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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2020

In-silico analysis of SARS-CoV-2 genomes: Insights from SARS encoded non-coding RNAs

Recently a novel coronavirus (SARS-CoV-2) emerged from Wuhan, China and has infected more than 571000 people leading to more than 26000 deaths. Since SARS-CoV-2 genome sequences show similarity with those of SARS, we sought to analyze all the available SARS-CoV-2 genomes based on the insights obtained from SARS genome specifically focusing on non-coding RNAs. Here, results are presented from the dual approach i.e identifying host encoded miRNAs that might regulate viral pathogenesis as well as identifying viral encoded miRNAs that might regulate host cell signaling pathways and aid in viral pathogenesis. Analysis utilizing first approach resulted in the identification of 10 host encoded miRNAs that could target the genome of both the viruses (SARS-CoV-2 and SARS reference genome). Interestingly our analysis revealed that there is significantly higher number of host miRNAs that could target SARS-CoV-2 genome as compared to the SARS reference genome. Results from second approach involving SARS-CoV-2 and SARS reference genome identified a set of virus encoded miRNAs which might regulate host signaling pathways. Our analysis further identified a similar "GA" rich motif in SARS-CoV-2 genome that was shown to play a vital role in lung pathogenesis during severe SARS infections. Hence, we successfully identified human and virus encoded miRNAs that might regulate pathogenesis of both these coronaviruses and the fact that more number of host miRNAs could target SARS-CoV-2 genomes possibly reveal as to why this virus follows mild pathogenesis in healthy individuals. We identified non-coding sequences in SARS-CoV-2 genomes that were earlier reported to contribute towards SARS pathology. The study provides insights into the overlapping sequences among these viruses for their effective inhibition as well as identifying new drug targets that could be used for development of new antivirals.

microbiology↗

bioRxiv2020

An Algorithm to Build a Multi-genome Reference

1MotivationNew DNA sequencing technologies have enabled the rapid analysis of many thousands of genomes from a single species. At the same time, the conventional approach of mapping sequencing reads against a single reference genome sequence is no longer adequate. However, even where multiple high-quality reference genomes are available, the problem remains how one would integrate results from pairwise analyses. ResultTo overcome the limits imposed by mapping sequence reads against a single reference genome, or serially mapping them against multiple reference genomes, we have developed the MGR method that allows simultaneous comparison against multiple high-quality reference genomes, in order to remove the bias that comes from using only a single-genome reference and to simplify downstream analyses. To this end, we present the MGR algorithm that creates a graph (MGR graph) as a multi-genome reference. To reduce the size and complexity of the multi-genome reference, highly similar orthologous1 and paralogous2 regions are collapsed while more substantial differences are retained. To evaluate the performance of our model, we have developed a genome compression tool, which can be used to estimate the amount of shared information between genomes. Availabilityhttps://github.com/LeilyR/Multi-genome-Reference.git Contactweigel@tue.mpg.de

bioinformatics↗

bioRxiv2020

Enrichment of genomic variation in pathways linked to autism

The genetic heterogeneity of autism has stymied the search for causes and cures. Even whole-genomic studies on large numbers of families have yielded results of relatively little impact. In the present work, we analyze two genomic databases using a novel strategy that takes prior knowledge of genetic relationships into account and that was designed to boost signal important to our understanding of the molecular basis of autism. Our strategy was designed to identify significant genomic variation within a priori defined biological concepts and improves signal detection while lessening the severity of multiple test correction seen in standard analysis of genome-wide association data. Upon application of our approach using 3,244 biological concepts, we detected genomic variation in 68 biological concepts with significant association to autism in comparison to family-based controls. These concepts clustered naturally into a total of 19 classes, principally including cell adhesion, cancer, and immune response. The top-ranking concepts contained high percentages of genes already suspected to play roles in autism or in a related neurological disorder. In addition, many of the sets associated with autism at the DNA level also proved to be predictive of changes in gene expression within a separate population of autistic cases, suggesting that the signature of genomic variation may also be detectable in blood-based transcriptional profiles. This robust cross-validation with gene expression data from individuals with autism coupled with the enrichment within autism-related neurological disorders supported the possibility that the mutations play important roles in the onset of autism and should be given priority for further study. In sum, our work provides new leads into the genetic underpinnings of autism and highlights the importance of reanalysis of genomic studies of complex disease using prior knowledge of genetic organization. Author SummaryThe genetic heterogeneity of autism has stymied the search for causes and cures. Even whole-genomic studies on large numbers of families have yielded results of relatively little impact. In the present work, we reanalyze two of the most influential whole-genomic studies using a novel strategy that takes prior knowledge of genetic relationships into account in an effort to boost signal important to our understanding of the molecular structure of autism. Our approach demonstrates that these genome wide association studies contain more information relevant to autism than previously realized. We detected 68 highly significant collections of mutations that map to genes with measurable and significant changes in gene expression in autistic individuals, and that have been implicated in other neurological disorders believed to be closely related, and genetically linked, to autism. Our work provides leads into the genetic underpinnings of autism and highlights the importance of reanalysis of genomic studies of disease using prior knowledge of genetic organization.

