Phytophthora includes many plant pathogens important in agricultural and environmental systems. Natural interspecific hybridization has been reported several times in Phytophthora, and although the fundamental processes of interspecific hybridization and the consequences of subsequent ecological distribution are poorly understood, reports suggest some hybrids can infect a broader host range and display enhanced virulence compared to the putative parental species. During a survey carried out at the University of Aberdeen in 2014–2015, of oomycetes present in ornamental plants purchased via the internet, a batch of oomycete isolates remained unidentified, showing, in some isolates, features generally related to hybridization. The aim of this study was to determine whether hybridization events had occurred between endemic and introduced oomycetes, probably/possibly facilitated through the international plant trade. The list of isolates examined included a putative hybrid closely related to Phytophthora cryptogea. The putative hybrid isolate was further characterized, and pathogenicity were tests carried out on Eucalyptus globulus, using an isolate of P. cryptogea as a positive control. Cloning of ITS, COXI and β-tubulin genes resulted in different sequence versions of the putative hybrid isolate; after mapping and a polymorphism position comparison, it was concluded that the studied isolate contained genetic information from P. cryptogea, P. erythroseptica, P. kelmanii, P. sansomeana and Phytopythium chamaehyphon. A PCR-RFLP assay, a NEBcutter analysis and flow cytometry analysis (genomes ranged between 0.168 to 0.269 pg/2C) added further evidence of the hybrid nature of this isolate. The putative hybrid presented complex growing patterns ranging from rosaceous to chrysanthemum-like and had an optimum growth temperature of 25 °C. Although the putative hybrid produced visible symptoms of disease on E. globulus seedlings, assessment of the relative susceptibility of E. globulus to P. cryptogea and the putative hybrid indicated that P. cryptogea was significantly more virulent than the putative hybrid, based on mortality, disease severity and foliar symptoms.The oomycete genus  Phytophthora and Pythium [Phytophthora, being introduced [Phytophthora species to hybridize being reported to contribute to the emergence of new plant pathogens [Phytophthora species interact in soil, host tissue, or water and form interspecific progeny. The resulting new combination of traits from each parental species has been shown to alter host specificities and the hybrids were able to infect plants outside the host range of the parental species [The most important oomycete plant pathogen genera affecting agricultural and horticultural crops, ornamental plants and forest ecosystems are  Pythium ,2,3. The Pythium ; increas Pythium . The con Pythium . The inttroduced ,7,8. In athogens ,10. Hybr species , causing species ,13,14,15Phytophthora species established in laboratory studies has been confirmed by the detection of hybrids in agro-ecosystems. First detected in the south east of the UK on dying alders in the 1990s, the pathogen, thought to have emerged from Phytophthora cambivora and a species related to Phytophthora fragariae [Although thought to be rare in nature, there is evidence that natural interspecific hybrids occur in oomycetes . The potragariae , spread ragariae ,16. It iragariae ,18. Compragariae ,19.Phytophthora Clade 8b were reported by [Phytophthora Clade 8a, during a study on the phylogenetic relationships between species in the Phytophthora cryptogea complex and related species, Phytophthora erythroseptica and Phytophthora sansomeana, 19 hybrid isolates with multiple polymorphisms in the nuclear sequences were observed [Phytophthora Clade 6 species  that were either highly polymorphic or were unsequenceable; four different hybrid types, that presumably emerged from sexual recombination, were identified in this study, with physiological traits tending to resemble those of the maternal parents. Natural hybridization also appeared to be common among five closely related indigenous Clade 6 Phytophthora species isolated from waterways and riparian ecosystems in Western Australia [Phytophthora hybrid species classified under ITS clade 7a were identified in 2017 [Phytophthora by developing a strategy which combined genome-wide genetic fingerprinting and genome size assessment [Hybridization events in orted by  through observed . In 2013observed , the hybustralia . The nuc in 2017  in Taiwasessment . The appPhytophthora and Pythium species underlines the importance for their detection. As suggested above, hybridization events are preceded by contact between parental species under appropriate conditions which allow somatic or sexual hybridization; such contact may be facilitated by human activities such as in nurseries, the international plant trade and managed landscapes, where contact between species is enabled and favored. Following hybridization, hybrids proceed with new evolutionary traits and selection pressures may consequently result in rapid spread, exclusion of progenitors from the niche, successful competition for resources and/or changes in virulence enabling colonization of new hosts [Phytophthora, including Clade 1, Clade 2, Clade 6, Clade 7, Clade 8 and Clade 9. Therefore, detecting, identifying and characterizing new putative hybrids during oomycete surveys is clearly an important step in the development of efficient control and management strategies, and in improving understanding of plant diseases caused by oomycetes.The increasing body of literature on hybridization in ew hosts . OverallQuantification of oomycete diversity present in the roots and compost of hardy ornamental plants bought from nurseries, retailers and internet sellers, was undertaken in recent work at the University of Aberdeen  using both isolation and molecular analyses . In the Pinus mugo plant, with no foliar symptoms; Pythium dissotocum was identified from this substrate as well, and Phytopythium littorale and Pythium sterilum were found on the roots of the same plant. In 2020, isolate P3 was revived after 3 years storage on agar at 12 °C; pure cultures were maintained on potato dextrose agar .To further reduce the chances of cross contamination with other oomycetes, bacteria, opportunistic fungi or a mixture of strains, a single hyphal tip culture method was used for subculturing [−1, Oxoid, Cambridge, UK) and incubated in the dark at 25 °C for 7 days before proceeding with DNA extraction.An oomycete survey of ornamental nursery stock was carried out at the University of Aberdeen in 2015, where woody ornamental plants (99) were analyzed destructively . Isolateulturing . A 6 mm DNA was extracted from 50–100 mg washed and dried mycelium following the protocol of  and storFive molecular markers were used with the primers shown in 2, 0.2 mM each dNTP, 0.5 μM final concentration of each primer and 1.25 U Taq polymerase. Final volume was made up to 25 μL with water. PCR reactions were performed using a Life Technologies Veriti Thermal Cycler  with the following program: initial denaturation step ; 35 cycles ; annealing for 30 s at ; elongation step . After amplification, a final extension step  was included. Five reactions were performed for the potential hybrid isolate (P3) to reduce the potential for PCR bias. PCR products and amplicon sizes were checked and purified as standard. Sequences were analyzed and assembled using Geneious and the consensus sequences compared to sequences in GeneBank using the Basic Local Alignment Tool (BLAST).DNA amplification was carried out using Promega Go Taq G2 DNA Polymerase . The reaction mixture contained 2 ng DNA per reaction, 5 μL 5× buffer containing 1.5 mM MgClIsolate P3 showed double chromatogram patterns in ITS sequences, a feature typical of previously reported hybrids; thus, a cloning assay was carried to further elucidate this hybrid hypothesis.Purified amplification products of ITS, COX I and β-tubulin gene subsequences of putative hybrid isolate P3 were cloned using the Promega pGEM-T Easy Vector System Kit ; T cloning is a subcloning technique that avoids the use of restriction enzymes and where amplified inserts are cloned into linearized vectors with complementary 3′ thymine overhangs. Ligation and transformation were carried out according to manufacturer’s protocol. Single white colonies were picked from the transformation plates, inoculated individually into 5 mL LB with ampicillin and incubated at 37 °C with shaking at 150 rpm overnight. A DNA plasmid prep ) following the manufacturer’s protocol and plasmid DNA was sequenced by Eurofins Scientific . All sequences were analyzed with Geneious, with the main objective of detecting the presence of dimorphic positions; for each cloned region, the different cloning types  were detected and grouped before building a reference map.Phytophthora cryptogea E2  was used as comparison . The experiment was assisted using the NEB Cutter online tool , which provided visualization of expected banding patterns following NEB enzyme digestion of DNA sequence.A PCR-RFLP assay was established to reveal polymorphic sequence positions in the P3 hybrid isolate for ITS, COX I, COX II and β-tubulin genes. Amplification products were digested using Taq I and EcoRV Restriction Enzymes  using the supplier’s protocol. At least three PCR products were digested for each ITS, COX I, COX II and β-tubulin, and each digestion was repeated at least three times to uncover possible changes in the banding patterns. P. cryptogea could be one of the parental species of P3; thus, P. cryptogea E2 (University of Aberdeen culture collection isolate) was also used in this assay for comparison. The genome size of Phytophthora cryptogea had been recently analyzed using FC [Estimation of DNA content in the putative hybrid P3 isolate was carried out. During cloning, it was determined that using FC .P. cryptogea E2 were subcultured in 90 mm diam. Petri dishes containing 5 mL pea broth for 6–10 days. The assay was carried out using four internal DNA reference standards: Arabidopsis thaliana, Raphanus sativus, Glycine max and Brassica oleracea, with genome sizes (pg) of 2C = 0.32, 2C = 1.02, 2C = 2.34, 2C = 0.598, respectively [Phytophthora infestans 88,069 , was also carried out; although this isolate had not been analyzed by flow cytometry previously, some publications on P. infestans provided consistent results: 2C = 0.4–0.6 (pg) depending on the strain [2 of young leaf tissue for plant samples, and 100 mg of fresh mycelia were chopped with a sterile scalpel for 60 s. on a Petri dish containing 100 µL of Nuclei Extraction Buffer, the mixture left to stand for 30 s. and an additional 500 µL of Nuclei Extraction Buffer added. After standing for 60 s. the suspension was filtered through a 15 µm filter. For each sample and replicate, an unstained control (tube containing only the filtered suspension), and a stained tube to which 2 mL of propidium iodide staining solution was added after the filtering step, were prepared. Samples were covered with aluminum foil and left for 2 h prior to use. Measurements were made using a BD Fortessa  equipped with 7 lasers, emitting at a fixed wavelength of 488 nm. Fluorescence was recorded through 695/40 and 670/14 