Biology subjects

Chebotarov, D.

Publications and source records attributed to Chebotarov, D..

8 recordsLinked to original sources

bioRxiv2025

A pan-gene catalogue of Asian cultivated rice

The rice genome underpins fundamental research and breeding, but the Nipponbare (japonica) reference does not fully encompass the genetic diversity of Asian rice. To address this gap, the Rice Population Reference Panel (RPRP) was developed, comprising high-quality assemblies of 16 rice cultivars to represent japonica, indica, aus, and aromatic varietal groups. The RPRP has been consistently annotated, supported by extensive experimental data and here we report the computational assignment, characterization and dissemination of stably identified pan-genes. We identified 25,178 core pan-genes shared across all cultivars, alongside cultivar-specific and family-enriched genes. Core genes exhibit higher gene expression and proteomic evidence, higher confidence protein domains and AlphaFold structures, while cultivar-specific genes were enriched for domains under selective breeding pressure, such as for disease resistance. This resource, integrated into public databases, enables researchers to explore genetic and functional diversity via a population-aware "reference guide" across rice genomes, advancing both basic and applied research.

genomics↗

bioRxiv2023

A meta-analysis of rice phosphoproteomics data to understand variation in cell signalling across the rice pan-genome

Phosphorylation is the most studied post-translational modification, and has multiple biological functions. In this study, we have re-analysed publicly available mass spectrometry proteomics datasets enriched for phosphopeptides from Asian rice (Oryza sativa). In total we identified 15,522 phosphosites on serine, threonine and tyrosine residues on rice proteins. We identified sequence motifs for phosphosites, and link motifs to enrichment of different biological processes, indicating different downstream regulation likely caused by different kinase groups. We cross-referenced phosphosites against the rice 3,000 genomes, to identify single amino acid variations (SAAVs) within or proximal to phosphosites that could cause loss of a site in a given rice variety. The data was clustered to identify groups of sites with similar patterns across rice family groups, for example those highly conserved in Japonica, but mostly absent in Aus type rice varieties - known to have different responses to drought. These resources can assist rice researchers to discover alleles with significantly different functional effects across rice varieties. The data has been loaded into UniProt Knowledge-Base - enabling researchers to visualise sites alongside other data on rice proteins e.g. structural models from AlphaFold2, PeptideAtlas and the PRIDE database - enabling visualisation of source evidence, including scores and supporting mass spectra.

bioinformatics↗

bioRxiv2023

HPC-based genome variant calling workflow (HPC-GVCW)

A high-performance computing genome variant calling workflow was designed to run GATK on HPC platforms. This workflow efficiently called an average of 27.3 M, 32.6 M, 168.9 M, and 16.2 M SNPs for rice, sorghum, maize, and soybean, respectively, on the most recently released high-quality reference sequences. Analysis of a rice pan-genome reference panel revealed 2.1 M novel SNPs that have yet to be publicly released.

genomics↗

bioRxiv2023

Rice Gene Index (RGI): a comprehensive pan-genome database for comparative and functional genomics of Asian rice

To integrate the genomic information of the rice pan-genome, we performed comparative analyses and established a user-friendly Rice Gene Index (RGI, https://riceome.hzau.edu.cn) platform with 16 platinum standard reference genomes and supplementary transcriptome data. To logically organize and scientifically the index of 744,233 genes among rice accessions, we detected 112,658 Ortholog Gene Indices, and provide GeneCard pages to query genomic, transcriptomic, and homology information for each gene. The RGI allows users to search for relationships and comprehensive information of genes in keyword-based, sequence-based, and relationship-based ways. Furthermore, users can visualize these relationships at local and global scales corresponding to Microcollinearity and Macrocollinearity modules.

genomics↗

bioRxiv2022

Pan-genome inversion index reveals evolutionary insights into the subpopulation structure of Asian rice (Oryza sativa)

