Cucurbita ficifolia is one of the squash species most resistant to fungal pathogens, and has especially high resistance to melon Fusarium wilt. This species is therefore an important germplasm resource for the breeding of squash and melon cultivars.C. ficifolia were high, but that different populations showed no significant genetic differentiation or geographical structure, and that individual C. ficifolia plants with fruit rinds of a similar color did not form independent clusters. A Mantel test conducted in combination with geographical distance and environmental factors suggested that genetic distance was not correlated with geographical distance, but had a significant correlation with environmental distance. Further associations between the genetic data and five environmental factors were analyzed using whole-genome association analysis. SNPs associated with each environmental factor were investigated and genes 250 kb upstream and downstream from associated SNPs were annotated. Overall, 15 marker-trait-associated SNPs (MTAs) and 293 genes under environmental selection were identified. The identified genes were involved in cell membrane lipid metabolism, macromolecular complexes, catalytic activity and other related aspects. Ecological niche modeling was used to simulate the distribution of C. ficifolia across time, from the present and into the future. We found that the area suitable for C. ficifolia changed with the changing climate in different periods.Whole-genome resequencing of 223 individuals from 32 populations in Yunnan Province, the main cucurbit production area in China, was performed and 3,855,120 single-nucleotide polymorphisms (SNPs) and 1,361,000 InDels were obtained. SNP analysis suggested that levels of genetic diversity in C. ficifolia accessions has allowed identification of genetic markers, such as SNPs and InDels. The SNPs identified in this study suggest that environmental factors mediated the formation of the population structure of C. ficifolia in China. These SNPs and Indels might also contribute to the variation in important pathways of genes for important agronomic traits such as yield, disease resistance and stress tolerance. Moreover, the genome resequencing data and the genetic markers identified from 223 accessions provide insight into the genetic variation of the C. ficifolia germplasm and will facilitate a broad range of genetic studies.Resequencing of the The online version contains supplementary material available at 10.1186/s12870-023-04602-3. A common topic in ecological genetics is the effect of a changing environment on the distribution and composition of genetically variable populations , as wellCurcubita ficifolia Bouché (Cucurbitaceae) is a short-day plant, is sensitive to temperature and is not heat-resistant. The plant is monoecious and has unisexual flowers. It is known as “black seed squash” in English after its black seeds, and the Chinese name translates "rice noodle squash" or "Black Seeded’ figleaf squash" in Chinese [C. ficifolia is a trailing herb with perennial roots. In sunny, warm environments, the plant grows as a perennial, but in areas that get severe winter frosts, the roots die off over winter and the plant grows as an annual. New vines can grow as much as 20 m in a year, and more than 50 high-yield squashes can be produced per plant in this time [C. ficifolia has strong resistance to a number of environmental stresses, including cold and drought, it grows well on barren soils and is also resistant to several diseases. The species also shows a particularly high resistance to melon Fusarium wilt and is therefore an important germplasm resource for the breeding of new cucurbit cultivars. Chinese  as the fhis time . A singlhis time . The ripC. ficifolia. Some studies have focused on its pharmacological effects, and C. ficifolia extract has been found to increase the secretion of insulin, playing an important role in lowering blood sugar and can therefore be helpful in the treatment of diabetes [C. ficifolia extracts can also modulate systemic chronic inflammation in obese mice, where they may have beneficial effects on the adaptive immune system [C. ficifolia as a rootstock onto which other species of Cucurbita can be grafted, and have found that C. ficifolia rootstocks confer improved yields and enhanced resistances to cold, salt and diseases including Fusarium wilt [C. ficifolia rootstock and grown in plastic greenhouses have increased foreign income from fresh produce in Liaoning, Shandong and several other provinces in China, by virtue of the early market supply and high quality of the grafted plants. Moreover, C. ficifolia has become an excellent germplasm resource for improving the disease resistance in new cultivars. Brazil exports the largest volume of C. ficifolia worldwide, and Japan imports the most [To date, there have been few studies investigating diabetes –14. C. fe system . Other sium wilt , 16–19. the most .C. ficifolia originated in Central and South America [C. ficifolia in China, but the species has a long history of cultivation in Yunnan, Sichuan, Guizhou and other higher altitude regions [C. ficifolia grows well at high altitudes, and much of Yunnan Province is thus suitable for its cultivation, with this province becoming the main production area in China. C. ficifolia is an important breeding germplasm resource for cucurbits, however, to date there have been only a few genetic studies investigating this species. In order to more effectively utilize and develop this species as a genetic resource, a better understanding of its genetic diversity, the extent by which its populations differ genetically and the factors underlying these patterns are required. America , and the America . There i regions . C. ficiCucurbita pepos, pumpkins, cucumbers, watermelons and melons, and many SNPs controlling horticulturally important phenotypes have been discovered [C. ficifolia in agriculture, the C. ficifolia genome has not to date been studied in depth. In this project, we investigated genetic variation in different C. ficifolia populations in Yunnan using whole-genome resequencing. The main aims of the study were: (1) to use whole-genome resequencing to obtain a library of SNP markers, and to evaluate genetic diversity in C. ficifolia in Yunnan, (2) to use population genetic approaches to elucidate the genetic structure of C. ficifolia within and among populations, as well as to investigate the evolutionary patterns behind rind of different colors, and (3) to analyze how geographical and environmental distances affect the genetic structure of C. ficifolia. The data will improve the utilization and development of C. ficifolia germplasm resources.Whole genome resequencing and genome-wide association studies (GWAS) have been used to investigate the genomes of several widely grown cucurbit crops, including scovered –28. HoweTwo hundred twenty-three individuals were collected from the field in Yunnan province of China. In order to avoid the homogenization of research materials, phenotypic traits were recorded and analyzed for all the samples. The length, breadth, and thickness of the seeds, the thousand seed weight were analyzed for each sample Fig. . The aveC. ficifolia individuals on an Illumina NovaSeq6000-sequencer generated 758.08 Gbp of clean data, with a total of 2.2 million 100 bp paired-end reads (332 Gb of sequence data), 93.63% of which had Q values ≥ 30. The average alignment rate of samples with the reference genome was 93.17%, the average depth of coverage was 9 × and the genome coverage was 66.11% (with at least one base coverage).There is, to date, no published genome information available for C. ficifolia. We mapped our resequencing data to whole genomes of four species of Cucurbita . The mapping rate to the C. moschata genome was found to be the highest (93.88%), and the C. moschata genome was therefore selected as the reference genome for this study. After mapping to the C. moschata reference genome [C. ficifolia samples are summarized in Fig. C. moschata genome as a reference. The densities of the genes, SNPs and InDels were evenly distributed over all 20 pseudochromosomes , and the genetic diversity of C. ficifolia was high, with a π of 0.354 (0.252–0.418). The expected heterozygosity (HE) was 0.319 (0.221–0.404), the observed heterozygosity (HO) was 0.392 (0.315–0.466), the polymorphism information content (PIC) was 0.251 (0.173–0.316) and the Shannon Wiener index (I) was 0.465 (0.320–0.587)  errors value reached the lowest value at K = 3, indicating that the optimal grouping of C. ficifolia was 3 ; white (-W); and decorative . The three rind colors did not form independent clusters in either the reconstructed phylogenetic tree or in our genetic structure analysis. However, individuals from the same local population, regardless of the color of the rind, tended to cluster in the same branch, indicating that individuals of different colors within the local population were closely related, while individuals with the same rind color from different regions were less related.The rind of r = 0.007; P = 0.176), although there was a more obvious relationship between genetic and environmental distances . In order to exclude interference from environmental or geographical factors, partial Mantel tests were conducted. These tests agreed with the simple Mantel tests, and showed no correlation between genetic and geographic distance ; when we controlled for geographical distance, genetic distance and environmental distance were still correlated   = 5 as the reference point, the five environmental factors were associated with a total of 15 MTAs  from the 32 sampling regions in an association analysis in order to identify any SNP sites associated with climate traits. We used several different statistical programs and simulations for this analysis, and performed comparisons in GEMMA (LM and LMM models), FaST-lmm, and EMMAX. The results varied to some extent with the different statistical models. The LM model of GEMMA found the greatest number of relevant marker-trait associated SNPs. Taking logTAs Fig. , using tC. ficifolia cell activity, molecular function and biological processes in response to different environmental conditions.Some genes, including “gene control cellular component: integral component of membrane” (GO: 0016021), “mitochondrial inner membrane” (GO: 0005743), and “spindle microtubule” (GO: 0005876) were revealed when we annotated the MTAs with duration of annual sunshine. This indicated that different durations of annual sunshine have an effect on the cell structure of C. ficifolia in different populations.A total of 293 genes within 250 kb of these MTAs (including both up- and downstream genes) were identified Table S. An enriC. ficifolia, we performed ecological niche modeling to simulate the distribution of C. ficifolia during the present distribution, and that in the future (2080). All models performed well, with AUC values > 0.9 (n = 10 replicate model runs) [C. ficifolia prefers a cooler environment, with a long growth period and fruit maturation in between November and January period. If it is too cold in winter, the fruit does not normally produce seed. Several years of data verification and field investigations suggest that the C. ficifolia populations in China are currently found mainly distributed in Yunnan and the surrounding areas. The distribution of C. ficifolia simulated by the ecological niche modeling based on environmental factors    in resequencing studies  [Citrullus colocynthis, π = 6.75 × 10−3) and citron melon  had much greater nucleotide diversity than did the watermelons Citrullus mucosospermus (π = 0.792 × 10−3) and C. lanatus (π = 0.56 × 10−3) [C. ficifolia has relatively high genetic variation, which could provide good germplasm resources for the breeding of novel cucurbit cultivars and the improvement of races. This resequencing study of different local Chinese populations of C. ficifolia will provide a good basis for subsequent investigations using GWAS and other means to explore the excellent genetic resources of this species.The study of genetic diversity provides