blue filters with constant amplification settings throughout the experiment. Data were analyzed using FlowJo v10.71 software. The following parameters were recorded for each sample: forward light scatter (FS), to estimate relative size of particles, side light scatter (SS), to estimate relative optical complexity of particles, relative fluorescence intensity of PI-stained nuclei (FL) and half peak coefficient of variation (CV) of the G0/G1 peak to estimate nucleus integrity and variation in DNA staining [P3 and e strain . The assstaining . DNA conGenome sizes were recorded as pg DNA/2C in which 2C corresponds to the complete DNA content of the nucleus  and alsoP. cryptogea [Colony growth rates and viability were analyzed using 3 different growth media: (1) 10% clarified V8A, (2) PDA, and (3) malt extract agar . Cultures were incubated at 5, 10, 15, 20, 25, 30 and 40 °C. P3 agar plugs (six mm diam) from 5–7 d-old cultures grown on PDA were placed at the center of Petri dishes containing the different media and incubated at 20 °C . The margin of initial colony growth was marked before transferring cultures to different temperatures. The diameter of each colony was measured daily for 10 days. The experiment was carried out in triplicate. After 10 days, cultures incubated at the highest and lowest temperatures were placed at 20 °C (24 h) to establish if growth could occur thus to check for viability ,36. Resuryptogea .Phytophthora, and certain Phytopythium species, as it inhibits the growth of Pythium species; however, there are certain Phytophthora species which are sensitive to [P. cryptogea to hymexazol has not been reported, P. cryptogea E2 was also tested. Following the protocol of [P. cryptogea E2 were subcultured to PDA, with and without hymexazol (50 µg mL−1.) and incubated at 20 °C. Six replicates were prepared, diameter growth measured, and mycelial characteristics observed over 10 days.Hymexazol, is often added to the PARP culture medium for the specific isolation of itive to ,38. In [itive to  the effetocol of , 6 mm diEucalyptus globulus plants were germinated using double autoclaved substrate  and incubated (18 °C to 20 °C: 12 h photoperiod (80.72 µmol m−2 s−1); 60% humidity.) in a phytotron and sprayed with water every two days for 4–6 weeks until young seedlings emerged.P. cryptogea E2 and isolate P3 were prepared following the protocols given in [2 plugs of each isolate were transferred to 150 mL glass jars containing 50 g millet grain  and 35 mL 20% V8 broth . Controls (20) were mock-inoculated with 5 mm2 sterile PDA plugs. Inoculated millet jars were shaken by hand every two days to ensure homogeneous distribution of inoculum growth and left in the dark at 25 °C for 15 days prior to plant-soil inoculation [Inocula of given in ,41. Isolculation .P. cryptogea E2, P3 or control inoculum added and gently mixed. Young healthy Eucalyptus globulus seedlings were transplanted to each pot and watered every two days until harvesting. Greenhouse conditions were 20–25 °C day–15–20 °C night, 12 h photoperiod . There were 20 replicates per treatment.Plastic pots (1.5 L) were filled with All Purpose Growing Medium , 20 g of inoculated millet grain with Three weeks after inoculation, plants were harvested, and number of dead/alive plants recorded giving ‘mortality rate’. Foliar symptoms and root rot were rated visually using a modified 0–4 disease severity scale ,44:Foliar symptoms: 0 = foliage without visible infection symptoms; 1 = foliage yellowing; 2 = foliage yellowing and tip wilting; 3 = yellowing, tip and total foliage wilting; 4 = plant death.Root rot disease severity: 0 = roots without visible infection or discoloration; 1 = roots with light discoloration and light root and stem rot; 2 = short roots with discoloration; 3 = short roots with severe discoloration and root rot; 4 = plant death.After evaluation for visible infections and symptoms, roots were washed in tap water and root length, fresh and dry weight determined. Root length measurements were carried out with electronic digital callipers. Plants were weighed (wet weight and dry weight) on an analytical balance; plants were dried to constant weight in a Gallenkamp drying oven at 60 °C, generally for 24–48 h.Data: mortality (percentage dead plants); Root Disease Severity (RootDS); Foliar Symptoms; plant length ; fresh weight (g); dry weight (g) were analyzed using R  with an Open-Source License.t test) indicating “var. equal= TRUE” in the R command; when all groups followed a normal distribution, but not variance homogeneity, the differences were tested using the Welch Two Sample T-Test indicating “var. equal = FALSE” in the R command; when normality could not be assumed, the non-parametric Wilcoxon rank sum Test was used. The variable Mortality was binary, thus a “2-sample test for equality of proportions without continuity correction” (Pearson’s Chi-Squared test) was used. RootDS and Foliar Symptoms (0–4) variables were qualitative ordinal variables that could not be properly analyzed as continuous variables. Thus, data were analyzed using the Wilcoxon test to illustrate differences between control and inoculated plants.Analysis 1 compared inoculated plants with control plants. Plant length (height), fresh weight and dry weight were considered continuous variables. Normality was examined using the Shapiro-Wilk Normality Test and adjusted by the Holm method, whereas homogeneity of variances was tested using the Levene Test with the mean as centre. When all groups followed a normal distribution and variances were equal, differences were analyzed using the Two Sample T-Test  was used to compare the effects of P. cryptogea E2 and isolate P3 on E. globulus, based on the variable ‘Mortality’. The other variables (Root DS and Foliar Symptoms) were analyzed using the Wilcoxon rank sum test.Analysis 2 compared pathogenicity of p < 0.05 was used.In all cases a significance level of P. cryptogea as the nearest match, and P. erythroseptica as the second closest match, whereas BLAST against COXI indicated an even closer relationship with P. cryptogea.BLAST searches of ITS sequences from proposed hybrid P3 suggested a close relationship with P. cryptogea MH136878.1 as reference, using the map as a reference tool in Geneious; additional closely related species were also added to the mapping reference comparison to analyze the similarities between the dimorphic positions and other potential parental species. The species chosen for the comparison list were those with high homology and percentage query cover when blasting P3 sequences in NCBI. Overall, 4 cloning types were identified and grouped for COXI and β-tubulin, whereas 8 cloning types were identified and grouped for the ITS region , 3 (5%) and 4 (35%) were very similar to Type 1 and thus to P. cryptogea, with a few more polymorphism positions that did not correspond to P. cryptogea. It was noticeable that for all Cloning Types some of the dimorphic positions did not correspond to any of the species added as reference comparisons .COXI cloning analysis showed 15 variable polymorphic positions with the prevalence of Cloning Type 1 , representing sequence information of P. cryptogea, P. erythroseptica and Phy. chamaehyphon. Cloning Types 1, 2 (14.29%) and 3 (14.29%) showed similarities predominantly with P. cryptogea and, when the nucleotide differed from P. cryptogea, it corresponded with the base composition of P. erythroseptica. Thus, Cloning Types 1, 2 and 3 produced different combinations of P. cryptogea and P. erythroseptica sequences, respectively, with polymorphisms at variable positions. Cloning Type 4, also representing 14.29% of the total, showed identical sequence composition to Phy. chamaehyphon at all polymorphic positions found, providing strong evidence that Phy. chamaehyphon was involved in the hybridization.Tubulin 5_6 cloning analysis resulted in the grouping of 4 different cloning types with the prevalence of Cloning Type 1 . Tubulin 5_6 was the region showing the most polymorphic positions with exact position patterns with one of the compared species used in the map to reference P. cryptogea. Cloning Types 1 (4.55%), 2 (13.64%), 4 (6.82%) and 5 (4.55%) were mainly identical to P. cryptogea, with the exception of isolated variable positions that could correspond to P. erythroseptica, P. sansomeana or P. kelmanii. In contrast, Cloning Types 6 (13.64%), 7 (9.09%) and 8 (13.64%) showed different combinations of polymorphic positions that corresponded mainly to P. erythroseptica, P. sansomeana and P. kelmanii, with lower similarities to P. cryptogea. Analyses of the results are shown and summarized in P. cryptogea E2 sequences were observed and also among P3 cloning sequences. Polymorphisms detected in P3 (P. x cryptogea related Hybrid) during cloning assays with COXI, TUBULIN 5_6 AND ITS are shown in detail in the ITS cloning analysis resulted in 8 different cloning types with the prevalence of Cloning Type 3  which was identical to P. cryptogea E2 in different regions. A different banding pattern in some of the regions would increase evidence that P3 has close similarities to P. cryptogea but is actually a different species; and (b) Observe different fragmenting patterns in P3, which would indicate a hybridization process with each banding pattern corresponding to a different parental species.The presence of differential base pairs in the studied regions fragmenting at particular positions was also examined in a PCR-RFLP assay to: (a) Compare the banding patterns between P3 and P. cryptogea E2 sequences (objective a), but also among P3 cloning sequences (objective b). The PCR-RFLP assay was carried out using Taq I and EcoRV as discriminatory enzymes cutting at 5′-TCGA-3′ and 5′-GATATC-3′, respectively. Interpretation was assisted using the NEB Cutter online tool to provide visualization of expected banding patterns after enzyme digestion of a DNA sequence. The results are shown in P. cryptogea E2. Different plant and oomycete species  with published genome sizes available (either by FC or NCBI) were used as standards. The DNA content measurement by FC was estimated by the relative position of the peaks between the reference and the objective sample which is highly dependent on the selection of the standard, the extraction buffer, the chopping intensity and speed, and thus, the user extracting the nuclei. The results presented for this assay are considered an approximation of genome size and used for a relative comparison of P3 with P. cryptogea, to test the P3 x P. cryptogea-Hybrid hypothesis.DNA content was measured using FC for both P3 and R. sativus and G. max (data not shown). P. infestans and A. thaliana appeared to be the most suitable standards with the most stable results. A histogram exhibiting the G0/G1 peaks produced for A. thaliana and R. sativus as standards is shown to illustrate the importance of a genome size similarity to achieve accurate results .Genomes based on FC analyses  ranged b results F,G. The P. cryptogea [Colony growth rates and viability of P3 were analyzed to compare results with the published literature of growth rates and optimum temperature of ryptogea .P. x cryptogea-related hybrid) produced clumped mycelia with submerged colony edges and a stellate pattern , a dispersed growth with a rosaceous pattern in PDA , and