Application Of Genotyping-by-sequencing Research Articles

Cutting-Edge of Genotyping by Sequencing (GBS) for Improving Drought and Salinity Stress Tolerance in Watermelon (Citrullus lanatus L.): A Review

AbstractGenotyping by sequencing (GBS) is a very helpful approach and one of the most useful techniques for examining and analysing the genetic variation of various lines and varieties. GBS technology was used to identify single nucleotide polymorphisms (SNPs) and assess genetic variation in several watermelon accessions. GBS application in watermelon breeding programs has recently become a popular technique among many breeders. Watermelon (Citrullus lanatus L.) is a warm-season crop that is widely cultivated for its delicious fruit. And it is one of the most economically significant crops in the world. However, watermelon cultivation is frequently hampered by abiotic stressors such as drought and salinity. Recently, there has been a growing body of research on the mechanisms that allow watermelon to tolerate these stresses and improve crop yield. Generally, cucurbits are beneficial to human health, they provide necessary minerals, fibre, and nutrient components. Therefore, this review demonstrates the cutting edge of using GBS technology to identify genetic design of several features in watermelon to improve abiotic stresses (drought and saline). The application of the GBS technique has provided a distinct advantage in watermelon breeding studies. Based on GBS approach, many new candidate genes in watermelon lines control a variety of traits including saline and drought tolerance, fruit rind color, disease tolerance, nutrient components, size, and fruit shape were discovered. Modern breeding techniques are being used to develop economically viable vegetable crops that will meet customer preferences and needs. Further research is needed to enhance watermelon production.

Population genetics of Todarodes pacificus (Cephalopoda: Ommastrephidae) in the northwest Pacific Ocean via GBS sequencing.

The common squid, Todarodes pacificus, is an important commercial species that inhabits the northwest Pacific Ocean, particularly the East Japan Sea, the Pacific coast of Japan, and the East China Sea. In this study, we chose 29 individuals from three areas: one type from the Sea of Japan and two types from the East China Sea. A total of 43,529 SNPs were obtained using genotyping-by-sequencing (GBS). Our analyses revealed low genetic diversity and genetic differentiation in each type. Heterozygote deficiency and inbreeding have caused this low level of genetic diversity. Population structure analysis indicated that the three types were genetically similar, which may be attributed to strong gene flow combined with the demographic history events during the last 2 million years. This new GBS application technique provides valuable information for the conservation of marine species genetics and could be useful for the effective management of this resource.

Analysis of chrysanthemum genetic diversity by genotyping-by-sequencing

Application of next-generation sequencing to very large genomes, such as chrysanthemum (Chrysanthemum sp.), faces challenges including repeated sequences, limited short-reads, and various contigs in massive fragments. Genotyping-by-sequencing (GBS) can overcome many of these drawbacks by high-multiplexing, and potential genotyping-sequencing approaches could have wide-ranging utilizations in chrysanthemum breeding. The study aimed to establish an approach for GBS application and to elucidate a phylogenomic structure in an individual with a large genome. We identified single nucleotide polymorphism (SNP) for SNP calling (279,189 markers) and SNP filtering (7758 markers) that will promote analysis of chrysanthemum population genetics. We conclude that GBS is the best approach for genotyping in chrysanthemum and can be applied in genetic breeding in various plants.

In-silico detection of aneuploidy and chromosomal deletions in wheat using genotyping-by-sequencing

BackgroundShort read sequencing technologies, such as genotyping-by-sequencing (GBS), have been utilized in genetic mapping, marker development, and population genomic studies. High-throughput and multiplexing capability coupled with low cost make GBS an appropriate tool for molecular research. Here, we present the application of GBS to characterize wheat aneuploid stocks and detect chromosomal aberrations including aneuploidy and chromosomal deletions. These aneuploids are an important resource that have been used in wheat genetics and genomics studies to localize genes, determine physical positions, and develop chromosome bin maps.ResultsUsing GBS, we mapped sequence reads and quantified read coverage across chromosome bins. Using this approach, we confirmed known deletions and aneuploid stocks. In addition, we were also able to fully characterize these stocks and to identify several novel deletions and aneuploids. With this knowledge and a quick detection tool at our disposal, we can easily isolate these deletions and aneuploids into distinct lines.ConclusionWe envision this tool to replace the intensive cytogenetics techniques, such as C-banding, and fluorescent- and genomic-in situ hybridization to accurately detect chromosome dosage and segmental deletions in wheat genetic stocks as well as other crop species.

Genotyping-by-Sequencing Enhances Genetic Diversity Analysis of Crested Wheatgrass [Agropyron cristatum (L.) Gaertn.

