Genotyping-by-sequencing Libraries Research Articles

Genotyping by sequencing for the construction of oil palm (Elaeis guineensis Jacq.) genetic linkage map and mapping of yield related quantitative trait loci.

Oil palm (Elaeis guineensis Jacq.) is one of the major oil-producing crops. Improving the quality and increasing the production yield of oil palm have been the primary focuses of both conventional and modern breeding approaches. However, the conventional breeding approach for oil palm is very challenging due to its longevity, which results in a long breeding cycle. Thus, the establishment of marker assisted selection (MAS) for oil palm breeding programs would speed up the breeding pipeline by generating new oil palm varieties that possess high commercial traits. With the decreasing cost of sequencing, Genotyping-by-sequencing (GBS) is currently feasible to many researchers and it provides a platform to accelerate the discovery of single nucleotide polymorphism (SNP) as well as insertion and deletion (InDel) markers for the construction of a genetic linkage map. A genetic linkage map facilitates the identification of significant DNA regions associated with the trait of interest via quantitative trait loci (QTL) analysis. A mapping population of 112 F1 individuals from a cross of Deli dura and Serdang pisifera was used in this study. GBS libraries were constructed using the double digestion method with HindIII and TaqI enzymes. Reduced representation libraries (RRL) of 112 F1 progeny and their parents were sequenced and the reads were mapped against the E. guineensis reference genome. To construct the oil palm genetic linkage map, informative SNP and InDel markers were used to discover significant DNA regions associated with the traits of interest. The nine traits of interest in this study were fresh fruit bunch (FFB) yield, oil yield (OY), oil to bunch ratio (O/B), oil to dry mesocarp ratio (O/DM) ratio, oil to wet mesocarp ratio (O/WM), mesocarp to fruit ratio (M/F), kernel to fruit ratio (K/F), shell to fruit ratio (S/F), and fruit to bunch ratio (F/B). A total of 2.5 million SNP and 153,547 InDel markers were identified. However, only a subset of 5,278 markers comprising of 4,838 SNPs and 440 InDels were informative for the construction of a genetic linkage map. Sixteen linkage groups were produced, spanning 2,737.6 cM for the maternal map and 4,571.6 cM for the paternal map, with average marker densities of one marker per 2.9 cM and one per 2.0 cM respectively, were produced. A QTL analysis was performed on nine traits; however, only QTL regions linked to M/F, K/F and S/F were declared to be significant. Of those QTLs were detected: two for M/F, four for K/F and one for S/F. These QTLs explained 18.1-25.6% of the phenotypic variance and were located near putative genes, such as casein kinase II and the zinc finger CCCH domain, which are involved in seed germination and growth. The identified QTL regions for M/F, K/F and S/F from this study could be applied in an oil palm breeding program and used to screen palms with desired traits via marker assisted selection (MAS).

Genotyping-by-Sequencing Technology in Plant Taxonomy and Phylogeny.

Genotyping-by-sequencing (GBS) is a method to discover and genotype simultaneous genome-wide high-throughput single nucleotide polymorphisms(SNPs). GBS is based on reducing genome complexity with restriction enzymes. Here we describe a method developed by Elshire et al. for constructing simplified GBS libraries and recent bioinformatic approaches developed to analyze the large volume of polymorphism data generated by this method. GBS approach is suitable for population studies, taxonomic and phylogenic studies, germplasm characterization, and breeding and trait mapping for a wide range of organisms, including plants with complex genomes.

Application of Low Coverage Genotyping by Sequencing in Selectively Bred Arctic Charr (Salvelinus alpinus).

