Brassica napus has created a narrow gene pool, limiting the ability to produce improved varieties through crosses between B. napus cultivars. One mechanism that has contributed to the adaptation of important agronomic traits in the allotetraploid B. napus has been chromosomal rearrangements resulting from homoeologous recombination between the constituent A and C diploid genomes. Determining the rate and distribution of such events in natural B. napus will assist efforts to understand and potentially manipulate this phenomenon. The Brassica high-density 60K SNP array, which provides genome-wide coverage for assessment of recombination events, was used to assay 254 individuals derived from 11 diverse cultivated spring type B. napus. These analyses identified reciprocal allele gain and loss between the A and C genomes and allowed visualization of de novo homoeologous recombination events across the B. napus genome. The events ranged from loss/gain of 0.09 Mb to entire chromosomes, with almost 5% aneuploidy observed across all gametes. There was a bias toward sub-telomeric exchanges leading to genome homogenization at chromosome termini. The A genome replaced the C genome in 66% of events, and also featured more dominantly in gain of whole chromosomes. These analyses indicate de novo homoeologous recombination is a continuous source of variation in established Brassica napus and the rate of observed events appears to vary with genetic background. The Brassica 60K SNP array will be a useful tool in further study and manipulation of this phenomenon.The heavy selection pressure due to intensive breeding of  B. rapa (A genome), B. nigra (B genome) and B. oleracea (C genome); and three allotetraploids created from each pair-wise hybridization of these genomes: B. juncea (A and B genomes), B. napus (A and C genomes) and B. carinata (B and C genomes). Of these Brassica species, B. napus (canola or oilseed rape) is the most economically important and is believed to have been formed in the last 10,000 years centered around Mediterranean Europe  locus that had a major effect on the control of homoeologue pairing and recombination  and genomic in situ hybridization (GISH) to distinguish the A and C genome chromosomes in B. napus  and an established B. napus parent line showed a significant increase in homoeologous recombination between the A and C genomes relative to a population derived from a cross between two adapted B. napus parent lines , Maris Haplona, PAK85912, Surpass 400, Svalof’s Gulle, Topas, Tribune, Zhongyou 821) based on diverse geographical distribution  and where available molecular information  and selecting for an individual with a complete AACC genome followed by selfing for several generations . Plants were grown in a greenhouse at 18° with a 16/8 hr photoperiod (day/night). Hand pollinations were used to cross the B. napus individuals with the Australian B. napus cultivar “Rainbow” to produce a testcross population for each line. Young leaf tissue of sixteen individuals for each of the populations was harvested and freeze-dried for DNA extraction. Three of the testcross populations, PAK85912, Zhongyou821 and Maris Haplona were expanded to 48 individuals each, though two of the PAK85912 progeny were determined to be selfs and were disregarded from the data set.Ten B. rapa and B. oleracea genome assemblies  based method (Murray and Thompson 1980). DNA was quantified with the Quant-it Picogreen dsDNA assay kit  and 200 ng was hybridized to the Brassica 60K Infinium array  that could be used to determine the homoeologous alignment of the A and C genomes.The results of the BLAT alignment from aligning the flanking sequences from the SNP loci to the B. rapa and B. oleracea genome assemblies  under BioProject ID PRJNA454160. Supplemental material available at Figshare: https://doi.org/10.25387/g3.6207530.Tables S1-S10 contain the SNP marker data for all testcross populations. Table S11 lists all HeR, duplication and deletion events found in the testcross populations. Table S12 provides details of the SNP markers used for homoeologous alignment of A and C genomes. Table S13 shows the compressed SNP data which summarizes B. napus lines with the Australian B. napus cultivar Rainbow. In total, 256 individuals were assayed with the Brassica 60K SNP array, two lines were identified as self progeny. Initially 16 individuals for each of the 10 B. napus testcross populations were assessed and three populations with differing levels of observed events, PAK85912, Maris Haplona and Zhongyou821, were expanded to 46-48 individuals each. For each individual, the meiosis of both the B. napus line and the testcross parent Rainbow could be assessed, meaning the products of 508 meioses were evaluated.Recombination rates for an individual can be determined by studying the products of meiosis or the genotypes of resulting progeny in the subsequent generation. Ten test populations were derived by crossing ten spring-type Although the nature of polyploid genomes can impact the use of hybridization based tools such as Infinium arrays, the Brassica 60K SNP array was designed such that ∼58% of the loci on the array were estimated to amplify a single genome , produced patterns with the expected three, but also one, four and five distinct clusters and were used to score the testcross populations. In each population, between 4–19% of the polymorphic markers showed these aberrant cluster patterns. These loci had the hallmarks of single copy SNPs, with parental alleles optimally separated  and heterozygote genotypes falling equi-distant between the two, yet additional clusters were observed across the horizontal plane. Those showing four distinct clusters had testcross individuals falling into three different groups: 1) with either one of the two parents; 2) in the expected AB cluster; or c) in a new cluster between the AB group and one of the parents . These presented . Lastly,resented .B. napus. Because only a single A or C genome locus can be scored for each SNP, it was necessary to first identify the syntenic regions between the genomes that can be identified by the SNP loci on the array, and then look for reciprocal allele gain and loss at SNP loci in those regions, thus determining the level and distribution of HeR events. The flanking sequences of the SNPs on the Brassica 60K array were aligned against the genomic sequence of B. rapa (A genome) and B. oleracea (C genome) which produced a clear alignment of homoeologues with comprehensive genome coverage that was in concordance with previous analyses  events by definition result in the exchange of chromosomal material between syntenic regions of the A and C genome within analyses . In someB. napus testcross parents because allele gain and loss can only be visualized when the two parents have opposing alleles. The large number of usable markers on the Brassica 60K array maximized the ability to identify homoeologous regions and determine if an event involved the two homoeologues or if only one genome was duplicated or deleted. The number of informative polymorphic markers in each testcross population is summarized in Genome-wide coverage and density of SNP markers along the chromosomes is important to ensure there is sufficient polymorphism between Rainbow and the 10 For each of the testcross individuals the genotypes for each A genome SNP locus were aligned with the genotypes for the SNPs from the homoeologous region of the C genome to allow ready visualization of the reciprocal allele gain and loss. For a given individual, when the SNP loci from say the C genome showed an extra copy of the C genome allele from one parent (scored as ABB or AAB), the allele from the corresponding region in the A genome was missing (scored as A0 or B0) (Supplementary Table S13). This gain/loss pattern was observed along both homoeologues for at least three physically linked SNP markers in order to confidently determine a HeR exchange had occurred. The number of physically linked loci identifying HeR affected regions ranged from 3-1879, with only four events defined by the minimum number of loci, and the majority of the rearrangements  were identified by 10 or more physically linked loci (Supplementary Table S11).B. napus varieties. These types of events could be seen in the current analyses, where all individuals of a testcross family are not in the expected central heterozygous cluster for a set of homoeologous SNP loci, but are biased toward one parent at SNP loci for one genome while at the homoeologous loci, all individuals are in the other parental homozygous cluster, indicating a duplication and deletion, respectively. Detection of such an event is shown in 1 populations can be used to identify historical HeR fixed events in B. napus lines.Recent studies using whole genome  in the parental line and thus only inherited in a subset of the population and was not considered in subsequent analysis. Generally these events seemed to occur at similar levels to de novo events and testcross populations with high levels of de novo HeR also exhibited high levels of these segregating events (Tables S1-S10).The focus of the study was to identify de novo events were found where both the deletion and duplication of SNP loci in the corresponding homoeologous regions could be detected  were more common than internal exchanges that require a second recombination (43 events). Many of the HeR events (36%) as seen for A3/C3, A4/C4, A5/C5, and A9/C8 were effectively terminal, involving gain/loss of the chromosome ends . It was B. napus so pairing of these chromosomes is certainly possible  though unpaired deletion and duplication events for A1 and C1 were not disproportional  compared to other chromosomes . The othB. napus lines used are established breeding lines they showed varying rates of de novo homoeologous recombinaton. Rainbow and PAK85912 had the highest rates with 22% of individuals having at least one deletion, duplication or gain/loss HeR and Surpass 400 had the lowest rate with no events in the 16 individuals tested. The ACSRsyn1 line was produced through interspecific crossing  and was expected to have a high rate of homoeologous recombination, but only four events were observed in the 16 testcross lines, which is equivalent to the rates observed in Rainbow and PAK85912 and presumably results from stability selected over multiple generations.Though the One of the advantages of using the SNP