The research focused on the Eastern yellowjacket, a common North American social wasp that acts as an important arthropod predator in natural and disturbed environments. Colonies are founded by a single queen and can contain thousands of workers, along with hundreds of new queens, or gynes, and males, by the end of the reproductive season. Queens typically mate with an average of six males, producing multiple paternal lineages, or patrilines, within each nest. This polyandrous mating system provided the basis for testing whether genetic differences among a queen’s mates influenced the wing shape of her female offspring. The researchers collected 10 colonies in Atlanta, Georgia, in November 2021 and November 2022, when the reproductive cycle made workers, gynes and males available in each colony.

To measure wing geometry, the team removed the right forewing from each wasp and imaged it with a dissection microscope. A single researcher manually placed 19 anatomical landmarks, primarily at vein intersections and other venation features, and 12 curves tracing corresponding wing regions. The choices were designed to be consistently identifiable across castes, allowing comparisons among individuals and castes. Wings damaged in ways that obscured the landmarks or curves were excluded, leaving a final dataset of 965 measured wings, with approximately 100 individuals from each colony. A Generalized Procrustes Alignment removed differences in position, orientation and scale, while each individual’s centroid size was retained separately for allometric analyses. Principal component analysis summarized the resulting shape space, and Procrustes ANOVAs with 1,000 permutations tested differences associated with caste, colony and patriline. Here, “wing shape” means the multivariate geometry of the selected landmarks and curves after alignment; it does not refer to the presence or absence of veins, their branching patterns or changes in vein identity.

The clearest result was a separation among the three castes in the forewing shape space. The first principal component accounted for 29.16% of total shape variation and the second for 18.47%. Caste was statistically associated with wing shape, and all pairwise caste comparisons showed significant divergence. The study also found significant differences among colonies nested within caste, with colony effects accounting for 19.15% of total shape variation. That colony-level pattern cannot be assigned to one mechanism from these data. Individuals in a colony share nutrition, brood care, nest microclimate and other developmental conditions, while separate colonies can differ in maternal genotype, patriline composition and socially mediated developmental effects. The colony result is therefore consistent with a mixture of environmental and genetic contributions, rather than evidence that either category alone produced the differences.

The team extracted DNA from the posterior legs of female wasps and genotyped them at six highly variable microsatellite markers. These markers were used to infer relatedness and paternal-family membership, not assumed to be causal loci for wing shape. Within a colony, females with compatible multilocus genotypes were assigned to the same patriline and treated as full-sib subfamilies; females assigned to different patrilines shared the same mother and were treated as maternal half-sibs. Patriline had a significant effect on wing shape in both female castes after colony differences were accounted for. Bayesian mixed-effects models estimated narrow-sense heritability along the primary shape axis at 0.275 for workers, with a 95% highest posterior density interval of 0.091 to 0.489, and 0.264 for gynes, with an interval of 0.103 to 0.494. Both intervals excluded zero. These estimates indicate that additive genetic differences contributed to within-colony variation in the measured primary shape axis, although they do not identify the particular genes or regulatory mechanisms responsible.

Body size was not strongly coupled to wing shape within colonies. A pooled multivariate model detected a significant caste-by-size interaction, but preliminary analyses showed that between-colony differences in body size, particularly among gynes, dominated the pooled allometric signal. Separate within-colony analyses were therefore used to examine individual-level size–shape relationships. None of the ten colonies showed a significant relationship among gynes, and their slopes varied in direction. Workers generally had negative or near-zero slopes, but only one colony reached significance, at p = 0.012; the weak and inconsistent pattern does not establish systematic negative allometry. No colony showed significant allometry among males, although that analysis had limited statistical power because each colony contributed only 10 males. Across the castes, the results do not support a strong developmental link between body size and forewing shape within nests.

Cross-caste comparisons showed that paternal relatedness leaves a measurable but small imprint on morphology. The analysis included 16,403 possible worker–gyne pairs from the 10 colonies. Pairs sharing a patriline were closer in overall multivariate shape space than maternal half-sister pairs assigned to different patrilines within the same colony. In a mixed-effects model with colony as a random effect, half-sister pairs were estimated to be 0.00109 shape-space units farther apart than full-sister pairs, with a standard error of 0.00011. The difference was highly significant, with t = 10.22, 16,390 degrees of freedom and p < 0.0001. Colony identity accounted for approximately 19% of the variation in worker–gyne distance, while the remainder was associated with the individual-pair level. The mean difference amounted to only about 2% of the within-colony range of pairwise distances, but it was estimated with high precision and was consistent across colonies. No single principal component dominated the resemblance; it emerged from many small differences distributed across multiple shape axes.

Genetic correlation models showed that this family resemblance did not amount to tight genetic constraint between the female castes. Patrilines explained substantial variation within each caste, but correlations between matching principal components in workers and gynes were centered near zero. The correlation between worker PC1 and gyne PC1 was −0.0010, with a 95% highest posterior density interval from −0.37 to 0.37. The estimate for worker PC2 and gyne PC2 was 0.0001, with an interval from −0.39 to 0.37. Other cross-component and cross-caste correlations were similarly weak, and their intervals overlapped zero. These results mean that full-sister workers and gynes were more similar overall, while the particular directions in which paternal family influenced their major shape axes were largely decoupled. The analysis is compatible with a modular genetic architecture, but it did not directly test genetic modularity or identify loci responsible for the effects.

The observed patterns are consistent with the different flight demands of the castes. Workers rely heavily on flight for foraging and nest defense, whereas gynes use it for dispersal and colony founding, and males fly mainly during mating periods. Worker wings were tightly clustered in shape space, while male wings showed greater shape variability. Those patterns are compatible with differences in the strength or direction of selection, although the study did not directly measure aerodynamic performance or test the underlying selective mechanisms. It likewise cannot establish that flight requirements caused the observed shape differences. The researchers did not quantify how a particular wing geometry affects survival, reproduction or colony performance, and the six-marker panel was not designed to detect genotype-by-environment interactions or causal genetic variants. The result is instead an observational separation of measured shape differences among castes, colonies and patrilines.

Overall, the study shows that Eastern yellowjacket wing morphology reflects several overlapping influences rather than a single cause. Caste differences were strong, colonies retained distinct shape signatures, and paternal family identity accounted for a meaningful portion of female wing-shape variation within nests. At the same time, the genetic effects of family membership were expressed differently across workers and gynes, with weak correlations along the main shape axes. The findings support the possibility that selection associated with the social division of labor can be associated with distinct wing forms in wasps that share much of their genetic architecture. They also illustrate how multiple mating can preserve heritable variation within colonies while leaving room for caste-specific divergence, without showing that any particular wing shape causes a fitness advantage.

Subject of Research: Genetic and colony-level determinants of caste-specific forewing shape in the Eastern yellowjacket wasp.

Article Title: Same Genes, Different Wings: Wing Shape Divergence Among Castes in a Social Wasp

Article References: Murray, K. A., Orr, S. E., Goodisman, M. A. D., Gosse, E. L., Hill, R., & Kovacs, J. L. (2026). Same Genes, Different Wings: Wing Shape Divergence Among Castes in a Social Wasp. Ecology and Evolution, 16(10), Article e74478. https://doi.org/10.1002/ece3.74478

Image Credits: AI Generated

DOI: 10.1002/ece3.74478

Keywords: Eastern yellowjacket, social wasps, wing morphology, geometric morphometrics, caste divergence, quantitative genetics, patrilines, polyandry, colony variation, insect flight, Same, Genes

The investigation used two publicly available gene-expression datasets from the Gene Expression Omnibus. GSE26051 served as the training cohort, while differential-expression results from GSE180836 contributed to candidate-gene discovery and screening. Because GSE180836 informed candidate selection, it was not used as an independent validation cohort. The selected biomarkers were instead assessed by reverse-transcription quantitative PCR, or RT-qPCR, in a separate clinical cohort containing 30 participants. This design meant that the principal laboratory confirmation came from clinical samples rather than from a second independent analysis of the public transcriptomic datasets.

To identify differentially expressed genes associated with the macrophage polarization-related transcriptional signature, the researchers combined differential-expression analysis with weighted gene co-expression network analysis, known as WGCNA. Three machine-learning algorithms were then applied to screen candidate biomarkers: least absolute shrinkage and selection operator, support vector machine-based recursive feature elimination, and the Boruta algorithm. The analysis selected PTCHD1, NEURL1, and ST8SIA5, all of which were significantly downregulated in the training cohort GSE26051.

