Although the primary objective of forensic DNA analyses of unidentified human remains is positive identification, cases involving historical or archaeological skeletal remains often lack reference samples for comparison. Massively parallel sequencing (MPS) offers an opportunity to provide biometric data in such cases, and these cases provide valuable data on the feasibility of applying MPS for characterization of modern forensic casework samples. In this study, MPS was used to characterize 140-year-old human skeletal remains discovered at a historical site in Deadwood, South Dakota, United States. The remains were in an unmarked grave and there were no records or other metadata available regarding the identity of the individual. Due to the high throughput of MPS, a variety of biometric markers could be typed using a single sample.Using MPS and suitable forensic genetic markers, more relevant information could be obtained from a limited quantity and quality sample. Results were obtained for 25/26 Y-STRs, 34/34 Y SNPs, 166/166 ancestry-informative SNPs, 24/24 phenotype-informative SNPs, 102/102 human identity SNPs, 27/29 autosomal STRs (plus amelogenin), and 4/8 X-STRs (as well as ten regions of mtDNA). The Y-chromosome  and mtDNA profiles of the unidentified skeletal remains are consistent with the R1b and H1 haplogroups, respectively. Both of these haplogroups are the most common haplogroups in Western Europe. Ancestry-informative SNP analysis also supported European ancestry. The genetic results are consistent with anthropological findings that the remains belong to a male of European ancestry (Caucasian). Phenotype-informative SNP data provided strong support that the individual had light red hair and brown eyes.This study is among the first to genetically characterize historical human remains with forensic genetic marker kits specifically designed for MPS. The outcome demonstrates that substantially more genetic information can be obtained from the same initial quantities of DNA as that of current CE-based analyses.The online version of this article (doi:10.1186/s12864-016-3087-2) contains supplementary material, which is available to authorized users. The paramount goal of forensic DNA testing of human skeletal remains is identification of the unknown individual. A variety of genetic markers can be used to achieve identification, including highly polymorphic autosomal short tandem repeat (STR) loci and lineage markers . However, reference samples must be available for comparison for these markers to be informative. In mass disasters, missing persons cases, or cases involving historical/archaeological remains, sometimes there are no clues as to the person’s potential identity and/or there are no associations made with a reference sample or reference pedigree via a database search . In suchMassively parallel sequencing (MPS) of ancestry- and phenotype-informative SNPs, with its expanded capacity for marker typing, offers the ability to develop investigative leads in such cases –16. ThusIn 1874, the discovery of gold in the Black Hills of South Dakota set off one of the last great gold rushes in America. In 1876, miners moved to the area and formally established the city of Deadwood, now a U.S. historical landmark. Deadwood’s original cemetery, Ingleside, was located near the town’s core business district and contained approximately 100 burials . In 1878, the individuals interred there were relocated to the hills above Deadwood, and Mount Moriah Cemetery was established.th century would simply have had unhealthy teeth extracted  were completed as described in –36. Inpuwww.yhrd.org). A PCA plot of ancestry-informative SNP data was generated with the Illumina® ForenSeq™ Universal Analysis Software. Mitochondrial DNA sequence alignment was performed with the mitoSAVE workbook [http://haplogrep.uibk.ac.at/) [http://hirisplex.erasmusmc.nl) [30X and 10X coverage were set as minimum detection thresholds for the autosomal markers and mtDNA typed by MPS in this study, respectively. The Y haplogroup was determined using the ancestry feature and metapopulation tool of the Y-STR haplotype reference database YHRD  . Phenotyusmc.nl) , 10.DNA concentrations recovered from the right femur powder fractions ranged from 0.0147–0.3350 ng/μl for elution #1 and 0–0.0579 ng/μl for elution #2, respectively. The elution volume for each DNA extract was 30 μl, and the total DNA recovered per elution is reported in Table A variety of STR and SNP markers were analyzed via CE and MPS. No DNA was detected in any of the negative controls and reagent blanks, and positive controls yielded the correct type for all analyses.Y-STR typing results varied among the samples Tables  and 3. AThe composite 17-locus Y-STR profile generated with AmpFlSTR® Yfiler™ and the additional Y STR loci from the Illumina® ForenSeq™ DNA Signature Prep Kit is consistent with the R1b haplogroup. R1b is the most common Y haplogroup in Western Europe, spanning 80 % of the population in Ireland, western Wales, the Scottish Highlands, the Atlantic fringe of France, Catalonia, and the Basque country. It also is common around the Caucasus and in Anatolia, in parts of Russia, and in Central and South Asia –45.In addition to Y-STR data, a consensus Y-SNP profile was compiled using data from three different bone powder fractions from the Deadwood unidentified skeletal remains. All 34 upper clade Y-SNPs in the HID-Ion AmpliSeq™ Identity Panel provided typing results [Additional file Ancestry-informative SNP results were obtained for 51 of the 54 SNP markers amplified via the Illumina® ForenSeq™ DNA Signature Prep Kit, and for all 165 markers tested using the HID-Ion AmpliSeq™ Ancestry Panel. Depth of coverage ranged from 31x to 2240x (170 ± 107) and 53x to 1190x (379 ± 243), respectively. Fifty-three of the ancestry-informative SNPs in the Illumina® ForenSeq™ kit are included in the HID-Ion AmpliSeq™ Ancestry Panel, and 51 of these SNPs yielded results with both panels. The results were concordant, and a composite profile was generated [Additional file An in-house PCR multiplex assay comprised of short amplicons (~200 bp in length) at targeted sites on the coding and non-coding regions (HVI and HVII) of the mitochondrial DNA (mtDNA) genome was used to characterize the maternal lineage of the Deadwood skeletal remains. A total of 10 regions of the mtDNA genome were assayed . The mtDNA regions targeted by the in-house multiplex assay increase discrimination power by 17.4 % beyond sequencing of HV1 and HVII alone (unpublished data). Quality sequencing results were obtained for all 10 regions, with a range in coverage of 19x to 23,987x for 95.3 % of the targeted regions. Nine of the 10 regions sequenced had greater than 1000x coverage (14133–14301 had an average coverage of ~100x)  allowed for the following haplotype to be constructed for the reported region . These data provided sufficient genetic information to determine that the most likely mtDNA haplogroup is H1 with numerous subgroups of H1  giving 83.2 % quality score via HaploGrep [Twenty-four phenotype-informative SNPs were assayed using the Ion Torrent PGM® and HID-Ion AmpliSeq™ Externally Visible Characteristics (EVC) Prototype Panel. Results were obtained for 23 of the 24 phenotype-informative SNPs assayed, with a depth of coverage of 33x to 1419x (282 ± 205) (Table http://hirisplex.erasmusmc.nl), which generates individual probabilities for four hair color categories , two hair color shades , and three eye color categories  [Additional testing was performed on the skeletal samples using the Illumina® ForenSeq™ DNA Signature Prep Kit and MiSeq® platform. Results were obtained for all 24 phenotype-informative SNP markers assayed, with a depth of coverage of 32x to 1187x (288 ± 407). Typing results were concordant between assays and between the two MPS platforms. A composite phenotype-informative SNP profile was generated and is shown in Additional file , brown) , 10. The, brown)  and averThe Illumina® ForenSeq™ DNA Signature Prep Kit and the HID-Ion AmpliSeq™ Identity Panel also contain markers that do not contribute to the characterization of bioancestry or phenotype, but nonetheless were able to be typed. With the Illumina® ForenSeq™ DNA Signature Prep Kit, results were obtained for 88/95 human identity SNPs, 27/29 autosomal STRs (plus amelogenin), and 4/8 X-STRs. Range in coverage for the human identity SNPs, autosomal STRs, and X-STRs were 32x-1085x (217 ± 213), 31x-2838x (297 ± 485), and 31x-361x (170 ± 107), respectively. With the HID-Ion AmpliSeq™ Identity Panel, results were obtained for 90/90 human identity SNPs [Additional files th-century human skeletal remains discovered at the site of Deadwood’s first cemetery, historic preservation officials enlisted a number of forensic specialists to conduct analyses on the remains that could assist in his identification [In an effort to learn more about the late-19fication –21, 53. The Y-chromosome  and mitochondrial DNA (mtDNA) profiles of the unidentified skeletal remains are consistent with the R1b and H1 haplogroups, respectively. Both of these haplogroups are the most common ones in Western Europe. The ancestry-informative SNPs also indicated a European background. These genetic results are consistent with the findings of a previous anthropological report which determined that the Deadwood unidentified skeletal remains belong to a male of European ancestry (Caucasian). The phenotype-informative SNPs provided strong support that the individual had light red hair and brown eyes. This study is among the first known historical remains case that has been characterized with genetic panels designed specifically for forensic human identification purposes. The results were highly informative. The study demonstrates the potential of MPS to analyze unidentified human skeletal remains and to provide substantially more genetic information from the same initial quantities of DNA sample as that of CE-based analyses. Using the Illumina® ForenSeq™ DNA Signature Prep Kit, results were obtained for 25/26 Y-STRs, 88/95 human identity SNPs, 51/54 ancestry-informative SNPs, 24/24 phenotype-informative SNPs, 27/29 autosomal STRs (plus amelogenin), and 4/8 X-STRs. With the HID-Ion AmpliSeq™ Identity Panel, results were obtained for 34/34 Y-SNPs and 90/90 human identity SNPs. The HID-Ion AmpliSeq™ Ancestry Panel yielded data for 165/165 ancestry-informative SNP markers assayed. Combined results for all MPS panels included genetic data for 25/26 Y-STRs, 34/34 Y SNPs, 166/166 ancestry-informative SNPs, 24/24 phenotype-informative SNPs, 102/102 human identity SNPs, 27/29 autosomal STRs (plus amelogenin), and 4/8 X-STRs (as well as ten regions of mtDNA).An important point about DNA testing of historical or archaeological skeletal remains should be emphasized. Six bone sections/cuttings were taken, and bone powder fractions from each were analyzed. Adjacent bone sections yielded vastly different results in terms of DNA quantity and number of allele calls; some regions of bone did not yield any DNA, while other areas yielded complete profiles. These findings are consistent with a previous study performed on the 120-year-old skeletal remains of an American Civil War soldier , which rWith its capacity for simultaneous analysis of a multitude of different types of DNA markers, MPS technology holds promise for use in the characterization of historical and archaeological remains, and in missing persons cases. In addition, in mass disasters or other types of cases where reference samples are not available/known, genetic markers such as ancestry-informative and phenotype-informative SNPs can provide data for craniofacial reconstructions that could be useful for positive identification.


