GWAS identifies candidate gene controlling resistance to anthracnose disease in white lupin.Lupinus albus L.) is a promising grain legume to meet the growing demand for plant-based protein. Its cultivation, however, is severely threatened by anthracnose disease caused by the fungal pathogen Colletotrichum lupini. To dissect the genetic architecture for anthracnose resistance, genotyping by sequencing was performed on white lupin accessions collected from the center of domestication and traditional cultivation regions. GBS resulted in 4611 high-quality single-nucleotide polymorphisms (SNPs) for 181 accessions, which were combined with resistance data observed under controlled conditions to perform a genome-wide association study (GWAS). Obtained disease phenotypes were shown to highly correlate with overall three-year disease assessments under Swiss field conditions (r > 0.8). GWAS results identified two significant SNPs associated with anthracnose resistance on gene Lalb_Chr05_g0216161 encoding a RING zinc-finger E3 ubiquitin ligase which is potentially involved in plant immunity. Population analysis showed a remarkably fast linkage disequilibrium decay, weak population structure and grouping of commercial varieties with landraces, corresponding to the slow domestication history and scarcity of modern breeding efforts in white lupin. Together with 15 highly resistant accessions identified in the resistance assay, our findings show promise for further crop improvement. This study provides the basis for marker-assisted selection, genomic prediction and studies aimed at understanding anthracnose resistance mechanisms in white lupin and contributes to improving breeding programs worldwide.White lupin (The online version contains supplementary material available at 10.1007/s00122-021-04014-7. Lupinus albus L., 2n = 50) is a grain legume with a high-protein content and various health benefits that shows great potential to complement soybean and meet the growing demand for plant-based protein  still persist, and has been cultivated for more than 4000 years across the Mediterranean and Eastern Africa , which contains numerous important plant pathogens  to identify SNP markers for pod shattering  and phenotyped for anthracnose resistance under controlled conditions. These accessions were shown to be variable for key agronomic traits  accessions were collected across the Mediterranean region, Atlantic islands, Eastern Africa, Europe, Chile and Australia from seed genebanks and local partners. The accessions are described in Electronic Supplemental Material 1 (ESM_1). In total, the 200 accessions include commercial cultivars, breeding lines and traditional land races. The collection includes a large number of landraces from CREA’s white lupin world collection , and the shoot fresh weight is expressed relative to a control (SFWrel). All of the experiments were performed in a randomized complete block design with a minimum of 8 replicates per accession.The white lupin collection was phenotyped for anthracnose resistance under controlled conditions  using the high-throughput protocol described by Alkemade et al. . Stem woe et al. ). Disease et al. . At 10 de et al. ), the le2. Total field size was 304 m2 in Full-Reuenthal and 259 m2 in Feldbach. Trials were performed in a randomized complete block design consisting of 4 replicates. The field trials relied on natural infection and were scored 80, 100 and 135 days after sowing. The DSI ranged from 1  to 9 (dead), as described in Alkemade et al. . Field trials were performed within six row plots according to Alkemade et al.  at threee et al. . The sAUlme4  were included as fixed effects, while environment, environment x accession and replicated block nested in environment were fitted as random factors, after confirming the assumptions of normality of residuals and homogeneity of variance. To achieve a normal distribution, data were transformed with a square root (yield), log10 (SFWrel), square (sAUDPCCC), or logit (LSrel) transformation. The mean separation between accessions and the overall mean of all accessions combined was analyzed using Dunnett’s test (P ≤ 0.05). The data are presented as non-transformed estimated least-squares means obtained using the aforementioned mixed model. Estimated means of controlled and field conditions were correlated using the Pearson correlation coefficient. Broad sense heritability (H2) was estimated as: genotypic variance/phenotypic variance  and quantified with a Quant-iT™ PicoGreen™ dsDNA Assay Kit . Samples were genotyped in four different batches referred to as TX2016-1 (88 samples), TX2016-2 (32 samples), EL2018 (40 samples) and EL2020 (40 samples), using slightly different procedures as follows:ApeKI  and ligated to unique barcodes and common adapters. Equal volumes of ligated products were pooled and purified with NucleoSpin Gel and PCR Clean-up . Template DNA (50 ng) was mixed with two primers (ESM_2) and KAPA Library Amplification Readymix . Amplification steps were as follows: 5 min at 72 °C, 30 s at 98 °C and 10 cycles with 10 s at 98 °C, 30 s at 65 °C and 30 s at 72 °C. Sequencing was performed at the University of Texas (USA) on four Illumina HiSeq 2000  lanes, at 100 bp single end. DNA samples for libraries EL2018 and EL2020 were sent to The Elshire Group Ltd.  for library preparation and sequencing. Library preparation was performed according to Elshire et al. (Genotyping-by-sequencing (GBS) libraries for TX2016-1 and TX2016-2 were prepared with a modified Elshire et al.  protocole et al.  as descrL. albus genome version 1.0 .GBS raw reads were demultiplexed using axe demultiplexer (Murray and Borevitz r2) between markers using LD.decay in R  pair-wise LD estimates were used to calculate average LD decay within a sliding window of 5 kb. LD decay was visualized by plotting r2 estimates against genetic distance (kb). A pairwise distance matrix derived from Euclidean distance of the full SNP dataset was calculated in R to construct a Ward Hierarchical clustering tree  of SNP markers was calculated as the pairwise squared correlation coefficient (rel and SFWrel. The association between SNPs and phenotypes was determined by performing a single-trait GWAS following a single-locus mixed linear model (MLM) and multi-locus Bayesian information and linkage disequilibrium iteratively nested keyway (BLINK) model . The first ten principal components (PCs) were included as covariates to control for population structure, and the Astle kinship matrix was included to account for cryptic relatedness  plots were generated within statgenGWAS.A genome-wide association study (GWAS) was performed on 181 accessions and 4,611 SNPs using estimated least-square means for the traits disease score (sAUDPC), LSr2 > 0.5) with a significant SNP and when within 10 kb of significant SNPs. Candidate genes were located using the white lupin reference genome (v 1.0) browser , peanut (Arachis hypogea), common bean (Phaseolis vulgaris), soybean (Glycine max) and model species Medicago truncatula (LPWG Candidate genes were considered when containing a significant SNP or a SNP in LD (ula LPWG . The potP < 0.0001) for all three anthracnose related traits, sAUDPC, LSrel and SFWrel, were observed with heritabilities of 0.77, 0.78 and 0.74, respectively. Significant (P ≤ 0.05) Pearson correlations were found between the three traits (r > (−)0.86; ESM_4). For twelve selected accessions, strong correlations were observed between these three traits and the overall disease assessment means of three-year field trials in Switzerland (r > (−)0.8; ESM_5). We did not observe complete resistance against anthracnose, which we interpret as evidence that resistance in white lupin is quantitative. For sAUDPC, LSrel and relative SFWrel, 8, 13 and 2 accessions, respectively, were more resistant than the respective overall mean . Six of these accessions originated from Ethiopia, two from Chile and one being the newly available commercial variety Frieda. In contrast, seven accessions were more susceptible than the overall mean. Remarkably, the Ethiopian landrace P27175 was resistant in one seed batch (FiBL 39) but susceptible in another (FiBL 19) and showed distinct heterozygosity rates of 0.77% and 32.2%, respectively (ESM_1). Resistant FiBL025 (R-6020) and susceptible LAP0119b (Aster) seeds showed a black-speckled morphology typical for wild graecus types.Disease phenotyping of 200 white lupin accessions under controlled conditions revealed a range of resistant and susceptible accessions Fig. . Strong r2 = 0.45), and SNPs were in linkage (r2 > 0.5) over an average distance of 2.5 kb (ESM_6). Cluster analysis on the full SNP dataset distinguished 4 subgroups (I–IV) based on bootstrap support values (BS) > 90 and a branch length threshold of 10  < 5%, missing SNP marker rate > 10%, missing rate per accession > 20% and heterozygosity > 40% . LD decayed to half its maximum value at 2.9 kb (P = 1.08E-05), we identified two highly significant SNPs, Lalb_Chr05_2957601 and Lalb_Chr05_2957940, for both sAUDPC  and LSrel  and SFWrel (P = 2.72E-07), and between Lalb_Chr05_2957940 and LSrel  following a MLM and BLINK model. We included the first 10 principal components (PCs) and the Astle kinship matrix to correct for population structure. The first 10 PCs explained 24% of the genetic variance. The resulting Q-Q plots revealed that the model was well calibrated, as we observed a good approximation between the expected and observed