Seven newly sequenced chloroplast genomes from the order Watanabeales (Trebouxiophyceae, Chlorophyta): Phylogenetic and comparative analysis

Comparative Analysis of Chloroplast Genomes in Cephaleuros and Its Related Genus (Trentepohlia): Insights into Adaptive Evolution

Cephaleuros species are well-known as plant pathogens that cause red rust or algae spot diseases in many economically cultivated plants that grow in shady and humid environments. Despite their prevalence, the adaptive evolution of these pathogens remains poorly understood. We sequenced and characterized three Cephaleuros (Cephaleuros lagerheimii, Cephaleuros diffusus, and Cephaleuros virescens) chloroplast genomes, and compared them with seven previously reported chloroplast genomes. The chloroplast sequences of C. lagerheimii, C. diffusus, and C. virescens were 480,613 bp, 383,846 bp, and 472,444 bp in length, respectively. These chloroplast genomes encoded 94 genes, including 27 tRNA genes, 3 rRNA genes, and 64 protein-coding genes. Comparative analysis uncovered that the variation in genome size was principally due to the length of intergenic spacer sequences, followed by introns. Furthermore, several highly variable regions (trnY-GTA, trnL-TAG, petA, psbT, trnD-GTC, trnL-TAA, ccsA, petG, psaA, psaB, rps11, rps2, and rps14) were identified. Codon bias analysis revealed that the codon usage pattern of Cephaleuros is predominantly shaped by natural selection. Additionally, six chloroplast protein-coding genes (atpF, chlN, psaA, psaB, psbA, and rbcL) were determined to be under positive selection, suggesting they may play a vital roles in the adaptation of Cephaleuros to low-light intensity habitats.

A randomized optimal k-mer indexing approach for efficient parallel genome sequence compression

Next Generation Sequencing (NGS) technology generates massive amounts of genome sequence that increases rapidly over time. As a result, there is a growing need for efficient compression algorithms to facilitate the processing, storage, transmission, and analysis of large-scale genome sequences. Over the past 31 years, numerous state-of-the-art compression algorithms have been developed. The performance of any compression algorithm is measured by three main compression metrics: compression ratio, time, and memory usage. Existing k-mer hash indexing systems take more time, due to the decision-making process based on compression results. In this paper, we propose a two-phase reference genome compression algorithm using optimal k-mer length (RGCOK). Reference-based compression takes advantage of the inter-similarity between chromosomes of the same species. RGCOK achieves this by finding the optimal k-mer length for matching, using a randomization method and hashing. The performance of RGCOK was evaluated on three different benchmark data sets: novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Homo sapiens, and other species sequences using an Amazon AWS virtual cloud machine. Experiments showed that the optimal k-mer finding time by RGCOK is around 45.28 min, whereas the time for existing state-of-the-art algorithms HiRGC, SCCG, and HRCM ranges from 58 min to 8.97 h.

Complete mitochondrial and chloroplast DNA sequences of the freshwater green microalga Medakamo hakoo

We report the complete organellar genome sequences of an ultrasmall green alga, Medakamo hakoo strain M-hakoo 311, which has the smallest known nuclear genome in freshwater green algae. Medakamo hakoo has 90.8-kb chloroplast and 36.5-kb mitochondrial genomes containing 80 and 33 putative protein-coding genes, respectively. The mitochondrial genome is the smallest in the Trebouxiophyceae algae studied so far. The GC content of the nuclear genome is 73%, but those of chloroplast and mitochondrial genomes are 41% and 35%, respectively. Codon usages in the organellar genomes have a different tendency from that in the nuclear genome. The organellar genomes have unique characteristics, such as the biased encoding of mitochondrial genes on a single strand and the absence of operon structures in chloroplast ribosomal genes. Medakamo hakoo will be helpful for understanding the evolution of the organellar genome and the regulation of gene expression in chloroplasts and mitochondria.