Biology subjects

Guo, K.

Publications and source records attributed to Guo, K..

At least 19 recordsLinked to original sources

bioRxiv2026

Dynamic merging of enhancer- and promoter-associated assemblies is coupled to transcriptional bursting

Classical models attribute distal enhancer function to chromatin looping, whereas emerging models propose that spatially organized assemblies of transcriptional regulators also facilitate enhancer-promoter communication. To investigate how these processes relate to transcription, we developed an endogenous-tagging-based four-color live-cell imaging platform and an integrated quantitative analysis pipeline in mouse embryonic stem cells (mESCs), enabling simultaneous visualization of regulatory assembly dynamics, chromatin organization and transcriptional bursting at the endogenous Sox2 locus. We find that the pluripotency transcription factor OCT4 and the coactivator BRD4 form numerous spatially distinct but dynamically interacting assemblies. At non-bursting Sox2 alleles, the promoter and the distal Sox2 enhancer SCR occupy distinct assembly environments, with stronger BRD4 association at the SCR than at the promoter. At bursting Sox2 alleles, transcription is coupled to transient merging and partial overlap of enhancer- and promoter-associated assemblies, with the SCR, promoter and nascent RNA frequently sharing OCT4/BRD4-enriched assembly environments across a broad range of SCR-promoter distances. Pharmacological perturbation of bromodomain-dependent BRD4 function preferentially suppresses long-duration, high-amplitude bursts. Together, our findings support a model in which transcriptional bursting is coupled to the dynamic reorganization and merging of enhancer- and promoter-associated regulatory assemblies, linking chromatin-looping and assembly-based views of enhancer-promoter communication.

molecular biology↗

bioRxiv2026

Graded and cross-reactive JAK-receptor interactions broaden the one-receptor, one-JAK rule

Cytokine receptors signal through a dedicated Janus kinase (JAK) that is thought to be constitutively bound to the receptor intracellular domain (ICD). We tested this one-receptor, one-JAK model biophysically. A bead-based screen of JAK1 and TYK2 against 32 receptor ICDs, confirmed by microscale thermophoresis to measure affinity, revealed dissociation constants spanning tens of nanomolar to tens of micromolar, indicating that many interactions are not high-affinity and may not be constitutive. Binding was also widely cross-reactive: GMCSFR bound both JAK1 and TYK2, and IL2R{beta} bound TYK2 far more tightly than JAK1. In cells, GM-CSF signaled through JAK1 when JAK2, JAK3, and TYK2 were inhibited. JAK-receptor pairing is therefore permissive and graded rather than exclusive and constitutive.

biochemistry↗

bioRxiv2026

DiffRhyShiny: A Benchmarking-Informed Platform for Differential Rhythmicity Analysis with Dependence-Aware Evidence Integration

Motivation: Differential rhythmicity analysis identifies condition-specific changes in biological oscillations, but diverse algorithmic assumptions complicate method selection. Furthermore, integrating complementary evidence across different tools while accounting for statistical dependence remains an unresolved challenge. Results: We benchmarked seven algorithms across diverse rhythmic scenarios, revealing that optimal selection depends heavily on specific biological variations and experimental designs. To overcome single-algorithm limitations, we introduced Kost's Method, a dependence-aware p-value integration approach. Building on this framework, we developed DiffRhyShiny, an interactive web platform that automates robust differential rhythmicity analysis, consensus evaluation, and visualization. Furthermore, we validated the platform's performance and statistical rigor using both extensive simulated scenarios and real-world transcriptomic datasets. Availability and implementation: DiffRhyShiny is freely available at https://omicsai.shinyapps.io/diffrhyshiny, with the latest source code at https://github.com/liuchuan111/diffrhyshiny. The code and data to reproduce all benchmarking results are archived on Figshare at https://doi.org/10.6084/m9.figshare.33070100.

bioinformatics↗

bioRxiv2026

TFAM Dependent Mitochondrial Fitness Limits CD8⁺ T Cell Immunopathology and Sustains Protective Immunity during Viral Pneumonia