Clinical testing supported two of the three candidates more clearly than the third. PTCHD1 and NEURL1 were each significantly downregulated in tendinopathy samples relative to controls in the cohort of 30, with P values below 0.01 for both comparisons. ST8SIA5 also exhibited a downward trend, but the difference did not reach statistical significance, with P = 0.074. On this evidence, PTCHD1 and NEURL1 were the more strongly supported markers associated with tendinopathy, while ST8SIA5 remained a candidate showing a consistent but inconclusive expression pattern.

The researchers also constructed a diagnostic nomogram from the selected biomarkers and evaluated it using receiver operating characteristic and calibration analyses. The model achieved an area under the ROC curve above 0.7 and showed good calibration. These results indicate that the model discriminated between the groups represented in the study, but the reported evidence does not establish its diagnostic performance in larger or more diverse populations. The distinction is particularly important because the public dataset GSE180836 contributed to candidate discovery rather than serving as an independent validation set, while the clinical cohort used for RT-qPCR confirmation included only 30 participants.

Functional enrichment and gene-set analyses associated the biomarker-related network with pathways including PI3K–Akt signaling and extracellular matrix–receptor interaction. These are computational associations within the studied expression data, not evidence that PTCHD1 or NEURL1 directly controls macrophage polarization or that either gene is a therapeutic target. Similarly, a drug–gene interaction analysis identified 16 potential therapeutic compounds, but the source reports network-level candidates rather than experimental tests of treatment effects. The study’s strongest supported finding is therefore the clinical association of reduced PTCHD1 and NEURL1 expression with tendinopathy, alongside a gene-based model that showed discrimination above 0.7 AUC in the available validation material.

Subject of Research: Macrophage-associated transcriptional biomarkers for tendinopathy

Article Title: Identification of genes associated with a macrophage polarization-related transcriptional signature as biomarkers for tendinopathy based on bioinformatics analysis

Article References: Ren, L., He, C., & Qin, Y. (2026). Identification of genes associated with a macrophage polarization-related transcriptional signature as biomarkers for tendinopathy based on bioinformatics analysis. Scientific Reports. https://doi.org/10.1038/s41598-026-75576-z

Image Credits: AI Generated

DOI: 10.1038/s41598-026-75576-z

Keywords: tendinopathy, macrophage polarization, PTCHD1, NEURL1, ST8SIA5, gene biomarkers, RT-qPCR, WGCNA, machine learning, diagnostic nomogram, Identification, genes

The genes in question, BMP15 and GDF9, are among the most celebrated regulators of female fertility in all of mammals. Both encode growth factors secreted by the oocyte, the egg cell itself, and both belong to the transforming growth factor-beta superfamily, a large group of signaling proteins that orchestrate development throughout the body. During folliculogenesis, the process by which ovarian follicles mature, BMP15 and GDF9 are produced by oocytes within growing follicles and act on the surrounding granulosa and cumulus cells in a paracrine fashion. BMP15 drives granulosa cell proliferation, cumulus expansion, and follicular development, while GDF9, located on ovine chromosome 5, is essential for early follicle progression, normal ovulation, fertilization, and subsequent reproductive performance. The stakes are high: in GDF9-null mice, and in ewes carrying naturally occurring inactivating GDF9 mutations, follicular development arrests entirely beyond the primary stage.

What makes these genes especially tantalizing for sheep breeders is their dosage-sensitive behavior. Landmark studies in New Zealand and Irish flocks showed that mutations in BMP15 can increase ovulation rate in heterozygous carriers while rendering homozygous carriers completely infertile—an unusual genetic pattern that made BMP15 a poster child for prolificacy research. Similar associations emerged in Cambridge and Belclare sheep, and Chinese breeds such as the prolific Small-tailed Han sheep have been screened extensively for BMP15 and GDF9 variants. Given this pedigree, the Qinghai team reasoned that if Tibetan sheep carried functional variants in these genes, those variants might explain—or eventually help breeders improve—their characteristically small litters.

The study combined gene cloning, bioinformatic prediction, quantitative real-time PCR, and a genotyping technology called improved multiplex ligase detection reaction, or iMLDR. From Tibetan ewes raised on a single commercial farm in Gonghe County, the researchers collected jugular vein blood from 200 healthy adults aged three to four years, each with complete litter-size records spanning two to three parities. All ewes were naturally mated during the same autumn breeding season, with no exogenous hormones administered, and lambing records were verified by farm technicians. A separate group of six six-month-old ewes from the same flock provided twelve tissues—hypothalamus, heart, lung, kidney, liver, spleen, muscle, uterus, ovary, oviduct, rumen, and duodenum—snap-frozen in liquid nitrogen for exploratory expression profiling.

Cloning revealed predicted open reading frames of 468 base pairs within the BMP15 fragment and 405 base pairs within the GDF9 fragment, encoding 155 and 134 amino acids respectively. Because these lengths fall far short of the known full-length ovine precursor proteins, the sequences must be regarded as partial coding fragments rather than complete coding sequences—a limitation the authors emphasize throughout. Phylogenetic analysis confirmed the fragments belong squarely with domestic sheep: the predicted amino acid sequences showed the highest similarity to Ovis aries reference sequences, followed by yak, with the lowest similarity to domestic dog for BMP15 and to cichlid fish for GDF9. Bioinformatic prediction painted a contrasting portrait of the two protein fragments. The BMP15 fragment showed slight overall hydrophobicity, with a grand average of hydropathicity of 0.026, and carried one transmembrane-like segment near its N-terminus spanning roughly residues 10 through 27. The GDF9 fragment was hydrophilic overall, with a hydropathicity average of minus 0.323, and carried a predicted Sec-type signal peptide with a potential cleavage site between amino acids 25 and 26—a hallmark of proteins targeted to the classical secretory pathway. The BMP15 fragment was predicted to be stable, with an instability index of 35.21, while the GDF9 fragment, at 53.62, was predicted unstable. Both fragments were dominated by random coils and alpha-helices, and each carried 13 predicted phosphorylation sites.

The expression results delivered one genuine surprise. As expected, GDF9 transcript abundance was highest in the ovary, consistent with its established role as an oocyte-derived factor, followed by kidney and uterus. But BMP15, rather than peaking in the ovary, showed its highest expression in the oviduct—the tube where gamete transport, fertilization, and early embryo–maternal communication occur—with a relatively high signal also detected in the liver. The authors stress that these extra-ovarian BMP15 signals are preliminary observations from an exploratory analysis: the ewes’ estrous-cycle stages could not be determined, reference-gene stability was not systematically evaluated across tissues, and no protein-level or spatial-localization validation was performed. Still, the oviduct finding hints at a potential extra-ovarian expression pattern that previous work in goats, where BMP15 generally showed more tissue-restricted expression, had not suggested.

The heart of the study, however, lay in its association analysis. From the team’s prior whole-genome resequencing data for Tibetan sheep, four single-nucleotide polymorphisms were selected: two in BMP15, located on the X chromosome, and two in GDF9, on chromosome 5. Standardized annotation using the Ensembl Variant Effect Predictor against the ovine ARS-UI_Ramb_v3.0 reference genome classified the variants as two synonymous and two missense changes. The missense variants were BMP15 p.Leu251Pro, a leucine-to-proline substitution at amino acid position 251, and GDF9 p.Arg87His, an arginine-to-histidine substitution at position 87. The synonymous variants altered codons from GTG to GTA and CTA to CTG without changing the encoded valine and leucine residues. Probing the potential impact of the missense substitutions with SIFT, the team found both predicted to be tolerated, with scores of 0.16 and 0.12 respectively—preliminary evidence that these substitutions may not disrupt protein function.

Genotyping all 200 ewes by iMLDR on an ABI 3730XL analyzer revealed a population with limited variation. Three loci showed very low heterozygosity, with the synonymous BMP15 variant and the missense GDF9 variant each carried by only seven heterozygous animals out of 200. The GDF9 synonymous locus was the most polymorphic, with heterozygosity of 0.43 and a polymorphic information content of 0.34. No locus deviated significantly from Hardy–Weinberg equilibrium. When the researchers modeled the relationship between genotype and litter size using a General Linear Model that accounted for parity effects, the verdict was unambiguous: none of the four SNPs showed a significant association with litter size, with all P values exceeding 0.05 and partial eta-squared effect sizes ranging from less than 0.001 to 0.008—indicating very small genotype effects. Haplotype reconstruction identified three haplotypes for each gene, but linkage disequilibrium analysis showed weak allelic correlation between the two SNPs within each gene: although the D-prime statistic reached 1.0 for both pairs, the r-squared values were a mere 0.001 for BMP15 and 0.039 for GDF9.

