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Genomics

Explore bioRxiv genomics preprints on sequencing, gene expression and genetic variation. Read source abstracts and verify methods in the manuscript; preprints are not peer reviewed.

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bioRxiv2019

The Tung Tree (Vernicia Fordii) Genome Provides A Resource for Understanding Genome Evolution and Oil Improvement

Tung tree (Vernicia fordii) is an economically important woody oil plant that produces tung oil containing a high proportion of eleostearic acid ([~]80%). Here we report a high-quality, chromosome-scale tung tree genome sequence of 1.12 Gb with 28,422 predicted genes and over 73% repeat sequences. Tung tree genome was assembled by combining Illumina short reads, PacBio single-molecule real-time long reads and Hi-C sequencing data. Insertion time analysis revealed that the repeat-driven tung tree genome expansion might be due to long standing long terminal repeat (LTR) retrotransposon bursts and lack of efficient DNA deletion mechanisms. An electronic fluorescent pictographic (eFP) browser was generated based on genomic and RNA-seq data from 17 various tissues and developmental stages. We identified 88 nucleotide-binding site (NBS)-encoding resistance genes, of which 17 genes may help the tung tree resist the Fusarium wilt shortly after infection. A total of 651 oil-related genes were identified and 88 of them were predicted to be directly involved in tung oil biosynthesis. The fewer phosphoenolpyruvate carboxykinase (PEPC) genes, and synergistic effects between transcription factors and oil biosynthesis-related genes may contribute to high oil content in tung seeds. The tung tree genome should provide valuable resources for molecular breeding and genetic improvement.

bioinformatics↗

bioRxiv2020

Genome Detective Coronavirus Typing Tool for rapid identification and characterization of novel coronavirus genomes

SummaryGenome Detective is a web-based, user-friendly software application to quickly and accurately assemble all known virus genomes from next generation sequencing datasets. This application allows the identification of phylogenetic clusters and genotypes from assembled genomes in FASTA format. Since its release in 2019, we have produced a number of typing tools for emergent viruses that have caused large outbreaks, such as Zika and Yellow Fever Virus in Brazil. Here, we present The Genome Detective Coronavirus Typing Tool that can accurately identify novel coronavirus (2019-nCoV) sequences isolated in China and around the world. The tool can accept up to 2,000 sequences per submission and the analysis of a new whole genome sequence will take approximately one minute. The tool has been tested and validated with hundreds of whole genomes from ten coronavirus species, and correctly classified all of the SARS-related coronavirus (SARSr-CoV) and all of the available public data for 2019-nCoV. The tool also allows tracking of new viral mutations as the outbreak expands globally, which may help to accelerate the development of novel diagnostics, drugs and vaccines. AvailabilityAvailable online: https://www.genomedetective.com/app/typingtool/cov * Contactkoen@emweb.be and deoliveira@ukzn.ac.za Supplementary informationSupplementary data is available online.

bioinformatics↗

bioRxiv2020

Comparative analysis of seven short-reads sequencing platforms using the Korean Reference Genome: MGI and Illumina sequencing benchmark for whole-genome sequencing

BackgroundMGISEQ-T7 is a new whole-genome sequencer developed by Complete Genomics and MGI utilizing DNA nanoball and combinatorial probe anchor synthesis technologies for generating short reads at a very large scale - up to 60 human genomes per day. However, it has not been objectively and systematically compared against Illumina short-read sequencers. FindingsBy using the same KOREF sample, the Korean Reference Genome, we have compared seven sequencing platforms including BGISEQ-500, MGISEQ-T7, HiSeq2000, HiSeq2500, HiSeq4000, HiSeqX10, and NovaSeq6000. We measured sequencing quality by comparing sequencing statistics (base quality, duplication rate, and random error rate), mapping statistics (mapping rate, depth distribution, and %GC coverage), and variant statistics (transition/transversion ratio, dbSNP annotation rate, and concordance rate with SNP genotyping chip) across the seven sequencing platforms. We found that MGI platforms showed a higher concordance rate of SNP genotyping than HiSeq2000 and HiSeq4000. The similarity matrix of variant calls confirmed that the two MGI platforms have the most similar characteristics to the HiSeq2500 platform. ConclusionsOverall, MGI and Illumina sequencing platforms showed comparable levels of sequencing quality, uniformity of coverage, %GC coverage, and variant accuracy, thus we conclude that the MGI platforms can be used for a wide range of genomics research fields at approximately half the cost of the Illumina platforms.

