Bemisia tabaci (Hemiptera: Aleyrodidae) is among the 100 worst invasive species in the world. As one of the most important crop pests and virus vectors, B. tabaci causes substantial crop losses and poses a serious threat to global food security.The whitefly B. tabaci Middle East-Asia Minor 1 (MEAM1), the first genome sequence in the Aleyrodidae family, which contains 15,664 protein-coding genes. The B. tabaci genome is highly divergent from other sequenced hemipteran genomes, sharing no detectable synteny. A number of known detoxification gene families, including cytochrome P450s and UDP-glucuronosyltransferases, are significantly expanded in B. tabaci. Other expanded gene families, including cathepsins, large clusters of tandemly duplicated B. tabaci-specific genes, and phosphatidylethanolamine-binding proteins (PEBPs), were found to be associated with virus acquisition and transmission and/or insecticide resistance, likely contributing to the global invasiveness and efficient virus transmission capacity of B. tabaci. The presence of 142 horizontally transferred genes from bacteria or fungi in the B. tabaci genome, including genes encoding hopanoid/sterol synthesis and xenobiotic detoxification enzymes that are not present in other insects, offers novel insights into the unique biological adaptations of this insect such as polyphagy and insecticide resistance. Interestingly, two adjacent bacterial pantothenate biosynthesis genes, panB and panC, have been co-transferred into B. tabaci and fused into a single gene that has acquired introns during its evolution.We report the 615-Mb high-quality genome sequence of B. tabaci genome contains numerous genetic novelties, including expansions in gene families associated with insecticide resistance, detoxification and virus transmission, as well as numerous horizontally transferred genes from bacteria and fungi. We believe these novelties likely have shaped B. tabaci as a highly invasive polyphagous crop pest and efficient vector of plant viruses. The genome serves as a reference for resolving the B. tabaci cryptic species complex, understanding fundamental biological novelties, and providing valuable genetic information to assist the development of novel strategies for controlling whiteflies and the viruses they transmit.The The online version of this article (doi:10.1186/s12915-016-0321-y) contains supplementary material, which is available to authorized users. Bemisia tabaci (Hemiptera: Aleyrodidae) is particularly important because of its ability to infest more than 1000 plant species [B. tabaci-transmitted viruses on a global scale include tomato, cassava, cotton, cucurbits, sweet potato, and numerous other species. Bemisia tabaci-transmitted Tomato yellow leaf curl virus (TYLCV) causes one of the most devastating diseases affecting tomato production [B. tabaci, one of the 100 worst invasive alien species in the world (http://www.issg.org).Whiteflies are notorious agricultural pests that have become major threats to global food security and cause damage to crops by direct feeding and efficient transmission of numerous viruses infecting food, fiber, and ornamental crops worldwide. Among the 1556 known whitefly species in 161 genera [ species  and tran species . Major coduction  and has oduction  and are oduction . FurtherBemisia tabaci was first identified as a new pest species in 1889 in Greece [B. tabaci to various biotypes on the basis of several biological properties such as host range, behavior, insecticide resistance, and virus transmission capacity [B. tabaci differentiation. For example, at least 34 genetic groups (or cryptic species) of B. tabaci have been discriminated based on the sequence divergence of the mitochondrial cytochrome oxidase I (MtCOI) gene [n Greece  and is nn Greece . Early wcapacity , 13 has OI) gene –17, inclOI) gene , 18.B. tabaci whitefly are limited. Multiple transcriptome data are available, addressing the phylogenetic relationship and transcriptome sequence divergence of different B. tabaci species [B. tabaci genome is still greatly needed for further resolution of the species complex conundrum. In addition, a reference genome will assist our understanding of the molecular mechanisms underlying virus transmission, detoxification, host adaptation, and insecticide resistance.Despite its agronomic importance, genomic resources for the  species , 20, res species , insecti species , develop species –25, and  species . HoweverB. tabaci MEAM1, which was assembled using a hybrid approach involving Illumina short reads and PacBio long reads. This assembly represents the first genome sequence of a member of the family Aleyrodidae. The availability of the B. tabaci genome not only provides novel insights into the underlying mechanisms of the whitefly’s global invasiveness and high virus transmission capacity but also presents valuable information to help understand the B. tabaci species complex and to facilitate the development of improved strategies for efficient whitefly management.Here, we present a high-quality draft genome sequence of B. tabaci colony established from a single female collected at the United States Department of Agriculture (USDA)-Agricultural Research Service (ARS) in Charleston, South Carolina (SC) were used for genome sequencing  [B. tabaci genome, among which 13,562 (87%) were supported by our RNA-Seq data, 7321 (47%) by homologous proteins, and 6473 (41%) by both. Of these, 81% were functionally annotated  and D. melanogaster (142.6 Mb) genomes, the number of protein-coding genes in the two species was similar . The mean coding sequence length of the genomes was also similar, while the mean intron and untranslated region (UTR) lengths in B. tabaci were considerably larger than those in D. melanogaster  of repeat sequences were identified in the me (38%) . Among t% of repeB. tabaci protein-coding genes with those of five exopterygotan insects, eight endopterygotan insects, and two non-insect arthropod species , forming a lineage together with three other hemipteran insects: Nilaparvata lugens (brown planthopper), Rhodnius prolixus (Triatomid bug), and Diaphorina citri (Asian citrus psyllid) , Bombyx mori (silkworm), and Plutella xylostella (diamondback moth), whose genomes share high synteny [B. tabaci, A. pisum, N. lugens, R. prolixus, and D. citri, are highly divergent, consistent with previous reports suggesting that B. tabaci and A. pisum diverged about 250 million years ago [H. melpomene and B. mori diverged about 103 million years ago [We compared id) Fig. . Interes synteny . Our anaears ago , whereasears ago .B. tabaci genome, 10,334 (8372 gene families) had detectable homologs in the other 15 arthropods, including 2817 (2427 gene families) that were conserved in all 16 species , which is transmitted by B. tabaci in a persistent circulative manner, or Tomato chlorosis virus , which is transmitted in a semipersistent, non-circulative manner, to the corresponding whiteflies feeding on virus-free tomato plants for the same time periods. We found that during the acquisition feeding of TYLCV- or ToCV-infected tomato plants, a large number of cathepsin genes were differentially expressed including 20 cathepsin B, five cathepsin L-like, three cathepsin F, and one cathepsin F-like genes , UDP-glucuronosyltransferases (UGTs), glutathione S-transferases (GSTs), ABC transporters (ABCs), and carboxylesterases (CCEs)  with 20 members, the CYP4CS subfamily with 14 genes, and the CYP402C subfamily with 12 members  and A. pisum (72), but substantially more than the amount found in other insects (4 to 38). Additionally, 22 GST  gene family, which has not been previously associated with detoxification or insecticide resistance in insects, showed striking responses to Mospilan treatment. A total of 134 and 16 PEBP genes were responsive to Mospilan treatment in the MED resistant and susceptible populations, respectively, all of which were down-regulated Fig. . PEBPs aies Fig. . By compPortiera aleyrodidarum and one or more additional bacteria, generically known as secondary symbionts [Portiera, and two secondary endosymbionts, Hamiltonella and Rickettsia. The genomes of the three endosymbionts were assembled de novo, with each assembled into a single contig. The assembled genome of Portiera was complete with a size of 352 kb, while those of Hamiltonella and Rickettsia were nearly complete, with sizes of 1.74 Mb and 1.38 Mb, respectively  phage genes and numerous genes involved in the type II/III secretion systems. Approximately 22% of the Rickettsia genes are homologous to transposable elements, suggesting that the genome is highly dynamic. Comparative analysis of the B. tabaci genome with the Portiera and Hamiltonella genomes identified genes coding for complementary reactions in multiple metabolic pathways, including essential amino acid biosynthesis  had predicted enzymatic functions. HGTs of bacterial origin mainly contributed to amino acid synthesis, vitamin synthesis, and lipid metabolism, while those of fungal origin mainly contributed to carbohydrate processes, pro-oxidant functions, and lipid metabolism. Two cases of co-transfer of two genes were identified: bioA-bioD phylogenetically allied with the bacterium Cardinium and panB-panC allied with the bacterium Pseudomonas, which encode enzymes in the biosynthesis pathways of biotin (vitamin B7) and pantothenate (vitamin B5), respectively. The bioA and bioD genes are adjacent to one another in the Cardinium genome; however, in the B. tabaci genome they are arranged as two sets of adjacent genes, with the bioA truncated in one pair (Bta00841), and bioD truncated in the second pair (Bta01938)  [B. tabaci-Portiera association may be capable of pantothenate synthesis by a shared metabolic pathway between the horizontally acquired gene in the insect genome and the symbiont gene  , suggestene Fig. .Fig. 4HoB. tabaci genome contains a gene of fungal origin annotated as squalene synthase  genes of fungal origin in the hthalene . In funghthalene . One of B. tabaci represents one of the most agronomically significant pests. Our analysis of the B. tabaci genome also included chemosensory genes, immunity-related genes, and genes in the RNA interference (RNAi) pathway  several B. tabaci-specific gene clusters that are tandemly duplicated and uniquely responsive to feeding on virus-infected plants; (2) largely expanded gene families including cathepsins, CYPs, UGTs, and PEBPs that have potential roles in virus transmission, polyphagy, detoxification, and/or insecticide resistance; and (3) numerous genes horizontally transferred from bacteria and fungi, including those involved in essential amino acid and hopanoid/sterol synthesis, in addition to APOs with putative roles in detoxification. The B. tabaci genome reported here provides an important