Bulked Segregant Analysis

Platform Overview

Bulked segregant analysis (BSA) is a technique employed to quickly identify phenotype associated genetic markers. Main workflow of BSA contains selecting two groups of individuals with extremely opposing phenotypes, pooling the DNA of all individuals to form two bulk of DNA, identifying differential sequences between two pools. This technique has been extensively employed in identifying genetic markers strongly associated by targeted genes in plant/animal genomes.

Service Workflow

Material selection
Library construction and sequencing
Marker identification
Association Analysis

Bioinformatic Analysis

You can choose from following three BSA related strategies depending on size and complexity of genome and particular research goals:
Resequencing-BSA SLAF-BSA transcriptome-BSA (BSR)

BSA with Biomarker Technologies

Biomarker Technologies has accumulated massive experience in population genetic studies, covering hundreds of species. Our technical group has contributed to over 60 publications in high impact journals, such as Nature Communication, Molecular Plant, Plant Biotechnology Journal, The Plant Journal, etc., accumulated IF over 220.
50+ skilled experts in analysis
Diverse successful cases
Highly-experienced technical team
3 distributed computer cluster servers
In-depth data interpretation
Optimized reports delivery
Professional after-sale support
Rapid analysis

Service Specification

Results Demo

Raw Data QC

It is crucial to ensure the quality of sequencing data is adequate for a reliable downstream analysis. Assessments on data production, base quality score, nuceotide distribution, etc. are processed to estimate reliability of sequencing

Genetic Variation Identification

Single Nucleotide Polymorphism (SNP) and Insertion-Deletion (InDel) are typical genetic markers, which are of great frequency and diveristy. Identification of SNP and InDels is processed by GATK and samtools. variation site is annotated by SnpEff.

Association Analysis

Traits related genes can be identified by association analysis on genetic markers (SNPs and Indels identified from parents and offspring mixed pools) and traits of interest by SNP-Index and ED analysis.

Functional annotation on candidate regions

Genes in candidate regions can be annotated against vaious database, e.g. NR, Swiss-prot, GO, KEGG, COG, etc. by BLAST, which enables narrowing down of candidate regions based on gene functions and rapid identification of candidate genes.


1What is the recommended mixed pooling size?
For study on quantitative traits, we recommended to select 5%-10% of the population for pooling. For Resequencing-BSA and BSR studies, minimum of 30 samples each are required and in SLAF-BSA, minimum of 50 samples are required. It has been reported that a larger poolling can lead to better results (300 samples/pool vs 160 samples/pool).
2 Is it available to identify traits associated Indels, structural variation (transposon slip), etc. by BSA study?
Yes. Currently, BSA association analysis is mainly based on SNPs, as SNP is one of the most frequent markers on genome compared to Indels or other structural variations, which empowers more accurate mapping. However, if a trait is induced by other variations, it is very likely to be linked with some SNP. We could identify candidate regions by SNPs. Other variations on corresponding candidate regions can be further identified, which helps seek traits associated ones.
3Can I do BSA without parenting samples?
Yes, BSA projects without parenting samples, we can use ED to process association analysis.
4I have two groups, but neither of it has enough samples, can I mixed two groups for sequencing?
5How can I have more accurate mapping by SLAF-BSA study?
We recommend to do resequencing on two parenting samples, which largely helps in narrowing down candidate regions. Resequencing on both parenting samples and offspring pools obviously can provide more SNPs compared to SLAF, which leads to more accurate mapping.
6What's the difference between SLAF-BSA (non-reference) and BSR?
SLAF-BSA on species without reference genome can only provide some associated tags. This type of data won't provide further information. In non-ref BSR, unigenes can be assembled and processed for functional annotation. Candidate regions identified by association analysis can be further annotated.
7What is suitable for Mutmap?
Chemical or physical mutagenesis; wild type parenting resequencing+mutant offspring mixed pooling sequencing; With reference genome; Family population with trait separation.

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