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PubMed2025

Reproductive Isolation due to Divergent Ecological Selection Is Accompanied by Vast Genomic Instability in Experimentally Evolved Yeast Populations.

Populations evolving independently in divergent environments accumulate genetic differences and potentially evolve reproductive isolation as a by-product of divergence. The speed and mechanisms underlying this process are difficult to investigate because we rarely get the opportunity to witness them in natural settings, and histories of selection and gene flow between populations are often unknown. Here, we experimentally evolved yeast for 1000 generations of evolution in both divergent and parallel environments. At regular time points during experimental evolution, we made crosses between parallel- and divergent-evolving populations to measure postzygotic reproductive isolation (gamete viability). We used whole genome population sequencing to determine the mutational load, the number and types of structural variation, and other genomic features of the parent, F1 and F2 intraspecific hybrids. We found evidence for large-scale phenotypic and genome-wide differentiation in response to divergent laboratory selection. Divergent-selected populations produced hybrids with reduced gamete viability-a classic signature of postzygotic reproductive isolation in the form of hybrid breakdown. Parallel-selected populations, on the other hand, remained more reproductively compatible (with exceptions). We found that F2 hybrid genomes contained vast genomic instability, that is, new structural variants (especially insertions, deletions and interchromosomal translocations) that were not observed in parent and F1 genomes, which is likely a result of chromosome missegregation and recombination errors in hybrid meiosis. Our results provide phenotypic and genomic evidence that partial reproductive isolation evolved due to adaptation to divergent environments, consistent with predictions of ecological speciation theory.

Reproductive Isolation↗
PubMed2025

Comparative Analysis of Mammalian Adaptive Immune Loci Revealed Spectacular Divergence and Common Genetic Patterns.

Adaptive immune responses are mediated by the production of adaptive immune receptors, antibodies, and T-cell receptors, which bind antigens, thus causing their neutralization. Unlike other proteins, adaptive immune receptors are not fully encoded in the germline genome and result from a complex of somatic processes collectively called V(D)J recombination affecting germline immunoglobulin (IG) and T-cell receptor (TR) loci consisting of template genes. While various existing studies report extreme diversity of antibodies and T-cell receptors, little is known about the diversity of germline IG and TR loci. To overcome this gap, the first comparative analysis of full-length sequences of IG/TR loci across 46 mammalian species from 13 taxonomic orders was performed. First, germline gene counts were shown to correlate in immunoglobulin heavy chain immunoglobulin heavy chain (IGH)/immunoglobulin lambda (IGL) loci and T-cell receptor alpha (TRA)/T-cell receptor beta (TRB) and anticorrelate in immunoglobulin kappa (IGK)/IGL, possibly indicating coevolution between corresponding chains. Second, structures of IG/TR loci were analyzed, and it was shown that IG/TR loci formed by long arrays of high multiplicity repeats are more common for species that have experienced population bottlenecks. Finally, haplotypes of IG/TR loci with little or no sequence similarity within a species were found, suggesting that they may have a limited potential for homologous recombination. These results demonstrate that IG/TR loci are rapidly evolving genomic regions whose structural variation is shaped by the population history of the species and open new perspectives for immunogenomics studies.

Animals↗
PubMed2025

PARTAGE: Parallel analysis of replication timing and gene expression.

The human genome is partitioned into functional compartments that replicate at specific times during the S-phase. This temporal program, referred to as replication timing (RT), is co-regulated with the 3D genome organization, is cell type-specific, and changes during development in coordination with gene expression. Moreover, RT alterations are linked to abnormal gene expression, genome instability, and structural variation in multiple diseases, including cancer. However, mechanistic links between RT, large-scale 3D genome architecture, and transcriptional regulation remain poorly understood. A major limitation is that current approaches require the separate profiling of RT and transcriptomes from independent batches of samples, obscuring the complex co-regulation between the epigenome and transcriptome. Here, we developed PARTAGE, a multiomics approach that enables joint profiling of copy number variation (CNV), RT, and gene expression from the same sample, providing a more accurate integrative view of the complex relationships between RT and gene regulation.

Journal Article↗
PubMed2026

Graph-based pan-genome reveals structural and functional diversity across oil palm domestication gradients.

