Genome wide association study of genes controlling resistance to Didymella rabiei Pathotype IV through genotyping by sequencing in chickpeas (Cicer arietinum)

Ascochyta blight (AB) is a major disease in chickpeas (Cicer arietinum L.) that can cause a yield loss of up to 100%. Chickpea germplasm collections at the center of origin offer great potential to discover novel sources of resistance to pests and diseases. Herein, 189 Cicer arietinum samples were genotyped via genotyping by sequencing. This chickpea collection was phenotyped for resistance to an aggressive Turkish Didymella rabiei Pathotype IV isolate. Genome-wide association studies based on different models revealed 19 single nucleotide polymorphism (SNP) associations on chromosomes 1, 2, 3, 4, 7, and 8. Although eight of these SNPs have been previously reported, to the best of our knowledge, the remaining ten were associated with AB resistance for the first time. The regions identified in this study can be addressed in future studies to reveal the genetic mechanism underlying AB resistance and can also be utilized in chickpea breeding programs to improve AB resistance in new chickpea varieties.

Mapping of QTLs associated with yield and related traits under reproductive stage drought stress in rice using SNP linkage map

BACKGROUND

Drought stress is a major constraint for rice production worldwide. Reproductive stage drought stress (RSDS) leads to heavy yield losses in rice. The prospecting of new donor cultivars for identification and introgression of QTLs of major effect (Quantitative trait locus) for drought tolerance is crucial for the development of drought-resilient rice varieties.

METHODS AND RESULTS

Our study aimed to map QTLs associated with yield and its related traits under RSDS conditions. A saturated linkage map was constructed using 3417 GBS (Genotyping by sequencing) derived SNP (Single nucleotide polymorphism) markers spanning 1924.136 cM map length with an average marker density of 0.56 cM, in the F3 mapping population raised via cross made between the traditional ahu rice cultivar, Koniahu (drought tolerant) and a high-yielding variety, Disang (drought susceptible). Using the Inclusive composite interval mapping approach, 35 genomic regions governing yield and related traits were identified in pooled data from 198 F3 and F4 segregating lines evaluated for two consecutive seasons under both RSDS and irrigated control conditions. Of the 35 QTLs, 23 QTLs were identified under RSDS with LOD (Logarithm of odds) values ranging between 2.50 and 7.83 and PVE (phenotypic variance explained) values of 2.95-12.42%. Two major QTLs were found to be linked to plant height (qPH1.29) and number of filled grains per panicle (qNOG5.12) under RSDS. Five putative QTLs for grain yield namely, qGY2.00, qGY5.05, qGY6.16, qGY9.19, and qGY10.20 were identified within drought conditions. Fourteen QTL regions having ≤ 10 Mb QTL interval size were further analysed for candidate gene identification and a total of 4146 genes were detected out of these 2263 (54.63%) genes were annotated to at least one gene ontology (GO) term.

CONCLUSION

Several QTLs associated with grain yield and yield components and putative candidate genes were identified. The putative QTLs and candidate genes identified could be employed to augment drought resilience in rice after further validation through MAS strategies.

Genetic structure of an endangered species Ormosia henryi in southern China, and implications for conservation

BACKGROUND

The evergreen broadleaved forest (EBLF) is an iconic vegetation type of East Asia, and it contributes fundamentally to biodiversity-based ecosystem functioning and services. However, the native habitat of EBLFs keeps on decreasing due to anthropogenic activities. Ormosia henryi is a valuable rare woody species in EBLFs that is particularly sensitive to habitat loss. In this study, ten natural populations of O. henryi in southern China were sampled, and then genotyping by sequencing (GBS) was applied to elucidate the standing genetic variation and population structure of this endangered species.

RESULTS

In ten O. henryi populations, 64,158 high-quality SNPs were generated by GBS. Based on these markers, a relatively low level of genetic diversity was found with the expected heterozygosity (He) ranging from 0.2371 to 0.2901. Pairwise F_ST between populations varied from 0.0213 to 0.1652, indicating a moderate level of genetic differentiation. However, contemporary gene flow between populations were rare. Assignment test and principal component analysis (PCA) both supported that O. henryi populations in southern China could be divided into four genetic groups, and prominent genetic admixture was found in those populations located in southern Jiangxi Province. Mantel tests and multiple matrix regression with randomization (MMRR) analyses suggested that isolation by distance (IBD) could be the possible reason for describing the current population genetic structure. In addition, the effective population size (Ne) of O. henryi was extremely small, and showed a continuous declining trend since the Last Glacial Period.

CONCLUSIONS

Our results indicate that the endangered status of O. henryi is seriously underestimated. Artificial conservation measures should be applied as soon as possible to prevent O. henryi from the fate of extinction. Further studies are needed to elucidate the mechanism that leading to the continuous loss of genetic diversity in O. henryi and help to develop a better conservation strategy.

GRAS-Di SNP-based molecular characterization and fingerprinting of a Turkish Corylus avellana core set provide insights into the cultivation and breeding of hazelnut in Turkey

Hazelnut (Corylus avellana L.) is an economically and socially important product for Turkey, the country that leads global production of this crop. The preservation of Turkish hazelnut genetic diversity and informed breeding of new cultivars are crucial for maintaining quality and crop yield stability. In this study, genotyping by random amplicon sequencing (GRAS-Di) was used to identify single-nucleotide polymorphisms (SNPs) in a panel of 96 individuals representing the Turkish national hazelnut collection. The resulting 7609 high-quality SNPs were physically mapped to the Tombul cultivar reference genome and used for population structure and diversity analyses. These analyses revealed that cultivars are not less diverse than wild accessions and that 44% of the panel had admixed ancestry. The results also indicated that recently released Turkish cultivars are highly similar to each other, suggesting that diversity analysis is an important tool that should be employed to prevent future genetic bottlenecks in this crop. A minimal marker algorithm was used to select a set of seven SNP markers that were capable of differentiating the panel accessions. These fingerprinting markers should be useful for the propagation of true-to-type elite cultivars that can be used to renew Turkey's aging hazelnut orchards.

Double Digest Restriction-Site Associated DNA Sequencing (ddRADseq) Technology

Double digest restriction-site associated DNA sequencing (ddRADseq) technology combines genome reduced representation by digestion with two restriction enzymes and next generation sequencing (NGS) to obtain thousands of markers (SNP, SSR, and InDels) and genotype tens to hundreds of samples simultaneously. In this chapter, we describe a 96-plex derived ddRADseq protocol that can be set up to obtain different depth of coverage per locus and can be exploited to model and non-model plant species.

Innovations in double digest restriction-site associated DNA sequencing (ddRAD-Seq) method for more efficient SNP identification

We present an improved ddRAD-Seq protocol for identifying single nucleotide polymorphisms (SNPs). It utilizes selected restriction enzyme digestion fragments, quick acting ligases that are neutral with the restriction enzyme buffer eliminating buffer exchange steps, and adapters designed to be compatible with Illumina index primers. Library amplification and barcoding are completed in one PCR step, and magnetic beads are used to purify the genomic fragments from the ligation and library generation steps. Our protocol increases the efficiency and decreases the time to complete a ddRAD-Seq experiment. To demonstrate its utility, we compared SNPs from our protocol with those from whole genome resequencing data from Gossypium herbaceum and Gossypium arboreum. Principal component analysis demonstrated that the variability of the combined data was explained by the genotype (PC1) and methodology applied (PC2). Phylogenetic analysis showed that the SNPs from our method clustered with SNPs from the resequencing data of the corresponding genotype. Sequence alignments illustrated that for homozygous loci, more than 90% of the SNPs from the resequencing data were discovered by our method. Our analyses suggest that our ddRAD-Seq method is reliable in identifying SNPs suitable for phylogenetic and association genetic studies while reducing cost and time over known methods.

A first look at sea-lavenders genomics - can genome wide SNP information tip the scales of controversy in the Limonium vulgare species complex?

BACKGROUND

Sea-lavenders (Limonium Mill., Plumbaginaceae) are a cosmopolitan group of diploid and polyploid plants often adapted to extreme saline environments, with a mostly Tethyan distribution, occurring in the Mediterranean, Irano-Turanian, Euro-Siberian and in the New World. The halophylic Limonium vulgare polyploid complex in particular, presents a large distribution throughout extreme salt-marsh habitats and shows little morphological but high taximetric variation, frequently blurring species delimitation. In this work we pursue three main goals: assert whether SNP data from polyploid individuals has the resolution to distinguish the seven sampled species, to better understand how genetically structured Limonium vulgare is, and attempt to identify specific molecular mechanisms for the differentiation between L. maritimum and L. vulgare. For this purpose, 95 individuals were genotyped using Genotyping by Sequencing (GBS), which were assembled as two independent datasets using IPYRAD. All analyses performed downstream of assembly were fully automated. Phylogenetic inference, PCA, and admixture plots were used to infer answers to the study's main goals.

RESULTS

Close to 10,000 SNPs were obtained for each dataset. Phylogenetic analyses reveal that polyploid data can be used to infer species relationships. Population structure analyses suggest a genetically structured L. vulgare. A set of 34 SNPs were found to be fully segregated between L. vulgare and L. maritimum, two of which are potentially linked to proteins that might be involved in the speciation process.