advance for understanding whitefly biology, with implications for insect pest management and associated virus control. Furthermore, the B. tabaci genome represents the first genome sequence in the Aleyrodidae family and is highly divergent from other sequenced hemipteran genomes, providing a valuable resource for future comparative and evolutionary genomic studies.The whitefly B. tabaci MEAM1 colony established from a single female collected at the USDA-ARS in Charleston, SC, USA in April 2013, as described in Chen et al. [Bemisia tabaci) F:5’- GAGGCTGRAAAATTARAAGTATTTGG-3’, R:5’- CTTAAATTTACTGCACTTTCTGCCAYATTAG-3’ which amplified 478 bp, 303 bp, 405 bp, and 745 bp of the MtCOI gene, respectively [Genomic DNA was isolated from approximately 6500 haploid male individuals from a n et al. . The colectively . PCR ampThree Illumina paired-end libraries, with insert sizes of approximately 300 bp, 500 bp, and 1 kb, and three Illumina mate pair libraries, with insert sizes of 3–5 kb, 8–10 kb, and 15–20 kb, were constructed using the Genomic DNA Sample Prep kit and the Nextera Mate Pair Sample Preparation kit, respectively, following the manufacturer’s instructions . These libraries were sequenced on the Illumina HiSeq 2500 system. In addition, one PacBio library was prepared and sequenced on a total of 27 SMRT cells of the PacBio RSII Sequencing System using the P5C3 chemistry .The Illumina reads were first processed to collapse duplicate read pairs into unique read pairs. Duplicate read pairs were defined as those having identical bases in the first 100 bp of both left and right reads. Illumina adapter and low-quality bases were trimmed from the reads using Trimmomatic . Reads sBrassica oleracea L.) on which the isogenic MEAM1 colony was reared. Tissues were surface sterilized by submersion in a petri dish containing 70% ethanol. The eggs were gently separated from nymphs and pupae using a small paintbrush. Isolated nymph and pupa samples were rinsed with sterile water. Approximately 1500 adult whiteflies reared on broccoli (B. oleracea L. var. botrytis) at the USDA-ARS in Charleston, SC were transferred to either TYLCV-infected or uninfected tomato (Solanum lycopersicum cv. Moneymaker) cuttings and allowed to feed for 24, 48, or 72 h, respectively. For each treatment and time point, two compound leaves were collected from TYLCV-infected or uninfected plants and transferred to a flask filled with water, which was then sealed with Parafilm and placed in an insect-proof cage. Whiteflies were added to each cage and allowed to feed for 24, 48, or 72 h under controlled conditions at 28 ± 1 °C, a 14:10 (L:D) h photoperiod, and ~60% humidity. A total of 200–500 living whiteflies were collected at the end of each time point and stored at –80 °C until processing. Three biological replicates were performed for each sample. A similar experiment under the same environmental conditions was performed using adults from a MEAM1 colony maintained at the USDA-ARS in Salinas, California (CA), but these white flies were fed on ToCV-infected or uninfected tomato (cv. Moneymaker) plants.Eggs, nymphs, and pupae were collected from leaves of collard plants  treated with the insecticide Mospilan at an LC30 dose  with the dipping method, as previously described [For insecticide treatment experiments, adults of two MED populations, PyriR, which is susceptible to the insecticide Mospilan (acetamiprid), and 9-2103, which is resistant, were fed on cotton seedlings . Differential expression analyses were performed using edgeR [P values were adjusted for multiple testing using the false discovery rate (FDR) [Total RNA was purified using the Ambion TRIzol Reagent  according to the manufacturer’s protocol. Strand-specific RNA-Seq libraries were constructed following the protocol described in Zhong et al.  and sequg TopHat , and theg TopHat . For genng HISAT . Raw coung edgeR . The reste (FDR) . For eacB. tabaci genome were first identified de novo using RepeatModeler (http://www.repeatmasker.org/RepeatModeler.html), which integrates the output of RECON [B. tabaci genome, a library consisting of the de novo repeat elements identified by RepeatModeler and the Repbase library (http://www.girinst.org/repbase/index.html) were used to screen the assembled B. tabaci genome using RepeatMasker and RepeatRunner, which are integrated into the MAKER annotation pipeline [Repeat elements in the of RECON  and Repeof RECON  to buildpipeline . Miniatupipeline .B. tabaci genome were predicted with MAKER [Drosophila melanogaster and A. pisum proteomes were aligned to the B. tabaci genome using Spaln [B. tabaci mRNA sequences collected from GenBank were aligned to the genome using Spaln [Protein-coding genes in the th MAKER , which ith MAKER  and SNAPth MAKER  were useng Spaln  with defng Spaln , and onlng Spaln  using Inng Spaln , and thoB. tabaci predicted genes were annotated by comparing their protein sequences against UniProt (TrEMBL and SwissProt), fruit fly, and pea aphid proteomes, as well as the InterPro domain database. GO annotation was performed using Blast2GO [The Blast2GO .B. tabaci and 13 other insects, as well as two additional non-insect arthropod species , 57 °C (Cardinium), 58 °C , or 60 °C  for 1 m, extension at 72 °C for 1 m, and a final extension at 72 °C for 5 m. PCR products were visualized on a 1% agarose gel.Diagnostic PCR assays using the primers described in Pan et al.  indicateive gene . PCR ampB. tabaci, i.e., Portiera, Hamiltonella, and Rickettsia, were de novo assembled using the PacBio long reads. The error-corrected PacBio reads corresponding to the three symbiont genomes were first extracted by aligning the reads to the reference sequences of related species [http://zombie.cb.k.u-tokyo.ac.jp/sprai/). The final assembled contigs were corrected for base errors with iCORN2 [The genomes of the three symbionts present in  species –90. The h iCORN2  using thh iCORN2  and Glimh iCORN2 . The finh iCORN2 . The preh iCORN2 .B. tabaci genome sequences were first masked for repeat regions, and then translated in six frames. Potential polypeptides (PPPs) having lengths of at least 60 amino acids were kept. Furthermore, the high-quality and cleaned RNA-Seq datasets were de novo assembled using Trinity [B. tabaci genome, and only those that could be aligned were used in the analysis. To identify HGTs of bacterial origin, the assembled transcript and genome-translated PPP sequences were compared against two protein databases derived from complete proteomes in UniProt [h, was calculated by subtracting the bit score of the best eukaryote match from that of the best bacteria/fungus match. We defined candidate HGTs as those with h ≥ 30 and the bit score of the best bacterial or fungus protein hit ≥100 as described in Crisp et al. [The  Trinity . The ass UniProt , one conp et al. . For eacp et al. . Each alp et al.  using a


B. tabaci populations collected from various agricultural areas across the country and we determine their biotype status. Molecular data were subsequently interpreted in an ecological context supplied from a species distribution model to infer habitat suitability and hereafter the potential connection paths between sampling localities. An analysis of landscape resistance to B. tabaci genetic flow was thus applied to take into account habitat suitability, genetic relatedness and functional connectivity of habitats within a varied landscape matrix. We shed light on the occurrence of three geographically delineated genetic groups with high levels of genetic differentiation within each of them. Potential migration corridors of this pest were then established providing significant advances toward the understanding of genetic features and the dynamic dispersal of this pest. This study supports the hypothesis of a long-distance dispersal of B. tabaci followed by infrequent long-term isolations. The Inference of population sources and colonization routes is critical for the design and implementation of accurate management strategies against this pest.Combining landscape ecology and genetics provides an excellent framework to appreciate pest population dynamics and dispersal. The genetic architectures of many species are always shaped by environmental constraints. Because little is known about the ecological and genetic traits of Tunisian whitefly populations, the main objective of this work is to highlight patterns of biodiversity, genetic structure and migration routes of this pest. We used nuclear microsatellite loci to analyze  Bemisia tabaci, is an economically important agriculture pest consisting of at least 34 cryptic members [B. tabaci, 34 genetic groups have been discriminated [B. tabaci is now considered as a complex of well-defined groups that are referred to biotypes and which are distinguishable according to host specialization, reproductive compatibility, differential resistance to different classes of insecticide and efficiency in transmitting phytoviruses [The sweet potato whitefly,  members . It is h members ,3. Basediminated . Currentiminated ,5. B. taoviruses .B. tabaci is expanding its distribution in the Mediterranean basin [B. tabaci populations, and so their potential geographic range [B. tabaci across the landscape [Both direct observation and model predictions show that an basin . Temperaic range ,8. Host andscape ,10. Undeandscape ,12. Answandscape –15, whicandscape ,17.B. tabaci population dynamics and dispersal in Tunisia. Previously, it was reported that the high divergence between the mitochondrial cytochrom oxidase I (mtCOI) sequences among B. tabaci clades suggested that ecological factors, particularly climatic and tectonic events, have contributed to the extreme diversification of B. tabaci [B. tabaci population were assessed a few years ago [TaqI) of the mtCOI gene and sequencing indicated that the sampled whiteflies clustered into the B and Q biotypes. Genetic investigation driven by several approaches including molecular variance (AMOVA), selective neutrality and genetic haplotype network tests supported the hypothesis that Tunisian B. tabaci populations underwent a potential expansion followed by gene flow restriction [The population genetics of many pest species are shaped by environmental gradients ,19. A co. tabaci ,6,20. Inears ago . In depttriction .B. tabaci groups and thus, could be used as ‘‘integrated barcodes”, they do not answer the same questions as integrated nuclear, morphological, and ecological data sets [B. tabaci populations. Out of the 50 described loci [B. tabaci genetic studies [Although mtCOI markers have been extensively used to provide insights into ata sets ,23. Suchata sets ,24. In cbed loci ,25–29, a studies , were seB. tacaci population and species distribution modeling (SDM) [B. tabaci populations in Tunisia. We used large-scale