Molecular characterization of unsequenced plant species with complex genomes is now possible by genotyping-by-sequencing (GBS) using recent next generation sequencing technologies. This study represents the first use of GBS application to sample genome-wide variants of crested wheatgrass [Agropyron cristatum (L.) Gaertn.] and assess the genetic diversity present in 192 genotypes from 12 tetraploid lines. Bioinformatic analysis identified 45,507 single nucleotide polymorphism (SNP) markers in this outcrossing grass species. The model-based Bayesian analysis revealed four major clusters of the samples assayed. The diversity analysis revealed 15.8% of SNP variation residing among the 12 lines, and 12.1% SNP variation present among four genetic clusters identified by the Bayesian analysis. The principal coordinates analysis and dendrogram were able to distinguish four lines of Asian origin from Canadian cultivars and breeding lines. These results serve as a valuable resource for understanding genetic variability, and will aid in the genetic improvement of this outcrossing polyploid grass species for forage production. These findings illustrate the potential of GBS application in the characterization of non-model polyploid plants with complex genomes.

Genotyping-by-sequencing empowered genetic diversity analysis of Jordanian oat wild relative Avena sterilis

Recent advances in next generation sequencing technologies make genotyping-by-sequencing (GBS) more feasible for molecular characterization of plant germplasm with complex and unsequenced genomes. Here we applied the GBS technology to assess the genetic diversity of 275 hexaploid oat wild relative (Avena sterilis) plants collected from 24 natural populations in Jordan. Total genomic DNAs were extracted and digested with restriction enzymes PstI and MspI. Three Illumina MiSeq sequencing runs generated 556 paired-end FASTQ files with 127,128,438 raw sequences. Bioinformatics analysis identified an informative matrix of 275 samples × 12,999 SNP markers. Analysis revealed 52.4% of SNP variation residing among 24 populations and eight major genetic clusters of the samples. Most samples were grouped together within their original populations. A significant association of pairwise population genetic distances was found with latitudinal or longitudinal differences. Two natural populations were highly differentiated from the others, and 30 highly distinct A. sterilis samples were identified from seven populations. These findings are useful for understanding genetic variability and conservation of natural A. sterilis populations, and they demonstrate the advances of the GBS application for germplasm characterization of crop wild relatives with complex genomes.

Analysis of genetic relatedness among Indian cattle (Bos indicus) using genotyping-by-sequencing markers.

Genetic relatedness of 24 animals belonging to seven Indian cattle breeds was studied using high throughput genotyping-by-sequencing (GBS) markers. GBS produced 93.6million reads with an average of about 3.9million reads per animal. A total of 107488 SNPs were identified in these individuals. When only one SNP per read was considered, a total of 60261 SNPs representing independent reads were identified with an average SNP-to-SNP distance of 45kb across the bovine reference genome. About 24% of the GBS-SNP markers were more than 100kb apart. Of these, 58322 SNPs mapped to autosomes, 1645 to the X chromosome and 28 to the Y chromosome. The average SNP-to-SNP distance on the X chromosome was 91.3kb, whereas on the Y chromosome it was 1546.4kb. The minor allele frequency within the Indian cattle varied from 0.103 (Ongole) to 0.177 (Siri), whereas Holstein cattle had the lowest value of 0.089. This is the first application of GBS in cattle of South Asia. The baseline information generated in this study might prompt implementation of GBS in breeding of cattle belonging to this region.

Parent-progeny imputation from pooled samples for cost-efficient genotyping in plant breeding.

The increased usage of whole-genome selection (WGS) and other molecular evaluation methods in plant breeding relies on the ability to genotype a very large number of untested individuals in each breeding cycle. Many plant breeding programs evaluate large biparental populations of homozygous individuals derived from homozygous parent inbred lines. This structure lends itself to parent-progeny imputation, which transfers the genotype scores of the parents to progeny individuals that are genotyped for a much smaller number of loci. Here we introduce a parent-progeny imputation method that infers individual genotypes from non-barcoded pooled samples of DNA of multiple individuals using a Hidden Markov Model (HMM). We demonstrate the method for pools of simulated maize double haploids (DH) from biparental populations, genotyped using a genotyping by sequencing (GBS) approach for 3,000 loci at 0.125x to 4x coverage. We observed high concordance between true and imputed marker scores and the HMM produced well-calibrated genotype probabilities that correctly reflected the uncertainty of the imputed scores. Genomic estimated breeding values (GEBV) calculated from the imputed scores closely matched GEBV calculated from the true marker scores. The within-population correlation between these sets of GEBV approached 0.95 at 1x and 4x coverage when pooling two or four individuals, respectively. Our approach can reduce the genotyping cost per individual by a factor up to the number of pooled individuals in GBS applications without the need for extra sequencing coverage, thereby enabling cost-effective large scale genotyping for applications such as WGS in plant breeding.