bioinformatics↗

bioRxiv2020

In silico analysis of DNA re-replication across a complete genome reveals cell-to-cell heterogeneity and genome plasticity

DNA replication is a complex and remarkably robust process: despite its inherent uncertainty, manifested through stochastic replication timing at a single-cell level, multiple control mechanisms ensure its accurate and timely completion across a population. Disruptions in these mechanisms lead to DNA re-replication, closely connected to genomic instability and oncogenesis. We present a stochastic hybrid model of DNA re-replication that accurately portrays the interplay between discrete dynamics, continuous dynamics, and uncertainty. Using experimental data on the fission yeast genome, model simulations show how different regions respond to re-replication, and permit insight into the key mechanisms affecting re-replication dynamics. Simulated and experimental population-level profiles exhibit good correlation along the genome, which is robust to model parameters, validating our approach. At a single-cell level, copy numbers of individual loci are affected by intrinsic properties of each locus, in cis effects from adjoining loci and in trans effects from distant loci. In silico analysis and single-cell imaging reveal that cell-to-cell heterogeneity is inherent in re-replication and can lead to a plethora of genotypic variations. Our thorough in silico analysis of DNA re-replication across a complete genome reveals that heterogeneity at the single cell level and robustness at the population level are emerging and co-existing principles of DNA re-replication. Our results indicate that re-replication can promote genome plasticity by generating many diverse genotypes within a population, potentially offering an evolutionary advantage in cells with aberrations in replication control mechanisms.

systems biology↗

bioRxiv2020

Metagenome-Assembled Genome Binning Methods Disproportionately Fail for Plasmids and Genomic Islands

Metagenomic methods are an important tool in the life sciences, as they enable simultaneous characterisation of all microbes in a community without time-consuming and bias-inducing culturing. Metagenome-assembled genome (MAG) binning methods have emerged as a promising approach to recover individual genomes from metagenomic data. However, MAG binning has not been well assessed for its ability to recover mobile genetic elements (MGEs), such as plasmids and genomic islands (GIs), that have very high clinical/agricultural/environmental importance. Certain antimicrobial resistance (AMR) genes and virulence factor (VF) genes are noted to be disproportionately associated with MGEs, making studying their transmission a public health priority. However, the variable copy number and sequence composition of MGEs relative to the majority of the host genome makes them potentially problematic for MAG binning methods. To systematically investigate this, we simulated a low-complexity metagenome comprising 30 GI-rich and plasmid-containing bacterial genomes. MAGs were then recovered using 12 current prediction pipelines and evaluated for recovery of MGE-associated AMR/VF genes. Here we show that while 82-94% of chromosomes could be correctly recovered and binned, only 38-44% of GIs were recovered and, even more notably, only 1-29% of plasmid sequences were found. Most strikingly, no plasmid-borne VF or AMR genes were recovered and within GIs, only between 0-45% of AMR or VF genes were identified. We conclude that short-read MAGs are largely ineffective for the analysis of mobile genes, including those of public-health importance like AMR and VF genes. We propose that microbiome researchers should instead primarily utilise unassembled short reads and/or long-read approaches to more accurately analyse metagenomic data