During respiratory virus infection, CD8 T cells kill infected cells and establish antigen-specific memory, but mechanisms regulating these functions remain incompletely understood. Here, we identify mitochondrial transcription factor A (TFAM)-dependent mitochondrial fitness as a regulator of CD8 T cell function during influenza infection. Human CD8 T cells exhibited an age-associated decline in TFAM expression and mitochondrial function. To model this physiologically relevant decline and determine its consequences for antiviral immunity, we generated CD8 T cell-specific TFAM-haploinsufficient mice. TFAM insufficiency disrupted mitochondrial integrity and bioenergetics and increased mitochondrial DNA and oxidative stress. During influenza infection, TFAM-insufficient CD8 T cells exhibited increased cytotoxic and inflammatory activity associated with lung immunopathology without improved viral control. This early phenotype was followed by loss of effector function, diminished antigen-specific responses, reduced protection following adoptive transfer, and impaired heterosubtypic recall immunity. Thus, TFAM-dependent mitochondrial fitness is a cell-intrinsic regulator that limits immunopathology while sustaining recall immunity.

immunology↗

bioRxiv2026

Shank3 mutation disrupts affective touch encoding in the dorsal medial prefrontal cortex of Beagle dogs

Individuals with autism spectrum disorder (ASD) often show aversion to affective touch (AT). However, the neural mechanism of this abnormality in cortices remains poorly understood probably due to the lack of effective animal models. Here, we used a canine model to address this issue by leveraging the intimate dog-human interactions. In a newly-designed heterospecific AT paradigm, we found that dogs carrying mutations in Shank3, a high-risk gene for ASD, avoided human AT. In vivo single-unit recording analysis showed that AT-evoked oscillations in the dorsal medial prefrontal cortex (dmPFC) were significantly altered in Shank3 mutant dogs. Shank3 mutation also reduced the number of neurons encoding AT in the dmPFC. Importantly, the aversion to AT and altered neural processing in Shank3 mutants were largely rescued by a GABAA receptor antagonist pentylenetetrazole. Together, these findings provide neural mechanisms for abnormal AT processing in ASD and suggest potential biomarkers for therapeutic strategies.

neuroscience↗

bioRxiv2026

Local IFNγ signaling contributes to the regenerative decline of aged alveolar progenitor cells

The lungs are highly susceptible to chronic disease in advanced age, likely due to the uniquely compromised repair function of alveolar type II (AT2) cells, facultative progenitor cells that maintain the gas exchange surface. Using aging mouse models, single-cell sequencing, and ex vivo organoid assays, we found that homeostatic aged AT2 cells exhibited an Interferon {gamma} (IFN{gamma}) response associated with IFN{gamma}+ CD8+ T cells in tertiary lymphoid structures (TLS). Aged AT2 cells exhibit impaired regeneration in organoid assays and lost markers of an IFN{gamma} response outside the lung microenvironment, demonstrating that elevated local IFN{gamma} influences the state of AT2 cells. Neutralization of IFN{gamma} signaling and immunoproteasome knockout mice with attenuated IFN{gamma} levels partially rescued aged AT2 cell regeneration. Our findings demonstrate that local IFN{gamma} signaling in aging lungs actively represses alveolar regeneration, establishing chronic inflammatory signaling as a cause of age-related decline in the lung. Halting chronic inflammatory processes restored alveolar regeneration and may provide a means to improve lung health in old age.

cell biology↗

bioRxiv2026

ProtoCloud: a Prototypical Self-explaining Model for Single-cell Analysis

Cell type annotation is a fundamental task in single-cell genomics. Although various methods have been developed for automatic cell type annotation, they often function as black-box models, making predictions without explaining their reasoning and lacking proper uncertainty estimation for their predictions. Furthermore, they often struggle to annotate rare cell types. We introduce ProtoCloud, a self-explaining deep generative model trained end-to-end to embed cells into a structured, low-dimensional space organized around cell type-specific prototypes. Coupled with a specifically-designed data augmentation strategy, it matches or outperforms existing methods in cell type annotation across 11 large-scale datasets, particularly for rare cell types. Moreover, ProtoCloud improves data annotation quality by identifying and re-annotating mis-annotated training cells through a built-in certainty quantification mechanism based on cell-prototype similarity. Finally, ProtoCloud provides interpretable predictions by identifying key genes that drive its classifications, facilitating the discovery of both known and novel cell type marker genes. Applied to a time-course dataset of post-injury retinal neurons, ProtoCloud successfully annotates previously unassigned cells; on the esophageal cell atlas, it identifies rare but potentially important cell populations and their marker genes relevant to esophageal inflammation.

