Fusarium asiaticum is one of the pivotal members of the Fusarium graminearum species complex (FGSC) causing Fusarium head blight (FHB) on wheat, barley and rice in large parts of Asia. Besides resulting in yield losses, FHB also causes the accumulation of mycotoxins such as nivalenol (NIV) and deoxynivalenol (DON). The aim of this study was to conduct population studies on F. asiaticum from Southern China through mitochondrial genome analyses. All strains were isolated from wheat or rice from several geographic areas in seven provinces in Southern China. Based on geographic location and host, 210 isolates were selected for next generation sequencing, and their mitogenomes were assembled by GRAbB and annotated to explore the mitochondrial genome variability of F. asiaticum. The F. asiaticum mitogenome proves extremely conserved and variation is mainly caused by absence/presence of introns harboring homing endonuclease genes. These variations could be utilized to develop molecular markers for track and trace of migrations within and between populations. This study illustrates how mitochondrial introns can be used as markers for population genetic analysis. SNP analysis demonstrate the occurrence of mitochondrial recombination in F. asiaticum as was previously found for F. oxysporum and implied for F. graminearum. Furthermore, varying degrees of genetic diversity and recombination showed a high association with different geographic regions as well as with cropping systems. The mitogenome of F. graminearum showed a much higher SNP diversity while the interspecies intron variation showed no evidence of gene flow between the two closely related and sexual compatible species. Fusarium graminearum species complex (FGSC) are the main causal agents of Fusarium head blight (FHB) and infect wheat (Triticum aestivum L.), maize (Zea mays L.) and other small grain cereals, causing significant losses in grain quality and yield around the world  and southwest of China, where FHB is the most prevalent  is a crucial element for p debris . In Brazon wheat , whereasng areas . In soutrotation .Fusarium populations  and rnl (mtLSU). All of these genes are encoded on the same strand and genes are organized in the same order  and regarded as one ecological region. The Hunan Province is a transition region between plains and mountains, its northern part is adjacent to MLRYR. The Sichuan and Fujian Provinces are both mountainous regions. The cropping system is also different among these regions. In the MLRYR, which is the main wheat producing area in Southern China, wheat-rice rotation is predominant. In Sichuan Province, crop diversity is much higher and the acreage of wheat is significantly smaller compared to MLRYR (Fusarium strains were isolated from diseased wheat heads and perithecia on rice stubble (debris of the previous crop) by a single-spore isolation procedure described previously . Random sheared shotgun library with specific index of each F. asiaticum strain was made using the Illumina TruSeq DNA Sample Prep Kit, according to manufacturer’s protocols (Illumina). The concentration of independent genomic library was quantitated by QUBIT 3.0 fluorometer. The 210 independent libraries were pooled with equal amount by adjusting the solution volume and then were sequenced using the Illumina HiSeq X Ten platform which supported the acquisition of 2 × 150 bp paired-end reads at ∼50X coverage per sample. Subsequently, Casava 1.8 software was used to de-multiplex reads which were filtered for quality using fastp with forced polyG tail trimming (-g) and minimum quality Phred score ≥ 20 (-q 20). The F. graminearum strains were sequenced by other research groups, and their mitochondrial genome sequences were downloaded and analyzed in this study  with the SPAdes assembler , which h strains . Isolate2, NCBI’s ORF Finder3, CD-Search .P-value for rbarD from the number of reshuffles indicated in sample (p.rD), and principal component analysis (PCA) were performed with R package Poppr  . The geoF. culmorum mitogenome (accession number NC_026993.1) was added to the non-intronic alignment of the F. asiaticum and F. graminearum strains. The alignment was generated by MUSCLE v3.8.31. Phylogenetic analysis was conducted using the ML method which was run using IQ-Tree with model selection and 1000 bootstraps with the F. culmorum strain as outgroup. The best model selected was TPM2u + I + G4.A F. asiaticum strains were assembled into single circular DNA molecules, with the total size ranging from 89,966 to 98,925 bp. All mitogenomes encoded the same set of genes: 14 Protein coding genes (PCGs), 28 tRNA, two rRNA, and one large open reading frame with unknown function (LV-uORF), all with the same orientation and order. The intronic regions vary in length from 44, 676 to 53,583 bp, which accounts for almost half of the entire length of the mitogenome in each strain.The complete mitogenomes of all 210 F. asiaticum mitogenomes, including 76 SNPs and 44 indels  are putatively due to an additional intron insertion inside an already present intron, because the insert region coded for an additional HEG. Among the seven introns which showed presence/absence pattern, three were absent in most isolates: two (atp9-i181 and cob-i779) were just present in one strain and one (cox2-i552) was found in four strains. We investigated the size composition of the other four introns. As shown in Within the 210 F. asiaticum mitogenome alignment. Excluding gapped sites, this yielded 30 parsimony informative positions out of the 48376 bp-long alignment. Subsequently, the 30 sites were manually curated at which point 8 were removed, because they were due to length variations of neighboring poly tracts, resulting in 22 reliable parsimony informative sites. The curated alignment was used for analysis in PopArt, where 13 haplotypes were detected among the 210 F. asiaticum isolates. Composition of haplotypes in four regions was similar with one predominant haplotype found in all regions (180265) , while 171156 and the 180197 haplotype group shared the cob-C163T SNP. The three additional SNPs involved were the same on all three branches. These three SNPs are adjacent to each other and are located in an intergenic region. Although only five sites are indicative of recombination, they represent 23.8% of the parsimony informative sites used for this analysis. Furthermore, considering the low level of variation observed it is highly unlikely that two SNPs located in coding sequences of highly conserved genes have independent origins or that same three adjacent SNPs mutated the same way in three different backgrounds.Parsimony informative sites were extracted from the non-intronic regions of the (180265) . The intaplotype . There waplotype . Howeverpulation . DetaileF. asiaticum, all 210 strains were genotyped based on their intron composition (P = 0.0099) linkage disequilibrium with a high rbarD value (0.1758) was observed in Sichuan, indicating limited genetic exchange among strains from this province. Although linkage disequilibrium could be a result of gene flow from other populations, considering that Sichuan shows the highest haplotype diversity and it is a mountainous region limited genetic exchange is the most likely explanation. In the other three regions, the rbarD values were much lower and not significant at the 0.05 level, suggesting genetic exchange among these populations. Pairwise Nei’s genetic distance of the four populations ranged from 0.001 to 0.01  and one F. asiaticum specific intron (cob-i823), which were fixed in one species and absent from the other species. Interestingly, some introns showed clear association with the two species. Atp9-i181 and cob-i779 were absent in most F. asiaticum strains (209/220), but fixed in the F. graminearum population. The size of nad2-i762 was different in the two species, 1475 bp in F. asiaticum and 1465 bp in F. graminearum. A similar situation was also found in cox2-i228, of which the size in most F. asiaticum strains (208/220) was 1146 bp, while a 1159 bp intron was mainly found in F. graminearum (16/24) as well as one strain with a 1146 bp intron, one with a 1147 intron bp and six strains with no intron at that location at all. Based on genotypes of intron size, 41 and 15 MLGs were identified in F. asiaticum and F. graminearum populations respectively. Taking into account the difference of population size, F. graminearum showed a higher eMLG value indicating higher genotypic diversity within the population. Simpson’s index, haploid genetic diversity and Nei’s gene diversity index also suggested a higher level of diversity of F. graminearum than of the F. asiaticum population .A total of 42 introns was identified in pulation . In a PCanalysis . ApplyinF. asiaticum, F. graminearum and F. culmorum, as outgroup (A maximum likelihood phylogenetic tree was constructed based on the non-intronic (exonic and intergenic regions) alignment of outgroup . The twoF. asiaticum was the predominant species on both wheat and barley  of the closely related species F. graminearum   . The sizF. graminearum mitogenomes (F. asiaticum isolates (N = 210) in this study. The genetic variation in the mitochondrial genome is the result of two types of events: (i) small sequence variations (SNPs and short indels) and (ii) intron gain or loss. In our previous study, length variation across F. graminearum mitogenomes was found to be largely due to variation of intronic regions  which was suggested to be due to geographical barriers observed in this mountainous region and a recent migration of population inferred by unbiased gene flow. In contrast, in middle and lower reaches of Yangtze River Region the pathogen behaved as a random mating population with frequent outcrossing , which is in contrast to our previous study  dispersed in the population. The absence frequency of the other four introns in each ecological region showed significant relation with population genetic structure. Limited genetic exchange in the Sichuan population may restrict the spread of introns, which resulted in a higher absence frequency of three introns  in this region. In the other three regions random mating may have promoted the spread of each of these introns. The specific alleles in the Sichuan population also reflect the low recombination with other regions.It has been reported that mitochondrial introns can spread through horizontal transfer during sexual and clonal reproduction . The preF. asiaticum and F. graminearum revealed more variations than intraspecies of F. asiaticum. The LV-uORF is a high variable region in some Fusarium species. However, the variations in LV-uORF between F. asiaticum and F. graminearum were relatively small. Nevertheless, significant more SNPs were found in the LV-uORF region of interspecies than intraspecies comparisons and 20 of 32 SNPs caused non-synonymous substitutions, while no nonsense mutations were obserced. This fuels