Thrips tabaci is a taxonomically difficult group of putatively cryptic species. This study examines population genetic structure of T. tabaci and reproductive isolation among lineages of this species complex using microsatellite markers and mitochondrial COI sequences. Overall, genetic structure supports T. tabaci as a cryptic species complex, although limited interbreeding occurs between different clonal groups from the same lineage as well as between individuals from different lineages. These results also provide evidence that thelytoky and arrhenotoky are not fixed phenotypes among members of different T. tabaci lineages that have been generally associated with either reproductive mode. Possible biological and ecological factors contributing to these observations are discussed.Knowledge of the relative influence of population- versus species-level genetic variation is important to understand patterns of phenotypic variation and ecological relationships that exist among and within morphologically indistinguishable cryptic species and subspecies. In the case of cryptic species groups that are pests, such knowledge is also essential for devising effective population management strategies. The globally important crop pest  Thrips tabaci Lindeman (Thysanoptera: Thripidae), is a globally important insect pest that exhibits remarkable variation in biological and ecological traits within and among populations. Observed population differences include reproductive mode variation, ploidy, host plant preferences as well as differences in vector competency to transmit plant viruses and insecticide resistance [T. tabaci as a cryptic species complex comprised of three genetically distinct lineages exhibiting sufficient mitochondrial COI sequence variation to suggest that these lineages represent different species [Tomato spotted wilt virus (TSWV). These lineages were characterized by Brunner et al. 2004 [Onion thrips, sistance –11. StudT. tabaci is not a fixed phenotype within the lineage, as reported by several other authors [T. tabaci lineages with reproductive mode [Although classifications based on reproductive mode associations are generally accepted in the literature, population genetic studies to date have not resolved whether these groups are reproductively isolated from each other . The fir authors ,13,14. E authors  found thive mode . In thisive mode ,16.T. tabaci in New York onion agroecosystems using both COI sequence data and microsatellite markers. These agroecosystems were considered ideal for addressing our questions because past studies have reported the presence of individuals from lineages 2 and 3 in multiple locations throughout the state. The objectives of this study were to examine 1) population structuring in relation to geographic distance between onion production systems that are distributed throughout the state; 2) reproductive isolation of lineages 2 and 3 in this landscape; and 3) include individuals that were characterized in Nault et al.’s study [Taken together the previously described studies highlight the need to better understand the reproductive isolation of individuals from different lineages, and characterize which lineages exhibit variation in sex determination of offspring by parthenogentically reproducing females. In our study we investigated population genetic structure of ’s study  to examiNo specific permits were required for the described field studies. Verbal permission was obtained from all private landowners to collect insects.T. tabaci were sampled in discrete locations in New York, USA that were former lakes or swamps that had been drained for agricultural production over 100 years ago  exceeds 3,000 hectares and is surrounded by a landscape comprising primarily field and vegetable crops, but which also includes non-cultivated hosts for T. tabaci populations [T. tabaci due to the general lack of suitable host plants [T. tabaci adults likely disperse between onion fields and surrounding habitat patches [T. tabaci dispersers within and among muck regions are not known. Although T. tabaci adults are capable of long-distance dispersal [Populations of ears ago . These lulations . In centt plants . In sout patches , and bet patches ,20 in weispersal , populatispersal ,23.T. tabaci were collected from onion plants grown in commercial production mucks in New York. In 2003, T. tabaci were characterized for their reproductive mode phenotype (see [All ype (see ). Brieflype  and late-season (July and August)  . Early-  sampled . Samples sampled ,9  before analysis. Sequences were condensed into haplotypes using the Map module [Thrips hawaiiensis Morgan (Genbank: AB277226), T. palmi Karney (Genbank: KF144144), Frankliniella occidentalis Pergande , and F. intonosa Trybom (Genbank: NC_021378) COI sequences from Genbank were included in the analysis as outgroups.Genomic DNA was extracted from individual thrips using the DNeasy Kit . Microsatellite and COI markers were amplified according to the protocol in Jacobson et al. ,7. The Cp module  in Mobylp module . Phylogep module . Maximump module  gamma diT. tabaci has populations of mixed ploidy , and allele dosage in partial heterozygotes cannot be determined , microsatellite genotypes were analyzed using PCA cluster analysis executed in the R program Polysat [T. tabaci  described in Jacobson et al. . For the Polysat . This proidy see ,7. Indivilibrium . Analyseas known . IndividBayesian model-based clustering of individuals into populations was examined using STRUCTURE version 2.3.4  for indiT. tabaci individuals collected in all three years. Phylogenetic relationships examined using ML methods in MEGA identified two major clades in this study, which corresponded to lineages 2 and 3 . The cohorts of offspring from virgin females belonging to lineage 2 had sex ratios highly skewed toward male production . Virgin females from 2003 from lineage 3 produced cohorts of offspring for which the opposite was observed; a greater proportion of their progeny were females  (see ).Mean allelic richness of microsatellite loci was calculated for COI haplotypes; all individuals from lineage 2 were grouped together, and different COI clonal types from lineage 3 were each analyzed separately. Maximum number of alleles per locus ranged from 3 to 15, and mean allelic richness was 6.5 alleles per locus across all individuals, 5 for lineage 2, and 6.5 for lineage 3. Among individuals with different COI haplotypes from lineage 3, mean allelic richness varied: 5.9 for NY-HT1, 9 for NY-HT2, and 5.2 for NY-HT3, respectively.T. tabaci; therefore, these samples were re-run. As an additional check, DNA was extracted from a subsample of brothers from the cohorts in which putative diploid males were observed, and amplified at the same loci showing duplicate bands .The ineage 3 . FST valT. tabaci as a cryptic species complex even though ongoing gene flow occurs. Results from this study and Li et al. 2015 [T. tabaci, and the fitness of their offspring to determine species-level classification of T. tabaci are needed. Both Bayesian and PCA analyses of microsatellite markers show populations are generally structured by clonal groups that can be differentiated based on COI sequences. This is consistent with previous studies reporting phenotypic differences in virus transmission and host plant associations among different clonal groups of T. tabaci [T. tabaci that contributes to the success of individuals in lineage 3 . Patterns of population differentiation calculated using Polysat and STRUCTURE provide evidence for gene flow in the field, and support results from a recent laboratory investigation showing T. tabaci from lineages 2 and 3 successfully mate in the laboratory at low frequency [T. tabaci from lineage 3  than for lineage 2 individuals . Gene flow among divergent asexual and sexual taxa also provides opportunities for hybridization that can contribute to creation of new parthenogenetic lineages [T. tabaci lineages, and the influence of ongoing gene flow on genetic diversity and polyploidy.These results provide new evidence consistent with . tabaci , and indrequency –38, inclrequency ,40. Occalineages , ecologilineages ,42, and lineages ,44. FutuT. tabaci in the New York landscape are structured according to clonal groups. Our data provide no evidence for geographic structuring of T. tabaci populations in New York, which contrasts with previous findings of genetic differentiation of T. tabaci in North Carolina [T. tabaci in North Carolina is neither temporally nor spatially stable; populations of T. tabaci are highly variable year-to-year and location-to-location, and populations rarely reach high numbers, which limits the number of individuals dispersing in the landscape [T. tabaci populations commonly reach densities of one or more thrips per onion plant in managed onion mucks of 40 to 14,000 hectares per muck and ca. 247,000 plants per hectare. With populations reaching such high levels in New York, there will be more individuals present in the landscape to disperse, and a greater likelihood that some dispersers successfully establish in other areas. Dispersing T. tabaci have been caught on traps using unmanned, aerial vehicles flown 50 to 60 m above onion fields in the Elba muck [T. tabaci (Nault unpublished) that may establish populations or mate with resident populations. However, to our knowledge, transplants have not been planted in some of the mucks sampled in our study.Results from all of the population genetic analyses indicate that populations of Carolina ,7. The Nandscape . In complba muck , suggestT. tabaci was documented across onion production mucks in New York. This resistance was the result of intense selection imposed by the widespread, prophylactic use of these insecticides for T. tabaci management [T. tabaci populations within New York onion production systems during 2003. Currently, management programs for T. tabaci in New York onion fields include rotations of 3–4 insecticides, each with a different mode of action and, ideally, targeting different T. tabaci generations during the growing season. This change in insecticide stewardship, which is designed to delay the onset of resistance by reducing consistent selection pressure on T. tabaci populations may underlie the greater genetic diversity observed for the 2011–2012 populations. Further research would be needed to define the role of management practices on population genetic diversity.Another notable result from the population genetic study is the apparent change in population structure between 2003 and 2011–2012, even among individuals from the same clonal groups. The PCA conducted on individuals in 2003 show that individuals from the three COI haplotypes collected that year cluster into three distinct groups, whereas in 2011–12 the genetic variation is greater within population clusters. This difference in genetic variation, within and among clusters suggests that something changed in this habitat that has allowed a greater amount of genetic variation to exist in these populations in 2011–2012 compared with 2003. During 2001–2003 widespread resistance to pyrethroid insecticides in nagement ,23. It iT. tabaci offspring in both lineage 2 and lineage 3. T. tabaci is one of the few thysanopterans reported to exhibit multiple reproductive mode phenotypes; arrhenotoky is the reproductive mode generally associated with this order [T. tabaci are phenotypes that may vary over time. Based on these observations, caution is needed when making conclusions about reproductive mode that are based on phenotypic classifications alone [Across the tree of life there is an impressive amount of diversity in reproductive behavior and sex determination mechanisms . Future studies aimed at characterizing the reproductive cytology and mechanisms responsible for sex determination in T. tabaci will provide insights on the influence of reproductive factors responsible for the divergence of these groups, maintenance of polyploidy, and role of limited gene flow on genetic diversity. Future studies that include genetic characterizations of the populations studied will also help characterize the number of groups present, and generate hypotheses about the ecological factors driving the large degree of phenotypic variation in traits related to reproduction, host plant preference, insecticide resistance, and virus transmission among lineages and clonal groups in T. tabaci.Evidence to date suggests that Sequence data is available in Genbank: accession numbers KR152257 and KR152258S1 Fig(PDF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.


