Genomic methods have proved to be important tools in the analysis of genetic diversity across the range of species and can be used to reveal processes underlying both short- and long-term evolutionary change. This study applied genomic methods to investigate population structure and inbreeding in a common UK dog breed, the Labrador Retriever.We found substantial within-breed genetic differentiation, which was associated with the role of the dog  and also with coat colour . There was little evidence of geographical differentiation. Highly differentiated genomic regions contained genes and markers associated with skull shape, suggesting that at least some of the differentiation is related to human-imposed selection on this trait. We also found that the total length of homozygous segments  was highly correlated with inbreeding coefficient.This study demonstrates that high-density genomic data can be used to quantify genetic diversity and to decipher demographic and selection processes. Analysis of genetically differentiated regions in the UK Labrador Retriever population suggests the possibility of human-imposed selection on craniofacial characteristics. The high correlation between estimates of inbreeding from genomic and pedigree data for this breed demonstrates that genomic approaches can be used to quantify inbreeding levels in dogs, which will be particularly useful where pedigree information is missing.The online version of this article (doi:10.1186/s12864-017-3933-x) contains supplementary material, which is available to authorized users. Over recent years, there has been increased concern about the genetic health of domesticated animal species and its relationship to levels of inbreeding and genetic diversity. This problem has been particularly pronounced in dogs, where founder effects at breed formation, extensive use of popular sires and intensive selection practices have had a negative impact on the genetic health of many breeds  and haveThe Labrador Retriever derives from working dogs of the Labrador/Newfoundland region of Canada that were brought in the nineteenth century to Britain by aristocrats and used as retrievers for hunting. Following an association between the Earl of Malmesbury and Duke of Buccleuch, a breeding program was established at the Scottish Buccleuch Kennels in the 1880s, which contributed to the foundation of the modern Labrador Retriever breed. The breed was formally recognized by the Kennel Club in 1903 (and in 1917 by the American Kennel Club). Labrador Retrievers are noted for their retrieving ability but also for their easy temperament, making them popular family pets. It is by a large margin the most populous Kennel Club-registered breed in the UK . Labrador Retrievers are also the most popular breed in many other developed countries, including the U.S.A., Australia, Canada, and Sweden. Labrador Retrievers are predisposed to a large number of heritable disorders , includiWhile traditional pedigree-based methods can be used to characterise breed attributes, the development of molecular genetic tools has provided additional resources with the potential for finer-scale analysis. While the uptake of molecular methods was initially slower in companion animals than in livestock, high-density single nucleotide polymorphism (SNP) arrays are available for the major companion animal species , providing a valuable tool for genetic diversity characterisation and for the inference of demographic and selection processes. If the costs of high-throughput sequencing continue to fall, this strategy may become the preferred alternative to commercial SNP arrays. The aim of this study was to apply high-density SNP data to elucidate population-level processes in the UK Labrador Retriever population.The animals in the study were Kennel Club-registered UK Labrador Retrievers born between 2002 and 2008. The samples were collected as part of a project on canine hip dysplasia , 10; allp < 8.0E-8, applying a Bonferroni correction), leaving 117,971 SNPs for further analysis.1008 DNA samples were genotyped using the Illumina canine high density beadchip containing 173,662 SNPs. Quality control was applied to assure both sample and marker quality. A sample call rate threshold of 95% was applied, removing 272 samples with low call rate and 8 females misidentified as males by Illumina Genome Studio software (i.e. with low heterozygosity on the X chromosome), leaving 728 animals in the final sample . Initial marker quality criteria were applied using Genome Studio. A total of 59,260 markers were discarded for low call rate (<98%), low reproducibility (GTS < 0.6), low or confounded signal (ABR mean < 0.3) and low minor allele frequency (MAF < 0.01). Further quality control on the markers was applied using PLINK , removinPhenotypic and lifestyle information was collected from dog owners using a questionnaire  , 14 for g, separating the individual from its furthest ancestor, where all 2g ancestors of the individual are known, = 3.58, mean equivalent generations (sum of (1/2)n terms over all known ancestors, where n is the number of generations separating the individual from the ancestor) = 5.58.Analysis of pedigree-based inbreeding was performed on a pedigree of 25,526 animals including the genotyped animals. Calculations of inbreeding coefficients were conducted using ENDOG software . The folNe, which predicts the rate of decrease in heterozygosity) was estimated as 1/(2 ∆F L) where F is the inbreeding coefficient, ∆F is the annual rate of inbreeding and L is the average generation interval (estimated as 4.5 years for the UK Labrador Retriever population E(r2) =nsidered  and to 2nsidered . Distancnsidered . Averagen = 728) . AssuminROH was defined as the total length of ROHs in the genome divided by 2,198,710,490, which is the number of base pairs covered by the CanineHD chip, according to CanFam2.0. Basic FROH statistics were calculated for the full dataset and for subgroups. χ2 tests were used to test for association between cluster assignment and a subset of overlapping ROH segments.Runs of homozygosity (ROH) in the full dataset were identified using PLINK  using thST [For each SNP marker across the genome, unbiased estimates of Weir and Cockerham’s FST  were calST  to compaST , 33 but ST values were averaged across sliding windows. In order to determine how best to define these windows , we compared the distribution of numbers of SNPs per window of fixed physical size to the distribution of physical sizes per window of fixed number of SNPs, where an odd number of SNPs was used to give equal numbers of markers on either side of the central SNP and the choice of numbers of SNPs per window  was based on previous studies using high-density SNP panels [ST values were averaged across sliding windows of 9, 13 and 17 SNPs . For each window size, the top 0.05% of FST windows were identified as differentiated regions [ST windows were grouped together in regions.To reduce random effects of individual SNPs with extreme allele frequency differences, individual FP panels , 34. TheP panels , thus in regions , 34. MarCanis familiaris reference list [LiftOver  was usednce list .In order to characterise the structure of the UK Labrador Retriever population, Principal Components and Structure analyses were performed. The first 250 principal components (PCs) from the PCA of the genotype data, chosen according to Kaiser’s criterion of inclusion of all components with eigenvalues greater than one , explainThe Structure analysis of one-third of the markers showed the same clustering results as those for the LD-pruned markers, thus we describe the former below. The log likelihood profile increased from K = 1 to 5, but was fairly flat for K ≥ 2 and delta K was maximized at K = 2 . The average membership coefficients of yellow and black dogs for the two clusters were similar  while the average membership coefficients of chocolate dogs for both clusters were lower (0.060 and 0.107).Ne was 55. Two modifications to the dataset were made to assess effects on the estimated Ne. If the oldest dogs in the pedigree  were removed, the estimate was 66. If individuals with inbreeding coefficient equal to 0  are removed, the estimate of Ne was 82.The relationship between the annual rate of inbreeding and time (birthdate) was used to estimate the inbreeding effective population size, based on the UK Labrador Retriever pedigree. Assuming a generation interval of 4.5 years and using the entire pedigree with birthdates, the estimate of Ne, based on the pattern of pairwise LD as a function of marker distances. LD shows the typical decreasing exponential relationship with marker distance  provides an Ne estimate for ~1 generation in the past; estimates ranged from 74 to 88, depending on whether mutation is accounted for and whether r2 was adjusted for sample size.For comparison with the pedigree-based estimates, high-density SNP data was also used to estimate nce Fig. , with avROH ranged from 0.067 to 0.56 . The Pearson correlation coefficient between the pedigree-based inbreeding coefficient (Fpedigree) and FROH  was 0.78  . The slope of the regression of FROH onto Fpedigree was 0.94 (s.e. 0.028). The characteristics of FROH within the role and coat colour groups were generally similar to those for the full dataset, although chocolate dogs and showdogs were somewhat distinct and both had higher values of FROH than the other groups. Mean values of FROH for the three coat colour groups were the following: 0.20 (se 1.2e-04) for black, 0.23 (5.7e-04) for chocolate and 0.21 (2.8e-04) for yellow; for the three role groups: 0.20 (1.3 e-04) for gundogs, 0.21 (2.0 e-04) for pets and 0.26 (1.6 e-04) for showdogs. The correlation coefficients between Fpedigree and FROH for the three coat colour groups were the following: 0.79 (black), 0.74 (chocolate) and 0.77 (yellow); for the three role groups: 0.76 (gundogs), 0.81 (pets) and 0.84 (showdogs). The slopes of the regression of FROH onto Fpedigree for the three coat colour groups were the following: 0.96 (se 0.036) for black, 0.89 (0.075) for chocolate and 0.97 (0.059) for yellow; for the three role groups: 0.99 (0.046) for gundogs, 0.97 (0.041) for pets and 0.87 (0.086) for showdogs.Pedigree-based inbreeding coefficients were compared with ROH characteristics for the population. Pedigree-based inbreeding coefficients for the population ranged from 0.0000795–0.337 (mean = 0.0702) Fig. . The numed) Fig.  while thELAVL2, which encodes a neural-specific RNA-binding protein). Other regions of high ROH coverage  were found on CFA5, 24, 25, 32 and 35.The longest ROH in the genome (~115 Mb) was found on CFA1 in the most inbred individual  in the study. ROHs covered by >400 (55%) individuals were found on CFA1 and CFA11. The ROHs that were shared by the largest number of dogs (581) were defined by SNPs on CFA11 , a region that does not include any annotated genes (the closest gene is ST) between the groupings highlighted in the population structure analyses. Having identified that K = 2 was the best estimate of cluster number, individuals were chosen for the differentiation analysis based on their membership coefficient for the two clusters from the K = 2 Structure analysis. Individuals were initially selected with extreme membership coefficients (> 0.90) and that were classified as either showdog or gundog; half-siblings were then removed, which left 115 “Cluster 1” dogs (gundogs) and 27 “Cluster 2” dogs (showdogs). In order to fairly compare Cluster 1 and Cluster 2, 27 Cluster 1 dogs with the highest membership coefficients were selected for differentiation analysis .We identified regions of the genome showing the greatest levels of differentiation  encompassed 20 regions on 12 chromosomes . The maximum FST-windows values for each window size were identified as the top 24 values: FST-windows-9 values >0.700, FST-windows-13 > 0.619, FST-windows values-17 > 0.602. Protein-coding genes found within 0.5 Mb of the highly differentiated regions are shown in Additional file p-value was “regulation of anatomical structure morphogenesis” (p = 1.79e-04), which showed ~6-fold enrichment.The top 0.05% of Fp = 0.009). This difference was still significant (p = 0.002) when the most highly inbred dog  than the 27 Cluster 1 dogs  described above (p < 0.001).There was not a strong correspondence between the differentiated regions and the ROHs. However, five of the 20 highly differentiated regions coincided with 12 “overlapping” ROHs, those found in multiple individuals (where the overlap involved >2 SNPs). For all 12 of these overlapping segments, there was a significant association between cluster membership  and ROH grouping, as defined by the alleles at individual SNPs , we investigated the differentiated regions for the presence of genes that could be related to these groupings. The regions did not include either of the two genes known to determine coat colour in Labrador Retrievers , suggesting that the stratification has not primarily been driven by selection for coat colour.The FRegarding the role groups, there are morphological features that are known to differ between gundogs and showdogs. Showdogs tend to have heavier builds, with shorter legs compared to gundogs. In terms of head shape, showdogs tend to have shorter muzzles and slightly wider heads , 52. ThePAFAH1B1 , MNT  and SMG6  [HIC1 gene, located just outside the differentiated region , functions as a growth regulator and has also been associated with MDS and craniofacial development. HIC1-deficient mice were shown to carry developmental abnormalities, including several craniofacial defects, acrania , exencephaly (brain located outside of the skull) and underdeveloped ear [HIC1 was also strongly associated with cleft palate in a genome-wide association study of humans [ALX3  and CDK14 , both of which have been associated with craniofacial development [The CFA9 region is of particular interest: it overlaps an orthologous chromosomal region on human chromosome 17p in which deletions of various sizes are associated with Miller-Dieker syndrome (MDS), a congenital malformation associated with brain and craniofacial disorders  . Deletio405,748) –58. In af humans . Other gBehavioural characteristics have also been shown to differ between gundogs and showdogs in the Labrador Retriever breed , 64. WhiOnly five of the 20 highly differentiated regions coincided with overlapping ROHs that were shared across individuals, suggesting that selection for cluster-related phenotypes is not strongly associated with extended homozygosity in the genome. However, for the overlapping ROHs that did coincide with differentiation regions, there was a significant association between cluster membership and ROH grouping, as defined by the alleles at individual SNPs, so it may be the case that some ROHs are related to selection for cluster-related phenotypes.pedigree and FROH (0.78), while some studies in cattle and pigs have shown lower correlations, for example, 0.015 in Brazilian Landrace pigs and 0.24 in Brazilian Large White pigs [ROH.This study demonstrates the great potential for using genomic data to estimate inbreeding levels in domesticated animal species. The concept of using regions of homozygosity to estimate inbreeding levels dates back to 1999  and it wite pigs ; 0.47 inite pigs . These cBoth pedigree- and genomic-based estimates of effective population size were somewhat lower than those published previously for Labrador Retrievers. Our pedigree-based estimate for the full dataset (54.5) was lower than that published by the KC , althouThis study demonstrated that the UK Labrador Retriever population showed evidence of genetic stratification into two groups, one of which was primarily associated with working dogs and the other with showdogs; pet dogs were a mixture of both types. Genetic differentiation was also seen between the three main coat colour types, with chocolate dogs primarily associated with the showdog grouping. Identification of the genomic regions showing the greatest differentiation between the two sub-populations provided evidence that this stratification is related to morphological differences between showdogs and working dogs. Specifically, the differentiated regions included several genes associated with craniofacial development, which may contribute to the differences in head shape between the two groups. This study also found that the total length of homozygous segments  was highly correlated with the pedigree-based inbreeding coefficient.Additional file 1:Questionnaire used to determine phenotypic and lifestyle information. (PDF 394 kb)Additional file 2: Figure S1.a. Distributions of physical size for windows of fixed number of SNPs . b. Distributions of number of SNPs for windows of fixed physical size . (PPTX 117 kb)Additional file 3:Annotation of highly-differentiated regions: description of protein-coding genes found within 0.5 Mb of highly-differentiated regions Table . (XLSX 1


Arachis accessions representing Arachis hypogaea botanical classes, A-, B-, and K- genome diploids, a synthetic amphidiploid, and a tetraploid wild species. RNASeq was performed on pools of three tissues, and de novo assembly was performed. Realignment of individual accession reads to transcripts of the cultivar OLin identified 306,820 biallelic SNPs. Among 10 naturally occurring tetraploid accessions, 40,382 unique homozygous SNPs were identified in 14,719 contigs. In eight diploid accessions, 291,115 unique SNPs were identified in 26,320 contigs. The average SNP rate among the 10 cultivated tetraploids was 0.5, and among eight diploids was 9.2 per 1000 bp. Diversity analysis indicated grouping of diploids according to genome classification, and cultivated tetraploids by subspecies. Cluster analysis of variants indicated that sequences of B genome species were the most similar to the tetraploids, and the next closest diploid accession belonged to the A genome species. A subset of 66 SNPs selected from the dataset was validated; of 782 SNP calls, 636 (81.32%) were confirmed using an allele-specific discrimination assay. We conclude that substantial genetic variability exists among wild species. Additionally, significant but lesser variability at the molecular level occurs among accessions of the cultivated species. This survey is the first to report significant SNP level diversity among transcripts, and may explain some of the phenotypic differences observed in germplasm surveys. Understanding SNP variants in the Arachis accessions will benefit in developing markers for selection.To test the hypothesis that the cultivated peanut species possesses almost no molecular variability, we sequenced a diverse panel of 22  Arachis hypogaea L.) is one of many polyploid species belonging to the genus Arachis, family Fabaceae, and is native to South America; many of these species come from a region including Brazil, Bolivia, and Paraguay , 831 (United States), and 582 (China) accessions  point toTechnology for DNA sequencing and SNP analysis has made great progress recently, both for high throughput and for low cost per sequence. Due to the ubiquity of SNPs, and the far greater power to identify polymorphisms than other types of marker analysis, sequencing is able to identify genetic diversity better than other marker types. RNASeq allows transcriptome profiling and SNP identification with high read depth at much lower cost than whole genome sequencing. Annotation of assembled RNASeq reads can help in understanding the function of a gene or a transcript. Annotations have been used in several crops for establishing genetic information where limited knowledge exists  to estimate number of genes in peanut, (c) to compare to the expected phylogenic relationships of the Arachis accessions, (d) to highlight SNPs specific to one accession or to a group of market types or to a group of different genome affiliations, and (e) to validate the SNPs obtained from the bioinformatics calls that can be used in a breeding program.The hypothesis of the current work is that, commensurate with the phenotypic differences observed in the field, there is actually a substantial amount of unrealized genetic diversity in peanut at the nucleotide level (both among the diploid and tetraploid species accessions). Although recent studies at the genome levels were carried out in two progenitor wild species . Accessions OLin, Tamrun OL07, Jupiter, and New Mexico Valencia C were sequenced on an Illumina GAIIx using 2 × 54 paired-end reads as reported previously . The GATK variant calling tool was used to identify SNPs and indels among these genotypes using default parameters for UnifiedGenotyper at a ploidy level of 2. Parameters of MQ  > 40.0, AF (Allele Frequency) > 0.10, and DP (Read Depth) > 50 were used to filter the SNP calls using vcftools  was performed using the File S3), including treatment with RNaseA during homogenization, and purified using the Qiagen DNAeasy miniprep kit . Sixty-six pairs of primers (File S4) were designed to perform validation of allele calls in the sequenced genotypes. For each putative SNP, two allele-specific forward primers, and one common reverse primer were designed .Genomic DNA was prepared from seed tissue of the 12 sequenced accessions  in a final volume of 10 µl containing 1× KASP Reaction Mix , 0.14 µl assay mix, and 10–20 ng of genomic DNA. The following cycling conditions were used: 15 min at 94°; 10 touchdown cycles of 20 sec at 94°, 60 sec at 65–57° (dropping 0.8° per cycle); and 26 cycles of 20 sec at 94°, 60 sec at 57°, and read at 37° for 5 sec. Fluorescence detection of the reaction was performed using a built-in scanner and the data were analyzed using the LightCycler 480 software .de novo the reads for each block and phase using parallelized runs. Haplotype information along with bam files were passed through readphaser to sort the reads within each block into phases based on HapCUT tables, and reassembled.To resolve homeologs in the peanut tetraploid reference sequence, we used the phasing approach. Genome-specific assemblies in tetraploid peanut using the phasing approach were generated by aligning OLin raw reads to the OLin reference transcriptome  using the BWA backtrack approach. Polymorphisms among the mapped reads were detected using the GATK software as it has been shown to perform well on RNAseq data  with defTo evaluate the resolution of the assemblies generated from each of these approaches, we mapped the raw reads back to each assembly. SNPs were called on each of these assemblies using GATK. Parameters used to evaluate assemblies were the number of heterozygous SNPs, homozygous SNPs, and number of SNPs per transcript.De novo assemblies and annotations described in this manuscript have been deposited at Figshare at the following URLs: https://dx.doi.org/10.6084/m9.figshare.3580650.v2, https://dx.doi.org/10.6084/m9.figshare.3580656.v2, https://dx.doi.org/10.6084/m9.figshare.3580659.v1, and https://dx.doi.org/10.6084/m9.figshare.3580662.v1.BAM files are deposited in SRA database under bioproject PRJNA248910: SRR1534396, SRR1535034, SRR1535035, SRR4039437, SRR4039359, SRR4039358, SRR4039357, SRR4039017, SRR4039016, SRR4039015, SRR4038966, SRR4038965, SRR4038285, SRR4037988, SRR4038281, SRR4038254, SRR4038252, SRR4038060, SRR4037987, SRR4037985, SRR4037986, and SRR4037959. A. hypogaea, including different subspecies, and originating from different continents . Annotation of the sequences from the consensus assembly identified numerous transcription factors. Transcription factors accounted for 4.4% of the 165,892 transcripts in the consensus assembly, and these were categorized based on their DNA-binding domain (File S2). Transcription factors were assigned to different groups; b-ZIP, MADS, MYB, AP2/ERF, and C2H2, were among the top five categories , New Mexico Valencia C (3451), and Tamrun OL07 (3923). Landraces had more SNPs relative to OLin, ranging from 7081 to 10,832 SNPs . SNP div to OLin .For the wild species, the number of SNPs relative to OLin was far higher: for A- genome diploid accessions, from 106,882 to 117,812 per accession; for B-genome diploids, from 96,241 to 109,797; for the K-genome diploids, 157,444 to 168,289; and for natural and synthetic amphidiploids, 14,340 and 87,574, respectively . OLin reA total of 40,382 unique SNPs was present among the cultivated accessions in 14,719 transcripts, and 291,115 unique SNPs were present among the diploid accessions in 26,320 transcripts . The aveA. magna GKSSc30097 compared to OLin was 32,430, more than the 18,092 unique SNPs between the tetraploid ancestor B- genome A. ipaënsis (GKPSSc30076) and OLin , and the synthetic amphidiploid A- and K- genome (TxAG-6), and the differences were reflected in the number of unique SNPs  was designed to validate the alleles called by the bioinformatic approach, and was tested on genomic DNA of 12 sequenced accessions (File S3). A total of 782 SNP calls (12 genotypes and 66 primers) was selected, including the calls from