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ABSTRACTProviding hands-on practical education without access to laboratories during the Covid-19 pandemic has required creativity and innovation. In this paper, co-authored by academic staff and students, we describe an at-home mobile phone-based ‘spectrophotometer’ experiment used in an introductory undergraduate biology course. Using colour picker apps, a smartphone can be used to quantify concentration, which was used to compare the strengths of different brands of tea. The protocol is designed to be low-cost and safe to perform outside of a laboratory. Students used the methods to learn important biochemical methods such as preparing dilutions, constructing calibration curves, normalising data and testing a hypothesis. We reflect on the experience of developing and using the protocol from a staff and student perspective, which highlights the advantages of this approach in terms of student independence and inclusivity. We also suggest alternative experiments that could be performed using the protocol. We encourage biology educators to think creatively about the possibilities for using mobile phones or at-home experiments in their teaching. Our experience suggests that at-home experiments like this protocol will have value even after the pandemic is over, particularly in terms of inclusivity.

Genomic databases of allele frequency are extremely helpful for evaluating clinical variants of unknown significance; however, until now, databases such as the Genome Aggregation Database (gnomAD) have focused on nuclear DNA and have ignored the mitochondrial genome (mtDNA). Here, we present a pipeline to call mtDNA variants that addresses three technical challenges: (1) detecting homoplasmic and heteroplasmic variants, present, respectively, in all or a fraction of mtDNA molecules; (2) circular mtDNA genome; and (3) misalignment of nuclear sequences of mitochondrial origin (NUMTs). We observed that mtDNA copy number per cell varied across gnomAD cohorts and influenced the fraction of NUMT-derived false-positive variant calls, which can account for the majority of putative heteroplasmies. To avoid false positives, we excluded contaminated samples, cell lines, and samples prone to NUMT misalignment due to few mtDNA copies. Furthermore, we report variants with heteroplasmy ≥10%. We applied this pipeline to 56,434 whole-genome sequences in the gnomAD v3.1 database that includes individuals of European (58%), African (25%), Latino (10%), and Asian (5%) ancestry. Our gnomAD v3.1 release contains population frequencies for 10,850 unique mtDNA variants at more than half of all mtDNA bases. Importantly, we report frequencies within each nuclear ancestral population and mitochondrial haplogroup. Homoplasmic variants account for most variant calls (98%) and unique variants (85%). We observed that 1/250 individuals carry a pathogenic mtDNA variant with heteroplasmy above 10%. These mtDNA population allele frequencies are freely accessible and will aid in diagnostic interpretation and research studies.