Mining for SNPs and SSRs using SNPServer, dbSNP and SSR taxonomy tree

High density SNP mapping and QTL analysis for time of leaf budburst in Corylus avellana L

The growing area of European hazelnut (Corylus avellana L.) is increasing, as well as the number of producing countries, and there is a pressing need for new improved cultivars. Hazelnut conventional breeding process is slow, due to the length of juvenile phase and the high heterozygosity level. The development of genetic linkage maps and the identification of molecular markers tightly linked to QTL (quantitative trait loci) of agronomic interest are essential tools for speeding up the selection of seedlings carrying desired traits through marker-assisted selection. The objectives of this study were to enrich a previous linkage map and confirm QTL related to time of leaf budburst, using an F₁ population obtained by crossing Tonda Gentile delle Langhe with Merveille de Bollwiller. Genotyping-by-Sequencing was used to identify a total of 9,999 single nucleotide polymorphism markers. Well saturated linkage maps were constructed for each parent using the double pseudo-testcross mapping strategy. A reciprocal translocation was detected in Tonda Gentile delle Langhe between two non-homologous chromosomes. Applying a bioinformatic approach, we were able to disentangle ‘pseudo-linkage’ between markers, removing markers around the translocation breakpoints and obtain a linear order of the markers for the two chromosomes arms, for each linkage group involved in the translocation. Twenty-nine QTL for time of leaf budburst were identified, including a stably expressed region on LG_02 of the Tonda Gentile delle Langhe map. The stability of these QTL and their coding sequence content indicates promise for the identification of specific chromosomal regions carrying key genes involved in leaf budburst.

Skim-based genotyping by sequencing

Genotyping by sequencing (GBS) is a relatively new method used to determine the differences in the genetic makeup of individuals. Its novelty stems from a combination of two already available methods: genotyping and next-generation sequencing. Depending on the individual study design GBS protocols can take multiple forms, however most share a sequence of core steps that have to be undertaken. These include: sequencing of the DNA from the individuals of interest (usually two parents of a mapping population and their progeny), mapping of the sequencing reads to the reference sequence, SNP calling and filtering, SNP genotyping and imputation, followed by haplotype identification and downstream analysis. GBS has a range of applications from general marker discovery, haplotype identification, and recombination characterization to quantitative trait locus (QTL) analysis, genome-wide association studies (GWAS), and genomic selection (GS). It has already been applied to a range of plant species including: rice, maize, artichoke, and Arabidopsis thaliana. It is a promising approach which is likely to provide new and important insights into plant biology.

Bioinformatics: identification of markers from next-generation sequence data

With the advent of sequencing technology, next-generation sequencing (NGS) technology has dramatically revolutionized plant genomics. NGS technology combined with new software tools enables the discovery, validation, and assessment of genetic markers on a large scale. Among different markers systems, simple sequence repeats (SSRs) and Single nucleotide polymorphisms (SNPs) are the markers of choice for genetics and plant breeding. SSR markers have been a choice for large-scale characterization of germplasm collections, construction of genetic maps, and QTL identification. Similarly, SNPs are the most abundant genetic variations with higher frequencies throughout the genome of plant species. This chapter discusses various tools available for genome assembly and widely focuses on SSR and SNP marker discovery.

Molecular marker databases

The detection and analysis of genetic variation plays an important role in plant breeding and this role is increasing with the continued development of genome sequencing technologies. Molecular genetic markers are important tools to characterize genetic variation and assist with genomic breeding. Processing and storing the growing abundance of molecular marker data being produced requires the development of specific bioinformatics tools and advanced databases. Molecular marker databases range from species specific through to organism wide and often host a variety of additional related genetic, genomic, or phenotypic information. In this chapter, we will present some of the features of plant molecular genetic marker databases, highlight the various types of marker resources, and predict the potential future direction of crop marker databases.

New technologies for ultrahigh-throughput genotyping in plant taxonomy

Molecular genetic markers represent one of the most powerful tools for the analysis of variation between plant genomes. Molecular marker technology has developed rapidly over the last decade, with the introduction of new DNA sequencing methods and the development of high-throughput genotyping methods. Single nucleotide polymorphisms (SNPs) now dominate applications in modern plant genetic analysis. The reducing cost of DNA sequencing and increasing availability of large sequence data sets permit the mining of this data for large numbers of SNPs. These may then be used in applications such as genetic linkage analysis and trait mapping, diversity analysis, association studies, and marker-assisted selection. Here we describe automated methods for the discovery of SNP molecular markers and new technologies for high-throughput, low-cost molecular marker genotyping. Examples include SNP discovery using autoSNPdb and wheatgenome.info as well as SNP genotyping using Illumina's GoldenGate™ and Infinium™ methods.

