F1 hybrid varieties with higher performance, a phenomenon known as heterosis. The inability to fully exploit heterosis in outcrossing grasses is partially responsible for lower levels of improvement in breeding programmes compared with inbred crops. However, SI can be overcome in forage grasses to create self-compatible populations. This is generating interest in understanding the genetical basis of self-compatibility (SC), its significance for reproductive strategies and its exploitation for crop improvement, especially in the context of F1 hybrid breeding.Self-incompatibility (SI) systems prevent self-fertilization in several species of Poaceae, many of which are economically important forage, bioenergy and turf grasses. Self-incompatibility ensures cross-pollination and genetic diversity but restricts the ability to fix useful genetic variation. In most inbred crops it is possible to develop high-performing homozygous parental lines by self-pollination, which then enables the creation of Lolium–Festuca complex and the use of SC to develop immortalized mapping populations for the dissection of a wide range of agronomically important traits. The germplasm available is a valuable practical resource and will aid understanding the basis of inbreeding depression and hybrid vigour in key temperate forage grass species.We review the literature on SI and SC in outcrossing grass species. We review the currently available genomic tools and approaches used to discover and characterize novel SC sources. We discuss opportunities barely explored for outcrossing grasses that SC facilitates. Specifically, we discuss strategies for wide SC introgression in the context of the A better understanding of the genetic control of additional SC loci offers new insight into SI systems, their evolutionary origins and their reproductive significance. Heterozygous outcrossing grass species that can be readily selfed facilitate studies of heterosis. Moreover, SC introduction into a range of grass species will enable heterosis to be exploited in innovative ways in genetic improvement programmes. S locus containing at least two tightly linked genes, encoding the male and female-specific SI determinants that mediate the self/non-self-pollen recognition. If the S alleles carried by the pollen and pistil match, the pollen is recognized as ‘self’, thus preventing self-fertilization and the resulting inbreeding.Self-incompatibility (SI) is the most widespread mechanism for promoting outcrossing in hermaphrodite flowering plants. Described by Charles Darwin as ‘the ability of some plants to reject their own pollen’, SI is considered the mating system of ancestral angiosperms . The firThe breakdown of SI caused a change from outcrossing to self-fertilization in the evolutionary history of many flowering plants , genetic mapping studies employ highly heterozygous pseudo-F1 or pseudo-F2 populations that need to be maintained clonally. This is labour-intensive and potentially compromises the genetic integrity of the population over time.Thus, genetic mapping and dissection of agronomic traits have been useful strategies for the development of targeted approaches to DNA marker trait selection in many inbred crops by developing durable immortalized inbred line-based genetic resources. These include recombinant inbred lines (RILs) produced through recurrent rounds of inbreeding . These pSeveral self-incompatible species of the Poaceae are economically valuable forage crops and represent a fundamental component in many ruminant production systems. Self-incompatibility has acted as a barrier to their improvement and forage yield advances in breeding have been small . CurrentThe need to accelerate breeding progress in forage grasses for traits such as biomass and seed yield, nutritional quality and disease resistance is stimulating grass breeders to develop hybrid breeding technologies as an alternative to recurrent population selection strategies. For this reason, overcoming SI and exploiting SC to breed forage grasses as an inbred line-based crop is gaining interest  or in tapetal cells . In a self-pollination event, the products of male and female determinants interact with each other and trigger the pollen inhibition response that leads to SI  (Beta vulgaris) (Lilium martagon)   and fourartagon) . Of thesS and Z, which are located on chromosomes 1 and 2, respectively    containing the DUF247 domain of unknown function appeared to be the most likely candidate for the pollen SI determinant as it possessed the high level of allelic variability expected of an SI determinant gene affected by frequency-dependent selection   and rye cereale) , later bL. perenne Z locus. Two genes were identified as plausible candidates for either the pollen or stigma determinants. Interestingly, one of these was a gene encoding a protein containing a DUF247 domain (LpDUF247) similar to the S locus-linked LpSDUF247 gene, with the other candidate gene encoding either a putative tetratricopeptide repeat-like domain-containing protein or a ubiquitin-specific protease (LpTC116908). These findings lend support to a hypothesis put forward by LpSDUF247 have also been identified in other grass species, such as wild rice (Oryza barthii) and sorghum (Sorghum bicolor), suggesting that this gene could function as an SI determinant throughout the Poaceae (2+) signalling and protein phosphorylation are involved in the recognition and/or inhibition of incompatible pollen. Two independent expression studies found that transcripts predicted to code for proteins containing calcium-binding domains were enriched during the SI response in L. perenne and in sheepgrass (Leymus chinensis) , a naturally self-compatible species. By analysing SC segregation in backcrossing generations of L. temulentum–L. perenne and L. temulentum–annual ryegrass (Lolium multiflorum) interspecific hybrids, Z locus. This was inferred from distorted segregation of the GOT/3 isozyme locus in selfed progeny of first-generation backcross plants. Information available at the time showed that the GOT/3 locus was not linked to the S locus and therefore distorted segregation was inferred to have been associated with the Z locus. Later, linkage mapping experiments located the GOT/3 locus on linkage group (LG) 3  (Arabidopsis lyrata (Identifying sources of SC is more effective with the advent of next-generation sequencing (NGS)-based technologies and reference genome assemblies of grass species . Performin vitro self-pollination to phenotype SC with high resolution and accuracy  (Zea mays) (Pisum sativum) (Solanum lycopersicum) (Hordeum vulgare)  offers a high-throughput screening of point mutations at genes of interest in populations mutagenized by chemical treatment  proceed to the next generation. Rounds of recurrent phenotypic selection are made to gradually increase performance and at the same time populations are tested for uniformity. When the desired levels of performance and uniformity are reached the population is then intermated in isolation from possible contaminant pollen from outside sources for several generations to produce commercial quantities of seed. Levels of genetic improvement in forage grass yield have been noticeably modest in comparison with other crops ((Z. mays . RegardlL. perenne (Panicum virgatum)   and otheirgatum) . These aF1 hybrid breeding strategies by producing elite homozygous parental lines capturing favourable genetic diversity. These lines can be crossed for testing heterotic combinations to maximize combining ability in F1 hybrids. Although the challenges are considerable, the transition from populations to inbred line-based F1 hybrid breeding is gaining traction , overcoming inbreeding depression by incorporating SC in selected germplasm is feasible and provides the possibility of creating novel, valuable inbred germplasm for F1 hybrid breeding . For effective exploitation of SC in breeding programmes it is crucial that a broad base of self-compatible germplasm is available. Introgressing SC within the Lolium genus would present little difficulty because all species have the same ploidy level (2n = 2x = 14) and show high levels of homoeologous chromosome pairing in interspecific hybrid offspring  autopolyploids, exhibit an effective SI system and transfer of SC into a range of inter-fertile polyploid Lolium and Festuca species and hybrids could be proposed. For SC to be expressed in grass polyploids, introgressing SC into polyploid germplasm is a necessity and offers potential advantages over self-compatible diploid counterparts. For instance, theory predicts that polyploidy reduces the effect of the inbreeding depression that inevitably arises after repeated selfing of highly heterozygous plants (n = 2x = 28) L. perenne the source of SC on LG 5 is functional  complex produce viable inter-generic hybrids (× Festulolium) that are of increasing interest to farmers because of their inherent superior abiotic stress tolerance and adaptability to a range of climate change scenarios  is straightforward and natural hybrids are commonly found where the species are sympatric. Though previous reports have shown difficulties in producing seeds in sufficient quantity from the interspecific hybrids between L. perenne and F. pratensis, embryo rescue can increase the numbers of individuals recovered . Thus, the generic Lolium × Festuca hybrids, × Festulolium, provide a valuable target for transferring SC, especially as they display heterosis and reduced genetic load brought about by the combination of contrasting genomes  (Dactylis glomerata)  (Z. mays (Heterosis is a complex trait expressed through the action of multiple loci . In riceF1 hybrids exploiting genetic variation for hybrid vigour. Fundamental studies of the genetic basis of the heterosis that SC facilitates will be critical for targeted practical application. The systematic investigation of the agronomic performance of hybrids and the design of efficient seed production systems will be pivotal for efficient production of first-generation hybrid or pure-line cultivars. Afforded by SC mutations, research exploring heterosis in normally outcrossing species, with high levels of accumulated heterozygosity and genetic diversity, offers the prospect of contributing significantly to our understanding of heterosis currently gained from model species and self-fertile crops.Identifying and characterizing the basis of SC in grasses serves to provide a better understanding of the genes involved in the induction of SC, and knowledge of how SC arises in normally self-incompatible species can help biologists determine the pathways involved in the SI process in grasses. This offers insights into the evolutionary relationship of the grass SI system with other SI systems and, more widely, with other cell–cell recognition processes in living organisms. The subsequent exploitation of SC has the potential to promote more effective breeding methodologies based on the development of population or https://academic.oup.com/aob and consist of the following. Table S1: summary of published literature on SI breakdown to SC in flowering plants. References S1: references cited in Table S1.Supplementary data are available online at mcab043_suppl_Supplementary-Material-S01Click here for additional data file.mcab043_suppl_Supplementary-Material-S02Click here for additional data file.


