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bioRxiv2022

Oat chromosome and genome evolution defined by widespread terminal intergenomic translocations in polyploids

Structural chromosome rearrangements involving translocations, fusions and fissions lead to evolutionary variation between species and potentially reproductive isolation and variation in gene expression. While the wheats (Triticeae, Poaceae) and oats (Aveneae) all maintain a basic chromosome number of x=7, genomes of oats show frequent intergenomic translocations, in contrast to wheats where these translocations are relatively rare. We aimed to show genome structural diversity and genome relationships in tetraploid, hexaploid and octoploid Avena species and amphiploids, establishing patterns of intergenomic translocations across different oat taxa using fluorescence in situ hybridization (FISH) with four well-characterized repetitive DNA sequences: pAs120, AF226603, Ast-R171 and Ast-T116. In A. agadiriana (2n=4x=28), the selected probes hybridized to all chromosomes indicating that this species originated from one (autotetraploid) or closely related ancestors with the same genomes. Hexaploid amphiploids were confirmed as having the genomic composition AACCDD, while octoploid amphiploids showed three different genome compositions: AACCCCDD, AAAACCDD or AABBCCDD. The A, B, C, and D genomes of oats differ significantly in their involvement in non-centromeric, intercalary translocations. There was a predominance of distal intergenomic translocations from the C-into the D-genome chromosomes. Translocations from A- to C-, or D- to C-genome chromosomes were less frequent, proving that at least some of the translocations in oat polyploids are non-reciprocal. Rare translocations from A- to D-, D- to A- and C- to B-genome chromosomes were also visualized. The fundamental research has implications for exploiting genomic biodiversity in oat breeding to through introgression from wild species potentially with contrasting chromosomal structures and hence deleterious segmental duplications or large deletions in amphiploid parental lines.

plant biology↗

bioRxiv2022

Modular gene interactions drive modular pan-genome evolution in bacteria.

Depending on the scale of observation, bacterial genomes are both organized and fluid. While individual bacterial genomes show signatures of organization (e.g., operons), pan-genomes reveal genome fluidity, both in terms of gene content and order (synteny). Here we ask how mutational forces (including recombination and horizontal gene transfer) combine with selection and gene interactions to shape genome organization and variation both within and across strains. We first build an evolutionary simulation model to assess the impact of gene interactions on pan-genome structure. A neutral evolutionary model can produce transient co-segregation of initially linked genes but is vulnerable on longer time-scales to perturbing mutational events. In contrast, incorporation of modular gene fitness interactions can produce sustainable clusters of linked and co-segregating genes, with the network of co-segregation recapitulating the defined simulation ground-truth network of gene interactions. To test our model predictions, we exploit the increasing number of closed genomes in model species to define gene co-segregation networks in the pan-genomes of Escherichia coli and Pseudomonas aeruginosa. Using these highly curated pan-genomes, we identify modular clusters of physically linked and co-segregating genes and show that the resulting co-segregation networks map onto underlying gene-regulatory and metabolic gene interaction networks. The results imply that co-segregation networks can contribute to accessory genome annotation, and more generally that gene interactions are the primary force shaping genome structure and operon evolution.

evolutionary biology↗

bioRxiv2022

The global biogeography of angiosperm genome size is shaped by climate and range size

O_LIAngiosperms, which inhabit diverse environments across all continents, exhibit significant variation in genome sizes, making them an excellent model system for examining hypotheses about the global distribution of genome size. These include the previously proposed large-genome-constraint, mutational-hazard, polyploidy-mediated, and climate-mediated hypotheses. C_LIO_LIWe compiled the largest genome size dataset to date, encompassing >5% of known angiosperm species, and analyzed genome size distribution using a comprehensive geographic distribution dataset for all angiosperms. C_LIO_LIWe observed that angiosperms with large range sizes generally had small genomes, supporting the large-genome-constraint hypothesis. Climate was shown to exert a strong influence on genome size distribution along the global latitudinal gradient, while the frequency of polyploidy and the type of growth form had negligible effects. In contrast to the unimodal patterns along the global latitudinal gradient shown by plant size traits and polyploid proportions, the increase in angiosperm genome size from the equator to 40-50{degrees}N/S is probably mediated by different (mostly climatic) mechanisms than the decrease in genome sizes observed from 40-50{degrees}N northwards. C_LIO_LIOur analysis suggests that the global distribution of genome sizes in angiosperms is mainly shaped by climatically-mediated purifying selection, genetic drift, relaxed selection, and environmental filtering. C_LI

