Sexual reproduction has contributed to a significant degree of variability in cultivated grapevine populations. However, the additional influence of spontaneous somatic mutations has played a pivotal role in shaping the diverse landscape of grapevine agrobiodiversity. These naturally occurring selections, termed 'clones,' represent a vast reservoir of potentially valuable traits and alleles that hold promise for enhancing grape quality and bolstering plant resilience against environmental and biotic challenges. Despite their potential, many of these clones remain largely untapped.In light of this context, this study aims to delve into the population structure, genetic diversity, and distinctive genetic loci within a collection of 138 clones derived from six Campanian and Apulian grapevine varieties, known for their desirable attributes in viticulture and winemaking. Employing two reduced representation sequencing methods, we extracted Single-Nucleotide Polymorphism (SNP) markers. Population structure analysis and fixation index (FST) calculations were conducted both between populations and at individual loci. Notably, varieties originating from the same geographical region exhibited pronounced genetic similarity.The resulting SNP dataset facilitated the identification of approximately two hundred loci featuring divergent markers (FST ≥ 0.80) within annotated exons. Several of these loci exhibited associations with essential traits like phenotypic adaptability and environmental responsiveness, offering compelling opportunities for grapevine breeding initiatives. By shedding light on the genetic variability inherent in these treasured traditional grapevines, our study contributes to the broader understanding of their potential. Importantly, it underscores the urgency of preserving and characterizing these valuable genetic resources to safeguard their intra-varietal diversity and foster future advancements in grapevine cultivation. According to the data from the Food and Agriculture Organization , Italy hhttp://catalogoviti.politicheagricole.it) more than 1,100 varieties have been collected and described; however, the actual number of grape varieties cultivated and kept in germplasm collections in Italy is much higher and cannot be estimated with certainty. The invaluable germplasm of Italian grapes includes many autochthonous varieties. Although sexual reproduction has led to a great variability among varieties , spontaneous somatic mutations have further contributed to the kaleidoscope of grapevine diversity with the so-called clones . An effective approach to explore the inter- and intra-varietal diversity relies on the use of molecular markers. Microsatellites are the most used markers in grapevine, and a standard set of nine loci is currently used for international cataloguing  (n. 20) and aglianico lasco (n.64), and the white-berry greco b. (n. 24). aglianico lasco has loose clusters able to reduce the development of mold during ripening. camaiola has intense ruby red colour berries suitable for violet hues wines, and greco b. fruits give rise to high quality wines appreciated for the complex aroma profiles  and malvasia nera di brindisi , and to the white-berry minutolo b. (n. 6). nero di troia is a high-quality, flavourful variety cultivated mainly in northern Apulia to make an ever-increasing number of monovarietal wines or blends. malvasia nera is a variety of Greek origin, widely cultivated in the southern part of Apulia, which produces fruity wines often together with the local variety negramaro. minutolo b. is an aromatic white variety with relatively small and loose clusters, which in the past was widely grown in the specific area of Apulia region called Itria Valley. The map of the sampling sites is shown in aglianico del vulture, aglianico taurasi, aglianico del taburno and sangiovese) and two international (chardonnay and merlot) varieties were used for microsatellite (SSR) analysis.A total of 138 grapevine clones belonging to 6 autochthonous varieties of Southern Italy were sampled in Campania and in Apulia  utilities included in Stacks v2.53 (https://www.elshiregroup.co.nz/) as described in Campanian genetic material was genotyped using ddRADseq . The ddRks v2.53  were useddRADseq and GBS produced two Variant Call Format (VCF) files respectively for Campanian and Apulian varieties, which underwent SNP filtering using VCFtools v. 0.1.16 . For thePLINK v.1.90  was used2 values against the physical distance of the markers, and the LD decay was estimated at the critical level of r2 = 0.20.For each dataset, linkage disequilibrium (LD) analysis was performed using the Golden Helix SNP and Variation Suite (SVS) v.8.8.3 (Golden Helix Inc.). The “Nonlinear Regression” function was used to plot the rvcf-merge utility of VCFtools (–relatedness2 option in VCFtools. The dataset was LD pruned (r2 = 0.50) using SVS.After removing the duplicates, bcftools +fixref  was usedVCFtools  was usedVCFtools  and PLINVCFtools  were usehttp://tree.bio.ed.ac.uk/software/figtree; Allele frequency and ancestry estimation were performed on filtered and pruned dataset using ADMIXTURE v. 1.3.0 , with 10Aglianico Lasco clones using the Qiagen Plant DNeasy Maxi Kit , following the manufacturer’s procedure. Microsatellite analysis was carried out with seven nuclear markers  from http://www.vivc.de/). The phylogenetic clustering tree was constructed with the neighbour joining method using MEGA X  within annotated exons were considered for the search for candidate genes. Grapevine gene annotations were retrieved at https://urgi.versailles.inra.fr/Species/Vitis/Annotations.Per-site FA total of 114,465 and 180,840 SNP markers were scored in the 108 Campanian and in the 30 Apulian clones, respectively. After filtering, 59,149 and 17,296 SNPs were retained in the Campanian and Apulian datasets, respectively  SNPs were retained in the Campanian and Apulian datasets, respectively.Malvasia showed the greatest number of SNPs within genes , while Greco B. showed the least . In all the varieties there were more transitions (Ts)  than transversions (Tv)  and the average Ts/Tv ratio was higher in the Campanian varieties (4.60) than in the Apulian ones (1.80)  Table 1.Camaiola and Apulian germplasm, whereas 47 and 13 duplicates were removed in Aglianico Lasco and Greco B., respectively, resulting in a final number of 78 clones   resulting in 500 SNPs, out of which 280 fall within genes. Population diversity was analysed using different approaches. The population structure indicated K = 6 and K = 7 as the best numbers of sub-populations, based on cross-validation error (Aglianico Lasco which was separated into two sub-populations (henceforth AL1 and AL2), comprising nine and four clones, respectively. Individuals belonging to the sub-populations Minutolo, Camaiola, AL2, Greco B. and Nero di Troia shared a co-ancestry coefficient (qi) > of 0.99, whereas the clones of AL1 and Malvasia had greater variability with qi ranging from 0.99 to 0.60 and from 0.99 to 0.57, respectively. The clones AL1-62, AL1-1, Malvasia-100 and Malvasia-101 resulted admixed. In addition, clone AL1-18 was grouped with clones belonging to Camaiola instead of Aglianico Lasco. DAPC analysis was then performed which confirmed the existence of seven clusters  were scattered in the fourth quadrant together with Malvasia Nera and Minutolo. Inter-varietal structuring within clones was supported by the neighbour-joining tree  than AL1 (h = 0.427), AL2 (h = 0.456), Minutolo (h = 0.173), Nero Di Troia (h = 0.236) and Malvasia Nera (h = 0.350). This was supported by the within-population sum of squares (SSWP) from the AMOVA analysis, where SSWP was 349.636 and 423.789 for Greco B. and Camaiola, respectively. The highest SSWP was found in AL1 (2097.001). Additionally, the AMOVA revealed high genetic variability within (41%) and between (59%) populations. Further investigation of genetic distances was performed using the genetic fixation index (FST) between sub-populations as emerged from clustering of ADMIXTURE and DAPC , with the highest value detected between Camaiola and Minutolo/Nero di troia (FST =0.58), followed by Nero di Troia with FST mean value > 0.48. Clones belonging to AL1 showed the lowest mean values (FST = 0.27) with lower FST (0.16) detected with AL2.The analysis of haplotype diversity corroborated these results, in fact n index FST betweAn additional intra-variety IBS and Kinship analysis was performed for AL1 and AL2 individuals. The pairwise genetic distance range was different within the two populations, 0.61-0.70 for AL1 and 0.78-0.99 for AL2. IBS values calculated between AL1 and AL2 individuals showed that IBS ranged from 0.53 to 0.73.Aglianico Lasco into two populations (namely AL1 and AL2) was further investigated using a set of seven discriminating microsatellite markers and the varieties Aglianico del Vulture, Aglianico Taurasi, Aglianico del Taburno, Sangiovese, Chardonnay and Merlot. The neighbour joining tree differentiated two main clusters  analysis at individual loci. All comparisons revealed numerous loci with an FST value > 0.25 (high differentiation)  followed by Nero di troia (N. = 404) and Minutolo (N. = 317), while AL1 showed the lowest number (N. = 117). An upset plot showing the co-occurrence of pairwise divergent loci is shown in Camaiola had the largest number of divergent genes between the other varieties, 100 against AL2, 91 against Minutolo, 85 against Nero di Troia, 81 against Malvasia, 57 against Greco B. and 39 against AL1 , VIT_215s0021g01230 and VIT_212s0059g02300 (only in Nero di Troia vs MINUTOLO) and VIT_205s0029g01285 (mostly found in Nero di Troia comparisons), which are involved in “cellular component organisation and biogenesis”, “primary metabolism”, “regulation of gene expression” and “stress response”, respectively. Additional information associated with the 200 gene-associated divergent SNPs was retrieved from published data and allowed the identification of 63 SNPs associated with genes involved in grape phenology and adaptation to the environment  and VIT_215s0048g02790 (mostly in Camaiola comparisons) were the most enriched in divergent SNPs. They are annotated as ferredoxin-related gene and PMT26 methyltransferase, respectively, and known to be linked to the initiation of berry ripening  performed for samples from Campania, according to the method proposed by in silico approach. Remarkably, after removing duplicate clones from each variety, we successfully merged all clones into a single dataset consisting of 2,235 SNP markers that was then used for cross-varietal analysis. To date, only Six varieties were genotyped with two RRS strategies; GBS was used for the Apulian clones, while ddRADSeq for the Campanian ones. These methods differ in the number and type of restriction enzymes (REs) used to digest and access the genome and affected the total number of SNPs spanning on the reference genome. As expected, the ddRAD-seq dataset has more SNPs compared to fewer SNPs from GBS data, due to more restriction sites that are more polymorphic than GBS . The RE th genes . OtherwiAglianico Lasco population, where more than 70% of collected