SDM to infer the climatic suitability of the landscape for B. tabaci and pathways based on least-cost distance between individuals with a high level of genetic relatedness. Using this approach, we mapped landscape resistance to B. tabaci genetic flow and we identified the landscape elements, such as natural barriers, that isolate B. tabaci populations and the potential connection corridors between sampling localities. These corridors reflected the dual sources of the connection: both genetic distance and environmentally suitable paths of migration inferred from the SDM. Thus, modeling landscape resistance and potential migration corridors represents a major advance for the prioritizing B. tabaci elimination campaigns, at the national level.Molecular data are also important and useful in conjunction with other sources of information such as ecology data ,30. By mng (SDM) , we wereB. tabaci adults corresponding to 59 distinct populations were collected during 2014–2016 from both open fields and greenhouses . The mixture was incubated for 60 min at 55°C, then at 100°C for 10 min, and finally at 0°C for 5 min. A centrifugation step was performed at 1,000 rpm for 5 min to pellet debris. DNA quantification was performed with ND-1000 spectrophotometer .B. tabaci samples was determined through (i) The PCR- RFLP (TaqI) of a fragment of the mitochondrial gene (mtCOI) [31 imp [Taq DNA polymerase (MP BIOMEDICALS), 2 μl of extracted DNA, and sterile water. PCR amplifications were performed on a T professional trio system thermalcycler  using the following cycling program: One first denaturation step of 4 min at 94°C followed by 35 amplification cycles . A final step of extension is performed at 72°C for 10 min. PCR products were purified  and digested with 1 U of TaqI restriction enzyme with 2 μl of the corresponding buffer (10X) in a final volume of 20 μl, for 2 h at 65°C. PCR products or cleaved fragments were separated in 2% agarose gel and visualized by staining with ethidium bromide. For the second approach, microsatellite marker amplifications were carried out using primers developed by [The Biotype status of  (mtCOI)  and (ii) [31 imp . For the [31 imp , 5 μl ofloped by  and valiloped by . PCR-ampSeven microsatellite markers were selected based on their previous use . AmplifiB. tabaci populations, the basic genetic population parameters such as the number of alleles detected per locus (Na), the polymorphism information content (PIC) values, the observed (Ho) and the expected heterozygosity (He) as well as significance values for deviations from the Hardy–Weinberg equilibrium (HWE) were determined.To evaluate the genetic diversity of Multiple co-inertia analysis (MCOA) approach was performed to identify alleles characterizing geographic groups and to evaluate the efficiency of each marker to build population structure since this technique allows each locus to be analyzed separately . Then, tB. tabaci is unlikely to occur. ENFA is a specific multivariate ordination technique that relies on presence-only data to compare a species’ environmental niche and the environmental characteristics of the studied area. To this end, ENFA compares the distribution of the environmental predictors between the occurrence locations and the whole studied area and assigns a degree of suitability to each point on a map . We used as environmental predictors 19 bioclimatic variable data provided by WorldClim database (version 1.4) [B. tabaci [Ecological niche factor analysis (ENFA)  was usedion 1.4) . This bi. tabaci ,43.http://data.gbif.org, 2016)  . To evalB. tabaci and the great number of host species for this phytophagous insect [http://www.glcn.org/databases/lc_gc-africa_en.jsp) at 300-m resolution. The resulting map, reflecting both abiotic  and biotic (host and/or prey availability) constraints, was used to create a resistance surface. To this end, a transition matrix was computed from the habitat suitability values to define the connectedness between adjacent pixels. We used King's graph as a neighborhood function, in which a given pixel is considered to be connected to the eight adjacent pixels. Each cell on a resistance surface is assigned a cost value, with high costs given to unsuitable cells that restrict dispersal and low costs to suitable cells that facilitate dispersal [B. tabaci to traverse a cell, which could be in this case a function of mortality risk, energetic costs, food availability and interactions between each of these factors.Climatic suitability cells located in Tunisia were first taken from the ENFA prediction map. Given the strong link between s insect , we assiispersal . Thus, hST paire-wise genetic distance matrix, we extracted likely genetically identical samples: pairs with Wright's FST index [Based on a Wright's FST index  lower thST index ,50. The All data processing and statistical analysis were performed using R 3.1 .B. tabaci populations collected on different hosts throughout the country and clustered them into three major geographic groups: North, Sahel and South (B. tabaci populations were assigned to either biotype B or Q according to PCR-RFLP (TaqI) patterns of the mtCOI gene fragment in conjunction with a diagnostic microsatellite marker. Two restriction patterns  and  corresponding to biotype B and Q respectively, were revealed  per locus ranged from 6 (detected in locus 177 in the Sahel) to 18 (detected in locus BT4 in the North). The North displayed the highest average Na value (13.42) while the Sahel showed the lowest (8.00). The observed (Ho) and expected (He) heterozygoties ranged from 0.001 to 1.00 and from 0.74 to 0.92 respectively. Regarding polymorphism information content (PIC), all considered loci displayed high values, ranging from 0.82 to 0.92, attesting to the effectiveness of these SSR markers for detecting variability .Out of the 113 revealed alleles, 19, 57 and 29were not detected in the North, the Sahel and the South, respectively. Subsequently, we outlined the most group-specific alleles for each region corresponding to 23 alleles in the North, 11 alleles in the South and only 3 specific alleles in the Sahel .B. tabaci populations, based on allelic frequencies and single-marker analysis  whereas variation among localities within geographic groups accounted for 0.141% and 2.063%, respectively. Results also showed that genetic differentiation among the three geographic groups was very limited . It was assumed that the largest part of variability could be attributed to differences between localities devoted to each geographic group rather than between groups themselves [B. tabaci populations [B. tabaci populations on the island of La Réunion [ Tunisia ,53, but emselves ,53. Beyoulations . SSR marulations . Indeed, Réunion , around  Réunion , 57,58 a Réunion .B. tabaci populations. The MCOA two-dimensional space is a useful graphical tool that compares the usefulness of each marker for discriminating populations. This method provides a systemic view of the whitefly population structure focusing on the part of each allele in building it. Based on allelic frequencies of single-markers, the MCOA approach allowed the identification of those alleles that contribute most to the genetic topology of Our results also suggested that there was a low level of geographic isolation between the geographic groups. The major part of genetic diversity was observed at the population level within geographical groups for both the B  and the Q  biotypes. Only 60% of defined genotypes were assigned to the geographic group where they were collected. Genotypes therefore displayed variability within the same geographic group and could be closely related to genotypes in distinct geographic groups.B. tabaci using the ENFA model showed geographical patterns of distribution similar to those obtained by [B. tabaci. The kernel density estimates of annual mean temperature values within occurrence data show thermal tolerance limits between 10–37°C with an optimum at 26°C , was used to create a resistance surface  and thenthe wind . This isthe wind . Our dat studies  suggestec groups . Indeed,B. tabaci, we have provided the first pest risk analysis of B. tabaci to plant health in Tunisia. The predictions of areas suitable for establishment can be used to support pest management tactics and strategies such as incursion monitoring in areas not yet infested but having a high risk of infestation (cf. as is the case for north-western regions). However, it is important to note that predictions made in this study reflect only the potential distribution of B. tabaci. Thus, we propose in the future to refine the method by also mapping the current distribution of B. tabaci. Accurately mapping such distribution and projecting the potential distribution of B. tabaci are both relevant tasks for managing this plant pests. For instance, control and eradication efforts should focus on the current distribution while containment efforts should focus on the interface between the current and potential distributions [B. tabaci interactions and the integration of wind effects on dispersion using for instance Lagrangian dispersion models.The knowledge gained during this study have several applications for pest management. First, by developing a map of the potential distribution of ibutions . MappingB. tabaci predators in crops to decrease both pest population densities and dispersal. Indeed, the use of host plants infested by predators early in the season, in the proximity of crops which are often infested by whiteflies and taking into account preferential routes of migration would permit predators populations to be established prior to whitefly attack. To fully exploit an IPM over a long time scales, knowledge of the parasitic or predatory natural enemies of B. tabaci should be further investigated. Generalists ‘predators have been shown to reduce pest pressure and to enhance natural enemy activities [B. tabaci biological control agents corresponding to a mixture of the polyphagous predatory Coleoptera and two whitefly-specific parasitoids have been tested to be implemented in the design of biological pest control plans [The thorough understanding of whitefly population structure and migration corridors of whiteflies is also particularly important for proper management guidance to plan an effective integrated pest management strategy (IPM) in Tunisia. Today, particular attention is paid to enhancing biological control methods. This would require the use of tivities . They activities . Employitivities ,66. Indeol plans . ExploriS1 FigTaqI digestion.L: Ladder 100 bp, Biomatik. Pattern 1: 634bp, 144bp corresponding to Q biotype. Pattern 2: 440 bp, 220bp, 144 bp corresponding to B biotype. (-): Negative control: mtCOI amplified fragment (778 bp) without (TIF)Click here for additional data file.