evolutionary biology↗

bioRxiv2023

Predicting Protein-encoding Gene Content in Escherichia coli Genomes

In this study, we built machine learning classifiers for predicting the presence or absence of the variable genes occurring in 10-90% of all publicly available high-quality Escherichia coli genomes. The BV-BRC genus-specific protein families were used to define orthologs across the set of genomes, and a single binary classifier was built for predicting the presence or absence of each family in each genome. Each model was built using the nucleotide k-mers from a set of 100 conserved genes as features. The resulting set of 3,259 XGBoost classifiers had a per-genome average macro F1 score of 0.944 [0.943-0.945, 95% CI]. We show that the F1 scores are stable across MLSTs, and that the trend can be recapitulated through sampling with a smaller number of core genes or diverse input genomes. Surprisingly, the presence or absence of poorly annotated proteins, including "hypothetical proteins", were easily predicted (F1 = 0.902 [0.898-0.906, 95% CI]). Models for proteins with horizontal gene transfer-related functions, including transposition- (F1 = 0.895 [0.882-0.907, 95% CI]), phage- (F1 = 0.872 [0.868-0.876, 95% CI]), and plasmid-related (F1 = 0.824 [0.814-0.834, 95% CI]) functions had slightly lower F1 scores, but were still accurate. Finally, we applied the models to a holdout set of 419 diverse E. coli genomes that were isolated from freshwater environmental sources and observed an average per-genome F1 score of 0.880 [0.876-0.883, 95% CI], demonstrating the extensibility of the models. Overall, this study provides a framework for predicting variable gene content using a limited amount of input sequence data. ImportanceHaving the ability to predict the protein-encoding gene content of a genome is important for a variety of bioinformatic tasks, including assessing genome quality, binning genomes from shotgun metagenomic assemblies, and assessing risk due to the presence of antimicrobial resistance (AMR) and other virulence genes. In this study, we built a series of binary classifiers for predicting the presence or absence of variable genes occurring in 10-90% of all publicly available E. coli genomes. Overall, the results show that a large portion of the E. coli variable gene content can be predicted with high accuracy, including genes with functions relating to horizontal gene transfer.

bioinformatics↗

bioRxiv2023

Inferring patterns of recombination and divergence with ancient and modern treponemal genomes

BackgroundTreponemal diseases pose significant global health risks, presenting severe challenges to public health due to their serious health impacts if left untreated. Despite numerous genomic studies on Treponema pallidum and the known possible biases introduced by the choice of the reference genome used for mapping, few investigations have addressed how these biases affect phylogenetic and evolutionary analysis of these bacteria. In this study, we assessed the impact of selecting an appropriate genomic reference on phylogenetic and evolutionary analyses of T. pallidum. ResultsWe designed a multiple-reference-based (MRB) mapping strategy using four different reference genomes and compared it to traditional single-reference mapping. To conduct this comparison, we created a genomic dataset comprising 77 modern and ancient genomes from the three subspecies of T. pallidum, including a newly sequenced 17th-century genome (35X coverage) of a syphilis-causing strain (designated as W86). Our findings show that recombination detection was consistent across different references, but the choice of reference significantly affected ancient genome reconstruction and phylogenetic inferences. The high-coverage W86 genome obtained here also provided a new calibration point for Bayesian molecular clock dating, improving the reconstruction of the evolutionary history of treponemal diseases. Additionally, we identified novel recombination events, positive selection targets, and refined dating estimates for key events in the species history. ConclusionsThis study highlights the importance of considering methodological implications and reference genome bias in High-Throughput Sequencing-based whole-genome analysis of T. pallidum, especially of ancient or low-coverage samples, contributing to a deeper understanding of this pathogen and its subspecies.