genomics↗

bioRxiv2025

Reciprocal Homoeologous Replacement of MYB Factors Drives the Evolutionary Trade-off between Yield and Fiber Quality in Cotton

The long-standing phenotypic trade-off between Upland cotton (Gossypium hirsutum, high yield) and Sea Island cotton (G. barbadense, high quality) represents a major bottleneck in cotton breeding and industrialization. Despite rapid advances in genomics, the genomic structural variations driving the divergence of these two domestication strategies, and their subsequent impact on downstream transcriptional networks, remain unclear. This study integrates multi-tissue transcriptomic atlases spanning the full growth period with pan-genomic analyses of both Upland and Sea Island cotton, proposing a "Reciprocal Selective Retention (RSR)" strategy adopted by the two species during evolution. Transcriptomic analysis revealed that while the transcriptional chassis of the two species is highly conserved, a drastic "phase inversion" occurs during fiber development. Sea Island cotton appears to trade off for quality by specifically activating a "delayed elongation" module (at 20 DPA), whereas Upland cotton initiates a "precocious filling" program to pursue yield. Further Weighted Gene Co-expression Network Analysis (WGCNA), combined with genomic Presence/Absence Variation (PAV) analysis, identified a set of key transcription factors exhibiting a "3-vs-3" reciprocal loss pattern. Upland cotton specifically retained CRF10, WIND1, and MYB93, constructing a genetic foundation of "robust root system and strong regeneration" to support high yield. Conversely, Sea Island cotton specifically retained MYB111 and ERF105/017 to maintain long-staple characteristics and environmental buffering. Whole-genome structural variation and microsynteny analyses confirmed that these differences stem from asymmetric physical deletions (e.g., a 5 kb deletion in MYB111) or fragment sequence collapse (e.g., a 15.9 kb sequence divergence in MYB93) on homologous chromosomes. The RSR model proposed in this study not only offers a novel insight into the genetic roots of the negative correlation between yield and quality but also provides clear genomic targets for precision improvement using gene-editing technologies such as CRISPR.

genomics↗

bioRxiv2025

A Combinatorial mRNA Therapy for Treating Rheumatoid Arthritis and Osteoarthritis by Inhibiting Inflammation and Promoting Cartilage Regeneration

Rheumatoid arthritis (RA) and osteoarthritis (OA) are debilitating joint disorders with distinct etiologies but share common pathological features of chronic inflammation and progressive cartilage damage. Current therapeutic options are largely palliative and yet fail to achieve desired effect. In this study, we developed a combinatorial mRNA therapy using a rationally engineered lipid nanoparticle (LNP) containing a novel ionizable lipid for enhanced cartilage penetration upon intra-articular administration. This LNP co-delivers mRNAs encoding two complementary therapeutic proteins: interleukin-1 receptor antagonist (IL-1Ra) for inflammation attenuation and a C-terminal truncated derivative of angiopoietin-like 3 (ANL3) for cartilage regeneration. In pre-clinical models including collagen-induced arthritis mice, TNF-transgenic mice with spontaneous RA and destabilization of medial meniscus (DMM) surgical OA model, this "one-shot" combinatorial therapy significantly ameliorated disease severity, reduced synovitis and bone erosion, and potently promoted the regeneration of hyaline-like cartilage. Mechanistically, transcriptomic profiling of joint specimens revealed that the combinatorial therapy concurrently suppressed inflammatory pathways and extracellular matrix degradation pathways, meanwhile upregulating anabolic genes facilitating chondrogenesis. Collectively, our study establishes a versatile and synergistic mRNA therapy that offers a potent disease-modifying immunomodulatory strategy capable of addressing the long-standing unmet needs in arthritis treatment.

immunology↗

bioRxiv2025

NF-κB driven inflammation mediates loss of upper airway epithelial tolerance to Streptococcus pneumoniae during influenza co-infection

