DNA Polymerases for Whole Genome Amplification: Considerations and Future Directions

Ordóñez, Carlos D.; Redrejo-Rodríguez, Modesto

doi:10.3390/ijms24119331

Cited by 10 publications

(3 citation statements)

References 174 publications

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“…We proceed to demonstrate the practical efficacy of FSFP by engineering the Phi29 DNA polymerase 47 through wet-lab experiments (“Methods”). Phi29 DNA polymerase has a pivotal role in biotechnological applications and has been rigorously validated as an efficient isothermal DNA amplification enzyme 47 , 48 . Improving the thermostability in Phi29 has currently attracted great research interest 49 – 51 .…”

Section: Resultsmentioning

confidence: 99%

“…Phi29 DNA polymerase is extensively employed in various DNA amplification techniques, such as rolling-circle amplification, multiple displacement amplification (MDA), and non-specific whole genome amplification (WGA). It has been rigorously validated as an efficient isothermal DNA amplification enzyme 47 , 48 . Each amplification method necessitates distinct enzymatic characteristics.…”

Section: Methodsmentioning

confidence: 99%

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Enhancing efficiency of protein language models with minimal wet-lab data through few-shot learning

Zhou,

Zhang,

et al. 2024

Nat Commun

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Accurately modeling the protein fitness landscapes holds great importance for protein engineering. Pre-trained protein language models have achieved state-of-the-art performance in predicting protein fitness without wet-lab experimental data, but their accuracy and interpretability remain limited. On the other hand, traditional supervised deep learning models require abundant labeled training examples for performance improvements, posing a practical barrier. In this work, we introduce FSFP, a training strategy that can effectively optimize protein language models under extreme data scarcity for fitness prediction. By combining meta-transfer learning, learning to rank, and parameter-efficient fine-tuning, FSFP can significantly boost the performance of various protein language models using merely tens of labeled single-site mutants from the target protein. In silico benchmarks across 87 deep mutational scanning datasets demonstrate FSFP’s superiority over both unsupervised and supervised baselines. Furthermore, we successfully apply FSFP to engineer the Phi29 DNA polymerase through wet-lab experiments, achieving a 25% increase in the positive rate. These results underscore the potential of our approach in aiding AI-guided protein engineering.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Enhancing efficiency of protein language models with minimal wet-lab data through few-shot learning

Zhou,

Zhang,

et al. 2024

Nat Commun

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“…Understanding the properties of DNA polymerases is instrumental for the improvement of existing methods and for the development of new methods. The article by Ordóñez and Redrejo-Rodríguez [4] contained in this Special Issue is the first review covering the types and properties of DNA polymerases specifically in relation to the performance of WGA. After explaining the most important WGA methods with special attention to the DNA polymerases employed, the authors review the characteristics of the different DNA polymerases available and how they impact parameters such as the fidelity, bias, and coverage of the different WGA methods.…”

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confidence: 99%

Special Issue on Whole Genome Amplification

Jäger

2023

IJMS

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Recent Innovations and Technical Advances in High‐Throughput Parallel Single‐Cell Whole‐Genome Sequencing Methods

Qiao,

Cheng,

Miao

et al. 2024

Small Methods

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Single‐cell whole‐genome sequencing (scWGS) detects cell heterogeneity at the aspect of genomic variations, which are inheritable and play an important role in life processes such as aging and cancer progression. The recent explosive development of high‐throughput single‐cell sequencing methods has enabled high‐performance heterogeneity detection through a vast number of novel strategies. Despite the limitation on total cost, technical advances in high‐throughput single‐cell whole‐genome sequencing methods are made for higher genome coverage, parallel throughput, and level of integration. This review highlights the technical advancements in high‐throughput scWGS in the aspects of strategies design, data efficiency, parallel handling platforms, and their applications on human genome. The experimental innovations, remaining challenges, and perspectives are summarized and discussed.

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DNA Polymerases for Whole Genome Amplification: Considerations and Future Directions

Cited by 10 publications

References 174 publications

Enhancing efficiency of protein language models with minimal wet-lab data through few-shot learning

Enhancing efficiency of protein language models with minimal wet-lab data through few-shot learning

Special Issue on Whole Genome Amplification

Recent Innovations and Technical Advances in High‐Throughput Parallel Single‐Cell Whole‐Genome Sequencing Methods

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