Investment in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing in Africa over the past year has led to a major increase in the number of sequences that have been generated and used to track the pandemic on the continent, a number that now exceeds 100,000 genomes. Our results show an increase in the number of African countries that are able to sequence domestically and highlight that local sequencing enables faster turnaround times and more-regular routine surveillance. Despite limitations of low testing proportions, findings from this genomic surveillance study underscore the heterogeneous nature of the pandemic and illuminate the distinct dispersal dynamics of variants of concern—particularly Alpha, Beta, Delta, and Omicron—on the continent. Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve while the continent faces many emerging and reemerging infectious disease threats. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century.

SARS-CoV-2 across Africa: The impact of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has been hard to track in African countries, largely because of patchy data. Wilkinson et al . curated viral genomes collected in 2021 from several countries across the continent. Outbreaks during 2020 in each African country were initiated by imported cases, mostly from Europe. As the pandemic developed, case numbers in African countries were likely many times higher than reported, and subsequent waves of the pandemic appear to have been more severe. Consequently, high-transmission variants have emerged that have spread within the continent, and African countries must be included in global control efforts. —CA

We compare the powers of three methods for the QTL analysis of non-normally distributed traits. We describe the nonparametric and the logistic regression approaches recently proposed in the literature and study the properties of the standard regression interval mapping method when the trait is not normally distributed. It is shown that the standard approach is robust against non-normality and behaves quite well for both continuous and discrete characters. The loss of power compared with the nonparametric or the logistic approach is generally minor. Moreover, the least squares estimation procedure of the regression interval mapping is not affected by departure from normality. The use of other approaches could be restricted to extreme cases where the trait distribution is very skewed.

Introduction: The majority of autoimmune diseases such as rheumatoid arthritis (RA) and autoimmune thyroid diseases (AITDs) are characterized by a striking female predominance superimposed on a predisposing genetic background. The role of extremely skewed X-chromosome inactivation (XCI) has been questioned in the pathogenesis of several autoimmune diseases. Methods: We examined XCI profiles of females affected with RA (n = 106), AITDs (n = 145) and age-matched healthy women (n = 257). XCI analysis was performed by enzymatic digestion of DNA with a methylation sensitive enzyme (HpaII) followed by PCR of a polymorphic CAG repeat in the androgen receptor (AR) gene. The XCI pattern was classified as skewed when 80% or more of the cells preferentially inactivated the same X-chromosome. Results: Skewed XCI was observed in 26 of the 76 informative RA patients (34.2%), 26 of the 100 informative AITDs patients (26%), and 19 of the 170 informative controls (11.2%) (P < 0.0001; P = 0.0015, respectively). More importantly, extremely skewed XCI, defined as > 90% inactivation of one allele, was present in 17 RA patients (22.4%), 14 AITDs patients (14.0%), and in only seven controls (4.1%, P < 0.0001; P = 0.0034, respectively). Stratifying RA patients according to laboratory profiles (rheumatoid factor and anti-citrullinated protein antibodies), clinical manifestations (erosive disease and nodules) and the presence of others autoimmune diseases did not reveal any statistical significance (P > 0.05). Conclusions: These results suggest a possible role for XCI mosaicism in the pathogenesis of RA and AITDs and may in part explain the female preponderance of these diseases.