P-values , associated with LSrel (ESM_7 and Table P = 5.00E–5)), were found on chromosome 1  for LSrel, on chromosome 13  for SFWrel and on chromosome 6  for sAUDPC (ESM_9).Analysis with the BLINK model identified an additional SNP on chromosome 5, Lalb_Chr05_3706534 P = .91E-07, r2 > 0.5) to a significant SNP or when located within 10 kb of a significant SNP. The significant SNPs Lalb_Chr05_2957601 and Lalb_Chr05_2957940 are both located within an exon of the same gene: Lalb_Chr05g0216161 . Homologs in closely related species encode leucine-rich repeat (LRR) receptor-like serine/threonine-protein kinases, which are often implicated in plant defense against fungal pathogens  to overall three-year field plot disease assessments in Switzerland, confirming field-relevance of high-throughput phenotyping under controlled conditions . Principal component analysis showed overlap between Groups II, III and IV, while only Group I, exclusively containing landraces from the South-Eastern Mediterranean, formed a clearly distinct group. Group III consisted primarily of Egyptian and Ethiopian landraces, with Ethiopian accessions strongly grouping together. Landraces from Ethiopia were previously reported to form a distinct group within white lupin  resistance in white lupin , the RING finger protein gene, CaRFP1, containing a VWFA domain, was shown to act as E3 ubiquitin ligase and was highly upregulated during C. coccodes infection . Homolol et al. . In peppLalb_Chr05g0217341. Homologs of Lalb_Chr05g0217341 in closely related legume species encode for paired amphipathic helix protein Sin3-like 4 proteins, which are known to be involved in powdery mildew (Podosphaera fusca) resistance in cucumber  in apple  in rice , could only explain 16 to 34% of disease phenotypic variance, the identification of few low peak SNPs and the quantitative nature of the trait suggests that anthracnose resistance is under polygenic control as indicated by Książkiewicz et al.  could also imply oligogenic control.SNP Lalb_Chr05_3706534 is located in the non-coding region of z et al. , but theLalb_Chr05g0216161 gene, e.g., via gene expression studies, could shed first light on white lupin resistance mechanisms against anthracnose disease. The obtained dataset also provides a basis for marker-assisted selection and the development of genomic prediction models for anthracnose resistance. Overall, this study contributes to understanding the genetic make-up of anthracnose resistance in white lupin and supports future crop improvement.This study showed that GWAS, thanks to the weak population structure, fast LD decay and the availability of a high-quality reference genome, is a powerful tool to identify resistance loci in white lupin and provides the basis for further gene mapping. Further characterization of the E3 ubiquitin ligase encoding Supplementary file1 (PDF 998 kb)Supplementary file2 (XLSX 38 kb)Supplementary file3 (XLSX 2751 kb)Below is the link to the electronic supplementary material.


Weeds represent one of the major constraints for faba bean crop. The identification of molecular markers associated with key genes imparting tolerance to herbicides can facilitate and fasten the efficient and effective development of herbicide tolerant cultivars. We phenotyped 140 faba bean genotypes in three open field experiments at two locations in Lebanon and Morocco against three herbicide treatments  and one in greenhouse where T1 and T3 were applied. The same set was genotyped using genotyping by sequencing (GBS) which yield 10,794 high quality single nucleotide polymorphisms (SNPs). ADMIXTURE software was used to infer the population structure which revealed two ancestral subpopulations. To identify SNPs associated with phenological and yield related traits under herbicide treatments, Single-trait (ST) and Multi-trait (MT) Genome Wide Association Studies (GWAS) were fitted using GEMMA software, showing 10 and 14 highly significant associations, respectively. Genomic sequences containing herbicide tolerance associated SNPs were aligned against the NCBI database using BLASTX tool using default parameters to annotate candidate genes underlying the causal variants. SNPs from acidic endochitinase, LRR receptor-like serine/threonine-protein kinase RCH1, probable serine/threonine-protein kinase NAK, malate dehydrogenase, photosystem I core protein PsaA and MYB-related protein P-like were significantly associated with herbicide tolerance traits. Vicia faba L.), also known as broad bean, fava bean, horse bean and field bean, was first domesticated in the Near East around 9000–10,000 BC3. The recent estimates suggest that it is extensively grown on 2.57 M ha area distributed across 38 countries with global production of 5.4 million tonnes4. Faba bean is an important source of food and feed for human and animal consumption because its seeds are rich in proteins, carbohydrates, fibers and micronutrients5. Faba bean plays an important role in sustainable agriculture and ecosystem services because of its ability to improve soil fertility by fixing atmospheric nitrogen6, and its potential to enhance the grain yield of succeeding/companion crops when planted in rotation or intercropped with cereals7. Concerted efforts have been undertaken to improve yield, adaptation to different environments, tolerance to abiotic stresses including heat, drought, waterlogging and frost10 resistance to biotic stresses such as diseases, insect pests, viruses and parasitic weeds12, seed quality13 and other agronomic traits. These efforts have more than doubled the global average yield from 0.9 tonnes/ha in 1964 to 2.1 tonnes/ha in 20194. However, the current production remains insufficient to meet its global consumption. Faba bean performance is highly influenced by environments and genotype × environment (GE) interaction, making phenotypic selection for quantitative traits of breeders’ interest inefficient and cumbersome.Faba bean (14. Thanks to the advances in the next generation sequencing technologies (NGS) that has enabled the generation of large volumes of sequences17 and facilitated the discovery of single nucleotide polymorphisms (SNPs) that can be associated with key breeding traits either through biparental mapping or through genome wide association studies (GWAS)18. Unlike biparental mapping, GWAS utilizes natural populations and exploits linkage disequilibrium (LD) to detect SNP-trait associations with higher resolution19. However, the power of GWAS depends on the size and structure of the population used for the analysis20. While it is sometimes not feasible to phenotype large populations in a single field trial, multiple field trials, e.g. different treatments, locations or seasons, can be jointly analyzed in one model named as multi-variate or multi-trait GWAS which has shown to have higher power compared to the standard single-trait GWAS21. Such approach can assist conventional breeding by implementing marker assisted selections in early generations22. Although significant progress has been made in faba bean genomics and many genetic maps are available25, the marker density of most of them is still too low to enable accurate prediction of desired traits. SNPs correlated with traits of interest such as resistance to ascochyta and broomrape or vicine-convicine content29 have been identified, however, no study was conducted to associate SNPs with herbicide tolerance in faba bean.Faba bean has a relatively large genome size of 13 Gb30. When weeds are left uncontrolled, they cause severe loss on grain yield of up to 70%31. An integrated approach with many control measures has been recommended to provide protection against weeds34 but with limited success. Many studies have acknowledged breeding for weed resistance by selecting for morphological characteristics that promote competition and allelopathy such as early seedling emergence, seedling growth, greater plant height, greater root volume37, but the resistance against most parasitic weeds is a difficult task because of its complex nature and low heritability39. Thus, recent studies have focused on developing herbicide tolerant faba bean lines41. Abou-Khater et al.42 evaluated faba bean germplasm for traits associated with tolerance to metribuzin and imazethapyr, two herbicides commonly available that can control the majority of weeds threatening faba bean production. They found that crop phenology, plant architecture and grain yield related traits were greatly affected by the herbicide treatments. Although useful sources for herbicide tolerance were identified by the authors, such field techniques are very laborious and require multi-environmental data. Associating the herbicide tolerance related traits42 with molecular markers to select for herbicide tolerance would facilitate the detection of useful markers that can be used to select herbicide tolerant lines in early generations. Keeping this in mind, the present study was undertaken to identify candidate loci significantly associated with tolerance to two post emergence herbicides, namely metribuzin and imazethapyr under different environments using GWAS and to identify associated SNP markers that can be used for introgressing such traits into desired agronomic background.Weeds are among the difficult-to-control biotic stresses that affect faba beanp-value < 0.001 except for the RIGCC  values for each genotype and treatment across field trials. The genotypic effects for all studied traits and