Solanum lycopersicum L.) accessions enriched in ‘da serbo’  long shelf life (LSL) materials (152 accessions) mostly originating from Italy and Spain. The rest of the materials originate from different countries and include landraces for fresh consumption, elite cultivars, heirlooms, and breeding lines. Apart from their LSL trait, ‘da serbo’ landraces are of remarkable interest for their resilience. We identified 32,799 high-quality SNPs, which were used for model ancestry population structure and non-parametric hierarchical clustering. Six genetic subgroups were revealed, clearly separating most ‘da serbo’ landraces, but also the Spanish germplasm, suggesting a subdivision of the population based on type and geographical provenance. Linkage disequilibrium (LD) in the collection decayed very rapidly within <5 kb. We then investigated SNPs showing contrasted minor frequency allele (MAF) in ‘da serbo’ materials, resulting in the identification of high frequencies in this germplasm of several mutations in genes related to stress tolerance and fruit maturation such as CTR1 and JAR1. Finally, a mini-core collection of 58 accessions encompassing most of the diversity was selected for further exploitation of key traits. Our findings suggest the presence of a genetic footprint of the ‘da serbo’ germplasm selected in the Mediterranean basin. Moreover, we provide novel insights on LSL ‘da serbo’ germplasm as a promising source of alleles for tolerance to stresses.Double digest restriction-site associated sequencing (ddRAD-seq) is a flexible and cost-effective strategy for providing in-depth insights into the genetic architecture of germplasm collections. Using this methodology, we investigated the genomic diversity of a panel of 288 diverse tomato ( Solanum lycopersicum L.) is the most economically important vegetable crop, being widely grown and appreciated for its organoleptic and nutritional properties. Its cultivation is spread on a global surface of 4.76 million hectares with a production of 182 million tons1. The domestication of tomato had its origins in the Andean region of South America, fitting a model in which a pre-domestication phase took place in the Andean region, with the domestication being completed in Mesoamerica3 and not so long before the discovery of America4. This process led to a series of morphological and physiological changes, the most important of which has been the increase of the size and weight of fruits and the variation of shape3. During the XVI century, tomato was introduced in Europe and mostly in Spain and Italy, where further domestication occurred, resulting in the development of a high diversity of local varieties. For this reason, the Mediterranean basin of Europe is recognized as a secondary center of diversification for tomato6.Tomato . At the same time, identity, ethical and cultural aspects attract the interest of customers who show greater appreciation for typical products and traditional cuisine. For this reason, in recent years there has been an increasing interest in local landraces, which, although not as productive as commercial cultivars and often vulnerable to major pests8, have a closer tie with the territory and local customs and are better adapted to the small-scale economies.The last century has been characterized by a boost of breeding activities aimed at introducing and selecting novel variation toward the development of various types of cultivars for different uses and destinations . The first tomato cultivars developed by growers through selection and propagation are known as heirloom varieties. Heirlooms are characterized by unique features related to their appearance , flavor, and significance for specific local markets10 and is associated with high resilience, manifested in the tolerance to different abiotic and biotic stresses, as well as to a high soluble solids content providing excellent organoleptic properties11. This syndrome of phenotypic characteristics of the LSL ‘da serbo’ landraces results in a clear differentiation from the standard fresh consumption tomatoes. The particular characteristics of the LSL ‘da serbo’ materials may be also used as a selective trait12, in fact, they have been selected in semiarid summer conditions with poor irrigation or rain-fed10. The greater attention to organic farming and sustainability in agriculture has sparked an increasing interest in the ‘da serbo’ LSL cultivars. The potential of these LSL materials and their diversity have not been extensively characterized and are not yet fully exploited in tomato breeding programs. Indeed, apart from the long shelf life and resilience characteristics, ‘da serbo’ LSL germplasm may represent a potential source of other traits of agricultural interest.Among these, ‘da serbo’  tomato materials are typical long shelf life (LSL) tomatoes landraces that diversified in the Mediterranean region and which have been traditionally cultivated in Southern Italy and Spain. These LSL tomatoes are generally small, mostly round, although a wide range of shapes can be found, with thick cuticle, and different colors, from yellow to red with several shades. The extended shelf-life might have been the primary selection criteria17 to few thousand of markers 20. These studies revealed patterns of genetic diversity due to breeding activities, adaptation to the cultivation environment, market type and destination of use. Whole-genome sequencing and re-sequencing projects accelerated the development of high-throughput genotyping methods21. Double digest restriction-site associated DNA (ddRAD-seq) is a method based on the development of multiplexed libraries obtained through the enzymatic digestion of the whole genomic DNA followed by binding to specific adapters (reduced representation libraries). By reducing the portion of the sequenced genome, it generates a large set of SNP markers which can be used to infer very precisely the genetic diversity and population structure of large germplasm collections22. Moreover, the adoption of double restriction enables paired-end sequencing of identical loci across many samples ensuring higher accuracy in the mapping of reads with respect to genotyping by sequencing (GBS) or single RAD digestion (RAD-seq)23. The application of ddRAD-seq technology has been successful in many species including Solanaceae crops25; while, so far, its application to tomato for the investigation of germplasm collections has been limited. Indeed, to date, studies are addressed principally to ddRAD-seq in silico optimization protocols23.The diversity of local landraces and heirlooms of tomato has been investigated using PCR based fragment analysis or custom DNA arrays (Golden-Gate) involving from a few hundred markers26. The first version, obtained by a combination of short-read 454 and a Sanger paired-end read sequencing, consisted of approximately 900 Mb and 34,727 protein-coding gene models. Versions SL2.50 and SL3.0 have been widely used as a reference for SNP calling in various tomato population studies. Very recently, a high quality de novo assembly of the tomato reference genome (SL4.0), obtained through a combination of long-read sequencing methodologies and optical mapping, has been released27. The new version reduced the number of the unknown bases and unplaced contigs by around 2,000 and 30-fold, respectively. Moreover, 4,794 novel genes have been reported compared to the previous version. The new genes information has been implemented by the sequencing of 13 diverse tomato accessions . These novel resources allow a better exploitation of the genomic information on germplasm resources.A reference genome sequence of tomato has been available since 2012In the present study, we analyzed the genome-wide diversity of a collection of 288 tomato accessions using ddRAD-seq genotyping aiming to provide biological knowledge for biodiversity-based breeding. The represented tomato accessions included a wide range of landraces for fresh consumption and LSL ‘da serbo’ retrieved from the Mediterranean basin, as well as representative heirlooms and elite cultivars grown across the world. Population structure and diversity within subpopulations have been inferred by combining Bayesian and non-parametric approaches. Then we investigated in depth the genomic diversity of ‘da serbo’ materials, identifying those alleles subjected to selective sweeps and putatively responsible for the syndrome of phenotypic characteristics of LSL types. The collection studied, as well as a mini-core collection selected for genomic diversity, represents diversified panels to be exploited for future association mapping studies toward the determination of genomic regions responsible of traits underlying resilience and amenable to breeding.S. lycopersicum) accessions were assembled from the germplasm collections from the Universitat Politècnica de València , the Research Center for Vegetable and Ornamental Crops , and the Tomato Genetics Resource Center . The germplasm panel included materials originating from 27 different countries of Europe, Asia, Africa and America  and ligated to barcoded adapters. Samples were pooled on multiplexing batches and bead purified. For each pool, targeted fragments distribution was collected on a BluePippin instrument (Sage Science Inc.). The gel eluted fraction was amplified with oligo primers that introduced TruSeq indexes and subsequently bead purified. The resulting libraries were checked with both Qubit 2.0 Fluorometer  and Bioanalyzer DNA assay . Libraries were finally processed with Illumina cBot for cluster generation on the flowcell, following the manufacturer’s instructions and sequenced with V4 chemistry paired end 125 bp mode on HiSeq2500 instrument .In silico analysis on the tomato reference genome was used to select the best combination of two restriction enzymes and the best fragment size distribution to obtain the desired number of loci. Such analysis suggested that the 29. The quality distribution plot was generated using FASTQ and filtered data were then aligned to reference tomato genome (versions SL3.0 and SL.4.0) using BWA-MEM with default parameters30. Only uniquely aligned reads  were selected for downstream analysis. Genomic sequences related to S. lycopersicum (versions SL3.0 and SL4.0) were obtained from Sol Genomics (https://solgenomics.net). Detection of all covered loci from the aligned reads was done using the gstacks program included in Stacks v2.029, while filtering of detected loci was carried out using the included populations program with the option –r = 0.75, in order to retain only loci that are represented in at least 75% of the population. In addition, polymorphic homozygous markers were identified among the accessions using inhouse PERL scripts. Functional annotation of the identified variants associated genes was performed