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At least 19 recordsLinked to original sources
PubMed2026

Genome-wide association and selective sweep analyses reveal genetic loci for teat number trait in pigs.

Teat number is a key reproductive trait for the commercial pig industry, as an optimum number enhances weaned piglet survival rate. This study aimed to identify single nucleotide polymorphisms (SNPs) and genomic regions that are associated with teat number in the Large White sow. A total of 1000 French Large White sows were used in an analysis of total, left/right, and maximum unilateral teat number. Environmental factor, Spearman correlation, genome-wide association study (GWAS), linkage disequilibrium, and selective sweep analyses were conducted, with validation performed in a population of 1145 Landrace pigs. Genetic statistics showed that this population's teat number had moderate-low genomic heritability (h2 = 0.17-0.21) and weak negative correlation with weaned piglet litter weight. Parity and season affected teat development. GWAS identified 17 candidate SNPs on SSC 4, 7, and 17. Combined with selective sweep analysis, two key regions on SSC 7 were found, with four teat number-related SNPs, annotated to VRTN, DIO2, NRXN3. These candidate genes are associated with thoracic vertebrae development, hormone regulation during the early stage of teat formation, and nervous system development. These five SNPs showed similar results in the Landrace pig validation population; non-mutant homozygotes had 0.25-1.15 more teats than mutant ones in both populations. This study contributes to the identification of key variant loci associated with teat number-related traits in sows, thereby providing reliable molecular markers and a theoretical basis for marker-assisted selection of sow reproductive performance.

Animals↗
PubMed2025

Sweeps in Space: Leveraging Geographic Data to Identify Beneficial Alleles in Anopheles gambiae.

As organisms adapt to environmental changes, natural selection modifies the frequency of nonneutral alleles. For beneficial mutations, the outcome of this process may be a selective sweep, in which an allele rapidly increases in frequency and perhaps reaches fixation within a population. Selective sweeps have well-studied effects on patterns of local genetic variation in panmictic populations, but much less is known about the dynamics of sweeps in continuous space. In particular, because limited movement across a landscape leads to unique patterns of population structure, spatial dynamics may influence the trajectory of selected mutations. Here, we use forward-in-time, individual-based simulations in continuous space to study the impact of space on beneficial mutations as they sweep through a population. In particular, we show that selection changes the joint distribution of allele frequency and geographic range occupied by a focal allele and demonstrate that this signal can be used to identify selective sweeps. We then leverage this signal to identify in-progress selective sweeps within the malaria vector Anopheles gambiae, a species under strong selection pressure from vector control measures. By considering space, we identify multiple previously undescribed variants with potential phenotypic consequences, including mutations impacting known IR-associated genes and altering protein structure and properties. Our results demonstrate a novel signal for detecting selection in spatial population genetic data that may have implications for genomic surveillance and understanding geographic patterns of genetic variation.

Animals↗
PubMed2025

Sweeps in space: leveraging geographic data to identify beneficial alleles in Anopheles gambiae.

As organisms adapt to environmental changes, natural selection modifies the frequency of non-neutral alleles. For beneficial mutations, the outcome of this process may be a selective sweep, in which an allele rapidly increases in frequency and perhaps reaches fixation within a population. Selective sweeps have well-studied effects on patterns of local genetic variation in panmictic populations, but much less is known about the dynamics of sweeps in continuous space. In particular, because limited movement across a landscape leads to unique patterns of population structure, spatial dynamics may influence the trajectory of selected mutations. Here, we use forward-in-time, individual-based simulations in continuous space to study the impact of space on beneficial mutations as they sweep through a population. In particular, we show that selection changes the joint distribution of allele frequency and geographic range occupied by a focal allele and demonstrate that this signal can be used to identify selective sweeps. We then leverage this signal to identify in-progress selective sweeps within the malaria vector Anopheles gambiae , a species under strong selection pressure from vector control measures. By considering space, we identify multiple previously undescribed variants with potential phenotypic consequences, including mutations impacting known IR-associated genes and altering protein structure and properties. Our results demonstrate a novel signal for detecting selection in spatial population genetic data that may have implications for genomic surveillance and understanding geographic patterns of genetic variation.

Journal Article↗
PubMed2026

Interference of Competing Beneficial Mutations on Recombining Chromosomes.

