Germplasm collections are basic tools for conservation, characterization, and efficient use of olive genetic resources. The identification of the olive cultivars maintained in the collections is an important ongoing task which has been performed by both, morphological and molecular markers. In the present study, based on the sequencing results of previous genomic projects, a new set of 1,043 EST-SNP markers has been identified. In order to evaluate its discrimination capacity and utility in diversity studies, this set of markers was used in a representative number of accessions from 20 different olive growing countries and maintained at the World Olive Germplasm Collection of IFAPA Centre ‘Alameda del Obispo’ , one of the world’s largest olive germplasm bank. Thus, the cultivated material included: cultivars belonging to previously defined core collections by means of SSR markers and agronomical traits, well known homonymy cases, possible redundancies previously identified in the collection, and recently introduced accessions. Marker stability was tested in repeated analyses of a selected number of accessions, as well as in different trees and accessions belonging to the same cultivar. In addition, 15 genotypes from a cross ‘Picual’ × ‘Arbequina’ cultivars from the IFAPA olive breeding program and a set of 89 wild genotypes were also included in the study. Our results indicate that, despite their relatively wide variability, the new set of EST-SNPs displayed lower levels of genetic diversity than SSRs in the set of olive core collections tested. However, the EST-SNP markers displayed consistent and reliable results from different plant material sources and plant propagation events. The EST-SNPs revealed a clear cut off between inter- and intra-cultivar variation in olive. Besides, they were able to reliably discriminate among different accessions, to detect possible homonymy cases as well as efficiently ascertain the presence of redundant germplasm in the collection. Additionally, these markers were highly transferable to the wild genotypes. These results, together with the low genotyping error rates and the easy and fully automated procedure used to get the genotyping data, validate the new set of EST-SNPs as possible markers of choice for olive cultivar identification. SNP marBased on olive transcriptomic data derived from OLEA and OLEAGEN genomic projects , we inte1 and OLEA2 projects, data from transcript libraries derived from fruits, at different stages of development, from high- and low-phenolics varieties . The olive accessions were SNP genotyped by means of the Golden Gate assay performed on the Illumina’s Bead Array TM at the Human Genotyping Unit-CEGEN of the Spanish National Cancer Research Centre . All the results referred in this study are based on the analysis of the final set of 1,043 markers.A total of 5,154 SNPs was identified from 2,733 contigs. From this set of SNPs, 3,000 were randomly chosen for amplification in a representative sample of 36 olive cultivars, being 2,399 those with a consistent amplification. Among them, only a set of 1,043 loci fulfilled all the above-mentioned selection criteria and were used for further genotyping studies . Total DNA was extracted from fresh leaves of each sample following the protocol described by To evaluate the suitability of the new EST-SNP markers for cultivar identification, diversity studies, and their transferability into the wild germplasm, several cultivated and wild genotypes were included in the study, as well as some seedlings from an inter-varietal cross progeny , established more than 45 years ago. This collection represents the first international attempt of conservation and management of the olive germplasm and was supported by the International Olive Council (IOC) through a FAO-INIA project . At presSupplementary Table 2) and it included: (a) 60 technical duplicates from a total of 28 accessions, resulted from at least two independent DNA extractions of the same tree; (b) 15 accessions which were represented by more than one tree (33 samples); (c) 26 accessions introduced at different moments in the collection, but sharing the same names and found, in a later stage, to belong to the same cultivars by means of different molecular markers (Supplementary Table 2). Each core set consisted in increasing numbers of cultivars: 18, 27, 36, 45, or 68, respectively representing from 5 to 19% of the whole collection). The EST-SNP genotyping of cultivated material also included (h) other economically important cultivars coming from all over the Mediterranean basin.In order to validate the utility of the new EST SNP markers for the unambiguous identification of olive germplasm collections and trying to clarify the most important issues for their effective management, a total of 325 cultivated samples were selected for the EST-SNP analysis. The cultivated plant material comprise olive accessions from 20 different olive growing countries ( markers  d) other markers  (e) 16 w markers  was inclOlea europaea subsp. europaea var sylvestris), from the ex situ Wild Olive Repository of IFAPA, Córdoba (Supplementary Table 3). Most of these wild genotypes (73) came from prospecting surveys in oleaster forests of different Spanish areas . Besides, 16 genotypes which belong to O. europaea subsp. guanchica, originally from Canary Islands, were also included in the present study. Finally, 15 genotypes from a cross ‘Picual’ x ‘Arbequina’ cultivars from the IFAPA olive breeding program , Number of Effective Alleles (Ne), Minor Allele Frequency (MAF), Shannon’s Information Index (I), Observed (Ho) and Expected Heterozygosity (He), and Fixation Index (F). Cervus v.3.0.7 software (Null) for each EST-SNP locus.Pairwise multilocus matching was applied within the entire cultivated set of samples, in order to measure the distance between each pair by using the GenAlex 6.5 software . Key gensoftware  was usedstϕ that were equivalent to the proportion of the total variance that is partitioned between two populations/groups.The diversity values found for the set of EST-SNP markers in the core collections were compared with those obtained by the 32 SSRs used for their development . Pairwis4.The evolutionary history inferred by the Neighbor-Joining method using the MEGA7 software , was perFigure 1A). Thus, the left side of the histogram included a small part of the pairwise comparisons  displaying the lowest allelic differentiation , i.e., only up to 0.005% of the total number of the EST-SNP alleles. While the pairwise comparisons displaying high allelic differences  for each pair of accessions, were included at the right side of the histogram. A high percentage (92%) of the pairwise comparisons included at the left side of the histogram were characterized by lack of allelic differentiation between them . This is the case for all duplicated samples (60 from 28 different accessions), resulting from independent DNA extractions from the same tree (Table 1 and Supplementary Table 2).The 1,043 EST-SNP markers used to analyze the set of 325 cultivated samples under study, gave rise to 52,650 pairwise comparisons. The histogram constructed on distances proportional to the number of different alleles for all comparisons, showed two parts which were clearly separated by a large gap between them (Table 1 and Supplementary Table 2). Overall, independent DNA extractions from the same tree as well as from different trees and accessions of the same cultivar fully matched at all genotyped SNP loci, confirming thus the reliability and the stability of this new set of markers for olive cultivar genotyping.The EST-SNP genotyping did not reveal any allelic differences between different trees belonging to the same accessions (33). Similarly, no allelic differentiation was found between the accessions (26) distinguished by different register numbers, because of their introduction at different moments in the collection, but sharing the same names and same molecular profiles, according to previous identification studies . Thus, the pairwise comparison of all accessions made possible the detection of 59 redundancy groups with two or more cultivars/accessions, encompassing a total of 164 cultivated samples with identical EST-SNP profiles . Among them, the largest group of redundancies was that of the main Italian cultivar ‘Frantoio,’ including 7 identical accessions . Whereas ‘Maelia,’ and ‘Razzola’ displayed very little allelic differentiation to ‘Frantoio’  and between them .All the redundant genotypes, either the ones described previously in the collection as well as the new redundancies identified in the present study, were also found at the left side of the histogram . Identical profiles were also observed among the recently introduced and not previously identified accessions, sharing 38 of them the same SNP genotype with at least another accession. New cases of identity among cultivars were highlighted, such as the group of accessions ‘Confetto,’ ‘Manna,’ ‘Nera di Gonnos,’ ‘Sivigliana da Mensa,’ ‘Maiorca’ and ‘Nocellara Messinese,’ as well as the pair of accessions ‘Rossellino’ and ‘Rosino.’ In addition, some of the newly introduced accessions shared the same genotype with other cultivars from different countries, previously introduced in the collection . This is the case of the pairs of accessions ‘Bianchera’ – ‘Istarska Bjelica’ , ‘Grossa di Spagna’ – ‘Gaydorelia’ , as well as the group formed by the cvs. ‘Bella di Spagna’ and ‘Santa Caterina’ with ‘Gordal Sevillana’ .The same EST-SNP profiles were obtained in all cases of previously described synonymies . For instance, no EST-SNP’s differentiation was found within a group of cultivars from neighboring countries such as ‘Alameño de Marchena’ and ‘Cañivano Blanco’ from Spain, ‘Picholine Marocaine,’ ‘Haouzia’ and ‘Menara’ from Morocco, as well as the Algerian cultivar ‘Sigoise.’ The same was found for the redundancy group formed by the Syrian ‘Abou Choki-1126,’ the Cypriot ‘Athalassa’ and the Lebanese ‘Beladi’ cultivars (Supplementary Table 4). And that included either probable mutation cases without effect on the phenotype traits (as in the case of cv ‘Frantoio’ and ‘Frantoio A. Corsini’), as well as those with modifications in the leaf morphology , fruits and even agronomic traits (‘Zarza’ and ‘Lechín de Sevilla’). While very slight allelic differentiations were displayed in the cases of the pairs ‘Picudo’ - ‘Picudo de Fruto Rojo’ and ‘Dulzal’ – ‘Manzanilla de Sevilla,’ with 9 and 10 different alleles out of 2,086 (0.0044–0.0049%), respectively.In additional, identical EST-SNP profiles were also found for synonymy cases which had been described as potential somatic mutations cases in previous identification studies .Supplementary Tables 2, 4).This set of EST-SNP markers confirmed other cases of previously identified redundancies due to possible errors in different stages of plant material conservation and management. This was the case of trees of the cultivars ‘Tanche,’ ‘Hamed,’ ‘Adkam,’ which grouped together with ‘Itrana,’ ‘Manzanilla de Sevilla’ and ‘Shami’ groups, respectively. Possible management errors may also occur during the introduction of new germplasm into the collection. Thus, the finding of the same EST-SNP profile for the pair of the recently introduced accessions ‘Ravece’ and ‘Rotondella’ may be due to propagation and/or planting errors, as well as possible donor collection’s mistakes (Supplementary Table 5) were included among the non-redundant genotypes. In addition, similar allelic differentiation with the non-redundant cultivated genotypes were also found for the 15 genotypes from the cross ‘Picual’ x ‘Arbequina’  and the wild genotypes . These results may indicate a seedling origin of the non-redundant accessions of our collection.Overall, the use of the set of 1,043 EST-SNP markers for genotyping of the samples under study made possible the identification of 156 non-redundant cultivated genotypes which showed a high allelic differentiation