Arctic charr (Salvelinus alpinus) is a species of high economic value for the aquaculture industry, and of high ecological value due to its Holarctic distribution in both marine and freshwater environments. Novel genome sequencing approaches enable the study of population and quantitative genetic parameters even on species with limited or no prior genomic resources. Low coverage genotyping by sequencing (GBS) was applied in a selected strain of Arctic charr in Sweden originating from a landlocked freshwater population. For the needs of the current study, animals from year classes 2013 (171 animals, parental population) and 2017 (759 animals; 13 full sib families) were used as a template for identifying genome wide single nucleotide polymorphisms (SNPs). GBS libraries were constructed using the PstI and MspI restriction enzymes. Approximately 14.5K SNPs passed quality control and were used for estimating a genomic relationship matrix. Thereafter a wide range of analyses were conducted in order to gain insights regarding genetic diversity and investigate the efficiency of the genomic information for parentage assignment and breeding value estimation. Heterozygosity estimates for both year classes suggested a slight excess of heterozygotes. Furthermore, FST estimates among the families of year class 2017 ranged between 0.009 – 0.066. Principal components analysis (PCA) and discriminant analysis of principal components (DAPC) were applied aiming to identify the existence of genetic clusters among the studied population. Results obtained were in accordance with pedigree records allowing the identification of individual families. Additionally, DNA parentage verification was performed, with results in accordance with the pedigree records with the exception of a putative dam where full sib genotypes suggested a potential recording error. Breeding value estimation for juvenile growth through the usage of the estimated genomic relationship matrix clearly outperformed the pedigree equivalent in terms of prediction accuracy (0.51 opposed to 0.31). Overall, low coverage GBS has proven to be a cost-effective genotyping platform that is expected to boost the selection efficiency of the Arctic charr breeding program.

NanoGBS: A Miniaturized Procedure for GBS Library Preparation.

High-throughput reduced-representation sequencing (RRS)-based genotyping methods, such as genotyping-by-sequencing (GBS), have provided attractive genotyping solutions in numerous species. Here, we present NanoGBS, a miniaturized and eco-friendly method for GBS library construction. Using acoustic droplet ejection (ADE) technology, NanoGBS libraries were constructed in tenfold smaller volumes compared to standard methods (StdGBS) and leading to a reduced use of plastics of up to 90%. A high-quality DNA library and SNP catalogue were obtained with extensive overlap (96%) in SNP loci and 100% agreement in genotype calls compared to the StdGBS dataset with a high level of accuracy (98.5%). A highly multiplexed pool of GBS libraries (768-plex) was sequenced on a single Ion Proton PI chip and yielded enough SNPs (~4K SNPs; 1.5 SNP per cM, on average) for many high-volume applications. Combining NanoGBS library preparation and increased multiplexing can dramatically reduce (72%) genotyping cost per sample. We believe that this approach will greatly facilitate the adoption of marker applications where extremely high throughputs are required and cost is still currently limiting.

PSVIII-31 Genome-wide estimation of linkage disequilibrium using American mink genotyping-by-sequencing data

Abstract Linkage disequilibrium (LD) has been defined as the correlation between alleles at different loci in the genome. The LD levels can be influenced by the evolutionary processes and historical events in populations. The main objective of this study was to estimate the LD levels at different distances of American mink genome using genotyping-by-sequencing (GBS) data. A total of 285 American mink (Neovison vison) were sequenced based on GBS libraries prepared by digesting the genomic DNA with the restriction enzyme ApeKI. After quality control, 13,321 single nucleotide polymorphism (SNP) markers located on 46 Scaffolds were used to determine the extension of LD in the genome. The average r2 was computed for all syntenic SNP pairwise at inter-marker distances from 0 up to 1 Mb. The average r2 between adjacent SNPs was 0.29, ranged from 0.18 to 0.53 across all scaffolds. In addition, the average distance between adjacent markers was 51 kb. The average r2 above 0.3 was observed in less than 1 kb distances and declined with increase in distances between markers. The average r2 was estimated to be less than 0.2 for markers more than 10 kb apart. Furthermore, the average LD level was decreased to 0.08 for inter-marker distances between 0.9 and 1 Mb. The results of this study can be used to determine the optimum maker density required for obtaining enough accuracy and power in both genomic selection and genome-wide association studies.

Genotyping-by-sequencing approaches using optimized two-enzyme combinations in Asian pears (Pyrus spp.)