array to detect HeR events is the relatively dense marker coverage as compared to RFLP or SSR markers. Smaller exchanges can be identified and the marker density allows for more precise physical positioning of the breakpoints. Calculating the distance from the identified recombination event to the nearest segregating marker gives an indication of how the density of the markers is an improvement over older marker technologies. In this data set the smallest interval to which the recombination could be positioned was estimated to be 172 bp, while the largest was 8.7 Mb with an average size of 0.4 Mb (Table S11).B. napus is an excellent system for studying homoeologous recombination, relatively few studies have analyzed the prevalence of de novo events, in part because of the limits of molecular marker technology. However, the high-density array formats for SNP markers make them ideal for quantifying homologous and homoeologous recombination rates, and the depth of coverage of markers on the array helps to overcome the limitations of studying each genome independently.Though de novo HeR was assayed in 508 meioses derived from 11 established B. napus lines, of these PAK85912 and Rainbow proved the most unstable. For each line, between 21–22% of the testcross individuals showed evidence of de novo segmental chromosome duplication or loss (excluding aneuploidy) presumed to be the result of homoeologous recombination or homoeologous associations. Previous studies of AC amphihaploids have suggested genotype contributes to the observed rates of HeR in Brassica species . In the 46 PAK85912 testcross lines there were five confirmed HeR events as well as five deletions and 4 duplications that are likely caused by chromosome mispairing, recombination and segregation. Rainbow had 30 HeR exchanges, 22 deletions and 12 duplications in the 254 individuals studied. In contrast, Zhongyou821 only had five duplication/deletion events with no HeR observed in 48 testcross lines. Considering all populations and the increased marker depth, the observed levels are comparable to those seen in a study using RFLP markers by B. napus DH population derived from a Canadian spring-type and a European winter line. Further studies will be required to assess the true range in absolute rates of de novo HeR in established B. napus; however, the cumulative evidence that genotype contributes to variation in HeR in established B. napus suggests the evolution of a genetic mechanism(s) to control levels of homoeologous recombination, possibly inherited from the progenitor diploids, and the variation between genotypes implies the quantitative nature of this trait.In the current study, de novo events, the genome of origin and chromosome position contribute significantly to prevalence and directionality of the exchange , which are syntenic along their entire length, indicating the importance of homology in determining efficiency of chromosome exchange. The gain and loss of sub-telomeric regions of homoeologous chromosomes  was also more widely prevalent, a phenomenon previously referred to as “homogenisation” (As observed in other studies of HeR, including fixed and isation” . Centromde novo segmental deletions were found to be higher in the A genome, 27 of the 42 deletions were from the A genome, though the chromosomal material lost was 120 Mb as compared to the C genome, which lost 149 Mb through deletions. This could represent ascertainment bias from the SNP array since proportionally there are a lower number of informative markers per Mb derived from the C genome making it more difficult to detect small deletions (B. rapa in B. napus breeding strategies, which could have led to biased capture of A genome regions by lone C genome chromosomes forming aberrant pairing structures in AAC triploids. One intriguing possibility for the apparent instability of the C genome in B. napus is the suggestion that paternal genomes are disproportionally affected in neopolyploids (B. rapa was the possible maternal progenitor of B. napus (The A genome dominated HeR events such that it replaced the C genome in 66% of events, this bias held with segmental duplications, with 17 of the 26 duplications involving A genome chromosomes. In contrast to eletions . He et aB. napus .B. napus and chromosome compensation between the highly syntenic chromosomes in the polyploid nucleus is proposed to provide genome balance in the monosomic lines (B. napus might appear high. However, none of the observed events including the aneuploids are fixed in the testcross lines, and it would be expected that continual selection, for example in the field, for highly fertile euploids would invariably negate the presence of aneuploids and other rearrangements unless they led to a selective advantage. It would be interesting to study the effect of different parental genotypes in the development of hybrids, since it might be expected that high levels of meiotic instability would impact hybrid vigor.Twenty-five aneuploid events were found among the 508 meioses, interestingly the A genome once more featured more dominantly than the C genome, with 14 of the events involving seven of the ten A genome chromosomes, and nine of which resulted in chromosome additions. As with other events A1/C1 and A2/C2 accounted for almost 50% of the events; such aneuploids were prevalent in early generations of resynthesized ic lines  and alloic lines  the leveB. napus and its establishment as a major oilseed crop became apparent through sequence analyses of the B. napus genome that showed a number of important traits for Brassica oil and meal quality were derived from homoeologous recombination events (B. napus was shown when a homoeologous recombination event was found to be segregating in replicate lines from the variety used to generate the B. napus genome assembly (B. napus, offering the opportunity to generate novel variation that could be exploited for crop improvement. The use of high-density SNP arrays has become the standard method for genetic mapping in segregating populations, genotyping of elite lines, studies of genotypic diversity, and identification of chromosomal deletions (B. napus genome possible; in combination with cytological analysis this will present a complete picture of chromosome pairing at meiosis and the resulting homoeologous recombination that affects gamete viability, phenotypic variation and plant fitness. The SNP coverage in concert with the available B. napus genome sequence (The importance of homoeologous recombination in the developmental history of modern


Teladorsagia circumcincta, Haemonchus contortus and Trichostrongylus colubriformis were determined. Data were analysed using genome-wide association studies (GWAS) and regional heritability mapping (RHM).This study aimed at identifying genomic regions that underlie genetic variation of worm egg count, as an indicator trait for parasite resistance in a large population of Australian sheep, which was genotyped with the high-density 600 K Ovine single nucleotide polymorphism array. This study included 7539 sheep from different locations across Australia that underwent a field challenge with mixed gastrointestinal parasite species. Faecal samples were collected and worm egg counts for three strongyle species, i.e. Ovis aries (OAR) chromosome 2 that was highly significantly associated with parasite resistance at a genome-wise false discovery rate of 5%. RHM revealed additional significant regions on OAR6, 18, and 24. Pathway analysis revealed 13 genes within these significant regions , which have various roles in innate and acquired immune response mechanisms, as well as cytokine signalling. Other genes involved in haemostasis regulation and mucosal defence were also detected, which are important for protection of sheep against invading parasites.Both RHM and GWAS detected a region on This study identified significant genomic regions on OAR2, 6, 18, and 24 that are associated with parasite resistance in sheep. RHM was more powerful in detecting regions that affect parasite resistance than GWAS. Our results support the hypothesis that parasite resistance is a complex trait and is determined by a large number of genes with small effects, rather than by a few major genes with large effects.The online version of this article (10.1186/s12711-019-0479-1) contains supplementary material, which is available to authorized users. Gastrointestinal nematode infections (GNI) are one of the most important health problems that affect sheep and other grazing ruminants in Australia and worldwide. The annual cost associated with nematode infections in the Australian sheep industry has been estimated at $436 million for lost production and treatment costs . The effThe identification of genes or genomic regions that are responsible for parasite resistance could greatly improve the accuracy of genomic prediction and therefore result in genetic improvement for this trait , 6. GenoTeladorsagia circumcincta, Haemonchus contortus and Trichostrongylus colubriformis) using both GWAS and RHM approaches.Genome-wide significant SNPs identified from GWAS for complex traits in sheep, and other species such as humans, have generally failed to explain most of the genetic variation, e.g. , 15. SucH. contortus, or 500 epg in sites predominated by other species, faecal samples were collected from all individual animals. Worm eggs were then counted using a modified McMaster counting technique [T. circumcincta, H. contortus and T. colubriformis. The analysis included 7539 animals with both phenotype and genotype data. The distribution of the frequency of WEC records across different ages (days) is shown in Fig. Parasite resistance, as measured by worm egg counts (WEC), was investigated in lambs from a large multi-breed sheep population from the information nucleus (IN) flock of the Australian Sheep Cooperative Research Centre (CRC). Details on the IN flock, design and trait measurements are described in Van der Werf et al. . Lambs wechnique . Worm egVarious breeds were represented in the population but with a significant proportion of Merino genes (70.0%), and only this breed had a substantial proportion of purebred animals (45.2%). The remaining breeds were represented mainly by crossbred offspring of their sires in crosses with Merino or Border Leicester × Merino ewes. Breed group size ranged from 3493 sheep for purebred Merino to 97 for a Poll Dorset/Suffolk/White