Hucho taimen), the world’s largest freshwater salmonid, is threatened, endangered, or extirpated across much of its range due to anthropogenic activity including overfishing and habitat degradation. We generated genetic data using high throughput sequencing of reduced representation libraries for taimen from multiple drainages in Mongolia and Russia. Nucleotide diversity estimates were within the range documented in other salmonids, suggesting moderate diversity despite widespread population declines. Similar to other recent studies, our analyses revealed pronounced differentiation among the Arctic (Selenge) and Pacific (Amur and Tugur) drainages, suggesting historical isolation among these systems. However, we found evidence for finer-scale structure within the Pacific drainages, including unexpected differentiation between tributaries and the mainstem of the Tugur River. Differentiation across the Amur and Tugur basins together with coalescent-based demographic modeling suggests the ancestors of Tugur tributary taimen likely diverged in the eastern Amur basin, prior to eventual colonization of the Tugur basin. Our results suggest the potential for differentiation of taimen at different geographic scales, and suggest more thorough geographic and genomic sampling may be needed to inform conservation and management of this iconic salmonid.Population genetic analyses can evaluate how evolutionary processes shape diversity and inform conservation and management of imperiled species. Taimen ( Reduced representation approaches such as restriction site-associated DNA sequencing (RADseq) and genotyping-by-sequencing (GBS)3 have facilitated genome-wide population genetic analyses in organisms without genomic resources, and have often recovered patterns of fine-scale genetic structure and resolved patterns of recent diversification that were not evident with traditional molecular marker systems5. Such approaches have improved our understanding of patterns of population structure and connectivity7, the frequency and dynamics of hybridization9, and the potential for species response to environmental change11, and have guided the identification of conservation or management units13.Population genetic data is relevant for shaping conservation, restoration, and management activities, and for understanding the response of populations to environmental change. Modern high throughput sequencing technologies have enabled genome-wide perspectives and improved our ability to quantify genetic variation across populations, including those of conservation concern14, due to anthropogenic factors including aquaculture15, introduced species, habitat degradation, overfishing, and climate change18. Population genetic data have been central to understanding evolutionary history of sensitive salmonid populations20 and for guiding their conservation and management21. High throughput sequencing in salmonids has improved the delineation of evolutionarily significant units12 and the detection of introgression between introduced and native populations23, as well as identifying the genetic basis of adaptive phenotypes26. These perspectives, however, have mostly been limited to certain regions where substantial funding has been allocated to bolster fisheries conservation and management, such as the North American Pacific Northwest .Globally, many salmonid fishes have experienced sharp declines, especially in recent decades28. Still, headwater regions across Siberia and northern Mongolia host some of the world’s most pristine rivers and wetlands, receiving some of the highest ecological and chemical status ratings from the European Water Framework Directive standards . Here, in the remote headwaters of river basins, species including Siberian taimen (Hucho taimen), lenok (Brachymystax lenok and B. tumensis), grayling , and pike (Esox lucius and E. reichertii) are thought to be more abundant compared to other parts of northern Asia31, as there are fewer disturbances from hatcheries, large habitat modifications to the landscape , and dam development.In contrast, salmonids occurring in sparsely populated regions of northern Asia have received comparatively little research attention. Despite hosting some of the world’s most isolated aquatic ecosystems, and being among the least densely populated regions in the world, salmonid populations in this region are rapidly declining as a result of anthropogenic influences with cascading effects on riverine ecosystems33. Reaching up to 2 m in length and 100 kg in weight34, taimen reside in home ranges of large and variable size  with movements over 200 km recorded for tagged individuals in northern Mongolia , a characteristic that could limit the potential for spatial genetic differentiation. However, taimen form pair bonds from weeks to months before moving to spawning areas , and upon reaching an acceptable spawning area, a male will aggressively attack other males within a 20 m radius of the female37. Thus, the apparent monogamous nature of taimen spawning behavior, as well as the timing of pair bond formation, could potentially promote spatial genetic differentiation at some scales despite large movements.The taimen is the world’s largest salmonid, and one of the most ancient extant members of subfamily Salmoninae34. Similar to most of the world’s largest freshwater fish species38, taimen have been negatively affected by human activity and are listed as “Vulnerable” on the IUCN Red List39. Anthropogenic disturbances  have substantially decreased its native range, including putative extirpations of populations in the Volga, Ural, and Pechora River basins40. Further, large stretches of rivers in northern Mongolia have seen local extirpations associated with rapid increases in industrialization40. Consequently, taimen are listed as threatened or endangered in Mongolia, portions of Russia, Kazakhstan, and China28. Though experiencing population declines across much of its historic range, several of the remaining population strongholds exist in the rivers of northern Mongolia and Siberia31.Taimen were historically found from the west slope of the Ural Mountains in Eastern Europe to the Pacific Ocean in the east, to the Arctic Circle in the north and the Gobi Desert in southern Mongolia45. Variation across three mtDNA regions has shown substantial divergence between populations in different basins, with one distinct clade consisting of the Amur (Pacific) and Lena (Arctic) drainages and the other consisting of the Yenesei  and Khatanga (Arctic) drainages41. More recently, Marić et al.45 found two distinct haplogroups representing individuals from the (1) Lena and Amur basins and the (2) Volga (Caspian Sea outflow), Ob (Arctic), Yenesei (Arctic), and Khatanga (Arctic) basins. Kaus et al.46 used both mitochondrial and nuclear markers and found pronounced population differentiation between populations from the Amur basin (Pacific) and the Upper Yenesei (Arctic) and Selenge  basins with analyses identifying two ancestral genetic clusters that the authors suggested should be considered separate evolutionarily significant units (ESUs). Importantly, none of the aforementioned studies detected any evidence for genetic differentiation or isolation by distance within these large basins, perhaps suggesting that management plans should be implemented at the basin scale. While the lack of evidence for genetic structure across finer geographic scales within basins is consistent with the potential for large movement and population connectivity among river systems, it could alternatively reflect gaps in our understanding and sampling of taimen genetic variation.Understanding patterns of genetic diversity and differentiation among river systems and basins at different geographic scales will be critical for informing taimen conservation strategies. Previous research utilized mtDNA and microsatellite markers to illustrate broad phylogeographic relationships in taimen across its native range47) to characterize population genetic structure and diversity of taimen within and among several major river drainages in Mongolia and Russia. Specifically, we used single nucleotide polymorphism (SNP) data from multiple sampling sites within one Arctic and two Pacific drainages to (1) characterize levels of genetic differentiation among drainages, (2) evaluate the potential for fine-scale differentiation within drainages, and (3) quantify levels of genetic diversity across sampling sites. We additionally used coalescent-based demographic modeling to infer the demographic and historical context of divergence between two groups of taimen within one Pacific drainage for which we detected unanticipated genetic differentiation at smaller spatial scales. Our results shed further light on the evolutionary history of taimen and suggest the need for more thorough geographic and genomic sampling to facilitate the development of effective strategies for conservation and management.Here, we used high throughput sequencing of reduced representation libraries  and EcoRI (6-base recognition site). To the EcoRI cut-sites, we ligated Illumina adaptors embedded with unique 8–10 bp barcode sequences which were used to tag DNA from each individual. An Illumina sequencing adaptor was ligated to the MseI cut-sites. We then pooled the uniquely barcoded samples and amplified fragments using Illumina PCR primers. To reduce the portion of the genome sampled for sequencing, libraries were size selected for fragments ranging from 350 to 450 bp using a Pippin Prep unit  at the University of Texas Genome and Sequencing Analysis Center . Full details on the laboratory methods used for library preparation can be found in Ref.48 Size selected libraries were then sequenced on two lanes of an Illumina HiSeq 2500 at the University of Wisconsin-Madison Biotechnology Center’s Genome Center .We used a reduced representation approach based on two restriction endonucleases to generate ddRADseq libraries. DNA was digested with restriction endonucleases E. coli and PhiX, and for Illumina sequencing adaptors, using bowtie2_db49 and a pipeline of Perl and bash scripts (http://github.com/ncgr/tapioca). Importantly, barcode sequences all differed by a minimum of three bases, allowing us to detect one or two base sequencing errors within them. A custom Perl script (available at DRYAD doi: https://doi.org/10.5061/dryad.wstqjq2kd) was used to correct 1 or 2 bp sequencing errors in barcode sequences, remove barcodes and cut-site associated bases, and match sequences with individual sample names. Reads were then split into fastq files specific to each individual. We then removed individuals represented by volumes of sequencing data lower than the 1st quartile of the distribution spanning all samples to reduce the fraction of missing data and to increase the number of loci retained for analyses of a sufficient number of