the debate whether or not the ORF is actually coding for a protein or not. Based on the relatively high number of non-synonymous substitutions it at least seems under a different selection pressure compared to other mitochondrial genes.Comparative mitogenomic analyses between F. asiaticum mitogenomes were in intronic regions and size differences are primarily related to the presence/absence of introns. All population genetic parameters  revealed a higher level of diversity in F. graminearum compared to F. asiaticum. Therefore, we can conclude that the mitogenome of F. asiaticum was more conserved than F. graminearum. This is also in agreement with the global distribution of the two species. F. graminearum is widely distributed all over the world with high genetic diversity. In contrast, F. asiaticum seems to be a regional species mainly encountered in East Asia and some confined regions elsewhere, where it coincides with rice production (F. graminearum isolates studied by F. asiaticum isolates from the present study originated from Southern China within 4 years. Therefore, additional F. asiaticum strains from locations outside China as well as historical collections should be involved in the future to further confirm the conservation of mitogenome of this species. Hybrids between F. graminearum and F. asiaticum can be generated by in vitro crosses (F. graminearum and F. asiaticum on a large evolutionary time scale. Moreover, comprehensive surveys were performed in New Zealand (F. graminearum species complex was between F. meridionale and F. asiaticum reported from Nepal (As expected, the main variations observed among the oduction . The sma crosses . However Zealand , Japan ( Zealand , and Chi Zealand  but the om Nepal . Our detF. asiaticum, which is highly conserved within the species. The length variation was mainly due to presence/absence of intron which harbored homing endonuclease genes. Intron patterns can be used as genetic markers for monitoring population dynamics. Recombination in mitogenomes was identified in F. asiaticum as was previously reported for the asexual species F. oxysporum and the homothallic species F. graminearum. Different levels of genetic diversity and recombination were observed in different ecological regions, which coincided with geographic characteristics and cropping conditions. The interspecies analysis revealed a higher diversity of the global species F. graminearum than F. asiaticum and clear interspecies differences. The results of this research extend our knowledge on the variability and recombination of mitochondrial genome of F. asiaticum and improve our understanding of the evolution and dispersal of this species. It also demonstrates the power of population genomics and the application to track and trace migration using the mitogenome.Based on the mitochondrial genomic analysis of a large population, we constructed a pan-mitogenome of The datasets generated for this study can be found in the GenBank, the accession numbers are listed in HZ, WC and JF conceived and designed the experiments. MY performed the experiments. MY, HZ, and BB analyzed the data. MY, HZ, BB, TL, CW, and AD wrote the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Ligularia and Cremanthodium was previously confirmed using a couple of DNA markers. However, the mechanism of this intergeneric hybridization and the role of reproductive isolation in the process of hybridization remain unclear. Here we used double-digest restriction site-associated DNA sequencing (ddRAD-seq) to further quantify the occurrence of hybridization, the genetic structure of the hybrid population and the role of reproductive isolation between Ligularia nelumbifolia and Cremanthodium stenoglossum. The results based on the ddRAD-seq SNP data sets indicated that hybridization between L. nelumbifolia and C. stenoglossum was restricted to F1s, and no gene introgression was identified between these two species. STRUCTURE analysis and maximum likelihood (ML) tree results showed a slightly larger genetic contribution of L. nelumbifolia to putative hybrid F1s. We deduced that the reproductive isolation between these two parent species is not well-developed but still strong enough to maintain the genetic integrity of the species, and that their F1s are sterile or with low fertility. Given the poorly resolved phylogenetic relationship between Ligularia and Cremanthodium, the occurrence of natural hybridization between L. nelumbifolia and C. stenoglossum may provide new insights into the re-circumscription and re-delimitation of these two genera.Natural hybridization is frequent in plants and is considered an important factor facilitating speciation. The natural intergeneric hybridization between  Ligularia nelumbifolia and Cremanthodium stenoglossum. The hybridization between these two species is an early hybridization event, and their hybrids were limited to the F1 generation and therefore species genetic integrity might be maintained. Compared to the parent species C. stenoglossum, L. nelumbifolia made a slightly larger genetic contribution to their putative hybrid F1 generation. The hybridization between these two species provides a new insight into the re-circumscription and re-delimitation of these two genera.Natural hybridization is common in plants and results in different evolutionary consequences for hybridizing species. Here, we used ddRAD-seq to explore the natural hybridization between  Natural hybridization occurs in ~25 % of plant species . HomoploThe Qinghai–Tibetan Plateau (QTP) is the highest and one of the most extensive plateaus in the world, and has been considered as one of the most important biodiversity hotspots in the world , are both perennial alpine plants and share several morphological traits  complex, a fairly diversified clade that contains more than 200 species that are endemic to the QTP in eastern Asia  sequencing to quantify the extent of hybridization in this hybrid zone. Double-digest restriction site-associated DNA can generate massive genome-wide single-nucleotide polymorphism (SNP) data sets, without any prior genomic information, thus making it widely applied to evolutionary studies involving resolving long-standing taxonomic problems, species boundaries in taxonomically complex groups, population genetics and phylogenetic research  how and to what extent does intergeneric hybridization occur; and (ii) can the genetic data offer information to help understand the genetic structure of the hybrid populations and the mechanism of reproductive isolation.L. nelumbifolia and C. stenoglossum were selected as the study taxa from Ganzi County, Sichuan province of China, where the average altitude is about 4600 m [see  L. nelumbifolia, C. stenoglossum and their hybrid populations were randomly collected, with 20 individuals for each taxon. The materials were dried immediately in silica gel and genomic DNA was extracted using the modified CTAB protocol  were discarded. Read quality and Guanine cytosine (GC) content were assessed by FastQC v.0.11.8  and removal algorithm (r) were implemented to remove highly repetitive stacks and over-merged tags. The minimum depth of coverage required to create a stack (m) was set to five, and the maximum nucleotide mismatch allowed between stacks (M) was two. In cstacks, which creates a catalogue of all loci across the population (or from just the parents if processing a genetic map), we set the catalogue of loci built with the mismatch number allowed between sample tags (n) as four. Finally, the SNP data set was generated in the populations pipeline with the genotype of each individual for every polymorphic site. A locus had to be present in at least 75 % of the individuals (r = 0.75) and in each of the four populations (p = 4) as the optimal parameters.For Stacks analysis, we implemented K was set to range from 1 to 10 with 10 replicates per K. The run was set for 25 000 steps of burn-in followed by 100 000 Markov chain Monte Carlo algorithms (MCMC) iterations. No population priors were applied in the analyses. The optimal K value was identified using STRUCTURE HARVESTER , F2 class (F2), backcross to P1 (BCP1) or backcross to P2 (BCP2). Given the limitation of the NEWHYBRIDS software, which can only analyse about 400 SNPs, the SNPs were randomly selected using a python script. The program ran for 100 000 MCMC iterations with 25 000 iterations as burn-in.A Bayesian clustering method was applied in NEWHYBRIDS v.1.1  to calcuL. subspicata were employed as the outgroup, and the GTR + G nucleotide substitution model was applied in the ML tree inference with 1000 bootstrap replicates . A principal coordinate analysis (PCoA) was conducted for all individuals using GenAlex v.6.5  paired-end reads in total  of 80 individuals. On average, 15.3 million reads were processed per individual for these 80 individuals, ranging from 0.17 million (G19) to 55.5 million (Cs20) K = 2, the posterior log probability of the data, L(K), achieved the largest increase and the delta K value was the maximum . The distribution of several individuals from L. nelumbifolia and C. stenoglossum was scattered, which might be due to high genetic differences among individuals.Principal coordinate analysis identified three well-differentiated clusters , correspL. nelumbifolia, C. stenoglossum) as well as the outgroup L. subspicata were separately recovered as clades. Furthermore, the morphotypes G and P were closer to L. nelumbifolia, which was consistent with the results of STRUCTURE.The best tree from a full ML search showed that the 78 investigated individuals and three outgroup individuals formed four clades with high bootstrap values . IndividL. nelumbifolia and C. stenoglossum were assigned to one parent, respectively (1 class (P = 1.000).NEWHYBRIDS analysis indicated that individuals of ectively , consistLigularia species have been reported  markers indicated that all observed hybrids were the F1 generation, implying the sterility of F1s . It is possible that factors related to climate change, human interference or something else have promoted the migration of L. nelumbifolia, which has shifted its distribution to a higher altitude. In this situation it may have accidentally interbred with the alpine C. stenoglossum and the hybrids have remained at the early phase. Infrageneric hybridization between taxa from different altitudes has been reported, such as the hybridization in an altitudinal hybrid zone on Mount Etna between two ragwort species (the low elevation Senecio chrysanthemifolius and high elevation S. aethnensis) , putative hybrids morphotype P (d–f), morphotype G (g–i) and C. stenoglossum (j–l) investigated in this study.process_radtags.ustacks and number of matched loci in sstacks.FST values for L. nelumbifolia, C. stenoglossum and hybrid population (combines morphotypes G & P) based on 2540 SNPs.plab012_suppl_Supplementary_MaterialsClick here for additional data file.


