Currently, swine breeding has entered the genomics era, with genome selection becoming the mainstream technology. Lean meat pigs are the mainstay of livestock farming, with the primary focus being on improving meat production efficiency. Therefore, competition in breeding of lean meat pig is essentially a race to enhance meat production efficiency, and improving breeding efficiency is the key to winning this competition. 

After three years of dedicated research and development, the Yingzi Gene & Huazhong Agricultural University team has achieved numerous breakthroughs in the field of pig functional genomics and breeding technology. At the 21st National Conference on Animal Genetics and Breeding held on October 16, Professor Li Xinyun, the Chief Expert of Wuhan Yingzi Gene Technology Co., Ltd. (a subsidiary of Yingzi Technology), was invited to introduce the research achievements of the pig breeding team led by Professor Zhao Shuhong to the entire audience. 

Li Xinyun Giving a Report at the Conference

In terms of breeding, there are four factors that influence its efficiency: Selection intensity, genetic variation, intergenerational intervals, and the accuracy of genetic evaluation. The first three primarily rely on breeding facilities, while the fourth one largely depends on researchers. Based on these considerations and insights, Li Xinyun and the team members embarked on pig functional genomics research and pig genomic breeding research. The team's research objectives are very clear:

1.Pig Functional Genomics Research

The aim is to unearth genomic information with breeding value, in simple terms, to identify genes and variations with breeding value.

2.Pig Genomic Breeding Research

The aim is to efficiently utilize genomic and phenotypic information to enhance the accuracy of genetic evaluation and improve the breeding efficiency.

The team has also achieved a series of research outcomes - 

In the field of gene discovery, the team has developed the whole-genome association analysis tool rMVP, the integrated omics platform ISwine, and CRISPR mutant libraries for functional gene discovery, all of which have been used to identify numerous functional genomic loci in pigs and design a new generation of pig functional gene chips by leveraging such information, not only increasing the genomic information contents valuable for breeding, but also laying the foundation on improving pig breeding efficiency.

Among these, rMVP features high computing efficiency, high detection efficiency, and abundant result output. It is currently the only tool capable of rapidly visualizing millions of markers. Since its release in 2017, it has been downloaded and installed over 100,000 times. At the 2019 International Society for Animal Genetics Conference, more than half of the studies on whole-genome association analysis utilized rMVP, making it an international mainstream tool in this field. 

At the conference, Li Xinyun introduced the team's latest research achievement - the "HiBLUP Breeding Big Data Computing Platform", which is designed to primarily address the challenge of efficiently computing large genomic selection and breeding data. It has now been upgraded to Version 2.0. 

Li Xinyun Introducing HiBLUP

Looking back at the development of breeding in the 1960s, American statistical geneticist C.R. Henderson developed the BLUP algorithm, which opened a significant gateway from genetic theory to practical breeding. In 2001, Meuwissen introduced genomic information into breeding value evaluation, pioneering the concept of genomic selection. Today, genomic selection has become the mainstream technology in animal breeding.

Currently, the computing strategies adopted by traditional breeding tools are difficult to break free from their dependence on FSPAK algorithm (patented in the United States); as the number of genotyping individuals increases, FSPAK and its improved algorithms face challenges including difficulties in computing large genome relationship matrices, maxing existing tools in adequate for handling large genomic breeding datasets. 

China's research and application of pig genomic breeding technology started relatively late. Moreover, pig breeding is a complex and resource-intensive undertaking with challenging benefit assessments, making it less attractive for companies to invest in. This has resulted in inadequately independent innovation in China's pig genomic breeding, lower efficiency in breeding, and limited international competitiveness.

Li Xinyun stated, "Many of the technologies, equipment, and tools used in performance testing, genetic evaluation, and genome detection in China rely heavily on foreign sources. If we continue to imitate without independent innovation, there will be no room for surpassing." In the long term, what is most needed to win the battle of transformation in the breeding industry is independent innovation.

To break down international barriers, Li Xinyun's team has tirelessly developed the HiBLUP 2.0 breeding big data computing platform. This platform employs a completely new computing strategy, completely eliminating the reliance on foreign breeding computing patents. It has the ability to rapidly process large populations and millions of markers for breeding big data and encompasses all the calculations needed for genomic selection and breeding! 

HiBLUP Interface

Neither relying on any third-party software packages and nor subject to any breeding computing patent both at home and abroad, HiBLUP is currently considered the only software capable of conducting genomic selection and breeding computing, covering all computing steps in genomic selection and breeding.

HiBLUP adopts innovative algorithmic approaches and intelligent weighting to construct the optimal model and enhance the accuracy of selection and breeding, and utilizes algorithm innovation, parallel computing and hardware acceleration to improve the computing efficiency. The more the genotyping individuals are, the greater the computing efficiency will be. It is the only breeding computing software capable of efficiently handling millions of populations and tens of millions of markers. Compared with similar international software, HiBLUP can significantly save computing resources and reduce costs for the same amount of data. 

HiBLUP is highly intelligent, user-friendly, and easy to learn. 

In short, HiBLUP 2.0 is feature-rich, user-friendly, and leads internationally in both selection and breeding accuracy and computing cost-efficiency. 

Currently, the pig farming level in China lags behind that of developed countries, and to narrow this gap, Yingzi Technology has entered into a strategic partnership with Huazhong Agricultural University to engage in continuous research and innovation. On one hand, they are developing smart pig farming equipment and software, which is to utilize information technology to enhance farming standards. On the other hand, they are continuously investing in the development of genomic breeding technology to improve the performance of breeding pigs.

It is believed that by continually focusing on "Genetic Inheritance, Precision Nutrition, Production Management, Biosecurity, and Environmental Control", China's pig farming and its efficiency will surely continue to improve.