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bioRxiv2020

Establishment of quantitative RNAi-based forward genetics in Entamoeba histolytica and identification of genes required for growth

While Entamoeba histolytica remains a globally important pathogen, it is dramatically understudied. The tractability of E. histolytica has historically been limited, which is largely due to challenging features of its genome. To enable forward genetics, we constructed and validated the first genome-wide E. histolytica RNAi knockdown mutant library. This library allows for Illumina deep sequencing analysis for quantitative identification of mutants that are enriched or depleted after selection. We developed a novel analysis pipeline to precisely define and quantify gene fragments. We used the library to perform the first RNAi screen in E. histolytica and identified slow growth (SG) mutants. Among genes targeted in SG mutants, many had annotated functions consistent with roles in cellular growth or metabolic pathways. Some targeted genes were annotated as hypothetical or lacked annotated domains, supporting the power of forward genetics in uncovering functional information that cannot be gleaned from databases. While the localization of neither of the proteins targeted in SG1 nor SG2 mutants could be predicted by sequence analysis, we showed experimentally that SG1 localized to the cytoplasm and cell surface, while SG2 localized to the cytoplasm. Overexpression of SG1 led to increased growth, while expression of a truncation mutant did not lead to increased growth, and thus aided in defining functional domains in this protein. Finally, in addition to establishing forward genetics, we uncovered new details of the unusual E. histolytica RNAi pathway. These studies dramatically improve the tractability of E. histolytica and open up the possibility of applying genetics to improve understanding of this important pathogen. Author SummaryEntamoeba histolytica is a globally important pathogen that is dramatically understudied. One of the major limitations of this organism is its challenging genome. RNAi is the state-of-the-art tool for genetic manipulation in E. histolytica, though the RNAi pathway has several noncanonical features. Here, we harnessed the RNAi pathway to enable RNAi-based forward genetics for the first time in this organism. We validated the RNAi library by performing the first E. histolytica RNAi screen and identified slow growth mutants. We showed that independently-generated mutants also exhibited slow growth phenotypes, and we characterized protein localization and domains for some of the identified slow growth genes. The RNAi library that we constructed enables modern, quantitative Illumina deep sequencing analysis to identify mutants that are enriched or depleted after selection. We developed a novel analysis pipeline to precisely define and quantify full-length gene fragments inferred from read mapping. Our approach differs from previous approaches for analysis of RNAi screens, and it better represents the actual DNA fragments and their quantities. This study dramatically improves the tractability of this important pathogen. Moreover, the strategies behind this RNAi library, and its analysis, are novel, and can be applied to other organisms. Author ContributionsA.B. designed and performed the experiments, except fragmentation of gDNA, immunofluorescence, and growth curves with expression of full-length or truncated proteins. R.L.S. performed SG1 and SG2 immunofluorescence experiments. M.C.R. performed growth curves with expression of full-length or truncated proteins. W.H. generated transfectants expressing full-length SG2. C.G.B. fragmented gDNA and processed the fragments to enable subsequent plasmid library construction. T.S.Y.T. and H.W.M. performed Gal/GalNAc lectin immunofluorescence experiments. S.S.H. designed the analysis strategy for Illumina sequencing data, and analyzed all Illumina sequencing data. M.L.S. oversaw the Illumina analysis approach. K.S.R. performed growth curves, conceived of the overall approach and oversaw the design and analysis of the experiments. A.B., S.S.H., and K.S.R. wrote the manuscript.

microbiology↗

bioRxiv2020

Coordinated evolution between N2 neuraminidase and H1 and H3 hemagglutinin genes increased influenza A virus genetic diversity in swine

AO_SCPLOWBSTRACTC_SCPLOWThe neuraminidase (NA) and hemagglutinin (HA) of influenza A virus (IAV) are essential surface glycoproteins. In this study, the evolution of subtype N2 NA paired with H1 and H3 subtype HA in swine was evaluated to understand if genetic diversity of HA and NA were linked. Using time-scaled Bayesian phylodynamic analyses, the relationships of paired swine N2 with H1 or H3 from 2009 to 2018 were evaluated. These data demonstrated increased relative genetic diversity within the major N2 clades circulating in swine (N2.1998 between 2014-2017 and N2.2002 between 2010-2016). Relative genetic diversity of NA-HA pairs (e.g., N2.1998B/ H1.Delta1B) were correlated, suggesting intergene epistasis. Preferential pairing was observed among specific NA and HA genetic clades and this was associated with gene reassortment between cocirculating influenza A strains. Using the phylogenetic topology of inferred N2 trees, the expansion of genetic diversity in the NA gene was quantified and increases in diversity were observed subsequent to NA-HA reassortment events. The rate of evolution among NA-N2 clades and HA-H1 and HA-H3 clades were similar. The frequent regional movement of pigs and their influenza viruses is a possible explanation driving this pattern of drift, reassortment, and rapid evolution. Bayesian phylodynamic analyses demonstrated strong spatial patterns in N2 genetic diversity, and that frequent interstate movement of N2 clades homogenized diversity. The reassortment and evolution of NA and its influence on HA evolution may affect antigenic drift, impacting vaccine control programs and animal health.

