Utilities for high-throughput analysis of B-cell clonal lineages

There are at present few tools available to assist with the determination and analysis of B-cell lineage trees from next-generation sequencing data. Here we present two utilities that support automated large-scale analysis and the creation of publication-quality results. The tools are available on the web, and are also available for download so that they can be integrated into an automated pipeline. Critically, and in contrast to previously published tools, these utilities can be used with any suitable phylogenetic inference method and with any antibody germline library, and hence are species-independent

BranchClust: a phylogenetic algorithm for selecting gene families

BACKGROUND: Automated methods for assembling families of orthologous genes include those based on sequence similarity scores and those based on phylogenetic approaches. The first are easy to automate but usually they do not distinguish between paralogs and orthologs or have restriction on the number of taxa. Phylogenetic methods often are based on reconciliation of a gene tree with a known rooted species tree; a limitation of this approach, especially in case of prokaryotes, is that the species tree is often unknown, and that from the analyses of single gene families the branching order between related organisms frequently is unresolved. RESULTS: Here we describe an algorithm for the automated selection of orthologous genes that recognizes orthologous genes from different species in a phylogenetic tree for any number of taxa. The algorithm is capable of distinguishing complete (containing all taxa) and incomplete (not containing all taxa) families and recognizes in- and outparalogs. The BranchClust algorithm is implemented in Perl with the use of the BioPerl module for parsing trees and is freely available at . CONCLUSION: BranchClust outperforms the Reciprocal Best Blast hit method in selecting more sets of putatively orthologous genes. In the test cases examined, the correctness of the selected families and of the identified in- and outparalogs was confirmed by inspection of the pertinent phylogenetic trees

Substrate-specific clades of active marine methylotrophs associated with a phytoplankton bloom in a temperate coastal environment

Marine microorganisms that consume one-carbon (C1) compounds are poorly described, despite their impact on global climate via an influence on aquatic and atmospheric chemistry. This study investigated marine bacterial communities involved in the metabolism of C1 compounds. These communities were of relevance to surface seawater and atmospheric chemistry in the context of a bloom that was dominated by phytoplankton known to produce dimethylsulfoniopropionate. In addition to using 16S rRNA gene fingerprinting and clone libraries to characterize samples taken from a bloom transect in July 2006, seawater samples from the phytoplankton bloom were incubated with 13C-labeled methanol, monomethylamine, dimethylamine, methyl bromide, and dimethyl sulfide to identify microbial populations involved in the turnover of C1 compounds, using DNA stable isotope probing. The [13C]DNA samples from a single time point were characterized and compared using denaturing gradient gel electrophoresis (DGGE), fingerprint cluster analysis, and 16S rRNA gene clone library analysis. Bacterial community DGGE fingerprints from 13C-labeled DNA were distinct from those obtained with the DNA of the nonlabeled community DNA and suggested some overlap in substrate utilization between active methylotroph populations growing on different C1 substrates. Active methylotrophs were affiliated with Methylophaga spp. and several clades of undescribed Gammaproteobacteria that utilized methanol, methylamines (both monomethylamine and dimethylamine), and dimethyl sulfide. rRNA gene sequences corresponding to populations assimilating 13C-labeled methyl bromide and other substrates were associated with members of the Alphaproteobacteria (e.g., the family Rhodobacteraceae), the Cytophaga-Flexibacter-Bacteroides group, and unknown taxa. This study expands the known diversity of marine methylotrophs in surface seawater and provides a comprehensive data set for focused cultivation and metagenomic analyses in the future