Why did the famous prolificacy genes come up empty? The authors point to several plausible explanations. First, Tibetan sheep produce so few twins that phenotypic variation in litter size is extremely limited, reducing statistical power to detect genotype–phenotype associations even when they exist. Second, while 200 ewes is a respectable sample, it may still be insufficient for SNPs with small genetic effects, particularly when some genotypes occur at very low frequencies—the GG genotype at one BMP15 locus appeared in only three animals, and the CT genotype at another in only seven. Third, and perhaps most fundamentally, both missense variants were predicted by SIFT to be tolerated, suggesting these particular loci may simply not be causal variants affecting litter size, nor in strong linkage disequilibrium with functional variants that do. The findings echo a broader lesson from prolificacy genetics: dosage-sensitive mutations that dramatically alter ovulation rate in some breeds, such as the BMP15 mutations of Cambridge and Belclare sheep or the FecB mutation of Booroola Merinos, are not necessarily present—or relevant—in every population.

The study’s real contribution is baseline data. By characterizing partial sequences, exploratory expression profiles, population-genetic parameters, haplotypes, and linkage disequilibrium for BMP15 and GDF9 in Tibetan sheep, the team has laid groundwork for future identification and validation of reproduction-related functional variants in this high-altitude breed. The authors call for full-length coding sequence cloning, protein-level validation with Western blotting and immunohistochemistry, larger sample sizes, and in vivo and in vitro functional assays to clarify the complete molecular structures and biological functions of these oocyte-secreted growth factors. Until then, the genetic roots of Tibetan sheep’s modest fertility remain an open question—one shaped, the evidence suggests, not by single famous mutations but by the complex interplay of hypoxia adaptation, energy metabolism, endocrine regulation, and ovarian function forged across thousands of generations on the Roof of the World.

Subject of Research: Genetics

Article Title: Genetic variants of BMP15 and GDF9 genes and their association with litter size in Tibetan sheep

Article References: Zhang, L., Zhang, Y., Deng, Y., He, N., Sun, R., & Zhang, J. (2026). Genetic variants of BMP15 and GDF9 genes and their association with litter size in Tibetan sheep. Frontiers in Animal Science, 7, Article 1904014. https://doi.org/10.3389/fanim.2026.1904014

Image Credits: AI Generated

DOI: 10.3389/fanim.2026.1904014

Keywords: Genetic, variants, BMP15, GDF9, genes, association, litter, size, Tibetan, sheep, scientific research

Triaptosis is a newly characterized modality of programmed cell death that depends on endosomal function, distinguishing it from apoptosis, necroptosis, and other better-known death pathways. Because triaptosis relies on the lipid kinase VPS34 and endosome-mediated signaling, it intersects with autophagy and endocytosis machinery that tumors frequently co-opt for survival. Its implications for cancer prognosis, however, remained unclear prior to this work.

The research team, led by Xirong Cui and Mao Liu of Neijiang First People’s Hospital, analyzed bulk transcriptomic and clinical data from the TCGA-STAD cohort and the GSE62254 gastric cancer dataset, alongside single-cell RNA sequencing data from GSE183904. They calculated triaptosis-related gene (TRG) scores for each tumor sample using single-sample gene set enrichment analysis, then identified differentially expressed genes between high- and low-TRG-score tumors and between tumor and normal tissue. These candidate genes underwent functional enrichment analysis, Cox proportional hazards regression, and least absolute shrinkage and selection operator (LASSO) regression to construct a prognostic signature that was externally validated in an independent cohort.

The resulting model comprises three genes: ASPN, GRB14, and VTN. ASPN encodes asporin, an extracellular matrix protein previously linked to gastric cancer invasion, migration, and macrophage M2 polarization. GRB14 is an adaptor protein that regulates insulin and growth factor signaling and has been implicated in gastric cancer progression through the PI3K/AKT pathway. VTN encodes vitronectin, a glycoprotein of the extracellular matrix whose overexpression correlates with impaired survival in gastric cancer patients. All three genes showed significantly higher mRNA expression and protein levels in the SGC-7901 gastric cancer cell line than in the non-malignant GES-1 gastric epithelial cell line, verified by reverse transcription-quantitative PCR and Western blotting.

When patients were stratified by the TRG-based risk score, two groups emerged with notably different survival outcomes. High-risk patients exhibited higher stromal scores and distinct immune profiles compared with low-risk patients, with fifteen immune cell types differing significantly between the two groups. The researchers also compared pathway activity, somatic mutation landscapes, tumor mutational burden, and predicted drug sensitivity across risk groups, finding that the signature captured biologically meaningful differences beyond survival statistics alone.

Single-cell RNA sequencing analysis added a cellular dimension to the findings. Fibroblasts and pericytes emerged among the cell types with the highest TRG activity, and the three prognostic genes were significantly overexpressed in fibroblasts. Cell-cell communication analysis revealed that fibroblasts showed enhanced signaling with pericytes in the gastric cancer microenvironment, whereas tumor-derived fibroblasts displayed weaker communication with macrophages, suggesting immune microenvironment remodeling associated with triaptosis activity.

The concentration of the prognostic signal in fibroblasts is particularly intriguing given growing evidence that cancer-associated fibroblasts drive gastric cancer progression, angiogenesis, metastasis, and immunosuppression. Prior work has shown that collagen-rich extracellular matrix produced by these fibroblasts can promote immune evasion through IL4I1-AHR signaling, and that fibroblast heterogeneity shapes the immunosuppressive microenvironment that limits responses to immunotherapy. The new findings suggest that triaptosis-related gene activity in fibroblasts may be a previously unrecognized component of this stromal contribution to prognosis.

The study’s methodology reflects a broader trend in computational oncology: integrating bulk and single-cell transcriptomics with machine learning approaches to extract clinically actionable signatures from public datasets. Similar triaptosis-focused models have recently been constructed for melanoma and hepatocellular carcinoma, indicating that the cancer research community is rapidly probing this novel cell death modality across tumor types. The gastric cancer study distinguishes itself by combining external validation with experimental verification at both the mRNA and protein levels in cell lines.

The authors suggest that the three-gene signature holds potential value for risk stratification and personalized treatment planning in gastric cancer. Because the signature is associated with distinct immune and genomic features, it may eventually help identify patients who could benefit from specific therapeutic strategies, including immunotherapy approaches tailored to the immune microenvironment characteristics of high-risk tumors. The findings also open questions about whether triaptosis pathways in stromal cells could be therapeutically targeted to modify the tumor microenvironment.

Limitations remain, as the signature was developed and validated in retrospective cohorts rather than prospectively, and the experimental verification was confined to cell lines rather than patient tissue. Nonetheless, the study provides a technically rigorous exploration of triaptosis in gastric cancer, linking a novel cell death modality to a stromal-cell-centered prognostic framework. As triaptosis research matures, studies like this one may help clarify whether endosome-dependent cell death pathways represent the next frontier in cancer prognosis and therapy development.

Subject of Research: Exploration and experimental verification of triaptosis-related prognostic genes and cells in gastric cancer

Article Title: Exploration and experimental verification of triaptosis-related prognostic genes and cells in gastric cancer

Article References: Cui, X., Qiu, H., Zhang, H., Xu, H., & Liu, M. (2026). Exploration and experimental verification of triaptosis-related prognostic genes and cells in gastric cancer. Molecular Biology Reports, 53(1), Article 1541. https://doi.org/10.1007/s11033-026-12704-y

Image Credits: AI Generated

DOI: 10.1007/s11033-026-12704-y

Keywords: Exploration, experimental, verification, triaptosis-related, prognostic, genes, cells, gastric, cancer, scientific research

The original study, published in December 2022 by researchers at Mashhad University of Medical Sciences in Iran and Amsterdam University Medical Centers in the Netherlands, had proposed a mechanistic link between TWIST1, a well-known developmental transcription factor, and the activation of cancer stem cell marker genes in esophageal cancer cells. The paper argued that TWIST1 promotes epithelial-mesenchymal transition, a biological program in which epithelial cells lose their polarity and adhesion properties and acquire invasive, mesenchymal characteristics, thereby fueling tumorigenesis in esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma is the most common form of esophageal cancer globally and remains one of the most aggressive solid tumors, with five-year survival rates often below 20 percent in many regions. The disease is particularly prevalent in parts of Asia, including the so-called esophageal cancer belt stretching from northern Iran through Central Asia to China, which is precisely where the research team was based. Understanding the molecular drivers of this cancer has been a major research priority, and TWIST1 had long been suspected of playing a central role in the epithelial-mesenchymal transition that allows esophageal cancer cells to invade surrounding tissue and metastasize to distant organs.