C9orf72 expansions in relation to genetic ancestry and age at onset (AAO) and to use these measures to discriminate the behavioral from the language variant syndrome in a large pan-European cohort of frontotemporal lobar degeneration (FTLD) cases.We sought to characterize We evaluated expansions frequency in the entire cohort . We then focused on the bvFTD and PPA cases and tested for association between expansion status, syndromes, genetic ancestry, and AAO applying statistical tests comprising Fisher exact tests, analysis of variance with Tukey post hoc tests, and logistic and nonlinear mixed-effects model regressions.C9orf72 pathogenic expansions in 4% of all cases . Expansion carriers differently distributed across syndromes: 12/101 FTLD-MND (11.9%), 40/800 bvFTD (5%), and 4/495 PPA (0.8%). While addressing population substructure through principal components analysis (PCA), we defined 2 patients groups with Central/Northern (n = 873) and Southern European (n = 523) ancestry. The proportion of expansion carriers was significantly higher in bvFTD compared to PPA  6.4; confidence interval (CI) 2.31–24.99]), as well as in individuals with Central/Northern European compared to Southern European ancestry . Pathogenic expansions and Central/Northern European ancestry independently and inversely correlated with AAO. Our prediction model  predicted a diagnosis of bvFTD with 64% accuracy.We found C9orf72 expansions, AAO, PCA-based Central/Northern European ancestry, and a diagnosis of bvFTD, implying complex genetic risk architectures differently underpinning the behavioral and language variant syndromes.Our results indicate correlation between pathogenic  Several studies had shown high frequencies of pathogenic C9orf72 expansions in Northern vs Southern European patients (North–South axis), especially in historically isolated populations (such as the Finnish14), leading to the hypothesis that a Scandinavian founder might be at the basis of the spread of the C9orf72 expansion.15 Other studies (based on the geographic location of the recruiting sites) challenged the North–South axis concept, reporting a high frequency (∼25%) of pathogenic expansions in the Spanish population10 or implying to the existence of more than 1 risk haplotype.16–19In FTLD, repeat expansions in C9orf72 repeat expansions exhibit marked phenotypic and pathologic heterogeneity, suggesting presence of additional  modifiers.20 Despite conflicting studies reporting either direct or inverse correlation between repeat length and age at onset (AAO), C9orf72 expansions have been suggested to act as a genetic modifier of AAO.21–24Patients with FTLD with abnormal ifgcsite.wordpress.com/) phase III initiative, aiming at (1) characterizing C9orf72 expansions in relation to genetic ancestry and AAO and (2) assessing the usefulness of these measures in discriminating the behavioral from the language variant syndrome.We analyzed 1,396 FTLD cases gathered through the International FTD Genetics Consortium (IFGC) . The samples were recruited by clinicians and research groups who are part of the IFGC network and based in Italy, Spain, Germany, the Netherlands, Belgium, the United Kingdom, Sweden, Norway, Slovenia, or the United States . Patients were diagnosed at each contributing site  in a harmonized fashion according to international consensus criteria such as those of Neary et al.2 (for FTLD), Rascovsky et al.25 (for bvFTD), Gorno-Tempini et al.3 (for PPA [semantic dementia or PNFA]), and Strong et al.4 (for FTLD-MND).FTLD cases were collected between 2016 and 2018  , which led to the exclusion of 44 population outliers, and allowed us to address population substructure within the cohort . We also assessed cryptic relatedness and excluded 14 first- or second-degree related individuals, leaving a cohort of 1,396 cases (group 0)—for which C9orf72 expansion status  was known—for analyses. Frequencies of pathogenic expansions were assessed in group 0 and further analyses were performed in (1) 1,295 cases (group 1: n = 800 bvFTD and n = 495 PPA) with known C9orf72 expansion status; (2) 1,179 cases  with known C9orf72 expansion status and AAO data available; and (3) 734 cases  with AAO and repeat counts  .We first assessed the frequency of pathogenic expansions in the entire cohort (group 0). The information on presence/absence of expansions was used as a binary variable . We then investigated differences in the frequencies of pathogenic expansions across bvFTD and PPA and the Nordic and Mediterranean clusters in group 1 (Fisher exact test) and in group 3 (logistic regression); in the latter, we used rc as a categorical variable  considering the following 4 categories: no expansions (rc = 2/3), short expansions (4 ≤ rc ≤ 8), intermediate expansions (9 ≤ rc ≤ 24), and long expansions (rc ≥ 25), the latter representing expansions in the pathogenic range (see references t test and logistic regression) and in group 3 . In the latter case, we used rc as a categorical variable (see above).We then evaluated association between AAO and syndrome, genetic ancestry, and expansions  alone and with genetic ancestry as a covariate in group 2  using (1) presence/absence of pathogenic expansions (as binary variable [see above] for group 2) or (2) rc , ancestry as binary variable, and AAO as continuous variable using logistic regression models . A summary of the analyses workflow can be found in All analyses were performed using R studio .29 were available on the NeuroArray.26 We filtered out 7 markers in order to keep 13 informative SNPs  matching 13 of the 20 used in Mok et al.15 We evaluated the proportion of cases carrying at least 1 risk allele  for each marker assessing expansion vs nonexpansion carriers (with/without ancestry stratification).Twenty  of the original 42 single nucleotide polymorphisms (SNPs) constituting the (Finnish) risk haplotypedoi.org/10.5522/04/12418157.All data generated or analyzed during this study are included in this published article and supplementary files 1 and 2 at p = 2.17 × 10−5; OR 6.4; 95% CI 2.31–24.99, p = 4.7 × 10−2; OR 1.6; CI 0.0061 [2.5%]–0.94 [97.5%]) and long  rc ranges .We assessed the frequency of pathogenic expansions in the entire cohort and across the different syndromes in the group 0 cases . Four pedoi.org/10.5522/04/12418157) to cluster the group 1 cases based on their genetic makeup. There were 2 major clusters: cluster 1 (Mediterranean) included most of the cases (439/500 [87.8%]) recruited from Southern European sites ; cluster 2 (Nordic) included most of the cases (627/795 [78.8%]) recruited from Central and Northern European sites . Samples recruited from Eastern European (Slovenia) and North American sites distributed across both clusters, although with a higher prevalence within cluster 2 (167/795 [21%]) vs cluster 1 (42/500 [8.4%]).We performed PCA  and long  rc ranges .We observed a significantly higher prevalence of pathogenic expansions in the Nordic (35/795 [4.4%]) vs the Mediterranean (9/500 [1.8%]) cluster (Fisher exact test: doi.org/10.5522/04/12418157)—we analyzed the distribution of pathogenic expansions across syndromes and clusters. Stratified Fisher exact test showed significant differences in the distribution of the pathogenic expansions between bvFTD and PPA in the Nordic (but not the Mediterranean) cluster , and between the Nordic and the Mediterranean clusters for the bvFTD (but not PPA) syndrome , suggesting that ancestry (Nordic) and syndrome (bvFTD) are independently associated with pathogenic expansions  and PPA (326/795 [41%] vs 169/500 [33.8%]), respectively  and the Nordic (61.3) and Mediterranean (64.3) clusters  (doi.org/10.5522/04/12418157). We then assessed the relationship between pathogenic expansions and AAO via logistic regression. First, we identified a significant correlation between a decrease in AAO and presence of pathogenic expansions . When we included genetic ancestry in the model, we observed a significant correlation with a decrease in AAO, with no difference in using either cluster  or PC1  as covariate and an almost 4-fold goodness of fit increase . Of note, when comparing the 2 regression models (with/without genetic ancestry as covariate) through the log-likelihood R2 ratio test, the difference (between the 2 models) appeared not to be due to chance (p < 10−12) .We assessed AAO in the group 2 cases . Mean AAt test: p = 2.1 × 10−7; CI 2.32–5.09; supplementary table 8A, doi.org/10.5522/04/12418157); (2) syndrome—mean AAO 61.7 and 63.5 in the bvFTD and PPA syndromes, respectively , and (3) expansion length—mean AAO 63.2 for both no and short expansions, 61 for intermediate expansions, and 58 for long expansions  . We then assessed the relationship between expansion length (see above) and AAO via logistic regression. First, we identified a significant correlation between a decrease in AAO and both intermediate and long expansions  . When we included genetic ancestry in the model, we observed a significant correlation with a decrease in AAO, no difference in using either cluster  or PC1  as covariate and an almost 3-fold goodness of fit increase . Of note, when comparing the 2 regression models (with/without genetic ancestry as covariate) through the log-likelihood R2 ratio test, the difference (between the 2 models) appeared not to be due to chance (p < 10−12) . These findings were further supported by nonlinear mixed-effects model regression using genetic ancestry as random effect covariate .We further evaluated the relationship between expansion length  and AAO in the group 3 cases . First, 29 available to us—were seen in (1) 40/56 (71.4%) expansion carriers vs 380/1,340 (28.4%) nonexpansion carriers in the entire cohort; (2) 33/47 (70.2%) expansion carriers vs 228/826 (27.6%) nonexpansion carriers in the Nordic cluster; and (3) 7/9 (77.8%) expansion carriers vs 152/514 (29.6%) nonexpansion carriers in the Mediterranean cluster. Comparing the proportion of risk allele carriers (expansion vs nonexpansion carriers) for each single marker, 5/13 markers  were significant in the Nordic cluster, and none in the Mediterranean cluster . Rs2477518 showed variable frequencies for the risk allele (T) across expansion vs nonexpansion carriers (and the 2 clusters), thus making this most probably a negligible marker within this stretch, as hinted previously.17 Rs3849942, previously suggested as a surrogate marker for the risk haplotype,15 was not among the SNPs available to us. We used rs868856, displaying strongest linkage disequilibrium with rs3849942 , as informative proxy: the risk allele segregated differently across expansion vs nonexpansion carriers in the Nordic and Mediterranean cluster (as for rs2453556), possibly suggesting these 2 as the most conserved markers of the original risk haplotype across populations in expansion carriers .All of the risk alleles for the 13 markers—shortest informative stretch of the original risk haplotypedoi.org/10.5522/04/12418157) and ∼0.62  in predicting bvFTD; there were no differences in the outcome when using either cluster or PC1 as covariates in both (LOOCV and K-fold) models.We then sought to build a model to predict syndrome (bvFTD vs PPA) and assess its accuracy. We analyzed both groups 2 and 3 cases using expansion status (presence/absence of expansion for group 2 and the 4 rc factor levels for group 3 [see Methods]), genetic ancestry (using either cluster or PC1) as binary variables, and AAO as a continuous variable in logistic regression models. We observed an accuracy of ∼0.64  of the Finnish risk haplotype29 appeared to be conserved across the Nordic expansion carriers, whereas there was a similar tendency for (just) 2 of such markers in the Mediterranean expansion carriers. Several studies had shown high frequencies of long C9orf72 expansions in Northern vs Southern European patients (North–South axis).13–15 Other studies (based on the geographic location of the recruiting sites) challenged