samples was duplicated. This redundancy is probably linked to the propagation history of clones, likely deriving from few homogenous plots of mother plants which were multiplied by local growers in a restricted cultivation area, under similar environmental pressures and selection criteria. After elimination of duplicated individuals, we were left with a set of 78 individuals that we employed in downstream investigations. We found that Camaiola, Greco B., Minutolo, Malvasia, and Nero di Troia split into separated populations. This finding indicates that these varieties are represented by clones with a genetically uniform profile. An exception was found in the population of Aglianico Lasco which separated into two groups called AL1 and AL2. To shed lights on the genotypic identity of each sub-population of Aglianico Lasco, we performed a comparative analysis based on microsatellites using, among others, the main red variety grown in Campania (Aglianico) with which Aglianico Lasco is generally matched and confused. The AL1 population included individuals genetically similar to all Aglianico biotypes , whereas AL2 grouped individuals with microsatellite profiles divergent from those of AL1. The high IBS values and the Kinship coefficient within AL2  of the most renowned cultivar Aglianico, whichhas at least three different biotypes inside.As acknowledged by the International Organization of Vine and Wine in resolutions OIV-VITI 424/2010 and OIV-VITI 564B-2019, a crucial conservation strategy to protect the world heritage of grapevine is based on the assessment of intra-varietal diversity and polyclonal selection . In thisthin AL2 Table S2Misattribution of names is frequently reported in grapevine  and is cTo explain the genetic diversity of the varieties under study, it is necessary to consider their origin and ancestry. Despite PCA plot did not reflect the geographical grouping, neighbour-joining tree clearly separated the Campanian from the Apulian varieties, indicating that the geographical origin could be one of the main drivers in defining varietal relationships in grapevine species, as observed in other studies .Nero di Troia takes its name from the city of Troia in the Daunia region, where it is mainly cultivated. It derives from the spontaneous crossing between the French Bouteillan and the Bombino bianco, giving origin also to other Apulian varieties such as Bombino nero and Impigno  and its offspring; this confirms the centrality of Visparola in the origin of many grapevine varieties of Southern Italy  where numerous molecular, biochemical, and physiological changes occur that strongly impact the quality of wine  in grapevine samples grown under changing environmental conditions . Among tAglianico Lasco) as well in identifying possible recent introduced outgroup variety such as Camaiola for Campania. This is a crucial task in any germplasm management and conservation strategy. Finally, we identified several divergent SNP loci within genes involved in grapevine phenology and environmental adaptation. This evidence emphasises that some traits, such as those related to budding, flowering, and fruit quality could have played a key role in assessing whether a given cultivar was adapted to specific local climatic conditions.In this study, we used genome-wide SNP datasets generated by the GBS and ddRADSeq methods to assess the clonal diversity of six traditional grapevine varieties. We have shown that merging different SNP datasets is possible and valuable to study the inter- and intra-specific genetic diversity of grape populations. This provided that the same reference genome is used. Through such an approach, we have provided a repeatable framework to streamline future computational studies based on the retrieval of information from partial analyses performed at different times and with different techniques. Our results also demonstrated the value of advanced genomic methods in the study of population structure and synonymy/homonymy detection (as exemplified by The original contributions presented in the study are included in the article/FT, CM, CV, and RA designed the experiment. CM, CV, PN, and RA established the grapevine collection. ES, SP, MM, FT, and ND’A carried out part of the bioinformatic and the genetic diversity analyses and detected loci under selection. VF and CV performed genetic diversity indices and SSR analysis. All authors were involved in the data interpretation. CV, FT, MM, and RA wrote the draft manuscript. CV, MM, and FT critically revised the manuscript for important intellectual content. DC, PN, CM, RA, ND’A, and FT finalised the latest version of the manuscript. All authors contributed to the article and approved the submitted version.


The goal of this study was to verify the effect of heterogeneity of variance (HV) on milk production in up to 305 days of lactation (L305) of daughters of Girolando, Gir and Holstein sires, as well as in the genetic evaluation of these sires and their progenies. in Brazil. The model included contemporary groups  as a fixed effect, cow age at calving (linear and quadratic effects) and heterozygosity (linear effect) as covariates, in addition to the random effects of direct additive genetic and environmental, permanent and residual. The first analysis consisted of the single-trait animal model, with L305 records (disregarding HV). The second considered classes of standard deviations (SD): two-trait model including low and high classes (considering HV), according to the standardized means of L305 for herd-year of calving. The low SD class was composed of herds with SD equal to or less than zero and the high class with positive SD values. Estimates of (co)variance components and breeding values were obtained separately for each scenario using Bayesian inference via Gibbs sampling. Different heritability was estimated. Higher for the high DP class in the Gir (0.20) and Holstein (0.15) breeds, not occurring the same in the Girolando breed, with a lower value among the classes for the high DP (0.10). High values of genetic correlations were also found between low and high SD classes  for the Girolando, Gir and Holstein breeds, respectively. Like the order correlations (Spearman) which were also high for the three breeds analyzed . Thus, the presence of HV had a smaller impact for L305 and did not affect the genetic evaluation of sires. The use of local breeds adapted to a specific environment is one of the OIE’s recommendations , seekingIn this context, genotype x environment interaction (GEI) emerges as a possible problem in defining strategies for the use of genetic resources, due to the fact that genotypes with favorable performance in one environment may not have all their genetic potential expressed in another environment . In addiThe heterogeneity of variance in milk production is a form of GEI and when it occurs, the production of the progenies of a given breeder will be weighted by the proportion of SD of the herds in which their progenies are being evaluated. The result of this is that the productions of these daughters, from more variable herds, will present a greater weight in the genetic evaluation of breeders than progenies with production from less variable herds .However, if the GEI is not expressive, records of daughters in different environments may alleviate the lower response to selection caused by GEI. If there is significant interaction between genotype and environment in the expression of a given productive characteristic, better said, if the genetic correlation between environments is less than 0.70; different improvement programs will be required for genetic assessment in each of the environments .Therefore, it is essentially important to choose appropriate environmental descriptors in GEI studies –14. The India is the world’s largest dairy producer, with the largest proportion of production coming from small herds, averaging less than two dairy cows per herd. These cows are mostly multi-generation indefinite crosses between exotic dairy breeds and indigenous cattle, with no record of performance or pedigree. Initial results from a performance recording program indicate a strong potential for genomic selection to improve milk production in these animals. The performance of animals with different racial compositions, in different Indian environments, will allow better guidance for small producers on the ideal racial composition for each environment. These results highlight the effect of GEI on dairy production, showing that the best animals for one environment will not necessarily be the same in another .effect on the ranking of breeders 29], who It was possible to observe that the high SD class with the highest average, highest SD and lowest CV, between classes, exhibited homogeneity in the milk production of the animals, in the three breeds used in this study, indicating that the criterion for forming the SD classes was efficient.In all breeds, there was an increase in the posterior means of the estimates of the variance components referring to the additive genetic effect, permanent environment and residual effect Tables –4.This increase occurred from low to high phenotypic SD, however, this change was not proportional to the point that heritabilities, repeatability and correlations remained constant in the different analyses.The increase in the estimates of the genetic and residual variance components, according to the increase in the production level of the herds, has been reported in other studies –35 with It is noteworthy that, for the Girolando breed, the posterior mean of the estimation of permanent environment variance for the high SD class was 98.36% higher than the low SD class. This had a great impact on the calculation of the total phenotypic variance. In general, environmental variation was responsible for an important part of the total variation of the evaluated trait, causing low heritabilities.Geweke’s criterion , which cFor the Girolando breed, the posterior means of heritability, considering the SD classes, were close, being 0.10 for the high SD and 0.12 for the low SD. This shows that, although the herds are in different environments, genetic factors act in a similar way in both.Comparing the a posteriori mean of heritability in general analysis (0.09), there is a great difference in relation to the values reported by , who obtThe subsequent mean of heritability found in the general analysis (0.17) for the Gir breed was much lower than that reported by  with valPosterior means of heritability of 0.12, 0.15 and 0.11  approximate from those found by  in generHeritability values were, in general, higher in the high SD classes, with the exception of the Girolando breed, mainly due to the influence of the posterior estimate of the permanent environment variance in this breed.In many cases, the more intensive the management of the herd for milk production, the greater the heritability  and thisDifferences in heritability estimates may also be due to non-compliance between the populations studied and the different analysis methods used. However, ignoring these differences between heritability estimates, although small, raises doubts