BACKGROUND: Oil palm (Elaeis guineensis Jacq.), the world's most land-efficient oil crop, underpins global vegetable oil supply yet faces mounting constraints from limited expansion, climate stress, and disease pressure. These challenges highlight the urgent need for genomic resources that capture species-wide diversity to support sustainable improvement. While recent reference assemblies have advanced trait discovery, single linear genomes fail to represent the full spectrum of structural and gene-content variation, limiting resolution of agronomic alleles. RESULTS: Here, we constructed a graph-based pan-genome from 30 diverse oil palm assemblies representing wild, semi-domesticated, and commercial accessions. We characterized structural variants, gene presence-absence variation, and copy-number gains, with focusing on functional stratification and resistance gene dynamics. The graph-based pan-genome revealed extensive structural and gene-content variation, including a large conserved core, complemented by shell and unique fractions enriched or biased toward regulatory, stress-responsive, and defense-related functions. Structural variation and duplication-derived copy-number gains contributed substantially to gene-content diversity, with semi-domesticated accessions exhibiting the greatest variability. Resistance gene repertoires showed contrasting patterns: receptor-like kinases remained comparatively stable, whereas the CNL subclass of NLR genes contributed disproportionately to shell-genome variation and duplication-associated turnover. CONCLUSIONS: This graph-based pan-genome provides a curated multi-assembly reference and comparative framework for oil palm genomics. By capturing structural variants, gene-content variations, copy-number gains, and resistance gene dynamics across domestication gradients, it establishes a foundation for future pan-GWAS analysis, functional genomics, and molecular breeding strategies aimed at improving resilience and productivity in this globally important crop.

Arecaceae↗
PubMed2026

Genome-wide SNP data reveal geographic structure and landscape-associated genomic differentiation in a widespread lizard in arid Eastern Central Asia.

Arid landscapes provide important systems for examining how geographic structure and environmental heterogeneity shape genomic differentiation. In topographically complex desert regions, however, it remains challenging to determine whether population structure primarily reflects landscape resistance, geographic distance, or contemporary environmental variation. Here, we use genome-wide SNP data to investigate population structure, phylogenetic relationships, historical gene flow, demographic history, and landscape correlates of genomic differentiation in the variegated racerunner (Eremias vermiculata), a widespread lacertid lizard across arid Eastern Central Asia. Analyses of 164 individuals recovered six geographically structured nuclear clusters associated with major desert basins and mountain-bounded regions. Nuclear phylogenies resolved two broad regional clades corresponding to northeastern and southwestern parts of the species' range, while PCA and ADMIXTURE analyses recovered six finer-scale genetic clusters. Mitochondrial phylogenies, based on combined NCBI-derived Cyt b and COI sequences from the same individuals, recovered four deeper maternal lineages. These patterns indicate overall phylogeographic agreement between nuclear and mitochondrial datasets, with genome-wide SNPs providing finer-scale resolution of population structure. Demographic reconstructions further uncovered regionally heterogeneous Late Pleistocene histories among clusters, including signals of expansion, stability, and decline. Landscape genomic analyses revealed that genomic differentiation is primarily associated with landscape resistance, particularly elevation and land cover, as well as geographic distance, whereas contemporary environmental variables explained comparatively little variation after controlling for spatial structure. Together, our results suggest that genomic differentiation in E. vermiculata reflects the interplay of persistent landscape configuration, historical connectivity, and region-specific demographic histories across arid Eastern Central Asia. More broadly, this study highlights the value of integrating phylogeographic and landscape genomic approaches for understanding population differentiation and evolutionary history in topographically heterogeneous desert ecosystems.

Arid Eastern Central Asia↗
PubMed2025

Genetic Differentiation is Constrained to Chromosomal Inversions and Putative Centromeres in Locally Adapted Populations With Higher Gene Flow.