the North–South axis concept,10 or the founder effect implying the existence of more than 1 risk haplotype.16–19 All this taken together, our current data appear to support the North–South axis hypothesis and suggest that rearrangements (and instability)19 at the C9orf72 locus might have occurred, reducing the level of conservation of the original risk haplotype across the European population.To our knowledge, the current work is unique in that, prior to characterizing the expansions, we excluded population-substructure bias using genome-wide genotyping data to cluster the cases on the basis of their genetic makeup. After PCA, we identified 2 distinct clusters including samples with geographic ancestry corresponding to Southern Europe (Mediterranean cluster) and Central/Northern Europe (Nordic cluster). Our analyses not only showed that patients from the Nordic cluster presented significantly higher frequency of pathogenic 30–34—suggests that C9orf72 expansions might serve as useful genetic fingerprint to define subpopulations of FTLD  found a significant inverse correlation between C9orf72 expansion length and AAO. In addition, and interestingly, our data also indicate that Central/Northern European genetic ancestry contributes to a decreased AAO (independently from the expansions), possibly implying a more complex genetic signature (or architecture), and subsequently molecular mechanisms, underpinning this feature. Clearly, disease mechanisms that involve C9orf72 expansion length and AAO are complex, thus it is likely that additional factors might further modulate their relationship and effect on the phenotype .Despite some previous conflicting reports of direct (or inverse) correlation between While using expansion length, genetic ancestry, and AAO in a regression model to discriminate behavioral from language variant subtypes, we found that such measures supported a prediction of bvFTD with 64% accuracy.35 genetic variability characterizing and differentiating Nordic vs Mediterranean subjects (such as in the case of our cohort) might influence predisposition to harboring longer repeat expansions. In other repeat expansion diseases—e.g., Huntington disease or other microsatellite diseases, including myotonic dystrophy and spinocerebellar ataxias35—the presence of specific haplogroups in Western European populations occurs with a manifold increase in prevalence of repeats compared to other ethnic groups and populations.36 Second, different genetic risk architectures underpinning different  subpopulations of patients may exist within the FTLD population.Our results have a number of implications. First, provided that significant variation exists in the genetic architecture of the Caucasian population,38 These concepts, reinforced by our study, warrant further characterization of genetic, environmental, and additional clinical measures to fine-tune models able to predict disease outcome to complement diagnostic criteria, and possibly assist in the identification of informative cohorts for tailored clinical trials and the development of effective personalized therapies.In a nutshell, our results imply that a significantly higher proportion of FTLD cases, with Nordic rather than Mediterranean genetic ancestry, is likely to develop bvFTD in presence of intermediate and long (pathogenic) expansions, whereas long (pathogenic) expansions are  negligible in PPA, regardless of ancestry. Clearly, multiple factors including genetic heterogeneity, epigenetic changes, ethnicity, as well as environmental factors and habits that may subsist within and across multicultural cohorts, all together, contribute to disease predisposition, onset, and progression.


Small ruminant lentiviruses (SRLV) cause an incurable multiorganic disease widely spread in sheep and goats that disturbs animal welfare and production. In the absence of a vaccine, control measures have been traditionally based on early diagnosis and breeding with virus-inactivated colostrum with segregation of seropositive animals. However, antigenic heterogeneity, poor antibody production due to low viral load, and single strain design of most available ELISA, pose a threat to SRLV diagnosis. Genome-wide association studies have described TMEM154 E35K polymorphism as a good genetic marker for selection of resistant animals in some American and European breeds. In this study, a multitargeted serological and virological screening of more than 500 animals from four different breeds  attending to SRLV infection status was performed. Then, animals were genotyped to characterize TMEM154 E35K polymorphism. ELISA procedures, individually considered, only identified a proportion of the seropositive animals, and PCR detected a fraction of seronegative animals, globally offering different animal classifications according to SRLV infection status. TMEM154 allele frequency differed substantially among breeds and a positive association between seroprevalence and TMEM154 genotype was found only in one breed. Selection based on TMEM154 may be suitable for specific ovine breeds or SRLV strains, however generalization to the whole SRLV genetic spectrum, ovine breeds, or epidemiological situation may need further validation. Small ruminant lentivirus (SRLV) infection widely affects animal health and production by causing a wasting disease characterized by chronic inflammation of carpal joints, udder, central nervous system, and/or lungs . InfectiIn addition to their use in control programs, the detection of antibodies through ELISA tests along with molecular tools has been used to identify association between breeds and susceptibility patterns to SRLV infection. Genome wide association studies (GWAS) have opened the possibility to apply genetic selection programs by describing a number of candidate genes associated to SRLV seroreaction ,19,20,21In this study, we analyzed TMEM154 E/K genotype association with SRLV infectious status in approximately 500 sheep belonging to different flocks, production systems, and breeds according to three different ELISAs and a PCR-based molecular test.SRLV diagnosis through ELISA was carried out using three different commercial tests based on different strains and antigens. An animal was considered infected in the Total ELISA classification when tested positive to at least one of the ELISAs.At the population level, ELISA testing indicated that all the flocks were infected with a seroprevalence ranging from 3.5% to 100%. Individually considered, the different ELISAs showed important differences when examining intraflock seroprevalence. Interestingly, two flocks of the churra breed were classified as uninfected taking into account results from ELISA#1. However, Total ELISA analysis indicated a seroprevalence of 60% .Considering animals by breed, assaf flocks were the most infected showing a seroprevalence up to 89%, depending on the ELISA tested. When considering the results from the three ELISA tests, seropositive animals reached 97.3% , being aInterestingly, the combination of all ELISAs revealed a global seroprevalence higher than 65%, practically doubling the performance offered by kits individually considered. Indeed, efficiency of individual ELISAs varied from 0% to 100% according to flocks  and fromDiagnosis through commercial PCR resulted as sensitive as ELISA, since the overall PCR reactivity was around 44% compared to 46.4%, 44.9%, and 42.7% for ELISAs #1, #2, and #3, respectively . As showAmong seronegative samples, 54 out of 179 (30%) were identified as qPCR positive, whereas 135 seropositive samples resulted negative in qPCR. When considering each ELISA individually, PCR detected a 22.37%, 34.53%, and 37.94% of seronegative animals to ELISAs #1, #2, and #3, respectively .Total infected animal classification, revealed by ELISA or PCR, allowed the evaluation of PCR efficiency compared to ELISA. qPCR efficiency reached 79% in assaf animals and decreased to 32% in churra flocks. Intraflock efficiency in assaf flocks peaked at 95.8%, whereas highly seropositive churra flocks were not detected by qPCR .Animal classification into infected and uninfected after ELISA  and qPCRn = 10) from the studied population were employed to amplify a 335bp region of the TMEM154 gene . Exceptions to this general picture were evident when analyzing data obtained after ELISA#2 testing of latxa and raza Navarra breeds, since differences were found in ELISA absorbance according to TMEM154 genotype  and susceptible (E/K and E/E) samples, suggesting poor association between TMEM154 genotype and SRLV infection D.Relationship between SRLV infection status and TMEM154 genotyping was evaluated using association and relative risk, and regression statistical analyses. Animals from the assaf and churra breeds did not show significant association between TMEM154 genotype and SRLV antibody occurrence, except for ELISA#2 in churra animals . SimilarMolecular diagnosis led to a classification of animals into infected or uninfected that was not associated with TMEM154 genotype in the sheep analyzed. However, when combining PCR and ELISA results , association was found in the case of the latxa Navarra breed. The relative risk of being seropositive when encoding a susceptible genotype, homozygous or heterozygotes, was moderate within quoted significant associations, and varied from 1.54 to 3.59 . IdenticLentivirus infection remains one of the major threats in ovine and caprine species in spite of the surveillance and control programs driven from the 1990s in different countries by serological screening with available tools. However, ELISA testing has some inherent disadvantages that jeopardize SRLV diagnosis. On one hand, selection of diagnosis escape mutants could explain previously described diagnostic concerns ,27. On tSerological screening revealed that antibody detection using more than one ELISA test significantly improved diagnosis, since the proportion of positive animals considerably increased when the three tests were included. Individual ELISA efficiency in seropositive samples varied among flocks being higher in heavily infected flocks, whereas in those showing moderate seroprevalence, efficiency decreased to 0%. Increased seroprevalence recorded in assaf flocks may be due to the intensive dairy production system that implies close contact between animals and long-term indoor housing, contributing to increased virus transmission . InteresOne possible explanation may rely on the unmatched antigenic ELISA design with the circulating strains. Sheep are likely infected by a mix of lentiviruses including strains of different genotypes, even within the same flock or individual ,34,35, tAlternative control strategies explored so far include genetic selection of resistant variants. Based on genome-wide association studies (GWAS), TMEM154 specific alleles at position 35 (E/K) have been associated to SRLV infection susceptibility, in terms of serological reaction ,24,26, bFluorogenic probes were efficient and easy-to-design tools to genotype ovine DNA for E35K SNP. Allele frequency reflected previous observations and did significantly differ among breeds. Raza Navarra, a meat-oriented breed, showed a KK-resistant genotype frequency higher than 80%, very similar to previous results obtained in rasa Aragonesa, a closely related breed . DespiteAmong breeds studied, only latxa breed showed a constant association between TMEM154 genotyping and SRLV infection status regardless of the test used for animal classification. Similarly, raza Navarra animals classified by ELISA#2 as uninfected more likely encoded a K/K resistant genotype. Regarding proviral load, no association was found with TMEM154 genotype as shown in The lack of association described in this study may be due to the existence of other missense mutations within TMEM154 gene different from E35K such as D33N, T44M, I70N, or G38R  that mayAnother explanation may rely on the SRLV circulating