reduction indexes were significant across trials at a LT Table . Our resLT Table . In addiLT Table . MoreoveLT Table .Table 1COur results also showed that the first HDS1) and second (HDS2) herbicide damage scores per genotype varied from 1 to 5 across trials. Combined results of the herbicide damage scores (HDS1 and HDS2) showed that after one month of the herbicide application, 5 and 42% genotypes recovered from the damaged caused by metribuzin and imazethapyr treatments while damages in 56 and 10% genotypes exacerbated , and A/G (4029 SNPs), followed by A/T 836 SNPs), G/T (761 SNPs), A/C (619 SNPs), and C/G (298 SNPs). The average CV values for the 100 replicates of the population structure started to increase directly after K = 2 indicating the presence of two ancestral subpopulations in the germplasm set used in the present study. However, we presented the results of K up to 4 because their 100 replicate runs resulted in comparable classification of genotypes into ancestral subpopulations with top > 20% of replicates having almost the exact log-likelihood values  for DFLR was associated with three treatments  in TR16, while another five SNPs were associated with two scores for PLHT or DFLR  were associated with a specific trait and its correspondence RI score. Another five SNPs showed association with two different traits of which SNODE_3696_16 and SNODE_77186_51 were associated with GYPPLT in TR16, treatments M and I respectively, while SNODE_22383_32 was associated with RI in TR16, treatment M, for the same traits. SNODE_239220_75 was associated with TR19_DMAT_I and TR16_NPPT_I_RI, while SNODE_7114_58 showed associations with five DFLR and DMAT across environments/treatments . Analyzing all 103 traits (including RI scores) with the ST-GWAS model resulted in only 10 highly significant associations with the Bonferroni threshold as well as 110 suggestive associations for only 66 traits while the remaining traits had no associated SNPs  resulted in 14 highly significant associations and 64 suggestive associations for all traits represented by 72 SNPs Table . The larSCONTIG127798_41 associated with reduction index of GCC and DFLR is located within a gene annotated as acidic endo-chitinase annotation, SNODE_14298_44 associated with the reduction index of PLHT is located within a gene annotated as LRR receptor-like serine/threonine-protein kinase RCH1, SNODE_3696_16 associated with GYPLT is located within a gene annotated as Probable serine/threonine-protein kinase NAK, SNODE_4187_38 associated with the reduction index of DFLR is located within a gene annotated as malate dehydrogenase, SNODE_559376_60 associated with the reduction index of NPPLT is located within a gene annotated as photosystem I core protein PsaA, while SNODE_7114_58 associated with DFLR is located within a gene annotated as MYB-related protein P-like 53, the first common enzyme in the biosynthesis of the branched-chain amino acids54 causing the death of meristematic cells. On the other hand, significant increase in the number of branches in herbicide treated plants could be caused by the plant recovery which occurs at the lateral meristem in dicots resulting in the development of new branches. The genotypic variation observed in the herbicide damage scores (HDS) highlights the difference in the reaction of each genotype toward post emergence herbicide application in faba bean. This observation was expected as the evaluated genotypes are genetically diverse22. The differences observed between the first (HDS1) and the second (HDS2) scores were due to the recovery or deterioration of the plants one month after herbicide treatment. The recovery might result from the metabolism of the herbicides into inactive compounds55. Therefore, the observed differences in the genotype ability to recover might be due to differential rate of metabolic degradation for imazethapyr treatment47 and to differential disruption of electron transfer for metribuzin treatment.Weed menace is a serious threat to faba bean production, and the identification of herbicide-tolerant varieties is one of the most effective methods for weed control. The results obtained from the present field and greenhouse studies demonstrated how the post-emergence application of metribuzin or imazethapyr negatively affects faba bean plants. Herbicide application affected the crop phenology by delaying flowering and maturity. Although the delayed flowering helps plant escape the risk of frost in regions like Western Australia, there might be a potential yield penalty as the plants run out of moisture before it can fill its grain2222 . As expected, MT-GWAS analysis exposed higher detection power compared to ST-GWAS analysis due to the larger datapoint fitted in the model which is equivalent to increasing the population size21. This was revealed by the larger number of highly significant as well as suggestive association per trait detected  has also been demonstrated in different studies66. Burns et al.67 concluded that herbicide stress is perceived similarly to other abiotic stresses and reported modification in the level of the protein kinase gene family in the multiple herbicide resistant Avena fatua.Identification of key genes, mechanisms and functional markers is essential to develop herbicide tolerant faba beans. The associations between some genes identified in this study and herbicide tolerance have been reported previously in different crops. Acidic endochitinase and malate dehydrogenase which were found to be associated with the reduction indexes of DFLR and GCC were among the proteins affected by the application of sulfonylurea herbicide in soybeansMYB gene family that comprises one of the richest groups of transcription factors in plants. Members of this family have a well-established role in abiotic stress responses69. Bhoite et al.70 found also that the transcription factors MYB were significantly expressed under metribuzin stress. The photosystem I (PS I) core protein PsaA that is found in the present study to be associated with the reduction index of NPPLT is a subunit membrane protein complex involved in photosynthesis. PS I and PS II drive the light reaction of photosynthesis. The first stage of the light reaction occurs in PS II whereas the final stage of the light reaction occurs in PS I71. The metribuzin applied to faba bean plants in this study inhibits PS II by disrupting electron transfer through binding to the D1 protein of the photosystem II complex in chloroplast thylakoid membranes51. This mode of action explains the involvement of the PS I in the reaction toward herbicide application especially that PS II comes first in the path of the electron flow followed by PS I.The MYB-related protein P-like which was found associated with DFLR is involved in herbicide tolerance belongs to the The described mechanism of action of the annotated genes suggests that DFLR_RI and GCC_RI are associated with tolerance to imazethapyr while DFLR and NPPLT_RI are associated with tolerance to metribuzin, and GYPLT and PLHT_RI are associated with tolerance to both herbicides.Weeds represent a major problem to faba bean crop which limits its expansion in many production regions. By excluding faba bean and other legume from the cropping system, cereal monoculture will continue to deplete the soil, lowering its quality and indirectly reducing yield and quality of the produce. Herbicide tolerant faba bean lines could be a game changer in the reintegration of faba bean in modern cropping systems as it contributes to the reduction of production cost by avoiding excessive use of manual weeding. Considering the many advantages of herbicide tolerance in faba bean, it is imperative to breed elite cultivars that features this trait. However, field selection is very costly and time consuming. The integration of genomic selection and marker assisted selection will improve selection accuracy, increase the selection intensity and shorten the breeding cycle when selecting at early generations. In the present study, we identified genomic regions associated with tolerance to imazethapyr and metribuzin herbicides as highly significant associations between SNPs markers and phenological and yield traits related to herbicide tolerance were detected using multi-trait association. These markers will be useful for improving the efficiency of faba bean programs and represent important steps towards the selections for herbicide tolerance.major, 17 minor, 63 equina and 9 paucijuga genotypes42. In addition to the test genotypes, a total of 6 faba bean cultivars  were included in the experiments. The seeds used in the current experiments are sourced from the reserve seeds that are multiplied each year under insect-proof cages in order to ensure purity of the evaluated accessions.A set of 134 faba bean genotypes comprising 118 landraces from 42 countries and 16 ICARDA breeding lines that were used to establish a reference set under the Generation Challenge Program (GCP) was used for phenotyping and genotyping in the present study. Previous assessment with Simple Sequence Repeat (SSR) markers showed that the set was genetically diverse and comprised 45 A total of four experiments were conducted: three field and one greenhouse experiments.42. At Terbol, a total precipitation of 343 mm and 810 mm was recorded respectively during 2015/2016 and 2018/2019 cropping seasons. Supplemental irrigation (30 mm) was provided at Terbol station in 2015/2016 season during