Introduction to LP-WGS
Low-pass whole genome sequencing (LP-WGS) is a sequencing method between high-throughput sequencing (HTS) and genotyping technology. It reduces the cost by reducing the sequencing depth, while maintaining a high sensitivity of mutation detection. This method has important application value in genetic research of complex traits, rare mutation detection and chromosome microarray analysis in low-income and middle-income countries.
The main advantages of LP-WGS are its cost-effectiveness and flexibility. Compared with the traditional high-throughput sequencing, LP-WGS can significantly reduce the sequencing cost, making it more suitable for large-scale population research and areas with limited resources. In addition, LP-WGS is excellent in detecting structural variation (SVs) and copy number variation (CNVs), which can provide more comprehensive genetic information than genotyping.
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Current Market Status of LP-WGS
The LP-WGS market is in a rapid development stage worldwide. With the continuous progress of gene sequencing technology and the significant reduction of cost, the application fields of LP-WGS are gradually expanding, including but not limited to disease diagnosis, drug discovery and development, personalized medicine, agriculture and animal research. At present, the global gene sequencing market has reached tens of billions of dollars, and it is expected to continue to maintain rapid growth in the next few years.
The current situation of LP-WGS market is characterized by the continuous expansion of technology application fields, covering scientific research and clinical aspects, the continuous expansion of market scale driven by the rapid growth of 20%-25% of the global gene sequencing market, the reduction of sequencing cost, the fierce competition among enterprises, uneven regional development, mature markets in developed countries such as Europe and the United States, and great room for development in developing countries
Technological innovation promotes development: With the continuous progress of sequencing technology, LP-WGS will develop in the direction of higher Qualcomm capacity, higher resolution and lower cost. For example, the emergence of new sequencing platforms and technologies will further improve sequencing efficiency and accuracy and reduce sequencing cost.
Multi-domain application expansion: In addition to the existing clinical diagnosis, scientific research and other fields, LP-WGS is expected to be applied in drug research and development, health management, agricultural breeding and other fields. For example, in drug research and development, through in-depth analysis of patients' genetic information, it provides targets and basis for drug research and development, and accelerates the process of drug research and development.
Deepening the integration with other technologies: The integration with artificial intelligence, big data, cloud computing and other technologies will be closer. Artificial intelligence and machine learning can be used for more accurate data analysis and interpretation, improving the accuracy and reliability of test results. Cloud computing facilitates the storage and transmission of massive data and realizes remote data processing and analysis.
The demand for personalized medical care is increasing: The development of precision medical care makes the demand for individual genetic information increasing. LP-WGS can provide important genetic data support for personalized medical care, help doctors to formulate more accurate treatment plans and improve the treatment effect, so it will be more and more widely used in personalized medical care.
Further globalization of the market: With the improvement of global medical level and the emphasis on gene technology, the LP-WGS market will be further globalized, and enterprises will strengthen their layout and cooperation in the international market, promote the global sharing of technology and services, and narrow the gap between different regions.
The main technology suppliers in the LP-WGS market are as follows:
Illumina: It is a global leader in gene sequencing, and its products are widely used in scientific research and clinical fields. Although its market share in China has declined, Illumina is still an important player in the global market.
Thermo Fisher Scientific: Thermo Fisher Scientific also has an important layout in the field of gene sequencing equipment, and its products and technologies have a high market share in the world.
Berry gene: Berry gene launched a dynamic mutation detection technology based on the third generation sequencing platform, demonstrating its strength in technological innovation.
Huada Zhizao: It is one of the leading gene sequencing equipment manufacturers in China, and its products cover middle/low-pass and high-throughput sequencing Instrument. Huada Zhizao's share in the low-pass sequencer market is increasing, and it is expected to occupy a larger share in the global market in the future.
Technological Drivers and Cost Efficiency
LPWGS is a cost-effective and improved alternative method for genome association research, which has obvious advantages compared with SNP array. The following are the specific ways to reduce the cost.
Technological progress and cost reduction: With the continuous progress of gene sequencing technology, the sequencing cost has decreased significantly. For example, the development of technology in high-throughput sequencing has reduced the sequencing cost from $5,000 in 2008 to less than $100 in 2023. LP-WGS, as a more economical option, further reduces the cost. LP-WGS reduces the depth and coverage of sequencing, reduces the requirements of hardware computing resources and time, and thus reduces the overall cost.
Wide application range: As a low-cost alternative to chromosome microarray analysis in low-income and middle-income countries, LP-WGS can effectively reduce the cost of genomics research. In the study of complex diseases and trait genetics, LP-WGS provides the same competitiveness as genotyping array, and reduces the measurement error of polygenic risk score.