between them. As expected, all previously well-known homonymy cases (the same generic name for different cultivars) such as ‘Abbadi,’ ‘Manzanilla,’ ‘Toffahi,’ ‘Carrasqueño’ (Supplementary Table 6). In general, a relatively wide variability was found for the genetic parameters determined in this group of cultivars. Thus, minor allele frequency (MAF) values ranged from 0.02 to 0.50 in non-redundant cultivars, with an average of 0.24 (data not shown). A total of 41.6% of the EST-SNP marker set displayed MAF values between 0.30 and 0.50. Ho values ranged from 0.03 to 0.994, averaging 0.37, while He ranged from 0.04 to 0.50, with mean values of 0.32. Shanon diversity index (I) values ranged from 0.09 to 0.69, being the mean value of 0.49. PIC values ranged from 0.04 to 0.37 with mean values of 0.26; only 48 EST-SNPs showed PIC values below 0.1, while 75% showed values higher than 0.2. The mean average fixation index (F) was -0.123, ranging from -0.987 to 0.487. Most of the EST-SNPs did not diverge or showed not significant deviation from Hardy–Weinberg equilibrium.All new EST-SNP markers resulted polymorphic in the non-redundant cultivars identified in the present study. The mean number of Ne per locus was 1.53 (Table 2). However, as expected, higher diversity values were found for the SSR markers. The average EST-SNP effective number of alleles did not vary at all core levels (1.54–1.55), whereas higher and relatively wider ranges were found for SSRs . Similarly, the mean Ho and He based on SSR markers displayed higher values than those calculated for EST-SNP markers. The same tendency was also detected for SSRs’ I values which superseded all the EST-SNP ones.Both previously reported SSR and the EST-SNP markers analyzed here, when compared in different core cultivar sets, were informative .The EST-SNP analysis of 89 wild genotypes revealed that only 23 loci were monomorphic, and Nstϕ value was significant (p < 0.001), suggesting the existence of genetic differentiation between them.The One-way AMOVA showed that, although a great part of the genetic diversity was attributable to differences within wild and cultivated genotypes (61%), Figure 2). Cultivars and wild plants resulted into two clearly separated clusters, with a few exceptions of cultivars  included in the group of wilds while only one wild genotype (W168) was intermixed in the cultivated pool. The individuals of the inter-varietal cross progeny formed a clear subgroup within the cultivated varieties. Another subgroup was distinguished within the wilds and was represented by the samples from Canary Islands. Bootstrap values strongly supported the branching shaping of the dendrogram.The relationships between cultivars, wild genotypes and crossbred progenies are presented in the NJ round tree  showed a high EST-SNP allelic differentiation. The 15 genotypes from the cross of ‘Picual’ x ‘Arbequina’ cultivars displayed similar allelic differentiation as the non-redundant cultivated genotypes, revealing thus high heterozygosity and low inbreeding within olive cultivars.High ranges of allelic differentiation were also found for the wild genotypes, indicating a very high transferability of the new EST-SNP markers in the wild germplasm. Interestingly, diversity values in the wilds were lower than in cultivars probably due to crossing events between neighboring genotypes.The genetic diversity within wild and cultivated genotypes clearly confirms the genetic differences between them, as already reported in previous studies by means of different markers , 2010. CWhen setting up the new EST-SNP fingerprinting technique, one important concern was related to its reproducibility. On this respect, 100% concordance was found from multiple samples derived from independent DNA extractions of the same trees and/or different trees of the same cultivars. Besides, identical EST-SNP profiles were detected in some cases of previously identified or new introduced accessions, sharing the same names but coming from different plant sources and propagation events, i.e., doted by different register numbers. At the same time, in accordance to previous identification studies  by meansMost of olive varieties are traditional and can boast a multi- centennial origin, maintained over time in still alive trees  or throuWhen using SSR markers, a less pronounced difference was found between possible intra-cultivar versus inter-cultivar variability , and/or Another important issue within the olive genetic resources refer to well established synonyms, i.e., varieties with different names but identical molecular profile. In this sense, identical EST-SP profiles were observed both in previously described as well as in the new synonymy cases found among the cultivars in the present study. The existence of numerous cases of synonymy is the consequence of the millennial history of olive cultivation, which has favored a continuous migration and human displacement of olive cultivars among neighboring regions and countries, introducing cultivars into different regions and acquiring different names based on different local customs, tree bearing, fruit shape, etc. .The presence of redundant genotypes, i.e., accessions that do not differ at all from the main profile of each cultivar, may occur frequently in olive germplasm banks . The higThe homonyms have usually been troublesome in olive cultivar identification as, historically, naming of cultivars have been based on common morphological traits (particularly of the fruit), toponyms or practical utility of the cultivars . The setO. europaea subsp. guanchica genotypes. This is likely because they derived from conserved transcribed gene regions, shared among genomes of phylogenetically related species and subspecies (In agreement with previous studies in olive with DArTs , or EST-bspecies . Howeverbspecies . This reIn accordance to previous studies, , the ESTThe high number of EST-SNPs developed in the present study, the relatively wide range of variability detected, their low intra-cultivar variation and genotyping error rates, and the fully automated procedure for the EST-SNP genotyping, indicate that they may become the markers of choice for olive germplasm identification, including both cultivars and wild plants. The availability of genome sequence data on cultivars  and wildIn Conclusion, The present work represents a pilot study on the validation of EST-SNP markers for olive germplasm management with special attention to cultivar identification. The generated EST-SNPs showed a high variability in cultivated germplasm and also highly level of transferability to the wild relatives. The new EST-SNP markers revealed to be as efficient or even more than other molecular markers previously used for genotyping accessions at the IFAPA WOGB collection. The high number of EST-SNPs developed will allow the selection of an optimum core set of markers that will find a significant application for the identification studies in olive, to serve as a common and comparable set of markers for the entire olive research community. The olive DNA fingerprinting by means of a reliable panel of EST-SNP markers might represent a good opportunity to establish a universal and automated platform able to compare data across different laboratories, germplasm collections and genotyping platforms.AB, RdlR, LB, and RM contributed to the conception and design of the work. AB and LB contributed to plant material collection. CB, OT, JG-P, AM-M, NC, and RM performed the molecular work including SNP mining and selection. AB, RdlR, RM, and IL contributed to genotype scoring, and data analysis,and interpretation. AB prepared the first draft of the manuscript. All the authors critically reviewed the manuscript prior to submission, read and approved the final version of the manuscript, and agreed to be accountable for accuracy, integrity, and appropriateness 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.


Mycobacterium avium subspecies paratuberculosis (MAP) infection, resulting in enormous economic losses worldwide. There is currently no effective cure for MAP infection or a vaccine, it is thus important to explore the genetic variants that contribute to host susceptibility to infection by MAP, which may provide a better understanding of the mechanisms of paratuberculosis and benefit animal genetic improvement. Herein we performed a genome-wide association study (GWAS) to identify genomic regions and candidate genes associated with susceptibility to MAP infection in dairy cattle.Paratuberculosis is a contagious, chronic and enteric disease in ruminants, which is caused by P < 5 × 10− 5) were identified with GRAMMAR-GC and ROADTDRIPS, respectively. A total of 10 functional genes were in proximity to  these SNPs, including IL4, IL5, IL13, IRF1, MyD88, PACSIN1, DEF6, TDP2, ZAP70 and CSF2. Functional enrichment analysis showed that these genes were involved in immune related pathways, such as interleukin, T cell receptor signaling pathways and inflammatory bowel disease (IBD), implying their potential associations with susceptibility to MAP infection. In addition, by examining the publicly available cattle QTLdb, a previous QTL for MAP was found to be overlapped with one of regions detected currently at 32.5 Mb on BTA23, where the TDP2 gene was anchored.Using Illumina Bovine 50 K  and GeneSeek HD  chips, two analytical approaches were performed, GRAMMAR-GC and ROADTRIPS in 937 Chinese Holstein cows, among which individuals genotyped by the 50 K chip were imputed to HD SNPs with Beagle software. Consequently, 15 and 11 significant SNPs  contains supplementary material, which is available to authorized users. Mycobacterium avium subspecies paratuberculosis (MAP) , where ≤0.45 is negative; 0.45 < S/P < 0.55 is suspect; S/P ≥ 0.55 is positive. ELISA suspect results were excluded because of their uncertainty. Out of the 8214 detected cows, 185 positive individuals (case) and 760 negative individuals (control) from 6 herds were used for GWAS. ELISA results were employed as a binary trait .A total of 8214 Chinese Holstein cows from 7 dairy farms belonging to the Beijing Sanyuan Dairy Farm Center were fed under the same management throughout this study. We collected a 500 μL blood sample from the caudal vein of each cow and performed a regular quarantine inspection of the farms during September 2014. Serum extracted from blood samples were stored at 4 °C until testing; within 5 days after collection. The commercially available, ELISA kit  was used according to the manufacturer instructions to measure the antibody levels of each serum sample. The The individuals in this study were divided into 2 sub-groups for genotyping. Five hundred and thirty three cows belonging to the first sub-group were genotyped with the Illumina Bovine SNP50 BeadChip  after extracting DNA from whole blood using routine procedures. DNA was isolated from whole blood with a commercially available kit, the DP318 Blood DNA Kit . The DNA of the remaining 412 cows in the second sub-group were extracted from hair by GeneSeek with QIAamp® DNA Mini Kit  and then genotyped with the GeneSeek Genomic Profiler HD v2 . The genotype data were deposited in the Additional files , individuals genotyped by the Illumina Bovine SNP50 BeadChip were imputed to GeneSeek Genomic Profiler HD v2. Imputation was performed using BEAGLE 3.3.2  default To further evaluate imputation accuracy, we randomly selected 100 cows genotyped by the high-density chip, obtained the common SNPs between the two panels, and masked genotypes of SNPs left. We classified this small subset of cows as the study population, while the remaining cows genotyped by the high-density panel were classified as the reference population. After imputation, we compared the imputed and masked actual genotypes of the selected 100 cows to calculate the percentage of genotypes that are consistent between them.P values < 10− 6 and > 5% missing genotypes. A dataset containing 109,607 SNPs and 937 animals (182 