Finding signatures of selective sweeps in genomes is a major goal of current population genomics, as it allows estimating the rate of beneficial mutations going to fixation and identifying the genes involved in selection. Models of recurrent selective sweeps traditionally assume that in chromosomal regions of normal recombination rates at most one beneficial allele is on the way to fixation. We review and extend here the theoretical studies on interference between closely linked beneficial mutations suggesting that this assumption may be violated. We show that interference between beneficial mutations may lead to substantially increased fixation times even in chromosomal regions of normal recombination rates. Furthermore, we discuss how interference can be detected in population genomic studies by analyzing genetic footprints of selective sweeps, and search for empirical evidence of interference in published datasets.

fixation times↗
PubMed2025

Accessible, realistic genome simulation with selection using stdpopsim.

Selection is a fundamental evolutionary force that shapes patterns of genetic variation across species. However, simulations incorporating realistic selection along heterogeneous genomes in complex demographic histories are challenging, limiting our ability to benchmark statistical methods aimed at detecting selection and to explore theoretical predictions. stdpopsim is a community-maintained simulation library that already provides an extensive catalog of species-specific population genetic models. Here we present a major extension to the stdpopsim framework that enables simulation of various modes of selection, including background selection, selective sweeps, and arbitrary distributions of fitness effects (DFE) acting on annotated subsets of the genome (for instance, exons). This extension maintains stdpopsim's core principles of reproducibility and accessibility while adding support for species-specific genomic annotations and published DFE estimates. We demonstrate the utility of this framework by comparing methods for demographic inference, DFE estimation, and selective sweep detection across several species and scenarios. Our results demonstrate the robustness of demographic inference methods to selection on linked sites, reveal the sensitivity of DFE-inference methods to model assumptions, and show how genomic features, like recombination rate and functional sequence density, influence power to detect selective sweeps. This extension to stdpopsim provides a powerful new resource for the population genetics community to explore the interplay between selection and other evolutionary forces in a reproducible, user-friendly framework.

Journal Article↗
PubMed2025

Polaris: Polarization of ancestral and derived polymorphic alleles for inferences of extended haplotype homozygosity in human populations.

SUMMARY: Statistical methods that measure the extent of haplotype homozygosity on chromosomes have been highly informative for identifying episodes of recent selection. For example, the integrated haplotype score (iHS) and the extended haplotype homozygosity (EHH) statistics detect long-range haplotype structure around derived and ancestral alleles indicative of classic and soft selective sweeps, respectively. However, to our knowledge, there are currently no publicly available methods that classify ancestral and derived alleles in genomic datasets for the purpose of quantifying the extent of haplotype homozygosity. Here, we introduce the Polaris package, which polarizes chromosomal variants into ancestral and derived alleles and creates corresponding genetic maps for analysis by selscan and HaploSweep, two versatile haplotype-based programs that perform scans for selection. With the input files generated by Polaris, selscan and/or HaploSweep can produce the appropriate sign (either positive or negative) for outlier iHS statistics, enabling users to distinguish between selection on derived or ancestral alleles. In addition, Polaris can convert the numerical output of these analyses into graphical representations of selective sweeps, increasing the functionality of our software. RESULTS: To demonstrate the utility of our approach, we applied the Polaris package to Chromosome 2 in the European Finnish, Middle Eastern Bedouin, and East African Maasai populations. More specifically, we examined the regulatory sequence in intron 13 of the MCM6 gene associated with lactase persistence (i.e. the ability to digest the lactose sugar present in fresh milk), a region of intense interest to human evolutionary geneticists. Our analyses showed that derived alleles (at known enhancers for lactase expression) sit on an extended haplotype background in the Finnish, Bedouin, and Maasai consistent with a classic selective sweep model as determined by iHS and EHH statistics. Importantly, we were able to immediately identify this target allele under selection based on the information generated by our software. We also explored outlier statistics across Chromosome 2 in two distinct datasets from these populations: (i) one containing polarized alleles generated with Polaris and (ii) the other containing unpolarized alleles in the original phased vcf file. Here, we found an excess of outlier statistics on Chromosome 2 in the unpolarized datasets, raising the possibility that a subset of these "hits" of selection may be unreliable. Overall, Polaris is a versatile package that enables users to efficiently explore, interpret, and report signals of recent selection in genomic datasets. AVAILABILITY AND IMPLEMENTATION: The Polaris package is free and open source on GitHub (https://github.com/alisi1989/Polaris) and DropBox (https://www.dropbox.com/scl/fo/mlxizft5267vem9u62qkn/AAnM0qX923zPzQBlPX8iteM?rlkey=uezrp4t2waffpj0nmo1evr320&e=1&st=jaodccws&dl=0).