strains and not related to the host. This association was firstly described in animals from the United States and infected with a genotype A2 strain, that may not require a functional TMEM154 to infect sheep ; TurkishLittle is known about TMEM154 function; apart from the transmembrane location, GWAS studies have identified TMEM154 as a candidate for asthma severity  and for Our results suggest that the relationship between TMEM154 E/K genotyping and susceptibility patterns when facing SRLV infection is not clear for all breeds and SRLV genotypes, and should be tested in a case-by-case manner in order to avoid selection of infected animals as resistant. Combined serological and molecular diagnosis are highly recommended to accurately classify infected animals in order to provide robust studies.n = 194), raza Navarra , assaf , and churra  ovine breeds from northern Spanish flocks were obtained. All sheep belonged to 18 different flocks dedicated to dairy or meat production. Flocks 1 and 2 from the raza Navarra breed (meat flocks focused on semi-intensive lamb production), and flocks 4 and 5 from the Latxa Navarra breed  were likely infected by different genotypes of SRLV [Blood samples of the latxa Navarra  ; ELITESTGenomic DNA was extracted from buffy coat samples with E.Z.N.A. tissue/blood kit  following the manufacturer’s instructions. DNA was quantified at 260–280nm  and stored at −20 °C until use.5 to 5. Results were expressed as provirus copy number/250 ng of DNA.Real time PCR was performed with 250 ng of DNA in an Agilent sequence detector system using the commercial kit EXOone Maedi Visna-CAEV oneMix kit, following manufacturer’s instructions . Six-fold serial dilutions of the positive control were prepared to generate a standard curve (cycle threshold vs. copy number) from which copy number values were extrapolated. Positive control copy number ranged from 5 × 10An animal was considered as infected when at least one ELISA test or one PCR method revealed a positive result .2 , 230 μM dNTPs , 400 nM of forward and reverse primer, 200 nM of each probe , 0.04 U/uL of Taq DNA polymerase  in a final volume of 25 μL. Samples were submitted to an initial denaturation at 95 °C/5 min, followed by 45 cycles of 55 °C 30 s. Allelic discrimination was analyzed using BIO-RAD CFX96 software. This new method for ovine TMEM154 genotyping was evaluated with plasmids encoding each of the versions (E or K) obtained from the sequencing. Equimolar mixes of these plasmids were mixed to mimic heterozygote samples. Plasmid controls encoding E, K alleles or the equimolar mix were included in each plate when analyzing biological samples.Setting-up TMEM154 E/K genotyping involved a first step, in which 10 DNA samples from SRLV seronegative (5) and seropositive (5) latxa Navarra animals were used. Amplification of the corresponding TMEM154 region  followinDiagnostic efficiency was determined for each of the ELISAs in comparison with the total seropositive  and infected  population. Efficiency of diagnostic PCR was calculated as regarding to the Total infected.Differences in the distribution of allele frequencies between groups of SRLV infected and uninfected samples were tested by Fisher´s exact test. The relative risk (RR) to be detected by ELISA or PCR was estimated for animals carrying one and/or two copies of the putative susceptible allele (risk factor) with the method of Altman . NonparaThe SPSS program (v. 25.0) for Windows was used for statistical analyses and alpha error was set at 0.05.The combination of different serological and molecular methods was useful and needed to accurately classify animals into SRLV infected or uninfected. Combined diagnosis significantly improved performance of tests individually considered. TMEM154 frequencies of raza Navarra, latxa Navarra, and churra breeds resembled those of resistant sheep, however, infection rate was high as determined by the combined strategy used. SRLV infection status was associated with TMEM154 genotyping only in latxa navarra animals.Antigenic heterogeneity of SRLV greatly challenges accurate serological diagnosis with available methods, and commercial molecular tests are currently passing from the bench to the market demonstrating a convincing benefit. It is not only SRLV control or surveillance programs that are profoundly affected by this diagnostic drawback, but also scientific studies requiring strict animal classification into infected and uninfected animals. Controversy in studies evaluating production losses derived from SRLV infection, or linking host genetic features with specific traits, may have suffered from this inaccuracy when identifying infected animals.TMEM154 involvement on SRLV patterns of susceptibility may require a further evaluation in specific breeds and genotypes of SRLV.


Spatially explicit simulations of gene flow within complex landscapes could help forecast the responses of populations to global and anthropological changes. Simulating how past climate change shaped intraspecific genetic variation can provide a validation of models in anticipation of their use to predict future changes. We review simulation models that provide inferences on population genetic structure. Existing simulation models generally integrate complex demographic and genetic processes but are less focused on the landscape dynamics. In contrast to previous approaches integrating detailed demographic and genetic processes and only secondarily landscape dynamics, we present a model based on parsimonious biological mechanisms combining habitat suitability and cellular processes, applicable to complex landscapes. The simulation model takes as input (a) the species dispersal capacities as the main biological parameter, (b) the species habitat suitability, and (c) the landscape structure, modulating dispersal. Our model emphasizes the role of landscape features and their temporal dynamics in generating genetic differentiation among populations within species. We illustrate our model on caribou/reindeer populations sampled across the entire species distribution range in the Northern Hemisphere. We show that simulations over the past 21 kyr predict a population genetic structure that matches empirical data. This approach looking at the impact of historical landscape dynamics on intraspecific structure can be used to forecast population structure under climate change scenarios and evaluate how species range shifts might induce erosion of genetic variation within species. The definition of the agent, over which mechanisms are acting and whose interactions with the landscape generate emergent genetic patterns is crucial. Depending on the research questions, the agent can be (a) genes , mutation , recombination , or hybridization  influence the permeability to the dispersal of a species or using the outputs of SDMs.Process‐based models of intraspecific genetic diversity and structure represent a simplification of the reality, and their development is generally done along three main lines of abstraction: (a) the nature of the modeled agent , (b) the detail of the mechanisms , and (c) the characterization of the landscape dynamic. A first line of abstraction is the characterization of the agent, which might depend on the mechanisms and the type of emergent pattern , generalized additive models (GAM) with the  Hastie, , gradien3.4FST, chord distance, or distance‐based principal components analysis  and thus decreases the possible geographic distance over which a population can disperse. A population can disperse to another cell as long as the least cost path between them is cheaper than the dispersal distance of that population. We prepared matrices with different costs: Crossing unsuitable habitat and glaciers had a cost factor of 1.1 to 1.25, and crossing the (frozen) sea had a cost factor of 1.1 to 3.We precomputed matrices of connectivity between all the cells that are suitable for the species for all 100‐year time steps from the LGM to the present. Cost distance and electric circuit are common tool in landscape genetics to investigate the connectivity among populations  among occupied cells over time. Two populations are connected if the species dispersal capability (d) is higher than the least cost path between them. Disconnected populations accumulate differentiation by drift, while connected one loss genetic differentiation over time by gene flow. After preliminary analyses (data not shown), we found that during the colonization process, genetic differentiation by drift occurred faster than genetic homogenization by gene flow. Therefore, we set the accumulation of divergence to occur three times as fast as the reduction. Step 3: Dispersal allows gene flow among connected cells at a distance d as presented above, but further allows the colonization of uncolonized cells. Species can disperse to all connected cells, which have a least cost path less than the dispersal distance d. The cells occupied by the species will change over time together with the genetic distance matrix quantifying pairwise differentiation between all the occupied cells.The model components are defined as the following steps. As a burn‐in at the start of the simulation, we replicated the oldest time step  for 50 time steps to accumulate genetic differentiations between the isolated populations before the dynamic simulation starts. As parameters in the illustration simulations, we randomly draw dispersal distances for each cell from a Weibull distribution with shapes of 1 and 2.5 with median dispersal ranges from 2.1 km to 26 km per year (95% quantile ranging from 4.7 to 89 km/year). Values were selected according to the reported changes in calf ground location which reach a maximum speed of 15 km/year , we removed all populations which are not included in both the model and the genetic dataset for the comparison (see Results). We applied a buffer of 200 km around the genetic sampling location to assign the location to the simulation cluster.We applied a principal coordinate analysis (PCoA) on the pairwise distance matrices obtained from our model as well as the Cavalli‐Sforza chord distance 44.1The AUC value for the averaged model ensemble was 0.81 , the Kappa value 0.49 , and the TSS 0.58 . We observed a large congruence between the projections of the four different SDMs. On average, 71% of cells, which were classified as suitable habitat, were predicted by all models, 87% by at least three and 95% by at least two models. The congruence between the models generally decreased over time. The average congruence between all four models between the present and 5’000 years BP was 76%, while it decreased to 64% between 15,000 years BP to 20,000 years BP. All SDMs showed two distinct refugia in northern America during the LGM. The northeastern refugia located in Alaska close to the Bering Strait and the southern one from the plains in the Midwest toward the Atlantic  as well as with FST  dispersal ability, (b) habitat suitability from SDMs, and (c) landscape connectivity shape the gene flow between populations and the generation of intraspecific structure over time. Our approach remains simple in nature and further properties can be considered. In particular, our approach simulates beta diversity, but not alpha diversity: considering continuous suitability as a proxy of carrying capacity within cells can provide the means to integrate all diversity facets within the same framework. In a future development, the strength of our framework could be reinforced by the use of ancient DNA that could, when available, simultaneously validate past distribution modeling as well as genetic lineage occurrences. Furthermore, the simulation model provides expectation for neutral genetic markers and it remains to be seen how processes can be integrated in a simplified form to study adaptive loci (e.g., Rebaudo, et al., None declared.Supplementary MaterialClick here for additional data file.


