Population Genomic Data Research Articles

Deciphering genomic signatures in different Indian milch cattle breeds

In the present study, the population genomic data of different cattle breeds were explored to decipher the genomic regions affected due to selective events and reflected in the productive, reproductive, thermo-tolerance, and health-related traits. To find out these genomic deviations due to selective sweeps, four statistical tools (Tajima’s D, CLR, ROH, and iHS) were used on four indigenous cattle breeds. Several candidate genes were found to be related to milk production (ADARB, WDR70, and CA8), reproductive (PARN, FAM134B2, and ZBTB20), and health-related traits (SP110, CXCL2, CLXCL3, CXCL5, IRF8, and MYOM1). Our findings serve as a foundation for identifying selective sweeps responsible for the genetic variation of traits. These sweeps could hold functional significance for multiple cattle breeds across various subcontinents. However, to enhance the robustness of the results, further studies with high-density arrays or whole-genome sequencing, employing greater resolution and larger sample sizes, are warranted.

Integrative taxonomy of Metarhizium anisopliae species complex, based on phylogenomics combined with morphometrics, metabolomics, and virulence data

Metarhizium anisopliae (Clavicipitaceae, Hypocreales) is a globally distributed entomopathogenic fungus, which has been largely studied and used in agriculture for its potent entomopathogenicity. Since its taxonomic establishment as a member of Metarhizium, many closely related taxa have been described with highly similar morphology (cryptic species). A holotype specimen of M. anisopliae is not extant, and the ex-neotype strain (CBS 130.71) does not form a monophyletic clade with other strains, up to now, recognized as M. anisopliae sensu stricto. In this study, we have conducted an integrative taxonomic treatment of M. anisopliae sensu lato by including the ex-neotype strain of M. anisopliae, other unknown strains from our collections identified as M. anisopliae s. lat., as well as other known species that have been previously delimited as closely related but distinct to M. anisopliae. By including whole-genome sequencing, morphometric analysis, LC–MS based metabolomics, and virulence assays, we have demonstrated that M. anisopliae s. str. should also include M. lepidiotae (synonym), and that M. anisopliae s. str. differentiates from the other species of the complex by its metabolome and less severe entomopathogenicity. New taxa, namely M. hybridum, M. neoanisopliae and M. parapingshaense spp. nov., are proposed. The novel taxa proposed here have strong phylogenomics support, corroborated by fine-scale differences in the length/width of conidia/phialides, while the metabolomics and virulence data still largely overlap. We have also demonstrated via population genomics data the existence of local clonal lineages, particularly the one corresponding to the persistence of a biocontrol candidate strain that has been used in the field application for three years. This study showcases the utility of combining various data sources for accurate delimitation of species within an important group of fungal biocontrol agents against pest insects.

The genetic basis of the kākāpō structural color polymorphism suggests balancing selection by an extinct apex predator.

The information contained in population genomic data can tell us much about the past ecology and evolution of species. We leveraged detailed phenotypic and genomic data of nearly all living kākāpō to understand the evolution of its feather color polymorphism. The kākāpō is an endangered and culturally significant parrot endemic to Aotearoa New Zealand, and the green and olive feather colorations are present at similar frequencies in the population. The presence of such a neatly balanced color polymorphism is remarkable because the entire population currently numbers less than 250 birds, which means it has been exposed to severe genetic drift. We dissected the color phenotype, demonstrating that the two colors differ in their light reflectance patterns due to differential feather structure. We used quantitative genomics methods to identify two genetic variants whose epistatic interaction can fully explain the species' color phenotype. Our genomic forward simulations show that balancing selection might have been pivotal to establish the polymorphism in the ancestrally large population, and to maintain it during population declines that involved a severe bottleneck. We hypothesize that an extinct apex predator was the likely agent of balancing selection, making the color polymorphism in the kākāpō a "ghost of selection past."

Population Genomic Scans for Natural Selection and Demography.

Uncovering the fundamental processes that shape genomic variation in natural populations is a primary objective of population genetics. These processes include demographic effects such as past changes in effective population size or gene flow between structured populations. Furthermore, genomic variation is affected by selection on nonneutral genetic variants, for example, through the adaptation of beneficial alleles or balancing selection that maintains genetic variation. In this article, we discuss the characterization of these processes using population genetic models, and we review methods developed on the basis of these models to unravel the underlying processes from modern population genomic data sets. We briefly discuss the conditions in which these approaches can be used to infer demography or identify specific nonneutral genetic variants and cases in which caution is warranted. Moreover, we summarize the challenges of jointly inferring demography and selective processes that affect neutral variation genome-wide.