Suffolk/White Dorper/Border Leicester/Merino cross. The breed content of the population is in Table p value testing Hardy–Weinberg equilibrium less than 10−15, if the heterozygosity rate deviated by more than 3 standard deviations from the population mean and if they were located on the X and Y chromosomes. Furthermore, an individual was removed if the correlation of the genotypes with another sample  was equal or higher than 0.99. After applying the quality control measures, 48,599 SNPs were retained for the analyses.Animals were genotyped with the Illumina 50 K SNP panel . Several quality measures were applied to the 50 k SNP data. SNPs were removed if they had a minor allele frequency (MAF) lower than 0.01, a call rate lower than 90%, an Illumina Gentrain score (GC) lower than 0.6, a ® HD SNP BeadChip panel . The high-density (HD) genotypes were imputed using a reference set of 1881 animals with real HD genotypes. This reference set of HD genotyped animals represented four main breeds : 1042 represented various crosses of these breeds, while purebreds included 677 Merino, 47 White Suffolk, 44 Poll Dorset, 32 Border Leicester, and 39 from 10 other breeds. After applying the same quality measures as above, 510,065 SNPs were retained, and these 1881 HD animals were then used as a reference set to impute the 50 K genotypes to HD using Minimac3 [All animals with WEC phenotypes were then imputed from 50 K genotypes to the 600kOvine InfiniumMinimac3 . Prior tMinimac3 . The accIn order to reduce computation time, a two-step association analysis was performed. First, phenotypes were pre-adjusted for fixed effects using the following model: program  as folloage in R , and \doRHM analyses were carried out on the whole genome using the MTG2 software . Each chmentclass2pt{minimFor the RHM approach, LRT was assumed to follow a mixture of ibutions . In totaOvis aries (OAR) chromosomes 2 and 6 by including the most significant SNP as a fixed covariate in the model and testing all SNPs in the region that were not in strong LD with the conditional SNP  was performed on the genomic relationship matrix using MTG2. The first two principal components (PC) of the genotyped animals were plotted and samples were coloured according to their breed compositions, as known from pedigree information.http://www.ensembl.org/biomart) and UCSC Genome Bioinformatics (http://genome.ucsc.edu). Because the sheep genome is not completely annotated compared to the human genome, human orthologous genes were used to explore their molecular functions. Biological pathways associated with these identified genes were obtained using the BioSystem Tools (https://www.ncbi.nlm.nih.gov/biosystems), which contains pathways from the main databases including: KEGG (Kyoto Encyclopedia of Genes and Genomes), Pathway Interaction Database (PID), WikiPathways and Reactome.Candidate genes in the significant regions were obtained from Ensembl  based on GWAS. In addition, RHM using 200-SNP windows identified a region that contains two overlapping windows between 17.6 and 18.9 Mbp on OAR18, and a region on OAR24 between 40.4 and 41.9 Mbp.The results from the RHM analyses using window sizes of 1000, 500 and 200 SNPs are in Table Figure The significant regions identified by RHM were re-analysed using 200-SNP windows for Merino sheep only to validate whether the same target regions persisted within the Merino sheep population. The results show that the significance of the peaks for the target regions on OAR2, 18, and 24 decreased, whereas the peak in the OAR6 region was maintained Fig. . These rp-values of the fourth and fifth top ranked SNPs  at 111 Mbp on OAR2 became 0.38, whereas the p-values for the second and third significant SNPs (rs424521894 and rs413835864) at 107 Mbp remained lower than 10−4. When GWAS was conditioned on rs424521894 SNP, the p-value for rs413835864 became 0.9, whereas p-values for rs421630816 remained lower than 2 × 10−5. GWAS analysis conditioned on rs425769499 SNP, which is the top ranked SNP in the region between 117 and 118 Mbp, was also performed and the p-values for all significant SNPs on OAR2 remained lower than 10−4. LD between rs424521894, rs421630816, and rs425769499, i.e. the top SNP in each of the three regions between 107 and 108, 110 and 112, and 117 and 118 Mbp, was zero for all pairwise comparisons. However, LD between rs424521894 and rs413835864 SNPs of the same region was moderate . Six distinct haplotypes were identified in this haplotype block  are plotted and annotated by breed composition of the animals Fig. . Only PuPathway analysis was performed to link genes within the significant regions on OAR2, 6, 18 and 24 to their biological pathways using the BioSystem Tools from NCBI. The analysis linked 84 genes Table  to 271 ucis-interaction effects between causal genes in that given region. Our results show that some candidate genes within a given region share similar mechanisms related to the immune system, which suggests that some possible interaction effects take place between those genes for protecting the host against parasite infections.Our study aimed at detecting genomic regions with effects on parasite resistance in a large population of sheep naturally challenged in the field with mixed parasite species. Both RHM and GWAS identified the region on OAR2 as being significant (FDR of 5%). However, RHM identified additional significant regions at the FDR of 5%, i.e. the regions on OAR6, 18 and 24, which were not detected by GWAS. Both methods use genomic information in different ways, and their power to detect genomic regions depends on the genetic architecture behind the trait. According to Nagamine et al. , when trGenomic regions that were identified by RHM as significant explained only a small proportion of the trait variation, r et al. , Riggio mentclasspt{minimar et al. , and Leer et al.  who repor et al. , as wellRegions with a higher impact on parasite resistance were found on OAR2 and OAR6. RHM using 1000-SNP windows identified two regions between 106.4 and 121.1 Mbp on OAR2 and between 30.1 and 42.3 Mbp on OAR6 that were significantly associated with parasite resistance at the genome-wide significance level. Fine-mapping of the region on OAR6 with 200-SNP windows revealed a large region between 35.27 and 38.76 Mbp that passed the genome-wide significance level (FDR ≤ 0.05). Fine-mapping of the region on OAR2 with 200-SNP windows revealed three adjacent regions between 106.9 and 108.4 Mbp, 110.1 and 113.3 Mbp, and 117.0 and 118.1 Mbp that were significant at the genome-wide significance level. Stepwise conditional analyses showed that the proportion of phenotypic variance explained by significant regions gradually increased from 0.4% when regional heritability was based on SNPs from the region between 106.9 and 108.4 Mbp to 0.8% when regional heritability was based on SNPs from all three significant regions on OAR2. These results suggest that several causal mutations are likely responsible for the genetic variation in the OAR2 region.T. colubriformis, which was identified in an outcross of Romney and Coopworth sheep, and which partially overlapped with the QTL region (117.9–133.9 Mbp) reported by Davies et al. [Nematodirus spp. in Scottish blackface sheep. Furthermore, the region on OAR6 has been reported by Riggio et al. [Strongyles in Scottish Blackface sheep. The authors identified a genome-wide significant SNP for Strongyles fecal egg count (FEC) in this region on OAR6 using GWAS, and confirmed a QTL region between 33 and 39 Mbp by RHM analysis. The identified region on OAR6 also corresponds to the QTL (25.1-62.6 Mbp) region reported by Silva et al. [H. contortus and Trichostrongylus spp in a backcross population of Red Maasai and Dorper sheep. Interestingly, both regions on OAR2 and OAR6 have also been reported as being under selection in a large number of sheep breeds from the Sheep HapMap dataset [A comparison with previous studies showed that the region on OAR2 fell within the QTL region (61.7–137.9 Mbp) reported by Crawford et al.  for resis et al.  for resio et al.  for resia et al.  for resin 117.9–1.9 Mbp re dataset . RHM ana dataset .GALNTL6  was the only gene annotated in the region between 106.9 and 108.4 Mbp on OAR2. GALNTL6 harbours the second and third most significant SNPs detected by GWAS analysis and contains haplotype block 6 (107.33–107.38 Mbp), the only haplotype block identified as having a significant effect on parasite resistance. GALNTL6 is a member of a highly conserved family of proteins that are responsible for the synthesis of mucin-type O-glycans. Several genes from this family, such as GALNT1, GALNT4 and GALNT8, have also been reported as being of importance for sheep resistance to gastrointestinal parasite infections [H. contortus had unchanged gastric mucin profiles two days after infection, which demonstrates that animals are able to control mucin levels based on their immunological status. In vitro studies showed that parasite feeding and motility are restricted when larvae were co-cultured with sheep intestinal mucus [fections , 35. Abofections , 37. Mucfections –41. Furtfections  found thal mucus .SH3 domain containing ring finger 1 (SH3RF1); E3 ubiquitin-protein ligase HERC2 (HERC2); presentation, and cytoplasmic FMR1 interacting protein 1 (CYFIP1); and protein tyrosine phosphatase, non-receptor type 18 (PTPN18). SH3RF1 and HERC2 are involved in the MHC class I mediated antigen processing and presentation pathway. This pathway activates type-1 T lymphocytes (Th1), which is characterized by the production of the cytokine interferon (IFN)-gamma among other cytokines, providing effective cellular response and protection against chronic parasite infection [CYFIP1 encodes a protein involved in the Fcgamma receptor (FCGR) dependent phagocytosis pathway, a crucial event in the immune system that permits effector cells such as macrophages to uptake and eliminate infectious pathogens. This event is mediated by immunoglobulin (IgG) binding to Fc gamma receptors (Fc gamma R) on the effector cells [PTPN18 is involved in the B cell receptor signalling pathway, which is essential for the expression of other genes involved with B cell differentiation, proliferation and immunoglobulin (Ig) production.The region between 110.1 and 113.3 Mbp on OAR2 harbours four genes that are directly involved in immune pathways: nfection . CYFIP1 or cells . PTPN18 paladin (PALLD), and probable