The availability of the bovine genome sequence and SNP panels has improved various genomic analyses, from exploring genetic diversity to aiding genetic selection. However, few of the SNP on the bovine chips are polymorphic in buffalo, therefore a panel of single nucleotide DNA markers exclusive for buffalo was necessary for molecular genetic analyses and to develop genomic selection approaches for water buffalo. The creation of a 90K SNP panel for river buffalo and testing in a genome wide association study for milk production is described here.The genomes of 73 buffaloes of 4 different breeds were sequenced and aligned against the bovine genome, which facilitated the identification of 22 million of sequence variants among the buffalo genomes. Based on frequencies of variants within and among buffalo breeds, and their distribution across the genome, inferred from the bovine genome sequence, 90,000 putative single nucleotide polymorphisms were selected to create an Axiom® Buffalo Genotyping Array 90K.This 90K “SNP-Chip” was tested in several river buffalo populations and found to have ∼70% high quality and polymorphic SNPs. Of the 90K SNPs about 24K were also found to be polymorphic in swamp buffalo. The SNP chip was used to investigate the structure of buffalo populations, and could distinguish buffalo from different farms. A Genome Wide Association Study identified genomic regions on 5 chromosomes putatively involved in milk production.The 90K buffalo SNP chip described here is suitable for the analysis of the genomes of river buffalo breeds, and could be used for genetic diversity studies and potentially as a starting point for genome-assisted selection programmes. This SNP Chip could also be used to analyse swamp buffalo, but many loci are not informative and creation of a revised SNP set specific for swamp buffalo would be advised. Bubalus bubalis bubalis, 2n = 50) which has a global distribution, but are the predominant type found in the west from India to Europe. The second type, the Swamp Buffalo , is found more frequently in the eastern Asian countries, particularly from India through China, Indonesia and the Philippines. The buffalo population in Asia is more than 188 million, representing 95% of the world population  and preserved at -20°C until DNA extraction. DNA was extracted from thawed buffy coat using a classic procedure by incubating at 55°C per 30 minutes with proteinase K  and 10% SDS followed by 2 phenol-chloroform  extractions and a chloroform extraction . DNA wasThe IWBGC produced sequence for 86 buffaloes from 8 breeds with a depth between 5 and 12X by Illumina paired-end reads, yielding a total of 470X genome coverage. Of these data, sequences of 4 breeds were used for SNP discovery yielding a total of 22,293,567 SNPs.http://bio-bwa.sourceforge.net/) . It should be noted that the endpoints of the gap surrounding Pi are the nearest flanking loci on each side that are polymorphic in breed j.The algorithm used to select SNP for the assay was based on that used to select SNP for the Illumina BovineSNP50 . This apThe probes on the Axiom Buffalo Genotyping Array 90K were designed using the standard Affymetrix design pipeline. At the time of writing, more than a hundred custom Axiom arrays have been designed using this pipeline.th position) and the reference genome. In this case, Bos taurus UMD3.1 was used as the reference genome.The Affymetrix design pipeline uses a number of stringent rules to identify the SNPs with the highest probability of conversion. At the end of this process, all the SNPs that are unlikely to provide a good conversion are filtered out. The basic input data required by the pipeline are the SNP 71mers , only one probeset was created. For the SNPs with two recommended flanks, the sequence with the highest p-convert value was selected.Additional 33,040 SNPs were selected to provide uniform predicted coverage of the buffalo genome and reach the total number of 90,000 SNPs, even though no recommended flank could be identified. In order to maximize the chance of conversion, for these additional SNPs two separate probesets (one for each flank) were designed.The selected SNPnuon were aligned with the UMD3.1 bovine reference then queried against the buffalo reference sequence (NCBI GCF_000471725.1) to create a 71mer sequence flanking each SNP. Each SNP selected was named based on the (bovine) chromosome and position and the reference and alternative allele noted. In addition, if a SNP was present in the first 25 bases or last 25 bases of the 71mer, these were notated as 5' or 3' SNPs within the probe.Blood samples were obtained for 619 Italian Mediterranean buffalo from 4 farms in the Lombardy region , and lactation records pedigree information was provided by the Italian Buffalo Breeders Association (ANASB). DNA was extracted from the blood sample as described above and genotyped with the Buffalo 90K Axiom Array.Quality control (QC) on genotypes discarded replicated individuals and those with call rate (CR) lower than 10%. Only the best quality SNP probe category “PolyHighRes” called by the Affymetrix’ SNPolisher R package were retained and SNPs with a minor allele frequency (MAF) and a CR lower than 1% and 10% respectively were rejected. Preliminary analysis of the genetic structure of the population was conducted using the Multidimensional Scaling Plot statistics .LactRecord is a 270 days in milk (DIM) conventional lactation record, μ is the general mean, Farm is a fixed farm effect , CalvYear is a fixed effect for calving year , CalvSeason is a fixed effect for season of calving , Calvings is a fixed effect for the number of calvings , Age is a covariate for age (in months), Polygenic is a polygenic effect for animal r, and e is the random residual, with e~ N. The second step of the procedure involved the GWA study, using the random residual of each individual, obtained from the above model, as pre-corrected phenotype. A significance threshold, corrected for residual population inflation (lambda) but not for multiple testing, of p ≤ 1 x 10−4 was used to retain SNPs for further analyses.Associations between SNP genotypes and lactation records were tested by fitting all SNP simultaneously using the GRAMMAR procedure (Genome-Wide Rapid Association using Mixed Model and Regression), applied within the GenABEL package . The GWA® Software  and InnateDB for details on the genes identified by the network [Putative genes 100kb down- and up-stream of all significant SNPs on at least one of the cross-validation runs were retrieved using Ensembl BIOMART , and use network . For IPA


To assess the practical usability of MTA-seq, we applied it to the genotyping of genome-wide single-nucleotide polymorphisms (SNPs) identified in natural accessions  by comparing the re-sequencing data with that of reference accession Bd21. Examination of SNP-genotyping accuracy in 443 amplicons from eight parental accessions and an F1 progeny derived by crossing of Bd21 and Bd3-1 revealed that ~95% of the SNPs were correctly called. The assessment suggested that the method provided an efficient framework for accurate and robust SNP genotyping. The method described here enables easy design of custom target SNP-marker panels in various organisms, facilitating a wide range of high-throughput genetic applications, such as genetic mapping, population analysis, molecular breeding, and genomic diagnostics.Next-generation sequencing (NGS) technologies have enabled genome re-sequencing for exploring genome-wide polymorphisms among individuals, as well as targeted re-sequencing for the rapid and simultaneous detection of polymorphisms in genes associated with various biological functions. Therefore, a simple and robust method for targeted re-sequencing should facilitate genotyping in a wide range of biological fields. In this study, we developed a simple, custom, targeted re-sequencing method, designated “ These datasets provide valuable information for developing genetic tools to discover useful genes for applications in molecular breeding and diagnostics.Recent advances in high-throughput sequencing technologies have accelerated research and developments in the field of genomics Metzker, . The draIn forward-genetics approaches, genotyping at a genome, as well as a population scale, is the primary step to elucidate associations between genetic polymorphisms and traits of interest, which is essential to perform genetic mapping in quantitative trait locus (QTL) analyses and genome-wide association studies  ,” which enabled us to genotype >400 SNPs simultaneously  and the Vogel Lab method (http://1ofdmq2n8tc36m6i46scovo2e.wpengine.netdna-cdn.com/wp-content/uploads/2015/05/Vogel-lab-Crossing-Brachypodium-2-3-2010.pdf). Anthers were pulled out from the female parent by inserting tweezers into the palea to prevent self-fertility, and the lemma was pushed back to close the floret until pollination. After emasculation, all flowers, except the one targeted for crossing, were removed. Next, flowers with very mature anthers were selected. Appropriate anthers with a yellowish-white color were selected, transferred onto a glass slide, and incubated at 37°C for 5 min to dehisce efficiently. The dehisced anthers were picked up with tweezers and stacked into a female floret to apply the pollen to the stigma. After several days, a developing endosperm was observed if successfully pollinated.Artificial crossing was performed according to the Garvin Lab method  using the BWA-MEM (v0.7.12) , Bd3-1 (SRS290395), Bd21-3 (SRP010886), Bd30-1 (SRS190910), BdTR12c (SRS190847), and Koz-3 (SRS190848) described previously  to the Bd21 reference genome (Bdistachyon_192_v1.2) with the Torrent Mapping Alignment Program on the Torrent Server (Thermo Fisher Scientific K. K.). Unreliable SNPs having >5% of different nucleotides between our Bd21 reads and the reference genome were removed from the candidate SNP dataset.B. distachyon accessions analyzed, we excluded genomic regions, including SNPs, discovered by at least one of the five SNP callers from the input genomic sequences for the primer design.Primer3 (v2.2.3)  in the VarScan software (v2.3.7) .The workflow of the MTA-seq method is shown in Figure The total reads obtained for each accession in this study were randomly sampled to generate 0.01, 0.02, 0.04, 0.07, 0.1, 0.15, 0.2, 0.4, 0.7, 1, 2, and 3 million-read datasets. SNPs were called from the random sampling data with the “mpileup2cns” command of VarScan (v2.3.7)  of e Figure , indicatB. distachyon accessions, Bd21, Bd1-1, Bd3-1, Bd21-3, Bd30-1, Koz-1, Koz-3, and Koz-4, as well as an F1 hybrid derived from crossing of Bd21 and Bd3-1 to assess the genotyping accuracy of MTA-seq for heterozygous alleles. We performed MTA-seq using an Ion Torrent semiconductor sequencer (Ion Proton) and obtained 5.5 million to 7.5 million reads for each accession  in an individual by MTA-seq Table . AlthougOne of the strongest advantages of multiplex PCR-based genotyping methods, including MTA-seq, is that they flexibly allow the addition of target SNPs of interest. For example, after QTL identification using genome-wide SNP markers as reported in this study, locus-specific SNP markers accumulated in a QTL region can easily be added to the MTA-seq format to narrow the location of the QTL and identify the genes underlying the QTL. Importantly, MTA-seq can be applied to any SNP in any organism if a reference genome is available. Conversely, a limitation of the MTA-seq method is that the DNA sequence around the target SNPs must be known in order to design primers.Recently, other non-commercial SNP-genotyping methods combining NGS technology with multiplex PCR, such as a three-round multiplex PCR-based SNP genotyping method  With regard to the amount of genomic DNA used as the multiplex PCR template, MTA-seq and the other two methods were found to require comparable amounts of input DNA .