QTL-seq Analysis

QTL-seq Analysis Online Inquiry

CD Genomics uses bioinformatics to provide QTL-Seq analysis service and help you quickly locate the extreme trait genes. Our unique skills in data analysis can meet customers' personalized data analysis needs and provide the most comprehensive data analysis.

Introduction of QTL-Seq Analysis

Quantitative trait locus (QTL)-Seq is a method that combines bulked segregant analysis (BSA) and high-throughput whole-genome re-sequencing to detect the major locus of a certain quantitative trait in a segregating population.

QTL-Seq selects parents that show a contrasting phenotype on a trait of interest to build a segregating population—either F2 recombinant inbred lines, double haploid, or backcross populations—and then selects two groups of individual plants, each showing segregation of the trait to one of the parents, as two mixed pools to perform genotype analysis. The genomic position of the polymorphic molecular markers that shows significant segregation of genotypes is the region harboring the major QTL. Currently, BSA has been updated to QTL-Seq through the replacement of traditional markers such as RAPD (random amplification polymorphic DNA) or RFLP (restriction fragment length polymorphism) to SNP (single nucleotide polymorphism) markers, accompanied by high-throughput re-sequencing and SNP-index analysis. QTL-Seq has been widely and successfully used in many crop populations.

A simplified scheme of QTL-seq as applied to rice Fig 1. A simplified scheme of QTL-seq as applied to rice (Takagi H; et al.2013)

Application of QTL-Seq Analysis

Special economic animals



Only mixed analysis of selected individuals in the population is necessary for genotyping according to traits, which can greatly reduce the workload and cost of research.

QTL-Seq shows much higher efficiency than the traditional QTL mapping, which is typically time-consuming and involves labor-intensive genotyping and maintenance of the mapping populations.

CD Genomics QTL-Seq Analysis Pipeline

The original input data can be whole genome resequencing data or transcriptome sequencing data.

CD Genomics QTL-Seq analysis pipeline - CD Genomics.

Bioinformatics Analysis Content

Standard analysis

Quality evaluation of sequencing data

Raw data filtering

Gene coverage analysis
In-depth sequencing analysis

SNP detection
Annotation of SNP location and function
Information statistics of SNP conversion and subversion
SNP hybrid information statistics

InDel detection
Annotation of InDel location and function
InDel hybrid information statistics

Advanced analysis

Comparison of polymorphism between parents

SNP frequency analysis of offspring

Target trait related area positioning

Analysis of target region candidate genes

The original input data is usually whole genome sequencing data or transcriptome sequencing data. If you have other types of data for BSA analysis, please feel free to contact us for details.

Turnaround Time

QTL-Seq Analysis

About one to two weeks, it’s depends on the specific scale of the project (number of samples and phenotype types) and the type of data (whole genome sequencing data or transcriptome sequencing data). For more information, please contact us.

CD Genomics has over a decade of experience in QTL-Seq analysis. If you have any questions about how we can help you, please get in touch. We look forward to working with you!


  1. Takagi H; et al. QTL-seq: rapid mapping of quantitative trait loci in rice by whole genome resequencing of DNA from two bulked populations. Plant Journal, 2013, 74(1):174-183.
* For Research Use Only. Not for use in diagnostic procedures.
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