microbiology↗

bioRxiv2023

Large-scale genomic rearrangements boost SCRaMbLE in Saccharomyces cerevisiae

Genomic rearrangements contribute to gene copy number alterations, disruption of protein-coding sequences and/or perturbation of cis-regulatory networks. SCRaMbLE, a Cre/loxP-based system implanted in synthetic yeast chromosomes, can effectively introduce genomic rearrangements, and is thus a potential tool to study genomic rearrangements. However, the potential of SCRaMbLE to study genomic rearrangements is currently hindered, because a strain containing all 16 synthetic chromosomes is not yet available. Here, we constructed a yeast strain, SparLox83, containing 83 loxPsym sites distributed across all 16 chromosomes, with at least two sites per chromosome. Inducing Cre recombinase expression in SparLox83 produced versatile genome-wide genomic rearrangements, including inter-chromosomal events. Moreover, SCRaMbLE of the hetero-diploid strains derived from crossing SparLox83 with strains possessing synthetic chromosome III (synIII) from the Sc2.0 project led to increased diversity of genomic rearrangements and relatively faster evolution of traits compared to a strain with only synIII. Analysis of these evolved strains demonstrates that genomic rearrangements can perturb the transcriptome and 3D genome structure and can consequently impact phenotypes. In summary, a genome with sparsely distributed loxPsym sites can serve as a powerful tool to study the consequence of genomic rearrangements and help accelerate strain engineering in Saccharomyces cerevisiae.

synthetic biology↗

bioRxiv2023

The temporal and genomic scale of selection following hybridization

1Genomic evidence supports an important role for selection in shaping patterns of introgression along the genome, but frameworks for understanding the dynamics underlying these patterns within hybrid populations have been lacking. Here, we develop methods based on the Wavelet Transform to understand the spatial genomic scale of local ancestry variation and its association with recombination rates. We present theory and use simulations to show how wavelet-based decompositions of ancestry variance along the genome and the correlation between ancestry and recombination reflect the joint effects of recombination, genetic drift, and genome-wide selection against introgressed alleles. Due to the clock-like effect of recombination in hybrids breaking up parental haplotypes, drift and selection produce predictable patterns of local ancestry variation at varying spatial genomic scales through time. Using wavelet approaches to identify the genomic scale of variance in ancestry and its correlates, we show that these methods can detect temporally localized effects of drift and selection. We apply these methods to previously published datasets from hybrid populations of swordtail fish (Xiphophorus) and baboons (Papio), and to inferred Neanderthal introgression in modern humans. Across systems, we find that upwards of 20% of the variation in local ancestry at the broadest genomic scales can be attributed to systematic selection against introgressed alleles, consistent with strong selection acting on early-generation hybrids. We also see signals of selection at fine genomic scales and much longer time scales. However, we show that our ability to confidently infer selection at fine scales is likely limited by inherent biases in current methods for estimating local ancestry from genomic similarity. Wavelet approaches will become widely applicable as genomic data from systems with introgression become increasingly available, and can help shed light on generalities of the genomic consequences of interspecific hybridization.

evolutionary biology↗

bioRxiv2023

Genome analysis of the Jomon dogs reveals the oldest domestic dog lineage in Eastern Eurasia

Dog is the oldest domesticated animal that established close relationships with humans. Due to its ancient origin, when, where, and whether a single or dual domestication event occurred is still under debate. The dogs in the Jomon period (Jomon dogs) in the Japanese archipelago had little change in morphology from 10,000 to 3,000 years ago. Therefore, we expected that the ancient genome of the Jomon dogs would provide a clue to reveal the characteristics of the ancient East Asian dogs. Here, we have sequenced the genomes of three 6000-year-old Jomon dogs, one 3000-4000-year-old Jomon dog, and four late 8th century dogs excavated in Japan. Our analyses suggest that the Jomon dogs are a distinct lineage from the previously known ancient dogs and are one of the oldest among the dogs in East Eurasian lineages. In addition, the genome of the Jomon dogs contained 9.5% of the genome of Japanese wolf ancestry due to a single introgression event. We estimated the proportion of the Jomon dog lineage genome in the genomes of dogs, which indicates that the genomic composition derived from the Jomon dog lineage is one of the major sources of modern dog genomes. Furthermore, we estimated the early admixture events of dogs in East Eurasia by analyzing the ancient genomes of the Jomon dogs. Due to the admixture events, the Jomon dog-derived genome has been one of the genomic sources of a wide range of modern dogs.

