Tenualosa ilisha) species, collected from nine strategic habitats, across their diverse migratory habitats, which include sea, estuary, and different freshwater rivers. The NextRAD technique successfully identified 15,453 single nucleotide polymorphism (SNP) loci. Outlier tests using the FST OutFLANK and pcadapt approaches identified 74 and 449 SNPs (49 SNPs being common), respectively, as putative adaptive loci under a divergent selection process. Our results, based on the different cluster analyses of these putatively adaptive loci, suggested that local adaptation has divided the Hilsa shad population into two genetically structured clusters, in which marine and estuarine collection sites were dominated by individuals of one genetic cluster and different riverine collection sites were dominated by individuals of another genetic cluster. The phylogenetic analysis revealed that all the riverine populations of Hilsa shad were further subdivided into the north-western riverine (turbid freshwater) and the north-eastern riverine (clear freshwater) ecotypes. Among all of the putatively adaptive loci, only 36 loci were observed to be in the coding region, and the encoded genes might be associated with important biological functions related to the local adaptation of Hilsa shad. In summary, our study provides both neutral and adaptive contexts for the observed genetic divergence of Hilsa shad and, consequently, resolves the previous inconclusive findings on their population genetic structure across their diverse migratory habitats. Moreover, the study has clearly demonstrated that NextRAD sequencing is an innovative approach to explore how dispersal and local adaptation can shape genetic divergence of non-model anadromous fish that intersect diverse migratory habitats during their life-history stages.The migration of anadromous fish in heterogenic environments unceasingly imposes a selective pressure that results in genetic variation for local adaptation. However, discrimination of anadromous fish populations by fine-scale local adaptation is challenging because of their high rate of gene flow, highly connected divergent population, and large population size. Recent advances in next-generation sequencing (NGS) have expanded the prospects of defining the weakly structured population of anadromous fish. Therefore, we used NGS-based restriction site-associated DNA (NextRAD) techniques on 300 individuals of an anadromous Hilsa shad ( Tenualosa ilisha (subfamily Alosinae) is an anadromous and important trans-boundary fish that lives in the Bay of Bengal and migrates to the upstream rivers of Bangladesh (86% share), India (8% share), and Myanmar (4% share) for feeding, breeding, and the nursing of offspring [The Hilsa shad ffspring ,2. Sinceffspring . While tffspring . Howeverffspring . Moreove Myanmar % share fWhile Hilsa shad is largely anadromous, it has also been indicated that the fish may follow an amphidromous migratory pattern, because both immature and mature fish often migrate between marine and freshwaters not only for breeding, but also for feeding purposes . In addiThe discrimination of populations, as management units, needs to be overtly implemented for the sustainable exploitation of the anadromous fish species. However, most of the anadromous fish species are distributed across diverse habitat types, causing natural selection to play an important role in promoting genetic discrimination and local adaptation . As an aThe recent development of next-generation sequencing (NGS) techniques has expanded the prospects of providing insights into the molecular basis of local adaptation for fish with a low genetic differentiation. This technique allows for the genotyping of thousands of genome-wide single nucleotide polymorphism (SNP) loci for ecologically important fish, without any reference genomes, to discover a large number of genetic markers . The disST OutFLANK and pcadapt approaches to ascertain a set of neutral and adaptive genetic markers to better understand whether there is a neutral and/or adaptive genetic variation associated with their distribution in heterogenic environments. Finally, we conducted a homology search to align the NextRAD sequence tags of the adaptive loci to the known genes in public databases in order to elucidate the homologous functions of these genes, which might be associated with the divergence local adaptation of Hilsa shad.The degree of genetic discrimination among the Hilsa shad populations, available in different migratory routes, has remained obscure until today. Therefore, the aims of the present study are to discriminate the fine-scale genetic divergence of Hilsa shad populations and to reconcile previous inconclusive findings on the population genetic structure across their diverse migratory habitats. In this study, we employed the NextRAD sequencing technique to genotype 15,453 SNP loci for 300 individuals of Hilsa shad, collected from nine strategic habitats, including sea, estuary, and different rivers in Bangladesh. The different spatial analyses, using the entire 15,453 SNP dataset, revealed a very weak genetic discrimination among the different population of Hilsa shad. Therefore, we applied both the FIn the geographical region of Bangladesh, Hilsa shad mainly inhabits the Bay of Bengal (sea), including the lower regions of the estuary (Meghna estuary), but it migrates to the upstream rivers, mainly the Ganges–Brahmaputra–Meghna (GBM) river systems, during the spawning season and returns to its original habitat, after spawning, in adulthood. Jamuna River  joins the Padma River  in Goaland, in the Rajbari district of Bangladesh, and the combined flow of the Padma and Jamuna Rivers flow downwards, forming the Padma River. The Meghna, coming from the northeast region of the country, joins with the Padma further downstream in Chandpur and flows downwards to the south, forming the Meghna River, which finally meets the Bay of Bengal through the formation of a large estuary, named the Meghna Estuary . haor basin , where waters settle the sediment loads, before a confluence, named the Meghna. Due to these characteristics, the Meghna River and its tributaries are considered to be clear water rivers, and their suspended sediment concentrations are about 20–750 mg/l [According to the geography of Bangladesh, the Padma–Jamuna Rivers are considered to be the northwestern rivers, which together discharge about 1 billion tons of sediment annually, placing the Padma–Jamuna in the top three rivers in the world . Therefo750 mg/l , but the750 mg/l . T. ilisha were collected from nine strategic habitats across the migratory routes of Hilsa shad, including sea, estuary, and major freshwater river systems in Bangladesh  by fragmenting the genomic DNA ,40 with http://sourceforge.net/projects/bbmap/): bbmap/bbduk.shin=reads/run_ 1612/1612_GTAGAGGACTAAGCCT_S483_L006_R1_001_subset.fastq.gzout=reads/run_1612/1612_GTAGAGGACTAAGCCT_S483_L006_R1_001_t.fastq.gz ktrim=r k=17 hdist=1 mink=8 ref=bbmap/resources/nextera.fa.gz minlen=100 ow=t qtrim=r trimq=10. A de novo reference was created by evenly collecting a total of 10 million reads from the samples and excluding reads that had counts of <7 or >1000. The remaining loci were then aligned to each other to identify allelic loci and collapse allelic haplotypes into a single representative. All reads were mapped to the reference, with an alignment identity threshold of 0.95, using bbmap (BBMap tools). Genotype calling was conducted using callvariants (BBMap tools) . The vcf was filtered to remove alleles with a population frequency of <3%. Loci that were heterozygous in all samples or had more than 2 alleles in a sample  were removed. The absence of artifacts was checked by counting the SNPs at each read nucleotide position and determining that the SNP number did not increase with the reduction of the base quality at the end of the read. The reads were trimmed using bbduk in custom scripts of SNPsaurus, LLC  The original shadstringent.vcf file contained data for 26,718 SNPs loci, existing within a catalog of 92,721 consensus NextRAD tagged sequences of 150 bases each. A column containing a unique ID for each SNP locus was added to the unfiltered vcf file, using a custom perl script to remove the redundancy among loci. Further filtering steps included the removal of complex SNPs with more than two alleles, an overall minor allele frequency of less than 5%, and a completeness of data among samples of less than 80%. Likewise, samples containing a completeness of data of less than 80% among the remaining loci, a minimum quality score lower than 30, and a mean depth per genotype lower than 20 were removed from the dataset. Additionally, where there were multiple SNPs located in a single NextRAD sequence tag, only the first cataloged SNP was kept in the dataset so as to avoid the possibility of a single NextRAD locus having a disproportionate effect on the analyses. The unique IDs for the SNP loci that passed quality control standards were transferred to a whitelist, which was used to filter the original vcf file using a custom perl script. After all of the filtering steps were complete, a total of 15,453 individual SNP loci remained in the dataset.p-values of each locus to detect adaptive loci [ST threshold value to 0.05 in the OUTFLANK approach and the false discovery rate (FDR) threshold value to 0.05 in the pcadapt approach. A neutral loci dataset and an adaptive loci dataset were created from the output of these two approaches for all downstream analyses. The GenoDive version 3.0  was used to conduct analysis of molecular variance (AMOVA) analyses on both datasets [ST to determine the genetic differences between collection