The impact of genome structure on adaptation is a growing focus in evolutionary biology, revealing an important role for structural variation and recombination landscapes in shaping genetic diversity across genomes and among populations. This is particularly relevant when local adaptation occurs despite gene flow, where clustering of differentiated loci can maintain locally adapted variants by reducing recombination between them. However, the limited genomic resources for nonmodel species, including reference genomes and recombination maps, have constrained our understanding of these patterns. In this study, we leverage the Atlantic silverside-a nonmodel fish with extensive local adaptation across a steep latitudinal gradient-as an ideal system to explore how genome structure influences adaptation under varying levels of gene flow, using a newly available reference genome and multiple recombination maps. Analyzing 168 genomes from four populations, we found a continuum of genome-wide differentiation increasing from south to north, reflecting higher connectivity among southern populations and reduced gene flow at northern latitudes. With increasing gene flow, the number and clustering of FST outlier loci also increased, with differentiated loci found exclusively within large haploblocks harboring inversions and smaller peaks overlapping putative centromeric regions. Notably, sequence divergence was only evident in inversions, supporting their role in adaptive divergence with gene flow, whereas centromeric regions appeared differentiated because of low recombination and diversity, with no indication of elevated divergence. Our results support the hypothesis that clustered genomic architectures evolve with high gene flow and enhance our understanding of how inversions and centromeres are linked to different evolutionary processes.

Gene Flow↗
PubMed2026

Low-pass whole-genome sequencing reveals genomic diversity and ecotype-specific adaptation in indigenous Tigrayan chickens.

Indigenous chickens play a critical role in food security and climate resilience in smallholder systems, yet their genomic diversity and adaptive potential remain insufficiently characterised. This study employed low-pass whole-genome sequencing (LP-WGS; 0.2-1.99×) to investigate genomic diversity, population structure, inbreeding and candidate environment-associated genomic variation in 33 chickens from highland, midland, and lowland agroecologies in the Tigray region of northern Ethiopia. After imputation and stringent filtering, 23.4 million high-confidence SNPs were retained, including ~ 17% novel variants, indicating substantial uncharacterised genetic diversity in these populations. SNP density (13.8 ± 8.6 SNPs/kb) was comparable to values reported from high-coverage Ethiopian chicken datasets, demonstrating the suitability of LP-WGS for population genomics in resource-limited settings. Marked differences in genomic diversity were observed among ecotypes: midland chickens showed the highest nucleotide diversity (π = 0.00267), followed by lowland (π = 0.00233), whereas highland chickens showed the lowest diversity (π = 0.00203) and elevated genomic inbreeding (FROH and FHOM ≈ 0.18). Population structure analyses revealed clear genetic separation among ecotypes. PCA (13.91% variation explained) distinguished lowland chickens along PC1 and separated highland from midland along PC2, while ADMIXTURE and FST patterns supported three major ancestral genomic backgrounds. Functional annotation of private missense variants uncovered distinct adaptive signatures reflecting the contrasting agroecological conditions. Highland chickens showed enrichment of candidate genes potentially involved in physiological processes relevant to high-altitude environments, including cold response, angiogenesis, cardiovascular regulation and metabolic homeostasis (eg., PARP1, ACOX2, ITGB3, EDNRB, SOX8, and SOX10). Midland chickens exhibited candidate signals of selection in genes with known roles in innate antiviral immunity, bacterial defence and inflammatory regulation (eg., BAK1, CLSTN1, CYSLTR1, CYSLTR2, CXCR7, GIPR, DSCAM, GDAP1, TLR3, TLR4, TLR7, IFIH1, ADORA1, EPHB1, and TMPRSS2). Lowland chickens displayed candidate variants associated with heat-stress response, DNA damage repair, oxidative balance and cardiovascular support under extreme temperatures (e.g., MLH1, BDKRB1, GPR19, FLT1, CCL18, TGM2, and RAMP3). Overall, the results indicate substantial genomic differentiation among ecotypes and suggest candidate environment-associated genetic divergence across Tigray's diverse agroecological zones. These populations may represent important reservoirs of adaptive genetic variation for climate-resilient poultry breeding, warranting further functional validation and conservation-oriented management.

Animals↗
PubMed2026

Whole-Genome Sequencing Reveals Population Structure, Genetic Diversity, and Selection Signatures in Kazakh Dromedary and Bactrian Camels.