Haplotypes↗
PubMed2026

High-Density Genome-Wide Association Mapping Identifies Candidate Loci Associated with Maize Stalk Cell Wall Composition.

Maize (Zea mays L.) stalk cell wall composition is a key determinant of forage digestibility, lodging resistance, and biomass utilization efficiency. Although previous genome-wide association studies (GWAS) have identified loci associated with lignin (LIG), cellulose (CEL), and hemicellulose (HC), advances in genomic resources provide an opportunity to revisit existing phenotypic datasets at substantially higher resolution. Here, we re-analyzed a maize association panel consisting of 341 diverse inbred lines using an expanded genotype dataset containing 10.77 million SNPs, two derived compositional indices (CEL/HC and [LIG/(CEL + HC)], and six complementary GWAS models. Across all traits and models, we identified 855 unique significant SNPs associated with 579 candidate genes. Among the traits examined, LIG/(CEL + HC) yielded the greatest number of associations, suggesting that indices representing the relative balance among cell wall components may better capture the genetic architecture of cell wall composition than individual component measurements alone. Integration of multiple GWAS models with functional enrichment, haplotype, and selective sweep analyses prioritized three biologically relevant candidate genes encoding a MYB58 transcription factor, the glycosyltransferase Xt9, and a putative xyloglucan 6-xylosyltransferase. Haplotype analysis revealed significant effects of Xt9 and the xyloglucan 6-xylosyltransferase on cell wall composition, while selective sweep analysis identified Xt9 as a target of repeated selection during maize domestication, ecological adaptation, and modern breeding. Although these candidate genes provide promising targets for future investigation, the associations identified here are based on a single association panel and require functional and independent population validation. Collectively, our results demonstrate how high-density genotyping combined with complementary GWAS models can refine candidate associations and generate testable hypotheses from existing phenotypic datasets.

cell wall composition↗
PubMed2019

Identifying loci under positive selection in complex population histories.

Detailed modeling of a species' history is of prime importance for understanding how natural selection operates over time. Most methods designed to detect positive selection along sequenced genomes, however, use simplified representations of past histories as null models of genetic drift. Here, we present the first method that can detect signatures of strong local adaptation across the genome using arbitrarily complex admixture graphs, which are typically used to describe the history of past divergence and admixture events among any number of populations. The method-called graph-aware retrieval of selective sweeps (GRoSS)-has good power to detect loci in the genome with strong evidence for past selective sweeps and can also identify which branch of the graph was most affected by the sweep. As evidence of its utility, we apply the method to bovine, codfish, and human population genomic data containing panels of multiple populations related in complex ways. We find new candidate genes for important adaptive functions, including immunity and metabolism in understudied human populations, as well as muscle mass, milk production, and tameness in specific bovine breeds. We are also able to pinpoint the emergence of large regions of differentiation owing to inversions in the history of Atlantic codfish.

Animals↗
PubMed2026

Multidimensional GWAS analyses on longitudinal phenotypes reveal candidate genes regulating multi-stage egg production traits in Wannan yellow chicken.