genetics↗

bioRxiv2020

An integrative analysis of genomic and exposomic data for complex traits and phenotypic prediction

Complementary to the genome, the concept of exposome has been proposed to capture the totality of human environmental exposures. While there has been some recent progress on the construction of the exposome, few tools exist that can integrate the genome and exposome for complex trait analyses. Here we propose a linear mixed model approach to bridge this gap, which jointly models the random effects of the two omics layers on phenotypes of complex traits. We illustrate our approach using traits from the UK Biobank (e.g., BMI & height for N [~] 35,000) with a small fraction of the exposome that comprises 28 lifestyle factors. The joint model of the genome and exposome explains substantially more phenotypic variance and significantly improves phenotypic prediction accuracy, compared to the model based on the genome alone. The additional phenotypic variance captured by the exposome includes its additive effects as well as non-additive effects such as genome-exposome (gxe) and exposome-exposome (exe) interactions. For example, 19% of variation in BMI is explained by additive effects of the genome, while additional 7.2% by additive effects of the exposome, 1.9% by exe interactions and 4.5% by gxe interactions. Correspondingly, the prediction accuracy for BMI, computed using Pearsons correlation between the observed and predicted phenotypes, improves from 0.15 (based on the genome alone) to 0.35 (based on the genome & exposome). We also show, using established theories, integrating genomic and exposomic data is essential to attaining a clinically meaningful level of prediction accuracy for disease traits. In conclusion, the genomic and exposomic effects can contribute to phenotypic variation via their latent relationships, i.e. genome-exposome correlation, and gxe and exe interactions, and modelling these effects has a great potential to improve phenotypic prediction accuracy and thus holds a great promise for future clinical practice.

genetics↗

bioRxiv2021

Sorghum pan-genome explores the functional utility to accelerate the genetic gain

Sorghum (Sorghum bicolor L.) is one of the most important food crops in the arid and rainfed production ecologies. It is a part of resilient farming and is projected as a smart crop to overcome the food and nutritional challenges in the developing world. The development and characterisation of the sorghum pan-genome will provide insight into genome diversity and functionality, supporting sorghum improvement. We built a sorghum pan-genome using reference genomes as well as 354 genetically diverse sorghum accessions belonging to different races. We explored the structural and functional characteristics of the pan-genome and explain its utility in supporting genetic gain. The newly-developed pan-genome has a total of 35,719 genes, a core genome of 16,821 genes and an average of 32,795 genes in each cultivar. The variable genes are enriched with environment responsive genes and classify the sorghum accessions according to their race. We show that 53% of genes display presence-absence variation, and some of these variable genes are predicted to be functionally associated with drought traits. Using more than two million SNPs from the pan-genome, association analysis identified 398 SNPs significantly associated with important agronomic traits, of which, 92 were in genes. Drought gene expression analysis identified 1,788 genes that are functionally linked to different conditions, of which 79 were absent from the reference genome assembly. This study provides comprehensive genomic diversity resources in sorghum which can be used in genome assisted crop improvement.