evolutionary biology↗

bioRxiv2023

Genome evolution and introgression in the New Zealand mud snails Potamopyrgus estuarinus and Potamopyrgus kaitunuparaoa

We have sequenced, assembled, and analyzed the nuclear and mitochondrial genomes and transcriptomes of Potamopyrgus estuarinus and Potamopyrgus kaitunuparaoa, two prosobranch snail species native to New Zealand that together span the continuum from estuary to freshwater. These two species are the closest known relatives of the freshwater species P. antipodarum--a model for studying the evolution of sex, host-parasite coevolution, and biological invasiveness--and thus provide key evolutionary context for understanding its unusual biology. The P. estuarinus and P. kaitunuparaoa genomes are very similar in size and overall gene content. Comparative analyses of genome content indicate that these two species harbor a near-identical set of genes involved in meiosis and sperm functions, including seven genes with meiosis-specific functions. These results are consistent with obligate sexual reproduction in these two species and provide a framework for future analyses of P. antipodarum--a species comprising both obligately sexual and obligately asexual lineages, each separately derived from a sexual ancestor. Genome-wide multigene phylogenetic analyses indicate that P. kaitunuparaoa is likely the closest relative to P. antipodarum. We nevertheless show that there has been considerable introgression between P. estuarinus and P. kaitunuparaoa. That introgression does not extend to the mitochondrial genome, which appears to serve as a barrier to hybridization between P. estuarinus and P. kaitunuparaoa. Nuclear-encoded genes whose products function in joint mitochondrial-nuclear enzyme complexes exhibit similar patterns of non-introgression, indicating that incompatibilities between the mitochondrial and the nuclear genome may have prevented more extensive gene flow between these two species. Significance StatementNo whole-nuclear genome sequences are currently available for snails of the genus Potamopyrgus, best known for Potamopyrgus antipodarum, an invasive species of rivers and lakes worldwide, and a famous model for the study of the evolution of sex. We have sequenced and analyzed the genome of sexual P. estuarinus and P. kaitunuparaoa, the closest known relatives of P. antipodarum. We show that 1) the genomes are very similar in gene content and size, 2) P. kaitunuparaoa is the closest relative to P. antipodarum, 3) significant introgression has occurred between P. estuarinus and P. kaitunuparaoa; these genomes set the stage for powerful direct analyses of the genomic features, e.g., sex to asexual transitions and invasive success, that make P. antipodarum unique.

evolutionary biology↗

bioRxiv2024

Transformer Model Generated Bacteriophage Genomes are Compositionally Distinct from Natural Sequences

Novel applications of language models in genomics promise to have a large impact on the field. The megaDNA model is the first publicly available generative model for creating synthetic viral genomes. To evaluate megaDNAs ability to recapitulate the nonrandom genome composition of viruses and assess whether synthetic genomes can be algorithmically detected, compositional metrics for 4,969 natural bacteriophage genomes and 1,002 de novo synthetic bacteriophage genomes were compared. Transformer-generated sequences had varied but realistic genome lengths and 58% were classified as viral by geNomad. However, the sequences demonstrated consistent differences in various compositional metrics when compared to natural bacteriophage genomes by rank-sum tests and principal component analysis. A simple neural network trained to detect transformer-generated sequences on global compositional metrics alone displayed a median sensitivity of 93.0% and specificity of 97.9% (n = 12 independent models). Overall, these results demonstrate that megaDNA does not yet generate bacteriophage genomes with realistic compositional biases and that genome composition is a reliable method for detecting sequences generated by this model. While the results are specific to the megaDNA model, the evaluate framework described here could be applied to any generative model for genomic sequences.