aerial, cottony growth showing a median pattern between rosaceous and petaloid in MEA . Isolate P3 had an optimum growth temperature range at approximately 25–30 °C in all media and remained viable after incubation at 5 or 40 °C. The fastest diameter growth rates measured were in 10% CV8 (15.55 mm/day) and PDA (15.17 mm/day), with a comparable slower growth rate in MEA (11.54 mm/day)  A–D.P. cryptogea E2 were grown in PDA with or without hymexazol: both isolates proved insensitive to this antibiotic  plant of known susceptibility to many Phytophthora species. Young seedlings of E. globulus were inoculated with isolate P3 and P. cryptogea E1 to evaluate the ability of P3 to infect woody plants. In this context, “pathogenicity” was defined as the ability of the pathogen to cause disease, and “virulence” as the extent of the pathology (disease) caused.An P. cryptogea E2 showed pathogenicity to E. globulus plants (p < 0.05). In comparison to the control plants where no mortality was observed, inoculation with P. cryptogea E2 and P3 led to the death of 20% plants, (p = 0.03501) and 15% plants (p = 0.07172), respectively   C. Plant  × 10−8) D, fresh  × 10−8) E and dry × 10−8) E were alUnidentified oomycetes isolated from ornamental plants during previous work at the University of Aberdeen  were subPythium [Phytophthora [Phytophthora, allowing the user to work with molecular and morphological data, and emphasizing species of high economic impact and regulatory concern for the United States; that resource has also proven valuable for international researchers working with the genus Phytophthora [Advances in molecular techniques have enabled more in-depth examinations of phylogenetic relationships within various groups of microorganisms including oomycetes ,46. AmonPythium  and Phytophthora ,50,51,52ophthora .The ITS region is sensitive to concerted evolution because it is located in rRNA genes that are repeated in tandem arrays of several hundred copies in each genome , howeverP. cryptogea was most likely involved in the parentage of the proposed hybrid. Cloning of ITS, COXI and β-tubulin genes resulted in different sequence versions of P3 that were grouped into Cloning Types; overall, 4 cloning types were identified and grouped for COXI and β-tubulin, whereas 8 cloning types were identified and grouped for the ITS region.In this current work, following an in-depth analysis of ITS and COXI sequences and NCBI databases, sequencing of β-tubulin was carried out. Dimorphic double peaks in sequence chromatograms for ITS, COXI and β-tubulin, typical of hybrids, were observed. The sequence data indicated that P. cryptogea, P. erythroseptica, P. kelmanii, P. sansomeana and Phy. chamaehyphon. It was noticeable that for all Cloning Types some of the dimorphic positions did not correspond to any of the species added as reference comparisons . COXI cloning sequences would be expected to contain sequences of one of the putative parent species via maternal inheritance [P. cryptogea, some of the dimorphic positions of all Cloning Types  did not correspond to either P. cryptogea or any of the species added to the reference list, suggesting somatic hybridization; that is, when different Phytophthora species are present in a common habitat, the zoospores can interact. Two interacting zoospores may fuse so that both nuclei are enveloped by one membrane. An example of this mechanism of hybridization was reported by [P. nicotianae and P. capsici. Another, different mechanism of somatic hybridization can occur by heterokaryon formation through which hyphae of two species can fuse and a species hybrid is formed.After mapping and a polymorphism position comparison, it was concluded that P3 sequences contained genetic information from eritance . For COXorted by  which dePhy. chamaehyphon was involved in the hybridization might point to a potential intergeneric hybridization. It is essential to explore this suggestion further to determine the extent of plasticity of evolution and hybridization in oomycetes.A similar occurrence was found in the ITS cloning sequence mapping, in which the presence of a polymorphism pattern failed to correspond to any reference species used in the map . One possible scenario is that P3 may have resulted from a relatively ancient hybridization and the background of the events has been lost, thereby obscuring the whole hybridization background of the isolate ,57. The P. cryptogea E2 and P3 sequences, and also among P3 cloning sequences. Nevertheless, interesting results were found from cloning ITS, COXI and β-tubulin, and given the results using COXII in the PCR- RFLP assay, it could have been interesting to carry out additional cloning with COXII to obtain more information regarding other possible parental species involved in the hybridization process. This work illustrated the difficulties and the importance of choosing and working with different DNA regions for species delimitation and examine potential hybridization processes; as shown in this study, species identification and hybrid detection can lead to uncertain or erratic results if only ITS and/or mitochondrial markers are used.The PCR-RFLP assay and the NEBcutter analysis added further evidence of the hybrid nature of isolate P3; the results of both assays showed that the banding patterns differed between P. cryptogea E2, except when using G. max or R. sativus as reference standards. Flow Cytometry analysis genomes ranged between 0.168 to 0.269 pg/2C, depending on the standard used. The results of DNA content estimation of isolate P3 were found to be reproducible when the standard used was close in genome size to the objective species  which we consider the most feasible approximation . These results were supported by the genome size measurements made using FC by [P. cryptogea isolates that ranged from 0.221 to 0.224 pg/2C.In plant pathology, detection, characterization and quantitation of pathogens are crucial for the development and application of control measures. A DNA content estimation of the incompletely characterized isolate P3 was carried out using FC with a range of reference standards. Similar results were obtained in replicate assays for P3 and ng FC by , who estP. cryptogea. Based on other publications, a higher genome size of a hybrid (double or triple) would be expected, due to the hybridization background, which would have resulted in a larger number of loci compared to the number found in the progenitors. It remained clear that isolate P3 was not a new strain of P. cryptogea, as a rapid ITS sequencing and BLAST analysis might suggest. The similar genome size could be explained by similarities between some of the potential parental species , however, with these findings, the finding of a Pythium species being involved in the hybridization process remains unclear; highly divergent progenitors share only a limited number of loci and may produce hybrids showing a substantial increase in numbers of loci [An unexpected result in this assay was the similarity in genome size between P3 and  of loci . This fiP. cryptogea to this antibiotic/fungicide, with slower growth resulting but not complete inhibition. There are no specific reports of the effects of this fungicide on growth rates of the potential parental Phytophthora species listed above, although hymexazol has been reported to have a species/strain-specific effect [Isolate P3 presented complex growing patterns, ranging from rosaceous to chrysanthemum-like, and had an optimum growth temperature of 25 °C. In terms of sensitivity to hymexazol, the results suggested a relative insensitivity of both P3 and c effect .E. globulus to P. cryptogea E2 and P3 and indicated that P. cryptogea E2 was significantly more virulent than P3, based on mortality, disease severity and foliar symptoms. In contrast, the variables height, or wet and dry weight of plants did not vary significantly between P3 and P. cryptogea E2, with such variables being significantly different for both isolates compared to controls. Although isolate P3 was less virulent than P. cryptogea, it was capable of producing disease symptoms in inoculated E. globulus. The reduced aggressiveness of P. x cryptogea-related hybrid P3 compared with P. cryptogea E2 towards E. globulus is consistent with the reported reduction in aggressiveness of some hybrids towards hosts of the parental species. However, it has been recognised that intra-specific hybridization between different oomycete species, divergent races of the same species, or populations from different ecological niches could generate pathogens with new host specificities and increased or decreased virulence [Assessment of the relative susceptibility of irulence ,58.Eucalyptus propagation programme, the nursery stage is a crucial point in terms of the risk of losing plants to pre-and post-emergence damping off, or root and collar rot disease [Phytophthora cryptogea has been reported to cause damping off and root rot disease of Eucalyptus spp. in nurseries, among others Phytophthora and Pythium spp., such as Phytophthora cinnamomi, P. citricola and Pythium anandrum [In any  disease . Phytophanandrum ,61.Phytophthora species supports that of previous studies demonstrating that many Pythium and Phytophthora species cause damping-off and root rot in several ornamental and forest plants [Phytophthora and Pythium species outbreaks that have occurred in Europe due to the introduction of contaminated plants [Pythium and Phytophthora hybrids deserve in depth examination.This work showing damping-off and root rot by t plants ,63,64,65d plants ,8,66. ThP. cryptogea . In addition, inoculation of reported hybrid species on a wider range of ornamental plants  under environmental conditions closer to those found in the field is required to better assess the threat hybrids pose to plant communities. It has been clear for some time that Phytophthora and Pythium pathogens are extremely adaptable [Phytophthora hybrids. It is essential that we now look to establish this hypothesis beyond doubt.Future research examining the functionality of polymorphisms found in the P3 isolate and other reported hybrids, i.e., whether these changes alter the function of a gene or set of genes, will contribute to the understanding of the mechanistic basis by which a particular polymorphism is associated with a specific change in aggressiveness, infection rate, or mode of action when attacking the host. It is clear from this work and previous publications, that hybridization in oomycetes poses a considerable threat in terms of the emergence of novel, potentially highly damaging taxa ,24,34,56daptable , and map