diploid and tetraploid accessions for validation using KASP technology. Genotyping of two diploid accessions with 66 primers confirmed 88.52% of the 122 SNP calls, while 10 tetraploid accessions confirmed 80.00% of the 660 SNP calls (File S3).Accuracy of SNP calls was demonstrated by validation of selected SNPs by KASP marker analysis. A subset of 66 primer pairs (Y axis) identified three groups: A-genome diploids as the first group; tetraploids, TxAG-6 (synthetic tetraploid) and K- genome as the second group; and B- genome diploids as the third group (X axis) separated TxAG-6, K-genome diploids, and the tetraploids from each other. Clustering of genotypes for tetraploids using PCA failed to reveal evidence of subspecies of hypogaea, even after the third PCA including 22 accessions. To distinguish subspecies of tetraploids, we employed the PCA approach on the same set of SNPs from the tetraploids separately, and it was possible to distinguish var hypogaea from var fastigiata  that contained >1 SNP, which were therefore good candidates for polymorphism phasing . Assuminde novo assembly approach, but had lesser representation of the transcriptome, as only 76–78% of the reads mapped back. Variant calls from phased assemblies indicated a sharp decrease in the number of heterozygous SNPs, and the number of contigs with multiple SNPs per transcript was lower compared to the de novo assembly . The raw reads aligning to the reference ranged from 84 to 89%, suggesting that the assembly used in this study had a good representation of the peanut transcriptomes. A total of 520 SNPs was identified by comparing the OLin transcriptome to the reference assembly; this may suggest the presence of gene copy number variation, call errors, or artifacts in the software used. The presence of SNPs when mapping reads back to the same reference has been cited previously (Medicago truncatula (1.96 SNPs per kilobase)  . Tetraploid accessions were used to confirm the SNP calls that could be eventually used in population studies. The overall validation success rate of 81.32% of 782 selected SNP sites was much higher than in a previous study by Another goal of this research was to identify SNP markers that could be useful in breeding programs. Of the 782 selected SNP calls tested, 81% were confirmed on the LightCycler 480, which is significantly better than results of previous studies in peanut . Collectively, these datasets have the potential for enabling SNP identification throughout the genome for any polymorphic gene of interest, thus making the tagging of specific genes with molecular markers a possibility.Annotations of the transcripts in the consensus assembly and the OLin assembly by de novo assembly suggest that there are about 25,000–31,500 unique transcripts in diploid and tetraploid Arachis roots, leaves, and developing pod tissues. This number could be a minimum value, as not all tissues were sampled. The number of transcripts in tetraploids could be twice that of diploids because of homeologous copies. Given the allo-tetraploid nature of the peanut, genes from both genomes are similar, and tools used in the study in general could not distinguish homeologous genes from each other. Consensus assemblies had more contigs than any other assembly by itself, which suggested that each genotype has a certain percentage of transcripts that could not be merged at a minimum sequence similarity threshold of 95%. This increase in the number of transcripts could be due to the larger differences among species/accessions used, or differences in expression of transcripts in samples. For tetraploids, the increase in number of transcripts in the consensus assembly can also be a result of the presence of homeologs. Consensus and individual assemblies from this study could benefit annotation of the genome for rare transcripts and gene expression studies.Results of de novo assembly parameters. Tetraploid SNP calls consisted of many apparently heterozygous state genotypes, and to reduce these heterozygous calls, we evaluated the phasing approach. We utilized the postassembly approach reported by de novo assembly. One way to estimate the reduction of homeolog collapse would be to observe the number of heterozygous variants upon mapping the reads back. Reduction in heterozygous SNP calls compared to the reference would be the first step for improving the assembly qualities.In the case of diploids, the success rate of SNP validation was greater than for tetraploid calls. Complexity of the tetraploid genome resulting from homeologous copies may have affected the outcomes of validation. Based on previous studies in complex polyploids, such as wheat  longer sequence reads, because shorter reads can affect the extension of contigs with the poor quality on the ends of reads; (b) higher read coverage to support the haplotypes, because lower read depth haplotypes could be dropped by the phasing based approach; and (c) using the genome sequence of diploid progenitor species to avoid collapse, and to obtain a better representation of transcripts.vs. homeologous SNPs for genetic mapping and QTL analysis, study of genome rearrangements after polyploidization, and expression bias among genes and genomes. Outcomes of this research will help increase of genomic resources in peanut, and benefit QTL mapping relevant for agronomic traits.We report the first survey of significant SNP level and transcript level diversity in a wide array of peanut germplasm. Highlighted untapped genetic variability among accessions may explain some of the phenotypic differences observed in germplasm surveys. Transcriptome analysis among cultivated accessions, and comparison to wild species will open many avenues for future research. Among these are relationships of cultivated tetraploid species to their diploid ancestors, evolutionary development of the cultigen, distinguishing of homologous


Selol is an organic selenitetriglyceride formulation containing selenium at +4 oxidation level that can be effectively incorporated into catalytic sites of of Se-dependent antioxidants. In the present study, the potential antioxidative and cytoprotective effects of Selol against sodium nitroprusside (SNP)-evoked oxidative/nitrosative stress were investigated in PC12 cells and the underlying mechanisms analyzed. Spectrophoto- and spectrofluorimetic methods as well as fluorescence microscopy were used in this study; mRNA expression was quantified by real-time PCR. Selol dose-dependently improved the survival and decreased the percentage of apoptosis in PC12 cells exposed to SNP. To determine the mechanism of this protective action, the effect of Selol on free radical generation and on antioxidative potential was evaluated. Selol offered significant protection against the elevation of reactive oxidative species (ROS) evoked by SNP. Moreover, this compound restored glutathione homeostasis by ameliorating the SNP-evoked disturbance of GSH/GSSG ratio. The protective effect exerted by Selol was associated with the prevention of SNP-mediated down-regulation of antioxidative enzymes: glutathione peroxidase (Se-GPx), glutathione reductase (GR), and thioredoxin reductase (TrxR). Finally, GPx inhibition significantly abolished the cytoprotective effect of Selol. In conclusion, these results suggest that Selol effectively protected PC12 cells against SNP-induced oxidative damage and death by adjusting free radical levels and antioxidant system, and suppressing apoptosis. Selol could be successfully used in the treatments of diseases that involve oxidative stress and resulting apoptosis. Oxidative stress is defined as an imbalance between the generation and detoxification of reactive oxygen species (ROS). Brain is particularly vulnerable to oxidative stress due to its high oxygen demand , high levels of iron and unsaturated fatty acids along with relatively inefficient antioxidative defense 4− 4− . Direct otein P) –16. Accuotein P) . Se defiotein P) –22. Se cotein P)  and in aotein P) .selenomethionine), Sec (selenocysteine), and MeSeCys (methylselenocysteine)  tetrazolium reduction assay revealed that Selol containing selenium at 5–400 μg/ml did not affect cell survival ]4− [− generation in human dopaminergic neuroblastoma cells (SH-SY5Y) [Oxidative stress is increasingly recognized as an important mechanism of neurodegenerative disorders and thus has become an attractive therapeutic target. PC12 cells serve as a common model for the investigation of neurotoxic effects of stress  as well (CN6)]4− . TreatmeSH-SY5Y) . SNP-evoSH-SY5Y) –45. In aSH-SY5Y) , 47. SNP•OH), (NO) (after oxidation to the NO+ form) and peroxynitrite (ONOO−). The reaction results the formation of thiyl radicals (GS•) that are, in turn, combining with other thiyl radicals to form glutathione disulfide [2+/H2O2) or amyloid β. The effect was mediated by increased GPx protein and activity [GPx1 and GPx4 [Txnrd1, GPx1, and Gsr is under the control of Nrf2 (nuclear factor-erythroid 2-related factor 2). Nrf2 promotes the regulation of the intracellular redox environment and cytoprotection via binding to the promoter sequences termed antioxidant responsive element (ARE) and up-regulating the transcription of ARE-containing antioxidant genes [Potential therapeutic approaches for the treatment of neurodegenerative disorders include Se-based interventions through incorporation of selenoamino acids into antioxidative enzymes . We provisulfide . We showisulfide . In addiactivity . In our activity . Howeveractivity . Moreoveand GPx4 . The expnt genes –60. Treant genes .GPx1 mRNA expression and in parallel increased Gsr and Txnrd1 mRNAs. We interpreted that the depletion of enzymatic activity of GR and TrxR after SNP exposure led to compensatory upregulation of their expression to cope with the stress. However, poor correlation between GPx activity and its mRNA expression in the presence of SNP may indicate that translational or posttranslational mechanism(s) might be involved in its regulation. Such post-translational modifications might involve not only enzymatic reactions, but also direct free radical-induced damage, such as S-nitrosylation. Such modulation occurs e.g. in the case of the thioredoxin—TrxR system [GPx1 mRNA may be the target of two stop codon-mediated modulation mechanisms: mRNA abundance control (probably via degradation) and a translational change (the meaning of UGA is modified from ‘stop’ to ‘selenocysteine’). Under standard conditions, the UGA stop codon is bypassed and selenocysteine is incorporated, but at conditions of selenium deficiency, this UGA sequence seems to revert to its standard meaning as a termination codon. This additionally leads to a reduction in GPx1 mRNA, possibly through a mechanism that ensures the removal of aberrant mRNAs that prematurely terminate transcription [GPx1 under condition of SNP that may facilitate the protein synthesis, and may further elevate its activity. Selol at the same time decreased the level of Gsr and Txnrd1 in SNP-treated cells. To further characterize the activation of antioxidant enzymes by Selol under condition of SNP, we used GPx inhibitor . Either SAu or SNP significantly reduced Se-GPx activity when administered alone, but SAu in combination with SNP did not further reduce Se-GPx activity. Selol prevented Se-GPx inhibition caused by SNP, but not by SAu or SNP in combination with SAu. This suggests that the effect of Selol might be linked to the antagonistic action against SNP/SNP-produced ROS, in accordance with our in vitro DCF data. However, blockage of Se access to the enzyme’s catalytic center by SAu could not be ruled out. Our results showed that treatment with SAu prevented the protective effect of Selol against SNP-induced apoptosis, again suggesting the involvement of Se-GPx in the protective effect of Selol against SNP-evoked toxicity. As SAu is also able to inhibit the activity of TrxR [In our study, SNP significantly decreased R system . Interescription –67. Toge of TrxR , this enIn summary, we propose a model whereby Selol modulates the impact of SNP on GPx and other antioxidant enzymes and prevents SNP-induced cell death. This successful in vitro application in a model of ROS-/RNS-mediated cytotoxicity suggests Selol as a promising compound in therapy of diseases related to oxidative/nitrosative damage and dopaminergic cells death. This potentially attractive mechanism deserves further in vivo clarification including in-depth analysis of Selol’s impact on other aspects of neuronal death mechanisms.