samples per sampled locality.Raw sequencing data was filtered for contaminant sequences including 50 to generate contig consensus sequences  built from clustering the unique sequences in our entire dataset with a minimum match percentage of 90%. This de novo clustering algorithm, also utilized by the commonly used RADseq pipeline dDocent51 was used to generate a partial reference to serve as a target for subsequent read mapping. We used bwa v0.7.552 to map sequences generated for each individual to the partial reference based on an edit distance of three. Sequence alignment map (.sam) files were converted to binary alignment map (.bam) files with samtools v1.353, before samtools v1.3 and bcftools v1.353 were used to identify and call variants across the alignments of all individuals. We calculated genotype likelihoods for SNPs at sites with a minimum base quality of 20, maximum coverage depth of 100, minimum map quality of 20, minimum site quality of 20, and minimum genotype quality of 10. We used vcftools v0.1.1454 to further filter called variants. We retained only bi-allelic SNPs with minor allele frequencies (MAF) greater than 0.04, and those where at least 60% of individuals had at least one read. We randomly sampled one SNP per 100 bp contig and discarded individuals with missing data at more than 30% of loci.Since we quantified substantial genetic differentiation among samples from the two major outflows  levels between 0 and 0.6, and read ratio deviance (D) between − 18 and 18. We took these steps to exclude potentially misassembled genomic regions representing duplicate or diverged duplicate loci.As mis-assembly of reads representing paralogous regions can lead to genotyping error in high throughput sequencing data57 which is based on the correlated allele frequency model of structure58. We used entropy to infer the number of k ancestral populations represented by the data and to estimate admixture proportions (q) for individuals. Importantly, this model accounts for statistical uncertainty arising from sequencing and alignment error and stochastic variation in coverage depth inherent in low to medium coverage sequencing data60. Because entropy provides posterior estimates of genotype probabilities at each locus for each individual, it allows for the incorporation of genotype uncertainty into downstream population genetic analyses. To seed and speed the convergence of Markov chain Monte Carlo runs, we first generated starting values for the q parameter. We conducted a principal component analysis (PCA) on the covariance matrix of genotype likelihoods calculated above using the prcomp function in R version 4.161 and then used k-means clustering and linear discriminant analyses (LDA) to estimate ancestry proportions for each individual for models representing k = 2 through k = 9 (or through k = 6 for the Pacific dataset). We ran entropy models for k = 2 through k = 9 (or k = 6) ancestral groups, with 5 replicate chains per k. We ran 100,000 MCMC iterations, retaining every tenth step after a burn-in of 30,000 steps. Model fit was assessed using the deviance information criterion (DIC), where lower DIC values represent better model fit. We conducted entropy runs separately for (1) the set of SNP genotype likelihoods for all individuals and (2) the subset of samples representing locations within the Pacific drainages. We used genotype probabilities from entropy for the majority of the population genetic analyses described below.We quantified population structure without a priori sample information using the Bayesian ancestry-based model entropy v1.2ST62 and Nei’s D63 based on population allele frequencies. As metrics of genetic diversity for each sampling location, we calculated nucleotide diversity , Watterson’s theta , and the scaled difference between the two (Tajima’s D66) using methods that incorporate genotype uncertainty implemented in ANGSD68. We used the de novo artificial reference genome and individual .bam files to estimate site allele frequency likelihoods using the “doSaf 1” tool. We then used site allele frequency likelihoods as input for REALSFS68 to generate folded site frequency spectrum likelihoods. Using “doSaf 1,” we calculated posterior allele frequency probabilities. Lastly, we used the thetastat utility from ANGSD to estimate per-locus measures of each diversity metric and generated the per-population average of these values over all contigs and nucleotides. For comparison with other studies, we also calculated expected heterozygosity based on allele frequencies.We additionally characterized genetic variation with PCA using the prcomp function in R. As metrics of pairwise genetic differentiation among populations, we calculated Hudson’s F70. Before generating the SFS, we further filtered the vcf file generated above. First, we removed variants with MAF < 0.1 to guard against rare variants that could represent sequencing errors and trimmed outlier loci with FST > 0.15 (the 0.95 quantile of the FST distribution) between the two populations. We generated the unfolded SFS for each population using easySFS (https://github.com/isaacovercast/easySFS#easysfs) on the stringently filtered .vcf file, down sampling populations to sizes of 10 and 10 .As we found unexpected evidence for divergence between taimen in the Tugur mainstem and its tributaries, we used a coalescent-based demographic modeling approach to explore parameters characterizing the divergence and demographic history of these two populations. The site frequency spectrum (SFS) contains the signatures of divergence and demographic processes , and high throughput sequencing data has substantially improved our ability to estimate such parameters from population genetic data69. These models represented two-population divergence (Tugur mainstem and Tugur tributaries), with and without migration, and with and without population expansion or contraction. We ran 50,000 coalescent simulations per replicate and a total of 50 replicates, with minimum (-n) of 100,000 simulations for a total (-L) of 40 cycles. We used a mutation rate for salmonids  of 8e−9 bp per generation for model estimation , and to estimate coalescent effective population size. For each model, the replicate with the smallest difference between the maximum expected likelihood (MEL) and the maximum observed likelihood (MOL) represented the best-fit run67. To account for differences in the number of parameters included in each model, we calculated AIC scores for each model’s best-fit run. We then calculated ∆AIC to compare models.Using the unfolded SFS, we estimated demographic parameters for eight different models using coalescent simulation and a maximum likelihood framework in fastsimcoal2Following parameter estimation for the best fit model, we calculated 95% confidence intervals for each parameter. Using the maximum likelihood parameters from the *_maxL.par file, we generated 100 bootstrap replicates of the SFS. Next, we estimated parameters of these 100 SFS using the same 50-replicate analyses described above. The best-fit model parameter estimates for each of the new 100 simulated SFS were used to calculate mean parameter estimates and subsequently to infer 95% confidence intervals.https://dataview.ncbi.nlm.nih.gov/object/ PRJNA745962). Both the sequence data and the vcf file are available at DRYAD (doi: https://doi.org/10.5061/dryad.wstqjq2kd).After filtering for contaminants and removing individuals lacking sufficient sequencing data, we retained 174 individuals with a mean number of 1,898,867 reads per individual. bwa mapped reads from all individuals onto the de novo partial reference consisting of 221,178 genomic regions. After variant calling and filtering based on sequencing coverage and quality, we retained 7597 loci with MAF > 0.04. We additionally discarded 1551 SNPs that potentially represented paralogous regions, leaving a final set of 6046 SNPs from 174 individuals . Sequence data is available on NCBI’s Short Read Archive  and 0.00132 for θW (range 0.00077–0.00178). Genetic diversity was consistently higher in Pacific drainages  than in the Arctic drainage , as was HE . No populations from the Arctic drainage had confidence intervals that overlapped with those in the Pacific drainages. Importantly, for taimen localities sampled in the current work, sample size was unrelated to both genetic diversity metrics .Given pronounced genetic differentiation between the Arctic and Pacific drainages and evidence for finer-scale differentiation among river systems within the Pacific drainages, we conducted assembly and variant calling separately for Pacific populations. Unique reads were assembled into a partial reference consisting of 160,858 contigs. Following reference mapping, variant calling, subsequent bioinformatic processing, and paralog filtering, we retained 3961 SNPs from 83 individuals  for the Pacific subset. The vcf file associated with the Pacific subset is available at DRYAD  were differentiated from samples taken in the mainstem Tugur  and fecundity-at-age data presented by Ref.34. Following the ancestral divergence event, asymmetrical gene flow was inferred between mainstem and tributary clusters, with greater gene flow from the mainstem to tributaries. Coalescent Ne for tributaries was substantially lower than that of the mainstem , and the model indicated population contraction in the latter.After the more stringent filtering with vcftools v0.1.14, we retained 1971 variants from which we constructed the unfolded SFS. Coalescent simulations using fastsimcoal2 were run for eight models spanning variation in divergence and demography of the Tugur mainstem and Tugur tributary populations  based on 1229 SNPs in a concatenated alignment similarly illustrated deep divergence among taimen sampled from the Pacific and Arctic drainages  form a continental divide that likely severed any recent connectivity between the Arctic and Pacific river systems. This geologic feature is associated with deep phylogeographic breaks for other taxa occurring in this region, including other salmonids , as well as other groups of freshwater fishes . Divergence time estimates from mtDNA analyses indicate divergence across this divide in the range of 1–2.5 mya for Cottus78 and 0.5–2 mya for taimen45.Our population genetic analyses illustrate substantial genetic differentiation consistent with significant historical isolation between taimen from the Arctic and Pacific drainages (mean Funpublished data.). This variation is consistent with isolation and independent evolution, and could possibly be due in part to ecological differences among drainages on either side of this divide, such as riverscape and landscape topography72, constituent riparian species composition35, and marine food web subsidies from seasonal spawning runs of chum salmon in the Tugur basin, but not the Selenge basin72. Unfortunately, the