using SnpEff (v 3.1) (http://snpeff.sourceforge.net/). Gene diversity31 and Polymorphic Information Content (PIC)32, which can range from 0.0 to 0.5 for bi-allelic SNPs, were manually calculated.Demultiplexing of raw Illumina reads was carried out using the process_radtags utility included in Stacks v2.033 with K ranging from 1 to 15. One thousand bootstrap replicates were run to estimate parameter standard errors. Ten-fold cross-validation (CV) procedure was performed and CV scores were used to determine the best K value. Non-parametric study of population structure was also carried out using AWclust34, with k-means clusters ranging from 1 to 40. The optimal number of clusters was inferred by the Bayesian Information Criterion statistics. Genetic relationships among individual accessions were finally assessed by the construction of a dendrogram based on the allele sharing distance and Ward’s clustering algorithm34. Polymorphic Information Content (PIC), Heterozygosity (H) and Gene Diversity were calculated using Power Marker software35. Multidimensional scaling (MDS) was performed using the ggscatter function implemented (https://rpkgs.datanovia.com/ggpubr/reference/ggscatter.html) in Rstudio36. Variants pruned for LD were used. The relationship between accessions was visualized by plotting scores for the first two PCs.Model-based ancestry estimation was obtained using the ADMIXTURE softwareTo identify genetically redundant accessions, a dissimilarity matrix was calculated using VCF2dis.1.0.py script. The dissimilarity index between two accessions was calculated from the entire VCF file as the proportion of unmatching alleles between two accessions: a null value (=0.00000) indicates redundant accessions.http://mapman.gabipd.org/). Moreover, we implemented Core Hunter v. 2.0 to build a mini-core collection based on genotypic data37. The Core Hunter software was run in R with default parameters using the variants pruned for LD (http://www.r-project.org/), which allows choosing sampling intensity and the genetic measures to be used as selection criteria.To identify private SNPs in ‘da serbo’ landraces compared with the others, MAF values were computed at individual SNP loci in the two groups separately. Only SNPs that showed contrasting MAF values (> 0.4 in ‘da serbo’ and < 0.2 in the other cultivars) were further analyzed for their biological function using MapMan . Traits analyzed included: (i) green shoulder ; (ii) external fruit color ; (iii) fruit predominant shape ; (iv) fruit firmness ; (v) average fruit weight on a bulk of 18 fruits (in grams). Principal component analysis was performed using the computer package XLSTAT 2012.1.27, led to identifying ~26.000 SNP less compared with the previous annotation. Differences in length ranged from a minimum of 292,053 bp (Chr 7) to a maximum of 6,991,656 bp (Chr 3). The greatest difference in size was observed for the unlinked SNPs (chromosome 00) which were halved in the new annotation (~10.000 SNP less). Except for chromosomes 6 and 10, the SL4.0 allowed a higher percentage of SNPs distributed along each chromosome. The total number of SNPs and their distribution along chromosomes for SL3.0 and SL4.0 are reported in Supplementary Table The sequencing of RADs libraries in 288 tomato genotypes produced a total of 1,036,589,344 raw reads, corresponding to an average of 3.5 million read pairs per sample. We identified 277,335 SNPs in the previous annotated genome references (SL3.0), whereas 246,936 SNPs were identified using the new reference genome (SL4.0). The decreased total genome size of SL4.0 with respect to SL3.0 , due to the shorter chromosomes lengthS. pimpinellifolium. The two other Peruvian cultivars LA1313 and PI365927, held 54,166 and 68,247 SNPs, respectively.  database under the accession number BioProject ID PRJNA638535.Three of them, harbored a higher number of variants . In particular, the breeding line holding the greater number of SNPs  is LA2934 containing introgressions of the wild species Out of 246,936 SNPs, found using the latest tomato annotation (SL4.0), 10% (23.377 SNPs) were localized in 48% (2.297/4.794) of newly annotated genes. Most of these SNPs  have a possible modifier effect, followed by 721 with moderate impact, 608 with low impact and 57 with high impact. Most of these SNPs were localized in upstream gene regions , downstream gene regions , introns , 5′ UTR regions , 3′ UTR regions (820)  lower than 0.5.The first cluster (named “K1”), contained 10 cultivars from Peru, USA, Spain, France, Russia, Philippines and Falkland Islands, 23 Spanish landraces of which fourteen were ‘da serbo’, two heirlooms and one cultivar from Algeria, whereas 5 heirlooms, 4 landraces for fresh consumption , three breeding lines and one cultivar from Greece were placed in K2. The clusters K3 and K6 were the most abundant in terms of the number of genotypes, with 81 and 96, respectively. In particular, in cluster K3 most of the genotypes came from Italy (17 landraces of which 5 were ‘da serbo’), Spain (17 landraces of which 13 were ‘da serbo’) and France (8 cultivars and 3 landraces). Seventeen heirlooms, two breeding lines and 12 cultivars from various world regions were also included in K3. Similarly, 26 accessions from Italy (of which 10 were ‘da serbo’), 39 from Spain (of which 17 were ‘da serbo’), 11 heirloom, 14 cultivars, 5 unknown and one breeding line were included in K6. The cluster K4 grouped 11 ‘da serbo’ Spanish genotypes with 5 cultivars, one heirloom and a breeding line, whereas 7 landraces from Italy (2 ‘da serbo’ and 5 for fresh use), 10 cultivars, 7 heirlooms (five retrieved from the USA) and 4 breeding lines were included in K5. Nine accessions were classified as admixed, as they showed values for the highest cluster membership coefficient (FST) values, measuring the population (K) differentiation based on SNP data, are reported in Table FST = 0.185). Considering the average q-value at K = 6  equal to 2 with 42 and 246 accessions, respectively  equal to 6. The score plot in the first two components Fig.  clearly The second score plot based on the biological status of accessions Fig. , evidencr2 between pairs of SNPs using PopLDdecay to estimate the linkage disequilibrium (LD) patterns in our collection and within the different major subgroups . Linkage disequilibrium of the entire population decays very rapidly (within <5 kb). Landraces for fresh consumption and improved cultivars showed the lowest LD values  and Pop25 (DS9) had a dissimilarity value of 0.00158, whereas the landraces Varrone (FC33) and Laura (FC34) showed a value of 0.00204 . This gene encodes for motor proteins acting in vesicular transport on cortical microtubules and regulates cell wall mechanics during cell elongation in plants39. As a cytoskeleton protein, it is likely involved in response to drought stress40. In addition, it has been recently shown that this class of kinesins enters into the nucleus in response to cold stress in rice, suggesting a role in osmotic stress conditions41.In order to detect alleles differentiating ‘da serbo’ accessions from the rest of the germplasm collection, we computed the MAF values at individual SNP loci in both sets. A total of 53 SNPs showed contrasting values in the ‘da serbo’ group (MAF > 0.4) compared with other types (MAF < 0.2)  are important for plant growth, development, and damage prevention from light excess under drought condition42. By contrast, guanylate-binding proteins act as molecular switches to regulate diverse cellular processes, including bacterial and virus responses, by alternating between active (GTP-bound) and inactive conformation (GDP-bound)43. Investigating the biological role of the remaining genes harboring SNPs with contrasting MAF values, we noticed that the genes included in the bins 17 (Protein biosynthesis), 20 (Cytoskeleton organization) and 21  also seem to have such function in biotic stress response44. One of them  is a component of ARPF2-ARRS1 assembly complex, which play an essential role in ribosome biogenesis and probably in ribosome stress response45, whereas Solyc11g013490.2 (bin 21) was identified as hexosyltransferase non-classical Arabinogalactan-protein, a family of hydroxyproline-rich glycoproteins ubiquitous in the plant kingdom and involved in several processes, from plant growth and development to reproduction46. Two other coding regions: Solyc10g083610.2 (bin 11) and Solyc05g050280.3-Solyc05g050290.3, bin (5) were implicated in phytohormone action. In particular, Solyc10g083610 encodes for a Raf-like serine/threonine (Ser/Thr) protein kinase annotated as CTR1 (Constitutive triple response), whereas Solyc05g050280 transcribed for Jasmonate Resistant 1 (JAR1). In tomato and Arabidopsis, CTR1 has been reported to be involved in ethylene biosynthesis, being a negative regulator of signal transduction47. When the receptors perceive ethylene, CTR1 kinase activity is shut off, thereby leading to responses. By contrast, JAR1 encodes an enzyme that conjugates jasmonic acid (JA) to isoleucine, which was recently shown to be essential for pathogen defense48.The other genes with high MAF values in ‘da serbo’ genotypes were pre-pro-cysteine proteinase , Cytochrome b561  and Guanylate-binding protein . Cysteine proteinases are known to be involved in protein maturation, degradation, and protein re-built in response to different stress conditionsSingle genes were involved in photosynthesis processes (bin 1), lipid metabolism (bin 5), chromatin organization (bin 12), DNA damage response (bin 14), RNA biosynthesis (bin 15), protein modification bin 18), and solute transported (bin 24), whereas 15 genes did not show any functional description and were grouped in the group with not assigned function (bin 35)  (Solyc10g006880), rin (ripening inhibitor) (Solyc05g012020) and Cnr (Colorless non-ripening) (Solyc02g077920), since they are related to a strong ripening impairment mainly related to ethylene insensitivity51. One polymorphism was found in the intergenic region of nac-nor, whereas two were detected in the rin region (one intergenic and one synonymous variant). All the variants detected passed the quality filtering. Regarding Cnr, four different variants, of which one passed quality filtering, were also identified. Only one was found in the upstream region and the minor allele was identified in 13 cultivars, 6 heirlooms, 4 unknown, 3 landraces and in one ‘da serbo’ genotype (data not shown).We also specifically looked for polymorphisms in Tapping the diversity of crops is a prerequisite for efficient genetic improvement, conservation, and management of germplasm resources. The present work was aimed to study the genomic diversity of a diverse panel of cultivated tomato germplasm and to identify loci under selection and putatively responsible for the syndrome of differences