evolutionary biology↗

bioRxiv2020

Heritable Genetic Background Alters Survival and Phenotype of Mll-AF9-Induced Leukemias

The MLL-AF9 fusion protein occurring as a result of t(9;11) translocation gives rise to pediatric and adult acute leukemias of distinct lineages, including acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), and mixed phenotype acute leukemia (MPAL). The mechanisms underlying how this same fusion protein results in diverse leukemia phenotypes among different individuals is not well understood. Given emerging evidence from genome-wide association studies (GWAS) that genetic risk factors contribute to MLL-rearranged leukemogenesis, here we tested the impact of genetic background on survival and phenotype of a well-characterized Mll-AF9 knockin mouse model. We crossed this model to five distinct inbred strains (129, A/J, C57BL/6, NOD, CAST), and tested their F1 hybrid progeny for dominant genetic effects on Mll-AF9 phenotypes. We discovered that genetic background altered peripheral blood composition, with Mll-AF9 CAST F1 demonstrating significantly increased B lymphocyte frequency while the remainder of the strains exhibited myeloid-biased hematopoiesis, similar to the parental line. Genetic background also impacted overall survival, with Mll-AF9 A/J F1 and Mll-AF9 129 F1 having significantly shorter survival, and Mll-AF9 CAST F1 having longer survival, compared to the parental line. Furthermore, we observed a range of hematologic malignancies, with Mll-AF9 A/J F1, Mll-AF9 129 F1 and Mll-AF9 B6 F1 developing exclusively myeloid cell malignancies (myeloproliferative disorder (MPD) and AML) whereas a subset of Mll-AF9 NOD F1 developed MPAL and Mll-AF9 CAST F1 developed ALL. This study provides a novel in vivo experimental model to evaluate the underlying mechanisms by which MLL-AF9 results in diverse leukemia phenotypes and provides definitive experimental evidence that genetic risk factors contribute to survival and phenotype of MLL-rearranged leukemogenesis.

cancer biology↗

bioRxiv2020

Co-expression networks from gene expression variability between genetically identical seedlings can reveal novel regulatory relationships

Co-expression networks are a powerful tool to understand gene regulation. They have been used to identify new regulation and function of genes involved in plant development and their response to the environment. Up to now, co-expression networks have been inferred using transcriptomes generated on plants experiencing genetic or environmental perturbation, or from expression time series. We propose a new approach by showing that co-expression networks can be constructed in the absence of genetic and environmental perturbation, for plants at the same developmental stage. For this we used transcriptomes that were generated from genetically identical individual plants that were grown in the same conditions and for the same amount of time. Twelve time points were used to cover the 24h light/dark cycle. We used variability in gene expression between individual plants of the same time point to infer a co-expression network. We show that this network is biologically relevant and use it to suggest new gene functions and to identify new targets for the transcription factors GI, PIF4 and PRR5. Moreover, we find different co-regulation in this network based on changes in expression between individual plants, compared to the usual approach requiring environmental perturbation. Our work shows that gene co-expression networks can be identified using variability in gene expression between individual plants, without the need for genetic or environmental perturbations. It will allow further exploration of gene regulation in contexts with subtle differences between plants, which could be closer to what individual plants in a population might face in the wild. Author summaryPlant development and response to changes in the environment are strongly regulated at the level of gene expression. That is why understanding how gene expression is regulated is key, and transcriptome approaches have allowed the analysis of transcription for all genes of the genome. Extracting useful information from the high amount of data generated by transcriptomes is a challenge, and gene co-expression networks are a powerful tool to do this. The principle is to find genes that co-vary in expression in different conditions and to pair them together. Communities of genes that are more closely linked are then identified and this is the starting point to look for their implication in the same pathway. Co-expression networks have been used to identify new regulation and function of genes involved in plant development and their response to the environment. They were constructed using transcriptomes generated on plants experiencing genetic or environmental perturbation. We show that co-expression networks can in fact be constructed in the absence of genetic and environmental perturbation. Our work will allow further exploration of gene co-regulation in contexts with subtle differences between plants, which could be closer to what individual plants in a population might face in the wild.