bioinformatics↗

bioRxiv2024

Assembly, comparative analysis, and utilization of a single haplotype reference genome for soybean

Cultivar Williams 82 has served as the reference genome for the soybean research community since 2008, but is known to have areas of genomic heterogeneity among different sub-lines. This work provides an updated assembly (version Wm82.a6) derived from a specific sub-line known as Wm82-ISU-01 (seeds available under USDA accession PI 704477). The genome was assembled using Pacific BioSciences HiFi reads and integrated into chromosomes using HiC. The 20 soybean chromosomes assembled into a genome of 1.01Gb, consisting of 36 contigs. The genome annotation identified 48,387 gene models, named in accordance with previous assembly versions Wm82.a2 and Wm82.a4. Comparisons of Wm82.a6 with other near-gapless assemblies of Williams 82 reveal large regions of genomic heterogeneity, including regions of differential introgression from the genotype Kingwa within approximately 30 Mb and 25 Mb segments on chromosomes 03 and 07, respectively. Additionally, our analysis revealed a previously unknown large ([~]20 Mb) heterogeneous region in the pericentromeric region of chromosome 12, where Wm82.a6 matches the Williams haplotype while the other two near-gapless assemblies do not match the haplotype of either parent of Williams 82. In addition to the Wm82.a6 assembly, we also assembled the genome of soybean line Fiskeby III, a rich resource for abiotic stress resistance genes. A genome comparison of Wm82.a6 with Fiskeby III revealed the nucleotide and structural polymorphisms between the two genomes within a QTL region for iron deficiency chlorosis resistance. The Wm82.a6 and Fiskeby III genomes described here will enhance comparative and functional genomics capacities and applications in the soybean community.

plant biology↗

bioRxiv2024

Chromosome-level genome assemblies for two quinoa inbred lines from northern and southern highlands of Altiplano where quinoa originated

Quinoa, an annual allotetraploid plant native to the Andean highlands of South America, is emerging as an important seed crop for global food and nutrition security due to its ability to grow in marginal environments and its excellent nutritional properties. Because quinoa is partially allogamous, we have developed quinoa inbred lines necessary for molecular genetic analysis. Our comprehensive genomic analysis showed that the quinoa inbred lines fall into three genetic subpopulations: northern highland, southern highland, and lowland. Lowland and highland quinoa are the same species, but have very different genotypes and phenotypes. Lowland quinoa has relatively small grains and a darker grain color, and is widely tested and grown around the world. In contrast, the white, large-grained highland quinoa is grown in the Andean highlands, including the region where quinoa originated, and is exported worldwide as high-quality quinoa. Recently, we have shown that viral vectors can be used to regulate endogenous genes in quinoa, paving the way for functional genomics of quinoa. However, although a high-quality assembly has recently been reported for a lowland quinoa line, genomic resources of the quality required for functional genomics are not available for highland quinoa lines. Here we present high-quality chromosome-level genome assemblies for two highland inbred quinoa lines, J075 representing the northern highland line and J100 representing the southern highland line, using PacBio HiFi sequencing and dpMIG-seq. The assembled genome sizes of J075 and J100 are 1.29 and 1.32 Gb, with contigs N50 of 66.3 and 12.6 Mb, and scaffold N50 of 71.2 and 70.6 Mb, respectively, comprising 18 pseudochromosomes. The repetitive sequences of J075 and J100 represent 72.6% and 71.5% of the genome, the majority of which are long terminal repeats (Gypsy and Copia), representing 44.0% and 42.7% of the genome, respectively. The de novo assembled genomes of J075 and J100 were predicted to contain 64,945 and 65,303 protein-coding genes, respectively. The high quality genomes of these highland quinoa lines will facilitate quinoa functional genomics research on quinoa and contribute to the identification of key genes involved in environmental adaptation and quinoa domestication.

plant biology↗

bioRxiv2024

K-mer Genome-wide Association Study for Anthracnose and BCMV Resistance in the Andean Diversity Panel