cases and 755 controls) was used for further analysis. All SNP positions were determined according to the Bos taurus UMD 3.1 assembly [Then we implemented PLINK  and remoassembly .Differences in allele frequencies between subpopulations of admixed populations can lead to false association in a GWAS . In ordey is the liability vector for case/control observations; W is a matrix of covariates (fixed effects that contain herd and parity); α is a vector of the corresponding coefficients including the intercept; x is a vector of genotypes of a marker at the locus tested; β is the effect size of the marker; u is a vector of random polygenic effects with a covariance structure as β~N , Vg is the polygenic additive variance; ε is a vector of residual errors with ε~N , I is the identity matrix, and Ve is the residual variance component.We performed a GWAS using the Genome-wide Rapid Association using Mixed Model and Regression-Genomic Control (GRAMMAR-GC) approach , 45, a skth SNP. The deflation factor ζ is estimated as ζ = median T, is genotype vector at a test SNP for n individuals . V is a vector of length n coding for phenotype information (disease status) and known relationships.Y.Here P values of SNPs were derived from an asymptotic chi-square distribution with 1 degree of freedom. In addition, the fixed effects used here was the same as above.ROADTRIPS 2.0 provides three association tests named RM test, Rχ test and RW test. According to the authors’ recommendation, the RM test is the most powerful among the three tests when pedigree information is available. Compared with the Rχ test and the RW test, the RM test can use the phenotypic information of individuals with missing genotypes provided that they have a genotyped relative at the tested marker. Considering the features of the RM test and the data structure of this study being based on a corrected pedigree, we adopted the RM test for association analysis. P value thresholds of 5 × 10− 7 and 5 × 10− 5 were considered as genome-wide “strong” and “moderate” association respectively.Following the suggestion of the Welcome Trust Case Control Consortium , two P vMAP susceptibility in the Animal QTL database  [Using BioMart in the Ensembl database (Ensembl Genes 92), genes within 1 Mb of the significant SNPs were retrieved based on the UMD 3.1 assembly. To provide insight into the functional enrichment of genes identified, we carried out GO (Gene Ontology) and Pathway analysis using KOBAS 3.0 . KOBAS ab/index) .2 < 0.85 and found an average allelic R2 of 96.7% for imputed genotypes. Then we took a small subset including 100 cows genotyped by the high-density chip for calculating the imputation accuracy. Finally, the percentage of consistent genotypes was 97.03%, which suggested a high accuracy of imputation.After imputation, we discarded SNPs with allelic RP values for the majority of SNPs corresponded well to the expected P values under the null hypothesis of no association. However, a few departures which mean the P values of these SNPs were higher than the expected P values under the null hypothesis indicated associations with the trait being studied , we obtained the 232 IDs for genes located within or overlapped with the regions nearby these SNPs (< 1 Mb) , such as immune response-regulating signaling pathway, regulation of leukocyte proliferation and immune response-activating signal transduction. Fifteen significant pathways were found, including those related to immune responses (P < 0.05) such as autoimmune thyroid disease and enrichment of the interleukin signaling pathway . After comparing these QTLs with the regions within 1 Mb of the 26 significant SNPs, 2 QTLs identified before [MAP susceptibility were found. This implies the functional genes, such as TDP2 (tyrosyl-DNA phosphodiesterase 2) around these SNPs are likely candidates for MAP susceptibility traits.Until now, 6 JD tolerance and 161 d before , 37 locaMAP infection, the consistency was not high. The genomic regions and genes regarded as candidates for the target traits were variable among previous studies. The difference between genomic regions identified by different studies is because of different trait definitions except for statistical methodologies [There have been multiple GWASs conducted in different cattle population –37, and dologies . There wdologies , 31, 33,dologies , tissue dologies  and compdologies , ELISA pdologies , and ELIdologies .− 5) using GRAMMAR-GC with BTA23 owning the most SNPs. The most significant SNP, BovineHD2200003382 (P = 1.13E-14) was identified on BTA22 (Table − 5) using ROADTRIPS with the most significant SNP, BTB-01281916 (P = 1.21E-08) identified on BTA3  and BovineHD0200035709 (ROADTRIPS), on BTA7 ~ 14.81 Kb was found between BovineHD0700017491 (GRAMMAR-GC) and BTA-79476-no-rs (ROADTRIPS), on BTA7 ~ 1.91 Mb was found between BovineHD0700007000 (GRAMMAR-GC) and BovineHD0700006447 (ROADTRIPS) and ~ 0.76 Mb was found between BovineHD0700006647 (GRAMMAR-GC) and BovineHD0700006447 (ROADTRIPS). Combining the results of these two methods, 26 significant SNPs were obtained. The most SNPs were found on BTA7 followed by BTA23.IL4, IL5, IL13 and IRF1. The genes, IL4 (interleukin 4), IL5 and IL13 are type 2 cytokines, that may be the predominant cytokines produced by CD4+ and other T cells in lymph nodes during the subclinical infection of MAP [MAP infection disease was characterized by a gradual shift in the immune responses from cell-mediated immune response to antibody mediated immune response while IL4, IL5 and IL13 can promote the Th2 antibody-mediated immune response. Therefore, these three genes might play important roles in the pathogenesis of the disease [IRF1, interferon regulatory factor 1, plays an important role in many immune responses including the Type 1 (Th1) cell-mediated immune response. Cell mediated immunity is an important host defense mechanism against intracellular pathogens including MAP [IL6, IL12B, and inducible nitric oxide synthase (NOS2) that function in the pathogenesis of human IBD [Among the 26 significant SNPs detected by two methods, BovineHD0700006447 (23.5 Mb) located on BTA7 in this study was close to SNPs detected by Pant et al. (20.6 Mb ~ 22.3 Mb) . Genes nn of MAP . As prevn of MAP –56, in t disease . IRF1, iding MAP . In addiuman IBD –60.MyD88 (myeloid differentiation primary response gene 88) which encodes a cytosolic adapter protein that plays a central role in the innate and adaptive immune response. MyD88 functions as an essential signal transducer in the interleukin-1 and Toll-like receptor signaling pathways [The most significant SNP, BovineHD2200003382 detected by GRAMMAR-GC was located at 11.3 Mb on BTA22. Genes within 1 Mb of this location includes pathways .PACSIN1 and DEF6 that are related to immune response. PACSIN1 (protein kinase C and casein kinase substrate in neurons 1), belonging to a family of cytoplasmic phosphoproteins, participates in the regulation of endocytosis [DEF6  is a guanine nucleotide exchange factor (GEF) for RAC (MIM 602048) and CDC42 (MIM 116952) that are highly expressed in B and T cells [TDP2 (tyrosyl-DNA phosphodiesterase 2). This gene encodes a member of a superfamily of divalent cation-dependent phosphodiesterases. The encoded protein associates with CD40, tumor necrosis factor (TNF) receptor-75 and TNF receptor associated factors (TRAFs) that inhibits nuclear factor-kappa-B activation. In addition, TDP2 has sequence and structural similarities with APE1 endonuclease, which is involved in both DNA repair and the activation of transcription factors [SNP BovineHD4100015938 on BTA23 (8.98 Mb) was close to ARS-BFGL-NGS-109956 (7.84 Mb) and ARS-BFGL-NGS-115177 (7.87 Mb) reported by Zare et al. . The genocytosis  and reguocytosis . DEF6  encodes an enzyme belonging to the protein tyrosine kinase family that plays a role in T-cell development and lymphocyte activation. This enzyme, phosphorylated on tyrosine residues upon T-cell antigen receptor (TCR) stimulation, functions in the initial step of TCR-mediated signal transduction in combination with the Src family kinases, Lck and Fyn and plays an essential role in the process of thymocyte development [ZAP70 in cows naturally infected with MAP and revealed that the surface expression of ZAP70 was decreased in CD4+ T cells of both subclinical and clinical animals indicating a change in T cell phenotype with disease state [CSF2 (colony stimulating factor 2), also known as CSF and GMCSF, encodes a cytokine that controls the production, differentiation, and function of granulocytes and macrophages. This gene has been localized to a cluster of related genes at chromosome region 5q31 that are known to be associated with interstitial deletions in the 5q- syndrome and acute myelogenous leukemia. Other genes in the cluster include those encoding interleukins 4, 5, and 13 [Interleukin, T cell receptor signaling pathway and inflammatory bowel disease (IBD) pathways are related to immune or inflammatory response. Two genes including elopment . In addielopment . Leite ese state . CSF2  overlapped with one QTL associated with e et al. .The present study focused on the potential function of 10 candidate genes. Future analysis is necessary to investigate the biological processes and molecular mechanism of these genes to anchor immune alterations and possible triggers that result in clinical paratuberculosis.MAP infection in Chinese Holstein cattle using two statistical approaches, GRAMMAR-GC and ROADTRIPS. Twenty-six significant SNPs located on 15 chromosomes were detected based on data after imputation. Ten genes within less than 1 Mb of these SNPs were involved in immune response pathways, implying their potential associations with susceptibility to MAP. These genes included IL4, IL5, IL13, IRF1, MyD88, PACSIN1, DEF6, TDP2, ZAP70 and CSF2. By examining the QTLdb, the 32 ~ 33 Mb region of BTA23 may be a genomic region associated with MAP infection.We performed a case-control GWAS for Additional file 1:MAP file of SNP data. (MAP 3577 kb)Additional file 2:PED file of SNP data. (PARTIAL 776 kb)Additional file 3:Figure S1. PCA plot based on SNP data. (TIFF 175 kb)Additional file 4:Figure S2. Q-Q plot based on SNP data using GRAMMAR-GC. (TIFF 175 kb)Additional file 5:Figure S3. Q-Q plot based on SNP data using ROADTRIPS. (TIFF 179 kb)Additional file 6:Table S1. The features of genes based on GRAMMAR-GC. (XLSX 20 kb)Additional file 7:Table S2. The features of genes based on RODATRIPS. (XLSX 15 kb)Additional file 8:Table S3. The features of genes based on GRAMMAR-GC and RODATRIPS. (XLSX 26 kb)Additional file 9:Table S4. Functional enrichment of GO and Pathway analysis of 343 genes. (XLSX 32 kb)