dry-spell periods, while no irrigation was provided in case of highly and well distributed rains in 2018/2019. A total of 134 genotypes were evaluated at Terbol using Alpha lattice design. In 2015/2016 season, the field experiment was conducted with two replicates and 15 blocks and with the cultivar FLIP86-9842 and in 2018/2019 the field experiment was conducted with 3 replicates and 14 blocks and the following cultivars FLIP86-98, ILB1814, Ed-damer, Hudeiba-93,Shambat-75 and SML.A total of three field experiments were conducted at two ICARDA research stations: Marchouch  in Morocco and Terbol  in the Bekaa Valley of Lebanon. Marchouch station is characterized by the semi-arid environment with a Vertisol soil, mostly silty clay, while Terbol station is characterized by cool and high rainfall winter and moderate wet spring with a deep and rich clay loam soil. Each experiment comprised three treatments applied at the pre-flowering stage : T1-Metribuzin @250 g ai/ha, T2-Imazethapyr @ 75 g ai/ha and T3- No herbicide application. Faba bean genotypes were sown in rotation with cereals in mid-December at Marchouch 2014/2015, late November at Terbol 2014/2015 and 2018/2019 main seasons. Each genotype was planted in 2 m long two-row plot with 0.5 m spacing between rows. At Marchouch, the crop received 291 mm of precipitation during the cropping season in addition to 30 mm irrigation during early vegetative phase; the crop was exposed to intermittent drought and heat. 120 genotypes along with the three following cultivars FLIP86-98,ILB1814 and Hudeiba-93were evaluated at Marchouch using Augmented designThe germplasm genotypes along with six checks  were evaluated in an alpha design with two replicates and two treatments: 250 g ai/ha of metribuzin and untreated treatment during 2017/2018 cropping season. Three seeds per pot for each genotype were sown in this experiment. Irrigation was provided regularly to maintain 100% soil water capacity in pots. Temperature inside the greenhouse was fixed at 24 to 28 °C the optimal day time temperature of faba bean.−1 and 75 g ai ha−1 respectively at the inflorescence stage BBCH code 507272 for the field experiments and at the stem elongation stage BBCH code 3072 for the greenhouse experiment using an electric sprayer with automated flow (375 L/ha). In the field, the herbicide was sprayed early in the morning to ensure a low wind speed. Details of traits scored in each trial can be found in Supplementary Table The herbicide treatments applied in all experiments are metribuzin , imazethapyr  and the control treatment  in which no herbicide was applied. The doses of herbicides applied are the recommended doses as per the labels of metribuzin (Sencor: Bayer) and imazethapyr (Pursuit: BASF). Both herbicides were uniformly sprayed at the rate of 250 g ai ha72. The herbicide damage score (HDS) was recorded in all the four experiments using a 1-5 scale42 (Supplementary Table 42:T́ is the average of plots treated with herbicide (metribuzin or imazethapyr); Ć is the mean of genotypes under untreated conditions.Observations  sequencing on an Illumina HiSeq 2500 produced approximately 4 million reads per genotype. Raw read sequences were processed using TASSEL-GBS 5.0 with the default parameters74. A faba bean sequence database was constructed using 223,801 genomic and transcriptomic faba bean sequences downloaded from NCBI and pulsedb databases  and additional faba bean sequences constructed using the Trinity assembler from one run of the GBS files. These sequences were used as a reference to align GBS sequence tags and indexed using Bowtie2 version 2.2.475 Bowtie2 was used to align GBS tags to faba sequences using the–very-sensitive-local option. Resulting SNPs were filtered with 20x coverage, where SNPs with more than 15% missing data or less than 5% minor allele frequency (MAF) were removed. SNPs were named by contig base pair position.Genomic DNA was extracted from young leaf tissues for each tested genotype using the DNeasy 96 Plant Kit  Qiagen Plant DNA Preparation Kit. For the preparation of the GBS library, the two restriction enzymes, 76. Significance of variation among genotypes and treatments was assessed in terms of P-values. The analysis of variance (ANOVA), means of genotypes, means of treatments and interactions between genotypes and treatments were estimated with standard errors using best linear unbiased prediction (BLUP) values using GenStat software. BLUPs were used to conduct all downstream analyses. Multi environment trials analysis (META) were conducted to evaluate variation among genotypes, treatments and the genotype × treatment interaction across trials for the traits recorded in more than one trial. Genotype and treatment were fitted as fixed parameters while environment (year-location) were fitted as random parameter.The spatial statistical model was applied for variance analysis for all quantitative data using the Automatic Spatial Analysis of Row-Column modules of Genstat 19 edition77 was used to infer population structure with the number of underlying subpopulations (K) ranges between 2 and 20. The analysis was run with 100 random replicates and 20 cross validations. The most probable K was determined at the point when the average cross validation (CV) values across the 100 replicates started to increase. Single-trait (ST) and Multi-trait (MT) GWAS was fitted using GEMMA software21 by fitting each trait independently  or fitting all field or greenhouse records together  with the default parameters and by fitting the genomic relatedness matrix as a covariate to control for population stratification78. Bonferroni correction was used to determine the significant threshold at p < 0.05 but all SNPs with p < 1E−4 were presented as suggestive associations. Pairwise linkage disequilibrium (LD) between associated SNPs within each trait was estimated with the r2 statistics following Weir79 to determine the SNPs that are associated with the same quantitative trait locus (QTL). Genomic sequences containing herbicide tolerance associated SNPs were aligned against the NCBI database using BLASTX tool using default parameters to annotate potential candidate genes underlying the causal variants.ADMIXTURE softwareThe authors confirm that the study complies with local and national regulations. The seeds were collected from the genebank of the International Center for Agricultural Research in the Dry Areas (ICARDA) for research purposes according the International Treaty of Plant Genetic Resources for Food and Agriculture (ITPGRFA). For the collection of seeds, all relevant permits or permissions have been obtained.The seeds flow from ICARDA GenBank at Terbol to Morocco was made following the phytosanitary regulations of both countries and using the Standard Material Transfer Agreement (SMTA) governed by ITPGRFA. The experiments were conducted at ICARDA sites at Terbol and Marchouch in accordance to National and International regulations.Supplementary Information.


CTNNA3, PARD3, and PTPRM), cell adhesion molecules , salivary secretion , and hippo signaling pathway . These findings provide valuable molecular markers for brucellosis resistance breeding in sheep and novel insights into the genetic mechanism of brucellosis resistance.Brucellosis is a zoonotic disease and a major public health problem. However, the genetic mechanism of brucellosis in sheep remains unclear. In this study, serum samples were collected from 6,358 sheep from the F2 population (Dorper sheep ♂ × Hu sheep ♀), and antibody levels were continuously measured at 14 days and 1, 2, 3, 4, 5, 6, 7, 8, 9, and 10 months after administration of brucellosis vaccine. Finally, 19 brucellosis-resistant group (BRG) sheep and 22 brucellosis-susceptible group sheep (BSG) were screened for whole-genome sequencing. Using the fixation index, Fisher’s exact test, and chi-square test, a total of 205 candidate SNP sites were identified. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis suggested that 138 candidate genes were significantly enriched in adherens junction ( Brucella, female animals often present abortion and infertility, whereas male animals show orchitis, which seriously affects their production performance and hinders the development of animal husbandry, causing serious economic losses. Certain developed countries such as Canada, Britain, the Netherlands, Australia, and other countries have eliminated brucellosis. However, brucellosis continues to pose an economic burden in countries such as Saudi Arabia  GC genotype may be a risk factor for the development of focal complications of brucellosis, whereas the GG genotype may be a protective factor against brucellosis  has been widely used in the study of candidate genes between groups, including genes associated with traits such as musical aptitude  under permission no. DK-005.A total of 6,358 F2 sheep (Dorper sheep ♂ × Hu sheep ♀) were selected from a sheep farm in Gansu, China. The experimental sheep were all female adult individuals, and there was no historical selection process. Throughout the research process, all the experimental sheep were provided with the same growth environment, the same feeding management, sufficient pellets, and drinking water to ensure that the breeding environment of all sheep was as uniform as possible. The Brucellosis Vaccine  used in this study was purchased from China Qilu Animal Health Co., Ltd.  . After lThe following procedure was used for the standard SAT procedure for brucellosis in sheep: (1) normal saline containing 0.5% carbolic acid was used to dilute the serum and SAT antigen to be tested. Six test tubes were prepared to dilute each serum sample to be tested; 1.15 ml diluent was added to the first tube, and 0.5 ml diluent was added to the rest of the tubes. (2) Next, 0.1 ml of serum sample was added to the first tube using a 1-ml pipette and mixed well by sucking up the mixture in the test tube into the pipette and then blowing it into the test tube along the wall of the test tube, three to four times. After mixing, 0.25 ml of the mixed solution was sucked up with a pipette and discarded. Then, 0.5 ml of the mixture in the first test tube was added to the second tube using a clean pipette and mixed well using the above mixing. (3) This dilution method was used to complete the dilution in the third, fourth, fifth, and sixth tubes. Finally, 0.25 ml of the mixture in the sixth tube was discarded. After completing the dilution, the dilution degree of the serum of the first to sixth tubes is 1:12.5, 1:25, 1:50, 1:100, 1:200, and 1:400, respectively. (4) Next, 0.5 ml of 20-fold diluted antigen was added to each diluted serum sample and shaken evenly. Thus, the degree of serum dilution was 1:25, 1:50, 1:100, 1:200, 1:400, and 1:800, respectively. Each test tube was incubated at 37°C for 24 h, after which the tubes were checked for self-coagulation. (5) Positive and negative control serum samples and antigen control samples were established for each test. The methods used for dilution and antigen addition for positive and negative control serum samples were the same as described above.With reference to the turbidity of Wheat-than, the clarity of the supernatant and the degree of bacterial aggregation were determined as follows: (1) Complete bacterial agglutination and 100% precipitation with 100% clarity of the supernatant were judged as “++++.” (2) Almost complete bacterial agglutination and 75% clarity of the supernatant were judged as “+++.” (3) Significant bacterial agglutination and 50% clarity of the supernatant were judged as “++.” (4) Presence of agglutination and precipitation and 25% clarity of the supernatant was judged as “+.” (5) Absence of precipitation of agglomerates and uniformly turbid supernatant was recorded as “−.”RBT and SAT methods to group experimental sheep. RBT is a qualitative method to determine Brucella positivity and negativity, while SAT is a more accurate and quantitative method to determine Brucella positivity and negativity. RBT and SAT results were divided into positive and negative. Top19 test sheep with negative BRT and the smallest SAT antibody titer were selected as BRG, and Top22 test sheep with positive BRT and the largest SAT antibody titer were selected as BSG.After antibody detection, jugular vein blood samples (5 ml) from 19 BRG sheep and 22 BSG sheep were collected for DNA extraction. DNA was extracted using an EasyPure Blood Genomic DNA Kit . DNA was then dissolved in elution buffer  and stored at 20°C. After dilution to 100 ng/μl, the 41 genomic DNA samples were used to generate 41 libraries with a mean insertion size of 500 bp. The libraries were sequenced using 150 bp paired-end reads using an Illumina NovaSeq 6000 system .1. The duplicates generated because of excessive amplification during library preparation were labeled by Picard software and were not used as evidence for subsequent mutation detection. The Genome Analysis Toolkit  was used to detect variation information in BAM files and generate variant call format (VCF) files. The software VCFtools (version 0.1.14) was used to filter the detection results of SNPs. The screening criteria of SNPs were as follows: (1) the number of support (coverage depth) of SNPs > 3; (2) missing rate per site < 10%; (3) minimum allele frequency (maf) > 5%; (4) removes indel sites. Finally, a total of 6,643,365 SNPs were identified. SNPs were annotated using the ANNOVAR (K. FastQC (version 0.10.1) software was used to control the read quality of the original sequence. Linker sequences and sequences containing the uncalled base N were deleted, and the sequences shorter than 60 bp were discarded. The clean reads were mapped onto the sheep reference genome Oar v.4.0 with the Burrows–Wheeler Aligner   using thNOVAR K.  based onNOVAR K. .FST), Fisher’s exact test, and chi-square test, were used to detect SNP sites with significant differences in allele frequency between BRG and BSG. The top 1,000 SNPs were defined as the significantly different loci.Three methods, fixation index  of all SNP sites. FST quantifies the allele frequency differences between BRG and BSG, and SNP sites with large FST values may become putative selection sites. The FST values were calculated for each pair of loci following the methods of Weir and Cockerham  was used to calculate the fixation index  were calculated using Haploview4.2. The first 1,000 SNPs were defined as significant SNPs, which will be used for subsequent analysis of candidate genes.Association analysis was performed for BRG group versus BSG group with the PLINK (version 1.9) software, using the Fisher’s exact test and chi-square test . PearsonFinally, to further identify the credible SNPs, the top 1,000 SNPs detected by the above three methods were intersected to identify the overlapping SNPs.The identified SNPs were annotated as the closest genes with a nearest gene distance of 1 kb (Oar_v4.0). The genes were defined as candidate genes. KOBAS software was used to test the statistical enrichment of candidate genes in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis .p < 0.01). The results of the agglutination brucellosis Rose Bengal plate agglutination test are shown in n = 19 and BSG, n = 22). The system produced a total of 977.167 Gb of raw data. After inspecting the raw data for quality, we filtered out low-quality sequences and sequences containing joints, resulting in 948.21 Gb of clean data. The effective sequencing rate (clean_data/raw_data) was 97.04%  were identified: adherens junction, cell adhesion molecules (CAMs), salivary secretion, and Hippo signaling pathway , Fisher’s exact test, and chi-square test] were used to identify Brucella susceptibility genes in the sheep genome. The experimental sheep were grouped on the basis of the serum levels of Brucella antibodies of different individuals. Sheep with low serum antibody persistence were classified as brucellosis susceptible, and those with high serum antibody persistence were classified as brucellosis resistant. Then, SNP loci showing differences in allele frequency between BRG and BSG were identified as candidate loci closely associated with Brucella resistance  in this study, which may be due to the small sample size. Therefore, in the follow-up study, the sample size should be expanded and the FDR or Bonferroni methods should be used for screen candidate genes and SNP sites.Unfortunately, no SNP loci reached significant levels after In conclusion, four significant pathways and nine candidate genes related to brucellosis susceptibility in sheep were identified by whole-genome resequencing using brucellosis-susceptible and brucellosis-resistant sheep. These pathways and genes are closely related to the process of cell adhesion. These results provide valuable candidate genes and lay an important foundation for the study of brucellosis in sheep.https://www.ncbi.nlm.nih.gov/, SRR11971264–SRR11971304.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: The animal study was reviewed and approved by Ethics Committee of Gansu Agriculture University (China). Written informed consent was obtained from the owners for the participation of their animals in this study.FL and WW designed the experiments. XL and WW analyzed the data. XL wrote the manuscript. CL, DZ, GL, XZ, YKZ, YZ, and ZS contributed to sample collection and prepared biological samples. WW, QW, and XL revised the manuscript. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


In the vicinity of these SNPs, four genes such as pre-B-cell leukaemia homeobox 1 (PBX1), GPATCH1, MPHOSPH6, and MRM1 were identified. Four other significant SNPs  all located on chromosome 1 were strongly (p ≤ 7.6E−5) associated with chicken antibody response to ND. The closest genes to these four SNPs were cell division cycle 16 (CDC16), zinc finger, BED-type containing 1 (ZBED1), myxovirus (influenza virus) resistance 1 (MX1), and growth factor receptor bound protein 2 (GRB2) related adaptor protein 2 (GRAP2). Besides, other SNPs and genes suggestively (p ≤ 1.5E−5) associated with BW and antibody response to ND were reported. This work offers a useful entry point for the discovery of causative genes accountable for essential QTLs regulating BW and antibody response to ND traits. Results provide auspicious genes and SNP-based markers that can be used in the improvement of growth performance and ND resistance in IC populations based on gene-based and/or marker-assisted breeding selection.A chicken genome has several regions with quantitative trait loci (QTLs). However, replication and confirmation of QTL effects are required particularly in African chicken populations. This study identified single nucleotide polymorphisms (SNPs) and putative genes responsible for body weight (BW) and antibody response (AbR) to Newcastle disease (ND) in Rwanda indigenous chicken (IC) using genome-wide association studies (GWAS). Multiple testing was corrected using chromosomal false detection