In genotyping-by-sequencing (GBS) library construction, restriction enzyme (RE) can influence the size and number of DNA fragments. The objective of the present study was to improve GBS efficiency in pears (Pyrus spp.) by selecting optimized RE combination. To prove GBS efficiency of selected RE combination, population structure and genetic diversity results of Asian pears were compared in two single nucleotide polymorphisms (SNP) sets derived from different GBS libraries. After in silico digestion, ApeKI, ApeKI/TfiI, and ApeKI/MseI were selected to construct GBS libraries and the number of SNPs obtained from ApeKI/TfiI library were about six times more than that from the ApeKI library. In addition, the SNPs of ApeKI/TfiI library showed high accuracy in classification of Asian pear accessions. Thus, ApeKI/TfiI combination is recommended for construction of GBS library in pears because such RE combination could provide genome-wide and numerous informative SNPs for pear genetic studies.

Identification of quantitative trait loci associated with flowering time in perilla using genotyping-by-sequencing.

Understanding the transition to the reproductive period is important for crop breeding. This information can facilitate the production of novel varieties that are better adapted to local environments or changing climatic conditions. Here, we report the development of a high-density linkage map based on genotyping-by-sequencing (GBS) for the genus perilla. Through GBS library construction and Illumina sequencing of an F2 population, a total of 9607 single-nucleotide polymorphism (SNP) markers were developed. The ten-group linkage map of 1309.39cM contained 2518 markers, with an average marker density of 0.56cM per linkage group (LG). Using this map, a total of six QTLs were identified. Thesequantitative trait loci (QTLs) are associated with three traits related to flowering time: days to visible flower bud, days to flowering, and days to maturity. Ortholog analysis conducted with known genes involved in the regulation of flowering time among different crop species identified GI, CO and ELF4 as putative perilla orthologs that are closely linked to the QTL regions associated with flowering time. These results provide a foundation that will be useful for future studies of flowering time in perilla using fine mapping, and marker-assisted selection for the development of new varieties of perilla.

Protocol: a versatile, inexpensive, high-throughput plant genomic DNA extraction method suitable for genotyping-by-sequencing

BackgroundThe recent development of next-generation sequencing DNA marker technologies, such as genotyping-by-sequencing (GBS), generates thousands of informative single nucleotide polymorphism markers in almost any species, regardless of genomic resources. This enables poorly resourced or “orphan” crops/species access to high-density, high-throughput marker platforms which have revolutionised population genetics studies and plant breeding. DNA quality underpins success of GBS methods as the DNA must be amenable to restriction enzyme digestion and sequencing. A barrier to implementing GBS technologies is access to inexpensive, high-throughput extraction methods that yield sequencing-quality genomic DNA (gDNA) from plants. Several high-throughput DNA extraction methods are available, but typically provide low yield or poor quality gDNA, or are costly (US$6–$9/sample) for consumables.ResultsWe modified a non-organic solvent protocol to extract microgram quantities (1–13 μg) of sequencing-quality high molecular weight gDNA inexpensively in 96-well plates from either fresh, freeze-dried or silica gel-dried plant tissue. The protocol was effective for several easy and difficult-to-extract forage, crop, horticultural and common model species including Trifolium, Medicago, Lolium, Secale, Festuca, Malus, Oryza, and Arabidopsis. The extracted DNA was of high molecular weight and digested readily with restriction enzymes. Contrasting with other extraction protocols we assessed, Illumina-based sequencing of GBS libraries developed from this gDNA had very uniform high quality base-calls to the end of sequence reads. Furthermore, DNA extracted using this method has been sequenced successfully with the PacBio long-read platform. The protocol is scalable, readily automated without requirement for fume hoods, requires approximately three hours to process 192 samples (384–576 samples/day), and is inexpensive at US$0.62/sample for consumables.ConclusionsThis versatile, scalable and simple protocol yields high molecular weight genomic DNA suitable for restriction enzyme digestion and next-generation sequencing applications including GBS and long-read sequencing platforms such as PacBio. The low cost, high-throughput, and extraction of high quality gDNA from a range of fresh and dried source plant material makes this method suitable for many sequencing and genotyping applications including large-scale sample screening underpinning breeding programmes.