(2) With regard to the size of the amplicon for genotyping, GT-seq was performed with less than 100 bp of amplicon, whereas the size of amplicon for three-round multiplex PCR-based method and MTA-seq was 107–160 and 150–200 bp, respectively. Shorter amplicon size may be more suitable for samples in which the genomic DNA is heavily degraded.B. distachyon genomic DNA samples simultaneously, with 95.3–97.5% accuracy. Although the number of samples capable of being handled can be increased to 384 by using a greater number of adapters , the relatively small sample number is the weakest point of MTA-seq, as compared with the other two methods.(3) The throughput and accuracy rate of MTA-seq SNP calling are comparable to, or slightly superior than, those of the two above mentioned methods. The three-round multiplex PCR-based method allowed genotyping of 37 SNPs in 757 human genomic DNA samples simultaneously, with a SNP-calling accuracy rate of 90.5%, whereas GT-seq allowed genotyping of 192 SNPs in 2,068 steelhead trout genomic DNA samples, with a SNP-calling accuracy rate of 96.4%. Using MTA-seq, we genotyped 443 SNPs in nine (4) With respect to the length of primers, primers used in MTA-seq range from 18-31 bases in length, whereas the other two methods used much longer primers . The reason for the longer primer length used by these two methods is the addition of adapters by two- or three-round multiplex PCR, unlike the present MTA-seq method in which adapters are added by ligation. Generally, shorter primers are beneficial as their synthesis is relatively inexpensive.NGS offers a powerful tool that enables users to obtain several gigabases of nucleotide sequence, with reduced cost and time. Whole-genome re-sequencing enables us to determine genetic diversity at a high resolution in an unbiased manner  will accelerate forward-genetics approaches, not only in YO and KM: Designed the experiments and wrote the manuscript; YO and MS: Performed the experiments; YO, KT, and KI: Analyzed the NGS data; All authors read and approved the final manuscript for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Eucalyptus benthamii (n =505) and Eucalyptus pellita (n =732). Both species are of increasing commercial interest for the development of germplasm adapted to environmental stresses.The advent of high-throughput genotyping technologies coupled to genomic prediction methods established a new paradigm to integrate genomics and breeding. We carried out whole-genome prediction and contrasted it to a genome-wide association study (GWAS) for growth traits in breeding populations of E. benthamii and 0.44 in E. pellita for diameter growth. Predictive abilities using either Genomic BLUP or different Bayesian methods were similar, suggesting that growth adequately fits the infinitesimal model. Genomic prediction models using ~5000–10,000 SNPs provided predictive abilities equivalent to using all 13,787 and 19,506 SNPs genotyped in the E. benthamii and E. pellita populations, respectively. No difference was detected in predictive ability when different sets of SNPs were utilized, based on position , as long as the total number of SNPs used was above ~5000. Predictive abilities obtained by removing relatedness between training and validation sets fell near zero for E. benthamii and were halved for E. pellita. These results corroborate the current view that relatedness is the main driver of genomic prediction, although some short-range historical linkage disequilibrium (LD) was likely captured for E. pellita. A GWAS identified only one significant association for volume growth in E. pellita, illustrating the fact that while genome-wide regression is able to account for large proportions of the heritability, very little or none of it is captured into significant associations using GWAS in breeding populations of the size evaluated in this study.Predictive ability reached 0.16 in This study provides further experimental data supporting positive prospects of using genome-wide data to capture large proportions of trait heritability and predict growth traits in trees with accuracies equal or better than those attainable by phenotypic selection. Additionally, our results document the superiority of the whole-genome regression approach in accounting for large proportions of the heritability of complex traits such as growth in contrast to the limited value of the local GWAS approach toward breeding applications in forest trees.The online version of this article (doi:10.1186/s12864-017-3920-2) contains supplementary material, which is available to authorized users. Eucalyptus are the most planted hardwood trees worldwide due to their multipurpose applications , superior growth, high adaptability and wood quality T); X and Z are incidence matrices for the vectors for parameters b and m, respectively; e is a vector of the random error effects. The Z matrix takes values 2, 1 or 0 if the genotype of the ith marker is AA, Aa and aa, respectively, where a is the least frequent allele. Missing genotypes were replaced by the mean of the genotype for the given SNP. In all Bayesian models it was assumed that:The SNP effects were estimated using five different Bayesian genome-wide regression models, namely Bayesian Ridge-Regression (BRR), Bayes A, Bayes B, Bayes Cπ and Bayesian Lasso (BL) as implemented in the BGLR package . For them vector depend on the prior adopted. The respective priors used in the linear regression coefficients for each model are described in Additional file The assumptions of the Eucalyptus reference genome [E. benthamii and E. pellita respectively, down to 2000 in smaller increments of 1000 SNPs, 1500, 1250, 1000, 750, 500, 300, 250, 200, 150 and 100 SNPs) with either a cumulative (i) or non-cumulative (ii) sampling of SNPs. For each number of SNPs and sampling strategy, ten replicates were performed. The evenly spaced SNPs subsets (iii) were created using different target windows sizes, with 1 SNPs every 10, 50, 100, 250, 500 Kbp and 1 Mbp, resulting in variable average distances between SNPs , SNPs in approximate LE (r2 ≤ 0.2) with each other were chosen using PLINK v1.9 [The Bayesian Ridge-Regression (BRR) model was fitted using different subsets of SNPs of various sizes and selected using different criteria as described below. Initially a random sampling of SNPs stratified by chromosome was tested using (i) a cumulative approach, such that from the smallest subset of SNPs tested, additional ones were added to the previous set and (ii) a non-cumulative fashion, where different final sets of SNPs were randomly selected from all available SNPs. Next, variable positions of SNPs were tested, including: (iii) evenly spaced SNPs across the genome; (iv) only SNPs within gene models annotated in the e genome ; (v) SNPINK v1.9 . FinallyK = 2). In E. benthamii, 21 outlier individuals were removed and the remaining individuals were split into two subpopulations based on maximum genetic distance, one with 310 trees and the other with 174. For E. pellita, 26 outliers were excluded and the remaining 706 individuals were split into two subpopulations with 192 and 514 trees. As a control, a 10-fold cross-validation in each direction, with the same numbers of individuals used in the split populations, was carried out by random allocation of the individuals to training and validation sets.To assess the relative impact of relatedness versus historical LD on the predictive ability, BRR prediction models were fitted minimizing relatedness between training and validation populations. Individuals were split into training and validation sets based on a Principal Component Analysis (PCA) or STRUCTURE analysis  captured by the GRM calculated using all SNPs and e is the random residual effect. The covariate computed for population structure was based on the fact that the population had two subpopulations (K = 2). The variance structure of the MLMA model were g, e′) = 0, where G is the GRM between individuals calculated as described earlier [I is the identity matrix. For comparisons with the MLMA model, we also performed a linear model based association (LMA) analysis fitting each SNP independently. This single-SNP association analysis was carried out using PLINK [g). The Bonferroni procedure was implemented to control for type I error at α = 0.05 and the Benjamini & Hochberg procedure [A mixed linear model association (MLMA) analysis was performed using the GCTA software . This as earlier  and I isng PLINK  using a rocedure  was usedrocedure .E. benthamii and E. pellita respectively  and 49,518 (81.3%) were genotyped for .6% and 4r2) was calculated for all pairwise physical distances among all the polymorphic SNPs (MAF > 0) on each chromosome separately. The average, genome-wide LD for pair of SNPs within a 100 Kbp distance from each other was 0.141 and 0.271 for E. benthamii and E. pellita, respectively. When correcting the LD for biases due to relatedness and population structure (r2VS), the average estimates were reduced to 0.096 and 0.178 , while r2VS showed a slightly faster decay within 7.7 and 25.5 Kb (pink dots) for E. benthamii and E. pellita, respectively  within 14.7 and 66.2 Kb (green line), while r2V (correcting for relatedness) showed a slightly faster decay within 7.7 and 25.6 Kb (blue line), very similar to r2VS for E. benthamii and E. pellita, respectively  decaying to r2 = 0.2 at 14.5 Kb in E. benthamii and 35.8 Kb in E. pellita  estimated for DBH and WV were 0.326 and 0.297, and considerably lower for