERPRETATION AND CONCLUSIONS: At a transcriptional level HL is more closely related to Alk+ ALCL than to the B-NHL or B-cell samples investigated, although it is a B-cell derived lymphoma. The newly identified genes discriminating HL and ALCL may be pathobiologically important and may serve as possible therapeutic targets.

Adult↗

Transcriptomic shift in ethanol and amino acid metabolic genes regulated by Med15 during alcoholic fermentation.

Organisms that thrive in extreme environments provide natural experiments in evolution, revealing the genetic regulators that orchestrate complex phenotypic change. Wine yeast (WY) are specialized strains that are adapted to survive in the wine making environment while producing high concentrations of ethanol. In addition to large genomic changes that differentiate WY from yeast used in other industries, SNP and polyglutamine tract polymorphism in the transcriptional regulator Med15 are associated with the fermentation efficiency and stress response phenotypes of WY. In this study, we investigated the transcriptional differences during wine fermentation in transgenic lab strain yeast having integrated WY MED15 alleles. Compared to the unmodified lab strain (MED15 LAB), the same strain in which the MED15 locus was replaced with a MED15 allele from yeast isolated from palm wine, the fermented sap of palm (oil, date, coconut) trees (MED15 WY23), exhibited enhanced expression of amino acid biosynthesis genes as well as stress resistance and metabolic adaptation genes. Our experimental data confirm the role of arginine in efficient fermentation and suggest that certain MED15 alleles alter the expression patterns of arginine pathway genes in some cases improving carbon flux under nitrogen stress. The global benefits conferred by natural polymorphisms in a single transcriptional regulator highlight Med15 as a target for engineering of strains devoted to various types of alcohol production.

Ethanol↗

Transcriptional profiling of Arabidopsis tissues reveals the unique characteristics of the pollen transcriptome.

Pollen tubes are a good model for the study of cell growth and morphogenesis because of their extreme elongation without cell division. Yet, knowledge about the genetic basis of pollen germination and tube growth is still lagging behind advances in pollen physiology and biochemistry. In an effort to reduce this gap, we have developed a new method to obtain highly purified, hydrated pollen grains of Arabidopsis through flowcytometric sorting, and we used GeneChips (Affymetrix, Santa Clara, CA; representing approximately 8,200 genes) to compare the transcriptional profile of sorted pollen with those of four vegetative tissues (seedlings, leaves, roots, and siliques). We present a new graphical tool allowing genomic scale visualization of the unique transcriptional profile of pollen. The 1,584 genes expressed in pollen showed a 90% overlap with genes expressed in these vegetative tissues, whereas one-third of the genes constitutively expressed in the vegetative tissues were not expressed in pollen. Among the 469 genes enriched in pollen, 162 were selectively expressed, and most of these had not been associated previously with pollen. Their functional classification reveals several new candidate genes, mainly in the categories of signal transduction and cell wall biosynthesis and regulation. Thus, the results presented improve our knowledge of the molecular mechanisms underlying pollen germination and tube growth and provide new directions for deciphering their genetic basis. Because pollen expresses about one-third of the number of genes expressed on average in other organs, it may constitute an ideal system to study fundamental mechanisms of cell biology and, by omission, of cell division.

Arabidopsis↗

Tiling microarray analysis of rice chromosome 10 to identify the transcriptome and relate its expression to chromosomal architecture.

BACKGROUND: Sequencing and annotation of the genome of rice (Oryza sativa) have generated gene models in numbers that top all other fully sequenced species, with many lacking recognizable sequence homology to known genes. Experimental evaluation of these gene models and identification of new models will facilitate rice genome annotation and the application of this knowledge to other more complex cereal genomes. RESULTS: We report here an analysis of the chromosome 10 transcriptome of the two major rice subspecies, japonica and indica, using oligonucleotide tiling microarrays. This analysis detected expression of approximately three-quarters of the gene models without previous experimental evidence in both subspecies. Cloning and sequence analysis of the previously unsupported models suggests that the predicted gene structure of nearly half of those models needs improvement. Coupled with comparative gene model mapping, the tiling microarray analysis identified 549 new models for the japonica chromosome, representing an 18% increase in the annotated protein-coding capacity. Furthermore, an asymmetric distribution of genome elements along the chromosome was found that coincides with the cytological definition of the heterochromatin and euchromatin domains. The heterochromatin domain appears to associate with distinct chromosome level transcriptional activities under normal and stress conditions. CONCLUSION: These results demonstrated the utility of genome tiling microarray in evaluating annotated rice gene models and in identifying novel transcriptional units. The tiling microarray sanalysis further revealed a chromosome-wide transcription pattern that suggests a role for transposable element-enriched heterochromatin in shaping global transcription in response to environmental changes in rice.

Chromosomes, Plant↗

Laparoscopic donor nephrectomy gene expression profiling reveals upregulation of stress and ischemia associated genes compared to control kidneys.

We compared gene expression profiles from six donor kidneys prior to surgical manipulation to six kidneys removed after laparoscopic donor nephrectomy (LDN) and several hours of CO2 pneumoperitoneum. Biopsies were obtained from renal cortex and hybridized to Affymetrix HG-U133A GeneChips. For control kidneys, we identified 1380 genes present on all six samples that had a signal intensity >1,000. Functional classification of these revealed genes for cellular signaling (201; 15%), regulation of transcription (156; 11%), cellular transport (144; 10%) and cellular metabolism (111; 8%). A class comparison between the controls and LDN kidneys yielded 865 differentially expressed genes. Functional classification of the 502 genes differentially upregulated in LDN kidneys identified associations with apoptosis, cell adhesion, cell signaling, regulation of cell growth/proliferation, immune/inflammation, ischemia/stress response and proteolysis/peptidolysis. These data demonstrate an altered renal transcriptome induced by several hours of CO2 pneumoperitoneum and laparoscopic surgery characterized by upregulation of ischemia and injury associated genes.