Genomic Diversity as a Key Conservation Criterion: Proof-of-Concept From Mammalian Whole-Genome Resequencing Data.

Many international, national, state, and local organizations prioritize the ranking of threatened and endangered species to help direct conservation efforts. For example, the International Union for Conservation of Nature (IUCN) assesses the Green Status of species and publishes the influential Red List of threatened species. Unfortunately, such conservation yardsticks do not explicitly consider genetic or genomic diversity (GD), even though GD is positively associated with contemporary evolutionary fitness, individual viability, and with future evolutionary potential. To test whether populations of genome sequences could help improve conservation assessments, we estimated GD metrics from 82 publicly available mammalian datasets and examined their statistical association with attributes related to conservation. We also considered intrinsic biological factors, including trophic level and body mass, that could impact GD and quantified their relative influences. Our results identify key population GD metrics that are both reflective and predictive of IUCN conservation categories. Specifically, our analyses revealed that Watterson's theta (the population mutation rate) and autozygosity (a product of inbreeding) are associated with the current Red List categorization, likely because demographic declines that lead to "listing" decisions also reduce levels of standing genetic variation. We argue that by virtue of this relationship, conservation organizations like IUCN could leverage emerging genome sequence data to help categorize Red List threat rankings (especially in otherwise data-deficient species) and/or enhance Green Status assessments to establish a baseline for future population monitoring. Thus, our paper (1) outlines the theoretical and empirical justification for a new GD-based assessment criterion, (2) provides a bioinformatic pipeline for estimating GD from population genomic data, and (3) suggests an analytical framework that can be used to measure baseline GD while providing quantitative GD context for consideration by conservation authorities.

Multi-omics combined to investigate potential druggable therapeutic targets for stroke: A systematic Mendelian randomization study and transcriptome verification

ObjectiveStroke is a highly prevalent and disabling disease whose disease mechanisms are not fully understood. The discovery of disease-associated proteins with genetic evidence of pathogenicity provides an opportunity to identify new therapeutic targets. MethodWe examined the observed and causal associations of thousands of plasma and inflammatory proteins that were measured using affinity-based proteomic assays. First, we pooled >3000 relevant proteins using a fixed-effects meta-analysis of 2 population-based studies involving 48,383 participants, then investigated the causal effects of stroke and its subtype-associated proteins by forward Mendelian randomization using cis-protein quantitative locus genetic tools identified from genome-wide association studies of these >48,000 individuals. To improve the accuracy of causal estimation, we implemented a systematic Mendelian randomization model that accounts for cascading imbalances between instruments and tested the robustness of causal estimation through multi-method analyses. To further validate the hypothesis that ginsenoside Rg1 monomer acts on the five protein targets screened for drug-targeted regulation, we conducted a comparative analysis of the mRNA (gene) expression levels of a limited number of genes in the brain tissues of different groups of SD rats. The druggability of the candidate proteins was investigated and the mechanism of action and potential targeting side effects were explored by Phenome-wide MR. ResultsSix circulating proteins were identified to have a significant genetic association with stroke (PFDR < 0.05). For example, in patients with cardioembolic stroke, higher genetically predicted APRT was associated with a lower risk of cardioembolic stroke (ORivw [95 % CI] = 0.641 [0.517, 0.795]; P = 5.25 × 10−5, ORSMR [95 % CI] = 0.572, [0.397, 0.825], PSMR = 0.003). Mediation analyses suggested that atrial fibrillation, angina pectoris, and heart failure may mediate the association of CD40L, LIFR, and UPA with stroke. Molecular docking revealed promising interactions between the identified proteins and glycosides. Transcriptomic sequencing in animal models indicated that ginsenoside Rg1 may act through APRT, IL15RA, and VSIR pathways, with APRT showing significant variability in mRNA sequencing expression. Phenome-wide MR of the six target proteins showed an overwhelming predominance of PFDR > 0.05, indicating less toxicity. ConclusionsThe present study provides genetic evidence to support the potential efficacy of targeting the three druggable protein targets for the treatment of stroke. This is achieved by triangulating population genomic and proteomic data. Furthermore, the study validates the pathway mechanisms by which APRT, IL15RA, and VSIR dock ginsenoside Rg1 in animal models. This will help to prioritize stroke drug development.

Constipation is associated with an increased risk of major adverse cardiac events in a UK population.