The demographic and genetic diversity structure and the contributions of Spanish (PRE) and Arabian Purebred (PRá) horses to the process of conformation of the Hispano-Arabian (Há) horse breed were evaluated. Genetic diversity parameters  were evaluated using a discriminant canonical analysis to determine the partial contributions of each founder breed to the development of Há horse breed. The calculation of Nei genetic distances suggests the overlapping could be estimated in 29.55% of the gene pool of the Há having a PRE origin while 70.45% of the gene pool of the breed may derive from a PRá origin. Although a progressive loss of founder representation may have occurred, breeding strategies implemented considering mating between animals with the highest genetic conservation indices (GCI) may compensate for its effects.Genetic diversity and population structure were analyzed using the historical and current pedigree information of the Arabian (PRá), Spanish Purebred (PRE), and Hispano-Arabian (Há) horse breeds. Genetic diversity parameters were computed and a canonical discriminant analysis was used to determine the contributions of ancestor breeds to the genetic diversity of the Há horse. Pedigree records were available for 207,100 animals born between 1884 and 2019. Nei’s distances and the equivalent subpopulations number indicated the existence of a highly structured, integrated population for the Há breed, which is more closely genetically related to PRá than PRE horses. An increase in the length of the generation interval might be an effective solution to reduce the increase in inbreeding found in the studied breeds . Wright’s fixation statistics indicated slight interherd inbreeding. Pedigree completeness suggested genetic parameters were highly reliable. High GCI levels found for number of founders and non-founders and their relationship to the evolution of inbreeding permit controlling potential deleterious negative effects from excessively frequent mating between interrelated individuals. For instance, the use of individuals presenting high GCI may balance founders’ gene contributions and consequently preserve genetic diversity levels . The prospects of complementing already established endangered breeds or populations into a multi-breed composite population was proposed by Shrestha . This auThe aforementioned concept lays the basis for breeding programs either it is conservation plans seeking the sustainable management of native breeds, or the commercial development and utilization of specific crosses for practical purposes. Particular features of each population contribute to the genetic variability of the species to which it belongs. However, these particular features could dilute due to sub structuring, intermixing and/or consequent genetic drift over time .The origins of the Há horse breed  date bacSince its origins, Há horse breeders have sought complementarity between PRE and PRá horses . As suggBoth ancestor breeds have been reported to be more closely related to each other than other affine breeds such as Anglo-Arabian or The English Trotting Horse, as suggested by the genic and genotypic frequencies for blood systems “A” and “O” ,8,9.The improved features derived from composite vigour (heterosis) prompted authors such as Ibn al-’Awwam, agriculturist of the later 12th century, to refer to the cross between PRE and PRá as “the best” par excellence in his Kitāb al-filāha . This maAt first sight, Há horses may have a smaller size, a remarkable trend to fit eumetric proportions and rather lively gaits than its ancestor breeds (PRE and PRá horses). There are some archive records reporting the use of earlier Há breeding studs, as far back as 1778. However, the formal creation of the breed dates to the 1883, when an official breeding program was implemented coinciding with the introduction of Arabian horses to upgrade and expand other horse breeding programs. Although the breed is linked to the Andalusian countryside, where it gained popularity as a working cattle horse, its expansion and consolidation as a breed has been slow . The lacThe Há breed was formerly very common in the south of Spain , area in which it was presumably created and from which the breed would spread even internationally. However, an increased national and international demand for the PRE horses led to the decrease in Há breed effective numbers, until it became a minority rare breed by the mid-1980s. This situation led to the constitution of the Há horse breed studbook in 1986 and its later official recognition within the category of special protection through the inclusion of the breed in the Official Catalogue of Spanish Cattle Breeds (Orden APA/2129/2008) . The effContextually, the physical endurance, athletic qualities, balance in character of the PRá horse were, have been and still are combined with the versatility, predisposition to work and movement precision of the PRE horse. The evolution of the breeding strategies sought the recovery of the numbers of Há horses and can be evaluated in five stages. The first stage ranged from 1992 to 1995 and was marked by the use of 16 foundation Há stallions bred with (F1) 50:50 mares, resulting from the crossing between PRE dams and PRá sires. Afterwards, during the second stage which ran from 1996 to 1999, five selected PRá stallions were used to cover Há mares and one PRE stallion was selected to cover PRá mares. The third stage (2000–2005) was characterized by the predominant use of PRE horses covering more than 80% of the Há mares. A parallel breeding program dedicated to producing F1 Há individuals from PRE mares covered by both PRá stallions and five Há stallions of 50% and 75% PRá blood ratios obtained at the aforementioned stages. Simultaneously, the military covered PRá mares with PRE stallions, which had not been a frequent practice at the previous stages. Additionally, alongside these controlled breeding strategies, some mares were freely covered by Há stallions to produce F2 and F3 individuals optimally fitting the breed standard with the aim to improve the breed.The objective of the fourth stage, which run from 2006 until our days, was to include the F2 individuals with PRá blood percentages ranging between 62.5% and 37.5%. Such individuals used to be difficult to find at previous stages, but are the natural progression of outbreeding 25% and 75% Há horses to PRE or PRá horses. Contextually, Há stallions and mares of 25% and 75% PRá blood bred to each other produce a 50:50 fixed Há genotype. This strategy sought to ensure that the products derived from the aforementioned breeding program effectively ascribed to the breed standard. At the age of 3, individuals start to be trained in the development of the skills comprised by the disciplines of Spanish cowboy/western dressage (Doma vaquera) and cattle driving, for which it stands out above other breeds  .Although the evaluation of genetic diversity and demographic parameters raised research interest in the past , previouTherefore, the aim of this study is the development of a model to perform the discriminant canonical analysis of the contributions of PRE and PRá horses to the historical and present genetic diversity and demographic structure of the Há horse breed. Pedigree completeness was evaluated downwards, checking the repercussions of ancestors and founders, evaluating the structure of the population, its genetic variability, and connections between its genetic and demographic parameters, measuring the existing gene flow, and quantifying the risk of genetic diversity loss. The endangerment risk that the Há horse breed faces was evaluated to suggest effective conservation strategies, which in the case of the Há composite breed may reinforce its entity within the horse breed international panorama.Since the Hispano-Arabian (Há) horse breed is the product that results from the cross between the Spanish (PRE) and Arabian (PRá) purebred horses, the historical pedigree files for the three breeds were considered to build the historical pedigree database used in this study. The historical dataset comprised a total of 207,100 horses. Há historical pedigree database file was supplied by the Spanish Union of Purebred Hispano-Arabian Horses Breeders (UEGHá) and comprised 11,010 individuals, 4268 males and 6742 females, born between January 1950 and April 2019. The PRE historical pedigree database was supplied by the National Association of Purebred Spanish Horse Breeders (ANCCE) and comprised 172,797 individuals—83,408 males and 89,389 females, born between January 1884 and July 2019. Spanish PRá historical pedigree record was provided by the Spanish Association of Arabian Horse Breeders (AECCA). PRá historical pedigree database comprised a total of 23,293 individuals—11,143 males and 12,150 females, born between January 1898 and June 2019.All the analyses were performed on a population set from which all death animals had been removed to evaluate the evolution and trends described by diversity and population structure parameters. This population set comprised the currently living populations of the three breeds . Há current pedigree database file comprised 9997 individuals—4031 males and 5966 females, born between December 1984 and April 2019. PRE current pedigree comprised 141,357 individuals—69,184 males and 72,163 females, born between April 1984 and July 2019. Spanish PRá current pedigree record comprised a total of 13,576 individuals—6632 males and 6944 females, born between June 1985 and June 2019. A full description of the composition of the historical and current datasets is presented in n) where n is the number of generations setting the individual apart from each known ancestor [bn is the total number of ancestors of the animal, b and abg is the number of generations between b and its ancestor a [We studied the number of births to compute the maximum and mean number of offspring per stallion or mare. The pedigree completeness index (PCI) was computed summarizing the proportion of each ascending generation’s known ancestors, through the maximum number of traced generations; the number of complete traced generations; the number of complete equivalent generations, calculated as , was computed following the methods of Caballero and Toro [Individual inbreeding (F) was computed using the methods in Meuwissen and Luo . Each inz et al.  through s et al.  through and Toro , through−C)(1−α) ,28.ef), was calculated using kq is the probability of gene origin of the kth founder and f is the real number of founders [af), was determined by kp is the marginal contribution of a kth ancestor [gf) was computed as the inverse of twice the average coancestry as reported in Caballero and Toro [j was computed as Boichard, et al. [GD and GD* indicates the GD loss owed to genetic drift accumulated since the foundation of the population [efN) was computed using The effective number of founders   was calc, et al.  using S=fficient  and NeFiand Toro  using 1−pulation , and theand Toro . CFC verand Toro .A canonical discriminant analysis (CDA) was performed on genetic diversity parameters derived from pedigree analyses of inbreeding , average relatedness , average coancestry , non-random mating rate (α), genetic conservation index (GCI), number of maximum, complete and equivalent generations and number of offspring per individual using the breed  to which each animal belonged as a labeling classification criteria, to measure the variation of the genetic diversity parameters estimated, and to establish, identify and outline within population clusters ,35,36,37The choice to perform a forward stepwise analysis was made considering the following alternatives. On the one hand, the first option considered was to perform a regularized canonical discriminant analysis. Regularization has