CONCLUSION

Despite polyploid data analyses shortcomings, GBS generated SNPs have the resolution to discern all seven included species. Limonium vulgare revealed pronounced genetic structure along a geographical north-south cline. L. maritimum always appears as a distinct genetic entity. Segregated SNPs between L. vulgare and L. maritimum indicate salinity response and morphological trait control genes as potentially interesting to follow up for studying these species' divergence process.

ddRADseq-mediated detection of genetic variants in sugarcane

The article presents an optimization of the key parameters for the identification of SNPs in sugarcane using a GBS protocol based on two Illumina NextSeq and NovaSeq platforms. Sugarcane (Saccharum sp.), a world-wide known feedstock for sugar production, bioethanol, and energy, has an extremely complex genome, being highly polyploid and aneuploid. A double-digestion restriction site-associated DNA sequencing protocol (ddRADseq) was tested in four commercial sugarcane hybrids and one high-fibre biotype for the detection of single nucleotide polymorphisms (SNPs). In this work we tested two Illumina sequencing platforms, read size (70 vs. 150 bp), different sequencing coverage per individual (medium and high coverage), and single-reads versus paired-end reads. We also explored different variant calling strategies (with and without reference genome) and filtering schemes [combining two minor allele frequencies (MAFs) with three depth of coverage thresholds]. For the discovery of a large number of novel SNPs in sugarcane, we recommend longer size and paired-end reads, medium sequencing coverage per individual and Illumina platform NovaSeq6000 for a cost-effective approach, and filter parameters of lower MAF and higher depth coverages thresholds. Although the de novo analysis retrieved more SNPs, the reference-based method allows downstream characterization of variants. For the two best performing matrices, the number of SNPs per chromosome correlated positively with chromosome length, demonstrating the presence of variants throughout the genome. Multivariate comparisons, with both matrices, showed closer relationships among commercial hybrids than with the high-fibre biotype. Functional analysis of the SNPs demonstrated that more than half of them landed within regulatory regions, whereas the other half affected coding, intergenic and intronic regions. Allelic distances values were lower than 0.07 when analysing two replicated genotypes, confirming the protocol robustness.

Club-mosses (Diphasiastrum, Lycopodiaceae) from the Far East - Introgression and possible cryptic speciation

Hybridization occurs often in the genus Diphasiastrum (Lycopodiaceae), which corroborates reports for the two other recognized lycophyte families, Isoëtaceae and Selaginellaceae. Here we investigate the case of D. alpinum and D. sitchense from the Russian Far East (Kamchatka). Their hybrid, D. × takedae, was morphologically recognizable in 16 out of 22 accessions showing molecular signatures of hybridization; the remaining accessions displayed the morphology of either D. alpinum (3) or D. sitchense (3). We sequenced markers for chloroplast microsatellites (cp, 175 accessions from Kamchatka) and for the two nuclear markers RPB and LFY (175 and 152 accessions). A selection of 42 accessions, including all hybrid accessions, was analysed via genotyping by sequencing (GBS). We found multiple, but apparently uniparental hybridization, clearly characterized by a deviating group of haplotypes for D. sitchense and all hybrids. All accessions showing molecular signatures of hybridization in nuclear markers revealed the parental haplotype of D. sitchense, however only the LFY marker differentiated between the parent species. GBS, including 69,819 quality-filtered single nucleotid polymorphisms, unambiguously identified the hybrids and revealed introgression to occur. Most of the hybrids were F₁, but three turned out to be backcrosses with D. alpinum (one) and with D. sitchense (two). These observations are in contrast to prior findings on three European species and their intermediates where all three hybrids turned out to be independent F₁ crosses without evidence of recent backcrossing. In this study, backcrossing was detected, which indicates a limited fertility of the hybrid taxon D. × takedae. A comparison of accessions of Kamchatkian D. alpinum with plants from Europe indicated possible cryptic speciation. Accessions from the Far East had (i) a lower DNA content (7.0 vs. 7.5 pg/2C), (ii) different prevailing cp haplotypes, and (iii) RPB genotypes, and (iv) a clearly different SNP pattern in GBS. Diphasiastrum sitchense and the similar D. nikoënse, for the latter additional accessions from Japan were investigated, appeared as forms of one diverse species, sharing genotypes in both nuclear markers, although chloroplast haplotypes and DNA content show slight variations.

Genetic diversity and population structure of Caryopteris mongholica revealed by reduced representation sequencing

BACKGROUND

Caryopteris mongholica Bunge is a rare broad-leaved shrub distributed in the desert and arid regions of Mongol and North China. Due to land reclamation, natural habitat deterioration and anthropogenic activities in recent years, the wild resources have sharply reduced. To effectively protect and rationally use it, we investigated the genetic diversity and population structure from 18 populations across the range of C. mongholica in China by reduced representation sequencing technology.

RESULTS

We found the overall average values of observed heterozygosity (Ho), expected heterozygosity (He), and average nucleotide diversity (π) were 0.43, 0.35 and 0.135, respectively. Furthermore, the NM17 population exhibited higher genetic diversity than other populations. The phylogenetic tree, principal component analysis (PCA) and structure analysis showed the sampled individuals clustered into two main groups. The NM03 population, with individuals clustered in both groups, may be a transitional population located between the two groups. In addition, most genetic variation existed within populations (90.97%) compared to that among the populations (9.03%). Interestingly, geographic and environmental distances were almost equally important to the observed genetic differences. Redundancy analysis (RDA) identified optical radiation (OR), minimum temperature (MIT) and mean annual precipitation (MAP) related variables as the most important environment factors influencing genetic variation, and the importance of MIT was also confirmed in the latent factor mixed models (LFMM).

CONCLUSIONS

The results of this study facilitate research on the genetic diversity of C. mongholica. These genetic features provided vital information for conserving and sustainably developing the C. mongholica genetic resources.

Genetic mapping of powdery mildew resistance genes in wheat landrace Guizi 1 via genotyping by sequencing

BACKGROUND

Wheat (Triticum aestivum L.) powdery mildew (Pm), which caused by Blumeria graminis f. sp. tritici (Bgt), is a destructive disease worldwide that causes severe yield losses in wheat. Resistant wheat cultivars easily lose their ability to effectively resist newly emerged Bgt strains; therefore, identifying new resistance genes is necessary for breeding resistant cultivars.

METHODS AND RESULTS

Guizi 1 (GZ1) is a Chinese wheat cultivar with moderate and stable resistance to Pm. Genetic analysis indicated that the Pm resistance of GZ1 was controlled by a single dominant gene, designated PmGZ1. In total, 110 F₂ individual plants and their 2 parents were subjected to genotyping by sequencing (GBS), which yielded 23,134 high-quality single-nucleotide polymorphisms (SNPs). The SNP distributions across the 21 chromosomes ranged from 134 on chromosome 6D to 6288 on chromosome 3B. Chromosome 6A has 1866 SNPs, among which 16 are physically located between positions 307,802,221 and 309,885,836 in an approximate 2.3-cM region; this region also had the greatest SNP density. The average map distance between SNP markers was 0.1 cM. A quantitative trait locus (QTL) with a significant epistatic effect on Pm resistance was mapped to chromosome 6A. The logarithm of odds (LOD) value of PmGZ1 was 34.8, and PmGZ1 was located within the confidence interval marked by chr6a-307802221 and chr6a-309885836. Moreover, 74.7% of the phenotypic variance was explained by PmGZ1. Four candidate genes (which encoded two TaAP2-A and two actin proteins) were annotated maybe as resistance genes.

CONCLUSIONS

The present results provide valuable information for wheat genetic improvement, QTL fine mapping, and candidate gene validation.

Improving the accuracy of genomic predictions in an outcrossing species with hybrid cultivars between heterozygote parents: a case study of oil palm (Elaeis guineensis Jacq.)

Genomic selection (GS) is a method of marker-assisted selection revolutionizing crop improvement, but it can still be optimized. For hybrid breeding between heterozygote parents of different populations or species, specific aspects can be considered to increase GS accuracy: (1) training population genotyping, i.e., only genotyping the hybrid parents or also a sample of hybrid individuals, and (2) marker effects modeling, i.e., using population-specific effects of single nucleotide polymorphism alleles model (PSAM) or across-population SNP genotype model (ASGM). Here, this was investigated empirically for the prediction of the performances of oil palm hybrids for yield traits. The GS model was trained on 352 hybrid crosses and validated on 213 independent hybrid crosses. The training and validation hybrid parents and 399 training hybrid individuals were genotyping by sequencing. Despite the small proportion of hybrid individuals genotyped and low parental heterozygosity, GS prediction accuracy increased on average by 5% (range 1.4-31.3%, depending on trait and model) when training was done using genomic data on hybrids and parents compared with only parental genomic data. With ASGM, GS prediction accuracy increased on average by 3% (- 10.2 to 40%, depending on trait and genotyping strategy) compared with PSAM. We conclude that the best GS strategy for oil palm is to aggregate genomic data of parents and hybrid individuals and to ignore the parental origin of marker alleles (ASGM). To gain a better insight into these results, future studies should examine the respective effect of capturing genetic variability within crosses and taking segregation distortion into account when genotyping hybrid individuals, and investigate the factors controlling the relative performances of ASGM and PSAM in hybrid crops.

Skim-Based Genotyping by Sequencing Using a Double Haploid Population to Call SNPs, Infer Gene Conversions, and Improve Genome Assemblies

Genotyping by sequencing (GBS) is an emerging technology to rapidly call an abundance of single nucleotide polymorphisms (SNPs) using genome sequencing technology. Several different methodologies and approaches have recently been established, most of these relying on a specific preparation of data. Here we describe our GBS pipeline, which uses high coverage reads from two parents and low coverage reads from their double haploid offspring to call SNPs on a large scale. The upside of this approach is the high resolution and scalability of the method.

