CottonGVD: A Comprehensive Genomic Variation Database for Cultivated Cottons

Cultivated cottons are the most important economic crop, which produce natural fiber for the textile industry. In recent years, the genetic basis of several essential traits for cultivated cottons has been gradually elucidated by decoding their genomic variations. Although an abundance of resequencing data is available in public, there is still a lack of a comprehensive tool to exhibit the results of genomic variations and genome-wide association study (GWAS). To assist cotton researchers in utilizing these data efficiently and conveniently, we constructed the cotton genomic variation database (CottonGVD; http://120.78.174.209/ or http://db.cngb.org/cottonGVD). This database contains the published genomic information of three cultivated cotton species, the corresponding population variations (SNP and InDel markers), and the visualized results of GWAS for major traits. Various built-in genomic tools help users retrieve, browse, and query the variations conveniently. The database also provides interactive maps (e.g., Manhattan map, scatter plot, heatmap, and linkage disequilibrium block) to exhibit GWAS and expression GWAS results. Cotton researchers could easily focus on phenotype-associated loci visualization, and they are interested in and screen for candidate genes. Moreover, CottonGVD will continue to update by adding more data and functions.

MoG+: a database of genomic variations across three mouse subspecies for biomedical research

Laboratory mouse strains have mosaic genomes derived from at least three major subspecies that are distributed in Eurasia. Here, we describe genomic variations in ten inbred strains: Mus musculus musculus-derived BLG2/Ms, NJL/Ms, CHD/Ms, SWN/Ms, and KJR/Ms; M. m. domesticus-derived PGN2/Ms and BFM/Ms; M. m. castaneus-derived HMI/Ms; and JF1/Ms and MSM/Ms, which were derived from a hybrid between M. m. musculus and M. m. castaneus. These strains were established by Prof. Moriwaki in the 1980s and are collectively named the “Mishima Battery”. These strains show large phenotypic variations in body size and in many physiological traits. We resequenced the genomes of the Mishima Battery strains and performed a comparative genomic analysis with dbSNP data. More than 81 million nucleotide coordinates were identified as variant sites due to the large genetic distances among the mouse subspecies; 8,062,070 new SNP sites were detected in this study, and these may underlie the large phenotypic diversity observed in the Mishima Battery. The new information was collected in a reconstructed genome database, termed MoG+ that includes new application software and viewers. MoG+ intuitively visualizes nucleotide variants in genes and intergenic regions, and amino acid substitutions across the three mouse subspecies. We report statistical data from the resequencing and comparative genomic analyses and newly collected phenotype data of the Mishima Battery, and provide a brief description of the functions of MoG+, which provides a searchable and unique data resource of the numerous genomic variations across the three mouse subspecies. The data in MoG+ will be invaluable for research into phenotype-genotype links in diverse mouse strains.

Global quantification exposes abundant low-level off-target activity by base editors

Base editors are dedicated engineered deaminases that enable directed conversion of specific bases in the genome or transcriptome in a precise and efficient manner, and hold promise for correcting pathogenic mutations. A major concern limiting application of this powerful approach is the issue of off-target edits. Several recent studies have shown substantial off-target RNA activity induced by base editors and demonstrated that off-target mutations may be suppressed by improved deaminases versions or optimized guide RNAs. Here we describe a new class of off-target events that are invisible to the established methods for detection of genomic variations, and were thus far overlooked. We show that much of the off-target activity of the deaminases is nonspecific, seemingly stochastic, affecting a large number of sites throughout the genome or the transcriptome and accounting for the majority of off-target activity. We develop and employ a different, complementary, approach that is sensitive to the stochastic off-targets activity, and use it to quantify the abundant off-target RNA mutations due to current optimized deaminase editors. Engineered base editors enable directed manipulation of the genome or transcriptome at single-base resolution. We believe that implementation of this computational approach would facilitate design of more specific base editors. We provide a computational tool to quantify global off-target activity, which can be used to optimize future base editors.