Ascaris lumbricoides) and roundworm species (Trichuris trichiura and Trichuris muris) and estimates of haplotype frequencies elucidates the genetic diversity and provides insights into epidemiology and parasite biology.High-resolution insight into parasitic infections and diet of past populations in Northern Europe and the Middle East (500 BC- 1700 AD) was obtained by pre-concentration of parasite eggs from ancient latrines and deposits followed by shotgun sequencing of DNA. Complementary profiling of parasite, vertebrate and plant DNA proved highly informative in the study of ancient health, human-animal interactions as well as animal and plant dietary components. Most prominent were finding of soil-borne parasites transmitted directly between humans, but also meat-borne parasites that require consumption of raw or undercooked fish and pork. The detection of parasites for which sheep, horse, dog, pig, and rodents serves as definitive hosts are clear markers of domestic and synanthropic animals living in closer proximity of the respective sites. Finally, the reconstruction of full mitochondrial parasite genomes from whipworm ( Ascaris lumbricoides and the human whipworm Trichuris trichiura are still found at high prevalence. These two soil-transmitted parasites have been widely identified in archaeological samples associated with human remains and coprolites in areas where they are no longer endemic . BrAscaris genus or the species, A. lumbricoides or A. suum, were reported as A. lumbricoides. The most abundant vertebrate taxa (species or genus) with more than 3 uniquely assigned reads are reported in Canis contains Canis, Canis lupus, Canis lupus familiaris and Canis lupus chanco; Equus contains Equus, Equus (ferus) przewalskii and Equus (ferus) caballus; Felis contains Felis, Felis silvestris, Felis catus and Felis margarita; Ovis contains Ovis and Ovis orientalis.Mitochondrial sequence hits are reported as ‘helminths’, which includes the ‘platyhelminthes’ and ‘nematoda’ phylum assignations, whereas ‘vertebrates’ includes ‘vertebrata’ sub-phylum assignations. Reads were mapped to sample level prior to reporting in Homo sapiens and related primates; Bos, Gallus and Sus genera–observed many samples and DNA extraction controls and known to be common laboratory contaminants [Meleagris gallopavo (Wild Turkey)–was observed in all DNA extraction controls and more so in highly degraded samples from the Middle East; Pelodiscus sinesis (Chinese Softshell Turtle), Phelsuma guimbeaui and Phyllodactylus unctus (both Geckos)–which were identified in many samples although with a maximum of 5 reads.The following taxa have been excluded from the reported vertebrate results: aminants ; MeleagrVitis contains reads assigned to Vitis genus and Vitis vinifera and Vitis rotundifolia species; Humulus contains Humulus lupulus; Prunus contains Prunus and Prunus maximowiczii; Pyrus contains Pyrus and Pyrus spinosa; Pisum contains Pisum sativum; Fagopyrum contains Fagopyrum and Fagopyrum esculentum; Rheum contains Rheum palpatum; Lupinus contains Lupinus luteus; Lotus contains Lotus japonicus; Vaccinium contains Vaccinum macrocarpon; Hordeum contains Hordeum and Hordeum vulgare. Species with reads mapping to more than 1 of 4 extraction controls and more than 2 hits in a single control are not reported in Plastid sequence hits are reported at the genus level, as the database in its current form is lacking many species. Genus level hits as shown in T. trichiura and T. muris and the Ascaris genus by the LCA algorithm, were extracted using seqtk version 1.0-r31 and the subseq command. Reads were re-mapped to the T. trichiura sequence from humans in Uganda (KT449826), the Ascaris sp. sequence from haplotype 07 (PUG3-1-H07) or the T. muris sequence (NC_028621) using bowtie2. Sam output was converted to bam format, merged to library level and sorted using command sort in samtools version 1.2 [coverage and depths [samtools mpileup, bcftools call (version 1.2) and vcfutils vcf2fq.Reads assigned to the species ence NC_0621 usingd depths . MitochoT. trichiura and T. muris were aligned together with all mitochondrial genome sequence of Trichuris genera publicly available at NCBI, as was done for the Ascaris genus sequences. Certain reference sequences were re-arranged to start with the cox1 gene. Alignment was performed with mafft v7[globalpair setting at 1000 iterations. A tree was built through 1000 bootstraps using the Neighbor Joining method and Jukes-Cantor nucleotide distance model in the CLC Sequence Viewer 7 program, which was also used for visualization. The consensus mitochondrial genome sequences were annotated using Mitos WebServer (http://mitos.bioinf.uni-leipzig.de/index.py) and made publicly available (Genbank accession number will be inserted here).The consensus sequences from  mafft v7, using tAncient DNA damage patterns were assessed using mapDamage v2 , for heli.e. values outside the main body of the data (<6* inter quartile range (IQR)) were used for the analysis. This threshold was also used to distinguish 'true haplotypes' from haplotypes that could be an effect of sequencing errors below.In order to identify potential SNPs, heterozygous bases were identified from pileup files of each mitochondrial genome assembly. Values for consensus coverage depend on the DNA sequencing error rate and the number of heterozygous bases of the genome analysed. However, as the number of heterozygous bases is markedly lower than the number of homozygous bases, the vast majority of data points will fall around the DNA sequencing error rate. Hence, with an error rate of 5% (sequencing and ancient DNA damage), values for consensus coverage for each position forms a distributions around the average of 95%. To distinguish potential SNPs from the background of the error rate, the average and spread of the consensus coverage data was calculated across each mitochondrial genome and only positions where the consensus coverage could be identified as outliers, Next, clusters of potential SNPs were characterized using a window size of the read length (100bp). Sam files were then parsed with respect to the SNP clusters identified: for each cluster, reads covering all potential SNPs of the given cluster were analysed, counting all different haplotypes at that particular SNP cluster. In order to avoid a potential bias from ancient DNA damage, the following bases did not count towards the final haplotype assessment: Thymidine bases within the first ten base pairs of a read where the consensus base was Cytosine and Adenine bases within the last ten bases of a read where the consensus base was Guanine.T. trichiura worm isolates which all yield a single haplotype (data not shown).To retain only high confidence clusters, clusters were excluded if they were covered by less than 10 reads or less than one fourth of the mean coverage of the mitochondrial genome assembly. Furthermore, to filter out haplotypes that could be a result of sequencing errors, low abundance haplotypes constituting less than the threshold percentage described above (<1–6*IQR) were discarded. After filtering, the estimated (minimum) number of haplotypes for each mitochondrial genome was characterized, defined as the highest number of haplotypes identified in at least two different clusters. The fraction of each haplotype presented in Ascaris spp. and Trichuris spp. eggs, typically associated with human faeces, of which 21 subsamples from 14 distinct locations were chosen for further processing , chicken  and pig (Sus), which were present in most samples and in some controls, a dataset was compiled and used in the subsequent presentation. This dataset contains 605,635 unique hits (721 hits per million sequenced reads) to helminths (phylum Nematoda and Platyhelminthes) and 549 unique hits (0.6 per million) to vertebrates as well as 28,141 unique hits to edible plants when mapped against a plastid reference database (33 per million).Samples apparently rich in organic material were collected from recent archaeological excavations and museum collections . Samplesocessing . The majA. lumbricoides, Fasciola hepatica, Parascaris univalens, Toxocara spp., were identified in 35–100 μm particle size fractions, whereas parasites excreting smaller eggs, i.e. Dicrocoelium dendriticum, Enterobius vermicularis, Taenia spp. and Trichuris spp., were mainly identified in the 22–35 μm particle fractions. However, few discrepancies were noted, most often identification of parasites with small eggs among the larger particles (35–100 μm fraction), resulting from insufficient washing of filters.Taxa assignments, as identified by morphological examination and DNA assignation, were initially compared for individual particle size fractions. In general, parasites which excrete large eggs such as Capillaria , Diphyllobothrium (2), Enterobius (1), Taenia (3) and Toxocara (2). In contrast, DNA provided species level identifications for 6 different genera missed by morphological identification: Dicrocoelium dendriticum (6 samples), Diphyllobothrium latum (1), Enterobius vermicularis (2), Fasciola hepatica (1), Parascaris univalens (2) and Taenia hydatigena (1), and additionally provided species assignation for two distinct Taenia species (T. solium and T. hydatigena) and three distinct Trichuris species . DNA from both helminth and it’s typical definitive host were identified in a number of cases: D. dendriticum and Ovis (sheep) (identified in 4 of 5 cases), F. hepatica and Ovis (sheep) (1/1), P. univalens and Equus (horse) (1/2), Taenia hydatigena and Canis (dog) (1/3), T. muris and rodents (Rattus rattus (Black rat)) (1/5). Ancient DNA damage profiles are shown for helminth identified reads  to their closest reference mitochondrial genomes for further analysis. This yielded 11 samples with more than 90% bases covered for A. lumbricoides (average 96.6%), 10 samples for T. trichiura (average 100%) and one sample for T. muris (98.4%) (A. lumbricoides genomes (range 