bioinformatics↗

bioRxiv2020

CoV Genome Tracker: tracing genomic footprints of Covid-19 pandemic

SummaryGenome sequences constitute the primary evidence on the origin and spread of the 2019-2020 Covid-19 pandemic. Rapid comparative analysis of coronavirus SARS-CoV-2 genomes is critical for disease control, outbreak forecasting, and developing clinical interventions. CoV Genome Tracker is a web portal dedicated to trace Covid-19 outbreaks in real time using a haplotype network, an accurate and scalable representation of genomic changes in a rapidly evolving population. We resolve the direction of mutations by using a bat-associated genome as outgroup. At a broader evolutionary time scale, a companion browser provides gene-by-gene and codon-by-codon evolutionary rates to facilitate the search for molecular targets of clinical interventions. Availability and ImplementationCoV Genome Tracker is publicly available at http://cov.genometracker.org and updated weekly with the data downloaded from GISAID (http://gisaid.org). The website is implemented with a custom JavaScript script based on jQuery (https://jquery.com) and D3-force (https://github.com/d3/d3-force). Contactweigang@genectr.hunter.cuny.edu, City University of New York, Hunter College Supplementary InformationAll supporting scripts developed in JavaScript, Python, BASH, and PERL programming languages are available as Open Source at the GitHub repository https://github.com/weigangq/cov-browser.

evolutionary biology↗

bioRxiv2020

Horseshoe crab genomes reveal the evolutionary fates of genes and microRNAs after three rounds (3R) of whole genome duplication

Whole genome duplication (WGD) has occurred in relatively few sexually reproducing invertebrates. Consequently, the WGD that occurred in the common ancestor of horseshoe crabs ~135 million years ago provides a rare opportunity to decipher the evolutionary consequences of a duplicated invertebrate genome. Here, we present a high-quality genome assembly for the mangrove horseshoe crab Carcinoscorpius rotundicauda (1.7Gb, N50 = 90.2Mb, with 89.8% sequences anchored to 16 pseudomolecules, 2n = 32), and a resequenced genome of the tri-spine horseshoe crab Tachypleus tridentatus (1.7Gb, N50 = 109.7Mb). Analyses of gene families, microRNAs, and synteny show that horseshoe crabs have undergone three rounds (3R) of WGD, and that these WGD events are shared with spiders. Comparison of the genomes of C. rotundicauda and T. tridentatus populations from several geographic locations further elucidates the diverse fates of both coding and noncoding genes. Together, the present study represents a cornerstone for a better understanding of the consequences of invertebrate WGD events on evolutionary fates of genes and microRNAs at individual and population levels, and highlights the genetic diversity with practical values for breeding programs and conservation of horseshoe crabs.

evolutionary biology↗

bioRxiv2020

RefKA: A fast and efficient long-read genome assembly approach for large and complex genomes

Recent advances in long-read sequencing have the potential to produce more complete genome assemblies using sequence reads which can span repetitive regions. However, overlap based assembly methods routinely used for this data require significant computing time and resources. Here, we have developed RefKA, a reference-based approach for long read genome assembly. This approach relies on breaking up a closely related reference genome into bins, aligning k-mers unique to each bin with PacBio reads, and then assembling each bin in parallel followed by a final bin-stitching step. During benchmarking, we assembled the wheat Chinese Spring (CS) genome using publicly available PacBio reads in parallel in 168 wall hours on a 250 CPU system. The maximum RAM used was 300 Gb and the computing time was 42,000 CPU hours. The approach opens applications for the assembly of other large and complex genomes with much-reduced computing requirements. The RefKA pipeline is available at https://github.com/AppliedBioinformatics/RefKA

bioinformatics↗

bioRxiv2021

Influenza A virus defective viral genomes are inefficiently packaged into virions relative to wild-type genomic RNAs