Corylus spp.) occurs through the frequent formation of blank nuts. Although the condition is associated with embryo abortion, we have not yet identified the regulatory genes involved. Therefore, this study aimed to determine the genes related to embryo abortion in hazel. We performed whole-genome re-sequencing and single-nucleotide polymorphism (SNP) analysis on four mutant hazelnut trees  bearing blank nuts and four wild-type trees . A paired comparison of Empty1 vs. Full1, Empty2 vs. Full2, Empty3 vs. Full3, and Empty4 vs. Full4, along with the intersection of Empty1 to Empty4, revealed 3 081 common SNPs in the four blank-nut mutants. Of these, 215 synonymous SNPs in exonic regions were distributed across 178 candidate genes. Heterozygosity analysis showed that average homozygous and heterozygous SNP ratios were respectively 0.409 and 0.591 in the samples. According to Gene Ontology classification, candidate genes were enriched in the categories of binding, catalysis, molecular transducer, transporter, and molecular function regulator. Among these, 18 of 178 genes had homozygous SNPs in Empty1–4. Cis elements in the promoter region of starch synthase 4 (SS4) contain the RY-element, implying seed-specific expression. Starch granules were absent from Empty1–4 cotyledon cells, but abundantly present in Full1–Full4 cotyledon cells. The blank-nut phenotype has heavier nut shells. Overall, we conclude that single-nucleotide variants of Acetyl-CoA carboxylase 1 (ACC1), intracellular sodium/hydrogen exchanger 2 (NHX2), UDP-glycosyltransferase 74E2 (UGT74E2), DEFECTIVE IN MERISTEM SILENCING 3 (DMS3), DETOXIFICATION 43 (FRD3), and SS4 may induce embryo abortion, leading to blank-nut formation. Our results will benefit future research on how the gain or loss of candidate genes influences seed development. Moreover, our study provides novel prospects for seedless cultivar development.Yield loss in the economically important hazelnut ( Corylus spp., Betulaceae, Fagales) is an important wind-pollinated species. Its nutritious and delicious nut is an important raw material for several food processing industries (Corylus heterophylla and hybrid hazel (C. heterophylla × C. avellana) are the most important species cultivated in China. Among these, the cultivation area of C. heterophylla is more than 1.0 million hm  in both cultivated and wild palms in sub-Saharan Africa  and of C. heterophylla was collected and equally mixed following the method of C. heterophylla, using a simple sequence repeat (SSR)-based technique at Jilin Normal University. Seven primer pairs were used, according to the method of In 2017, we found four hazel mutants that had borne only blank nuts for several years, in Northeast China. These mutant plants were distributed in four artificial orchards modified from hazel nature forest, in four different locations, namely Siping, Tieling, Kaiyuan, and Huludao Cities. In the orchard in Siping City, one plant bearing normal edible nuts, and another that had borne only blank nuts for several years, were selected; they were named Full1 and Empty1, respectively. To make the genetic background as close as possible, the spatial distance between the Empty1 plant and reference Full1 was less than 3.0 m. Similarly, Full2 and Empty2 (mutant) from Tieling City, Full3 and Empty3 (mutant) from Kaiyuan City, and Full4 and Empty4 (mutant) from Huludao City were sampled and analyzed. Blank nuts contain only small and unformed ovules, with no edible content Figure 1C. heterophylla plants mentioned above were collected and stored in liquid nitrogen for whole-genome re-sequencing. Meanwhile, some nut quality indexes were investigated, including shell weight, kernel weight, nut total weight, kernel ratio , diameter, and blank-nut ratio.In 2018, young leaves of the eight https://www.ncbi.nlm.nih.gov/Traces/study) (Accession number: PRJNA529018).DNA was isolated using the DNeasy Plant Mini Kit  according to manufacturer’s recommendations. DNA quality was evaluated by electrophoresis on a 0.8% agarose gel, and analyzed using a Nanodrop spectrophotometer  and Qubit 2.0 Fluorometer . Genomic DNA was fragmented randomly using ultrasound. Fragments ranging from 200 to 500 bp in length were recycled by electrophoresis, and were connected with adaptors to generate clusters for sequencing. Eight paired-end fragment libraries averaging 300 bp were generated and sequenced on an Illumina HiSeq 2000 platform  following Illumina protocols. The raw data were submitted to the National Center for Biotechnology Information (NCBI)  to detect the genomic mutations in our samples using Burrows–Wheeler Aligner software (https://broadinstitute.github.io/picard/) were used to remove duplicate reads, and the BAM file generated was used to calculate sequencing depth and coverage. Genome Analysis Toolkit (GATK) and SAMtools were used to map the obtained genome sequence data to the reference hazelnut genome and call high-quality SNPs (http://evolution.genetics.washington.edu/phylip.html) was used to construct the phylogenetic tree of the eight hazel samples, using neighbor-joining method  paired reads with adaptor sequences; (2) paired reads with more than 10% unknown bases (N); (3) paired reads with a base quality value less than Q20; (4) paired reads shorter than 25 bp in length; and (5) paired reads with other than A, T, C, or G at the 5′ end. The filtered sequences were aligned to the reference Jefferson hazelnut genome (software . Picard ity SNPs . GATK soity SNPs  and remoity SNPs . Based ohttp://bioinformatics.psb.ugent.be/webtools/Venn/) were used to make SNP-paired comparisons of Empty1 vs. Full1, Empty2 vs. Full2, Empty3 vs. Full3, and Empty4 vs. Full4, thereby identifying the SNPs unique to the blank-nut mutants. A common intersection of SNPs was also generated from the comparisons. Candidate genes with common and unique SNPs in their exon regions were selected for Gene Ontology (GO) analysis using WEGO 2.0 (http://wego.genomics.org.cn/). Genes associated with embryo development were considered to be those involved in transporter activity function (starch synthase 4 (SS4) promoter (a 2 000 bp region upstream of the start codon) were analyzed using PlantCARE (http://bioinformatics.psb.ugent.be/webtools/plantcare/html/).To narrow the range of candidate genes, several analyses were performed in succession on detected SNPs and their positional data. First, online Venn Diagram tools  , acetyl-CoA carboxylase 1  , sodium/hydrogen exchanger 2  . Approximately 30 ng of genomic DNA was amplified using a Bio-Rad thermal cycler . The reaction volume was 20 µl, comprising 1.0 µl genomic DNA template, 0.4 µM primers, and 10.0 µl 2 × Taq plus Master Mix . The thermocycling protocol was as follows: 95°C for 5 min, followed by 35 cycles of 95°C for 30 s, 55°C for 20 s, and 72°C for 60°s. Amplicons were subsequently cloned into the pMD19-T vector (Takara), transformed into Escherichia coli DH5a cells following manufacturer protocol, and sequenced by Sangon Biotech Co., Ltd .Genomic DNA from each sample was PCR-amplified. Three primer pairs designed using the reference sequence of The cotyledons were isolated from the seeds under a stereoscope, and cut into cubes of edge length 1–2 mm. These cubes were fixed in 4% polyformaldehyde solution for 24 h and stored in 70% ethanol at −20°C until further use. The samples were then dehydrated in gradient ethanol solutions. Dehydration, embedding, and aggregation were performed using the LR White Resin Embedding Kit , following the protocol of the manufacturer; 0.5% periodic acid and Schiff reagent were used to stain starch granules in the cotyledons. Cytogenetic observation of starch granules in the sections was performed and photographed using optical light microscopy.C. heterophylla samples have a close genetic relationship with C. avellana.The base error rate was lower than 0.02%. The percentage of bases with Phred value >20 was more than 94%. The GC count per read followed a normal distribution. These results indicate that library construction and quality by Illumina sequencing were reliable.Whole-genome re-sequencing of our eight samples generated 42.01 Gb of clean data; statistical analysis results are shown in Mapping of our genome sequencing data to the reference hazelnut genome using GATK was performed to call high-quality SNPs. In the samples of Empty1, Empty2, Empty3, and Empty4, 1 494 330, 1 539 833, 2 065 212, and 214 6447 SNPs were identified, respectively Table 2;Paired comparisons of SNPs between two samples from the same orchard were carried out to identify unique SNPs in the blank-nut mutants using Venn Diagrams tools. Consequently, 820 705, 797 299, 1 578 029, and 880 405 were identified by paired comparison of Empty1 vs. Full1, Empty2 vs. Full2, Empty3 vs. Full3, and Empty4 vs. Full4, respectively Table S1SS4, g16468), Acetyl-CoA carboxylase 1 , and sodium/hydrogen exchanger 2 . The results were consistent with those from whole-genome re-sequencing.We identified 14 908 159 SNPs in all eight samples. Among these samples, homozygous (1/1) SNP ratios ranged from 0.377 to 0.445, while heterozygous (0/1) SNP ratios ranged from 0.552 to 0.629. The 1/2 heterozygous genotype was scarce, with a ratio of <0.004 in all samples. Average homozygous and heterozygous SNP ratios were 0.409 and 0.591, respectively Figure 3We assigned 178 candidate genes to the following three GO categories: biological processes, cellular components, and molecular functions Figure 4SS4 (g16468) had the RY-element indicative of seed-specific regulation, however  to an alkaline arginine (R). At the same position, Full1–4 maintained a high degree of similarity with related sequences in C. avellana, Q. suber, and J. regia. The results of SS4 SNP heterozygosity analysis show that Empty1, 2, and 4 were heterozygous (0/1), while Empty3 was homozygous (1/1) at this SNV loci  is unique to China and the major source of hazelnut products in China (C. avellana) genome, revealed that the two plants are closely related. Thus, the C. avellana genome information can also be used for C. heterophylla gene identification and mining. In Northeast China, many artificial hazel orchards have been created by modifying natural C. heterophylla forests, for the purposes of protecting forests. Compared with the nuts of C. heterophylla × C. avellana cultivars, those of C. heterophylla possess thicker shells, lower kernel ratio, higher blank-nut ratio, and poorer nut quality. However, C. heterophylla has exceptional cold resistance and thus the potential to be cultivated in more regions. Therefore, this was an unprecedented opportunity to identify important genes regulating kernel development, using our four blank-nut mutant germplasms. Evolutionary tree analysis based on obtained SNP information showed that Full2, Empty2, Full3, and Empty3 are on four different genetic branches . Consistent with this, we found that most SNPs were heterozygous. The fact that 37.7–44.5% of SNPs were homozygous implies that selfing likely plays an important role in hazelnut population formation and evolution.C. heterophylla indicates simultaneous base mutation in both alleles, which appears more likely than heterozygous SNP mutation to induce observable phenotypes. After filtering unannotated genes, integrated biological functions, and embryo-abortion characteristics, we identified a set of gene products implicated in regulating blank-nut formation, including ACC1, NHX2, UDP-glycosyltransferase 74E2 (UGT74E2), DEFECTIVE IN MERISTEM SILENCING 3 (DMS3), and DETOXIFICATION 43 (FRD3)  Table 6.ACC1 may impair citrate conversion to long-chain fatty acids and trigger physiological disorders in ovules. Furthermore, ACC1 loss-of-function led to abnormal embryo morphogenesis and embryo lethality in transgenic Arabidopsis seeds  is an auxin glycosyltransferase. In olerance . Immunoholerance .DNA methylation is an epigenetic alteration related to gene silencing. In the RNA-directed DNA methylation (RdDM) pathway, DMS3 is required in producing Pol V-dependent transcripts, suggesting a regulatory role in DNA methylation and gene silencing . The totFRD3 encodes a membrane protein belonging to the multidrug and toxin efflux family, which is involved in transporting small organic molecules. In Arabidopsis, frd3 mutant plants were defective in either iron-deficiency signaling or iron distribution, indicating that FRD3 is an important component of iron homeostasis  contains 543 amino acids, and the sequence is well conserved across the SS4 proteins of species sequenced to date (Oryza sativa L.) double-mutant SSIIIa and SSIVb (ss3a ss4b) generated spherical starch granules in seeds, whereas single mutants produced polyhedral starch granules similar to wild-type  to an alkaline arginine (R) in Empty1, Empty2, Empty3, and Empty4, whereas this region in Full1, Full2, Full3, and Full4 was similar to those in C. avellana, Q. suber, and J. regia. An SNV of SS4 at the N terminal might impair appropriate protein localization and induce the failure of starch-grain biosynthesis. This hypothesis is consistent with previous data showing ovule abortion soon after fertilization  and the Science and Technology Research Project of The Education Department of Jilin Province .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.