QTL mapping and GWAS reveal candidate genes controlling capsaicinoid content in Capsicum.

SummaryCapsaicinoids are unique compounds produced only in peppers (Capsicum spp.). Several studies using classical quantitative trait loci (QTLs) mapping and genomewide association studies (GWAS) have identified QTLs controlling capsaicinoid content in peppers; however, neither the QTLs common to each population nor the candidate genes underlying them have been identified due to the limitations of each approach used. Here, we performed QTL mapping and GWAS for capsaicinoid content in peppers using two recombinant inbred line (RIL) populations and one GWAS population. Whole‐genome resequencing and genotyping by sequencing (GBS) were used to construct high‐density single nucleotide polymorphism (SNP) maps. Five QTL regions on chromosomes 1, 2, 3, 4 and 10 were commonly identified in both RIL populations over multiple locations and years. Furthermore, a total of 109 610 SNPs derived from two GBS libraries were used to analyse the GWAS population consisting of 208 C. annuum‐clade accessions. A total of 69 QTL regions were identified from the GWAS, 10 of which were co‐located with the QTLs identified from the two biparental populations. Within these regions, we were able to identify five candidate genes known to be involved in capsaicinoid biosynthesis. Our results demonstrate that QTL mapping and GBS‐GWAS represent a powerful combined approach for the identification of loci controlling complex traits.

Optimization of Genotyping-by-sequencing (GBS) in Chrysanthemums: Selecting Proper Restriction Enzymes for GBS Library Construction

Chrysanthemum is one of the most popular ornamental flowers in Korea due to its great diversity of colors and forms. To understand this diversity and to efficiently breed chrysanthemum varieties, a genetic diversity assessment of Korean native chrysanthemum populations using molecular markers is required. Genotyping-by-sequencing (GBS) is a newly developed and widely used next generation sequencing (NGS) method based on the single nucleotide polymorphism (SNP) marker system. In this study, we tested three restriction enzyme combinations (ApeKI, ApeKI/MseI, and ApeKI/MspI) for GBS library construction using eight Korean native Chrysanthemum spp. accessions. Three libraries were constructed and sequenced on the Illumina NextSeq 500 platform and results were analyzed in the Stacks de novo GBS pipeline. Overall, the ApeKI/MseI combination showed the best library quality, highest number of tags, and SNP generation potential.

Genotyping by sequencing reveals the interspecific C. maxima / C. reticulata admixture along the genomes of modern citrus varieties of mandarins, tangors, tangelos, orangelos and grapefruits.

The mandarin horticultural group is an important component of world citrus production for the fresh fruit market. This group formerly classified as C. reticulata is highly polymorphic and recent molecular studies have suggested that numerous cultivated mandarins were introgressed by C. maxima (the pummelos). C. maxima and C. reticulata are also the ancestors of sweet and sour oranges, grapefruit, and therefore of all the “small citrus” modern varieties (mandarins, tangors, tangelos) derived from sexual hybridization between these horticultural groups. Recently, NGS technologies have greatly modified how plant evolution and genomic structure are analyzed, moving from phylogenetics to phylogenomics. The objective of this work was to develop a workflow for phylogenomic inference from Genotyping By Sequencing (GBS) data and to analyze the interspecific admixture along the nine citrus chromosomes for horticultural groups and recent varieties resulting from the combination of the C. reticulata and C. maxima gene pools. A GBS library was established from 55 citrus varieties, using the ApekI restriction enzyme and selective PCR to improve the read depth. Diagnostic polymorphisms (DPs) of C. reticulata/C. maxima differentiation were identified and used to decipher the phylogenomic structure of the 55 varieties. The GBS approach was powerful and revealed 30,289 SNPs and 8,794 Indels with 12.6% of missing data. 11,133 DPs were selected covering the nine chromosomes with a higher density in genic regions. GBS combined with the detection of DPs was powerful for deciphering the “phylogenomic karyotypes” of cultivars derived from admixture of the two ancestral species after a limited number of interspecific recombinations. All the mandarins, mandarin hybrids, tangelos and tangors analyzed displayed introgression of C. maxima in different parts of the genome. C. reticulata/C. maxima admixture should be a major component of the high phenotypic variability of this germplasm opening up the way for association studies based on phylogenomics.