related to LSL cultivars.55. Approaches to investigate the diversity of traditional varieties including vintage and landraces have been performed with a low56, or medium marker-throughput20 in collections not larger than a hundred of accessions20 with few exceptions comprising a large proportion of improved cultivars56. These studies ascertained population stratification due to selection history, geographic adaptation and market destination20. Landraces were reported to have a lower allelic diversity compared to contemporary varieties, although the former may be richer in rare alleles17. In fact, modern varieties are developed through introgression breeding increasing the allelic assortment in established genetic backgrounds54. On the contrary, local varieties have been less exploited in terms of breeding and cultivation, having been replaced by high yielding varieties, particularly in intensive agricultural systems57. Therefore, the genetic composition of landraces is mainly due to selection driven by local practices in specific agricultural systems as well as environmental factors.As a model species, tomato has been widely exploited for breeding, genomics and biology researches, being among the first vegetable crops having the whole genome sequence released. Within tomato populations genetics, efforts have been principally addressed toward the dissection of the genetic basis of advanced recombinant materials, elite germplasm, and wild species58. The occurring heterozygosity across the whole collection is in agreement with previous evidence reporting values ranging from 1 to 4% in traditional varieties and higher values in the improved varieties3.The gene pool could contribute to broadening and improving the genetic base of current modern varieties. A deeper exploration would give more insight to be exploited for tomato improvement. In this regard, we applied ddRAD sequencing protocol detecting 246,936 polymorphic sites and of 32,779 high-quality SNPs used to infer population structure and phylogenetic relationships using parametric and non-parametric computations. The abundance and whole-genome coverage provided by ddRAD based SNPs provide a high measure of genomic diversity in particular at the intra-specific level, where fewer polymorphisms occur compared to the inter-specific level15. The number of K clusters identified can be considered consistent to define the population structure. Wang and colleagues54, and Bauchet and collaborators56, identified population structure within the typologies studied detecting 9 and 6 clusters in collections of 348 and 300 individuals, respectively. We also investigated the level of redundancy among accessions. The lowest values (<0.002 and <0.003) were found within landraces for fresh consumption as well within LSL, confirming how in situ conservation better maintains the genetic identity of tomato landraces due to reduced gene flow and genetic drift59. The MDS plot confirmed a low gene flow between LSL ‘da serbo’ materials and the other groups of accessions. Furthermore, allele exchange was observed between Italian landraces, heirlooms and elite cultivars, suggesting their greater exploitation in breeding programs. An LD decay within a few kilobases was observed in the 288 accessions studied. Robbins and colleagues evidenced an overall LD decay within a few cM with differences between the fresh market and processing market types14. The same trend was observed by Bauchet and collaborators reporting an LD fluctuating according to the genetic groups studied54. Both authors highlighted the breeding history and gene recombination as the main factors influencing the observed LD values. Moreover, the homozygosity level and mating system are two additional components affecting LD in crops. In fact, in outcrossing species, the LD can decay within hundreds of bp while for highly selfing species the LD may extend to 10 kb60. Moreover, accessions with different biological statuses can exhibit diverse LD values. As an example, in maize, the LD decay of landraces has been proven to be 100-fold less than in elite lines61. The same trend has been observed in heterogenous germplasm of barley61. The mini-core collection set of 58 tomato accessions was built with the objective to maximize genetic diversity with a reduced number of accessions. This mini-core collection represents the whole genetic and phenotypic diversity of the collection studied and could be useful to identify traits of agronomic and qualitative interest in tomato. Phenotyping is a major bottleneck to address in breeding due to costs and time required62. The establishment of a mini-core collection encompassing most of the diversity could be a valid solution to deeply explore the phenotypic diversity, overcoming the bottleneck of using very large collections to identify key traits for genetic improvement.The results indicated a certain differentiation within the collection on the basis of biological status and provenance of accessions. Although a certain level of admixture was found between contemporary varieties, heirlooms, and landraces, the ‘da serbo’ LSL types were genetically more distinct. Moreover, a higher number of structured subgroups were found in landraces with respect to contemporary varieties. Indeed, although LSL and fresh consumption landraces represent 52% of the whole collection, fewer alleles were shared with the other typologies. Our observations are in agreement with previous researches that do not report subpopulation structures in varieties developed from advanced breeding programs such as cultivars and heirlooms, evidencing how the subpopulation structure is determined by natural selection and breeding historyalc, nor and cnr66. In particular, the alc mutation has been found in Spanish LSL ‘da serbo’ genotypes, which are commonly called ‘de penjar’ in Catalonia and Valencia and ‘de ramellet’ in the Balearic Islands67. In the ‘Alcobaça’ landrace the alc mutation was associated to a reduction of ethylene production  transcription factor were found, endorsing the idea that genetic determinants of the LSL fruit phenotype may be different between Italian and Spanish landraces. In our study, we identified few polymorphisms in nor-nac, rin and Cnr, mainly localized in intergenic regions except for one variant detected in Cnr. Previously, Casals and collaborators12, identified a polymorphism in the second exon of the gene nac-nor, consisting of a replacement of thymine by adenine in the coding sequence responsible of the alcobaca  mutation. In the same study12, the analysis of the rin region excluded its involvement as a cause of long shelf life in the Spanish ‘de penjar’ varietal types. Bota and colleagues67, also detected the presence of the alc mutation in a collection of Spanish ‘de ramellet” accessions from Majorca island. Our results suggest that, in addition to alc, other variants in rin, nac-nor and Cnr might be involved in the development of LSL ‘da serbo’ shelf life. We cannot exclude that our approach did not cover the region of alc previously studied12 due to the reduced genome representation occurring with ddRAD genotyping. Therefore, target sequencing may be used to verify the presence of such variants in this gene. Some SNPs were instead identified in ethylene signal transduction genes. Indeed, two SNPs were localized in intron regions of Constitutive Triple Response 1 (CTR1), an important negative regulator of ethylene signaling. CTR1 has a central position in the ethylene-response pathway, acting downstream of the ethylene receptors and upstream of EIN2, a membrane-integrated metal transporter-like protein69. In the presence of ethylene, the function of CTR1 is inhibited and EIN2 can translocate in the nucleus inducing the expression of ethylene-responsive genes70. By contrast, in absence of ethylene, CTR1 can phosphorylate EIN2, which becomes inactive and does not induce its response.Although the LSL are usually related to higher phenotypic performance and stress tolerance, the molecular mechanisms underlying the extended shelf-life and tolerance to drought cultivation conditions are not fully understood. To date, the LSL phenotype has been related to different mutations in genes such as CTR1 is also involved in salt tolerance71. A mutant inactivating the allele-kinase in CTR1 (ctr1-1), exhibited an increased salt tolerance during the germination and post-germination stages, suggesting a role of CTR1 as negative regulator71. Therefore, the two variants identified in CTR1 intron might play a dual role. On the one hand, they may act as enhancers, as already described in many plants such as Arabidopsis and rice73 In this scenario, CTR1 might be expressed at a higher level even in the presence of ethylene, inhibiting the expression of related genes, which may lead to the extended shelf life of ‘da serbo’ accessions. On the other hand, intronic variants may induce aberrant splicing, resulting in defective protein products. In this case, CTR1 might have an abnormal structure which can increase the tolerance to osmotic stresses such as salt and drought. However, since much remains unclear in respect to the signal transduction pathways from CTR1 to EIN2 in different plant species, other studies are ongoing to clarify the effect of the two variants identified.In addition, it has been shown that JASMONATE RESISTANT 1 (JAR1), a coding-protein having a key role in the biosynthesis of jasmonate48. A variety of functions are associated with JAR1 including resistance to biotic stress. Previous studies evidenced a correlation between jasmonate and reduced ethylene emission in ‘de Peniar’ accessions68, suggesting how the LSL fruit phenotype may be also related to non-ethylene mediated ripening regulation as in the non-ripening tomato mutants75.Interesting variants were also identified in 20, who identified a kinesin harboring a non-synonymous SNP in Italian ‘da serbo’, we found a SNP in the 3’-UTR region of Solyc09g075480.3. The underlying gene has high similarity to kinesin-14, which has a role in cell wall synthesis, acting in the deposition and orientation of cellulose microfibrils76. Other interesting variants were identified in cysteine proteinases (CP), cytochromes b561 (Cyt-b561) and guanylate-binding proteins (GBP). CP are mainly involved in protein rebuilt following external stimuli and in the protection against misfolded or damaged proteins77. The process could involve the rebuilding of cold and heat shock proteins, dehydration-induced proteins and pathogenesis-related proteins. Examples were reported in pea and Arabidopsis for which CP induced by water deficit are responsive to salt stress80. In tomato, CP are reported to have an active role in biotic and abiotic stress defense and suppression of autonecrosis82. Similarly, Cytochromes b561 are intrinsic membrane proteins