Egg production performance directly determines the economic viability of indigenous chicken breeding. However, the genetic regulation of multi-stage egg production traits remains difficult to characterize due to their complex and dynamic nature. Here, we integrated a multidimensional GWAS framework, including single-trait GWAS, multi-trait GWAS (MTAG), and longitudinal trajectory-based GWAS (TrajGWAS), to identify stage-specific and shared genetic effects underlying egg production traits in Wannan yellow chickens (WNY). Whole-genome sequencing of 354 WNY hens (10× depth) and quality control yielded 14,253,816 SNPs for analysis. Selective sweep analyses comparing red jungle fowl, commercial layers, and WNY identified a genomic region containing IGF1 under significant selection pressure. Single-trait GWAS identified SNPs 4_57990480 (BMPR1B) and 17_370912 (LOC112531479) associated with egg production across three laying stages (21-30, 31-40, and 21-40 weeks). MTAG further identified loci 8_4336468 (FASLG) and 21_654726 (CHD5) with shared effects across the laying period, whereas TrajGWAS revealed longitudinal associations involving PRKG1 and identified dynamic loci associated with clutch traits, including GRID1. For clutch traits, stage-specific loci were detected for average clutch size (ACS) and maximum clutch size (MCS), including SNP 8_8542036 at 21-30 weeks, PROK1 at 31-40 weeks, and CUL5, ALKBH8 across the entire laying period. These results demonstrate that integrating complementary GWAS strategies improves the resolution of genetic architecture underlying egg production traits by capturing trait-specific, shared, and stage-dependent genetic effects. The identified GWAS loci and selective-sweep candidate regions provide insights into the genetic architecture of egg production traits and breed differentiation.

Egg production↗
PubMed2026

Wheat breeding during and after the "green revolution" contributed to the reduced use of elite nitrogen metabolism alleles linked to nitrogen use efficiency.

The wheat "Green Revolution (GR)" that occurred from the 1960s to the 1970s significantly enhanced the harvest index and resistance to lodging, thereby increasing grain production, but at the cost of reduced nitrogen (N) use efficiency (NUE) in wheat. The NUE of wheat is mainly regulated by N metabolism genes (NMGs). However, the evolutionary process of NMGs during GR and post-GR wheat breeding, as well as which of them affect NUE, remains unclear. Here, we collected 265 wheat varieties that were released before, during, and after the GR and investigated grain yield per plant and 24 other traits under different N supply conditions. Next, we identified the genotypes of these wheat varieties using a 100 K targeted sequencing array. Then, we systematically analyzed the signatures in the genomes of GR and post-GR released varieties compared with pre-GR released varieties through population divergence (Fst) and nucleotide diversity (π) ratio analyses, and found that 41 NMGs were located within the selective sweep regions during the GR and post-GR breeding. We further identified 118 quantitative trait loci (QTLs) involved in regulating NUE through genome-wide association studies (GWAS). Four NMGs-NRT1 AND PEPTIDE TRANSPORTER FAMILY 2.7-D (TaNPF2.7-D), TaNPF2.3-D, TaNPF2.7 L-D, and QUASIMODO2-B (TaQUA2-B)-were located within overlapping regions of selective sweeps and NUE-related QTLs. Notably, the elite haplotypes of these genes for NUE are less utilized in GR and post-GR released cultivars. Furthermore, we found that TaNPF2.7-D positively regulates nitrate exudation as well as the wheat development. Collectively, our findings uncover an important reason for the reduction in NUE in modern cultivars and provide a valuable resource for improving wheat NUE.

Triticum↗
PubMed2026

Genomic and phenotypic diversification of Pseudomonas aeruginosa during sustained exposure to a ciliate predator.

UNLABELLED: Predator-mediated selection is an important ecological force shaping bacterial evolution, but its effects on genomic adaptation and virulence in opportunistic pathogens are not fully understood. Here, we used experimental evolution to study how exposure to the ciliate predator Tetrahymena thermophila affects Pseudomonas aeruginosa. Replicate populations were evolved for 60 days with or without the predator, followed by whole-genome shotgun metagenomic sequencing and phenotypic analyses. Both treatments showed strong selection and evidence of parallel evolution at gene and nucleotide levels, indicating constrained adaptation. However, predator exposure altered evolutionary dynamics. Predator-evolved populations showed a wider distribution of mutation frequencies, with many mutations persisting at intermediate frequencies, consistent with increased clonal interference and ongoing competition among lineages. In contrast, populations evolved without predators showed more high-frequency mutations, consistent with selective sweeps, although some low-frequency variants remained. Despite substantial genomic change, phenotypic outcomes were variable. Virulence in an invertebrate host model did not consistently increase. Instead, evolved isolates showed context-dependent changes, including modest decreases or occasional increases. Competition assays also showed no consistent fitness advantage for predator-evolved isolates, suggesting trade-offs between predator resistance and growth in other environments. Overall, predator-mediated selection reshaped evolutionary dynamics by maintaining diversity and altering the balance of lineages rather than producing uniform increases in virulence. These results highlight how ecological complexity influences adaptive evolution and the context-dependent nature of pathogen traits. IMPORTANCE: Opportunistic pathogens such as Pseudomonas aeruginosa often evolve in environmental settings before infecting hosts, raising questions about how ecological interactions influence virulence. Predator-mediated selection has been suggested to increase virulence via coincidental evolution, but evidence is inconsistent. Here, we show that exposure to a eukaryotic predator does not consistently elevate virulence but does reshape evolutionary dynamics by altering how mutations spread in populations. Predator-exposed populations retained more intermediate-frequency mutations, consistent with increased clonal interference and ongoing competition among lineages, whereas non-predator populations were dominated by selective sweeps. These differences were also reflected in functional targets of adaptation, with predator exposure favoring mutations in genes involved in environmental sensing and interaction. Together, these findings suggest that ecological complexity shapes the dynamics of adaptation rather than driving a single evolutionary outcome, highlighting that virulence is an emergent property influenced by underlying evolutionary processes.