Association genetics of chilling injury susceptibility in peach (Prunus persica (L.) Batsch) across multiple years

Peach and nectarine (Prunus persica L.) are highly perishable; they ripen and deteriorate quickly at ambient temperature. Storage at low temperature (0–5 °C) is a common strategy used to slow the ripening processes and to extend shelf life. However, if susceptible varieties are held too long at a low temperature, they will not ripen properly and will develop chilling injury (CI) symptoms like mealiness (M), flesh browning (FB), and flesh bleeding (FBL). Understanding the genetic control of these traits to produce CI resistant cultivars will greatly benefit producers, shippers and consumers. In this study, we evaluated a population of 51 individuals from Pop-DG across 4 years with CI traits observed in one or two time points to detect molecular marker association with selected 960 single-nucleotide polymorphisms (SNPs) from 1,536 SNPs chip. Genotypic and phenotypic data were analyzed by general linear model and mixed linear model to see comparative results from both analyses. Among 960 SNPs used, 22 SNPs were found associated with CI susceptibility traits like M, FB, and FBL. Many SNP markers were located in or close to previously reported quantitative trait loci mapped by linkage analysis.

An experimental verification of the predicted effects of promoter TATA-box polymorphisms associated with human diseases on interactions between the TATA boxes and TATA-binding protein

Human genome sequencing has resulted in a great body of data, including a stunningly large number of single nucleotide polymorphisms (SNPs) with unknown phenotypic manifestations. Identification and comprehensive analysis of regulatory SNPs in human gene promoters will help quantify the effects of these SNPs on human health. Based on our experimental and computer-aided study of SNPs in TATA boxes and the use of literature data, we have derived an equation for TBP/TATA equilibrium binding in three successive steps: TATA-binding protein (TBP) sliding along DNA due to their nonspecific affinity for each other ↔ recognition of the TATA box ↔ stabilization of the TBP/TATA complex. Using this equation, we have analyzed TATA boxes containing SNPs associated with human diseases and made in silico predictions of changes in TBP/TATA affinity. An electrophoretic mobility shift assay (EMSA)-based experimental study performed under the most standardized conditions demonstrates that the experimentally measured values are highly correlated with the predicted values: the coefficient of linear correlation, r, was 0.822 at a significance level of α<10⁻⁷ for equilibrium K(D) values, (-ln K(D)), and 0.785 at a significance level of α<10⁻³ for changes in equilibrium K(D) (δ) due to SNPs in the TATA boxes (δ= -ln[K(D,TATAMut)]-(-ln[K(D,TATAMut)])). It has been demonstrated that the SNPs associated with increased risk of human diseases such as α-, β- and δ-thalassemia, myocardial infarction and thrombophlebitis, changes in immune response, amyotrophic lateral sclerosis, lung cancer and hemophilia B Leyden cause 2-4-fold changes in TBP/TATA affinity in most cases. The results obtained strongly suggest that the TBP/TATA equilibrium binding equation derived can be used for analysis of TATA-box sequences and identification of SNPs with a potential of being functionally important.

Next-generation sequencing applications for wheat crop improvement

Bread wheat (Triticum aestivum; Poaceae) is a crop plant of great importance. It provides nearly 20% of the world's daily food supply measured by calorie intake, similar to that provided by rice. The yield of wheat has doubled over the last 40 years due to a combination of advanced agronomic practice and improved germplasm through selective breeding. More recently, yield growth has been less dramatic, and a significant improvement in wheat production will be required if demand from the growing human population is to be met. Next-generation sequencing (NGS) technologies are revolutionizing biology and can be applied to address critical issues in plant biology. Technologies can produce draft sequences of genomes with a significant reduction to the cost and timeframe of traditional technologies. In addition, NGS technologies can be used to assess gene structure and expression, and importantly, to identify heritable genome variation underlying important agronomic traits. This review provides an overview of the wheat genome and NGS technologies, details some of the problems in applying NGS technology to wheat, and describes how NGS technologies are starting to impact wheat crop improvement.