Community-based breeding programs (CBBPs) have shown, at pilot scale, to be effective and beneficial in achieving genetic progress and in improving livelihoods of smallholder communities. In Ethiopia 134 sheep and goat CBBPs were operational producing their own improved rams and bucks. Based on experience the implementation of further programs is possible with appropriate private and public support. A different challenge is the efficient dissemination of the improved genetics produced in current CBBPs to create population-wide economic impact. We present a framework applied to the Ethiopian Washera sheep breed to meet this challenge. We propose the establishment of a genetic improvement structure that supports a meat commercialization model based on the integration of community-based breeding program cooperatives, client communities and complementary services such as fattening enterprises. We calculated that the recently established 28 community-based breeding programs in the Washera breeding tract can provide genetically improved rams to 22% of the four million head. To reach the whole population 152 additional CBBPs are needed. We simulated the genetic improvements obtainable in the current 28 CBBPs assuming realized genetic progress in CBBPs of a similar breed and calculated the expected additional lamb carcass meat production after 10 years of selection to be 7 tons and the accumulated discounted benefit 327 thousand USD. These benefits could be increased if the CBBPs are linked to client communities by providing them with improved rams: additional meat production would be 138 tons with a value of 3,088 thousand USD. The total meat production of the existing Washera CBBPs was calculated at 152 tons and the joint meat production of CBBPs if integrated with client communities would be 3,495 tons. A full integration model, which includes enterprises purchasing lambs for fattening, can produce up to 4,255 tons of meat. We conclude that Washera CBBPs cooperatives can benefit from a higher level of organization to produce population-wide genetic improvement and economic benefits. Unlike in the dairy and chicken industries, for low input sheep and goat smallholder systems the proposed commercialization model puts breeder cooperatives at the center of the operation. Cooperatives need to be capacitated and supported to become fully functional business ventures. Livelihood of smallholder farmers often relies on their ruminant livestock or poultry. Improving efficiency of smallholder systems is a major aim of research efforts and development projects, which usually focus on issues such as product marketing, pastoral range management, feed production, healthcare and genetic improvement e.g., . The latImplementation of genetic improvement programs in smallholder small ruminant conditions is difficult for several reasons  and effeAn additional challenge and opportunity is the efficient dissemination of the improved genetics produced in current individual CBBPs to create population-wide impact. Assuming demand for sheep and goat products continues to grow, a new supply chain structure will benefit from the support provided by CBBPs role of genetic improvement providers, i.e., breeding cooperatives, supplying improved sires to client communities which benefit from the higher productivity of their animals and can concentrate on efficient meat production within their smallholder systems. Such a structure would resemble pyramidal genetic structures known to work in developed countries. Development of a more structured and commercially-oriented small ruminant meat supply chain on a large scale requires a conceptual framework and several enabling activities. In this paper we present a framework applied to a specific sheep population, the Ethiopian Washera sheep breed. We proposed the necessary steps to establish a genetic improvement structure that supports a meat commercialization model based on the integration of CBBP cooperatives, client communities and complementary services such as fattening enterprises. The paper also demonstrates the potential impact, both genetic and the expected economic benefit, when a large proportion of the total sheep breed population is influenced by improved local genetics, and discusses implementation issues.The experience in established CBBPs demonstrates that selected surplus males become of increasing interest by neighboring farmers and communities to be used for breeding . Thus, iRecent experiences demonstrated the financial feasibility of fattening Horro and Bonga sheep . In the Washera, also known as Agew or Dangla, is short fat tail; large body size; short-haired; predominantly brown; both males and females are polled; reared by Amhara and Agew communities in Ethiopia . The breThe pilot Washera CBBPs were established in 2021 through a typical approach in which the community establishes a cooperative where members formally agree on breeding goal, recording and selection procedures. Farmers with promising male lambs are paid to retain these lambs till final selection as replacement rams using a revolving fund which is cashed once these sires are cast for age and sold for meat. All unselected male lambs are culled for meat. In 2022 there were 28 community-based breeding initiatives covering several districts in five clusters  which weA recent survey  indicates a total of 3,233 households engaged in the CBBPs with a mean flock size of 12.08 sheep including 6.73 breeding females. The total number of sires was estimated assuming communities follow the suggested mating ratio of 25 breeding females per sire and a serving period of 2.5 years. A ram survival rate of 0.95 was assumed. The total number of lambs produced were calculated assuming a conception rate of 0.9 and survival to selection or culling age 0.9 and a lambing interval of 8 months, all assumptions were based on field data. The figure for litter size (lambs born per ewe lambing) was taken from survey results in each cluster. Thus, assuming all female lambs and only replacement male lambs are kept for breeding, then a total of 17,154 Washera lambs are annually culled for meat .via the CBBP cooperatives.The Washera meat production and commercialization model is proposed by combining existing up-scaling and out-scaling CBBP approaches. In this model, CBBPs produce improved breeding males for client communities, here called production units, which produce the bulk of lambs for meat and lambs for individual fattening enterprises or fattening cooperatives. In the proposed model CBBP cooperatives are the key organizations establishing the necessary business links between smallholder farmers in the village and market players who supply consumers. Thus, establishing a commercialization model of large scale that integrates production units, fattening enterprises, and supply of lambs to the live market or for processing in slaughter houses The integration strategies were modelled with assumptions on numbers of potential ram lambs available for production units, proportions of lambs produced in these units sold for meat or diverted to be finished in individual fattening enterprises or cooperatives as well as number of additional CBBPs required to impact the whole Washera population. The meat production and commercialization model were parameterized such that a range of situations could be tested to predict industry scale, genetic progress and economic impact.a) Non-integrated scenario–the current situation where all surplus male lambs in CBBPs are culled for meat. No formal integration between CBBPs and production units or fattening enterprises and cooperatives.b) Partially integrated scenario–above average CBBP male lambs are supplied for breeding in production units. No integration with fattening stations is considered in this case.c) Integrated scenario–CBBPs supply rams to production units and these supply lambs to fattening enterprises with three fattening capacity options (see details in 2.5).The analyses were done considering a planning period of 10 years and the following three levels or scenarios of integration.Washera sheep provide meat for sale and consumption. Hence, sustained improvement of litter size (LS) and lamb weight (SMW) are obvious breeding goals. Selected animals should also be adapted to their production systems, particularly resilient to the environments and regular climatic hazards which may be exacerbated by climate change.Genetic progress for these traits has not yet been calculated from field data in Washera CBBPs. In order to get an estimate of performance in current Washera sheep CBBPs, the genetic progress obtained in CBBPs of Horro breed was used. This breed has similar performance characteristics as Washera, for example, average litter size in Horro is 1.36 lambs/lambing and average lamb weight is 20.0 kg  while foPotential annual genetic progress in both SMW and LS was calculated using selection index theory  and assuMeat production was calculated for each production chain integration level by calculating the number and weight of male lambs culled or male lambs fattened considering dressing percentages of 44.2 and 49.48, respectively . For theFor the integrated scenario which also considers lamb fattening enterprises, three cases  were calculated: considering the current fattening capacity of 3,900 lambs (c1), increasing fattening capacity at the current rate of 1,000 more lambs a year up to 13,900 at year ten (c2), and increasing fattening capacity up to all acceptable (above average) lambs for fattening (c3). Following the financial feasibility analysis of The slight but sustained increase in number of lambs and lamb weight due to genetic improvement of LS and SMW were also considered when calculating meat production but reported separately from a scenario of no genetic improvement. Sensitivity of the assumed rates of genetic progress in LS and SMW on meat production and economic outcome was tested setting rates to 80% and 120% of those observed in Horro CBBPs.Economic benefit of the different scenarios was calculated as revenue minus cost over a 10-year planning horizon assuming a discount rate of 0.07 as in previous studies  to make In the partially-integrated scenario the economic benefit at CBBP level was calculated as before but considering that a proportion of lambs are sold for breeding and all male lambs in the production units are culled for meat. The only additional cost considered for production units was an overprice of purchased young CBBP rams. This additional cost for production units and additional income for CBBPs was taken as equivalent to 1 kg live lamb price (4.5 USD). The light annual increase in lamb weights and number of lambs due to genetic improvement were considered and reported separately.In the three cases of fully integrated systems, those including fattening enterprise, the benefit per kg “finished” meat was calculated as the difference between meat market price minus fattening cost per kg. Costs included veterinary services and other associated costs such as concentrate feeding and watering troughs. This cost per kg was assumed to be 65% of its price, a figure obtained as average cost in two fattening experiments applied to young CBBP Horro rams .The financial analysis for the three integration scenarios does not include other expenses than those related to the linking and fattening. Selection costs were considered for CBBPs since there would be no CBBP without selection and fattening costs didn’t include basal feed costs. Economic parameters were calculated separately with and without genetic improvement. selection costs, income from sale of cull lambs and income from sale of lambs for breeding were considered for CBBPs; costs due to purchase of breeding lambs, income from sale of lambs either for meat or for fattening were considered for production units; and costs due to purchase of lambs for fattening, costs of fattening and income from sale of fattened lambs were considered for fattening enterprises. Costs