rates of 5 and 10% for significant and suggestive thresholds, respectively. BioMart data mining and variant effect predictor tools were used to annotate SNPs and candidate genes, respectively. A total of four significant SNPs  significantly ( The genome-wide identification of genes linked to complex traits started in the 1990s . The mosThe use of GWAS in chickens has been to ascertain major loci related to economic traits . Most ecChicken has been threatened by various diseases  includinDespite the existing QTL reports for BW and antibody response to ND in chicken, replication and confirmation of these QTL effects in IC in Rwanda have not been done. Growth performance and antibody response to ND of IC in Rwanda have been evaluated . This stAll chicken manipulations were carried out as per the revised Animals Act 1986 with the approval of the ethical clearance committee of the College of Agriculture, Animal Sciences and Veterinary Medicine, University of Rwanda . The birds were humanely handled, and during the research, none of them was sacrificed.Indigenous chicken (IC) used in this study were kept under the same conditions on- station at the University of Rwanda in the Eastern region, Nyagatare district as explained in The live body weights (BWs) of 185 ICs were weighed at the 20th week, and immune response to ND [mainly immunoglobulin Y (IgY)] titres recorded after 7 days from the second immunization  as outliBlood samples from 185 ICs were collected using an EDTA tube. Promega genomic DNA extraction kit was used to extract genomic DNA from blood. The concentration and quality of Genomic DNA were assessed using NanoDrop™ 2000 spectrophotometer (Thermo Scientific™ Nanodrop 2000) and gel electrophoresis (1% agarose) ensuring they met genotyping requirements. Genotyping-by-sequencing (GBS) approach  was used to obtain the raw reads .Raw reads were trimmed through sickle  and aligp < 10−6), call rate >95%, heterozygosity >0.4, and minor allele frequency >0.05. Genotype imputation was performed  based on the centred identical-by-state (IBS) approach was used to test the population structure. Pairwise IBS distances were computed using independent SNPs. MDS components were got using the MDS-plot option based on the IBS matrix. Due to the internal population structure, the first MDS component was included as a covariate in the statistical model for assessing SNP effects on growth and antibody response attributes to account for sample stratification. Tassel 5.2.60 was used to construct a relative kinship matrix (K) using 65,945 independent SNP markers .The analysis for GWAS was performed using Tassel 5.2.60 . SNPs siy is the vector of quantitative traits (20-week bodyweight and antibody response to Newcastle disease); β, vectors containing fixed effect  and covariates (population structure); u, a vector of random effect of the relative kinship matrix constructed by matrix simple matching coefficients based on the independent SNPs; e, a vector of random residuals; and X and Z are design matrices.where p of the 5% Bonferroni genome-wide significance was computed. Therefore, the threshold value of p of the 5% Bonferroni genome-wide significance was 7.6E−5 . Similarly, the threshold value of p for the significance of suggestive linkage allowing one false-positive effect in a genome-wide test (x-axis) and observed (y-axis) values of p from each, the, respectively, associated trait was shown by the Quantile-quantile (QQ) plots  plots . A comprsoftware .BioMart data-mining  and varip is higher, it reflects more enriched clusters. When an ES is more than unity, the functional category is overrepresented.Database for Annotation, Visualization, and Integrated Discovery DAVID;  was usedGenome-wide association study using genotyping by sequencing identified SNPs and putative genes linked to growth performance and immune response to Newcastle disease virus in indigenous chicken in Rwanda.Multidimensional scaling analysis of 65,945 SNPs with the first two components revealed an internal population structure as explained by the variance among individuals’ population stratification .p ≤ 7.6E−5) associated with 20-week BW were detected on chromosomes 8, 11, and 19. Furthermore, rs318161016, a suggestive SNP (p ≤ 1.5E−5) associated also with BW was detected on chromosome 4 , G-patch domain containing 1 (GPATCH1), M-phase phosphoprotein 6 (MPHOSPH6), and mitochondrial rRNA methyltransferase 1 (MRM1) were the closest to the significant SNPs (Fibroblast growth factor 2 (FGF2) was reported in the vicinity of a suggestive SNP  was strongly (p ≤ 7.6E−5) associated with the IC antibody response to ND after 7 days from the second immunization. Additionally, 10 suggestive SNPs (p ≤ 1.5E−5) detected on chromosomes 2, 4, 8, 13, 17, 19, and 26 influenced also antibody response to ND in IC in Rwanda , zinc finger, BED-type containing 1 (ZBED1), myxovirus (influenza virus) resistance 1 (MX1), and growth factor receptor bound protein 2 (GRB2) related adaptor protein 2 (GRAP2) were the closest to the significant SNPs (ubiquitin-associated domain containing 1 (UBAC1), tubulin epsilon and delta complex 1 (TEDC1), Ras association domain family member 5 (RASSF5), intraflagellar transport 22 (IFT22), jumonji and AT-rich interaction domain containing 2 (JARDI2), gamma-aminobutyric acid A receptor, beta 2 (GABRB2), zinc finger homeobox 4 (ZFHX4), adenylate cyclase-activating polypeptide 1 (ADCYAP1), pterin-4 alpha-carbinolamine dehydratase 2 (PCBD2), and albumin (ALB) were mapped in the neighborhood of the identified suggestive SNPs  gene complexes and rise their DNA-binding affinity and specificity. PBX1 gene and homeodomain proteins were required for Hox proteins to control downstream target genes that in turn regulate growth, differentiation, and morphogenesis during development. The expression pattern of this gene suggests its importance in early nervous system development. This gene was initially identified for its role in the translocation of the chromosome which happens in pre-B acute lymphoblastic leukaemia  family  and 2 (FGFBP2) in modulating chicken growth  family . The samn growth . Anothern growth . GPATCH1unctions . This geunctions . Moreoveunctions . The rol miRNome . Besidesck tiger . Howeverhylation , but itsPBX1, GPATCH1, MPHOSPH6, and MRM1 be novel targets for 20-week BW. For additional validation of the importance of these genes, studies including their silencing and overexpression need to be conducted both in-vivo and in-vitro. Since growth performance is the utmost crucial trait of selection, getting profound insights into the growth molecular mechanism would result in a more efficient selection for growth performance in chickens.In the present study, some QTLs for 20-week BW are overlapping those already found in previous studies and others have never been reported. This study, therefore, postulates that these genomic regions may play a key role in the fundamental molecular mechanisms that are responsible for BW. These genomic regions are hence separate in many various chicken populations, confirming the difference in BW revealed in IC gene pools in Rwanda . Besidesp ≤ 7.6E−5) associated with antibody (Ab) response to ND were detected on chromosome 1 . This study confirmed the findings by Host antibody response to viruses is a composite process . Immune Conversely, results from this study differed from those previously reported . Yonash The current study used IC resource populations, while other previous studies were based on broiler and layer populations . The prep ≤ 1.5E−5) were detected on chromosomes 2, 4, 8, 13, 17, 19, and 26. However, apart from chromosomes 2, 4, and 13 which were reported earlier  have been revealed with the development of several molecular technologies and assays in chickens  are still under a validation process  associated with Ab response to ND in IC populations in Rwanda. The gene ontology annotation advises that all these genes contribute to the regulation of transcription, binding, transport, cytokine activity, and immune responses. Among these genes, four were near the significant SNPs . These genes might be used as putative genes to be further explored to determine associations with Ab response to ND in IC populations in Rwanda.This study revealed, however, 14 putative genes  and infectious bursal disease virus  were found to be associated with suggestively correlated SNPs for Ab response to ND in this study. All these candidate genes for Ab response to ND have not been heretofore directly associated with immune response in poultry (Ten genes ( poultry . Some of poultry . Further poultry  could be poultry  for chicGenomic regions that putatively control body weight and antibody response to Newcastle disease in an indigenous chicken were identified in the current study. This information provides insights on the genetic control of these traits and makes available genetic markers that could be useful for selective breeding programs to improve growth performance and ND resistance in IC. Few of the genomic regions overlapped with hitherto reported QTL regions provide evidence for confirmation of these QTLs and their corresponding effects. In addition, the variants and genes uncovered for the first time in this study, merit further scrutiny to understand the fundamental molecular mechanisms before practical application.The original contributions presented in the study are included in the article/The animal study was reviewed and approved by The Research Screening and Ethical Clearance Committee of the College of Agriculture, Animal Sciences, and Veterinary Medicine, University of Rwanda. Written informed consent was obtained from the owners for the participation of their animals in this study.RH and KN: conception of the work and data analysis. CH: contributed to the data acquisition. RH, KN, and NY: results interpretation. RH: drafting the article. KN, CK, NY, and TO: critical revision of the article and final approval of the version to be published. All authors contributed to the article and approved the submitted version.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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