insight into the origins and evolution, particularly the micro-evolution, of biodiversity. The information generated from these studies can inform animal and plant breeding programs . the gen × 10−3) . Similar × 10−3) , 27. C. Isolation brought about by geographical distance (IBD) and isolation from environmental distance (IBE) are recognized as important drivers of genetic differentiation –39. Gene FST value among Chinese populations of C. ficifolia was 0.03, indicating that the degree of genetic differentiation among different C. ficifolia populations was very small. However, the pairwise FST values between certain populations was extremely high, for example. YA and JD: 0.841  [C. ficifolia. Interestingly, the plants with green-rinded fruits have been shown to have greater resistance to Fusarium wilt than those with rinds of other colors [We found that individuals from the same population have a close genetic relationship, however, orative” . Individ. (1990) , who sayr colors .C. ficifolia occurred mostly due to environmental factors. C. ficifolia is a perennial plant, but grows as an annual in cold areas. In Yunnan, China, C. ficifolia is perennial, with a long annual growth cycle. The squash matures in December, and in the mild climate of Yunnan, the seeds mature. However, other parts of China are generally too cold in December for natural seed maturity. In other words, the growth and spread of C. ficifolia is sensitive to climate. The genetic distances observed between the C. ficifolia subpopulations in our study were obviously correlated with environmental distance, which supports our speculation. In order to verify this speculation, ecological niche modeling was used to simulate the distribution of C. ficifolia across time, from the present and into the future. The results from the ecological niche modeling suggest that the distribution of C. ficifolia will change again in the future. The analysis also suggested that environmental factors mediated the formation of the population structure in this species. As the global climate warms, the range of C. ficifolia will move northwards. In addition, because this species is a horticultural plant, human interference and the agricultural use of selected germplasms should also be considered to explain the observed population structure of C. ficifolia.From Mantel and partial Mantel tests, a correlation between genetic and environmental distance was revealed. We speculate that the patterns of genetic structure in C. ficifolia production areas in China. Between 3–19 individual plants were sampled from each of 32 locations . All 223 individuals were from landraces and samples were taken from plants at least 50 m apart.The length, breadth, and thickness of the seeds, the thousand seed weight and the squash rind color were recorded for each sample. Fresh leaf samples were stored at -80 °C and total DNA was extracted using the CTAB method [The sampling locations were chosen to cover the main B method . DNA wasCucurbita moschata [The Illumina NovaSeq6000 sequencing platform was used to randomly fragment the genomic DNA, and the fragments were used to construct libraries of ~ 450 base-pair (bp) inserts and to produce paired-end reads of 150 bp. The raw sequencing data were then filtered using fastp 0.21.0 with the parameters “fastp -q 10 -u 50 -y -g -Y 10 -e 20 -l 100 -b 150 -B 150”. Low-quality reads  and poly-Ns (regions where > 10% of the bases were Ns) were removed. Adapter sequences were trimmed from both ends of the reads and low-quality bases (Q ≤ 13) were removed. The clean reads were then compared with the reference genome moschata  using thmoschata . Samtoolmoschata  was usedSNPs and InDels were identified using GATK v3.8  with joipopulations program in the Stacks1.0 pipeline [HO); expected heterozygosity (HE); Nei’s genetic diversity (π)) for each SNP. The pairwise fixation index (FST) was calculated using Arlequin [The pipeline , 52 was Arlequin  to exami r2 value = 1 was assumed for a marker distance of 0 kb, and LD decay for each population was evaluated at a cut-off of r2 = 0.1.Linkage disequilibrium (LD) decay was calculated between pairs of polymorphic sites using PopLDdecay v3.41  with 3.8Cucurbita moschata. EIGENSOFT [PLINK51 v1.90  was usedIGENSOFT  was usedIGENSOFT ,  = 5 were also fixed as candidate regions. The candidate genes screened using the above thresholds were then functionally annotated. Quantile–quantile plots were used to determine the optimum model, and the linear models were tested by plotting P values obtained from the association tests against an expected probability distribution. A cut-off of 0.05 was used to determine significance.In the IBD test described above, we found that genetic distance was significantly correlated with environmental distance. Based on this, we investigated which of the SNPs responded to environmental factors. We used our resequenced SNPs data and the five key environmental factors mentioned above  from the 32 sampling regions in an association analysis in order to identify any SNP sites associated with climate traits. Each individual in the same population (location) was given the same environmental data, and geographical location, phenotypic information and meteorological factors for each individual were added to the analysis and are shown in Table SC. ficifolia, we applied ecological niche modeling (ENM) to simulate the distribution of C. ficifolia during the the present and in the future. ENM was performed in MAXENT v3.3.3 [C. ficifolia. In this experiment, we projected the model of climate suitability generated with ecological niche modeling using current climate data onto the global circulation model for the year 2080. The prediction performance analyses were evaluated in MAXENT by calculating the area under the receiver operation characteristic curve.In order to further determine the impact of environmental factors on the distribution of T v3.3.3 , 66, as T v3.3.3 . The 32 C. ficifolia accessions, which has allowed identification of genetic markers, such as SNPs and InDels. The SNPs discovered in this study suggest that environmental factors mediated the formation of the population structure of C. ficifolia. These SNPs and Indels might contribute to the variation in important pathways of genes for important agronomic traits such as yield, disease resistance and stress tolerance. Moreover, the genome resequencing data and the genetic markers identified from 223 accessions provide insight into the genetic variation of the C. ficifolia germplasm and facilitate a broad range of genetic studies.The availability of reference genomes and the continuous improvements of genetic data analysis methods are fostering resequencing studies. In this study, we performed the resequencing of Additional file 1: Table S1. Geographical location, phenotypic information and meteorological factors of sample sites.Additional file 2: Table S2. SNP and InDel information.Additional file 3: Table S3. Pairwise fixation index (FST) values among 32 populations.Additional file 4: Table S4. Gene number annoated from different databases.Additional file 5: Figure S1. GO Enrichment analysis of marker-trait association related genes.


Melanotaenia splendida splendida. We used an integrative riverscape genomics and morphometrics framework to assess the influence of these factors on both putative adaptive and non-adaptive spatial divergence. We found that neutral genetic population structure was largely explainable by restricted gene flow among drainages. However, environmental associations revealed that ecological variables had a similar power to explain overall genetic variation, and greater power to explain body shape variation, than the included neutral covariables. Hydrological and thermal variables were the strongest environmental predictors and were correlated with traits previously linked to heritable habitat-associated dimorphism in rainbowfishes. In addition, climate-associated genetic variation was significantly associated with morphology, supporting heritability of shape variation. These results support the inference of evolved functional differences among localities, and the importance of hydroclimate in early stages of diversification. We expect that substantial evolutionary responses will be required in tropical rainforest endemics to mitigate local fitness losses due to changing climates.To conserve the high functional and genetic variation in hotspots such as tropical rainforests, it is essential to understand the forces driving and maintaining biodiversity. We asked to what extent environmental gradients and terrain structure affect morphological and genomic variation across the wet tropical distribution of an Australian rainbowfish,  Empirical studies are fundamental to the advancement of evolutionary theory and are increasingly relevant as we grapple with the novel selective forces of anthropogenic environmental change. Both adaptive and non-adaptive processes contribute to the proliferation of biodiversity, but there remains much to explore about their relative roles  , endemic to tropical north-eastern Australia. The species is abundant throughout its distribution, including several river systems in the complex rainforest landscape of the Wet Tropics of Queensland World Heritage Area  were sampled from nine rainforest creek sites across five drainages in the Wet Tropics of Queensland, north-eastern Australia . Of these, 208 individuals . DM. duboulayi , mean nucleotide diversity (π), and proportion of polymorphic loci (PP). We also calculated Wright’s fixation indices (F-statistics) in R  were obtained from the National Environmental Stream Attributes v1.1.3, a supplementary product of the Australian Hydrological Geospatial Fabric  significant PCos of waterway distances. For each pRDA, we used the full set of SNP genotypes as a response matrix, and an explanatory matrix containing only environmental variables previously associated with genotype (p < 0.1) in the global RDA (full details S1h).We first ran a global RDA using the full SNP dataset as the multivariate response matrix, and the six environmental variables Fig. , centredM. s. splendida collected during field sampling using TPSDIG2 2.31  to implement phenotype-environment analyses (PEAs). We used the same set of environmental explanatory variables (above), this time testing body shapes  as response variables. We again controlled for putatively neutral genetic structure , plus the additional covariable of body size (log centroid size). Inputs for the body shape response variable and size covariable were created in R, using functions developed by Claude  genetic variation could be attributed to environmentally associated morphological variation throughout the study region. This could indicate both a heritable component to the associated body shape traits , as well as provide further support for their adaptive advantages. In R, we ran a global RDA using the four significant PCs of individual Procrustes distances as explanatory variables, and 864 putative adaptive alleles (identified in the genotype-environment RDA controlling for Ω) as the multivariate response. The analysis was then repeated as a partial RDA using individual body size (log centroid) as a covariable (details S1k), the results of which isolated only the genotype-phenotype interactions best explained by environmental selection.M. duboulayi reference genome . After variant filtering and removal of lower-quality samples, we retained 14,540 putatively unlinked SNPs (Table HE) ranging from 0.278 to 0.321 (mean = 0.293), and proportion of polymorphic loci (PP) ranging from 0.252 to 0.391 (mean = 0.329). Population subdivision accounted for a substantial proportion of the neutral variation, with global FST = 0.165, and FIT = 0.205. None of the site-specific FIS values , followed by the more centrally located Saltwater Creek . In addition to being the smallest drainage systems sampled, both are located along the coastal boundary of the species distribution  grouped more closely in the DAPC, indicating similarities in genetic variation which may result from a more recent shared history. The