bioinformatics↗

bioRxiv2021

Genomic evaluation of Bordetella spp. originating from Australia

Bordetella pertussis is the primary causative agent of pertussis, a highly infectious respiratory disease associated with prolonged coughing episodes. Pertussis infections are typically mild in adults, however in neonates, infections can be fatal. Despite successful vaccine uptake, the disease is re-emerging across the globe, therefore it is critical to determine the mechanism by which B. pertussis is escaping vaccination control. Studies have suggested that significant changes have occurred in B. pertussis genomes in response to whole cell and acellular vaccines. Continued molecular monitoring is therefore crucial for public health surveillance. High-resolution molecular surveillance of B. pertussis can be achieved through the sequencing of the whole genome. In public health laboratories, whole genome sequencing is primarily performed by short-read sequencing technologies as they are most cost-effective. However short read sequencing does not resolve the extensive genomic rearrangement evident in Bordetella genomes. This is because repeat regions present in Bordetella genomes are collapsed by downstream analysis. For example, the B. pertussis genome contains more than 200 copies of the IS481 insertion element, hence assemblies generally consist of >200 contigs. Advancements in long-read technologies however increase the potential to circularise and close genomes by bridging the locations of the IS481 insertion element. In this study, we aimed to contextualise the Bordetella spp. circulating in NSW, Australia and assess their relationship with global isolates utilising core genome, SNP and structural clustering analysis using long read technology. We report five closed genomes of Bordetella spp. isolated from Australian patients. Two of the three B. pertussis closed isolates, were unique with their own genomic structure, while the other structurally clustered with global isolates. We found that Australian B. holmesii and B. parapertussis strains cluster with global isolates and do not appear to be unique to Australia. Australian draft B. holmesii SNP analysis showed that between 1999 and 2007, isolates were relatively similar, however post-2012, isolates were distinct from each other. The closed isolates can also be used as high-quality reference sequences for both surveillance and other investigations into pertussis spread.

microbiology↗

bioRxiv2021

Full-length Genome of the Ogataea polymorpha strain HU-11 reveals large duplicated segments in subtelomeic regions

BackgroundCurrently, methylotrophic yeasts (e.g., Pichia pastoris, Ogataea polymorpha, and Candida boindii) are subjects of intense genomics studies in basic research and industrial applications. In the genus Ogataea, most research is focused on three basic O. polymorpha strains--CBS4732, NCYC495, and DL-1. However, the relationship between CBS4732, NCYC495, and DL-1 remains unclear, as the genomic differences between them have not be exactly determined without their high-quality complete genomes. As a nutritionally deficient mutant derived from CBS4732, the O. polymorpha strain CBS4732 ura3{Delta} (named HU-11) is being used for high-yield production of several important proteins or peptides. HU-11 has the same reference genome as CBS4732 (noted as HU-11/CBS4732), because the only genomic difference between them is a 5-bp insertion. ResultsIn the present study, we have assembled the full-length genome of O. polymorpha HU-11/CBS4732 using high-depth PacBio and Illumina data. Long terminal repeat (LTR) retrotransposons, rDNA, 5 and 3 telomeric, subtelomeric, low complexity and other repeat regions were curated to improve the genome quality. Particularly, we detected large duplicated segments (LDSs) in the subtelomeric regions and exactly determined all the structural variations (SVs) between CBS4732 and NCYC495. New findings mainly include(1) the genomic differences between HU-11/CBS4732 and NCYC495 include single nucleotide polymorphisms, small insertions and deletions, and only three SVs; (2) six genes were incorporated into CBS4732 from Cyberlindnera jadinii by horizontal gene transfer and may bring HU-11/CBS4732 new biological functions or physiological properties; (3) many recombination events may have occurred on chromosome 4 and 5 of CBS4732 and NCYC495 ancestors and two large segments were acquired by CBS4732 and NCYC495 from chromosome 6 and C. jadinii during recombination, respectively; and (4) the genome expansion in methylotrophic yeasts is mainly driven by large segment duplication in subtelomeric regions. ConclusionsThe present study preliminarily revealed the complex relationship between CBS4732, NCYC495, and DL-1. The new findings provide new opportunities for in-depth understanding of genome evolution in methylotrophic yeasts and lay the foundations for the industrial applications of O. polymorpha CBS4732, NCYC495, DL-1, and their derivative strains. The full-length genome of the O. polymorpha strain HU-11/CBS4732 should be included into the NCBI RefSeq database for future studies of Ogataea spp..

bioinformatics↗

bioRxiv2021

Bayesian genome-wide analysis of cattle traits using variants with functional and evolutionary significance