Identification of yield-related genes through genome-wide association: case study of weeping forsythia, an emerging medicinal crop

KEY MESSAGE

This study identified candidate genes related to fruit yield for an emerging medicinal crop, weeping forsythia.

BACKGROUND

The genetic basis of crop yield is an agricultural research hotspot. Identifying the genes related to yield traits is the key to increase the yield. Weeping forsythia is an emerging medicinal crop that currently lacks excellent varieties. The genes related to fruit yield in weeping forsythia have not been identified.

OBJECTIVE

Thus, we aimed to screen the candidate genes related to fruit yield of weeping forsythia by using genome-wide association analysis.

METHODS

Here, 60 samples from the same field and source of weeping forsythia were collected to identify its yield-related candidate genes. Association analysis was performed on the variant loci and the traits related to yield, i.e., fruit length, width, thickness, and weight.

RESULTS

Results from admixture, neighbor-joining, and kinship matrix analyses supported the non-significant genetic differentiation of these samples. Significant association was found between 2 variant loci and fruit length, 8 loci and fruit width, 24 loci and fruit thickness, and 13 loci and fruit weight. Further search on the 20 kb up/downstream of these variant loci revealed 1 gene related to fruit length, 16 genes related to fruit width, 12 genes related to fruit thickness, and 13 genes related to fruit weight. Among which, 4 genes, namely, WRKY transcription factor 35, salicylic acid-binding protein, auxin response factor 6, and alpha-mannosidase were highly related to the fruit development of weeping forsythia.

CONCLUSION

This study identify four candidate genes related to fruit development, which will provide useful information for the subsequent molecular-assisted and genetic breeding of weeping forsythia.

Beyond the Cereal Box: Breeding Buckwheat as a Strategic Crop for Human Nutrition

While intensification of farming systems is essential for achieving the Millennium Development Goal of "Zero hunger", issues such as availability of nutritious foods would demand increased attention if any long-term form of food security is to be achieved. Since wheat, rice and maize have reached near to 80 percent of their yield potential and reliance on these crops alone would not be sufficient to close the gap between demand and supply, there is a need to bring other climate-resilient and nutritionally dense crops into agricultural portfolio. Buckwheat (Fagopyrum spp.) has attracted considerable interest amongst global scientific community due to its nutritional and pharmaceutical properties. The gluten free nature of buckwheat, nutritionally balanced amino acid composition of its grain protein, and high levels of anti-oxidants, such as rutin, makes buckwheat an important crop with immense nutraceutical benefits. However, a key challenge in buckwheat cultivation is the variation in yield between years, which impacts the entire value chain. Current information on buckwheat indicates existence of significant phenotypic variation for agronomic and nutritional traits. However, genetic bottlenecks in conventional breeding restrict effective utilization of the existing diversity in mainstreaming buckwheat cultivation. Availability of high density buckwheat genome map for both the cultivated species viz. F. esculentum and F. tataricum would add to our understanding of genetic basis of their agronomic traits. The review examines the potential of buckwheat as a strategic crop for human nutrition and prospects of effective exploitation genomic information of common and Tartary buckwheat for genome assisted breeding.

Facilitating population genomics of non-model organisms through optimized experimental design for reduced representation sequencing

BACKGROUND

Genome-wide data are invaluable to characterize differentiation and adaptation of natural populations. Reduced representation sequencing (RRS) subsamples a genome repeatedly across many individuals. However, RRS requires careful optimization and fine-tuning to deliver high marker density while being cost-efficient. The number of genomic fragments created through restriction enzyme digestion and the sequencing library setup must match to achieve sufficient sequencing coverage per locus. Here, we present a workflow based on published information and computational and experimental procedures to investigate and streamline the applicability of RRS.

RESULTS

In an iterative process genome size estimates, restriction enzymes and size selection windows were tested and scaled in six classes of Antarctic animals (Ostracoda, Malacostraca, Bivalvia, Asteroidea, Actinopterygii, Aves). Achieving high marker density would be expensive in amphipods, the malacostracan target taxon, due to the large genome size. We propose alternative approaches such as mitogenome or target capture sequencing for this group. Pilot libraries were sequenced for all other target taxa. Ostracods, bivalves, sea stars, and fish showed overall good coverage and marker numbers for downstream population genomic analyses. In contrast, the bird test library produced low coverage and few polymorphic loci, likely due to degraded DNA.

CONCLUSIONS

Prior testing and optimization are important to identify which groups are amenable for RRS and where alternative methods may currently offer better cost-benefit ratios. The steps outlined here are easy to follow for other non-model taxa with little genomic resources, thus stimulating efficient resource use for the many pressing research questions in molecular ecology.

High-density mapping for gray leaf spot resistance using two related tropical maize recombinant inbred line populations

Gray leaf spot (GLS) caused by Cercospora zeae-maydis or Cercospora zeina is one of the devastating maize foliar diseases worldwide. Identification of GLS-resistant quantitative trait loci (QTL)/genes plays an urgent role in improving GLS resistance in maize breeding practice. Two groups of recombinant inbred line (RIL) populations derived from CML373 × Ye107 and Chang7-2 × Ye107 were generated and subjected to genotyping-by-sequencing (GBS). A total of 1,929,222,287 reads in CML373 × Ye107 (RIL-YCML) and 2,585,728,312 reads in Chang7-2 × Ye107 (RIL-YChang), with an average of 10,961,490 (RIL-YCML) and 13,609,096 (RIL-YChang) reads per individual, were got, which was roughly equal to 0.70-fold and 0.87-fold coverage of the maize B73 RefGen_V4 genome for each F₇ individual, respectively. 6418 and 5139 SNP markers were extracted to construct two high-density genetic maps. Comparative analysis using these physically mapped marker loci demonstrated a satisfactory colinear relationship with the reference genome. 11 GLS-resistant QTL have been detected. The individual QTL accounted for 1.53-24.00% of the phenotypic variance explained (PVE). The new consensus QTL (qYCM-DS3-3/qYCM-LT3-1/qYCM-LT3-2) with the largest effect was located in chromosome bin 3.05, with an interval of 2.7 Mb, representing 13.08 to 24.00% of the PVE. Further gene annotation indicated that there were four candidate genes (GRMZM2G032384, GRMZM2G041415, GRMZM2G041544, and GRMZM2G035992) for qYCM-LT3-1, which may be related to GLS resistance. Combining RIL populations and GBS-based high-density genetic maps, a new larger effect QTL was delimited to a narrow genomic interval, which will provide a new resistance source for maize breeding programs.

Characterization of a haplotype-reference panel for genotyping by low-pass sequencing in Swiss Large White pigs

BACKGROUND

The key-ancestor approach has been frequently applied to prioritize individuals for whole-genome sequencing based on their marginal genetic contribution to current populations. Using this approach, we selected 70 key ancestors from two lines of the Swiss Large White breed that have been selected divergently for fertility and fattening traits and sequenced their genomes with short paired-end reads.

RESULTS

Using pedigree records, we estimated the effective population size of the dam and sire line to 72 and 44, respectively. In order to assess sequence variation in both lines, we sequenced the genomes of 70 boars at an average coverage of 16.69-fold. The boars explained 87.95 and 95.35% of the genetic diversity of the breeding populations of the dam and sire line, respectively. Reference-guided variant discovery using the GATK revealed 26,862,369 polymorphic sites. Principal component, admixture and fixation index (F_ST) analyses indicated considerable genetic differentiation between the lines. Genomic inbreeding quantified using runs of homozygosity was higher in the sire than dam line (0.28 vs 0.26). Using two complementary approaches, we detected 51 signatures of selection. However, only six signatures of selection overlapped between both lines. We used the sequenced haplotypes of the 70 key ancestors as a reference panel to call 22,618,811 genotypes in 175 pigs that had been sequenced at very low coverage (1.11-fold) using the GLIMPSE software. The genotype concordance, non-reference sensitivity and non-reference discrepancy between thus inferred and Illumina PorcineSNP60 BeadChip-called genotypes was 97.60, 98.73 and 3.24%, respectively. The low-pass sequencing-derived genomic relationship coefficients were highly correlated (r > 0.99) with those obtained from microarray genotyping.

CONCLUSIONS

We assessed genetic diversity within and between two lines of the Swiss Large White pig breed. Our analyses revealed considerable differentiation, even though the split into two populations occurred only few generations ago. The sequenced haplotypes of the key ancestor animals enabled us to implement genotyping by low-pass sequencing which offers an intriguing cost-effective approach to increase the variant density over current array-based genotyping by more than 350-fold.

Genome wide association mapping for heat tolerance in sub-tropical maize

Background

Heat tolerance is becoming increasingly important where maize is grown under spring season in India which coincide with grain filling stage of crop resulting in tassel blast, reduced pollen viability, pollination failure and barren ears that causes devastating yield losses. So, there is need to identify the genomic regions associated with heat tolerance component traits which could be further employed in maize breeding program.