geographically sparse and clumped nature of our sampling led to a strong correlation between geographic and environmental distances (based on 19 BioClim variables) among sampling localities, which precluded formal tests of environmental influences on spatial genetic structure.Taimen from the Arctic and Pacific outflows do differ in a few key morphological traits, including average mass per length, and density and size of spot patterns . A younger taimen lineage in the Arctic drainage would be consistent with limited differentiation among populations often seen in Arctic fishes85, and also with variation in genetic diversity among the regions we sampled.We did not detect genetic differentiation among sites within the Arctic drainage Figs. , 3, thou89. For example, our values for taimen were similar to those reported for Atlantic salmon , a species that has also been strongly influenced by recent glacial periods90. Lower diversity in the Arctic drainage is consistent with the hypothesis that Arctic populations are younger, and/or suffered recent bottlenecks during Pleistocene glacial activity in this region82.For all metrics, levels of genetic diversity were consistently lower for the three Arctic drainage sites than those from Pacific drainage sites Table . MeasureST = 0.033). This pattern could be consistent with the Yablonovy and Stanovoi Mountain ranges acting as a divide for aquatic fauna separating the headwaters of the Lena (just north of the Tugur) and Amur basins91, although a lack of sampling over a large area between the Onon and Tugur sites limits our understanding of geographic features associated with spatial genetic structure. As in the Arctic drainage, we did not detect evidence for differentiation among sampling sites within the Amur basin. However, given the size and complexity of the Amur basin combined with the population structure documented across the basin in other salmonids , it is possible that more thorough sampling could reveal additional structure.Our analyses revealed clear, though less pronounced, genetic differentiation between the two Pacific drainages (Amur and Tugur). Taimen from the Onon River (Amur basin) were differentiated from those occurring 1800–2000 km to the east in the Tugur basin , suggesting ecological factors may underlie isolation. Reproductive isolation has evolved within a number of salmonid species due to spatiotemporal differences in spawning , or morphological specialization . Additionally, although taimen populations typically do not differentiate at smaller spatial scales, anadromous Sakhalin taimen (Parahucho perryi) demonstrate population genetic structure arising from differences in spawning grounds and homing behavior97. While we are unaware of such mechanisms underlying divergence in taimen, our results indicate the potential for differentiation at smaller geographic scales than previously detected and the need for further study to understand its evolutionary causes and consequences for management.Our analyses revealed unexpected evidence for fine-scale genetic differentiation between two groups of taimen sampled in the Tugur basin. Though sampling locations within this basin are highly proximate , suggesting a history of such connectivity77. The location of a potential paleo connection between the Tugur and Nimelen, a lower Amur tributary, is apparent in a low-relief area where active channels in tributaries of the two rivers are separated by < 1 km and by a drainage divide of < 10 m. One hypothesized scenario is that the Tugur was forced south and joined the lower Amur during Pleistocene “back-arc glaciation” of a Sea of Okhotsk marine ice sheet and the Stanovoi glacier complex to the west before drainages reorganized and became independent during glacier retreat100. A similar pattern of glaciation has been hypothesized to generate paleohydrological connections between the proto Tugur drainage and mid-Amur drainages of the Bureya and Zeya Rivers .A possible, if not likely, scenario underlying divergence in the Tugur basin is that ancestral tributary taimen diverged in isolation in the eastern Amur, before paleohydrological connections allowed colonization of the Tugur basin. Consistent with this hypothesis, taimen in the Tugur tributaries are intermediate with respect to those from the Tugur mainstem and the western Amur basin samples in both PCA and ancestry-based analyses Figs. , 3. Alth101, and the majority of the watershed is protected within the Tugursky Nature Reserve, a regional zakaznik .Understanding the historical and geographic context of differentiation in the Tugur basin as well as the mechanisms potentially maintaining it will require further study. Our results are based on relatively sparse spatial sampling only in the western Amur basin. More thorough sampling of the eastern Amur basin, especially where it nears the Tugur, will be necessary to more thoroughly characterize the geographical context and origin of divergence among taimen in the Tugur basin. Similarly, additional sampling within the Tugur basin could improve understanding of the spatial distribution of the genetically differentiated groups detected here. As importantly, an understanding of ecological, morphological, and life history variation among taimen in this system will be critical for understanding potential mechanisms underlying and maintaining differentiation. Further work here is warranted as the Tugur River continues to support the largest individuals of the world’s largest salmonid103) increase in frequency and intensity, and as translocation efforts are considered for regions where populations have declined or have been extirpated. Genetic diversity is often considered a key parameter for conservation and restoration, as it is commonly viewed as a proxy for population resilience and evolutionary potential105. Nucleotide diversity estimates for all of our sampling sites were in the range of estimates published for other salmonids89, and do not reflect severely reduced diversity. Although, Tajima’s D estimates were slightly positive for the Amur basin, which could be consistent with population declines here. However, our sampling was limited to regions with healthy river systems and those that have yet to exhibit strong population declines, and may not represent standing variation in other areas of the distribution.Given substantial and widespread declines of taimen populations, an understanding of genetic diversity and spatial genetic structure could be critical for informing taimen conservation. The demarcation of taimen management units could become important as anthropogenic influences known to impact fish populations  are often used to designate lineages of conservation importance. Kaus et al.46 proposed two taimen ESUs across northern Mongolia that largely correspond to our Selenge (Arctic) and Amur (Pacific) basin sites. Our results indicating the presence of substantial genetic divergence among these basins lend support for two separate units that might require separate conservation and management strategies. The hierarchical population structure recovered in this study suggests that ecologically relevant genetic variation might be partitioned at smaller spatial scales than previously considered, and we thus caution against the translocation of taimen among geographically and ecologically distinct populations before more thorough genetic sampling can be completed. The differentiated groups we detected in the Tugur basin could reflect ecological and historical variation warranting unique conservation consideration, though further study is clearly needed. Indeed, the additional evidence for population structure within the Pacific drainages suggests that our understanding of taimen genetic structure across different riverscapes is likely limited by both the geographic and genomic extent of sampling. Due to difficulty in sampling via fly fishing, our sampling was opportunistic, geographically sparse, and less than ideal for quantifying how environmental and hydrological variation may influence spatial genetic structure across the distribution. Future studies with more comprehensive sampling within and across basins could be essential for developing a finer scale understanding of the factors influencing evolutionary history of taimen across Siberia and the rest of its range.Evolutionarily significant units (ESUsSupplementary Information.


Clostridioides difficile infection (CDI) is a large intestine disease caused by toxins produced by the spore-forming bacterium C. difficile, which belongs to Gram-positive bacillus. Using antibiotics treatment disturbances in the gut microbiota and toxins produced by C. difficile disrupt the intestinal barrier. Some evidence indicates fecal microbiota transplantation and probiotics may decrease the risk of CDI recurrence. This study aimed to evaluate the efficacy of fermented mango by using the lactic acid bacteria Lactobacillus acidophilus and develop innovative products in the form of fermented mango jam. L. acidophilus-fermented mango products inhibited the growth of C. difficile while promoting the growth of next-generation probiotic Faecalibacterium prausnitzii. Both supernatant and precipitate of mango-fermented products prevented cell death in gut enterocyte-like Caco-2 cells against C. difficile infection. Mango-fermented products also protected gut barrier function by elevating the expression of tight junction proteins. Moreover, L. acidophilus-fermented mango jam with high hydrostatic pressure treatment had favorable textural characteristics and sensory quality. Clostridioides difficile (formerly Clostridium difficile) infection (CDI) is 10-fold higher in older adults than in young adults ) and b* (yellowness/blueness [+/−]) ) .The appearance, odor, texture, flavor, and overall acceptability of each sample were evaluated by panelists. For a trained sensory panel, panelists were trained to isolate each factor and to focus on each independently of the others for evaluation of the property that is of interest to the researcher. There are 20 panelists in this study, including 9 men and 11 women. Assign a rating to each parameter on a 9-point descriptive hedonic scale, in which 9 is reserved for the highest-quality sample .p value < 0.05 were considered statistically significant.The data were expressed as means ± SD. The statistical analysis was performed by one-way analysis of variance (ANOVA) to compare among groups through Duncan’s multiple-range test . Statistic differences with a L. acidophilus, L. plantarum subsp. plantarum, and L. paracasei subsp. paracasei have been used to ferment plant products to improve their antioxidation, anti-inflammation, and lipid metabolism, as well as abilities to prevent acute gastric ulcers, antiatherosclerosis, and antiobesity [L. acidophilus BCRC14079-fermented mango pulp (30%) after 1, 3, and 5 d of