Comparative Chloroplast Genome Analyses of the Winter-Blooming Eastern Asian Endemic Genus Chimonanthus (Calycanthaceae) With Implications For Its Phylogeny and Diversification

Chimonanthus of Calycanthaceae is a small endemic genus in China, with unusual winter-blooming sweet flowers widely cultivated for ornamentals and medicinal uses. The evolution of Chimonanthus plastomes and its phylogenetic relationships remain unresolved due to limited availability of genetic resources. Here, we report fully assembled and annotated chloroplast genomes of five Chimonanthus species. The chloroplast genomes of the genus (size range 153,010 – 153,299 bp) reveal high similarities in gene content, gene order, GC content, codon usage, amino acid frequency, simple sequence repeats, oligonucleotide repeats, synonymous and non-synonymous substitutions, and transition and transversion substitutions. Signatures of positive selection are detected in atpF and rpoB genes in C. campanulatus. The correlations among substitutions, InDels, and oligonucleotide repeats reveal weak to strong correlations in distantly related species at the intergeneric levels, and very weak to weak correlations among closely related Chimonanthus species. Chloroplast genomes are used to reconstruct a well-resolved phylogenetic tree, which supports the monophyly of Chimonanthus. Within Chimonanthus, C. praecox and C. campanulatus form one clade, while C. grammatus, C. salicifolius, C. zhejiangensis, and C. nitens constitute another clade. Chimonanthus nitens appears paraphyletic and is closely related to C. salicifolius and C. zhejiangensis, suggesting the need to reevaluate the species delimitation of C. nitens. Chimonanthus and Calycanthus diverged in mid-Oligocene; the radiation of extant Chimonanthus species was dated to the mid-Miocene, while C. grammatus diverged from other Chimonanthus species in the late Miocene. C. salicifolius, C. nitens(a), and C. zhejiangensis are inferred to have diverged in the Pleistocene of the Quaternary period, suggesting recent speciation of a relict lineage in the subtropical forest regions in eastern China. This study provides important insights into the chloroplast genome features and evolutionary history of Chimonanthus and family Calycanthaceae.

A high-quality fungal genome assembly resolved from a sample accidentally contaminated by multiple taxa

Contamination in sequenced genomes is a relatively common problem and several methods to remove non-target sequences have been devised. Typically, the target and contaminating organisms reside in different kingdoms, simplifying their separation. The authors present the case of a genome for the ascomycete fungus Teratosphaeria eucalypti, contaminated by another ascomycete fungus and a bacterium. Approaching the problem as a low-complexity metagenomics project, the authors used two available software programs, BlobToolKit and anvi'o, to filter the contaminated genome. Both the de novo and reference-assisted approaches yielded a high-quality draft genome assembly for the target fungus. Incorporating reference sequences increased assembly completeness and visualization elucidated previously unknown genome features. The authors suggest that visualization should be routine in any sequencing project, regardless of suspected contamination.

Prediction and Analysis in silico of Genomic Islands in Aeromonas hydrophila

Aeromonas are Gram-negative rods widely distributed in the environment. They can cause severe infections in fish related to financial losses in the fish industry, and are considered opportunistic pathogens of humans causing infections ranging from diarrhea to septicemia. The objective of this study was to determine in silico the contribution of genomic islands to A. hydrophila. The complete genomes of 17 A. hydrophila isolates, which were separated into two phylogenetic groups, were analyzed using a genomic island (GI) predictor. The number of predicted GIs and their characteristics varied among strains. Strains from group 1, which contains mainly fish pathogens, generally have a higher number of predicted GIs, and with larger size, than strains from group 2 constituted by strains recovered from distinct sources. Only a few predicted GIs were shared among them and contained mostly genes from the core genome. Features related to virulence, metabolism, and resistance were found in the predicted GIs, but strains varied in relation to their gene content. In strains from group 1, O Ag biosynthesis clusters OX1 and OX6 were identified, while strains from group 2 each had unique clusters. Metabolic pathways for myo-inositol, L-fucose, sialic acid, and a cluster encoding QueDEC, tgtA5, and proteins related to DNA metabolism were identified in strains of group 1, which share a high number of predicted GIs. No distinctive features of group 2 strains were identified in their predicted GIs, which are more diverse and possibly better represent GIs in this species. However, some strains have several resistance attributes encoded by their predicted GIs. Several predicted GIs encode hypothetical proteins and phage proteins whose functions have not been identified but may contribute to Aeromonas fitness. In summary, features with functions identified on predicted GIs may confer advantages to host colonization and competitiveness in the environment.