Results

An association mapping panel, consisting of 662 doubled haploid (DH) lines, was evaluated for yield contributing traits under normal and natural heat stress conditions. Genome wide association studies (GWAS) carried out using 187,000 SNPs and 130 SNPs significantly associated for grain yield (GY), days to 50% anthesis (AD), days to 50% silking (SD), anthesis-silking interval (ASI), plant height (PH), ear height (EH) and ear position (EPO) were identified under normal conditions. A total of 46 SNPs strongly associated with GY, ASI, EH and EPO were detected under heat stress conditions. Fifteen of the SNPs was found to have common association with more than one trait such as two SNPs viz. S10_1,905,273 and S10_1,905,274 showed colocalization with GY, PH and EH whereas S10_7,132,845 SNP associated with GY, AD and SD under normal conditions. No such colocalization of SNP markers with multiple traits was observed under heat stress conditions. Haplotypes trend regression analysis revealed 122 and 85 haplotype blocks, out of which, 20 and 6 haplotype blocks were associated with more than one trait under normal and heat stress conditions, respectively. Based on SNP association and haplotype mapping, nine and seven candidate genes were identified respectively, which belongs to different gene models having different biological functions in stress biology.

Conclusions

The present study identified significant SNPs and haplotype blocks associated with yield contributing traits that help in selection of donor lines with favorable alleles for multiple traits. These results provided insights of genetics of heat stress tolerance. The genomic regions detected in the present study need further validation before being applied in the breeding pipelines.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07463-y.

Genome- wide structural and functional variant discovery of rice landraces using genotyping by sequencing

Rice landraces are vital genetic resources for agronomic and quality traits but the undeniable collection of Kerala landraces remains poorly delineated. To effectively conserve, manage, and use these resources, understanding the genomic structure of germplasm is essential. Genotyping by sequencing (GBS) enables identification of an immense number of single nucleotide polymorphism (SNP) and insertion deletion (InDel) from 96 rice germplasm. In the present study, a total of 16.9 × 10⁷ reads were generated, and among that 16.3 × 10⁷ reads were mapped to the indica reference genome. Exploring GBS data unfolded a wide genomic variations including 82,59,639 SNPs and 1,07,140 Indels. Both neighbor-joining tree and principal coordinate analysis with InDel markers revealed the selected germplasm in this study as highly diverse in structure. We assembled unmapped reads which were further employed for gene ontology analysis. These unmapped sequences that are generally expelled from subsequent studies of GBS data analysis may exist as an unexplored resort for several novel significant biological findings. The discovery of SNPs from the haplotyping results of GS3 and GIF1 genes provided insight into marker- assisted selection based on grain size and yield and can be utilized for rice yield improvement. To our knowledge, this is the first report on structural variation analysis using the GBS platform in rice landraces collected from Kerala. Genomic information from this study endows with valuable resources for perceptive rice landrace structure and can also facilitate sequencing-based molecular breeding.

Large scale SNP unearthing and genetic architecture analysis in sea-captured and cultured populations of Cynoglossus semilaevis

Knowledge on population structure and genetic diversity is a focal point for association mapping studies and genomic selection. Genotyping by sequencing (GBS) represents an innovative method for large scale SNP detection and genotyping of genetic resources. Here we used the GBS approach for the genome-wide identification of SNPs in a collection of Cynoglossus semilaevis and for the assessment of the level of genetic diversity in C. semilaevis genotypes. GBS analysis generated a total of 55.12 Gb high-quality sequence data, with an average of 0.63 Gb per sample. The total number of SNP markers was 563, 109. In order to explore the genetic diversity of C. semilaevis and to select a minimal core set representing most of the total genetic variation with minimum redundancy, C. semilaevis sequences were analyzed using high quality SNPs. Based on hierarchical clustering, it was possible to divide the collection into 2 clusters. The marine fishing populations were clustered and clearly separated from the cultured populations, and the cultured populations from Hebei was also distinct from the other two local populations. These analyses showed that genotypes were clustered based on species-related features. Differential significant SNPs were also captured and validated by GBS and SNaPshot, with linkage disequilibrium and haplotype analysis, seven SNPs have been confirmed to have obvious differentiation in two populations, which may be used as the characteristic evaluation sites of sea-captured and cultured Cynoglossus semilaevis populations. And SNP markers and information on population structure developed in this study will undoubtedly support genome-wide association mapping studies and marker-assisted selection programs. These differential SNPs could be also employed as the characteristic evaluation sites of sea-captured and cultured Cynoglossus semilaevis populations in future.

Phylogenomics and molecular species delimitation reveals great cryptic diversity of leaf-toed geckos (Phyllodactylidae: Phyllodactylus), ancient origins, and diversification in Mexico

We utilize the efficient GBS technique to obtain thousands of nuclear loci and SNPs to reconstruct the evolutionary history of Mexican leaf-toed geckos (Phyllodactylus). Through the incorporation of unprecedented sampling for this group of geckos, in combination with genomic data analysis, we generate mostly consistent phylogenetic hypotheses using two approaches: supermatrix and coalescent-based inference. All topologies depict three, mutually exclusive major clades. Clade I comprises P. bordai and all species closer to P. bordai than to any other Phyllodactylus. Clade II comprises P. nocticolus and all species closer to P. nocticolus than to any other Phyllodactylus. Clade III comprises P. tuberculosus and all species closer to P. tuberculosus than to any other Phyllodactylus. Analyses estimate the age for the most recent common ancestor of Phyllodactylus in the Eocene (~43 mya), and the ancestors of each major clade date to the Eocene-Oligocene transition (32-36 mya). This group includes one late-Eocene lineage (P. bordai), Oligocene lineages (P. paucituberculatus, P. delcampi), but also topological patterns that indicate a recent radiation occurred during the Pleistocene on islands in the Gulf of California. The wide spatial and temporal scale indicates a complex and unique biogeographic history for each major clade. The 33 species delimited by BPP and stepping-stone BFD*coalescent based genomic approaches reflect this history. This diversity delimited for Mexican leaf-toed geckos demonstrates a vast underestimation in the number of species based on morphological data alone.

Comparisons of improved genomic predictions generated by different imputation methods for genotyping by sequencing data in livestock populations

Background

Genotyping by sequencing (GBS) still has problems with missing genotypes. Imputation is important for using GBS for genomic predictions, especially for low depths, due to the large number of missing genotypes. Minor allele frequency (MAF) is widely used as a marker data editing criteria for genomic predictions. In this study, three imputation methods (Beagle, IMPUTE2 and FImpute software) based on four MAF editing criteria were investigated with regard to imputation accuracy of missing genotypes and accuracy of genomic predictions, based on simulated data of livestock population.

Results

Four MAFs (no MAF limit, MAF ≥ 0.001, MAF ≥ 0.01 and MAF ≥ 0.03) were used for editing marker data before imputation. Beagle, IMPUTE2 and FImpute software were applied to impute the original GBS. Additionally, IMPUTE2 also imputed the expected genotype dosage after genotype correction (GcIM). The reliability of genomic predictions was calculated using GBS and imputed GBS data. The results showed that imputation accuracies were the same for the three imputation methods, except for the data of sequencing read depth (depth) = 2, where FImpute had a slightly lower imputation accuracy than Beagle and IMPUTE2. GcIM was observed to be the best for all of the imputations at depth = 4, 5 and 10, but the worst for depth = 2. For genomic prediction, retaining more SNPs with no MAF limit resulted in higher reliability. As the depth increased to 10, the prediction reliabilities approached those using true genotypes in the GBS loci. Beagle and IMPUTE2 had the largest increases in prediction reliability of 5 percentage points, and FImpute gained 3 percentage points at depth = 2. The best prediction was observed at depth = 4, 5 and 10 using GcIM, but the worst prediction was also observed using GcIM at depth = 2.

Conclusions

The current study showed that imputation accuracies were relatively low for GBS with low depths and high for GBS with high depths. Imputation resulted in larger gains in the reliability of genomic predictions for GBS with lower depths. These results suggest that the application of IMPUTE2, based on a corrected GBS (GcIM) to improve genomic predictions for higher depths, and FImpute software could be a good alternative for routine imputation.

Detection of QTLs associated with mungbean yellow mosaic virus (MYMV) resistance using the interspecific cross of Vigna radiata × Vigna umbellata

Mungbean (Vigna radiata) and ricebean (V. umbellata) were utilized to obtain an inter-specific recombinant inbred line (RIL) population with the objective of detecting quantitative trait loci (QTL) associated with mungbean yellow mosaic virus (MYMV) resistance. To precisely map QTLs, accurate genetic linkage maps are essential. In the present study, genotyping-by-sequencing (GBS) platform was utilized to develop the genetic linkage map. The map contained 538 single nucleotide polymorphism (SNP) markers, consisted of 11 linkage groups and spanned for 1291.7 cM with an average marker distance of 2.40 cM. The individual linkage group ranged from 90.2 to 149.1 cM in length, and the SNP markers were evenly distributed in the genetic linkage map, with 30-79 SNP markers per chromosome. The QTL analysis using the genetic map and 2 years (2015 and 2016) of phenotyping data identified five QTLs with phenotypic variation explained (PVE) from 10.11 to 20.04%. Of these, a QTL on chromosome 4, designated as qMYMV4-1, was major and stably detected in the same marker interval in both years. This QTL region harbours possible candidate genes for controlling MYMV resistance. The linkage map and QTL/gene (s) for MYMV resistance identified in this study should be useful for QTL fine mapping and cloning for further studies.

Genome-wide association study of vitamin E using genotyping by sequencing in sesame (Sesamum indicum)

BACKGROUND

At least eight structurally related forms of vitamin E occur in nature, four tocopherols and four tocotrienols, all of which are potent membrane-soluble antioxidants. In this study, we detected two major isoforms in sesame (Sesamum indicum L.) seed: γ-tocopherol and β-tocotrienol. The objective of this study is to investigate the genetic basis of these vitamin E isoforms.

METHODS

We  conducted a genome-wide association study (GWAS) using 5962 genome-wide markers, acquired from 96 core sesame accessions. The GWAS was performed using generalized linear (GLM) and mixed linear (MLM) models.