been reported to improve the estimate of covariance matrices in situations where the number of predictors is larger than the number of data, as in such cases regularization may lead to an improvement of the efficiency of discriminant analysis. However, this was not our case as the nature of the variables considered may lead to the occurrence of considerable problems of multicollinearity. Such multicollinearity problems may derive from the fact that some of the variables initially considered, were computed including others (which were included too) among the terms in their formulas. As a result, even if models were simplified, removed variables may still be considered somehow.Additionally, the analysis used in the present study must be robust in cases of highly unequal sample sizes. To approach such compromising situation, we used the approximation proposed by Roemisch et al.  of a regFurthermore, even if unequal sample sizes are acceptable as reported by Poulsen and French , some reOn the other hand, after the stepwise canonical discriminant analysis approach was chosen, a decision had to be made on either to perform a backward or forward stepwise variable selection approach. As a drawback, stepwise residual sum of squares will typically be above that for best subset, if there is correlation between the predictors considered. For this reason, we performed a multicollinearity analysis and correlated variables exceeding minimally acceptable levels were discarded. Contextually, it must be considered that when regressors (variables) are independent, that is, they are not correlated, the variables chosen by either forwards or backwards stepwise selection methods will be exactly the same.Conclusively, forward stepwise selection method was chosen given it is rather effective (less time-consuming) than backward selection methods and provided observations do not need to be strictly greater than the number of variables, which may make this approach valid for future research facing the same sample contexts.(DA) routine of the Analysing Data package of XLSTAT Pearson Edition [Canonical Discriminant Analysis was performed using the Discriminant routine of the Classify package of the software SPSS version 25.0  and the  Edition . 2). A recommended maximum VIF value of 5 [Before running a discriminant canonical analysis (CDA), multicollinearity assumption should be tested for, to ensure redundancies in the variables considered do not affect the structure of the matrices or overinflate variance explanatory potential. The variance inflation factor (VIF) was computed and used as an indicator of multicollinearity. Computationally, it is defined as the reciprocal of tolerance: 1/, but which represent multiple variables (which can be directly observed). The maximum number of canonical correlations between two sets of variables is the number of variables in the smaller set. The first canonical correlation explains most of the relationship between sets . Canonic2. When significance is below 0.05, the corresponding function can be concluded to explain group adscription well [Wilks’ Lambda test assesses which variables significantly contribute to the discriminant function. As a rule of thumb, the closer Wilks’ lambda is to 0, the higher is the contribution of that variable to the discriminant function. Wilk’s Lambda significance can be tested using χion well .p < 0.001) are considered [Pillai’s trace criterion was used to test the assumption of equal covariance matrices in discriminant function analysis (DFA). As smaller significance levels  was performed to minimize overall variables into few meaningful variables that contributed most to variations in the breeds.Discriminant function analysis was used to determine the percentage assignment of individuals into their own breeds. The traditional approach to interpreting discriminant functions examines the sign and magnitude of the standardized discriminant weight  assigned to each variable in computing the discriminant functions. Small weights may indicate either that a certain variable is irrelevant in determining a relationship or that it has been discarded because of a high degree of multicollinearity with the rest of variables.Discriminant loadings represent the variance shared between independent variables and the discriminant function. Discriminant loadings can be interpreted as factor loadings to evaluate the relative contribution of each independent variable to the discriminant function. Variables exhibiting a discriminant loading of ≥|0.40| are considered substantially discriminating variables. Stepwise procedures may prevent non-significant variables from entering the function. Simultaneously, multicollinearity and other factors may preclude a variable from entering the equation, which does not necessarily exclude that it has a substantial effect. Loadings are relatively more valid than weights to interpret the discriminating power of independent variables due to their correlational nature.The comparison between variables measured on different scales can be performed considering standardized coefficients. Large absolute coefficients will denote a better discriminating ability. Discriminant scores can be computed by using the standardized discriminant function coefficients applied to data that have been centered and divided by the pooled within-cell standard deviations for the predictor variables, as discussed in IBM Corp. .−1 the inverse of the covariance matrix of measured variable x and The data were standardized following the standard procedures described by Manly  before se breeds . Additioe breeds  among thThe percentage of correctly classified cases is called the hit ratio . To estat-test for groups of equal size, in Press’ Q statistic, groups (breeds in our case) can be of unequal size [2 with one degree of freedom at a significance of 0.01. Under this assumption, when Press’ Q exceeds the critical value of χ2 = 6.63, cross-validated classification can be regarded as significantly better than chance.The validity of cross-validation can be supported by Press’s Q significance test of classification accuracy for original against predicted group memberships. In opposition to ual size . Press’ A progressively increasing trend was detected for birth number across PRá, PRE, and Há horses running from 1944 to 2006 when number of births in the three breeds dramatically decreased . The hisThe number of complete generations for each of the three breeds  in the historical population was 3.35 ± 1.43, 4.59 ± 1.43, and 2.96 ± 1.42, respectively. However, for the currently living population the numbers of complete generations were 4.03 ± 1.42, 4.86 ± 1.42, and 3.04 ± 1.42, respectively. The number of equivalent generations in the three horse breeds was 5.76 ± 2.09, 8.36 ± 2.09, and 6.15 ± 2.08, respectively. For the currently living population, the number of equivalent generations were 7.11 ± 2.09, 8.85 ± 2.08, and 6.34 ± 2.08, respectively. As can be observed, the average number of equivalent generations, that is the number of generations separating the individual apart from each known ancestor , tends tPedigree completeness index (PCI) for the first generation (know parents) experienced a slight increase between 6.81–0.06% when the historical and current populations were compared. Minimum PCI (58.01%) was reached at the fifth generation (great-great-grandfather acquaintances) in the historical population of the Há horse breed. By contrast, the maximum PCI was reached at the first generation (known grandparents) in the current population of the Spanish horse breed (99.99%). A summary of the analysis of the maximum number of traced generations, PCI , number of maximum generations, number of complete generations, and number of equivalent generations in the studied population sets is shown in Although Summary of the statistics derived from pedigree analysis including maximum progeny per stallion and mare, mean age of stallions and mares in reproduction and foals of stallions and mares selected for breeding is shown in The average progeny per mare in the historical population was 3.54 ± 3.10, 4.28 ± 3.40, and 2.73 ± 2.44 for PRá, PRE, and Há horse breed, respectively. Similarly, for the currently living population of the same breeds, average progeny per mare was 3.13 ± 2.55, 3.68 ± 2.73, and 2.45 ± 2.21, respectively. The minimum average progeny per mare was that of the Há currently living population 2.45 ± 2.21, whereas the maximum average progeny per mare was reported for the historical 4.28 ± 3.40 PRE breed population. Contrastingly, the minimum average progeny per stallion was found for the currently living PRá population 7.08 ± 11.04, while a maximum of 13.67 ± 26.52 was reported for the historical population of the PRE horse.Progeny of stallions selected for breeding in the current population for PRá, PRE, and Há horse breed were 97.92%, 99.93%, and 80.94%, respectively, while the same parameter referred to mares reported values of 98.85%, 49.74%, and 94.08%, respectively. The lowest percentage for this parameter was obtained for the current population of stallions of the Há horse breed (80.94%) and the historical population of Spanish mares (48.27%). The average age of the stallions in reproduction for the historical population of PRá, PRE, and Há horse breeds was 22.14 ± 4.99, 23.87 ± 4.99, and 18.21 ± 4.99, respectively, while for their currently living populations was 23.32 ± 5.81, 25.31 ± 5.82, and 17.66 ± 5.74, respectively.In the case of the historical population of PRá, PRE, and Há, average age of the mares in reproduction was 23.01 ± 4.84, 23.73 ± 4.97, and 21.65 ± 4.80, respectively, while average age of mares in reproduction in the currently living PRá, PRE, and Há populations was 24.55 ± 5.09, 24.17 ± 5.09, and 20.50 ± 4.03, respectively. The shortest age difference between males and females was reported for the PRE horse population . However, the greatest difference was reported for the Há population, for which males in reproduction were 2.84 years younger than mares in reproduction, as shown in Historical inbreeding levels for PRá, PRE, and Há horse breeds were 6.79%; 8.42% and 2.85%, respectively, with these values increasing in the currently living populations to 8.44%, 8.50%, and 2.89%, respectively . Inbred Non-random mating degree was 0.06, 0.03, and 0.01 for the historical population of PRá, PRE, and Há horse breeds, respectively, while for the currently living population of the same breeds, non-random mating degree was 0.08, 0.03, and 0.01, respectively .Average coancestry in the historical population of the PRá, PRE, and Há horse breeds was 0.6%, 5.57%, and 2.06%, respectively. Values of average coancestry in the currently living PRá, PRE, and Há horse breed populations were 0.72%, 5.62%, and 2.13%, respectively . The genA summary of the results for the analysis of probabilities of gene origin, ancestral contributions and loss of genetic diversity is shown in gf) in the historical PRá, PRE, and Há horse breeds was 11.02, 7.90, and 7.61, respectively. Current gf was 7.45, 13.47, and 13.94 for PRá, PRE, and Há horse breeds, respectively.The effective number of ancestors was 56, 379, and 876 for the historical PRá, PRE, and Há horse breed, respectively . Comparafg) translated into higher than 93% levels of genetic diversity (lower than 7% levels of genetic diversity loss) were found as reported in Numbers of founder genome equivalents  explained 15.48–30.37% of the gene pool of the population of PRá horses. For PRE horses, the single ancestor with identification number 194 explained from 15.00% to 29.56%, respectively. For the Há horse breed, the single ancestor with identification number 200,862 explained from 10.92% to 21.75%, respectively.The numbers of equivalent subpopulations reported in the