The retraction note, published by the editors of BMC Cancer, states that after the original publication, concerns were raised about similarities between several microscopy images presented in Figure 4 of the paper. Specifically, the editors noted that GFP-labeled YM-1 cells shown in panels 4B, 4D, and 4H were similar to GFP-labeled KYSE-30 cells shown in panel 4E. Additional similarities were noted between panels 4C and 4I, both showing GFP-labeled KYSE-30 cells, and between panels 4F and 4J, showing GFP-labeled YM-1 cells, and panel 4G, showing GFP-labeled KYSE-30 cells. Further concerns involved panel 4C, showing GFP plus TWIST1-transfected KYSE-30 cells, and panel 4D, showing GFP-labeled YM-1 cells at low magnification, as well as panels 4C, 4E, and 4G, showing GFP plus TWIST1-transfected KYSE-30 cells, and panel 4H, showing GFP-labeled YM-1 cells at medium magnification.

These image overlaps are significant because Figure 4 of the original paper was central to the study’s core claims about how TWIST1 affects cancer stem cell populations in esophageal cancer cells. The figure apparently presented fluorescence microscopy images of two different esophageal cancer cell lines, YM-1 and KYSE-30, some of which had been engineered to overexpress TWIST1. The purpose of these experiments was to demonstrate that forcing TWIST1 expression into esophageal cancer cells increases the population of cells expressing cancer stem cell markers, which are thought to be responsible for tumor initiation, resistance to chemotherapy, and relapse after treatment.

The retraction note makes clear that the authors did not respond to these concerns when raised by the editors. The editors state that they have therefore lost confidence in the data and conclusions of the article. Four of the authors named in the retraction note, Sima Ardalan Khales, Sina Mozaffari-Jovin, Dirk Geerts, and Mohammad Reza Abbaszadegan, did not respond to correspondence from the publisher about the retraction itself. The retraction note does not indicate whether any of the authors disputed the concerns or provided any explanation for the image similarities.

The original paper had been published as an open access article in BMC Cancer, a peer-reviewed journal that publishes research across all aspects of cancer research. The study had been cited by other researchers working on TWIST1, epithelial-mesenchymal transition, and cancer stem cells in esophageal cancer, meaning the retraction could affect how other groups interpret their own findings in this area. The retraction note does not state how many citations the paper received or whether any citing papers have been affected.

The retraction highlights a persistent challenge in cancer biology research, where fluorescence microscopy images are frequently used to demonstrate changes in cell populations, and where image duplication can be difficult to detect without sophisticated forensic analysis. In recent years, journals have increasingly turned to automated image integrity screening tools that can flag duplicated or manipulated images before or after publication. The concerns in this case were apparently raised after publication, and the fact that the authors did not respond to the editors’ queries meant the journal had no way to resolve the issues through clarification, correction, or author explanation.

Esophageal squamous cell carcinoma research has been particularly active in recent years, with multiple groups investigating the role of transcription factors like TWIST1, SNAIL, and ZEB1 in driving epithelial-mesenchymal transition and cancer stem cell properties. The retraction of this paper does not necessarily invalidate the broader hypothesis that TWIST1 plays a role in esophageal cancer progression, as other independent studies have examined similar mechanisms. However, the retraction does remove one specific piece of evidence from the literature, and researchers citing the original paper will now need to note that its data and conclusions have been formally withdrawn.

The retraction note, published in September 2026 as volume 26, article number 1090 of BMC Cancer, is available as an open access document under a Creative Commons license. The original article, published in December 2022 as volume 22, article number 1272, remains accessible online but is now clearly marked as retracted. The retraction note does not indicate whether any institutional investigation was conducted or whether any of the authors face further consequences. The editors of BMC Cancer have not issued any additional statements about the case beyond the formal retraction note.

Subject of Research: Retraction Note: TWIST1 activates cancer stem cell marker genes to promote epithelial‑mesenchymal transition and tumorigenesis in esophageal squamous cell carcinoma

Article Title: Retraction Note: TWIST1 activates cancer stem cell marker genes to promote epithelial‑mesenchymal transition and tumorigenesis in esophageal squamous cell carcinoma

Article References: Khales, S. A., Mozaffari‑Jovin, S., Geerts, D., & Abbaszadegan, M. R. (2026). Retraction Note: TWIST1 activates cancer stem cell marker genes to promote epithelial‑mesenchymal transition and tumorigenesis in esophageal squamous cell carcinoma. BMC Cancer, 26(1), Article 1090. https://doi.org/10.1186/s12885-026-16871-w

Image Credits: AI Generated

DOI: 10.1186/s12885-026-16871-w

Keywords: Retraction, Note, TWIST1, activates, cancer, stem, cell, marker, genes, promote, epithelial, mesenchymal

The core problem the team set out to address is one of the most quietly consequential issues in clinical genomics: ancestry bias. Many widely used computational tools for predicting whether a genetic variant is harmful are trained on clinical databases and population datasets that heavily under-represent global diversity. European populations dominate these resources, so the statistical patterns the tools learn reflect the variants and genetic backgrounds of European-ancestry individuals. When the same tools are applied to variants found in African, East Asian, South Asian, Latino, or Middle Eastern populations, their predictions can become unreliable — and, in a clinical setting, that unreliability translates directly into uneven diagnostic outcomes. A variant might be confidently classified as benign in one population and left indeterminate, or worse, misclassified, in another.

Bora and colleagues turned to two families of methods that are, by design, free of this ancestry bias. The first is experimental: multiplexed assays of variant effect, or MAVEs. These are high-throughput laboratory techniques that measure the functional consequence of thousands of variants simultaneously, typically by synthesising all possible mutations in a gene region and scoring how each one affects protein function or abundance in a pooled cell population. Methods such as variant abundance by massively parallel sequencing (VAMP-seq) quantify how stable each variant protein is inside cells, while deep mutational scanning approaches measure effects on activity or interaction. Because MAVEs measure function directly, their evidence does not depend on which human populations have been sequenced or clinically characterised.

The second family is computational: population-free variant effect predictors, or VEPs. The team focused on three leading examples — GEMME, EVE, and CPT-1. These tools infer the likely impact of a variant without relying on human clinical datasets. GEMME works by tracing the evolutionary conservation of each position and substitution across thousands of homologous protein sequences, reasoning that positions and amino acid changes conserved through evolution are less tolerant to mutation. EVE takes a different route, using a statistical model — a variational inference approach — trained on the vast evolutionary record contained in protein sequence families to estimate how likely a given amino acid is at a given position. CPT-1 incorporates structural biophysics, estimating the change in the Gibbs free energy (ΔΔG) that a variant induces in the folded protein, a quantity that reflects how strongly the mutation destabilises the protein’s three-dimensional structure. All three draw on evolutionary and physical principles rather than on human population data, making them inherently unbiased with respect to ancestry.

The study evaluated MAVE- and VEP-based classification across five cancer-associated genes for which high-quality MAVE datasets exist. The genes include well-known hereditary cancer players such as PTEN, a tumour suppressor whose loss predisposes carriers to breast, thyroid, and endometrial cancers, and TP53, the guardian of the genome, mutated in Li-Fraumeni syndrome. The team calibrated the experimental and computational evidence to the ACMG/AMP guidelines — the framework issued by the American College of Medical Genetics and Genomics and the Association for Molecular Pathology that clinicians worldwide use to combine evidence into five-tier variant classifications ranging from benign to pathogenic. This calibration step is technically demanding: it requires translating raw assay scores or predictor outputs into the standardised evidence strengths (strong, moderate, supporting, and so on) that the guidelines accept.

The results reveal a nuanced division of labour between the two approaches. MAVEs proved to be more conservative and more decisive classifiers. They assigned fewer variants to the pathogenic category, but they also produced fewer indeterminate classifications — meaning that when a MAVE does speak, it tends to speak clearly. The assays showed heightened sensitivity in the regions that had actually been functionally assayed, which makes sense: within the windows of the gene that the experiment covers, the direct measurement of function is the most reliable evidence available. VEPs, by contrast, identified a broader range of pathogenic variants overall, because they can score every variant in the protein, not just those covered by the assay. Each approach, in other words, has blind spots the other can fill.

