MicroBinfie Podcast, 97 Advances in sequencing technologies

Released on December 29, 2022

Recent Advancements in Genome Sequencing Technologies

In a recent episode of the Microbial Bioinformatics podcast, three experts—Andrew, Lee, and Nabil—came together to discuss the latest advances in genome sequencing technologies, focusing on developments shared at conferences and within the community.

Key Highlights from the Discussion

Cutting-edge Instruments and Features

• Element Biosciences: A new instrument from this company captured particular interest from Nabil.
• Illumina: Andrew highlighted the adaptive sequencing feature that allows for the selective processing of desired genetic reads while filtering out unwanted ones.

Technological and Computational Developments

• There is significant progress in the computing power of sequencing labs, where gaming computers are being repurposed to aid data analysis.
• Illumina's Complete Long-Read Solution and NextSeq Kits: Contentious discussion about the efficiencies these bring to the sequencing scene.
• PacBio and Hi-Fi Sequencing: Growing popularity due to the ability to achieve high fidelity readings.

4th Generation Sequencing

• Longer reads are paving the way for this advancement despite challenges with software adapting to new formats.
• Nabil emphasized the importance of focusing on data quality over merely increasing quantity.

Software Limitations and Challenges

Long-Read Handling Capabilities

• Andrew described constraints in sequencing software, notably that it is often hard-coded to handle only up to 300 paired-end reads, which can result in crashes when limits are exceeded.

Query on Software Limits

• Lee questioned if source code constraints in Spades or SKESA affect handling larger datasets.
• Andrew explained that developers may impose limits on memory or stack size, leading to processing issues with larger datasets.

Conclusion

The conversation underscored that the hard-coded and data processing limitations should not be seen as permanent barriers. As genome sequencing technologies continue to evolve, so should the software solutions, adapting to effectively manage more complex genetic datasets in future advancements.

Episode 97 transcript