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The statistics of bulk segregant analysis using next generation sequencing.

ABSTRACT: We describe a statistical framework for QTL mapping using bulk segregant analysis (BSA) based on high throughput, short-read sequencing. Our proposed approach is based on a smoothed version of the standard G statistic, and takes into account variation in allele frequency estimates due to sampling of segregants to form bulks as well as variation introduced during the sequencing of bulks. Using simulation, we explore the impact of key experimental variables such as bulk size and sequencing coverage on the ability to detect QTLs. Counterintuitively, we find that relatively large bulks maximize the power to detect QTLs even though this implies weaker selection and less extreme allele frequency differences. Our simulation studies suggest that with large bulks and sufficient sequencing depth, the methods we propose can be used to detect even weak effect QTLs and we demonstrate the utility of this framework by application to a BSA experiment in the budding yeast Saccharomyces cerevisiae.

SUBMITTER: Magwene PM

PROVIDER: S-EPMC3207950 | biostudies-literature | 2011 Nov

REPOSITORIES: biostudies-literature

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The statistics of bulk segregant analysis using next generation sequencing.

Magwene Paul M PM Willis John H JH Kelly John K JK

PLoS computational biology 20111103 11

We describe a statistical framework for QTL mapping using bulk segregant analysis (BSA) based on high throughput, short-read sequencing. Our proposed approach is based on a smoothed version of the standard G statistic, and takes into account variation in allele frequency estimates due to sampling of segregants to form bulks as well as variation introduced during the sequencing of bulks. Using simulation, we explore the impact of key experimental variables such as bulk size and sequencing coverag ...[more]

PMID: 22072954

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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

The statistics of bulk segregant analysis using next generation sequencing.

Publications

The statistics of bulk segregant analysis using next generation sequencing.

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