neighbour-joining tree . Controlling for scaled allelic covariance Ω  found six environmental variables associated with 23% of the observed genetic variation among individuals  in Procrustes distances among most sampling sites, and among all drainages/populations , respectively found 11.9% and 11.6% of shape variation associated with environment  was associated with environment  between putatively adaptive genetic variation and morphology, to which 6.8% of divergence in those loci could be attributed. After controlling for possible allometric effects (centroid size) using pRDA, this figure was only slightly reduced to 6.5% . A clear association was found between both genetic and morphological variation and the drainage divisions of this highly structured catchment system, indicating an important role of gene flow limitations on population divergence. Despite this, a larger component of divergence was better explained by local environmental conditions, and especially by variables relating to hydroclimate. This pattern was particularly pronounced for the morphological component of diversity, providing further evidence for its functional relevance. Meanwhile, GxPxE associations identified highly significant relationships between major components of body shape divergence and ecologically associated genetic variants. Based on these consistencies, we propose that local evolutionary adaptation is a favourable contributor to the high phenotypic diversity renowned of M. s. splendida  were supported by both RDA and BAYPASS analytical approaches. Depending on the covariables included, partial RDAs attributed ~12–17% of allelic variation to associations with key environmental variables, in contrast to the ~10–15% of variation which could be equally well or better explained by neutral conditional variables. Although it is difficult to draw direct comparisons, such strong GEAs support, and even exceed, those previously described for related temperate and subtropical Australian rainbowfishes , with greater overlap among sites indicating that morphology may be more conserved than genotype. Environment accounted for ~7–14% of body shape variation in partial RDAs after accounting for conditional variables of neutral genetic structure and centroid size. These conditional variables accounted for a much larger 44–50% of shape variation, but intriguingly, most of this related to a large effect of size rather than of neutral genetic structure, which could only explain ~4% of shape variation alone. In contrast to the relatively large contribution of neutral structure in the GEAs, this pattern was surprising, yet plausible, under the premise of greater functional constraints on morphology than on genome-wide variation. While many genomic changes may have little functional relevance , it has been suggested that the effects of random drift on phenotypes, and particularly on morphology, are less likely to be truly neutral , including cdh2 (Cadherin-2) and SPTAN1 . Cdh2 is involved in early development . Positive values coincided with a more upturned head, smaller eye, reduced dorsal hump, and distended pelvic region. Much of this divergence appeared latitudinally, with upturned shape extremes more common in the higher rainfall northerly catchments of Hutchinson, Daintree, and Saltwater. In a variety of teleost species, an upturned head and flattened dorsal region have been associated with a tendency for surface dwelling and feeding Wootton , surfaceM. fluviatilis, Brauer et al. M. duboulayi, Smith et al. In addition to the described adaptive signals occurring throughout the region, our results suggested an important effect of drainage structure in demographic divergence. Both demographic and environmental association analyses indicated gene flow barriers across contemporary drainage boundaries, delineating populations and affecting broader patterns of diversity. This was reflected by low inter-drainage migration rates and genetic clustering within drainages. Some additional, shallow substructure was detected among sampling sites within drainages, possibly resulting from isolation by distance or other resistance within the stream network. Similar hierarchical configurations have been previously described for subtropical and temperate rainbowfishes (M. s. splendida. Climate projections for the Wet Tropics cluster region indicate increases in average temperature, as well as more extreme weather events including rainfall intensity (Hilbert et al. Both the strong effects of hydroclimate on intraspecies diversity, and the geographical confinement created by catchment structure, indicate that climate warming could place strong selective pressure on rainforest populations of Melanotaenia splendida splendida is one of the most abundant fishes in the Queensland Wet Tropics (Pusey et al. sensu Ralls et al. M. s. splendida. Consistent with a growing body of work in Australian rainbowfishes, both genomic and morphological divergence appeared relevant to local adaptation, including heritable and hydrologically associated traits identified in related species. Moreover, three-way associations detected among genotype, phenotype, and environment supported the possibility of heritable, climate-adaptive shape variation in M. s. splendida. Empirical evidence for the role of temperature and precipitation driving phenotypic divergence has been mounting in tropical rainforest research, however this is likely the first freshwater example to benefit from a high-resolution genomic dataset. Where possible, we suggest that future work should continue to integrate environmental, genomic, and phenotypic datasets to disentangle evolutionary processes applicable to both conservation and theoretical development.Our work indicates that the interplay between contemporary hydroclimatic variation and drainage connectivity has helped shape regional diversity in the tropical rainforest fish https://figshare.com/s/c4b75d40fea91ab38beb. Data will be made publicly available upon acceptance.The relevant data have been appropriately archived and are available at figshare: Supplemental Material


Przhevalskiana silenus larvae, has detrimental consequences for livestock. GWFI is usually not accurately detected by the traditional methods of detection. This study aimed to identify the best diagnostic method for the early detection of GWFI by comparing three enzyme-linked immunosorbent assay (ELISA) methods using Hypoderma purified antigen (Hypodermin C), the crude antigen of P. silenus, and a commercially available hypodermosis ELISA kit, in the Pothwar region of Punjab, Pakistan. The sampling was carried out in 1000 goats, randomly selected from four districts  of the Pothwar region, Punjab Pakistan. The seroprevalence, determined via ELISA with the crude P. silenus antigen, hypodermin C (HyC) antigen, and the commercial ELISA kit, was 17%, 15.5%, and 18.6%, respectively. Cohen’s Kappa test confirmed that all the three assays could be employed for the early detection of GWFI, while an indirect crude P. silenus antigen ELISA was more sensitive and accurate.Warble fly is a globally important pest of domesticated and wild animals in the northern hemisphere. Goat warble fly infestation (GWFI), triggered by the obligatory parasite Przhevalskiana silenus (warble fly) grubs cause myiasis in goats, in mountainous and semi-mountainous areas and different regions in Pakistan, and cause substantial losses to livestock. The palpation method for detecting warble flies generally neglects the infestation intensity; therefore, the development of a reliable and efficient diagnostic technique is extremely necessary. This study compared three indirect enzyme-linked immunosorbent assay (ELISA) methods for detecting anti-P. silenus antibodies using the hypodermin C (HyC) purified from Hypoderma spp. Larvae collected in cattle , the crude antigen from the first instar stage of P. silenus, and a commercial Bovine Hypodermosis Antibody ELISA kit (IDEXX Laboratory), for accurately estimating the seroprevalence of goat warble fly infestation (GWFI) in the Pothwar plateau, Punjab, Pakistan. The ELISA with the crude antigen of P. silenus proved very sensitive and specific, 91% and 93%, respectively. The optical density exhibited a monthly variation, and the antibody titer began increasing from June, continually increased from July to December, and gradually decreased thereafter until March. The study confirmed the endemic status of GWFI in the Pothwar region and identified that ELISA based on the crude antigen of P. silenus was a more sensitive and specific immunodiagnostic method for determining seroprevalence, and could be employed for initiating nationwide eradication campaigns. Przhevalskiana silenus , are obligatory parasites that feed on the living tissues of hosts for a variable period. This infection reduces host physiological functions and affects livestock and the leather industry by degrading the hide of infested animals [Myiasis in goats, caused by the grubs of  animals . The red animals . The inf animals .In endemic areas, an accurate diagnosis of myiasis holds much significance for the initiation of control strategies leading toward eradication policies. There are numerous diagnostic techniques designed for the diagnosis of goat warble fly infestation (GWFI). The traditional diagnostic approach relied entirely on the palpation in the flank and back region of the infested host, where nodules formed at a later phase of the infection. This physio clinical observation is usually inaccurate in detecting infestation at the first and second instar  stages, as they are occult under the host’s skin. Thus, there is a dire need for an efficient diagnostic method that assists the diagnosis and controls the infestation at the herd level in proper time (L1), and its prophylactic management to overcome economic impacts ,5. The aIn past, in vivo and in vitro studies reported the specific and nonspecific host’s immune responses to infestation by myiasis-causing larvae, and advances were made in immunological approaches by parasite the against their host. The broad investigations were conducted on the contribution of the antigens of myiasis-causing larvae as modulators of the host immune response. For the diagnostic and development of vaccination strategies, the practical implications of immunological knowledge are of great significance. An alternative to chemical treatments, the developing environmentally sustainable control methods proved more practical. Immunological methods for the detection of myiasis allows for reliable, easy, and cost-effective diagnosis of living animals, thus scheduling a timely diagnosis. Nevertheless, the data regarding the host immune response to myiasis-causing larvae are fragmentary compared to other ectoparasites .Hypoderma spp and other myiasis-causing larvae are considered to be useful for the immunodiagnosis of hypodermosis in various mammals [Przhevalskiana sp can be employed for the diagnosis of anti-Przhevalskiana sp antibodies using competitive ELISA [P. silenus for the accurate and timely diagnosis of GWFI. The optimized indirect ELISA became a verified immunodiagnostic procedure for the mass surveillance of this infestation [An enzyme-linked immunosorbant assay (ELISA) is extensively practiced for the detection of hypodermosis because of its accuracy. The detection of the circulating antibodies through ELISA has become renown and facilitated the eradication of this menace from various regions of the world ,10. The  mammals ,16,17,18 mammals ,19,20. F mammals . A recenve ELISA . Recentlestation .Przhevalskiana spp in the country has not been explored in detail, as the diagnosis of infestation was based merely on clinical examination. The present study aimed to compare three ELISA methods for the accurate detection of anti-P. silenus antibodies using the HyC antigen, crude antigen extracted from P. silenus, and a commercially available hypodermosis ELISA kit for estimating the seroprevalence of GWFI in the Pothwar plateau of Punjab, Pakistan.In the Pothwar plateau, goat farming is a widespread business not only for milk, meat, skin, and cheese production, but