involved in ascorbate regeneration known for its detoxification during aerobic metabolism and under stress conditions84. In watermelon, CYB561 has been reported to be induced by drought and high-light stress, suggesting a role for thermal dissipation of excess light energy, through functional interaction with apoplastic ASC oxidase85. In addition, through the modulation of levels of reactive oxygen species, ascorbate with its CYB561 activities are also implicated in the control of cell expansion, cell division, and programmed cell death85. Regarding GBP, it has been demonstrated how intravacuolar bacteria of infected cells stimulate the recruitment of antimicrobial guanylate binding proteins as part of a coordinated host defense program86.In agreement with surveys of Tranchida-Lombardo and colleaguesnac-nor, rin and Cnr may also be related to long shelf life and higher stress tolerance in Mediterranean ‘da serbo’ LSL tomato germplasm. Our results indicate putative genes under selection. The gained information suggests the possibility to further investigate specific genomic regions for the mining of novel alleles to be exploited for the improvement of long shelf life and resilient cultivars.Overall, these results support that mutations different from those previously known in genes such alc, nac-nor and cnr. Among the newly identified genes, those involved in biotic and abiotic stress conditions as well as in ethylene and jasmonate pathways may be worth being studied further. We finally provided breeders with a mini-core collection composed of the most diverse genotypes of our germplasm. Overall, the collections studied constitute a promising reservoir of genes for traits of interest, which could be further explored in genome-wide association studies and exploited in new tomato precision breeding programs.Using ddRAD-seq for high throughput SNP discovery and the latest tomato genome version for annotation, we showed for the first-time new clues in a large fraction of Mediterranean ‘da serbo’ gene pool, providing furthermore, a list of 2297 newly and never studied target genes with different functions and harboring SNPs. The genomic analysis highlighted a geographical footprint distinguishing the landraces developed in the Mediterranean basin secondary center of diversity of tomato. We then investigated the level of variation underlying long shelf-life landraces, detecting SNPs falling in gene regions other than the previously known Supplementary Table 1Supplementary Table 2Supplementary Table 3Supplementary Table 4Supplementary Table 5Supplementary Table 6Supplementary Table 7Supplementary Table 8Supplementary Figures


These results highlight the risk of false inclusion of a relative or even non-relatives in parentage testing with STRs. We then validated all ambiguous STR results by targeted sequencing with a custom panel containing 4,830 individual identification single nucleotide polymorphisms (IISNP), found that the ratio of mismatch loci to total SNPs was 1.78–6.95% in close relatives compared with 10.93–13.49% in unrelated pairs. Last, we reported three real cases with undetermined paternity by STRs and rectified them by dissecting with our IISNP panel. These results suggested that high-density IISNP panel can be used to identify and rectify misjudged cases effectively.Parentage testing is routinely performed by genotyping short tandem repeat (STR) through capillary electrophoresis in the present. However, ambiguous or even misjudged paternity based on STRs happens from time to time in cases where only one putative parent is available. We analyzed STR data of 7,818,969 unrelated pairs and 75 close-relative pairs and found that although the probability of a random false match between non-relatives was 4.22 × 10 Parentage testing plays a critical role in searching for missing persons , identif–3–10–4 per generation  value accompanied by separate genetic incompatibilities . Ambiguoneration , so it iIn addition, compared with the ambiguous STR results between close relatives, a random but perfect false match (RPFM) between unrelated individuals may also result in error. In other words, an unrelated person shares at least one allele with the child at all STR loci by chance and thus could be misjudged as the biological parent. RPFM may occur when searching for missing persons in a large population, such as finding the parents of rescued trafficked children in a large database .4–105 times higher genetic stability (forID 52-plex SNP panel is often used to solve the question of ambiguous paternity based on STRs (Single nucleotide polymorphisms (SNPs) are complementary markers to STRs, with their feature of 10tability  and greatability . It has tability . Consequ on STRs . HoweverIn this study, we first estimated the prevalence of ambiguous paternity in cases involving close relatives as well as the probability of random false match between non-relatives with STRs. Then we evaluated the performance of a custom panel with 4,830 individual identification SNPs (IISNP) in the above situations. Last, we reported three real cases with undetermined STR results and rectified them by dissecting with our IISNP panel.This study was approved by the Institutional Review Board Administration in Xi’an Jiaotong University (No. 2018-408). We collected three batches of samples: (1) 55 samples from eight families for close relative matching experiment, (2) 64 samples in 33 randomly false matched pairs, and (3) 6 samples in three cases with ambiguous STR results. For each participant, informed written consent was obtained, then blood sample was spotted on the anti-bacterial nucleic acid collection card .® dsDNA HS Assay Kits on Qubit® Fluorometer 3.0 .Blood genome DNA was extracted using the TIANamp Micro DNA kit  according to the manufacturer’s protocol. Extracted DNA was quantified with QubitFor close relative samples, 1 ng genome DNA was amplified using the HUMAN DNA Typing-YanHuang kit  on the thermal cycler . Then, STR genotyping of the PCR products was performed on the ABI 3500 genetic analyzer and analyzed with GeneMapper ID-X software . HUMAN DNA Typing-YanHuang kit contains 24 autosomal STR loci .For randomly matched study, existing STR data  of 3,955 unrelated individuals from our DNA center were collected after approval. STRtyper-21G kit contains 20 autosomal STR loci . We note that all STR kits in this study are commonly used commercial products, which are often used for parentage testing alone or in combination.r having n alleles A1, A2, …, An with corresponding allele frequency p1, p2, …, pn. The probability of excluding a random person from parentage at locus r is given by Qr(θ), where θ is the coancestry coefficient. θ = 0 implies the population is in Hardy–Weinberg equilibrium (HWE).According to the research from R unlinked autosomal loci were used, the probability that two unrelated persons sharing at least one allele at all loci by chance could be taken as RPFMR(θ).Supposing R(θ)  .R unlinked loci. According to the Chinese national technical specification for parentage testing  was calculated as the ratio of likelihood values of two hypotheses  based on the local allele frequency . The CPI testing , inclusip > 0.05) in Chinese Han; and (3) any two SNPs located on the same chromosome were in linkage equilibrium (r2 < 0.05). In the Chinese Han population, 98% SNPs in CHP4830 have a validated MAF value greater than 0.30.Based on the panel CHP5457 previously developed in our laboratory , an optiThe CHP4830 panel was used to validate all ambiguous cases according to the following approach. First, genome DNA was extracted using TIANamp Micro DNA Kit  according to the manufacturer’s protocol. One hundred nanograms of DNA was fragmented to 200–500 bp by the endonuclease. When going through end blunt, an “A” tail and adaptor was ligated to DNA fragments, and then DNA libraries were prepared. After that, target SNP regions were captured with probes and sequenced on the BGISEQ-500 platform  with a PE50 strategy.1 using the Burrows-Wheeler Aligner aln algorithm (v0.7.12). Finally, the Genome Analysis Toolkit UnifiedGenotyper was utilized to perform SNP calling for loci with coverage >30-fold.The raw sequencing reads were filtered out if they met one of these criteria: (1) N-content more than 1%; (2) reads overlapping >10 bp with the adapter sequence; (3) fraction of Q20 base less than 90%, and (4) duplicates derived from amplification. The obtained clean reads were aligned to human genome hg19To investigate the incidence of ambiguous or false inclusion in relatives, a total of 75 duos of the child and first-degree relatives  of the true parent were recruited. All samples were genotyped with HumDNA Typing-YanHuang . For each pair, the Mendelian incompatibilities were counted, and the CPI was calculated. Our results showed that 2 of 29 grandparent–grandchildren pairs showed one mismatch, and 1 of 20 uncle–niece pairs showed two mismatches. For 26 full sibling pairs, 1 pair matched in all loci, 3 pairs showed only one mismatch, and 7 pairs showed 2 mismatches. In total, 8.0% (6 of 75) close relative pairs showed no more than one mismatch , in whicTo evaluate the performance of SNPs in cases involving close relatives, we genotyped the samples with CHP4830. We calculated the mismatch ratio, the ratio of the number of mismatched loci to the total number of detected SNPs, and found the mismatch ratio 1.78–3.84% for full sibling was significantly lower than 4.07–6.95% for grandparents and 5.36–6.84% for uncle/aunt relationship, all of which were lower than 10.93–13.49% for non-relatives .2b24a. When both parents have heterozygous SNPs, the probability that a full sibling pair does not share an allele at this locus is 1/8. Thus, for a SNP to be tested, the possibility of not sharing an allele in a full sibling pair is 2b21/2a (2b24a∗1/8). Taking all SNPs together, the theoretical value of mismatch ratio between full sibling pair is also 2b21/2a because these loci are unlinked. As nearly all SNPs in CHP4830 have a validated MAF range in 0.3 to 0.5  from 3,955 individuals were collected after approval. Ignoring non-DNA information, such as age, gender, and district, STR data of each person were paired with all the others. After excluding the registered relatives, 7,818,969 comparisons were obtained. For each pair, the number of Mendelian incompatibilities was counted.