sites for the neutral and outlier datasets using the default settings, with the samples grouped by collection site. An isolation by distance analysis, using the outlier dataset, was conducted in the “adegenet” R package, using a pairwise distance matrix for all collection sites. Significance testing for the isolation by distance analysis was conducted through a Mantel test, using an Edward’s genetic distance matrix and a physical distance matrix between the collection sites, with 9999 iterations . In addition, each adaptive locus was subjected to a BLASTn search of all sequences in the NCBI non-redundant database . Principal component analysis (PCA) was conducted using the adegenet R package  and both the neutral and outlier datasets. The Bayesian clustering method, implemented in the STRUCTURE software v. 2.3.4 , was used to genetically assign individuals to clusters [The initial clustering analyses, through several spatial structuring programs using all 15,453 putative SNPs loci, revealed extremely low to no genetic structuring among all collected individuals from different environments. Therefore, we identified outlier SNPs using the adegenet v2.0.1 R package  and two ive loci ,44. Defaclusters . Simulatclusters . The calclusters . The cluclusters . Clusterhttps://ddbj.nig.ac.jp), with the DRA accession number: DRA009185. The data is publicly available from 24 December 2019. Our raw data for 300 individuals were submitted to the DDBJ . As expected, the outlier SNPs detected by the FST OutFLANK and pcadapt approaches showed higher significant FST values than the neutral SNPs, with a range of 0.020 to 0.327 (p ≤ 0.001) and 0.005 to 0.073 (p ≤ 0.001), respectively. In both approaches, higher FST values were observed between the Meghna estuary (ME) and upper Jamuna river (UJR)  and deep sea (DS) and UJR  collection sites. As anticipated, non-significant and lower FST values were observed between the collection sites from the two locations of sea, the sea and estuary, and the lower and upper portion of the same rivers and/or their tributaries.A pairwise Fere used . An appaST values of 0.097 and 0.015 for the FST OutFLANK and pcadapt approaches (p < 0.001), respectively  but no differentiation among individuals (−12.8% and −3.2%). A substantially low but significant divergence (p < 0.001) was observed (9.7% and 1.5%) among the different collection sites of Hilsa shad. Similarly, an overall FST value of 0.002 was observed in the putative panel of neutral SNP loci identified by both approaches (p < 0.001). Consistent with the putatively adaptive loci, the AMOVA analysis of the neutral loci for both approaches demonstrated a 100.5% variation between individuals, no variation (−0.7%) among individuals, and a substantially low (0.2%) but significant variation (p < 0.001) among the different collection sites of Hilsa shad  collection sites were dominated by individuals of cluster A, while different riverine (freshwater) collection sites were dominated by individuals of Hilsa shad of cluster B  of the outlier SNPs, using both the Fluster B . HoweverST OutFLANK approach demonstrated nine clusters at a finer-scale level under two major clusters, as revealed for the outlier datasets identified by the pcadapt approach  scatterplot on the putatively adaptive SNPs identified by the pcadapt approach also revealed two genetic clusters B. Howeveapproach A. Furtheapproach . Mixed aapproach .T. ilisha is composed of a single panmictic population  and the north-eastern riverine (clear freshwater) ecotypes.These clustering patterns were further confirmed by neighbor-joining (NJ) trees, reconstructed based on Nei’s genetic distances . The NJ ST OutFLANK and pcadapt approaches, revealed a strong and significant relationship between the genetic and geographic distance, with R2 = 0.4871 (p < 0.01) and R2 = 0.4369 (p < 0.01), respectively. Analyses of the neutral dataset indicated a high genetic connectivity and weak differentiation between the populations by geographical distance  outlier loci identified by the pcadapt approach and 11 out of 74 (13.9%) outlier loci identified by the FRevealing the spatial and temporal dispersal of fish stocks is important for the systematic monitoring and management of fish populations. This study applied NextRAD-based data to assign Hilsa shad individuals to their respective origin populations to explore the variation in stock components and catch compositions. Loci with a high resolving power and potentially important local adaptation to the environment were detected and validated. We observed a remarkable differentiation between the individuals of marine and estuarine collection sites in the south and freshwater riverine collection sites in the north of Bangladesh, with a slight mixing between them, confirming the general validity of the stock designations. In contrast to traditional markers for detecting genetic differentiation, the genomic approach identifies the traces of selection that shape population divergence . GeneticST estimates, based on the neutral dataset, indicates that a large fraction of the genome is undifferentiated among the collection sites, with 19.4% of estimates being <0.001 (p ≤ 0.001) . The neutral set of markers showed an extremely low to no genetic structuring between all collection sites individuals from the different environments. Pairwise F≤ 0.001) . As expeb gene nucleotide sequencing [The lack of genetic structure in the neutral loci indicates that all Hilsa shad individuals from different collection sites are connected via high levels of gene flow between the marine water and freshwater environments, which is consistent with previous studies using allozyme ,15, restquencing ,19. The quencing . The expquencing . ST OutFLANK , was an order magnitude greater than those in the putatively neutral loci dataset . While it is difficult to distinguish between differentiations caused by selection or drift processes [Our results concerning the outlier loci also indicate that the local conditions are sufficiently different to prevent the genetic homogenization of the Hilsa shad individuals collected from the different geographical regions through the selection process . We obserocesses , it is nrocesses  and likerocesses . Secondlrocesses ,7.Jatka) of a particular habitat return to their respective natal rivers (the rivers where they were born/nursed) for spawning as adults [ST values (p ≤ 0.01) to 0.127 (p ≤ 0.001). Accordingly, the Hilsa shad individuals from similar tributaries share similar structuring patterns, which evidently supports the isolation by distance (IBD) concept and the ecologically adaptive behavior of the Hilsa shad. This species spends most of its lifetime in the shallow sea (SS), becomes sexually mature, and migrates to its respective natal spawning grounds in the upper river systems [The STRUCTURE analysis of the outlier loci demonstrated that individuals from the various locations were assigned either entirely to one subpopulation or entirely to the other subpopulation, indicating that the admixture between these two genetically distinct ecotypes is very limited and may also be reproductively isolated from each other see the . The Hils adults . It is as adults ,6,7. Anos adults ,6,7. HowT values , SS is l systems . This mi systems . It is mThe NJ phylogenetic trees, based on the outlier loci detected by the two approaches, further subdivided the major riverine Hilsa shad clusters into two discrete sub-clusters: The north-eastern and north-western riverine groups. Therefore, the such structuring into two sub-clusters, which mirrors the spatial structuring that is maintained by environmental differences, such as the turbidity and salinity levels in the marine or brackish, muddy/turbid freshwater (north-western riverine) and clear freshwater (north-eastern riverine) habitats. Due to the effect of the different environmental conditions, the fishes of the north-western riverine habitats are of a bright silvery color, with a thicker structure, while the fishes of the north-eastern riverine are slimmer, a bit darker and elongated . PreviouST OutFLANK and pcadapt approaches, which successfully identified 74 and 449 SNPs, respectively  and north-western (turbid freshwater) riverine groups. Besides the environmental differences, these genetic discrimination of Hilsa shad population might also be related to spatial autocorrelation of genotype frequencies and the IBD pattern. Our study provides both a neutral and adaptive context for the observed genetic divergence of Hilsa shad and, consequently, reconciles the previous inconclusive findings on their population genetic structure across their diverse migratory habitats. In the context of fisheries management, our results suggest that it is important to maintain the genetic diversity of Hilsa shad in each habitat, as the fishes are capable of a high level of gene flow within the population but a lower variation across most of their migratory distribution range. Local adaptation due to the imposing selective pressure has a pivotal role in maintaining high frequencies of particular genetic traits in each heterogenic habitat. Therefore, special attention should be paid to the management of the upstream riverine Hilsa shad population, given that the selective pressures that maintain the adaptive genetic variations in these habitats are at a high risk due to increased fishing pressure and adverse climatic conditions. Ultimately, our study has clearly demonstrated that NextRAD sequencing is an innovative approach to exploring how dispersal and local adaptation can shape the genetic divergence of non-model anadromous fish that are found in diverse migratory habitats during their life-history stages.