RESULTS

LG08_6621957, on chromosome 8, was detected as having a significant association with γ-tocopherol in both models. It explained 20.9% of γ-tocopherol variation in sesame. For β-tocotrienol, no significant loci were detected according to the two models, but one locus, SLG03_13104062, explained 17.8% of the phenotypic variation. Based on structure and phylogenetic studies, the 96 accessions were clearly clustered into two subpopulations.

CONCLUSION

This study on sesame demonstrates and provides an evidence that genotyping by sequencing (GBS) based GWAS can be used to identifying important loci for small growing crops. The significant SNPs or genes could be useful for improving the vitamin E content in sesame breeding programs.

Genetic analyses of nitrogen assimilation enzymes in Brassica juncea (L.) Czern & Coss

Nitrogen (N) is a critical input for plant growth and development. A better understanding of N uptake and utilization is important to develop plant breeding strategies for improving nitrogen use efficiency (NUE). With that objective in mind, we assayed a SNP-genotyped association panel comprising 92 inbred lines for the activities of nitrate reductase (NR), nitrite reductase (NIR), glutamine synthetase (GS) and glutamate synthase (GOGAT). All these enzymes are associated with N assimilation. The experiments were carried out at two levels of N application: no added N (N₀) and agrnomically recommened dose (100 kg/ha) of N application (N₁₀₀). Genome wide association studies (GWAS) helped to identify several marker-trait associations (MTAs), involving chromosomes A01, A06, A08, B02, B04, B05 and B08. These explained high phenotypic variation (up to 32%). Annotation of the genomic region(s) in or around significant SNPs allowed prediction of genes encoding high affinity nitrate transporters, glutamine synthetase 1.3, myb-like transcription factor family protein, bidirectional amino acid transporter 1, auxin signaling F-box 3 and oxidoreductases. This is the first attempt to use GWAS for identification of enzyme QTLs to explain variation for nitrogen assimilation enzymes in Brassica juncea.

QTLian breeding for climate resilience in cereals: progress and prospects

The ever-rising population of the twenty-first century together with the prevailing challenges, such as deteriorating quality of arable land and water, has placed a big challenge for plant breeders to satisfy human needs for food under erratic weather patterns. Rice, wheat, and maize are the major staple crops consumed globally. Drought, waterlogging, heat, salinity, and mineral toxicity are the key abiotic stresses drastically affecting crop yield. Conventional plant breeding approaches towards abiotic stress tolerance have gained success to limited extent, due to the complex (multigenic) nature of these stresses. Progress in breeding climate-resilient crop plants has gained momentum in the last decade, due to improved understanding of the physiochemical and molecular basis of various stresses. A good number of genes have been characterized for adaptation to various stresses. In the era of novel molecular markers, mapping of QTLs has emerged as viable solution for breeding crops tolerant to abiotic stresses. Therefore, molecular breeding-based development and deployment of high-yielding climate-resilient crop cultivars together with climate-smart agricultural practices can pave the path to enhanced crop yields for smallholder farmers in areas vulnerable to the climate change. Advances in fine mapping and expression studies integrated with cheaper prices offer new avenues for the plant breeders engaged in climate-resilient plant breeding, and thereby, hope persists to ensure food security in the era of climate change.

Measuring sequencer size bias using REcount: a novel method for highly accurate Illumina sequencing-based quantification

Quantification of DNA sequence tags from engineered constructs such as plasmids, transposons, or other transgenes underlies many functional genomics measurements. Typically, such measurements rely on PCR followed by next-generation sequencing. However, PCR amplification can introduce significant quantitative error. We describe REcount, a novel PCR-free direct counting method. Comparing measurements of defined plasmid pools to droplet digital PCR data demonstrates that REcount is highly accurate and reproducible. We use REcount to provide new insights into clustering biases due to molecule length across different Illumina sequencers and illustrate the impacts on interpretation of next-generation sequencing data and the economics of data generation.

Genome-wide Association Study of a Panel of Vietnamese Rice Landraces Reveals New QTLs for Tolerance to Water Deficit During the Vegetative Phase

BACKGROUND

Drought tolerance is a major challenge in breeding rice for unfavorable environments. In this study, we used a panel of 180 Vietnamese rice landraces genotyped with 21,623 single-nucleotide polymorphism markers to perform a genome-wide association study (GWAS) for different drought response and recovery traits during the vegetative stage. These landraces originate from different geographical locations and are adapted to different agrosystems characterized by contrasted water regimes. Vietnamese landraces are often underrepresented in international panels used for GWAS, but they can contain original genetic determinants related to drought resistance.

RESULTS

The panel of 180 rice varieties was phenotyped under greenhouse conditions for several drought-related traits in an experimental design with 3 replicates. Plants were grown in pots for 4 weeks and drought-stressed by stopping irrigation for an additional 4 weeks. Drought sensitivity scores and leaf relative water content were measured throughout the drought stress. The recovery capacity was measured 2 weeks after plant rewatering. Several QTLs associated with these drought tolerance traits were identified by GWAS using a mixed model with control of structure and kinship. The number of detected QTLs consisted of 14 for leaf relative water content, 9 for slope of relative water content, 12 for drought sensitivity score, 3 for recovery ability and 1 for relative crop growth rate. This set of 39 QTLs actually corresponded to a total of 17 different QTLs because 9 were simultaneously associated with two or more traits, which indicates that these common loci may have pleiotropic effects on drought-related traits. No QTL was found in association with the same traits in both the indica and japonica subpanels. The possible candidate genes underlying the quantitative trait loci are reviewed.

CONCLUSIONS

Some of the identified QTLs contain promising candidate genes with a function related to drought tolerance by osmotic stress adjustment.

Improving genomic predictions by correction of genotypes from genotyping by sequencing in livestock populations

Background

Genotyping by sequencing (GBS) is a robust method to genotype markers. Many factors can influence the genotyping quality. One is that heterozygous genotypes could be wrongly genotyped as homozygotes, dependent on the genotyping depths. In this study, a method correcting this type of genotyping error was demonstrated. The efficiency of this correction method and its effect on genomic prediction were assessed using simulated data of livestock populations.

Results

Chip array (Chip) and four depths of GBS data was simulated. After quality control (call rate ≥ 0.8 and MAF ≥ 0.01), the remaining number of Chip and GBS SNPs were both approximately 7,000, averaged over 10 replicates. GBS genotypes were corrected with the proposed method. The reliability of genomic prediction was calculated using GBS, corrected GBS (GBSc), true genotypes for the GBS loci (GBSr) and Chip data. The results showed that GBSc had higher rates of correct genotype calls and higher correlations with true genotypes than GBS. For genomic prediction, using Chip data resulted in the highest reliability. As the depth increased to 10, the prediction reliabilities using GBS and GBSc data approached those using true GBS data. The reliabilities of genomic prediction using GBSc data were 0.604, 0.672, 0.684 and 0.704 after genomic correction, with the improved values of 0.013, 0.009, 0.006 and 0.001 at depth = 2, 4, 5 and 10, respectively.

Conclusions

The current study showed that a correction method for GBS data increased the genotype accuracies and, consequently, improved genomic predictions. These results suggest that a correction of GBS genotype is necessary, especially for the GBS data with low depths.

Electronic supplementary material

The online version of this article (10.1186/s40104-019-0315-z) contains supplementary material, which is available to authorized users.

Genome-wide association mapping identifies markers associated with cane yield components and sucrose traits in the Louisiana sugarcane core collection

Sugarcane is an economically important crop for both food and biofuel industries. Marker-assisted breeding in sugarcane is becoming a reality with the recent development and deployment of markers linked with disease resistance genes. Large linkage disequilibrium in sugarcane makes genome-wide association studies (GWAS) a better alternative to biparental mapping to identify markers associated with agronomic traits. GWAS was conducted on a Louisiana core collection to identify marker-trait associations (MTA) for 11 cane yield and sucrose traits using single nucleotide polymorphism (SNP) and insertion-deletion (Indel) markers. Significant (P < .05) MTAs were identified for all traits where the top ranked markers explained up to 15% of the total phenotypic variation. High correlations (0.732 to 0.999) were observed between sucrose traits and 56 markers were found consistent across multiple traits. These markers following validation in more diverse populations could be used in marker-assisted selection of clones in sugarcane breeding program in Louisiana and elsewhere.

QTL mapping in a maize F2 population using Genotyping-by-Sequencing and a modified fine-mapping strategy

Maize possesses a tremendous genetic diversity, most of which is deposited in a large number of landraces. However, the genetic basis of local diversity from maize landrace remains largely unknown. Traditional fine mapping of the causal gene for complex trait, based on the transition from the quantitative trait locus (QTL) to a single qualitative gene through backcrossing or the construction of heterogeneous inbred family (HIF), has achieved great success in model crop rice. However, this fine-mapping strategy did not work well in maize. In this study, an F₂ population derived from a maize landrace and an elite inbred line was firstly genotyped by genotyping by sequencing (GBS). QTL analysis further revealed 29 QTLs of 12 traits, most of which individually accounted for more than 10% of phenotypic variations. Next traditional fine-mapping method successfully narrowed down a major QTL of kernel color qCOK1, but failed in the fine mapping of another major QTL of ear height EH4 because the EH4 remained quantitative feature in the HIF. Based on the quantitative feature of the EH4 in the HIF, we then performed the correlation tests between genotypes and phenotypes in the descendant populations derived from the recombination plants to enable the process of fine mapping. Our modified fine-mapping strategy successfully narrowed down the EH4 into a 3.23-Mb region on chromosome 8. The modified fine-mapping method can be applied to fast clone the QTLs originated from maize landraces.