about the reliability of estimated reproductive values.In addition, heritability, and gradients of genetic variation between environments could imply a higher genetic response in herds with more intensive management. It becomes evident the need for further research considering VH in genetic evaluation models, including through models of reaction norms.Repeatability values indicated reasonable similarity between consecutive lactations of the same animal, suggesting the importance of permanent environmental effects in determining the expression of this trait. In general, comparing within each breed, repeatability values did not differ greatly, ranging from 0.31 to 0.32 (Girolando), 0.35 to 0.40 (Gir) and 0.28 to 0.31 (Holstein).Animals of the Girolando breed reported a repeatability value equal to 0.93 in general analysis The animals of the Girolando breed have repeatability values ranging from 0.33  to 0.93 For the Girolando, Gir and Holstein breeds, high values of genetic correlations were found Tables –4, betweIn view of this, as reported by other authors , 49–51, The order correlations (Spearman) between the genetic values obtained in the low and high SD analyzes and those obtained in the general analysis, taking into account all sires, were equal to or greater than 0.92 , and werThe order correlations (Spearman) between the genetic values obtained in the low and high SD analyzes and those obtained in the general analysis, taking into account all sires, were equal to or greater than 0.92 , and werHowever, when the correlation is performed for the 20% of the best sires, classified based on the genetic values estimated in the general analysis, there were reductions in the order correlations. Becoming higher for Gir and Holstein breeds, between low and high SD classes, 32.26% and 29.35%, respectively. As for the Girolando breed, the greatest impact was between the general analysis and the low SD class, with a reduction of this correlation by 9.47%.The greater the selection intensity, the lower the percentage of common animals between the classification groups, since the effect of errors in the classification order is more evident when a small number of animals are selected.The greater association of high SD classes with the general analysis indicates that more variable herds contribute with greater participation in the prediction of genetic values, in a situation that disregards variance heterogeneity. This is because the high SD classes had greater additive genetic variability.As with the sires, the order correlation was performed for their progenies . CorrelaHowever, there was a downward trend in correlation values as selection pressure increased. This became evident when the Spearman correlation considering only 20% of the best cows, according to the genetic value in the general analysis, decreased to values up to 0.62. However, there was a downward trend in the correlation values, as there was an increase in the selective intensity of the sires, since the Spearman correlation considering only 20% of the best cows, according to the genetic value in the general analysis, decreased to values of up to 0.62.A study analyzing breeding strategies in two environments, based on the highest mean genetic gain –56, founAlthough alterations were observed in order correlations, it is verified in There were only two cases of considerable change. The first was in the Holstein breed, in which only 6 animals of the 10 bests, remain in the analysis, considering the low SD class . The second happened in the analysis of the cows, in which only 5 animals, out of the top 10, remain in the analysis considering the low SD class, in the Gir breed.Other studies , 58–63 sThis indicates that in this research herd environments (included in SD classes) may be similar in some respects, although they differed in herd size and location regions.The HV existing in this study did not cause great harm in the genetic evaluation of sires in the three studied breeds. This was evidenced when observing the results obtained in the general analysis, which would similarly select the same sires within the HV classes.Estimates of heritability and genetic correlation for milk yield revealed that the heterogeneity of variance present is mainly genetic in nature. Therefore, the presence of variance heterogeneity did not affect the genetic evaluation of sires for the three breeds studied.Spearman’s correlations showed that there was no difference in the classification of sires without considering HV. However, this pattern was altered when the selection intensity increased in the sires, resulting in a considerable change in their ranking.In animal genetic evaluation models, it is important to verify the presence of HV, as well as its effect on the genetic evaluation of the breeders, especially in countries where there are large variations in the environment.S1 File(PDF)Click here for additional data file.


Lactiplantibacillus plantarum in enhancing folate of injera made with different cereals. Cereals were used alone or in combination (tef and sorghum (1:1), wheat and sorghum (3:1), sorghum (100%), and barley (100%)). L. plantarum previously isolated from tef dough and ersho (fermentation batch) collected from the households were used as starters. Folate content of the flour, dough, and injera was determined by microbiological assay. Contribution of consumption of injera made with different cereals to the folate requirement of children and women of reproductive age was evaluated. Among the studied cereals, the highest average folate content (49.9 μg/100 g) was observed in 100% sorghum flour and the least (32.2 μg/100 g) in 100% barley flour, on dry weight basis. After fermentation, the highest average folate content (60.1 μg/100 g) was observed in 100% sorghum dough fermented with L. plantarum. Highest average folate content (15.45 μg/100 g) per fresh weight was observed in wheat and sorghum (3:1)‐blend injera fermented with L. plantarum. Consumption of L. plantarum–fermented injera made with different cereals contributed up to 8% of the recommended folate intake of women of reproductive age.Fermentation can contribute to the supply of essential vitamins like folate, but studies exploring this potential are scarce. Injera is an Ethiopian fermented pancake‐like flatbread made from different cereals. The study aimed to investigate the effect of injera‐making process using different cereals  on folate content and to evaluate the effectiveness of  Lactiplantibacillus plantarum strain can be used as a potential folate source not only for injera made with tef but also for any injera that could be made with other cereals.L. plantarum contributed much more to folate RNI of children and women of reproductive ages than consumption of injera fermented with ersho.Consumption of any injeras fermented with  The raw materials  were obtained from the local market of Addis, Ethiopia.2.2injera making was obtained from the literature. The most commonly used grain types and mixing ratios for injera preparation were taken from Baye et al.  “Melkam” variety, tef (Eragrostis tef (Zucc.) Trotter) “Quncho” variety, wheat (Triticum aestivum) “Beka” variety, and barley (Hordeum vulgare) “Hb 1969” variety were selected for the current study. The blending ratios used in making the injera were as follows: sorghum alone (100%), sorghum and tef (1:1), wheat and sorghum (3:1), and barley alone (100%)  which was taken from household was used as inoculum to prepare traditional injera.Two different inoculums were prepared. A leftover from previous successful spontaneous fermentation batch . The pellets were washed twice with the same volume (9 mL) of sterile saline solution (0.9% NaCl) and resuspended in the same volume of solution. The final suspension contained around 109 colony‐forming units (cfu)/mL. The inoculum for the fermentation of injera with the folate‐producing L. plantarum P2R3FA was prepared by mixing this suspension with each of the respective cereal flour (1:1) (v/w).The folate‐producing 2.3.2injera‐making process was developed after detailed observations from 10 selected households. Households were selected deliberately, where blended cereals are used for injera making, and this resulted in a flow diagram presented in Figure L. plantarum strain and 62.5 g flour (1:1) (v/g); similar proportion was also used for ersho starter. Thereafter, 200 mL sterile tap water was carefully added to cover the surface of the batter and incubated for 4 days at room temperature (first‐phase fermentation). After 4 days of fermentation, liquid present on top of the batter was decanted and replaced by a similar amount of fresh tap water except for barley fermentation where there was no supernatant. Before baking injera from the fermented batter, 1/11th of the fermented batter was mixed with sterile tap water (1:3) (v/v), boiled for about 10 min, and cooled to a temperature of around 46°C. The resulting product (absit) was added back to the remaining fermented batter to enhance proper fermentation. In case of barley fermentation, sterile cold water was used instead of absit. The batter was allowed to ferment for 2 h at 25°C until gas production was observed (second‐phase fermentation). Finally, the fermented liquid batter (450 mL) was poured onto a hot clay with cover and was baked for 2 min to make the final product, injera. Three baking were performed for each inoculum mentioned under Section The traditional 2.3.3injera preparation, pH of the batter was measured initially before fermentation and after second‐stage fermentation. Fermented batter was sampled to measure dry matter (DM) and folate contents before the addition of absit, and injera was also sampled to measure DM and folate contents and subjected to sensory analysis. DM was analyzed by oven drying at 105°C. pH was measured using an aliquot of dough immediately after diluting it with deionized water (1:1) (v/v).During 2.42.4.1injera was determined in triplicates using the reference microbiological method after trienzyme extraction ‐5‐formyltetrahydrofolate (5‐HCO‐H4 folate) as the calibrant. Performance of the method was checked by testing a blank sample and certified reference material . Only folate contents in the range of certified value (500 ± 70 ng/g dry matter) were accepted. In addition, for triplicate samples, folate content variations of >10% were not accepted. Analytical procedures were carried out under yellow or subdued light. Alternatively, samples and calibrants were covered with aluminum foil. Sample extracts were kept under nitrogen atmosphere whenever necessary.The total folate content of tef flour, dough, and 2.4.2The effect of cooking (baking) and fermentation on the total folate content was evaluated and results were expressed as percentage retention.2.5injera consumption from the Ethiopian National Food Consumption Survey as indicated in Tamene, Kariluoto, et al. , using a 9‐point hedonic scale. The 30 judges of adult healthy volunteers were randomly selected and were provided with the randomly sequenced samples for testing. They were asked to evaluate the products for color, taste, odor, texture (mouth feel), and overall acceptability. As