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An integrated framework for discovery and genotyping of genomic variants from high-throughput sequencing experiments.

ABSTRACT: Recent advances in high-throughput sequencing (HTS) technologies and computing capacity have produced unprecedented amounts of genomic data that have unraveled the genetics of phenotypic variability in several species. However, operating and integrating current software tools for data analysis still require important investments in highly skilled personnel. Developing accurate, efficient and user-friendly software packages for HTS data analysis will lead to a more rapid discovery of genomic elements relevant to medical, agricultural and industrial applications. We therefore developed Next-Generation Sequencing Eclipse Plug-in (NGSEP), a new software tool for integrated, efficient and user-friendly detection of single nucleotide variants (SNVs), indels and copy number variants (CNVs). NGSEP includes modules for read alignment, sorting, merging, functional annotation of variants, filtering and quality statistics. Analysis of sequencing experiments in yeast, rice and human samples shows that NGSEP has superior accuracy and efficiency, compared with currently available packages for variants detection. We also show that only a comprehensive and accurate identification of repeat regions and CNVs allows researchers to properly separate SNVs from differences between copies of repeat elements. We expect that NGSEP will become a strong support tool to empower the analysis of sequencing data in a wide range of research projects on different species.

SUBMITTER: Duitama J

PROVIDER: S-EPMC3973327 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature

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An integrated framework for discovery and genotyping of genomic variants from high-throughput sequencing experiments.

Duitama Jorge J Quintero Juan Camilo JC Cruz Daniel Felipe DF Quintero Constanza C Hubmann Georg G Foulquié-Moreno Maria R MR Verstrepen Kevin J KJ Thevelein Johan M JM Tohme Joe J

Nucleic acids research 20140111 6

Recent advances in high-throughput sequencing (HTS) technologies and computing capacity have produced unprecedented amounts of genomic data that have unraveled the genetics of phenotypic variability in several species. However, operating and integrating current software tools for data analysis still require important investments in highly skilled personnel. Developing accurate, efficient and user-friendly software packages for HTS data analysis will lead to a more rapid discovery of genomic elem ...[more]

PMID: 24413664

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Project description:BackgroundThe recent development of next-generation sequencing DNA marker technologies, such as genotyping-by-sequencing (GBS), generates thousands of informative single nucleotide polymorphism markers in almost any species, regardless of genomic resources. This enables poorly resourced or "orphan" crops/species access to high-density, high-throughput marker platforms which have revolutionised population genetics studies and plant breeding. DNA quality underpins success of GBS methods as the DNA must be amenable to restriction enzyme digestion and sequencing. A barrier to implementing GBS technologies is access to inexpensive, high-throughput extraction methods that yield sequencing-quality genomic DNA (gDNA) from plants. Several high-throughput DNA extraction methods are available, but typically provide low yield or poor quality gDNA, or are costly (US$6-$9/sample) for consumables.ResultsWe modified a non-organic solvent protocol to extract microgram quantities (1-13 μg) of sequencing-quality high molecular weight gDNA inexpensively in 96-well plates from either fresh, freeze-dried or silica gel-dried plant tissue. The protocol was effective for several easy and difficult-to-extract forage, crop, horticultural and common model species including Trifolium, Medicago, Lolium, Secale, Festuca, Malus, Oryza, and Arabidopsis. The extracted DNA was of high molecular weight and digested readily with restriction enzymes. Contrasting with other extraction protocols we assessed, Illumina-based sequencing of GBS libraries developed from this gDNA had very uniform high quality base-calls to the end of sequence reads. Furthermore, DNA extracted using this method has been sequenced successfully with the PacBio long-read platform. The protocol is scalable, readily automated without requirement for fume hoods, requires approximately three hours to process 192 samples (384-576 samples/day), and is inexpensive at US$0.62/sample for consumables.ConclusionsThis versatile, scalable and simple protocol yields high molecular weight genomic DNA suitable for restriction enzyme digestion and next-generation sequencing applications including GBS and long-read sequencing platforms such as PacBio. The low cost, high-throughput, and extraction of high quality gDNA from a range of fresh and dried source plant material makes this method suitable for many sequencing and genotyping applications including large-scale sample screening underpinning breeding programmes.

Project description:Soybean (Glycine max) breeding involves improving commercially grown varieties by introgressing important agronomic traits from poor yielding accessions and/or wild relatives of soybean while minimizing the associated yield drag. Molecular markers associated with these traits are instrumental in increasing the efficiency of producing such crosses and Single Nucleotide Polymorphisms (SNPs) are particularly well suited for this task, owing to high density in the non-genic regions and thus increased likelihood of finding a tightly linked marker to a given trait. A rapid method to develop SNP markers that can differentiate specific loci between any two parents in soybean is thus highly desirable. In this study we investigate such a protocol for developing SNP markers between multiple soybean accessions and the reference Williams 82 genome. To restrict sampling frequency reduced representation libraries (RRLs) of genomic DNA were generated by restriction digestion followed by library construction. We chose to sequence four accessions Dowling (PI 548663), Dwight (PI 597386), Komata (PI200492) and PI 594538A for their agronomic importance as well as Williams 82 as a control.MseI was chosen to digest genomic DNA based on predictions that it will cut sparingly in the mathematically defined high-copy-number regions of the genome. All RRLs were sequenced on the Illumina genome analyzer. Reads were aligned to the Glyma1 reference assembly and SNP calls made from the alignments. We identified from 4294 to 14550 SNPs between the four accessions and the Williams 82 reference. In addition a small number of SNPs (1142) were found by aligning Williams 82 reads to the reference assembly (Glyma1) suggesting limited genetic variation within the Williams 82 line. The SNP data allowed us to estimate genetic diversity between the four lines and Williams 82. Restriction digestion of soybean genomic DNA with MseI followed by high throughput sequencing provides a rapid and reproducible method for generating SNP markers.

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An integrated framework for discovery and genotyping of genomic variants from high-throughput sequencing experiments.

Publications

An integrated framework for discovery and genotyping of genomic variants from high-throughput sequencing experiments.

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