R-Loop Tracker: Web Access-Based Tool for R-Loop Detection and Analysis in Genomic DNA Sequences

R-loops are common non-B nucleic acid structures formed by a three-stranded nucleic acid composed of an RNA–DNA hybrid and a displaced single-stranded DNA (ssDNA) loop. Because the aberrant R-loop formation leads to increased mutagenesis, hyper-recombination, rearrangements, and transcription-replication collisions, it is regarded as important in human diseases. Therefore, its prevalence and distribution in genomes are studied intensively. However, in silico tools for R-loop prediction are limited, and therefore, we have developed the R-loop tracker tool, which was implemented as a part of the DNA Analyser web server. This new tool is focused upon (1) prediction of R-loops in genomic DNA without length and sequence limitations; (2) integration of R-loop tracker results with other tools for nucleic acids analyses, including Genome Browser; (3) internal cross-evaluation of in silico results with experimental data, where available; (4) easy export and correlation analyses with other genome features and markers; and (5) enhanced visualization outputs. Our new R-loop tracker tool is freely accessible on the web pages of DNA Analyser tools, and its implementation on the web-based server allows effective analyses not only for DNA segments but also for full chromosomes and genomes.

A Portrait of Intratumoral Genomic and Transcriptomic Heterogeneity at Single-Cell Level in Colorectal Cancer

In the study of cancer, omics technologies are supporting the transition from traditional clinical approaches to precision medicine. Intra-tumoral heterogeneity (ITH) is detectable within a single tumor in which cancer cell subpopulations with different genome features coexist in a patient in different tumor areas or may evolve/differ over time. Colorectal carcinoma (CRC) is characterized by heterogeneous features involving genomic, epigenomic, and transcriptomic alterations. The study of ITH is a promising new frontier to lay the foundation towards successful CRC diagnosis and treatment. Genome and transcriptome sequencing together with editing technologies are revolutionizing biomedical research, representing the most promising tools for overcoming unmet clinical and research challenges. Rapid advances in both bulk and single-cell next-generation sequencing (NGS) are identifying primary and metastatic intratumoral genomic and transcriptional heterogeneity. They provide critical insight in the origin and spatiotemporal evolution of genomic clones responsible for early and late therapeutic resistance and relapse. Single-cell technologies can be used to define subpopulations within a known cell type by searching for differential gene expression within the cell population of interest and/or effectively isolating signal from rare cell populations that would not be detectable by other methods. Each single-cell sequencing analysis is driven by clustering of cells based on their differentially expressed genes. Genes that drive clustering can be used as unique markers for a specific cell population. In this review we analyzed, starting from published data, the possible achievement of a transition from clinical CRC research to precision medicine with an emphasis on new single-cell based techniques; at the same time, we focused on all approaches and issues related to this promising technology. This transition might enable noninvasive screening for early diagnosis, individualized prediction of therapeutic response, and discovery of additional novel drug targets.

Genome survey sequencing of common vetch (Vicia sativa L.) and genetic diversity analysis of Chinese germplasm with genomic SSR markers

Background Common vetch (Vicia sativa L.) is an annual legume with excellent suitability in cold and dry regions. Despite its great applied potential, the genomic information regarding common vetch currently remains unavailable. Methods and results In the present study, the whole genome survey of common vetch was performed using the next-generation sequencing (NGS). A total of 79.84 Gbp high quality sequence data were obtained and assembled into 3,754,145 scaffolds with an N50 length of 3556 bp. According to the K-mer analyses, the genome size, heterozygosity rate and GC content of common vetch genome were estimated to be 1568 Mbp, 0.4345 and 35%, respectively. In addition, a total of 76,810 putative simple sequence repeats (SSRs) were identified. Among them, dinucleotide was the most abundant SSR type (44.94%), followed by Tri- (35.82%), Tetra- (13.22%), Penta- (4.47%) and Hexanucleotide (1.54%). Furthermore, a total of 58,175 SSR primer pairs were designed and ten of them were validated in Chinese common vetch. Further analysis showed that Chinese common vetch harbored high genetic diversity and could be clustered into two main subgroups. Conclusion This is the first report about the genome features of common vetch, and the information will help to design whole genome sequencing strategies. The newly identified SSRs in this study provide basic molecular markers for germplasm characterization, genetic diversity and QTL mapping studies for common vetch.