Traditional cardiovascular risk factors, including hypertension, only explain part of major adverse cardiac events (MACEs). Understanding what other risk factors contribute to MACE is essential for prevention. Constipation shares common risk factors with hypertension and is associated with an increased risk of several cardiovascular diseases. We hypothesized that constipation is an underappreciated risk factor for MACE. We used the population healthcare and genomic data in the UK Biobank (n = 408,354) to study the contribution of constipation (ICD10 K59.0) to the risk of MACE, defined by any episode of acute coronary syndrome (ACS), ischemic stroke, and heart failure (HF). Analyses were controlled for traditional cardiovascular risk factors. We also assessed genetic correlations (rg) between constipation and MACE. Constipation cases (n = 23,814) exhibited a significantly higher risk of MACE compared with those with normal bowel habits [odds ratio (OR) = 2.15, P < 1.00 × 10-300]. Constipation was also significantly associated with individual MACE subgroups, in order: HF (OR = 2.72, P < 1.00 × 10-300), ischemic stroke (OR = 2.36, P = 2.02 × 10-230), and ACS (OR = 1.62, P = 5.82 × 10-113). In comparison with patients with constipation-free hypertension, patients with hypertension with constipation showed significantly higher odds of MACE (OR = 1.68, P = 1.05 × 10-136) and a 34% increased risk of MACE occurrence (P = 2.3 × 10-50) after adjustment for medications that affect gut motility and other traditional cardiovascular risk factors. Finally, we detected positive genetic correlations between constipation and MACE subgroups ACS (rg = 0.27, P = 2.12 × 10-6), ischemic stroke (rg = 0.23, P = 0.011), and HF (rg = 0.21, P = 0.0062). We identified constipation as a potential risk factor independently associated with higher MACE prevalence. These findings warrant further studies on their causal relationship and identification of pathophysiological mechanisms.NEW & NOTEWORTHY Analyzing 408,354 participants of the UK Biobank, we show that constipation cases exhibited a significantly higher risk of major adverse cardiac events (MACEs) than those with regular bowel habits. In comparison with patients with constipation-free hypertension, patients with hypertension with constipation showed significantly higher odds of MACE and a 34% increased risk of subsequent MACE occurrence. Finally, we detected positive genetic correlations between constipation and MACE. This association holds potential for therapeutic exploitation and prevention based on individuals' risk assessment.

Discordance between taxonomy and population genomic data: An avian example relevant to the United States Endangered Species Act.

Population genomics can reveal cryptic biological diversity that may impact fitness while simultaneously serving to delineate relevant conservation units. Here, we leverage the power of whole-genome resequencing for conservation by studying 433 individual lesser prairie-chicken (Tympanuchus pallidicinctus; LEPC, a federally endangered species of conservation concern in the United States) and greater prairie-chicken (Tympanuchus cupido; GRPC, a legally huntable species throughout much of its range). The genomic diversity of two formally recognized distinct population segments (DPSs) of LEPCs is similar, but they are genetically distinct. Neither DPS is depleted of its genomic diversity, neither is especially inbred, and temporal diversity is relatively stable in both conservation units. Interspecific differentiation between the two species was only slightly higher than that observed between LEPC DPSs, due largely to bidirectional introgression. The high resolution provided by our dataset identified a genomic continuum between the two species such that individuals sampled from the hybrid zone were imperfectly assigned to their presumptive species when considering only their physical characteristics. The admixture between the two species is reflected in the spectrum of individual ancestry coefficients, which has legal implications for the "take" of individuals under the Endangered Species Act. Overall, our data highlight the recurring dissonance between static policies and dynamic species boundaries that are increasingly obvious in the population genomic era.

Extreme genetic signatures of local adaptation in a notorious rice pest, Chilo suppressalis

ABSTRACT Climatic variation stands as a significant driving force behind genetic differentiation and the evolution of adaptive traits. Chilo (C.) suppressalis, commonly known as the rice stem borer, is a highly destructive pest that crucially harms rice production. The lack of natural population genomics data has hindered a more thorough understanding of its climate adaptation, particularly the genetic basis underlying adaptive traits. To overcome this obstacle, our study employed completely resequenced genomes of 384 individuals to explore the population structure, demographic history, and gene flow of C. suppressalis in China. This study observed that its gene flow occurred asymmetrically, moving from central populations to peripheral populations. Using genome-wide selection scans and genotype-environment association studies, we identified potential loci that may be associated with climatic adaptation. The most robust signal was found to be associated with cold tolerance, linked to a homeobox gene, goosecoid (GSC), whose expression level was significantly different in low and high latitudes. Moreover, downregulating the expression of this gene by RNAi enhances its cold tolerance phenotypes. Our findings have uncovered and delved into the genetic foundation of the ability of C. suppressalis to adapt to its environment. This is essential in ensuring the continued effectiveness and sustainability of novel control techniques.