described in Tamene et al.  and Tukey's post hoc tests. Mean differences were considered statistically significant for p values ≤.05.Statistical analysis of folate and sensory acceptability was computed using SPSS version 25 software. The folate analyses were carried out in triplicate and the average values and standard deviations were calculated. The differences between means of folate values in different cereal flour, dough, and 33.1L. plantarum ranged from 3.38 to 3.43 with an average value of 3.36 ± 0.07, whereas the pH value of ersho‐fermented doughs made with different cereals ranged from 3.30 to 3.42 with an average value of 3.41 ± 0.09. There was no significant difference in pH value of all doughs regardless of the cereal types and starters used.The pH of the initial dough made with four different blended cereals recorded at 25°C ranged from 5.5 to 6.1 with an average of 5.8 ± 0.3. After fermentation, the pH value of doughs made with different cereals and fermented with 3.2injera made with different cereals and starters were analyzed and results are shown in Table The DM content of flour, dough, and ersho‐fermented dough ranged from 35.6 ± 0.31% to 40.8 ± 0.25% by mass. For L. plantarum–fermented dough, the DM was in the range of 37.9 ± 0.94% and 41.5 ± 0.35% by mass. Significantly higher DM (41.5 ± 0.35% by mass) was observed for dough made with sorghum, whereas there was no significant difference in DM content between the doughs made from the other cereals.The average DM contents of injera made with ersho ranged from 37.2 ± 0.53% to 45.3 ± 0.26% by mass. With the exception of injera made with tef and sorghum blend, which had significantly higher DM (45.3 ± 0.26), there was no significant difference in DM contents for all the other injeras fermented with ersho. Regarding injera fermented with L. Plantarum, the average DM content ranged from 39.9 ± 0.4% to 44.7 ± 0.5% by mass. The DM of injera made from barley (39.9 ± 0.4% by mass) was significantly lower than the injera made from other cereals.The average DM content of 3.3The average folate contents of different blends of flour ranged from 32.2 ± 1.5 to 49.9 ± 1.1 μg/100 g (Table ersho ranged from 27.6 ± to 34.5 ± 0.7 μg/100 g. The highest folate content (34.5 ± 0.7 μg/100 g) was recorded in barley batter, however, it was not statistically different from folate of wheat and sorghum–blended dough (32.2 ± 1.3 μg/100 g). The lowest concentration of folate was observed in sorghum batter (27.6 ± 2.7 μg/100 g). However, it was not statistically different from the folate of tef and sorghum–blended dough (29.1 ± 0.9 μg/100 g).The average folate contents of different dough fermented with L. plantarum strain‐fermented doughs, the average folate contents were much higher and were in the range of 45.5 ± 1.3 and 60.1 ± 1.6 μg/100 g. The highest folate content (60.1 ± 1.6 μg/100 g) was recorded in sorghum batter, followed by wheat and sorghum–blended dough (56.9 ± 1.6 μg/100 g). Significantly lower concentration of folate was observed in L. plantarum–fermented barley batter (45.5 ± 1.3 μg/100 g) but was not significantly different from those of wheat and sorghum (3:1)– and sorghum and tef (1:1)‐blended doughs.For injera made with different cereals and fermented using ersho ranged from 17.5 ± 0.7 to 23.6 ± 0.7 μg/100 g. Among the different blends, significantly lower folate contents (17.5 ± 0.7 μg/100 g) were observed in tef and sorghum–blended injera. However, there was no significant difference in folate contents among the other injera samples (p ≥ .05).The average folate contents of L. plantarum–fermented injera made with different cereals had folate content between 30.2 ± 0.9 (tef–sorghum blend) and 35.4 ± 1.3 μg/100 g (wheat–sorghum blend) (Table ), with no significant differences between the different injeras.injera made with different cereal blends with L. plantarum fermentation was evaluated by comparing it to dough and injera obtained with ersho fermentation. In all cases, doughs fermented with the strain (L. plantarum) were found to have significantly higher folate contents than those fermented with ersho  had significantly higher folate contents as compared to all injeras fermented with ersho as shown in Table injeras, tef and sorghum (1:1)–blended injera had 17.5 ± 0.7 and 30.2 ± 0.9 μg/100 g, wheat and sorghum (3:1)–blended injera had 23.6 ± 0.7 and 35.4 ± 1.3 μg/100 g, sorghum injera had 23.4 ± 1.1 and 32.3 ± 5.1 μg/100 g, and barley injera had 20.8 ± 0.9 and 32.7 ± 1.5 μg/100 g folate contents when they were fermented with ersho and the strain, respectively.Similarly, in all cases, 3.4Percentage retention of folate after fermentation was calculated by comparing the amount of folate content in tef flour and dough on DM basis Figure . A valueL. plantarum ranged from 120 to 141% . This showed more than 100% folate retention for all of the doughs fermented with the strain regardless of the blend used. The highest retention (141%) was recorded in dough made with wheat and sorghum blend (3:1). In contrast, fermentation with ersho yielded retention ranging from 68% to 107%  for m Figure  and 68% o Figure .3.6injera made with different cereals and fermented with ersho was in the range of 7.82 ± 0.61 and 9.79 ± 0.28 μg/100 g per fresh weight (FW). The lowest average folate content (7.82 ± 0.61 μg/100 g FW) was recorded in barley injera and the highest (9.79 ± 0.28 μg/100 g FW) was observed in wheat and sorghum blend (3:1) injera was observed in barley and the highest (15.45 ± 0.58 μg/100 g FW) was noted in wheat and sorghum blend (3:1) injera.The average folate content of raTable . Howeverinjera consumption to folate requirements was calculated by estimating folate supplied by the average portion size of injera consumed by children (66 g/day) and women of reproductive age (202 g/day) . The overall acceptability test result showed that sorghum injera fermented with both inoculums (ersho and L. plantarum P2R3FA) was the least acceptable product, whereas tef and sorghum blended and 100% barley injeras fermented with both inoculums were the most acceptable injera. Looking at each specific parameter, with the exception of color, for all other sensory parameters , wheat and sorghum blended and 100% sorghum injeras fermented with both inoculums were found to be the least liked product.All of the samples made using different cereals and selected inoculums were found to be in the acceptable range with the exception of sorghum ts Table . The ov4injera is mainly produced from tef, but it is also prepared from other different cereals like barley, sorghum, and wheat either alone or in combination. Few studies focused on investigating the effect of tef injera preparation on folate contents and the extent to which folate‐producing strains (L. plantarum) can be used to enhance the folate content of injera. The current study investigated the effect of injera preparation made with different cereals fermented with ersho or a folate‐producing L. plantarum strain priorly isolated from tef fermentation. We evaluated the sensory acceptability of the resulting injera and estimated the contribution to folate requirement.In Ethiopia, injera preparation) was highly variable. In the case of doughs fermented with L. plantarum, although highly variable, fermentation leads to net folate production. However, doughs fermented with the traditional process using ersho led to reduction of folate with the exception of barley dough which may be due to the presence of other naturally occurring folate‐producing microorganisms and/or the lack of decantation process that may lead to folate loses. In contrast with fermentation, baking invariably led to folate losses, which is in line with findings from Tamene, Kariluoto, et al.  retained more than 75% of the folates. This finding suggests that folate losses can be minimized if injera baking process is optimized.As baking is the second major step in ersho‐fermented injera samples made from different cereals contributes to less than 5% of the folate RNI for children (1–3 years) and woman of reproductive age. Use of the same cereals with equivalent proportions but changing the inoculum (L. plantarum instead of ersho) yields injera with better folate contents, which can contribute to more than 5% of the daily folate requirement of both women and young children. Assuming that two servings (∼350 g/serving) of injera are consumed per day by women of reproductive age, injera made from cereals other than tef could contribute to more than 10% of the RNI if L. plantarum is used as inoculum. The present study clearly showed that all injera prepared using the traditional process had the lowest folate content as compared to its counterpart process which used L. plantarum.Based on portion size estimates obtained from the national food consumption survey, the average folate content in our injeras made using L. plantarum to folate requirement is a bit lower than tef injera fermented with the same strain . The study used a fixed proportion during blending of cereals but multiple proportions could yield a different result both on the folate content and sensory attributes of the final product. The present study focused only on few common cereals as there could be other cereals that can be used for making 5injera can either increase or decrease its folate content, while baking always leads to folate losses. Relative to injera fermentation with ersho, our L. plantarum strain almost always led to increases in folate content during fermentation and less loss during baking of the doughs. Consequently, injeras fermented with L. plantarum, irrespective of the type of cereal used, led to higher contribution to daily folate intake than injera fermented with ersho. Our study has clearly indicated that L. plantarum could be used for the development of fermented foods like injera prepared with different cereal types with better folate content and consumer preferences. This research also showed that L. plantarum strain can be used as a potential folate source not only for injera made with tef but also for any injera that could be made with other cereals. Further studies on safety characterization of the strain like antibiotic profile activity are recommended.Cereals such as wheat, barley, sorghum, and tef could be considered as sources of folate, and fermenting it to prepare Aynadis Tamene: Conceptualization ; formal analysis ; investigation ; methodology ; resources ; supervision ; validation ; writing – original draft ; writing – review and editing . Kaleab Baye: Conceptualization ; methodology ; project administration ; resources ; supervision ; validation ; writing – review and editing . Tesfaye Mekuriyaw: Formal analysis ; funding acquisition ; investigation ; writing – original draft .This work was partially supported by the DARE project, funded by the European Commission, DESIRA partnership for innovation program.The authors declare no conflict of interest.This study was approved by the Institutional Review Board of the College of Natural and Computational Sciences of Addis Ababa University.Written informed consent was obtained from all study participants for the sensory analysis.


