SAS-6 engineering reveals interdependence between cartwheel and microtubules in determining centriole architecture

Centrioles are critical for the formation of centrosomes, cilia and flagella in eukaryotes. They are thought to assemble around a nine-fold symmetric cartwheel structure established by SAS-6 proteins. Here, we have engineered Chlamydomonas reinhardtii SAS-6-based oligomers with symmetries ranging from five- to ten-fold. Expression of a SAS-6 mutant that forms six-fold symmetric cartwheel structures in vitro resulted in cartwheels and centrioles with eight- or nine-fold symmetries in vivo. In combination with Bld10 mutants that weaken cartwheel-microtubule interactions, this SAS-6 mutant produced six- to eight-fold symmetric cartwheels. Concurrently, the microtubule wall maintained eight- and nine-fold symmetries. Expressing SAS-6 with analogous mutations in human cells resulted in nine-fold symmetric centrioles that exhibited impaired length and organization. Together, our data suggest that the self-assembly properties of SAS-6 instruct cartwheel symmetry, and lead us to propose a model in which the cartwheel and the microtubule wall assemble in an interdependent manner to establish the native architecture of centrioles

A prototype forecasting system for bird-borne disease spread in North America based on migratory bird movements

Dataset consisting of seasonal distributions of all North American migratory bird species, subject to certain filters for inclusion

Reddy_sup_fileS5_alignments.tar

tar.gz file with four nexus format alignments. Folder also contains a README with additional information about the sequence alignments

Reddy_sup_fileS10_Prum_noJAR.tar

tar.gz file with three files: 1) a relaxed phylip format alignment of the Prum_noJAR data (concatenated alignments of the Prum et al. 2015 loci after excluding the loci that overlap with Jarvis et al. 2014); 2) a RAxML format partitioning file for the Prum_noJAR data; and 3) a Nexus format treefile with the estimates of phylogeny for Prum_noJAR generated by RAxML and IQ-TREE analyses. Folder also contains a README with additional information about the files

Reddy_sup_fileS3

List of taxa with voucher information and taxonomic details.An xlsx file with three sheets ("README", "EB2 species list", and "Full taxonomy"). The "Full taxonomy" sheet compares the clades proposed in Jarvis et al. 2014 and those proposed in Prum et al. 2015

Reddy_sup_fileS9_EB2noJAR_nextrees

Nexus treefile with the results of RAxML and IQ-TREE analyses of the EB2noJAR and EB2noJARnoFGB datasets using the EB2 taxon set. The data matrices used to generate these trees correspond to the EB2 data after excluding the sites overlapping with the Jarvis et al. (2014) data. The data matrix used to generate the noJARnoFGB trees also excludes the gene encoding beta-fibrinogen (FGB). Additional information about the trees can be found as comments in the nexus treefile

Reddy_sup_fileS11_backbone_trees

Nexus file containing: 1) the "backbone trees" (trees reduced to ordinal lineages) used for the tree clustering analysis; and 2) symmetric distances among the trees. The file contains embedded comments. If the file is executed in PAUP* it will echo this information to the screen, print the backbone trees, and conduct the tree clustering analysis

Data from: Why do phylogenomic data sets yield conflicting trees? Data type influences the avian tree of life more than taxon sampling

Phylogenomics, the use of large-scale data matrices in phylogenetic analyses, has been viewed as the ultimate solution to the problem of resolving difficult nodes in the tree of life. However, it has become clear that analyses of these large genomic data sets can also result in conflicting estimates of phylogeny. Here, we use the early divergences in Neoaves, the largest clade of extant birds, as a “model system” to understand the basis for incongruence among phylogenomic trees. We were motivated by the observation that trees from two recent avian phylogenomic studies exhibit conflicts. Those studies used different strategies: 1) collecting many characters [42 mega base pairs (Mbp) of sequence data] from 48 birds, sometimes including only one taxon for each major clade; and 2) collecting fewer characters (0.4 Mbp) from 198 birds, selected to subdivide long branches. However, the studies also used different data types: the taxon-poor data matrix comprised 68% non-coding sequences whereas coding exons dominated the taxon-rich data matrix. This difference raises the question of whether the primary reason for incongruence is the number of sites, the number of taxa, or the data type. To test among these alternative hypotheses we assembled a novel, large-scale data matrix comprising 90% non-coding sequences from 235 bird species. Although increased taxon sampling appeared to have a positive impact on phylogenetic analyses the most important variable was data type. Indeed, by analyzing different subsets of the taxa in our data matrix we found that increased taxon sampling actually resulted in increased congruence with the tree from the previous taxon-poor study (which had a majority of non-coding data) instead of the taxon-rich study (which largely used coding data). We suggest that the observed differences in the estimates of topology for these studies reflect data-type effects due to violations of the models used in phylogenetic analyses, some of which may be difficult to detect. If incongruence among trees estimated using phylogenomic methods largely reflects problems with model fit developing more “biologically-realistic” models is likely to be critical for efforts to reconstruct the tree of life

Reddy_sup_tableS1_evolutionary_rates

Table showing relative rates of sequence evolution for coding regions, introns, UCEs, and a mixed alignment that includes multiple types of genomic data. The data were obtained from the trees described by Jarvis et al. (2014)

Reddy_sup_fileS2_PrumLoci

Information about the loci used by Prum et al. 2015. An xlsx file with two sheets ("README" and "Prum locus information")