5x-284x), 303x for T. trichiura genomes (range 30x-818x) and 7x for T. muris. In particular A. lumbricoides genome coverage was low in areas of low sequence complexity . This is possibly a result of: 1) the rigorous pre-processing of sequence data or 2) that these regions are conserved between closely related species, resulting in read assignation to family level or higher. In contrast, the T. trichiura mitochondrial genome coverage only exhibited one problematic region (i.e. AT repeats up/downstream of bp 3230).Reads assigned to  (98.4%)  Tables. A. lumbricoides sequences exhibited some very high (Lithuania—VLN5 = 3205) and very low  estimated values, while averaging 792 potential SNPs across all samples. In contrast, the number of potential SNPs in T. trichiura sequences ranged 297–457 when excluding the Zoo286 sample from Viborg, Denmark (1605 SNPs), averaging 492 potential SNPs across all samples.The number of potential SNPs, identified as positions with low consensus coverage, was estimated for all reconstructed mitochondrial genomes. T. trichiura exhibiting a more uniform distribution than A. lumbricoides, as well as a higher number of identified haplotypes 6.0 (ranging 5–7) compared to 4.0 (ranging 2–7) for A. lumbricoides. To rule out that the estimated number of potential SNPs and haplotypes were influenced by the number of eggs in the sample or the sequencing depth, the following linear regression analysis were performed showing no statistical correlations: the number of eggs and number of potential SNPs in a sample , the number of sequencing reads and number of potential SNPs , the number of potential SNPs and average depth of coverage  and the number of haplotypes and average depth of coverage .The number of potential haplotypes was then counted in all samples, based on clusters of potential SNPs separated by no more than 100 bp (read length). This provides a conservative estimate, as it is restricted to haplotypes of SNPs spanned by a single sequencing read. Various thresholds were implemented to distinguish 'true haplotypes' from those originating from potential sequencing errors or DNA damage. Frequencies of haplotypes were estimated, with A. lumbricoides genomes group together with haplotypes H03 and H07 in a cluster which elsewhere is designated cluster B[T. trichiura sequences grouped with reference sequence from human isolates from Uganda, distinctly different to the other T. trichiura cluster observed in humans from China.Individual haplotype sequences could not be called as a result of the short read length; hence consensus sequences were called to investigate phylogenetic affiliations . A. lumbcluster B. T. tricAscaris lumbricoides, Trichuris trichiura and Trichuris muris, elucidated the genetic diversity and provided insights into epidemiology and parasite biology.Using a novel approach of applying shotgun sequencing on ancient parasite eggs that have been purified by filtering, we have obtained a new and much more detailed insight into parasitic infections of human populations of the past. In addition, the complementary profiling of helminth, vertebrate and plant DNA proved highly informative in the study of ancient health, human-animal interactions as well as the animals and plants they exploited. Finally, the reconstruction of full mitochondrial parasite genomes from A. lumbricoides, E. vermicularis and T. trichiura) by faecal contamination of the immediate environment, but also human helminths with indirect transmission where fish (D. latum) and pig (T. solium) are required as intermediate host, indicating human consumption of raw or undercooked fish and pork. The identification of parasites for which humans are not the definitive host e.g. D. dendriticum (sheep definitive host), F. hepatica (sheep), P. univalens (horse), T. hydatigena (dog), T. muris (rodent) and T. suis (pig) indicates that faeces from these domestic and synantropic animals are present in the samples and that they were living in proximity to humans at the respective sites. Notably, we identified two species of Trichuris that do not infect humans, T. suis from pigs and T. muris from rodents, which most likely would have been wrongly assigned to T. trichiura using traditional morphological approaches [T. hydatigena eggs is interesting as it reveals the presence of a canid definitive host. Using classical methodology, such eggs would very likely have been assigned to human infection with T. solium, as also found in the present study, or T. saginata after consumption of pork or beef, respectively [Capillaria eggs (not in reference database) in one sample and Toxocara eggs in two samples that were not identified in the DNA analysis.We identified helminths which are directly transmitted between humans  indicating that pig faeces were present in these samples. Assuming co-detection of T. suis and A. suum in pigs, similar to the level observed for T. trichiura and A. lumbricoides in humans, would imply that A. suum was also be present at those sites and in those samples. This may explain why these two samples exhibited the highest number of potential SNPs in their consensus mitochondrial sequences.We acknowledge that the taxonomic status of plotypes ,32. In sT. trichiura (average of 6.0 across samples) compared to A. lumbricoides (4.0). We interpret this as a result of worm biology, particularly in relation to the reproductive potential of an individual worm. The effective worm population of an infection, hence the worm burden, is typically 1–15 worms for Ascaris infections [Trichuris infections [T. trichiura infections and may explain the higher number of haplotypes.Reconstructing complete mitochondrial genomes of ancient parasites is novel and analysis of the associated genetic variation, opens for a more detailed level of information regarding the transmission biology of parasites . As the fections  and 10–6fections . The larA. lumbricoides cannot be used to distinguish Ascaris from humans and pigs, we show mitochondrial sequence affiliation to cluster B for all samples, particularly close resemblance to haplotype 03 and 07. Although, H03 and H07 are identified among isolates from humans and pigs in Africa, South America, and Asia they are more frequently found among samples from China [A. lumbricoides from Northern Europe and Jordan (650–1700AD) are more closely related to worms in Asia than to worms in Africa, which is in contrast to what we see for T. trichiura as outlined below. However, comparison of frequencies of haplotypes between geographical regions has to be interpreted with some caution due to the low number of genomes generated in the current study and as the phylogeny of Ascaris based on mitochondrial DNA is complex  was very closely related to worms found in present day Uganda while it has significantly diverged from present day China. This surprising finding indicates very high degrees of genetic mixing between T. trichiura in Uganda and Northern Europe (1000–1700AD) which does not fully align with the hypothesis that T. trichiura was dispersed globally along with human migrations [T. trichiura should be considered.In sheer contrast, the  T. suis ,36. The grations ,9. FurthIdentification of DNA in modern faecal samples has previously been used as indicators of host diet ,38. VertBaleaenoptera physalus , Capreolus capreolus (roedeer) and Lepus europaeus (European hare) were identified. Large whales, including fin whales, are still recurrently stranding on beaches in Denmark, which would have provided easy access to large amounts of meat and fat, while catching live fin whales would have been a major accomplishment in the Viking-age. A comparable exploitation of dead whale by ancient cultures in the Arctic was recently suggested by us [Clupea harengus (Atlantic herring) and Gadus morhua (Atlantic cod)), while both fresh- (Abramis brama (common bream) and Anguilla anguilla (European eel)) and saltwater species ) were identified in Kampen. This corresponds with their respective locations, Copenhagen at the sea and Kampen on the banks of the river Ijssel, just upstream of its estuary.In particular, we show that vertebrate DNA from domesticated animals is more abundant compared to that from wildlife animals. Wildlife findings are interesting as they clearly indicate hunting and fishing practices, as shown in samples from Denmark (1018–1400 AD), where ed by us . Anothere.g. kitchen refuse and as part of animal faeces) or as a means to initiate biological degradation processes in the latrine , but only minimally as a result of natural deposition. The most abundant edible plants found in the samples from Northern Europe included cabbages (Brassica), buckwheat (Fagopyrum), wheat (Hordeum), sweet peas (Lathyrus), legumes (Lotus), peas (Pisum) and more seasonal foods herein mainly fruits: strawberries (Fragaria), plums/cherries (Prunus), pears (Pyrus), rhubarb (Rheum), and berries possibly cranberry/blueberry (Vaccinium). Notably, carrots and potatoes which are consumed in large quantities today, were not identified, in agreement with their gradual introduction in Northern Europe from the 16–1700s [Vitis), as often used in wine production, were identified in high concentration in the Netherlands and less so in Copenhagen, Denmark. In contrast, hop (Humulus), as often used in beer production, was identified in Odense and Copenhagen, Denmark and in Lithuania. Finally, tobacco (Nicotiana) was identified at the docks in Copenhagen (Gammel Strand), which was also the site of highest sample diversity, plant as well as helminth and vertebrate.Earlier studies have used ancient environmental DNA analysis to study past ecosystems and human activities ,39–42. T16–1700s ,44. The In conclusion, sequencing of ancient samples often involves a DNA target enrichment step in order to obtain sufficient concentrations of endogenous DNA for sequencing . As a noS1 Appendix(DOCX)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.S6 Table(XLSX)Click here for additional data file.