Java Island is one of the islands in Indonesia which has local sheep breeds with specific characteristics and native development geography in certain regions. This study aimed to determine the genetic profiles and maternal origin of six local sheep breeds on Java Island.This study was conducted by identifying the profiles of complete mitochondrial DNA (mtDNA) displacement loop (D-loop) region sequences on a total of 22 individual in six local sheep breeds on Java Island, including Javanese thin-tailed (JTT), Javanese Fat-Tailed (JFT), Batur (BTR), Wonosobo (WSB), Garut (GRT), and Priangan (PRG) sheep. The D-loop region was amplified using specific primers, and the polymerase chain reaction (PCR) was performed. The PCR products were purified and sequenced.The mtDNA D-loop analysis identified 21 haplotypes in the analyzed 22 animals with 123 polymorphic sites (V) consisting of 60 singleton variable sites (S) and 63 parsimony informative sites (P). Within all breeds tested, the haplotype diversity, the average number of pairwise differences (K), and nucleotide diversity (Pi) were 0.99567, 25.36364, and 0.02153, respectively. The genetic distance (D) within groups and between groups was 0.001-0.006 and 0.004-0.036, respectively. The phylogeny resulted in the presence of two haplogroups (Hap), which are 5 Hap A and 16 Hap B. All JTT, JFT, BTR, and WSB breeds were in the same cluster in Hap B, whereas GRT and PRG breeds were in clusters in both Hap A and Hap B.The high genetic diversity in six local sheep breeds on Java Island suggests that they originated from different genetic sources. JTT sheep have closer genetic relationships to JFT, BTR, and WSB sheep, and they are close to European sheep, whereas GRT sheep have closer genetic relationships to PRG sheep. Both are closer to Asian sheep than to European sheep. Indonesia is an archipelago country that has specific characteristics in each Island and a variety of natural and human resources. Java Island is one of the islands in Indonesia, which consists of four provinces  and two special regions (Jakarta and Yogyakarta). In general, these regions have similar characteristics, but in certain regions, they have unique characteristics regarding geographic features, natural resources, social, and cultural background. The character of the region and different natural resources dictate the type a socio-cultural community that will be established, at least with respect to farming activities. Farming activities adjust to the conditions of the area, including the selection of livestock that is suitable for rising. Sheep are one of the many livestock raised by farmers on Java Island that have a notable value in society ,2. SheepOne method to determine genetic diversity, relationships and origins of local Indonesian sheep are to examine the mitochondrial DNA (mtDNA) profile. The mtDNA is an important genetic study tool in population and systematic molecular genetics because it has many copies with a rapid evolutionary rate and is inherited . One parThis study aimed to determine the complete mtDNA D-loop sequences of six local sheep breeds on Java Island, Indonesia. The results of this study can be used to determine genetic diversity, genetic distance, and relationships between local sheep breeds and other species of sheep on Java Island. Furthermore, the results can be added to databases and used to complement previous studies on genetic diversity and relationships of local Indonesian sheep, especially on Java Island.This study was approved by the Animal Care and Use Committee of the Faculty of Veterinary Medicine, Universitas Gadjah Mada, with the ethical clearance number 002/EC-FKH/Int/2019, and the National Political and Unity of Yogyakarta Special District with the approval number 074/1850/Kesbangpol/2019.This study was conducted using blood samples from 22 individual sheep in six populations of local sheep breeds on Java Island and is presented in http://primer3.UT.ee//) [Ovis aries (GenBank accession number: AF010406.1). The mtDNA D-loop region primer sequences were Alek-DLF: 5’-GAAGAAGCTATAGCCCCACT-3’ and Alek-DLR: 5’-GATTCGAAGGGCGTTACT-3’ that generated 1397 bp of the PCR product. The PCR reaction consisted of 4 μL of DNA template, 25 μL of KAPA2G Fast Ready Mix+Dye (Kapa Biosystems Ltd.), 2 μL of forward primer, 2 μL of reverse primer, and 17 of ddH2O. The PCR amplification was conducted using Cleaver GTC96S (Cleaver Scientific Ltd.) according to the program: 6-min of pre-denaturation at 94°C, followed by 35 cycles, each consisting denaturation at 94°C for 30-s, primers annealing at 47°C for 40-s, extension at 72°C for 90-s, then ending with a final extension at 72°C for 5-min, and storage at 4°C. The PCR product was visualized using 1.5% agarose gel, and electrophoresis was run at 100 mV for 30-min. The result of amplification could be seen on the UV illuminator. The purified PCR products were sequenced by 1st BASE-Asia, Malaysia.The DNA was extracted based on the manufacturer’s standard protocol using PureLink™ Genomic DNA Mini Kits . The mtDNA D-loop was amplified directly from the genomic DNA by polymerase chain reaction (PCR). The primer was designed using the Primer3 online version 4.1.0 program (UT.ee//)  based onThe product length of the D-loop region sequences amplification for each individual is 1800 bp and was analyzed using the molecular evolutionary genetics analysis (MEGA) version 7.0 software  . The D-lReference mtDNA D-loop region sequences of wild and domestic sheep of known haplogroup (Hap) types  were dowOvis aries (AF010406.1), was equal to 1180 bp. However, differences were found in the sequence at 908 where C nucleotide insertion and deletion in the sequence at 1037 except in the GRT2 sample, which still has a T nucleotide at the site.All local sheep breeds on Java Island have D-loop sequences of 1180 bp except for one sample (GRT2) that has a length of 1181 bp. The length of this sequence, as the long sequence of the D-loop on The alignment of mtDNA D-loop nucleotide sequences of local sheep breeds on Java Island enabled polymorphic site data to be obtained and is presented in The parameters of genetic diversity and HD of the mtDNA D-loop region in six subpopulations of local sheep breeds on Java Island are as shown in The value of genetic distance within and between groups is presented in The phylogenetic tree of 21 haplotypes in six subpopulations of local sheep breeds on Java Island and mtDNA D-loop sequences of wild sheep and domestic sheep categorized by Hap from GenBank are presented in O. aries (AF010406.1), which is 1800 bp, but there is a difference at the 908 site where the C nucleotide is inserted. A deletion occurs at the 1037 site except for GTR2 samples . The nucleotide composition of six local sheep on Java in this study was almost similar to Tibetan sheep [The sequence length, in this study, is the same as the length of the D-loop sequence in  samples , which h samples , but stian sheep ,27, Smalan sheep , and Alpan sheep , with thGenetic diversity, besides reflecting differences in traits between individuals, also reflects small differences in nucleotides . Geneticet al. [Genetic distance is the estimate of the closeness of genetic relationships or phylogenetics between the population, according to the Nei . Geneticet al. , who fouet al. , the valet al. . Apart fet al. ,42, compet al. ,43, wholet al. ,45, and et al.  and/or tAn HD value in the range ≥0 <0.5 was included in the low category, whereas an HD value in the range >0.5 ≤1 was included in the high category ,35. BaseThe results of analyzing 22 individual samples were used as the basis to form 21 unique haplotypes and one shared haplotype. A comparison of the number of individual samples and the number of haplotypes  indicateet al. [Domestic sheep were divided into five Hap, namely, A, B, C, D, and E . Based oet al.  that Indet al. ,55. Thiset al. , easternet al. , and Kaiet al.  that foret al. , Romaniaet al. , and Ibeet al.  where Haet al. , Tibetanet al. , and natet al. , where HOvis musimon (European Mouflon)  . In cont , and from Europe, including Britain, Portugal, and the Netherlands/Dutch, traded in this region. Java Island is one of the islands in the Nusantara (Indonesia) that is a strategic destination of various regions for exploring and trading [Indonesia is an archipelago country between two continents  and two oceans (Indian and Pacific). In the past, this area was named  trading ,65. This trading . No studThis study shows that most local sheep breeds on Java Island are included in Hap B, which are sheep that have a close relationship with European sheep, even though this country is on the Asian continent. However, there are also local sheep breeds on Java Island that are included in Hap A. This indicates that the sheep that developed on Java Island were the result of crossing Asian and European sheep. However, this study is still limited to a small number of samples, but it can be used as a database for further research. Observations with data from mtDNA are used to determine the maternal inheritance line. It is necessary to have additional observations of the male’s line so that both maternal and paternal lines can be known to find out more about the origin of developing breeds. In Indonesia, aside from Java Island, there are still other local sheep breeds that have been established by the Ministry of Agriculture, whereas others have not despite their long development in the region. Thus, further research on these breeds still needs to be done. In-depth studies need to be performed on the genetic profiles of local Indonesian sheep breeds with more samples, a wider area, more comparative data, and various other methods that can describe in more detail the origins, characteristics, and productivity of Indonesian sheep breeds.The high genetic diversity of six local sheep breeds on Java Island suggests that they originated from different genetic resources. The JTT sheep have a closer genetic relationship to the JFT, BTR, and WSB sheep, and they are close to European sheep. In contrast, the GRT sheep have a closer genetic relationship to the PRG sheep. Both are closer to Asian sheep than they are to European sheep.WTA supervised the present study, and IGSB and RW designed and coordinated the study. AI performed the experiment, analyzed the data, and wrote the manuscript. The final manuscript has been read and developed in consultation with all authors. All authors read and approved the final manuscript.


Social scientists have observed previously that patient support groups began to have significant influence over both research and clinical services of medical genetics in the early 2000s. This observation led to the idea of genetic citizenship, suggesting that the active participation and intervention of patient support groups in the rapidly growing field of medicine marked the emergence of a new form of citizenship. To understand how this citizenship emerged, this paper examines the development of umbrella organizations of genetic support groups in the USA and the UK. The historical analysis demonstrates that the ways in which these organizations developed differ considerably, and that their visions and activities reflected the different structural and cultural organizations of medical genetics in their respective countries. By recognizing the early work of these organizations as citizenship projects, this article argues that they helped rather different forms of genetic citizenship to emerge in the two countries. In this article, I study the rise of a form of citizenship associated with advances in medical genetics – that is, genetic citizenship. I do so through a historical analysis of the development of two organizations: the Alliance of Genetic Support Groups  in the USA and Genetics Interest Group  in the UK. These umbrella organizations – so called because they provide common organizational structures linking a number of different genetic disease organizations – were both established in the 1980s, and have since been active in the field of medical genetics in and beyond their respective countries. Earlier social studies of medical genetics have noted the importance of these organizations  individuals as potential citizens, and the ways in which they tried to act upon them” , 439. AnIn the next section, I first present a brief review of the literature on the new genetics, and contrast it with that on the active roles of patient organizations working in that field. Following a short section on methodology, I then present detailed histories of the AGSG and GIG. I show that the AGSG was developed as a venue through which patient organizations could share their knowledge and skills as resources with which they engage with professional genetic services. GIG, in contrast, was formed primarily to represent a unified voice of patient organizations in policy debates. In the discussion, I focus on the question of what their contribution to the citizenship project was, and argue that different genetic citizenship projects emerged in the two countries because the national specificities of healthcare and genetic services – what Parthasarathy  calls thAt the turn of the century, the term “the new genetics” was criticized by social