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.

Whole-genome single-nucleotide polymorphism (SNP) marker discovery and association analysis with the eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) content in Larimichthys crocea.

Whole-genome single-nucleotide polymorphism (SNP) markers are valuable genetic resources for the association and conservation studies. Genome-wide SNP development in many teleost species are still challenging because of the genome complexity and the cost of re-sequencing. Genotyping-By-Sequencing (GBS) provided an efficient reduced representative method to squeeze cost for SNP detection; however, most of recent GBS applications were reported on plant organisms. In this work, we used an EcoRI-NlaIII based GBS protocol to teleost large yellow croaker, an important commercial fish in China and East-Asia, and reported the first whole-genome SNP development for the species. 69,845 high quality SNP markers that evenly distributed along genome were detected in at least 80% of 500 individuals. Nearly 95% randomly selected genotypes were successfully validated by Sequenom MassARRAY assay. The association studies with the muscle eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) content discovered 39 significant SNP markers, contributing as high up to ∼63% genetic variance that explained by all markers. Functional genes that involved in fat digestion and absorption pathway were identified, such as APOB, CRAT and OSBPL10. Notably, PPT2 Gene, previously identified in the association study of the plasma n-3 and n-6 polyunsaturated fatty acid level in human, was re-discovered in large yellow croaker. Our study verified that EcoRI-NlaIII based GBS could produce quality SNP markers in a cost-efficient manner in teleost genome. The developed SNP markers and the EPA and DHA associated SNP loci provided invaluable resources for the population structure, conservation genetics and genomic selection of large yellow croaker and other fish organisms.

SNP discovery and genotyping using Genotyping-by-Sequencing in Pekin ducks.

Genomic selection and genome-wide association studies need thousands to millions of SNPs. However, many non-model species do not have reference chips for detecting variation. Our goal was to develop and validate an inexpensive but effective method for detecting SNP variation. Genotyping by sequencing (GBS) can be a highly efficient strategy for genome-wide SNP detection, as an alternative to microarray chips. Here, we developed a GBS protocol for ducks and tested it to genotype 49 Pekin ducks. A total of 169,209 SNPs were identified from all animals, with a mean of 55,920 SNPs per individual. The average SNP density reached 1156 SNPs/MB. In this study, the first application of GBS to ducks, we demonstrate the power and simplicity of this method. GBS can be used for genetic studies in to provide an effective method for genome-wide SNP discovery.

Toward the elucidation of cytoplasmic diversity in North American grape breeding programs

Plants have an intriguing tripartite genetic system: Nuclear genome × Mitochondria × Plastids and their interactions may impact germplasm breeding. In grapevine, the study of cytoplasmic genomes has been limited, and their role with respect to grapevine germplasm diversity has yet to be elucidated. In the present study, the results of an analysis of the cytoplasmic diversity among 6073 individuals (comprising cultivars, interspecific hybrids and segregating progenies) are presented. Genotyping by sequencing (GBS) was used to elucidate plastid and mitochondrial DNA sequences, and results were analyzed using multivariate techniques. Single nucleotide polymorphism (SNP) effects were annotated in reference to plastid and mitochondrial genome sequences. The cytoplasmic diversity identified was structured according to synthetic domestication groups (wine and raisin/table grape types) and interspecific-hybridization-driven groups with introgression from North American Vitis species, identifying five cytoplasmic groups and four major clusters. Fifty-two SNP markers were used to describe the diversity of the germplasm. Ten organelle genes showed distinct SNP annotations and effect predictions, of which six were chloroplast-derived and three were mitochondrial genes, in addition to one mitochondrial SNP affecting a nonannotated open reading frame. The results suggest that the application of GBS will aid in the study of cytoplasmic genomes in grapevine, which will enable further studies on the role of cytoplasmic genomes in grapevine germplasm, and then allow the exploitation of these sources of diversity in breeding.