and incomes were discounted and accumulated to year 10, when c2 and c3 reach their fattening capacity target. Annual and accumulated discounted revenues, costs and benefits were obtained for the three integration systems at each production tier. Return on investment (ROI) was calculated as accumulated discounted revenues over accumulated discounted costs.Meat production potential and economic impact were based on the current number of Washera CBBPs. The number of additional CBBPs required to reach the entire Washera population with improved males was extrapolated from the current landscape.After 10 years of selection in CBBPs the increase in SMW was 1.77 kg and in LS 0.021 lambs. First selected progeny in the CBBPs was born in year 0  and first improved males are used in production units in year 1 with improved progeny expressing superiority in year 2. In the early years SMW and LS trends improve rapidly in the CBBPs and the genetic trends in the production units follows with a delay (lag) achieving at year 10 about half the improvement of the ram provided by the CBBPs. The increase in litter size at year 10 implied additional 272 and 1,676 lambs in CBBP and client production units, respectively . At yearIn the current non-integrated situation, the 28 Washera CBBPs produce young replacement males for own use and all surplus male lambs  are culled for meat. In the partially integrated situation all CBBP lambs above average , excluding 5% of lambs culled for physical appearance are considered available for breeding. From these, 367 are used as own CBBP replacements and the remainder 7,956 are selected for use in production units. CBBP lambs not used for breeding  are culled for meat . This amAccording to data compiled from the regional livestock office the total Washera ewe population in the five production clusters was 2,147,875. With current up-scaled CBBPs only 22%  of the ewes in this population could be served with CBBP born rams. Assuming that new CBBPs in each cluster will be of the average CBBP size in the cluster, it was estimated that 152 additional CBBPs are required to serve the whole Washera ewe population. In cluster one there are no more CBBPs needed, in fact with the proposed up-scaling strategy there are rams in excess to serve 63,563 additional ewes at another CBBP site or in production units. On the other hand, in cluster 5, 62 additional CBBPs are required to cover the target population of 490,750 ewes . ClearlyCurrent annual meat production of the 28 CBBPs is about 152 tons (carcass weight) and in the partially integrated scenario 3,495 tons, 81 tons from culled lambs in CBBPs and 3,413 tons from culled lambs from production units . Note heThe additional annual discounted benefit due to genetic improvement of SMW and LS in 28 CBBPs and their client production units over 10 years of selection is shown in Return on investment (ROI) for the improvement program in the CBBP layer is much lower than in the production unit layer  more meat is produced  but onlyWe proposed a framework to impact the Washera sheep population with genetic improvement in litter size and lamb growth rate, affecting its entire lamb meat supply chain. The underlying structure is a pyramidal genetic structure where CBBPs cooperatives are the nucleus responsible for sustained genetic improvement and delivery of improved rams to production units. Eventually, genetic progress achieved in CBBPs reaches a large proportion of the total Washera population through reduction in genetic lags between tiers and through sustained improvements supported by current and future CBBPs. The proposed genetic improvement and dissemination model leading to a novel meat supply chain differs from models applied in the poultry and dairy cattle industry.In Ethiopia, experiences with improved layer and broiler chicken breeds, in particular with dual purpose breeds or crossbreds between commercial and indigenous breeds, as well as their dissemination, has been in place for a long time. The dynamics of genetic improvement is “facilitated” since production of genetically improved eggs and chicks can be centralized and performed on a large scale. Improved eggs and chicks can be easily transported and distributed, but mostly under better control of specialized suppliers. The productive impact of improved poultry germplasm is almost immediate because broiler growth or laying hens production is quickly realized and generation length is short. Projects facilitating farmer’s access to preferred locally adapted improved breeds and a sustained multiplication and delivery system together with feed and health services are already in place . These sDissemination of improved dairy cattle genetics has also been experienced for a long time in Ethiopia and in many African countries. In this case, generation length is high, but improvement can be channeled through artificial insemination (AI) centers where proven bulls (often imported from developed countries) provide semen to be used on site to inseminate local cows. Performance testing and pedigree recording is well established in many dairy industries, so that information can be processed using BLUP breeding values in order to detect young dairy bull candidates for the AI center. Thus, a business structure has evolved around cattle AI centers providing semen doses and insemination services .In most developing countries, breeding and genetic improvement services in sheep and goat are rather uncommon and are more complicated to apply compared to poultry or dairy cattle. In many developed countries population wide genetic improvement of sheep and goats relies on effective pyramidal genetic structures with a stud (nucleus) tier producing males for multipliers and these producing males for the base  population. Fresh and frozen semen AI services are available and progeny testing facilities as well as sire referencing schemes are offered. Controlled matings and systematic performance recording structures allows both within and across breed genetic evaluations and optimum use of genetic variability.In low-input smallholder situations such as in Ethiopia, pyramidal systems and structured crossbreeding are difficult to implement. Communal grazing of pastoral systems and limited infrastructure to control matings is challenging and therefore full pedigree recording is often impossible. This limits the ability to run proper population-wide BLUP evaluations. Insemination with frozen semen in sheep is also more challenging compared to other species and much costlier than in cattle since it requires laparoscopic AI instead of intrauterine non-surgery procedures. Moreover, farmers in smallholder systems have no easy access to improved genetics. Dedicated producers of locally adapted breeds are scarce. Frequently when improved genetics is available, it is from exotic breeds which in most cases are not at all adapted to smallholder system or environmental conditions faced locally.A strategy to overcome at least partially these limitations is to concentrate breeding activities in public research stations and distribute improved males to private farmers or communities . There aThe CBBP experience and its organization as cooperatives is conductive to solving most business-related issues and encourage genetic improvement limitations  to be addressed. A pyramidal structure can be emulated through the proposed out-and up-scaling strategy and integration of CBBPs, production units and fattening enterprises. The proposed framework overcomes key issues related to stakeholder roles, breeding goals, meat production scaling strategy, sustainability, resilience and independence. There are, of course implementation issues and areas for further adjustments and research needs.via improved rams and cooperative arrangements, through fattening and supplying finished lambs to better paying markets. Other collective arrangements may include lamb conditioning initiatives to provide export slaughter houses with appropriate lambs. Ultimately CBBPs can be seen as a “starting-point for initiators and participants to continuously discover new ways of collaboration and engagement” , allowing a population-wide genetic evaluation to be targeted and thereby increasing the access to genetic diversity and consequent genetic progress.Continuous genetic improvement has been achieved following an efficient performance recording protocol integrated with CBBP specific breeding value estimation systems. Breeding values were estimated for each CBBP separately since genetic links between CBBPs are weak or absent. In the long term, farmers would benefit from population-wide genetic evaluations and access to superior males across CBBPs. Such an evaluation is in principle not difficult but needs genetic links which can be created using reference sires, first within clusters and then across clusters. Artificial insemination will be a convenient tool to facilitate this linkage. A centralized database with a unique identification system and recording protocol applied across CBBPs has been progressively implemented . Involving personnel from a number of institutions, essentially from local agricultural stations and public extension service, is critical for success of such initiatives. This includes a strong collaboration as CBBPs must have a responsible extension officer network. These officers may attend one or more CBBPs and require periodical training related to the implementation, execution and monitoring of CBBPs. Senior extension officers and researchers are in charge of the most technically demanding genetic specific activities such as genetic evaluation, artificial insemination and ram selection. Evaluation of the programs and formal steps to implement adjustments and compliance requirements are also required and available .The necessary feed resource development, health intervention and market linkages require support and guidance. Such needs should be supported on top of genetic improvement. Under the Ethiopia Small ruminant value chain transformation (SmaRT Ethiopia) program, ICARDA and partners developed a number of innovations, including genetic improvement, dissemination of improved genetics, development of feed and forages, fattening of lambs/kids, animal health interventions, and innovative market outlet with capacity building and innovative credit accessibility through cooperative organization. These innovations were tested in different areas and positive socio-economic benefit reported . Pro pooNew research needs arise with implementation. If fattening initiatives multiply genetic improvement goals, CBBPs may need to consider additional traits such as growth rate to finishing weight and feed conversion or residual feed intake, since feeding cost would become an issue.CBBPs produced a big impact on livelihood of individual communities. We have shown how individual CBBPs can benefit from a higher level of organization with cooperatives as main actors to achieve genetic improvement at population-wide level and estimated the resulting economic benefits. Through effective integration with fattening enterprises and output markets, this could also lead to more organized structures in the Washera meat supply chains. Institutional efforts focusing on supporting the role of the different tiers of the structure is essential.