scientists as a rhetorical device serving to obscure a resurgence of eugenic thinking  recommended that genetic counseling should not just concentrate on explaining the medical aspect of genetic disorders but should also attend to the psychosocial impacts of genetic diagnosis . Reflecting the ongoing changes in medical genetics, she framed the conference theme as fostering an “interdisciplinary” approach to genetic services – inviting, for example, geneticists Edward Hsia and Arno Motulsky, clergyman Robert Baumiller and Eugene Lipman, legal scholars Alexander Capron and Phillip Reilly, genetic counselors Joan Burns and Joan Marks, and social work scholars Sylvia Schild and Rita Beck Black, as well as parents of patients with genetic disorders. By getting them all in the same room, the event successfully signaled that genetic services would be better delivered through interdisciplinary teamwork McKusick . Weiss’sGenetics Support Groups: Volunteers and Professionals as Partners . Before her departure, Weiss had begun to take a more active role in policy advocacy, notably around genetic discrimination . With the identification of the PXE gene in 2000, however, the group came to be seen as a successful model for patients and families to “participat[e] in research as active and critical collaborators as well as donors of genetic material” . The program was conducted at three regional services – Cardiff, Manchester, and the ICH – and its interim report appeared in 1987, recommending molecular genetics laboratories be integrated into genetic services . Many were already experiencing anxiety, simply from knowing that they had a 50% risk of developing the disease that had so dramatically changed their parents’ live  GIG , 2006. SIn May 1988, Hunt and Lavery made a poster presentation at the Clinical Genetics Society (CGS) meeting, setting out their intention to establish the association .GIG made several important developments in the early 1990s, including the appointment of Alastair Kent as its director. Although members of the management committee, particularly chairperson Ann Hunt, were passionate about GIG’s work, its activities, which relied on their voluntary work, remained responsive and somewhat haphazard, and the member organizations were not always well informed about them, inevitably leaving some dissatisfied (interviews UK03 and UK05). At the committee meeting held in January 1991, it was suggested that “it was time to review direction of GIG and to address major issues” GIG . GIG firAnother important development was the creation of the European Alliance of Genetic Support Groups in 1992. Ysbrand Poortman, who founded the Dutch umbrella organization for genetic disorders called VSOP, led its creation in response to political integration in Europe. In 1991, patient organizations were invited for the first time to the European Society of Human Genetics (ESHG) annual congress, and there a preliminary meeting to consider forming a pan-European organization was held .The different constitutions of the two umbrella organizations, and the different forms of genetic citizenship they embodied, were partly due to the visions and personalities of their founders. Yet they were also shaped by the different ways in which genetic services developed in the USA and the UK, and the different needs and opportunities they presented to patients and families affected by genetic disorders. In both countries, genetic services initially grew from the clinical and research interests of a handful of pioneer medical geneticists. From there, however, they followed rather different trajectories.In the USA, genetic services were shaped by “the model of business enterprises” (Mulvihill, Walters, and Wertz In contrast, genetic services in the UK developed under the National Health Service, and were shaped by the universalistic expectation that “any innovation of proven value should be available to all patients” (Harris and Wertz Genetic umbrella organizations in the USA and the UK thus pursued rather different citizenship projects, reflecting the divergent structural and cultural organizations of medical genetics in the two countries – what Parthasarathy  calls thet al. Of course, these differences were never clear cut or absolute, and there was considerable overlap. In both countries, genetic citizenship drew heavily on patients’ own experiences and the expertise that entailed. And in both countries, the multiplicity of different disease organizations sustained a diversity of initiatives aimed at securing the best services for patients, with which umbrella organizations inevitably became entangled. Not least, in both settings, the activity of umbrella organizations and their constituent disease organizations raise questions concerning any organization’s capacity and legitimacy to represent the interests of its members (Jongsma


Melospiza melodia) to quantify the differences in mean breeding values for major sex‐specific reproductive traits, specifically female extra‐pair reproduction and male paternity loss, between recent immigrants and the previously existing population. We thereby quantify effects of natural immigration on the means, variances, and cross‐sex covariance in total additive genetic values for extra‐pair paternity arising within the complex socially monogamous but genetically polygynandrous reproductive system. Recent immigrants had lower mean breeding values for male paternity loss, and somewhat lower values for female extra‐pair reproduction, than the local recipient population, and would therefore increase the emerging degree of reproductive fidelity of social pairings. Furthermore, immigration increased the variances in total additive genetic values for these traits, but decreased the magnitudes of the negative cross‐sex genetic covariation and correlation below those evident in the existing population. Immigration thereby increased the total additive genetic variance but could decrease the magnitude of indirect selection acting on sex‐specific contributions to paternity outcomes. These results demonstrate that dispersal and resulting immigration and gene flow can substantially affect quantitative genetic architectures of complex local reproductive systems, implying that comprehensive theoretical and empirical efforts to understand mating system dynamics will need to incorporate spatial population processes.Quantifying additive genetic variances and cross‐sex covariances in reproductive traits, and identifying processes that shape and maintain such (co)variances, is central to understanding the evolutionary dynamics of reproductive systems. Gene flow resulting from among‐population dispersal could substantially alter additive genetic variances and covariances in key traits in recipient populations, thereby altering forms of sexual conflict, indirect selection, and evolutionary responses. However, the degree to which genes imported by immigrants do in fact affect quantitative genetic architectures of key reproductive traits and outcomes is rarely explicitly quantified. We applied structured quantitative genetic analyses to multiyear pedigree, pairing, and paternity data from free‐living song sparrows ( Reproductive interactions among females and males, and resulting production of offspring, are critical processes that propagate genes across generations and thereby drive evolution. Evolutionary ecologists consequently aim to identify processes that shape reproductive outcomes, and particularly to understand what determines which males successfully sire females’ offspring. Paternity can be greatly affected by genes expressed in interacting females and males, and by associations between these genes across the sexes. Quantifying such cross‐sex genetic associations, and understanding how these associations are maintained and constrained, is therefore central to understanding the course of evolution.Cross‐sex genetic associations can be shaped by processes acting within any focal population, including local natural selection and mate choice . But, they could also be substantially affected by genes imported by immigrants. Resulting “gene flow” could increase local genetic variation, and alter the critical cross‐sex genetic associations. However, such effects have not been explicitly quantified in wild animal populations.Accordingly, we provide a framework for conceptualizing and estimating effects of immigrants on local genetic variation and cross‐sex genetic associations. We apply this framework to paternity data from free‐living song sparrows. These sparrows are socially monogamous but show substantial extra‐pair paternity; many offspring are sired by males other than a female's socially paired mate. We show that immigrants import genes that increase male paternity success and tend to decrease female infidelity; immigration therefore increased genetic pair fidelity in the recipient population. Furthermore, immigration weakened the cross‐sex genetic association between male paternity success and female infidelity, reducing the degree to which selection for male success would induce female infidelity. Our results illustrate how natural immigration can alter the genetic basis of complex reproductive systems, and imply that understanding evolutionary dynamics will require evolutionary ecologists to consider sexual selection in the context of large‐scale meta‐population systems.The pattern of paternity that emerges across offspring of interacting females and males in any population constitutes the outcome of sexual selection, and determines which genes and genotypes pass to subsequent generations. Identifying processes that shape paternity outcomes is therefore central to understanding the evolutionary dynamics of reproductive traits and overall reproductive systems  paternity occurring in socially monogamous or group‐living species. Here, a focal female's offspring could be sired by her socially paired male(s), or by other male(s) in the population Fig. . Such exExtra‐pair paternity reflects expression of numerous underlying traits, including simultaneous polyandry  and subsequent postcopulatory female choice, alongside mating frequency and postcopulatory siring success under sperm competition of a female's socially paired male . We thereby quantify effects of gene flow resulting from immigration on additive genetic means, variances, and covariances in female extra‐pair reproduction and male paternity loss relative to the existing local population. In doing so, we provide a general framework for understanding how natural immigration can alter the quantitative genetic architecture of the local reproductive system or other emergent traits, and illustrate how quantitative genetic consequences of immigration can now be explicitly evaluated in wild populations.Accordingly, we first present a general conceptual and analytical quantitative genetic framework for quantifying immigrant effects on means, variances, and cross‐sex covariances in additive genetic values. We highlight how this approach can be applied to extra‐pair paternity, which constitutes one key emergent trait that characterizes reproductive systems. We then implement such analyses using multigeneration pedigree, pairing, and paternity data from song sparrows  facilitate estimation of quantitative genetic parameters in wild populations in the absence of structured breeding designs Kruuk . Extensied Quaas .ui for any trait equals its breeding value ai for that trait  plus the product of the mean immigrant genetic group effect g and the proportion of the focal individual's genome qi that is expected to have originated from the immigrant genetic group  and genetic group contributions (qi) are inherited by offspring from parents following standard assumptions of the infinitesimal model of quantitative genetics variances) in and among focal traits, assuming these (co)variances are equal for the phantom parents of the founder and immigrant genetic groups  and Var(am), the cross‐sex additive genetic covariance cov, and the mean genetic group effect on each trait . The two traits could be sex‐limited phenotypes, as is often of interest in the context of reproductive systems, or could be the same phenotype expressed to different degrees . The variances and covariance in total additive genetic values (Var(uf), Var(um), and cov) can then be calculated as functions of estimated (co)variances of the two underlying variables ai and qi and the fixed effect g (see eq. um). Meanwhile,Specifically, given any two traits expressed by females and males , appropriately specified genetic groups animal models can directly estimate the additive genetic variances Var( see eq. :(2)Varuu relative to the variances and cross‐sex covariance in a, and hence the total genetic (co)variance. Equation (u) above Var(a) to a degree that depends on the magnitude of the difference in mean breeding value between the immigrant and founder groups ), and the variance in immigrant ancestry among individuals (Var(q)). As g2, Var(q), and Var(a) cannot be negative, Var(u) cannot be less than Var(a). Equation  relative to cov to a degree that depends on the signs and magnitudes of gf and gm, the magnitude of Var(q), and the sign and magnitude of cov. Consequently, cov could be larger or