Deletion-containing viral genomes (DelVGs) are commonly produced during influenza A virus infection and have been implicated in influencing clinical infection outcomes. Despite their ubiquity, the specific molecular mechanisms that govern DelVG formation and their packaging into defective interfering particles (DIPs) remain poorly understood. Here, we utilized next-generation sequencing to analyze DelVGs that form de novo early during infection, prior to packaging. Analysis of these early DelVGs revealed that deletion formation occurs in clearly defined hotspots and is significantly associated with both direct sequence repeats and enrichment of adenosine and uridine bases. By comparing intracellular DelVGs with those packaged into extracellular virions, we discovered that DelVGs face a significant bottleneck during genome packaging relative to wild type genomic RNAs. Surprisingly, packaged DelVGs exhibited no signs of enrichment for specific deletion characteristics suggesting that all DelVGs are equally limited in packaging efficiency. Our data provide the first unbiased, high-resolution portrait of the diversity of DelVGs that are generated by the IAV replication machinery and shed light on the mechanisms that underly DelVG formation. ImportanceDefective interfering particles (DIPs) are commonly produced by RNA viruses and have been implicated in modulating clinical infection outcomes, hence, there is increasing interest in the potential of DIPs as antiviral therapeutics. For influenza viruses, DIPs are formed by the packaging of genomic RNAs harboring internal deletions. Despite decades of study, the mechanisms that drive the formation of these deletion-containing viral genomes (DelVGs) remain elusive. Here, we used a specialized sequencing pipeline to characterize the first wave of DelVGs that form during influenza virus infection. This dataset provides an unbiased profile of the deletion-forming preferences of the influenza virus replicase. Additionally, by comparing the early intracellular DelVGs with those that get packaged into extracellular virions, we described a significant segment-specific bottleneck that limits DelVG packaging relative to wild type viral RNAs. Altogether, these findings reveal factors that govern the production of both DelVGs and DIPs during influenza virus infection.

microbiology↗

bioRxiv2021

Genomic islands targeting dusA in Vibrio species are distantly related to Salmonella Genomic Island 1 and mobilizable by IncC conjugative plasmids

Salmonella Genomic Island 1 (SGI1) and its variants are significant contributors to the spread of antibiotic resistance among Gammaproteobacteria. All known SGI1 variants integrate at the 3 end of trmE, a gene coding for a tRNA modification enzyme. SGI1 variants are mobilized specifically by conjugative plasmids of the incompatibility groups A and C (IncA and IncC). Using a comparative genomics approach based on genes conserved among members of the SGI1 group, we identified diverse integrative elements distantly related to SGI1 in several species of Vibrio, Aeromonas, Salmonella, Pokkaliibacter, and Escherichia. Unlike SGI1, these elements target two alternative chromosomal loci, the 5 end of dusA and the 3 end of yicC. Although they share many features with SGI1, they lack antibiotic resistance genes and carry alternative integration/excision modules. Functional characterization of IMEVchUSA3, a dusA-specific integrative element, revealed promoters that respond to AcaCD, the master activator of IncC plasmid transfer genes. Quantitative PCR and mating assays confirmed that IMEVchUSA3 excises from the chromosome and is mobilized by an IncC helper plasmid from Vibrio cholerae to Escherichia coli. IMEVchUSA3 encodes the AcaC homolog SgaC that associates with AcaD to form a hybrid activator complex AcaD/SgaC essential for its excision and mobilization. We identified the dusA-specific recombination directionality factor RdfN required for the integrase-mediated excision of dusA-specific elements from the chromosome. Like xis in SGI1, rdfN is under the control of an AcaCD-responsive promoter. Although the integration of IMEVchUSA3 disrupts dusA, it provides a new promoter sequence and restores the reading frame of dusA for proper expression of the tRNA-dihydrouridine synthase A. Phylogenetic analysis of the conserved proteins encoded by SGI1-like elements targeting dusA, yicC, and trmE gives a fresh perspective on the possible origin of SGI1 and its variants. Author summaryWe identified integrative elements distantly related to the Salmonella Genomic Island 1 (SGI1), a key vector of antibiotic resistance genes in Gammaproteobacteria. SGI1 and its variants reside at the 3 end of trmE, share a large, highly conserved core of genes, and carry a complex integron that confers multidrug resistance phenotypes to their hosts. Unlike members of the SGI1 group, these novel genomic islands target the 5 end dusA or the 3 end of yicC, lack multidrug resistance genes, and seem much more diverse. We showed here that, like SGI1, these elements are mobilized by conjugative plasmids of the IncC group. Based on comparative genomics and functional analyses, we propose a hypothetical model of the evolution of SGI1 and its siblings from the progenitor of IncA and IncC conjugative plasmids via an intermediate dusA-specific integrative element through gene losses and gain of alternative integration/excision modules.