Phaseolus vulgaris L., characterizing 86 geo-referenced wild accessions using genotyping by sequencing (GBS) to discover single nucleotide polymorphisms (SNPs). The wild beans represented Mesoamerica, Guatemala, Colombia, Ecuador/Northern Peru and Andean groupings. We found high polymorphism with a total of 22,845 SNPs across the 86 accessions that confirmed genetic relationships for the groups. As a second objective, we quantified allelic associations with a bioclimatic-based drought index using 10 different statistical models that accounted for population structure. Based on the optimum model, 115 SNPs in 90 regions, widespread in all 11 common bean chromosomes, were associated with the bioclimatic-based drought index. A gene coding for an ankyrin repeat-containing protein and a phototropic-responsive NPH3 gene were identified as potential candidates. Genomic windows of 1 Mb containing associated SNPs had more positive Tajima’s D scores than windows without associated markers. This indicates that adaptation to drought, as estimated by bioclimatic variables, has been under natural divergent selection, suggesting that drought tolerance may be favorable under dry conditions but harmful in humid conditions. Our work exemplifies that genomic signatures of adaptation are useful for germplasm characterization, potentially enhancing future marker-assisted selection and crop improvement.Drought will reduce global crop production by >10% in 2050 substantially worsening global malnutrition. Breeding for resistance to drought will require accessing crop genetic diversity found in the wild accessions from the driest high stress ecosystems. Genome–environment associations (GEA) in crop wild relatives reveal natural adaptation, and therefore can be used to identify adaptive variation. We explored this approach in the food crop  Arabidopsis lyrata, Arabidopsis thaliana, Arabidopsis halleri, Fagus sylvatica, and Understanding the genomic signatures associated with environmental variation is of great interest as it provides insights into how organisms adapt to their environment . Recent Arabidopsis for drought resistance and water use efficiency, Medicago truncatula, Sorghum bicolor, and Cenchrus americanus. Our group has focused on exploring the marker × environment association approach with wild relatives of the food crop common bean (Phaseolus vulgaris L.) and we have shown candidate genes such as DREB, ASR, and ERECTA to have haplotypes associated with drought tolerance  finding 3,200–21,000 SNPs/genotype. MseI and TaqI enzymes along with size selections to compare the feasibility of double digestion and small fragment size generation with four bp cutters, to the ApeK1 method for 25 Mesoamerican beans, finding up to 12.5 times more usable SNPs with an 8X coverage. More recently, Among the most comprehensive marker systems for common bean SNP detection is the method called genotyping by sequencing (GBS). This technique has the flexibility of being adaptable to wild relatives with no previous sequence information needed although a reference genome for the species is useful . To dateWild bean are thought to have diverged from its sister species in the tropical Andes  to laterFurther wild germplasm characterization is important as common bean is a key source of nutrients and dietary protein for over 500 million people in Latin America and Africa and more than 4.5 out of 23 million hectares are grown in zones where drought is severe, such as in northeastern Brazil, coastal Peru, the central and northern highlands of Mexico, and in Eastern and Southern Africa . This siPhaseolus vulgaris were used in this study, extracted from 86 geo-referenced wild common bean accessions (Supplementary Table S1). All the genotypes were provided by the Genetic Resources Unit at the International Center for Tropical Agriculture and are preserved under the treaty for genetic resources from the Food and Agriculture Organization hereafter abbreviated as the FAO collection. These accessions were selected to be a representative of a core collection for wild beans , fed by monthly environmental data averaged for the years 1970–2000, is hereafter referred as bioclimatic-based drought index. Two properties of this index must be noted. First, it assumes that plant distribution is in equilibrium with niche requirements and ecological forces, so that the errant presence of poorly adapted genotypes can be discarded . One 96-plex GBS assay was made according to ApeKI digestions at the Biotechnology Resource Center of the Institute for Genomic Diversity . Genotyping and SNP calling were done with TASSEL software v. 3.0 . Genomic DNA was extracted using the QIAGEN DNeasy Plant Mini Kit , following the manufacturer’s instructions, and quantified using a Qubite v. 3.0  based one genome , using te genome . A custoP-values were inspected to assess whether excessive numbers of false positives were generated and choose in this way the optimum model. Significant associations were determined using a strict Bonferroni correction of P-values at alpha = 0.001, leading to a significance threshold of 4.4 × 10-8  or -log10(4.4 × 10-8) = 7.36. The construction of customized PCoA and Manhattan diagrams was carried out with the software R v.3.3.1 (R Core Team).In order to account for possible demographic effects we examined subpopulation structure in the 86 geo-referenced wild common bean accessions using principal coordinates analysis (PCoA) implemented in the software Trait Analysis by aSSociation, Evolution and Linkage, Tassel v.5 . The sam3.Potential candidate genes were identified within the 1,000 bp sections flanking each SNP marker that was associated with the bioclimatic-based drought index by using the common bean reference genome  and the 6 bps, step size = 200 kb) to describe patterns of variation and overall divergence across the genome. We computed per-window averages of SNP density, nucleotide diversity as measured by π  when computed in sliding windows that contained or did not contain at least one marker that was associated with the bioclimatic-based drought index. Each summary statistic of windows containing and not containing associated SNPs was randomly resampled with replacement (bootstrapping) across windows within grouping factor (associated vs. no associated), and the overall mean was stored for each grouping factor. This step was iterated 1,000 times using customized R scripts. Bootstrapping was performed independently for each summary statistic in order to eliminate correlations among these.P. vulgaris reference genome, 10.1% had multiple matches and 18.7% were unaligned. A total of 197,314 putative SNP markers where identified in the aligned tags. Of these, 47% with more than 20% missing data, a default threshold used for GBS studies . The centromeres according to The raw Illumina DNA sequence data  were processed through the GBS analysis pipeline as implemented in TASSEL-GBS v3.0. The GBS analysis generated 1,625,330 unique sequence clusters tags, . Of the  studies , and fur studies . Still tFigure 2, compare to Supplementary Figure S2) whereas MLM models controlling for population structure and using a kinship matrix more effectively reduced the false positive rate . The MLM model with the first two PCoA axes scores used as covariates, was the best at controlling for false positives because it exhibited the smoothest transition toward significant outliers.The GBS-derived SNP markers recovered the well-described Andean and Mesoamerican genepool structure and five within-genepool subpopulations, as depicted by the principal components analysis  . This group of SNPs had an average R2 of 51.3% ± 0.4, fairly stable across markers (Supplementary Table S2). The 115 SNPs were clustered in 90 different regions, defined here as overlapping 1,000 bp sections that flanked associated markers. Associated SNPs and regions were widespread in all 11 common bean chromosomes (Table 1).This last model yielded a total of 115 SNP markers associated with the bioclimatic-based drought index at the Bonferroni-corrected significance threshold of 7.36 -logR2 of 51.1% ± 0.3. After this chromosome, Pv3 was also notable for having four regions with an average number of 2.5 associated SNPs per region.Chromosomes Pv3 and Pv8 had the highest number of associated SNPs with 21 and 32 SNPs clustered in 16 and 21 different regions, respectively. Chromosomes Pv1, Pv2, Pv4, Pv5, Pv6, and Pv9 contained an intermediate number of associated SNPs with 11, 6, 11, 7, 12, and 9 SNPs clustered in 11, 6, 8, 6, 8, and 9 different regions, respectively. Chromosomes Pv7, Pv10 and Pv11 had the fewest number of associated SNPs with 3, 2, and 1 SNPs clustered in 3, 1, and 1 different regions, respectively. Chromosome Pv8 had more regions with at least two associated SNPs than any other chromosome, and these regions had more associated SNPs that in any other chromosome for a total of five regions with an average number of 3.2 associated SNPs in each region. The single region that contained the most associated SNPs was also situated on chromosome Pv8 with 6 SNPs and an average Supplementary Table S3). Most genes were from chromosomes Pv1, Pv3, and Pv8 with 11, 14, and 16 genes. Only two regions, at chromosomes Pv1 and Pv8 and containing a total of seven different SNPs, spanned two or more genes. The one in Pv8 was the region with more associated SNPs. One of the two genes in this region encoded an ankyrin repeat-containing protein, which was associated with osmotic regulation via the assembly of cation channels in the membranes  was used to explore the patterns of genome-wide diversity. Marker density decayed drastically toward the centromeres. Average marker density was 44 SNPs per million base pairs . Average nucleotide diversity as measured by π was 0.3 per million base pairs . Average Watterson’s theta (𝜃) was 0.20 per million base pairs . Average Tajima’s D was 0.68 per million base pairs .A sliding window analysis , lower scores for Watterson’s theta (𝜃) scores  and more positive Tajima’s D scores  than windows without associated markers. Nucleotide diversity, as measured by π, was slightly elevated in associated windows when compared with no associated windows .These statistics were compared between 1 Mb sliding windows that contained (associated windows) or did not contain at least one marker that was associated with the bioclimatic-based drought index (non-associated windows). Genomic windows containing at least one associated SNP had overall higher SNP density . Both of these results imply that the genetic sources for drought tolerance are abundant in wild common bean and that natural drought tolerance may be favorable under dry conditions but harmful in more humid conditions. The awareness about this trade-off, upon which natural divergent selection has been acting for thousands of years, may aid the breeding of new drought tolerant varieties specifically adapted to unique micro-environments and local regions rather than varieties, eventually obsolete, originally intended for a wider range of environments. Below we first discuss the evidence that support the main conclusion of widespread divergent adaptation to drought. Later, we follow up by discussing the implications of this finding.It is well known that selective processes, such as purifying selection and local adaptation (divergent selection), differentially imprint regions within the same genome, causing a heterogeneous departure of genetic variation from the neutral expectations and from the background trend . SpecifiSince divergent selection tends to homogenize haplotypes within the same niche and fix polymorphisms in different populations, few haplotypes with high frequency are retained, matching high values of nucleotide diversity and Tajima’s D, and low values of the Watterson’s theta (𝜃) estimator . In thisYet, genomic signatures associated with habitat heterogeneity can still result from causes other than adaptation and selection , for exaApeK1 restriction enzyme for the first time in wild accessions of common bean, possibly leading to problems like missing data due to sequence divergence compared to the cultivated reference genome. Nonetheless, wild-cultivated divergent regions with a high proportion of missing data seem to be rare because the U-shaped pattern of SNP density is just as expected when using a non-methylation sensitive enzyme. This decay in diversity proportional to the decay in the rate of recombination (toward the centromeres) was first described in D. melanogaster and has been confirmed in many organisms since then  that is known for growing in desert and semi-arid environments. Our group is currently running this initiative as part of a larger project spanning several other candidate genes, such as DREB, ASR, and ERECTA (The potential candidate genes identified in this study should be validated as candidates for drought tolerance through re-sequencing and controlled drought stress treatments under green house and field conditions, ideally in a diverse panel of common bean accessions and closely related species, such as Tepary bean (d ERECTA .The work presented here ultimately illustrates that genomic signatures of adaptation are useful for germplasm characterization, potentially enhancing future marker-assisted selection and crop improvement. We envision that GEA studies coupled with estimates of genome-wide diversity will become more common in the oncoming years. They both might allow assessing the naturally available genetic variability for adaptation to various types of stress that, like drought, are expected to worsen with climate change. For instance, frost , 2016, nThe pipeline configuration file and SNP dataset are archived at the Dryad Digital Repository under doi: 10.5061/dryad.j2c24.AC designed the study with insights from MB. AC collected and analyzed the data. AC wrote the manuscript with contributions from MB.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.