also because this species can exploit massive areas of peripheral lands that is unfavorable for crop cultivation and rearing other species. The prevalence of GWFI has been reported from many parts of Pakistan, whereas direct and indirect economic impacts due to this infestation have not been precisely indicated. So far, the position of myiasis in goats by The warble fly is endemic to semi-hilly, riverine, and mountainous areas of Pakistan ; that isBlood samples were collected from 1000 goats that were randomly selected (25 per month per district) from four district , of the Pothwar region, Punjab, Pakistan. Ten sites belonging to three different categories, namely, farms, houses, and veterinary hospitals, from each of the four districts were selected for sampling during the study period, which lasted from June 2018 to March 2019. Blood was drawn from the jugular vein and placed in 10 mL non-Ethylenediaminetetraacetic acid (EDTA) tubes and centrifuged to separate the sera. The sera were then allocated in Eppendorf tubes (1 mL) and stored for further analysis at −20 °C. The samples of the positive sera were collected from goats infested with warble fly in the Pothwar region of Pakistan, while the negative sera samples were obtained from the Lancaster Goats, Scotland.P. silenus antibodies based on the crude antigen extract obtained from the L1 of P. silenus. This sampling was carried out from 100 P. silenus-infested goats, from a slaughter house in Saddar, Rawalpindi, from June to September. The L1 was extracted from the dissection of hypodermal tissues of the slaughtered goats, and after washing with normal saline, they were preserved in a phosphate buffer saline solution (PBS) at −20 °C. The larval identification was achieved based on their morphological features [An indirect ELISA was performed for detecting anti-features ,27.P. silenus was prepared by adding 10 L1 per 5 mL (0.1 M) tris-hydrochloric acid (pH = 7.5), were then grinded in tissue homogenizer, using five cycles of 1 min at 14,000 rpm. The homogenized material was placed in an ice bath to stop the temperature rise that could otherwise denature the proteins by activating the enzymatic processes between the cycles. The homogenate was centrifuged at 10,000 rpm for 5 min, followed by the separation of the supernatant in aliquots, and kept at −20 °C.The crude antigen of The Pierce Bicinchoninic Acid (BCA) technique was used for the estimation of protein concentration in the antigen.Hypoderma lineatum first instars obtained from cattle slaughtered in local slaughterhouses, Rawalpindi [Hypodermin C was purified from walpindi .P. silenus and incubated at 37 °C, overnight. Then 200 μL of the dilution buffer PTL (1.2 g skim milk + 60 mL of PBS-Tween) was dispensed in each well and blocked at 37 °C for 30 min. The plate was then washed 4 times (3 times with 100 μL + 1 time with 200 μL PT). Of the diluted sera, 100 μL (1:10) were added in duplicate. The negative and positive sera (standards) were also added in same dilutions and incubated for 1 h. The plate was then washed with PT (1 time 200 μL + 3 times with 100 μL), followed by an addition of 50 μL  of rabbit anti-goat IgG (H + L)  immuno-conjugate (horseradish peroxidase conjugate). Then, the incubation was set at 37 °C for 1 h and washed again (1 stretch of 200 μL and 2 stretches of 100 μL PT + 2 stretches 100 μL PBS). The TMB substrate  was then poured in each well and placed in the dark for 5–20 min, followed by the addition of 100 μL, 3 N sulfuric acid, then the reaction stopped. The optimal density (OD) was measured at 492 nm using a FLUOstar OPTIMAspectrophotometer . The following formulae were used for calculating the specificity and sensitivity (Equations (1) and (2)):An indirect ELISA was performed using a simple 96-well microtitration plate . The plate was coated with 100 μL (5 μL/mL) of the crude antigen of P. silenus antibody detection based on the HyC antigen, an indirect ELISA was standardized using 100 μL (2 μL/mL) HyC antigen and 50 μL  immuno-conjugate (horseradish-peroxidase conjugated) rabbit anti-bovine Ig G (H + L) (Geneway: GWBC158CO) in each well. The ELISA protocol, with minor modifications, was used for the bioassay [For anti-bioassay ,28. The The following formula (Equation (3)) was used for calculating the cut-off values:The sample, with an OD value less than the cut-off value, was regarded as negative, while those more than the cut-off value was considered positive.A Bovine Hypodermosis Antibody ELISA kit  was found commercially. The ELISA protocol was given by the manufacturer of the test kit ,30. A wa−;The following formula is used to calculate NCxwhere,−;The following formula is used to calculate PCxwhere,The following formula is used to calculate S/P%;where,P. silenus.The samples with seropositivity (S/P%) more than 55% were regarded as positive, while those with S/P% greater than 45%, but less than 55%, were suspected to be positive, and the samples with S/P% less than 45% were regarded as negative for P. silenus-infested goats with prominent nodules. This sampling was carried out in the month of December, from the slaughter houses of the study area.The validation of ELISA was performed on two hundred sera samples taken from 2) test, and the variables will be considered statistically significant at p< 0.05. The inter-rater reliability between the different diagnostic methods were analyzed via Cohen’s Kappa test, using SPSS, version 18.The district- and month-wise seroprevalence was statistically evaluated by Pearson’s chi-square  was performed on one thousand goat sera obtained from various districts of the Pothwar region, Punjab, Pakistan. Two hundred warble-fly-infested goats were selected for ELISA validation. The blood sampling was performed in the month of December from goats with prominent nodules, and an indirect ELISA was performed. The developed crude antigen of P. silenus ELISA showed a sensitivity and specificity of 98%.An indirect ELISA, using the crude antigen of P. silenus larvae and HyC antigen were 0.38 (0.224 ± 0.156) and 0.226 (0.153 ± 0.073), respectively. The sensitivity of the ELISA tests using the crude antigen, HyC antigen, and the commercial kit was determined to be 91%, 88%, and 90%, respectively, while the specificity was determined to be 93%, 93%, and 90%, respectively. Cohen’s Kappa test confirmed that the findings of all three assays moderately vary and could be employed for the early detection of GWFI. , 17% (170/1000), and 15.5% (155/1000), respectively, showing a significant difference (p < 0.05). The study revealed that the seroprevalence was higher in the Jhelum district, being 30.8%, 28%, and 25.6% as determined via an ELISA using the commercial kit, crude antigen of P. silenus, and HyC antigen ELISA, respectively. In the Rawalpindi district, the seroprevalence was determined to be 24.4%, 23.6%, and 22.4%, respectively; the seroprevalence was low in Chakwal district  and the lowest in the Attock  district  in the seroprevalence  were analyzed for GWFI through ELISA, and the OD was determined at a wavelength of 492 nm and 450 nm. The findings revealed that the OD values exhibited a monthly variation. The antibody titer started increasing from June and increased continually from July to December, but decreased gradually thereafter until March. The peak antibody titer was found in the months of November–December, followed by a decrease afterward. The highest seroprevalence was observed in winter months, i.e., November to December, and the lowest in March. The seroprevalence was 47%, 45%, and 44% in December by crude evalence a–c.P. silenus, a Dipterian fly, belongs to the family Oestridae; is responsible for heavy economical losses in livestock and the leather industry due to perforated skin and hides [Hypoderma spp. antibodies at an early stage of infection [H. lineatum antigen and anti-P. silenus antibody) [nd hides . The warnd hides ,5. Variond hides . It has nfection . The comntibody) ,32,33. Tntibody) .P. silenus for the serodiagnosis of GWFI in the Pothwar region of Punjab, Pakistan, and the results were compared with HyC antigen ELISA and commercial ELISA kit. It has been confirmed that an indirect ELISA helps diagnose GWFI at an earlier stage, because at this stage, some animals have antibodies in their blood, but they do not show any nodules; whereas, the physio clinical examination diagnoses the infestation at the later stage. When nodules start appearing on an animal body and much damage has been done to the host. The sensitivity and specificity of the indirect crude antigen (P. silenus) ELISA are higher than those of HyC antigen ELISA and the commercial kit. Statistical analysis, with the Cohen’s Kappa, test confirmed that the results of all the three immunodiagnostic methods varied moderately, which confirmed that all the three serological methods could be employed for the early detection of GWFI. However, of the three methods, the developed indirect ELISA method based on the crude antigen of P. silenus proved to be the most accurate and had a higher sensitivity and specificity. Contrary to that, a previous study reported that a commercial ELISA kit is highly accurate and has a high sensitivity and specificity of 92.2% and 98.1%, respectively [P. silenus antigen is more sensitive and cost-effective, whereas the commercial kit previously used is expensive and cannot be procured by the farmers of developing countries.The present study, is the first to perform an ELISA using the crude antigen of ectively . An earlectively . The devP. silenus antigen, HyC antigen, and the commercial ELISA kit was 17%, 15.5%, and 18.6%, respectively. The results of descriptive analysis revealed that the seroprevalence of GWFI was higher in the Jhelum and Rawalpindi districts, but low in Chakwal and Attock. The differences among the seroprevalence of GWFI across the districts were determined to be significant (p < 0.05). Similarly, the goats of the Khoshab and Chakwal districts of the Punjab province were examined  for the prevalence of warble. The larvae were collected from the infested goats and identified as P. silenus. The results showed that the prevalence of GWFI was 17.8% (89/500) [The overall district-wise seroprevalence of GWFI was also studied across the districts of Rawalpindi, Jhelum, Attock, and Chakwal. The seroprevalence determined by ELISA with the crude (89/500) . This st(89/500) , 24.9% [(89/500) , in Iran(89/500) , and Jor(89/500) , GWFI re(89/500) . These r(89/500) . The pre(89/500) , as well(89/500) .p < 0.05). The sera obtained from the goats randomly selected from the study area were analyzed for GWFI through ELISA, and the OD was determined at a wavelength of 492 nm and 450 nm. The findings revealed that the OD values exhibited a monthly variation. The antibody titer started increasing from June, and increased continually from July to December, but decreased gradually thereafter unit March. The highest seroprevalence was observed in the winter months, i.e., November to December, and the lowest in March. However, hand palpation showed no infestation from March to September, as the larvae were at a subclinical phase, which were only detected through serological tests. The results of ELISA tests revealed that the antibody titer in the blood samples of the animals infested with warble flies increased from June to September. The antibodies were not seen before the month of June as in these months, the fly was in a different developmental stage. In Pakistan, the life cycle of myiasis starts from April and L1 starts appearing from June to September, making this period ideal for serodiagonsis by ELISA as animals show a higher antibody titer. The highest seroprevalence was observed in the winter months, i.e., November to December, and the lowest in March. These observations are in agreement with the decline in the OD values which depends on the maturation of the instars [The seroprevalence of GWFI was monitored in a monthly manner during the study period (June–March), and revealed significant differences  could be employed for the early detection of GWFI, and showed better results as compared to traditional palpation method. During the study, an ELISA with the crude antigen of P. silenus was developed that proved to be a more rapid, sensitive, and specific immunodiagnostic method for determining the seroprevalence of GWFI. In a comparative study of HyC antigen ELISA, anti-bovine immunoconjugate was used that showed better results, but it is suggested that for more specificity, anti-goat immunoconjugate could be used. This is a cross-sectional study where each animal was sampled once, so different animals were sampled in each month. Taking that in consideration, a longitudinal study that follows the same animals over time will be performed in future to determine the monthly variation in OD. The findings highlight that the developed ELISA should be used in other parts of Pakistan to find the exact status of this infestation. Furthermore, this strategy can be employed for initiating nationwide GWFI eradication campaigns.In conclusion, the present study identified the endemic status of GWFI and is accomplished as an alarming threat to animal health in the Pothwar region of Pakistan. The study confirmed that all three ELISA bioassays (crude