Limited genomic resources and closely linked marker-trait associations for common beans (Phaseolus vulgaris L.) have limited breeders from fully utilizing molecular genetics technologies to maximize genetic gain. The emergence of virulent races of anthracnose (caused by Colletotrichum lindemuthianum) and Bean Common Mosaic Virus (BCMV) highlight the need for improved methods to identify and incorporate pan-genomic variation in breeding for disease resistance. We sequenced the P. vulgaris Andean Diversity Panel (ADP) and performed a genome-wide association study (GWAS) to identify associations for resistance to BCMV and eight races of anthracnose. Historical single nucleotide polymorphism (SNP)-chip and phenotypic data enabled a three-way comparison between SNP-chip, reference-based whole genome shotgun sequence (WGS)-SNP, and reference-free k-mer GWAS. Across all traits, there was excellent concordance between SNP-chip, WGS-SNP, and k-mer GWAS results--albeit at a much higher marker resolution for the WGS data sets. Significant k-mer haplotype variation revealed selection of the linked I-gene and Co-u traits in North American breeding lines and cultivars. Due to k-mer mapping criteria and the absence of target loci in the reference genome due to structural variation, only 9.1 to 47.3% of the significantly associated k-mers were mapped to the reference genome. To determine the genetic context of cis-associated k-mers, we generated whole genome assemblies of four ADP accessions and identified an expanded local repertoire of disease resistance genes associated with resistance to anthracnose and BCMV. With access to variant data in the context of a pan-genome, high resolution mapping of agronomic traits for common bean is now feasible. CORE IDEASO_LIK-mer-based GWAS offers new advantages for mapping pan-genomic variation C_LIO_LIComparison of reference-based SNP to reference-free k-mer GWAS C_LIO_LINovel discovery of cis-associated k-mers for dry bean disease resistance C_LI PLAIN LANGUAGE SUMMARYImproving disease resistance in crop species such as bean is critical. We surveyed the genomes of a diverse set of bean lines and identified sequences associated with resistance to a fungal and viral pathogen. Access to the genomes of this diversity panel of beans will permit additional discoveries on the role of structural variation in phenotypes, including disease resistance.

plant biology↗

bioRxiv2024

Capturing changes to animal complexity from quantifiable patterns in genomic data

A prevailing problem in evolutionary biology is elucidating the "genotype-phenotype map" that characterizes how genomic activities regulate different aspects of organismal morphology and their variability in both space and time. Here, we explore potential causality between genome content and both morphological complexity and disparity by compiling the regulatory components (i.e., transcription factors, RNA binding proteins, and microRNA families) as well as a representative set of non-regulatory "housekeeping genes" in 32 species belonging to a wide variety of animal phyla, altogether encapsulating a number of varying genomic characteristics and morphological diversities. A principal component analysis of these four non-overlapping genomic components from each of these 32 species in relation to their last common ancestor revealed that no relationship exists between genome space and disparity, as changes to animal body plans appear to be largely the result of changes to the gene regulatory networks that govern animal development rather than gaining or losing specific sets of regulatory genes. However, using both phylogenetically correlated as well as phylogenetically uncorrelated statistical tests, we find a strong relationship between the loss of all considered gene types and the advent of some parasitic taxa, as well as between microRNA innovations and organismal complexity. While this analysis of genomic features suggests how complexity and disparity are each encoded in the genome, further analysis of the regulatory networks in which they participate should provide a more comprehensive description of how organisms diversify their morphologies over time through alterations in their genomic components. SIGNIFICANCE STATEMENTVariation in morphological form can be measured by considering either disparity (i.e., the amount of variance in morphological form) or complexity (i.e., the difference in the number of their "parts" including genes or cells). To date, discerning the genomic basis of either has remained largely unknown. Here, we compile the regulatory genome of the last common ancestor of bilaterian metazoans, including its transcription factors, RNA-binding proteins and microRNA families, and ask how changes to these repertoires potentially reflects changes in either disparity or complexity. We find that although there is no relationship between the regulatory genome and disparity, there is a robust relationship between the loss of regulatory genes relative to housekeeping genes, especially in parasitic taxa. Further, there is a strong relationship between increases to microRNAs and complexity, which likely reflects the unique role microRNAs play in increasing both the accuracy and the precision of gene expression during development.