The headline finding is what happens when the two are combined. By merging the clinical evidence strengths derived from MAVEs and from VEPs, the team reclassified over 90 percent of variants of uncertain significance across two reference datasets — the SG10K_Health cohort from Singapore’s National Precision Medicine programme, which includes Chinese, Malay, Indian, and other Southeast Asian ancestries, and the Mexico City Prospective Study, which captures Latino and admixed American populations. That figure is remarkable: nine out of ten variants that would otherwise sit in diagnostic limbo were moved to at least likely benign or likely pathogenic. For a patient carrying one of these variants, the difference between a VUS and a likely benign result can be the difference between indefinite anxiety and a clear answer.

The team also isolated variants where the MAVE-based and VEP-based classifications disagreed, and these discordances are technically informative. They highlight method-specific limitations: a MAVE may miss variants whose effects are context-dependent or outside the assayed region, while a VEP may misjudge variants in positions where evolutionary conservation is a poor guide to human disease relevance, or where structural destabilisation does not translate into loss of function. Understanding where and why the two approaches diverge is essential for building robust combined classifiers — and for knowing when a single line of evidence should be trusted.

The broader significance of the work lies in its implications for equity in clinical genomics. Under-represented populations have long borne the brunt of the VUS problem: because most clinical variant databases are European-dominated, variants in non-European patients are more likely to be left unclassified, delaying diagnosis and preventive care. By drawing on evidence sources that are ancestry-blind by construction — direct functional measurement and evolutionary or biophysical inference — the combined MAVE-plus-VEP framework offers a path to variant interpretation that generalises across populations. The authors suggest this could help mitigate disparities in hereditary cancer diagnosis across ancestries, a goal that becomes increasingly urgent as genome sequencing expands globally.

There are, of course, practical hurdles ahead. High-quality MAVE datasets exist for only a fraction of clinically relevant genes, and scaling the assays to the full exome remains a formidable experimental challenge. The calibration of assay scores and predictor outputs to ACMG/AMP evidence strengths must be standardised and validated across laboratories before widespread clinical adoption. But the study demonstrates the principle clearly: experimental and computational evidence, each ancestry-unbiased, each with complementary strengths, can be combined to resolve the vast majority of uncertain variants in hereditary cancer genes. As genome medicine matures, this kind of evidence integration may become the standard by which the promise of precision oncology is extended — fairly — to everyone.

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Subject of Research: Combining MAVEs and computational predictors improves variant classification across ancestries in hereditary cancer genes

Article Title: Combining MAVEs and computational predictors improves variant classification across ancestries in hereditary cancer genes

Article References: Bora, N., Badonyi, M., Pathak, A. K., Manisekaran, R. G., Marsh, J. A., Ngeow, J., & SG10K_Health Consortium (2026). Combining MAVEs and computational predictors improves variant classification across ancestries in hereditary cancer genes. Genome Medicine. https://doi.org/10.1186/s13073-026-01799-4

Image Credits: AI Generated

DOI: 10.1186/s13073-026-01799-4

Keywords: Combining, MAVEs, computational, predictors, improves, variant, classification, across, ancestries, hereditary, cancer, genes

Olfactory receptors are the molecular gatekeepers of smell. Expressed in the olfactory epithelium of the nasal cavity, these G protein-coupled receptors each carry seven alpha-helical transmembrane domains and span roughly 310 amino acids. When odorant molecules drift into the nose, they bind to these receptors in a combinatorial fashion: a single odorant can activate multiple receptors, and each receptor can respond to several odorants. The brain then reads the resulting pattern of neural activity as a unique odor code, allowing animals to distinguish an enormous range of chemical cues in their environment—from the scent of ripe fruit to the chemical signature of an approaching predator.

The size of this receptor repertoire varies enormously across mammals, and those differences often track ecological niches. The African elephant holds the record with nearly 2,000 putatively functional olfactory receptor genes, while cetaceans—the whales and dolphins—retain only a few dozen. During the evolutionary transition from land to water, marine mammals lost vast numbers of these genes, and toothed whales compensated by evolving echolocation. The platypus, with roughly 350 functional receptors, traded olfaction for electroreception in its semi-aquatic lifestyle. Primates, including humans, also experienced accelerated olfactory gene loss, likely tied to their greater reliance on vision and, in some lineages, a dietary shift from fruit foraging to leaf eating.

But the giant panda is a terrestrial mammal that never left the land. So why would its olfactory genome look degraded? The research team, led by Liwen Kang of China, hypothesized that habitat, dietary specialization, and habitat breadth are the key drivers of olfactory receptor evolution within Carnivora—the order that includes cats, dogs, bears, seals, and civets. Their prediction was straightforward: species with narrow ecological niches and specialized diets, whether marine carnivorans or bamboo-eating pandas, should possess fewer intact olfactory receptor genes and a higher proportion of pseudogenes compared with generalist terrestrial carnivorans.

To test this, the researchers annotated olfactory receptor genes from the whole-genome sequences of 25 carnivoran mammals spanning nine families, from big cats like the leopard and tiger to pinnipeds like the ringed seal and Steller sea lion. Using the Genome2OR pipeline—an automated annotation tool that outperforms older methods and maps 92.3 to 99.4 percent of its sequences to the curated HORDE database—they identified a total of 20,685 intact olfactory receptor genes. The results were unambiguous: marine carnivorans carried only 333 to 367 intact genes, while terrestrial carnivorans carried 702 to 1,393. The proportion of pseudogenes—genes rendered nonfunctional by frameshift mutations, premature stop codons, or severe structural disruptions—was significantly higher in marine species, ranging from 49.31 to 59.82 percent, compared with 24.15 to 49.75 percent in terrestrial ones.

The giant panda stood out immediately. Among terrestrial carnivorans, it possessed the lowest number of intact olfactory receptor genes at 702—considerably fewer than other bear species, which ranged from 813 to 1,276. Its pseudogene proportion was exceptionally high at 49.75 percent, reaching levels comparable to fully marine carnivorans. This finding challenges a previous study of 23 mammalian species that included the panda but reported no evidence of olfactory degeneration. The discrepancy likely stems from differences in genome assembly versions and annotation pipelines: earlier studies reported 611, 645, or even 408 functional genes for the panda depending on the method used, while the current work, with updated chromosome-level assemblies and standardized full-length prediction algorithms, recovered 702.

To trace the evolutionary history of these genes, the researchers organized all intact genes into 374 orthologous gene groups—clusters of genes descended from a single ancestral gene in the carnivoran common ancestor. Most groups contained relatively few genes, but the number of intact genes per group varied considerably among species. In one large group, the American black bear carried 124 intact genes while the ringed seal carried only 16. Marine carnivorans had significantly fewer orthologous groups overall, ranging from 190 to 200, compared with 259 to 333 in terrestrial species. The giant panda had the fewest among terrestrial carnivorans at 259.

Phylogenetic reconstruction revealed that every one of the 25 species has lost dozens to more than one hundred complete olfactory receptor genes that were present in their most recent common ancestor. Marine carnivorans lost far more ancestral groups—174 to 184—than terrestrial carnivorans, which lost 41 to 115. The giant panda lost the largest number among terrestrial carnivorans at 115 ancestral groups. Meanwhile, selective pressure analysis showed that all carnivorans operate under purifying selection, with omega values below 1, meaning deleterious mutations are still preferentially eliminated. But the intensity of that selection varied: orthologous groups from marine carnivorans and the giant panda consistently displayed elevated omega values relative to other terrestrial carnivorans, indicating relaxed purifying selection and accelerated accumulation of loss-of-function variants.

To identify the ecological factors driving these patterns, the researchers constructed generalized linear models quantifying the independent effects of habitat type, diet type, and habitat breadth on olfactory receptor copy number, pseudogene proportion, and selective pressure. For intact gene counts, habitat type was the primary predictor: terrestrial species averaged 1.79 times more intact genes than aquatic species, and generalist diets conferred an additional 1.54-fold advantage. For pseudogene proportion, diet type dominated—generalist species had an odds ratio of only 45.2 percent relative to specialists, meaning they were far less likely to carry nonfunctional receptor genes. Habitat breadth showed no significant effect on gene counts but was positively correlated with pseudogene proportion.

The convergent loss of olfactory receptor genes in marine carnivorans likely reflects their aquatic sensory environment, where most environmental odorants are unavailable and olfactory cues carry little survival value. In the giant panda, the researchers argue, the driving factors are different but equally powerful: pandas inhabit forests overwhelmingly covered by bamboo, where diverse environmental odorants are less critical for survival, and their nearly exclusive bamboo diet creates a stable, uniform food resource that lowers the ecological demand for broad-spectrum odor detection. Together, these factors weaken the purifying selection that normally maintains full olfactory sensitivity, allowing disruptive mutations to accumulate and pseudogenes to proliferate.