smaller than cov with the same sign, or the sign could be reversed, potentially transforming a negative cross‐sex covariance in a into a positive cross‐sex covariance in u  and Var(am)) and the cross‐sex additive genetic covariance ) can be estimated given sufficient observations of paternity outcomes across breeding attempts made by females and males of known and varying relatedness (see Methods section). The total additive genetic variance in liability for extra‐pair paternity  that is available for selection can then be estimated as:gf and gm alongside Var(af), Var(am), and cov. The quantities Var(uf), Var(um), and cov can then be calculated  form female–male social pairings that defend territories and care for dependent broods ), and detectable additive genetic variance in male liability to lose (or achieve) paternity (Var(am), Reid et al. af,am)) was estimated to be weakly positive , but with substantial uncertainty that might partly reflect unknown structure in the data  and male paternity loss Var(am), the cross‐sex additive genetic covariance cov, and immigrant genetic group effects on each sex‐limited trait  through their own reproduction or that of surviving offspring produced during 1989–1992. We defined the founder genetic group as the phantom parents of all other individuals with unknown parents remaining in the pedigree after pruning to informative phenotyped individuals and their known ancestors variances, yielding estimates of permanent individual, pair, and year variances , Var(um), and cov using equations (q) as a constant estimated across all phenotyped individuals (Supporting Information aT) and Var(uT)  and cor were calculated as the respective covariances divided by the geometric mean of the variances. Latent‐scale heritabilities were calculated as the focal additive genetic variance divided by the sum of all estimated variance components ,,uf), VaT) eqs.  and 5. Tgf and gm to the observed phenotypic scale. We computed these effects for the middle year of the phenotypic dataset (2004) given mean male age across all observations (2.7 years), and compared the effect of mean observed q to q = 0 (representing an isolated population with no recent immigration). Finally, for purely illustrative purposes to aid conceptual insight, we computed and plotted posterior mean predicted values of afi, ami, ufi, and umi for all phenotyped individuals hatched between 2003 and 2012. Most of these individuals have phenotyped ancestors and descendants and numerous contemporary relatives, meaning that predicted breeding values are likely to be relatively little biased toward an individual's own phenotype.To illustrate the biological magnitude of estimated genetic effects of immigrants in altering the local mean extra‐pair paternity rate, and hence the reproductive system, we back‐transformed latent‐scale estimates of The dataset comprised 1177 broods and associated observations of extra‐pair paternity spanning 1993–2016 , whereas 12 female immigrants contributed ≥1 female and/or male offspring with an observed phenotype. Overall, all 17 female immigrants contributed to observed phenotypes either directly and/or through offspring. In contrast, only five male immigrants reared at least one brood during 1993–2016 and hence had an observed paternity phenotype , and one additional male immigrant contributed offspring with observed phenotypes. The other eight recent male immigrants did not breed, and therefore had no direct impact on any genetic characteristics of the focal population.qi) were 0.39 ± 0.24 SD and 0.38 ± 0.20 SD across all 295 phenotyped females and 309 phenotyped males, respectively ) and male paternity loss (Var(am), Table gf and gm, were negative for both traits (Table gf) overlapped zero, but that for male paternity loss (gm) scarcely did, and ∼97% of posterior density was negative (Table q = 0.37 would experience a predicted decrease in extra‐pair paternity rate from 0.37 (95% CI 0.10–0.63) to 0.18 (95% CI 0.06–0.28) compared to an otherwise identical population with no immigration and hence q = 0 .The genetic groups animal model estimated moderate additive genetic variances, and hence heritabilities, in female extra‐pair reproduction ) was negative, with a 95% CI that only marginally overlapped zero ) was less negative than that in breeding value , Table However, as both immigrant genetic group effects uf)) and male paternity loss (Var(um)) were slightly greater than the estimated variances in breeding values (Var(af) and Var(am), following eq. uf,um)) was considerably less negative than that in breeding value , Tables The variances in total additive genetic values for female extra‐pair reproduction (Var(uf) and Var(um) compared to Var(af) and Var(am), and the decrease in the (negative) magnitude of cor compared to cor, meant that Var(uT) exceeded Var(aT) by approximately 50%  compared to those in breeding values (ai). They thereby increased the total genetic variance available to generate an evolutionary response to selection and potentially altered the effective magnitude of indirect selection on sex‐specific reproductive strategy. Immigration therefore substantially altered the phenotypic expression and evolutionary potential of a key reproductive outcome, extra‐pair paternity, that can affect population‐wide distributions of survival, reproductive success, relatedness, and parental care  immigrants may originate from different source populations from previous immigrants with different mean breeding values for reproductive traits, and/or breeding values in immigrants’ source populations may have changed over time. There are still few rigorous data on extra‐pair paternity rates in other song sparrow populations. A North Carolina population showed lower mean phenotypic values than Mandarte (∼14% versus 28% chicks, ∼19% versus 44% broods; Krippel et al. Alternatively or additionally, the subset of individuals that immigrate into Mandarte and successfully breed may have changed over time. Specifically, individuals with high breeding values for extra‐pair reproduction or paternity loss may now be less dispersive, or be more likely to fail to breed following dispersal and hence have zero genetic impact on recipient populations. Such associations between dispersal and reproductive traits have been extensively examined in the context of outcrossing versus selfing (Massol and Cheptou Meanwhile, the observed differences in mean breeding values for extra‐pair paternity between recent immigrant song sparrows and defined founders may also reflect local evolutionary processes. Specifically, local direct or indirect selection, or drift operating in the small focal population, could have caused the genetic contributions of individuals with high breeding values for female extra‐pair reproduction and male paternity loss to increase across years. This hypothesis cannot be directly tested because breeding values for lineages that went locally extinct before 1993 cannot be evaluated. Future analyses with more years of data could test for increasing local mean breeding values since 1993. Indeed, current analyses suggested a slight increase in phenotypic extra‐pair paternity rate across years despite the negative effects of recent immigrants (Table However, it remains unclear how local selection could act to increase extra‐pair paternity; male paternity loss is likely to experience negative direct selection because low within‐pair paternity success is positively genetically correlated with low extra‐pair reproductive success (Reid et al. Overall, our conceptual framework and empirical results have important general implications for quantifying and interpreting the magnitude of cross‐sex genetic correlations, and associated indirect selection and sexual conflict, in wild populations. In showing that gene flow resulting from natural immigration can increase total additive genetic variance, and alter the cross‐sex genetic correlation for key reproductive traits, they imply that micro‐evolutionary dynamics of perplexing reproductive traits and systems, including extra‐pair paternity and polyandry, might not be understandable solely in terms of local components of selection. There is increasing evidence of spatial variation and local adaptation in reproductive and sexually selected traits in diverse systems, including latitude (Taylor et al. Associate Editor: A. CharmantierAppendix S1. Definitions and derivations.Appendix S2. Details of quantitative genetic analyses.Appendix S3. Additional summaries of dataset and results.Click here for additional data file.


Prunus armeniaca L.) germplasm was performed using molecular markers. Genetic diversity and structure of the cultivated apricot genetic resources were analyzed to decipher the history of diffusion of this species around the world. A common set of 25 microsatellite markers was used for genotyping a total of 890 apricot accessions in different collections from the center of origin to the more recent regions of apricot culture. Using a Bayesian model-based clustering approach, the apricot genotypes can be structured into five different genetic clusters (FST = 0.174), correlated with the geographical regions of origin of the accessions. Accessions from China and Central Asia were clustered together and exhibited the highest levels of diversity, confirming an origin in this region. A loss of genetic diversity was observed from the center of origin to both western and eastern zones of recent apricot culture. Altogether, our results revealed that apricot spread from China and Central Asia, defined as the center of origin, following three major diffusion routes with a decreasing gradient of genetic variation in each geographical group. The identification of specific alleles outside the center of origin confirmed the existence of different secondary apricot diversification centers. The present work provides more understanding of the worldwide history of apricot species diffusion as well as the field of conservation of the available genetic resources. Data have been used to define an apricot core collection based on molecular marker diversity which will be useful for further identification of genomic regions associated with commercially important horticultural traits through genome-wide association studies to sustain apricot breeding programs.The characterization of the largest worldwide representative data set of apricot ( Evaluation of the extent and structure of genetic variation in germplasm collections has important implications for plant breeding programs and the conservation of genetic resources.In fact, the domestication process of crop species involves the production of populations with modified traits selected according to human pressure compared to ancestral material .Prunus armeniaca L.) which belongs to the Rosaceae family, is cultivated worldwide. It is an important fruit in the Northern hemisphere, representing the third most planted stone fruit species after peach and plum. Among all temperate fruits, apricot represents the seventh in terms of worldwide production. Apricots are native to China and Central Asia, arising following two successive domestication events, one in Western Central Asia  and one in China  markers that rely on genomic sequences have been proven to be the most widely used type of DNA marker in characterizing germplasm collections, because of their easy use, relatively low cost, high degree of polymorphism and informativeness provided by the large number of alleles per locus  evaluate the genetic diversity ii) describe worldwide apricot population structure, iii) elucidate the demographic history of diffusion for the apricot species from the center of origin to the recent regions of culture, and iv) estimate the domestication bottlenecks within cultivated apricot.The objectives were to: Apricot germplasm included 890 cultivated accessions from different geographic origins. The accessions were collected from the worldwide distribution of apricot species to cover the broadest genetic diversity possible. The strategy was to select accessions reflecting the local variability in each country, excluding accessions derived from breeding programs. Using passport data, we discerned seven geographical groups from the East to the West: Group 1 “Eastern Asia,” Group 2 “Central Asia,” Group 3 “Irano-Caucasian,” Group 4 “Continental Europe,” Group 5 “Mediterranean Europe,” Group 6 “North Africa,” and Group 7 “America.” Detailed information on the 890 accessions used in this study is provided in Genomic DNA was extracted following the protocol described in Prunus reference genetic map and the ease of amplification in apricot species. Microsatellite markers were amplified with the same multiplex panels and thermal profiles as described by The 890 apricot accessions were genotyped using a set of 25 neutral SSR markers , which wA), the number of effective alleles (NE), the major allele frequency, and the Shannon’s Information index (I). The observed (HO) and expected (HE) heterozygosities, and the population inbreeding coefficient FIS were calculated using the GENETIX v4.05 program  after scaling down to the smallest partitioning level to avoid a group size-dependent bias on results.Summary statistics were obtained for each