ContextFunctional genomics studies have revealed genomic regions with regulatory and evolutionary significance. Such information independent of association analysis may benefit fine-mapping and genomic selection of economically important traits. However, systematic evaluation of the use of functional information in mapping, and genomic selection of cattle traits is lacking. Also, Single Nucleotide Polymorphisms (SNPs) from the high-density (HD) panel are known to tag informative variants, but the performance of genomic prediction using HD SNPs together with variants supported by different functional genomics is unknown. AimsWe selected six sets of functionally important variants and modelled each set together with HD SNPs in Bayesian models to map and predict protein, fat, and milk yield as well as mastitis, somatic cell count and temperament of dairy cattle. MethodsTwo models were used: 1) BayesR which includes priors of four distribution of variant-effects, and 2) BayesRC which includes additional priors of different functional classes of variants. Bayesian models were trained in 3 breeds of 28,000 cows of Holstein, Jersey and Australian Red and predicted into 2,600 independent bulls. Key resultsAdding functionally important variants significantly increased the enrichment of genetic variance explained for mapped variants, suggesting improved genome-wide mapping precision. Such improvement was significantly higher when the same set of variants were modelled by BayesRC than by BayesR. Combining functional variant sets with HD SNPs improves genomic prediction accuracy in the majority of the cases and such improvement was more common and stronger for non-Holstein breeds and traits like mastitis, somatic cell count and temperament. In contrast, adding a large number of random sequence variants to HD SNPs reduces mapping precision and has a worse or similar prediction accuracy, compared to using HD SNPs alone to map or predict. While BayesRC tended to have better genomic prediction accuracy than BayesR, the overall difference in prediction accuracy between the two models was insignificant. ConclusionsOur findings demonstrate the usefulness of functional data in genomic mapping and prediction. ImplicationsWe highlight the need for effective tools exploiting complex functional datasets to improve genomic prediction.

genetics↗

bioRxiv2021

Complete and high-quality genomes of novel microbial species from a meromictic lake using a workflow combining long- and short-read sequencing platforms

BackgroundMost of Earths bacteria have yet to be cultivated. The metabolic and functional potentials of these uncultivated microorganisms thus remain mysterious, and the metagenome-assembled genome (MAG) approach is the most robust method for uncovering these potentials. However, MAGs discovered by conventional metagenomic assembly and binning methods are usually highly fragmented genomes with heterogeneous sequence contamination, and this affects the accuracy and sensitivity of genomic analyses. Though the maturation of long-read sequencing technologies provides a good opportunity to fix the problem of highly fragmented MAGs as mentioned above, the methods error-prone nature causes severe problems of long-read-alone metagenomics. Hence, methods are urgently needed to retrieve MAGs by a combination of both long- and short-read technologies to advance genome-centric metagenomics. ResultsIn this study, we combined Illumina and Nanopore data to develop a new workflow to reconstruct 233 MAGs--six novel bacterial orders, 20 families, 66 genera, and 154 species--from Lake Shunet, a secluded meromictic lake in Siberia. Those new MAGs were underrepresented or undetectable in other MAGs studies using metagenomes from human or other common organisms or habitats. Using this newly developed workflow and strategy, the average N50 of reconstructed MAGs greatly increased 10-40-fold compared to when the conventional Illumina assembly and binning method were used. More importantly, six complete MAGs were recovered from our datasets, five of which belong to novel species. We used these as examples to demonstrate many novel and intriguing genomic characteristics discovered in these newly complete genomes and proved the importance of high-quality complete MAGs in microbial genomics and metagenomics studies. ConclusionsThe results show that it is feasible to apply our workflow with a few additional long reads to recover numerous complete and high-quality MAGs from short-read metagenomes of high microbial diversity environment samples. The unique features we identified from five complete genomes highlight the robustness of this method in genome-centric metagenomic research. The recovery of 154 novel species MAGs from a rarely explored lake greatly expands the current bacterial genome encyclopedia and broadens our knowledge by adding new genomic characteristics of bacteria. It demonstrates a strong need to recover MAGs from diverse unexplored habitats in the search for microbial dark matter.