Data processing and analysis optimization: By optimizing the data processing flow and algorithm, LP-WGS can process a large amount of data more efficiently and reduce the calculation cost. For example, interpolation algorithm and reference interpolation can improve data quality, thus reducing the cost of subsequent analysis. LP-WGS performed well in the quality control before whole exon sequencing (WES), which can accurately predict the proportion of high coverage targets, thus improving the experimental efficiency.
Example of higher experimental efficiency (Lohr et al., 2014)
Multi-domain application: The application of LP-WGS in medicine, agriculture, environmental science and other fields makes it an economical and efficient research tool. For example, in the medical field, LP-WGS can be used to diagnose genetic diseases and cancer. In the agricultural field, it can be used to cultivate disease-resistant crop varieties.
With the continuous development of gene sequencing technology, improving the efficiency and accuracy of sequencing has become the focus of research. The following are the main methods to improve the efficiency and accuracy of sequencing.
Automation and intelligence: With the development of information, automation and intelligent technology, gene sequencing process has become more efficient. For example, automated and accelerated bioinformatics tools can significantly reduce data processing time. Automated single cell isolation and genome amplification technologies are also being developed, further improving the sequencing efficiency.
Multi-platform integration: Combining different sequencing platforms and technologies, such as high-throughput sequencing and single molecule sequencing, a more comprehensive genome analysis can be achieved. For example, combining high-throughput sequencing and single molecule sequencing can improve the detection ability of complex samples.
Approaches to detect, characterize, and identify GMOs by application of WGS (Holst-Jensen et al., 2016)
Data processing and analysis optimization: The quality and accuracy of sequencing data can be improved by optimizing the data processing flow and algorithm. For example, using advanced bioinformatics tools and algorithms can reduce the error rate and improve the sequencing accuracy.
LP-WGS has significantly reduced the cost through technological progress and optimization of data processing flow, while high-throughput sequencing technology, next-generation sequencing technology, single-molecule real-time sequencing, optimized capture protocol, automation and intelligent technology and multi-platform combination have significantly improved the sequencing efficiency and accuracy. These advances not only promote the development of genomics research, but also provide strong technical support for clinical diagnosis, agricultural breeding and environmental protection.
Application Areas of LP-WGS
LP-WGS has broad prospects in clinical diagnosis, population genomics and personalized medicine.
A) Clinical diagnosis
a) Cancer detection
The application of low-pass genome-wide sequencing in cancer detection mainly focuses on early diagnosis and tumor heterogeneity. For example, low coverage sequencing of bladder cancer to detect the variation of DNA copy number in urine sediment has been proved to be useful for preoperative noninvasive diagnosis of bladder cancer and postoperative tumor progress monitoring. In addition, the low-pass sequencing of circulating tumor DNA(ctDNA) is also used to detect mutations in circulating tumor DNA, which provides a new idea for early diagnosis of cancer.
b) Diagnosis of hereditary diseases
LP-WGS also shows great potential in the diagnosis of hereditary diseases. For example, the low-depth genome-wide sequencing analysis of 17q21.31 microsyndrome reveals the clinical phenotypic characteristics of the syndrome and provides a new tool for clinical diagnosis. In addition, family identification of autosomal recessive Schwachman-Diamond syndrome (SDS) and functional study of MEF2A gene also provide important information for the diagnosis and treatment of this disease.
Variants assessed as requiring genome sequencing over exome sequencing to be identified within our cohort (Monica et al., 2023)
B) Population genomics
a) Race and population genetics
LP-WGS plays an important role in the study of race and population genetics. For example, a study conducted a comprehensive chromosome translocation analysis on 2,658 cancer patients by low-pass filtering whole genome sequencing, revealing the genetic characteristics of different races and populations. In addition, LP-WGS has also been used to study the genetic history and population migration trajectory of Native Americans.
Country involvement in NatAm population genomic research (Israel et al., 2022)
b) Animal Genetics
In the field of animal genetics, LP-WGS is used to explore the molecular germplasm characteristics of pig breeds. For example, by analyzing the high-density sequencing data of Taihu pigs, the researchers successfully identified SNP loci related to high fertility. In addition, low-pass genome-wide sequencing has also been used to study the key genes of pig fat deposition and their variations.