Streptococcus pneumoniae asymptomatically colonizes the human nasopharynx, where epithelial tolerance maintains mucosal homeostasis. However, influenza A virus (IAV) co-infection transforms this tolerogenic state into an inflammatory environment that promotes bacterial outgrowth and invasion. Here, we identify a TGF-{beta}1 dependent epithelial program that sustains mucosal tolerance during Spn colonization and demonstrate that IAV co-infection disrupts this pathway through IL-17RA-NF-{kappa}B driven inflammation in the nasopharynx. In a murine colonization model, TGF-{beta}1 blockade enhanced pro-inflammatory cytokine production and neutrophil recruitment, resulting in inflammation-driven Spn clearance. IAV co-infection suppressed epithelial TGF-{beta}1 signaling, increased TRAF6/NF-{kappa}B activation, and impaired tight junction integrity, leading to Spn dissemination. Mechanistically, IL-17RA signaling contributed to the hyperactivation of the TRAF6/NF-{kappa}B axis. Pharmacologic inhibition of TRAF6 or NF-{kappa}B restored epithelial barrier function and reduced Spn translocation in a human air-liquid interface nasopharyngeal epithelial model. These findings reveal a conserved epithelial signaling axis through which influenza disrupts mucosal tolerance and promotes Spn invasion, highlighting the canonical TRAF6-NF-{kappa}B pathway as a potential therapeutic target to preserve epithelial integrity and mitigate Spn infection during viral-bacterial co-infection of the upper respiratory tract.

immunology↗

bioRxiv2025

Genomic prediction of disease resistance provides a path to marker assisted restoration in a wetland foundation tree species

Tree species worldwide are under threat from non-native pathogens that impact forests and the ecosystem services they provide. Myrtle rust, caused by Austropuccinia psidii, is one example, first detected in Australia in 2010. This fungal pathogen infects immature tissue from a wide range of Myrtaceae hosts, including the wetland foundation species Melaleuca quinquenervia. Durable restoration action for this species would preferentially incorporate disease resistant individuals. Our aim for this study was to provide a molecular assay to identify and select resistant individuals and seed lots for restoration. We conducted artificial inoculation of a panel of seedlings and measured their immune responses to myrtle rust. We then performed whole genome sequencing (3.2M common SNPs) and conducted a Genome Wide Association Study (N = 492), which revealed clusters of significantly associated SNPs in three chromosomal regions, including clusters of putative R genes. Associated SNPs were filtered to a panel of 1,049 for a highly accurate genomic prediction model (R = 0.83). This provides a relatively inexpensive approach to identifying resistant individuals or seed lots for restoration and a template for managing myrtle rust impacts while maintaining population genetic diversity.

plant biology↗

bioRxiv2025

Targeting ZNRF3 and RNF43 to Restore Regeneration and Reverse Metabolic Dysfunction-Associated Steatotic Liver Disease

Liver regeneration and hepatocyte metabolic identity are disrupted in metabolic dysfunction-associated steatotic liver disease (MASLD) and its advanced form, metabolic dysfunction-associated steatohepatitis (MASH), yet the mechanisms of restore liver regeneration and reprogram metabolism for disease reversal remains poorly understood. Here, we show that {beta}-Catenin activity progressively declines in hepatocytes during MASH in both humans and mice, coinciding with impaired regeneration and defective lipid clearance. Targeted deletion of the endogenous WNT pathway inhibitors ZNRF3 and RNF43 in hepatocytes after MASH onset reactivates {beta}-Catenin signaling, leading to robust regression of steatosis, inflammation, and fibrosis, and restoring regenerative capacity across multiple fatty liver disease models. Mechanistically, this therapeutic effect is driven by {beta}-Catenin-dependent induction of the alternative bile acid synthesis pathway without disrupting systemic lipid homeostasis. Importantly, both short-and long-term deletion of ZNRF3/RNF43 restores liver function without triggering tumorigenesis or hepatotoxicity, indicating a safe therapeutic window. These findings reveal that physiological activation of WNT/{beta}-catenin signaling via ZNRF3 and RNF43 offers a viable regenerative and metabolic strategy for reversing fatty liver disease.

cell biology↗

bioRxiv2025

Opposing effects of systemic and pancreas-specific inhibition of BCKDK on pancreatic carcinogenesis