microbiology↗

bioRxiv2021

SigTools: Exploratory Visualization for Genomic Signals

MotivationWith the advancement of sequencing technologies, genomic data sets are constantly being expanded by high volumes of different data types. One recently introduced data type in genomic science is genomic signals, which are usually short-read coverage measurements over the genome. An example of genomic signals is Epigenomic marks which are utilized to locate functional and nonfunctional elements in genome annotation studies. To understand and evaluate the results of such studies, one needs to understand and analyze the characteristics of the input data. ResultsSigTools is an R-based genomic signals visualization package developed with two objectives: 1) to facilitate genomic signals exploration in order to uncover insights for later model training, refinement, and development by including distribution and autocorrelation plots. 2) to enable genomic signals interpretation by including correlation, and aggregation plots. Moreover, Sigtools also provides text-based descriptive statistics of the given signals which can be practical when developing and evaluating learning models. We also include results from 2 case studies. The first examines several previously studied genomic signals called histone modifications. This use case demonstrates how SigTools can be beneficial for satisfying scientists curiosity in exploring and establishing recognized datasets. The second use case examines a dataset of novel chromatin state features which are novel genomic signals generated by a learning model. This use case demonstrates how SigTools can assist in exploring the characteristics and behavior of novel signals towards their interpretation. In addition, our corresponding web application, SigTools-Shiny, extends the accessibility scope of these modules to people who are more comfortable working with graphical user interfaces instead of command-line tools. AvailabilitySigTools source code, installation guide, and manual is available on http://github.com/shohre73. Contactshohre_masoumi@sfu.ca

bioinformatics↗

bioRxiv2021

Genomic analysis of extended-spectrum beta-lactamase (ESBL) producing Escherichia coli colonising adults in Blantyre, Malawi reveals previously undescribed diversity.

Escherichia coli is a ubiquitous bacterium and one of the most prevalent Gram-negative species associated with drug resistant infections. The large number of sequenced genomes available have provided us with a consistently growing knowledge base to further understand pathogenesis and epidemiology of this organism. However, data from sub-Saharan Africa (sSA) are underrepresented in global sequencing efforts and E. coli genetic diversity from this region is poorly described. To reduce this gap, we investigated extended-spectrum beta-lactamase (ESBL)-producing E. coli colonising adults in Blantyre, Malawi to assess the bacterial diversity and AMR determinants and to place these isolates in the context of the wider population structure. We performed short-read whole-genome sequencing of 473 colonising ESBL E. coli isolated from human stool and contextualised the genomes with a previously curated multi-country species wide collection of 10,146 genomes. The most frequently identified sequence types (STs) in our collection were the globally successful ST131, ST410 and ST167, and the dominant ESBL genes were blaCTX-M, mirroring global trends. However, 37% of Malawian isolates did not cluster with any isolates in the curated multicountry collection and a core gene phylogeny was consistent with locally spreading subclades within globally dominant clones, including in ST410 and ST167. We also found Carbapenemase genes in our collection at low frequency; we used long read sequencing to characterise selected ESBL and carbapenemase-associated plasmids, demonstrating the presence of globally distributed carbapenemase carrying plasmids. Increased genomic surveillance of E. coli from Malawi and sSA is necessary to understand local, regional and global transmission of both E. coli and the AMR genes they commonly carry. Impact StatementDrug-resistant Escherichia coli producing extended-spectrum beta lactamase (ESBL) or carbapenemase enzymes have been identified by the World Health Organisation as priority pathogens of global concern, and whole genome sequencing has provided insight into mechanisms of virulence, antimicrobial resistance, and the spread of high-risk clones. However, studies analysing large numbers of E. coli using whole-genome data often focus on opportunistic use of hospital diagnostic collections in high-income settings. Understanding how the genomic epidemiology of E. coli in low- and middle-income countries (including many of the nations of sub-Saharan Africa) differs is essential to provide insight into local, and global drivers of transmission. We therefore sequenced 473 ESBL-producing E. coli genomes colonising adults in Blantyre, Malawi. We analyse determinants of antimicrobial resistance and virulence and place the isolates in wider context using a previously published global E. coli collection that was generated to represent the whole species diversity of sequences publicly available at the time of generation. We find that there is diversity in Malawian isolates not reflected in the curated global collection: widely successful antimicrobial-resistance associated E. coli sequence types are represented in Blantyre, but locally circulating subclades are apparent. Furthermore, given the high number of ESBL producing pathogens causing infections there is an unmet need for carbapenem antimicrobials which are still active against ESBL-producers but are not yet widely available in our setting. We find that carbapenemases (enzymes that can render bacteria resistant to carbapenems) in our collection are unusual but present and carried on globally disseminated plasmids. So too are globally successful, stably carbapenemase-associated E. coli lineages. Although the Malawian isolates analysed typically lacked carbapenemases, carbapenem use is increasing in Malawi and their unstewarded use will accelerate selection for carbapememases in E. coli in the future. Our study highlights the need for robust stewardship protocols and ongoing genomic surveillance as these agents are introduced. Data SummaryAll data and code to replicate this analysis are available as the blantyreESBL v1.3 R package (https://doi.org/10.5281/zenodo.5554081) available at https://github.com/joelewis101/blantyreESBL. Reads from all isolates sequenced as part of this study have been deposited in the European Nucleotide Archive, under PRJEB26677, PRJEB28522 and PRJEB36486 (short reads) and PRJNA869071 (Nanopore reads and hybrid assemblies). Accession numbers (as well as accession numbers of publicly available genomes used in this analysis) linked to sample metadata are provided in the R package and as supplementary data to this manuscript.