–6. Note that two samples matched twice with non-relatives. Subsequently, we used CHP4830 to genotype these random matched samples, then calculated the mismatch ratio in each pair. The result showed that the fraction of mismatch loci to total SNPs was between 10.04% and 13.29%  and 1.08 × 10–5 in the substructure population (θ = 0.02), which is consistent with our observed value 4.22 × 10–6 , child and alleged father shared alleles in all 19 loci, with a CPI of 1.65E+05 . Howevertrue one .In case II, for kit 1 , two genetic inconsistencies  between child and alleged mother were found in 20 autosomal STRs, and the CPI was 1.28E–04; thus, no clear conclusion could be drawn . For kitIn case III, two genetic inconsistencies (D13S317 and D13S325) were found with a CPI 1.52E–03 by kit HumDNA Typing (FGI). As the child was homozygous at both loci, we inferred that the incompatible loci may result from allele dropout . Of 4,15TM system, Ochiai predicted that the probability of matches with only 1 mismatch in 21 STRs for full siblings was 23.5% , we took 100 random samples of 50, 100, 150, 200, 300, 400, 500, 600, 800, or 1,000 SNPs and counted the number of mismatch loci. No mismatches were found when sampling up to 200 SNPs. When sampling 300–600 SNPs, a minimum of 1–3 mismatches were found. When continuing to extend the simulation, 6–24 mismatches were found when sampling up to 800 SNPs, and 8–27 mismatches found when sampling up to 1,000 SNPs . When us–5 when one mismatch is allowed, which is comparable to the predicted match probability 8.59 × 10–5 between non-relatives by using 21 STRs in the GlobalFilerTM system  can be found in the article/The studies involving human participants were reviewed and approved by the Institutional Review Board Administration in Xi’an Jiaotong University (No. 2018-408). The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.LC conceived and designed the experiments and wrote the manuscript. XM and SW performed the experiments. HY and LC were involved in the data analysis. BZ and SL revised the manuscript. All authors had 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 early 20th century, Cuban farmers imported Charolais cattle (CHFR) directly from France. These animals are now known as Chacuba (CHCU) and have become adapted to the rough environmental tropical conditions in Cuba. These conditions include long periods of drought and food shortage with extreme temperatures that European taurine cattle have difficulty coping with.Bos indicus. We used the extended haplotype homozygosity (EHH) approach to identify regions in the genome that may have had an important role in the adaptation of CHCU to tropical conditions. Putative selection events occurred in genomic regions with a high proportion of Bos indicus, but they were not sufficient to explain adaptation of CHCU to tropical conditions by Bos indicus introgression only. EHH suggested signals of potential adaptation in genomic windows that include genes of taurine origin involved in thermogenesis  and hair development (CCHCR1 and CDSN). Within these genes, we identified single nucleotide polymorphisms (SNPs) that may have a functional impact and contribute to some of the observed phenotypic differences between CHCU and CHFR animals.In this study, we used whole-genome sequence data from 12 CHCU individuals together with 60 whole-genome sequences from six additional taurine, indicus and crossed breeds to estimate the genetic diversity, structure and accurate ancestral origin of the CHCU animals. Although CHCU animals are assumed to form a closed population, the results of our admixture analysis indicate a limited introgression of Bos indicus genes in CHCU. We observed possible signals of recent adaptation to tropical conditions between CHCU and CHFR founder populations, which were largely independent of the Bos indicus introgression. Finally, we report candidate genes and variants that may have a functional impact and explain some of the phenotypic differences observed between CHCU and CHFR cattle.Whole-genome data confirm that CHCU cattle are closely related to Charolais from France (CHFR) and Canada, but also reveal a limited introgression of  Climate change and global warming are among the main challenges currently faced by Agriculture and Livestock husbandry. In this scenario, it is fundamental to investigate the mechanisms that allow animals to adapt to high temperatures. The hot temperature conditions of tropical climates today might resemble those that animals raised outdoors under temperate climates, such as most beef cattle and small ruminants, will face in the future. Therefore, animals that currently live in hot climates and that have a European or temperate climate origin can provide clues into the genetic mechanisms underlying adaptation to increasing temperatures .Bos taurus, of European origin, and Indian zebu breeds Bos indicus, which diverged ~ 250,000 years ago [B. indicus breeds produce less meat and of lower quality but are more adapted to heat and parasites than taurine breeds. For that reason, they were imported to tropical American regions starting in the mid-19th century [B. taurus and B. indicus, such as the Brangus, Texas Longhorn, Santa Gertrudis, among others, also coexist with pure B. indicus breeds. These mixed breeds exhibit a good resistance to parasites and heat, and also produce carcasses of much higher quality than pure B. indicus breeds.Cattle breeds can be divided into temperate taurine breeds  century , 4. UndeB. indicus blood group allele (U’1), at a very low frequency. More recently, Rodriguez-Valera et al. [FST) = 0.049) is observed between CHFR and CHCU cattle. Genetic and phenotypic differentiation can be caused by genetic drift, i.e., as a consequence of the importation of a small number of individuals and by selection of beneficial variants that promote adaptation to the tropical environment. A number of statistics have been proposed to distinguish changes produced by genetic drift from those due to adaptation . This population has adapted to the breeding conditions in the Cuban tropical environment in ~ 20 generations of breeding. In this short period of time, several clear phenotypic differences between the original French Charolais (CHFR) and its Cuban counterpart have appeared. CHCU cattle are smaller than CHFR, with weights of 34 vs. 46 kg at birth and 290 vs. 493 kg for heifer’s weight at 18 months, respectively . Also, Cn .Because SNP array genotype data are biased and have a low resolution, for our study, we obtained whole-genome sequence data from 72 animals, including 12 CHCU animals, to provide an unbiased estimation of the population structure and to fine-map regions that could have played a role in the adaptation to tropical conditions of the Chacuba population.B. indicus breed whereas BRG and TXL are admixed breeds between B. indicus and B. taurus cattle. Data on the French and Canadian LIMS individuals were merged in the analyses reported here.Seventy-two whole-genome sequences from taurine, indicine and crossbred cattle were analyzed. CHCU cattle have been maintained under pedigree control at the “Manuel Fajardo” genetic center that is located in Jiguani (Granma Province) with a current census of ~ 700 animals. Therefore, the genetic relationship between animals can be accurately tracked and we used this information to select 12 unrelated CHCU animals that were sequenced in this work. We also used 15 French Charolais (CHFR)  and sequhttps://github.com/miguelperezenciso/NGSpipeline. In brief, to identify whether a position is equal to that in the reference genome, polymorphic or missing, first we generated a fasta file from the gVCF file for each individual and generated a multi-individual VCF file by using the individual file. Once the multiple sample file was obtained, SNPs with more than 20% missing data across samples and populations were removed. Finally, we imputed the missing genotypes and inferred phases with the Beagle 4.1 software [All the sequences were mapped against the bovine reference assembly (UMD3.1.1) using the Burrows-Wheeler aligner (BWA) v. 0.7.12-r1039 software . PCR dupsoftware .Genetic variants that alter transcription factor binding sites (TFBS) were predicted with a custom script using the TFBS models from the JASPAR  software in consecutive non-overlapping 30-kb windows. This software implements algorithms that allow for missing data [https://github.com/CRAGENOMICA/Tang_Rsb). As putative selection events, we retained the windows with a ‘permutation p-value’ lower than 0.05 among the 2000 windows that contained the SNPs with the largest Rsb value. The ‘permutation p-value’ was obtained by randomly shuffling the CHCU and CHFR samples and running the Rsb algorithm along the whole genome. The process was repeated 100 times and we computed the number of times the observed Rsb statistics was larger than the values obtained from permutation, and obtained a ‘permutation p-value’ for each SNP. This process aims at correcting for different levels of disequilibrium along the genome that may locally inflate Rsb values. In a second step, we performed the same procedure but this time between CHFR and CHCA, to exclude the Rsb intervals that were common between CHFR and CHCA and not specific to CHCU. Therefore, we focused only on the Rsb intervals with signals exclusively from CHCU.We estimated Watterson’s nucleotide variability (θ)  and diffFST,  between ing data . For theing data . The EHHing data  were comB. indicus introgression in CHCU. Nevertheless, K = 2 was also the value that resulted in the lowest cross-validation error. The program was run either by including all the SNPs or with pruned data from which SNPs in strong disequilibrium were removed, but the results were identical. To get a more precise map of potential admixture, we used the ELAI software [The software ADMIXTURE v1.3.0  was run software , which iB. indicus breed (BRM), 6,839,436 to the taurine breeds and 1,176,249 to CHCU. As expected [B. indicus samples were more variable than B. taurus samples, i.e. the nucleotide variability was equal to 0.0035 per bp for BRM but was two times lower for LIMS and European Charolais  and 12.5 (CHCU)  and French Charolais (0.05)  Table . The ploB. indicus into CHCU and although it was small [B. indicus BRM breed, whereas it reveals a small introgression of B. indicus in CHCU. This is also reflected when only the BRM, CHFR and CHCU breeds are represented in the PCA plot  autosomes BTA12, 13 and 23 had the highest proportions of B. indicus introgression  across all animals. On a per individual basis, the highest proportion of B. indicus introgression was found for the CHCU11 individual, i.e. 47% on BTA12, followed by CHCU10, i.e. 45% on BTA13. In contrast, on average the lowest proportion of B. indicus introgression was found for individuals CHCU12 (6.5%), CHCU4 (7.4%) and CHCU2 (7.5%) and for chromosomes BTA5 (2.4%), BTA15 (2.7%) and BTA28 (3.9%). Additional file B. indicus genome in CHCU and the FST value between CHCU and CHFR across windows. A higher proportion of B. indicus was moderately correlated (0.19) with a greater differentiation between the Charolais populations.To evaluate more precisely the extent and impact of software , which pmes Fig.  and [seeAmong the 2000 