HT (0.088). Estimates of genomic heritabilities varied depending on the method used, with GBLUP and BL yielding considerably lower heritabilities than the pedigree-based ones and those obtained using other Bayesian methods , while the genomic estimated heritabilities based on SNP data were considerably higher (e.g. 0.414–0.527 for DBH using the different methods)  were higher for all traits, compared to those estimated for E. benthamii . Heritabilities estimated including or not lower frequency SNPs (MAF < 0.05) in the genomic relationship matrix were equivalent for both species, varying within the standard error of the estimates  followed the same trend as the estimated genomic heritabilities  of ±0.044. In E. pellita, the variation was smaller, with estimates ranging from 0.358 to 0.550 for DBH, with the ten-fold average equal to 0.441 ± 0.019 , were slightly higher than those using 500 randomly sampled SNPs , indicating that genome-wide marker coverage is critical for capturing the additive genetic variance (Table E. benthamii and 1773 for E. pellita) and not to the fact that they are located on a single chromosome. We did not have sufficient numbers of SNPs on a single chromosome to compare to the larger random subsets of 3000 or 5000 to see the effect on predictions.When only SNPs located on single chromosomes were used, heritabilities dropped on average by 30–45% when compared to using all SNPs  compared to the predictive abilities achieved when the same number of individuals were used to build the model without controlling for relatedness , GS models were fitted trying to minimize relatedness between training and validation sets based on genetic differentiation determined by a PCA  in del Fig. . FurtherEucalyptus in particular. Our results corroborate previous reports in forest trees showing encouraging perspectives of using genome-wide SNP data to capture large proportions of trait heritability and predict traits such as height and diameter growth with accuracies as good as or better than those attainable by conventional phenotypic selection.This study makes a further step towards the experimental assessment of whole-genomic prediction of complex traits in species of forest trees in general and of E. benthamii  using GBLUP were slightly lower than those reported for E. grandis x E. urophylla (0.46–0.55) [E. benthamii, predictive abilities were lower (~0.16), possibly the result of (i) the larger effective population size; (ii) the relatively limited number of individuals used for model training (only ~500); and (iii) the limited genetic diversity available in this species and particularly so in this introduced population in Brazil, also indicated by the low heritability found in our study as well as in others with similar germplasm [Predictive abilities of growth traits using GBLUP and different Bayesian methods reached similar results for all traits, in line with previous reports in forest trees , 20, 22.46–0.55) . For E. Eucalyptus. A better assessment will be possible when predictions are carried out across breeding generations testing variable SNP densities.Prediction models using ~5000 SNPs provided predictive abilities almost equivalent to using all available SNPs for all traits and no difference was observed using different sets of SNPs. These results suggest that genomic prediction is largely driven by relatedness such that once a certain number of randomly sampled SNPs across the genome are used, suitable predictive ability is reached. This outcome indicates that low-density SNP chips could be contemplated as a way to reduce cost of GS in line to what has been the case for domestic animals , 49. It E. benthamii than E. pellita  [E. pellita population comes from a clonal seed orchard established with advanced selections such that a smaller effective population size and more extensive LD was expected.We observed a major impact of relatedness on predictions, more so in ita Fig.  consiste≈4–6 Kb) , the E. E. pellita even after attempting to minimize relatedness between training and validation sets  when compared to populations used in previous GWAS in forest trees , our results are consistent with the fact that very few associations were also found for growth in all those reported GWAS to date [E. benthamii) and provide useful phenotype predictions, very little of the heritability is captured into significant associations using the GWAS approach. Reasons for this major discrepancy are not surprising and have been widely discussed in the plant, animal and human literature [The objective of our GWAS was to assess the value of this approach in closed breeding populations under selection and compare it to whole-genome prediction from the standpoint of how much genetic variation could be captured for practical breeding. After duly controlling for population structure and experimental fixed effects, and applying experiment-wide corrections for multiple tests, we identified only one significant association for volume growth in ita Fig. . Despite to date –59. Popu to date , 57, 59.terature –62. TheyEucalyptus breeding population reported promising results using a regional heritability mapping, an approach able to capture both common and rare allelic effects that individually contribute too little variance to be detected by conventional GWAS [A potential criticism to our GWAS is the fact that it was carried out in a breeding population with limited diversity and not in a canonical GWAS population sampled from the wild. GWAS studies for growth traits in forest trees have in fact targeted collections of trees derived from natural populations sampling large amounts of diversity. The goal of those studies has been to detect associations that would potentially allow gene discovery or even the identification of the elusive QTN (quantitative trait nucleotide) . Howevernal GWAS . The avanal GWAS , as recenal GWAS .Eucalyptus breeding. We also conclude that more important to GS than the number and position of the SNPs fitted in the model, is the extensive LD created in closed breeding populations with small effective population sizes. Lower density SNP panels with ~5000 to 10,000 SNPs, distributed across the genome, should provide a good compromise between genotyping costs and predictive ability in such standard breeding populations advanced by open pollinated breeding. However, further experiments are necessary to evaluate the performance of such SNP densities across generations of breeding. Our results also illustrate the superiority of the whole-genome regression approach in accounting for large proportions of the heritability in contrast to the limited value of the local GWAS approach for breeding applications. To provide useful GWAS data toward breeding for growth traits in Eucalyptus and likely in all forest trees, it will be necessary first to massively increase the sample size, such that sufficient power is reached to detect at least part of the slightly larger effects segregating in the target breeding population. In the meantime, the encouraging results of genomic prediction that we, and others, have shown in this and other studies should probably receive greater attention if the objective is to impact breeding practice.This study contributes further experimental data supporting the positive prospects of genomic selection to predict complex traits such as height and diameter growth in forest trees with accuracies equivalent or superior to those achievable by phenotypic selection. We show that genetic relatedness captured by the SNP data between training and validation populations and, by extension, to future selection candidates, is what will most likely determine the successful use of genomic selection in Additional file 1:Description of the Bayesian methods used for genomic predictions. (DOCX 25 kb)Additional file 2:Supplementary Tables S1 through S4 and supplementary Figures S1 through S4. Supplementary figure legends are contained within the file. (DOCX 1558 kb)Additional file 3:2a) and residual variance (σ2e) obtained with different prediction methods, different position-based SNP sampling methods and sampling related or unrelated individuals in the E. benthamii and E. pellita breeding populations. (XLS 55 kb)Estimates of additive genetic variance (σ


Prunus avium L.) is an economically important non-climacteric tree fruit crop in the Rosaceae family and has undergone a genetic bottleneck due to breeding, resulting in limited genetic diversity in the germplasm that is utilized for breeding new cultivars. Therefore, it is critical to recognize the best platforms for identifying genome-wide polymorphisms that can help identify, and consequently preserve, the diversity in a genetically constrained species. For the identification of polymorphisms in five closely related genotypes of sweet cherry, a gel-based approach (TRAP), reduced representation sequencing (TRAPseq), a 6k cherry SNParray, and whole genome sequencing (WGS) approaches were evaluated in the identification of genome-wide polymorphisms in sweet cherry cultivars. All platforms facilitated detection of polymorphisms among the genotypes with variable efficiency. In assessing multiple SNP detection platforms, this study has demonstrated that a combination of appropriate approaches is necessary for efficient polymorphism identification, especially between closely related cultivars of a species. The information generated in this study provides a valuable resource for future genetic and genomic studies in sweet cherry, and the insights gained from the evaluation of multiple approaches can be utilized for other closely related species with limited genetic diversity in the breeding germplasm.Identification of genetic polymorphisms and subsequent development of molecular markers is important for marker assisted breeding of superior cultivars of economically important species. Sweet cherry ( Application of different molecular tools and access to plant genomes has facilitated identification of genome-wide polymorphisms and thus, development of molecular markers that can be utilized in breeding programs Prunus avium L.) is a member of the Rosaceae family, which represents many other important crop species, including apple, peach, plum, almond, strawberry, raspberry and rose Sweet cherry  and kept frozen at − 80 °C prior to processing.2.2Total genomic DNA was extracted from young leaf tissue using cetyltrimethylammonium bromide (CTAB) phenol chloroform extraction method 2.32, 0.2 mM dNTPs, 0.02 mM 700- and 800-IR dye-labeled arbitrary primers, 0.2 mM fixed primer  with components in the following final concentrations: 10 ng DNA, 1.5 mM MgCl2.42 (50 mM), and 1 × Taq polymerase buffer (10 × stock). Complementary, custom adaptors were then annealed to the sheared DNA, the annealed product was purified and extracted according the NEBNext FastDNA Library Prep protocol. The libraries were quantified, pooled, and sequenced using the Ion Torrent PGM . The sequencing run included 850 flows on a 318C chip producing single reads of various lengths.Genomic DNA (~ 1 μg) was isolated from ‘Glory’ and ‘Staccato’ young leaf tissue. The reduced representation of the genome was achieved by performing TRAP PCR with fixed primers targeting MADS-box, PPR1, and PPR2 gene families . AmplifiThe sequenced libraries  generated ~ 230 Mb combined data for ‘Glory’ and ‘Staccato’ genotypes, comprised of 795k reads with an average read length of 145 nucleotides. The sequencing data was processed through the Stacks program to identify loci containing polymorphisms 2.5For this experiment, ‘Bing’, ‘Sweetheart’, ‘Glory’, ‘Kimberly’ and ‘Staccato’ sweet cherry cultivars were analyzed using the sweet cherry 6k Infinium II SNParray The identified SNPs were filtered to remove missing data, assigned numeric codes corresponding to respective AA/AB/BB genotype, and categorized for downstream population structure analysis.2.6For all the genotypes, approximately 25 × coverage sequence data represented by 2 × 100 paired end reads, were generated with the Illumina HiSeq 2000 sequencing platform. All short read sequenced data was submitted to NCBI under the following accession numbers: SRS1706059 - Bing_Illumina; SRS1706061 - Sweetheart_Illumina; SRS1706060 - Staccato_Illumina; SRS1706062 - Glory_Illumina; SRS1706063 - Kimbery_Illumina. Stacks 2.7A SNP-based population structure analysis was conducted for both the SNParray and the Stacks data using STRUCTURE Analysis of K values from 1 to 5 was specified, along with 5 iterations of the defined STRUCTURE analysis. Upon completion of the Structure run, Structure Harvester was used for identification of most likely K-value based on the data The NTSys software To run NTSys, the input files were uploaded, and the following functions run: 1.) Qualitative data Dis/Similarity method, 2.) SAHN UPGMA clustering method 3.) Tree plot graphic generation function. The result is a tree dendrogram representing WGS SNP-based genetic relationships . The K2 2.8To validate the NTSys and STRUCTURE outputs, Excel was used to calculate the number of SNPs in pairwise comparisons between each genotype, with Bing as the reference genotype. The resulting data was prepared as a distance matrix— genetic distance (or genotypic variation) increases as the number of SNPs increases.The data was saved as a *.txt file and imported into R studio as a “dist” object for further analysis. A dendrogram similar to the one generated by NTSys was produced using the R “plot” and “hclust” functions. As with NTSys, the UPGMA (“average”) method of hierarchical clustering was employed to generate a Euclidian distance-based tree dendrogram which could be compared to the results of the NTSys output .33.1Given the documented lack of genetic diversity within the cultivars of sweet cherry, it is important to understand the pedigree information regarding the five genotypes used in this study namely, ‘Bing’, ‘Sweetheart’, ‘Staccato’, ‘Glory’ and ‘Kimberly’. ‘Sweetheart’ is known to be the maternal parent of ‘Staccato’ while the paternal parent is unknown as it was developed via open pollination. ‘Van’ and ‘Newstar’ (pollinator) are the parents of ‘Sweetheart’, but ‘Sweetheart’ and ‘Staccato’ have no known familial relationship to the other three genotypes used in this study. Previously published SNP marker analysis has shown the paternal parent of ‘Bing’ to likely be ‘Napoleon’ P. avium) and 1482 from allotetraploid sour cherry (P. cerasus) accessions The first approach, TRAP assay, is a PCR-based technique that uses one fixed primer targeting a conserved DNA sequence usually representing a gene family across the genome and one or two arbitrary primers with either an AT- or GC-rich core that anneal to an intron or an exon, respectively 3.2By specifically targeting a flowering-related gene family, we were able to identify polymorphisms between ‘Glory’ and ‘Staccato’ using the TRAP approach 3.3The reduced representation of the genome was achieved by performing TRAP PCR, followed by generating NGS sequence data from the amplified products. By applying the Stacks pipeline and populations map to the TRAPseq data, 942 polymorphic loci corresponding to SNPs between ‘Glory’ and ‘Staccato’ out of 24,984 total loci were identified . This coArabidopsis to regulate flowering time The Blast2GO gene annotation suite was used to identify the top NCBI Blast hit corresponding to each of the polymorphic loci identified via the TRAPseq analysis. Among the annotated loci were: G-type lectin S-receptor-like serine threonine- kinases, which have been implicated in drought, salinity and cold tolerance 3.4SNParray analysis enabled the identification of 1385 polymorphic loci out of the 5696 representative loci in the five cultivars namely ‘Bing’, ‘Sweetheart’, ‘Glory’, ‘Kimberly’, and ‘Staccato’. This corresponds to a 24.3% SNP detection rate. The SNParray has been used previously to genotype sweet cherry cultivars and determine their genetic relatedness 3.5For each of the five genotypes analyzed using SNParray, 22.2 × average coverage of Illumina HiSeq paired end read data, or 4.6–5.5 Gb of sequence data were generated. SNPs were identified using the Stacks workflow While WGS enables the largest coverage of the genome, sequencing of random regions reduces the comparable areas across samples. Perhaps enhancing the depth of coverage can alleviate this limitation. The major strength of all sequencing based approaches over SNParray is that it directly couples SNP discovery with genotyping by identification of genome wide polymorphisms directly in the target samples.The Blast2GO gene annotation suite was also used to identify the top NCBI Blast hit corresponding to each of the polymorphic loci identified by the WGS. The annotated loci included: RNA-directed DNA polymerases, receptor kinases, which have been implicated in brassinosteroid signaling 3.6STRUCTURE and NTSys were used to analyze and produce graphical representations of population structure respectively , Fig. 6.4Multiple methods of polymorphism detection were evaluated across five closely related genotypes of sweet cherry. Each of the described approaches resulted in detection of polymorphisms, although certain ones provided higher resolution of detection between closely related genotypes.The TRAP method allowed for identification of polymorphic regions between ‘Glory’ and ‘Staccato’. This represents the first gel-based evidence of genetic differences between these two genotypes, which were previously only distinguished by delayed fruit maturity phenotype. The observed 4.4% rate of polymorphism detection, however, is not necessarily representative of the detection rate for the TRAP approach in general. The efficiency of polymorphism identification for this method is largely dependent upon both the genetic similarity of cultivars tested as well as the specificity of the fixed primer target. While it has been demonstrated that polymorphic regions can be detected even among highly genetically similar cultivars, this success was largely dependent upon the design of primers targeting the flowering-related VRN2 gene. We recommend a primer screen of various putative gene targets in order to identify the most promising fixed primer candidates for this analysis.The TRAPseq approach allowed for identification of 942 polymorphisms between ‘Glory’ and ‘Staccato’ using Stacks The cherry SNParray represented 5696 SNPs derived from sweet and sour cherry accessions The WGS approach, not surprisingly, provided the highest resolution of polymorphism detection among the five genotypes analyzed. This method is advantageous in that it provides genome wide coverage and can be easily implemented in species with little or no genomic information. WGS can be limited by the depth of coverage and assembly methodology. This is especially true around polymorphic repeat regions of the genome. However, when combined with the Stacks short-read approach, the effectiveness of polymorphism detection of the WGS approach greatly increases. Processing of short reads in Stacks allowed the consideration of only regions with putative polymorphisms, which could then be used in population structure analysis of the five genotypes.‘Bing’ is the most genetically distinct from the other genotypes analyzed, as supported by the results of NTSys, STRUCTURE, and the R clustering algorithms , Fig. 6.The only previously described difference between ‘Glory’ and ‘Staccato’ is based on phenotypic observation of delayed fruit maturity. Using three different methods, TRAP, TRAPseq, and WGS, it has been demonstrated that these two genotypes are subtly distinct from one another and ‘Glory’ is most likely a spontaneous mutation or ‘sport’ derived from Staccato. Thus, it seems that ‘Glory’ and ‘Staccato’, despite their high genetic similarity, are indeed distinct genotypes. Further analysis will allow us to determine whether polymorphisms between ‘Glory’ and ‘Staccato’ arose from a mutation(s) in a flowering related gene(s), as is suggested by the TRAP assay.In summary, the sequencing based approaches evaluated in this study have generated a robust dataset of predicted polymorphisms in sweet cherry. We expect that the described methods, used in conjunction with one another, will be highly useful in genetics and genomics –based research in other closely related species of agronomic importance.TRAPseq loci from Stacks output.Supplementary File 1.Top Blast Hits for TRAPseq loci (Blast2GO).Supplementary File 2.Verification of SNParray derived polymorphisms.Supplementary File 3.SNParray STRUCTURE input file.Supplementary File 4.Original SNParray data.Supplementary File 5.Preparation of WGS Stacks output for STRUCTURE and NTSys.Supplementary File 6.WGS STRUCTURE input file.Supplementary File 7.SNParray NTSys input file.Supplementary File 8.WGS NTSys input file.Supplementary File 9.Validation of NTSys output for SNParray using pairwise SNP counts.Supplementary File 10.Validation of NTSys output for WGS using pairwise SNP counts.Supplementary File 11.Top Blast Hits for WGS loci (Blast2GO).Supplementary File 12.The following are the Supplementary data related to this article.The authors declare no competing interests.Conceived and designed the experiments: AD, BK, SH, TK, RS.Performed the experiments: SH, BK, TK.Analyzed the data: SH, RH, BK, TK, AD.Contributed reagents/materials/analysis tools: AD, RS, TK.Wrote the paper: AD, SH, BK, RH.