Dissecting the Pathogenesis of Diabetic Retinopathy Based on the Biological ceRNA Network and Genome Variation Disturbance

Background. Diabetic retinopathy (DR) is the most important manifestation of diabetic microangiopathy. It is essential to explore the gene regulatory relationship and genomic variation disturbance of biological networks in DR progression. Methods. In this study, we constructed a comprehensive lncRNA-mRNA ceRNA network of DR procession (CLMN) and explored its topological characteristics. Results. Modular and functional analysis indicated that the organization of CLMN performed fundamental and specific functions in diabetes and DR pathology. The differential expression of hub ceRNA nodes and positive correlation reveals the highly connected ceRNA regulation and important roles in the regulating of DR pathology. A large proportion of SNPs in the TFBS, DHS, and enhancer regions of lncRNAs will affect lncRNA transcription and further cause expression variation. Some SNPs were found to disrupt the lncRNA functional elements such as miRNA target binding sites. These results indicate the complex nature of genotypic effects in the disturbing of CLMN and further contribute to gene expression variation and different disease phenotypes. Conclusion. The identification of individual genomic variations and analysis of biological network disturbance by these genomic variations will help provide more personalized treatment plans and promote the development of precision medicine for DR.

Reference-agnostic representation and visualization of pan-genomes

Background The pan-genome of a species is the union of the genes and non-coding sequences present in all individuals (cultivar, accessions, or strains) within that species. Results Here we introduce PGV, a reference-agnostic representation of the pan-genome of a species based on the notion of consensus ordering. Our experimental results demonstrate that PGV enables an intuitive, effective and interactive visualization of a pan-genome by providing a genome browser that can elucidate complex structural genomic variations. Conclusions The PGV software can be installed via conda or downloaded from https://github.com/ucrbioinfo/PGV. The companion PGV browser at http://pgv.cs.ucr.edu can be tested using example bed tracks available from the GitHub page.

Diversity and Evolution of pogo and Tc1/mariner Transposons in the Apoidea Genomes

Bees (Apoidea), the largest and most crucial radiation of pollinators, play a vital role in the ecosystem balance. Transposons are widely distributed in nature and are important drivers of species diversity. However, transposons are rarely reported in important pollinators such as bees. Here, we surveyed 37 bee genomesin Apoidea, annotated the pogo and Tc1/mariner transposons in the genome of each species, and performed a phylogenetic analysis and determined their overall distribution. The pogo and Tc1/mariner families showed high diversity and low abundance in the 37 species, and their proportion was significantly higher in solitary bees than in social bees. DD34D/mariner was found to be distributed in almost all species and was found in Apis mellifera, Apis mellifera carnica, Apis mellifera caucasia, and Apis mellifera mellifera, and Euglossa dilemma may still be active. Using horizontal transfer analysis, we found that DD29-30D/Tigger may have experienced horizontal transfer (HT) events. The current study displayed the evolution profiles (including diversity, activity, and abundance) of the pogo and Tc1/mariner transposons across 37 species of Apoidea. Our data revealed their contributions to the genomic variations across these species and facilitated in understanding of the genome evolution of this lineage.

Construction and Validation of a Platinum Sensitivity Predictive Model With Multiple Genomic Variations for Epithelial Ovarian Cancer

Platinum-based chemotherapy is still the standard of care after cytoreductive surgery in the first-line treatment for epithelial ovarian cancer. This study aims to integrate novel biomarkers for predicting platinum sensitivity in EOC after initial cytoreductive surgery precisely. To this end, 60 patients were recruited from September 2014 to October 2019. Based on the duration of progress-free survival, 44 and 16 patients were assigned to platinum-sensitive and platinum-resistant group, respectively. Next generation sequencing was performed to dissect the genomic features of ovarian tumors obtained from surgery. Multiple genomic variations were compared between two groups, including single-nucleotide variant, single base or indel signature, loss of heterozygosity (LOH), whole-genome duplication (WGD), and others. The results demonstrated that patients with characteristics including positive SBS10a signature (p < 0.05), or FAM175A LOH (p < 0.01), or negative WGD (p < 0.01) were significantly enriched in platinum-sensitive group. Consistently, patients with positive SBS10a signature (15.8 vs. 10.1 months, p < 0.05), or FAM175A LOH (16.5 vs. 9.2 months, p < 0.05), or negative WGD (16.5 vs. 9.1 months, p < 0.05) have significantly longer PFS than those without these genetic features. By integrating these three biomarkers, a lasso regression model was employed to train and test for all patients, with the AUC value 0.864 in platinum sensitivity prediction. Notably, 388 ovarian cancer patients from TCGA dataset were leveraged as independent validation cohort with AUC value 0.808, suggesting the favorable performance and reliability of this model.