windows with the largest positive Rsb value, we selected the 407 windows with a ‘permutation p-value’ lower than 0.05 and exclusive of CHCU Fig. , i.e., wATP9A, GABBR1, PGR, PTPN1 and UCP1) involved in thermotolerance and two (CCHCR1 and CDSN) involved in hair development  gene, which, if inactivated, induces hypothermia in mice [GABBR1 can potentially modify the binding site of transcription factors  gene, we detected 382 SNPs including three located in the 3′UTR and seven located in the upstream region that can potentially alter TFBS. Inactivation of PTPN1 in mice results in an increase in adaptative thermogenesis [UCP1 gene and 77 upstream SNPs, including four that are fixed  for the alternative alleles in CHCU , which contained 466 SNPs within our bovine samples, among which one SNP (rs462034580) can potentially impact splicing of this gene, 194 SNPs are located in the upstream region, and three are missense deleterious SNPs . Interestingly, one of the CDSN deleterious mutations (rs434552200) is nearly fixed for the alternative allele in CHCU, with a frequency of 0.994. Further experimental analysis of the impact of these variants is needed to determine whether they are involved in some of the phenotypic differences between CHCU and CHFR.Regarding hair development, 133 SNPs were found within the air loss . Three SCreole cattle refer to the descendants of the first European animals that have adapted to local tropical conditions on the American continent. However, as Burgos-Paz et al.  showed fB. indicus animals, as previously suggested by Rodriguez-Valera et al. [B. indicus is in the order of 4 to 8%, depending on the method used or the individual considered  genomic intervals, since our aim was to detect regions in which the putative selective pressure is specific to the Cuban population. Moreover, the detection of putative signatures of selection in [Our results confirmed 17 of the 104 genomic regions reported by Rodriguez-Valera et al. . The difction in  was baseATP9A, GABBR1, PGR, PTPN1 and UCP1 were putatively under selection. Previously, Dikmen et al. [PGR and rectal temperature in US Holstein lactating cows exposed to heat stress. This SNP (rs109506766) is an intronic G/C SNP and, interestingly, the frequency of the G allele differs between CHCU and CHFR (0.38 versus 0.53). We also found several SNPs in PGR that had large differences in allele frequency between CHCU and CHFR and that might have a potential functional impact. For example, 16 of these SNPs can alter the binding sites of transcription factors, and interestingly, seven of these candidate regulatory variants modify the binding sites of heat shock factors.Within the selective windows, we found seven genes related to thermotolerance and hair development Table , which an et al.  reportedprogesterone receptor (PGR) gene, which is conserved among 70 eutherian mammals. Several studies have shown that progesterone has a vasoconstrictive effect, which reduces the cutaneous blood flow when the temperature of the skin increases, and ultimately decreases heat dissipation  in the codon for an arginine amino-acid within the ligand-binding domain of the on (e.g. . Moreoveon (e.g. . These funcoupling protein 1 (UCP1) gene is predominantly expressed in brown adipose tissue and plays major roles in regulating body temperature, metabolic rate and controlling energy expenditure via both non-shivering thermogenesis and diet-induced thermogenesis [UCP1 is essential for maintaining body temperature in non-cold conditions [UCP1 have been found to be associated with milk yield, milk fat percentage and milk protein percentage [UCP1 might partly explain the heat tolerance of the CHCU cattle. These variants should have a negative impact on UCP1 by reducing its activity or expression, and thus it would be interesting to perform an experimental confirmation.The mitochondrial ogenesis . UCP1 isnditions . Variantrcentage , but to CCHCR1 is involved in hair development and encodes the coiled-coil alpha-helical rod protein 1, which is expressed in basal keratinocytes [CCHCR1 that is associated with alopecia areata, an auto-immune disease affecting the hair follicle. We found several functional candidate variants within CCHCR1 that had large differences in allele frequency between CHCU and CHFR. For example, two of these SNPs can potentially disrupt the binding sites of heat shock factors. As previously mentioned, the corneodesmosin (CDSN) gene is also related to hair development. Mutations in the human CDSN are associated with hypotrichosis simplex, a scalp-specific hair loss [Cdsn showed rapid hair loss, which confirms the essential role of Cdsn for maintaining the architecture of the hair follicle [inocytes . Its exainocytes , 45. Intinocytes  have ideair loss  and micefollicle , 48.B. indicus in CHCU. We observed signals of recent adaptation to tropical conditions between CHCU and CHFR founder populations, which are largely independent of the B. indicus introgression, which suggests that most of the selection events are caused by soft sweeps. Some of the identified regions harbor genes that are involved in thermogenesis  and hair development (CCHCR1 and CDSN). We also report the presence of SNPs within these genes that can have a functional impact and might explain some of the phenotypic differences observed between CHCU and CHFR animals. Future experimental work is needed to evaluate the role of these a priori relevant genes in CHCU adaptation.In conclusion, analysis of whole-genome data confirms that the CHCU animals included in this study are closely related to Charolais cattle from France and Canada, but also reveal a limited introgression of Additional file 1: Table S1. Description of the samples included in this study.Additional file 2: Figure S1. Proportion of indicus per CHCU samples.Additional file 3: Figure S2. Relationship between proportion of indicus in CHCU and FST CHCU-CHFR, each dot corresponds to the FST value of a 30-kb window.Additional file 4: Table S2. Description of the intervals identified as selective sweeps between Cuban and French Charolais.Additional file 5: Table S3. Putative regulatory SNPs (rSNPs) located upstream of interesting genes.


We found that several of these mutations occur at low frequency in many cattle and bison parasite populations in North America, suggesting increased use of benzimidazole drugs in cattle has the potential to result in widespread emergence of resistance in multiple parasite species. This work illustrates a post-genomic approach to large-scale surveillance of early emergence of anthelmintic resistance in the field.As genomic research continues to improve our understanding of the genetics of anthelmintic drug resistance, the revolution in DNA sequencing technologies will provide increasing opportunities for large-scale surveillance for the emergence of drug resistance. In most countries, parasite control in cattle and bison has mainly depended on pour-on macrocyclic lactone formulations resulting in widespread ivermectin resistance. Consequently, there is an increased interest in using benzimidazole drugs which have been used comparatively little in cattle and bison in recent years. This situation, together with our understanding of benzimidazole resistance genetics, provides a practical opportunity to use deep-amplicon sequencing to assess the risk of drug resistance emergence. In this paper, we use deep-amplicon sequencing to scan for those mutations in the isotype-1  Collected fecal samples were cultured and stored as previously described.Sampled bison herds were originally described in Avramenko et al.  and have et al., . Exact i, et al. . Approxi  and at https://www.nemabiome.ca/index.html, and the results from these previous papers have been included with permission. Figures from both Avramenko et al. (http://creativecommons.org/licenses/by/4.0/). These data provide context for the species assessed for each sample, and are a reflection of the total percentage of the population a particular species represents.Nemabiome ITS-2 metabarcoding was previously carried out on all populations assessed in this paper. This provides the relative quantification of all nematode species present within mixed-species samples. Exact details regarding the method and the original results can be found in Avramenko et al.  for the  ), AC)), Supplementary Table S1 (F200L (TTC > TTA)) and S2 (F167L (TTC > TTA))]. The F200Y (TTC > TAC) SNP was found above the 0.1% species threshold in all five species, primarily in calves from Oklahoma; C. oncophora , O. ostertagi , C. punctata , H. placei  and T. axei   at 1.7% [data not shown as H. contortus were only identified at >200 reads in two samples (US6 and US10)]. The F167Y (TTC > TAC) SNP was identified in just two of the five species at low frequency; O. ostertagi  and C. punctata  (CG) mutation was detected in O. ostertagi in one animal (US 6) at 0.51%, but was not detected in any other animal or species. The F167L and F200L SNPs were identified in C. punctata, C. oncophora, O. ostertagi and H. contortus in several animals at <1% frequency (Supplementary Tables S1 and S2).A total of 38 individual stocker cattle entering feedlots in Oklahoma (22), Arkansas (3) and Nebraska (13) were assessed. Isotype-1 –57.43%) . The F2023–0.3%) , Table 2β-tubulin reads were identified in these samples, above the 200 reads per species threshold, for C. punctata, C. pectinata, H. placei, H. contortus and T. axei. The frequencies of non-synonymous mutations at codons 167, 198 and 200 were determined for these five species . The F200Y (TTC > TAC) SNP was found above 0.1%, in C. punctata , C. pectinata , H. placei  and H. contortus . The F167Y (TTC > TAC) SNP was also found above 0.1% for C. punctata , H. placei  and H. contortus . The F200L (TTC > TTA) SNP was detected in C. punctata , C. pectinata  and H. placei . The F167L (TTC > TTA) SNP was detected in C. pectinata, H. placei and T. colubriformis in several herds <1%.Calves from a total of 26 herds from Sao Paulo State, Brazil were assessed; isotype-1 β-tubulin reads mapping to just three species were identified; C. oncophora, O. ostertagi and C. punctata . The data for C. punctata were analysed for just those four herds for which there were at least 200 reads mapping to this parasite species . The frequencies of non-synonymous mutations at codons 167, 198 and 200 were determined . At the detection frequency threshold of 0.1%, none of the F167Y (TTC > TAC), E198A (GAA > GCA) and F200Y (TTC > TAC) SNPs that have been previously associated with benzimidazole resistance in trichostrongylid nematodes were identified in any of these herds. The majority of worms had the susceptible genotype at each of the three codons. F167L (TTC > TTA) and F200L (TTC > TTA) SNPs, which have not been previously associated with benzimidazole