ATP-dependent RNA helicase DDX60 (DDX60). PALLD contains the top significant SNPs identified by GWAS analysis. The role of PALLD is poorly understood, although it has been found to play an essential role in organizing the skeletal muscle [DDX60 is important for the production of inflammatory cytokines such as type 1 interferon [DDX60 has been detected following viral infections [DDX60 is essential to initiate the innate antiviral mechanism.Other potential genes of interest in this region include: l muscle . DDX60 iterferon . In humafections , 49, whibridging integrator 1 (BIN1), which encodes a protein being involved in Fc gamma R-mediated phagocytosis pathway, and mitogen-activated protein kinase kinase kinase 2 (MAP3K2), which is involved in the IL-1 signalling pathway. MAP3K2 plays an important role in the IκB kinase (IKK) activation, which is essential for NF-κB (nuclear factor kappa-light-chain-enhancer of activated B cells) signalling [interferon (IFN)-gamma, IL-1, IL-2, IL-6, and IL-12, in epithelial cells, lymphocytes and monocytes [The region between 117.0 and 118.1 Mbp on OAR2 overlaps with two important genes involved in immune pathways: gnalling . NF-κB ronocytes . The Κ lonocytes .HERC3, HERC5 and HERC6) that are associated to four biological pathways (Table The region between 35.27 and 38.76 Mbp on OAR6 overlaps with three genes from the HERC family of ubiquitin ligases (secreted phosphoprotein 1 (SPP1) and integrin binding sialoprotein (IBSP). SPP1 encodes a protein involved in toll-like receptors (TLR) signalling. TLR are innate immune receptors that detect pathogen invasion in the intestinal mucosa and are essential for mounting a type-2 immune response [IBSP is involved in the interleukin-11 (IL-11) signalling pathway. IL-11 accelerates platelet recovery [H. contortus, can cause severe blood loss, leading to haemorrhagic anaemia. Maintaining haemostasis is important for sheep recovery following infection as a way to minimise anaemia. Furthermore, haemostasis serves as a defence mechanism to expel parasites from the host body since clotting at the infection site significantly reduces blood supply to adult worms, inhibiting feeding and survival at the infection sites [The OAR6 region also contains two immune genes: response , 54. Thiresponse . IBSP isrecovery , which iligand dependent nuclear receptor corepressor like (LCORL) and ATP binding cassette subfamily G member 2 (ABCG2). LCORL contains the sixth most significant SNP detected by GWAS analysis. In most mammalian species, LCORL contains trinucleotide repeats in the coding region, resulting in an expanded polyalanine tract in the amino-terminal region of its encoded protein [LOCRL are not known.Other candidate genes in the OAR6 region include:  protein . The ext protein , 59. At ABCG2 is highly expressed in the canalicular membrane of the liver, kidney, colon, and in the epithelia of the small intestine [ABCG2 plays a major role in multidrug resistance [ABCG2 at the apical surface of the intestinal epithelium, a layer of cells that forms a physical barrier between mucosa and the gut luminal content, suggests a potential role for this gene in protecting the host from parasites that try to destroy the lining of the lumen to access the bloodstream.ntestine , 61. ABCsistance . The expinterferon stimulated exonuclease 20 (ISG20) gene, which regulates different cytokine signalling pathways in the immune system including ‘Interferon signalling’ and ‘Interferon alpha/beta signalling’ pathways, and de-etiolated homolog 1 (DET1) gene which encodes a protein involved in the ‘class I MHC mediated antigen processing and presentation’ pathway.The region between 17.64 and 18.92 on OAR18 overlaps with the LFNG O-fucosylpeptide 3-beta-N-acetylglucosaminyltransferase (LFNG) gene, which plays an important role in T lymphocyte differentiation and development through regulating notch signalling [MAF bZIP transcription factor K (MAFK) gene is another candidate gene in this region that is involved in the haemostasis pathway (see Additional file H. contortus infection.Fine mapping RHM analysis using smaller windows identified a novel region on OAR24 between 40.4 and 41.9 Mbp. This region overlaps with the gnalling . The MAFThis study identified significant genomic regions on ovine chromosomes 2, 6, 18, and 24 that are associated with parasite resistance in sheep. These results show that RHM is more powerful in detecting regions for parasite resistance and capturing variance than single SNP GWAS. The identified regions overlap with candidate genes that are involved in innate and acquired immune mechanisms, as well as cytokine signalling. Genes involved with haemostasis and mucus production are also relevant for host protection against parasite infections. Our results support the hypothesis that parasite resistance is a complex trait, and is determined by a large number of genes with various roles, rather than by a few genes with a major role in resistance.Additional file 1: Table S1. List of candidate genes and the biological pathways they belong to.


Notably, sorghum CLAVATA1 receptor like kinase, known for regulation of plant growth, and the ETHYLENE RESPONSIVE TRANSCRIPTION FACTOR gene RAP2-7, known to suppress transition to flowering, were significantly associated with plant height. In addition, the YELLOW SEED1 like MYB transcription factor and TANNIN1 showed strong association with pericarp color validating previous observations. Overall, the genetic architecture of natural variation representing the complex Ethiopian sorghum germplasm was established. The study contributes to the characterization of genes and alleles controlling agronomic traits, and will serve as a source of markers for molecular breeding.The eastern Africa region, Ethiopia and its surroundings, is considered as the center of origin and diversity for sorghum, and has contributed to global sorghum genetic improvement. The germplasm from this region harbors enormous genetic variation for various traits but little is known regarding the genetic architecture of most traits. Here, 1425 Ethiopian landrace accessions were phenotyped under field conditions for presence or absence of awns, panicle compactness and shape, panicle exsertion, pericarp color, glume cover, plant height and smut resistance under diverse environmental conditions in Ethiopia. In addition, F1 hybrids obtained from a subset of 1341 accessions crossed to an A1 cytoplasmic male sterile line, ATx623, were scored for fertility/sterility reactions. Subsequently, genotyping-by-sequencing generated a total of 879,407 SNPs from which 72,190 robust SNP markers were selected after stringent quality control (QC). Pairwise distance-based hierarchical clustering identified 11 distinct groups. Of the genotypes assigned to either one of the 11 sub-populations, 65% had high ancestry membership coefficient with the likelihood of more than 0.60 and the remaining 35% represented highly admixed accessions. A genome-wide association study (GWAS) identified loci and SNPs associated with aforementioned traits. GWAS based on compressed mixed linear model (CMLM) identified SNPs with significant association (FDR ≤ 0.05) to the different traits studied. The percentage of total phenotypic variation explained with significant SNPs across traits ranged from 2 to 43%. Candidate genes showing significant association with different traits were identified. The sorghum  Sorghum bicolor (L.) Moench] is the fifth most important cereal crop following wheat, rice, maize, and barley in both total production and acreage in the world  is now more widely-used to identify candidate genes underlying traits of interest. With its power in overcoming the major limitations of bi-parental populations, it is becoming a more common approach in trait identification  particulAlthough the use of GWAS to delineate genomic regions with important traits in sorghum have been shown in several studies , huge ga1.A total of 1425 Ethiopian sorghum landrace accessions were sampled from more than 9000 sorghum accessions maintained at the Ethiopian Biodiversity Institute (EBI) and the national agricultural research centers in Ethiopia. The selected accessions represent different sorghum growing regions and different agro-climatic zones. The global positioning system (GPS) was not captured at the time of collection but details on locality, agro-climatic information and race classification are included with the phenotype data that have been deposited on Purdue university repositoryThese materials were planted during 2015 and 2016 growing seasons at three different locations, Bako (9°08′N/37°03′E), Arsi Negelle (7°21′N/38°42′E) and Haramaya (9°24′N/42°01′E), representing three different climatic regions . Each acSporisorium sorghi) damage score using a rating scale of 1–5, where 1 represents highly resistant and 5 is significant head damage; (8) male sterility. To study sterility reaction of the landraces, a total of 1341 accessions were initially crossed to an A1 cytoplasmic male sterile line, ATx623, during 2014 season and F1 seeds were harvested from each cross. All the F1 hybrids were grown on a single row plot during 2015 season, and three plants were carefully bagged before flowering. At flowering, individual plots were visually inspected for pollen shedding. At physiological maturity, the bags from all heads were opened and plants were carefully examined for seed set. Accessions whose hybrids completely failed to set seed from all bagged plants were designated as non-restorers (B) while those whose hybrids produced normal seed were designated as restorers (R). Others that have incomplete seed set were scored as partial restores (P). To reduce ambiguity, accessions with clear-cut fertility or sterility responses scored as either B or R were considered for GWAS analysis.Pure-lines in each accession were obtained by selecting and selfing five single heads representing the most frequent genotype within a row. The homogeneity was confirmed by planting the materials for at least one season. The five plants representing each accession were tagged and data on the following traits were collected following the standard descriptors used in sorghum germplasm characterization with some modifications . Briefly2.DNA was extracted from a week-old freeze dried seedlings representing one of the five tagged plants of 1425 accessions following acetyl trimethylammonium bromide (CTAB) protocol