Genome-wide identification of SNPs and copy number variation in common bean (Phaseolus vulgaris L.) using genotyping-by-sequencing (GBS)

Next-generation sequencing technologies have increased markedly the throughput of genetic studies, allowing the identification of several thousands of SNPs within a single experiment. Even though sequencing cost is rapidly decreasing, the price for whole-genome re-sequencing of a large number of individuals is still costly, especially in plants with a large and highly redundant genome. In recent years, several reduced representation library approaches have been developed for reducing the sequencing cost per individual. Among them, genotyping-by-sequencing (GBS) represents a simple, cost-effective, and highly multiplexed alternative for species with or without an available reference genome. However, this technology requires specific optimization for each species, especially for the restriction enzyme (RE) used. Here we report on the application of GBS in a test experiment with 18 genotypes of wild and domesticated Phaseolus vulgaris. After an in silico digestion with different RE of the P. vulgaris genome reference sequence, we selected CviAII as the most suitable RE for GBS in common bean based on the high frequency and even distribution of restriction sites. A total of 44,875 SNPs, 1940 deletions, and 1693 insertions were identified, with 50 % of the variants located in genic sequences and tagging 11,027 genes. SNP and InDel distributions were positively correlated with gene density across the genome. In addition, we were able to also identify putative copy number variations of genomic segments between different genotypes. In conclusion, GBS with the CviAII enzyme results in thousands of evenly spaced markers and provides a reliable, high-throughput, and cost-effective approach for genotyping both wild and domesticated common beans.

Genotyping-By-Sequencing for Plant Genetic Diversity Analysis: A Lab Guide for SNP Genotyping

Genotyping-by-sequencing (GBS) has recently emerged as a promising genomic approach for exploring plant genetic diversity on a genome-wide scale. However, many uncertainties and challenges remain in the application of GBS, particularly in non-model species. Here, we present a GBS protocol we developed and use for plant genetic diversity analysis. It uses two restriction enzymes to reduce genome complexity, applies Illumina multiplexing indexes for barcoding and has a custom bioinformatics pipeline for genotyping. This genetic diversity-focused GBS (gd-GBS) protocol can serve as an easy-to-follow lab guide to assist a researcher through every step of a GBS application with five main components: sample preparation, library assembly, sequencing, SNP calling and diversity analysis. Specifically, in this presentation, we provide a brief overview of the GBS approach, describe the gd-GBS procedures, illustrate it with an application to analyze genetic diversity in 20 flax (Linum usitatissimum L.) accessions and discuss related issues in GBS application. Following these lab bench procedures and using the custom bioinformatics pipeline, one could generate genome-wide SNP genotype data for a conventional genetic diversity analysis of a non-model plant species.

Mining conifers’ mega-genome using rapid and efficient multiplexed high-throughput genotyping-by-sequencing (GBS) SNP discovery platform

Next-generation sequencing (NGS) technologies are revolutionizing both medical and biological research through generation of massive SNP data sets for identifying heritable genome variation underlying key traits, from rare human diseases to important agronomic phenotypes in crop species. We evaluated the performance of genotyping-by-sequencing (GBS), one of the emerging NGS-based platforms, for genotyping two economically important conifer species, lodgepole pine (Pinus contorta) and white spruce (Picea glauca). Both species have very large genomes (>20,000 Mbp), are highly heterozygous, and lack reference sequences. From a small set (six accessions each) of independent replicated DNA samples and a 48-plex read depth, we obtained ~60,000 SNPs per species. After stringent filtering, we obtained 17,765 and 17,845 high-coverage SNPs without missing data for lodgepole pine and white spruce, respectively. Our results demonstrated that GBS is a robust and suitable method for genotyping conifers. The application of GBS to forest tree breeding and genomic selection is discussed.

A Robust, Simple Genotyping-by-Sequencing (GBS) Approach for High Diversity Species

Advances in next generation technologies have driven the costs of DNA sequencing down to the point that genotyping-by-sequencing (GBS) is now feasible for high diversity, large genome species. Here, we report a procedure for constructing GBS libraries based on reducing genome complexity with restriction enzymes (REs). This approach is simple, quick, extremely specific, highly reproducible, and may reach important regions of the genome that are inaccessible to sequence capture approaches. By using methylation-sensitive REs, repetitive regions of genomes can be avoided and lower copy regions targeted with two to three fold higher efficiency. This tremendously simplifies computationally challenging alignment problems in species with high levels of genetic diversity. The GBS procedure is demonstrated with maize (IBM) and barley (Oregon Wolfe Barley) recombinant inbred populations where roughly 200,000 and 25,000 sequence tags were mapped, respectively. An advantage in species like barley that lack a complete genome sequence is that a reference map need only be developed around the restriction sites, and this can be done in the process of sample genotyping. In such cases, the consensus of the read clusters across the sequence tagged sites becomes the reference. Alternatively, for kinship analyses in the absence of a reference genome, the sequence tags can simply be treated as dominant markers. Future application of GBS to breeding, conservation, and global species and population surveys may allow plant breeders to conduct genomic selection on a novel germplasm or species without first having to develop any prior molecular tools, or conservation biologists to determine population structure without prior knowledge of the genome or diversity in the species.