Nature is the international weekly journal of science: a magazine style journal that publishes full-length research papers in all disciplines of science, as well as News and Views, reviews, news, features, commentaries, web focuses and more, covering all branches of science and how science impacts upon all aspects of society and life.

Phylogenies provide a useful way to understand the evolutionary history of genetic samples, and data sets with more than a thousand taxa are becoming increasingly common, notably with viruses (e.g., human immunodeficiency virus (HIV)). Dating ancestral events is one of the first, essential goals with such data. However, current sophisticated probabilistic approaches struggle to handle data sets of this size. Here, we present very fast dating algorithms, based on a Gaussian model closely related to the Langley–Fitch molecular-clock model. We show that this model is robust to uncorrelated violations of the molecular clock. Our algorithms apply to serial data, where the tips of the tree have been sampled through times. They estimate the substitution rate and the dates of all ancestral nodes. When the input tree is unrooted, they can provide an estimate for the root position, thus representing a new, practical alternative to the standard rooting methods (e.g., midpoint). Our algorithms exploit the tree (recursive) structure of the problem at hand, and the close relationships between least-squares and linear algebra. We distinguish between an unconstrained setting and the case where the temporal precedence constraint (i.e., an ancestral node must be older that its daughter nodes) is accounted for. With rooted trees, the former is solved using linear algebra in linear computing time (i.e., proportional to the number of taxa), while the resolution of the latter, constrained setting, is based on an active-set method that runs in nearly linear time. With unrooted trees the computing time becomes (nearly) quadratic (i.e., proportional to the square of the number of taxa). In all cases, very large input trees (>10,000 taxa) can easily be processed and transformed into time-scaled trees. We compare these algorithms to standard methods (root-to-tip, r8s version of Langley–Fitch method, and BEAST). Using simulated data, we show that their estimation accuracy is similar to that of the most sophisticated methods, while their computing time is much faster. We apply these algorithms on a large data set comprising 1194 strains of Influenza virus from the pdm09 H1N1 Human pandemic. Again the results show that these algorithms provide a very fast alternative with results similar to those of other computer programs. These algorithms are implemented in the LSD software (least-squares dating), which can be downloaded from http://www.atgc-montpellier.fr/LSD/ , along with all our data sets and detailed results. An Online Appendix, providing additional algorithm descriptions, tables, and figures can be found in the Supplementary Material available on Dryad at http://dx.doi.org/10.5061/dryad.968t3 .

Evolutionary analyses show that H7 influenza viruses probably transferred from ducks to chickens in China on at least two independent occasions, and that reassortment with H9N2 viruses generated the H7N9 outbreak lineage that recently emerged in humans in China, and a related previously unrecognized H7N7 lineage; these H7N7 viruses are shown to have the ability to infect ferrets, and the current pandemic threat could extend beyond H7N9 viruses. Yi Guan and colleagues examine the evolutionary history of the H7N9 influenza virus recently emerged in humans in China. From field surveillance conducted soon after the emergence of the outbreak, the authors provide a number of new avian influenza genomes: 34 H7N7 genomes, 3 H7N9 genomes and 19 H9N2 genomes, as well as 197 sequences from archived isolates collected in southern China between 2000 and 2013. They find that H7 viruses probably transferred from ducks to chickens on at least two independent occasions and that reassortment with H9N2 viruses generated the H7N9 outbreak lineage — and also another previously unrecognized H7N7 lineage. These H7N7 viruses have the ability to experimentally infect ferrets, and although there is little evidence to suggest these viruses are mammalian adapted, the authors suggest that the current pandemic threat could extend beyond H7N9 viruses. A novel H7N9 influenza A virus first detected in March 2013 has since caused more than 130 human infections in China, resulting in 40 deaths1,2. Preliminary analyses suggest that the virus is a reassortant of H7, N9 and H9N2 avian influenza viruses, and carries some amino acids associated with mammalian receptor binding, raising concerns of a new pandemic1,3,4. However, neither the source populations of the H7N9 outbreak lineage nor the conditions for its genesis are fully known5. Using a combination of active surveillance, screening of virus archives, and evolutionary analyses, here we show that H7 viruses probably transferred from domestic duck to chicken populations in China on at least two independent occasions. We show that the H7 viruses subsequently reassorted with enzootic H9N2 viruses to generate the H7N9 outbreak lineage, and a related previously unrecognized H7N7 lineage. The H7N9 outbreak lineage has spread over a large geographic region and is prevalent in chickens at live poultry markets, which are thought to be the immediate source of human infections. Whether the H7N9 outbreak lineage has, or will, become enzootic in China and neighbouring regions requires further investigation. The discovery here of a related H7N7 influenza virus in chickens that has the ability to infect mammals experimentally, suggests that H7 viruses may pose threats beyond the current outbreak. The continuing prevalence of H7 viruses in poultry could lead to the generation of highly pathogenic variants and further sporadic human infections, with a continued risk of the virus acquiring human-to-human transmissibility.

As sequence data sets used for the investigation of pathogen transmission patterns increase in size, automated tools and standardized methods for cluster analysis have become necessary. We have developed an automated Cluster Picker which identifies monophyletic clades meeting user-input criteria for bootstrap support and maximum genetic distance within large phylogenetic trees. A second tool, the Cluster Matcher, automates the process of linking genetic data to epidemiological or clinical data, and matches clusters between runs of the Cluster Picker.

The capacity for some pathogens to jump into different host-species populations is a major threat to public health and food security. Staphylococcus aureus is a multi-host bacterial pathogen responsible for important human and livestock diseases. Here, using a population-genomic approach, we identify humans as a major hub for ancient and recent S. aureus host-switching events linked to the emergence of endemic livestock strains, and cows as the main animal reservoir for the emergence of human epidemic clones. Such host-species transitions are associated with horizontal acquisition of genetic elements from host-specific gene pools conferring traits required for survival in the new host-niche. Importantly, genes associated with antimicrobial resistance are unevenly distributed among human and animal hosts, reflecting distinct antibiotic usage practices in medicine and agriculture. In addition to gene acquisition, genetic diversification has occurred in pathways associated with nutrient acquisition, implying metabolic remodelling after a host switch in response to distinct nutrient availability. For example, S. aureus from dairy cattle exhibit enhanced utilization of lactose—a major source of carbohydrate in bovine milk. Overall, our findings highlight the influence of human activities on the multi-host ecology of a major bacterial pathogen, underpinned by horizontal gene transfer and core genome diversification.

In 1918, a strain of influenza A virus caused a human pandemic resulting in the deaths of 50 million people. A century later, with the advent of sequencing technology and corresponding phylogenetic methods, we know much more about the origins, evolution and epidemiology of influenza epidemics. Here we review the history of avian influenza viruses through the lens of their genetic makeup: from their relationship to human pandemic viruses, starting with the 1918 H1N1 strain, through to the highly pathogenic epidemics in birds and zoonoses up to 2018. We describe the genesis of novel influenza A virus strains by reassortment and evolution in wild and domestic bird populations, as well as the role of wild bird migration in their long-range spread. The emergence of highly pathogenic avian influenza viruses, and the zoonotic incursions of avian H5 and H7 viruses into humans over the last couple of decades are also described. The threat of a new avian influenza virus causing a human pandemic is still present today, although control in domestic avian populations can minimize the risk to human health. This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’. This issue is linked with the subsequent theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’.