SSR marker using POPGENE v1.32 software  to estim program . FIS valPOP v4.0  accordinPOP v4.0  was applK) from 1 to 10. Each run consisted of a burn-in period of 100,000 steps followed by 1,000,000 Markov Chain Monte Carlo (MCMC) iterations, assuming an admixture model and correlated allele frequencies. No prior information was used to define the clusters. For the choice of the most likely number of clusters (K) supported for our dataset, the plateau criterion proposed by K method, described by H’) of runs. CLUMPP output was used directly as input for DISTRUCT v1.1  were assessed using the DARWin software package v6.0.14 .In order to take into account the historical admixture events between the identified clusters, we adopted the tree-based approach implemented in TreeMix v1.13 . TreeMixA), number of effective alleles (NE), number of private alleles , number of unique alleles , allelic richness (AR), observed heterozygosity (HO), expected heterozygosity (HE), and inbreeding coefficient (FIS).Summary statistics were calculated for the material grouped according to the geographic regions of origin as well as for each cluster identified by the model-based Bayesian clustering method, including the mean number of alleles per locus  the apricot geographic groups according to the origin of the material; and (ii) the genetic clusters defined by STRUCTURE analysis.Pairwise Futations . Pairwisutations . Analysiutations  was condIn recent populations subjected to a bottleneck, observed heterozygosity is higher than expected given the number of alleles in a population if this population is at the mutation-drift equilibrium . This heA combination of coalescent-based simulation of the evolutionary processes  and ApprThe development of the core collection was established based on the genotyping data using the advanced maximization strategy (M), implemented by modifying the heuristic algorithm in the PowerCore software program as described by P < 0.0001; Summary statistics of the 25 microsatellite loci over the 890 apricot accessions are listed in A = 19.88), number of effective alleles per locus (NE = 7.694), number of private alleles (97), number of unique alleles (66), allelic richness (AR = 13.752) and observed and expected heterozygosity values  (A = 7.8), allelic richness (5.412), and observed and expected heterozygosity values (HO = 0.495 and HE = 0.572), while the “Continental Europe” group exhibited the lowest mean number of effective alleles per locus (NE = 2.898), and no private and unique alleles were encountered. Except for the “North Africa” and “America” groups, all groups displayed a significant heterozygosity deficit  . In contST) among the seven apricot geographic groups were all highly significant and within the same range (0.032–0.187) (ST = 0.187). However, a low differentiation was observed between the “America” group and both “Irano-Caucasian” and “Mediterranean Europe” groups  as well as between the “Mediterranean Europe” and “North Africa” groups (FST = 0.038). Similar results were obtained when computing pairwise genetic distances among the seven apricot geographic groups  . They inc groups . The Neic groups . The “EaK values (ΔK) revealed two levels of clustering at K = 2 (ΔK = 2447.0) and K = 5  generated by CLUMPP for the 10 runs, similar results were obtained as the highest similarity coefficient (H’) was observed for K = 2 (H’ = 0.999) and K = 5  and some accessions from the “America” group, while the second cluster included all the remaining accessions  grouped accessions from “Central Asia” and China. Cluster 3  grouped accessions from the “Irano-Caucasian” group as well as the seed propagated accessions from “North Africa.” Cluster 4  comprised accessions from the “Continental Europe” group. Finally, Cluster 5  included accessions from the “Mediterranean Europe” group and some graft-propagated accessions from “North-Africa” (qI < 0.8). We noted that the “America” geographical group enclosed the highest number of admixed accessions , for what genotypes that were mainly composed by Cluster 5 (18 accessions) and Cluster 2 (12 accessions).We used the second level of clustering at analyses . For anaqI ≥ 0.8 . Cluster-Africa” . In tota-Africa” . The remThe unrooted Neighbor-Joining tree (NJ) of the 890 accessions based on dissimilarity scores as well as the multivariate Principal Coordinate Analysis (PCoA) revealed a similar pattern as inferred with the model-based Bayesian clustering analysis, with a clear genetic discrimination of the five clusters , 3. BothBased on log-likelihood and residual variance values, the most predictive model suggested the presence of three migration events . A firstA = 17.08), effective number of alleles (NE = 6.680), private alleles (163), unique alleles (45), allelic richness (AR = 10.911) and expected heterozygosity (HE = 0.813). In contrast, Cluster 4 displayed the lowest values of total allele number (82), mean number of alleles per locus (NA = 3.28), effective number of alleles (NE = 1.707), allelic richness (AR = 2.540), and expected heterozygosity (HE = 0.360). In addition, Cluster 4 included only one private allele and no unique allele . Similar results were obtained when computing the pairwise genetic distances among the five genetic clusters  as compared with variation among clusters (17%). Regarding the geographic groups, the genetic variation within groups was 92%, while the genetic variation among groups was 8% .P < 0.05; An excess of heterozygosity is an indicator of recent bottleneck, while a deficit as a result of inbreeding is a sign of expansion. Both represent departures from a Hardy-Weinberg equilibrium. For the BOTTLENECK analysis, Wilcoxon signed rank tests were not significant under both TPM (with 95% single-step mutations) and SMM mutation models; only the test based on the IAM identified a heterozygosity excess for Cluster 1 and Cluster 2 , Cluster 3 received little introgression from basal/ancestral germplasm, and Cluster 5 returns no signal . Estimations of the timings of events are not reported here, because they are scaled to mutation rates  and because they are constrained by the order of events in the phylogenetic tree, thus making the posteriors hard to interpret.Coalescent modeling and Approximate Bayesian Computing (ABC) were used to infer the evolutionary parameters associated with the domestication history of cultivated apricot. Empirical summary statistics fitted the cloud of simulated summary statistics . Ratios To conserve an overview for the whole genetic diversity of the studied germplasm, a core collection that contained 34.38% (306 accessions) of the 890 apricot accessions was constructed capturing 100% of the total alleles . The corRegarding the identified genetic clusters, the constructed core collection was mainly composed by accessions from Cluster 2 (122 accessions) and the admixed accessions (111 accessions), followed by accessions from Clusters 3 (36 accessions), Cluster 1 (24 accessions), Cluster 5 (11 accessions), and Cluster 4 (only 2 accessions).The current study used nuclear SSR genotyping to analyze the genetic diversity and structure of cultivated apricot accessions from a worldwide collection (Japan to North America) in order to clarify the demographic history of diffusion of this species from its center of origin.P. armeniaca and closely related species was involved in apricot domestication in Central and Eastern Asia where self-incompatible cultivars prevailed. In combination with seed-propagation, genetic diversity of apricot germplasm was largely preserved at early stages of domestication and it can be related to the difficulties in apricot grafting propagation in comparison with plum, apple and peach species. Similarly, moderate loss of genetic diversity in cultivated Chinese cherry was also evidenced by The 890 accessions revealed a total of 609 alleles with a mean value of 24.36 alleles per locus. It highlights the highest level of diversity ever described within a worldwide apricot collection, compared with results obtained in previous studies focusing on apricot diversity at a large scale. In fact, Thus, we can conclude that a large part of the cultivated apricot genetic diversity was captured in the already available collections. The collaboration within the network of repositories associated with this study enabled us to capture the largest part of the existing variability due to the complementarity of the worldwide collections. The high level of diversity observed in the repositories located worldwide compared with the one observed in the center of origin and in the primary diversification centers is also observed in tomato where huge differences are observed between sub-species in America each of them being strongly adapted to their particular region of development .Overall, we revealed that apricot accessions around the world clustered into five clearly differentiated gene pools. Strong relationships between memberships of accessions within the clusters defined by STRUCTURE and their geographical regions of origin were identified. Similar results of the association between the genetic structure and the geographic origin of the material were also reported in other fruit crops such as date palm , and oliAccessions from China and the “Central Asia” geographic group were clustered together (Cluster 2) exhibiting the highest level of genetic variability characterized by a higher allelic richness and expected heterozygosity values. In addition, this cluster (Cluster 2), which was the most represented in the constructed core set, enclosed a unique variability with 163 private alleles and 45 unique alleles supporting the notion that China and Central Asia represented two primary centers of origin for apricot species. We confirmed the results reported by Considering the others clusters, the presence of private alleles for Cluster 1 , Cluster 3  and Cluster 5  could be associated with the existence of different centers of diversification in the related geographical regions following the apricot diffusion from its center of origin mediated by the main civilizations. In fact, it was accepted in several studies that the Irano-Caucasian region represented here by Cluster 3 was considered a secondary zone of apricot diversification . MoreovePrunus species, there was also no evidence of bottlenecks in any populations of Prunus lannesiana in Izu Islands in Japan under the IAM, SMM or TPM assumptions (The evidence for a genetic bottleneck in the five identified genetic clusters was ambiguous. When testing either the extreme model or the in-between model (TPM with 95% of single-step mutations), evidence is lacking for the case of a recent bottleneck in apricot diffusion around the world. In fact, umptions , while, umptions . Moreoveumptions .The demographic history of crop domestication has been recently assessed using microsatellite markers and model-based Bayesian clustering method in sweet cherry , olive , date paBefore revealing the history of diffusion routes of cultivated apricot species, it is important to confirm the original center of origin. Overall, our study provided strong support that the region of Central Asia including China constituted the center of origin of apricot species which included a high and particular genetic diversity that can be considered as a reservoir of potentially interesting genes to sustain modern breeding programs. For the Central Asian cluster, the ABC method revealed that the apparent increased effective population size may be the consequence of the massive introgression of highly diverse wild material in the cultivated gene pool which would have raised genetic diversity as also suggested by These multiple domestication events have already been suggested in different fruit species such as olive , grapeviThe first diffusion route was through the Eastern Asia to Japan (Cluster 1) where apricots present low chilling requirements. Apricot was first introduced to Japan from China about 2,000 years ago. However, in contrast to other introduced fruit species such as pear  or persiThe second diffusion route was from the Irano-Caucasian region (Cluster 3) through the Mediterranean countries to Morocco (Cluster 5). Indeed, Finally, the third apricot dissemination route was through the Continental European countries (Cluster 4). In fact, apricot accessions from this region, which were self-compatible and specifically adapted to winter frost through high chilling requirements, appeared to be distantly related to the accessions from Mediterranean Europe, confirming previous studies which demonstrated that the Eastern European accessions can be clearly distinguished from other cultivars of European origin . Plant tPlum Pox Virus resistance occurring in North American germplasm also has a Chinese origin. Similar results were reported in peach, indicating that most modern cultivars in North America appeared to have originated from only a few old cultivars used in early twentieth-century North American breeding programs and coming from China (Apricot accessions from the “America” group displayed a higher level of admixture (60%) mainly with Cluster 2 and Cluster 5. The assigned accessions (18/45 accessions), they belonged to either cluster 2 (10 accessions) or