Modeling biases from low-pass genome sequencing to enable accurate population genetic inferences.

Low-pass genome sequencing is cost-effective and enables analysis of large cohorts. However, it introduces biases by reducing heterozygous genotypes and low-frequency alleles, impacting subsequent analyses such as demographic history inference. We developed a probabilistic model of low-pass biases from the Genome Analysis Toolkit (GATK) multi-sample calling pipeline, and we implemented it in the population genomic inference software dadi. We evaluated the model using simulated low-pass datasets and found that it alleviated low-pass biases in inferred demographic parameters. We further validated the model by downsampling 1000 Genomes Project data, demonstrating its effectiveness on real data. Our model is widely applicable and substantially improves model-based inferences from low-pass population genomic data.

Genome resequencing reveals population divergence and local adaptation of blacklegged ticks in the United States.

Tick vectors and tick-borne disease are increasingly impacting human populations globally. An important challenge is to understand tick movement patterns, as this information can be used to improve management and predictive modelling of tick population dynamics. Evolutionary analysis of genetic divergence, gene flow and local adaptation provides insight on movement patterns at large spatiotemporal scales. We develop low coverage, whole genome resequencing data for 92 blacklegged ticks, Ixodes scapularis, representing range-wide variation across the United States. Through analysis of population genomic data, we find that tick populations are structured geographically, with gradual isolation by distance separating three population clusters in the northern United States, southeastern United States and a unique cluster represented by a sample from Tennessee. Populations in the northern United States underwent population contractions during the last glacial period and diverged from southern populations at least 50 thousand years ago. Genome scans of selection provide strong evidence of local adaptation at genes responding to host defences, blood-feeding and environmental variation. In addition, we explore the potential of low coverage genome sequencing of whole-tick samples for documenting the diversity of microbial pathogens and recover important tick-borne pathogens such as Borrelia burgdorferi. The combination of isolation by distance and local adaptation in blacklegged ticks demonstrates that gene flow, including recent expansion, is limited to geographical scales of a few hundred kilometres.

The genome-wide signature of short-term temporal selection

Despite evolutionary biology's obsession with natural selection, few studies have evaluated multigenerational series of patterns of selection on a genome-wide scale in natural populations. Here, we report on a 10-y population-genomic survey of the microcrustacean Daphnia pulex. The genome sequences of [Formula: see text]800 isolates provide insights into patterns of selection that cannot be obtained from long-term molecular-evolution studies, including the following: the pervasiveness of near quasi-neutrality across the genome (mean net selection coefficients near zero, but with significant temporal variance about the mean, and little evidence of positive covariance of selection across time intervals); the preponderance of weak positive selection operating on minor alleles; and a genome-wide distribution of numerous small linkage islands of observable selection influencing levels of nucleotide diversity. These results suggest that interannual fluctuating selection is a major determinant of standing levels of variation in natural populations, challenge the conventional paradigm for interpreting patterns of nucleotide diversity and divergence, and motivate the need for the further development of theoretical expressions for the interpretation of population-genomic data.

Pitfalls and windfalls of detecting demographic declines using population genetics in long-lived species.

Detecting recent demographic changes is a crucial component of species conservation and management, as many natural populations face declines due to anthropogenic habitat alteration and climate change. Genetic methods allow researchers to detect changes in effective population size (Ne) from sampling at a single timepoint. However, in species with long lifespans, there is a lag between the start of a decline in a population and the resulting decrease in genetic diversity. This lag slows the rate at which diversity is lost, and therefore makes it difficult to detect recent declines using genetic data. However, the genomes of old individuals can provide a window into the past, and can be compared to those of younger individuals, a contrast that may help reveal recent demographic declines. To test whether comparing the genomes of young and old individuals can help infer recent demographic bottlenecks, we use forward-time, individual-based simulations with varying mean individual lifespans and extents of generational overlap. We find that age information can be used to aid in the detection of demographic declines when the decline has been severe. When average lifespan is long, comparing young and old individuals from a single timepoint has greater power to detect a recent (within the last 50 years) bottleneck event than comparing individuals sampled at different points in time. Our results demonstrate how longevity and generational overlap can be both a hindrance and a boon to detecting recent demographic declines from population genomic data.