Branched-chain amino acid (BCAA) metabolism is perturbed in patients with pancreatic cancer, but the contribution of systemic or pancreas-intrinsic BCAA catabolism to pancreatic carcinogenesis is unclear. We show here that pancreas-specific loss of DBT, the E2 subunit of the branched-chain keto-acid dehydrogenase (BCKDH) complex required for BCAA oxidation, strikingly exacerbates premalignant pancreatic intraepithelial neoplasia (PanIN) lesions in KC (p48-Cre;KrasLSL-G12D/+) mice. However, deletion of upstream enzyme BCAT2 neither phenocopied nor rescued loss of DBT in KC mice, ruling out involvement of both upstream and downstream metabolites as mediators of PanIN promotion. Instead, we observed that DBT deficiency led to loss of the kinase BCKDK, a negative regulator of the BCKDH complex, and that, remarkably, pancreas-specific loss of BCKDK phenocopied DBT deficiency in accelerating PanIN formation. These data thus support a model in which pancreas BCKDK restrains tumorigenesis. In contrast, systemic treatment of KC mice with the BCKDK inhibitor BT2, which inhibits BCKDH phosphorylation across many tissues except the pancreas, reduced PanIN formation and preserved normal acinar area. Together the data reveal the promotion of BCAA catabolism systemically, but not within the pancreas, as a promising intervention strategy to suppress tumor initiation.

cancer biology↗

bioRxiv2025

Molecular Mechanisms of Chinese Medicine in Regulating Colorectal Cancer Immune Microenvironment: Insights from Single-Cell Transcriptomics and Network Pharmacology

BackgroundThe molecular mechanisms underlying the efficacy of Traditional Chinese Medicine (TCM) in colorectal cancer treatment remain largely unexplored. We developed a computational systems biology approach integrating single-cell transcriptomics with network pharmacology to elucidate the potential mechanisms of TCM in modulating colorectal cancer progression. MethodsWe developed an integrated computational pipeline for multi-omics data analysis combining single-cell transcriptomics with network pharmacology. Raw single-cell RNA-seq data from 3 normal tissues and 3 colorectal tumors were obtained from GEO database and processed using a customized workflow in R. Quality control, normalization, and dimensionality reduction were performed using the Seurat v4.0 algorithm, followed by unsupervised clustering to identify cell subpopulations. Differentially expressed genes (DEGs) were identified using MAST algorithm with adjusted p-value < 0.05 and |log2FC| > 1.0. These computationally identified DEGs were subsequently mapped to a comprehensive Traditional Chinese Medicine (TCM) database using a network pharmacology approach to predict herb-target interactions. In parallel, we integrated TCGA RNA-seq data (STAR-counts) with clinical information, applying log2(TPM+1) transformation for normalization. We then implemented a machine learning-based correlation analysis to construct gene-cell-immunity-pathway networks, using weighted gene co-expression network analysis (WGCNA) to identify key regulatory modules. ResultsOur computational analysis of single-cell RNA-seq data identified 109 differentially expressed genes (DEGs) that define the molecular signature of colorectal cancer microenvironment. Clustering algorithms revealed 14 distinct cell subpopulations, with predominant immune cell infiltration, particularly B and T lymphocytes, suggesting a complex immune regulatory network. Network pharmacology analysis mapped these DEGs to potential therapeutic targets, computationally predicting interactions with 140 traditional Chinese herbs. These herbs were classified into 8 functional categories. Through integrative multi-omics analysis and pathway enrichment algorithms, we identified core regulatory networks comprising 23 genes and 39 significantly enriched signaling pathways (FDR < 0.01) that orchestrate immune cell function in the tumor microenvironment. Notably, our analysis in silico revealed previously uncharacterized gene-pathway interactions that may explain the immunomodulatory effects of specific herbal compounds. ConclusionsOur systems biology and computational analysis revealed a potential mechanism by which 8 categories of Chinese herbal medicines and 23 genes across 39 signaling pathways may regulate colorectal cancer progression through modulation of specific gene regulatory networks and immune cell functions. These findings demonstrate the value of integrative computational approaches in elucidating complex biological mechanisms of traditional medicines

immunology↗

bioRxiv2025

Revealing the unexpected interplay between the Proteasome Activator PA200 and the immunoproteasome