C) Personalized medical care
a) Personalized treatment of tumor
LP-WGS plays an important role in individualized treatment of tumors. For example, through the screening of CRISPR/Cas9 library, researchers discovered the role of ADCY7 gene in T cell immune regulation in hepatocellular carcinoma, which provided a new target for immunotherapy of hepatocellular carcinoma. In addition, the screening of therapeutic targets for Ewing sarcoma shows that the combination of Seclidemstat and other drugs may become a new strategy for the treatment of Ewing sarcoma in the future.
b) Personalized treatment of hereditary diseases
LP-WGS also shows potential in personalized treatment of genetic diseases. For example, by analyzing the genome data of patients with 17q21.31 microsyndrome, researchers revealed the genetic mechanism of the syndrome and provided new ideas for personalized treatment.
Future Trends and Outlook for LP-WGS
In terms of technological innovation, LP-WGS will develop in the direction of improving throughput and resolution in the future. Technology suppliers such as Illumina and Huada Zhizao will continuously optimize sequencing technology, further shorten sequencing time, improve detection accuracy and reduce false positive and false negative rates. At the same time, the cost will continue to decrease, making it affordable for more medical institutions and patients. It will also be deeply integrated with artificial intelligence and big data, and use AI algorithm to analyze and interpret sequencing data more accurately and mine potential genetic information.
LP-WGS has broad prospects in personalized medicine and genome research. In personalized medicine, it can accurately predict the risk of diseases by analyzing individual genetic characteristics, such as predicting the possibility of chronic diseases such as cardiovascular disease and diabetes in advance, helping people adjust their lifestyles or intervene with drugs in advance. But also can formulate individualized treatment scheme for complicated diseases such as tumors according to the genetic data of patients, so as to improve the treatment effect and reduce the side effects of drugs.
In the field of genome research, it can play an important role in large-scale population genomics research, obtain high-density markers at low cost, solve the problem of high cost in large genome species research, genotype species/varieties with less genomics research, detect unknown mutations, expand downstream applications such as genome-wide association study and whole genome selection breeding, and promote genome research.Conclusion
The present situation of LP-WGS in the market shows its remarkable advantages in cost, flexibility and application scope. In the future, with the continuous improvement of technology and further reduction of cost, LP-WGS is expected to be widely used in more fields, especially in precision medicine, disease screening and agricultural breeding. However, the industry still needs to overcome technical challenges and cope with the risks brought by market competition in order to achieve sustainable development.
For industry practitioners, the rapid development of low-pass whole genome sequencing technology requires continuous improvement of their professional quality and keeping up with sequencing technology innovations, such as new sequencing principles, algorithm optimization and other cutting-edge knowledge. At the same time, we should actively participate in interdisciplinary cooperation and join hands with experts in bioinformatics, clinical medicine and other fields in order to mine valuable information from marine sequencing data and promote the transformation of clinical application.
In the future, we will focus on technological innovation to reduce costs, improve efficiency and accuracy, expand application scenarios, dig deeper in the fields of rare disease diagnosis and precise tumor treatment, provide a more comprehensive perspective for disease research and diagnosis and treatment by using multi-genomics fusion technology, pay attention to market dynamics, explore emerging markets such as developing countries, and promote the wider application of low-pass genome-wide sequencing.
References:
- Mazzonetto PC, Villela D., et al. "Low-pass whole genome sequencing as a cost-effective alternative to chromosomal microarray analysis for low- and middle-income countries." Am J Med Genet A (2024): e63802 https://doi.org/10.1002/ajmg.a.63802
- Lohr JG, Adalsteinsson VA., et al. "Whole-exome sequencing of circulating tumor cells provides a window into metastatic prostate cancer." Nat Biotechnol (2014): 479-484 https://doi.org/10.1038/nbt.2892
- Holst-Jensen A, Spilsberg B., et al. "Application of whole genome shotgun sequencing for detection and characterization of genetically modified organisms and derived products." Anal Bioanal Chem (2016): 4595-4614 https://doi.org/10.1007/s00216-016-9549-1
- Aguilar-Ordoñez I, Guzmán-Linares., et al. "A Tale of Native American Whole-Genome Sequencing and Other Technologies." Diversity 2022 (14): 647 https://doi.org/10.3390/d14080647
- Wojcik MH, Lemire G., et al. "Unique Capabilities of Genome Sequencing for Rare Disease Diagnosis." medRxiv (2023): 13 https://doi.org/10.1101/2023.08.08.23293829
- Simon M, Kuschel LP., et al. "Rapid DNA methylation-based classification of pediatric brain tumors from ultrasonic aspirate specimens." J Neurooncol (2024): 73-83 https://doi.org/10.1007/s11060-024-04702-6
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