currently living population for PRá, PRE, and Há horse breeds were 1.58, 0.18, and 0.44, respectively. The parameters referring to the effective size of the population calculated through the individual inbreeding rate and coancestry rate, as well as the number of equivalent subpopulations can be found in The average Nei genetic distance between PRá, PRE, and Há horse breed historical and current populations was 0.013 and 0.025, respectively . The meaIT) was 0.03 for the historical population and 0.04 for the currently living population when breed was chosen as the subdivision criteria. The inbreeding coefficient relative to the subpopulation (FIS) varied from 0.02 for the historical population to 0.01 for the current population (ST) was 0.01 for the historical population and 0.03 for the currently living population. Wright’s F statistics , the inbpulation . The corNo variable was discarded provided all component loadings for the genetic diversity parameters were above |0.5|. This suggested the fact that those variables presenting a potential redundant confounding nature had been previously discarded, for instance, when multicollinearity (VIF) was tested. p < 0.05 obtained for Pillai’s trace criterion suggests that there is a difference across all the three breeds considered in this analysis  and variance inflation factor (VIF) were analyzed to identify those variables that were responsible for multicollinearity between variables. VIF estimation suggested the parameters of inbreeding  and equivalent generations (VIF > 4) should not be considered in the analyses. After the removal of these variance explanatory redundant variables, the results for tolerance and VIF can be observed in Inbreeding , average relatedness , average coancestry , non-random mating rate (α), genetic conservation index (GCI), number of maximum, complete and equivalent generations, and number of offspring per individual were included at a preliminary stage of the analysis performed in this study. Tolerance  for the first function on the x axis and those values for the second discriminant function on the y axis. Centroids describe the central observation for each breed group. The probability that an unknown case belongs to a particular group was calculated by measuring the relative distance of Mahalanobis to the centroid of a that particular population. To compute discriminant scores or centroids, the mean for each breed was substituted in the two first dimensions . Then, tWhen classification and leave-one-out cross-validation matrices are evaluated, it can be observed that 89.54%, 98.77% and 49.95% of the horses had been correctly classified for PRá, PRE, and Há horse breeds, respectively. Cross-validation was performed and Press’ Q value was calculated as follows;2 critical value for one degree of freedom at a 95% confidence level (p < 0.01), predictions were significantly better than chance. Hence, there is a correct classification rate of at least 50% [Contextually, as Press’ Q statistic was above 6.63 (significance level of 0.01), χeast 50% .The Há horse breed is a composite breed which derives from the cross between PRE and PRá horse individuals. To better understand Há horses, we may have to go back and study its ancestor breeds. This may enable the gathering of a very comprehensive amount of information to study the evolution of genetic diversity and of factors affecting it. The examination of the dendrogram constructed from Nei genetic distances and the spatial distribution reported after the discriminant analyses  suggest The Mediterranean breeds considered in the study  present strong differential physiological, behavioural and morphological differences ,10,12,65According to Aparicio Sánchez , such foThe drastic reduction in the number of PRE horses  was a diGeographical barriers or socio-political considerations may not have played an important role in the loss of diversity of the population given the low levels of genetic diversity loss found in our study, which could be ascribed to the process of genetic drift within the population. Overall, the generation interval in Há is rather long, with a global mean for the four selection paths of around 14.81 years. Nevertheless, this is in line with other studies considering the PRE horse breed (10.1 years) , largelyPCI in the three breeds studied are very high for the first five generations (from parents to great-great grandparents), which is common to autochthonous horse breeds as supported by Giontella, et al. . The higThe use of robust pedigrees with completeness indices of around 80% have reported to allow reliable estimations of inbreeding values, resulting in medium to high correlations with genomic inbreeding in horse breeds . AverageThe use of breeds with dissimilar performance characteristics enhances the opportunities for the maximization of their average genetic merit in the resulting product. This is taken advantage to meet requirements for specific functionality, production and/or marketing situations. When breeds used in the foundation of a composite breed do not contribute equally, as suggested by our results, since there is a loss of heterozygosity between the first and second generations . Then, iAlthough genetic erosion may have occurred at a very low rate, the population of Há horses has remained stable. These results suggest, timely action must be taken to control the increase in inbreeding through the years in the two ancestor breeds as levels are starting to approach compromising levels, which may result in the expression of deleterious effects derived from inbreeding in the population. One of the most relevant effects resulting from reduced genetic diversity is inbreeding depression, which in turn, may end up compromising the performance of domestic animals . SantanaIn this context, the large number of stallions used in reproduction may have contributed to the stabilization of inbreeding. Still, the presence of highly inbred animals in the population in percentages of 4.60%, 19.41%, and 30.55% in the currently living Há, PRE, and PRá horse populations implies the excessive use of certain individuals is still patent. These findings support the fact that currently, the major concern in managing the genetic diversity of the Há horse breed is the short-term decrease in genetic variability due to the loss of genetic contributions from founders and ancestors, more than the long-term effect of inbreeding itself as it was suggested in literature ,86,87,88When aiming to develop a genetically healthy breeding strategy, ΔR is a very useful parameter since it allows breeders to preserve the genetic pool of a certain population ,89. BecaLevels of genetic diversity in the present population are over 93% for the three breeds. However, in the context of Há horses as a composite breed whose studbook is still open, these high levels may not ensure the preservation of the gene pool of the founding population, as this population may constantly be changing . In suchefN) for PRá, PRE, and Há horse breed were 10, 11.40, and 23.57, respectively. These values support those reported in the literature [The determination of Mendelian sampling of the non-founders of a population has recently been reported to be of help when determining partial inbreeding in equine populations . Inbreedterature ,93, eventerature . Either terature ,92.eN), where eN is the effective population size.FAO/UNEP  proposedeN is complex, but certain criterion must be considered to permit a correct interpretation of this parameter. For instance, the sex ratio must be equal and individuals must randomly mate. A number of additional “ideal” characteristics could be stated. In practice, eN is always smaller than the actual number of breeding individuals. Thus, eN must equal at least 50 if our aim is to keep inbreeding rate below 1%. Still, even if inbreeding rate is 1%, the loss of genetic diversity is appreciable after a few generations, and a gradual erosion of genetic variation cannot be avoided. Eventually, the population will become virtually homozygous, the time depending on eN. Consequently, 1% criterion must be viewed as short-term criterion. A population with an effective size of 50 will lose about a quarter of its genetic diversity after 20–30 generations, and along with this, much of its capacity to adapt to changing conditions [The definition of nditions .eN must be increased. FAO/UNEP [eN, G being the number of generations the population is likely to retain its fitness at a relatively high level. Still, to conserve short-term fitness, or to maintain short-term fitness in captive populations other criteria must be accounted for, given effective population size is considerably affected by unbalanced sex ratios, population size evolution, by a non-random distribution of progeny among families, and other characteristics of the breeding systems implemented.To maintain a genetically healthy population in these situations, FAO/UNEP  suggestsIn line with these suggestions, Leroy, et al.  have repAs suggested by Gutiérrez et al. , valuablThe imbalance between effective population size calculated via individual inbreeding and via coancestry rate suggests that the introduction of new reproductive individuals and the design of a plan for recommendable breeding pairs within the breeds populations could be a viable alternative to maintain the lowest possible ΔR coefficients, thereby preventing the increase in the probability of inbreeding deleterious effects from occurring and increasing the future genetic variability and effective size of the breeds.ef and af could be used to assess the occurrence of changes in genetic drift and recent bottlenecks in a population, which are corroborated if (e/faf)>1, respectively. In our study, ef and af were 2.35, 1.54, and 1.48, respectively, for each of the horse breeds considered . This finding is indicative of the fact that genetic drift may not have been stable in the three horse breeds studied, with a progressive loss of founder representation, which had previously been reported in the literature [ef/fa, our study confirms that an increasing trend has been described by GCI over time. Hence, the fact that founder representation is being progressively gained, not only in the Há horse breed, but also in its two ancestor breeds, may derive from the attempts of breeders and breeding associations to plan matings, trying to compensate for the aforementioned loss of founder representation.Contextually, Alderson  would suterature ,101. DesThe Há horse breed population has a defined genetic structure, which may still be partially supported by its two ancestor breeds with a higher representation of PRá horses. The unbalanced contribution of PRá horses to the development of Há horses may also contribute to the fact that breeding practices and possibly reproductive physiology adapts more to those carried in the PRá horse than the PRE breed, which may additionally explain the slightly lengthened generation intervals. Although genetic erosion may have occurred at a very low rate, the population of Há horses has remained stable. The major concern in managing the genetic diversity of the Há horse breed is the short-term decrease in genetic variability due to the loss of genetic contributions from founders and ancestors, more than the long-term effect of inbreeding itself. The large number of stallions used in reproduction may have contributed to the stabilization of inbreeding. Reduced ΔR may act balancing the gene contributions of the founders in the population, and consequently itsgenetic diversity. Although a progressive loss of founder representation may have occurred, breeding strategies implemented considering mating between animals with the highest levels of GCI may compensate for the aforementioned loss of founder representation.