Lasiodiplodia theobromae is an important disease on mango plantations in the United Arab Emirates (UAE). In this study, 53 actinobacterial isolates were obtained from mango rhizosphere soil in the UAE, of which 35 (66%) were classified as streptomycetes (SA) and 18 (34%) as non-streptomycetes (NSA). Among these isolates, 19 (12 SA and 7 NSA) showed antagonistic activities against L. theobromae associated with either the production of diffusible antifungal metabolites, extracellular cell-wall-degrading enzymes (CWDEs), or both. Using a “novel” mango fruit bioassay, all isolates were screened in vivo for their abilities to reduce lesion severity on fruits inoculated with L. theobromae. Three isolates, two belonging to Streptomyces and one to Micromonospora spp., showed the strongest inhibitory effect against this pathogen in vitro and were therefore selected for tests on mango seedlings. Our results revealed that the antifungal action of S. samsunensis UAE1 was related to antibiosis, and the production of CWDEs  and siderophores; whilst S. cavourensis UAE1 and M. tulbaghiae UAE1 were considered to be associated with antibiotic- and CWDE-production, respectively. Pre-inoculation in greenhouse experiments with the most promising actinobacterial isolates resulted in very high levels of disease protection in mango seedlings subsequently inoculated with the pathogen. This was evident by the dramatic reduction in the estimated disease severity indices of the mango dieback of individual biocontrol agent (BCA) applications compared with the pathogen alone, confirming their potential in the management of mango dieback disease. L. theobromae-infected mango seedlings treated with S. samsunensis showed significantly reduced number of defoliated leaves and conidia counts of L. theobromae by 2- and 4-fold, respectively, in comparison to the other two BCA applications. This indicates that the synergistic antifungal effects of S. samsunensis using multiple modes of action retarded the in planta invasion of L. theobromae. This is the first report of BCA effects against L. theobromae on mango seedlings by microbial antagonists. It is also the first report of actinobacteria naturally existing in the soils of the UAE or elsewhere that show the ability to suppress the mango dieback disease.Dieback caused by the fungus  Mangifera indica L.), frequently recognized as “the king of fruits,” is a popular fruit in tropical and subtropical regions  Griffon and Maubl.   and/or CWDEs capable of inhibiting L. theobromae, (ii) select the promising isolates using a novel mango fruit bioassay which we developed, to assess their potential to reduce disease progression on fruits, and (iii) evaluate the differences in the potential of the promising isolates with known mode(s) of antagonism under greenhouse conditions, for their effectiveness in controlling mango dieback disease. Our results demonstrate the potential to use selected actinobacteria with more than a single mode of action as antagonists to be incorporated into sustainable IPM strategies to manage dieback disease in mango orchards in the UAE and elsewhere.Previously, we identified L. theobromae (DSM 105134), was previously reported as the cause of mango dieback disease in the UAE . The pathogen was cultured on potato dextrose agar  plates, supplemented with 25 mg l−1 ampicillin  to suppress bacterial contaminants. The fungus was sub-cultured every 10 days on PDA plates at 28°C.The pathogen, Five rhizosphere soil samples were collected from 30 cm depth under healthy mango trees in sealable plastic bags. The rhizosphere soil samples were air-dried for 4 days at 25°C . In order to increase and decrease the populations of filamentous actinobacteria and other bacteria, respectively, the soil pre-treatments described by Hayakawa and Nonomura  was prepared by mixing high-titer phage suspensions of each polyvalent Streptomyces phage. Seven plates were inoculated with 0.2 ml aliquots of the phage-treated soil suspension, dried and incubated in dark at 28°C for 14 days. Control treatments were considered as plates without phages.For the NSA recovery, four polyvalent 10 colony forming units (cfu) g−1 dry soil, were purified on oatmeal agar plates (ISP medium 3) amended with 0.1% yeast extract   following inoculation with L. theobromae, described above, onto each mango fruit according to the following combinations: (i) a sterile non-inoculated PDA agar plug ; (ii) the antagonist alone (BCA) with a sterile PDA agar plug above it; (iii) L. theobromae (Lt) alone with a sterile PDA agar plug below it; and (iv) pairing L. theobromae and the antagonists together (BCA+Lt), with the BCA on the mango surface and L. theobromae-inoculated plug on top of the BCA. The antagonists were inoculated onto the mango surface 24 h prior the pathogen in order to allow time for the secretion of antifungal metabolites and/or chitinase onto the mango surface. Each mango fruit was inoculated with the four treatment combinations for each BCA of four fruits/tray in triplicates. Trays were covered with aluminum foil and incubated under humid conditions in dark at 28°C for 4 days. The lesion diameters were measured in order to determine disease indices. To fulfill Koch's postulates, all diseased fruit tissues were incubated on PDA plates at 28°C in dark for 5 days.Mature mango fruits (cv. Badami) were placed in plastic trays on sterile paper towels moistened with sterile distilled water, and were inoculated by placing the agar plugs (11 mm) colonized by the actinobacterial isolates and/or L. theobromae using the cup plate technique as previously described  or fungicidal (no pathogen growth from the plug).Briefly, dialysis membrane  with adhering colonies were removed from the agar plates and the center of each plate was inoculated with a disc (5 mm diameter) of −1. The plates were inverted and a piece of filter paper (soaked in 0.5% picric acid in 2% sodium carbonate) was placed in the lid of each Petri dish, and incubated at 28°C for 5 days  agar developed by Schwyn and Neilands , were in−1 of either L. theobromae cell wall fragments, colloidal chitin, or laminarin (Sigma-Aldrich) were prepared. Flasks containing each substrate were inoculated with 2 ml of a 20% glycerol suspension of each BCA (108 cfu ml−1), incubated on a rotary shaker  at 250 rpm for 7 days, and further centrifuged at 12,000 × g for 30 min. The supernatant was filtered using 0.22 μm Millipore membranes  and used as a source of crude enzymes . The colony diameter (mm) of L. theobromae was measured after 5 days at 28°C.The filter-sterilized crude culture filtrate for each BCA (section Determination of CWDE Activities of the BCA Candidates) using fish meal extract broth or colloidal chitin broth  , Braunschweig, Germany, using the primers 900R (5′-CCGTCAATTCATTTGAGTTT-3′); 357F (5′-TACGGGAGGCAGCAG-3′) and 800F (5′-ATTAGATACCCTGGTAG-3′)  software , BCA2 (isolate #29) and BCA3 (isolate #44), was carried out using 16Identification of BCA1 and BCA2 isolates was further confirmed based on cultural, morphological, and physiological characteristics as described by Locci . ScanninL. theobromae culture or non-colonized plugs (controls)  seedlings were surface-sterilized with 70% ethanol, mechanically wounded, and inoculated with 5 mm PDA plugs colonized with In vivo evaluations of the BCAs were also carried out on mango seedlings. We aimed to investigate the efficacy of the three BCA treatments to manage dieback disease. Similar to the L. theobromae treatment described above, methods of inoculation with the pathogen and BCA application were used. All BCA treatments were preventive (seedlings treated with each BCA 1 week before L. theobromae inoculation). The treatments/groups used for this experiment were as follows:Healthy controls (C): Non inoculated control seedlings;Lt): Seedlings inoculated with L. theobromae only;Diseased controls : Seedlings inoculated with either S. samsunensis, S. cavourensis or M. tulbaghiae, respectively;Biocontrol treatment without pathogen : Seedlings inoculated with either S. samsunensis, S. cavourensis or M. tulbaghiae, respectively, 1 week before L. theobromae inoculation.Preventive biocontrol treatment (−1 m−2 s−1) at 28°C. Corresponding with the disease symptoms/recovery, disease severity index (DSI) was recorded at 3 and 9 weeks post inoculation (wpi) using the following scale: 0 = no apparent symptoms, 1 = 1–10%, 2 = 11–25%, 3 = 26–50%, 4 = 51–75%, and 5 = 76–100% necrotic or dark brown area around the point of inoculation  and inoculated seedlings were maintained under controlled greenhouse conditions of 15 h light/9 h dark under fluorescent lights . Each mango fruit was inoculated with the four treatments and each tray contained four fruits with three replicate trays for each isolate. Significant differences between means at in vitro evaluation of BCA against L. theobromae. Experiments were repeated in triplicates using five plates per treatment for each time with similar results.ANOVA and Duncan's multiple range test at 5% level of significance were used to analyze the in vivo treatments against L. theobromae in the greenhouse trial, six plants were used for each treatment. ANOVA and Duncan's multiple range test