In breeding programmes, the observed genetic change is a sum of the contributions of different selection paths represented by groups of individuals. Quantifying these sources of genetic change is essential for identifying the key breeding actions and optimizing breeding programmes. However, it is difficult to disentangle the contribution of individual paths due to the inherent complexity of breeding programmes. Here we extend the previously developed method for partitioning genetic mean by paths of selection to work both with the mean and variance of breeding values.First, we extended the partitioning method to quantify the contribution of different paths to genetic variance assuming that the breeding values are known. Second, we combined the partitioning method with the Markov Chain Monte Carlo approach to draw samples from the posterior distribution of breeding values and use these samples for computing the point and interval estimates of partitions for the genetic mean and variance. We implemented the method in the R package AlphaPart. We demonstrated the method with a simulated cattle breeding programme.We show how to quantify the contribution of different groups of individuals to genetic mean and variance and that the contributions of different selection paths to genetic variance are not necessarily independent. Finally, we observed that the partitioning method under the pedigree-based model has some limitations, which suggests the need for a genomic extension.We presented a partitioning method to quantify sources of change in genetic mean and variance in breeding programmes. The method can help breeders and researchers understand the dynamics in genetic mean and variance in a breeding programme. The developed method for partitioning genetic mean and variance is a powerful method for understanding how different selection paths interact within a breeding programme and how they can be optimised.The online version contains supplementary material available at 10.1186/s12711-023-00804-3. Analysing genetic trends is essential for identifying key breeding actions and optimising breeding programmes. The observed genetic change is a sum of contributions from different selection paths represented by groups of individuals. However, these contributions are difficult to quantify due to the inherent complexity of breeding programmes. Contributions of selection paths differ because of differences in selection intensity, accuracy, genetic variation, generation interval, and dissemination. To quantify the contributions, García-Cortés et al.  developeFurthermore, the method assigns parent breeding values and Mendelian sampling terms to analyst-defined paths, such as sex, origin, selection path, etc. By aggregating these partitions by other variables, such as year, the method summarises the contributions of different groups of individuals to the overall genetic trend. This approach has been used to quantify the contributions of different countries to the overall genetic trend in the global Brown Swiss population , global In addition to the contribution of paths to changes in genetic mean, breeding programmes should also consider analysing changes in genetic variance to fully understand the source of genetic change in a population , 7. FurtThe aim of this paper is to extend the method of García-Cortés et al.  to (i) pIn this section, we delve into the theory of partitioning breeding values and the computation of their mean and variance.Let variance –14.p levels, representing our paths of interest, and for any set a priori using the equality:a posteriori). They first calculated the conditional expectation of breeding values given phenotype data   \documenmentclass2pt{minimtic mean . Such anThe presented partitioning of genetic variance holds for true breeding values. However, when EBV are available, we cannot substitute  in Eqs.  and 5)  \documenmentclass2pt{minimn et al.  that invn et al. . Second,In the previous subsection, we assumed that the true breeding values were known. However, in reality, we infer breeding values from phenotype data. To this end, we fitted the standard pedigree-based model to data described in the “mentclass2pt{minimWe sampled from the posterior distribution of all model parameters with the Gibbs algorithm (a Markov Chain Monte Carlo (MCMC) method) as implemented in . First, It is imperative to note that the proposed partitioning method requires samples from the posterior distribution ith MCMC , an alteith MCMC , 17. TheThe partitioning methodology depends on well-calibrated estimates of breeding values. If the used model  does notlibrated . Workingt be the index for the generation with t respectively as t. We then evaluated the agreement between the variables j category of individuals t in replicate r. We obtained the posterior distribution of our quantities of interest for the partitions and categories in each replicate: First, we evaluated the agreement between true and estimated mean and variance of breeding values over generations using the concordance correlation coefficient defined by . Let t bfficient . This copedigree information for individual (id), sire (Fid) and dam (Mid);partition variable (path)—colPath;breeding values for one or multiple traits—colBV;grouping variable  by paths using:The partitioning method is implemented in the AlphaPart R package , 18. TheWe summarise the partitions using the grouping variable (time) using:where object is an object of class AlphaPart with breeding value partitions, by represents the column by which summary function FUN is applied. For this work, we included an extra argument cov that controls how the covariances are displayed in the output. If cov = FALSE, the default, all covariances are returned in a single column as T be the number of traits and S be the number of samples of breeding values. Suppose data is a data frame containing columns for individual (id), father (Fid), mother (Mid), path (path), and generation (Gen). Now suppose a more general case where bv_samples represents a data frame containing a column for the individual (id) identification and S columns for the samples of breeding values, as shown in Fig. We further describe how to use the posterior samples of breeding values from the “To evaluate the method and AlphaPart implementation, we simulated a simple cattle breeding programme over 40 generations with 1000 individuals per generation. The first 20 years represented a burn-in phase, where we selected the best 5 males (out of 500) as sires based on their phenotype and mated them with all 500 females from the previous generation and all 500 females from the current generation. These matings produced 1000 selection candidates for the next generation. After the burn-in phase, we tested two selection scenarios over a further 20 generations: we selected the 5 best males from 500 male candidates based on (i) their phenotypes  genetic variance in the breeding programme pertained to female and non-selected male paths, which were not the most relevant individuals for disseminating genetic gain, indicating that the selected male path drove changes in genetic mean. While this is an obvious result, it shows the power of the method for more complex cases. A negative correlation between female and selected male partitions in Fig. By partitioning the genetic mean and variance, we showed that in the high-accuracy scenario, the covariance between contributions of females and selected males plays an important role when partitioning the genetic variance. Consequently, in this case A negative covariance between breeding value partitions is expected in some cases. We are aware of two cases. The first is when paths represent sexes, as in this study. The second is when paths represent a foreign and a domestic breeding programme. Covariance arises from the proportional relationship between contribution of paths as well as their values, as shown in Additional file A positive covariance is not likely to happen when paths represent sexes in a target population for a reason explained in the previous paragraph. However, it can happen when we import individuals that are not well-adapted to the domestic environment. Such individuals contribute negatively to the next generation of offspring  with explicit representation of Mendelian sampling terms;" title="Click here to edit">) and error term;" title="Click here to edit">), where 1 represents a vector of ones, Figure S2. Definition of the statistical model, priors and posteriors: representation of gender as the path variable.Additional file 2: Figure S3. Distribution of breeding value partitions by sex and selection status  over generations for medium-accuracy scenario  over generations for high-accuracy scenario.Additional file 4: Figure S5. Correlation between females (F) and selected males (M(S)) partitions using true breeding values for the medium- and high-accuracy scenarios and one simulation replicate.Additional file 5: Figure S6. Partitions of genetic mean and variance bysex,by sex and selection status , andthe Pearson correlation between F and Mpartitions for the medium- and high-accuracy scenarios by sex and selection status using true breeding values for 30 simulation replicates.Additional file 6: Figure S7. Estimated and true genetic means and variances over 40 generations by selected males), non-selected males), and femalesin the medium-accuracy scenario. The solid line represents the equality line Additional file 7: Figure S8. Estimated and true genetic means and variances over 40 generations by selected males), non-selected males), and femalesin the high-accuracy scenario. The solid line represents the equality line Additional file 8: Figure S9. Pointand intervalestimates for inbreeding over generation considering all animals in a specific generation.Additional file 9: Figure S10. The difference between true and estimated Mendelian sampling termsis distributed over generations. The totalis partitioned by selected males), non-selected males), and femalespaths in the medium- and high-accuracy selection scenario. We are considering 30 replicates .Additional file 10: Figure S11 Partitioning of the total genetic meanover generations by selected males), non-selected males), and femalespaths in the medium-accuracy and high-accuracy scenario. We considered one replicate without accounting for inbreeding in the model .Additional file 11: Figure S12. Partitioning of the total Mendelian Sampling termover generations by selected males), non-selected males), and femalespaths in the medium-accuracy and high-accuracy scenario. We considered one replicate without accounting for inbreeding in the model .Additional file 12: Figure S13. Partitioning of the total genetic varianceover a generation by selected males), non-selected males), and femalespath in the medium-accuracy and high-accuracy scenario. We considered one replicate without accounting for inbreeding in the model .Additional file 13: Figure S14. Example ofnegative andpositive covariance partitions.