Species Identification And Phylogeny Of Phycinae Hakes And Related Gadoid Fishes

The term hake refers to a number of species belonging to multiple families of fish in the suborder Gadoidei and includes two main groups: Phycinae hakes (family Gadidae) and Merluccius spp. hakes (family Merlucciidae). The use of the common name hake for this diverse group of fish prompts questions such as: how are these species related and how can they be differentiated? Chapter one details the development of the Rapid Gadoid Identification Assay (RaGIA) for molecular identification of 11 gadoid fishes (including six hakes) using Polymerase Chain Reaction Restriction Fragment Length Polymorphism (PCR-RFLP). RaGIA was used for species identification of fillets of hake, pollock and haddock sold in southern Maine markets. Testing found that market labeling was accurate; however, there were inconsistences in the labels provided by the fish distributors (from whom the markets obtained their fillets). Chapter two explores the development of a phylogeny, based on a mitochondrial DNA gene and a nuclear encoded gene, which includes members of the families Gadidae and Merlucciidae. The resulting phylogeny was used for morphological character mapping and investigation of trait evolution in this group. Consistent with previous studies, the analysis resolved the families Gadidae, as well as several subfamilies, and Merlucciidae with strong support. The putative Lotinae subfamily clade was not resolved in this analysis and suggests that further study is needed to investigate the monophyly of this group. The three dorsal fins and two anal fins morphological states as well as the life history characteristic of the absence of an egg oil globule were all found to be characteristic of the Gadinae, the most derived clade of the Gadoidei

A 2-million-year-old ecosystem in Greenland uncovered by environmental DNA

Late Pliocene and Early Pleistocene epochs 3.6 to 0.8 million years ago1 had climates resembling those forecasted under future warming2. Palaeoclimatic records show strong polar amplification with mean annual temperatures of 11–19 °C above contemporary values3,4. The biological communities inhabiting the Arctic during this time remain poorly known because fossils are rare5. Here we report an ancient environmental DNA6 (eDNA) record describing the rich plant and animal assemblages of the Kap København Formation in North Greenland, dated to around two million years ago. The record shows an open boreal forest ecosystem with mixed vegetation of poplar, birch and thuja trees, as well as a variety of Arctic and boreal shrubs and herbs, many of which had not previously been detected at the site from macrofossil and pollen records. The DNA record confirms the presence of hare and mitochondrial DNA from animals including mastodons, reindeer, rodents and geese, all ancestral to their present-day and late Pleistocene relatives. The presence of marine species including horseshoe crab and green algae support a warmer climate than today. The reconstructed ecosystem has no modern analogue. The survival of such ancient eDNA probably relates to its binding to mineral surfaces. Our findings open new areas of genetic research, demonstrating that it is possible to track the ecology and evolution of biological communities from two million years ago using ancient eDNA

Unexpected mitochondrial genome diversity revealed by targeted single-cell genomics of heterotrophic flagellated protists

This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this recordData availability: Complete mtDNA sequences assembled from this study are available at GenBank under the accession numbers MK188935 to MK188947, MN082144 and MN082145. Sequencing data are available under NCBI BioProject PRJNA379597. Reads have been deposited at NCBI Sequence Read Archive with accession number SRP102236. Partial mtDNA contigs and other important contigs mentioned in the text are available from Figshare at https://doi.org/10.6084/m9.figshare.7314728. Nuclear SAG assemblies are available from Figshare at https://doi.org/10.6084/m9.figshare.7352966. A protocol is available from protocols.io at: https://doi.org/10.17504/protocols.io.ywpfxdn.Code availability: The bioinformatic workflow is available at https://doi.org/10.5281/zenodo.192677; additional statistical analysis code is available at https://doi.org/10.6084/m9.figshare.9884309.Most eukaryotic microbial diversity is uncultivated, under-studied and lacks nuclear genome data. Mitochondrial genome sampling is more comprehensive, but many phylogenetically important groups remain unsampled. Here, using a single-cell sorting approach combining tubulin-specific labelling with photopigment exclusion, we sorted flagellated heterotrophic unicellular eukaryotes from Pacific Ocean samples. We recovered 206 single amplified genomes, predominantly from underrepresented branches on the tree of life. Seventy single amplified genomes contained unique mitochondrial contigs, including 21 complete or near-complete mitochondrial genomes from formerly under-sampled phylogenetic branches, including telonemids, katablepharids, cercozoans and marine stramenopiles, effectively doubling the number of available samples of heterotrophic flagellate mitochondrial genomes. Collectively, these data identify a dynamic history of mitochondrial genome evolution including intron gain and loss, extensive patterns of genetic code variation and complex patterns of gene loss. Surprisingly, we found that stramenopile mitochondrial content is highly plastic, resembling patterns of variation previously observed only in plants.Gordon and Betty Moore FoundationLeverhulme TrustDavid and Lucile Packard FoundationRoyal SocietyEuropean Molecular Biology OrganizationCONICYT FONDECYTGenome Canad