microbiology↗

bioRxiv2021

SemiBin: Incorporating information from reference genomes with semi-supervised deep learning leads to better metagenomic assembled genomes (MAGs)

Metagenomic binning is the step in building metagenome-assembled genomes (MAGs) when sequences predicted to originate from the same genome are automatically grouped together. The most widely-used methods for binning are reference-independent, operating de novo and allow the recovery of genomes from previously unsampled clades. However, they do not leverage the knowledge in existing databases. Here, we propose SemiBin, an open source tool that uses neural networks to implement a semi-supervised approach, i.e. SemiBin exploits the information in reference genomes, while retaining the capability of binning genomes that are outside the reference dataset. SemiBin outperforms existing state-of-the-art binning methods in simulated and real microbiome datasets across three different environments (human gut, dog gut, and marine microbiomes). SemiBin returns more high-quality bins with larger taxonomic diversity, including more distinct genera and species. SemiBin is available as open source software at https://github.com/BigDataBiology/SemiBin/.

bioinformatics↗

bioRxiv2022

Genome-wide analyses of PAM-relaxed Cas9 genome editors reveal substantial off-target effects by ABE8e in rice

PAM-relaxed Cas9 nucleases, cytosine base editors and adenine base editors are promising tools for precise genome editing in plants. However, their genome-wide off-target effects are largely undetermined. Here, we conduct whole-genome sequencing (WGS) analyses of transgenic plants edited by xCas9, Cas9-NGv1, Cas9-NG, SpRY, nCas9-NG-PmCDA1, nSpRY-PmCDA1 and nSpRY-ABE8e in rice. Our results reveal different guide RNA (gRNA)-dependent off-target effects with different editors. De novo generated new gRNAs by SpRY editors lead to additional but not substantial off-target mutations. Strikingly, ABE8e results in ~500 genome-wide A-to-G off-target mutations at TA motif sites per transgenic plant. The preference of the TA motif by ABE8e is also observed at the target sites. Finally, we investigate the timeline and mechanism of somaclonal variation due to tissue culture, which chiefly contributes to the background mutations. This study provides a comprehensive understanding on the scales and mechanisms of off-target and background mutations during PAM-relaxed genome editing in plants.

genetics↗

bioRxiv2022

Genome-wide analyses of histone modifications and chromatin accessibility reveal the distinct genomic compartments in the Irish potato famine pathogen Phytophthora infestans

Phytophthora infestans, the causal agent of potato late blight, is a devastating plant disease that leads to Irish potato famine and threatens world-wide food security. Despite the genome of P. infestans has provided fundamental resource for studying the aggressiveness of this pandemic pathogen, the epigenomes remain poorly understood. Here, utilizing liquid chromatography-tandem mass spectrometry (LC-MS/MS), we demonstrate post-translational modifications (PTM) at P. infestans core histone H3. The PTMs not only include these prevalent modifications in eukaryotes, and also some novel marks, such as H3K53me2 and H3K122me3. We focused on the trimethylations of H3K4, H3K9 and H3K27 and H3K36, and profiled P. infestans epigenomes employing Native Chromatin Immunoprecipitation followed by sequencing (N-ChIP-seq). In parallel, we mapped P. infestans chromomatin accessibility by Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq). We found that adaptive genomic compartments display significantly higher levels of H3K9me3 and H3K27me3, and are generally in condense chromatin. Interestingly, we observed that genes encoding virulence factors, such as effectors, are enriched in open chromatin regions that barely have the four histone modifications. With a combination of genomic, epigenomic, transcriptomic strategies, our study illustrates the epigenetic states in P. infestans, which will help to study genomic functions and regulations in this pathogen. Author summaryEpigenetics play an important role in various biological processes of eukaryotes, including pathogenicity of plant pathogens. However, the epigenetic landscapes are marginally known in oomycetes that are fungal-like organisms and comprise lots of destructive plant pathogens. In this study, using the Irish potato famine pathogen Phytophthora infestans as a model, we conducted genome-wide studies of histone post modifications and chromatin accessibility, and demonstrate the relationship of gene expression and evolution with the epigenetic marks. We found that one of the most important classes of virulence proteins, effectors, are enriched in open chromatin regions that barely have eu- and hetero-chromatic marks. This study provides an overview of the oomycete epigenetic atlas, and advances our understanding of the regulation of virulence factors in plant pathogens.