Meloidogyne species, cause extensive damage to agriculture and horticultural crops. As Vitis vinifera cultivars are susceptible to root knot nematode parasitism, rootstocks resistant to these soil pests provide a sustainable approach to maintain grapevine production. Currently, most of the commercially available root knot nematode resistant rootstocks are highly vigorous and take up excess potassium, which reduces wine quality. As a result, there is a pressing need to breed new root knot nematode resistant rootstocks, which have no impact on wine quality. To develop molecular markers that predict root knot nematode resistance for marker assisted breeding, a genetic approach was employed to identify a root knot nematode resistance locus in grapevine. To this end, a Meloidogyne javanica resistant Vitis cinerea accession was crossed to a susceptible Vitis vinifera cultivar Riesling and results from screening the F1 individuals support a model that root knot nematode resistance, is conferred by a single dominant allele, referred as MELOIDOGYNE JAVANICA RESISTANCE1 (MJR1). Further, MJR1 resistance appears to be mediated by a hypersensitive response that occurs in the root apical meristem. Single nucleotide polymorphisms (SNPs) were identified using genotyping-by-sequencing and results from association and genetic mapping identified the MJR1 locus, which is located on chromosome 18 in the Vitis cinerea accession. Validation of the SNPs linked to the MJR1 locus using a Sequenom MassARRAY platform found that only 50% could be validated. The validated SNPs that flank and co-segregate with the MJR1 locus can be used for marker-assisted selection for Meloidogyne javanica resistance in grapevine.Plant parasitic nematodes, including root knot nematode  Plant parasitic nematodes are major soil-borne pests that cause extensive damage to a wide range of crops with an estimated cost of $80 billion (USD) per year . To dateV. vinifera  x V. x champinii, open pollinated Dogridge 5) [V. x champinii, open pollinated Dogridge 5) are highly vigorous and take up excess potassium, which reduces wine quality [V. champinii and 1613 Couderc [V. acerifolia x V. riparia) and 1613 Couderc, using a Design II mating analysis [V. rupestris x V. vinifera [V. riparia x V. rupestris) [The commercially available grapevine rootstocks that display resistance to root knot nematode such as Dog Ridge  –17, recepestris) .Vitis spp. [V. cinerea Engelm. Ex Millard is highly resistant to a M. incognita pathotype identified in California [V. cinerea accession called a C2-50, which provides complete resistance to an aggressive M. javanica pathotype. In order to develop molecular markers for predicting root knot nematode resistance in grapevine, the V. cinerea C2-50 accession was crossed to a susceptible V. vinifera cultivar Riesling. Using a root knot nematode-screening assay, F1 individuals were screened and results indicate that root knot nematode resistance is conferred by a single dominant allele. A genotyping-by-sequencing approach was used for association genetics and to generate genetic maps. Both approaches were used to localize the root knot nematode resistance locus to a chromosome region. A subset of SNPs surrounding the root knot nematode resistance locus was validated for potential use for marker-assisted breeding. Using an in vitro screening method, root knot nematode resistance appears to be mediated by cellular necrosis in the root meristem, which may function to limit migration of the nematode.Marker assisted selection is an effective approach to combine desired traits of interest into crop breeding programs –21. Nexttis spp. –29, as wtis spp. . A previlifornia . It was 1 individuals derived from a cross of a V. cinerea accession C2-50  with V. vinifera Riesling  were planted at the CSIRO vineyard. DNA typing was performed using ten microsatellite markers, VVS2 [1 individuals before initiating the root knot nematode screening assay. Three dormant cuttings for C2-50, Riesling and the 90 F1 individuals were propagated and transplanted into 6.5 x 6.5 x 20 cm pots for nematode screening. Four to five weeks after transplanting the rooted cuttings in soil, the vines were screened for root knot nematode resistance.Ninety Frs, VVS2 , VVMD5, rs, VVS2 , VrZAG62rs, VVS2 , VVMD27,rs, VVS2  and VVIPrs, VVS2  to verifM. javanica ‘pt 1103P’ pathotype, which is able to effectively parasitize the moderately resistant 1103 Paulsen rootstock, was used in the root knot nematode screening assay [M. javanica ‘pt. 1103P’ was propagated on susceptible Solanum lycopersicum (tomato) cv California Red Cherry plants at 22–25°C in a glasshouse. Eight weeks after inoculation, galls containing the M. javanica ‘pt. 1103P’ egg masses were dissected from the infected tomato roots and incubated in water at 30°C for 72 h to promote hatching. Subsequently, a 500 μl aliquot of hatched nematodes was pipetted onto a microscope slide and the number of juvenile nematodes was counted using a Zeiss Stemi 2000-C stereomicroscope. Based on the number of nematodes per 500 μl, approximately 1000 M. javanica ‘pt. 1103P’ juveniles were added to each potted cutting and incubated for 8 weeks in the glasshouse at 22–25°C. Plants were classified as susceptible if the root knot nematodes are able to complete their life cycle by producing egg masses on the roots. For egg mass determination, the roots for each replicated cutting were washed gently in water to remove the soil and incubated in 0.01 g/L of erioglaucine disodium salt for 60 min to stain the egg masses. Egg masses were counted under a Daylight Magnifying Lamp (Model number: A22020-01). A chi-square goodness of fit test was performed with the phenotype data using X2 = total of (O-E)2/E for resistance and susceptible phenotypes, with one degree of freedom. For each replicated screen, C2-50 and Riesling were included as controls for resistant and susceptible genotypes.The aggressive ng assay . M. java1 individuals was performed at the Australian Genome Research Facility using the Nucleic Acid Extraction service, which utilizes the NucleoSpin® 96 Plant II DNA extraction kit (http://www.mn-net.com). The Cornell University Biotechnology Resource Center (BRC) provided the GBS service as described by [ApeKI methylation sensitive restriction endonuclease to reduce genome complexity prior to the construction of the library. Single-end 100 bp sequence reads were generated using Illumina HiSeq 2000/2500 . Note: the library was generated from a 96 well-plate containing the 90 F1 individuals and two samples of Riesling and C2-50. This library was sequenced 2X in order to maximize the number of reads at each locus. SNP discovery and genotyping was performed by the BRC as described by [V. vinifera ‘PN40024’ reference genome [http://datadryad.org/review?doi=doi:10.5061/dryad.1d7n9.DNA isolation for C2-50, Riesling and the Fribed by . Brieflyribed by . In thise genome  using Bue genome . SNPs wee genome . The vare genome  consistee genome . In thise genome . The C2-M. javanica ‘pt 1103P’ resistance using TASSEL 5.0 [1 individuals. Association mapping using the general linear model (GLM) was used to analyze the C2-50 and Riesling numerical data sets with 1000 permutations. For association mapping using the mixed linear model (MLM) [p-values identified by GLM and MLM were adjusted for false discovery rate according to the Bonferroni and Benjamini-Hochberg procedures using the R/multtest package [Single SNP association analysis was performed with the C2-50 (3974) and Riesling (2973) SNP sets to identify markers that associate with SSEL 5.0 . Resultsel (MLM) , a kinshel (MLM) . The raw package .http://datadryad.org/review?doi=doi:10.5061/dryad.1d7n9.Linkage mapping was performed with R/OneMap  using thMJR1 locus were used to create 372 C2-50 SNP set, S18_26580875 (92.5 cM), S18_26558715 (93.6 cM), S18_27884817 (95.9 cM), S18_30104225 (97.0 cM), S18_30236024 (98.1 cM), S18_31160355 (99.2 cM), S18_32680428 (100.3 cM) and S18_33954011 (101.4 cM). Note: S18_27884817 was present in the 367 SNP set. To perform the binary trait method, the resistant and susceptible phenotypes were converted to values equal to 0 and 1, respectively. The one-dimensional genome scan was performed using the scanone function with the argument model = ‘binary’. The LOD threshold value was determined by 1000 permutations with alpha = 0.05. For single-QTL analysis, two phenotype data sets were used for interval mapping: (1) the average number of egg masses per root system (EM/R) and (2) the average number of egg masses per root weight (g: EM/RW). After importing the C2-50 and Riesling maps together with the genotype and phenotype data, the calc.genoprob function with step = 1 was used to calculate multipoint genotype probabilities. Next, the one-dimensional genome scan was performed using the scanone function with the Haley-Knott regression method, method = “hk”. LOD threshold values were estimated by 1000 permutations .Interval mapping was performed using R/QTL . The C2-1 individuals plus C2-50 and Riesling Nucleic Acid using the NucleoSpin® 96 Plant II DNA extraction kit. Thirty SNPs that spanned the M. javanica ‘pt. 1103P’ resistance locus were validated using the SNP genotyping Sequenom MassARRAY iPLEX platform  [http://www.agrf.org.au/services/genotyping). The SNP genotypes determined by the GBS pipeline and the Sequenom MassARRAY platform were compared to validate each SNP.DNA was isolated from 65 FCA, USA) . This SNM. javanica ‘pt 1103P’, twenty egg masses were isolated from tomato roots and surface sterilized by vigorously shaking the eggs in 0.5% chlorine solution for 4 min at 22°C. After centrifugation at 1000 xg for 5 min, the chlorine solution was removed and the eggs were washed with sterile water five times in laminar flow cabinet to remove residual chlorine. After the final wash, the eggs were resuspended in 1.0 ml of sterile water and incubated at 30°C to promote hatching. To maintain a sterile culture of root knot nematodes, Cucumis sativus roots were inoculated with sterile M. javanica ‘pt 1103P’ juveniles and egg masses were collected and hatched [To obtain a sterile population of  hatched .1 individuals. After removing the leaves, the nodal cuttings were washed in sterile water. Ten nodes from each genotype were incubated in a solution containing 5% active chlorine plus 0.1% Tween 20 for 12 hrs at 22°C. In a laminar flow cabinet, nodal cuttings were rinsed three times with sterile water and the basal end of the node was trimmed and inserted in callus initiation media (PIV) [Single node cuttings, 3–4 cm in length