Thalassia hemprichii, at a fine spatial scale (~80 km) in the Kimberley coast, western Australia, a complex seascape with strong, multidirectional currents greatly influenced by extreme tidal ranges . We incorporated genetic data from a panel of 16 microsatellite markers, overwater distance, oceanographic data derived from predicted passive dispersal on a 2 km‐resolution hydrodynamic model, and habitat characteristics from each meadow sampled. We detected significant spatial genetic structure and asymmetric gene flow, in which meadows 12–14 km apart were less connected than ones 30–50 km apart. This pattern was explained by oceanographic connectivity and differences in habitat characteristics, suggesting a combined scenario of dispersal limitation and facilitation by ocean current with local adaptation. Our findings add to the growing evidence for the key role of seascape attributes in driving spatial patterns of gene flow. Despite the potential for long‐distance dispersal, there was significant genetic structuring over small spatial scales implicating dispersal and recruitment bottlenecks and highlighting the importance of implementing local‐scale conservation and management measures.Understanding patterns of gene flow and processes driving genetic differentiation is important for a broad range of conservation practices. In marine organisms, genetic differentiation among populations is influenced by a range of spatial, oceanographic, and environmental factors that are attributed to the seascape. The relative influences of these factors may vary in different locations and can be measured using seascape genetic approaches. Here, we applied a seascape genetic approach to populations of the seagrass,  Thalassia hemprichii, in a complex coastal setting with the world's largest tropical tides, we detected significant spatial genetic structure and asymmetric gene flow over small spatial scales. This pattern was explained by oceanographic connectivity and differences in habitat characteristics and highlights the importance of implementing local‐scale conservation and management measures.Using a seascape genetic approach for the seagrass,  Understanding the genetic structure and the processes that generate them is highly informative for a broad range of conservation practices  has been the simplest model used to explain genetic differentiation, whereby gene flow decreases with distance from the original population Wright, . HoweverGene flow is dependent on the combination of these processes as described above  Ascherson, 1871 and investigated the factors that are known to influence genetic structure . We incorporated genetic data from a panel of 16 microsatellite markers, a biophysical dispersal simulation, and environmental data into a seascape genetic approach using partial RDA analysis , ranged from 2 to 73 km. The distance calculation was performed based on high‐resolution bathymetric data from the US National Oceanic and Atmospheric Administration (NOAA) using the package marmap in R , the Sunday Islands group including mainland sites (seven sites), and intermediate sites between the first two groups (two sites)  water depth (m) relative to mean sea level (determined from Google Earth version 7.1.2.2041); (ii) dominant sediment type through visual assessment using Wentworth's categories  . Extractions were done using the Nucleospin Plant II Kit  with the PL2/PL3 buffer system.We collected a total of 650 samples (meristematic region of seagrass leaves). At each sampling site, a total of 50 samples, separated by at least 2 m were either collected randomly in a circular area with a diameter of ~50 m and 5–10 25 m‐transects starting from the center of the circle, or if this was not possible because of the patchy nature of the meadow, then samples were collected haphazardly across the patches in a similar area. Samples were collected by wading at low tide. Due to the presence of saltwater crocodiles, it was not feasible to SCUBA dive. Clear meristematic sections of the leaf were cut into strips and then immediately stored in silica to rapidly dry and preserve the DNA. DNA was extracted from 2 to 3 pieces (5–10 mm in size) of silica dried samples using AGRF extraction service .Microsatellite amplification was conducted on 16 polymorphic microsatellite loci: Thh5, Thh34, Thh15, TH66, TH37, TH43, TH43, Thh8, TH34, Thh41 TH52, TH07, Thh29, Thh1, Thh36, and Thh3  the expected number of individuals with the same MLG was estimated. Noyon site was excluded from further analysis as the marker system was not powerful enough to detect MLGs. MLGs were identified using the package poppr in R /(N−1)  accounting for different sample sizes using the package poppr  calculated in Genetix 4.05 , (2) private allele richness (PA), (3) observed heterozygosity (HO), and (4) unbiased expected heterozygosity  were calculated using HP‐Rare  in the program codidi  among the populations. We set the number of panmictic clusters (K) to be tested from K = 1 to K = 11, with a burn‐in of 105 replications. We performed 20 iterations for each K value. Determining the “true” K was based on Evanno et al. . A fourth order Runge‐Kutta sub‐time‐stepping scheme was used to update the particle locations every hour  was visualized using the package qgraph  to determine the relative contribution of geographic distance (GD), oceanographic connectivity (OC), and environmental factors  in driving genetic differentiation (GS). As this analysis required both the response and the explanatory variables to be single or multicolumn numeric matrices, we transformed the “raw” data of GS, GD, OC, and EN into new data frames suitable for the analysis. First, we constructed a new matrix for the response variable (GS) by retaining all positive axes derived from a principal coordinate analysis (PCoA) on the linearized Rousset, . Second,igraph package in R , (ii) closeness—defined as the number of steps required to access every other site from a given site, (iii) betweenness—the number of shortest connections between two sites that go through the site of interest, and (iv) transitivity—defined as the extent to which the adjacent sites of a site are connected to each other. For calculating closeness and betweenness, the package treats the connection weights as “cost” instead of “connection strength”, thus it represents the cost needed to connect nodes (higher closeness and betweenness imply a higher degree of isolation)  into dummy variables, and combined them with the numerical data (water depth and number of other seagrass species). Then, we ran a correspondence analysis  on the transformed environmental data. The variable most responsible in driving the environmental differentiation was sediment type. We constructed the EN data frame based on the first three CA axes from the correspondence analysis representing 97.6% of the variance of the data.R2 to determine the amount of variation attributed to each explanatory variable controlling the effect of the other variables  and without controlling the effect of the other ones , and the shared fraction of variation by any combination of explanatory variables  . A significant heterozygote deficit was detected in some sampling sites  , rather than technical issues like the presence of null alleles , indicating a low chance of association between loci  varied greatly from 0.36 to 0.94 (Table nA) ranged from 24  to 36 (Mermaid Island), while AR ranged from 1.47 (Bedford Island—North) to 1.84 . The highest expected heterozygosity (HNB) was found at Longitude Island (0.216), with the lowest Sunday Island—South (0.131).Genotypic diversity . All pairwise FST were significantly greater than zero (p < .01), except between the two Sunday Island populations (p = .066) and varied by more than an order of magnitude, from 0.022 to 0.336 between Longitude Island and Bedford Island North, where sites were separated by only 12 km  or were highly admixed between the two remaining clusters. At K = 4, individuals from Bathurst Island became distinct from those at Longitude Island, but the clustering pattern of the remaining individuals did not change significantly . The most northern sites were also intertidal at a mean sea level of 0 m, whereas the other sites ranged from depths of 1 to 5 m below sea level  nor oceanographic connectivity  but it was closest with environmental distance .The highest OC was between sites in the Sunday Island group  and the lowest OC was between these sites and the most northerly sites (Bathurst and Longitude islands) Figure . The OC p > .05), indicating that oceanographic connectivity and the environment factors do not explain the genetic differentiation independently but in combination.The variance partitioning analysis revealed that oceanographic connectivity and the environment were both significant drivers of genetic differentiation Table . The mar44.1T. hemprichii. However, patterns of differentiation were idiosyncratic with respect to geographic proximity, with some of the closely situated sampling sites being the most differentiated and assigned to a different population cluster. Other population genetic studies on T. hemprichii have been at a much larger spatial scales, 500–1000s of kilometers .  in governing patterns of gene flow. Population differentiation is the consequence of barriers of gene flow imposed by the interactions between species’ biological traits and their environment. This is supported by a combined oceanographic connectivity and environment relationship with the patterns of gene flow revealed in our study. These mechanisms have been proposed in other locations for Perna perna . Significant heterozygote deficits observed in some sampling sites might be a microevolutionary consequence of founder events as the founder population generally represent a small proportion of the genetic variation from a larger source population Mayr, . Under tAcropora spicifera, Houtman Abrolhos Islands ; data curation (lead); formal analysis (lead); funding acquisition (supporting); investigation ; methodology ; project administration (supporting); resources ; software ; supervision (supporting); validation ; visualization ; writing – original draft ; writing – review and editing . Kor Jent van Dijk: Investigation (supporting); methodology (supporting); resources (supporting); software (supporting); supervision (supporting); writing – review and editing (supporting). Gary Andrew Kendrick: Conceptualization (supporting); investigation (supporting); supervision (supporting); writing – review and editing (supporting). Ming Feng: Formal analysis (supporting); methodology (supporting); resources (supporting); validation (supporting); writing – review and editing (supporting). Oliver Berry: Conceptualization (supporting); formal analysis (supporting); investigation (supporting); methodology (supporting); resources (supporting); writing – review and editing (supporting). Christopher Kavazos: Formal analysis (supporting); writing – review and editing (supporting). Kathryn McMahon: Conceptualization (lead); data curation ; formal analysis ; funding acquisition (lead); investigation ; methodology ; project administration (lead); resources (lead); software ; supervision (lead); validation ; visualization ; writing – original draft ; writing – review and editing .None declared.Figure S1Click here for additional data file.Appendix S1Click here for additional data file.


