Rapid gene-based SNP and haplotype marker development in non-model eukaryotes using 3'UTR sequencing

Fruit Development in Sweet Cherry

Fruits are an important source of vitamins, minerals and nutrients in the human diet. They also contain several compounds of nutraceutical importance that have significant antioxidant and anti-inflammatory roles, which can protect the consumer from diseases, such as cancer, and cardiovascular disease as well as having roles in reducing the build-up of LDL-cholesterol in blood plasma and generally reduce the risks of disease and age-related decline in health. Cherries contain high concentrations of bioactive compounds and minerals, including calcium, phosphorous, potassium and magnesium, and it is, therefore, unsurprising that cherry consumption has a positive impact on health. This review highlights the development of sweet cherry fruit, the health benefits of cherry consumption, and the options for increasing consumer acceptance and consumption.

Transcriptome characterization and screening of molecular markers in ecologically important Himalayan species (Rhododendron arboreum)

Rhododendron arboreum is an ecologically prominent species, which also lends commercial and medicinal benefits in the form of palatable juices and useful herbal drugs. Local abundance and survival of the species under a highly fluctuating climate make it an ideal model for genetic structure and functional analysis. However, a lack of genomic data has hampered additional research. In the present study, cDNA libraries from floral and foliar tissues of the species were sequenced to provide a foundation for understanding the functional aspects of the genome and to construct an enriched repository that will promote genomics studies in the genera. Illumina’s platform facilitated the generation of ∼100 million high-quality paired-end reads. De novo assembly, clustering, and filtering out of shorter transcripts predicted 113 167 non-redundant transcripts with an average length of 1164.6 bases. Of these, 71 961 transcripts were categorized based on functional annotations in the Gene Ontology database, whereby 5710 were grouped into 141 pathways and 23 746 encoded for different transcription factors. Transcriptome screening further identified 35 419 microsatellite regions, of which, 43 polymorphic loci were characterized on 30 genotypes. Seven hundred and nineteen transcripts had 811 high-quality single-nucleotide polymorphic variants with a minimum coverage of 10, a total score of 20, and SNP% of 50.

Comparison of traditional and new generation DNA markers declares high genetic diversity and differentiated population structure of wild almond species

Wild almond species as sources of genetic variation may have crucial importance in breeding. A total of 389 accessions of 18 species have been analysed using inter-retrotransposon amplified polymorphism (IRAP), retrotransposon-microsatellite amplified polymorphism (REMAP), sequence-specific amplification polymorphism (S-SAP), amplified fragment length polymorphism (AFLP), inter simple sequence repeat (ISSR) and simple sequence repeats (SSR). Retrotransposon markers indicated the presence and movement of some Ty3-gypsy and Ty1-copia-elements in almond genome. Since transposable elements are associated with large-scale genome alterations, REMAP produced more reliable phylogenetic inferences than AFLP where homoplasy may affect clustering. In addition, high resolution melting (HRM) analysis was developed to detect SNPs. HRM analysis revealed 1:189 bp frequency of SNPs in exon positions, and the transition-to-transversion proportion was 1.84:1. The low transition bias suggests low methylation levels in almond genome. The polymorphic information content (PIC) was the highest for SSR markers, while SNPs had an average PIC of 0.59, which is close to the values of the rest of the markers. Huge genetic diversity, fragmented population structure and footprints of human selection was confirmed by merging information from all marker strategies. Considering time, cost and performance HRM can be a marker of choice in future studies of Prunus diversity.

Genomic and functional characterization of coleopteran insect-specific α-amylase inhibitor gene from Amaranthus species

The smallest 32 amino acid α-amylase inhibitor from Amaranthus hypochondriacus (AAI) is reported. The complete gene of pre-protein (AhAI) encoding a 26 amino acid (aa) signal peptide followed by the 43 aa region and the previously identified 32 aa peptide was cloned successfully. Three cysteine residues and one disulfide bond conserved within known α-amylase inhibitors were present in AhAI. Identical genomic and open reading frame was found to be present in close relatives of A. hypochondriacus namely Amaranthus paniculatus, Achyranthes aspera and Celosia argentea. Interestingly, the 3'UTR of AhAI varied in these species. The highest expression of AhAI was observed in A. hypochondriacus inflorescence; however, it was not detected in the seed. We hypothesized that the inhibitor expressed in leaves and inflorescence might be transported to the seeds. Sub-cellular localization studies clearly indicated the involvement of AhAI signal peptide in extracellular secretion. Full length rAhAI showed differential inhibition against α-amylases from human, insects, fungi and bacteria. Particularly, α-amylases from Helicoverpa armigera (Lepidoptera) were not inhibited by AhAI while Tribolium castaneum and Callosobruchus chinensis (Coleoptera) α-amylases were completely inhibited. Molecular docking of AhAI revealed tighter interactions with active site residues of T. castaneum α-amylase compared to C. chinensis α-amylase, which could be the rationale behind the disparity in their IC₅₀. Normal growth, development and adult emergence of C. chinensis were hampered after feeding on rAhAI. Altogether, the ability of AhAI to affect the growth of C. chinensis demonstrated its potential as an efficient bio-control agent, especially against stored grain pests.