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Subject of Research: Genetics

Article Title: Similar degenerative patterns of olfactory receptor genes in the giant panda and marine carnivores

Article References: Kang, L., Chen, J., Hong, M., Wei, W., Xiang, Z., & Zhang, Z. (2026). Similar degenerative patterns of olfactory receptor genes in the giant panda and marine carnivores. iScience, 29(11), Article 117936. https://doi.org/10.1016/j.isci.2026.117936

Image Credits: AI Generated

DOI: 10.1016/j.isci.2026.117936

Keywords: Similar, degenerative, patterns, olfactory, receptor, genes, giant, panda, marine, carnivores, scientific research

The tool, called ParaDISM — short for Paralog Disambiguating Mapper — refines standard alignments rather than replacing them. The core idea is to use a multiple sequence alignment of the reference sequences themselves to identify disambiguating positions: spots in the alignment where the highly homologous copies actually differ. A read or read pair is assigned to a particular gene copy only when the read carries sequence-specific evidence that unambiguously supports that copy. Reads that lack sufficient evidence for a gene of origin are reported as unassigned. This conservative strategy deliberately prioritizes specificity and precision — the positive predictive value of read placement — over sensitivity, accepting that some reads will go unplaced rather than risk placing them wrongly.

Why does this trade-off matter? In short-read high-throughput sequencing, the reads are so short that highly similar genomic copies create genuine ambiguity. Standard mappers such as Bowtie2, BWA-MEM2 and minimap2 use sophisticated scoring schemes to pick the best match, but when several locations tie, the choice is essentially arbitrary. Reads placed on the wrong paralog can carry variants from one gene copy into another, generating false positive variant calls. Those false positives can propagate through pipelines and, in clinical contexts, can lead researchers and clinicians to chase mutations that do not actually exist. ParaDISM attacks the problem at the alignment stage, before variant calling, by demanding stronger evidence before committing a read to a location.

The pipeline’s technical workflow is straightforward in concept. First, it takes the reference sequences for a region of interest — for example, a gene and its paralogs or pseudogene copies — and builds a multiple sequence alignment among them. From that alignment, it extracts the positions where the copies differ, the disambiguating positions. Then it examines each read: if the read spans or contains bases that match the sequence-specific pattern of one copy and contradict the patterns of the others, the read is confidently assigned to that copy. If the read’s evidence is insufficient — because it covers only regions where all copies are identical, for instance — it is left unassigned. The output is a refined BAM file, the standard Binary Alignment/Map format, so ParaDISM can slot into existing pipelines as a precision-focused add-on before the variant calling step.

An optional iterative refinement procedure addresses the sensitivity cost of the stringent placement criteria. In the first pass, ParaDISM calls variants from the confidently assigned reads. It then updates the reference sequences to incorporate sample-specific evidence — effectively personalizing the reference to the individual’s own variants — and re-processes the remaining unassigned reads. This gives the pipeline a second chance to place reads that were ambiguous against the generic reference but become unambiguous once the sample’s own sequence is known. The iterative loop mitigates the loss of sensitivity caused by the strict criteria for read placement while preserving the precision gains.

How well does it work? The team evaluated ParaDISM using extensive computational simulation experiments and the Genome in a Bottle HG002 benchmark, a widely used reference sample from the National Institute of Standards and Technology with a well-characterized genome. Performance was assessed both in terms of read alignment and the resulting short variant calls. Compared with Bowtie2, BWA-MEM2 and minimap2, ParaDISM reduced the number of misalignment artifacts, thereby increasing the specificity and precision of subsequent single nucleotide variant calls in highly homologous regions. The tool does not claim to outperform standard mappers everywhere; rather, it refines their output in the specific genomic contexts where homology makes their placements unreliable.

The researchers applied ParaDISM to two real-world case studies. The first involved five public tumour exomes at the GNAQ/GNAQP1 locus. GNAQ is a gene implicated in cancers including natural killer/T-cell lymphoma, and GNAQP1 is a pseudogene copy whose sequence similarity complicates variant interpretation. The second case study involved 18 short-read sequencing datasets from patients diagnosed with autosomal dominant polycystic kidney disease — 15 exomes and 3 targeted panel sequencing datasets. Autosomal dominant polycystic kidney disease is caused by variants in genes such as PKD1, which has a highly homologous pseudogene, making variant calling in this region notoriously difficult with short reads. ParaDISM was used to reanalyze these datasets, providing a stronger level of evidence for variants called in the homologous regions.

The clinical logic behind ParaDISM’s design is worth emphasizing. In applications where false positive variant calls have more severe consequences than false negative ones — such as identifying causal mutations for genetic disorders — a precision-focused tool is exactly what is needed. Missing a genuine variant is unfortunate, but reporting a variant that does not exist can trigger unnecessary follow-up, unnecessary wet-lab confirmation experiments, or even incorrect clinical conclusions. Where experimental confirmation of shortlisted variants is necessary, ParaDISM can be used to prioritize variants with strong support, reducing the cost and effort spent attempting to confirm false positive calls. The pipeline can also be run alongside the results of standard mappers to cross-check results and identify unreliable read placement and variants potentially caused by misalignment artifacts.

ParaDISM is open source, available under the MIT license at github.com/BioGeMT/ParaDISM, and its developers describe it as a refinement layer for BAM files rather than a replacement for standard mappers. The work emerged from a Maltese research collaboration spanning the Department of Applied Biomedical Science and the Centre for Molecular Medicine and BioBanking at the University of Malta, with funding from the Malta NGS project, the Genomics of Rare Diseases Project, and several European Union Horizon Europe programmes including Marie Skłodowska-Curie grants. The ADPKD study was approved by the University of Malta Research Ethics Committee, and written informed consent was obtained from all participants.

For the broader genomics community, ParaDISM represents a pragmatic response to a persistent technical challenge. As short-read sequencing remains the workhorse of clinical exome sequencing, panel sequencing and tumour genomics, genes with highly homologous copies will continue to generate ambiguous reads and unreliable variant calls. Tools that explicitly quantify and demand evidence for read placement — rather than silently accepting arbitrary choices among equally good matches — offer a path toward more trustworthy variant interpretation in these difficult regions. By refining alignments before variant calling and reporting unassigned reads transparently, ParaDISM gives analysts a clearer picture of where the evidence is strong and where it is not, and it invites pipelines to treat homologous regions with the caution they deserve.

Subject of Research: ParaDISM: precise mapping of short reads to genes with highly homologous regions

Article Title: ParaDISM: precise mapping of short reads to genes with highly homologous regions

Article References: Tzimotoudis, D., Farrugia, R., Zammit, J., Cini Masini, M., Balestrucci, A., Borg Carbott, F., Bezzina Wettinger, S., Alexiou, P., & Ciach, M. A. (2026). ParaDISM: precise mapping of short reads to genes with highly homologous regions. BMC Bioinformatics. https://doi.org/10.1186/s12859-026-06701-y

Image Credits: AI Generated

DOI: 10.1186/s12859-026-06701-y

Keywords: ParaDISM, precise, mapping, short, reads, genes, highly, homologous, regions, scientific research

Transposable elements constitute a major component of vertebrate genomes. In humans they occupy nearly half of the DNA, and in fish the fraction can be similarly substantial, varying widely among lineages. For decades these repeats were dismissed as junk DNA, but modern genomics has recast them as major players in evolution. By inserting into new sites and promoting recombination between repeat copies, they can drive gene innovation and chromosomal rearrangements. Yet this creative capacity carries a cost. Unrestrained transposable element activity can compromise genomic integrity, and in mammals persistent activation of these elements has been linked to inflammatory and carcinogenic pathways, including chronic inflammation, cancer progression and autoimmune disease. The vertebrate body therefore deploys two key restraining mechanisms: epigenetic control, which chemically silences the repeats, and immune surveillance, which detects their transcripts as molecular signatures of danger.

Teleost fish, the most diverse group of bony vertebrates, represent an early vertebrate lineage in which the immune architecture is largely conserved relative to mammals. They possess inflammatory molecules, cell-surface and signalling receptors, and antiviral genes that mirror their mammalian counterparts. What has remained largely unexplored until now is the relationship between the mobile DNA fraction of fish genomes and this immune machinery. Fish transposable elements have been catalogued in individual species, and databases such as FishTEDB now consolidate consensus sequences, but a systematic interrogation of their overlap with immune genes across the ray-finned fishes had never been attempted on this scale.

