The high-throughput technologies for genetic variation detection in animals and plants mainly include whole genome resequencing, simplified genome sequencing, liquid-phase capture sequencing, and solid-phase chip, etc. low-coverage whole-genome sequencing (LcWGS) is increasingly being applied in genetic breeding of animals and plants after taking typing efficiency and cost factors into account. LcWGS refers to the use of approximately ~1× resequencing data for genetic variation typing. By utilizing reference population's gene information constructed by high-coverage resequencing (>20x) for gene imputation, LcWGS can acquire whole-genome genetic variations with lower costs, making it more favorable for genetic breeding research and application in animals and plants.

Yingzi Gene has developed efficient genotype imputation processes with and without reference, allowing for accurate acquisition of whole-genome genetic variation typing results. For genome research and genomic breeding, we offer two types of services. 

1. Genome Research

The "Whole Genome Locus - LcWGS" service is introduced, which is to impute the whole genome genetic variations and obtain whole genome variation typing results.

2. Genome Breeding

The "Functional Locus - LcWGS" service is introduced, which is to impute whole-genome functional locus and obtain whole genome functional mutation locus typing results, striking a balance between imputation time and breeding efficiency.

Technical advantages:

Rich in Information: It can provide genetic variations across the entire genome, and offer even more comprehensive data

Accurate Typing: With our proprietary imputation algorithm, the accuracy of gene typing can reach up to 98%

Cost-effective: Under similar cost circumstances, more genetic variation information can be obtained

Technology Roadmap:

Genotype Imputation Principle: 

Genotype Imputation Principle with Reference

The fundamental principle of Genotype Imputation is to construct shared haplogype segments by using genetic variation linkage disequilibrium and recombination information between reference populations or other individuals within the same population and the target population, and then utilize this haplotype information to infer the genotype of missing loci in the population to be imputed.

Genotype Imputation Principle without Reference

In the case where the individual to be imputed has ancestry from multiple populations, the process involves constructing ancestral haplotypes for the individual to be imputed by using their sequence data. The probabilities of generating different ancestral haplotypes for the individual are calculated and the ancestral haplotypes are optimized. After the calculations are completed, the sample haplotypes are used to update their corresponding ancestral haplotypes. Finally, the genotype imputation is performed using the calculated sample haplotype probabilities and the updated ancestral haplotypes.

Case:

Yingzi Gene conducted low-coverage resequencing genotyping on 1,992 Yorkshire pigs (with an average sequencing depth of 0.77x), and conduct high-coverage sequencing typing on a randomly selected subset of 20 ndividuals (with an average sequencing depth of 21.28x). When comparing the genotype results between low-coverage and high-coverage sequencing, the consistency between the two methods exceeded 98%.

Application scenarios:

Genome Research 

Genomic Breeding