A primary aim of microbial ecology is to determine patterns and drivers of community distribution, interaction, and assembly amidst complexity and uncertainty. Microbial community composition has been shown to change across gradients of environment, geographic distance, salinity, temperature, oxygen, nutrients, pH, day length, and biotic factors 1-6 . These patterns have been identified mostly by focusing on one sample type and region at a time, with insights extra polated across environments and geography to produce generalized principles. To assess how microbes are distributed across environments globally-or whether microbial community dynamics follow funda mental ecological 'laws' at a planetary scale-requires either a massive monolithic cross environment survey or a practical methodology for coordinating many independent surveys. New studies of microbial environments are rapidly accumulating; however, our ability to extract meaningful information from across datasets is outstripped by the rate of data generation. Previous meta analyses have suggested robust gen eral trends in community composition, including the importance of salinity 1 and animal association 2 . These findings, although derived from relatively small and uncontrolled sample sets, support the util ity of meta analysis to reveal basic patterns of microbial diversity and suggest that a scalable and accessible analytical framework is needed.The Earth Microbiome Project (EMP, http://www.earthmicrobiome. org) was founded in 2010 to sample the Earth's microbial communities at an unprecedented scale in order to advance our understanding of the organizing biogeographic principles that govern microbial commu nity structure 7,8 . We recognized that open and collaborative science, including scientific crowdsourcing and standardized methods 8 , would help to reduce technical variation among individual studies, which can overwhelm biological variation and make general trends difficult to detect 9 . Comprising around 100 studies, over half of which have yielded peer reviewed publications (Supplementary Table 1), the EMP has now dwarfed by 100 fold the sampling and sequencing depth of earlier meta analysis efforts 1,2 ; concurrently, powerful analysis tools have been developed, opening a new and larger window into the distri bution of microbial diversity on Earth. In establishing a scalable frame work to catalogue microbiota globally, we provide both a resource for the exploration of myriad questions and a starting point for the guided acquisition of new data to answer them. As an example of using this Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of r...

Tunicates or urochordates (appendicularians, salps and sea squirts), cephalochordates (lancelets) and vertebrates (including lamprey and hagfish) constitute the three extant groups of chordate animals. Traditionally, cephalochordates are considered as the closest living relatives of vertebrates, with tunicates representing the earliest chordate lineage. This view is mainly justified by overall morphological similarities and an apparently increased complexity in cephalochordates and vertebrates relative to tunicates. Despite their critical importance for understanding the origins of vertebrates, phylogenetic studies of chordate relationships have provided equivocal results. Taking advantage of the genome sequencing of the appendicularian Oikopleura dioica, we assembled a phylogenomic data set of 146 nuclear genes (33,800 unambiguously aligned amino acids) from 14 deuterostomes and 24 other slowly evolving species as an outgroup. Here we show that phylogenetic analyses of this data set provide compelling evidence that tunicates, and not cephalochordates, represent the closest living relatives of vertebrates. Chordate monophyly remains uncertain because cephalochordates, albeit with a non-significant statistical support, surprisingly grouped with echinoderms, a hypothesis that needs to be tested with additional data. This new phylogenetic scheme prompts a reappraisal of both morphological and palaeontological data and has important implications for the interpretation of developmental and genomic studies in which tunicates and cephalochordates are used as model animals.

Correspondence to H.P. email: herve.philippe@umontreal.ca -2 - PrefaceAs more complete genomes are sequenced, phylogenetic analysis is entering a new era -that of phylogenomics. One branch of this expanding field aims to reconstruct the evolutionary history of organisms based on the analysis of their genomes. Recent studies have demonstrated the power of this approach, which has the potential to provide answers to a number of fundamental evolutionary questions. However, challenges for the future have also been revealed. The very nature of the evolutionary history of organisms and the limitations of current phylogenetic reconstruction methods mean that part of the tree of life may prove difficult, if not impossible, to resolve with confidence. Introductory paragraphUnderstanding phylogenetic relationships between organisms is a prerequisite of almost any evolutionary study, as contemporary species all share a common history through their ancestry. The notion of phylogeny follows directly from the theory of evolution presented by Charles Darwin in "The Origin of Species" 1 : the only illustration in his famous book is the first representation of evolutionary relationships among species, in the form of a phylogenetic tree. The subsequent enthusiasm of biologists for the phylogenetic concept is illustrated by the publication of Ernst Haeckel's famous "trees" as early as 1866 2 .Today, phylogenetics -the reconstruction of evolutionary history -relies on using mathematical methods to infer the past from features of contemporary species, with only the fossil record to provide a window on the evolutionary past of life on our planet. This reconstruction involves the identification of HOMOLOGOUS CHARACTERS that are shared among different organisms, and the inference of phylogenetic trees from the comparison of these characters using reconstruction methods (BOX 1). The accuracy of -3 -the inference is therefore heavily dependent upon the quality of models for the evolution of such characters. Because the underlying mechanisms are not yet well understood, reconstructing the evolutionary history of life on Earth based solely on the information provided by living organisms has turned out to be difficult.Until the 1970s, which brought the dawn of molecular techniques for sequencing proteins and DNA, phylogenetic reconstruction was essentially based on the analysis of morphological or ultrastructural characters. The comparative anatomy of fossils and extant species has proved powerful in some respects; for example, the main groups of animals and plants have been delineated fairly easily using these methods. However, this approach is hampered by the limited number of reliable homologous characters available; these are almost non-existent in micro-organisms 3 and are rare even in complex organisms.The introduction of the use of molecular data in phylogenetics 4 led to a revolution.In the late 1980s, access to DNA sequences increased the number of homologous characters that could be compared from less than 100 to more than 1,000, ...