More than 100 grapevine varieties are registered as suitable for wine production in “Douro” and “Trás-os-Montes” Protected Designations of Origin regions; however, only a few are actually used for winemaking. The identification of varieties cultivated in past times can be an important step to take advantage of all the potential of these regions grape biodiversity. The conservation of the vanishing genetic resources boosts greater product diversification, and it can be considered strategic in the valorisation of these wine regions. Hence, one goal of the present study was to prospect and characterise, through molecular markers, 310 plants of 11 old vineyards that constitute a broad representation of the grape genetic patrimony of “Douro” and “Trás-os-Montes” wine regions; 280 samples, grouped into 52 distinct known varieties, were identified through comparison of their genetic profiles generated via 6 nuclear SSR and 43 informative SNP loci amplification; the remaining 30 samples, accounting for 13 different genotypes, did not match with any profile in the consulted databases and were considered as new genotypes. This study also aimed at evaluating the population structure among the 65 non-redundant genotypes identified, which were grouped into two ancestral genetic groups. The mean probability of identity values of 0.072 and 0.510  were determined. Minor differences were observed between frequencies of chlorotypes A and D within the non-redundant genotypes studied. Twenty-seven pedigrees were confirmed and nine new trios were established. Ancestors of eight genotypes remain unknown. V. vinifera samples is the first prerequisite for the correct management of germplasm collections, selection of suitable parents for breeding programs, and clarification of synonyms, homonyms, and naming inaccuracies among grape varieties [The wine denominations “Douro”, the oldest demarcated and regulated winemaking region in the world, and “Trás-os-Montes”, represent approximately 29% of the Portuguese vineyard area for wine production  . These Parieties ,4,5,6.Identification of grape varieties has been generally based on the phenotypic traits of vegetative and reproductive structures, but morphological features are not sufficiently reliable for the classification of closely related varieties due to genotype–environment interactions . MoreoveV. vinifera [V. vinifera spp. sativa (cultivated grapevine), by analysing their distribution in local V. vinifera spp. sylvestris and sativa [SSR markers, because of their high degree of polymorphism, reproducibility, and co-dominant nature, have become the markers of choice for exchange of information concerning grapevine genetic resources . Severalvinifera . Chlorotd sativa , and to At the present time, SNP markers are considered one of the most powerful tools recently developed ,13,20. AThe sequence of the grapevine reference genome is available ,24 and cV. vinifera populations, to infer genetic structure, and to identify kinship relationships [V. vinifera subsp. vinifera and sylvestris) germplasm were also been undertaken, using the ICVV sets of 48 [Vitis International Variety Catalogue  includes SNP data of 112 markers for many varieties [These SNP markers are used to investigate genetic variability, discriminating among wild and cultivated ionships ,36,37,38ts of 48 . Currentarieties .VIVC database and the ICVV-SNP database, respectively; (ii) evaluation of genetic diversity and relationships among the grape genotypes detected, through SSR and SNP (240 SNP) markers; (iii) determination of chlorotypes and their frequencies through cpSSR and SNP loci amplification; and (iv) determination of first-order kinship relationships among grape varieties using the 240-SNP set.As a result of changes in worldwide wine consumption and European Union incentives , radicalA total of 310 grapevines were sampled in traditional vineyards throughout “Douro” and “Trás-os-Montes” PDO regions . These vSamples were characterised using molecular markers, namely Simple Sequence Repeats (SSR) and Single Nucleotide Polymorphisms (SNP), starting by varietal identification and followed by population structure, genetic diversity, and pedigree analyses with non-redundant genotypes.All samples were initially analysed with six nuclear microsatellites  and thrAn SNP array was first proposed as an alternative to SSR for varietal identification by Cabezas et al. . These aNon-redundant genotypes for the 48-SNP set were then genotyped with 192 additional SNP loci for subsequent analyses of population structure, genetic diversity, and parentage relationships. However, only 226 out of 240 SNP markers were informative; 14 SNPs were discarded, because data produced by 11 SNP were missing in at least 61% of the samples, and three SNP were monomorphic in the genotypes analysed.VIVC and ICVV-SNP databases, respectively. The VIVC database includes 5424 genetic profiles [VIVC data, the varieties ‘Hebén’, ‘Mouratón’, ‘Montua’, ‘Tempranillo’, ‘Palomino‘, ’Parraleta’, ‘Grec Rouge’, and ‘Trousseau Noir’ are synonyms of the Portuguese varieties ‘Mourisco Branco’, ‘Tinta Gorda’, ‘Diagalves’, ‘Aragonez’, ‘Malvasia Rei’, ’Tinta Caiada’, ‘Rabigato Francês’, and ‘Bastardo’, respectively , ‘Mouratón’ and ‘Síria’ (17), ‘Roseira’ (16), ‘Marufo’ (13), ‘Tempranillo’ (13), ‘Camarate Tinto’, ‘Carrega Branco’, and ‘Malvasia Preta’ (11), and ‘Trousseau Noir’ (10). These most commonly found genotypes across the sampled old vineyards may reflect their relevance in the past century.Sixteen identified genotypes  and eight non-identified genotypes  were found only once in the study . The selection of plants was based on the difficulty of their morphological identification by ampelographers, where only 31 out of 310 samples were previously named but mainly with local names . MicrosaMoreover, ‘Mourisco’ and ‘Bastardinho’ samples share the same nSSR and SNP profiles, but were revealed to be the ‘Mouratón’ (syn. ‘Tinta Gorda’) genotype described by Cunha et al. . ‘MourisVIVC and ICVV-SNP databases. This fact led to the conclusion that the two first samples were incorrectly named, but further analysis of the other two samples is needed to clarify if they are a situation of naming inaccuracy. Nevertheless, all four samples were considered as new genotypes , one to a table variety (1.9%), 14 to varieties with a double wine/table use (26.9%), and one to a variety with double table/raisin use 1.9%; .There are 343 authorised varieties for wine production in Portugal . All varAnother fact to take into account was that seven red varieties  and five white  listed as suitable for production of PDO wines are described as late-maturing ones ,52. HencV. vinifera germplasm diversity studies assessed with SSR markers. An analysis of 51 varieties using the six OIV loci described a range of 7 (VVMD27) to 11 (VVS2) alleles, with an average of 8.2 [SNP and SSR profiles were compared to assess the genetic diversity of the 65 non-redundant genotypes and these results are summarised in e of 8.2 . The nuce of 8.2  showed ae of 8.2 , also usThe allele size varied between 132 (VVS2) and 263 bp (VVMD7). VVMD7-239 and ssrVrZAG62-191 alleles were the most frequent, with over 43% of frequency. On the other hand, 25 alleles (43.86%) showed a frequency lower than 5%, eight of them being unique alleles . SpecifiV. vinifera spp. sativa germplasm studied by Emanuelli et al. [Allele frequencies and genetic parameters were also determined for the 226 SNP set . The mini et al.  (MAF = 0Ne) differed from 3.928 (VVMD7) to 6.995 (VVMD5), and an average number of 4.962 effective alleles was obtained for nSSR markers, similar to the mean Ne value (4.658) attained by Castro et al. [Ne ranged from 1.016 (SNP625_278) to 1.999 (SNP1327_56), with an average of 1.604, which is consistent with other reports on the genetic diversity of cultivated grape varieties .Ho) varied between 0.785 (VVMD7 and VrZAG62) and 0.954 (VVMD5); the lowest expected heterozygosity (He) was detected at VVMD7 locus with 0.745 and the highest one at VVS2 locus with 0.820 (Ho = 0.859 and He = 0.790) was similar to that observed for other sets of grape varieties analysed with SSR markers (Ho = 0.833 and He = 0.767 in [Ho = 0.833 and He = 0.769 in [p < 0.05) from HWE at the six SSR loci analysed. Differences between SNPs and SSRs were also observed with respect to heterozygosity. The observed heterozygosity  and expected (He = 0.351) heterozygosity values than SSRs (p < 0.05) between Ho and He values was found. However, deviation from the HWE (p < 0.05) was observed for 13.27% of the SNP markers; for 23 SNPs (10.18%), Ho was significantly higher than He, whereas Ho was significantly lower than He in the remaining seven SNPs (3.09%).As expected, SSR loci, due to the SSR multiallelic nature and high level of polymorphism, exhibited a significantly higher heterozygosity than biallelic SNP loci. This trend was observed by Emanuelli et al. . On averhan SSRs . For 196PIC values for each of the six nSSR and 226 SNP loci. VVMD7 and VVMD5 markers displayed the minimum (0.736) and maximum (0.844) PIC values, respectively  and 0.492 . PIC vaNP locus  or by co−7) was considerably higher than that determined for the 226 SNP set  used for the varietal identification would give a similar identification power as 14 microsatellites. The global probability of identity (PI) obtained for the six SSR set (1.0 × 10chl) of the 65 non-redundant genotypes was determined using ccmp3, ccmp5, and ccmp10 loci, which were considered the three most polymorphic chloroplastidial microsatellite (cpSSR) loci in grapevine [The chlorotype , but a high percentage of chl D was also detected  could be a consequence of crosses between non-Iberian introduced varieties and Portuguese native germplasm. Chlorotypes of ‘Carrega Branco’, ‘Nevoeira’, ‘Roseira’, and the 13 new genotypes identified were determined for the first time in this work, as no previous references were found in the literature or databases used. Most of these genotypes bear chl D, except ‘Nevoeira’ and ‘NG013’  [The genetic stratification in the set of 65 non-redundant grape genotypes was tested through a STRUCTURE analysis, using 226 SNP profiles. The delta ion (ΔK)  suggesteq-value) threshold of 0.7 for genetic group assignment was considered. Twenty (30.77%) and 18 (27.69%) genotypes were assigned to SNP-group 1 and SNP-group 2, respectively. The percentage of admixed genotypes was 41.54%  was performed to infer the distribution of genetic relationships among structure groups as revealed by 226 SNP loci A. The fiAn Unweighted Pair Group Method with Arithmetic Mean (UPGMA) distance tree was constructed to investigate the genetic relationship among the 65 non-redundant genotypes from genetic distance matrices  and duos (parent—offspring pairs) involving genotypes analysed and the corresponding LOD values and the number of mismatching loci are presented in Pedigree results revealed 36 compatible trios, with high LOD values, ranging from 52.20 to 101.40, using a maximum of two mismatching loci as threshold, with the confirmation of 27 already reported trios see .Several grape varieties have been previously reported to have an important role in the establishment of local genetic networks, such as ‘Hebén’, ‘Alfrocheiro’, and ‘Marufo’ in the Iberian Peninsula ,59,60. Ichl D) and ‘Hebén’ (chl A) need to cross-pollinate to produce descendants, a process that increases genetic diversity and increases hybrid plant vigour, which could have favoured their selection as seed donors by early farmers to ensure grape production [Unlike hermaphrodite grape varieties, female progenitors, such as ‘Marufo’ (oduction .chl A), a variety classified by Lacerda Lobo [chl D as the female progenitor ‘Marufo’ and obtained from hybridisation events between the referred variety and seven different Portuguese (six) and French (one) varieties (chl A), an old variety from Douro wine region. ‘NG006’, ‘NG007’, ‘NG008’, and ‘NG003’ resulted from the cross between ‘Marufo’ and, respectively, ‘Tinto Cão’, ‘Camarate Tinto’, ‘Folha de Figueira’, and ‘Trousseau Noir’ . Moreover, two new pedigrees were proposed as a result of crosses between ‘Marufo’ and ‘Trincadeira’ (‘NG009’ and ‘NG011’ as progenies). The participation of ‘Marufo’ and ‘Vinhão’ (chl A) as genitors of ‘Tinta Mesquita’ and ‘NG012’ was also observed  was found to be a parent in eight trios previously described, two of them together with ‘Hebén’ (chl A), and six with ‘Cayetana Blanca’  [‘Alfrocheiro’ (h chl A) ,59,60.q-value > 0.7 for group assignment) could be explained by parentage analysis. For example, both ‘Touriga Fêmea’ and ‘NG007’ were determined as admixture genotypes; ‘Touriga Fêmea’ is a progeny derived from ‘Malvasia Fina’ and ‘Touriga Nacional’ , whereas ‘NG007’ is a reliable result of a cross between ‘Marufo’ and ‘Camarate Tinto’  were considered. Five reliable duos were detected and summarised in However, no reliable trios or duos within the ICVV-SNP database were found for other genotypes, mainly the Iberian ones: ‘Tamarez’, ‘Tinta Francisca’, ‘NG005’, and ‘NG013’. Since the ICVV-SNP database includes a high number of Iberian profiles and even so no parentage relationships were established, most likely progenitors of the referred genotypes are extinct or close to. Their extinction, as proposed by Cunha et al. , may be V. vinifera in “Douro” and “Trás-os-Montes” PDO regions, 310 plants were sampled across 11 different old mixed variety vineyards, all predating the 1970s  agarose gel electrophoresis containing Gel-GreenTM Nucleic Acid Gel Stain 0.5x  and stored at −20 °C until use. The final concentration was confirmed using a NanoDrop® ND-1000 UV-Vis spectrophotometer .Genomic DNA was extracted according to Doyle & Doyle , with soVitis characterisation—VVS2, VVMD5, VVMD7, VVMD27, ssrVrZAG62, and ssrVrZAG79. The forward primer of each pair was fluorescently labelled with 6-FAM (VVMD5 and VVMD27), VIC (VVMD7 and ssrVrZAG62), or NED (VVS2 and ssrVrZAG79). Two multiplex PCRs (A and B) were carried out as previously described by Castro et al. [Samples were analysed with the set of six nuclear microsatellite (nSSR) loci recommended by OIV  for Vitio et al. , with 0.The chlorotype was determined using the three chloroplastidial microsatellite (cpSSR) loci designed by Weising & Gardner : ccmp3, w/v) containing Gel-GreenTM Nucleic Acid Gel Stain 0.5x (Biotium). Fluorescently labelled cp and nSSR products were separated by capillary electrophoresis using the ABI PRISM® 3130 automated sequencer  and GeneScanTM 500 LIZ®  as the internal lane size standard. Data produced were analysed by Peak Scanner v1.0 software . The sizes of the amplicons were scored in base pairs (bp) based on the relative migration of the internal size standard.All PCR products were visualised by electrophoresis on 2.0% agarose gels , and samples that produced nSSR profiles that did not match with those of the VIVC database were also genotyped for a set of 240 SNP markers previously identified by Lijavetzky et al. [DNA samples from non-redundant genetic profiles  of alleles. For SNP data, numerical values were assigned to each nucleotide .Non-redundant grapevine genotypes with genetic profiles for 6 nSSR and 48 SNP loci were used for grape variety identification. Genetic profiles for 240 SNP loci were used for population structure and genetic diversity analyses.Na), the average number of effective alleles (Ne), observed heterozygosity (Ho) and gene diversity or expected heterozygosity (He) were calculated through the GenAlEx software (version 6.5) [To compare SSR and SNP results, genetic parameters of polymorphism, such as the average number of different alleles per locus (ion 6.5) . They wePIC was calculated as follows: PIC = He − (2 × MAF2 × (1-MAF)2), where MAF was the minor allele frequency.Polymorphism information content (PIC)  of each q-value). Structure analyses were performed using the STRUCTURE software (version 2.3.4) ,73,74,75To assess the relationship among the non-redundant genotypes, the pairwise genetic distance matrix was computed based on SNP data, through the ‘Genetic Distance’ procedure in the GenAlEx software (version 6.5) , for subData from the 240 SNP set were also used to identify possible first-order kinship relationships—trios (mother–father–offspring) and duos (possible parent–offspring pairs)—among the non-redundant grape genotypes in the study, since their SNP profiles merged with those of the ICVV-SNP database. The likelihood-based method in the CERVUS software was used (version 3.0) . The likSSR and SNP analyses were very useful in the identification and characterisation of the plants analysed and overcame the ampelography difficulties in grapevine prospections to contribute to the ultimate goal of conserving grape varietal legacy in Northeast Portugal. Further morphological, agronomical, and oenological analyses are being undertaken to complement the molecular data reported in this study.In the present work, 280 plants in the “Douro” and “Trás-os-Montes” PDO regions were identified and grouped into 52 different grape varieties. Thirteen additional unique genotypes were also detected from the study of other 30 vines, which were clustered, along with cv. Marufo (mother of the majority of these new genotypes), in an exclusive independent cluster, accordingly to UPGMA data. Some of these 13 new genotypes could be considered minor neglected Portuguese grape varieties, while others, found only in plants belonging to a single local vine grower still using traditional techniques for grapevine propagation, are probably individual grapevines that emerged as seedlings and can be the initial steps of the establishing of local grape varieties as it occurred in the past. Altogether, their discovery highlights once more the huge patrimony of the Portuguese grape germplasm. The aforementioned observations emphasise the constant demand for prospection and identification of old grape material in traditional vineyards, to enlarge the knowledge about the still existing varietal diversity for its conservation, characterisation, and eventual exploitation. The broader the knowledge, the greater the chances to overcome biotic and abiotic stresses affecting the vineyards today.