Genetic diversity is associated with invasion dynamics during establishment and expansion stages by affecting the viability and adaptive potential of exotics. There have been many reports on the comparison between the genetic diversity of invasive alien species (IAS) in and out of their native habitats, but the conclusions were usually inconsistent. In this work, a standard meta-analysis of the genetic diversity of 19 invasive plants based on 26 previous studies was carried out to investigate the general trend for the change of IASs’ genetic diversity during their invasion process and its real correlation with the invasion fate. Those 26 studies were screened from a total of 3557 peer-reviewed publications from the ISI Web of Science database during the period of January 2000 to May 2022. Based on the selected studies in this work, a general reduction of IASs’ genetic diversity was found in non-native populations compared to that in native ones, while the difference was not significant. This finding suggested that regardless of the change in genetic diversity, it had no substantial effect on the outcome of the invasion process. Therefore, genetic diversity might not serve as a reliable indicator for risk assessment and prediction of invasion dynamic prediction in the case of IASs. Biological invasion is a process in which alien species invade a new region from its native habitat naturally or artificially, causing great ecological degradation and economic losses . The begThe process of a successful invasion of an IAS can be divided into three steps  , all of Further, there have been plenty of reports on the change in genetic diversity of the alien species at the DNA level after their invasion ,21,22; hIn this work, based on the inconsistent results of the previous studies on the changes of genetic diversity between native and non-native plant populations, a comprehensive meta-analysis was carried out for the re-statistics of those pieces of literature to investigate the general changing trends of IASs’ genetic diversity and explore the correlation of genetic diversity and invasion fate. The result of this work will be helpful to determine whether genetic diversity can be used as an indicator in risk assessment and invasion dynamic prediction of IASs.Acacia saligna and Phyla canescens are tropical originated, while the others grow in temperate zone. The different genetic diversity indexes used in those studies included gene diversity (Hj), allelic richness (AR), number of alleles (Na), and expected heterozygosity (HE). Fifteen papers used more than one of those indicators, and the highest-ranking indicator was preferably utilized in our work.Firstly, we removed duplicate records and reviews, books, and patents before screening (23 records). Secondly, based on article titles and abstracts, 2908 records not dealing with invasive plants were excluded. Thirdly, articles having parameters such as average value, standard deviation (or standard error), sample size (the number of populations in native or non-native range), and other relevant data that were required in the meta-analysis were selected. As a result, only 26 articles were found to have quantitative analyses of the genetic diversity of invasive plants  in both native and non-native populations , which mQ = 155.906, I2 = 83.323, Tau Squared = 1.008, p < 0.001).A conventional meta-analysis by the inverse-variance weighted method was performed in this study to compare the genetic diversity levels of the IASs between their native and non-native ranges. After testing the heterogeneity among studies derived from the fixed effect model, the weighted mean effect size was found to correlate to the high heterogeneity among each study  was employed to cope with the high heterogeneity, which implies that we assumed that differences among studies are not only due to sampling error but also due to true random variation, as is the rule for ecological data . The mea = 0.251 . The resp = 0.572 > 0.05). Therefore, these findings suggested the reliability of the meta-analysis conducted in this work, affirming that the results were not influenced by potential biases.The sensitivity analysis conducted in this study showed no significant change in the mean effect size compared with the previous one, indicating the good stability of our data . The funThis study employed a meta-analysis approach, which yielded a negative effect size and a 95% CI overlapping zero based on the 26 selected studies. These results indicate that there is no significant change in IASs’ genetic diversity between native and non-native populations. Although genetic diversity seems not to play a decisive role in determining the fate of invasion, it is important to note that the observed changes in genetic diversity vary among specific species.The decline of genetic diversity within non-native populations may be due to various causes. Alien species would obtain a small size population after arriving in a new environment; therefore, only a small fraction of the population’s original genetic variation could be carried there, which is called the “founder effect” ,40. The Bunias orientalis and Arctotheca populifolia did not show a decrease in genetic diversity compared to their native ones, which might be due to the high level of propagule pressure through multiple introduction events [However, it is noteworthy that the non-native populations of n events ,17. Genen events ,43,44,45Based on the current hypothesis, IASs encounter the founder effect and population bottleneck during their introduction into a non-native range ,31, resuAccording to the hypothesis of ‘pre-adaptation’, when the new habitats are similar to the native ranges, there are few adaptive challenges for the IASs to establish new populations ,48. A siTaken together, the decrease in genetic diversity within non-native populations does not necessarily mean a decrease in invaders’ fitness or much less failure of invasions.A successful invasion is roughly divided into three stages: introduction, establishment, and expansion ,61. BiolPrevention, eradication, and control are three successive steps in IAS management proposed by the CBD . However, once a non-native species is established in a new region, it is extremely difficult to be eradicated or control . Risk asThe number of comparative research studies focusing on invasive alien plant species has witnessed a steady increase over the past few decades. These studies have primarily aimed to measure various traits exhibited by these plants in both their native and non-native ranges. However, despite this growing body of research, the investigation of genetic diversity in invasive alien plants between their native and non-native populations remains relatively scarce in this study because of the screening criteria. Moreover, the existing studies display a considerable degree of heterogeneity in terms of the study design. As a consequence of this limited number of studies and high heterogeneity, the statistical ability to detect significant differences in the mean effect size from zero is currently constrained. It is essential to address these limitations to ensure robust and reliable findings in this field of research. To achieve this, we propose that future research endeavors should encompass a larger number of invasive alien plant species and incorporate group-specific comparisons. By broadening the scope of the study and including multiple species, it will be possible to draw more comprehensive and robust generalizations regarding the genetic diversity of invasive alien plants. Furthermore, it is worth noting that the mean effect size has been found to correlate with the high heterogeneity observed in each study. This correlation highlights the need for further investigation into the underlying factors contributing to this heterogeneity. By gaining a deeper understanding of the sources of variation among studies, we can refine our research methodologies and improve the comparability and reliability of the findings.Moreover, comprehending the underlying reasons behind the diminished genetic diversity in prosperous invasive alien plant species is crucial for comprehending their invasive mechanisms and enhancing the effectiveness of weed risk assessment systems. In light of our preliminary findings, we further propose that future research should prioritize the investigation of key genes that regulate phenotypic traits, rather than focusing solely on the genetic variation of invasive alien plants.The ISI-Web of Science database was used to search the peer-reviewed publications on the genetic diversity of invasive plants from January 2000 to May 2022 with the keywords including  AND (comparison OR comparative OR compare) AND (plant OR plants) AND (varia* OR divers* OR richness OR polymorph*) AND (gene OR phenot*) AND (establ* OR adapt* OR inva*). As a result, a total of 3543 articles were retrieved. Meanwhile, we obtained 14 relevant papers from other sources.The following 3 criteria were applied to screen the publications: (1) they were original research papers rather than reviews, books, or patents; (2) their subjects were invasive plant species; (3) and the parameters including the average, standard deviation (or standard error), sample size (the number of populations in native or non-native range), and other relevant data required for the meta-analysis could be directly obtained or calculated from articles. Finally, only 26 out of the 3557 articles were found to meet the above criteria. These papers include quantitative analyses of the genetic diversity of IASs  in both native and non-native populations, from which we summarized 27 datasets of 19 invasive alien plants  for the A meta-analysis is a re-statistical tool for generalization from a collection of inconsistent experimental results reported by different researchers on one topic, which has been widely used for resolving discrepancies in genetic studies . This apThere are two models for meta-analysis including the fixed effect model and the random effect one. The major assumption of a fixed effect model is that all effect sizes share a common mean value; thus, the variation among data is solely caused by the sampling error. However, this assumption is unrealistic for most biological meta-analyses, especially those involving multiple populations, species, and/or ecosystems ,81. The Sd), and sample size (n) of the control group (native populations) and the treated group (non-native populations) from each study of the included articles. If only the standard error (Se) is provided only, the following equation was used to transform it to Sd:We extracted the parameters including the average (x), standard deviation  that was not biased by small sample sizes as corresponding common effect size statistics to analyze the difference between the mean effect sizes of the two groups [d is the preferred measure of effect size for traditional meta-analysis because it has lower Type I error rates than other measures [d was calculated referred to Zhou’s method [S is the standard deviation within each group and calculated as follows:J is a weighting factor based on the number of populations (n) in each case, calculated asWe chose the standardized mean difference  of native and non-native ranges, respectively. The variance of Hedges’ d was calculated as follows:I2 statistics in conjunction with Q-statistics. When the Q value is significant and I2 > 75, the effect size of the included studies is meant to be heterogeneous and there are differences among them. The heterogeneity between studies is caused by two sources of variability. One is sampling error, which is always present in a meta-analysis because every single study uses different samples. Another is the indeterminate number of characteristics that vary among the studies, such as those related to the characteristics of the samples, variations in the treatment, the design quality, and so on [If the 95% confidence interval (CI) overlaps zero, it indicates that the result is not significant. Heterogeneity was measured using nd so on . The rannd so on , which hIn addition, the existence of publication bias should be noted and a sensitivity analysis should be carried out. Sensitivity analysis is performed by the ‘one study removed’ function, which is helpful for obtaining a realistic perspective of the potential impact of biases . Every tA meta-analysis was carried out to explore the trend of genetic diversity changing of IASs and its role in influencing the process of invasion in this study. The results revealed a general reduction in genetic diversity during the invasive process, but the difference was not significant. Our finding indicated that population genetic diversity was not a substantial influence on the success of plant invasion. Consequently, the utility of genetic diversity as a commonly employed indicator in risk assessment and the prediction of invasion dynamics for IASs may be limited.