Phased Genotyping-by-Sequencing Enhances Analysis of Genetic Diversity and Reveals Divergent Copy Number Variants in Maize.

High-throughput sequencing (HTS) of reduced representation genomic libraries has ushered in an era of genotyping-by-sequencing (GBS), where genome-wide genotype data can be obtained for nearly any species. However, there remains a need for imputation-free GBS methods for genotyping large samples taken from heterogeneous populations of heterozygous individuals. This requires that a number of issues encountered with GBS be considered, including the sequencing of nonoverlapping sets of loci across multiple GBS libraries, a common missing data problem that results in low call rates for markers per individual, and a tendency for applicability only in inbred line samples with sufficient linkage disequilibrium for accurate imputation. We addressed these issues while developing and validating a new, comprehensive platform for GBS. This study supports the notion that GBS can be tailored to particular aims, and using Zea mays our results indicate that large samples of unknown pedigree can be genotyped to obtain complete and accurate GBS data. Optimizing size selection to sequence a high proportion of shared loci among individuals in different libraries and using simple in silico filters, a GBS procedure was established that produces high call rates per marker (>85%) with accuracy exceeding 99.4%. Furthermore, by capitalizing on the sequence-read structure of GBS data (stacks of reads), a new tool for resolving local haplotypes and scoring phased genotypes was developed, a feature that is not available in many GBS pipelines. Using local haplotypes reduces the marker dimensionality of the genotype matrix while increasing the informativeness of the data. Phased GBS in maize also revealed the existence of reproducibly inaccurate (apparent accuracy) genotypes that were due to divergent copy number variants (CNVs) unobservable in the underlying single nucleotide polymorphism (SNP) data.

Development of SNP markers using genotyping-by-sequencing for cultivar identification in rose (Rosa hybrida)

In this study, we developed single nucleotide polymorphism (SNP) markers to identify cultivars of the polyploid Rosa hybrida using genotyping-by-sequencing (GBS). Sequences obtained from GBS libraries of the genomes of 79 rose cultivars were aligned to contigs created by de novo assembly, and these contigs ranged from 200 to 2,591 bp, with an average of 305 bp per contig. We selected 1,778 SNPs from 13,488 putative SNPs. SNP markers that were present in more than 70% of the 79 cultivars were selected and evaluated, both on the basis of polymorphism information content values and level of heterozygosity, and 20 SNP markers were ultimately selected for high- throughput analysis. From these 20 SNP markers, 4 were successfully converted to markers for DNA chip assays. High resolution melting analysis was carried out to further distinguish rose genotypes. Using a set of seven SNP markers, we identified 70.9% of the 79 rose cultivars, and 87.5% of the 16 new cultivars developed in Goyang City. This paper is the first to report the development of a SNP marker set to identify Rosa hybrida cultivars by GBS.

Low-depth genotyping-by-sequencing (GBS) in a bovine population: strategies to maximize the selection of high quality genotypes and the accuracy of imputation