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Our understanding of the origins, the functions and/or the structures of biological sequences strongly depends on our ability to decipher the mechanisms of molecular evolution. These complex processes can be described through the comparison of homologous sequences in a phylogenetic framework. Moreover, phylogenetic inference provides sound statistical tools to exhibit the main features of molecular evolution from the analysis of actual sequences. This chapter focuses on phylogenetic tree estimation under the maximum likelihood (ML) principle. Phylogenies inferred under this probabilistic criterion are usually reliable and important biological hypotheses can be tested through the comparison of different models. Estimating ML phylogenies is computationally demanding though and careful examination of the results is warranted. This chapter focuses on PhyML, a software that implements recent ML phylogenetic methods and algorithms. We illustrate the strengths and pitfalls of this program through the analysis of a real data set. PhyML v3.0 is available from http://atgc.lirmm.fr/phyml 2 1 Introduction.

International audienceUntil recently, molecular phylogenies based on a single or few orthologous genes often yielded contradictory results. Using multiple genes in a large concatenation was proposed to end these incongruences. Here we show that single-gene phylogenies often produce incongruences, albeit ones lacking statistically significant support. By contrast, the use of different tree reconstruction methods on different partitions of the concatenated supergene leads to well-resolved, but real (i.e. statistically significant) incongruences. Gathering a large amount of data is not sufficient to produce reliable trees, given the current limitation of tree reconstruction methods, especially when the quality of data is poor. We propose that selecting only data that contain minimal nonphylogenetic signals takes full advantage of phylogenomics and markedly reduces incongruence

Until now the most efficient solution to align nucleotide sequences containing open reading frames was to use indirect procedures that align amino acid translation before reporting the inferred gap positions at the codon level. There are two important pitfalls with this approach. Firstly, any premature stop codon impedes using such a strategy. Secondly, each sequence is translated with the same reading frame from beginning to end, so that the presence of a single additional nucleotide leads to both aberrant translation and alignment.We present an algorithm that has the same space and time complexity as the classical Needleman-Wunsch algorithm while accommodating sequencing errors and other biological deviations from the coding frame. The resulting pairwise coding sequence alignment method was extended to a multiple sequence alignment (MSA) algorithm implemented in a program called MACSE (Multiple Alignment of Coding SEquences accounting for frameshifts and stop codons). MACSE is the first automatic solution to align protein-coding gene datasets containing non-functional sequences (pseudogenes) without disrupting the underlying codon structure. It has also proved useful in detecting undocumented frameshifts in public database sequences and in aligning next-generation sequencing reads/contigs against a reference coding sequence.MACSE is distributed as an open-source java file executable with freely available source code and can be used via a web interface at: http://mbb.univ-montp2.fr/macse.

Resolving the early diversification of animal lineages has proven difficult, even using genome-scale datasets. Several phylogenomic studies have supported the classical scenario in which sponges (Porifera) are the sister group to all other animals ("Porifera-sister" hypothesis), consistent with a single origin of the gut, nerve cells, and muscle cells in the stem lineage of eumetazoans (bilaterians + ctenophores + cnidarians). In contrast, several other studies have recovered an alternative topology in which ctenophores are the sister group to all other animals (including sponges). The "Ctenophora-sister" hypothesis implies that eumetazoan-specific traits, such as neurons and muscle cells, either evolved once along the metazoan stem lineage and were then lost in sponges and placozoans or evolved at least twice independently in Ctenophora and in Cnidaria + Bilateria. Here, we report on our reconstruction of deep metazoan relationships using a 1,719-gene dataset with dense taxonomic sampling of non-bilaterian animals that was assembled using a semi-automated procedure, designed to reduce known error sources. Our dataset outperforms previous metazoan gene superalignments in terms of data quality and quantity. Analyses with a best-fitting site-heterogeneous evolutionary model provide strong statistical support for placing sponges as the sister-group to all other metazoans, with ctenophores emerging as the second-earliest branching animal lineage. Only those methodological settings that exacerbated long-branch attraction artifacts yielded Ctenophora-sister. These results show that methodological issues must be carefully addressed to tackle difficult phylogenetic questions and pave the road to a better understanding of how fundamental features of animal body plans have emerged.