Formal methods applied to the analysis of phylogenies: Phylogenetic model checking

Los árboles filogenéticos son abstracciones útiles para modelar y caracterizar la evolución de un conjunto de especies o poblaciones respecto del tiempo. La proposición, verificación y generalización de hipótesis sobre un árbol filogenético inferido juegan un papel importante en el estudio y comprensión de las relaciones evolutivas. Actualmente, uno de los principales objetivos científicos es extraer o descubrir los mensajes biológicos implícitos y las propiedades estructurales subyacentes en la filogenia. Por ejemplo, la integración de información genética en una filogenia ayuda al descubrimiento de genes conservados en todo o parte del árbol, la identificación de posiciones covariantes en el ADN o la estimación de las fechas de divergencia entre especies. Consecuentemente, los árboles ayudan a comprender el mecanismo que gobierna la deriva evolutiva. Hoy en día, el amplio espectro de métodos y herramientas heterogéneas para el análisis de filogenias enturbia y dificulta su utilización, además del fuerte acoplamiento entre la especificación de propiedades y los algoritmos utilizados para su evaluación (principalmente scripts ad hoc). Este problema es el punto de arranque de esta tesis, donde se analiza como solución la posibilidad de introducir un entorno formal de verificación de hipótesis que, de manera automática y modular, estudie la veracidad de dichas propiedades definidas en un lenguaje genérico e independiente (en una lógica formal asociada) sobre uno de los múltiples softwares preparados para ello. La contribución principal de la tesis es la propuesta de un marco formal para la descripción, verificación y manipulación de relaciones causales entre especies de forma independiente del código utilizado para su valoración. Para ello, exploramos las características de las técnicas de model checking, un paradigma en el que una especificación expresada en lógica temporal se verifica con respecto a un modelo del sistema que representa una implementación a un cierto nivel de detalle. Se ha aplicado satisfactoriamente en la industria para el modelado de sistemas y su verificación, emergiendo del ámbito de las ciencias de la computación. Las contribuciones concretas de la tesis han sido: A) La identificación e interpretación de los árboles filogeneticos como modelos de la evolución, adaptados al entorno de las técnicas de model checking. B) La definición de una lógica temporal que captura las propiedades filogenéticas habituales junto con un método de construcción de propiedades. C) La clasificación de propiedades filogenéticas, identificando categorías de propiedades según estén centradas en la estructura del árbol, en las secuencias o sean híbridas. D) La extensión de las lógicas y modelos para contemplar propiedades cuantitativas de tiempo, probabilidad y de distancias. E) El desarrollo de un entorno para la verificación de propiedades booleanas, cuantitativas y paramétricas. F) El establecimiento de los principios para la manipulación simbolica de objetos filogenéticos, p. ej., clados. G) La explotación de las herramientas de model checking existentes, detectando sus problemas y carencias en el campo de filogenia y proponiendo mejoras. H) El desarrollo de técnicas "ad hoc" para obtener ganancia de complejidad alrededor de dos frentes: distribución de los cálculos y datos, y el uso de sistemas de información. Los puntos A-F se centran en las aportaciones conceptuales de nuestra aproximación, mientras que los puntos G-H enfatizan la parte de herramientas e implementación. Los contenidos de la tesis están contrastados por la comunidad científica mediante las siguientes publicaciones en conferencias y revistas internacionales. La introducción de model checking como entorno formal para analizar propiedades biológicas (puntos A-C) ha llevado a la publicación de nuestro primer artículo de congreso [1]. En [2], desarrollamos la verificación de hipótesis filogenéticas sobre un árbol de ejemplo construido a partir de las relaciones impuestas por un conjunto de proteínas codificadas por el ADN mitocondrial humano (ADNmt). En ese ejemplo, usamos una herramienta automática y genérica de model checking (punto G). El artículo de revista [7] resume lo básico de los