fermentation. The pH value decreased significantly (p < 0.05), as fermentation progressed from days 3 to 5 (L. acidophilus BCRC14079 produced lactic acid (L. acidophilus BCRC14079 growth in mango pulp (30%). The number of L. acidophilus BCRC14079 increased after mango pulp had been fermenting for 3 days, which can exceed approximately 1010 CFU/mL. However, the number of L. acidophilus BCRC14079 was lower on day 5, suggesting that the growth of L. acidophilus BCRC14079 in mango pulp as a fermentative material is limited.iobesity ,28. Moreiobesity . Titratas 3 to 5 A. An inctic acid B. FigureC. difficile develops antibiotic resistance to a number of antibiotics. Therefore, alternative treatment or prevention strategies are needed. The fermented products were centrifuged and divided into L. acidophilus BCRC14079-fermented mango supernatant and precipitate. The inhibition of C. difficile growth by L. acidophilus BCRC14079-fermented mango extracts was evaluated.The focus of CDI treatment guidelines is to stop continuing using antibiotics and switching to metronidazole and vancomycin ,31. HoweL. acidophilus BCRC14079-fermented mango supernatant and precipitate could inhibit the growth of C. difficile dose dependently (31.25–500 μg/mL). The suppressive effect of L. acidophilus BCRC14079-fermented mango supernatant was similar to that of L. acidophilus BCRC14079-fermented mango precipitate (24 h treatment). In addition, a dose of 250 μg/mL was used to evaluate the inhibitory effect in C. difficile treated with mango extracts, L. acidophilus BCRC14079-fermented mango supernatant, and L. acidophilus BCRC14079-fermented mango precipitate for 8, 12, 18, 24, and 36 h. As shown in L. acidophilus BCRC14079-fermented mango supernatant to inhibit C. difficile growth was greater than that of the mango extract and L. acidophilus BCRC14079-fermented mango precipitate during 18–36 h.As shown in C. difficile belongs to Gram-positive bacillus that produces spores. It is an important pathogenic bacterium in adults and children. C. difficile was first isolated from the intestinal tract of infants and was clinically important when it became one of the main causes of antibiotic-associated diarrhea [C. difficile to produce resistant spores, partly due to the inability to recover the gut microbiota after antibiotic treatment; importantly, 25% of CDI patients may occur recurrence, and the rate of secondary recurrence can be as high as 40–60% [diarrhea . Recurres 40–60% ,32.C. difficile. Toxins A and B of C. difficile are secreted and bound to host receptors, subsequently, entered into the cytoplasm of enterocytes [L. casei LBC80R and L. acidophilus CL1285 against CDI has been reported [L. reteri products on inhibiting C. difficile colonization has been evaluated [L. acidophilus BCRC14079-fermented mango can inhibit the growth of C. difficile.Cytotoxins toxin A and toxin B are cytotoxic proteins, which are the principal virulence factors of erocytes ,31, whicerocytes ,34. In areported . Moreovevaluated . We founC. difficile and reduces the risk of infection. The intestinal mucosa is the first site for the contact between host and pathogen  while infection. Intestinal epithelial cells are able to produce mucin, which can form a mucosal barrier to block tissue represent sits and avoid pathogenic infection.In a cell model, toxins A and B have been shown to induce cell necrosis and apoptosis in intestinal epithelial cells ,37. TherL. acidophilus BCRC14079-fermented mango. As shown in L. acidophilus BCRC14079-fermented mango supernatant and precipitate (250 μg/mL) treatment significantly increased the expression of mucin-13, ZO-1, and OCC in Caco-2 cells when compared with mango-extract treatment.Apart from mucin, epithelial integrity is associated with intestinal tight junction proteins such as zonula occludens-1 (ZO-1) and occludin (OCC). These proteins regulate cellular permeability and maintain intestinal barrier functions . We inveC. difficile-derived toxin A causes cell apoptosis and reduction of mucosal integrity in Caco-2 cells [C. difficile infection in Caco-2 cells, and their results showed that the cell viability was decreased after 60 min infection [C. difficile for 30, 60, 90, 120, 150, and 180 min. As shown in C. difficile treatment for 120 min. In addition, both L. acidophilus BCRC14079-fermented mango supernatant and precipitate extract treatment markedly alleviated the cytotoxic effect of C. difficile on Caco-2 cells  were suppressed by Rho signaling mediation, leading to enterocytes disruption [L. acidophilus BCRC14079-fermented mango has the potential to improve the intestinal barrier and attenuate cell death induced by C. difficile in Caco-2 cells.One study has found that -2 cells . Janvilinfection . We inve-2 cells B. A resesruption . In our L. acidophilus BCRC14079-fermented mango on the growth of F. prausnitzii  significantly increased growth of F. prausnitzii . Evidence suggests that some dietary factors may influence the abundance of F. prausnitzii [F. prausnitzii [F. prausnitzii.The population of ondition . Severalusnitzii . Severalusnitzii . Mango iF. prausnitzii produces short-chain fatty acid butyrate in the colon, which inhibits the growth of C. difficile. Moreover, some anti-inflammatory bacteria such as F. prausnitzii and lactic acid bacteria support the innate immune response and minimize bacterial burden and negative effects during antibiotic and C. difficile exposure [L. rhamnosus R0011) supplements have shown intestinal protection against CDI [F. prausnitzii-cultured supernatant showed the ability for inhibiting inflammatory cytokines production in Caco-2 cells [L. acidophilus BCRC14079-fermented mango can suppress the growth of C. difficile, increase the expression of tight junction proteins, and inhibit C. difficile by promoting the growth of F. prausnitzii and increasing the level of butyrate. These results show that L. acidophilus BCRC14079-fermented mango can be developed as a health product to improve the intestinal microenvironment and gut microbiota, and has the potential to be used in the adjuvant treatment of CDI.exposure . Antioxiinst CDI . Moreove-2 cells . SCFAs p-2 cells . For exa-2 cells . Taken tJam, a kind of medium-moisture food product, is prepared by boiling fruit pulp with sugar, acid, pectin, and/or other substances to achieve a suitable and strong consistency to maintain the texture of the fruit. Jam is usually made by mixing fruit and sugar in a ratio of 45%:55% by weight. Typically, jams are widely consumed for breakfast and incorporated into bakery products and confectionery. With the increasing attention to health and wellness, and the increasing incidence of obesity, metabolic syndrome, and diabetes, the interest in low-calorie foods has also increased . For exaL. acidophilus BCRC14079-fermented mango was investigated in this study for developing the fermented jam that contained probiotics. Browning and color loss were found to be higher in the heat-treatment group than the HPP-treatment group under all conditions  among all groups (C. difficile. This jam was fermented using lactic acid bacteria L. acidophilus BCRC14079 and treated with HPP to retain its physicochemical, textural, and rheological properties.We assessed textural characteristics, including hardness, adhesiveness, and cohesiveness . We founl groups . Many foL. acidophilus BCRC14079-fermented mango products exhibited beneficial effects by promoting the growth of F. prausnitzii and protected intestinal cells against C. difficile infection via preventing the cell death of Caco-2 cells. This enteroprotective role of L. acidophilus BCRC14079-fermented mango products is related to improve the gut barrier function through upregulating tight junction proteins expression and mucin secretion. A novel type of mango jam that was fermented by L. acidophilus BCRC14079 and treated with high hydrostatic pressure processing was produced, which had favorable textural characteristics and sensory quality, and had the potential to be developed as an innovative food product for inhibiting the growth of pathogens and improving the human health.In this study,


American Criollo pigs are thought to descend mainly from those imported from the Iberian Peninsula starting in the late 15th century. Criollo pigs subsequently expanded throughout the Americas, adapting to very diverse environments, and possibly receiving influences from other origins. With the intensification of agriculture in the mid-20th century, cosmopolitan breeds largely replaced Criollo pigs, and the few remaining are mostly maintained by rural communities in marginal areas where they still play an important socio-economic and cultural role. In this study, we used 24 microsatellite markers in samples from 1715 pigs representing 46 breeds with worldwide distribution, including 17 American Criollo breeds, with the major focus of investigating their genetic diversity, structure and breed relationships. We also included representatives of the Iberian, Local British, Hungarian, Chinese and Commercial breeds, as well as Wild Boar, in order to investigate their possible influence in the genetic composition of Criollos. Our results show that, when compared with the other breeds, Criollo pigs present higher levels of genetic diversity, both in terms of allelic diversity and expected heterozygosity. The various analyses indicate that breed differentiation overall explains nearly 21% of the total genetic diversity. Criollo breeds showed their own identity and shared a common genetic background, tending to cluster together in various analyses, even though they differ from each other. A close relationship of Criollos with Iberian breeds was revealed by all the different analyses, and the contribution of Iberian breeds, particularly of the Celtic breeds, is still present in various Criollo breeds. No influence of Chinese breeds was detected on Criollos, but a few were influenced by Commercial breeds or by wild pigs. Our results confirm the uniqueness of American Criollo pigs and the role that Iberian breeds have played in their development. The first domestic swine arriving in the American continent came from the Canary Islands, in the second voyage of Columbus in 1493 –4. As haThe intricacies of the American colonization process and the result of nearly 500 years of adaptation to distinct environmental conditions have contributed to the highly heterogeneous genetic pool currently represented by Criollo pigs. In addition, various pig breeds from different origins, including China, have arrived in America over the years and may have been mixed with local populations, adding to the complexity of the genetic structure of Criollo pig populations .The intensification of pig production throughout the world in the second half of the 20th century has threatened many local populations, and Criollo pigs were led to near extinction. The