Pseudomonas aeruginosa↗
PubMed2026

Identification of Candidate Genes Associated with Growth Traits in Procambarus clarkii Using Whole-Genome Resequencing.

Growth is a critical economic trait in all aquaculture industries. To address issues such as germplasm degradation, a comprehensive understanding of the growth and development mechanisms, along with genetic improvement strategies, for Procambarus clarkii (P. clarkii) is urgently required. In this study, we performed whole-genome resequencing on 89 individuals from five cultured stocks to investigate growth traits (body length) and identified a total of 46,919,297 high-quality single nucleotide polymorphisms (SNPs). Based on these SNPs, we conducted principal component analysis (PCA), phylogenetic analysis, and population genetic structure analysis. Furthermore, we performed selective sweep analysis (using FST, Pi, and XP-CLR) and a genome-wide association study (GWAS) to identify genetic variants associated with growth traits. The results revealed significant genetic differentiation among the five cultured stocks, with the Ma'anshan cultured stock exhibiting the fastest linkage disequilibrium (LD) decay. Additionally, long-term aquaculture in different geographical regions resulted in distinct genetic differences among cultured stocks. Through selective sweep analysis, the intersection of FST, Pi, and XP-CLR across the five populations yielded several growth-related candidate genes: Nephrin, Somatostatin, zinc finger protein 154, and yeti. Subsequent the GWAS identified two candidate genes associated with growth traits: Cullin-associated and neddylation-dissociated protein 1 (CAND1) and Baculoviral IAP repeat-containing protein 8 (BIRC8). These genes are presumed to play pivotal roles in the growth and development of P. clarkii. Overall, our findings provide new insights into the genetic mechanisms underlying growth and development in P. clarkii, and these identified genes serve as promising candidates for further functional studies and genetic improvement of this species.

Polymorphism, Single Nucleotide↗
PubMed2026

Natural variants of CsSHN1 orchestrate a temporal regulatory cascade driving fruit skin netting in cucumber.

Fruit skin netting (russeting, Rs) forms when epidermal microcracks are sealed by a suberized periderm, reducing marketability. We previously identified the Rs locus (CsSHN1), which encodes an AP2/ERF transcription factor, as a major determinant of cucumber skin netting, but how fruit growth is temporally coupled to periderm formation remains unclear. Here, we integrated population genomics, time-series multiomics, DNA affinity purification sequencing (DAP-seq), and transgenic assays to decode the CsSHN1-mediated regulatory network. Six functionally relevant CsSHN1 variants were identified across 325 cucumber accessions. Allele distribution and selective sweep analyses revealed breeding-driven selection for smooth fruit skin. Overexpression of a netted allele in a smooth background induced epidermal fissures, altered cell geometry, and increased fruit size, demonstrating a dosage-sensitive effect. Time-series transcriptomics and metabolomics of near-isogenic lines (NILs) defined 3 developmental phases of netting: early suppression of lignin and trehalose genes preceding cracks, growth-driven fissuring accompanied by cell-wall remodeling and defense activation, and maturation-stage cell-wall degradation with strong induction of ligno-suberin biosynthesis. Across the cucumber genome, DAP-seq identified approximately 8,000 in vitro CsSHN1 binding sites. These binding sites were significantly enriched for the GCC-box motif and included genes involved in cutin and suberin biosynthesis. Together, these results show that CsSHN1 orchestrates fruit skin netting through a growth-coupled temporal regulatory cascade, providing a mechanistic framework for manipulating fruit epidermal properties.