Understanding the genomic basis of environmental adaptation is essential for the conservation and genetic improvement of domestic camels. In this study, we investigated the population structure, genetic diversity, and genomic variation potentially associated with environmental adaptation of Kazakh dromedary and Bactrian camels using whole-genome sequencing. Whole-genome sequencing data were generated for Kazakh camels (15 dromedaries and 16 Bactrian camels) and integrated with 131 publicly available genomes representing camel populations from the Arabian Peninsula, Iran, Xinjiang, Inner Mongolia, and Mongolian wild camels. Population structure, genetic diversity, and genome-wide selection were evaluated using principal component analysis, ADMIXTURE, nucleotide diversity, linkage disequilibrium, runs of homozygosity, genomic inbreeding (FROH), and selection scans based on FST, θπ ratio, and XP-EHH. Population genomic analyses revealed clear differentiation between dromedary and Bactrian camels, whereas Kazakh camel populations exhibited higher nucleotide diversity (θπ = 1.307-1.551 × 10-3), and lower genomic inbreeding (median FROH: 0.037-0.056) than Arabian populations. Genome-wide selection analyses identified MC4R as the prominent candidate gene in Kazakh dromedaries and RYR1 as a prominent candidate gene in Kazakh Bactrian camels. Functional enrichment analyses highlighted pathways related to energy metabolism, thermogenesis, calcium signaling, skeletal muscle function, mitochondrial activity, and oxidative stress response. These findings provide new insights into genomic variation potentially associated with environmental adaptation in Kazakh camels and offer valuable genomic resources for future conservation, breeding, and evolutionary studies.

MC4R↗
PubMed2021

Long-read sequencing to interrogate strain-level variation among adherent-invasive Escherichia coli isolated from human intestinal tissue.

Adherent-invasive Escherichia coli (AIEC) is a pathovar linked to inflammatory bowel diseases (IBD), especially Crohn's disease, and colorectal cancer. AIEC are genetically diverse, and in the absence of a universal molecular signature, are defined by in vitro functional attributes. The relative ability of difference AIEC strains to colonize, persist, and induce inflammation in an IBD-susceptible host is unresolved. To evaluate strain-level variation among tissue-associated E. coli in the intestines, we develop a long-read sequencing approach to identify AIEC by strain that excludes host DNA. We use this approach to distinguish genetically similar strains and assess their fitness in colonizing the intestine. Here we have assembled complete genomes using long-read nanopore sequencing for a model AIEC strain, NC101, and seven strains isolated from the intestinal mucosa of Crohn's disease and non-Crohn's tissues. We show these strains can colonize the intestine of IBD susceptible mice and induce inflammatory cytokines from cultured macrophages. We demonstrate that these strains can be quantified and distinguished in the presence of 99.5% mammalian DNA and from within a fecal population. Analysis of global genomic structure and specific sequence variation within the ribosomal RNA operon provides a framework for efficiently tracking strain-level variation of closely-related E. coli and likely other commensal/pathogenic bacteria impacting intestinal inflammation in experimental settings and IBD patients.

Animals↗
PubMed2026

Whole-genome sequencing implicates rare, low-frequency and structural non-coding variation at the SCN5A locus in Brugada syndrome.

Brugada syndrome (BrS) is an inherited cardiac condition characterized by a hallmark ECG pattern and an increased risk of sudden cardiac death. Central to the aetiology of BrS, the SCN5A region harbours both common non-coding risk variants and rare coding variants that are causative in approximately 20% of patients. However, rare non-coding genetic variation in this region remains largely unexplored. Here, we used whole-genome sequencing (WGS) of 752 European-ancestry BrS cases and 1,827 ancestry-matched controls to identify BrS-associated rare non-coding genetic variation at the SCN5A locus. Sliding-window and cis-regulatory element (CRE)-based rare-variant aggregate testing implicated three conserved CREs, including a dense aggregation of case singleton variants within a 178 bp enhancer in intron 17 of SCN5A which replicated in an independent BrS cohort. Prioritised BrS-associated rare and low-frequency non-coding variants within these elements were predicted to alter cardiac transcription factor motifs, and altered CRE activity in hiPSC-CM luciferase assays or were associated with BrS-relevant ECG endophenotypes in the UK Biobank. Single-variant analysis across the region identified a Bonferroni-significant five-fold case-enriched low-frequency variant within a known CRE in intron 1 of SCN5A, which replicated, was associated with slower cardiac conduction in the UK Biobank and accounted for part of the BrS GWAS signal at this locus. Structural variant analyses identified a 10.5 kb deletion upstream of SCN5A in a BrS case that encompassed a cardiac CRE and reduced sodium current density in a hiPSC-CM model, as well as a 6 kb BrS-enriched retrotransposon insertion in SCN5A that appeared to underlie part of the GWAS signal in this region. Together, these findings implicate rare and low-frequency non-coding variation at the SCN5A locus in BrS susceptibility and demonstrate the value of targeted WGS analysis of key disease loci.