Evaluation of multiple approaches to identify genome-wide polymorphisms in closely related genotypes of sweet cherry (Prunus avium L.)

Identification of genetic polymorphisms and subsequent development of molecular markers is important for marker assisted breeding of superior cultivars of economically important species. Sweet cherry (Prunus avium L.) is an economically important non-climacteric tree fruit crop in the Rosaceae family and has undergone a genetic bottleneck due to breeding, resulting in limited genetic diversity in the germplasm that is utilized for breeding new cultivars. Therefore, it is critical to recognize the best platforms for identifying genome-wide polymorphisms that can help identify, and consequently preserve, the diversity in a genetically constrained species. For the identification of polymorphisms in five closely related genotypes of sweet cherry, a gel-based approach (TRAP), reduced representation sequencing (TRAPseq), a 6k cherry SNParray, and whole genome sequencing (WGS) approaches were evaluated in the identification of genome-wide polymorphisms in sweet cherry cultivars. All platforms facilitated detection of polymorphisms among the genotypes with variable efficiency. In assessing multiple SNP detection platforms, this study has demonstrated that a combination of appropriate approaches is necessary for efficient polymorphism identification, especially between closely related cultivars of a species. The information generated in this study provides a valuable resource for future genetic and genomic studies in sweet cherry, and the insights gained from the evaluation of multiple approaches can be utilized for other closely related species with limited genetic diversity in the breeding germplasm.

CisSERS: Customizable In Silico Sequence Evaluation for Restriction Sites

High-throughput sequencing continues to produce an immense volume of information that is processed and assembled into mature sequence data. Data analysis tools are urgently needed that leverage the embedded DNA sequence polymorphisms and consequent changes to restriction sites or sequence motifs in a high-throughput manner to enable biological experimentation. CisSERS was developed as a standalone open source tool to analyze sequence datasets and provide biologists with individual or comparative genome organization information in terms of presence and frequency of patterns or motifs such as restriction enzymes. Predicted agarose gel visualization of the custom analyses results was also integrated to enhance the usefulness of the software. CisSERS offers several novel functionalities, such as handling of large and multiple datasets in parallel, multiple restriction enzyme site detection and custom motif detection features, which are seamlessly integrated with real time agarose gel visualization. Using a simple fasta-formatted file as input, CisSERS utilizes the REBASE enzyme database. Results from CisSERS enable the user to make decisions for designing genotyping by sequencing experiments, reduced representation sequencing, 3’UTR sequencing, and cleaved amplified polymorphic sequence (CAPS) molecular markers for large sample sets. CisSERS is a java based graphical user interface built around a perl backbone. Several of the applications of CisSERS including CAPS molecular marker development were successfully validated using wet-lab experimentation. Here, we present the tool CisSERS and results from in-silico and corresponding wet-lab analyses demonstrating that CisSERS is a technology platform solution that facilitates efficient data utilization in genomics and genetics studies.

Construction of High Density Sweet Cherry (Prunus avium L.) Linkage Maps Using Microsatellite Markers and SNPs Detected by Genotyping-by-Sequencing (GBS)