microbiology↗

bioRxiv2022

Reconstructing the 3D genome organization of Neanderthals reveals that chromatin folding shaped phenotypic and sequence divergence

Changes in gene regulation were a major driver of the divergence of archaic hominins (AHs)--Neanderthals and Denisovans--and modern humans (MHs). The three-dimensional (3D) folding of the genome is critical for regulating gene expression; however, its role in recent human evolution has not been explored because the degradation of ancient samples does not permit experimental determination of AH 3D genome folding. To fill this gap, we apply novel deep learning methods for inferring 3D genome organization from DNA sequence to Neanderthal, Denisovan, and diverse MH genomes. Using the resulting 3D contact maps across the genome, we identify 167 distinct regions with diverged 3D genome organization between AHs and MHs. We show that these 3D-diverged loci are enriched for genes related to the function and morphology of the eye, supra-orbital ridges, hair, lungs, immune response, and cognition. Despite these specific diverged loci, the 3D genome of AHs and MHs is more similar than expected based on sequence divergence, suggesting that the pressure to maintain 3D genome organization constrained hominin sequence evolution. We also find that 3D genome organization constrained the landscape of AH ancestry in MHs today: regions more tolerant of 3D variation are enriched for introgression in modern Eurasians. Finally, we identify loci where modern Eurasians have inherited novel 3D genome folding patterns from AH ancestors and validate folding differences in a high-frequency locus using Hi-C, revealing a putative molecular mechanism for phenotypes associated with archaic introgression. In summary, our application of deep learning to predict archaic 3D genome organization illustrates the potential of inferring molecular phenotypes from ancient DNA to reveal previously unobservable biological differences.

evolutionary biology↗

bioRxiv2022

The genomic landscapes of desert birds are structured by contemporary features

Spatial models show that genetic differentiation between populations can be explained by factors ranging from geographic distance to environmental resistance across the landscape. However, genomes exhibit a landscape of differentiation, which could indicate that multiple spatial models better explain divergence in different portions of the genome. We test whether alternative geographic predictors of intraspecific differentiation vary across the genome in ten bird species that co-occur in Sonoran and Chihuahuan Deserts of North America. Using population-level genomic data, we characterized the genomic landscapes across species and modeled five predictors that represented historical and contemporary mechanisms. The characteristics of genomic landscapes differed across the ten species, influenced by varying levels of population structuring and admixture between deserts. General dissimilarity matrix modeling indicated that the best-fit models differed from the whole genome and partitions along the genome. Almost all of the historical and contemporary mechanisms were important in explaining genetic distance, but particularly historical and contemporary environment, while contemporary abundance, position of the barrier to gene flow, and distance explained relatively less. Individual species have significantly different patterns of genomic variation. These results illustrate that the genomic landscape of differentiation was influenced by alternative geographic factors operating on different portions of the genome.

evolutionary biology↗

bioRxiv2022

Complete chloroplast genomes and phylogeny in three Euterpe palms (E. edulis, E. oleraceae and E. precatoria) from different Brazilian biomes