Journal Article↗
PubMed2025

In silico prediction of the impact of genomic variations in the small conductance calcium activated potassium channel SK3 structure and function.

The small-conductance calcium-activated potassium channel SK3, encoded by the KCNN3 gene, plays a critical role in regulating dopaminergic neuron (DN) firing patterns by modulating after hyperpolarization currents. SK3 dysfunction has been implicated in neuropsychiatric and neurodegenerative disorders. We analyzed structural and functional consequences of KCNN3 splicing and genetic variation. Alternative splicing variants of the KCNN3 gene were retrieved from the Ensembl database and aligned using T-Coffee, manually inspected and curated. Protein domains were identified with Pfam 35.0, SMART 9.0, and InterPro 98.0, and visualized. An AlphaFold2 model of SK3 full-length protein (UniProt: Q9UGI6) used as reference and structural models of its splicing variants were predicted with ColabFold. Functional domains (S1-S6 transmembrane helices, H5 pore loop, and calmodulin-binding) were defined and superimposed onto the AlphaFold2 reference. Domain integrity was assessed based on completeness of all expected residue indices within each functional region. SNPs and CNVs across all coding KCNN3 splicing variants were analyzed, classified, and filtered to isolate pathogenic variants prioritizing non-synonymous amino acid substitutions. Differential variant impacts across splicing isoforms were assessed by mapping variant positions to individual transcript protein sequences and used to predict functional consequences. Two long and two short splicing variants are known. Short variants lack the motif required for potassium channels. Pathogenic variants result from missense mutations resulting in amino acid substitutions. In all cases, the consequential effects depend on the specific location and role of the amino acid being changed.

SK3 channels↗
PubMed2024

Comparative analysis of chloroplast genomes in ten holly (Ilex) species: insights into phylogenetics and genome evolution.

In order to clarify the chloroplast genomes and structural features of ten Ilex species and provide insights into the phylogeny and genome evolution of the genus Ilex, we conducted a comparative analysis of chloroplast genomes using bioinformatics methods. The chloroplast genomes of ten Ilex species were obtained, and their structural features and variations were compared. The results indicated that all chloroplast genomes in the genus Ilex exhibit a double-stranded circular structure, with sizes ranging from 157,356 to 158,018 bp, showing minimal differences in size. The chloroplast genomes of the ten Ilex species have a relatively conservative gene count, with a total of 134 to 135 genes, including 88 or 89 protein-coding genes, and a conserved number of 8 rRNA genes. Each chloroplast genome contains 3 to 123 SSR (Simple Sequence Repeat) sites, predominantly composed of mononucleotide and trinucleotide repeats, with no detection of pentanucleotide or hexanucleotide repeats. The variation in dispersed repeat sequences among Ilex species is minimal, with a total repeat sequence number ranging from 1 to 14, concentrated in the length range of 30 to 42 base pairs. The expansion and contraction of chloroplast genome boundaries among Ilex species are relatively stable, with only minor variations observed in individual species. Variations in non-coding regions are more pronounced than those in coding regions, with the variability in the Large Single Copy region (LSC) being the highest, while the variability in the Inverted Repeat region A (IRa) is the lowest. The divergence time among Ilex species was estimated using the MCMC-tree module, revealing the evolutionary relationships among these species, their common ancestors, and their differentiation throughout the evolutionary process. The research findings provide a valuable reference for the systematic study and molecular marker development of Ilex plants.

Genome, Chloroplast↗
PubMed2026

The Rise of Plant Pan-Genomes: From Genome Variation to Predictive Breeding.