Cucumis sativus↗
PubMed2026

Population Genomics of Almond (Prunus dulcis) Reveals Region-Specific Selection and a Complex History of Domestication.

The domestication of perennial crops in the Mediterranean Basin remains unclear, particularly regarding the genomic consequences of human-mediated demographic shifts and selection. We analysed 8.1 million single nucleotide polymorphisms from 96 cultivated almond (Prunus dulcis) accessions from Europe, North America, Central Asia, and New Zealand, alongside four wild relatives. Population structure analyses revealed four geographically differentiated cultivated groups (Central Asian, North American, and two European) and three wild populations (P. spinosissima, P. orientalis, and P. fenzliana). Cultivated almonds retained high genetic diversity, consistent with weak domestication bottlenecks typical of outcrossing perennials. Elevated diversity and private allele counts in Central Asian cultivars, together with limited evidence of crop-wild gene flow, support Central Asia as an important reservoir of ancestral cultivated diversity that may have played a major role during the early stages of almond domestication. In contrast, allele sharing consistent with historical wild-to-crop introgression-especially involving P. orientalis-has contributed to the genomic composition of European and North American almonds. Genome-wide scans for selective sweeps showed most genes overlapping candidate sweep regions were population-specific, though often associated with similar biological functions, including stress responses and agronomic traits. This suggests repeated targeting of comparable pathways during and post-domestication, despite distinct selection histories. Notably, a subset of candidate genes detected in cultivated populations also occurs in wild relatives, particularly P. orientalis. This overlap is consistent with shared ancestral variation, introgression/gene flow between wild and cultivated lineages, and/or parallel adaptation. Altogether, our results support a complex domestication and diversification history for almonds, shaped by geographic expansion, gene flow with wild relatives, and recurrent selection acting in different regions. This study highlights wild relatives as important reservoirs of genetic diversity and emphasises the need for broader geographic sampling to clarify their contributions to almond domestication and adaptation.

Prunus dulcis↗
PubMed2015

Evolutionary genomics of Culex pipiens: global and local adaptations associated with climate, life-history traits and anthropogenic factors.

We present the first genome-wide study of recent evolution in Culex pipiens species complex focusing on the genomic extent, functional targets and likely causes of global and local adaptations. We resequenced pooled samples of six populations of C. pipiens and two populations of the outgroup Culex torrentium. We used principal component analysis to systematically study differential natural selection across populations and developed a phylogenetic scanning method to analyse admixture without haplotype data. We found evidence for the prominent role of geographical distribution in shaping population structure and specifying patterns of genomic selection. Multiple adaptive events, involving genes implicated with autogeny, diapause and insecticide resistance were limited to specific populations. We estimate that about 5-20% of the genes (including several histone genes) and almost half of the annotated pathways were undergoing selective sweeps in each population. The high occurrence of sweeps in non-genic regions and in chromatin remodelling genes indicated the adaptive importance of gene expression changes. We hypothesize that global adaptive processes in the C. pipiens complex are potentially associated with South to North range expansion, requiring adjustments in chromatin conformation. Strong local signature of adaptation and emergence of hybrid bridge vectors necessitate genomic assessment of populations before specifying control agents.

Adaptation, Biological↗
PubMed2026

A pangenome framework uncovers the role of deletions in repeated evolution of cave-derived traits.