Boundary Effects Cause False Signals of Range Expansions in Population Genomic Data.

Studying range expansions is central for understanding genetic variation through space and time as well as for identifying refugia and biological invasions. Range expansions are characterized by serial founder events causing clines of decreasing genetic diversity away from the center of origin and asymmetries in the two-dimensional allele frequency spectra. These asymmetries, summarized by the directionality index (ψ), are sensitive to range expansions and persist for longer than clines in genetic diversity. In continuous and finite meta-populations, genetic drift tends to be stronger at the edges of the species distribution in equilibrium populations and populations undergoing range expansions alike. Such boundary effects are expected to affect geographic patterns in genetic diversity and ψ. Here we demonstrate that boundary effects cause high false positive rates in equilibrium meta-populations when testing for range expansions. In the simulations, the absolute value of ψ (|ψ|) in equilibrium data sets was proportional to the fixation index (FST). By fitting signatures of range expansions as a function of ɛ |ψ|/FST and geographic clines in ψ, strong evidence for range expansions could be detected in data from a recent rapid invasion of the cane toad, Rhinella marina, in Australia, but not in 28 previously published empirical data sets from Australian scincid lizards that were significant for the standard range expansion tests. Thus, while clinal variation in ψ is still the most sensitive statistic to range expansions, to detect true signatures of range expansions in natural populations, its magnitude needs to be considered in relation to the overall levels of genetic structuring in the data.

A historical stepping-stone path for an island-colonizing cactus across a submerged "bridge" archipelago.

Here we use population genomic data (ddRAD-Seq) and ecological niche modeling to test biogeographic hypotheses for the divergence of the island-endemic cactus species Cereus insularis Hemsl. (Cereeae; Cactaceae) from its sister species C. fernambucensis Lem. The Cereus insularis grows in the Fernando de Noronha Islands (FNI), a Neotropical archipelago located 350 km off the Brazilian Atlantic Forest (BAF) coast. Phylogeographic reconstructions support a northward expansion by the common ancestor of C. insularis and C. fernambucensis along the mainland BAF coast, with C. insularis diverging from the widespread mainland taxon C. fernambucensis after colonizing FNI in the late Pleistocene. The morphologically distinct C. insularis is monophyletic and nested within C. fernambucensis, as expected from a progenitor-derivative speciation model. We tested alternative biogeographic and demographic hypotheses for the colonization of the FNI using Approximate Bayesian Computation. We found the greatest support for a stepping-stone path that emerged during periods of decreased sea level (the "bridge" hypothesis), in congruence with historical ecological niche modeling that shows highly suitable habitats on stepping-stone islands during glacial periods. The outlier analyses reveal signatures of selection in C. insularis, suggesting a putative role of adaptation driving rapid anagenic differentiation of this species in FNI.

Temporal challenges in detecting balancing selection from population genomic data.

The role of balancing selection in maintaining genetic variation remains an open question in population genetics. Recent years have seen numerous studies identifying candidate loci potentially experiencing balancing selection, most predominantly in human populations. There are however numerous alternative evolutionary processes that may leave similar patterns of variation, thereby potentially confounding inference, and the expected signatures of balancing selection additionally change in a temporal fashion. Here we use forward-in-time simulations to quantify expected statistical power to detect balancing selection using both site frequency spectrum- and linkage disequilibrium-based methods under a variety of evolutionarily realistic null models. We find that whilst site frequency spectrum-based methods have little power immediately after a balanced mutation begins segregating, power increases with time since the introduction of the balanced allele. Conversely, linkage disequilibrium-based methods have considerable power whilst the allele is young, and power dissipates rapidly as the time since introduction increases. Taken together, this suggests that site frequency spectrum-based methods are most effective at detecting long-term balancing selection (>25N generations since the introduction of the balanced allele) whilst linkage disequilibrium-based methods are effective over much shorter timescales (<1N generations), thereby leaving a large time frame over which current methods have little power to detect the action of balancing selection. Finally, we investigate the extent to which alternative evolutionary processes may mimic these patterns, and demonstrate the need for caution in attempting to distinguish the signatures of balancing selection from those of both neutral processes (e.g. population structure and admixture) as well as of alternative selective processes (e.g. partial selective sweeps).

Identification of novel homozygous asthenoteratospermia-causing ARMC2 mutations associated with multiple morphological abnormalities of the sperm flagella.