Plant pan-genomics is entering a new phase beyond genome variation discovery, requiring a shift from cataloguing genomic diversity toward understanding how variation generates biological function and breeding value. Here, we propose that the future of plant pan-genomics will be shaped by three conceptual transitions. First, structural variation (SV), presence-absence variation (PAV), and haplotype diversity should be interpreted not merely as genomic differences, but as regulatory components that influence gene networks, chromatin organization, and complex traits. Second, the expansion from species-level pan-genomes to genus-level super pan-genomes provides an evolutionary framework for uncovering adaptive genetic modules preserved in wild relatives and overlooked during domestication. Third, integrating pan-genomes with pan-omics, three-dimensional genome analyses, and artificial intelligence will enable the transformation of genomic variation into predictive models for crop improvement. We further propose that the ultimate value of pan-genomes lies not in generating increasingly complete genome collections, but in establishing a mechanistic bridge between genome diversity, biological function, and breeding decisions. This transition will move crop improvement from empirical selection toward rational genome design, where evolutionary diversity can be systematically interpreted, predicted, and engineered.

Journal Article↗
PubMed2024

Haplotype-resolved genome assembly and implementation of VitExpress, an open interactive transcriptomic platform for grapevine.

Haplotype-resolved genome assemblies were produced for Chasselas and Ugni Blanc, two heterozygous Vitis vinifera cultivars by combining high-fidelity long-read sequencing and high-throughput chromosome conformation capture (Hi-C). The telomere-to-telomere full coverage of the chromosomes allowed us to assemble separately the two haplo-genomes of both cultivars and revealed structural variations between the two haplotypes of a given cultivar. The deletions/insertions, inversions, translocations, and duplications provide insight into the evolutionary history and parental relationship among grape varieties. Integration of de novo single long-read sequencing of full-length transcript isoforms (Iso-Seq) yielded a highly improved genome annotation. Given its higher contiguity, and the robustness of the IsoSeq-based annotation, the Chasselas assembly meets the standard to become the annotated reference genome for V. vinifera. Building on these resources, we developed VitExpress, an open interactive transcriptomic platform, that provides a genome browser and integrated web tools for expression profiling, and a set of statistical tools (StatTools) for the identification of highly correlated genes. Implementation of the correlation finder tool for MybA1, a major regulator of the anthocyanin pathway, identified candidate genes associated with anthocyanin metabolism, whose expression patterns were experimentally validated as discriminating between black and white grapes. These resources and innovative tools for mining genome-related data are anticipated to foster advances in several areas of grapevine research.

Vitis↗
PubMed2024

Diversity of ribosomes at the level of rRNA variation associated with human health and disease.

With hundreds of copies of rDNA, it is unknown whether they possess sequence variations that form different types of ribosomes. Here, we developed an algorithm for long-read variant calling, termed RGA, which revealed that variations in human rDNA loci are predominantly insertion-deletion (indel) variants. We developed full-length rRNA sequencing (RIBO-RT) and in situ sequencing (SWITCH-seq), which showed that translating ribosomes possess variation in rRNA. Over 1,000 variants are lowly expressed. However, tens of variants are abundant and form distinct rRNA subtypes with different structures near indels as revealed by long-read rRNA structure probing coupled to dimethyl sulfate sequencing. rRNA subtypes show differential expression in endoderm/ectoderm-derived tissues, and in cancer, low-abundance rRNA variants can become highly expressed. Together, this study identifies the diversity of ribosomes at the level of rRNA variants, their chromosomal location, and unique structure as well as the association of ribosome variation with tissue-specific biology and cancer.

Humans↗
PubMed2026

Ancient DNA and Human Physiology.