cluster 5 (7 accessions), suggesting that these two gene pools contributed to the genetic basis of apricot material from America which was recently introduced and thus used through human hybridization. In fact, when studying markers linked to disease resistance in apricot, om China .P. armeniaca L. species as well as the establishment of a core collection. Furthermore, from the center of origin, we have found evidence for three different diffusion routes, clarifying the worldwide scenario of domestication history for apricots. These results offer new opportunities for apricot breeding programs in the future related to (i) the maintenance of genetic diversity, (ii) defining strategies for efficient conservation of the genetic resources of this species, and (iii) improving quantitative traits using a genomic selection approach. Finally, the exploitation of the broad genetic diversity of apricot germplasm obtained will help genome-wide association studies linked to candidate genes in order to dissect complex traits as instigated by Plum Pox Virus and/or the implementation of prospective multi-trait selection approaches for maximizing Value for Crop Use and Sustainability (VCUS) and minimizing the impact of climatic changes and biotic stress impacts.In conclusion, this large-scale analysis in apricot germplasm constituted a good example of the efficiency and high value of coordinated international actions to enhance the knowledge of worldwide variability. In fact, our study has provided a wider perspective on genetic diversity and structure within The datasets generated for this study can be found in the public repositories. The full list of accessions and corresponding accession numbers can be found in HB and J-MA conceived and designed the experiments. BK, TZ, CD’O, CL, HI, DC, LK, NT-F, WL, and J-MA provided the samples. GR and AR performed the experiments. HB, CS, IS, and J-MA analyzed the data. HB wrote the manuscript. J-MA, IS, and CS assisted in editing the manuscript. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Ministère des Forêts, de la Faune et des Parcs) has been proactive in reducing the “research–implementation” gap, thanks to prolific collaborations with many academic researchers. Among these associations, our department's outstanding partnership with Dr. Louis Bernatchez yielded significant contributions to harvest management, stocking programmes, definition of conservation units, recovery of threatened species, management of invasive species and forensic applications. We discuss key evolutionary biology concepts and resulting concrete examples of their successful implementation that derives directly or indirectly from this successful partnership. While old and new threats to wildlife are bringing new challenges, we expect recent developments in eDNA and genomics to provide innovative solutions as long as the research–implementation bridge remains open.Successfully implementing fundamental concepts into concrete applications is challenging in any given field. It requires communication, collaboration and shared will between researchers and practitioners. We argue that evolutionary biology, through research work linked to conservation, management and forensics, had a significant impact on wildlife agencies and department practices, where new frameworks and applications have been implemented over the last decades. The Quebec government's Wildlife Department (MFFP:  Louis Bernatchez's laboratory at Laval University  data for the analysis of population structure did the integration of evolutionary applications in wildlife management expand. This new expertise encouraged the emergence of wildlife genetic specialists working in both fundamental and applied research. This period was also the beginning of multiple collaborations between academic geneticists  and MFFP wildlife managers to exploit this new potential for acquiring knowledge that could refine management decisions. Such collaborations were critical in facilitating  the understanding, recognition and implementation of this field in our department.Today, biologists working in wildlife management have been trained in an “evolutionary‐enlightened” context and have access to multiple molecular tools to meet their needs. Recent works, exemplified here by many cited article, are good examples of evolutionary applications that provided data to guide the development of revised management practices, new conservation strategies and more efficient law enforcement to name a few. Such projects would not have been possible without past efforts in education and implementations by governmental and academic teams. Lately, the constant increase in new molecular tools implementation  in our department makes it clear that evolutionary applications will continue to be a valuable contribution and represent an important aspect of wildlife management.From conceptual research and technical developments, many applications have emerged into specific fields of applied evolutionary biology. The genetic structure of populations has been described for a plethora of systems worldwide, allowing for a more precise definition of management units that is based on connectivity, genetic diversity and effective size , provide tangible decisions and are integrated increasingly into our frameworks. Generally, such theoretical considerations and technologies are integrated into these frameworks after a developmental phase (in collaboration or not) provided by fundamental research. Several factors can make the contribution of these innovations “silent” after being taken up into wildlife management, leading to an apparent disconnect between fundamental and applied practitioners. The forces governing success in academic and governmental contexts act differently in terms of their focus and scale Figure . The fee2In our specific context, the contribution of evolutionary biology to the management of exploited wildlife species falls into two broad categories. The first is the greater recognition of issues directly linked to the evolution of exploited species; this includes, although not limited to, cases of reduced genetic diversity  in Lake Saint‐Jean (Quebec) clearly benefited from population structure studies. Tessier, Bernatchez, and Wright . In this context, the noninvasive genetic sampling of hair collected in the field has heightened our knowledge of American black bear abundance by using an adapted mark–recapture approach based on individual identification  populations were strongly correlated with stocking intensity; they identified a threshold value where genetic homogenization between the source and stocked populations could be expected. On the other hand, they also suggested that the genetic consequences of stocking could be temporary, as populations could experiment a genetic “purge” of exogenous alleles if no more stockings are conducted. Consequently, the new MFFP guidelines for lake trout states that populations should only be supplemented using a local source if they have been subjected to fewer than 15 stocking events and none of these events had a density >74 individuals/ha, as these populations are likely to have conserved their genetic integrity and must be protected. For lake trout populations having been subjected to more than 15 stocking events using an exogenous source or lakes that have experienced intense stocking events , supplementation with fish from another lake may be allowed in some instances to enhance angling success, given that such heavily stocked populations have already lost their genetic integrity and may attract anglers that would have otherwise targeted wilder populations.In an effort to assess the potential genetic alterations associated with Quebec stocking practices, Valiquette et al.  demonstr2.2.2Molecular data can be used to assess the reproductive fate of stocked individuals and therefore the longer term demographic effect of enhancement activities. While numerous studies using tagging approaches have shown that stocked Atlantic salmon have a reduced survival rate  continuum  glacial races  at the ecotype, herd and subpopulation levels for management and conservation strategies. Courtois, Bernatchez, Ouellet, and Breton  is increasingly considered within management frameworks. Over the last two decades, genetic and genomic inputs have served as intricate proxies to study or integrate the relationships acting in caribou  in Quebec are due in many respects to contributions of conservation genetics. The copper redhorse is a catostomid fish species, endemic to the province of Quebec; its distribution range comprises the St. Lawrence River and some tributaries, including the Richelieu River where its only currently known and remaining spawning sites are located  regions  and white‐tailed deer  using allozymes and having an extremely limited statistical power. In 2007, microsatellite panels and provincial population genetic databases were developed  or American black bear attack, wildlife officers submit, when available, biological evidence collected at the site of an attack  to compare the evidence with samples collected from a suspected aggressor captured afterwards. Finding an individual match allows the search for the aggressor to be halted and provides a renewed sense of safety for the neighbouring community.The MFFP also uses individual identification via molecular markers for investigations where the perpetrator is an animal. When a wildlife attack on a human is reported, such as a coyote  ivory cases . Once the validation study is completed, this new tool should serve in investigations where identification of the caribou ecotype is needed.In Quebec, specific designations and their pertaining regulations apply to the boreal and mountain (Gaspésie population only) ecotypes of caribou Section . From a 5Building on these successes, the MFFP is moving forward in implementing more evolutionary coherent practices for wildlife conservation and management. Considering evolutionary coherent management practices in our future management plans means to minimize the negative impacts consequent to harvest regulations and stocking programmes. To this end, harvest size range is now scrutinized to limit human‐induced evolution and maintain intact evolutionary trajectories. In addition to limit artificial selection, we now have strong support to encourage a proper angling experience which could satisfy our most enthusiastic sports fishermen and preserve vulnerable fish populations. Before Richard et al. , few stuIntegrating evolutionary concepts into management strategies does not always necessitate conducting our own long‐term monitoring studies, but could gain from scientific developments to improve management practices. For example, we used the model developed by Ryman and Laikre  to refinFrom these established evolutionary principles, our department is able to transition into a more comprehensive application of evolutionary biology and broaden the scope of application to new ramifications among contemporary conservation issues. Over the last decades, increased international transits and climate change have facilitated the spread and dispersion of novel parasites and pathogens  technologies and, more broadly, the use of ‐omic frameworks. Indeed, genomics has compelling possibilities with the increased resolution of traditional genetic metrics that could refine fisheries management, abundance estimation models, monitoring of stocking programmes, mixed‐stock analysis and forensics (e.g., microhaplotypes; McKinney, Seeb, & Seeb, 6Overall, evolutionary applications in wildlife sciences have grown rapidly, and as demonstrated by examples of past and present collaborative effort between MFFP and academics, mainly Dr. Bernatchez, the implementation of evolutionary concepts had a major impact on critical conservation issues. Looking ahead, before genomic applications are widely used in wildlife conservation applications, important aspects remain to be addressed. For the wildlife forensic community, this revolves predominantly around the production of official standards and guidelines, as well as establishing criteria for all possible technological, interpretation and reporting issues. We argue that just as what we considered novel genetic methods 20 years ago and now consider “traditional” and “standard,” present‐day genomic approaches will quickly prove their potency in solving challenging diverse conservation issues, democratizing such technology again. From our standpoint, it is clear that as long as practitioners continue to collaborate and maintain awareness of academic research by asking the right questions, requesting the development of specific tools and adapting to genomic methods, genomic conceptual developments and applications will cross the bridge and make the leap into widespread implementation. The MFFP is very fortunate to benefit from this tight collaboration with academic researchers. Such a bridge was not built in a single day or one successful cooperation. Our advice to build a long‐term flourishing collaboration is for both parties to communicate their needs, act in transparency and seize all opportunities to develop projects together for the benefit of wildlife, science and future generations.None declared.