To close that gap, the researchers combined a PRISMA-based systematic literature review with an extensive BLASTn screening. They took transposable element consensus sequences from FishTEDB and searched them against GenBank entries for Actinopterygii, the ray-finned fishes, looking for sequence matches that landed within immune-related loci. The computational strategy was complemented by EggNOG annotation and enrichment analysis, which assigns genes to orthologous groups and functional categories, allowing the team to test whether transposable element-gene associations were overrepresented in immune-related functional classes rather than distributed randomly across the genome.

The results were unambiguous. The screening revealed frequent transposable element sequence matches to immune-related loci across teleost species, touching inflammatory molecules, cell-surface and signalling receptors, and antiviral genes. The EggNOG functional profiling, performed across eight teleost species, supported a recurrent association between transposable element sequences and immune-related annotations. Most tellingly, the enrichment analysis found significant enrichment of immune-related transposable element-gene associations in six of the eight species analysed. In other words, in the majority of the fish genomes examined, the mobile DNA sequences were not scattered uniformly across all gene classes but clustered disproportionately around genes that the immune system uses.

The biological significance of this clustering remains an open question, and the authors are careful to frame it as such. Transposable element insertions near immune genes could be functionally neutral, a by-product of how repeats accumulate in certain chromosomal contexts. Alternatively, they could reflect genuine regulatory interplay. In mammals, transposable element-derived sequences have been domesticated as regulatory elements that instruct the immune system, contributing promoters and enhancers to interferon genes and other immune loci. The new review situates fish within this broader vertebrate picture, discussing the possible regulatory mechanisms by which fish transposable elements might influence immune gene expression, and the epigenetic context, including DNA methylation, that normally keeps their activity in check.

Experimental evidence from fish models already hints that this interplay is real. In zebrafish embryos, loss of DNA methylation activates retrotransposons and triggers antiviral signalling, a phenomenon known as viral mimicry, in which the cell responds to derepressed endogenous repeats as if they were invading pathogens. Similar viral mimicry responses have been documented in mammalian cancer cells treated with DNA-demethylating agents. In the gilthead seabream, carrageenin-induced inflammation has been shown to modulate transposable element expression in skin and brain tissue, directly linking an inflammatory stimulus to mobile element activity in a farmed fish species. Environmental factors also matter: retrotransposon methylation and activity in wild European eels vary with body size, and the Rex3 retroelement in teleosts shows an intriguing relationship with environmental temperature.

The review also maps the diversity of transposable elements in fish genomes, which spans retrotransposons, DNA transposons and endogenous retroviruses, some of which are relics of past infections that have been repurposed as evolutionary innovations. Fish genomes have repeatedly captured and mobilized host genes through elements such as Helitron transposons, and piggyBac-like transposons have been found fused with herpesviruses in teleosts, illustrating the porous boundary between mobile elements and viral genomes. Horizontal transfer of transposons between vertebrate lineages adds another layer of dynamism to this genomic ecosystem, meaning that the mobile DNA repertoire of any fish species is shaped not only by vertical inheritance but also by cross-species invasion.

Looking forward, the authors outline future directions that integrate transposable element annotation with genomic mapping, epigenetic analyses, transposable element transcription and immune gene expression. Such integrative approaches would clarify whether the observed transposable element-immune associations have regulatory consequences for fish health, disease resistance and stress responses. The stakes extend beyond basic biology. Aquaculture is a rapidly growing food sector in which immune regulation, welfare and disease control are central concerns, and farmed fish face inflammatory challenges from pathogens, parasites and environmental stressors. If transposable elements turn out to be embedded in the regulatory architecture of fish immune genes, they could become targets for selective breeding, epigenetic intervention or genome editing aimed at improving disease resistance in farmed species.

Overall, the study provides a comprehensive perspective on the intricate relationship between transposable elements, epigenetic regulation and immune system dynamics in teleost fish, and argues for their inclusion in future studies of fish immune regulation, health and aquaculture. What was once dismissed as genomic junk is emerging, in fish as in mammals, as a potential instructor of the immune system, and the bony fishes, with their conserved immune architecture and rich mobile element diversity, now offer a comparative vantage point from which the deep evolutionary history of this genomic dialogue can finally be read.

Subject of Research: Genetics

Article Title: Transposable elements, immune-related genes and epigenetic context in teleost fish: insights from a systematic review and in silico analysis

Article References: Campos-Sánchez, J. C., & Ortega-Villaizan, M. D. M. (2026). Transposable elements, immune-related genes and epigenetic context in teleost fish: insights from a systematic review and in silico analysis. Heredity. https://doi.org/10.1038/s41437-026-00893-y

Image Credits: AI Generated

DOI: 10.1038/s41437-026-00893-y

Keywords: transposable elements, teleost fish, immune system, epigenetics, genomics, aquaculture, viral mimicry, Heredity, Transposable, elements, immune-related, genes

Because ducks live in direct contact with their litter, a fecal-oral transmission route is established that raises the risk of enteritis, viral hepatitis, and parasitic disease. Standard practice calls for thorough litter removal and replacement after each flock, followed by stringent washing, disinfection, and resting of the housing. But rising costs and limited availability of litter materials mean many farmers simply sun-dry and till the existing litter between batches, a shortcut that produces frequent disease outbreaks, heavier antibiotic use, and reduced farming efficiency, particularly in southern China. Against this backdrop, a team of researchers from Fujian Agriculture and Forestry University and the Fujian Academy of Agricultural Sciences set out to test whether a fermentation technology could attack the problem at its biological source, and their findings, published in Frontiers in Microbiomes, offer a detailed portrait of what happens to the viral and resistance-gene landscape of duck litter when high-temperature fermentation is applied.

The technology under investigation, known as compound microbial intelligent membrane high-temperature fermentation, integrates three components: a compound microbial agent, functional nano- and molecular membranes that cover the compost pile, and an intelligent control system that regulates the fermentation process. The microbial agent used in the study combined Bacillus subtilis, Bacillus licheniformis, Lactobactillus plantarum, and Saccharomyces cerevisiae at defined concentrations, applied at one kilogram per ton of litter material. The functional molecular membrane allows water vapor to evaporate while containing malodorous gases including ammonia and hydrogen sulfide, and the enclosed process prevents the leachate contamination of soil and groundwater that traditional open composting can cause through rainwater runoff. Bioheat generated by microbial fermentation maintains pile temperatures within a range of 80 to 85 degrees Celsius, hot enough to inactivate pathogens and weed seeds, and the entire process requires no turning or dedicated factory buildings, allowing one operator to manage multiple piles simultaneously.

To evaluate the technology’s impact, the researchers collected litter samples from four commercial duck farms in Fujian Province, five samples per farm for a total of twenty. Farm 1 employed deep-layer fermentation without prophylactic antibiotics, designated DL-D, with fermentation piles constructed to a height of 2.0 to 2.5 meters. Farm 2 used shallow-layer fermentation without prophylactic antibiotics, DL-S-NAF, with piles 0.8 to 1.2 meters high. Farm 3 was a conventional operation without fermentation or prophylactic antibiotics, DL-S, and Farm 4 was a conventional farm using prophylactic antibiotics without fermentation, DL-S-ANF. Piles were covered with the functional intelligent membrane and fermented for 15 to 18 days, with the intelligent control system maintaining aeration at 0.3 to 0.5 cubic meters per minute per ton of material and temperature monitored daily at three depths. Initial moisture content was adjusted to 55 to 65 percent.

The analytical approach, called metaviromics, involved extracting both DNA and RNA from the litter samples, enriching viral particles through sequential filtration and polyethylene glycol precipitation, and subjecting the resulting nucleic acids to high-throughput sequencing. Approximately 1.01 billion raw paired-end reads were generated from the twenty DNA virome samples, totaling roughly 151.5 gigabases. After quality filtering, host genome subtraction against the duck reference genome, and de novo assembly using MEGAHIT, the team screened contigs of at least 2,000 base pairs using DeepVirFinder, VirSorter2, VIBRANT, and the IMG/VR database, identifying 57,032 candidate viral sequences. Quality assessment with CheckV and removal of sequences classified as Not-determined left 23,130 viral sequences, which clustered at 95 percent average nucleotide identity over 85 percent alignment coverage into 18,321 viral operational taxonomic units, or vOTUs, with a combined length of 95.33 megabases.