The proteasome activator PA200 binds to the catalytic core of the proteasome, the 20S, and activates its proteolytic activities. The cellular function of PA200 is poorly understood and appears to be cell type and differentiation specific. Recent evidence suggests that PA200 not only binds to the standard 20S (s20S) proteasome but also to the specialized immunoproteasome (i20S) which plays a key role in anti-viral and anti-tumor immunity. We here investigated the interaction of PA200 and the immunoproteasome in detail. We show the very first cryo-EM structures of the singly- and doubly-capped i20S-PA200 complexes that revealed no major difference regarding the first binding event of PA200 to the i20S vs. the s20S. However, first PA200 binding triggered a subtle and long range allosteric bending of the i20S barrel which was not seen in the s20S-PA200 complexes. This resulted in major structural rearrangements in the opposite unbound ring - the displacement of atoms up to 5.4 [A] and the increase in its outer diameter - thereby increasing the occupancy of the second PA200 binding site. Mass photometry confirmed higher occupancy of PA200 to the i20S versus the s20S. Binding of PA200 to the i20S enhanced proteasomal activation compared to the s20S. Co-expression of PA200 and the i20S in cells and tissues, however, is restricted but their interaction is favored upon co-expression. The expression of PA200 and the catalytic subunits of the i20S is differentially regulated depending on the cellular context. Our data also suggest that PA200 has the potential to regulate i20S gene expression whereas the i20S has no effects on PA200 expression. Overall, this work sheds new light on the interaction of PA200 with the i20S from a structural, mechanistic and cellular point of view. Importantly, we identify PA200 as a key regulator of the i20S whenever PA200 and the catalytic subunits of the i20S are co-expressed in the same cell.

biochemistry↗

bioRxiv2025

Leveraging mRNA platform for the development of vaccines against egg allergy

Food allergy has posed a major global health burden due to the rising prevalence and lack of effective prophylactic strategies. During the past decades, allergen-specific immunotherapy (AIT) has been used as a disease-modifying therapy for food allergic conditions, but due to the long-term treatment duration, poor patient compliance and unexpected adverse reactions, only a minority of patients benefit from AIT therapy. In this proof-of-concept study, using well-established mRNA platform, we developed mRNA vaccine candidates encoding for the major egg white allergen Gal d2 (also known as ovalbumin) and comprehensively evaluated the prophylactic efficacy against anaphylaxis in a Gal d2-induced allergic mouse model. Two vaccine formulations, Gal d2 mRNA vaccine and Gal d2-IL-10 mRNA vaccine, both demonstrated effective ability in preventing the onset of allergic disease, which is largely attributed to the versatilities of mRNA vaccine in eliciting allergen-blocking antibody, shifting Th2 towards Th1 immunity, as well as in generating peripheral tolerance.

immunology↗

bioRxiv2024

Spatial Perturb-Seq: Single-Cell Functional Genomics within Intact Tissue Architecture

We develop Spatial Perturb-Seq, an in vivo CRISPR technology that interrogates multiple genes within single cells of intact tissues. We apply Spatial Perturb-Seq to screen risk genes for neurodegenerative diseases in the mouse brain, uncovering cell autonomous and cell-cell microenvironmental effects within the spatially intact tissue. Spatial Perturb-Seq functionally screens multiple genes in situ and in vivo, identifying candidate genes underlying dysregulated neuronal intercellular communication pathways in Lrp1 signalling and ephrin-Eph receptor interactions.

cell biology↗

bioRxiv2024

Genomics and resistance assays inform the management of two tree species being devastated by the invasive myrtle rust pathogen

Myrtle rust is a plant disease caused by the invasive fungal pathogen Austropuccinia psidii (G. Winter) Beenken, which has a global host list of 480 species. It was detected in Australia in 2010 and has caused the rapid decline of native Myrtaceae species, including rainforest trees Rhodamnia rubescens (Benth.) Miq. (scrub turpentine) and Rhodomyrtus psidioides (G.Don) Benth. (native guava). Ex situ collections of these species have been established, with the goal of preserving remaining genetic variation. Analysis of reduced representation sequencing (DArTseq; n = 444 for R. rubescens and n = 301 for R. psidioides) showed genetic diversity is distributed along a latitudinal gradient across the range of each species. A panel of samples of each species (n = 27 for R. rubescens and n = 37 for R. psidioides) were resequenced at genome scale, revealing large historical e]ective population sizes, and little variation among individuals in inferred levels of deleterious load. In Rhodamnia rubescens, experimental assays (n = 297) identified individuals that are putatively resistant to myrtle rust. This highlights two important points: there are tangible pathways to recovery for species that are highly susceptible to rust via a genetically informed breeding program, and there is a critical need to act quickly before more standing diversity is lost.

genomics↗