BackgroundGenotyping-by-sequencing (GBS) has emerged as a powerful and cost-effective approach for discovering and genotyping single-nucleotide polymorphisms. The GBS technique was largely used in crop species where its low sequence coverage is not a drawback for calling genotypes because inbred lines are almost homozygous. In contrast, only a few studies used the GBS technique in animal populations (with sizeable heterozygosity rates) and many of those that have been published did not consider the quality of the genotypes produced by the bioinformatic pipelines. To improve the sequence coverage of the fragments, an alternative GBS preparation protocol that includes selective primers during the PCR amplification step has been recently proposed. In this study, we compared this modified protocol with the conventional two-enzyme GBS protocol. We also described various procedures to maximize the selection of high quality genotypes and to increase the accuracy of imputation.ResultsThe in silico digestions of the bovine genome showed that the combination of PstI and MspI is more suitable for sequencing bovine GBS libraries than the use of single digestions with PstI or ApeKI. The sequencing output of the GBS libraries generated a total of 123,666 variants with the selective-primer approach and 272,103 variants with the conventional approach. Validating our data with genotypes obtained from mass spectrometry and Illumina’s bovine SNP50 array, we found that the genotypes produced by the conventional GBS method were concordant with those produced by these alternative genotyping methods, whereas the selective-primer method failed to call heterozygotes with confidence. Our results indicate that high accuracy in genotype calling (>97%) can be obtained using low read-depth thresholds (3 to 5 reads) provided that markers are simultaneously filtered for genotype quality scores. We also show that factors such as the minimum call rate and the minor allele frequency positively influence the accuracy of imputation of missing GBS data. The highest accuracies (around 85%) of imputed GBS markers were obtained with the FIMPUTE program when GBS and SNP50 array genotypes were combined (80,190 to 100,297 markers) before imputation.ConclusionsWe discovered that the conventional two-enzyme GBS protocol could produce a large number of high-quality genotypes provided that appropriate filtration criteria were used. In contrast, the selective-primer approach resulted in a substantial proportion of miscalled genotypes and should be avoided for livestock genotyping studies. Overall, our study demonstrates that carefully adjusting the different filtering parameters applied to the GBS data is critical to maximize the selection of high quality genotypes and to increase the accuracy of imputation of missing data. The strategies and results presented here provide a framework to maximize the output of the GBS technique in animal populations and qualified the PstI/MspI GBS assay as a low-cost high-density genotyping platform. The conclusions reported here regarding read-depth and genotype quality filtering could benefit many GBS applications, notably genome-wide association studies, where there is a need to increase the density of markers genotyped across the target population while preserving the quality of genotypes.

Fast-GBS: a new pipeline for the efficient and highly accurate calling of SNPs from genotyping-by-sequencing data

BackgroundNext-generation sequencing (NGS) technologies have accelerated considerably the investigation into the composition of genomes and their functions. Genotyping-by-sequencing (GBS) is a genotyping approach that makes use of NGS to rapidly and economically scan a genome. It has been shown to allow the simultaneous discovery and genotyping of thousands to millions of SNPs across a wide range of species. For most users, the main challenge in GBS is the bioinformatics analysis of the large amount of sequence information derived from sequencing GBS libraries in view of calling alleles at SNP loci. Herein we describe a new GBS bioinformatics pipeline, Fast-GBS, designed to provide highly accurate genotyping, to require modest computing resources and to offer ease of use.ResultsFast-GBS is built upon standard bioinformatics language and file formats, is capable of handling data from different sequencing platforms, is capable of detecting different kinds of variants (SNPs, MNPs, and Indels). To illustrate its performance, we called variants in three collections of samples (soybean, barley, and potato) that cover a range of different genome sizes, levels of genome complexity, and ploidy. Within these small sets of samples, we called 35 k, 32 k and 38 k SNPs for soybean, barley and potato, respectively. To assess genotype accuracy, we compared these GBS-derived SNP genotypes with independent data sets obtained from whole-genome sequencing or SNP arrays. This analysis yielded estimated accuracies of 98.7, 95.2, and 94% for soybean, barley, and potato, respectively.ConclusionsWe conclude that Fast-GBS provides a highly efficient and reliable tool for calling SNPs from GBS data.

Genome-Wide SNPs Identification and Determination of Proteins Associated with Stress Response in Sorghum (<i>Sorghum bicolor</i> L. Monech) Accessions