The results revealed a clear structural pattern in the litter virome. DNA viral communities were dominated by the phyla Uroviricota and Nucleocytoviricota, with Caudoviricetes and Megaviricetes as the predominant classes, and their relative abundances remained remarkably stable across all four treatment groups, with Uroviricota accounting for roughly 94 to 95 percent of DNA viral reads in every group. RNA viral communities told a different story. Pisuviricota and Lenarviricota emerged as the dominant phyla, and their proportions fluctuated markedly among treatments: Pisuviricota reached 85.27 percent in the DL-S-NAF group but only 68.79 percent in the unfermented DL-S group, while Lenarviricota ranged from 13.75 percent in DL-S-NAF to 28.07 percent in DL-S. At the class level, Pisoniviricetes and Leviviricetes dominated the RNA viral assemblage, with Pisoniviricetes peaking at 82.17 percent in the shallow-layer fermentation group.

Crucially, the fermentation treatments significantly reduced RNA viral abundance, with a corresponding decreasing trend for DNA viruses. Alpha diversity analysis showed no significant differences in DNA viral richness or diversity among groups, suggesting high structural stability of the bacteriophage-dominated DNA communities, but the Shannon and Simpson indices for RNA viruses revealed significant differences between the unfermented DL-S group and both fermentation groups. Beta diversity analysis using non-metric multidimensional scaling and principal coordinates analysis confirmed significant differences in viral community structure across the experimental groups, with the first two principal coordinates accounting for 63.32 percent of DNA viral community variation and 55.39 percent of RNA viral community variation. The heightened sensitivity of RNA viruses is mechanistically attributable to the chemical lability of RNA under the alkaline pH generated by ammonia release during fermentation, coupled with lipolytic disruption of viral envelopes at elevated temperatures.

The resistome findings were equally striking. Total antibiotic resistance gene abundance followed a clear hierarchical trend of DL-D less than DL-S-NAF less than DL-S less than DL-S-ANF, indicating that antibiotic usage was the principal driver of ARG enrichment while fermentation was an effective method for their reduction. Fermentation treatments markedly decreased the loads of specific ARGs including sul1, sul2, tetB(P), and qacEdelta1, which confer resistance to sulfonamides and tetracyclines. The abundances of floR, aadA, qacEdelta1, tet(X), and cfr(A) in the three antibiotic-free groups were significantly lower than in the antibiotic-using farm group. Metal resistance genes including arsC, arsM, merA, copR, and corR showed a parallel reduction, with the overall MRG trend being DL-D less than DL-S-NAF less than DL-S-ANF less than DL-S. Biocide resistance genes including mdeA, actP, smdB, cpxA, and galE, and bacterial virulence factors including groEL2 and lirB, were similarly attenuated by the fermentation process.

A counterintuitive finding was the relatively high abundance of efflux pump mechanism genes such as TaeA, conferring pleuromutilin and tiamulin resistance, in the deep-layer fermentation group. The researchers suggest this may reflect adaptive mechanisms activated by microorganisms in response to metabolic stress such as organic acid accumulation within the fermentation environment, or alternatively that these efflux pumps serve dual physiological functions including metabolite export and pH homeostasis rather than mediating antibiotic resistance per se. The substrate promiscuity of MFS and RND-family efflux transporters, fulfilling ancestral roles in metabolite export under acidic fermentation conditions, offers a plausible explanation for this apparent outlier. Similarly, the opposing MRG trends between unfermented and fermented groups likely reflect redox-driven metal speciation shifts: oxidative dissolution in aerated shallow litter mobilizes bioavailable metals that select for MRG maintenance, whereas sulfidogenic conditions during thermophilic fermentation promote metal precipitation, alleviating this selective pressure.

An exploratory single-sample in-depth metavirome analysis, conducted on a representative DL-D sample because it exhibited the most distinct viral community profile and the lowest ARG abundance, identified 34 viral operational taxonomic units and 343 viral genes, of which 210 received functional annotation in at least one database. The viral community was dominated by Uroviricota members of the families Winoviridae, Salasmaviridae, Mesyanzhinovviridae, and Orlajensenviridae, with Nucleocytoviricota members including Mimiviridae also well-represented. KEGG pathway enrichment showed viral genes were predominantly associated with metabolism and genetic information processing, with translation-related functions constituting the largest category. The resistome analysis identified ARG subtypes including TaeA, Bado_rpoB_RIF, and aminocoumarin resistance genes, MRGs conferring resistance to arsenic, mercury, chromium, copper and zinc, and nickel and cobalt, BRGs associated with quaternary ammonium compounds, triclosan, hydrogen peroxide, and hydrochloric acid, and virulence factors involved in effector delivery, immune modulation, biofilm formation, exoenzyme production, and stress survival.

The co-enrichment of biocide resistance genes and virulence factors within the antibiotic-using farm group provides evidence for the prevalent co-occurrence of disinfectant resistance, antibiotic resistance, and virulence determinants in duck farming environments, driven by physical linkage of these determinants on class 1 integrons and conjugative plasmids that enable antibiotic-mediated co-selection to amplify resistance and virulence traits through genetic hitchhiking. This finding aligns with prior work on Riemerella anatipestifer, a major duck pathogen, in which isolates from Guizhou province harbored quaternary ammonium compound resistance genes while demonstrating severe multidrug resistance, and whole-genome studies reporting that over 90 percent of R. anatipestifer isolates carried tet(X). The detection of Riemerella phage vB_RanS_CRP19 in the litter virome suggests the viral community may harbor phages with potential biocontrol applications against this pathogen.

The study’s authors conclude that RNA viruses, particularly Pisuviricota, are sensitive bioindicators for ecological health assessment in litter environments, and that the antibiotic-free fermentation system represents a promising strategy for improving duck health and welfare while curbing the dissemination of antimicrobial resistance at its source in poultry production. The phylum Pisuviricota encompasses significant duck pathogens including Duck Tembusu virus, and its abundance patterns may reflect the interplay of sustained high temperatures and acidic conditions during fermentation that inhibit certain bacteria while providing competitive advantages to thermotolerant or acidophilic organisms and their associated viruses. The notable enrichment of Negarnaviricota, which includes influenza viruses, in the deep-layer fermentation group indicates that deep anaerobic environments may be more conducive to the persistence of such viruses, suggesting that fermentation design parameters matter.

Several limitations temper the conclusions. The sample size of five per group was relatively modest, potentially limiting statistical power to detect subtle differences in viral community composition. The cross-sectional design provides only a snapshot of the virome and resistome, and longitudinal studies are needed to understand temporal dynamics during fermentation. Functional validation through culture-based or in vitro experiments is warranted to confirm the biological significance of the identified resistance genes and virulence factors, and the study was conducted in a single geographic region, so generalizability to other climatic zones and farming systems requires further investigation. The mechanistic interpretations advanced, including thermal inactivation kinetics, host-community turnover, and redox-driven metal speciation, remain hypotheses warranting validation through time-course studies integrating metaviromic, metatranscriptomic, and metabolomic measurements.

Nevertheless, the work provides the first comprehensive metaviromic characterization of duck litter treated with compound microbial intelligent membrane fermentation, and its central message is clear: this technology effectively reduces viral abundance, particularly that of RNA viruses, and significantly decreases the loads of antibiotic resistance genes, metal resistance genes, biocide resistance genes, and virulence factors. In an era when antimicrobial resistance is recognized as one of the foremost threats to global health, interventions that curb the dissemination of resistance genes at their agricultural source carry significance well beyond the duck house. The finding that RNA viruses respond more sensitively to treatment than their DNA counterparts offers a practical monitoring tool, and the demonstration that an antibiotic-free fermentation system can attenuate the co-enrichment of resistance and virulence determinants points toward farming practices that protect both animal welfare and public health.

Subject of Research: Compound microbial intelligent membrane fermentation reshapes the virome and reduces various resistance genes in duck litter

Article Title: Compound microbial intelligent membrane fermentation reshapes the virome and reduces various resistance genes in duck litter

Article References: Sun, T., Mei, G., Mo, J., Li, M., Ma, Y., Zhao, M., Peng, S., Lin, F., Chen, J., Ma, Y., & Li, Z. (2026). Compound microbial intelligent membrane fermentation reshapes the virome and reduces various resistance genes in duck litter. Frontiers in Microbiomes, 5, Article 1897965. https://doi.org/10.3389/frmbi.2026.1897965

Image Credits: AI Generated

DOI: 10.3389/frmbi.2026.1897965

Keywords: Compound, microbial, intelligent, membrane, fermentation, reshapes, virome, reduces, various, resistance, genes, duck