with a stem diameter of approximately 5 mm, were isolated from developing shoots of C2-50, Riesling and 12 C2-50 x Riesling Fia (PIV) . After bia (PIV) .2EDTA and 1.86 g/L FeSO4), 3% sucrose and 0.8% phytagel, pH 5.7 (KOH), for two days at 24°C in the dark. After isolating M. javanica ‘pt 1103P’ juveniles as described by [M. javanica ‘pt 1103P’ juveniles per volume of sample. Roots from C2-50, Riesling and 12 C2-50 x Riesling F1 individuals were inoculated with approximately 25 M. javanica ‘pt 1103P’ juveniles and incubated at 24°C in the dark. Roots were visually inspected for a hypersensitive response (HR), root growth cessation and gall formation every 10–12 hours. For each genotype, control roots were inoculated with sterile water to access the viability of the roots. For each experiment, not all of the roots on each plate displayed a response, such as gall formation or HR, after incubation with the juvenile nematodes. Therefore, we calculated the percentage of roots that displayed gall formation or HR. Roots from each genotype were screened at least three times. Roots were imaged using a Zeiss Stemi 2000-C stereomicroscope with a Spot FLEX® digital camera.For the root knot nematode screening, 8–10 roots were excised from each genotype and placed on nematode screening media (NSM) containing macroelements and microelements , B5 vitaribed by , the numM. javanica pt ‘1103P’. During this step, roots were monitored during the incubation period and immediately placed in water when the transparency of the necrotic region was reduced. After rising 5 times in water, the roots were boiled in an acid fuchsin staining solution (3.5% acid fuchsin and 25% acetic acid in water) for 10 sec then cooled to 22°C. Finally, the roots were incubated in a destaining solution (33% acetic acid and 33% glycerol in water) for 4 hours and the roots were imaged using a Zeiss Axioskop2 microscope with a Spot FLEX® digital camera.To visualize nematodes, the in vitro grown roots were incubated in 10% bleach for 5–10 min, three days after inoculation with V. cinerea C2-50, an accession in the CSIRO Rootstock Collection, were screened for root knot nematode resistance and results showed that M. javanica ‘pt 1103P’ failed to parasitize this accession, as no egg mass development occurred on the roots for each of the replicated cuttings , is conferred by a single allele in C2-50, which can be explained by two hypotheses. In the first hypothesis, C2-50 is heterozygous dominant for MJR1 (MJR1/mjr1) and Riesling is homozygous recessive (mjr1/mjr1). Alternatively, the second hypothesis predicts that resistance is conferred by a recessive allele (mjr1), in which C2-50 is homozygous (mjr1/mjr1) and Riesling is heterozygous (MJR1/mjr1) for the recessive allele.Using a glasshouse based root knot nematode screening method , 90 F1 i1 individuals, as well as C2-50 and Riesling parents. Next generation sequencing produced 345,007,280 acceptable sequence reads (Genotyping-by-sequencing (GBS) was performed on the 90 Fce reads  and the ce reads . After Sce reads . Given tce reads . After Sce reads . In ordece reads . Note: SMJR1 using the C2-50 (3974 SNPs) and Riesling (2973 SNPs) SNP sets. Using this approach, 7 SNPs on chromosome 18 from position 31787750 to 33070986 in the C2-50 SNP set had high association based on p-values equal to 0 and R2 equal to 1 .A single SNP association analysis using GLM was performed to map ual to 1 . In addito 0.955 . In addito 0.955 . To furtto 0.871 . In contto 0.871  Tables. Vitis genetic maps produced by next generation sequencing [The C2-50 and Riesling SNP sets were reduced to 367 and 403 SNPs, respectively, as described in the material methods and R/OneMap was used to curate and construct the genetic maps. For each SNP set, 19 linkage groups (LGs) were produced and the final size for the C2-50 and Riesling genetic maps were 1587.3 and 1706.4 cM, respectively  Tables, quencing ,25,26,28MJR1 locus, the phenotype data for each F1 individual was converted to a genotype. Given that the phenotype data closely matched a 1:1 ratio and SNPs from C2-50 on chromosome 18 display high association with M. javanica ‘pt 1103’ resistance, it is highly likely that the genotype of the C2-50 was heterozygous for MJR1, while Riesling was homozygous recessive. Therefore, resistant and susceptible F1 individuals were assigned either an MJR1/mjr1 or mjr1/mjr1 genotype, respectively. To map the MJR1 locus, the MJR1 marker was included in the reduced C2-50 (367) and Riesling (403) SNP sets and linkage analysis was performed using R/OneMap. Results from the genetic mapping showed that MJR1 mapped to linkage group 18 (LG18) at 102.6 cM using the C2-50 367 SNP set .In order to map the  SNP set . In thisectively . When thMJR1 using the binary and standard models available in R/QTL [p-value = 0.0) at 106 cM, which is in close proximity to S18_33162606 at 105.9 cM    . Alterna= 0.003) , results= 0.008) . Both LO SNP set .MJR1 locus was to identify a set of SNPs for predicting resistance to M. javanica ‘pt. 1103P’ for marker assisted selection. Therefore, 36 SNPs that mapped in close proximity to MJR1 were selected for SNP genotyping using the Sequenom MassARRAY platform [MJR1  was detected on LG18 and cosegregated with S18_32680428 at position 100.3 cM  or 7.75 , respectively, which is in close proximity to S18_32680428 , zero egg masses developed on the resistant F1 individuals, while a range of egg masses developed on the susceptible F1 individuals .The ividuals . Using tot trail . Gallingot trial . Cellula1 mapping population derived from a C2-50 x Riesling cross was used to map the M. javanica ‘pt. 1103P’ resistance locus, MJR1. Results from the nematode-screening assay performed on the parents and F1 individuals indicated that M. javanica ‘pt. 1103P’ resistance is controlled by a single dominant allele, which is derived from the C2-50 female parent. Genetic studies indicate that resistance to M. incognita is conferred by a single dominant allele in the V. champinii rootstocks Harmony, Freedom, Dog Ridge and Ramsey [V. champinii derived rootstocks.In this manuscript, an Fd Ramsey . At thisM. arenaria ‘pt Harmony’ for the nematode screening. Complete resistance with no egg mass development occurred in 10-23B (V. doaniana) [V. simpsoni) [M. arenaria ‘pt Harmony’ reproduction occurred in RS-3 (Ramsey (V. champinii) x Schwarzmann (V. riparia x V. rupestris)) [V. champinii) x Schwarzmann (V. riparia x V. rupestris)); [V. champinii x GA-3, 4, 5) [M. javanica ‘pt 1103P’ induced cell necrosis in the root meristem of the V. cinerea accession C2-50, which likely functions to inhibit root knot nematode migration, as well as perturb giant cell specification from vasculature initial cells. Given that the M. javanica ‘pt 1103P’ cellular necrotic induced phenotype was only apparent in the six resistant F1 genotypes this indicates that this mode of immunity is mediated by MJR1. The differences in the HR induced spatial patterns between C2-50, 10-23B, Demko 10-17A, RS-3 and RS-9 suggest that these genotypes possess different resistant genes, which is of interest for breeding rootstocks with durable resistance to root knot nematode.For protection against root knot nematode feeding, plants have evolved resistance mechanisms to reduce or eliminate reproduction. Experimental studies have shown that a subset of root knot nematode resistant plants exhibit a localized hypersensitive response (HR) induced during penetration, migration and/or gall development ,57. In goaniana)  and Demkimpsoni) . In 10-2impsoni) , while cimpsoni) . A low lestris)) , RS-9 (Rstris));  and 6-193, 4, 5) , which a3, 4, 5)  and 6-193, 4, 5) . In RS-93, 4, 5) . In contSolanum peruvianum, S. arcanum and Prunus cerasifera [R-genes containing the NB and LRR domains have been identified in the Vitis vinifera genome [R-genes and results showed that clusters of R-genes are located on chromosome 18 [MJR1. Chromosome 18 also contains loci, which confer resistance to Plasmopara viticola [Erysiphe necator [Vitis and Muscadinia species. Results showing a high level of sequence similarity between V. vinifera and M. rotundifolia at the Uncinula necator/Plasmopara viticola resistant locus on chromosome 12 indicates that the group of R-genes at this locus are evolutionarily related in these two species [R-genes, annotated as TMV resistance genes and 5 disease resistance genes implicated in plant immunity are located between S18_30711041 and S18_33954011 on chromosome 18 of PN40024 (data not shown), it may be possible that the resistant gene(s) at MJR1 in C2-50 are evolutionarily related to the resistant genes at the corresponding locus in V. vinifera.Genetic and molecular studies have resulted in the identification and functional characterization of root knot nematode resistance genes in rasifera –63. Thesa genome –67. An iviticola –75 and E necator ,77 in No species . Given tMJR1 locus. The TASSEL-GBS pipeline was designed for marker discovery and SNP calling in inbred crops with the aim of identifying a large number of markers at low sequencing coverage [MJR1 for marker assisted selection, results show that a validation step is necessary for assessing markers when the TASSEL-GBS pipeline is utilized for SNP discovery and genotyping in Vitis spp. and possibly other highly heterozygous plant species. To improve the accuracy of the SNP calling step, sequence tags >64 bp could be utilized for the alignment step. Alternatively, a RAD sequencing approach [Recent studies have utilized next generation sequencing approaches to generate genetic maps for identifying favorable horticultural traits including powdery mildew resistance/susceptibility, flower sex and fruit quality traits in grapevine –29. In ocoverage . While Gcoverage , as wellcoverage ,80, are coverage –21,81. Fcoverage –87. Whilapproach ,80 combiapproach .1 mapping population [M. javanica ‘pt 1103P’ resistance, SNPs that co-segregated and were tightly linked to MJR1 also displayed significant association with nematode resistance. As indicated by Barba et al., 2014, single SNP association can easily be performed with a greater number of markers compared to standard genetic mapping software. Therefore, single SNP association may serve as a useful tool to narrow down a set of markers for genetic mapping.Single SNP association analysis is used to map traits of interest in populations of unrelated individuals . Howeverpulation . ResultsMJR1 maps at approximately 100 cM on LG18 in V. cinerea C2-50. In addition, SNPs at the MJR1 locus had high genome wide association. Based on the position of these SNPs from 