Characterizing Palestinian snake melon (Cucumis melo var. flexuosus) germplasm diversity and structure using SNP and DArTseq markers

BACKGROUND

Crop landraces embody a source of beneficial genes potentially providing endurance to environmental stress and other agronomic qualities including yield. Our study included 88 snake melon accessions (Cucumis melo var. flexuosus) collected from 9 districts in the Palestinian West-Bank. These accessions represent four landraces of Palestinian snake melon: Green, and White Baladi, and Green, and White Sahouri.

RESULTS

This is the first report on successful application of genotyping by sequencing in snake melon. Nine thousand seven hundred fifty single-nucleotide polymorphism (SNP) and 7400 DArTseq genetic markers were employed to evaluate genetic biodiversity and population structure of Palestinian snake melon germplasm collection. Clustering based on neighbor-joining-analysis, principle coordinate and Bayesian model implemented in Structure showed that patterns of genetic diversity of snake melon landraces depends on their geographical source and unraveled the presence of two major local landraces (Sahouri, and Baladi) with accessions from each group clustering together. A significant correlation was observed between both types of markers in Mantel correlation test. A significant association between genetic and geographic matrices (P < 0.0001) was also detected. AMOVA indicated that majority of variation (90%) was due to the difference within accessions.

CONCLUSION

The Palestinian landraces seem to have unique genes that may allow the enhancement of the global snake melon gene pool and developments of the plant production worldwide. Our subsequent objective is to detect genotypes with promising qualities and to conduct association mapping studies concentrating on Fusarium-wilt resistance, yield, and environmental stresses.

A comparison between genotyping-by-sequencing and array-based scoring of SNPs for genomic prediction accuracy in winter wheat

The utilization of DNA molecular markers in plant breeding to maximize selection response via marker-assisted selection (MAS) and genomic selection (GS) has revolutionized plant breeding. A key factor affecting GS applicability is the choice of molecular marker platform. Genotyping-by-sequencing scored SNPs (GBS-scored SNPs) provides a large number of markers, albeit with high rates of missing data. Array scored SNPs are of high quality, but the cost per sample is substantially higher. The objectives of this study were 1) compare GBS-scored SNPs, and array scored SNPs for genomic selection applications, and 2) compare estimates of genomic kinship and population structure calculated using the two marker platforms. SNPs were compared in a diversity panel consisting of 299 hard winter wheat (Triticum aestivum L.) accessions that were part of a multi-year, multi-environments association mapping study. The panel was phenotyped in Ithaca, Nebraska for heading date, plant height, days to physiological maturity and grain yield in 2012 and 2013. The panel was genotyped using GBS-scored SNPs, and array scored SNPs. Results indicate that GBS-scored SNPs is comparable to or better than Array-scored SNPs for genomic prediction application. Both platforms identified the same genetic patterns in the panel where 90% of the lines were classified to common genetic groups. Overall, we concluded that GBS-scored SNPs have the potential to be the marker platform of choice for genetic diversity and genomic selection in winter wheat.

Genomic prediction applied to high-biomass sorghum for bioenergy production

The increasing cost of energy and finite oil and gas reserves have created a need to develop alternative fuels from renewable sources. Due to its abiotic stress tolerance and annual cultivation, high-biomass sorghum (Sorghum bicolor L. Moench) shows potential as a bioenergy crop. Genomic selection is a useful tool for accelerating genetic gains and could restructure plant breeding programs by enabling early selection and reducing breeding cycle duration. This work aimed at predicting breeding values via genomic selection models for 200 sorghum genotypes comprising landrace accessions and breeding lines from biomass and saccharine groups. These genotypes were divided into two sub-panels, according to breeding purpose. We evaluated the following phenotypic biomass traits: days to flowering, plant height, fresh and dry matter yield, and fiber, cellulose, hemicellulose, and lignin proportions. Genotyping by sequencing yielded more than 258,000 single-nucleotide polymorphism markers, which revealed population structure between subpanels. We then fitted and compared genomic selection models BayesA, BayesB, BayesCπ, BayesLasso, Bayes Ridge Regression and random regression best linear unbiased predictor. The resulting predictive abilities varied little between the different models, but substantially between traits. Different scenarios of prediction showed the potential of using genomic selection results between sub-panels and years, although the genotype by environment interaction negatively affected accuracies. Functional enrichment analyses performed with the marker-predicted effects suggested several interesting associations, with potential for revealing biological processes relevant to the studied quantitative traits. This work shows that genomic selection can be successfully applied in biomass sorghum breeding programs.

A genetic linkage map of Pleurotus tuoliensis integrated with physical mapping of the de novo sequenced genome and the mating type loci

Background

Pleurotus tuoliensis (Bailinggu) is a commercially cultivated mushroom species with an increasing popularity in China and other Asian countries. Commercial profits are now low, mainly due to a low yield, long cultivation period and sensitivity to diseases. Breeding efforts are thus required to improve agronomical important traits. Developing saturated genetic linkage and physical maps is a start for applying genetic and molecular approaches to accelerate the precise breeding programs.

Results

Here we present a genetic linkage map for P. tuoliensis constructed by using 115 haploid monokaryons derived from a hybrid strain H6. One thousand one hundred and eighty-two SNP markers developed by 2b–RAD (type IIB restriction-site associated DNA) approach were mapped to 12 linkage groups. The map covers 1073 cM with an average marker spacing of 1.0 cM. The genome of P. tuoliensis was de novo sequenced as 40.8 Mb and consisted of 500 scaffolds (>500 bp), which showed a high level of colinearity to the genome of P. eryngii var. eryngii. A total of 97.4% SNP markers (1151) were physically localized on 78 scaffolds, and the physical length of these anchored scaffolds were 33.9 Mb representing 83.1% of the whole genome. Mating type loci A and B were mapped on separate linkage groups and identified physically on the assembled genomes. Five putative pheromone receptors and two putative pheromone precursors were identified for the mating type B locus.

Conclusions

This study reported a first genetic linkage map integrated with physical mapping of the de novo sequenced genome and the mating type loci of an important cultivated mushroom in China, P. tuoliensis. The de novo sequenced and annotated genome, assembled using a 2b–RAD generated linkage map, provides a basis for marker-assisted breeding of this economic important mushroom species.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4421-z) contains supplementary material, which is available to authorized users.

Development of species diagnostic SNP markers for quality control genotyping in four rice (Oryza L.) species

Species misclassification (misidentification) and handling errors have been frequently reported in various plant species conserved at diverse gene banks, which could restrict use of germplasm for correct purpose. The objectives of the present study were to (i) determine the extent of genotyping error (reproducibility) on DArTseq-based single-nucleotide polymorphisms (SNPs); (ii) determine the proportion of misclassified accessions across 3134 samples representing three African rice species complex (Oryza glaberrima, O. barthii, and O. longistaminata) and an Asian rice (O. sativa), which are conserved at the AfricaRice gene bank; and (iii) develop species- and sub-species (ecotype)-specific diagnostic SNP markers for rapid and low-cost quality control (QC) analysis. Genotyping error estimated from 15 accessions, each replicated from 2 to 16 times, varied from 0.2 to 3.1%, with an overall average of 0.8%. Using a total of 3134 accessions genotyped with 31,739 SNPs, the proportion of misclassified samples was 3.1% (97 of the 3134 accessions). Excluding the 97 misclassified accessions, we identified a total of 332 diagnostic SNPs that clearly discriminated the three indigenous African species complex from Asian rice (156 SNPs), O. longistaminata accessions from both O. barthii and O. glaberrima (131 SNPs), and O. sativa spp. indica from O. sativa spp. japonica (45 SNPs). Using chromosomal position, minor allele frequency, and polymorphic information content as selection criteria, we recommended a subset of 24 to 36 of the 332 diagnostic SNPs for routine QC genotyping, which would be highly useful in determining the genetic identity of each species and correct human errors during routine gene bank operations.

TSPmap, a tool making use of traveling salesperson problem solvers in the efficient and accurate construction of high-density genetic linkage maps

Background

Recent advances in nucleic acid sequencing technologies have led to a dramatic increase in the number of markers available to generate genetic linkage maps. This increased marker density can be used to improve genome assemblies as well as add much needed resolution for loci controlling variation in ecologically and agriculturally important traits. However, traditional genetic map construction methods from these large marker datasets can be computationally prohibitive and highly error prone.

Results

We present TSPmap, a method which implements both approximate and exact Traveling Salesperson Problem solvers to generate linkage maps. We demonstrate that for datasets with large numbers of genomic markers (e.g. 10,000) and in multiple population types generated from inbred parents, TSPmap can rapidly produce high quality linkage maps with low sensitivity to missing and erroneous genotyping data compared to two other benchmark methods, JoinMap and MSTmap. TSPmap is open source and freely available as an R package.

Conclusions

With the advancement of low cost sequencing technologies, the number of markers used in the generation of genetic maps is expected to continue to rise. TSPmap will be a useful tool to handle such large datasets into the future, quickly producing high quality maps using a large number of genomic markers.

Electronic supplementary material

The online version of this article (10.1186/s13040-017-0158-0) contains supplementary material, which is available to authorized users.