Febrile infection-related epilepsy syndrome (FIRES) is a severe childhood epilepsy with refractory status epilepticus after a typically mild febrile infection. The etiology of FIRES is largely unknown, and outcomes in most individuals with FIRES are poor.Here, we reviewed the current state-of-the art genetic testing strategies in individuals with FIRES. We performed a systematic computational analysis to identify individuals with FIRES and characterize the clinical landscape using the Electronic Medical Records (EMR). Among 25 individuals with a confirmed FIRES diagnosis over the last decade, we performed a comprehensive review of genetic testing and other diagnostic testing.Management included use of steroids and intravenous immunoglobulin (IVIG) in most individuals, with an increased use of immunomodulatory agents, including IVIG, plasma exchange (PLEX) and immunosuppressants such as cytokine inhibitors, and the ketogenic diet after 2014. Genetic testing was performed on a clinical basis in almost all individuals and was non-diagnostic in all patients. We compared FIRES with both status epilepticus (SE) and refractory status epilepticus (RSE) as a broader comparison cohort and identified genetic causes in 36% of patients with RSE. The difference in genetic signatures between FIRES and RSE suggest distinct underlying etiologies. In summary, despite the absence of any identifiable etiologies in FIRES, we performed an unbiased analysis of the clinical landscape, identifying a heterogeneous range of treatment strategies and characterized real-world clinical practice.FIRES remains one of the most enigmatic conditions in child neurology without any known etiologies to date despite significant efforts in the field, suggesting a clear need for further studies and novel diagnostic and treatment approaches. Historiic cause . While NThe underlying etiology for FIRES remains elusive. In some cases, an autoimmune or viral form of encephalitis is identified, although in most cases no underlying cause is identified. These cases are designated as cryptogenic and are an area of active investigation . A fulmiAmong studies focused on elucidating the etiology of FIRES, there has been an increased focus on potential underlying genetic factors as causative etiologies, though no genetic factors have ever been definitively identified. The lack of genetic explanation in FIRES stands in stark contrast to the genetic landscape of epilepsy more broadly in which the genetic yield is up to 33% with different forms of genetic testing , 10. StuGiven the rarity of NORSE and FIRES, a consistent barrier to identifying genetic etiologies is the limited population from which data can be systematically analyzed. While there have been reports of individuals with FIRES or NORSE having variants in genes associated fever-sensitive epilepsies or metabolic diseases, –19 many Therefore, in this retrospective study, we aimed to further delineate the genetic etiology of FIRES, as well as SE and RSE more generally. We used natural language processing (NLP) methods to identify children diagnosed with FIRES at a large tertiary center and systematically reviewed the genetic testing completed as part of their clinical care to identify a potential genetic etiology for FIRES. To determine how the genetic yield of FIRES fits within the broader landscape of children with non-FIRES related SE and RSE, we examined broader cohorts of children diagnosed with SE or RSE as their first presentation of seizure.2.2.1.This was a retrospective single-center observational study performed at Children’s Hospital of Philadelphia (CHOP). Individuals with FIRES were identified through NLP of free-text patient notes from the Electronic Medical Records (EMR) between 2013 and 2023 using the search terms “Febrile infection-related epilepsy” or “FIRES” or “new-onset refractory status epilepticus” or “NORSE” with “febrile infection.” Some individuals in our study were initially admitted to outside institutions prior to transfer to CHOP as a tertiary care center. We included these patients as we had access to shared EMRs from their hospitalizations at the time of their subsequent presentations to CHOP. We manually reviewed the selected charts to confirm the diagnosis of FIRES based on formal consensus criteria . Individuals were excluded if: (1) there was no documentation of preceding illness, remote history of illness without documentation, or lack of outside records to confirm preceding febrile illness; (2) the word “FIRES” was included in the chart but referred to family history or to a publication that included the search term or the differential diagnosis where FIRES was ultimately dismissed; or (3) the clinical history did not align with the formal consensus definition for FIRES. Accordingly, three individuals with NORSE but without sufficient clinical information to diagnose FIRES based on the characteristics defining FIRES described above were excluded. This study was completed and approved by the Institutional Review Board at CHOP.The following definitions were used. Status epilepticus (SE) was defined as 5 min or more of continuous clinical seizure activity or recurrent seizure activity without recovery between seizures. Refractory status epilepticus (RSE) was defined as SE persisting despite administration of at least two appropriate parenteral medications including a benzodiazepine, without a specific duration required. We used consensus guideline definitions of NORSE and FIRES . NORSE w2.2.We manually reviewed demographic and clinical data of 25 individuals with FIRES, including information on hospital admissions and genetic workup (see below). For each patient, we reviewed their prior medical and developmental history, history of preceding illness with fever, and age at time of hospitalization for FIRES and at discharge. For treatment strategies, all children were placed on anesthetic infusions during their hospital course ; however, detailed records about the dates of administration were limited so we focused only on whether anesthetic infusions were administered, number of anti-seizure medications at discharge, and the use of anti-inflammatory and immunomodulatory agents including intravenous immunoglobulin (IVIG), steroids, plasmapheresis (PLEX), and other immunomodulatory agents.2.3.SCN2A,” “POLG,” “gene,” “karyotype,” “microarray,” “epilepsy panel,” “exome,” and “mito.” Cases where genetic testing was performed but reports were not available for review were noted. We documented the type of genetic test , results, report date, coding and protein variant change, inheritance, and variant pathogenicity. Of note, genetic testing of individuals with FIRES spanned several years and tests were sent to and interpreted by different diagnostic labs, according to the discretion of the ordering provider. In the context of ongoing gene discovery, genes included on the gene panels have been variable depending on the year and may not have included more recently discovered genes.For individuals with confirmed diagnoses of FIRES, a comprehensive review of patient records was performed to identify elements of their diagnostic workup for FIRES, with particular attention to the timing and type of genetic testing. Previous genetic testing was identified in the EMR and stored as laboratory results, external media uploads, or within recent neurology and genetic clinical notes. Lastly, a free text search of medical charts was performed with the key words: “2.4.To characterize the clinical and genetic landscape of individuals with SE and RSE more broadly we used two cohorts: (1) 32,112 individuals with epilepsy in the Pediatric Epilepsy Learning Health System (PELHS) and (2) 1,894 individuals with presumed or confirmed genetic epilepsies at CHOP. First, using the PELHS cohort, we mapped the genetic and clinical landscape of non-FIRES RSE through systematic evaluation of the EMR, capturing more than 4.5 million full-text health care notes spanning 203,369 total patient-years. We limited our search in this cohort to the first presentation of RSE, as subsequent encounters with RSE documented in the patient notes could refer to a new RSE event or history of prior RSE. We assessed the overall distribution of RSE onset in this larger cohort and contrasted it with the wider distribution of onset in FIRES.PCDH19-related disorders might have “status epilepticus” in their patient charts due to a general clinical description of PCDH19-related disorder, rather than the patient’s specific phenotype.Secondly, in order to generate an understanding of genes that may be implicated in SE and RSE more broadly, we further delineated the genetics of children with SE and RSE using a dataset comprised of 1,894 individuals with presumed genetic epilepsy and neurodevelopmental disorders and characterized the genetic yield of SE. This resulted in 1,158 individuals in the CHOP cohort with SE. When performing NLP on patient notes to capture phenotypes such as the presence of certain seizure types of neurological features, we only parsed notes prior to a genetic diagnosis if applicable. The rationale was to control for bias associated with clinical impressions following a molecular diagnosis. For example, individuals with In our cohort of 1,894 individuals with presumed genetic epilepsies, we then focused only on individuals with a known genetic diagnosis who presented with RSE at first seizure presentation  in order to identify genetic etiologies associated with a NORSE-like presentation. We identified 208 individuals with RSE from NLP. Seventy-five of these individuals had a genetic diagnosis. Twenty-two of the 75 individuals presented with RSE at their first seizure presentation. We then manually reviewed patient charts of this smaller cohort and excluded the following: (1) individuals who did not have true RSE ; (2) individuals who had a pre-existing diagnosis of epilepsy; (3) one individual in whom the genetic diagnosis did not correlate with the RSE presentation; and (4) neonatal-onset RSE. We focused on genetic etiologies associated with RSE after the neonatal