To identify the genetic causes of multiple morphological abnormalities in sperm flagella (MMAF) and male infertility in patients from two unrelated Han Chinese families. Whole-exome sequencing was conducted using blood samples from the two individuals with MMAF and male infertility. Hematoxylin and eosin staining and scanning electron microscopy were performed to evaluate sperm morphology. Ultrastructural and immunostaining analyses of the spermatozoa were performed. The HEK293T cells were used to confirm the pathogenicity of the variants. We identified two novel homozygous missense ARMC2 variants: c.314C > T: p.P105L and c.2227A > G: p.N743D. Both variants are absent or rare in the human population genome data and are predicted to be deleterious. In vitro experiments indicated that both ARMC2 variants caused a slightly increased protein expression. ARMC2-mutant spermatozoa showed multiple morphological abnormalities (bent, short, coiled, absent, and irregular) in the flagella. In addition, the spermatozoa of the patients revealed a frequent absence of the central pair complex and disrupted axonemal ultrastructure. We identified two novel ARMC2 variants that caused male infertility and MMAF in Han Chinese patients. These findings expand the mutational spectrum of ARMC2 and provide insights into the complex causes and pathogenesis of MMAF.

Transposition of HOPPLA in siRNA-deficient plants suggests a limited effect of the environment on retrotransposon mobility in Brachypodium distachyon.

Long terminal repeat retrotransposons (LTR-RTs) are powerful mutagens regarded as a major source of genetic novelty and important drivers of evolution. Yet, the uncontrolled and potentially selfish proliferation of LTR-RTs can lead to deleterious mutations and genome instability, with large fitness costs for their host. While population genomics data suggest that an ongoing LTR-RT mobility is common in many species, the understanding of their dual role in evolution is limited. Here, we harness the genetic diversity of 320 sequenced natural accessions of the Mediterranean grass Brachypodium distachyon to characterize how genetic and environmental factors influence plant LTR-RT dynamics in the wild. When combining a coverage-based approach to estimate global LTR-RT copy number variations with mobilome-sequencing of nine accessions exposed to eight different stresses, we find little evidence for a major role of environmental factors in LTR-RT accumulations in B. distachyon natural accessions. Instead, we show that loss of RNA polymerase IV (Pol IV), which mediates RNA-directed DNA methylation in plants, results in high transcriptional and transpositional activities of RLC_BdisC024 (HOPPLA) LTR-RT family elements, and that these effects are not stress-specific. This work supports findings indicating an ongoing mobility in B. distachyon and reveals that host RNA-directed DNA methylation rather than environmental factors controls their mobility in this wild grass model.

Population genomics and morphological data bridge the centuries of cyanobacterial taxonomy along the continuum of Microcoleus species

The filamentous cyanobacterium Microcoleus is among the most important global primary producers, especially in hot and cold desert ecosystems. This taxon represents a continuum consisting of a minimum of 12 distinct species with varying levels of gene flow and divergence. The notion of a species continuum is poorly understood in most lineages but is especially challenging in cyanobacteria. Here we show that genomic diversification of the Microcoleus continuum is reflected by morphological adaptation. We compiled a dataset of morphological data from 180 cultured strains and 300 whole genome sequences, including eight herbarium specimens and the type specimen of Microcoleus. We employed a combination of phylogenomic, population genomic, and population-level morphological data analyses to delimit species boundaries. Finally, we suggest that the shape of the filament apices may have an adaptive function to environmental conditions in the soil.

Taking a color photo: A homozygous 25-bp deletion in Bace2 may cause brown-and-white coat color in giant pandas

Brown-and-white giant pandas (hereafter brown pandas) are distinct coat color mutants found exclusively in the Qinling Mountains, Shaanxi, China. However, its genetic mechanism has remained unclear since their discovery in 1985. Here, we identified the genetic basis for this coat color variation using a combination of field ecological data, population genomic data, and a CRISPR-Cas9 knockout mouse model. We de novo assembled a long-read-based giant panda genome and resequenced the genomes of 35 giant pandas, including two brown pandas and two family trios associated with a brown panda. We identified a homozygous 25-bp deletion in the first exon of Bace2, a gene encoding amyloid precursor protein cleaving enzyme, as the most likely genetic basis for brown-and-white coat color. This deletion was further validated using PCR and Sanger sequencing of another 192 black giant pandas and CRISPR-Cas9 edited knockout mice. Our investigation revealed that this mutation reduced the number and size of melanosomes of the hairs in knockout mice and possibly in the brown panda, further leading to the hypopigmentation. These findings provide unique insights into the genetic basis of coat color variation in wild animals.