modified for 96-well plates . A totalSorghum bicolor version 3.1.1 (Single nucleotide polymorphism (SNP) calling was performed with TASSEL GBS pipeline v5  based onon 3.1.1  accessibon 3.1.1 . Resultion 3.1.1  by removThe phenotypic data collected included ordinal categorical (panicle exsertion and glume cover), nominal categorical (pericarp color and panicle compactness and shape), binary (presence or absence of awns and fertility reactions) and quantitative trait (plant height and smut damage score). The frequency distribution of the categorical data across environments were visualized using histogram. Analysis of variance was conducted for plant height and smut damage score to assess the proportion of genotype to the total phenotypic variation and residual error. To partition the different variance components attributing to phenotypic variation, we implemented linear mixed effects model using an R software  package K-value was selected after considering (i) 10-fold cross-validations whereby the best K exhibits low cross-validation error compared to other K-values and (ii) good correspondence with the clustering pattern obtained by hierarchical cluster tree.To describe population structure in the Ethiopian sorghum landrace collection, pairwise distance-based hierarchical clustering was conducted by calculating genetic distance  based on 72,190 SNP markers in PLINK version 1.90 . A Ward’To further understand the pattern of genetic relatedness across accessions, principal components analysis (PCA) was conducted using the ggplot2 package  in R sofp-values were examined to determine how well the models accounted for population structure and familial relatedness. GWAS was performed both as cumulative and separately for each location/year across all the traits. Significant associations were determined for each trait using a false discovery rate- adjusted p < 0.05 as implemented in GAPIT. The Bonferroni error rate control known to extremely increase false negatives were also included in the analysis for comparison. Manhattan and Q–Q plots were visualized using the R package qqman  among accessions . AnalysiQuality control (QC) of genotypic data is a key step in GWAS. It involves removing SNPs with high rate of missing genotype/markers and setting a minimum minor allele frequency (MAF). Initially, 879,407 SNP markers were discovered from 1428 accessions genotyped. The quality control of SNP data based on individuals with <20% and markers with <40% missing and MAF greater than 0.05 produced 72,190 robust SNP markers with 1425 accessions passing the criteria at 95% genotyping rate. Allele frequency is also important in GWAS because genetic associations with SNPs having very low MAF can give false positive results. Our analyses revealed that 46% of the SNPs called in our study represented rare alleles with MAF < 0.05 .K = 2 to K = 20 indicated steep decrease until K = 11, showing optimal number of sub-population at K = 11  between unlinked loci consequently generating spurious marker-trait associations. In the current study, the ADMIXTURE analysis using 10-fold cross validation (CV) for t K = 11 . About 6t K = 11 .GWAS identified 102 different SNPs with significant association (FDR ≤ 0.05) to plant height, presence or absence of awns, glume cover, pericarp color, panicle compactness and shape, panicle exsertion, smut resistance and male sterility . At the The association study based on absence or presence data for awns identified eight SNPs with significant association to this trait (FDR < 0.01) at 72.6 Mb on chromosome 3. These SNPs are also highly linked, with strong LD  and explSerine/threonine-protein kinase-like (CCR4) while Sobic.006G091000 encodes a putative PHOSPHATASE METHYLESTERASE 1. A putative signal recognition particle 19 kDa protein encoded by Sobic.006G099800, previously linked to thermo tolerance was also identified. In addition, other genes in close-proximity to the most significant SNPs were identified including a ternary complex factor, MADS box interacting protein and a putative protein with 90% homology to Plastocyanin-like domain.A total of 24 SNPs on chromosome 2, 5, and 6 were significantly (FDR ≤ 0.05) associated with panicle compactness and shape. These SNPs accounted for up to 35.30% of the total phenotypic variance for the trait. In total, 15 regions across the genome were identified as having significant association with panicle compactness and shape. Among these, three genes Sobic.006G093400, Sobic.006G097900, and Sobic.006G096500 encode putative uncharacterized proteins and six encode proteins that share similarity to characterized proteins. Sobic.006G087900 encodes a putative LSM1 (Sm like proteins) protein was also identified adjacent to Sobic.006G094800.A single SNP (S6_46493884) within Sobic.006G094800 encoding a protein with no predicted or functionally defined domain, was identified on chromosome 6 for significant association with panicle exsertion. The SNP explains 23.71% of the phenotypic variation for panicle exsertion. Another gene model, Sobic.006G094600, encoding putative 2 explaining the total phenotypic variation of the trait ranges between 10.96 and 13.45%. Five of the SNPs are in the candidate gene similar to YELLOW SEED1 (Sobic.001G397900). This locus contains three genes encoding the MYB transcription factor YELLOW SEED1 , similar to YELLOW SEED1 and a third highly related MYB, likely to be a pseudogene. In addition, four additional loci harboring the gene models , two novel loci on chromosome 3 and chromosome 4 were significantly associated with pericarp color. The Sobic.004G280800 gene encodes a protein with high sequence identity (94.3%) to the maize WD repeat containing protein encoded by TRANSPARENT TESTA GLABRA1 (TTG1) gene. In addition, Sobic.001G400500, adjacent to Sobic.001G400400, predicted to encode a pectinestrase is another candidate gene associated with pericarp color.GWAS for pericarp color identified a total of 15 SNPs across three chromosomes  significantly associated with pericarp color, most of them being located within genes of predicted functions. of these 13 SNPs implicated in pericarp color are from chromosome 1 and displayed strong LD showing high linkage , whereas2 explaining the total variance in glume cover for all the SNPs is about 18%. SNPs within Sobic.006G095550, with no functional annotation, and a PEPTIDYL-PROLYL CIS-TRANS ISOMERASE (Sobic.006G095400) gene, AN INDOLE-3-ACETIC ACID-AMIDO SYNTHETASE GH3.8 (Sobic.001G331200) all show significant association with glume cover. In addition, adjacent to Sobic.006G095550, candidate genes FKBP77 (Fruktokinase binding proteins 77) and a PENTATRICOPEPTIDE REPEAT (PPR) gene were associated with glume cover.A total of three loci including two at 45.6 and 52.18 Mb on chromosome 6 and one at 61.9 Mb on chromosome 1were significantly associated with glume cover. The R2 indicating percent total phenotypic variance explained across the most significant SNPs is about 41%. The study also identified several new loci in 12 regions to be associated with plant height on chromosome 2, 5, 7, 8, and 9. The candidate genes defined by the SNPs associated with plant height encode a MYB domain protein 110, LIPOATE-PROTEIN LIGASE, and CHLOROPHYLL A/B-BINDING protein precursor. Two genes from chromosome 9, associated with plant height, were DIHYDROLIPOYL DEHYDROGENASE (Sobic.009G052200) and ETHYLENE-RESPONSIVE TRANSCRIPTION FACTOR . Furthermore, CLAVATA1 receptor like kinase (Sobic.002G172100), TYROSINE/NICOTIANAMINE AMINOTRANSFERASE (Sobic.005G200300) and CYTOCHROME P450 (Sobic.008G058500) were identified. Adjacent to the most significant SNPs, two candidate genes, Sobic.007G161800 and Sobic.008G058600 encoding Phosphofructokinase (PfkB) type carbohydrate kinase protein and a universal stress protein family from chromosome 7 and 8 respectively were identified.A total of 26 SNPs with significant association to plant height were identified with more than half (14 SNPs) on chromosome 9 followed by eight SNPs on chromosome 7, two on chromosome 8, single SNPs each on chromosome 5 and chromosome 2. The RR2-value of all the SNPs reported here are the lowest among the studied traits, explaining only about 2% of the total phenotypic variance for smut resistance. Several candidate genes including GLYCOSYLTRANSFERASE 3 and MYB transcription factor (Sobic.008G035800), MADS box protein (Sobic.006G189500), autophagy-related protein 8C precursor (Sobic.006G220900), and RWP-RK domain (Sobic.006G133900) were identified. RWP-RK proteins have a key role in regulating responses to nitrogen availability (AMINOMETHYLTRANSFERASE (Sobic.006G220800), lipoate-protein ligase B containing protein (Sobic.008G15200) and a TRANSCRIPTION TERMINATION FACTOR 2 (Sobic.003G428100) were identified.A total of 17 SNPs with significant association (FDR ≤ 0.05) to smut resistance were discovered based on our GWAS analysis. Of which, 12 SNPs were from chromosome 6, four on chromosome 8 and one on chromosome 3. The majority of the SNPs are associated with genes that have predicted functions . The R2-lability . In addiCALMODULIN-LYSINE N-METHYLTRANSFERASE (Sobic.004G017100) with significant identity to the rice Os09g0543100, previously implicated in abiotic stress responses was identified. The eight SNPs associated with male sterility on chromosome 4 spanned a 44.5 kb genomic region with high LD  was located near Sobic.004G017500, a candidate gene which encodes a putative BHLH transcription factor with high homology to ABORTED MICROSPORES (AMS). We have also identified Sobic.001G166200, annotated as a zinc finger family protein with candidate genes  with 96% sequence homology to oxidoreductase 2OG-Fe (II) oxygenase protein from maize adjacent to Sobic.001G166200.GWAS on the male sterility trait showed significant association in two major regions on chromosome 1 and 4. The different loci associated to male sterility were represented by nine SNPs, eight on chromosome 4 and one single SNP on chromosome 1. Most SNPs associated with male sterility fell in regions with predicted functions but two represented uncharacterized proteins. The  high LD , indicat2 for glume cover to high R2 for several others with at least one haplotype group in each of the traits  toward the expected level; they controlled false-positives and removed the confounding effects due to population structure.The population structure generated using hierarchical clustering, Admixture, and