Linkage maps are valuable tools in genetic and genomic studies. For sweet cherry, linkage maps have been constructed using mainly microsatellite markers (SSRs) and, recently, using single nucleotide polymorphism markers (SNPs) from a cherry 6K SNP array. Genotyping-by-sequencing (GBS), a new methodology based on high-throughput sequencing, holds great promise for identification of high number of SNPs and construction of high density linkage maps. In this study, GBS was used to identify SNPs from an intra-specific sweet cherry cross. A total of 8,476 high quality SNPs were selected for mapping. The physical position for each SNP was determined using the peach genome, Peach v1.0, as reference, and a homogeneous distribution of markers along the eight peach scaffolds was obtained. On average, 65.6% of the SNPs were present in genic regions and 49.8% were located in exonic regions. In addition to the SNPs, a group of SSRs was also used for construction of linkage maps. Parental and consensus high density maps were constructed by genotyping 166 siblings from a ‘Rainier’ x ‘Rivedel’ (Ra x Ri) cross. Using Ra x Ri population, 462, 489 and 985 markers were mapped into eight linkage groups in ‘Rainier’, ‘Rivedel’ and the Ra x Ri map, respectively, with 80% of mapped SNPs located in genic regions. Obtained maps spanned 549.5, 582.6 and 731.3 cM for ‘Rainier’, ‘Rivedel’ and consensus maps, respectively, with an average distance of 1.2 cM between adjacent markers for both ‘Rainier’ and ‘Rivedel’ maps and of 0.7 cM for Ra x Ri map. High synteny and co-linearity was observed between obtained maps and with Peach v1.0. These new high density linkage maps provide valuable information on the sweet cherry genome, and serve as the basis for identification of QTLs and genes relevant for the breeding of the species.

Analysis of gene expression changes in peach leaves in response to Plum pox virus infection using RNA-Seq

Differences in gene expression were studied after Plum pox virus (PPV, sharka disease) infection in peach GF305 leaves with and without sharka symptoms using RNA-Seq. For each sample, more than 80% of 100-nucleotide paired-end (PE) Illumina reads were aligned on the peach reference genome. In the symptomatic sample, a significant proportion of reads were mapped to PPV reference genomes (1.04% compared with 0.00002% in non-symptomatic leaves), allowing for the ultra-deep assembly of the complete genome of the PPV isolate used (9775 nucleotides, missing only 11 nucleotides at the 5' genome end). In addition, significant alternative splicing events were detected in 359 genes and 12 990 single nucleotide polymorphisms (SNPs) were identified, 425 of which could be annotated. Gene ontology annotation revealed that the high-ranking mRNA target genes associated with the expression of sharka symptoms are mainly related to the response to biotic stimuli, to lipid and carbohydrate metabolism and to the negative regulation of catalytic activity. A greater number of differentially expressed genes were observed in the early asymptomatic phase of PPV infection in comparison with the symptomatic phase. These early infection events were associated with the induction of genes related to pathogen resistance, such as jasmonic acid, chitinases, cytokinin glucosyl transferases and Lys-M proteins. Once the virus had accumulated, the overexpression of Dicer protein 2a genes suggested a gene silencing plant response that was suppressed by the virus HCPro and P1 proteins. These results illustrate the dynamic nature of the peach-PPV interaction at the transcriptome level and confirm that sharka symptom expression is a complex process that can be understood on the basis of changes in plant gene expression.

Single-nucleotide polymorphism identification and genotyping in Camelina sativa

Camelina sativa, a largely relict crop, has recently returned to interest due to its potential as an industrial oilseed. Molecular markers are key tools that will allow C. sativa to benefit from modern breeding approaches. Two complementary methodologies, capture of 3' cDNA tags and genomic reduced-representation libraries, both of which exploited second generation sequencing platforms, were used to develop a low density (768) Illumina GoldenGate single nucleotide polymorphism (SNP) array. The array allowed 533 SNP loci to be genetically mapped in a recombinant inbred population of C. sativa. Alignment of the SNP loci to the C. sativa genome identified the underlying sequenced regions that would delimit potential candidate genes in any mapping project. In addition, the SNP array was used to assess genetic variation among a collection of 175 accessions of C. sativa, identifying two sub-populations, yet low overall gene diversity. The SNP loci will provide useful tools for future crop improvement of C. sativa.

De novo transcriptome assembly and the identification of gene-associated single-nucleotide polymorphism markers in Asian and American ginseng roots