Analysis of phylogenetic relationships and genome size evolution of the Amaranthus genus using GBS indicates the ancestors of an ancient crop

The genus Amaranthus consists of 50-70 species and harbors several cultivated and weedy species of great economic importance. A small number of suitable traits, phenotypic plasticity, gene flow and hybridization made it difficult to establish the taxonomy and phylogeny of the whole genus despite various studies using molecular markers. We inferred the phylogeny of the Amaranthus genus using genotyping by sequencing (GBS) of 94 genebank accessions representing 35 Amaranthus species and measured their genome sizes. SNPs were called by de novo and reference-based methods, for which we used the distant sugarbeet Beta vulgaris and the closely related Amaranthus hypochondriacus as references. SNP counts and proportions of missing data differed between methods, but the resulting phylogenetic trees were highly similar. A distance-based neighbor joining tree of individual accessions and a species tree calculated with the multispecies coalescent supported a previous taxonomic classification into three subgenera although the subgenus A. Acnida consists of two highly differentiated clades. The analysis of the Hybridus complex within the A. Amaranthus subgenus revealed insights on the history of cultivated grain amaranths. The complex includes the three cultivated grain amaranths and their wild relatives and was well separated from other species in the subgenus. Wild and cultivated amaranth accessions did not differentiate according to the species assignment but clustered by their geographic origin from South and Central America. Different geographically separated populations of Amaranthus hybridus appear to be the common ancestors of the three cultivated grain species and A. quitensis might be additionally be involved in the evolution of South American grain amaranth (A. caudatus). We also measured genome sizes of the species and observed little variation with the exception of two lineages that showed evidence for a recent polyploidization. With the exception of two lineages, genome sizes are quite similar and indicate that polyploidization did not play a major role in the history of the genus.

Molecular Dissection of Seedling Salinity Tolerance in Rice (Oryza sativa L.) Using a High-Density GBS-Based SNP Linkage Map

BACKGROUND

Salinity is one of the many abiotic stresses limiting rice production worldwide. Several studies were conducted to identify quantitative trait loci (QTLs) for traits associated to salinity tolerance. However, due to large confidence interval for the position of QTLs, utility of reported QTLs and the associated markers has been limited in rice breeding programs. The main objective of this study is to construct a high-density rice genetic map for identification QTLs and candidate genes for salinity tolerance at seedling stage.

RESULTS

We evaluated a population of 187 recombinant inbred lines (RILs) developed from a cross between Bengal and Pokkali for nine traits related to salinity tolerance. A total of 9303 SNP markers generated by genotyping-by-sequencing (GBS) were mapped to 2817 recombination points. The genetic map had a total map length of 1650 cM with an average resolution of 0.59 cM between markers. For nine traits, a total of 85 additive QTLs were identified, of which, 16 were large-effect QTLs and the rest were small-effect QTLs. The average interval size of QTL was about 132 kilo base pairs (Kb). Eleven of the 85 additive QTLs validated 14 reported QTLs for shoot potassium concentration, sodium-potassium ratio, salt injury score, plant height, and shoot dry weight. Epistatic QTL mapping identified several pairs of QTLs that significantly contributed to the variation of traits. The QTL for high shoot K⁺ concentration was mapped near the qSKC1 region. However, candidate genes within the QTL interval were a CC-NBS-LRR protein, three uncharacterized genes, and transposable elements. Additionally, many QTLs flanked small chromosomal intervals containing few candidate genes. Annotation of the genes located within QTL intervals indicated that ion transporters, osmotic regulators, transcription factors, and protein kinases may play essential role in various salt tolerance mechanisms.

CONCLUSION

The saturation of SNP markers in our linkage map increased the resolution of QTL mapping. Our study offers new insights on salinity tolerance and presents useful candidate genes that will help in marker-assisted gene pyramiding to develop salt tolerant rice varieties.

Genome-wide SNP discovery and population structure analysis in pepper (Capsicum annuum) using genotyping by sequencing

Background

Knowledge on population structure and genetic diversity in vegetable crops is essential for association mapping studies and genomic selection. Genotyping by sequencing (GBS) represents an innovative method for large scale SNP detection and genotyping of genetic resources. Herein we used the GBS approach for the genome-wide identification of SNPs in a collection of Capsicum spp. accessions and for the assessment of the level of genetic diversity in a subset of 222 cultivated pepper (Capsicum annum) genotypes.

Results

GBS analysis generated a total of 7,568,894 master tags, of which 43.4% uniquely aligned to the reference genome CM334. A total of 108,591 SNP markers were identified, of which 105,184 were in C. annuum accessions. In order to explore the genetic diversity of C. annuum and to select a minimal core set representing most of the total genetic variation with minimum redundancy, a subset of 222 C. annuum accessions were analysed using 32,950 high quality SNPs. Based on Bayesian and Hierarchical clustering it was possible to divide the collection into three clusters. Cluster I had the majority of varieties and landraces mainly from Southern and Northern Italy, and from Eastern Europe, whereas clusters II and III comprised accessions of different geographical origins. Considering the genome-wide genetic variation among the accessions included in cluster I, a second round of Bayesian (K = 3) and Hierarchical (K = 2) clustering was performed. These analysis showed that genotypes were grouped not only based on geographical origin, but also on fruit-related features.

Conclusions

GBS data has proven useful to assess the genetic diversity in a collection of C. annuum accessions. The high number of SNP markers, uniformly distributed on the 12 chromosomes, allowed the accessions to be distinguished according to geographical origin and fruit-related features. SNP markers and information on population structure developed in this study will undoubtedly support genome-wide association mapping studies and marker-assisted selection programs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3297-7) contains supplementary material, which is available to authorized users.

Genome wide association study (GWAS) for grain yield in rice cultivated under water deficit

The identification of rice drought tolerant materials is crucial for the development of best performing cultivars for the upland cultivation system. This study aimed to identify markers and candidate genes associated with drought tolerance by Genome Wide Association Study analysis, in order to develop tools for use in rice breeding programs. This analysis was made with 175 upland rice accessions (Oryza sativa), evaluated in experiments with and without water restriction, and 150,325 SNPs. Thirteen SNP markers associated with yield under drought conditions were identified. Through stepwise regression analysis, eight SNP markers were selected and validated in silico, and when tested by PCR, two out of the eight SNP markers were able to identify a group of rice genotypes with higher productivity under drought. These results are encouraging for deriving markers for the routine analysis of marker assisted selection. From the drought experiment, including the genes inherited in linkage blocks, 50 genes were identified, from which 30 were annotated, and 10 were previously related to drought and/or abiotic stress tolerance, such as the transcription factors WRKY and Apetala2, and protein kinases.

Exome genotyping, linkage disequilibrium and population structure in loblolly pine (Pinus taeda L.)

Background

Loblolly pine (Pinus taeda L.) is one of the most widely planted and commercially important forest tree species in the USA and worldwide, and is an object of intense genomic research. However, whole genome resequencing in loblolly pine is hampered by its large size and complexity and a lack of a good reference. As a valid and more feasible alternative, entire exome sequencing was hence employed to identify the gene-associated single nucleotide polymorphisms (SNPs) and to genotype the sampled trees.

Results

The exons were captured in the ADEPT2 association mapping population of 375 clonally-propagated loblolly pine trees using NimbleGen oligonucleotide hybridization probes, and then exome-enriched genomic DNA fragments were sequenced using the Illumina HiSeq 2500 platform. Oligonucleotide probes were designed based on 199,723 exons (≈49 Mbp) partitioned from the loblolly pine reference genome (PineRefSeq v. 1.01). The probes covered 90.2 % of the target regions. Capture efficiency was high; on average, 67 % of the sequence reads generated for each tree could be mapped to the capture target regions, and more than 70 % of the captured target bases had at least 10X sequencing depth per tree. A total of 972,720 high quality SNPs were identified after filtering. Among them, 53 % were located in coding regions (CDS), 5 % in 5’ or 3’ untranslated regions (UTRs) and 42 % in non-target and non-coding regions, such as introns and adjacent intergenic regions collaterally captured. We found that linkage disequilibrium (LD) decayed very rapidly, with the correlation coefficient (r²) between pairs of SNPs linked within single scaffolds decaying to half maximum (r² = 0.22) within 55 bp, to r² = 0.1 within 192 bp, and to r² = 0.05 within 451 bp. Population structure analysis using unlinked SNPs demonstrated the presence of two main distinct clusters representing western and eastern parts of the loblolly pine range included in our sample of trees.

Conclusions

The obtained results demonstrated the efficiency of exome capture for genotyping species such as loblolly pine with a large and complex genome. The highly diverse genetic variation reported in this study will be a valuable resource for future genetic and genomic research in loblolly pine.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3081-8) contains supplementary material, which is available to authorized users.

Exploiting genotyping by sequencing to characterize the genomic structure of the American cranberry through high-density linkage mapping

Background

The application of genotyping by sequencing (GBS) approaches, combined with data imputation methodologies, is narrowing the genetic knowledge gap between major and understudied, minor crops. GBS is an excellent tool to characterize the genomic structure of recently domesticated (~200 years) and understudied species, such as cranberry (Vaccinium macrocarpon Ait.), by generating large numbers of markers for genomic studies such as genetic mapping.