Toxoplasma gondii is a zoonotic and foodborne intracellular parasite capable of inducing congenital infections, stillbirths and abortions in humans and animals, globally. The consumption of undercooked or raw mutton is “one of the vital risks” for acquiring toxoplasmosis: an asymptomatic condition in healthy persons, while life-threatening in immunodeficient individuals like "HIV/AIDS" patients.T. gondii infection in sheep.The current study has multiple objectives: to optimize a newly ELISA kit for Sheep, to find out the seroprevalence of ovine toxoplasmosis of two ecological zones of the Punjab, Pakistan through LAT and newly Optimized Sheep ELISA kit, to do the comparison of efficacies of various tests  and to determine the different meteorological parameters as the risk factors for A cross-sectional study was conducted on 400 sheep sera, 200 were collected from sheep raised on open grazing system by local farmers in the adjoining areas of Civil Veterinary Dispensaries (CVDs) of range-ecological zone i.e. tehsil Kot Chutta (Dera Ghazi khan). Similarly, the remaining 200 were collected from agro-ecological zone i.e. tehsil Sharaqpur (Sheikhupura), to evaluate the comparative efficacy of LAT with optimized ELISA kit and newly optimized ELISA kit with commercial ELISA kit.The newly ELISA kit optimized against a commercial ELISA kit was found to have 100% sensitivity, 97.6% specificity with 98% Positive Predictive Value, 100% Negative Predictive Value, Cut off value = 0.505, 28.28 LR+, 0.0104 LR-, and 2719.23 DOR. Seroprevalence of toxoplasmosis was detected significantly  higher in Sharaqpur  as compared to that in Kot Chutta . The highest seroprevalence was seen in the sheep of the 1–2 years age group , whereas the lowest in the oldest animals (≥ 4 years). Investigation of meteorological data of both the regions reveals that the zone with higher seroprevalence has relatively higher rainfall, higher humidity, lower environmental temperatures, and higher altitude as the critical factors, potentially behind the significant difference seen in seroprevalence level. The partial correlation of both tests (newly optimized ELISA kit and LAT) was 0.991 at maximum temperature in Sharaqpur while it was 0.981 in Kot Chutta.A novel significant correlation was found between the meteorological parameters  divided into yearly units of both the ecological zones, and year-wise seroprevalence (birth years of age-wise groups) of the corresponding regions. We hypothesize that such environmental conditions increase the risk of toxoplasmosis in grazing sheep, owing to a more favorable environment for coccidian oocyst survival. The ELISA kit optimized in this study will be helpful for the detection of seroprevalence of ovine toxoplasmosis in other ecological zones of Pakistan as well as of any other country in the world. More studies are recommended involving regions from other ecological zones of Pakistan to further explore the seroprevalence of ovine toxoplasmosis and to ratify the novel correlation of meteorological parameters with seroprevalence. Toxoplasma gondii can be transmitted by consumption of raw or undercooked meat  was found significantly higher as compared to other age groups  in both the zones . The meteorological parameters plotted in The Area of Under Curve (AUC) and a cut-off value of optimized ELISA were calculated by ROC as was determined in a previous study . In the The new optimized ELISA kit was developed using a recombinant form of Toxoplasma’s surface antigen-1 (rSAG1). The methodology was the same as reported earlier, with minor modifications (46). Thus, the rSAG1 in the optimized ELISA kit was employed @ 0.125μg/mL for coating of ELISA plate. The high accuracy at this low concentration is an advantage in terms of the economical use of this recombinant protein for coating ELISA plates. The optimum dilution of sheep serum for use in an optimized ELISA kit was 1/1600. This value was determined by studying all the 90 samples used for optimization. Similarly, the optimum duration for reading OD values after the addition of substrate was determined as 05 min based on data obtained from comparing OD values of 90 samples, read at various time intervals, i.e., 05 min., 10 min., 15 min., and 20 min. Subsequently, a secondary antibody was found to show optimum effect at a dilution of 1/10,000, lower than the dilution used previously for developing an ELISA kit of human toxoplasmosis . The secCommercial ELISA is a benchmark and is a confessed accurate serodiagnostic method for conducting Toxoplasma surveillance in various animals like sheep, goats, and bovines . The comT. gondii in sheep and goats reported from the various regions of Iran also falls in the close range, i.e., 24.5% and 33.3%, respectively [LAT and optimized ELISA kits revealed 42% (168/400) and 33.25% (133/400) samples as seropositive for toxoplasmosis, respectively, with significantly higher seropositivity in the Sharaqpur as compared to Kot Chutta. The seroprevalence determined through the optimized ELISA kit was lower than that observed by LAT. This difference can be expected as there can be several factors behind this difference. LAT is known to produce false positive results –51. In aectively ,55.T. gondii. Sheep constitute the common source of meat production in Kot Chutta (Dera Ghazi Khan) and Sharaqpur (Sheikhupura), as in the rest of Pakistan. The consumption of undercooked or raw mutton sheep is one of the major risk factors for toxoplasmosis [n = 200; Sharaqpur: n = 200), were scanned serologically for T. gondii-specific antibodies. Significantly higher seroprevalence  was detected in Sharaqpur as against that  in Kot Chutta . Analysis of meteorological data from both the regions points towards the high rainfall, low environmental temperatures, and high altitude as the important factors behind the significant difference in seroprevalence level, and thus potentially behind the enhanced risk of toxoplasmosis to grazing sheep, owing to a more favorable coccidian oocyst-survival in Sharaqpur. Sharaqpur is a greenish area located at a higher latitude (31°27’36.33°N), at a higher elevation from sea level (203.911m), with higher average rainfall (19.72mm) as compared to Kot Chutta, is a plain area, at a lower latitude (29°53’7.6128°N), at a lower elevation from sea level (112m), with lower average rainfall (10.41mm).The humid and temperate climate is considered one of the most common and important factors in the high prevalence of lasmosis . Kot ChuT. gondii was found relatively less in males as compared to female animals- and this is true in the case of detection through both techniques, i.e., LAT and optimized ELISA kit, as well as for both the regions. Higher susceptibility of female animals to protozoan parasites as compared to male ones has already been reported in the literature [The seroprevalence of terature ,57–59. Iterature ,60.Another interesting finding of the current study is that the highest seroprevalence was found in the animals having an age of 1–2 years whereas the lowest seroprevalence was seen in the oldest animals i.e., the animals aged more than 4 years. This was true for both the geographical regions as well as through both the diagnostic techniques compared in the study. This high rate of prevalence in animals aging 1–2 years points towards the higher susceptibility of this particular age group of sheep to toxoplasmosis on one hand whereas it may also indicate the availability of more favourable environmental factors in the birth year of this age-group as well as in the years following their birth year. For this aspect, there is a need to further explore the meteorological data to find out more specific explanation for this phenomenon as this particular age group in sheep, makes the significant part of animals meant for mutton production.LAT revealed a higher seroprevalence of toxoplasmosis in sheep samples from both the regions tested  as compared to the values detected through optimized ELISA .One crucial point is that through LAT, the highest seroprevalence was found in the age group 1–2 years, whereas 3.5 times less seroprevalence was seen in the age group 3–4 years in Kot Chutta. Normally, we consider that the seroprevalence of toxoplasmosis in all age groups of sheep are alike without involvement of environmental factors. As the cur-rent study assumed the involvement of environmental factors having significant impact, the difference of seroprevalence found among the various age groups of sheep, could be because of this effect. Subsequently, among these different age groups, 1–2 years age group was found more prone to get the infection of toxoplasmosis probably due to conducive environment for parasite-survival in their birth year.T. gondii infection [LAT is used as an initial screening test for identification of toxoplasmosis, having relatively less sensitivity and specificity  as companfection .LAT is not considered a substantative test regarding the diagnosis of toxoplasmosis ,63. The T. gondii infection was higher in Sharaqpur (Sheikhupura) than in Kot Chutta (D.G. Khan). In a study, Bastiaan G. et al. (2009) described that environmental factors usually affect the prevalence of toxoplasmosis. Three different effects on T. gondii were identified: (1) the survival of the pathogen affected by environmental changes; (2) due to in-creased rain or snow, sporulated oocysts dispersed throughout the environment; and (3) climate change influenced the ecology of hosts (transport). Environmental conditions are essential for the survival of oocysts. Worldwide, the prevalence of toxoplasmosis is high in tropical and humid areas and low in dry and hot areas [It is known that toxoplasmosis in animals can occur by eating infective oocysts from the environment ,65; hencot areas . Accordiot areas . That maT. gondii contaminates the environment in the more greenish area like Sharaqpur, enhancing the opportunity of sheep getting infected during grazing. Similar findings have been seen in Guilan province, Iran, in a study performed by Chaechi Nosrati et al. (2020) and in Nepal by Subedi et al. on sheep [In the extensive grazing system of sheep, the presence of wild and domestic felines spreading oocysts of on sheep ,56. Suchon sheep . In the In this study, no connection was found between health status and seropositivity of toxoplasmosis in sheep. All the seropositive animals displayed satisfactory health status and looked normal.A newly optimized ELISA kit is highly effective in determining the seroprevalence of Toxoplasma in sheep. A high prevalence of ovine toxoplasmosis in Sharaqpur observed in this study appears to be related to the region’s high rainfall, high elevation, and high humidity. A novel significant correlation was found between the meteorological parameters  divided into yearly units of both the ecological zones with year-wise seroprevalence (based on the birth years of age-wise groups) of the corresponding regions. Due to favorable climatic conditions, the environmental survival of Toxoplasma is assumed to be higher in the Sharaqpur region than in Kot Chutta region. The higher seroprevalence of ovine toxoplasmosis in sheep of Sharaqpur, as compared to that in Kot Chutta, strengthens this hypothesis.Newly ELISA kit was optimized through commercial ELISA kit by the evaluation of 90 sheep sera. Newly optimized ELISA kit (named as Sheep Toxo IgG ELISA kit) has 100% sensitivity, 97.6% specificity, 98% PPV, 100% NPV, 28.28 LR+, 0.0104 LR-, and 2719.23 DOR. Seroprevalence of ovine toxoplasmosis was detected higher in agro-ecological zone  than range-ecological zone . Highest seroprevalence was seen in age group of 1–2 years and the lowest in (≥ 4 years). As compared to the efficacies of LAT and commercial ELISA kit, newly optimized ELISA kit showed better results. Newly optimized ELISA kit (named as Sheep Toxo IgG ELISA kit) has 100% sensitivity, 97.6% specificity, 98% PPV, 100% NPV, 28.28 LR+, 0.0104 LR-, and 2719.23 DOR. Sheep Toxo IgG ELISA kit has been evidenced in the current study as more reliable and well-founded immunodiagnostic kit as compared to LAT. The seroprevalence of ovine toxoplasmosis in Sharaqpur and Kot Chutta was found having a significant relationship with the meteorological parameters (positive correlation with relative humidity and negative correlation with temperature). Further studies should be done in other parts of the world involving other ecological zones to ratify the relationship of ovine toxoplasmosis to meteorological parameters.S1 File(ZIP)Click here for additional data file.