We performed de novo transcriptome sequencing for Panax ginseng and Panax quinquefolius accessions using the 454 GS FLX Titanium System and discovered annotation-based genome-wide single-nucleotide polymorphism (SNPs) using next-generation ginseng transcriptome data without reference genome sequence. The comprehensive transcriptome characterization with the mature roots of four ginseng accessions generated 297,170 reads for 'Cheonryang' cultivar, 305,673 reads for 'Yunpoong' cultivar, 311,861 reads for the G03080 breeding line, and 308,313 reads for P. quinquefolius. In transcriptome assembly, the lengths of the sample read were 156.42 Mb for 'Cheonryang', 161.95 Mb for 'Yunpoong', 165.07 Mb for G03080 breeding line, and 166.48 Mb for P. quinquefolius. A total of 97 primer pairs were designed with the homozygous SNP presented in all four accessions. SNP genotyping using high-resolution melting (HRM) analysis was performed to validate the putative SNP markers of 97 primer pairs. Out of the 73 primer pairs, 73 primer pairs amplified the target sequence and 34 primer pairs showed polymorphic melting curves in samples from 11 P. ginseng cultivars and one P. quinquefolius accession. Among the 34 polymorphic HRM-SNP primers, four primers were useful to distinguish ginseng cultivars. In the present study, we demonstrated that de novo transcriptome assembly and mapping analyses are useful in providing four HRM-SNP primer pairs that reliably show a high degree of polymorphism among ginseng cultivars.

Development of EST-based SNP and InDel markers and their utilization in tetraploid cotton genetic mapping

Background

Availability of molecular markers has proven to be an efficient tool in facilitating progress in plant breeding, which is particularly important in the case of less researched crops such as cotton. Considering the obvious advantages of single nucleotide polymorphisms (SNPs) and insertion-deletion polymorphisms (InDels), expressed sequence tags (ESTs) were analyzed in silico to identify SNPs and InDels in this study, aiming to develop more molecular markers in cotton.

Results

A total of 1,349 EST-based SNP and InDel markers were developed by comparing ESTs between Gossypium hirsutum and G. barbadense, mining G. hirsutum unigenes, and analyzing 3′ untranslated region (3′UTR) sequences. The marker polymorphisms were investigated using the two parents of the mapping population based on the single-strand conformation polymorphism (SSCP) analysis. Of all the markers, 137 (10.16%) were polymorphic, and revealed 142 loci. Linkage analysis using a BC₁ population mapped 133 loci on the 26 chromosomes. Statistical analysis of base variations in SNPs showed that base transitions accounted for 55.78% of the total base variations and gene ontology indicated that cotton genes varied greatly in harboring SNPs ranging from 1.00 to 24.00 SNPs per gene. Sanger sequencing of three randomly selected SNP markers revealed discrepancy between the in silico predicted sequences and the actual sequencing results.

Conclusions

In silico analysis is a double-edged blade to develop EST-SNP/InDel markers. On the one hand, the designed markers can be well used in tetraploid cotton genetic mapping. And it plays a certain role in revealing transition preference and SNP frequency of cotton genes. On the other hand, the developmental efficiency of markers and polymorphism of designed primers are comparatively low.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1046) contains supplementary material, which is available to authorized users.

Transcriptomic evaluation of the nicotinic acetylcholine receptor pathway in levamisole-resistant and -sensitive Oesophagostomum dentatum

Nematode anthelminthic resistance is widespread for the 3 major drug classes commonly used in agriculture: benzamidazoles, macrocyclic lactones, and nicotinic agonists e.g. levamisole. In parasitic nematodes the genetics of resistance is unknown other than to the benzimidazoles which primarily involve a single gene. In previous work with a levamisole resistant Oesophagostomum dentatum isolate, the nicotinic acetylcholine receptor (nAChR) exhibited decreased levamisole sensitivity. Here, using a transcriptomic approach on the same isolate, we investigate whether that decreased nAChR sensitivity is achieved via a 1-gene mechanism involving 1 of 27 nAChR pathway genes. 3 nAChR receptor subunit genes exhibited ≥2-fold change in transcript abundance: acr-21 and acr-25 increased, and unc-63 decreased. 4 SNPs having a ≥2-fold change in frequency were also identified. These data suggest that resistance is likely polygenic, involving modulated abundance of multiple subunits comprising the heteropentameric nAChR, and is not due to a simple 1-gene mechanism.