Gossypium spp.) is the world’s important natural textile fiber and oil crop. Upland cotton accounts for more than 90% of the world’s cotton production, however, modern upland cotton cultivars have narrow genetic diversity. The amounts of genomic sequencing and re-sequencing data released make it possible to develop a high-quality single nucleotide polymorphism (SNP) array for intraspecific genotyping detection in cotton.High-throughput genotyping platforms play important roles in plant genomic studies. Cotton  associated with 10 salt stress traits into 288 G. hirsutum accessions for genome-wide association studies (GWAS), and eight significant SNPs associated with three salt stress traits were detected.Here we report a high-throughput CottonSNP80K array and its utilization in genotyping detection in different cotton accessions. 82,259 SNP markers were selected from the re-sequencing data of 100 cotton cultivars and used to produce the array on the Illumina Infinium platform. 77,774 SNP loci (94.55%) were successfully synthesized on the array. Of them, 77,252 (99.33%) had call rates of >95% in 352 cotton accessions and 59,502 (76.51%) were polymorphic loci. Application tests using 22 cotton accessions with parent/FWe developed CottonSNP80K array with high polymorphism to distinguish upland cotton accessions. Diverse application tests indicated that the CottonSNP80K play important roles in germplasm genotyping, variety verification, functional genomics studies, and molecular breeding in cotton.The online version of this article (doi:10.1186/s12864-017-4062-2) contains supplementary material, which is available to authorized users. Gossypium spp.) is the largest source of renewable fiber in the world and is also a significant oil crop. Upland cotton accounts for more than 90% of the world crop. However, modern upland cotton cultivars have narrow genetic diversity, due to their development from the limited quantity of resources in the United States [http://cottondb.org/), and 100,290 microsatellites have been mined in the genome of G. hirsutum, where 77,996 SSR markers been developed [Cotton  are the most abundant DNA sequence variation present in plant genomes, with virtually unlimited, evenly distributed along the genome, bi-allelic and co-dominant characteristics. In cotton, several studies on genome-wide SNP marker development and utilization have been reported recently. Using BAC-end sequences of 12 ectively . By meanG. hirsutum germplasms, as well as five other species. Using the array, 188 RIL populations from an intra-specific cross (HS46 and MARCABUCAG8US-1-88) were genotyped, and 71 QTLs for fiber quality and yield traits were detected [G. hirsutum accessions using 11,975 quantified polymorphic SNPs in the CottonSNP63K SNP array [Compared to re-sequencing analysis, SNP arrays can produce large-scale genotyping data through one hybridization procedure at a relatively low cost. So far, there are nearly a hundred different genotyping techniques to meet different SNP array needs, with different sample sizes and numbers of SNP loci. In high-density SNP genotyping, Illumina (Infinium ® technology) and Affymetrix (Affymetrix GeneTitan ® technology) are two of the most widely used SNP genotyping platforms in a variety of species. In agricultural crops, a variety of SNP arrays using different SNP resources have been developed using appropriate platforms. For example, in rice, RiceSNP6K , RiceSNPdetected . RecentlNP array . These rG. raimondii and G. arboreum [G. hirsutum acc. TM-1 [G. barbadense cv. Xinhai21 and G. barbadense acc. 3–79 [G. hirsutum and G. barbadense containing 519 framework SSRs and 4,999,048 SNPs, was constructed [The availability of data on the whole-genome of four different cotton species, two diploid cotton species, arboreum , 21, thecc. TM-1 , 23, andcc. 3–79 , 25, madstructed . Furtherstructed . In thisstructed  and re-sstructed , we focuG. hirsutum with an average coverage of 5× in the genome [Based on the high quality reference sequence of the TM-1 genome  and re-se genome , we deveThe genome-wide CottonSNP80K array was used to genotype 352 cotton cultivars/accessions  had high call rates >95% in these tested accessions. Of them, 59,502 SNPs (76.51%) showed polymorphic loci, with MAFs > 0.05 for 57,071 loci (95.91%) and MAFs > 0.1 for 48,940 (82.25%), respectively. Compared to the Yellow River Valley and the introduced accessions, the Yangtze River Valley and Northwestern inland region accessions had more SNPs with MAFs > 0.1  mutant, far higher than the 1.28% polymorphic rate from SSR markers reported previously [To detect the distinguishability of this array, the polymorphic SNP loci of several mutants and their corresponding donors with similar genetic backgrounds were mined Table . The neaeviously . In gene1 combinations: (V1 × TM-1), (V3 × TM-1), and (V8 × TM-1). The results showed that the heterozygous rate increased by 14.07–19.91% in F1, compared with the corresponding parents. In the parents, 99.02%, 98.55% and 99.11% of the polymorphic SNP loci showed perfect heterozygous loci in the corresponding F1 , V × TM-1, G. hirsutum accessions, including 299 from modern improved Chinese cultivars/accessions and 13 from the introduced landraces. We further classified the group into ten clusters, clusterI to clusterX. We found that the classification of 299 upland cotton accessions from four different ecological areas , was irrelevant to their geographical distribution, but highly related to the introduced landraces. Several landraces, from the United States and other countries, were assigned to different groups, respectively. For example: Uganda3, Stoneville4, DPL16, King, Stoneville2B, DPL15, and Foster6 were grouped into clustersI-VI andX, respectively, indicating that these landraces have high genetic diversity and contributed to the development of different breeding populations in China during the improvement of modern varieties. Further, PCA analysis also agreed well with the clustering results in the phylogenetic tree  were used to compare the genetic diversity between wild cotton, semi-wild cotton and upland cotton accessions. A neighbor-joining tree was constructed using 57,071 polymorphic SNP markers with MAFs >0.05 Fig. . As a reree Fig. .Fig. 4Ph2). The results showed that the distance of LD decay in the outgroup was shorter than in other groups, implying that cultivated upland cotton, especially that from the northern group, may have been under higher selective pressure during evolution. Further, the accessions from the Yangtze River Valley, the Yellow River Valley and the Northwestern inland groups showed the same LD patterns, indicating the narrow genetic diversity of modern improved cultivars. On average, the distance of LD decay in the 332 cotton accessions was ~700 K  analysis was performed for cotton accessions of different origins using PLINK software. Pairwise LD was estimated using squared allele frequency correlations  [High-density SNP arrays have been developed for a number of economically important crops, such as rice –11, maizcc. TM-1 , and 1,3cessions , therefo. (2017)  detectedG. hirsutum and G. barbadense was greater than 30%, implying the array has potential for interspecific genotyping analysis.Upland cotton accounts for more than 90% of the world’s cotton production, however, modern upland cotton cultivars have narrow genetic diversity. The CottonSNP80K array is more suitable for upland cotton intraspecific genotyping detection, which can greatly overcome the narrow genetic background and low genetic diversity. Using the CottonSNP80K array, genotyping analysis was performed on 352 cotton accessions. Of the 77,774 SNPs on the array, 59,502 (76.51%) were polymorphic loci, with 95.91%  and 82.25%  showing MAFs greater than 0.05 and 0.1, respectively. In the CottonSNP63K project, these parameters were much lower, at 66.8% (MAF > 0.05) and 55.8% (MAF > 0.1) . We also1 combinations, several mutants and their corresponding donors with similar genetic backgrounds, and the replicated cotton varieties were used for genotyping analysis. In the replication analysis, technical DNA replicates showed perfect consistency (100%) and different levels of variability were detected with biological replication types. Considerable genetic variation existed in cotton lines of different origins, which might be related to the cross-pollination nature of upland cotton with a 10–15% natural hybridization rate. Similarly, this variation was also found in other array projects [To evaluate the reproducibility and the distinguishability of the CottonSNP80K array, three parent/Fprojects , 35. ThuGossypium spp.) is the world’s most important fiber crop plant. While most of the >50 Gossypium species are diploid (n = 13), five are allopolyploids (n = 26), originating from an interspecific hybridization event between A- and D-genome diploid species [G. tomentosum, G. mustelinum and G. darwinii) and two cultivated species, upland cotton (G. hirsutum) and sea-island cotton (G. barbadense). In addition, upland cotton consists of seven semi-wild races, G. hirsutum race punctatum, morrilli, yucatanense, richmondii, marie-galante, latifolium and palmeri, and the domesticated upland cotton cultivars, which constitute about 90% of the world cotton production. In this study, using the CottonSNP80K array, 5, 13 and 312 cotton accessions from wild species, G. hirsutum races and cultivated upland cotton accessions, respectively, as well as 2 sea-island cotton accessions, were selected for phylogenetic analysis. We found that 20 accessions from wild, semi-wild and sea-island cotton were clustered together, with closer genetic relationships between 2 sea-island cotton accessions and wild species, and more similarity between semi-wild species and cultivated upland cotton. This might be because these SNP loci originated from intraspecific upland cotton variation. We also found that all 312 G. hirsutum accessions were sub-clustered ten groups, but these groupings were not related to their geographical distribution. A similar analysis was reported in a previous study that used 81,675 SNPs from the SLAF-seq of 355 cotton accessions, and population structure analysis showed that the tested accessions could be separated into nine subpopulations with no obvious geographic relationship [G. hirsutum accessions, including 299 from modern improved Chinese cultivars/accessions and 13 from the introduced landraces, into ten clusters, clusterI to clusterX. We found that the different introduced landraces were clustered in different subgroups, such as King (in the 1920s), Foster6 (in 1933), Stoneville2B (in 1947), DPL15 (in 1950) and DPL16 (in 1970), which were successively introduced into China from the USA and were grouped into clusters IV, X, V, VI and III, respectively. In addition, Stoneville 4, which was introduced from the USA in 1934 was grouped into cluster II. Uganda3, which was introduced from Uganda in 1959, was grouped into clusterI. Junmian1 was developed from the filial generation of multi-parents involved in C1470, C3521, and 147φ, which was introduced from the former Soviet Union in 1960s, and was grouped to cluster IX. These results suggest that the introduced upland cotton landraces have a high genetic diversity, which provides rich genetic resources for breeding modern improved cotton varieties in China.Cotton  of world’s total land area are salt affected . Compareel Table , Fig. 6.