Understanding and exploiting genetic diversity is a key factor for the productive and stable production of rice. Utilizing 16 high-quality genomes that represent the subpopulation structure of Asian rice (O. sativa), plus the genomes of two close relatives (O. rufipogon and O. punctata), we built a pan-genome inversion index of 1,054 non-redundant inversions that span an average of [~] 14% of the O. sativa cv. Nipponbare reference genome sequence. Using this index we estimated an inversion rate of 1,100 inversions per million years in Asian rice, which is 37 to 73 times higher than previously estimated for plants. Detailed analyses of these inversions showed evidence of their effects on gene regulation, recombination rate, linkage disequilibrium and agronomic trait performance. Our study uncovers the prevalence and scale of large inversions ([≥] 100 kb) across the pan-genome of Asian rice, and hints at their largely unexplored role in functional biology and crop performance.

genomics↗

bioRxiv2020

Multiple streams of genetic diversity in Japonica rice

In-depth studies on the genetic diversity of crops indicate that domestication is likely a drawn-out process that differs from the traditional representation of a simple rapid bottleneck. Asian cultivated rice provides a clear picture of multiple foundations of crop diversity. Among them, Japonica rice is likely the group derived from the first human manipulations of this species. We make use of the 3,000 Rice Genomes (3K RG) data set, first described in 2018, to explore the genetic diversity of traditional Japonica rice. After delineating introgressions from the Indica and cAus cultivar groups, we mask these traces to analyse Japonica diversity in more depth. We find differentiation between the established "temperate", "subtropical" and "tropical" subgroups, and identify stream-like traces of highly divergent sources from broad geographic ranges and subgroups. We characterize five such streams, most visible respectively in: 1) Indonesia, 2) continental Southeast Asia, 3) China, 4) uplands of Japan, and 5) Bhutan. These streams likely consist of ancient alien introgressions propagated through geneflow to different degrees. They currently appear as long genome segments conserved among specific germplasm groups, as well as shorter segments more broadly distributed across diverse germplasm along what could be adaptive corridors. They are all represented in the Japonica component of cBasmati varieties, thought to have emerged over two millennia ago. We thus provide strong evidence that Japonica, the group posited as being the most direct product of a simple domestication process in China, is an aggregate derived from multiple waves of admixture and represents a composite gene pool with ancient Asia-wide population dynamics.

genomics↗

bioRxiv2019

Twelve Platinum-Standard Reference Genomes Sequences (PSRefSeq) that complete the full range of genetic diversity of Asian rice

As the human population grows from 7.8 billion to 10 billion over the next 30 years, breeders must do everything possible to create crops that are highly productive and nutritious, while simultaneously having less of an environmental footprint. Rice will play a critical role in meeting this demand and thus, knowledge of the full repertoire of genetic diversity that exists in germplasm banks across the globe is required. To meet this demand, we describe the generation, validation and preliminary analyses of transposable element and long-range structural variation content of 12 near-gap-free reference genome sequences (RefSeqs) from representatives of 12 of 15 subpopulations of cultivated rice. When combined with 4 existing RefSeqs, that represent the 3 remaining rice subpopulations and the largest admixed population, this collection of 16 Platinum Standard RefSeqs (PSRefSeq) can be used as a pan-genome template to map resequencing data to detect virtually all standing natural variation that exists in the pan-cultivated rice genome.

genomics↗

bioRxiv2019

Predicting agronomic traits and associated genomic regions in diverse rice landraces using marker stability

To secure the worlds food supply it is essential that we improve our knowledge of the genetic underpinnings of complex agronomic traits. In this paper, we report our findings from performing trait prediction and association mapping using marker stability in diverse rice landraces. We used the least absolute shrinkage and selection operator as our marker selection algorithm, and considered twelve real agronomic traits and a hundred simulated traits using a population with approximately a hundred thousand markers. For trait prediction, we considered several statistical/machine learning methods. We found that some of the methods considered performed best when preselected markers using marker stability were used. However, our results also show that one might need to make a trade-off between model size and performance for some learning methods. For association mapping, we compared marker stability to the genome-wide efficient mixed-model analysis (GEMMA), and for the simulated traits, we found that marker stability significantly outperforms GEMMA. For the real traits, marker stability successfully identifies multiple associated markers, which often entail those selected by GEMMA. Further analysis of the markers selected for the real traits using marker stability showed that they are located in known quantitative trait loci (QTL) using the QTL Annotation Rice Online database. Furthermore, co-functional network prediction of the selected markers using RiceNet v2 also showed association to known controlling genes. We argue that a wide adoption of the marker stability approach for the prediction of agronomic traits and association mapping could improve global rice breeding efforts.

bioinformatics↗