Molecular genetics and genomics of the Rosoideae: state of the art and future perspectives

The Rosoideae is a subfamily of the Rosaceae that contains a number of species of economic importance, including the soft fruit species strawberry (Fragaria ×ananassa), red (Rubus idaeus) and black (Rubus occidentalis) raspberries, blackberries (Rubus spp.) and one of the most economically important cut flower genera, the roses (Rosa spp.). Molecular genetics and genomics resources for the Rosoideae have developed rapidly over the past two decades, beginning with the development and application of a number of molecular marker types including restriction fragment length polymorphisms, amplified fragment length polymorphisms and microsatellites, and culminating in the recent publication of the genome sequence of the woodland strawberry, Fragaria vesca, and the development of high throughput single nucleotide polymorphism (SNP)-genotyping resources for Fragaria, Rosa and Rubus. These tools have been used to identify genes and other functional elements that control traits of economic importance, to study the evolution of plant genome structure within the subfamily, and are beginning to facilitate genomic-assisted breeding through the development and deployment of markers linked to traits such as aspects of fruit quality, disease resistance and the timing of flowering. In this review, we report on the developments that have been made over the last 20 years in the field of molecular genetics and structural genomics within the Rosoideae, comment on how the knowledge gained will improve the efficiency of cultivar development and discuss how these advances will enhance our understanding of the biological processes determining agronomically important traits in all Rosoideae species.

Comparative genomics analysis in Prunoideae to identify biologically relevant polymorphisms

Prunus is an economically important genus with a wide range of physiological and biological variability. Using the peach genome as a reference, sequencing reads from four almond accessions and one sweet cherry cultivar were used for comparative analysis of these three Prunus species. Reference mapping enabled the identification of many biological relevant polymorphisms within the individuals. Examining the depth of the polymorphisms and the overall scaffold coverage, we identified many potentially interesting regions including hundreds of small scaffolds with no coverage from any individual. Non-sense mutations account for about 70 000 of the 13 million identified single nucleotide polymorphisms (SNPs). Blast2GO analyses on these non-sense SNPs revealed several interesting results. First, non-sense SNPs were not evenly distributed across all gene ontology terms. Specifically, in comparison with peach, sweet cherry is found to have non-sense SNPs in two 1-aminocyclopropane-1-carboxylate synthase (ACS) genes and two 1-aminocyclopropane-1-carboxylate oxidase (ACO) genes. These polymorphisms may be at the root of the nonclimacteric ripening of sweet cherry. A set of candidate genes associated with bitterness in almond were identified by comparing sweet and bitter almond sequences. To the best of our knowledge, this is the first report in plants of non-sense SNP abundance in a genus being linked to specific GO terms.

Transcriptome deep-sequencing and clustering of expressed isoforms from Favia corals

BACKGROUND

Genomic and transcriptomic sequence data are essential tools for tackling ecological problems. Using an approach that combines next-generation sequencing, de novo transcriptome assembly, gene annotation and synthetic gene construction, we identify and cluster the protein families from Favia corals from the northern Red Sea.

RESULTS

We obtained 80 million 75 bp paired-end cDNA reads from two Favia adult samples collected at 65 m (Fav1, Fav2) on the Illumina GA platform, and generated two de novo assemblies using ABySS and CAP3. After removing redundancy and filtering out low quality reads, our transcriptome datasets contained 58,268 (Fav1) and 62,469 (Fav2) contigs longer than 100 bp, with N50 values of 1,665 bp and 1,439 bp, respectively. Using the proteome of the sea anemone Nematostella vectensis as a reference, we were able to annotate almost 20% of each dataset using reciprocal homology searches. Homologous clustering of these annotated transcripts allowed us to divide them into 7,186 (Fav1) and 6,862 (Fav2) homologous transcript clusters (E-value ≤ 2e(-30)). Functional annotation categories were assigned to homologous clusters using the functional annotation of Nematostella vectensis. General annotation of the assembled transcripts was improved 1-3% using the Acropora digitifera proteome. In addition, we screened these transcript isoform clusters for fluorescent proteins (FPs) homologs and identified seven potential FP homologs in Fav1, and four in Fav2. These transcripts were validated as bona fide FP transcripts via robust fluorescence heterologous expression. Annotation of the assembled contigs revealed that 1.34% and 1.61% (in Fav1 and Fav2, respectively) of the total assembled contigs likely originated from the corals' algal symbiont, Symbiodinium spp.

CONCLUSIONS

Here we present a study to identify the homologous transcript isoform clusters from the transcriptome of Favia corals using a far-related reference proteome. Furthermore, the symbiont-derived transcripts were isolated from the datasets and their contribution quantified. This is the first annotated transcriptome of the genus Favia, a major increase in genomics resources available in this important family of corals.

A toolkit for bulk PCR-based marker design from next-generation sequence data: application for development of a framework linkage map in bulb onion (Allium cepa L.)