Ascaris lumbricoides / Ascaris suum circulating in humans and pigs, exploring potential zoonotic cycles in endemic areas in Brazil. We carried out cross-sectional surveys in four municipalities: Santa Isabel do Rio Negro (SIRN-AM) (n = 328); Nossa Senhora de Nazaré (NSN-PI) and Teresina (TER-PI) ; and Cachoeiras de Macacu (CAM-RJ) (n = 543). We also studied 61 fecal samples/adult worms obtained from pigs (n = 53 in NSN-PI and n = 8 in TER-PI). A ~450 bp fragment of the Ascaris cytochrome c oxidase subunit 1 (cox1) and ~400 bp of the NADH dehydrogenase subunit 1 (nad1) were amplified and sequenced. Maximum-likelihood (ML) tree and Median-joining (MJ) haplotype network analyses were performed. We also performed scanning electron micrographs of adult specimens. Positivity rates were 93/328 (28.4%) in SIRN-AM, 6/297 (2.0%) in TER-PI, 0/605 (0%) in NSN-PI, and 6/543 (1.1%) in CAM-RJ. In NSN-PI it reached 11/53 (20.7%) in pigs. The MJ network based on cox1 locus (383 bp) revealed three main clusters, one centered around haplotypes H01/H28/H32 and the other around H07/H11. The cox1 haplotypes had a heterogeneous distribution, showing no pattern by geographic region, and high haplotype diversity. The ML trees based on cox1 and nad1 loci showed a similar topology with each other, and with the haplotype networks. Three distinct clusters were observed. Sequences of cox1 and nad1 from humans and animals were distributed throughout the tree and it was not possible to differentiate specimens of human and swine origin. Ascaris populations obtained from humans and swine in different Brazilian regions are not discriminable through the genetic markers used, which indicates the potential for zoonotic transmission and the need for better control of these infections in swine herds, mainly when created in a peridomestic environment.In this study, we assessed the genetic diversity of  Ascaris lumbricoides and Ascaris suum are parasites of great importance to human and swine health, respectively ), mainly in Africa, Asia, and Latin America, with a single 400 mg dose of albendazole –10. ThisClassically considered an anthroponotic disease, there is evidence that ascariasis can cross the host species barrier (humans and pigs), circulating at the human-animal interface –14. NeveA. lumbricoides and A. suum. Morphologically, there are very few differences, these being restricted to details detectable by electron microscopy in the shape of the lips and size of the teeth, as evaluated and reviewed by Ansel and Thibaut ) of the Oswaldo Cruz Institute, Fiocruz. All subjects provided written informed consent and the parent or legal guardian of all children included in this study provided written informed consent on their behalf.A. lumbricoides/A. suum mitochondrial targets cytochrome c oxidase subunit 1  and NADH dehydrogenase subunit 1  were amplified [Ascaris lumbricoides/Ascaris suum nucleotide sequences were edited with Bioedit v.7.2.5 [cox1 sequences of SIRN-AM were published in [Parasitic DNA was obtained from three different sources: i) eggs obtained by spontaneous sedimentation ; ii) eggs obtained by Kato-Katz thick smears, as described by ; and iiimplified . PCR con v.7.2.5  softwareished in , accessihttps://blast.ncbi.nlm.nih.gov/Blast.cgi) was used to check similarity with Ascaris sequences. Orthologous sequences representing the diversity of Ascaris spp. were retrieved from GenBank  and added to the analyses. Ascaris spp. nucleotide sequences were aligned using the multiple sequence alignment ClustalW [cox1 and nad1 dataset was chosen using Bayesian Information Criterion (BIC) in Molecular Evolutionary Genetics Analysis (MEGA) v.7.0.20 software [The Basic Local Alignment Search Tool . In order to evaluate the intraspecific genetic diversity of Brazilian Ascaris populations, diversity indices were determined for each population pair using Pairwise Distance in ARLEQUIN v.3.5.2.2 software (http://cmpg.unibe.ch/software/arlequin35/) [Ascaris spp. were retrieved from [www.dpi.inpe.br/terraview).DNA Sequence Polymorphism (DNASP) v.6  was usedquin35/) . Ortholoved from   and 74 nad1 Ascaris sequences  were obtained. Alignments were performed with our new sequences (83 cox1 and 68 nad1 sequences) and Ascaris spp. reference sequences (169 cox1 and 53 nad1 sequences) from GenBank  revealed three main clusters of haplotypes, one centered around haplotypes H01/H28/H32 and the other around haplotype H07/H11  indicate significant genetic differentiation   .nad1 haplotype network was very similar to that of the cox1 locus, presenting three main groups of haplotypes . Several studies demonstrate this topology for Ascaris mitochondrial targets, in which two main groups are formed with i) clusters A and C; and ii) cluster B [A. lumbricoides and A. suum. It should, however, be noted that there was relatively low bootstrap support for the internal branches of the dendrograms, which may indicate low phylogenetic resolution when using mitochondrial DNA markers.In this study, we describe the genetic diversity of two mitochondrial loci of luster B ,35. Our A. lumbricoides / A. suum samples from Brazil. The number of different cox1 haplotypes obtained in this study– 17 haplotypes to cox1 and 32 haplotypes to nad1 –is similar to that found in previous studies in Asia and Africa [cox1 genetic diversity in Ascaris across Brazil. The present study adds to the growing database of Ascaris sequences from human and pig hosts, since nine and 26 new haplotypes have been described for cox1 and nad1, respectively. Interestingly, the haplotypes H59, H64, and H73—considered highly divergent haplotypes of A. lumbricoides / A. suum–were not found in the studied population. The high haplotypic diversity in Brazil can be explained by the migration for the peopling of the American continent: European settlers and African slaves being introduced from the 17th century and integrated with native Amerindian, which have Asian ancestry [We found high haplotype diversity in d Africa . Althougancestry ,37. Duricox1 haplotypes found, four had already been described in the country  [Ascaris in the country. The haplotype H01 was the most common in this study. Interestingly, it has been found in all Brazilian localities studied to date (this study and previous studies by [Ascaris sp. isolated from Sumatran orangutans (GenBank accession number LN600399) and chimpanzees [Of the eight and H32) ,21. Thisudies by ). This hudies by ,35,38. Fcox1 haplotypes (n = 8 previously described) were found to be originally from humans, four of them had already been described as infecting pigs  [Ascaris cox1 haplotypes described here may be new pig-like haplotypes. Nuclear targets have been used in an attempt to unravel the taxonomy of the Ascaris genus. The presence of hybrids [A. lumbricoides and A. suum [Although all and H32) ,21. Althand H32) , describ hybrids  and poss A. suum  has been A. suum .One limitation of the direct nucleotide sequencing of the amplicon—when it is obtained from egg pool—is that we can lose mixed infections caused by different haplotypes. Despite this, a wide variety of haplotypes were described in this study.A. suum species. The nucleotide sequences of the cox1 fragment allowed the characterization of these two specimens as A. suum.The morphological analysis of two adult specimens obtained by the necropsy of pigs revealed that their mouth parts were compatible with Ascaris lumbricoides / Ascaris suum is important in the improvement of control strategies. In this study, considering the three Brazilian states in which we obtained Ascaris-positive samples, the characterization of cross infections was only possible in Piauí, where we examined fecal samples from pigs and humans living in close contact to each other. In NSN-PI, pigs live in close proximity to human dwellings, having free access to houses and streets, so it is to be expected that humans and pigs were infected with the same Ascaris haplotype. Intriguingly, in NSN-PI, no human infection was observed with this parasite in the more than 600 analyzed samples [From a One Health perspective, the characterization of the zoonotic potential of  samples . Thus, wAscaris populations obtained from humans and swine in different Brazilian regions are not discriminable through the genetic markers used, which indicates the potential for zoonotic transmission and the need for better control of these infections in swine herds, mainly when created in peridomestic environment.It is concluded that S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S1 FigIn ML tree: circle: SIRN-AM; square: TER-PI. Only bootstrap values ≥70% are reported. In MJ network, the colors of the circles indicate the isolation continent: black: America; dark gray: Africa; diagonal: Asia; and light gray: Europe. The area of the circle is proportional to the sequence number.(TIF)Click here for additional data file.