microbiology↗

bioRxiv2022

Using landscape genomics to infer genomic regions involved in environmental adaptation of soybean genebank accessions

Understanding how crops adapt to specific environmental conditions is becoming increasingly important in the face of accelerating climate change, but the genetics of local adaptation remain little understood for many crops. Landscape genomics can reveal patterns of genetic variation that indicate adaptive diversification during crop evolution and dispersal. Here, we examine genetic differentiation and association signatures with environmental gradients in soybean (Glycine max) germplasm groups from China that were inferred from the USDA Soybean Germplasm Collection (N = 17,019 accessions) based on population structure and passport information. We recover genes previously known to be involved in soybean environmental adaptation and report numerous new candidate genes in selection signatures implicated by genomic resources such as the genome annotation and gene expression datasets to function in flowering regulation, photoperiodism and stress reaction cascades. Linkage disequilibrium network analysis suggested functional relationships between genomic regions with selection signatures, consistent with the polygenic nature of environmental adaptation. We tested whether haplotypes associated with environmental adaptation in China were present in 843 North American and 160 European soybean cultivars and found that haplotypes in major genes for early maturity have been selected during breeding, but also that a large number of haplotypes exhibiting putative adaptive variation for cold regions at high latitudes are underrepresented in modern cultivars. Our results demonstrate the value of landscape genomics analysis in genebank germplasm as a starting point for the study of crop environmental adaptation and have the potential to inform future research efforts focused on improved soybean adaptation. Functional validation of candidate genes will support understanding of their adaptive roles and likely enable the transfer of beneficial adaptive variation into modern breeding germplasm.

plant biology↗

bioRxiv2022

Ultra-high-throughput microbial single-cell whole genome sequencing for genome-resolved metagenomics

Microbes exist widely in nature. However, less than 1% of the species of microorganisms have been discovered so far, and more than 99% of microorganisms still remain unknown, which is called microbial dark matter. Unravelling microbial dark matter is not only helpful for exploring the unknown microbial world, but also of great significance for human health research. Ever since a long time ago, due to technical limitations, the microbiome, to a great extent, is still a black box. The traditional population-based metagenomic analysis tools are without single microbial resolution and they are stretched when studying rare and unknown microbial species. Here, we use high-throughput microdroplet technology to achieve the whole genome amplification of microbial single-cell genomes in pico-litter sized microdroplets, and develop subsequent library preparation steps such as indexing of the genome, to achieve the development of ultra-high-throughput microbial single-cell whole genome sequencing for genome-resolved metagenomics, aiming to provide a powerful new weapon for exploring microbial dark matter and other microbiological studies.

microbiology↗

bioRxiv2022

Genome-wide association and genomic prediction of growth traits in the European flat oyster (Ostrea edulis)