30711041 to 33954011 on chromosome 18 of the PN40024 reference genome, the estimated size of the MJR1 locus is 3.24 Mb. The resistance mechanism mediated by MJR1 involves localized cell necrosis in the root meristem, which may function to impair nematode migration and giant cell formation. Validated SNPs that cosegregate and the flank the MJR1 locus from 99.2 to 101.4 cM will serve as molecular markers for predicting root knot nematode resistance in V. cinerea C2-50 for rootstock development.In summary, traditional breeding approaches to develop rootstocks with resistance to plant parasitic nematodes and other soil borne pests is costly, time consuming and dependent upon labor-intensive work including plant propagation and nematode screening. However, employing a marker assisted breeding approach with molecular markers that predict nematode resistance would be an efficient and cost-effective approach. Moreover, marker assisted selection will allow for stacking multiple root knot nematode resistant loci into a single genetic background for producing new rootstocks with durable resistance. Using genetic mapping approaches, results show that S1 Fig1 individual. The standard deviation is displayed in the solid black lines. Note: egg mass development was detected on all three replicates for the susceptible F1 individuals.The (A) average number of egg masses per root system and (B) average number of egg masses per root weight (g) was determined by screening three propagated cuttings for each F(TIF)Click here for additional data file.S2 FigM. javanica ‘pt 1103P’ resistance using the Riesling 403 SNP set. No significant maximum LOD scores that were above the LOD threshold of 3.25 were detected in Riesling SNP set. for M. javanica ‘pt 1103P’ resistance. The LOD threshold was determined using 1000 permutations with alpha = 0.05.The binary model of mapping was used to localize (TIF)Click here for additional data file.S3 FigThe standard model of interval mapping identified a single QTL on LG18 for (A) egg mass per root system at 97 cM with a LOD score equal to 7.27, which was above the LOD threshold value equal to 5.34. A single QTL on LG18 for (B) egg mass per root weight was identified at 98 cM with a LOD score equal to 6.8, which was above the LOD threshold value equal to 4.77.(TIF)Click here for additional data file.S4 FigThe standard model of interval mapping was used to identify a single QTL in the Riesling 403 SNP set for (A) egg mass per root system (EM/R) and (B) egg mass per root weight (EM/RW). The LOD threshold values for EM/R and RM/RW were 6.14 and 4.80, respectively, with alpha = 0.05.(TIF)Click here for additional data file.S5 FigThe 372 C2-50 SNP set contains eight of the fifteen validated markers. The standard model of interval mapping identified a single QTL on LG18 at 100 cM using (A) egg mass per root system (EM/R) and (B) egg mass per root weight (EM/RW) with LOD values equal to 8.56 and 7.75. These LOD scores are above the threshold values equal to 5.54 and 4.81 for EM/R and EM/RW, respectively, with alpha = 0.05.(TIF)Click here for additional data file.S1 Tablep-values obtained from GLM were adjusted (Adj.) using Bonferroni and Benjamini-Hockberg (Ben Hoch). Note: the name of the SNP contains chromosome and position information. For example, S18_31787750 is located on chromosome 18 at position 31787750 in the PN40024 reference genome.Raw (XLSX)Click here for additional data file.S2 Tablep-values obtained from MLM were adjusted (Adj.) using Bonferroni and Benjamini-Hockberg (Ben Hoch). Note: the name of the SNP contains chromosome and position information. For example, S18_31787750 is located on chromosome 18 at position 31787750 in the PN40024 reference genome.Raw (XLSX)Click here for additional data file.S3 Tablep-values obtained from GLM were adjusted (Adj.) using Bonferroni and Benjamini-Hockberg (Ben Hoch). Note: the name of the SNP contains chromosome and position information. For example, S18_31114948 is located on chromosome 18 at position 31114948 in the PN40024 reference genome.Raw (XLSX)Click here for additional data file.S4 Tablep-values obtained from MLM were adjusted (Adj.) using Bonferroni and Benjamini-Hockberg (Ben Hoch). Note: the name of the SNP contains chromosome and position information. For example, S18_31114948 is located on chromosome 18 at position 31114948 in the PN40024 reference genome.Raw (XLSX)Click here for additional data file.S5 TableThe genetic map was constructed with 367 SNPs. This table contains the ordered markers with position information (cM) for each of the 19 linkage groups. Linkage group size is determined by the position (cM) of the last marker in each linkage group. The total size for the C2-50 genetic map is 1587.3 cM.(XLSX)Click here for additional data file.S6 TableFour hundred and three SNPs were used to construct the Riesling genetic map. The ordered markers and position (cM) for each of the 19 linkage groups is displayed. Linkage group size is determined by the position (cM) of the last marker in each linkage group. The size of the Riesling genetic map is 1706.4 cM.(XLSX)Click here for additional data file.S7 Table(XLSX)Click here for additional data file.


Fixed arrays of single nucleotide polymorphism (SNP) markers have advantages over reduced representation sequencing in their ease of data analysis, consistently higher call rates, and rapid turnaround times. A 6 K SNP array represents a cost-benefit “sweet spot” for routine genetics and breeding applications in rice. Selection of informative SNPs across species and subpopulations during chip design is essential to obtain useful polymorphism rates for target germplasm groups. This paper summarizes results from large-scale deployment of an Illumina 6 K SNP array for rice.O. sativa and diverse accessions of O. rufipogon or O. meridionalis. Collectively, the array was used to genotype over 40,000 rice samples. A set of 4606 SNP markers was used to provide high quality data for O. sativa germplasm, while a slightly expanded set of 4940 SNPs was used for O. sativa X O. rufipogon populations. Biparental polymorphism rates were generally between 1900 and 2500 well-distributed SNP markers for indica x japonica or interspecific populations and between 1300 and 1500 markers for crosses within indica, while polymorphism rates were lower for pairwise crosses within U.S. tropical japonica germplasm. Recently, a second-generation array containing ~7000 SNP markers, referred to as the C7AIR, was designed by removing poor-performing SNPs from the C6AIR and adding markers selected to increase the utility of the array for elite tropical japonica material.Design of the Illumina Infinium 6 K SNP chip for rice, referred to as the Cornell_6K_Array_Infinium_Rice (C6AIR), includes 4429 SNPs from re-sequencing data and 1571 SNP markers from previous BeadXpress 384-SNP sets, selected based on polymorphism rate and allele frequency within and between target germplasm groups. Of the 6000 attempted bead types, 5274 passed Illumina’s production quality control. The C6AIR was widely deployed at the International Rice Research Institute (IRRI) for genetic diversity analysis, QTL mapping, and tracking introgressions and was intensively used at Cornell University for QTL analysis and developing libraries of interspecific chromosome segment substitution lines (CSSLs) between The C6AIR has been successfully used to generate rapid and high-quality genotype data for diverse genetics and breeding applications in rice, and provides the basis for an optimized design in the C7AIR.The online version of this article (10.1186/s12284-017-0181-2) contains supplementary material, which is available to authorized users. Future challenges to sustainably produce food for 9.5 billion people by 2050 using less land and fewer inputs will require higher yields in intensive systems under increasingly variable environments. Modern plant breeding and genetic research programs aim to utilize the latest technologies to accelerate the annual rate of genetic gain to keep up with rice demand. High-throughput molecular marker techniques have enabled routine, low-cost genotyping for both targeted and genome-wide approaches. Targeted methods, where a few markers (<100) are used to genotype a large number of samples, provide an efficient strategy for forward selection of major genes in breeding programs. Genome-wide methods, including fixed arrays and next generation sequencing, provide marker densities appropriate for genome-wide association studies, QTL mapping, diversity analysis, DNA fingerprinting, impact assessment studies, and breeding applications such as genomic selection Thomson .high-density rice array  are the markers of choice for most high throughput genotyping applications because they are ubiquitous in eukaryotic genomes, cost-effective to assay using automated platforms, and because allele calling, data analysis and data-basing are straightforward due to their biallelic nature. A number of medium- or high-resolution SNP arrays in rice have been deployed, primarily for genome-wide association studies, including a 44 K SNP chip  was developed in Wuhan, China to provide polymorphic SNPs within and between the The primary alternative to fixed SNP arrays is reduced representation next-generation sequencing, such as restriction-site associated DNA (RAD) sequencing or genotyping by sequencing (GBS). These methods provide large numbers of genome-wide SNP markers at a low cost , was designed for use at both Cornell University and the International Rice Research Institute (IRRI). The design of the C6AIR includes 1571 SNP markers from legacy BeadXpress SNP sets and 4429 SNPs selected from whole genome re-sequencing data to be polymorphic within and between the target germplasm groups and mapping parents. This paper describes the efficacy of the C6AIR for QTL mapping, genetic diversity analysis, SNP fingerprinting of breeding lines, tracking of introgressions, and checking for recovery of recurrent parent background during marker-assisted backcrossing. Subsequently, an improved second-generation array was developed by removing SNPs that performed poorly on the 6 K array and increasing the number of bead types to just over 7000. This new 7 K rice array, referred to as the C7AIR, provides continuity with data sets from the C6AIR while increasing the number of high quality SNP loci for future use in genetics and breeding applications.Oryza sativa and O. sativa/O. rufipogon populations, incorporating markers from previous GoldenGate 384-SNP sets and selective SNPs from whole genome re-sequencing data. The