The growth of six-rowed barley is potentially important for breeding in agriculturally oriented countries, such as Kazakhstan. Nevertheless, until recently, very little attention was given to six-rowed barley in breeding projects in Kazakhstan, one of the largest countries in the world. In this study, phenotyping and single nucleotide polymorphism (SNP) genotyping data were generated from 275 accessions originating from six different breeding organizations in the USA as well as 9 accessions from Kazakhstan in field trials at six breeding institutions. The USA six-rowed barley was tested in comparison to local accessions over three years (2009–2011) based on analyses of key agronomic traits. It was determined that the average yield in the USA accessions in comparison to local lines showed heavier yield in all six tested sites. Principal Coordinate Analysis based on 1618 polymorphic SNP markers separated Kazakh lines from six USA barley origin groups based on PC1 (77.9%), and Montana lines from the remaining five USA groups based on PC2 (15.1%). A genome-wide association study based on eighteen field trials allowed the identification of 47 stable marker-trait associations (MTA) for ten agronomic traits, including key yield related characters such as yield per square meter, thousand grain weight, number of kernels per spike, and productive tillers. The comparison of chromosomal positions of identified MTA with positions of known genes and quantitative trait loci suggests that 25 out of those 47 MTAs are presumably novel. The analysis of 42 SNPs associated with 47 MTAs in the Ensemble genome annotation system ( Vrs1 gene is responsible for the SR spike in barley, since the loss of function of Vrs1 results in fully developed fertile spikelets with SR phenotype [In barley, two-rowed (TR) and six-rowed (SR) germplasm groups can be separated based on the arrangement of triplets at rachis nodes . In SR bhenotype . TR and henotype ,3,4 and henotype , 6. TR bhenotype .In Central Asia, the largest barley producer is Kazakhstan, which grows over 80% of the region’s barley , and SR Currently, the efficiency of breeding programs might be improved by the application of modern genomic technologies , 13, sucThe other conclusion drawn from the survey of GWAS articles for cereal crops, including barley, suggests a strong influence of environmental conditions on detection of QTL for yield components , 30, 31.The spring six-rowed barley panel consists of 275 accessions, which originated from six different breeding organizations in the USA and 9 accessions from Kazakhstan . The US In all studied locations except KO, the plants were grown in non-irrigated conditions. The locations of six field trial sites and their geographical, meteorological, and soil type data are given in Genievskaya et al., 2018 , as TR aNine accessions from Kazakhstan were genotyped using the GoldenGate Illumina 9K SNP chip at the TraitGenetics company . The SNP genotyping data of the USA accessions consisted of 3072 SNP markers  and werek values, Q-matrix for four identified clusters was developed. GWAS for the above-listed agronomic traits evaluated in six regions was performed using polymorphic SNPs, and implemented in the TASSEL 5 package [As the number of samples from Kazakhstan was insignificant, the GWAS was performed using only the USA set of SR barley. The SNP dataset was filtered using a 10% cutoff for missing data and markers with minor allele frequency ≥ 0.05 were considered for GWAS. Numbers of hypothetical groups ranging from k = 1 to 10 were assessed using 50,000 burn-in iterations followed by 100,000 recorded Markov-Chain iterations. The output from STRUCTURE , 35 was  package  and MLM  package , 39. A m package .t-test were calculated using the software package GraphPad Prism 5.0 . GGE Biplot methods were employed by using the GenStat package . The symmetric scaling option of both methods and available field data for all three sites were used in estimations.Statistical analyses of data, including multiple factor ANOVA, Pearson’s correlation and The Pearson correlation coefficient indicated a large environmental influence on barley performance in different locations, as averaged YM2 in six locations over three years was correlated only in three out of fifteen cases. In two of those three cases, the KB station showed the correlations with the KO and KA sites, while the KA site was highly correlated with the AK .In the YM2 analysis, the three-way ANOVA confirmed that the environment (E) plays a significant role, as Region and Year of the study were the only factors that significantly contributed to the yield performance . HoweverThe GGE biplot graph assessment suggests that six tested environments can be divided to four major regions, as conditions of barley growth in KA and KB, as well as AL and KO, were grouped together, and formed opposite mega-environments in the upper part of the GGE biplot graph . As genoUS SR accessions showed an outstanding field performance in comparison to local cultivars and breeding lines in irrigated plots of Kyzylorda region . Three MThe Pearson index analysis of the field data from the KB site suggested that yield is positively correlated to SMT, PH, and TGW . InteresAt the KB site, the highest averaged YM2 over three years was recorded for MT (2734.7 g/m) lines, followed by AB (2625.9 g/m) and BA (2562.5 g/m) accessions. In total, 28 US accessions showed better yield performance over the best local breeding line L50/T26 (2872.1 g/m). The highest averaged YM2 among individual accessions was scored by line 2627 (3778.6 g/m) originated in Utah .The genotyping of USA accessions allowed the identification of 1618 common polymorphic SNP markers distributed over all seven chromosomes with an average spacing of 0.704 cM. The number of SNP per chromosome ranged from 191 on chromosomes 1H and 4H to 260 on chromosome 3H. The data also included 62 SNPs with unknown (U) positions. Additional information for each individual U marker can be retrieved from Muñoz-Amatriaín et al., 2014  and the PCoA based on the analysis of 1618 polymorphic SNP markers was applied to assess the genetic relationship of the USA accessions from six different breeding organizations and Kazakh samples. The PCoA graph suggested that Kazakhs samples were well separated from the USA accessions . As PC1 The distribution lines of the QQ plots  for ten http://ensemblgenomes.org) suggests that only 2 out of 42 identified SNPs were outside of the genic region  and the number of MTA in other yield-related traits were as following, TGW (n = 6), RIL (n = 6), PT (n = 5), SL (n = 3), and NKS (n = 2) . The mosField trials in six different environments suggested that tested US SR accessions showed an outstanding field performance in comparison to local cultivars and breeding lines, as in all six locations the USA lines prevailed over Kazakh lines . The advAs the ANOVA revealed a significant contribution of E and GE in GEI for the studied agronomic traits , it was The genetic relationship of SR lines among groups of six different breeding origins based on the use of 1618 polymorphic SNP markers suggested a rather different outcome . The firVrs1 gene. Therefore, current GWAS was focused on the analysis of SR barley collection in six different locations in the country. In this study, the total number of MTA was 47 MTA for ten agronomic traits, which is nearly half as much as in similar research using TR barley based GWAS. A previously reported TR barley study scored 91 MTA for nine traits [Vrs1 gene was supported by the experiment. Furthermore, both that 22 out of 47 MTA were reported elsewhere  assays  for theiVrs1 gene was tested in six regions over three years, it was hypothesized that GWAS might uncover novel MTA for tested agronomic traits. Indeed, the study revealed that 25 out of 47 detected MTA were not previously reported in scientific articles and potentially can be novel associations for key agronomic traits in barley. Four presumably novel MTA were found for YM2, PT, and RIL, three for TGW, two for NKS, SL and SMT, and one MTA for HT and PH. The study shows the advantage of international exchange and evaluation of germplasm for enhancement of breeding projects in different parts of the world.The YM2 analysis suggests that the SR accessions from the USA outperformed local samples in all six studied locations. Obtained results indicated a high potential of the USA lines as valuable breeding material for local barley breeding projects. The field trials of SR barley from the USA at the KB site, which represents northern regions, which in turn are home to over 90% of the barley territory in the country, have allowed the identification of 28 US accessions that displayed better average yield performance than the best local breeding line. Since SR barley that carries non-functional S1 AppendixA–AK (Aktobe), B–AL (Almaty), C–KA (Karaganda), D–KB (Kostanai), E–KO (Kyzylorda), F–KV (South Kazakhstan).(PDF)Click here for additional data file.S1 Table(XLS)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(PDF)Click here for additional data file.


Allium cepa L.) is an economically important vegetable crop around the world. Genetic and genomic research into various onion accessions will provide insights into the onion genome to enhance breeding strategies and improve crops. However, the onion’s large genome size means that studies of molecular markers are limited in onion. This study aimed to discover high quality single nucleotide polymorphisms (SNPs) from 192 onion inbred lines relating to short-day cultivation in Korea. Paired-end (PE) double digested restriction site-associated DNA sequencing (ddRAD-seq) was used to discover SNPs in onion. A total of 538,973,706 reads (25.9 GB), with an average of 2,658,491 high-quality reads, were generated using ddRAD-seq. With stringent filtering, 1904 SNPs were discovered based on onion reference scaffolds. Further, population structure and genetic relationship studies suggested that two well-differentiated sub-populations exist in onion lines. SNP-associated flanking sequences were also compared with a public non-redundant database for gene ontology and pathway analysis. To our knowledge, this is the first report to identify high-quality SNPs in onion based on reference sequences using the ddRAD-seq platform. The SNP markers identified will be useful for breeders and the research community to deepen their understanding, enhance breeding programs, and support the management of onion genomic resources.Onion ( Allium cepa L., 2n = 16) is an important monocotyledonous crop that is widely cultivated and consumed worldwide. It belongs to the Amaryllidaceae family, which also includes garlic, shallots, and scallions. These crops are grown in temperate and tropical regions, highly valued for culinary purposes. They inhabits nutritional, medicinal and pharmacological benefits, including being anticarcinogenic, anti-inflammatory, antimicrobial, and antifungal [http://faostat.fao.org]). Most onions grown in Korea are short-day and open-pollinated while the annual production of onions is affected by several biotic and abiotic components of the ecosystem [Pseudomonas aeruginosa), viral , and fungal diseases , Stemphylium vesicarium; White Rot, Sclerotium cepivorum Berk; Basal Rot, Fusarium oxysporum f.sp.; Downy Mildew, Peronospora destructor; Onion Smut, Urocystis cepulae; Onion Smudge, Colletotrichum circinans; Black Mould, Aspergillus niger; and Neck rot, Botrytis allii). Environmental stresses (abiotic factors) such as high temperature, salinity, drought, and soil nitrogen deficiency also limit onion production and quality.Onion   and restIn this study, we used paired-end (PE) ddRAD-seq technology to develop a novel reference-based genome-wide SNP resource from onion inbred lines cultivated in Korea. Filtered high-quality SNPs from 192 cultivars related to short-day inbred lines were subjected to population structure and genetic relationship studies. In addition, we functionally annotated SNP flanking sequences to determine similarity with known genes and biological functions.The 192 short-day onion inbred lines used for this study were purchased from four Korean companies: Nonghyup Seed (NH: 40), Bio Energy Crop Research Institute (Muan) (B: 39), Changnyeong Onion Research Institute (CN: 36), and Nongwoo Seed (NW: 77) . To extret al. [Genomic DNA from each line was double-digested with PstI and EcoRI restriction enzymes. ddRAD-Seq libraries were constructed using two combinations of restriction enzymes, and the sequencing procedure published by Shirasawa et al.  was follhttp://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Low-quality sequences were removed using PRINSEQ (http://prinseq.sourceforge.net) [http://hannonlab.cshl.edu/fastx_toolkit). A total of 8,822,891 cleaned and filtered sequence reads of five libraries for B001, CNH001, CNJ001, NH001, and NW001 were assembled with “large or complex genome” mode of Newbler v3.0 (Roche). The resultant 12,718 sequences spanning 1,599,536 bases were used as a reference for the following analysis. The reads from the PE sequences of each accession were mapped to the reference sequence using Bowtie 2 (version 2.1.0) [Sequencing data obtained from 192 inbreds were examined for their quality using the FastQC tool (rge.net)  and adapn 2.1.0) . The resn 2.1.0) . Genomicn 2.1.0) . Missingn 2.1.0) , and theK values from 1–10 . For this, the Markov Chain Monte Carlo (MCMC) length of the burn-in period was set at 30,000 iterations, and after a burn-in period, the number of iterations was adjusted to 50,000 steps. The admixture model was implemented to obtain the optimal K value. We followed a delta-K procedure based on the method published by Evanno et al. [http://taylor0.biology.ucla.edu/structureHarvester/) [K value from independent runs. The population structure comprising SNPs detected from inbred lines were visualized using STRUCTURE with the following options: (i) select optimal K value run, (ii) show plot as ‘bar plots’, and (iii) sort by Q [The heterozygosity and the percentage polymorphic loci was calculated in the onion inbreds using GenAlex version6.03. The population structure of the Korean onion lines was estimated using STRUCTURE (version 2.3.4)  with dato et al. , using tvester/)  to estimGenAlEx software (version 6.5) was used to calculate pairwise relatedness (genetic distance) between inbred lines, and principal component analysis (PCA) was performed using TASSEL (version 5.2.42) . The genhttp://www.blast2go.com/b2ghome). The three major GO terms, biological process (BP), cellular component (CC), and molecular function (MF), were determined with annotation cut-offs of ≥ 55; GO weight, 5; and e-value hit filter, < 1.0E-6 [SNP-associated scaffold sequences were retrieved from the reference genome and used as BLASTX queries against the non-redundant protein database at the National Center for Biotechnology Information (NCBI). BLAST parameters were as follows: e-value cut-off, 1.0E-5; word size, 3; number of BLAST hits, 3; and other parameters, default. The most similar sequence matches for each SNP-associated scaffold was selected based on multiple hits, and these were used to find Gene Ontology (GO) terms, and enzyme and pathway details using Blast2GO suite (< 1.0E-6 . Details< 1.0E-6 .Genomic DNA isolated from 192 onion inbred lines was used to prepare ddRAD (PstI and EcoRI) representation libraries. These constructed libraries were then successfully sequenced using the Illumina HiSeq platform. PE sequencing of individuals yielded 538,973,706 reads, with an average of 2,807,154 (~2.8 million) reads per accession, covering 25.9 GB of sequenced data. An average of 2,658,491 high quality reads were obtained and used for reference genome alignment. The reference genome comprised 12,718 scaffolds, with an average scaffold length of 126 bp (range: 96–556 bp). An average of 33.3% reads were aligned to the onion reference genome, with the reference genome alignment ratio ranging between 17.2% and 51.5%. ddRAD-sequenced accessions contained 37.7% GC content on average (range 36–43%). A statistical summary of data collected about raw reads, cleaned reads, reference genome-mapped reads, and alignment ratios for individual accessions are summarized in Allium cepa [ucumis melo [Brassica napus [Mapped reads were further investigated to identify SNPs. A total of 1904 SNPs were identified from ddRAD-sequences of all 192 onion inbred line accessions, and these SNPs comprised 558 scaffolds . High-quium cepa , and simmis melo , Brassicca napus , and oilca napus . The traca napus , similarca napus , and higca napus . A genetca napus . Howeverca napus –46. TherHo) is less than the expected heterozygosity (He). The mean Ho and He of the onion inbred lines among the four populations were calculated as 0.00 and 0.36, respectively  among the four populations genotyped using 1,904 SNPs showed that the observed heterozygosity , green (Q2), and blue (mixture of Q1/Q2) colors can be seen . PhylogeAllium sativum) [In practice, breeders preferred to select plant materials based on their germplasm collections, relatedness limitations and long term consistent assistance to support breeding programs. Relatedness analysis is important for this purpose, and helps breeders to understanding the backgrounds of their plant materials. This model can also be used to obtain results for genomic selection and association-related studies in various plant species such as large garlic (sativum) , cowpea sativum) , and othsativum) .Asparagus officinalis, Allium species , and Daucus carota subsp. sativus. In addition, functional annotations resulted in 78 GO tserms with 41 blast hits. These 78 GO terms were further classified into three functional categories such as cellular component , molecular function , and biological process . Some scaffolds matched with more than one GO term, whereas a few matched only one GO term  . The rem GO term . Cellula GO term . Most scBiological process GO terms were also categorized into seven subcategories: cellular process (GO: 0009987), 21 scaffolds; metabolic process (GO: 0008152), 20 scaffolds; response to stimulus (GO:0050896) 2 scaffolds; cellular component organization or biogenesis (GO:0071840) 3 scaffolds; biological regulation (GO:0065007) 2 scaffolds; regulation of biological process (GO:0050789) 2 scaffolds; and signaling (GO:0023052), 1 scaffold. Detailed classification of level 3 GO terms are plotted in The number of annotated scaffolds discovered in this study is less than those in known genome sequences; this finding is similar to previous studies that have conducted de-novo transcriptome analysis. In addition, these kind of results obtained due to the sequence lengths, and depth SNP or scaffold coverage mean these results might be unique to Korean onion inbred lines . AnalysiWe identified highly valuable SNP resources from Korean onion lines using ddRAD-seq analysis. To our knowledge, this is the first report of reference scaffolds being used for the discovery of SNPs related to short-day cultivation in Korean onion lines. The high-quality SNPS identified from this study, with details of their genetic makeup and functional annotations, will be useful for deepening our understanding and updating our knowledge of onion genomic resources. Furthermore, markers developed from the SNPs we have found might be used for onion breeding programs, cultivar identification, marker-assisted selection programs, and high-density map development and validation with high throughput sequencing methods in future.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(DOC)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.S6 Table(XLSX)Click here for additional data file.


We propose that on‐farm conserved rice landraces during the short‐term domestication had a highly polygenic basis with many loci responding to selection rather than a few loci with critical changes in response to selection. Moreover, loci affecting important agronomic traits and biotic or abiotic stress responses have been particularly targeted in selection. A genome‐wide association study identified 90 significant signals for six traits, 13 of which were in regions of selective sweeps. Moreover, we observed a number of significant and interesting associations between loci and environmental factors, which implies adaptation to local environment. Our results provide insights into short‐term evolutionary processes and shed light on the underlying mechanisms of on‐farm conservation.Traditional rice landraces grown under on‐farm conservation conditions by indigenous farmers are extremely important for future crop improvement. However, little is known about how the natural selection and agriculture practices of indigenous farmers interact to shape and change the population genetics of rice landraces grown under on‐farm conservation conditions during the domestication. In this study, we sequenced DNA from 108 core on‐farm conserved rice landraces collected from the ethnic minority regions of Yunnan, China, including 56 accessions collected in 1980 and 52 accessions collected in 2007 and obtained 2,771,245 of credible SNPs. Our findings show that most genetic diversity was retained during the 27 years of domestication by on‐farm conservation. However, SNPs with marked allele frequency differences were found in some genome regions, particularly enriched in genic regions, indicating changes in genic regions may have played a much more prominent role in the short‐term domestication of 27 years. We identified 186 and 183 potential selective‐sweep regions in the  The “mpileup” command was used to identify SNPs and Indels with the parameters “‐m 2 –F 0.002 ‐d 1,000.” In the downstream analysis, the raw population variations were filtered by requiring a respective minimum and maximum coverage depth of 4 and 1,000, a minimum RMS (root mean square) mapping quality score of 20, and missing genotype >50% of the 108 rice accessions. Consequently, a total of 2,771,245 of SNPs and 432,174 indels  were retained for downstream analyses , which first runs a number of independent phylogenetic methods and then creates a combined tree using a stochastic context ‐free grammar approach. The bootstrap test  and genetic differentiation (FST) between rice landraces from 1980 to 2007 using VCFtools  was applied to quantify polymorphism levels . We used an empirical procedure and selected windows with significantly high log2 (θπ 1980/θπ 2007) and ZSTF values from their respective empirical distributions and considered these as regions with selective‐sweep signals along the genome. The values were at the right 5% tails, where the log2 (θπ 1980/θπ 2007) thresholds were 1.02 and 1.41 for indica and japonica, respectively, and ZSTF thresholds were 1.92 and 2.00, respectively. Then, adjacent selective‐sweep regions were merged together to form a whole putative selected region. To further confirm the selection signals identified, we performed a genome scan using a cross‐population composite likelihood approach XP‐CLR , were considered as selected regions.To detect regions with significant signatures of selective sweep, we Z‐transformed the distribution of 2.6indica and japonica, respectively. They were identified to undergo strong selection sweep. These genes were submitted to Gene Ontology (GO)  for ten agronomic traits: days to heading, plant height, panicle length, effective panicles, grains per panicle, grain length, grain width, grain length‐to‐width ratio, spikelet fertility, and 1,000‐grain weight. All landraces were planted on November 27, 2011, in the Hainan experimental station of Chinese Academy of Agricultural Sciences and July 16, 2012, in the Xishuangbanna experimental station of Yunnan Academy of Agricultural Sciences. Phenotypic measurements of the traits were recorded from the ten middle plants, and mean values of traits were calculated for each landrace. Finally, the average phenotypic value of two environments was used for the GWAS.http://www.maizegenetics.net/tassel). A kinship matrix (K‐matrix), the pairwise relationship matrix calculated by TASSEL v.5.0, and the Q‐matrix as a correction for population structure were used in the MLM association models to calculate P‐values to associate each SNP marker with the trait of interest and to avoid spurious associations by TASSEL v.5.0.Association analyses were conducted using MLMs . The K‐value was set to 2 based on the eigenvalues of the PCA of the genetic data as the number of latent factors. Five replicates were verified for convergence. The median z‐scores of five runs were used to re‐adjust the p‐values. For an expected value of the FDR (q = 5%), a list of candidate loci were obtained by using the Benjamini–Hochberg procedure.Latent factor mixed models (LFMM)  (Table FST = 0.026). A similar trend in genetic diversity was found in japonica . This result indicates that most genetic diversity in both indica and japonica landrace germplasms grown under on‐farm conservation conditions was retained during the short‐term period of domestication.We explored phylogenetic relationships among the 108 rice landraces through whole‐genome SNP analysis , but no excess of SNPs with high ΔAF in intergenic regions  between 7 Figure –S7. Onlyd Tables –S7. We fa Tables –S7.3.3indica and japonica landraces, we calculated the nucleotide diversity ratio (θπ 1980/θπ 2007) and genetic differentiation (FST) between rice landraces in 1980 and 2007 for sliding windows in both indica and japonica landraces, respectively  values, we identified 891 and 954 candidate regions with selective‐sweep signals  in log2 (θπ 1980/θπ 2007) and ZFST values compared with the genomic background in both indica and japonica  was observed for a region on chromosome 6 of the indica genome, which includes the SSIIa (Similar to Starch synthase IIA) gene , encompassed the entire coding region of Pid3 (Pyricularia oryzae resistance‐d3), which confers blast resistance to Magnaporthe oryzae  in the japonica genome and a SSIIa‐like gene tree  was detected in a region on chromosome 6 of the japonica genome, which includes the OsLIC1 gene  released by Q‐TARO . A total of 986 SNPs that obtained |z|‐scores greater than 5 (p < 10–10)  were associated with monthly temperature and precipitation, respectively  (Frichot 0) Table  were ass62 Table , which i62 Table , reflecty Tables –S22. Amo4To date, few studies have focused on the short‐term domestication process and the population dynamics underlying short‐term domestication are still poorly understood  was domesticated from wild rice (Oryza rufipogon) thousands of years ago  were found in indica and japonica genomes, which were likely directly targeted by selection during the 27‐year domestication period. Notably, we found that SNPs with marked allele frequency differences between rice landraces collected in 1980 and 2007 were enriched in genic regions, which suggests changes in genic regions may have played a much more prominent role in short‐term domestication than changes in intergenic regions.Rice   in the s Tables , S9. To In summary, we provide a large dataset of genomic variation observed in on‐farm conserved rice landraces in this study. We identified millions of SNPs in representative rice landraces collected in 1980 and 2007, providing an unprecedented opportunity to finely resolve genome‐wide genetic diversity and selection footprints in landraces grown under on‐farm conservation conditions during a short‐term period of domestication. We demonstrated that farmer selection in combination with natural selection played an important role and strong selection can leave its footprint on genome‐wide polymorphism patterns. We propose that on‐farm conserved rice landraces during short‐term domestication had a highly polygenic basis with many loci responding to selection rather than a few loci with critical changes in response to selection. Moreover, the loci affecting important agronomic traits and biotic or abiotic stress response were particularly targeted. Our integrative analyses demonstrate that the rice landraces grown under on‐farm conservation conditions have the potential to be a dynamic, evolving genetic system that can undergo continuous differentiation and variation in response to evolutionary pressures, both natural and those imposed by farmers. On‐farm, in situ conservation is a recommended strategy to conserve crop genetic resources. Click here for additional data file. Click here for additional data file.


