ddRAD genotyping

Technologies

Features and benefits

  • 1

    KeyGene licensed

  • 2

    Ascertain bias-free experiment

  • 3

    Discover and genotype diversity in one experiments

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    Customized and reproducible selection of genomic loci

  • 5

    Scalability of markers yield from thousands to hundreds of thousands

  • 6

    High recall rate

Services

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    DNA extraction service

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    DNA normalization

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    Library preparation and QCs

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    150bp paired-end sequencing

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    Data analysis to genotype tables

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    Complementary analyses:

    linkage - QTL mapping

    association studies (GWAS)

    molecular barcoding / varietal identification

    diversity and population structure​

Less is more

We were able to make an excellent map to anchor our genome assembly. IGATech support was very helpful.

Mark Aarts

Associate Professor in Plant Genetics
Wageningen University (Netherlands)

One of the major benefits of low error rate provided by Illumina platform is their utilization for accurate SNP calling. However, for large scale experiments where cost-effectiveness has to cope with massive panel of samples (breeding, ecology, association-studies, etc.), whole genome sequencing remains an unaffordable option. One of the most effective techniques in the cutting down of such cost is to reduce the genome to a fraction of its size before sequencing

The method of choice adopted by IGATech for genotyping-by-sequencing is the so-called ddRAD (double digest Restriction Associated DNA). The system provides complexity reduction by selecting genomic DNA fragments generated by cleavage by both restriction enzymes, one per side. This has the advantage of having each genomic locus characterized by a specific size in the library of fragments. Adopting in silico simulation it is possible to fine-tune the amount of genomic loci to be selected. 

AN "OPEN SYSTEM"

Genetic variability is sampled unbiasedly

ddrad

This capability allows to accommodate the adequate sequencing yield to obtain effective coverage to most of loci and thus providing high and reproducible genotyping ratio across individuals also in large cohorts. Moreover, compared to array-based solutions, sequencing is an “open system”, meaning that genetic variability is sampled unbiasedly: this has a critical impact on experiments involving genetic backgrounds and haplotypes not exhaustively represented by the panel of markers used in an array or any previous experiment.

Sample number Standard complexity (15k-30k loci) High complexity (ca. 50-100k loci) Standard bioinformatics (with reference genome)

96

65 euro/sample

85 euro/sample

8 euro/sample

192

55 euro/sample

75 euro/sample

7 euro/sample

288-384

46 euro/sample

65 euro/sample

6 euro/sample

480-864

39 euro/sample

57 euro/sample

5 euro/sample

960+

36 euro/sample

54 euro/sample

5 euro/sample

Over the past years we came to heavily rely on the excellent services provided by IGATech, whose expertise, efficiency, helpful and custom-oriented attitude accompanied us in our scientific growth in the field of genomics. A recent service extension is their double enzyme ddRAD Seq approach we are currently using with great success in several crop species.

Prof. Mario Enrico Pè

Director of the Institute of Life Science,
Scuola Superiore Sant'Anna, Pisa (Italy)

Expertise

IGATech has successfully conducted hundreds of genotyping-by-sequencing experiments on plants and animals, with genome size ranging from megabases to tens of gigabases. Despite such variability in genome size and complexity we manage to obtain effective complexity reduction and target more than 90% of sequencing data in loci with adequate coverage overall.

Our internally developed protocol is also suitable for the finding of discriminatory marker for varietal identification and contamination levels estimation also in food substrates.

Reproducible experiments and bioinformatics analyses are aimed to obtain high quality and comparable data. We provide tailored consultancy for every project to make sure the outcome will meet our customer expectations. Every genome and experimental design have its challenges: we cover them all.

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