few remaining populations currently existing are widely spread, often with very small census. Criollo pigs are now mostly maintained by rural communities in marginal areas, where village pigs are usually kept in a commensal relationship where they play an important role in sustainable economies by using local feed resources and converting domestic waste into animal protein .In addition to their social and historical importance, the elements of isolation and adaptation to extremely different environmental conditions that Criollo pigs experienced make them a highly valuable biological resource. They have had to adjust to very diverse climates, feed sources, health constraints, management systems, and disease threats. Their adjustments provide for the possibility of gaining a better understanding of the genetic background underlying the various mechanisms of adaptation that these populations have undergone .Studying the genetic history of Criollo pigs is essential for a better understanding of the importance of livestock throughout the period of discovery and colonization of the Americas, and how the introduction of breeds of other origins may reflect changes in food habits and agricultural practices over time. Furthermore, understanding the genetic diversity and structure of Criollo pigs is crucial for a better awareness of their importance and for the establishment of management programs aimed at their conservation.The genetic diversity and relationships of some Criollo pig breeds  as well Criollos (CRI): including animals from five populations from North America: Mulefoot (UMF), Red Wattle Hog (RWH), Guinea Hog (UGH) from the United States and Pelón Mexicano (MEX) and Baja California (BCS) from Mexico; one breed from Central America: Criollo Salvadoreño (SAL) from El Salvador; two breeds representing the Caribbean Islands: Criollo Cubano (CUB) from Cuba and Criollo de Guadalupe (GUA) from Guadeloupe Island and nine breeds from South America: Criollo Venezolano (VEN) from Venezuela; Zungo (ZUN), San Pedreño (CSP), and Criollo del Pacífico (CCP) from Colombia; Criollo Ecuatoriano (ECU) from Ecuador; Criollo Boliviano (BOL) from Bolivia; Pampa Rocha (UPR) from Uruguay; and Criollos from either Northeast Argentina Wet (NEW) and Dry (NED) regions; Iberian Peninsula breeds (IBE): including Retinto (RET), Entrepelado (ENT), Torbiscal (TOR), Negro de los Pedroches (NPE), Lampiño (LAM), Manchado de Jabugo (MJA), Chato Murciano (CHM), Negro Canario (NCA), Negro de Formentera (NFO), Negro Mallorquín (NMA), Euskal Txerria (ETX), and Celta (CEL), from Spain; Alentejano (ALE), Bisaro (BIS) and Malhado de Alcobaça (MAL) from Portugal; Local British breeds (LBR): composed by Berkshire (BSH), Tamworth (TWD) and Large Black (LBL) from UK; Commercial breeds (COM): consisting of five cosmopolitan breeds, Duroc (DUR), Pietrain (PIE), Large White (LWH), Landrace (LDR), and the commercial crossbred population Large White x Landrace (LLW); the Hungarian Mangaliça (MAN) breed; the Chinese Meishan (MSH) breed; Wild boar (WBO) populations: composed by wild boar samples obtained in Portugal (PWB), Spain (SWB), Poland (LWB) and Italy (IWB).A set of 24 microsatellite markers was used to analyze samples of 46 populations/breeds belonging to different countries/regions, as represented in The biological samples for genotyping were obtained in the framework of the CONBIAND network, as described by Gama et al.  for IberIGF1, S0002, S0005, S0026, S0068, S0090, S0101, S0155, S0178, S0215, S0225, S0226, S0227, S0228, S0355, S0386, SW024, SW072, SW240, SW632, SW857, SW911, SW936 and SW951.Individual genotyping has been previously reported by Gama et al.  for Ibere) and observed (Ho) heterozygosities per breed and group were calculated with the MICROSATELLITE Toolkit software for Excel  of the data were estimated across 10 runs for each K value. The most probable number of population clusters was determined by plotting L(K) and also with the distribution of ΔK [The Bayesian model-based method developed by Pritchard et al.  and implon of ΔK  calculaton of ΔK . The cluon of ΔK , which wEffective population size was estimated with NeESTIMATOR V2  using thm is the number of alleles in a given locus in a population sample and R is the allelic range. The GW statistic is expected to be very small in populations having been through bottlenecks and close to one in stationary population.The occurrence of genetic bottlenecks was investigated by two different approaches, (1) heterozygosity excess and (2) Garza-Williamson index (GW). In (1), the BOTTLENECK software was used to test for excess genetic diversity relative to that expected under mutation-drift equilibrium , as the e and Ho  and the highest values were observed in COM . The WBO had levels of genetic diversity slightly lower than those observed in CRI and IBE. The deficit in heterozygosity computed within each breed-group was significant in all breed-groups (p<0.001) and resulted in an f estimate with the highest values found in IBE (0.271), followed by LBR (0.236) and CRI breeds (0.194). The majority of the breed-groups were composed by more than one breed, therefore the f estimate should reflect the subdivision of populations forming the groups, in addition to their accumulated inbreeding. However, in the MSH and MAN groups only one breed is being considered, thus the estimated f should reflect mostly inbreeding rather than breed substructure.The diversity estimates observed for the various groups are in f (p<0.05) in 28 populations, with the highest f estimate of 0.285 observed in the MEX population. All breeds except CSP, UPR and BSH displayed departure from Hardy Weinberg Equilibrium at least in one locus (p<0.05).When genetic diversity was assessed by breed within group , the higf = 0.073±0.007, Ө = 0.210±0.006 and F = 0.267±0.009. These results reveal that the levels of breed differentiation were considerable, with multilocus Ө values indicating that approximately 21% of the total genetic variation corresponded to differences between breeds, while the remaining 79% were attributed to differences among individuals within breeds.The average F-statistics and their standard deviation were ST = 0.215) is mostly due to differences among breeds within the same region (fSC = 0.178) rather than differences between regions (fCT = 0.044).Partitioning of genetic variability among the different sources of variation (AMOVA test) indicated that nearly 4.4% of the total genetic variability was explained by the assumed breed-groups, whereas the differences among populations/breeds within groups represented about 17% of the total variability . The corӨ = 0.021), supporting their much closer relationship. The CRI then had distances of about 0.04 with the COM group and about 0.06 with the LBR and WBO. The estimated Nei distances pointed to the same relationships, i.e., a much closer relationship of CRI with IBE (DA = 0.061), while the distances with COM, WBO and LBR were increasingly larger. It should also be noticed that, for the CRI group, the distance with the MSH breed estimated by both methods was much larger than for any of the other breed-groups  clustered together and MAN was added to this group. Another group was represented by British local breeds, PIE and MSH. The third cluster grouped the IBE breeds of the Celtic group, the CHM, NCA and ETX, and nearly all the Criollo populations.At K = 5, the MSH separated from the other groups, while the UMF and ETX clustered together. The CRI group (with the exception of UMF and BCS) was mostly homogeneous and clustered with the CEL and BIS from the Iberian Peninsula, and the DUR from the COM group.The COM breeds grouped with CHM, NCA and the local British breeds. The Iberian breeds of the Mediterranean group remained in the same cluster with the WBO group.At K = 20, breeds in the Criollo group generally showed different ancestry relative to each other and, with very few exceptions, no influence could be detected from the MSH, commercial or British local breeds. Overall, Criollo breeds were either essentially distinct from all the other breed groups or showed signs of an Iberian influence. For example, the UMF was well isolated from the remaining breeds, while the UGH and UPR grouped in the same cluster but no relationship was detected with other breed groups. Moreover, RWH and DUR clearly showed signs of admixture, and some Criollo breeds such as BCS and BOL showed influence of WBO. The NEW and NED were well differentiated from most of the other breeds, but shared a common admixture pattern with MEX, SAL, CUB and ECU. On the other hand, the MEX, SAL and CUB also appeared to share a common genetic background with the Colombian breeds  and the ECU, as well as with the Iberian breeds of the Celtic group, which may reflect an influence of breeds such as BIS and NMA on Criollos. The influence of the CEL breed could also be detected in GUA, VEN, CSP and CCP, confirming the influence of Iberian Celtic breeds in various Criollo populations.Overall, at K = 20 the MAN and MSH breeds were well isolated from all the other breeds, and the commercial breeds LWH, LDR and LLW remained closely grouped. In local British breeds, the LBL separated from the BSH and TWR, which shared a common ancestry. In the wild boar, some separation occurred according to geographical origin, with the Italian group clearly isolated and the Polish group showing some signs of substructure. Among the Iberian pig breeds, the Mediterranean group of breeds clustered together, with some separation of the TOR and LAM breeds. Yet, most of the other Iberian breeds were well isolated and showed influence of a single ancestral population, possibly with the exception of BIS, which had signs of mixed ancestry.At K = 29, the clusters for individual breeds and groups were essentially the same described for K = 20. Again, the majority of the Criollo breeds had a mixed ancestry, and in most cases, they shared a common blended ancestry with each other. Nevertheless, a few of them were well isolated , were closely related (UGH and UPR), or showed a clear influence from another breed (RWH from DUR and BOL from WBO).The effective population size (Ne), estimated from linkage disequilibrium, differed considerably among the various breeds analyzed . OverallWhen Bottleneck software was used , heterozIt is well established that domestic swine did not exist in the American continent until 1493, when the first pigs and other livestock were brought from the Canary Islands in the second journey of Columbus. The process of recruitment, transportation and expansion of this first group of pigs brought to the New World is documented in the writings of the Dominican monk Bartolomé de las Casas, a narrator who described in detail the early years of discovery and colonization of the American continent in his treaty “Historia de las Indias” . In thisIn the newly discovered