The Brazilian palm fruits and hearts-of-palm of Euterpe edulis, E. oleracea and E. precatoria are an important source for agro-industrial production, but overexploitation requires conservation strategies to maintain genetic diversity. Chloroplast genomes have conserved sequences, which are useful to explore evolutionary questions. Besides the plastid DNA, genome skimming allows the identification of other genomic resources, such as single nucleotide polymorphisms (SNPs), providing information about the genetic diversity of species. We sequenced the chloroplast genome and identified gene content in the three Euterpe species. We performed comparative analyses, described the polymorphisms among the chloroplast genome sequences (repeats, indels and SNPs) and performed a phylogenomic inference based on 55 palm species chloroplast genomes. Finally, using the remaining data from genome skimming, the nuclear and mitochondrial reads, we identified SNPs and estimated the genetic diversity among these Euterpe species. The Euterpe chloroplast genomes varied from 159,232 to 159,275 bp and presented a conserved quadripartite structure with high synteny with other palms. In a pairwise comparison, we found a greater number of insertions/deletions (indels = 93 and 103) and SNPs (284 and 254) between E. edulis/E. oleracea and E. edulis/E. precatoria when compared to E. oleracea/E. precatoria (58 indels and 114 SNPs). Also, the phylogeny indicated a closer relationship between E. oleracea/E. precatoria. The nuclear and mitochondrial genome analyses identified 1,077 SNPs and high divergence among species (FST = 0.77), especially between E. edulis and E. precatoria (FST = 0.86). These results showed that, despite the few structural differences among the chloroplast genomes of these Euterpe palms, a differentiation between E. edulis and the other Euterpe species can be identified by point mutations. This study not only brings new knowledge about the evolution of Euterpe chloroplast genomes, but also these new resources open the way for future phylogenomic inferences and comparative analyses within Arecaceae.

evolutionary biology↗

bioRxiv2022

Genes ruler for genomes, Gnodes, measures assembly accuracy in animals and plants

Gnodes is a Genome Depth Estimator for animal and plant genomes, also a genome size estimator. It calculates genome sizes based on DNA coverage of assemblies, using unique, conserved gene spans for its standard depth. Results of this tool match the independent measures from flow cytometry of genome size quite well in tests with plants and animals. Tests on a range of model and non-model animal and plant genome assemblies give reliable and accurate results, in contrast to less reliable K-mer histogram methods. The problem of half-sized assemblies of duplication-rich Daphnia is addressed. A 20-year old Arabidopsis genome discrepancy is resolved in favor of 157Mb as measured with flow-cytometry. Not all genome DNA samples contain a genome, examples and reasons for this are discussed. The T2T completed human genome assembly of 2022 is complete by Gnodes measures, with about 5% uncertainty. With full genome DNA, Gnodes measures within 10%, usually within 5%, of flow cytometry, indicating they are both measuring the same content. Public URL: http://eugenes.org/EvidentialGene/other/gnodes/

bioinformatics↗

bioRxiv2022

Genome size changes by duplication, insertion and divergence in Caenorhabditis worms

Genome size has been measurable since the 1940s but we still do not understand the basis of genome size variation. Caenorhabditis nematodes show strong conservation of chromosome number but vary in genome size between closely related species. Androdioecy, where populations are composed of males and self-fertile hermaphrodites, has evolved from outcrossing, female-male dioecy, three times in this group. Androdioecious genomes are 10-30% smaller than dioecious species but large phylogenetic distances and rapid protein evolution have made it difficult to pinpoint the basis of these changes. Here, we analyze the genome sequences of Caenorhabditis and and test three hypotheses explaining genome evolution: 1) genomes evolve through deletions and genome shrinkage in androdioecious species; 2) genome size is determined by transposable element (TE) expansion and DNA loss through large deletions (the accordion model); and 3) TE dynamics differ in androdioecious and dioecious species. We find no evidence for these hypotheses in Caenorhabditis. Across both short and long evolutionary distances Caenorhabditis genomes evolve through small structural variant (SV) mutations including frequent duplications and insertions, predominantly in genic regions. Caenorhabditis have rapid rates of gene family expansion and contraction and we identify 71 protein families with significant, parallel decreases across self-fertile Caenorhabditis. These include genes involved in the sensory system, regulatory proteins and membrane-associated immune responses, reflecting the shifting selection pressures that result from self-fertility. Our results suggest that the rules governing genome evolution differ between organisms based on ecology, life style and reproductive system.