principal component analysis identified a clear differentiation across the large Ethiopian landrace collection used for this study , 3. The We conducted GWAS for eight traits related to morphological, agronomic and disease resistance based on cumulative data from different year/location and single year data for fertility reaction in sorghum. Awns, slender bristles located at tip of a glume or lemma in a grass spikelet, are known to be critically important for photosynthesis and transpiration . The curPanicle compactness and shape is among important descriptors used for panicle morphology in sorghum, as well as in the classification of sorghum to five major races and 10 intermediate sub race groups . It is pYELLOW SEED1 (Y1) on chromosome 1. The Y1 locus harbors two additional MYB genes which share high sequence identity to Y1. We consider this as the first precise mapping of YELLOW SEED1 locus using natural variants. In addition to YELLOW SEED1 MYB transcription factor that is previously described  on variation in panicle exsertion, with no functional annotation, was identified. Previously, multiple regions on chromosome 1, 2, 3, 6, 7, 9, and 10 were associated to the trait but with smaller effects (0.076 < R2 < 0.118)  . Sobic.0dw1, dw2, dw3 and dw4 are known to regulate plant height by altering the length of stem internodes  and another nearby QTL at 56.4 Mb found to correspond with qHT7.1, initially mapped at 55.2 Mbp (dw1 gene (Sobic.009G229800), whereas Sobic.007G161700 on chromosome 7 is 0.20 Mbp away from the previously reported dw3 (Sobic.007G163800) (ETHYLENE-RESPONSIVE TRANSCRIPTION FACTOR (RAP2-7) reported to suppress the transition to flowering time and confer flowering time delay was identified  . Our stuG163800) , and LIPG163800)  were ideG163800)  was alsoentified . The CLVentified , and TYRentified  and CYTOentified  were ideentified . Most ofSporisorium sorghi) is a major disease in almost all countries where open pollinated cultivars are widely grown, and seed treatment is not affordable. To the best of our knowledge this is the first effort to map sorghum head smut resistance using sequence-based mapping. An earlier mapping study (Brassica rapa (RWP-RK protein with a likely function in disease resistance and reported for its importance in cell differentiation and gametophytic development suggests the role of nutrients in defense (MADS-box gene has been associated to head smut resistance in maize (Sorghum smut (ng study  aimed atng study  and a MYng study . In addiica rapa  is associca rapa  is consi defense . MADS-boin maize . Of the ABORTED MICROSPORES (AMS), underlying male sterility in Maize (Cucumis melo L.)  cytoplasm. The current GWAS analysis for fertility reaction is based on a carefully filtered set of landraces that has been unambiguously, phenotyped as either non-restorers or full restorers with landraces scored with partial restoration excluded from the data set. We identified eight SNPs associated with male sterility on chromosome 4 spanning a 44.5 kb genomic region with high LD . The canin Maize , Melon (melo L.) , and Aramelo L.) . Cytoplamelo L.)  making aOur study involved field-based phenotyping and genotyping-by-sequencing of a large and diverse germplasm collection of sorghum landraces from Ethiopia. This approach helped define loci and discover candidate genes underlying the genetic variation in eight important traits. Sorghum germplasm from this region is one of the richest for trait diversity and the genes and alleles underlying those traits. This diversity has evolved under the diverse and unique environmental conditions and also selected by farmers for diverse uses. In addition to helping to better understand the genetic architecture of these traits, the study will enhance sorghum improvement effort around the world, as development of new markers will offer opportunities in improving the efficiency and precision of sorghum breeding. Functional validation of these newly discovered candidate genes is also important to affirm the statistical association results established here based on the GWAS analysis.All datasets for this study are included in the manuscript and the TeT, GE, and TM conceived and supervised the research work. TM, TeT, GE, GA, FM, KB, AT, HN, and GG initiated and designed the field and genotyping experiments. AS, AN, MM, AG, DL, AB, and HN performed field experiments and prepared leaf tissue samples. GG, HN, AA, and TM analyzed the data. GG wrote manuscript. HN, DL, TaT, TeT, GE, and TM edited the manuscript. All authors have read and approved the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Vitis vinifera subsp. sylvestris) and 48 cultivated (V. vinifera subsp. sativa) accessions at 54 K single-nucleotide polymorphisms (SNPs) to perform a whole-genome comparison of the main population genetic statistics. The analysis of Wright Fixation Index (FST) along the whole genome allowed us to identify several putative “signatures of selection” spanning over two thousand SNPs significantly differentiated between sativa and sylvestris. Many of these genomic regions included genes involved in the adaptation to environmental changes. An overall reduction of nucleotide diversity was observed across the whole genome within sylvestris, supporting a small effective population size of the wild grapevine. Tajima’s D resulted positive in both wild and cultivated subgroups, which may indicate an ongoing balancing selection. Association mapping for six domestication-related traits was performed in combination with population genetics, providing further evidence of different perception and response to environmental stresses between sativa and sylvestris.The application of population genetic methods in combination with gene mapping strategies can help to identify genes and mutations selected during the evolution from wild plants to crops and to explore the considerable genetic variation still maintained in natural populations. We genotyped a grapevine germplasm collection of 44 wild ( Vitis vinifera. They analyzed 54,000 single DNA letters spread across the genome and found evidence that natural wild grapevine populations are on the decline. They also identified several genomic regions related to stress responses that evolved differently in grapes bred to live in vineyards and their wild relatives. The findings suggest the need to conserve wild grapevines, which may harbor genes encoding resilience factors that could aid in the development of hardier wine-producing crops in the future.Wild and domesticated grapevine populations display genomic differences that likely arose as a result of evolutionary responses to different environmental pressures. Annarita Marrano of the Edmund Mach Foundation in San Michele All’adige, Italy, and colleagues characterized the genetic diversity found in 44 wild and 48 cultivated accessions of the Eurasian wine grape,  Vitis vinifera L.) is one of the most important crops worldwide for its global distribution and economic value1. V. vinifera L. exists as the cultivated form V. vinifera subsp. sativa  and the wild-form V. vinifera subsp sylvestris , which is assumed to be the ancestor of modern cultivars. The two subspecies exhibit several phenotypical differences, notably in flower sex, seed shape, bunch and berry size, and leaf morphology2. In particular, sylvestris is dioecious with separate male and female individuals, and in general produces few bunches with small, black and juiceless berries. On the contrary, sativa presents hermaphroditic flowers and enormous phenotypic variability regarding number, size, taste, and colour of the fruit. Previous surveys in grapevine collections have also outlined weak but clear genetic differentiation among cultivated and ex situ wild accessions5. The cultivated grapevine has broad genetic variation, which is likely the result of sexual reproduction, vegetative propagation, and somatic mutations occurring during the long history of grapevine cultivation1. In contrast, sylvestris is less diverse than the domesticated form6. The present distribution of the wild vinifera is fragmented in relict populations with very few individuals. The decline of sylvestris has drastically increased over the last two centuries because of the introduction of pests and diseases  from North America, and the anthropic impact on wild grapevine habitats7. Also, gene flow between cultivated and wild grapevines might lead to domestic introgression and genetic loss in the small relict populations of sylvestris8. Recently, several efforts have been devoted to the study of biotic and abiotic stresses-response in wild V. vinifera, revealing accessions tolerant to salt stress9, lime-induced chlorosis10 and downy mildew (Plasmopara viticola)11. These findings shift sylvestris into the center of attention as a valuable genetic resource for grapevine resilience breeding, which has been so far based on the exploitation of the innate resistance/tolerance of other Vitis species. The identification of genetic resistance in sylvestris may allow preserving the vinifera genomic background of high fruit quality in future breeding cycles. The need to investigate the genetic diversity of sylvestris becomes more significant considering the potential increased vulnerability to environmental changes and the appearance of new pests and diseases since the limited number of grape cultivars grown worldwide.The Eurasian grape  is an alternative to population genetics to uncover the genomic regions responsible for the phenotypic variation observed in V. vinifera. However, few studies of AM in fruit species have been reported so far, due to the difficulties in building up an ideal large association panel without an intricate pattern of population stratification and familial relatedness17. Chitwood et al.18 performed a genome-wide association scan (GWAS) to map the genetic basis of leaf morphology in grapevine, identifying a handful of SNPs associated with just four of the 13 phenotyped traits. This GWA study underlined the limited power of AM in grapevine, which can mainly be attributed to its rapid linkage disequilibrium (LD) decay19. More recently, Migicovsky et al.20 combined GWAS with selective sweep mapping to deal with the fast LD decay and increase the power of detecting loci targeted during the domestication and breeding of wine and table grapes.The morphological and genetic divergence between the two V. vinifera; (ii) the