ND4 and Cytb) and ecological niche modeling (ENM) to explore how the Quaternary climatic fluctuations and complex geography in Northwest China have shaped genetic diversity, genetic structure, and demographic history of the Alashan pit viper (Gloydius cognatus). Our results clearly show that the lineage diversification of G. cognatus is related to the expansions of deserts and/or the early Pleistocene integration of the Yellow River. The strong spatial genetic structure fits an isolation-by-distance model. The signature of demographic and range contractions during the last glacial maximum (LGM) is rejected by both mitochondrial evidence and ENM. In addition, the suitable habitat of G. cognatus is predicted to be decreased in the future, suggesting that conservation and management of evolutionary significant units (ESUs) should be a priority. Our findings provide the first insights on the evolutionary history of G. cognatus in arid Northwest China and adjacent areas throughout the Quaternary.Northwest China is characterized by unique geological and historical dynamics and endemic biota, but the joint influence of geography and past climate changes on the evolutionary history of endemic animals is poorly understood. We used two mtDNA genes  in 27 individuals representing 24 populations, the spatial genetic structure and demographic history of G. cognatus were examined across its geographic range. Phylogenetic analyses revealed two well-supported allopatric clades (each with two distinct subclades/lineages), distributed across the southern  and northern  regions. AMOVA analysis demonstrated that over 76% of the observed genetic variation was related to these lineage splits, indicating substantial genetic differentiation among the four lineages. A strong pattern of isolation-by-distance across the sampling populations suggested that geographic distance principally shaped the genetic structure. The four lineages diverged by 0.9–2.2% for the concatenated data, which were estimated to have coalesced ~1.17 million years ago (Mya), suggesting that the expansions of the Badain Jaran, Tengger, and Mu Us deserts during the Xixiabangma glaciation likely interrupted gene flow and triggered the observed divergence in the southern and northern regions. Subsequently, the early Pleistocene integration of the Yellow River and associated deserts expansion promoted the differentiation of S1 and S2 lineages (~0.9 Mya). Both mitochondrial evidence and ecological niche modeling (ENM) reject the signature of demographic and range contractions during the LGM for G. cognatus. In addition, ENM predicts that the suitable habitat of G. cognatus will contract in the future. As such, the conservation and management of ESUs should be a priority. Our findings provide the first insights on the lineage diversification and population dynamics of the Alashan pit viper in relation to geological history and Pleistocene climatic oscillations in arid Northwest China.The joint impacts of historical geological events and Quaternary climatic oscillations in Northwest China on species evolution have been examined extensively in plant under a phylogeographic perspective. However, animal phylogeographic analyses in this region are still limited. The Alashan pit viper,  Phylogeography may be the most useful tool for interpreting species responses to Quaternary climate changes from a genetic perspective. However, our current knowledge of Asian biogeography lags behind that of other regions, such as Europe and the Americas ,2,3,4. TMeanwhile, in recent years, phylogeographic studies in arid Northwest China have increased and mainly focus on the impact of the Quaternary climate fluctuations on species’ phylogeographic patterns, e.g., ,12,13,14Evidence from pollen records indicates that glaciation effects were not significant in the desert regions of Northwest China during the Quaternary . HoweverGloydius halys–G. intermedius species complex is a group of pit vipers widely distributed in the Palaearctic with 23 rows mid-back scales, which consists of 9 taxa of the Crotalinae subfamily (Viperidae family), including G. halys, G. cognatus, G. caucasicus, G. caraganus, G. stejnegeri, G. rickmersi, G. shedaoensis, G. changaoensis, and G. intermedius [G. caucasicus) has been elevated recently to species rank based on phylogeographic analyses and its four documented evolutionary significant units (ESUs) [G. rickmersi) was recently discovered and described from previously unnamed populations within this group in the strangest place from Kyrgyzstan [The ermedius ,34. Thesermedius ,36,37. Aermedius ,43,44,45s (ESUs) ; the AlaG. cognatus, was previously regarded as a synonym of Gloydius brevicaudus [G. halys [G. cognatus, was revalidated as a separate species by Shi et al. [G. halys–G. intermedius species complex in northern China were identified as G. intermedius [G. intermedius” represented three subspecies of G. halys, and elevated two of them to full species, namely G. cognatus and G. stejnegeri. According to Shi et al. [G. cognatus is mainly distributed in the vast desert or desertification grassland in Mongolia and Northwest China, and lives at an altitude of more than 1300 m or even more than 3000 m, thus, serving as an ideal species to evaluate the phylogeographic patterns of poikilotherm species in Northwest China and adjacent regions. Nevertheless, the genetic structure and evolutionary history of G. cognatus have not been rigorously investigated due in part to very limited sample size in previous studies [In the meantime, it should be noted that the Alashan pit viper, vicaudus  or a subG. halys ,47,48. Ti et al. , and itsi et al. . Historiermedius ,50. Throermedius  found thi et al. , G. cogn studies ,43. The To complement genetic analysis, ecological niche modelling (ENM) constitutes a powerful set of tools for investigating organisms’ evolutionary patterns and processes , since tG. cognatus across its distribution range. Specifically, we aimed to (i) document the phylogeographic structure and the timing of genetic diversification within the Alashan pit viper; (ii) to evaluate the correlation between genetic distance, geographic distance, and environmental distance; (iii) to explore the relationship between historical demographic changes and past climate fluctuations.In this study, through the combination of phylogeographic and ecological niche modeling analyses, we attempted to infer the spatial genetic structure and trace the population history of G. cognatus coming from 24 localities. Among them, there were 13 new collected individuals from localities in northwestern China, southeastern Kazakhstan, and Mongolia; information from the other 14 individuals from 12 localities was also retrieved from previous studies [G. halys collected from Mongolia was also included in this study as an outgroup. Based on the topography and landscape, we categorized the sampled sites a priori into seven geographic units: Ily Basin (IB), Junggar Basin (JB), Mongolian Plateau (MP), Qaidam Basin (QB), Lanzhou Basin (LB), Loess Plateau (LP), and Zoige Basin (ZB). Herein, MP is divided politically and geographically by the Gobi (desert) into the independent state of Mongolia  in the north and the Inner Mongolia Autonomous Region of China in the south. Pit vipers were identified via morphological determination following the classification system of Shi et al. [G. cognatus and especially the data from Shi et al. [ND4) and cytochrome b (Cytb) genes in this study. A detailed list of information about all specimens is provided in G. cognatus, with voucher numbers of GXG2728 and GXG3335, from the Cha’gan’guole village  in Qinghe County, Xinjiang, China  fragments of the ND4 gene were targeted for sequencing with the primers ND4/Leu [Cytb gene were targeted for sequencing using the primers LAM2N/HAM [ND4 and 50.8 °C for Cytb, 54 s of elongation at 72 °C, and a final extension of 10 min at 72 °C. Amplified products were visualized on 1% agarose gels and were sequenced for double strands after being commercially purified by Sangon Biotech  using the same primers as used for the PCR. Chromatograms, including sense and antisense, were edited and assembled using the SeqManII in DNASTAR 5.0  to obtain a single consensus sequence. All novel sequences were deposited in GenBank under accession numbers OR513115–OR513142  for 13 novel samples of G. halys . We ampl ND4/Leu . A totalAM2N/HAM . The PCROR513142 .Cytb, 65 for ND4) were considered in this study, including 28 generated in this study and 107 available from previous studies, accessible in GenBank , of which 301 are parsimony informative, with 126 in ND4 and 175 in Cytb.A total of 135 sequences  and maximum likelihood (ML) with partitioned models to infer phylogenetic trees and assess nodal support. Based on the study of Shi et al. [G. monticola and G. liupanensis were selected as the outgroup taxa  for each clade (with the number of samples > 3) with the concatenated mtDNA dataset. To evaluate if significant genetic differentiation and genetic structure exist among lineages of G. cognatus, we used Arlequin v3.5.2.2 [Fst) among lineages, and we used MEGA to calculate the average genetic distance between lineages and within lineage with uncorrected p-distance. To estimate the source and significance of genetic variation, AMOVA analysis was conducted in Arlequin with three grouping strategies: (i) two groups based on North and South clades; (ii) three groups based on the northern clade, S1, and S2; (iii) four groups according to each lineage.We used DNAsp v5.10  to calcuv3.5.2.2  to calcuG. cognatus. Pairwise genetic distances (p-distances) between sampling sites with precise location coordinates ) [To assess the relative contributions of geography and environment to the population differentiation, isolation-by-distance (IBD)  and isolt 2022)) . The biot 2022)) . The relt 2022)) . MeanwhiND4 and Cytb were retrieved from GenBank . We then compiled the dataset to date the most recent common ancestor (MRCA) of G. cognatus. PartitionFinder was used to select the best partition and evolutionary models in our analysis based on AICc. Following Asadi et al. [Gloydius: (i) the divergence of three populations of the genus Porthidium in South America, some 3.5 million years ago (Mya), using a normal distribution model , (ii) the divergence between Crotalus and Sistrurus before 9 Mya, using a lognormal prior model with a zero offset of 9 Mya , and, finally, (iii) the divergence of the Eurasian vipers clade  about 20 Mya, as suggested by fossil