Adult↗

Comparative genomics of Gossypium and Arabidopsis: unraveling the consequences of both ancient and recent polyploidy.

Both ancient and recent polyploidy, together with post-polyploidization loss of many duplicated gene copies, complicates angiosperm comparative genomics. To explore an approach by which these challenges might be mitigated, genetic maps of extant diploid and tetraploid cottons (Gossypium spp.) were used to infer the approximate order of 3016 loci along the chromosomes of their hypothetical common ancestor. The inferred Gossypium gene order corresponded more closely than the original maps did to a similarly inferred ancestral gene order predating an independent paleopolyploidization (alpha) in Arabidopsis. At least 59% of the cotton map and 53% of the Arabidopsis transcriptome showed correspondence in multilocus gene arrangements based on one or both of two software packages (CrimeStatII, FISH). Genomic regions in which chromosome structural rearrangement has been rapid (obscuring gene order correspondence) have also been subject to greater divergence of individual gene sequences. About 26%-44% of corresponding regions involved multiple Arabidopsis or cotton chromosomes, in some cases consistent with known, more ancient, duplications. The genomic distributions of multiple-locus probes provided early insight into the consequences for chromosome structure of an ancient large-scale duplication in cotton. Inferences that mitigate the consequences of ancient duplications improve leveraging of genomic information for model organisms in the study of more complex genomes.

Arabidopsis↗

Integrated transcriptomic and metabolomic analyses provide new insights into the response of black rockfish (Sebastes schlegelii) larvae to temperature fluctuations.

Sebastes schlegelii usually encounter elevated and fluctuating water temperatures near its upper thermal limit in summer, yet the hepatic responses of larvae to repeated temperature fluctuation regimes remain unclear. To address this question, S. schlegelii larvae were exposed for 8&#xa0;days to four thermal regimes: constant 18&#xa0;&#xb0;C (CT), constant 28&#xa0;&#xb0;C (HT), intermittent cooling from 18 to 8&#xa0;&#xb0;C followed by recovery to 18&#xa0;&#xb0;C (FL), and intermittent warming from 18 to 28&#xa0;&#xb0;C followed by recovery to 18&#xa0;&#xb0;C (FH). Survival rate was evaluated, and integrated liver transcriptomic and metabolomic analyses were performed. Final survival rates were 96.67% in the CT group, 97.78% in the FL group, and 77.78% in the FH group. Survival rate in the HT group (38.89%) was significantly lower than that in the other three groups (P&#xa0;<&#xa0;0.05). HTvsCT, FLvsCT, FHvsCT, and FHvsHT comparisons identified 2598, 1207, 622, and 2404 differentially expressed genes and 627, 606, 690, and 610 differential metabolites, respectively. KEGG enrichment analyses of DEGs and SDMs in HTvsCT highlighted HSP-mediated proteostasis, endoplasmic-reticulum protein processing, branched-chain and sulfur amino acid metabolism, glutathione metabolism, and central carbon metabolism, with upregulated hsp90aa1, bckdha, gclc, and pfkp and reduced levels of branched-chain amino acids and methionine. Compared with HT, FH showed attenuated disturbances in proteostasis, amino acid and redox regulation, and central carbon metabolism, together with recovery-associated glycerophospholipid turnover. FL primarily induced polyunsaturated fatty acid (PUFA)-related membrane lipid remodeling. These findings indicate that hepatic responses differed between continuous high-temperature exposure and temperature fluctuations and between fluctuation regimes.

Animals↗

Transposable Element Dynamics Drive the Genomic Evolution and Phenotypic Diversification of Allotetraploid Common Carp.

An important question in evolutionary biology is how polyploidization generates raw material for phenotypic diversification. Transposable elements (TEs) represent an underestimated source of genetic variation in eukaryotic genomes. By integrating 516 whole-genome resequencing datasets and 236 transcriptomes from common carp (Cyprinus carpio), a representative allotetraploid fish, we constructed the first population-scale landscape of TE insertions in teleosts. TE insertions are widespread in the carp genome and preferentially associated with stress-responsive genes, with DNA transposons as major contributors. Relaxed purifying selection and TE burst events coexist, generating abundant variation for subsequent subspecies differentiation. Compared with a closely related diploid species, carp exhibits more exonic TE insertions and shorter TE-gene distances, and multiple TE superfamilies expanded during tetraploidization. Genome-wide association analyses uncovered intragenic TE variants underlying domesticated traits missed by SNPs, including DNA transposon deletions associated with scale reduction and altered body shape. Notably, lighter-colored individuals harbor homozygous deletions of LTR and DNA transposons within mdfic2, whose knockout in zebrafish reduces pigmentation. Most trait-associated variants reflect lineage-specific loss of ancient TE insertions rather than recent transposition. Overall, these findings highlight the distinct role of TEs in polyploid genome evolution and phenotypic diversification, providing new insights into TE dynamics in vertebrates.

allotetraploidization↗