whole-genome scan for signatures of selection by using a combination of population genetics methods. Our results provide evidence of genetic differentiation between sativa and sylvestris individuals at genomic regions mainly involved in response to environmental stimuli. These findings draw attention to wild grapevines as a valuable source of resilience factors, whose re-discovery might be fundamental for sustainable agriculture in the future.In the present research, we assess the distribution and magnitude of the genomic differences between two populations of wild and domesticated grapevine. The study is organized into the following two main milestones, (i) the development of high-density SNP-based genotyping for a germplasm collection, including many authentic wild Vitis vinifera spp. sativa) and 44 wild female (Vitis vinifera spp. sylvestris) grapevines . Both the Synergy HT Multi-Mode Microplate Reader (BioTek) and the NanoDrop 8000 UV-Vis Spectrophotometers (Thermo Scientific) were used to inspect DNA concentration and purity. DNA samples were adjusted to a minimum concentration of 100 ng/µL in 10 µL aliquots. The commercial GrapeReseq 20 K SNPs array (http://urgi.versailles.inra.fr/Species/Vitis/GrapeReSeq_Illumina_20K)21 was used to genotype the whole population with the Infinium technology according to the Illumina protocol . The genomic DNA of the Pinot Noir cultivar was used as a control. SNPs genotypes were scored using the Genotyping Module v1.9 of the Illumina GenomeStudio Data Analysis software. SNPs with a Call Freq score 0 and a GenTrain < 0.6 were filtered out. Markers with a Cluster Sep score < 0.4 were visually inspected for accuracy of the SNP calling. SNPs with R mean score > 0.3 and with clusters not overlapped were retained. The obtained high-quality SNPs were merged in a unique panel with 37 K SNPs from a RAD-seq data set previously generated6. For the SNPs shared between the two experiments, only the SNP profiles from the 20 K Illumina array were retained. Samples and SNP loci with a call rate < 0.8 were filtered out. Genotype imputation was performed to fill in missing data using LinkImpute v1.1.1 software, which is based on a k-nearest neighbour genotype imputation method (LD-kNNi) designed to work with unordered markers22. Finally, SNPs with a minor allele frequency (MAF) < 0.05 were removed using Plink v1.9 software23.A germplasm collection of 48 cultivated , ranging from 1 to 10, was tested by ten independent iterations for each K. The most likely K value was chosen running the algorithm for multiple choices of K and by plotting the marginal likelihood of the data. The software CLUMPP v1.1.225 was used to find optimal alignments of the independent runs and the output was used directly as input into the program for cluster visualisation DISTRUCT v1.126. Moreover, a Principal Component Analysis (PCA) was performed as implemented in ‘adegenet’27 R package for the multivariate analysis of genetic markers.The genetic structure of the germplasm population was analysed with fastSTRUCTURE v1.0sativa and sylvestris subgroups separately by using Plink v1.9 software23. The classical r2 estimate of the correlation between genotypes was used. LD decay was explored by plotting the median r2 in sequential bins of 10 Kb against the physical position. Moreover, LD landscape of each chromosome was also inspected through heat-map visualisation with the software Haploview v4.128.Linkage disequilibrium (LD) was estimated between all SNPs with a MAF > 5% in the whole germplasm population and within FST) was measured between sativa and sylvestris accessions with VCFtools v0.1.1329, setting a sliding window of 100 kb with a step size of 10 kb. Genomic windows with the top 5% of FST values were selected as candidate regions for further analysis. To verify the empirical cutoff with low false discovery rate, we performed whole-genome permutation tests to ascertain the thresholds for identifying genomic regions highly differentiated between the two grapevine subgroups. In more detail, all the genotypes of sativa and sylvestris were shuffled, and the FST analysis was performed with the same parameters 1000 times. Nucleotide diversity (π) and Tajima’s D30 were estimated along the whole genome in 100-kb windows with a step size of 10 kb using VCFtools, to interpret better the results gained with the FST analysis and clarify how sativa and sylvestris genotypes differentiated. The grape gene annotation v2.1 hosted on http://genomes.cribi.unipd.it/grape/31 was used to investigate the putative gene functions of the genomic regions with the top 5% of FST values. In particular, the distribution of the identified genes into different biological processes was evaluated using the weight01 method provided by the R package topGO32. The Kolmogorov–Smirnov-like test was performed to assess the significance of over-representation of GO categories compared with all genes in the grapevine gene prediction. Also, differentiation in the genomic regions reported in the literature associated with flower and fruit traits was checked.Fixation index  plot was used to choose the model that better fit population structure and familial relatedness in the marker-trait association  were used to identify significant marker-trait associations. Manhattan plots were displayed accordingly using the ‘qqman’ v0.1.3 R package34. The positions of markers significantly associated with phenotypes were used to investigate the grapevine gene annotation v2.1. With regard to the extent of LD, windows of 10 kb upstream and downstream, the SNPs of interest were used to identify candidate genes. If the markers fell within long LD blocks, the entire genomic region located between the extreme SNPs was explored.Genotype-phenotype associations were tested for up to six domestication-related traits (single bunch weight (SBCW), single berry weight (SBW), yield, number of bunches per plant (NBCs), total soluble solids (Brix°) and pH; see Supplementary Note 6. We merged the two SNPs matrices in a unique panel since the distribution of allele frequencies within the sativa and sylvestris subgroups showed the same trend  < 0.05 were removed. Most of the SNPs with a low MAF came from the Vitis20K array  and model-based clustering. Figure sativa accessions and 36 sylvestris individuals, respectively, while Pinot Noir, Gewürtztraminer (an aromatic mutation of Traminer Rot) and Mornan Noir cultivars clustered together in a third separate group. Previous studies with microsatellite markers (SSRs)36 have already suggested the first-degree relationship of Pinot Noir and Traminer. Moreover, Pinot Noir and Traminer have presumably ancient origins, and many modern cultivars are their first-degree relatives37. Indeed, many of the 19 genotypes (13 sativa and six sylvestris) not assigned to a defined group by fastSTRUCTURE exhibited admixture with this small cluster  at short physical distances using the Vitis9K SNP array. Lijavetzky et al38. observed an even lower level of LD, which decayed within 100–200 bp in more than 200 gene sequences. On the other hand, Nicolas et al.17 found that the decay of LD down to 0.2 ranged from 9 to 458 kb. These discrepancies may be related to the low number of genomic regions investigated in both LD surveys compared to our genome-wide analysis of LD. We confirmed the evidence of a rapid LD decay in grapevine, which is in agreement with the high polymorphic rate of the grapevine genome39.We used the 26 K SNPs data set to estimate and validate the level of LD along the whole genome within the investigated germplasm collection of grapevine kb Fig. . Such rasylvestris group, where r2 reached values below 0.2 within 20 kb. Therefore, the increase in SNPs density throughout the genome did not have any significant contribution towards shaping the LD patterns within the two grapevine subpopulations. The longer extent of LD observed in the sylvestris subgroup can be related to an elevated level of inbreeding as well as to the common Italian origin of most of our wild accessions6. The differences in LD extent between sativa and sylvestris accessions were more evident by the comparison of the LD patterns on each chromosome. In particular, long-range LD (LRLD) between widely separated loci on the chromosome (distance > 1 Mb) was observed for almost all chromosomes in the sylvestris group  across the grapevine genome to identify genomic regions with altered allele frequency among the two V. vinifera subspecies. The overall level of genetic differentiation between cultivated and wild grapes was moderate (FST = 0.12). A similar genetic divergence was reported among Western European cultivars and wild genotypes4 as well as among grapevine accessions of sativa and sylvestris from Spain43 and Morocco44. This low level of genetic differentiation suggests gene flow between cultivated and wild individuals. However, we observed a non-random distribution of divergent sites along the whole genome: the 95th percentile of the FST empirical distribution was > 0.27, and no positive signals were found to pass this empirical cutoff after the permutation test  of those variants belonged to intergenic or UTR/intron regions, whereas the remaining 26.8% and 9.4 % were synonymous and nonsynonymous, respectively. All 19 chromosomes of the grapevine genome showed divergent sites, ranging from 14 to 382 bins on chr12 and chr4, respectively 46 was evaluated across the grapevine genome in sativa and sylvestris groups separately. As shown in Fig. πsylvestris/πsativa was 0.89, suggesting that π is slightly higher in the cultivated grapevine for most of the investigated genomic regions. Several surveys in grapevine germplasm collections consisting of both cultivated and wild V. vinifera accessions reported this overall lower genetic diversity in the wild gene pool compared to the cultivated panel47. The wild relatives are today present in low number in isolated populations, most likely due to the anthropogenic pressure on their natural habitats and the introduction of disease-causing agents from North America at the end of the 19th century7. On the other hand, the cultivated grape has a bigger effective population size present in multiple locations, where sexual crossing and somatic mutations coupled with a massive vegetative propagation have occurred, thus accumulating and increasing genetic variability. Nevertheless, our selection of sativa accessions from a core collection