Quality control is essential for genome assemblies; however, a consensus has yet to be reached on what metrics should be adopted for the evaluation of assembly quality. N50 is widely used for contiguity measurement, but its effectiveness is constantly in question. Prevailing metrics for the completeness evaluation focus on gene space, yet challenging areas such as tandem repeats are commonly overlooked. Achieving correctness has become an indispensable dimension for quality control, while prevailing assembly releases lack scores reflecting this aspect. We propose a metric set with a set of statistic indexes for effective, comprehensive evaluation of assemblies and provide a score of a finished assembly for each metric, which can be utilized as a benchmark for achieving high-quality genome assemblies.

Since the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak, convergent studies have provided evidence that host genetic background may contribute to the development of severe coronavirus disease (COVID-19). Here, we summarize how some genetic variations, such as in SARS-CoV-2 receptor angiotensin-converting enzyme 2 or interferon signaling pathway, may help to understand why some individuals can develop severe COVID-19.