Heterosis is the improved performance of hybrids compared with their parental components and is widely exploited in agriculture. According to quantitative genetic theory, genetic distance between parents at heterotic quantitative trait loci is required for heterosis, but how heterosis varies with genetic distance has remained elusive, despite intensive research on the topic. Experimental studies have often found a positive association between heterosis and genetic distance that, however, varied in strength. Most importantly, it has remained unclear whether heterosis increases continuously with genetic distance or whether there is an optimum genetic distance after which heterosis declines again. Here, we revisit the relationship between heterosis and genetic distance and provide perspectives on how to maximize heterosis and hybrid performance in breeding, as well as the consequences for the design of heterotic groups and the utilization of more exotic material and genetic resources. Heterosis, or hybrid vigor, is a phenomenon that has been recognized for over a century and refers to the increased performance of crosses compared to their parental components  but smaller than the maximum intraspecific genetic distance. Also this model is of course based on assumptions that may not necessarily hold true, like effect sizes being independent of genetic distance and the ratio of positive and negative contributions that enter the second term being constant over genetic distance. In addition, selection in breeding populations is different from natural populations and we must assume a considerable contribution of genetic drift that together would at least partially offset some of the assumptions. Nevertheless, this interesting model provides an explanation and a mathematical framework for an optimal mating distance and also for varying proportions of the different genetic effects over the genetic distance space.An interesting study recently suggested that even within a species there is an optimum genetic distance between the parents of a hybrid that maximizes the fitness by balancing the benefits of heterosis and the harm of genetic incompatibility  value is (P1 + P2)/2, so here 1 − MP becomes As for dominance effects, also epistatic effects can be both positive and negative  is proportional. But if, for example, plants do not mature in time due to adaptation issues or are severely affected by diseases to which they are not accustomed, then they cannot realize their true genetic yield potential and the estimated heterosis values can be biased. The direction of the confounding effect of adaptation on heterosis then depends on how the non-adapted parental component(s) and the hybrid are affected relative to each other. If one or both parental components are more severely affected than the hybrid, the midparent value will be reduced and the heterosis will be upwards biased. By contrast, if the hybrid suffers more strongly, this will reduce heterosis. Notably, this confounding effect of adaptation can also be caused by additive genetic effects, if the pleiotropic effect on grain yield or other target trait(s) is not additive, as may for example be the case when harvesting matured and not fully matured plots.On the other hand, adaptation is a likely cause of negative heterotic effects, as also the non-adapted allele can be dominant. In addition, the molecular pathways underlying adaptation are often finely tuned and thus epistatic incompatibilities can more easily arise if these co-evolved gene complexes are disrupted in an inter-population hybrid, which then has a higher probability of performing poorly. So ideally, experiments on heterosis would be done with only adapted material to exclude the potential confounding effects of adaptation. In practice, however, this will not be possible, as genetic distance will inevitably be associated with geographic distance and genetically more distant material will therefore in most cases also show a different adaptation, but even geographically close material may differ in its adaptation.From the above, we have seen that genetic distance is required for heterosis, but heterotic effects can be positive and negative and heterosis depends on maximizing the ratio of the total of the positive contributions relative to the negative ones. So what determines the number of positive and negative heterotic effects in established heterotic groups? Within a population, selection can work against segregating negative effects and can favor positive ones, but hybrid breeding is based on bringing together different populations.If lines are used, as is typical in hybrid breeding of both selfing as well as outcrossing crops, dominance effects cannot contribute to the per se improvement of each of the groups, as there is no heterozygosity in the lines as the final products. Nevertheless, there may be selection against the unfavorable allele, either in the homozygous state or if lines are developed through recurrent selfing also in the heterozygous state in early generations. Improvement of two heterotic groups in a heterotic pattern, however, occurs through reciprocal recurrent selection, which means that for negative dominance effect loci both heterotic groups should be pushed toward the favorable allele, as otherwise the hybrids between them are heterozygous for such loci which reduces heterosis and hybrid performance. This process may be rather slow due to the small effects of such loci for quantitative traits and the consequently low selection pressure against them. Notably, heterotic loci can be genetically independent from others but can also occur in linkage. If a positive heterotic locus with a small absolute effect is linked to a negative heterotic locus with a large absolute effect, selection may work against the latter and the same haplotype may get fixed in both groups thereby reducing the potentially possible genetic distance but benefitting heterosis and hybrid performance. This linkage between heterotic loci will also affect heterosis in most crops due to the commonly performed multi-trait selection, so that selection against a negative heterotic effect for one trait will reduce not only the genetic distance but potentially also the heterosis for another trait. Nevertheless, negative dominance effects are likely to be reduced over time within an existing heterotic pattern. Scientific studies on heterosis that are based on established heterotic patterns can, as a consequence, be expected to find a rather low proportion of negative heterotic effect loci and mainly those with very small effect sizes are remaining that anyhow cannot be mapped and identified. Thus, for any distant or not, non-co-selected groups of material, there should be more negative heterotic effects than for co-evolved groups. An indication for this comes from the recent study of Boeven et al.  in wheatAn important question that arises from these considerations is, if crosses between groups of a heterotic pattern might be advantageous to increase heterosis and hybrid performance. This challenges the central and long-standing paradigm of hybrid breeding that poses that the heterotic groups of an established heterotic pattern should be kept separated. This strict separation has been standard practice in hybrid breeding for decades to maximize heterosis but also as it simplifies hybrid breeding and offers a more favorable ratio of general (GCA) to specific combining ability (SCA) variances. However, just as for other germplasm groups, negative heterotic effects may also be present in the two groups of an established heterotic pattern. If for such loci the different alleles are fixed in the two heterotic groups, there is no way to select against them and the hybrids resulting from crosses between lines of these groups will inevitably be heterozygous and thus carry the burden of these negative heterotic effects. Fixation of the different alleles in the two groups may have existed from the very start in cases where the loci are not polymorphic in either of the founder groups, or may have arisen later through selection on certain genomic regions or simply by random genetic drift. It thus seems justified to assume that such negative heterotic effects exist also in established heterotic groups of adapted elite hybrid breeding material. In addition to reducing heterosis, the fixation of different alleles in the two groups can also further affect the hybrid performance. For loci with additive genetic effect, the hybrids cannot reach the performance of the favorable homozygous state, but only the intermediate value of the two homozygous classes.This situation can only be broken if the favorable allele is introgressed in the group where it is not present. This might be achieved by introgression of genetically distant material, however, with the potential disadvantage of adaptation issues or outbreeding depression associated with such material. A more direct approach, therefore, appears to be crosses between the two heterotic groups. Griffing (1963) and later on Cress  already discussed the point that through reciprocal recurrent selection no improvement is possible on loci that are fixed in the two groups. They suggested to mix the two heterotic groups and from this population develop two new heterotic groups through continued reciprocal recurrent selection. This would be advantageous for all loci for which the unfavorable allele was fixed in one of the groups. The major drawback of such an approach, however, would be the reduction in the expected heterozygosity of hybrids and with it the reduced heterosis and hybrid performance after the mixing of the groups. Only in the long run would genetic distance between the new heterotic groups and thus the high levels of heterosis be restored. This radical approach, therefore, does not seem suitable for established hybrid breeding programs that need to stay competitive also in the short run. In addition, also in this scenario, loci would get fixed in the two groups through selection and random drift.We therefore propose an alternative approach. We suggest that breeding crosses are not only made within each heterotic group as done so far, but to a smaller extent also between them Fig. . This ge1 of the cross A × B is backcrossed to both parents A and B. The idea was that if heterosis was due to dominance, it would be possible to exchange and accumulate favorable dominant alleles in the derived A‘ and B‘ lines, thereby improving them without affecting the hybrid performance. The motivation for this approach stemmed primarily from the poor performance of the early generation maize inbred lines and the necessity to improve them, while the idea of maintaining or increasing diversity was of no concern then. However, despite experiments supporting the approach, it was never widely adopted by maize breeders  can then be tested in field trials as a first step. The positive and negative heterotic effects can even with molecular markers not be determined beforehand, or only to a limited extent. This means that as a second step, the traditional approach of using testcrosses, so selected elite lines as testers or a tester mix from each of the established groups of a heterotic pattern, is used to produce hybrids with either the candidate population or if available with representative selected lines from that group. Based on the testcross performance, the decision is made whether a group is suited or not. In theory, one could as a next step extend the number of lines in the established target heterotic group and cross them with the candidate population or if inbred lines are available expand their number on both sides in order to use this population for mapping and effect estimation of heterotic loci, which could then be used for genomic-assisted approaches. However, the potential gain of such an approach will in most cases likely not justify the required resources and efforts.Another question concerns crops without established heterotic groups, as for example wheat. Zhao et al.  have recIn conclusion, hybrid breeding requires genetic distance between the parental components and thus between the heterotic groups in a breeding program. However, heterotic effects can be positive as well as negative and thus, heterosis and with it hybrid performance is not maximized by maximizing the genetic distance between parental components of a hybrid but by optimizing it.