territories, pork was often the only familiar meat available to the first colonists, and lard was an essential ingredient for several human activities . Of the As for other livestock species, these pigs of colonial descent became known as Criollos, and they expanded through every region of North and South America, adapting to a vast array of environments, including a wide range of conditions in terms of altitude, temperature, rainfall, etc. In addition to their primary role of providing food for local populations, Criollo pigs also gained importance by their ability to utilize native feed resources and convert domestic waste into pork, and expeditions often brought supplies of preserved salt-pork, which was essential for their maintenance for long periods of travel .Over the period of more than five centuries since their introduction in the Americas, Criollo pigs have undergone a process of fragmentation into various sub-populations. These have endured selection for adaptation to different environmental constraints, and genetic drift and bottlenecks have likely occurred over time. It is also possible that, throughout this period, exotic germplasm of European or Asian origin have been introduced in some Criollo populations , 39, incSome research on Criollo pigs has relied on mitochondrial DNA sequences and Y-chromosome markers to elucidate their origins , 41, 42.The possible influence that other pig breeds may have had on the current genetic structure of American Criollo populations has not been thoroughly investigated so far. In this work, we used microsatellite markers to assess genetic diversity, genetic relationships and the possible influences that pig breeds from Spain and Portugal, as well as other European breeds (including wild boars), commercial breeds and Chinese Meishan, may have had in the development of Criollo pig populations. Our study provides important information regarding the genetic diversity and structure of Criollo pig breeds, and also a new perception of the relationships among them and of their possible ancestral origins.Our results clearly show that Criollo pigs present high levels of genetic diversity, both in terms of allelic variation and expected heterozygosity. Indeed, the genetic diversity of Criollos is higher than that found in any of the other groups studied. This may reflect the history of Criollo pigs, including population fragmentation followed by genetic drift in the past, as well as the consequences of possible admixture with imported pig breeds. On the other hand, this high genetic diversity may also be a consequence of adaptation to very diverse environmental conditions of the various Criollo populations, which would lead to population divergence in case the microsatellite markers are not completely neutral or are linked to genomic regions under selection . In a reAt the breed level, large differences were observed, not only among the 46 breeds with a worldwide distribution included in our analyses, but also among the 17 Criollo breeds represented. The highest levels of genetic diversity in Criollo pigs were found in ECU from Ecuador and NEW from Argentina, and these are also the breeds which, in the analyses with STRUCTURE, reveal some of the more diversified contributions of ancestral populations. On the other hand, the Criollo breeds with the lowest levels of genetic diversity were the UMF and RWH, both from the United States. In the analyses with STRUCTURE, the UMF seems to be very homogeneous and to have a unique ancestral contribution, while the RWH is closely related with the Duroc; thus, the low genetic diversity observed in these two populations probably reflects past population decline or a possible founder effect.The majority of the Criollo breeds shows a significant deficit in heterozygosity. This likely reflects their reduced census sizes or possibly the existence of substructure in some populations, as a consequence of fragmentation and genetic isolation. Still, the analyses carried out to assess past effective population size did not reveal, for the majority of Criollos, the occurrence of census reduction nor the existence of strong bottlenecks in the past. On the contrary, various Iberian breeds have indications of strong reductions in effective population size, which is compatible with their recent history .For selectively neutral loci such as microsatellites, a reduction in allele number and heterozygosity are anticipated when a bottleneck occurs and the effective population size is reduced. However, they are expected to occur at different rates . Under tAssuming a critical value for the GW-test of 0.68, as derived from putatively stable populations , in our In our study, the estimated F-statistics indicated that nearly 21% of the total genetic diversity corresponded to breed differentiation, an estimate which is in line with the AMOVA results that indicate that the most important source of variability was the diversity among populations within groups (about 17%), while the fraction corresponding to the differentiation due to groups was only about 4% of the total variability. The high θ estimate in our study is in agreement with the results reported by Gama et al.  for natiOur results regarding breed structure and relationships strongly support the idea that Criollo breeds of pigs have their own identity and share a common genetic background, as they tend to cluster together in distance trees and in FCA analyses. However, no clear geographical pattern of distribution of genetic diversity could be identified. The closer relationship of Criollos with Iberian breeds was unquestionable, as revealed by all the different analyses, including Ө, Nei distance tree and FCA, where they are closer to Iberian breeds than to any of the other breed groups. Also clear was the lack of support for a possible contribution of Meishan pigs to Criollos, contrary to some speculations that have been made suggesting that the introduction in America of pigs from China, which probably took place between the 16th and 18th centuries , 74, 75,It is also interesting to notice that very few Criollos actually showed a close influence from commercial breeds, the major exception being the RWH, which clearly shares a common ancestry with DUR. This likely reflects a Criollo origin to the Duroc breed, which was developed in the United States from local genetic resources in the 1800s. Further evidence of the singular origin of Duroc is provided by its unique position relative to other commercial breeds. Given the expansion that cosmopolitan pig breeds have had all over the world, where they have often had an impact upon and endangered many local breeds , it coulIn addition to this general pattern, individual Criollo breeds showed some particular features regarding their relationships with other breeds. For example, the dendrogram based on Nei’s genetic distances, clustered 13 out of the 17 CRI populations with the BIS and CEL breeds from the Iberian group, suggesting that the Iberian influence on Criollos has been mostly through the Celtic group of breeds, which includes BIS and CEL (from the northern Iberian Peninsula), rather than from breeds of the Mediterranean group (from the south). This feature is further supported by the analyses with STRUCTURE, where various Criollo breeds share a common ancestry with the CEL breed, while others share ancestry with BIS and NMA, which are of Celtic-type. This was somewhat unexpected, as most ships sailing to America started their journey in southern Spain and the majority of the first explorers and settlers also came from the Extremadura and Andalusia regions in southern Spain . In thisOur study also uncovered a few other aspects for some particular breeds, including the clear influence of wild boars on the genetic make-up of BOL and BCS, which certainly reflects admixture of these populations with wild boars that have been introduced in the Americas for hunting, at least since the early 19th century .As revealed in the analyses with STRUCTURE, the vast majority of Criollo breeds have received contributions from a large number of ancestral populations, which they share with each other in most cases, even though in a heterogeneous way. However, Criollos generally differ from the other breeds included in our analyses, with the exception of Iberian breeds, whose contribution is often present in various Criollo breeds.Overall, this study shows that a diversified, but generally common, genetic background underlies the foundations of the gene pool of the majority of the Criollo breeds. Furthermore, all analyses also indicate that, in spite of this common background, Criollo breeds have diverged over time, and they currently differ from each other, such that most of them have their own identity and deserve to be recognized and protected to prevent their extinction, given the endangered status of many of them. The results of our study can be used to establish programs and strategies aimed at the conservation of this genetic pool, to be developed by the appropriate national institutions and breeders, according to the guidelines recommended by FAO .The long history of Criollo pigs in the Americas, starting from a narrow founder population and then expanding throughout the continent and evolving to adapt to extremely different environmental conditions, provides a unique opportunity to investigate the genetic mechanisms underlying adaptation to different challenges, including temperature, humidity, altitude, feed constraints, health challenges, etc. Further studies at the level of the whole genome are warranted to clarify these issues, for which the maintenance and in-depth study of Criollo populations are crucial.Our study with a broad representation of American Criollo pig populations and breeds representing their presumed ancestors reveals that Criollo pigs present higher levels of genetic diversity with a distinct identity, and in most cases Criollo breeds remain well differentiated. The influence of Iberian breeds, particularly of the Celtic group, is still present in various Criollo breeds, and a few Criollos reveal genetic contributions from Commercial breeds or from wild pigs. Our results can be instrumental for the recognition of Criollo breeds of pigs, to acknowledge the role that they play in rural development and for establishing the basis of selection and conservation programs aimed at their sustainable use. Furthermore, the long history of adaptation of Criollos to very diverse environmental conditions, after diverging from a common founder population, provides a unique opportunity to investigate genetic mechanisms underlying the ability to cope with various environmental challenges, which is an insight of major importance in a scenario of climate change.S1 FigThe Delta K graph indicated a maximum value at K = 29.(TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.