evolutionary biology↗

bioRxiv2024

Improvements in Prediction Performance of Ensemble Approaches for Genomic Prediction in Crop Breeding

The improvement of selection accuracy of genomic prediction is a key factor in accelerating genetic gain for crop breeding. Traditionally, efforts have focused on developing superior individual genomic prediction models. However, this approach has limitations due to the absence of a consistently "best" individual genomic prediction model, as suggested by the No Free Lunch Theorem. The No Free Lunch Theorem states that the performance of an individual prediction model is expected to be equivalent to the others when averaged across all prediction scenarios. To address this, we explored an alternative method: combining multiple genomic prediction models into an ensemble. The investigation of ensembles of prediction models is motivated by the Diversity Prediction Theorem, which indicates the prediction error of the many-model ensemble should be less than the average error of the individual models due to the diversity of predictions among the individual models. To investigate the implications of the No Free Lunch and Diversity Prediction Theorems, we developed a naive ensemble-average model, which equally weights the predicted phenotypes of individual models. We evaluated this model using two traits influencing crop yield--days to anthesis and tiller number per plant--in the Teosinte Nested Association Mapping dataset. The results show that the ensemble approach increased prediction accuracies and reduced prediction errors over individual genomic prediction models. The advantage of the ensemble was derived from the diverse predictions among the individual models, suggesting the ensemble captures a more comprehensive view of the genomic architecture of these complex traits. These results are in accordance with the expectations of the Diversity Prediction Theorem and suggest that ensemble approaches can enhance genomic prediction performance and accelerate genetic gain in crop breeding programs. Article summaryThis research targets selective breeding industries and researchers developing genomic prediction models to accelerate genetic gain in breeding programs. We applied the concept of an ensemble, combining multiple individual genomic prediction models, to predict key traits (days to anthesis and tiller number per plant) in a crop breeding dataset. Here, we show that an ensemble approach increased prediction accuracies and reduced prediction errors over individual genomic prediction models. These results indicate the potential for ensembles of multiple, diverse genomic prediction models to accelerate genetic gain in breeding programs by increasing the accuracy of selection decisions.

bioinformatics↗

bioRxiv2024

genomesizeR: An R package for genome size prediction

The genome size of organisms present in an environment can provide many insights into evolutionary and ecological processes at play in that environment. The genomic revolution has enabled a rapid expansion of our knowledge of genomes in many living organisms, and most of that knowledge is classified and readily available in the databases of the National Center for Biotechnology Information (NCBI). The genomesizeR tool leverages the wealth of taxonomic and genomic information present in NCBI databases to infer the genome size of Archeae, Bacteria, or Eukaryote organisms identified at any taxonomic level. This R package uses statistical modelling on data from the most up-to-date NCBI databases and provides three statistical methods for genome size prediction of a given taxon, or group of taxa. A straightforward weighted mean method identifies the closest taxa with available genome size information in the taxonomic tree, and averages their genome sizes using weights based on taxonomic distance. A frequentist random effect model uses nested genus and family information to output genome size estimates. Finally a third option provides predictions from a distributional Bayesian multilevel model which uses taxonomic information from genus all the way to superkingdom, therefore providing estimates and uncertainty bounds even for under-represented taxa. All three methods use: O_LIA list of queries; a query being a taxon or a list of several taxa. The package was designed to make it easy to use with data coming from environmental DNA experiments, but works with any table of taxa. C_LIO_LIA reference database containing all the known genome sizes, built from the NCBI databases, with associated taxa, provided in an archive to download. C_LIO_LIA taxonomic tree structure as built by the NCBI, provided in the same archive. C_LI genomesizeR retrieves the taxonomic classification of input queries, estimates the genome size of each query, and provides 95% confidence intervals for each estimate.