Fusarium oxysporum f. sp. phaseoli(Fop) J.B. Kendrich & W.C. Snyder is the causal agentof Fusarium wilt of common bean (Phaseolus vulgaris L.). Theobjective of this study was to develop microsatellite markers (SSRs) tocharacterize the genetic diversity of Fop. Two librariesenriched with SSRs were developed and a total of 40 pairs of SSRs werecharacterized. Out of these, 15 SSRs were polymorphic for 42Fop isolates. The number of alleles varied from two to ten,with an average of four alleles per locus and an average PIC(Polymorphic Information Content) of 0.38. The genetic diversity assessed bymicrosatellites for Fop was low, as expected for an asexualfungus, and not associated with geographic origin, but they were able to detectenough genetic variability among isolates in order to differentiate them.Microsatellites are a robust tool widely used for genetic fingerprinting andpopulation structure analyses. SSRs for Fop may be an efficienttool for a better understanding of the ecology, epidemiology and evolution ofthis pathogen. Fusarium oxysporum f. sp. phaseoli(Fop), causal agent of fusarium wilt in common bean, iscurrently considered one of the most important bean diseases  incontrast to other types of markers, since they use the agility of the PCR technique,are codominant and randomly scattered in the genome with a relatively high frequencyas well , five isolates belong to the micro-library of thePhytopathology Laboratory of EMBRAPA Rice and Beans , and eightisolates belong to the Phytopathology Laboratory of the Federal University of Viçosa- UFV  wasdemonstrated.Isolates IAC 11848 (ID:10) and IAC 12802 (ID:12) were used by Fop 46 (ID:11), 14435 (ID: 16), Fop42 (ID: 19), Fop UFV01 (ID: 24), Fop UFV02 (ID:25), Fop UFV03 (ID: 26), Fop UFV04 (ID: 27) and14629 (ID: 34) were used by Fusarium oxysporum f. sp. phaseoli of beanfields in Brazil.Isolates 11205 (ID:01), 11299 (ID:02), 11173 (ID:03), 11257 (ID: 4), 11472 (ID: 6),11178 (ID: 8), Fop 46 (ID: 11), Fop 48 (ID: 20) andFop 42 (ID: 19) of Fusarium oxysporum f. sp.phaseoli identified as races 2, 3 and 6, respectively, whichwere previously classified by Fop. Genomic DNA was extracted from fungi mycelium, accordingto the instructions of the Wizard Genomic DNA Purification kit (Promega). DNA wasdigested with an Afa I restriction enzyme (10 u/μL) (Invitrogen),followed by the ligation of the Afa 21 adapter fragments(5CTCTTGCTT ACGCGTGGACTA3) and Afa 25 (5TAGTCCACGCGTAAGCAAGAGCACA3). The enrichement process was performed by means of the hybridizationof the probes conjugated with biotin, (CT)8 and (GT)8.Two enriched microsatellite libraries  was taken fromthe −80 °C freezer and placed on ice. Then 2 μL of the ligation and 8 μl ofTransfobuffer (10X KCM and 10% PEG) were added, gently shaken, and left on ice for30 min. After that, the solution was removed and kept at room temperature for 10min. Then 450 μL of S.O.C. medium (Thermo Fisher Scientific) was added and incubatedat 37 °C for 1 hour in a shaker at 225 rpm. Transformed cells were plated in solidLB medium containing ampicillin (50 mg/mL), 60 μL IPTG (24 mg/mL), 60 μL X-Gal (20mg/mL). One volume of each  was placed on an opposite portionof the plate, spread with a Drigalsky handle until dry, and incubated overnight at37 °C. The plates were then refrigerated for 1-2 h so that the colonies turned blue.Positive clones were selected using the β- galactosidase gene. The clones from eachlibrary (race I and race II) were sequenced in a 3730 DNA Analyzer (AppliedBiosystems). The SSRs were designed using Primer3 Software.The fragments enriched for microsatellites were cloned into the plasmidial vectorpGEM-T and the transformation to competent cells was performed using a protocoladapted from Avi Levy, 1991 . For transformation, 100 μL ofFop isolate, and concentrations of the individual primer pairs, 1 μL DNA (50ng) of eachloci .The selection of the oligonucleotides used in the multiplex assembling consideredthat the same primers do not have complementarity between their bases and thefluorescences had different colors. After assembling the multiplex system, the 5’end labeling of the oligonucleotides was performed with the 6-FAM, NED, PET, and VICfluorophores so that only the forward primer was labeled with a fluorophore. Thesamples used in the genotyping were prepared in a reaction containing 8.85 μLformamide (Applied Biosystems), 0.15 μL standard marker  and 1 μL PCR product diluted 20 ×. The amplified fragments weregenotyped on a 3730 DNA Analyzer automated sequencer (Applied Biosystems). Productanalyses were performed using the Peak Scanner TM v.1 program (AppliedBiosystems).For the automated analyzer genotyping, multiplex sets were formed, containing threeto four microsatellite Polymorphism Information Content) was calculated basedon the number of alleles and frequency. The PIC values were determined by theexpression:The PIC . To verifythe genetic diversity within and between populations, the following werecalculated: Total heterozygosity (HT); Mean heterozygosity within thepopulation (Hs), population differentiation coefficient (GST). Theestimates of the number and frequency of haplotypes, AMOVA and WrightFST estimator (1978) were performed using the ARLEQUIN 3.1software (A binary data matrix 0 and 1 was generated from the coding of the presence (1)and absence (0) of polymorphic bands present in the isolates and thenintrapopulational genetic diversity analyses calculated through the POPGENE(Fusarium oxysporum f. sp.lycopersici strain 4287 (-10) from JGI version 1.0 (https://genome.jgi.doe.gov/Fusox1/Fusox1.home.html).Molecular markers were aligned to the The genetic structure of the sample was investigated using the Bayesianclustering algorithm implemented by Structure v.2.3.4 .FigureS1).From 384 clones that showed good sequencing quality for library 1 (American race),175 microsatellites were from the American race and from these, 61 clones did nothave microsatellites, representing an enrichment of 54.2%. From the totalmicrosatellites found for the American race, dinucleotides were the most abundant(82 sequences), followed by trinucleotides (72 sequences); and among the motifs, theAG dinucleotides were in greater number, followed by the trinucleotide TCA. For theBrazilian race, the most abundant motifs were also the dinucleotides (52 sequences),followed by trinucleotides (48 sequences); and among the motifs, GAG and GATtrinucleotides were found in a greater number, followed by AC dinucleotides (The perfect microsatellites presented the highest number (97 sequences), followed bythe compounds (63 sequences) and the imperfect ones (15 sequences) for the Americanrace library. For the Brazilian race library, the perfect microsatellites alsopresented the highest number (70 sequences), followed by the compounds (35sequences) and the imperfect ones (11 sequences).locus. The highest PIC(Polymorphic Information Content) value was 0.77 for Fop10-B01  by Fop UFV 01, IAC Fop 05/13 andFop UFV 02, which grouped externally in the dendrogram andfitted in the first group of Structure.Population analysis performed by Structure software also reinforced these results. The besloci in isolates within each stateranged from 4.17 to 84.32%, showing low genetic variability of the isolatescollected in the states of Goiás (15.62%), Pernambuco (13.54%), Minas Gerais (34%),Santa Catarina (14%) and Paraná (4.17%). The isolates derived from the state of SãoPaulo presented the highest genetic variability with 84% polymorphicloci and the isolates from the state of Paraná presented thelowest genetic variability with 4.17% polymorphic loci(TableS1).The percentage of polymorphic T) was intermediate (ST (0.12) and GST (0.33), indicated the genetic structurein the total sample  occurs inalmost all common bean Brazilian fields  is smaller than those of plantsand the longer the genome sequence, the longer the repeated units  was higher than the onereported by According to the annotation performed, it was found homology to a nudix hydrolase occurs in almost all common bean-producing areas (Fop is due to the diversity of physiological races that thepathogen presents, making necessary the study of the genetic and physiologicalvariability of the pathogen. Several control methods are available, but none areefficient. There is no completely resistant common bean cultivar available on themarket and no dominant resistance gene has been properly identified yet. Thedevelopment of tools allowing early detection of the pathogen and effective diseasecontrol relies on the knowledge of the pathogen diversity. This study is expected toserve as an important groundwork for further genetic variation research onF. oxysporum f. sp. phaseoli.In Brazil,