Ethnogenesis of Kazakhs took place in Central Asia, a region of high genetic and cultural diversity. Even though archaeological and historical studies have shed some light on the formation of modern Kazakhs, the process of establishment of hierarchical socioeconomic structure in the Steppe remains contentious. In this study, we analyzed haplotype variation at 15 Y-chromosomal short-tandem-repeats obtained from 1171 individuals from 24 tribes representing the three socio-territorial subdivisions  in Kazakhstan to comprehensively characterize the patrilineal genetic architecture of the Kazakh Steppe. In total, 577 distinct haplotypes were identified belonging to one of 20 haplogroups; 16 predominant haplogroups were confirmed by SNP-genotyping. The haplogroup distribution was skewed towards C2-M217, present in all tribes at a global frequency of 51.9%. Despite signatures of spatial differences in haplotype frequencies, a Mantel test failed to detect a statistically significant correlation between genetic and geographic distance between individuals. An analysis of molecular variance found that ∼8.9% of the genetic variance among individuals was attributable to differences among zhuzes and ∼20% to differences among tribes within zhuzes. The STRUCTURE analysis of the 1164 individuals indicated the presence of 20 ancestral groups and a complex three-subclade organization of the C2-M217 haplogroup in Kazakhs, a result supported by the multidimensional scaling analysis. Additionally, while the majority of the haplotypes and tribes overlapped, a distinct cluster of the O2 haplogroup, mostly of the Naiman tribe, was observed. Thus, firstly, our analysis indicated that the majority of Kazakh tribes share deep heterogeneous patrilineal ancestries, while a smaller fraction of them are descendants of a founder paternal ancestor. Secondly, we observed a high frequency of the C2-M217 haplogroups along the southern border of Kazakhstan, broadly corresponding to both the path of the Mongolian invasion and the ancient Silk Road. Interestingly, we detected three subclades of the C2-M217 haplogroup that broadly exhibits zhuz-specific clustering. Further study of Kazakh haplotypes variation within a Central Asian context is required to untwist this complex process of ethnogenesis. Central Asia is a region populated by a wide range of ethnicities and characterized by heterogeneous economic and linguistic landscapes. Being located along the Silk Road, Central Asian populations have been genetically and culturally influenced by a millennia-long interplay between East and West that underpins its highly diverse genetic landscape. Genetic studies of Bronze Age (3100–1300 BC) remains from Central Asia show substantial temporal changes in the genetic composition of populations, indicating extensive migrations and west-to-east expansions of sedentary herders from the western steppe that formed a homogeneous gene pool by the end of the second millennium BCE . In the The nomadic society of the Kazakh Steppe was organized based on a hierarchical patrilineal clan system of genealogical lineages. Individuals of the same genealogical lineage claim to share a common ancestor, and multiple genealogical lineages combine into clans that, collectively, form tribes. The 12 tribes of the Senior zhuz primarily occupied Southern and South-Eastern Kazakhstan, the seven tribes of the Middle zhuz reside in Eastern, Northern and Central Kazakhstan, while the three tribes in the Junior zhuz traditionally lived in Western Kazakhstan . Some ofDespite the globalization of the last centuries and the move to a sedentary lifestyle, the tribal-clan structure of the Kazakh people has persisted, and many modern Kazakhs know the tribal affiliation and history of their clan. Being a patrilineal custom, the transgenerational transmission of tribal-clan affiliation resembles inheritance of the non-recombining part of Y chromosome, even though the former is a social entity. The analysis of genetic markers of the Y chromosome has been successfully employed in many studies of human populations to reconstruct migration routes; the combination of extended Y-haplotypes in patrilocal communities with genealogical data can enhance our understanding of the fine-scale demographic dynamics of a population .N = 1,171 of Y-chromosomal haplotype diversity among all extant Kazakh tribes including the Tore and Kozha, with the primary goal of assessing the relationship of tribes and zhuz among the Kazakh people of modern-day Kazakhstan.To date, a multitude of studies has employed genetic markers to investigate the genetic diversity and differentiation of the Kazakh population in global , regionaSamples and DNA extraction: A total of 1171 Kazakh males were included in this study. Blood or saliva was sampled from unrelated males from all-known Kazakh clans throughout five geographic regions in Kazakhstan  generating STR profiles at 17-loci  (GATA-H4) . FragmenHaplogroup prediction and Y-SNP genotyping: Y-haplogroups were predicted using the online Y-DNA Haplogroup Predictors NevGen (http://www.nevgen.org) as well as Whit-Athey’s (http://www.hprg.com). Putative Y-haplogroups for 16 of the 20 predicted haplogroups were then definitively determined through the analysis of 16 Y-SNPs, genotyped by RFLP or allele specific PCR using nine primers designed from previous studies and seven primer pairs designed for this study (https://isogg.org/tree/index.html).is study . In Y-STis study . The nomHaplogroups: To visualize the clustering of Y-haplogroups in the region, the Y-haplogroups of all individuals were plotted with respect to their birthplace and sampling location  for each Y-STR marker was calculated by direct counting, and the genetic diversity (GD) of single-markers was calculated using Nei’s formula GD = n(1-Σpi2)/(n-1), where Pi is the relative frequency of the ith allele and n is the sample size . The number of unique haplotypes and their frequencies were obtained with the help of the R package Pegas  was performed by using the pairwise genetic distance between individuals based on Meirmans PT, as above, performing the PcoA and then extracting the first two dimensions for visualization with the help of the R package Ape (1) Y-haplogroups and 2) the tribal affiliations of individuals.re 2.3.4 . Given tre 2.3.4 , and thekage Ape . The indY-chromosome haplogroups in Kazakh population: 1171 Kazakh males were included in the study: 433 total individuals representing the 12 tribes in the Senior zhuz, 475 from seven tribes in the Middle zhuz, 241 from the Junior zhuz, and 22 samples from the Kozha (n = 16) and Tore (n = 6) tribes  tribes . Althoug) tribes . All ind) tribes . The loc) tribes . Haploty) tribes . Sixteen) tribes . Of the ) tribes . These sn = 6) (The most frequent haplogroup in the Kazakh population was C2-M217 (51.9% - 608 men). Haplogroup C2-M217 was present in all examined tribes and its frequency ranged from 11% in Kangly and Argyn to 100% in Shaksham (n = 6) . Anothern = 6) .n = 126) harbored haplogroup G1-M285. The highest frequency of the haplogroup G2a-P15 was observed in the Uak tribe . The N-M231 haplogroup had a global frequency of ∼6.9%, but was prevalent in the Sirgeli  and Uak  tribes, Tore tribe  and Jalayir tribe . Haplogroup J, represented by J1-M267 and J2-M172, had a global frequency of ∼6.2%, being frequent in the Ysty tribe  and J2-M172 ). Additionally, J2-M172 was also observed in the Kozha clan . Lastly, haplogroup Q had a low overall frequency of ∼3.1%, but was highly represented in the Kangly tribe , while its frequency was <5.5% in all other tribes , G (G1-M285 and G2a-P15), N-M231, J (J1-M267 and J2-M172), and Q-M242 were observed at frequencies <10% across tribes, but were found at higher frequencies in one or a few tribes. For example, haplogroup O2-M122, had a frequency of 8.03% in the sampled population, but was found in 52.3% of the individuals from the Naiman tribe. Haplogroup G had a global frequency of 7.9%, with the majority (7.1%) belonging to subclade G1-M285 and 0.8% to subclade G2a-P15, but the frequency varied between tribes, and ∼54% of the males from the Argyn tribe  and ∼71% (Model: ∼zhuz/tribe) of the variation in Y-STR diversity is attributable to variation within tribes. Variation in Y-STR diversity among zhuz, explained ∼9% of the variation in YSTR-diversity, a value that was lower than expected if the diversity was distributed randomly among the highest hierarchical level using a Monte Carlo permutation test, while the amount of variation within tribes was greater than expected  and 0.19 (Sirgeli vs Shaksham) (expected . Estimatexpected . Pairwishaksham) .Mantel test: Despite the apparent higher frequency of the C2-M217 haplogroup along the southern and western borders of Kazakhstan, tracking the Mongolian invasion  provided a closer examination of the relationship among A) tribes and B) haplogroups. This revealed that while many of the haplogroups fall in the middle of the coordinate with somewhat distinct clustering  , while tIn contrast to high haplotype diversity, the overall discrimination capacity of the 15 Y-STR loci was only 0.5517. This suggests that despite including only unrelated males in the study, individuals from the same or different tribes may have identical haplotypes presumably reflecting the deep patrilineal descent among Kazakhs. For example, the discrimination capacity in Chinese Han from Shanxi Province, Northern China was 0.9865, which indicates a high potential for differentiating between male individuals in this population . But in see below). In the AMOVA analyses, partitioning the genetic variance within and among tribes (model: ∼tribe), revealed that ∼27% of the genetic variance is found between tribes and ∼73% within tribes. This is similar to a recent study by Ashirbekov et al. (2017) who surveyed Y-STR polymorphism, including more detailed analyses of haplogroup subclades based on SNP polymorphism, for 1269 Kazakh men sampled from 10 tribes in Southern Kazakhstan , one in the middle (Kongyrat tribe) and one in the Senior zhuz . We assume that these clusters represent different daughter branches of the C-M217 haplogroup. A Y-STR study by Ashirbekov et al. sampled 564 individuals  from tenIn conclusion, although several papers have described genetic polymorphism at Y-STR’s among Kazakh tribes, this is the largest study, published in English, and represents individuals from tribes in all three zhuzes as well as individuals from the Kozha and Tore tribes. Overall, we find evidence of genetic differentiation between zhuz (∼10%) and between tribes within zhuz (∼20%) suggesting that there are differences in haplogroup structure among Kazakh tribes. Although we did not find evidence of a linear relationship between genetic and geographic distance among paired individuals (i.e. non-significant Mantel test), we observed the imprint of higher frequencies of C2 haplogroups along the southern and western border of Kazakhstan, which corresponds to both the path of the Mongolian invasion and the approximate route of the ancient Silk Road. A broader spatial and temporal analysis of the Y-STR diversity among Kazakh tribes within the context of other groups in Central Asia is needed to further elucidate this dynamic history