% of worlbidopsis . Anotherbidopsis , droughtbidopsis , cold [4bidopsis  and oxidbidopsis . A reacte damage . Therefoe damage . Indepenbidopsis . In summWith reduced computational requirements for downstream data processing, high call frequency, low error rates and ease of use, high-density SNP arrays are an attractive genotyping tool, which are widely applied in diversity studies and high-resolution dissection of complex traits , varietyG. hirsutum, high-density SNP arrays of CottonSNP80K was developed. By genotyping 352 cotton cultivars/accessions, the CottonSNP80K showed excellent efficiency with an average call rate of 99.23%. Application tests using cotton accessions with parent/F1 combinations or with similar genetic backgrounds showed that this array had high genotyping accuracy, good repeatability, and wide applicability. Phylogenetic relationship and GWAS analysis of salt stress traits showed that the CottonSNP80K played important roles in variety verification, genetic relationship identification, and molecular breeding in cotton. Compared to the previously reported CottonSNP63K array, the CottonSNP80K array showed higher SNP density with genome-wide distribution, more accurate addressable loci, and higher upland cotton intraspecific polymorphism, which will be a powerful tool for genetics and molecular breeding by design in cotton.Based on reference sequence of the TM-1 genome and re-sequencing data from 100 different cultivars of G. hirsutum acc. TM-1 and G. barbadense cv. Hai 7124), duplicated DNA samples, parent/F1 combinations, several mutants and their corresponding donors with similar genetic background, G. hirsutum cv. Zhongmiansuo12 and G. barbadense cv. Junhai 1, were genotyped. To investigate the genetic diversity and phylogenetic relationship, a core collection of 332 cotton accessions were chosen  . Ultimat2) of alleles was calculated to measure LD in each upland cotton group level using PLINK V1.90, and LD blocks containing SNP loci associated with target traits were generated using the R software package “LDheatmap”.PLINK V1.90 software  was emplP value of 1/n (1.8 × 10−5) after the Bonferroni correction, which n represented the number of SNP markers. To get more reliable results, the SNPs with P values lower than 1 × 10−5 were selected as finally significant trait-associated SNPs. Candidate genes were identified within 500 Kb upstream or downstream of peak SNPs (the most significant SNPs). Manhattan plots were performed using the R software package “qqman”. GO analysis was implemented using AgriGO, and genes in “response to stimulate” or “response to stress” terms were selected as candidate genes.A total of 54,588 SNPs (MAF > 0.05) were used for the GWAS analysis of 288 upland cotton accessions. We carried out GWAS analysis with TASSEL 5.0, which uses a Mixed Linear Model (MLM) with Q + K model for association tests  with k =Additional file 1: Figure S1.The flow chart of developing the CottonSNP80K array. (TIFF 229 kb)Additional file 2: Table S1.Basic information and their phylogenetic classification on cotton materials in this study. (XLSX 25 kb)Additional file 3: Table S2.Phenotype data of 10 salt-stress traits in the 288 tested cotton accessions. (XLSX 53 kb)Additional file 4: Table S3.Gene information of SNPs associated with salt-tolerance related traits within 1 Mb regions. (XLSX 31 kb)Additional file 5: Table S4.Information on candidate genes response to stimulus and stress. (XLSX 12 kb)Additional file 6: Table S5.Information on SNP loci in the CottonSNP80K array. (XLSX 9317 kb)


Xylosandrus crassiusculus. In order to discover the source populations of this globally invasive species, track its movement around the world, and test biogeographical scenarios, we combined restriction site‐associated DNA sequencing (RADseq) with comprehensive sampling across the species native and introduced range. From 1,365 genotyped SNP loci across 198 individuals, we determined that in its native range, X. crassiusculus is comprised of a population in Southeast Asia that includes mainland China, Thailand, and Taiwan, and a second island population in Japan. North America and Central America were colonized from the island populations, while Africa and Oceania were colonized from the mainland Asia, and Hawaii was colonized by both populations. Populations of X. crassiusculus in North America were genetically diverse and highly structured, suggesting (1) numerous, repeated introductions; (2) introduction of a large founding population; or (3) both scenarios with higher than expected outcrossing. X. crassiusculus, other wood‐boring insects, and indeed many other pests with unusual genetic structure continue to spread around the world. We show that contemporary genetic methods offer a powerful tool for understanding and preventing pathways of future biosecurity threats.Each year new exotic species are transported across the world through global commerce, causing considerable economic and ecological damage. An important component of managing invasion pathways is to identify source populations. Some of the most widespread exotic species are haplodiploid ambrosia beetles. The ability to mate with siblings (inbreed) and their transportable food source (symbiotic fungus) have enabled them to colonize most of the world and become pests of plant nurseries, lumber, and forests. One of the fastest spreading ambrosia beetles is  In an era of global commerce, it is also increasingly critical for determining the sources and pathways of organisms that cause harm to humans and ecosystems Hulme, . Such inOur ability to infer the history of populations used to be restricted by the availability of molecular markers, which were historically difficult and expensive to develop Avise, . HoweverThe Xyleborini ambrosia beetles (Coleoptera: Curculionidae: Scolytinae) are some of the most widespread invasive insects Haack, . Their sMany extraordinarily invasive insects possess extraordinary genetic and biological features. For example, haplodiploidy and/or female‐biased rapid reproduction is disproportionately represented among globally invasive pests Ehrlich, . ExampleXylosandrus crassiusculus  or high ? And, given that this is a highly inbred and haplodiploid species, will RADseq uncover population genetic structure expected from studies of regularly reproducing invasive species?In order to discover the source populations of the invasive 22.1X. crassiusculus beetles from the species' native and introduced range for genotyping‐by‐sequencing . The size‐selected and purified sequencing library was further pooled with a similarly constructed library consisting of 96 bar‐coded samples and then loaded on the Illumina NextSeq500 high‐output flow cell for a shared 150‐cycle sequencing run. Unfiltered demultiplexed sequences were deposited in NCBI GenBank Short Read Archive (Accessions: SRR4181068‐265).Specimens with at least 160 ng of nondegraded DNA were prepared for double‐digest restriction site‐associated sequencing  toolkit for a Phred score of 20 across 90% of the read. Quality‐filtered reads were demultiplexed using the FASTX Toolkit “barcode splitter.” Barcodes and restriction site nucleotides were then trimmed from the beginning of the read using “FASTX trimmer” from the FASTX Toolkit. Due to variation in read length, all reads were trimmed to 71 bases. This maximized the number of reads recovered per individual because downstream processing required that all reads be the same length per individual. The resulting FASTA files for each individual were processed using STACKS v. 1.24 , there was a minimum of nine reads per individual at a locus (‐m 9), and a minimum allele frequency of 0.05 per locus (‐a 0.05). The additional parameter that only a single SNP should be called per a read was specified using –write_single_snp. We reduced the potential confounding effect of the fungal sequence carryover in two ways: by removing the mycangium as described above and bioinformatically. Catalog loci were compared to a draft genome of Ambrosiella roeperi . Loci that aligned to the fungus genome with 99% similarity across the entire read were excluded from SNP calling by specifying them as blacklisted loci (‐B) in STACKS “populations.”Single‐nucleotide polymorphism (SNP) genotypes were generated from the output of 2.4tab from the package adegenet  was assessed using the cophenetic correlation coefficient. First, the cophenetic distances for hierarchical clustering using each fusion method were calculated using the function cophenetic {stats}. Then, the cophenetic distances were correlated with the original distance matrix with statscor. Dendrograms built using all five methods preserved the original distance matrix similarly well (c > 0.92) with complete linkage and average linkage (UPGMA) performing the best (c = 0.98). Similar hierarchical relationships were observed using complete linkage and average linkage; therefore, the space‐dilating complete linkage method was used for downstream analyses. Multiscale bootstrap resampling with 10,000 replicates was performed with pvclust package function pvclust to calculate p‐values for hierarchical clusters.Hierarchical clustering was used to associate nonnative beetles with native beetle populations and to determine the relationships between and among groups. This clustering method was deemed more suitable than nonhierarchical clustering because population substructure is likely when sampling across a global metapopulation. All hierarchical clustering was performed using K = 1 through K = 16, allowing for admixture. Change in log‐likelihood scores between K  and locations was tested by hierarchical analysis of molecular variance (AMOVA) in a‐score, which is the difference between observed discrimination and random discrimination, was calculated using adegeneta.score. Additional assessment of the optimum number of PCs to retain for the DAPC was performed through cross‐validation by subsetting the data into training and validation sets using xvalDapc. After the number of principal components was determined, the DAPC was performed using for a specified number of clusters  using the function dapc, and the probability of individual membership to each cluster was visualized using compoplot.Group membership probabilities for the clusters identified in hierarchical cluster analysis and for geographic location were determined using a Discriminant Analysis of Principal Components (DAPC), which has no model assumptions  was sequenced per individual, and 2,29,976 putative loci were identified. Mapping these putative loci to the fungal symbiont genome Ambrosiella roeperi resulted in the removal of 16% of loci suggesting that dissection and in silico removal of fungal symbiont reads were successful. Only 4,807 (2.5%) of the remaining putative loci were shared among 90% of the 198 beetles sequenced and had a minimum of nine reads per individual. Among the shared loci, 28.4% contained single‐nucleotide polymorphisms (SNPs or variant sites). Although 3,844 SNPs were identified, many of these SNPs were in the same locus (read), therefore only one SNP per locus was considered for genotyping which resulted in a total of 1,365 SNPs. Of the genome sampled here using ddRADseq 1.1% contained variation when all SNPs (variant sites) across all shared loci are considered, and 0.3% when only genotyped SNPs are considered.Using ddRADseq, we successfully sequenced over 11 billion bases of DNA for SNP discovery and genotyping in FIS (0.84) were high for the 1,365 genotyped SNPs (variant sites) and at most geographic locations  and inbreeding coefficient 3.2X. crassiusculus is comprised of at least two separate populations, sampled here: one in Southeast Asia including the mainland China, Thailand, and Taiwan, and one on most Japanese islands  primary clusters are observed  and between locations within subclusters . These populations are characterized by negative FIS values, low numbers of polymorphic sites (<3), and high proportion of heterozygous sites relative to SNPs  numerous, repeated introductions that blur between‐group differences, or (2) introduction of a large founding population that retained its genetic variation, or (3) any of the above scenarios with a more than expected degree of outcrossing. All three scenarios are also mutually compatible.Populations of X. crassiusculus especially at most U.S. locations given the documented continuous invasion of nonnative Xyleborini species through coastal areas , accession numbers SRR4181068‐265 under BioProject PRJNA342041. Analyses were performed using publicly available scripts and packages described in the methods.