custom-designed Infinium iSelect array consisted of 6000 attempted bead types, including 1571 SNP markers from legacy BeadXpress 384-SNP sets , 9 O. nivara, 28 O. rufipogon accessions, one O. meridionalis, one O. officianialis, and one O. punctata .The C6AIR was designed and developed to be informative for O. sativa populations. A subset of 4940 SNPs providing high quality data were routinely called at Cornell University, with the higher number most likely due to the inclusion of several O. rufipogon and O. meridionalis accessions in the analysis.Of the 6000 SNPs included in the initial design, 5274 genome-wide SNPs passed Illumina’s production quality control, out of which 1695 SNP markers localized within MSUv7 gene models .While the average number of polymorphic markers across diverse germplasm was quite high, polymorphism rates decrease with more closely related germplasm Fig. . For exaO. rufipogon and O. meridionalis, for QTL mapping, and to genotype elite material used in US breeding programs, mainly tropical japonica varieties. On the other hand, IRRI’s focus is mainly on indica varieties, though researchers in both institutions utilize all five O. sativa subgroups for genetics and breeding applications. Recent publications also highlight the utility of the Cornell 6 K rice chip for QTL analysis of heat, salinity and flooding tolerance , 2 O. meriodionalis (AA genome) and 1 Oryza officinalis (CC genome) accessions were genotyped  was able to distinguish tropical japonica, temperate japonica and aromatic varieties. Finally, the third PC (PC3) distinguished indica from aus varieties.Further analysis using Principal Component Analysis (PCA) of 232 SUB1 gene and another for the Xa7 gene. SUB1 confers submergence tolerance for up to 14 days at the vegetative stage, and the gene responsible for the phenotype has been cloned and characterized , it is desirable to be able to rapidly introgress chromosomal regions containing a gene or QTL of interest, while at the same time selecting for small size of a target introgression to avoid linkage drag. We highlight two examples of tracking introgressions using C6AIR: one for the cloned and well-characterized SUB1 region contains three SUB1 genes , located between 6.3–6.7 Mb on chromosome 9  and SUB1B (LOC_Os09g11480) are present in Nipponbare, but SUB1A, which is responsible for submergence tolerance, is missing from the reference genome . The introgression from DV85 into IR24 spanned between 26.3 Mb to 28.3 Mb  scheme, where the objective is to rapidly return the genetic background to the recurrent parent type. For example, in an MABC program aiming to transfer the O. rufipogon accessions  and two elite recurrent parents, the indica IR64 and tropical japonica Cybonnet. Genotyping with the C6AIR provided between 1311 to 1952 polymorphic genome-wide SNPs per library, and was used in each backcross generation to identify lines that carried the O. rufipogon introgression of interest, to precisely delimit the size of the target introgression, and to select against unwanted donor introgressions in the background. Although CSSL development was initiated using 384-SNP GoldenGate assays, the C6AIR proved to be much more efficient and informative for CSSL development than the lower resolution assays that preceded it.Six rice CSSL libraries were developed from crosses between three O.rufipogon parent IRGC105567 (NSF490)  Fig. . Each liEight CSSLs provided coverage of chromosome 1 in the Cybonnet X NSF490 population (C4–1 to C4–8), each line carrying a homozygous donor segment in the background of the recurrent parent Fig. . During indica, aus, and tropical japonica subpopulations, between any pairwise combination of accessions from the indica, aus, tropical japonica, temperate japonica, or aromatic (Group V) subpopulations, and between O. sativa and O. rufipogon. The array is expected to be moderately informative for detecting polymorphism within the aromatic (Group V) subpopulation, and least informative for detecting polymorphism within the temperate japonica subpopulation. Trait-specific markers include diagnostic SNPs for the SUB1A gene, grain quality characteristics, and loci for resistance to bacterial leaf blight, blast, brown planthopper, and tungro to enhance C7AIR utility for foreground selection and QTL profiling. The C7AIR is being beta-tested at this time and will be manufactured by Illumina as a consortium array for future use in rice genetics and breeding worldwide.To further improve the C6AIR, a second-generation Infinium rice array was recently developed by eliminating SNPs that performed poorly on the 6 K array and increasing the number of attempted bead types. This new 7 K–SNP array, referred to commercially as the Cornell-IR LD Rice Array, and by the user community as the Cornell_7K_Array_Infinium_Rice (C7AIR), provides continuity with the C6AIR, while increasing the number of high quality SNP loci that can be interrogated. The C7AIR includes 4007 SNPs from the 6 K array, 2056 SNPs from the 700,000-SNP HDRA selected to be informative for US rice germplasm, 910 SNPs from the 384-SNP GoldenGate sets , 189 SNPs from the 44 K array selected to be informative for US rice germplasm, and 21 gene-based SNPs from IRRI. SNPs on the C7AIR are expected to be informative for detecting genome-wide polymorphism between individuals within the O. sativa as well as O. rufipogon, it is especially useful for fingerprinting studies and, as summarized in this paper, finds a broad range of applications in rice breeding programs. The improved second generation C7AIR offers all of the benefits of the 6 K array with additional high quality SNP markers. These resources provide the rice community with rapid, cost-effective tools for low-density, genome-wide SNP genotyping across a wide range of rice germplasm, and with the potential to dramatically increase resolution via imputation when integrated with other publicly available high-density rice genome datasets.The C6AIR has proven to be an effective genotyping system for rice diversity analysis, QTL mapping, tracking introgressions, genetic stock development, and fingerprinting studies at both Cornell University and at the Genotyping Services Lab at IRRI over the last 4 years. Over 40,000 samples were run successfully, providing genotyping data for a large number of genetics, breeding and impact assessment projects of importance to people throughout the world. Arrays such as the C6AIR provide a relatively small but sufficient number of SNPs so that data can be handled without massive bioinformatics pipelines, while at the same time providing high enough resolution for most genetics and breeding applications. The SNPs on the C6AIR consistently have high call rates, including for heterozygotes, facilitating data management and integration of genotyping data across runs and populations. Because the C6AIR can readily distinguish the five major subgroups of Rice accessions used in this study are listed in Additional file O. sativa (400 non-overlapping SNPs/subpopulation), and 2429 SNPs were selected to be polymorphic for specific bi-parental cross combinations (including the O. sativa and O. rufipogon parents of the targeted CSSL populations). A larger candidate set of 800,468 SNPs were initially scored by the Illumina Assay Design Tool (ADT). After scoring the candidate set of SNPs, the subsequent selection of markers was done through several levels of filtering, including basic filtering: i) there were no SNPs within +/− 10 bp of target on either side; ii) no SNPs with minor homozygote count of more than 4 within +/− 35 bp occurring on both sides; iii) INDELS were removed; iv) SNPs with repetitive sequence and low minor allele frequencies in the set of 128 re-sequenced genomes were omitted; and specific filtering: the remaining SNPs were then screened for segregation properties of specific cross combinations, and for segregation within each of the 5 major subpopulations at minor allele frequency > 20% and observation rate within subpopulation >80%. The union set of SNPs, which satisfy either the subpopulation allele frequency criteria or cross segregation criteria were those that became candidates for the array. The final filtering was done to optimize genome spacing and polymorphism detection within and between species and subpopulations. The minimum resolution was at least 1 informative SNP per Mb for the intra- and interspecific bi-parental cross combinations used during the design phase. The SNP information is provided in Additional file The custom-designed Infinium iSelect C6AIR consisted of 6000 attempted bead types, including 1571 SNP markers from legacy BeadXpress 384-SNP sets  were used to determine the efficiency of the filtered markers in segregating the aforementioned groups. Final SNP data were merged with SNP map (Nipponbare MSU7) information and encoded with the physical position and chromosome number of the 4606 SNP markers  from 5274 SNPs that passed Illumina’s QC. Whereas, at IRRI a customized cluster file was used to generate the forward strand SNP data. The cluster file used at IRRI consists of 4606 high quality SNP markers, which had undergone stringent filtering. Representative samples coming from the 5 subgroups of cultivated rice  = 5, call rate = 0.8, resulting in 4940 filtered SNPs that were aligned and used for tree construction using the Geneious Tree Builder. The tree was constructed using the Tamura-Nei genetic distance model, the Neighbor-Joining tree building method, No Outgroup, the Bootstrap Resampling method; and Number of replicates = 100. The tree was visualized using Geneious 8.1.6 to generate a circular cladogram.Additional file 1: Fig. S1.Genome-wide marker coverage. a) Distribution of 5,274 markers successfully converted from C6AIR, and b) distribution of 1,695 markers that localize within MSUv7 gene models (PDF 291 kb)Additional file 2: Fig. S2.Distribution of the number of polymorphic markers found in pairwise comparisons across US rice germplasm (PDF 882 kb)Additional file 3: Table S1.Germplasm information (PDF 96 kb)Additional file 4: Fig. S3.O. sativa accessions (PDF 353 kb)Principal Components Analysis of diverse cultivated Asian rice accessions: PCA of 232 Additional file 5: Fig. S4.Pup1 development (PDF 476 kb)Use of C6AIR for background selection during TR22183-Additional file 6: Table S2.Information on the 6,000 SNPs used for the C6AIR design (CSV 1977 kb)Additional file 7: Fig. S5.Distribution of the frequency of “no call” (NC) alleles in (a) cultivated and (b) wild accessions using the Cornell 6 k Array Infinium Rice (PDF 1061 kb)