resistance in previous studies, were identified at low frequencies in C. oncophora and O. ostertagi from several herds. An E198Stop (GAA > TAA) SNP was identified in C. oncophora in two herds (CAN14 and CAN19) at the frequencies of 2.07% and 2.78%, respectively.A total of 43 Canadian beef cattle herds were assessed comprising herds from Alberta (19), Saskatchewan (7), Manitoba (2) and Ontario (15). Consistent with the species composition of these herds, as previously determined by ITS-2 rDNA nemabiome sequencing of the same samples, isotype-1 β-tubulin reads were identified in these samples, above the 200 reads per species threshold, for C. oncophora, O. ostertagi, O. bisonis, H. placei and T. axei. The frequencies of non-synonymous mutations at codons 167, 198 and 200 were determined for these five species . In the commercial bison herds, the F200Y (TTC > TAC) SNP was identified above 0.1% O. ostertagi  and O. bisonis , most of which were from Manitoba. The F167Y (TTC > TAC) SNP was not identified in any species from any herd. The F200L (TTC > TTA) SNP was identified in C. oncophora , O. ostertagi  and H. placei . The F167L (TTC > TTA) SNP was identified in O. ostertagi , H. placei  and T. axei .A total of 51 Canadian commercially farmed bison production groups from BC (5), Alberta (16), Saskatchewan (15) and Manitoba (15) were assessed. In addition, 55 individual animal samples from three Canadian national park conservation herds were assessed . Isotype-1 AC) nor F167Y (TTC > TAC) SNPs were identified in any species, in any animal. However, the F200L (TTC > TTA) SNP was identified in C. oncophora , O. ostertagi  and T. axei . The F167L (TTC > TTA) SNP was identified in C. oncophora , O. ostertagi , O. bisonis  and T. axei .In the conservation herds, neither the F200Y  SNP has been detected at low frequency in H. placei from Georgia, Florida and Arkansas, using a pyrosequence genotyping assay suggesting resistance is at the early stages of emergence in this parasite species  SNP in all of the six trichostrongylid nematode species identified  (AC) SNP in O. ostertagi, generally considered to be the most pathogenic GI nematode of cattle, from as many as 15 out of 34 of the stocker cattle tested   and 2. ONavarre, . These wet al., H. placei and to a lesser extent C. punctata, both of which are also pathogenic nematodes capable of causing clinical disease and production loss. Trichostrongylus axei is one of the less common trichostrongylid nematode species in cattle and was only found in sufficiently high numbers to test for the presence of benzimidazole-resistant SNPs in just five stocker cattle tested. The F200Y (TTC > TAC) SNP was found in T. axei from four out of the five animals for which this parasite species was tested and was as high as 57.43% in one of these animals (US5). This suggests that benzimidazole resistance may be more advanced for this parasite species in the USA. However, since T. axei comprised only 6.1% of the parasite population in this sample, this level of benzimidazole resistance would still not have been detected using the standard FECRT without coproculture, which does not discriminate between different trichostrongylid nematode species. It will be interesting to investigate if this parasite species becomes more predominant under the influence of selection if benzimidazole use increases in US beef cattle. The F167Y (TTC > TAC) SNP was also identified in both C. oncophora  and O. ostertagi , though it was only found at a frequency of <1%.The low frequency of benzimidazole resistance mutations that we have found in each parasite population means that resistance would not be phenotypically apparent and would not be detected by fecal egg count reduction test (FECRT) tests, particularly in mixed-species infections  SNP was only identified for a very small number of herds; C. punctata (one herd), C. pectinata (one herd) and H. placei (three herds) and was at very low frequency in each case (<4%) (AC) mutation was also found in C. punctata and H. placei in just one herd for each and at very low frequency in each case (<0.5%)  SNP was present at a very high frequency in each case (48.78–90.22%). The F167Y (TTC > TAC) SNP was also present at moderate to low frequencies in each of these cases (2.22–40.58%). Haemonchus contortus is primarily a sheep parasite, which can also infect cattle, and surveys of sheep have shown high levels of benzimidazole resistance throughout Brazil, including Sao Paulo State  , Table 1 (<0.5%) , Table 2β-tubulin gene were detected in the Canadian beef cattle herds by deep-amplicon sequencing using a sensitivity threshold of 0.1% frequency for each species in each population. Each of the samples used to generate DNA templates contain approximately 1000 L3 larvae in total, with C. oncophora and O. ostertagi comprising ~50% of the nematode populations each. Consequently, an average of ~500 L3 larvae, equating to ~1000 isotype-1 β-tubulin alleles, were screened for each species in each sample. Theoretically, this means that the lowest frequency that any allele can be present in any sample, corresponding to a single heterozygote, is 0.1%. Although we recognize that this could equate to lower than 0.1% frequency of sequence reads derived from a sample, due to the effect of amplification biases, we have used 0.1% as our operational detection threshold, to take a conservative approach. Nevertheless, we further explored the potential for O. ostertagi and C. oncophora being present below our 0.1% operational frequency threshold by determining the absolute number of each non-synonymous SNP at codons 167, 198 and 200 in the total dataset for each species when all samples were combined. For O. ostertagi, the F200Y (TTC > TAC) SNP was identified in 98 out of 276 852 sequences, and the F167Y (TTC > TAC) SNP in 23 out of 276 852 sequences; an overall prevalence of 0.035% and 0.008% across the 43 herds, respectively. For C. oncophora, the F200Y (TTC > TAC) SNP was identified in 212 out of 415 272 sequences, and the F167Y (TTC > TAC) SNP in 20 out of 415 272 sequences, giving them an overall frequency of 0.05% and 0.005% across the 43 herds, respectively. Consequently, it is possible that these benzimidazole resistance SNPs are present in the Canadian parasite populations at an extremely low frequency. However, at these very low frequencies, it is possible that these sequences were the result of contamination from other samples , or were more likely a result of PCR amplification or sequencing errors. More experimental work will need to be done to resolve this question.None of the previously described benzimidazole resistance-associated SNPs at codons 167, 198 and 200 of the isotype-1 AC), E198A (GAA > GCA) and F167Y (TTC > TAC) resistance mutations in the Canadian cattle herds suggests that the emergence of benzimidazole resistance is less likely than in the mid-southern USA. This is probably due to even lower use of this drug class in the Canadian beef cattle cow–calf sector over the last few decades than in the USA  benzimidazole resistance-associated SNP in O. ostertagi and O. bisonis in seven and one out of 50 commercial bison production groups, respectively. Although these were at relatively low frequency in most herds, the frequency was as high as 15.21% for O. ostertagi in one of the herds (AC) SNP was not seen above the 0.1% threshold frequency for O. ostertagi in any of 43 herds assessed (AC) SNP present in O. ostertagi, derived from Canadian commercial bison herds, is of concern. This parasite is highly pathogenic in bison and the emergence of resistance to benzimidazoles would be a major problem for the industry both in terms of animal welfare and production. Furthermore, O. ostertagi is the most economically important and pathogenic parasitic nematode of cattle in temperate regions. Consequently, the presence of benzimidazole-resistant O. ostertagi in the Canadian grazing ecosystem presents a risk of transmission into cattle  and F167L (TTC > TTA) SNPs were identified at low frequencies across a variety of species in a number of herds from all locations surveyed (AC) and F167Y (TTC > TAC) SNPs in nematodes and fungi , (E198 V GAA > GTA) and E198L (GAA > TTA) polymorphisms have clear functional evidence in fungi  and F167L (TTC > TTA), the F167L (TTC > TTA) polymorphism has been implicated in benzimidazole resistance in fungi  and F200Y (TTC > TAC) SNPs reduce the binding affinity of benzimidazoles by increasing the polarity in the binding pocket while the E198A (GAA > GCA) SNP and E198L (GAA > TTA) polymorphism are predicted to disrupt the formation of a key H-bond interaction  and F167L (TTC > TTA) SNPs could also affect benzimidazole binding affinity; however, further functional work in nematodes will be required to determine if this is the case.The F200L (TTC > TTTAA) of the isotype-1 β-tubulin gene was detected at a frequency of ~2% in two populations of C. oncophora from Canadian cattle . This mutation is predicted to result in a null allele and so a resistance phenotype. Null alleles have not been previously reported in the isotype-1 β-tubulin gene of trichostrongylid nematodes. This could be partly due to a bias in the approaches routinely used to screen for β-tubulin mutations which are unlikely to detect frameshift mutations or deletions. Alternatively, it could be due to a fitness cost to the loss of a functional copy of this gene, limiting the potential of null mutations to be selected to high frequency in the field. As with most previous studies, we have focused specifically on mutations previously shown to be associated with benzimidazole resistance. In future studies, it will be important to screen for additional mutations. Mining the data across the other codons in the amplified isotype-1 β-tubulin fragment in this study revealed premature stop codons in all species identified, from all regions sampled at codons 144, 153, 157, 158, 166, 172, 181, 183, 194, 208 (data not shown). In the majority of cases, these appeared at <1% frequency. The highest frequency was 18.5% at codon 183 in C. oncophora from farm CAN38. Such null alleles essentially remove the major drug target from the worm and so would be predicted to result in a resistance phenotype.A stop codon at codon 198 (GAA > In conclusion, this study provides a proof-of-concept of the power of deep-amplicon sequencing to screen for anthelmintic resistance mutations and the value of the information generated. The rapid progress in sequencing technologies coupled with our increasing understanding of the genetic basis of anthelmintic resistance will make such approaches increasingly feasible for both animal and human helminths. In the latter case, such approaches are urgently required to assess the risk and monitor for anthelmintic resistance emergence in mass drug administration programmes.