One of the two X chromosomes in female mammals is epigenetically silenced in embryonic stem cells by X chromosome inactivation (XCI). This creates a mosaic of cells expressing either the maternal or the paternal X allele. The XCI ratio, the proportion of inactivated parental alleles, varies widely among individuals, representing the largest instance of epigenetic variability within mammalian populations. While various contributing factors to XCI variability are recognized, namely stochastic and/or genetic effects, their relative contributions are poorly understood. This is due in part to limited cross-species analysis, making it difficult to distinguish between generalizable or species-specific mechanisms for XCI ratio variability. To address this gap, we measured XCI ratios in nine mammalian species , ranging from rodents to primates, and compared the strength of stochastic models or genetic factors for explaining XCI variability. Our results demonstrate the embryonic stochasticity of XCI is a general explanatory model for population XCI variability in mammals, while genetic factors play a minor role. XCI evolved to balance the gene dosage between females with two X-chromosomes and males with one X-chromosome4. While the exact timing can vary across species5, XCI usually occurs during preimplantation embryonic development6. During this process, one of the two X-alleles in each female cell is independently, randomly, and permanently chosen for transcriptional silencing to match the single X-allele in male embryos9. The choice of silenced X-allele is inherited through cell divisions, propagating the random choice of allelic inactivation down each cell’s subsequent lineage. This produces whole-body mosaicism for allelic X-chromosome expression in each adult mammalian female, originating from very early embryonic development10.Every female mammalian embryo undergoes X-chromosome inactivation (XCI) as an essential step for successful development12. XCI ratios affect the phenotypes of X-linked diseases, as they can either protect or expose individuals to disease variants13. The factors that influence XCI variability are mostly studied in mice and humans, and include stochasticity12 and genetics16, but their relative roles are controversial17. Cross-species comparisons of XCI variability stand to reveal general or species-specific mechanisms of XCI. For instance, genetic determinants of XCI are well-established in lab mice20, but not in humans22, where they are harder to identify and measure. Exploring XCI variability in other mammals presents the opportunity to test models of stochasticity or genetics in the context of evolution.In humans, both X-alleles are equally likely to be inactivated, but XCI ratios vary widely among adult females, from balanced to highly skewed1, it was recognized that the inherent embryonic stochasticity and permanence of XCI is the simplest explanation for the observed variability in XCI among adults and positions this adult variability as a window into embryonic events27. For example, flipping 10 coins is more likely to result in 8 heads than flipping 100 coins is likely to result in 80 heads, meaning that the variability in heads-to-tails ratios depends on the number of coins flipped. Similarly, the variability of XCI ratios in a population of female mammalian embryos is determined by the number of cells at the time of XCI  allele33. In humans, genetic influence on XCI is mostly observed in small family studies or disease cases, with no strong evidence for the broad allelic effects seen in mice22. Another genetic influence on XCI is allelic selection, where natural or disease-causing variants favor certain X-alleles38. However, evidence for allelic selection through natural variation remains elusive in human populations. Thus, the relative contributions of stochasticity and genetics to population XCI variability in mammals remain unclear with currently limited data from mouse and human studies.In addition to stochasticity, genetic effects can influence the choice of allelic inactivation and contribute to population variability in XCI ratios. Allelic inactivation during XCI is mediated by the cis-acting long non-coding RNA XIST39 dataset. Our approach leverages natural genetic variation to sample X-linked heterozygosity and eliminates the requirement for costly phased or strain specific genetic information to assess XCI ratios across diverse mammals at population scale. We start by establishing the population-level XCI ratio distributions for all nine mammalian species and use models of embryonic stochasticity to predict the number of cells fated for embryonic lineages , resulting in a total of 19,180 initial samples , includilineages , Fig. 2.lineages , as welllineages , may impWe use bulk RNA-sequencing (RNA-seq) data to measure the X-linked allelic expression of a sampled tissue by computing allele-specific expression ratios of heterozygous single nucleotide polymorphisms (SNPs). The parental proportion of X-linked allelic reads are expected to follow a binomial distribution dependent on the number of sampled reads and the XCI ratio of the tissue see . The bin41  from the EN-TEx consortium43, achieving nearly perfect agreement in XCI ratio estimates for samples with folded XCI ratios of 0.60 or higher, demonstrating the accuracy of our approach.We fold the distribution of reference allelic-expression ratios around 0.50 to aggregate data across both alleles and enable a robust estimate of the XCI ratio magnitude for the bulk RNA-seq sample . We fit 41 . Interes41 , suggestBy calling SNPs from RNA-seq reads and employing folded distributions to model reference-aligned allelic expression, we can estimate the magnitude of XCI in any female mammalian bulk RNA-seq sample. We source female annotated bulk RNA-seq samples of 8 non-human mammalian species from the SRA database , additioTo ensure the allelic variability we report from X-linked SNPs is specific to XCI, we estimate autosomal allelic imbalances for all samples using the same pipeline and approach as for the X-chromosome analysis . CompariAfter generating population distributions of XCI ratios for the 9 mammalian species, we next explore how well models of embryonic stochasticity explain the observed adult XCI ratio variability. The initial variability in XCI ratios among mammalian embryos is dependent on the number of cells present during XCI , where aAn important consideration when estimating embryonic cell counts from XCI variability in adult tissues is the fact adult tissues only represent the embryonic lineage of the blastocyst as opposed to extra-embryonic lineages. This positions XCI variability of adult tissue samples as informative for the number of cells present within the last common lineage decision for all adult cells, i.e. the number of cells present within the epiblast of the mammalian blastocyst. If XCI occurs after epiblast specification, the variability in XCI ratios is determined by the number of epiblast cells at the time of XCI. On the other hand, if XCI occurs before epiblast specification, XCI variability within the embryonic lineage is influenced by both the initial stochasticity of XCI and the stochasticity associated with cell sampling during epiblast lineage specification. The temporal ordering of XCI among these lineage events cannot be resolved without cross-tissue sampling of both the extra-embryonic and embryonic tissues. As such, estimating cell counts solely on XCI variability in adult tissues provides an estimate of the number of cells present within the epiblast of the embryo.For the least and most variable species (macaca and dog), the estimated autosomal imbalances offer additional context for the reported XCI population variability. The reported X-linked variability in macaca is in excess to the reported autosomal allelic variability . This deModeling XCI ratio variability across numerous species allows comparisons in light of evolution for determining generalizable or species-specific characteristics in XCI. Broadly, we demonstrate XCI ratios are variable in each species we assess, revealing variability in XCI ratios itself as a conserved characteristic of XCI. The exact variance in XCI ratios varies across the species, with differences in the timing of XCI and/or embryonic/extra-embryonic lineage specification (differences in cell counts) as one putative explanation. We compare our estimated cell counts to the evolutionary relationships among the species we assess , suggestAfter determining stochastic models can explain population XCI ratio variability across mammalian species, we turn to testing whether we can identify any genetic correlates with XCI ratios. Our approach leveraging natural genetic variation to quantify XCI ratios enables us to assess a large catalog of genetic variants for associations with XCI ratios across mammalian species . One putative genetic contribution to XCI ratio variability is allelic selection during development, where increased X-linked heterozygosity , is more likely to produce selective pressures between the two X-alleles. It follows that samples with higher X-linked heterozygosity would be expected to exhibit more variability in XCI ratios.44. The trend in heterozygosity across species is as expected, with rats (likely laboratory strains) as the most inbred . For each species, we rank the samples based on their estimated XCI ratio and score the placement of samples carrying a given variant within the ordered list , IRAK148, and FLNA49. This suggests our analysis is able to recover putative examples of selection impacting XCI ratios via disease-variants, though with small effect sizes and low frequencies in our sampled population. In general, we are unable to identify strong associations between genetic variation and XCI ratios across all 9 mammalian species, both along the whole X-chromosome and for individual variants.The distribution of AUROCs for each species show striking similarities to a null comparison , indicatWe modeled tissue XCI ratios from bulk RNA-seq samples across 9 mammalian species and found population-level variation in XCI ratios, reflecting differences in developmental events such as XCI timing or lineage specification. We showed that embryonic stochasticity models fit the XCI data well and estimated epiblast cell counts at the time of XCI across species. We also searched for genetic factors influencing XCI ratios and found a pervasive lack of strong genetic associations with XCI ratios, indicating that XCI variability is mainly driven by stochasticity rather than genetic variation in mammals.33 has supported the hypothesis that a similar genetic mechanism can exist in humans and drive population XCI variability21, though evidence for XCE-alleles in human populations remains inconclusive22 and data from other mammalian species is historically absent. Although genetic influences on XCI, particularly variants affecting XIST15 or disease-associated variants37, have been identified, they do not constitute a general mechanism that can fully account for observed population-level XCI variability. Comprehensive assessment of genetic influence on XCI would require combined DNA and RNA sequencing data, which is challenging to perform at a large scale across mammalian populations. Our approach for extracting heterozygous variants from RNA-seq data28, while providing a sample of genetic variability, is still able to assess hundreds of X-linked genes per species for associations with XCI and culminated in only weak evidence for limited genetic influence on XCI ratios. In contrast, we demonstrated models of embryonic stochasticity can explain population XCI variability with exceedingly small amounts of error consistently across mammalian species, providing a much more general explanation for population XCI variability.The lack of cross-mammalian comparisons of population XCI variability has previously limited our understanding on the sources of XCI variability in mammals. The existence of XCE-alleles in laboratory mice45 and stochastic allelic drift during development20. We found a link between the variance in X-linked allelic expression and the inbreeding level of some species  accounts for the lack of evidence for broad allelic-selection or individual variants influencing XCI ratio variability in mammals, as both parental alleles are mostly equivalent. This does not apply to disease variants, but they cannot explain the widespread XCI ratio variability across mammalian species. We find genes associated with increased XCI ratios that have prior evidence for causing highly skewed XCI in disease cases, but their effect sizes and population frequencies are small in our samples. Therefore, the inherent stochasticity of XCI during embryogenesis is the main source of the observed XCI ratio variability in mammalian populations.A general model of X-linked genetic variability depletion , where only samples annotated as female were selected, using the metadata provided through SRA. Details for download and processing of the GTEx39 data can be found here28. The entire sample processing pipeline uses a standard collection of bioinformatics software tools, all available for installation via Conda . All Snakemake workflow rules, environment setup procedure, analysis commands and options, and underlying libraries are available on Github at https://github.com/gillislab/cross_mammal_xci, and https://github.com/gillislab/xskew. Briefly, a .fastq file acts as input, for either single- or pair-end sequencing experiments, and a .vcf and .wig file are produced as outputs for subsequent compiling of allele-specific read counts in R v4.3.0. The R script used for combining the .vcf and .wig information is also made available at https://github.com/gillislab/cross_mammal_xci/tree/main/R. Genome generation and alignment was performed with STAR, with the addition of the WASP58 algorithm for identifying and excluding reference biased reads. We extract chromosome-specific alignments from the .bam file (X chromosome or specific autosomes) and use GATK tools to identify heterozygous