Ancient DNA (aDNA) enables the reconstruction of chronologically sampled genomes from ancient humans, animals, plants, pathogens, and microorganisms, as well as environmental DNA, providing a record of biological changes through time. Improvements in short and degraded DNA extraction methods and low-cost sequencing now enable the generation of broad, cross-regional datasets that expand evolutionary analyses from past population demography to biological mechanisms. By tracking temporal shifts of allele frequencies, integrating functional genomics resources (e.g., gene expression, chromatin structure variation), modeling population demography to separate selection from genetic drift, and aligning genetic changes with archaeological, cultural, and climatic data, aDNA has the potential to link sequence variation to physiological function within their temporal and environmental contexts. In this review, we summarize illustrative case studies from aDNA research spanning complex traits, dietary adaptations, and responses to pathogens and other environmental changes, showing how human biology has evolved under multiple selective pressures through time. These dated signals help triage experimental work and expose mechanisms that are rare or absent in living cohorts. Although some challenges remain, such as geographic and temporal sampling disparities, limitations in data resolution and variant detection, and genotype-phenotype uncertainties, rapid methodological progress and stronger ethical frameworks are expanding what can be inferred, making aDNA a promising tool for refining physiological pathways, their timing, and their drivers.

Humans↗
PubMed2025

Polyploidy-mediated variations in glutamate receptor proteins linked to Fusarium wilt resistance in upland cotton.

Cotton production in the US faces a serious threat from Fusarium oxysporum f. sp. vasinfectum race 4 (FOV4), a soil-borne fungus causing Fusarium wilt by infecting the roots and vascular system of susceptible cotton, leading to rapid wilting and death. Here, we investigate genetic mechanisms of resistance to FOV4 in the highly resistant upland cotton genotype "U1" using an early-generation segregating biparental population ("U1" × "CSX8308") with comprehensive genomic resources. Reference-grade genomic assemblies of the parents revealed minor structural variations between "U1" haplotypes, a high degree of collinearity at chromosome synteny and micro-synteny levels, and significant divergence from "CSX8308" with 8.9 million SNPs. QTL analysis identified significant markers on chromosomes D03 and A02 linked to reduced Fusarium wilt severity. Within these regions, two glutamate-receptor-like (GLR) genes showed structural variation and overlapped between translocated segments on A02 and D03, suggesting a rare but important reinforcing effect of parallel evolution between susceptible and resistant genotypes. Transcriptome profiles of "U1" under FOV4 infection reveal activation of calcium-binding proteins and transcription factors regulating plant hormones (ethylene, abscisic acid, jasmonic acid, and salicylic acid), along with enzymes involved in cell wall remodeling and phytoalexin production. Advancing cotton improvement depends on incorporating durable genetic disease resistance into high-yielding, high-quality cultivars.

Fusarium↗
PubMed2026

Pan-genomics and multi-omics for deciphering genetic variation and accelerating genetic improvement in ruminant livestock.

Livestock reference genomes have transformed the discovery of variants associated with production, reproduction, health, and environmental adaptation. Nevertheless, a single linear reference represents only one mosaic haplotype and incompletely captures sequence diversity within a species, particularly structural variants, copy-number changes, repeat-rich regions, and breed-specific sequences. Pangenomes address this limitation by integrating multiple high-quality assemblies or population-scale variants into a unified sequence or graph representation. Concurrently, multi-omics approaches connect genomic variation with transcriptomic, epigenomic, manuscriptproteomic, metabolomic, and microbiome responses, thereby improving biological interpretation of genotype-phenotype relationships. This review synthesizes recent progress in livestock pangenomics and multi-omics, with emphasis on cattle, goats, sheep, water buffalo, and chickens. It describes advances in long-read and haplotype-resolved sequencing, graph construction, structural-variant discovery and genotyping, functional annotation, and integrative analysis. Recent pangenome studies have uncovered substantial non-reference sequence, reduced reference bias, identified breed- and population-specific structural variants, and resolved candidate variants underlying pigmentation, body size, tail morphology, cashmere production, altitude adaptation, and other economically relevant traits. However, translation into routine breeding remains constrained by uneven population representation, inconsistent structural-variant definitions, limited functional annotation, computational demands, and insufficient validation across environments. Future progress will depend on diverse near-complete assemblies, graph-aware imputation and genomic prediction, long-read transcriptomics, single-cell and spatial omics, rigorous causal validation, and open, interoperable resources. Together, these developments can support more accurate, resilient, and biologically informed livestock improvement. Importantly, current dairy-cattle evidence indicates that pangenome-derived structural variants can substantially improve variant discovery and functional interpretation while yielding only marginal average gains in routine genomic prediction, favoring targeted augmentation rather than wholesale replacement of established SNP-based evaluations.

Animals↗