Groundnut varieties lacking FSD experience precocious seed germination during harvest imposing severe losses. Development of easy‐to‐use genetic markers enables early‐generation selection in different molecular breeding approaches. In this context, one recombinant inbred lines (RIL) population (ICGV 00350 × ICGV 97045) segregating for FSD was used for deploying QTL‐seq approach for identification of key genomic regions and candidate genes. Whole‐genome sequencing (WGS) data (87.93 Gbp) were generated and analysed for the dormant parent (ICGV 97045) and two DNA pools (dormant and nondormant). After analysis of resequenced data from the pooled samples with dormant parent (reference genome), we calculated delta‐SNP index and identified a total of 10,759 genomewide high‐confidence SNPs. Two candidate genomic regions spanning 2.4 Mb and 0.74 Mb on the B05 and A09 pseudomolecules, respectively, were identified controlling FSD. Two candidate genes—RING‐H2 finger protein and zeaxanthin epoxidase—were identified in these two regions, which significantly express during seed development and control abscisic acid (ABA) accumulation. QTL‐seq study presented here laid out development of a marker, GMFSD1, which was validated on a diverse panel and could be used in molecular breeding to improve dormancy in groundnut.The subspecies  Groundnut is an allotetraploid crop with a genome size of 2.7 Gbp and was domesticated in South and Central America from its wild ancestral species A. duranensis and A. ipaensis  has been used to accelerate dormancy in groundnut  and mitogen‐activated Protein Kinase Kinase 3 (MKK3) in barley  in wheat  or et al., et al.  can significantly shorten the breeding cycle time for the improvement of elite cultivars with desired traits  performed destructive method of phenotyping and showed clear trait segregation , 117 lines showed FSD between 2 and 3 days, 57 lines showed FSD up to 4–7, and 19 showed FSD up to 8–12 days. Interestingly, only 24 lines showed dormancy up to 13–15 days  used in this study had high phenotypic variability for FSD. The dormant parent ICGV 97045 was used as source for dormancy, which has FSD up to 15 days, whereas ICGV 00350 was used as nondormant parent which germinate within 48 hours. The previous genetic mapping effort using a subset (368) of large Fs Figure , S2. LatP < 0.05 , the dormant (D pool) and nondormant pool (ND pool). A total of 264.2 million reads for dormant parent (ICGV 97045), 215.5 million reads for dormant (D pool) and 223.7 million reads for nondormant (ND pool) were generated Tables . Highest5 Figure . Thus, a5 Figure . Of the 5 Figure , respectP value ≤ 0.01, ΔSNP index = −1). The negative sign of ΔSNP index indicates the presence of biasedness in the inheritance of parental genomes in the pools towards dormant parent or vice versa. The dormant pool had SNP index = 0 at all SNP positions indicating the contribution of alleles coming from the dormant parent, ICGV 97045 (Table viz Araip.S6QRU (encodes receptor‐like protein kinase), Araip.YHU92 , especially at the later stages of maturity when endogenous ABA accumulates  of B‐subgenome  of A‐genome which is appeared to be a hot spot for genes regulating seed development and ABA signalling , seven homologs of pentatricopeptide repeat (PPR) superfamily protein genes , two homologs of protein phosphatase 2C/2A family protein (Aradu.X74QT and Aradu.NF928), three homologs of GRAM domain protein/ABA‐responsive‐like , two homologs of heat shock proteins family genes (Aradu.YU6QF and Aradu.88GAJ) and one homolog for each serine carboxypeptidase 46 (Aradu.DFV35), Sec23/Sec24 protein transport family protein (Aradu.SXR6U), Ankyrin repeat family protein (Aradu.87ECD) and DDB1‐ and CUL4‐associated factor 8‐like (Aradu.U3RQV). Previously, these genes have been characterized to play important role in ABA biosynthesis/signalling, seed dormancy and germination , it provides the complete picture of transcriptomic shift for 22 different tissue including five important developmental stages of seed. Therefore, we surveyed the transcript abundance of these genes in the seed at different developmental stages. Interestingly, we found many of them identified as seed‐specific or highly expressed during development of groundnut seeds  on one gene g Figure . This geon Table . As the s Figure B.Based on the ΔSNP index, a total of 143 SNPs  technologies has greatly facilitated development of genome assembly, trait mapping and candidate gene discovery  and DArTseq platform  associated with the desired trait for the discovery of candidate genes. As a result, sequence comparison discovered distribution of 5,970 and 5,184 SNPs  on A‐ and B‐genome; among them only 767 and 1071 SNP were with ∆SNP index equivalent to −1. These highly significant SNPs  were mostly distributed among pseudomolecule—A09 (221 out of 767), A10 (356 out of 767) and B05 (897 out of 1071), suggesting plausible association of these three pseudomolecules with FSD trait.FSD/PHST/, et al.  that theSOUL heme‐binding family protein (Araip.X9V0W), RING‐H2 finger protein (Araip.YHU92), far1‐related sequence 6‐like (Araip.LKN71), ascorbate oxidase (Araip.K7Y13) and heavy metal transport/detoxification superfamily protein (Araip.2F1GS). Sequencing data suggested synonymous SNPs among genes encoding RING‐H2 finger protein, far1‐related sequence 6‐like and SOUL heme‐binding family protein, which are key regulator of developmental processes . Further, this genomic appeared as one of the key controllers of ABA biosynthesis in groundnut as this genomic region is home to several important genes which are known to participate in ABA signalling and control seed dormancy such as PPR superfamily protein gene, protein phosphatase 2C/2A family protein gene, GRAM domain protein/ABA‐responsive‐like and serine carboxypeptidase 46  is also substantially high in groundnut developing seeds, suggesting its role in ABA accumulation, which might also impact seed dormancy.Abscisic acid crosstalk with other hormones such as ethylene and gibberellic acids (GAs) is crucial during plant developmental processes including seed development and germination  and RING‐H2 finger protein (Araip.YHU92) might be the most relevant genes regulating preharvest sprouting caused due to lack of FSD in ground nut. Further, it would be interesting to know the genetic regulation of RING‐H2 finger protein transcription factor over ABA synthesis, as it could be plausible that this transcription factor might be binding to the promoter region of ZEP and ABA biosynthetic genes including NCED. Additionally, finding haplotypes associated with SNPs in these genes in the natural population(s) and breeding material and characterization of these gene(s) by genome editing tools will provide new insight towards the genetic control of FSD.Zeaxanthin epoxidase is one of the key enzymes involved in ABA biosynthesis, which catalyses the first step of ABA biosynthesis by epoxidation of zeaxanthin to violaxanthin  and are widely cultivated in the states of Tamil Nadu and Andhra Pradesh in India under both irrigated and rain‐fed condition. The nondormant parent, ICGV 00350, is drought‐tolerant genotype, but prone to sprout in the field, that is lacks fresh seed dormancy. In contrast, ICGV 97045 possesses fresh seed dormancy up to 15 days, and being used as donor parent for improving FSD in several varieties at ICRISAT. Our previous genetic mapping effort for FSD used a subset F2:3 population (368) . We followed then SSD for rest of the F2 lines and finally developed RIL population with 366 lines. For phenotyping, the noncured seed from freshly harvested mature pods (post rainy season) was used for the germination assay and enough care was taken to avoid test a damage while removing seeds from the pods. The maturity of pods was determined by the development of black coloration inside the shell as explained by Miller and Burns . Later, these libraries were used to generate 250 bases pair‐end reads by sequencing them on Illumina HiSeq platform with Reagent Kit v2 (500‐cycles).The WGS data were generated for three samples namely ICGV 97045 (dormant parent), dormant pool for fresh seed dormancy (D pool) and nondormant pool for non‐fresh seed dormancy (ND pool) were prepared and used for sequencing on Illumina HiSeq 2500 at Center of Excellence in Genomics and Systems Biology (CEGSB), ICRISAT, Hyderabad, as described in Pandey et al. . In briehttp://genome-e.ibrc.or.jp/home/bioinformatics-team/mutmap), developed at Iwate Biotechnology Research Center, Japan. For analysis, a reference tetraploid genome assembly for groundnut was constructed by using diploid genome assemblies of A. duranensis (A‐genome) and A. ipaensis (B‐genome) developed by Bertioli et al.  using Primer3  and 3 pmoles (0.15 μm) each of forward and reverse primers. The cycling conditions for PCR amplification were 94 °C‐4 min, 5 cycles of 94 °C‐20 s, 62 °C‐30 s, 72 °C‐30 s (extension), followed by 30–35 cycles of 94 °C‐20 s, 58 °C‐30 s, 72 °C‐30 s, final extension at 72 °C‐10 min.Polymerase chain reaction was carried out according to a previous report with minor modifications  that were used to create dormant and nondormant pool. Identified polymorphic markers were validated in a diverse panel consist of both FSD and non‐FSD accessions for their broader applicability.After PCR amplification, the alleles were scored on 2% agarose gel electrophoresis as present and absent. The markers were amplified using both dormant and nondormant parent parents used for development RIL population. Identified polymorphic markers were used to screen polymorphism between RILs FThe authors declare no conflict of interest.RKV, MKP and PJ conceived the idea. PJ, SSM and MTV developed and phenotyped RIL population. RK, MKV, MKP, YS and SSG performed the experiments. AWK performed the bioinformatics analysis. RK drafted the manuscript, and RKV and MKP finalized the MS.Figure S1 Schematic representation of QTL‐seq approach used for trait mapping in groundnut for fresh seed dormancy.Figure S2 Sequencing depth of the dormant parent ICGV 97045 Black line indicates the sliding window average of 2 Mb interval with 50 kb increment for SNP‐index.Figure S3 SNP‐index plots for 20 pseudomolecules dormant (D) pool with the dormant parent. Red lines indicate the sliding window average of 2 Mb interval with 50 kb increment for SNP‐index.Figure S4 SNP‐index plots for 20 pseudomolecules nondormant (ND) pool with the dormant parent.Figure S5 The Δ (SNP index) plot obtained by subtraction of dormant (D) pool SNP‐index from nondormant pool SNP‐index.Click here for additional data file.Table S1 FSD phenotyping details of RIL population.Click here for additional data file.Table S2 Details on the recombinant inbred lines selected for pooling and whole genome re‐sequencing.Click here for additional data file.Table S3 Details on whole genome re‐sequencing data generated on parental genotypes and pooled samples using Illumina 2500.Click here for additional data file.Table S4 SNP distribution on A‐ and B‐genome.Click here for additional data file.Table S5 List of important genes found on the QTL region on pseudomolecule B05 and hot spot region (114850050..115351249) of pseudomolecule A09 and their expression in groundnut seed.Click here for additional data file.Table S6 List of genes identified on the A09 hot spot region involved in the ABA biosynthesis and metabolism.Click here for additional data file.Table S7 List of selected markers designed and used for SNP validation assay.Click here for additional data file.