SNPs from that chromosome. The suite of GATK tools for identifying heterozygous variants from RNA-sequencing data was used following the GATK Best Practices recommendations. Specifically, the tools utilized include AddOrReplaceReadGroups -> MarkDuplicates -> SplitNCigarReads -> HaplotypeCaller -> SelectVariants -> VariantFiltration.All non-human mammalian fastq data was downloaded from the Sequencing Read Archive . In each case the latest assembly version path was used, and the genomic.fna and genomic.gtf was downloaded. Annotated and indexed genomes were generated with STAR using --runMode genomeGenerate with default parameters.Reference genomes and gene annotations (.gtf files) for each species were sourced from the NCBI Refseq database . Using the subset of skewed samples for each species, we averaged the folded allelic-expression ratios for all SNPs present in 1 mega-base (MB) bins across the X-chromosome . ChromosStarting with a single parental allele, the sampled maternal allelic-expression of a heterozygous X-linked SNP can be modeled with a binomial distribution, dependent on the ratio of active maternal X-alleles in the sample and the read depth of the SNP.60. Since SNPs vary in read-depth, we use a folded-normal model as an approximation of the underlying mixture of depth-dependent folded-binomial distributions. The probability of allelic-expression under the folded-normal model is defined as:Where The folded-normal model can also be applied to autosomal data to estimate allelic-imbalances. For each species, we extract chromosome-specific alignments from the .bam file for the two autosomes closest in size to the X-chromosome . We emplXCI is a binomial sampling event, where the number of cells choosing to inactivate the same X-allele follows a binomial distribution defined as:Embryonic XCI ratios can be modeled as: We estimate We model population XCI ratios as:We identify the normal distribution with minimum sum-squared error between its CDF and the empirical population XCI ratio CDF, minimizing error over the tails of the distributions with percentiles <= 0.40 or >= 0.60 . We compWe compute sample heterozygosity as the ratio of SNPs detected in a sample (20 read minimum) to the total number of unique SNPs identified across all samples for a given species. We quantify associations between X-linked heterozygosity and XCI ratios as the spearman correlation coefficient between the sample X-linked heterozygosity ratio and the fitted mean and variance of the maximum-likelihood folded-normal distribution of the sample . We onlyWe quantify the strength of XCI ratios as a predictor for the presence of a given variant through the AUROC metric. Given a ranked list of data (XCI ratios) and an indicator of true positives (samples with a given variant), the AUROC quantifies the probability a true positive is ranked above a true negative. An AUROC of 1 indicates all true positive samples were ranked above all true negative samples, demonstrating XCI ratios were a perfect predictor for the presence of that variant. An AUROC of 0.50 indicates random placement of true positives and negatives in the ranked list, demonstrating XCI ratios performed no better than random chance for predicting the presence of that variant. We compute the AUROC through the Mann-Whitney U-test, defined as:We estimate the power of each variant through bootstrap simulations. We randomly sample with replacement the XCI ratios of the true positive and true negative samples, those that either carry or do not carry a given variant. We match the sample size of the original true positive and negative labels. We compute a bootstrapped AUROC and p-value from the simulated data, repeating for 2000 simulations to compute a bootstrapped distribution of AUROCs. The AUROC power  is defin61 v4.3.0. All plots were generated using ggplot262 v3.4.2 functions. The phylogenetic tree in http://www.timetree.org/.All analysis was performed in RSupplement 1


The Speed-Gene study aims to identify genetic variants influencing athletic performance and human locomotion using motion capture technology. Currently, 60 female participants have completed the testing protocol, and the overall aim is to recruit 283 moderately trained, healthy Southeast Asian individuals . Participants will undergo biomechanical analysis and genetic testing. Several analyses will be performed, including (but not limited to) linear and angular kinematic analysis using motion capture technology, force plate dynamometry and genetic analyses to define novel power/torque related outcomes that would be more sensitive to allele-specific differences in athletic performance. Pretesting beverages will be provided, and activity history and current activity levels will be assessed by a questionnaire. The kinematic data will be obtained using a Qualisys Track Manager (QTM) system, and DNA will be extracted from white blood cells. The participants serve as their own controls. Although the Speed-Gene study is tightly controlled, our preliminary findings still indicate considerable individual variability. More participants and further genetic analysis are required to allow the investigation of potential underlying genetic mechanisms responsible for this individual variability. Over the last 30 years significant research has been conducted to uncover the genetic basis of athletic performance and health related fitness. Athletic performance is influenced by phenotypes, such as body size, explosive strength, muscle flexibility and maximal oxygen uptake, each of which results from a wide variety of genetic, physiological, anthropometric, and biomechanical factors, as well as their interactions . It is bFurthermore, several association studies have demonstrated that α-actinin-3 protein and angiotensin-converting enzyme have beneficial effects on abilities related to speed and power, including short-distance sprint time and vertical jump height , 6; howeIn this study, we aim to overcome these limitations and provide new insights into the influence of genetics on performance and human physiology. To this end, we will apply motion capture technology to explore how various genetic polymorphisms may affect more specific biological characteristics during explosive SSC-type movements. The overall goal of this study is to identify gene variants that influence torque production on certain joints and impact on various specific power related outcomes during explosive body movements as shown in Table 2 would be recruited for this study.Sprinters, power-oriented athletes, and anyone who regularly engage in heavy resistance training or sports related to sprinting will be excluded from our analysis. To ensure both body composition and genetic homogeneity, only female, Southeast Asian (for 3 generations) volunteers with a mean body mass index (BMI) of 23 kg/mParticipants will be excluded from the study if they respond “yes” to any of the eight PAR-Q questions or have any conditions that restrict their ability to exercise, such as high blood pressure or musculoskeletal disorders. The GPPAQ questionnaire will also be used for evaluating our cohorts’ current levels of physical activity. Participants whose work demands intense physical activity, such as handling very heavy objects , or participants who reported participating in power strength-related recreational activities, such as gym training, and tennis will be excluded.Seventy-two hours prior and throughout all tests, participants will be asked to abstain from coffee, alcohol, drugs, caffeine or other stimulants. Participants will be required to consume an energy drink containing mostly liquids and carbs (1 to 1.5 g•kg1 BM) before to the start of the test in order to allow appropriate access to carbohydrate energy stores.Each participant will receive test instructions one week prior to testing. As previously described  two hourAs illustrated in Fig. Data will be collected using motion capture technology, and processed using Qualisys Track Manager (QTM). Eleven reflective markers will be placed at precise anatomical sites on the trunk and lower extremities. In particular, they will be positioned on the sacrum (F), anterior superior iliac spine (left and right) (E), greater trochanter (left and right) (E), lateral condyle (left and right) (C), apex of the lateral malleolus (left and right) (B), and fifth metatarsal (left and right). Each of the nine cameras will have its exposure, threshold, frequency, and flash duration adjusted to precisely detect the reflecting marker position. If a marker’s reflection is unsatisfactory, we will adjust its threshold, exposure, or flash time to ensure that we can effectively observe the marker’s reflection on the computer screen. The wand and L-shaped structure supplied by the manufacturer will be used to calibrate the equipment prior to each testing session.The captured data from the reflecting marker (F) will be utilized to analyse kinematic data such as jump height, maximum velocity, acceleration and running times. The recorded data from reflective markers  will be used to identify the angular velocity and acceleration of the hip joint, while the data collected from reflective markers  will be used to detect the angular velocity and acceleration of the knee joint. For the measurement of torque in hip or knee joints, segmental mass will be multiplied by angular acceleration , followiOn the basis of the model shown in Fig. As shown in Fig. A spring-loaded lancet will be used to pierce the participant’s index finger tip skin in order to collect a small amount of blood (80–150 µl) as previously described . The DNAThe calculation of sample size is based on a conservative estimate of both the expected variation and the standard deviation for torque and power related measurements derived from our pilot work . Our powwww.quantitativeskills.com/sisa/) the genotype interactions on performance parameters will be further assessed using correlation analysis. Briefly, three genetic models  will be tested. The additive genetic model will be consisted of 0, 0.5 and 1, to represent I allele homozygotes, ID heterozygotes and homozygotes for the D allele, respectively; for the I allele dominant or D allele dominant genetic models, the corresponding values will be 0, 0, 1 or 0, 1, 1, respectively. The percentage of the genetic contribution to phenotypic variance explained by each genetic model will be estimated by expressing r2 from the correlation analyses (taken as an estimate of percentage variance explained under the model) as a percentage of the variance explained by genotype effects in the model-free ANOVAs, as previously described [To compare the effect of each performance parameter initially we will use the one-way analysis of variance (ANOVA). The Tukey’s post-hoc test will be used to determine statistical significant difference among the genotype groups. The level of significance will be set at 0.05. Then the quantitative genetic association data and performance parameters will be analysed using linear regression models, with related torque and power outcomes and alleles as covariates. As previously described  using thescribed . This prFor the preliminary results, a t-test was utilized for the comparison of the mean values between the female participants with different ACTN3 and ACE genotypes. To check the normality, we used the Kolmogorov Simonov test. The observed genotype counts were not significantly different from those expected under Hardy–Weinberg equilibrium (HWE).The preliminary results shown in Fig. Considering the complexity of athletic performance it seems evident that it does not fit straightforwardly into a single disciplinary framework and cross-disciplinary research is necessary. The planning and development this study combining biomechanical and genetic analysis began in 2020. Subsequently, recruitment and data collection were initiated at Mahidol University. To date, 60 female participants have completed the testing protocol, and 100 have completed the DNA isolation analysis. Although our study was tightly controlled, we still observed significant variability.The preliminary results demonstrate that, compared to their ACTN3 XX counterparts, ACTN3 RR homozygotes demonstrated a trend towards higher hip torque production within the DJ eccentric phase. Furthermore, female participants with the ACE DD genotype exhibit increased knee torque production within the CMJ eccentric phase compared to their ACE II counterparts, indicating the need for further research in this area.Recent in vivo evidence indicates that the ACTN3 gene influences the preservation of force with increasing muscle contraction velocity, rather than force itself . Based oThese results align with recent research findings obtained using isokinetic dynamometry tests that demonstrated that ACTN3 RR individuals exhibit larger peak torque at higher angular speeds (30–180 deg/s) than ACTN3 XX individuals . IsokineACE DD + ID female participants during CMJs compared to their ACE II counterparts demonstrates the polygenic nature of peak athletic performance, with each gene influencing certain performance characteristics. When there is large number of genes involved, it becomes hard to distinguish the exact effect of each individual gene variant on physical performance. Previous studies [Since DJs are considered a functional indicator of the explosive muscle power of leg extensor muscles, the difference detected in the hip joint enables us to hypothesize that the α-actinin-3 protein is likely to affect the extensor muscle group kinematic chain during the eccentric phase of these jumps. Within the DJ eccentric phase, noncontractile muscle supports contractile muscle, thereby increasing muscle force . Accordi studies , 22- [24More participants are being recruited to provide sufficient statistical power to investigate both specific (hypothesis-driven) and nonspecific (hypothesis-free) genetic variants as possible predictors, allow follow-up of these results with appropriate statistical analyses, and to expand the genetic analysis to include additional genetic loci and techniques.