The European flat oyster (Ostrea edulis) is a bivalve mollusc that was once widely distributed in Europe and represented an important food resource for humans for centuries. Populations of O. edulis experienced a severe decline across their biogeographic range mainly due to anthropogenic activities and disease outbreaks. To restore the economic and ecological benefits of European flat oyster populations, extensive protection and restoration efforts are in place within Europe. In line with the increasing interest in supporting restoration and oyster farming through the breeding of stocks with enhanced performance, the present study aimed to evaluate the potential of genomic selection for improving growth traits in a European flat oyster population obtained from successive mass-spawning events. Four growth-related traits were evaluated: total weight (TW), shell height (SH), shell width (SW) and shell length (SL). The heritability of the growth traits was moderate-low, with estimates of 0.45, 0.37, 0.22, and 0.32 for TW, SH, SW and SL, respectively. A genome-wide association analysis revealed a largely polygenic genetic architecture for the four growth traits, with two distinct QTLs detected on chromosome 4. To investigate whether genomic selection can be implemented in flat oyster breeding at a reduced cost, the utility of low-density SNP panels (down to 100 SNPs) was assessed. Genomic prediction accuracies using the full density panel were high (>0.83 for all traits). The evaluation of the effect of reducing the number of markers used to predict genomic breeding values revealed that similar selection accuracies could be achieved for all traits with 2K SNPs as for a full panel containing 4,577 SNPs. Only slight reductions in accuracies were observed at the lowest SNP density tested (i.e. 100 SNPs), likely due to a high relatedness between individuals being included in the training and validation sets during cross-validation. Overall, our results suggest that the genetic improvement of growth traits in oysters is feasible. Nevertheless, and although low-density SNP panels appear as a promising strategy for applying GS at a reduced cost, additional populations with different degrees of genetic relationship should be assessed to derive estimates of prediction accuracies to be expected in practical breeding programmes.

genetics↗

bioRxiv2022

OpenGenomeBrowser: A versatile, dataset-independent and scalable web platform for genome data management and comparative genomics

OpenGenomeBrowser is a self-hostable open-source platform that manages access to genomic data and drastically simplifies comparative genomics analyses. It enables users to interactively generate phylogenetic trees, compare gene loci, browse biochemical pathways, perform gene trait matching, create dot plots, execute BLAST searches, and access the data. It features a flexible user management system, and its modular folder structure enables the organization of genomic data and metadata, and to automate analyses. We tested OpenGenomeBrowser with bacterial, archaeal and yeast genomes. The largest instance currently contains over 1,400 bacterial genomes. Source code, documentation, tutorials and a demo server are available at opengenomebrowser.github.io.

bioinformatics↗

bioRxiv2022

Incorporating genome-wide association study results into genomic prediction enhances the predictive ability of growth and phenology traits in Norway spruce

Genomic prediction (GP) or genomic selection is a method to predict the accumulative effect of all quantitative trait loci (QTLs) effects by capturing the linkage disequilibrium between markers and QTLs. Thus, marker preselection is considered a promising method to capture Mendelian segregation effects, especially for an oligogenic trait. Using QTLs detected in the genome-wide association study (GWAS) could improve genomic prediction, including informative marker selection and adding a QTL with the largest effect size as a fixed effect. Here, we performed GWAS and genomic selection studies in a population with 904 clones from 32 full-sib families using a newly developed 50k SNP Norway spruce array. In total, GWAS identified 41 SNPs associated with budburst stage (BB) and the SNP with the largest effect size explained 5.1% of the phenotypic variation (PVE). For the other five traits like growth and wood quality traits, only 2 - 13 SNPs were detected and PVE of the strongest effects ranged from 1.2% to 2.0%. GP with approximately 100 preselected SNPs based on the smallest p-values from GWAS showed the largest predictive ability (PA) for the oligogenic trait BB. But for the other polygenic traits, approximate 2000-4000 preselected SNPs, indicated by the smallest Akaike information criterion to offer the best model fit, still resulted in PA being similar to that of GP models using all markers. Analyses on both real-life and simulated data also showed that the inclusion of a large QTL SNP in the model as a fixed effect could improve PA and accuracy of GP provided that the PVE of the QTL was [≥]2.5%.

genetics↗