Current efforts in sorghum breeding programs are exploiting genotyping-by-sequencing (GBS) data to provide full-genome scans for desired traits. The aim of this study was to utilize GBS approach for the identification of genomic regions associated with stress response in sorghum (Sorghum bicolor L. Monech) accessions. DNA samples of twenty sorghum accessions, having different response to drought, were used to prepare GBS libraries for sequencing. SNPs were called using the TASSELGBS pipeline and the tags that present at least 10 times in the dataset were considered and aligned to the reference genome of Sorghum bicolor. The identified SNPs were all compared with the published sorghum transcript related to stress response gene activity. Overall; 94.40% tags were aligned and 69,736 putative SNPs positions were identified. Blast search revealed homology to annotated heat and drought–tolerance associated genes which code for ATPases, Peroxidase, Hydrophobic protein LTI6A, Aquaporin SIP2-1, Aconitate hydratase and phosphatidylinositol-4-phosphate-5-kinase. The phylogeny of the 20 accessions was constructed using the generated SNPs data. Phylogenetic analysis data showed that the phenotypically tolerant line (El9) makes a separate cluster and the same for the accessions HSD8653 and HSD5612 near to the cluster that includes most accessions with known post-flowering drought tolerance (HSD7410, HDS10033, HSD8552, GESHEISH and HSD8849). Post-flowering drought sensitive accessions (Tabat, Wadahmed, HSD6468 and HSD6478) formed a separate cluster while the sensitive accession HSD9959 and the tolerant accessions HSD8511 and HSD9566 were distributed between the two clusters. Thus, cluster analysis confirmed the variation among accessions in post-flowering drought tolerance. With further validation, these markers may be used for marker assisted selection for breeding new sorghum genotypes with stress adaptation.

Effects of methylation-sensitive enzymes on the enrichment of genic SNPs and the degree of genome complexity reduction in a two-enzyme genotyping-by-sequencing (GBS) approach: a case study in oil palm (Elaeis guineensis).

Advances in next generation sequencing have facilitated a large-scale single nucleotide polymorphism (SNP) discovery in many crop species. Genotyping-by-sequencing (GBS) approach couples next generation sequencing with genome complexity reduction techniques to simultaneously identify and genotype SNPs. Choice of enzymes used in GBS library preparation depends on several factors including the number of markers required, the desired level of multiplexing, and whether the enrichment of genic SNP is preferred. We evaluated various combinations of methylation-sensitive (AatII, PstI, MspI) and methylation-insensitive (SphI, MseI) enzymes for their effectiveness in genome complexity reduction and enrichment of genic SNPs. We discovered that the use of two methylation-sensitive enzymes effectively reduced genome complexity and did not require a size selection step. On the contrary, the genome coverage of libraries constructed with methylation-insensitive enzymes was quite high, and the additional size selection step may be required to increase the overall read depth. We also demonstrated the effectiveness of methylation-sensitive enzymes in enriching for SNPs located in genic regions. When two methylation-insensitive enzymes were used, only 16% of SNPs identified were located in genes and 18% in the vicinity (± 5 kb) of the genic regions, while most SNPs resided in the intergenic regions. In contrast, a remarkable degree of enrichment was observed when two methylation-sensitive enzymes were employed. Almost two thirds of the SNPs were located either inside (32–36%) or in the vicinity (28–31%) of the genic regions. These results provide useful information to help researchers choose appropriate GBS enzymes in oil palm and other crop species.Electronic supplementary materialThe online version of this article (doi:10.1007/s11032-016-0572-x) contains supplementary material, which is available to authorized users.

Genotyping by Sequencing (GBS) in Apricots and Genetic Diversity Assessment with GBS-Derived Single-Nucleotide Polymorphisms (SNPs).

Genotyping by sequencing (GBS), which is a highly promising technique for molecular breeding, has been implemented in apricots, including Turkish, European, and Plum Pox Virus-resistant accessions. DNA samples were digested with the ApeKI restriction enzyme to construct a genome-complexity-reduced 90-plex GBS library. After filtering the raw sequences, approximately 28G of clean data were generated, and 17,842 high-quality single-nucleotide polymorphism (SNP) loci were discovered. A total of 561 SNP loci with 0 or 1 missing reads for the 90 accessions produced 1162 markers that were used for the cluster and population structure analysis of the same collection. The results of the SNP analysis indicated that the relation of the European accessions with the western Turkish apricots was accurately positioned. The resistant accessions from different sources were clustered together, confirming the previous finding that SEO/Harlayne-type resistance probably originated from the same source. The Malatya accessions produce most of the world's dried apricots and are likely to be a genetically distinct group. Simple sequence repeat (SSR) and self-incompatibly (SI) locus characterization of the accessions was also included. SI genotyping supported the SNP findings, demonstrating both the reliability of SNP genotyping and the usefulness of SI genotyping for understanding the history of apricot breeding. The SSR genotyping revealed a characterization similar to that of SNP genotyping with a slightly lower resolution in the dendrogram. In conclusion, the GBS approach was validated in apricots, with the discovery of a large number of SNPs, and was demonstrated to be reliable by fingerprinting the accessions in a more informative manner.

