Dataset Information

Fast and cost-effective genetic mapping in apple using next-generation sequencing.

ABSTRACT: Next-generation DNA sequencing (NGS) produces vast amounts of DNA sequence data, but it is not specifically designed to generate data suitable for genetic mapping. Recently developed DNA library preparation methods for NGS have helped solve this problem, however, by combining the use of reduced representation libraries with DNA sample barcoding to generate genome-wide genotype data from a common set of genetic markers across a large number of samples. Here we use such a method, called genotyping-by-sequencing (GBS), to produce a data set for genetic mapping in an F1 population of apples (Malus × domestica) segregating for skin color. We show that GBS produces a relatively large, but extremely sparse, genotype matrix: over 270,000 SNPs were discovered but most SNPs have too much missing data across samples to be useful for genetic mapping. After filtering for genotype quality and missing data, only 6% of the 85 million DNA sequence reads contributed to useful genotype calls. Despite this limitation, using existing software and a set of simple heuristics, we generated a final genotype matrix containing 3967 SNPs from 89 DNA samples from a single lane of Illumina HiSeq and used it to create a saturated genetic linkage map and to identify a known QTL underlying apple skin color. We therefore demonstrate that GBS is a cost-effective method for generating genome-wide SNP data suitable for genetic mapping in a highly diverse and heterozygous agricultural species. We anticipate future improvements to the GBS analysis pipeline presented here that will enhance the utility of next-generation DNA sequence data for the purposes of genetic mapping across diverse species.

SUBMITTER: Gardner KM

PROVIDER: S-EPMC4169160 | biostudies-literature | 2014 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Fast and cost-effective genetic mapping in apple using next-generation sequencing.

Gardner Kyle M KM Brown Patrick P Cooke Thomas F TF Cann Scott S Costa Fabrizio F Bustamante Carlos C Velasco Riccardo R Troggio Michela M Myles Sean S

G3 (Bethesda, Md.) 20140716 9

Next-generation DNA sequencing (NGS) produces vast amounts of DNA sequence data, but it is not specifically designed to generate data suitable for genetic mapping. Recently developed DNA library preparation methods for NGS have helped solve this problem, however, by combining the use of reduced representation libraries with DNA sample barcoding to generate genome-wide genotype data from a common set of genetic markers across a large number of samples. Here we use such a method, called genotyping ...[more]

PMID: 25031181

Similar Datasets

Project description:Phenotype-driven forward genetic experiments are among the most powerful approaches for linking biology and disease to genomic elements. Although widely used in a range of model organisms, positional cloning of causal variants is still a very laborious process. Here, we describe a novel universal approach, named fast forward genetics that combines traditional bulk segregant techniques with next-generation sequencing technology and targeted genomic enrichment, to dramatically improve the process of mapping and cloning multiple mutants in a single experiment. In a two-step procedure the mutation is first roughly mapped by ‘light’ sequencing of the bulk segregant pool, followed by genomic enrichment and deep-sequencing of the mutant pool for the linked genomic region. The latter step allows for simultaneous fine-mapping and mutation discovery. We successfully applied this approach to three Arabidopsis mutants, but the method can in principle be applied to any model organism of interest and is largely independent of the genome size. Moreover, we show that both steps can be performed in multiplex using barcoded samples, thereby increasing efficiency enormously. Inducible overexpression of the RETINOBLASTOMA-RELATED (RBR-OE) gene in Arabidopsis roots causes the complete differentiation of stem cells and premature differentiation of daughter cells, leading to a full exhaustion of the primary root meristem. In order to identify regulators of RBR function in cell differentiation, RBR-OE plants in the Columbia background (Col0) were treated with EMS mutagenesis and a set of genetic suppressors of RBR-OE, which restores root growth capacity, were isolated. In this study, we used one the identified suppressor lines, which segregated as a recessive mutation. Mapping populations were generated by outcrossing to Ler ecotype. Seedlings from the F2 population were grown for 15 days post germination (dpg). A pool of 60 seedlings each with a clear suppressor phenotype (homozygous for suppressor mutation) and of 60 seedlings showing RBOE phenotype (Heterozygous for the suppressor mutation) were prepared and genomic DNA was isolated with the RNeasy Plant Mini Kit from QIAGEN according to manufacturer's protocol. The other two, mutants 136 and 193 were obtained in fluorescence based mutant screen and a QCmarker based mutagenesis, respectively. Mutants were generated by chemical mutagenesis (EMS) in Colombia (Col) genetic background. Mutants were subsequently crossed to the Landsberg (Ler) ecotype to create the mapping populations. Bulk-segregant pools of about 200 mutant as well as wild-type plants were generated for every mutant line.

Dataset Information

Fast and cost-effective genetic mapping in apple using next-generation sequencing.

Publications

Fast and cost-effective genetic mapping in apple using next-generation sequencing.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets