No abstract

Diatoms are mostly photosynthetic eukaryotes within the heterokont lineage. Variable plastid genome sizes and extensive genome rearrangements have been observed across the diatom phylogeny, but little is known about plastid genome evolution within order- or family-level clades. The Thalassiosirales is one of the more comprehensively studied orders in terms of both genetics and morphology. Seven complete diatom plastid genomes are reported here including four Thalassiosirales: Thalassiosira weissflogii, Roundia cardiophora, Cyclotella sp. WC03_2, Cyclotella sp. L04_2, and three additional non-Thalassiosirales species Chaetoceros simplex, Cerataulina daemon, and Rhizosolenia imbricata. The sizes of the seven genomes vary from 116,459 to 129,498 bp, and their genomes are compact and lack introns. The larger size of the plastid genomes of Thalassiosirales compared to other diatoms is due primarily to expansion of the inverted repeat. Gene content within Thalassiosirales is more conserved compared to other diatom lineages. Gene order within Thalassiosirales is highly conserved except for the extensive genome rearrangement in Thalassiosira oceanica. Cyclotella nana, Thalassiosira weissflogii and Roundia cardiophora share an identical gene order, which is inferred to be the ancestral order for the Thalassiosirales, differing from that of the other two Cyclotella species by a single inversion. The genes ilvB and ilvH are missing in all six diatom plastid genomes except for Cerataulina daemon, suggesting an independent gain of these genes in this species. The acpP1 gene is missing in all Thalassiosirales, suggesting that its loss may be a synapomorphy for the order and this gene may have been functionally transferred to the nucleus. Three genes involved in photosynthesis, psaE, psaI, psaM, are missing in Rhizosolenia imbricata, which represents the first documented instance of the loss of photosynthetic genes in diatom plastid genomes.

The phenotype represents a critical interface between the genome and the environment in which organisms live and evolve. Phenotypic characters also are a rich source of biodiversity data for tree building, and they enable scientists to reconstruct the evolutionary history of organisms, including most fossil taxa, for which genetic data are unavailable. Therefore, phenotypic data are necessary for building a comprehensive Tree of Life. In contrast to recent advances in molecular sequencing, which has become faster and cheaper through recent technological advances, phenotypic data collection remains often prohibitively slow and expensive. The next-generation phenomics project is a collaborative, multidisciplinary effort to leverage advances in image analysis, crowdsourcing, and natural language processing to develop and implement novel approaches for discovering and scoring the phenome, the collection of phentotypic characters for a species. This research represents a new approach to data collection that has the potential to transform phylogenetics research and to enable rapid advances in constructing the Tree of Life. Our goal is to assemble large phenomic datasets built using new methods and to provide the public and scientific community with tools for phenomic data assembly that will enable rapid and automated study of phenotypes across the Tree of Life.

Scientists building the Tree of Life face an overwhelming challenge to categorize phenotypes (e.g., anatomy, physiology) from millions of living and fossil species. This biodiversity challenge far outstrips the capacities of trained scientific experts. Here we explore whether crowdsourcing can be used to collect matrix data on a large scale with the participation of nonexpert students, or "citizen scientists." Crowdsourcing, or data collection by nonexperts, frequently via the internet, has enabled scientists to tackle some large-scale data collection challenges too massive for individuals or scientific teams alone. The quality of work by nonexpert crowds is, however, often questioned and little data have been collected on how such crowds perform on complex tasks such as phylogenetic character coding. We studied a crowd of over 600 nonexperts and found that they could use images to identify anatomical similarity (hypotheses of homology) with an average accuracy of 82% compared with scores provided by experts in the field. This performance pattern held across the Tree of Life, from protists to vertebrates. We introduce a procedure that predicts the difficulty of each character and that can be used to assign harder characters to experts and easier characters to a nonexpert crowd for scoring. We test this procedure in a controlled experiment comparing crowd scores to those of experts and show that crowds can produce matrices with over 90% of cells scored correctly while reducing the number of cells to be scored by experts by 50%. Preparation time, including image collection and processing, for a crowdsourcing experiment is significant, and does not currently save time of scientific experts overall. However, if innovations in automation or robotics can reduce such effort, then large-scale implementation of our method could greatly increase the collective scientific knowledge of species phenotypes for phylogenetic tree building. For the field of crowdsourcing, we provide a rare study with ground truth, or an experimental control that many studies lack, and contribute new methods on how to coordinate the work of experts and nonexperts. We show that there are important instances in which crowd consensus is not a good proxy for correctness.

Diatoms are the largest group of heterokont algae with more than 100,000 species. As one of the single-celled photosynthetic organisms that inhabit marine, aquatic and terrestrial ecosystems, diatoms contribute ~ 45% of global primary production. Despite their ubiquity and environmental significance, very few diatom plastid genomes (plastomes) have been sequenced and studied. This study explored patterns of nucleotide substitution rates of diatom plastids across the entire suite of plastome protein-coding genes for 40 taxa representing the major clades. The highest substitution rate was lineage-specific within the araphid 2 taxon Astrosyne radiata and radial 2 taxon Proboscia sp. Rate heterogeneity was also evident in different functional classes and individual genes. Similar to land plants, proteins genes involved in photosynthetic metabolism have lower synonymous and nonsynonymous substitutions rates than those involved in transcription and translation. Significant positive correlations were identified between substitution rates and measures of genomic rearrangements, including indels and inversions, which is a similar result to what was found in legume plants. This work advances the understanding of the molecular evolution of diatom plastomes and provides a foundation for future studies.