Development of a High-Density Linkage Map and Tagging Leaf Spot Resistance in Pearl Millet Using Genotyping-by-Sequencing Markers.

Pearl millet [ (L.) R. Br; also (L.) Morrone] is an important crop throughout the world but better genomic resources for this species are needed to facilitate crop improvement. Genome mapping studies are a prerequisite for tagging agronomically important traits. Genotyping-by-sequencing (GBS) markers can be used to build high-density linkage maps, even in species lacking a reference genome. A recombinant inbred line (RIL) mapping population was developed from a cross between the lines 'Tift 99DB' and 'Tift 454'. DNA from 186 RILs, the parents, and the F was used for 96-plex KI GBS library development, which was further used for sequencing. The sequencing results showed that the average number of good reads per individual was 2.2 million, the pass filter rate was 88%, and the CV was 43%. High-quality GBS markers were developed with stringent filtering on sequence data from 179 RILs. The reference genetic map developed using 150 RILs contained 16,650 single-nucleotide polymorphisms (SNPs) and 333,567 sequence tags spread across all seven chromosomes. The overall average density of SNP markers was 23.23 SNP/cM in the final map and 1.66 unique linkage bins per cM covering a total genetic distance of 716.7 cM. The linkage map was further validated for its utility by using it in mapping quantitative trait loci (QTLs) for flowering time and resistance to leaf spot [ (Cke.) Sacc.]. This map is the densest yet reported for this crop and will be a valuable resource for the pearl millet community.

An ultra-high density genetic linkage map of perennial ryegrass (Lolium perenne) using genotyping by sequencing (GBS) based on a reference shotgun genome assembly.

High density genetic linkage maps that are extensively anchored to assembled genome sequences of the organism in question are extremely useful in gene discovery. To facilitate this process in perennial ryegrass (Lolium perenne L.), a high density single nucleotide polymorphism (SNP)- and presence/absence variant (PAV)-based genetic linkage map has been developed in an F2 mapping population that has been used as a reference population in numerous studies. To provide a reference sequence to which to align genotyping by sequencing (GBS) reads, a shotgun assembly of one of the grandparents of the population, a tenth-generation inbred line, was created using Illumina-based sequencing. The assembly was based on paired-end Illumina reads, scaffolded by mate pair and long jumping distance reads in the range of 3-40 kb, with >200-fold initial genome coverage. A total of 169 individuals from an F2 mapping population were used to construct PstI-based GBS libraries tagged with unique 4-9 nucleotide barcodes, resulting in 284 million reads, with approx. 1·6 million reads per individual. A bioinformatics pipeline was employed to identify both SNPs and PAVs. A core genetic map was generated using high confidence SNPs, to which lower confidence SNPs and PAVs were subsequently fitted in a straightforward binning approach. The assembly comprises 424 750 scaffolds, covering 1·11 Gbp of the 2·5 Gbp perennial ryegrass genome, with a scaffold N50 of 25 212 bp and a contig N50 of 3790 bp. It is available for download, and access to a genome browser has been provided. Comparison of the assembly with available transcript and gene model data sets for perennial ryegrass indicates that approx. 570 Mbp of the gene-rich portion of the genome has been captured. An ultra-high density genetic linkage map with 3092 SNPs and 7260 PAVs was developed, anchoring just over 200 Mb of the reference assembly. The combined genetic map and assembly, combined with another recently released genome assembly, represent a significant resource for the perennial ryegrass genetics community.