Structural variants (SVs) are increasingly recognized as key contributors to adaptive evolution, yet they remain underexplored compared with single-nucleotide variation. To understand how large-scale genomic changes shape repeated evolution, we leveraged multiple levels of sequence data across the powerful evolutionary model system of the Mexican tetra fish (Astyanax mexicanus). We constructed one of the first pangenome graphs from a naturally evolving vertebrate, enabling comprehensive discovery of SVs among 120 fish from 11 populations. We discover substantial amounts of structural variation and explore the roles of genomic biases and selection in shaping the distribution of these variants. More than 2400 high-confidence cave-specific deletions are enriched in biological pathways involved in vision, metabolism, and behavior and cluster nonrandomly in quantitative trait loci linked to cavefish traits. Additionally, 67 genes harbor unique deletions between independent cavefish lineages. These reused genes show evidence of population-specific selection (99% contain selective sweeps compared with 8%-15% in genes lacking SVs), indicating that deletions likely rose in frequency through repeated positive selection rather than drift. Together, these results reveal that recurrent deletion events have repeatedly contributed to the evolution of cave-adapted phenotypes and highlight deletions as underexplored contributors of adaptive evolution in extreme environments.

Animals↗
PubMed2025

Integrative Genomic, Transcriptomic and Epigenomic Analysis Reveals cis-regulatory Contributions to High-altitude Adaptation in Tibetan Pigs.

The Qinghai-Tibet Plateau, characterized by its extreme environmental conditions, presents significant challenges to life, making it an ideal region for studying adaptation and evolution. Tibetan pigs, known for their high genetic diversity and exceptional adaptability to high altitudes, serve as excellent models for investigating high-altitude adaptation. While previous studies have extensively identified genetic determinants associated with high-altitude adaptation, the molecular mechanisms, particularly cis-regulatory patterns, remain poorly understood. Here, we conducted a selective sweep analysis using 484 genomes from Chinese and Western pig breeds across various altitudes, revealing 38.56 Mb of genomic regions under selection in Tibetan pigs. Enrichment analysis identified the lung as the primary functional tissue involved in high-altitude adaptation, supported by tissue-specific transcriptional and regulatory patterns observed between Tibetan and Meishan pigs (low altitude). By integrating genomic, RNA-seq, ATAC-seq, and H3K27ac HiChIP data, we constructed comprehensive enhancer-promoter regulatory maps of candidate genes and pinpointed promising genetic determinants associated with high-altitude adaptation, including SNPs in EPAS1, KLF13, SPRED1, and CFD. These loci were predicted to influence chromatin accessibility and the interactions of regulatory elements, with altered binding strength of relevant transcription factors. Further in vitro experiments confirmed that these loci function as allele-specific enhancers, modulating the expression of target genes. Our findings elucidate the regulatory basis of high-altitude adaptation in Tibetan pigs and provide valuable insights for exploring hypoxia-related diseases in livestock and humans.

Animals↗
PubMed2026

Integrative Genomic and Transcriptomic Insights into High-Altitude Adaptation in Changthangi Goats.

The Changthangi goat, native to the high-altitude Ladakh Plateau in northern India, thrives in oxygen-deficient environments above 4,000 m. This study investigated the genetic basis of high-altitude adaptation in Changthangi goats by integrating comparative genomics and transcriptomics, using the tropical lowland Jamunapari goat as a comparative model. Whole-genome sequence data from 15 individuals per breed were analyzed using complementary selection sweep metrics, including nucleotide diversity, Tajima's D, iHS, CLR, XP-EHH, and FST. These analyses identified candidate genomic regions under strong selective pressure, encompassing genes involved in hypoxia sensing (HIF-1α, HIF-2α/EPAS1, EGLN1), angiogenesis (VEGFA, AGGF1, ZEB1), cardiovascular regulation (PRKCB, ESR1, RYR2), mitochondrial and energy metabolism (ACADSB, ACSS3, ACSL1), cellular stress tolerance (BCL2, ATM), and thermogenesis (UCP1, FGF21). Unlike previous caprine studies that primarily infer hypoxia adaptation from genomic signals alone, our study integrates cardiac transcriptomics to demonstrate that genomic selection in Changthangi goats is accompanied by coordinated transcriptional remodeling across interconnected physiological systems in a physiologically relevant tissue. Comparative cardiac transcriptomic profiling revealed concordant expression divergence in genes associated with oxygen transport, vascular remodeling, mitochondrial function, substrate utilization, redox balance, and genome maintenance. This integrative multi-omics framework provides a mechanistic view of caprine high-altitude adaptation and highlights the value of combining genomic selection analyses with tissue-specific transcriptional profiling to resolve complex adaptive traits.

Animals↗