Mangifera indica L.) is called “king of fruits” due to its sweetness, richness of taste, diversity, large production volume and a variety of end usage. Despite its huge economic importance genomic resources in mango are scarce and genetics of useful horticultural traits are poorly understood. Here we generated deep coverage leaf RNA sequence data for mango parental varieties ‘Neelam’, ‘Dashehari’ and their hybrid ‘Amrapali’ using next generation sequencing technologies. De-novo sequence assembly generated 27,528, 20,771 and 35,182 transcripts for the three genotypes, respectively. The transcripts were further assembled into a non-redundant set of 70,057 unigenes that were used for SSR and SNP identification and annotation. Total 5,465 SSR loci were identified in 4,912 unigenes with 288 type I SSR (n ≥ 20 bp). One hundred type I SSR markers were randomly selected of which 43 yielded PCR amplicons of expected size in the first round of validation and were designated as validated genic-SSR markers. Further, 22,306 SNPs were identified by aligning high quality sequence reads of the three mango varieties to the reference unigene set, revealing significantly enhanced SNP heterozygosity in the hybrid Amrapali. The present study on leaf RNA sequencing of mango varieties and their hybrid provides useful genomic resource for genetic improvement of mango.Mango ( Mangifera indica L.) is an evergreen dicotyledonous angiosperm. Although several tetraploid Mangifera species are reported, cultivated mango is a diploid tree (2n = 40) with a relatively small genome size of 439 Mbp [Mangifera belongs to order Sapindales of the family Anacardiaceae [Mango . Quantification of RNA was done using NanoDrop spectrophotometer and quality check for DNA contamination was done by electrophoresis in 1% denaturing agarose gel. To assess RNA integrity the samples were run on RNA 6000 Pico chip Bioanalyzer (Agilent). The transcriptome library was prepared after quantification and quality check of the Poly(A) RNA using SOLiD total RNA Seq kit for ‘Neelam’ and ‘Dashehari’ and Illumina MiSeq for ‘Amrapali’, respectively.de novo assembly approach using Velvet-Oasis software, which have been developed for short read assembly of transcriptome data and are based on de-Brujin graph algorithm [High quality sequence reads of cDNA libraries were used to generate transcript shotgun assembly (TSA) contigs. Transcripts for ‘Neelam’ and ‘Dashehari’ were assembled via lgorithm , 34 Longlgorithm . The asslgorithm  with defThe final assembled unigene contigs were used for mining of genomic-SSRs using MISA  and SSR Taq DNA polymerase (0.75 U) in a final reaction volume of 15 μl. The PCR reaction profile was denaturation at 94°C for 5 min followed by 35 cycles of 94°C for 1 min, 55°C for 1 min, 72°C for 1 min and finally, 72°C for a final extension of 7 min. Re-screening of primers that did not amplify at these conditions was done by decreasing the annealing temperature sequentially by 1°C, and for the primers producing multiple bands, by increasing the annealing temperature by 1°C [™ 5500 . The SSR profiles were scored manually, each allele was scored as present (1) or absent (0) for each of the SSR loci. The SSR markers giving consistent expected size products only (100–250 bp) were used for further analysis of variation.Genomic DNA was isolated from leaf samples of eight genotypes using CTAB method , quantife by 1°C . The optFor the annotation of TSA unigenes, BLAST algorithm  was usedKEGG Automatic Annotation Server (KAAS)  was usedThe unigene set was used as reference for mapping of high quality filtered sequence reads from all the three varieties using BWA with default parameters . To tracA total of 60,359,815, 58,212,961 and 4,853,226 raw sequence reads were generated for ‘Neelam’ (mango_N), ‘Dashehari’ (mango_D) and ‘Amrapali’ (mango_A), respectively using two runs of SOLiD sequencing with average read length of 50 bp (mango_N and mango_D) and one run of Illumina Miseq 2x250 (mango_A) with average read length of 250 bp. After quality check, adapter trimming and removal of low quality reads, 53,617,132, 47,818,267 and 4,313,270 high quality reads were retained for ‘Neelam’, ‘Dashehari’ and ‘Amrapali’, respectively. We performed three separate de-novo assemblies using Velvet-Oases assembly pipeline and CLC Genomic workbench 6.5.1 for the SOLiD and Miseq data, respectively. The assembly resulted in 27,528, 20,771 and 35,182 transcripts for mango_N, mango_D and mango_A with transcript N50 values of 557 bp, 451 bp and 591 bp and largest transcript size of 3,129 bp, 2,958 bp and 5,891 bp, respectively .TSA contigs of individual genotypes were further assembled into 70,057 non-redundant unigenes set, which was used as reference for the identification of genic-SSR and SNP . The meaRaw sequenced data described in this paper can be found in the Sequence Read Archive (SRA) database of the NCBI with SRA Accession number SRR1298995, SRR1297075, SRR1956775 under BioProject Number PRJNA193591, PRJNA193588, PRJNA279829 with TSA Accession number GBVX00000000, GBVW00000000, GEEEC00000000 for ‘Dashehari’, ‘Neelam’ and ‘Amrapali’, respectively.Citrus sinensis (28.76%), followed by Citrus clementina (17.43%), Theobroma cacao (6.8%), Jatropha curcas (4.44%) and Vitis vinifera (4.19%)  of the unigenes showed significant similarity to known proteins and were functionally annotated while 30,259 (43.2%) unigenes showed no significant hits. Mango unigenes showed the highest similarity with  (4.19%) . This rea indica .Gene ontology (GO) terms were assigned successfully to 26,001 of the BLASTX annotated unigenes using BLAST2GO, which were broadly categorized into three main categories; biological process (BP), cellular component (CC) and molecular function (MF) and were further classified into 47 functional groups . The mosTotal 8,958 unigenes were assigned Enzyme Commission (EC) numbers; the highly represented enzyme classes were hydrolases  transferases  and oxidoreductases . The large number of unigenes under these three major enzyme groups indicates expression of genes related to secondary metabolite biosynthesis pathway in the mango leaves , 53.KASS server was used for pathway mapping and orthologous gene assignment for the assembled unigenes, and we mapped 4,977 unigenes to 349 different KEGG pathways. The most represented pathway in terms of total number of hits from the transcript data were “ribosome”, “biosynthesis of amino acids”, “carbon metabolism”, “spliceosome”, “purine metabolism” and RNA transport which is quite similar to the results with the transcriptome of mango variety ‘Kent’ which showed the maximum transcripts representations for “biosynthesis of amino acids”, “ribosome” and “RNA transport” , but it A total of 5,465 SSR loci of different categories  were identified in 4,912 contigs, representing 7.01% of the total 70,057 unigenes. We excluded mononucleotide repeats, complex SSR and those having total lengths of <10 bp because SSR marker based mono-nucleotide repeats are not reproducible due to recombination slippage and PCR amplification problems, whereas complex SSRs show the least polymorphism . This exPCR primers were designed successfully from the unique sequences flanking 1,069 SSR loci for the development of genic-SSR markers and were designated MSSR1 to MSSR1069 (M = Mango). Primers could not be designed for the remaining 4,396 SSR loci because their flanking sequences were either too short or the nature of sequence did not fulfill our criteria for primer design. Of the 1,069 SSR markers, 227 type I SSR loci (n ≥ 20 bp)  were filThe non-redundant set of 70,057 transcripts was used as a reference for mapping of high quality reads from parents (‘Neelam’ and ‘Dashehari’) and hybrid  and total 42,984 SNP positions were identified with full details saved as text file. In-house shell scripts was written which reads the transcript name and its SNP position from this text file, and extracts all the mapping reads information at each SNP position, including the full read name, base call in the mapped read at SNP position and position of the SNP in the reads as well as in the reference transcript. The results were tabulated in an Excel sheet, which included variety wise information on heterozygosity at each SNP position. This helped identify level of heterozygosity in the parents and hybrid ‘Amrapali’ using stringent criteria. After quality filtration we identified 22,306 SNPs in 10,571 transcripts common to all the three genotypes with an average of 2.1 SNPs and a range of 1–16 SNPs per contig .vis-a-vis in its parental lines ‘Neelam’ and ‘Dashehari’ at the same position. ‘Amrapali’ showed 6,831 novel heterozygous SNP loci that were homozygous for contrasting alleles in the two parental varieties, which could be the basis of its superior performance. In addition, ‘Amrapali’ has maintained heterozygosity at 7,561 SNP loci that are heterozygous either in ‘Neelam’  or ‘Dashehari’  or both the parents . On the other hand there were 6,760 SNP loci, which were heterozygous in either one or both the parents but became homozygous in ‘Amrapali’ (We classified the SNPs into two categories: i) homozygous within a variety and ii) heterozygous within a variety, and found that in ‘Neelam’ the proportion of heterozygous SNPs was 49.3% while in ‘Dashehari’ it was only 30.19%. Interestingly, in their hybrid Amrapali the heterozygosity level increased to 64.5% . Furthermrapali’ . The losIn this study we have presented development and validation of a comprehensive set of genic-SSR and SNP markers in mango by deep sequencing of leaf transcriptome using next generation sequencing technology. Considering the need to generate large number of molecular markers for mango breeding applications, a set of 288 type I genic-SSR markers were developed, and a subset of these was validated successfully for robust amplification in eight mango varieties. These markers can be used for diversity analysis and genetic mapping of useful horticultural traits in mango. In addition, an analysis of 22,306 SNP loci in hybrid mango clone ‘Amrapali’ and its parental lines ‘Neelam’ and ‘Dashehari’ revealed substantially higher heterozygosity in ‘Amrapali’. Among the parental lines ‘Neelam’ showed significantly higher level of heterozygosity than ‘Dashehari’. The identified genic-SNPs provide much-needed resource for the development of high density, cost-effective genotyping assays which would greatly help the mango breeding programs and genome wide association studies for the yield and quality traits in mango.S1 FigCitrus sinensis (28.76%), Citrus clementina (17.43%), Theobroma cacao (6.8%), Jatropha curcas (4.44%) and Vitis vinifera (4.19%).Mango transcripts showed highest similarity with (TIF)Click here for additional data file.S2 FigThe most abundant SSRs were with five reiterations, the frequency of a given SSR structure and the number of repeat units in it showed an inverse relationship.(TIF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.