data, using a lognormal prior model with a zero offset of 17 Mya . Clock models and trees were linked, and a relaxed lognormal clock and birth–death process were implemented. In the second step, all sequences of G. cognatus were used to estimate the coalescent time of internal lineages according to the above age estimate for its MRCA : 0.68–1.67 Mya), set as a normal distribution model . A relaxed lognormal clock and constant-size coalescent tree prior were adopted. We performed 10 million generations of MCMC chain and sampled every 1000 generations. Models, prior settings, and parameters are listed in the To infer historical evolutionary processes, we used a Bayesian inference to estimate the time of divergence of major lineages using BEAST v1.8.4  on our c GenBank , which ii et al. , three cG. cognatus. First, we calculated the Tajima’s D [Fs [2R [p values with 10,000 simulated samples. These statistics have high power to detect population expansion for mtDNA under a variety of different circumstances, either when the sample size is large (Fs) or when the sample size is small (D), and the number of segregating sites is low (2R). Second, we used the ‘mismatch distribution’ function in Arlequin to draw mismatch distribution (MD) plot. We also estimated the sum of square deviations (SSD) and the Harpending’s raggedness index (Rg) as well as their respective p values with 10,000 bootstrap replicates to evaluate hypotheses concerning recent population growth for each clade. Third, to estimate the shape of population growth over time, we constructed Bayesian skyline plots (BSP) [We used three methods to infer variation in population size over time for the major clades of jima’s D , Fu’s Fs’s D [Fs , and R2  [Fs [R2  implements (BSP)  with BEAts (BSP) . We usedG. cognatus since the Pleistocene and until 2070, we conducted ENM using MaxEnt v3.4.1 [G. cognatus. We downloaded 19 climate variable factors for 5 different periods from the WorldClim database (http://www.worldclim.org) [To explore the impact of climate change on the potential distribution of t v3.4.1 . Maxent t v3.4.1 . Occurret v3.4.1 ,43. To rt v3.4.1  using SDt v3.4.1  in ArcGIt v3.4.1 ,89. The lim.org) : the conlim.org)  in ArcGIlim.org)  in R to lim.org) . This anlim.org) . Negativlim.org) . The areG. halys, while the remaining 12 samples were allied to G. cognatus. All samples of G. cognatus formed a monophyletic group  comprising two allopatric clades (North and South) with strong support. The samples in the well-supported Clade South  consisted of two allopatric subclades (phylogroups/lineages): S1 across the Qaidam, Lanzhou, and Zoige basins; S2 across the Chinese Loess Plateau . The well-supported Clade North  was also composed of two allopatric subclades/lineages: N1 covered the Ili Basin in Xinjiang and southeast Kazakhstan, while N2 contained the Junggar Basin and Mongolian Plateau (Inner Mongolia and West Mongolia). Overall, the four lineages corresponded to well-defined geographic regions, and no haplotype was shared among the different geographic regions.The tree topology was similar for the BI and ML analyses, and both indicated that pit vipers of the complex formed well-differentiated clades with high support values of PP and UFBoot, respectively . As expeG. cognatus, we analyzed our dataset, using the coalescent-based statistical parsimony network approach. As shown in To obtain additional insight into the relationships among the individuals of G. cognatus harbors high haplotype diversity (0.9767) and low nucleotide diversity (0.01427)  . NucleotFst values among the four lineages ranged from 0.616 (S1 and S2) to 0.809 (S1 and N2) (p < 0.01), indicating significantly high genetic differentiation, as well as a low genetic divergence among the four lineages  . The siglineages , with a Fct between groups accounted for the largest variation .The results of AMOVA are shown in the R² = 0.2438, p = 0.001), in accordance with the IBD pattern. The partial Mantel test showed that when the geographical barrier (Tianshan and Qilian mountains) was controlled, the genetic distance was significantly correlated with the geographic distance . When geographic distance was controlled, genetic distance had no significant correlation with the geographic barrier , which revealed that geographic barriers may have little effect on the genetic differentiation of G. cognatus.The results of the IBD and IBE analysis are shown in the R² = 0.1548, p > 0.05). A partial Mantel test showed that when environmental distance was controlled, genetic distance and geographic distance were significantly correlated . When geographic distance was controlled, the correlation between genetic distance and environmental distance was not significant . The results revealed that geographic distance played a greater role in the genetic differentiation of G. cognatus than environmental distance.The result of the Mantel test for the IBE  indicateG. cognatus separated from other species of the G. halys–G. intermedius complex in the early Pleistocene  . Accordingly, divergence between Clade South and Clade North commenced at ~1.17 Mya. After that, splits occurred within these two clades. The divergence between S1 and S2 lineages happened at 0.9 Mya (95% HPD: 0.49–1.39 Mya), and then the divergence between N1 and N2 lineages occurred at 0.59 Mya (95% HPD: 0.25–0.97 Mya) during the mid-Pleistocene.Our molecular dating analyses revealed that .99 Mya) . As show2R albeit with different results for Tajima’s D and Fu’s Fs , and one precipitation variable, precipitation of coldest quarter , were the variables that most contributed to the distribution of the species . This inG. cognatus is mainly in the arid region in Northwest China, with a small amount in Kazakhstan and Mongolia, generally between the QTP and the Altay Mountains, which is overall consistent with the sample collection information. The total highly suitable habitat area (HSHA) is 8.58 × 105 km2. During the LIG, the analysis did not support the existence of regions with a probability of distribution greater than 0.6 for G. cognatus , falling within the time frame of the boundary of Xixiabangma glaciation and the maximum glaciation , with the latter corresponding to MIS 14–18. During the maximum glaciation, there were two large cold periods in the Zoige Basin, which can be compared with the two glacial stages of Naynayxungla of Mt. Xixiabangma Region in the Himalayas . Based oSubsequent differentiation of the N1 and N2 lineages was dated to ~0.59 Mya (95% HPD: 0.25–0.97 Mya), falling with the time frame of the Naynayxungla glaciation. Lineage N2 comprises the samples from the Junggar Basin and Mongolian Plateau. As we know, the Junggar Basin is located in northern Xinjiang, and it includes Chinese and Mongolian parts, while the latter is restricted to the Barun-Khure Basin. On the one hand, the Junggar Basin is bounded by Dzungarian Alatau, Tarbagatay, and Saur mountains at the west, Tianshan Mountains at the south, and Altay Mountains at the north. On the other hand, there is one passage connecting it with arid areas of northern China and southern Mongolia (eastern). Thus, pit vipers could migrate between the Junggar Basin and adjacent areas despite the partial isolation of this region by mountains.Eremias arguta) from Bole  is phylogenetically nested within the Ily Basin group, belonging to an undescribed subspecies of E. arguta [The divergence of the N1 lineage may be associated with the long-standing (since the Late Pliocene) isolated position of the Ily Basin due to mountainous surroundings and a specific relatively temperate semi-arid climate, dominated by the penetration of westerly winds . Moreove. arguta . This fiFct = 55.92% or 74.57%) and significant (p < 0.001) portion of the genetic variance among the two clades or four lineages (Fst) between the main evolutionary lineages ranges from 0.616 to 0.809  glacial period on the QTP during the Quaternary. Slight expansion instead of shrinkage occurred for G. cognatus in the penultimate glaciation  by the International Union for Conservation of Nature (IUCN), and little attention has been paid to the conservation of other species. The results presented in this study provide a framework for designing proper conservation and management guidelines for the Alashan pit viper populations. The analyses of mtDNA sequences of the Alashan pit viper suggest the existence of two geographically structured mitochondrial clades, with two subclades/lineages recognized in each clade. The pairwise genetic distance between the four lineages within G. cognatus . The plausible strategy to conserve the genetic diversity of G. cognatus is to protect the unique ecosystem of stony gravel habitats; the establishment of desert nature reserves may be one of the best solutions. In the meantime, G. cognatus is one of the well-known venomous snakes that causes livestock damage in northwestern China. It has been reported that the LD50 of G. cognatus  from Xinyuan County in Xinjiang to mice is 0.38 mg/kg [G. cognatus is recognized as the most toxic species of Gloydius in China. Thus, the conflict between G. cognatus and herdsmen should also be considered when implementing the protection strategy. Reasonable planning of the range of pastoral areas and management of grazing is necessary to reduce the casualties and damages caused by contact between herdsmen and G. cognatus.It has been documented that various pit vipers of the habitats ,50, and 38 mg/kg , and G. G. cognatus, with the recognition of two major clades in northern and southern regions, as well as four distinct lineages distributed in different geographic landscapes. Significant genetic differentiation dominated by geographic distance exists between the four lineages. The divergence between the southern and northern clades is likely triggered by the expansions of the Badain Jaran, Tengger, and Mu Us deserts during the Xixiabangma glaciation in China. Both mtDNA evidence and ENM reject the signature of demographic and range contractions during the LGM for G. cognatus. The ENM also supports that the suitable habitat of G. cognatus will contract and be concentrated in the Junggar Basin in the future. Thus, plausible conservation measures should be undertaken in a timely manner. We recall that our study is based on only mtDNA fragments and inadequate samples, and future studies should undoubtedly focus on population genomics with more extensive sampling and sophisticated analyses.This study explores for the first time the genetic differentiation within