may overestimate the real level of nucleotide diversity in cultivated grapevines. A drastic reduction in nucleotide diversity of sylvestris individuals (πsylvestris/πsativa = 0) was observed on chromosomes 5, 14 and 15 at genomic regions with a total of 6 SNPs monomorphic in sylvestris. At the same time, sativa showed a reduction in nucleotide diversity on chromosomes 5, 12, and 19, where πsylvestris/πsativa had values higher than 10. However, except for the reduction of genetic diversity in sativa on chr19 (FST = 0.32), no divergence in allele frequencies was observed for the other genomic regions with extreme values of πsylvestris/πsativa. Both cultivated and wild individuals showed low minor allele frequency at those loci (MAF < 0.1). This reduction in nucleotide diversity in both subspecies may indicate reciprocal introgressions between wild and cultivated grapes or could reflect the occurrence of purifying selections, affecting diversity in both populations14.A shift in the allele distribution within populations may result from a sweep toward fixation of a selected locus and its nearby hitchhikers30. We observed mostly positive values of Tajima’s D in both wild (D: ~0.89) and cultivated (D: ~1.35) subgroups. As reported by Riahi et al.47, a positive value of Tajima’s D, especially for cultivated accessions, may indicate an excess of intermediate frequency alleles in these populations. Such configuration of allele frequencies may arise by balancing selection, which maintains both alleles at the selected loci48. According to Delph & Kelly49, this is the result of a heterozygote advantage or a spatial and temporal habitat heterogeneity. A balancing selection is in line with the high heterozygosity of grapevine genome and with the heterogeneity of uses and habitats to which V. vinifera is adapted.Another common test used to detect signals of selection as a distortion of allele frequency and nucleotide diversity is the Tajima’s D, which compares the number of pairwise differences between individuals with the total number of segregating polymorphismsWe looked at the new gene prediction v2.1 of the grapevine genome within windows of 20 kb around the SNPs detected as putatively under selection. Out of the 2032 predicted genes found in LD with the most significant SNPs, 1714 were annotated. Twelve functional classes were significantly enriched in the list of differentiated genes Table . Most  has acted to promote the high morphological variation observable nowadays in leaf shape and size within and between cultivated and wild grapevines51.Out of the 109 genes in the enriched classes, 14 showed SS4; VIT_211s0065g00150; FST = 0.4; Fig. 52. We also identified the nuclear transport factor 2 (NTF2) gene (VIT_217s0000g05240), which has a predicted role in response to abscisic acid (ABA), the main plant hormone promoting grape ripening53. NTF2 gene is located within the significant signature of selection on chr17, which includes candidate domestication-loci for berry size and development19. A reduction of nucleotide diversity in sativa accessions (πsylvestris/πsativa = 1.23) was observed at this locus, supporting evidence of a putative selection for berry composition and ripening traits in cultivated grapevines. Another diversified gene involved in the carbohydrate metabolism is the NADP-isocitrate dehydrogenase gene , which catalyses the oxidative decarboxylation of isocitrate. An upregulation of the genes encoding isocitrate dehydrogenases in tobacco (Nicotiana tabacum cv Xanthi) and grape (V. vinifera cv Sultanina) accompanied increased aminating activity of glutamate dehydrogenase (GDH) under stress conditions, such as salinity54.The list of genes with a significant differentiation between wild and cultivated grapevines was also particularly enriched in genes with a role in the carbohydrate metabolic processes Table . For inssativa and sylvestris were involved in response to different environmental stimuli, in agreement with recent findings55. For instance, we identified the 10 kDa chaperonin gene , the ‘LPA66’ gene (VIT_204s0008g00480), the rhomboid-like protein 11 gene , the desacetoxyvindoline 4-hydroxylase gene (VIT_204s0008g01360), and the FATB gene (VIT_217s0000g01100). The latter has revealed a crucial role in seed development and viability as well as in the promotion of the hypersensitive response (HR) to pathogen attack in Arabidopsis56. We also observed differences in allele frequencies at the ERF2 transcription factor (VIT_215s0021g01590) and ‘RAP2’ (VIT_218s0001g05250) genes, which encode two members of the APETALA 2/ethylene-responsive element-binding factor (AP2/ERF) family. ERF proteins are ethylene-responsive element (GCC box)-binding proteins, and in tobacco, the GCC box has been found in the promoter of many defense genes57. Instead, RAP2 is a dehydration-responsive element-binding protein (DREB) with a role in plant abiotic stress responses such as high-salt stress, water deficit, and extreme temperatures58. Finally, we identified a splicing factor 3b subunit 1-like gene (VIT_208s0040g00270), supporting that alternative splicing may contribute to evolutionary adaptation through the assortment of different protein isoforms as a quick response to selective pressure31.Several of the loci highly differentiated between sylvestris (πsylvestris/ πsativa ~0.95), associated with a positive value of the Tajima’s D (Dsylvestris = 1.41). These results imply that a balancing selection was likely acting in wild populations for adaptation to several environmental changes that may have occurred in their natural habitat along river banks. Our results are in line with recent studies on the tolerance of sylvestris genotypes to different stress conditions such as pathogen attack11 or calcareous soils10, which suggest that sylvestris grapevines represent valuable resources of resilience genes or alleles likely lost during the domestication process. This would have made cultivated grapevine dependent on agricultural means such as fertilisation, irrigation, weeding, and chemical plant protection. The CPN10 and RAP2 genes represent an exception to this trend. Indeed, lower genetic diversity  was observed at these loci in sativa accessions, suggesting a putative ongoing selection for adaptive mechanisms to salt stress in the cultivated grapevine.For almost all the stress-related genes identified, we observed a modest reduction in nucleotide diversity in 42 such as the genes for the xyloglucan endotransglycosylase 59, the histone deacetylase 2 C 60 and the cytochrome p450 78a3-like , which has been found to regulate fruit size during tomato domestication61. Moreover, we found a signature of selection spanning from 4.7 to 5.0 Mb on chr2 (FST ~ 0.31), including 4 SNPs in LD with the APT, SNP4AC and Vvib23 markers for flower sex62. We also observed differences in allele frequency (FST = 0.36) between wild individuals, bearing colored fruits, and cultivated genotypes, composed by both colored and white varieties, at one of the MYB-type transcription factor genes on chr2 4 and within other candidate genes identified at berry skin color QTLs63 , single bunch weight  and berry flesh pH  between each pair of variables in the whole population and the two subgroups separately. While in the entire population yield was more correlated  with both SBW and SBCW than with NBCs (R = 0.4), in sylvestris, it was highly correlated with both NBCs and SBCW rather than with SBW . These SNPs, separated by 6.7 kb, are in LD with five genes, among which a Ca2+ transporting ATPase endoplasmic reticulum-type-like gene , and one marker on chr14 significantly correlated with the total soluble solids  gene encodes a Na+/H+ antiporter, which is the downstream target of the Salt Overly Sensitive (SOS) signaling pathway, involved in controlling ion homoeostasis during salt stress69. We also identified the hypoxia up-regulated protein 1-like (HRE1) gene, which encodes an ERF transcription factor. HRE1 responds rapidly to oxygen deprivation by maintaining the expression of some anaerobic genes such as the alcohol dehydrogenase (ADH) gene70. Finally, the identification of the arginase gene, involved in the biosynthesis of polyamines, and the sugar transporter erd6-like 16-like gene, which encodes a monosaccharide transporter71, highlighted how sativa and sylvestris might present differences in the metabolisms of polyamines and sugars.We identified the highest number of marker-trait associations for the “Species,” a binary trait accounting for the level of genetic differentiation between cultivated and wild grapevineV.v. sylvestris. Moreover, we identified several genomic regions with divergent allele frequencies between grapevine cultivars and their wild relatives. These genomic regions showed significant enrichment in functional gene classes related to responses to biotic and abiotic stresses, unraveling different putative mechanisms of adaptation to environmental changes. While grapevine cultivars are almost entirely dependent on human agricultural practices, the wild forms included in our study seem to have kept facing the permanent environmental alterations in their natural habitats. Future genome-scans using broader grapevine populations including sylvestris from their current whole worldwide distribution may confirm whether the differentiation in stress-related genomic regions is common evidence between all wild and cultivated vinifera populations, or if it is limited to the analyzed ex situ germplasm. Moreover, our study provides candidate genes for future functional genomics studies, to assess how the two forms of V. vinifera react under particular environmental stresses such as water deficit and pathogen attacks. In conclusion, our results support the large potential of sylvestris as a source of resilience factors in future breeding programs to deal with climate change and the increasing demand of sustainable viticulture.We displayed a whole-genome survey of the genetic differentiation between wild and cultivated grapevines by using population genetics approaches. An overall reduction of genetic diversity was observed within the wild panel, supporting the occurrence of an ongoing progressive decline of natural wild grapevine populations, and the necessity of developing new strategies for the characterization and conservation of GENOMIC SIGNATURES OF DIFFERENT ADAPTATIONS TO ENVIRONMENTAL STIMULI BETWEEN WILD AND CULTIVATED Vitis vinifera L