Introgression.

Biologists have forever sought to understand how species arise and persist. Historically, species that rarely interbreed, or are reproductively isolated, were considered the norm, while those with incomplete reproductive isolation were considered less common. Over the last few decades, advances in genomics have transformed our understanding of the frequency of gene flow between species and with it our ideas about reproductive isolation in nature. These advances have uncovered a rich and often complicated history of genetic exchange between species - demonstrating that such genetic introgression is an important evolutionary process widespread across the tree of life (Figure 1).

Correspondence of aCGH and long-read genome assembly for detection of copy number differences: A proof-of-concept with cichlid genomes.

Copy number variation is an important source of genetic variation, yet data are often lacking due to technical limitations for detection given the current genome assemblies. Our goal is to demonstrate the extent to which an array-based platform (aCGH) can identify genomic loci that are collapsed in genome assemblies that were built with short-read technology. Taking advantage of two cichlid species for which genome assemblies based on Illumina and PacBio are available, we show that inter-species aCGH log2 hybridization ratios correlate more strongly with inferred copy number differences based on PacBio-built genome assemblies than based on Illumina-built genome assemblies. With regard to inter-species copy number differences of specific genes identified by each platform, the set identified by aCGH intersects to a greater extent with the set identified by PacBio than with the set identified by Illumina. Gene function, according to Gene Ontology analysis, did not substantially differ among platforms, and platforms converged on functions associated with adaptive phenotypes. The results of the current study further demonstrate that aCGH is an effective platform for identifying copy number variable sequences, particularly those collapsed in short read genome assemblies.

Graphery: interactive tutorials for biological network algorithms.

Networks have been an excellent framework for modeling complex biological information, but the methodological details of network-based tools are often described for a technical audience. We have developed Graphery, an interactive tutorial webserver that illustrates foundational graph concepts frequently used in network-based methods. Each tutorial describes a graph concept along with executable Python code that can be interactively run on a graph. Users navigate each tutorial using their choice of real-world biological networks that highlight the diverse applications of network algorithms. Graphery also allows users to modify the code within each tutorial or write new programs, which all can be executed without requiring an account. Graphery accepts ideas for new tutorials and datasets that will be shaped by both computational and biological researchers, growing into a community-contributed learning platform. Graphery is available at https://graphery.reedcompbio.org/.