SIGAR: Inferring Features of Genome Architecture and DNA Rearrangements by Split-Read Mapping

Nuclear dualism without extensive DNA elimination in the ciliate Loxodes magnus

Most eukaryotes have one nucleus and nuclear genome per cell. Ciliates have instead evolved distinct nuclei that coexist in each cell: a silent germline vs. transcriptionally active somatic nuclei. In the best-studied model species, both nuclei can divide asexually, but only germline nuclei undergo meiosis and karyogamy during sex. Thereafter, thousands of DNA segments, called internally eliminated sequences (IESs), are excised from copies of the germline genomes to produce the streamlined somatic genome. In Loxodes, however, somatic nuclei cannot divide but instead develop from germline copies even during asexual cell division, which would incur a huge overhead cost if genome editing was required. Here, we purified and sequenced both genomes in Loxodes magnus to see whether their nondividing somatic nuclei are associated with differences in genome architecture. Unlike in other ciliates studied to date, we did not find canonical germline-limited IESs, implying Loxodes does not extensively edit its genomes. Instead, both genomes appear large and equivalent, replete with retrotransposons and repetitive sequences, unlike the compact, gene-rich somatic genomes of other ciliates. Two other hallmarks of nuclear development in ciliates-domesticated DDE-family transposases and editing-associated small RNAs-were also not found. Thus, among the ciliates, Loxodes genomes most resemble those of conventional eukaryotes. Nonetheless, base modifications, histone marks, and nucleosome positioning of vegetative Loxodes nuclei are consistent with functional differentiation between actively transcribed somatic vs. inactive germline nuclei. Given their phylogenetic position, it is likely that editing was present in the ancestral ciliate but secondarily lost in the Loxodes lineage.

Comparative genomics reveals insight into the evolutionary origin of massively scrambled genomes

Ciliates are microbial eukaryotes that undergo extensive programmed genome rearrangement, a natural genome editing process that converts long germline chromosomes into smaller gene-rich somatic chromosomes. Three well-studied ciliates include Oxytricha trifallax, Tetrahymena thermophila, and Paramecium tetraurelia, but only the Oxytricha lineage has a massively scrambled genome, whose assembly during development requires hundreds of thousands of precisely programmed DNA joining events, representing the most complex genome dynamics of any known organism. Here we study the emergence of such complex genomes by examining the origin and evolution of discontinuous and scrambled genes in the Oxytricha lineage. This study compares six genomes from three species, the germline and somatic genomes for Euplotes woodruffi, Tetmemena sp., and the model ciliate O. trifallax. We sequenced, assembled, and annotated the germline and somatic genomes of E. woodruffi, which provides an outgroup, and the germline genome of Tetmemena sp. We find that the germline genome of Tetmemena is as massively scrambled and interrupted as Oxytricha's: 13.6% of its gene loci require programmed translocations and/or inversions, with some genes requiring hundreds of precise gene editing events during development. This study revealed that the earlier diverged spirotrich, E. woodruffi, also has a scrambled genome, but only roughly half as many loci (7.3%) are scrambled. Furthermore, its scrambled genes are less complex, together supporting the position of Euplotes as a possible evolutionary intermediate in this lineage, in the process of accumulating complex evolutionary genome rearrangements, all of which require extensive repair to assemble functional coding regions. Comparative analysis also reveals that scrambled loci are often associated with local duplications, supporting a gradual model for the origin of complex, scrambled genomes via many small events of DNA duplication and decay.

KOMB: K-core based de novo characterization of copy number variation in microbiomes

Characterizing metagenomes via kmer-based, database-dependent taxonomic classification has yielded key insights into underlying microbiome dynamics. However, novel approaches are needed to track community dynamics and genomic flux within metagenomes, particularly in response to perturbations. We describe KOMB, a novel method for tracking genome level dynamics within microbiomes. KOMB utilizes K-core decomposition to identify Structural variations (SVs), specifically, population-level Copy Number Variation (CNV) within microbiomes. K-core decomposition partitions the graph into shells containing nodes of induced degree at least K, yielding reduced computational complexity compared to prior approaches. Through validation on a synthetic community, we show that KOMB recovers and profiles repetitive genomic regions in the sample. KOMB is shown to identify functionally-important regions in Human Microbiome Project datasets, and was used to analyze longitudinal data and identify keystone taxa in Fecal Microbiota Transplantation (FMT) samples. In summary, KOMB represents a novel graph-based, taxonomy-oblivious, and reference-free approach for tracking CNV within microbiomes. KOMB is open source and available for download at https://gitlab.com/treangenlab/komb.

BleTIES: annotation of natural genome editing in ciliates using long read sequencing

SUMMARY

Ciliates are single-celled eukaryotes that eliminate specific, interspersed DNA sequences (internally eliminated sequences, IESs) from their genomes during development. These are challenging to annotate and assemble because IES-containing sequences are typically much less abundant in the cell than those without, and IES sequences themselves often contain repetitive and low-complexity sequences. Long-read sequencing technologies from Pacific Biosciences and Oxford Nanopore have the potential to reconstruct longer IESs than has been possible with short reads but require a different assembly strategy. Here we present BleTIES, a software toolkit for detecting, assembling, and analyzing IESs using mapped long reads.

AVAILABILITY AND IMPLEMENTATION

BleTIES is implemented in Python 3. Source code is available at https://github.com/Swart-lab/bleties (MIT license) and also distributed via Bioconda.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.