Background

Although modern sequencing technologies permit the ready detection of numerous DNA sequence variants in any organisms, converting such information to PCR-based genetic markers is hampered by a lack of simple, scalable tools. Onion is an example of an under-researched crop with a complex, heterozygous genome where genome-based research has previously been hindered by limited sequence resources and genetic markers.

Results

We report the development of generic tools for large-scale web-based PCR-based marker design in the Galaxy bioinformatics framework, and their application for development of next-generation genetics resources in a wide cross of bulb onion (Allium cepa L.). Transcriptome sequence resources were developed for the homozygous doubled-haploid bulb onion line ‘CUDH2150’ and the genetically distant Indian landrace ‘Nasik Red’, using 454™ sequencing of normalised cDNA libraries of leaf and shoot. Read mapping of ‘Nasik Red’ reads onto ‘CUDH2150’ assemblies revealed 16836 indel and SNP polymorphisms that were mined for portable PCR-based marker development. Tools for detection of restriction polymorphisms and primer set design were developed in BioPython and adapted for use in the Galaxy workflow environment, enabling large-scale and targeted assay design. Using PCR-based markers designed with these tools, a framework genetic linkage map of over 800cM spanning all chromosomes was developed in a subset of 93 F₂ progeny from a very large F₂ family developed from the ‘Nasik Red’ x ‘CUDH2150’ inter-cross. The utility of tools and genetic resources developed was tested by designing markers to transcription factor-like polymorphic sequences. Bin mapping these markers using a subset of 10 progeny confirmed the ability to place markers within 10 cM bins, enabling increased efficiency in marker assignment and targeted map refinement. The major genetic loci conditioning red bulb colour (R) and fructan content (Frc) were located on this map by QTL analysis.

Conclusions

The generic tools developed for the Galaxy environment enable rapid development of sets of PCR assays targeting sequence variants identified from Illumina and 454 sequence data. They enable non-specialist users to validate and exploit large volumes of next-generation sequence data using basic equipment.

Genetic diversity and relatedness of sweet cherry (prunus avium L.) cultivars based on single nucleotide polymorphic markers

Most previous studies on genetic fingerprinting and cultivar relatedness in sweet cherry were based on isoenzyme, RAPD, and simple sequence repeat (SSR) markers. This study was carried out to assess the utility of single nucleotide polymorphism (SNP) markers generated from 3' untranslated regions (UTR) for genetic fingerprinting in sweet cherry. A total of 114 sweet cherry germplasm representing advanced selections, commercial cultivars, and old cultivars imported from different parts of the world were screened with seven SSR markers developed from other Prunus species and with 40 SNPs obtained from 3' UTR sequences of Rainier and Bing sweet cherry cultivars. Both types of marker study had 99 accessions in common. The SSR data was used to validate the SNP results. Results showed that the average number of alleles per locus, mean observed heterozygosity, expected heterozygosity, and polymorphic information content values were higher in SSRs than in SNPs although both set of markers were similar in their grouping of the sweet cherry accessions as shown in the dendrogram. SNPs were able to distinguish sport mutants from their wild type germplasm. For example, "Stella" was separated from "Compact Stella." This demonstrates the greater power of SNPs for discriminating mutants from their original parents than SSRs. In addition, SNP markers confirmed parentage and also determined relationships of the accessions in a manner consistent with their pedigree relationships. We would recommend the use of 3' UTR SNPs for genetic fingerprinting, parentage verification, gene mapping, and study of genetic diversity in sweet cherry.

SNP Discovery through Next-Generation Sequencing and Its Applications

The decreasing cost along with rapid progress in next-generation sequencing and related bioinformatics computing resources has facilitated large-scale discovery of SNPs in various model and nonmodel plant species. Large numbers and genome-wide availability of SNPs make them the marker of choice in partially or completely sequenced genomes. Although excellent reviews have been published on next-generation sequencing, its associated bioinformatics challenges, and the applications of SNPs in genetic studies, a comprehensive review connecting these three intertwined research areas is needed. This paper touches upon various aspects of SNP discovery, highlighting key points in availability and selection of appropriate sequencing platforms, bioinformatics pipelines, SNP filtering criteria, and applications of SNPs in genetic analyses. The use of next-generation sequencing methodologies in many non-model crops leading to discovery and implementation of SNPs in various genetic studies is discussed. Development and improvement of bioinformatics software that are open source and freely available have accelerated the SNP discovery while reducing the associated cost. Key considerations for SNP filtering and associated pipelines are discussed in specific topics. A list of commonly used software and their sources is compiled for easy access and reference.