were used to determine the statistical significance (P < 0.05). All experiments were repeated independently three times with similar results.For the falling leaves and fungal conidia counts of the in vivo treatments. ANOVA and Duncan's multiple range test were conducted to determine the statistical significance at P < 0.05. Similar results were obtained in each replicate. For all statistical analyses, SAS Software version 9 was used  were tested for the DSI of the Streptomyces phages with high polyvalency were used to facilitate the isolation of NSA from rhizosphere samples on inorganic salt starch agar plates  reduced, but the numbers of NSA increased on the plates treated with the four phages  were readily isolated and identified to the genus level based on morphological features, distribution of aerial and/or substrate mycelia, presence/absence of aerial mycelia, and the stability or fragmentation of substrate mycelia.Fifty-three SA and NSA strains were isolated from mango rhizosphere, of which 35 SA 66.1%) and 18 NSA (33.9%) were obtained from inorganic salt starch agar plates. The % and 18 L. theobromae using the cut-plug method  isolates were capable of producing strong antifungal metabolites active against od Table . Eleven od Table ; thus weL. theobromae mycelial fragment agar  were ranked as highly active chitinase-producing isolates. These 12 isolates produced large clearing zones (>30 mm) around the colony on colloidal chitin agar plates and on ar Table . The remL. theobromae (Table Lt) alone were relatively large, brownish, round to elliptical, water-soaked and depressed, with clear margins  on the mango fruit surface, they completely suppressed the pathogen with no lesions formed compared with the treatment with the pathogen plug alone (Lt) (Table P < 0.05) reduced lesion development in comparison to the treatment with the pathogen alone  Table . Certainne Table .In general, ten isolates (6 SA and 4 NSA) totally prevented or reduced lesion development to varying degrees, whilst the remaining 9 isolates failed to reduce lesion formation Table . The isoL. theobromae, and that the preventive effect of isolates #12, #29 and #44 could have the potential to manage dieback disease on mango seedlings. The actinobacteria tested alone (BCA treatment) did not cause any harmful effects on mango fruits  retardation of the growth of L. theobromae, when compared to the antifungal metabolite non-producing BCA3 or control (Table P < 0.05) higher than those produced by BCA2  higher in the media amended with colloidal chitin or on media amended with the pathogen cell walls  higher on laminarin-amended medium. On the other hand, there were no detectable levels of chitinase or ß-1,3-glucanase by BCA2 when it was grown in media containing either colloidal chitin or L. theobromae cell walls, or in media containing laminarin or L. theobromae cell walls, respectively (Table P < 0.05) higher than those produced by BCA1.Chitinase production by BCA1 and BCA3 was significantly (L. theobromae (Table P < 0.05) inhibited the colony and mycelial growth of L. theobromae  reduction in the germination of the thick walled, mature conidia and the average length of germ tubes produced by L. theobromae was found when the pathogen was exposed to the crude culture filtrate of BCA1 and BCA2 , and BCA1 and BCA3  after 24 h of incubation , cytoplasmic coagulation and hyphal lysis in y Figure . There wh Figure . The path Figure . Myceliah Figure .S rRNA gene. The 16S rRNA gene sequences of BCA1 , BCA2  and BCA3  were compared with that of other actinobacteria. Comparisons of the 16S rRNA gene of BCA1, BCA2 and BCA3 with sequences in the GenBank database showed that these BCA candidates were streptomycete spp. for isolates #12 (BCA1) and #29 (BCA2) and a non-streptomycete sp. for isolate #44 (BCA3). BCA1 showed above 99% similarity to S. samsunensis (EU077190) and S. malaysiensis (AB249918)  and S. albolongus (AB184425) . The rest of the Micromonospora spp. showed 99.4% or less similarity than that with this specific strain  Figure , althoug) Figure ; while tn Figure .Streptomyces samsunensis  on ISP medium 3 produced typical brownish-black charcoal-like substrate mycelia without the formation of aerial mycelia  were observed  or on non-inoculated seedlings (C)  recovered when compared with seedlings inoculated with L. theobromae only (Lt) at all time points of assessments. These plants appeared to be healthy and were comparable to those that were inoculated with any of the corresponding BCA candidate alone  or without infection with L. theobromae (C)  showed disease progression until 9 wpi  showed no disease symptoms at any of the assessment time-points. There was a dramatic decrease in DSI in all L. theobromae-infected seedlings that were previously treated with any of the BCA candidates at 3 and 9 wpi, when compared with plants inoculated with the pathogen alone. In comparison with the L. theobromae-infected seedlings, the DSI of the preventive applications of individual BCA candidate  dropped from 2.83 to 0.17 at 3 wpi and from 4.33 to 0.17 at 9 wpi; providing 94.0 and 96.1% reduction in disease development, respectively. The three preventive treatments with the BCA candidates at 3 and 9 wpi did not show significant (P > 0.05) difference among the DSI measurements, and the BCA-treated plants without the pathogen. This suggests that the preventive treatment with BCA candidates a week before inoculation with L. theobromae effectively suppresses the pathogen invasion.We found significant differences between treatments when the DSI was assessed. Plants inoculated with pi Table . SeedlinL. theobromae; however, the differences of the DSI were indistinguishable among these BCA treatments. For that reason, we compared the responses of the biological control treatments to determine their effects on leaf defoliation and the production of conidia on the host plant. The number of falling leaves in seedlings inoculated with L. theobromae dramatically increased compared to any BCA-inoculated or non-inoculated seedlings at 6 wpi  caused a greater reduction in the number of conidia, followed by the other BCA-treated plants, Sc+Lt and Mt+Lt at the end of the greenhouse experiment  and Bacillus subtilis (EPCO16) reduced the pathogen population in vitro; and further strengthened the cell-wall structures of mango fruits against L. theobromae infection. This is consistent with the present study that many isolates killed the pathogen in vitro; whereas certain isolates completely arrested development of lesions, with others reducing only the lesion size or having no effect on the disease in the mango fruit bioassay  belonging to Streptomyces spp. confirm the findings from previous reports that SA are predominant among actinobacteria appearing in isolation plates and more often produce useful antibiotics and active secondary metabolites  was considered as M. tulbaghiae. The mechanisms involved in disease reduction or prevention of lesion development appeared to be antibiosis  for S. samsunensis and S. cavourensis, and the production of CWDEs such as chitinase and ß-1,3-glucanases for S. samsunensis and M. tulbaghiae. Several actinobacteria have been demonstrated to inhibit the growth of soil-borne plant pathogens such as Pythium ultimum, Rhizoctonia solani  may indicate that this response could be a result of synergetic effects of the multiple modes of action i.e., co-antagonism. Our results are in agreement with other reports that Streptomyces spiralis and Actinoplanes campanulatus which produced diffusible inhibitory antifungal metabolites and CWDEs were superior on Micromonospora chalcea which produced CWDEs only in controlling root rot and crown rot of cucumber caused by P. aphanidermatum , S. lydicus strain WYEC108  are commercial BCA products that reduce spore germination and inhibit hyphal growth of plant fungal pathogens  to the pathogen by the BCA (Martínez-Hidalgo et al., Lasiodiplodia disease. To our knowledge, the results demonstrate, for the first time, the isolation, identification and confirmation of the biocontrol potential of actinobacteria from soil native to the UAE, and likely to be naturally suited to be suppressive to L. theobromae. In order to make biocontrol more effective, future research focusing on development of novel formulations, broadening of host range targets, and increasing biomass production of BCAs in association with the use of biotechnology in improvement of BCA mechanisms will effectively develop schemes to widely manage the dieback disease using environmentally sustainable strategies.Together, the diffusible compounds and/or CWDEs produced by the BCA candidates were closely associated with the inhibition, suppression and destruction of in vitro and in vivo experiments. ES, KE-T, and SA performed in vivo greenhouse experiments. SA developed the phylogenetic analysis. KE-T and SA analyzed the data. FK and ES assisted with experiments and/or data evaluation. KE-T and SA wrote the manuscript. All authors critically revised the manuscript and approved the final version.KE-T and SA designed the research and supervised the study. FK, ES, and KE-T performed The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.