bioinformatics↗

bioRxiv2024

REPORTH: Determining orthologous locations of repetitive sequences between genomes

Repetitive sequences are a common feature of bacterial genomes. Some repetitive sequences such as REPINs are mobile within the genome but inherited only vertically from mother to daughter across bacterial genomes. Selfish elements in contrast are mobile within the genome but also travel horizontally from genome to genome. Yet, no matter the nature of the association between the repetitive elements and the host, it is difficult to study the evolutionary dynamics of repetitive sequences across genomes. If it is unclear whether two sequences in two different genomes are in orthologous positions, it is difficult to infer parameters like the replication rate, horizontal transfer rate and rate of loss. Here we present a tool to facilitate these analyses called REPORTH. REPORTH determines whether repetitive sequences in different but closely related bacterial genomes occur in orthologous genomic positions. Whether a position is orthologous or not depends on the orthology of flanking sequences. Flanking sequences are deemed orthologous if they are bidirectional best hits. All repetitive sequences that are found in orthologous positions across different genomes are grouped together. Analyses of these groups can be used to study the evolutionary dynamics of selfish repetitive elements such as insertion sequences, but also for mutualistic repetitive elements such as REPINs.

bioinformatics↗

bioRxiv2024

Genomic Architecture of the Resistance to Phytophthora Cactorum 2 (RPc2) Locus in Strawberry (Fragaria x ananassa)

Phytophthora crown rot (PhCR), caused by Phytophthora cactorum, is a soilborne disease with broad impacts to cultivated strawberries in the United States and worldwide. While a resistance locus, RPc2, has been identified in octoploid strawberries, the underlying genomic architecture and mechanism remain unclear. Here, we fine-mapped the RPc2 region to 546 kb, containing 92 genes, and constructed a chromosome-scale haplotype-phased genome of resistant breeding selection FL 16.33-8. Comparative genome analyses with high-quality octoploid reference genomes, Florida Brilliance (FaFB1) and Royal Royce (FaRR1), identified two candidate genes, Wall Associated Kinase 1 (WAK1) and Cyclic Nucleotide Gated Channel 1 (CNGC1). Gene functions were validated using an Agrobacterium-mediated transient expression assay. Furthermore, by leveraging the population structure of the RPc2 locus among genetically diverse breeding populations, we unveiled the complexity of genetic architecture and recent selective sweeps associated with RPc2. Notably, the predominant resistant haplotype (RPc2-H3) is prevalent in most commercial strawberry varieties in the US. The findings from this study are facilitating the advancement of genome-assisted breeding strategies for resistance to PhCR in strawberries. SummaryO_LIPhytophthora crown rot (PhCR), caused by the soilborne pathogen Phytophthora cactorum, is a disease with broad impacts to cultivated strawberries worldwide. The Resistance to Phytophthora Cactorum 2 (RPc2) locus is widespread in important cultivars and is a target of selection in breeding programs. Despite its importance, the genomic architecture and mechanisms of RPc2 remain poorly characterized. C_LIO_LIWe performed fine-mapping and delimited the genomic region to a 546 kb segment containing 92 genes. We developed a chromosome-scale haplotype-phased genome from an elite resistant line, FL16.33-8, and made comparisons to reference genomes of Florida Brilliance (FaFB1) and Royal Royce (FaRR1) to uncover gene sequence and structural variants in resistant accessions. C_LIO_LIThrough comparative genomics and transcriptome profiling, we identified three candidate genes, Wall Associated Kinase 1 (WAK1) and Cyclic Nucleotide Gated Channel 1 (CNGC1) and CNGC2. The functions of these genes were validated using a simplified Agrobacterium-mediated transformation method for transient gene expression in strawberry crowns and roots. C_LIO_LIAn examination of the population structure of the RPc2 locus among genetically diverse accessions (N=1029) revealed that the predominant H3 resistant haplotype is widespread in breeding accessions in the US, supporting the findings of a previous study on recent selective sweeps associated with RPc2. Results from this study are advancing genome-assisted breeding strategies for enhancing resistance to PhCR in strawberry. C_LI

plant biology↗