period to serve as a closer comparison group to FIRES/NORSE. This left us with four individuals carrying three separate genetic diagnoses. This subgroup also included two additional individuals. The first was the twin of another individual who had the same clinical presentation (4 months earlier) and was diagnosed with the same genetic condition. The second had been previously excluded from our FIRES database as she did not meet FIRES diagnostic criteria. This left six individuals who had presented with RSE as first seizure presentation and who were ultimately diagnosed with a genetic epilepsy syndrome.Lastly, we aimed to better understand phenotypic differences between individuals with SE at first onset of seizures, including subgroup of individuals with RSE, due to a genetic etiology versus individuals without a genetic diagnosis. We calculated odds ratios with 95% confidence intervals using Fisher’s exact test, stratifying individuals with and without an identified genetic etiology. Phenotypic associations between the two subgroups are presented as a phenogram, a previously published method that allows us to visualize the overall constellation of a selection of phenotypic features and severity of clinical presentations between groups –24.3.3.1.PCDH19; however, for this individual there was insufficient documentation for further study  the context of a publication reference that contained the word “FIRES” or for conditions that have been documented to be associated with FIRES or NORSE, or (2) patients for which a referral note was written but the individual was never evaluated at CHOP. This resulted in 59 individuals for manual chart review. Thirty-four individuals were excluded due to an alternative diagnosis, not meeting criteria for FIRES, or a remote history of FIRES with absence of documentation of the illness. There were eight individuals diagnosed with FIRES but excluded because of a lack of clinical information see . There wtudy see . Followitudy see .rhinovirus/adenovirus/Bartonella, Mycoplasma, Metapneumovirus, rhinovirus/parvovirus, E. coli urinary tract infection). Three individuals were ultimately diagnosed with autoimmune encephalopathy with anti-thyroid encephalitis (anti-thyroid peroxidase antibodies), Sjogren’s syndrome, and catastrophic antiphospholipid syndrome.In the 25 individuals with FIRES, the median age of onset of SE was 7.25 years . One individual remained hospitalized due to social factors and had been in the hospital for a duration of 2.8 years up to the time of inclusion. All children were noted to have some form of cognitive, speech, or physical impairment at the time of discharge . Six  with a median of three ASMs (IQR 3-4). Specific ASMs are listed in 3.3.Twenty-three (92%) individuals received genetic testing . FifteenSCN5A, associated with autosomal dominant cardiac conduction system dysfunctions and cardiomyopathy, and Individual 24 had a heterozygous pathogenic variant in FLG, associated with autosomal dominant eczema. Mitochondrial genome sequencing revealed that individual 14 had a likely pathogenic variant in MT-TK detected at ~4% heteroplasmy in blood and 3% heteroplasmy in brain tissue. Mitochondrial MT-TK variants are most associated with myoclonic epilepsy with ragged-red fibers (MERRF) syndrome at heteroplasmy levels markedly greater than in this individual  to identify candidate genes, but none were identified. There were 36 total VOUS revealed across all testing modalities. Genetic testing seizures , this ge3.4.As all genetic testing performed in our FIRES cohort was non-explanatory, we expanded the scope of our study to assess the genetic landscape of a broader group of individuals with SE and RSE, aiming to elucidate how FIRES fits more broadly into the context of SE and RSE. First, we identified 959 individuals with presence of RSE documented in 166,301 time-stamped patient encounters in a broader cohort of 32,112 individuals with childhood epilepsy . The higKCNT1, DEPDC5, and NPRL3, had at least one occurrence of SE prior to the genetic diagnosis. For other common genes in our cohort, including STXBP1, SCN1A, KCNQ2, SCN2A, fewer than 50% of individuals had at least a one-time presentation with SE prior to genetic diagnosis.Second, to better understand the genetic landscape of individuals presenting with RSE as well as SE more broadly, we examined our CHOP cohort, narrowing to evaluate only those individuals who had experienced SE or RSE. This yielded a genetic etiology for 36% of cases . RegardiPCDH19, two individuals with CACNA1A, two twin sisters with homozygous variants in RANBP2, and one individual with KCNA2. Each of these individuals presented prior to the age of 24 months, and only one presented with RSE after the age of 12 months. Each had genetic testing sent within a week of presentation, except for the individual with PCDH19, for whom data are not available  and idiopathic (non-FIRES) SE (n = 769). Individuals with identified genetic etiologies were more likely to have hypotonia , global developmental delay , and epileptic encephalopathy . Individuals without an identified genetic diagnosis had a two-fold higher risk of headache , attention deficit hyperactivity disorder,  and memory impairment  for extracting unstructured clinical data. The automatic assessment of clinical text poses challenges in clinical interpretation of large-scale datasets and requires consideration of potential biases. For example, for individuals with a genetic diagnosis, we were limited to assessing clinical features only prior to the diagnosis to prevent “note contamination,” or the bias when phenotypes associated with the genetic diagnosis more broadly is captured in the patient chart and does not necessarily describe or is inaccurate to the specific patient. Furthermore, identification of individuals with FIRES and distinguishing RSE from SE required subsequent manual chart review. In the latter case, we had to review on an individual basis to confirm critical details of case presentations. Nevertheless, we demonstrate that a data-driven method can facilitate the identification of individuals that meet predefined criteria such as FIRES or RSE across a large EMR database and healthcare system that captures dynamic medical care over the years, allowing us to identify 25 individuals who were ultimately determined to meet FIRES criteria and 6 individuals with inaugural RSE secondary to a genetic diagnosis.Another limitation of our study was the limited analysis of longitudinal clinical data, including the characterization of epilepsy histories and developmental trajectories over time following the initial presentation of FIRES. This included analysis of detailed medication histories. While anesthetic infusions were captured in our center’s medical records, we did not have data to the level of a minute or hour time scale for the initial presentations of patients who were admitted to an outside institution at disease onset prior to transfer of care to our center. Accordingly, we were not able to reconstruct medication landscapes for these patients. Thus, while our study revealed a trend toward increased use of ketogenic diet and immunomodulatory agents, interpretation of outcomes and efficacy of treatment strategies were limited due to a small sample size and high variability in the administration of the various therapies. Given the importance of understanding real-world clinical care, the reconstruction of medical treatment following hospital admission will be clinically meaningful. Nevertheless, in our study, we provide an objective picture of the heterogeneity in medical treatment using real-world data, including genetic testing in our cohort over the last decade for individuals with FIRES. We point to the importance of an early and comprehensive genetic work-up and the need for future studies to focus on assessment of longitudinal outcomes and trajectories in FIRES, which can be stratified by treatment strategies.6.In our study, we analyzed the phenotypic and genetic landscape of febrile-infection related epilepsy syndrome (FIRES) and introduced a conceptual framework outlining the identification and assessment of clinical histories of 25 individuals with FIRES through a computational approach in the EMR. Comparing FIRES to other epilepsies characterized by SE, we identified a gradient of diagnostic yield and genetic diagnosis and a spectrum of disease severity associated with RSE and NORSE-like presentations , inset. The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The study involving human participants were reviewed and approved per the Institutional Review Board at Children’s Hospital of Philadelphia. Written informed consent from the patients or patients legal guardian/next of kin was not required to participate in this study in accordance with the national legislation and the institutional requirements.DC, JX, AK, and IH contributed to the writing of the manuscript and figures. AG was responsible for data pulling using systematic computational analysis. DC conducted the manual review of all patients with FIRES. AK and JX conducted the analysis for larger cohorts in this study. KS, SR, and AK were responsible for interpretation of genetic testing from our CHOP and FIRES cohort. PG, MR, and NA were involved in the editing of this manuscript. All authors contributed to the article and approved the submitted version.IH was supported by The Hartwell Foundation through an Individual Biomedical Research Award. This work was also supported by the National Institute for Neurological Disorders and Stroke (K02 NS112600), the Eunice Kennedy Shriver National Institute of Child Health and Human Development through the Intellectual and Developmental Disabilities Research Center (IDDRC) at Children’s Hospital of Philadelphia and the University of Pennsylvania (U54 HD086984), and by intramural funds of the Children’s Hospital of Philadelphia through the Epilepsy NeuroGenetics Initiative (ENGIN). This study was also funded by the NORSE Institute (NORD GRT-00000167).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.