artículos de congreso previos y extiende la aplicación de lógicas temporales a propiedades filogenéticas no consideradas hasta ahora. Los artículos citados aquí engloban los contenidos presentados en las Parte I--II de la tesis. El enorme tamaño de los árboles y la considerable cantidad de información asociada a los estados (p.ej., la cadena de ADN) obligan a la introducción de adaptaciones especiales en las herramientas de model checking para mantener un rendimiento razonable en la verificación de propiedades y aliviar también el problema de la explosión de estados (puntos G-H). El artículo de congreso [3] presenta las ventajas de rebanar el ADN asociado a los estados, la partición de la filogenia en pequeños subárboles y su distribución entre varias máquinas. Además, la idea original del model checking rebanado se complementa con la inclusión de una base de datos externa para el almacenamiento de secuencias. El artículo de revista [4] reúne las nociones introducidas en [3] junto con la implementación y resultados preliminares presentados [5]. Este tema se corresponde con lo presentado en la Parte III de la tesis. Para terminar, la tesis reaprovecha las extensiones de las lógicas temporales con tiempo explícito y probabilidades a fin de manipular e interrogar al árbol sobre información cuantitativa. El artículo de congreso [6] ejemplifica la necesidad de introducir probabilidades y tiempo discreto para el análisis filogenético de un fenotipo real, en este caso, el ratio de distribución de la intolerancia a la lactosa entre diversas poblaciones arraigadas en las hojas de la filogenia. Esto se corresponde con el Capítulo 13, que queda englobado dentro de las Partes IV--V. Las Partes IV--V completan los conceptos presentados en ese artículo de conferencia hacia otros dominios de aplicación, como la puntuación de árboles, y tiempo continuo (puntos E-F). La introducción de parámetros en las hipótesis filogenéticas se plantea como trabajo futuro. Referencias [1] Roberto Blanco, Gregorio de Miguel Casado, José Ignacio Requeno, and José Manuel Colom. Temporal logics for phylogenetic analysis via model checking. In Proceedings IEEE International Workshop on Mining and Management of Biological and Health Data, pages 152-157. IEEE, 2010. [2] José Ignacio Requeno, Roberto Blanco, Gregorio de Miguel Casado, and José Manuel Colom. Phylogenetic analysis using an SMV tool. In Miguel P. Rocha, Juan M. Corchado Rodríguez, Florentino Fdez-Riverola, and Alfonso Valencia, editors, Proceedings 5th International Conference on Practical Applications of Computational Biology and Bioinformatics, volume 93 of Advances in Intelligent and Soft Computing, pages 167-174. Springer, Berlin, 2011. [3] José Ignacio Requeno, Roberto Blanco, Gregorio de Miguel Casado, and José Manuel Colom. Sliced model checking for phylogenetic analysis. In Miguel P. Rocha, Nicholas Luscombe, Florentino Fdez-Riverola, and Juan M. Corchado Rodríguez, editors, Proocedings 6th International Conference on Practical Applications of Computational Biology and Bioinformatics, volume 154 of Advances in Intelligent and Soft Computing, pages 95-103. Springer, Berlin, 2012. [4] José Ignacio Requeno and José Manuel Colom. Model checking software for phylogenetic trees using distribution and database methods. Journal of Integrative Bioinformatics, 10(3):229-233, 2013. [5] José Ignacio Requeno and José Manuel Colom. Speeding up phylogenetic model checking. In Mohd Saberi Mohamad, Loris Nanni, Miguel P. Rocha, and Florentino Fdez-Riverola, editors, Proceedings 7th International Conference on Practical Applications of Computational Biology and Bioinformatics, volume 222 of Advances in Intelligent Systems and Computing, pages 119-126. Springer, Berlin, 2013. [6] José Ignacio Requeno and José Manuel Colom. Timed and probabilistic model checking over phylogenetic trees. In Miguel P. Rocha et al., editors, Proceedings 8th International Conference on Practical Applications of Computational Biology and Bioinformatics, Advances in Intelligent and Soft Computing. Springer, Berlin, 2014. [7] José Ignacio Requeno, Gregorio de Miguel Casado, Roberto Blanco, and José Manuel Colom. Temporal logics for phylogenetic analysis via model checking. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 10(4):1058-1070, 2013