Journal of Phylogenetics & Evolutionary Biology

Organismal biology, the study of structure, function, ecology and evolution at the level of the organism, provides a rich arena for investigation on its own, but also plays a central role in answering conceptual questions about both ecology and evolution. Organisms connect ecology, physiology, and behavior to the fields of comparative genomics, evolutionary development, and phylogenetics. Organismal-level study is crucial throughout comparative biology, which becomes increasingly potent as the genomes of more and more organisms are sequenced and annotated. Faculty in EEB share a conviction that studies of ecological and evolutionary processes are more efficient, and their results more reliable, when they are solidly grounded in a naturalist's detailed familiarity with the organisms being studied.

The human microbiome is the ensemble of genes in the microbes that live inside and on the surface of humans. Because microbial sequencing information is now much easier to come by than phenotypic information, there has been an explosion of sequencing and genetic analysis of microbiome samples. Much of the analytical work for these sequences involves phylogenetics, at least indirectly, but methodology has developed in a somewhat different direction than for other applications of phylogenetics. In this article, I review the field and its methods from the perspective of a phylogeneticist, as well as describing current challenges for phylogenetics coming from this type of work.

Phylogenetics is the study of the evolutionary relatedness among groups of organisms. Molecular phylogenetics uses sequence data to infer these relationships for both organisms and the genes they maintain. With the large amount of publicly available sequence data, phylogenetic inference has become increasingly important in all fields of biology. In the case of natural product research, phylogenetic relationships are proving to be highly informative in terms of delineating the architecture and function of the genes involved in secondary metabolite biosynthesis.

Polyketide syntheses and non-ribosomal peptide syntheses provide model examples in which individual domain phylogenies display different predictive capacities, resolving features ranging from substrate specificity to structural motifs associated with the final metabolic product. This chapter provides examples in which phylogeny has proven effective in terms of predicting functional or structural aspects of secondary metabolism. The basics of how to build a reliable phylogenetic tree are explained along with information about programs and tools that can be used for this purpose. Furthermore, it introduces the Natural Product Domain Seeker, a recently developed Web tool that employs phylogenetic logic to classify ketosynthase and condensation domains based on established enzyme architecture and biochemical function.

Molecular phylogeneticsis that the branch of phylogeny that analyzes genetic, hereditary molecular differences, predominately in DNA sequences, to realize information on an organism's evolutionary relationships. From these analyses, it's possible to work out the processes by which diversity among species has been achieved. The results of a molecular phylogenetic analysis is expressed during a phylogenetic tree. Molecular phylogenetics is one aspect of molecular systematics, a broader term that also includes the utilization of molecular data in taxonomy and biogeography.

Molecular phylogenetics and molecular evolution correlate. Molecular evolution is that the process of selective changes (mutations) at a molecular level (genes, proteins, etc.) throughout various branches within the tree of life (evolution). Molecular phylogenetics makes inferences of the evolutionary relationships that arise thanks to molecular evolution and leads to the development of a phylogenetic tree. The figure displayed on the proper depicts the phylogenetic tree of life together of the primary detailed trees, consistent with information known within the 1870s by Haeckel.

Bioinformatics is an interdisciplinary field that develops methods and software tools for understanding biological data, especially when the info sets are large and sophisticated. As an interdisciplinary field of science, bioinformatics combines biology, computing, information engineering, mathematics and statistics to research and interpret the biological data. Bioinformatics has been used for in silicon analyses of biological queries using mathematical and statistical techniques.

Bioinformatics includes biological studies that use programming as a part of their methodology, also as a selected analysis "pipelines" that are repeatedly used, particularly within the field of genomics. Common uses of bioinformatics include the identification of candidates’ genes and single nucleotide polymorphisms (SNPs). Often, such identification is formed with the aim of higher understanding the genetic basis of disease, unique adaptations, desirable properties (esp. in agricultural species), or differences between populations. During a less formal way, bioinformatics also tries to know the organizational principles within macromolecule and protein sequences, called proteomics.