Results

We identified 10842 potentially mappable single nucleotide polymorphisms (SNPs) in a cranberry pseudo-testcross population wherein 5477 SNPs and 211 short sequence repeats (SSRs) were used to construct a high density linkage map in cranberry of which a total of 4849 markers were mapped. Recombination frequency, linkage disequilibrium (LD), and segregation distortion at the genomic level in the parental and integrated linkage maps were characterized for first time in cranberry. SSR markers, used as the backbone in the map, revealed high collinearity with previously published linkage maps. The 4849 point map consisted of twelve linkage groups spanning 1112 cM, which anchored 2381 nuclear scaffolds accounting for ~13 Mb of the estimated 470 Mb cranberry genome. Bin mapping identified 592 and 672 unique bins in the parentals and a total of 1676 unique marker positions in the integrated map. Synteny analyses comparing the order of anchored cranberry scaffolds to their homologous positions in kiwifruit, grape, and coffee genomes provided initial evidence of homology between cranberry and closely related species.

Conclusions

GBS data was used to rapidly saturate the cranberry genome with markers in a pseudo-testcross population. Collinearity between the present saturated genetic map and previous cranberry SSR maps suggests that the SNP locations represent accurate marker order and chromosome structure of the cranberry genome. SNPs greatly improved current marker genome coverage, which allowed for genome-wide structure investigations such as segregation distortion, recombination, linkage disequilibrium, and synteny analyses. In the future, GBS can be used to accelerate cranberry molecular breeding through QTL mapping and genome-wide association studies (GWAS).

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2802-3) contains supplementary material, which is available to authorized users.

Digital fragment analysis of short tandem repeats by high-throughput amplicon sequencing

High‐throughput sequencing has been proposed as a method to genotype microsatellites and overcome the four main technical drawbacks of capillary electrophoresis: amplification artifacts, imprecise sizing, length homoplasy, and limited multiplex capability. The objective of this project was to test a high‐throughput amplicon sequencing approach to fragment analysis of short tandem repeats and characterize its advantages and disadvantages against traditional capillary electrophoresis. We amplified and sequenced 12 muskrat microsatellite loci from 180 muskrat specimens and analyzed the sequencing data for precision of allele calling, propensity for amplification or sequencing artifacts, and for evidence of length homoplasy. Of the 294 total alleles, we detected by sequencing, only 164 alleles would have been detected by capillary electrophoresis as the remaining 130 alleles (44%) would have been hidden by length homoplasy. The ability to detect a greater number of unique alleles resulted in the ability to resolve greater population genetic structure. The primary advantages of fragment analysis by sequencing are the ability to precisely size fragments, resolve length homoplasy, multiplex many individuals and many loci into a single high‐throughput run, and compare data across projects and across laboratories (present and future) with minimal technical calibration. A significant disadvantage of fragment analysis by sequencing is that the method is only practical and cost‐effective when performed on batches of several hundred samples with multiple loci. Future work is needed to optimize throughput while minimizing costs and to update existing microsatellite allele calling and analysis programs to accommodate sequence‐aware microsatellite data.

Genomic variation among populations of threatened coral: Acropora cervicornis

Background

Acropora cervicornis, a threatened, keystone reef-building coral has undergone severe declines (>90 %) throughout the Caribbean. These declines could reduce genetic variation and thus hamper the species’ ability to adapt. Active restoration strategies are a common conservation approach to mitigate species' declines and require genetic data on surviving populations to efficiently respond to declines while maintaining the genetic diversity needed to adapt to changing conditions. To evaluate active restoration strategies for the staghorn coral, the genetic diversity of A. cervicornis within and among populations was assessed in 77 individuals collected from 68 locations along the Florida Reef Tract (FRT) and in the Dominican Republic.

Results

Genotyping by Sequencing (GBS) identified 4,764 single nucleotide polymorphisms (SNPs). Pairwise nucleotide differences (π) within a population are large (~37 %) and similar to π across all individuals. This high level of genetic diversity along the FRT is similar to the diversity within a small, isolated reef. Much of the genetic diversity (>90 %) exists within a population, yet GBS analysis shows significant variation along the FRT, including 300 SNPs with significant F_ST values and significant divergence relative to distance. There are also significant differences in SNP allele frequencies over small spatial scales, exemplified by the large F_ST values among corals collected within Miami-Dade county.

Conclusions

Large standing diversity was found within each population even after recent declines in abundance, including significant, potentially adaptive divergence over short distances. The data here inform conservation and management actions by uncovering population structure and high levels of diversity maintained within coral collections among sites previously shown to have little genetic divergence. More broadly, this approach demonstrates the power of GBS to resolve differences among individuals and identify subtle genetic structure, informing conservation goals with evolutionary implications.

Association analysis for disease resistance to Fusarium oxysporum in cape gooseberry (Physalis peruviana L)

BACKGROUND

Vascular wilt caused by Fusarium oxysporum is the most important disease in cape gooseberry (Physalis peruviana L.) in Colombia. The development of resistant cultivars is considered one of the most cost-effective means to reduce the impact of this disease. In order to do so, it is necessary to provide breeders with molecular markers and promising germplasm for introgression of different resistance loci as part of breeding schemes. Here we described an association mapping study in cape gooseberry with the goal to: (i) select promising materials for use in plant breeding and (ii) identify SNPs associated with the cape gooseberry resistance response to the F. oxysporum pathogen under greenhouse conditions, as potential markers for cape gooseberry breeding.

RESULTS

We found a total of 21 accessions with different resistance responses within a diversity panel of 100 cape gooseberry accessions. A total of 60,663 SNPs were also identified within the same panel by means of GBS (Genotyping By Sequencing). Model-based population structure and neighbor-joining analyses showed three populations comprising the cape gooseberry panel. After correction for population structure and kinship, we identified SNPs markers associated with the resistance response against F. oxysporum. The identification of markers was based on common tags using the reference genomes of tomato and potato as well as the root/stem transcriptome of cape gooseberry. By comparing their location with the tomato genome, 16 SNPs were found in genes involved in defense/resistance response to pathogens, likewise when compared with the genome of potato, 12 markers were related.

CONCLUSIONS

The work presented herein provides the first association mapping study in cape gooseberry showing both the identification of promising accessions with resistance response phenotypes and the identification of a set of SNP markers mapped to defense/resistance response genes of reference genomes. Thus, the work also provides new knowledge on candidate genes involved in the P. peruviana - F. oxysporum pathosystem as a foundation for further validation in marker-assisted selection. The results have important implications for conservation and breeding strategies in cape gooseberry.

Genome-wide association mapping for root traits in a panel of rice accessions from Vietnam

BACKGROUND

Despite recent sequencing efforts, local genetic resources remain underexploited, even though they carry alleles that can bring agronomic benefits. Taking advantage of the recent genotyping with 22,000 single-nucleotide polymorphism markers of a core collection of 180 Vietnamese rice varieties originating from provinces from North to South Vietnam and from different agrosystems characterized by contrasted water regimes, we have performed a genome-wide association study for different root parameters. Roots contribute to water stress avoidance and are a still underexploited target for breeding purpose due to the difficulty to observe them.

RESULTS

The panel of 180 rice varieties was phenotyped under greenhouse conditions for several root traits in an experimental design with 3 replicates. The phenotyping system consisted of long plastic bags that were filled with sand and supplemented with fertilizer. Root length, root mass in different layers, root thickness, and the number of crown roots, as well as several derived root parameters and shoot traits, were recorded. The results were submitted to association mapping using a mixed model involving structure and kinship to enable the identification of significant associations. The analyses were conducted successively on the whole panel and on its indica (115 accessions) and japonica (64 accessions) subcomponents. The two associations with the highest significance were for root thickness on chromosome 2 and for crown root number on chromosome 11. No common associations were detected between the indica and japonica subpanels, probably because of the polymorphism repartition between the subspecies. Based on orthology with Arabidopsis, the possible candidate genes underlying the quantitative trait loci are reviewed.

CONCLUSIONS

Some of the major quantitative trait loci we detected through this genome-wide association study contain promising candidate genes encoding regulatory elements of known key regulators of root formation and development.

Skim-Based Genotyping by Sequencing Using a Double Haploid Population to Call SNPs, Infer Gene Conversions, and Improve Genome Assemblies

Genotyping by sequencing (GBS) is an emerging technology to rapidly call an abundance of Single Nucleotide Polymorphisms (SNPs) using genome sequencing technology. Several different methodologies and approaches have recently been established, most of these relying on a specific preparation of data. Here we describe our GBS-pipeline, which uses high coverage reads from two parents and low coverage reads from their double haploid offspring to call SNPs on a large scale. The upside of this approach is the high resolution and scalability of the method.

Linkage of an ABCC transporter to a single QTL that controls Ostrinia nubilalis larval resistance to the Bacillus thuringiensis Cry1Fa toxin

Field evolved resistance of insect populations to Bacillus thuringiensis (Bt) crystalline (Cry) toxins expressed by crop plants has resulted in reduced control of insect feeding damage to field crops, and threatens the sustainability of Bt transgenic technologies. A single quantitative trait locus (QTL) that determines resistance in Ostrinia nubilalis larvae capable of surviving on reproductive stage transgenic corn that express the Bt Cry1Fa toxin was previously mapped to linkage group 12 (LG12) in a backcross pedigree. Fine mapping with high-throughput single nucleotide polymorphism (SNP) anchor markers, a candidate ABC transporter (abcc2) marker, and de novo mutations predicted from a genotyping-by-sequencing (GBS) data redefined a 268.8 cM LG12. The single QTL on LG12 spanned an approximate 46.1 cM region, in which marker 02302.286 and abcc2 were ≤ 2.81 cM, and the GBS marker 697 was an estimated 1.89 cM distant from the causal genetic factor. This positional mapping data showed that an O. nubilalis genome region encoding an abcc2 transporter is in proximity to a single QTL involved in the inheritance of Cry1F resistance, and will assist in the future identification the mutation(s) involved with this phenotype.