It is estimated that the impact of related genes on the risk of Alzheimer’s disease (AD) is nearly 70%. Identifying candidate causal genes can help treatment and diagnosis. The maturity of sequencing technology and the reduction of cost make genome-wide association study (GWAS) become an important means to find disease-related mutation sites. Because of linkage disequilibrium (LD), neither the gene regulated by SNP nor the specific SNP can be determined. Because GWAS is affected by sample size and interaction, we introduced empirical Bayes (EB) to make a meta-analysis of GWAS to greatly eliminate the bias caused by sample and the interaction of SNP. In addition, most SNPs are in the noncoding region, so it is not clear how they relate to phenotype. In this paper, expression quantitative trait locus (eQTL) studies and methylation quantitative trait locus (mQTL) studies are combined with GWAS to find the genes associated with Alzheimer disease in expression levels by pleiotropy. Summary data-based Mendelian randomization (SMR) is introduced to integrate GWAS and eQTL/mQTL data. Finally, we prioritized 274 significant SNPs, which belong to 20 genes by eQTL analysis and 379 significant SNPs, which belong to seven known genes by mQTL. Among them, 93 SNPs and 2 genes are overlapped. Finally, we did 10 case studies to prove the effectiveness of our method. It is estimated that the impact of related genes on the risk of AD is nearly 70%. Importantly, neuronal cell death precedes the appearance of cognitive symptoms for 10 years or more, suggesting that targeted treatment needs to be performed before symptoms appear. Therefore, the identification of AD biomarkers such as genes, RNAs , proteinRecently, Jansen et al.  publisheHowever, GWAS still has certain limitations. The SNP is not necessarily the true pathogenic locus, but only related to the SNP that actually causes the disease due to the LD. GWAS usually analyzes the edge effects of individual loci while ignoring the interaction of multiple genes in complex diseases . TherefoIt was found that about 80% of the genetic susceptibility loci detected by GWAS were located in the noncoding region of the genome, suggesting that the pathogenic loci may have regulatory functions on gene expression. An important role of large-scale eQTL research is to be able to prioritize SNP loci  in GWAS mQTL is mainly based on the analysis of cis-mQTL, that is, using Beta value of methylation level of CpG locus near a gene as dependent variable, screening all SNP variations in the chromosomal region upstream and downstream of the gene as independent variable and regressing each SNP locus S and methylation level M in this region one by one, so as to obtain SNP loci significantly related to the methylation level of a gene. There is no doubt that methylation affects gene expression. This is very similar to eQTL, both of which can cause changes in expression through mutations in a single locus. Therefore, in recent years, more and more studies have been carried out to screen genes related to traits by combining mQTL with GWAS. Hägg et al.  integratIn our previous paper , we haveSince Zhu et al. proposed “SMR” in 2016, it has become a common way to identify the genes whose expression levels are associated with a complex trait because of pleiotropy. Using GWAS and eQTL data, SMR could screen trait-related genes. After two years, they applied SMR to mQTL data. They found 7,858 DNAm sites which are related to 14 complex traits.xy is the effect of x on y, bzx is the effect of z on x, and bzy is the effect of z on y. The definition of bxy is bxy = bzy/bzx, which means the effect of gene expression on phenotype without confounding factors. This idea is based on the Mendelian randomization  , amyotroDue to the complex linkage effects and statistical errors of the samples, the contribution of GWAS to biological research is reduced. GWAS may associate common diseases with thousands of DNA mutations, that is, every DNA region that happens to be active in diseased tissues may be associated with disease . Many GWAs we discussed before in the introduction, the interaction of multiple genes is considered, that is, the statistical values of each SNP are revised within the whole genome. In this section, we will process GWAS data in two steps: 1. meta-analysis, 2. using EB, revise the statistical value of each SNP within the whole genome.Since SE denotes the standard error of each SNP, it represents the reliability of Beta values. Then, weight of each Beta should be:iSE denotes the standard error for study i, wi denotes the weight of Beta.Then, the Beta after meta-analysis would be:i denotes effect size estimate for study i.βThen, we could use the weight of each Beta to calculate the result of meta-analysis.Finally, the overall Z-score could be obtained by the original equation.After meta-analysis, we could summary several GWAS datasets into one dataset. Then, we used EB to integrate all the Z scores in the whole genomic level. As we know that the SNP could interact with each other, the Z score of all SNP should have some relationship and obey normal distribution.The overall Z-score we obtained before obeying normal distribution with standard deviation is 1. Then,iZ denotes the real Z score.Real Z score obeys normal distribution:Then, the marginal distribution of Moreover, the posterior distribution should be:Then, we could know that Then,From the properties of inverse chi-square distribution,Then,Therefore, the EB estimation of B isFinally, we can put the  into BaThen, we have done the meta-analysis and revised the statistical value of each SNP within the whole genome.As shown in For GWAS dataset, Scelsi M A et al. obtained the data from 1,517 Caucasian ADNI subjects. Lambert JC et al.’s dataset is consisted of 17,008 Alzheimer’s disease cases and 37,154 controls. Marioni R E et al. obtained data from 314,278 participants.For eQTL dataset, SNPs within 1Mb distance from each probe are available in these three datasets. After meta-analysis, the estimated effective sample size n = 1194.For mQTL dataset, 5kb, 500kb, and 20kb are the available distance for the three datasets, respectively. After meta-analysis, the estimated effective sample size n = 1160.We did a meta-analysis of five groups of GWAS data and integrated them into a GWAS file.The blue block in GWAS included 1,474,846 SNPs, mQTL included 6,966,746, and eQTL included 1,067,443 SNPs. There are 149,326 SNPs occur in both GWAS and eQTL and 408,896 SNPs occur in both GWAS and mQTL. Therefore, we use SMR to test these repeated SNPs in data sets.Note that some SNPs are marked by multiple probes, so one SNP may significant in more than one gene. One SNP may affect expression of multiple genes.In We set a threshold as 0.05/(number of probers). For eQTL data, the threshold is 0.05/8362 = 5.98e-06. For mQTL data, the threshold is 0.05/97263 = 5.14e-07. The numbers of SNPs and genes identified by the two experiments are shown in As we can see in In this section, we want to confirm whether the 25 AD-related genes we found have been reported by others. In order to be precise, we only use the literature that got AD-related genes by biological experiments, rather than the bioinformatics method or GWAS method.We found 10 of 25 genes are reported to be related to AD by biological experiments. Some literary works may found that the other 15 genes are related to AD via other methods, but we would not discuss in this paper. This case study verified the effectiveness of our method and we hope the other 15 genes could be verified by biological experiments in future.AD brings great burden to patients and society and identifying AD-related genes can help us known the machanism of AD then diagnose and treatment. In this paper, we used SMR to find AD-related genes by GWAS, eQTL, and mQTL. There are some overlaps between GWAS and the other two datasets, which means that some SNPs are related to AD due to the change of expression level. SMR is a method which can identify the genes whose expression levels are associated with a complex trait because of pleiotropy.Due to the LD and interaction between genes, GWAS data has bias. In order to overcome these, we did meta-analysis on five GWAS datasets and then used EB to revise the Z-score of each SNPs in whole-SNP level.Finally, we found 653 SNPs reached the threshold of significance and they are associated with 25 genes. Ninety-three of SNPs are significant in both GWAS&eQTL and GWAS&mQTL tests. We did 10 case studies at last, which means that the 10 of 25 genes we identified have been verified to correlated to AD by biological experiments in existing literary works.The direct link for accessing eQTL and mQTL data is as follows (origin from PMID: 29891976).https://cnsgenomics.com/data/SMR/Brain-eMeta.tar.gzeQTL data: https://cnsgenomics.com/data/SMR/Brain-mMeta.tar.gzmQTL data: GWAS dataset 1,2,3 are from paper PMID:29860282. The direct link is for accessing them is as following.https://www.ebi.ac.uk/gwas/studies/GCST006134 & ftp://ftp.ebi.ac.uk/pub/databases/gwas/summary_statistics/ScelsiMA_29860282_GCST006134https://www.ebi.ac.uk/gwas/studies/GCST006136 & ftp://ftp.ebi.ac.uk/pub/databases/gwas/summary_statistics/ScelsiMA_29860282_GCST006135https://www.ebi.ac.uk/gwas/studies/GCST006135 & ftp://ftp.ebi.ac.uk/pub/databases/gwas/summary_statistics/ScelsiMA_29860282_GCST006136GWAS data 4 is from PMID: 24162737. The direct link is for accessing it is as following:http://web.pasteur-lille.fr/en/recherche/u744/igap/igap_download.phpGWAS data 5 is from PMID: 29777097. The direct link is for accessing it is as following:http://datashare.is.ed.ac.uk/download/DS_10283_3364.zipAll code could be downloaded byhttps://github.com/zty2009/Integrate-GWAS-eQTL-and-mQTL-data-to-identify-Alzheimer-s-Disease-related-genesTZang and YW are the corresponding authors. They help to revise and support data for this data. TZhao and YH are the co-first authors. They wrote the code and write the paper.This work was supported by the National Natural Science Foundation of China (No: 61571152 and 61502125), the National High-tech R&D Program of China (863 Program) , the National Science and Technology Major Project [Nos: 2013ZX03005012 and 2016YFC1202302], the Heilongjiang Postdoctoral Fund (Grant No. LBH-Z15179), and the China Postdoctoral Science Foundation (Grant No. 2016M590291).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.