Organellar genomes, such as those from mitochondria and plastids, are important tools in phylogenetic and evolutionary analyses with the advent of better Next Generation Sequencing technologies. The mitogenomes and plastomes are relatively small compared with the nuclear genomes. The genes they encoded are often highly conserved and can provide a wealth of data on an organism's evolutionary history. In addition, these genes also encode proteins that carry out crucial functions, helping us gain high-level mechanistic insight into a cell's use of these organelles.
Best practice papers for organelle genome research are essential as they provide guidelines and recommendations for standardizing the experimental protocols and data analysis procedures. Additionally, best practice papers provide a framework for comparing results across different studies and datasets, essential for meta-analyses and large-scale organelle genomic studies. By following best practices, researchers can avoid common pitfalls and uncertainties, reduce errors, and increase the accuracy and reliability of their results. Many best practice papers may be available for nuclear genome analysis. They can be customized for the study of organelle genomes.
Mitochondrial DNA Part B considers the best practice paper as a review paper. There are several types of best practice papers we are looking for in particular, including:
- Sample collection and preparation: This includes guidelines for collecting, identifying, storing, and processing biological samples to ensure the integrity and quality of the organelle genomic data.
- Sequencing and data analyses: This includes best practices for appropriate sequencing, genome assembly, annotation, and visualization methods and tools.
- Quality control and validation: This includes protocols for assessing the quality and accuracy of organelle genomes' assembly and annotation results and strategies for validating organelle genomic studies' findings.
- Ethical considerations: This includes best practices for addressing data sharing and ownership issues.
- Reproducibility and transparency: This includes best practices for reporting data and methods clearly and transparently and strategies for ensuring that other researchers can replicate organelle genomic studies.
Disclosure Statement: Prof. Liu declares no conflict of interest regarding this work.