Diversity, function and evolution of aquatic vertebrate genomes

Aquatic vertebrates consist of jawed fish (cartilaginous fish and bony fish), aquatic mammals, reptiles and amphibians. Here, we present a comprehensive analysis of 630 aquatic vertebrate genomes to generate a standardized compendium of genomic data. We demonstrate its value by assessing their genome features as well as illuminating gene families related to the transition from water to land, such as Hox genes and olfactory receptor genes. We found that LINEs are the major transposable element (TE) type in cartilaginous fish and aquatic mammals, while DNA transposons are the dominate type in bony fish. To our surprise, TE types are not fixed in amphibians, the first group that transitioned to living on land. These results illustrate the value of a unified resource for comparative genomic analyses of aquatic vertebrates. Our data and strategy are likely to support all evolutionary and ecological research on vertebrates.

Genome features and antibiotic resistance of Pseudomonas aeruginosa strains isolated in patients with cystic fibrosis in the Russian Federation

Cystic fibrosis (CF) is a common genetic disease, manifested by airway obstruction and chronic respiratory infection. The most prevalent infectious agent in airways of CF patients is Pseudomonas aeruginosa. This study aimed to determine sequence-types, antimicrobial resistance phenotypes and genes defining adaptive antibiotic resistance in P. aeruginosa isolates recovered from CF patients in Russia. In total, 84 P. aeruginosa strains from 64 CF patients were analyzed. Susceptibility to antibiotics was determined by disk diffusion test. Whole-genome sequencing (WGS) was performed on MGISEQ-2000 platform. SPAdes software, Galaxy, ResFinder, PubMLST were used for analysis of WGS data. Examined P. aeruginosa isolates belonged to 53 different sequence-types (STs), including 6 new STs. High-risk epidemic clone ST235 (10%) and clonal CF P. aeruginosa strains ST17, ST242, ST274 (7%) were detected. Non-susceptibility to ticarcillin-clavulanate, cefepime, imipenem was observed in 63%, 12% and 25% of isolates, respectively; to tobramycin - in 24%, to amikacin - in 35%; to ciprofloxacin, levofloxacin - in 35% and 57% of strains, respectively. Multidrug-resistant phenotype was detected in 18% of isolates. In examined strains, genes of beta-lactamases VIM-2 (5 ST235 strains), VEB-1 (two ST2592 strains), GES-1 (1 ST235 strain), PER-1 (1 ST235 strain) were found. Ciprofloxacin-modifying enzyme CrpP gene was detected in 67% of isolates, aminoglycoside-modifying enzymes AAD, ANT, AAC genes - in 7%, 4%, 12% of strains, respectively. P. aeruginosa isolates from CF patients in Russia demonstrate a high clonal diversity, which is similar to other P. aeruginosa infections. The isolates of high-risk clone and clonal CF P. aeruginosa strains are detected.

Mitochondrial and Plastid Genomes of the Monoraphid Diatom Schizostauron trachyderma

We provide for the first time the complete plastid and mitochondrial genomes of a monoraphid diatom: Schizostauron trachyderma. The mitogenome is 41,957 bp in size and displays two group II introns in the cox1 gene. The 187,029 bp plastid genome features the typical quadripartite architecture of diatom genomes. It contains a group II intron in the petB gene that overlaps the large single-copy and the inverted repeat region. There is also a group IB4 intron encoding a putative LAGLIDADG homing endonuclease in the rnl gene. The multigene phylogenies conducted provide more evidence of the proximity between S. trachyderma and fistula-bearing species of biraphid diatoms.

Multiscale and integrative single-cell Hi-C analysis with Higashi

Single-cell Hi-C (scHi-C) can identify cell-to-cell variability of three-dimensional (3D) chromatin organization, but the sparseness of measured interactions poses an analysis challenge. Here we report Higashi, an algorithm based on hypergraph representation learning that can incorporate the latent correlations among single cells to enhance overall imputation of contact maps. Higashi outperforms existing methods for embedding and imputation of scHi-C data and is able to identify multiscale 3D genome features in single cells, such as compartmentalization and TAD-like domain boundaries, allowing refined delineation of their cell-to-cell variability. Moreover, Higashi can incorporate epigenomic signals jointly profiled in the same cell into the hypergraph representation learning framework, as compared to separate analysis of two modalities, leading to improved embeddings for single-nucleus methyl-3C data. In an scHi-C dataset from human prefrontal cortex, Higashi identifies connections between 3D genome features and cell-type-specific gene regulation. Higashi can also potentially be extended to analyze single-cell multiway chromatin interactions and other multimodal single-cell omics data.