evolutionary biology↗

bioRxiv2022

Genomic diversity and molecular epidemiology of a multidrug resistant Pseudomonas aeruginosa DMC30b isolated from hospitalized burn patient in Bangladesh

ObjectivesPseudomonas aeruginosa is a key opportunistic pathogen causing a wide range of community- and hospital-acquired infections in immunocompromised or catheterized patients. Here, we report the complete genome sequence of a multidrug resistant (MDR) P. aeruginosa DMC30b in order to elucidate the genetic diversity, molecular epidemiology, and underlying mechanisms for antimicrobial resistance and virulence. MethodsP. aeruginosa DMC30b was isolated from septic wound swab of a severe burn patient. Whole-genome sequencing (WGS) was performed under Ion Torrent platform. The genome was annotated using the SPAdes v. 3.12.01 in an integrated Genome Analysis Platform (IonGAP) for Ion Torrent sequence data. The genome was annotated using the NCBI Prokaryotic Genome Annotation Pipeline (PGAP). In-silico predictions of antimicrobial resistance genes (ARGs), virulence factor genes (VFGs) and metabolic functional potentials were performed using different curated bioinformatics tools. ResultsP. aeruginosa DMC30b was classified as MDR and belongs to sequence type 244 (ST244). The complete genome size is 6,994,756 bp with a coverage of 76.76x, G+C content of 65.7% and a BUSCO (Benchmarking Universal Single-Copy Orthologs) score of 100. The genome of P. aeruginosa DMC30b harboured two plasmids (e,g., IncP-6 plasmid p10265-KPC; 78,007 bp and ColRNAI_pkOIISD1; 9,359 bp), 35 resistomes (ARGs) conferring resistance to 18 different antibiotics (including four beta-lactam classes), and 214 VFGs. It was identified as the 167th ST244 strain among [~] 5,800 whole-genome sequences of P. aeruginosa available in the NCBI database. ConclusionP. aeruginosa DMC30b belongs to ST244 and was identified as the 167th such isolate to be submitted to NCBI, and the first complete ST244 genome from Bangladesh. The complete genome data with high genetic diversity and underlying mechanisms for antimicrobial resistance and virulence of P. aeruginosa DMC30b (ST244) will aid in understanding the evolution and phylogeny of such high-risk clones and provide a solid basis for further research on MDR or extensively drug resistant strains.

microbiology↗

bioRxiv2022

Single-molecule sequencing of animal mitochondrial genomes reveals chloroplast-like architecture and repeat-mediated recombination

Recent advances in long-read sequencing technology have allowed for single-molecule sequencing of entire mitochondrial genomes, opening the door for direct investigation of mitochondrial genome architecture and landscapes of recombination. We used PacBio sequencing to re-assemble mitochondrial genomes from two species of New Zealand freshwater snails, Potamopyrgus antipodarum and Potamopyrgus estuarinus. These assemblies revealed a [~]1.7 kb structure within the mitochondrial genomes of both species that was previously undetected by assembly of short sequencing reads and likely corresponding to a large non-coding region commonly present in mitochondrial genomes. The overall architecture of these Potamopyrgus mitochondrial genomes is reminiscent of the chloroplast genomes of land plants, harboring a large single-copy region (LSC) and a small single-copy region (SSC) separated by a pair of inverted repeats (IRa and IRb). Individual sequencing reads that spanned across the Potamopyrgus IRa-SSC-IRb structure revealed the occurrence of "flip-flop" recombination, apparently mediated by the IRs. We also detected evidence for two distinct IR haplotypes and recombination between them in wild-caught P. estuarinus, as well as extensive inter-molecular recombination between SNPs in the LSC region. Together, these observations suggest that mitochondrial inheritance is not strictly maternal in these snails. The chloroplast-like architecture and repeat-mediated mitochondrial recombination we describe here raise fundamental questions regarding the origins and commonness of such architecture, whether and how recombination mediates mitochondrial genome evolution, and the role of genome architecture in driving cytoplasmic genome biology and the maintenance of cytoplasmic genomes.

evolutionary biology↗