plant biology↗

bioRxiv2020

Genetic diversity increases food-web persistence in the face of climate warming

Genetic diversity provides the raw material for species to adapt and persist in the face of climate change. Yet, the extent to which these genetic effects scale at the level of ecological communities remains unclear. Here we experimentally test the effect of plant genetic diversity on the persistence of an insect food web under a current and future warming scenario. We found that plant genetic diversity increased food-web persistence by increasing the intrinsic growth rates of species across multiple trophic levels. This positive effect was robust to a 3{degrees}C warming scenario and resulted from allelic variation at two genes that control the biosynthesis of chemical defenses. Our results suggest that the ongoing loss of genetic diversity may undermine the persistence and functioning of ecosystems in a changing world. One Sentence SummaryThe loss of genetic diversity accelerates the extinction of inter-connected species from an experimental food web.

ecology↗

bioRxiv2020

Patterns of genetic variation in a prairie wildflower, Silphium integrifolium, suggest a non-prairie origin and untapped variation available for improved breeding.

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSPremiseC_ST_ABSUnderstanding the relationship between genetic structure and geography provides information about a species evolutionary history and can be useful to breeders interested in de novo domestication. The North American prairie is especially interesting because of its relatively recent origin and subsequent dramatic fragmentation and degradation. Silphium integrifolium is an iconic perennial American prairie wildflower targeted for domestication as an oilseed crop. Germplasm in the existing breeding program is derived from accessions collected in restricted geographic regions. We present the first application of population genetic data in this species to address the following goals (1) improve breeding programs by characterizing genetic structure and (2) identify the species geographic origin and potential targets and drivers of selection during range expansion. MethodsWe developed a reference transcriptome as a genotyping reference for samples from throughout the species range. Population genetic analyses were used to describe the distribution of genetic variation and demographic modeling was used to characterize potential processes that shaped variation. Outlier scans for selection and associations with environmental variables were used to identify loci linked to putative targets and drivers of selection. Key resultsGenetic variation partitions samples into three geographic clusters. Patterns of variation and demographic modeling suggest that the species origin is in the American southeast. Breeding program accessions are from the region with lowest observed genetic variation. ConclusionsThis iconic prairie species did not originate within the modern prairie. Breeding programs can be improved by including accessions from outside of the germplasm founding region, which has relatively little variation. The geographic structuring coupled with the identified targets and drivers of adaptation can guide collecting efforts towards populations with beneficial agronomic traits.

evolutionary biology↗

bioRxiv2020

Analysis of genetic diversity and association of seed and mucilage yields with inter simple sequence repeats (ISSR) polymorphism in a collection of Plantgao species

Analysis of genetic diversity in medicinal plants assists germplasm conservation and selection for use in breeding schemes. The aims of the present study were to assess genetic diversity and differentiation of several Plantago species using Inter Simple Sequence Repeats (ISSR) markers and identify marker-trait associations (MTAs). Thirty-one Plantago accessions belonging to eight species with various mating system and chromosome number were collected from geographical regions of Iran environments. Polymorphism in the DNA of Plantago accessions were analyzed using polymerase chain reaction (PCR) of 25 ISSR primers. The data for number of polymorphic bands were analyzed on the basis of several genetic diversity parameters. The results of gel analysis indicated that the ISSR primers amplified 5 to 21 polymorphic bands with 100 to 3000 bp size. The mean polymorphism was 83.83% and five primers showed 100% polymorphism among Plantago accessions. The Polymorphism Information Content (PIC) for ISSR as a dominant marker ranged from 0.1103 to 0.3829 with the mean 0.2727 in the species tested. Accessions in P. amplexicaulis and P. pysillum species represented the highest Neis and Shannons genetic diversity whilst the lowest obtained for P. lagopus. Analysis of phylogenetic network generated by the Neighbor-Net Algorithm showed moderate split of the eight species tested and the network depicted moderate conflict. The principal coordinate analysis (PCoA) results showed lower conflict in separation of accessions of the eight species. Fifty-six significant MTAs were detected for the traits tested in Plantago accessions, of which six were shared between three seed and mucilage traits and 24 were common between two traits. The coefficient of determination (R2) for the identified MTAs varied between 32 and 73%. In conclusion, the results of genetic diversity analysis suggested that ISSR marker could efficiently differentiate Plantago species and the information of genetic diversity might assist Plantago improvement and conservation.

plant biology↗

bioRxiv2020

Novel tunable spatio-temporal patterns from a simple genetic oscillator circuit

Multicellularity, the coordinated collective behaviour of cell populations, gives rise to the emergence of self-organized phenomena at many different spatio-temporal scales. At the genetic scale, oscillators are ubiquitous in regulation of multicellular systems, including during their development and regeneration. Synthetic biologists have successfully created simple synthetic genetic circuits that produce oscillations in single cells. Studying and engineering synthetic oscillators in a multicellular chassis can therefore give us valuable insights into how simple genetic circuits can encode complex multicellular behaviours at different scales. Here we develop a study of the coupling between the repressilator synthetic genetic ring oscillator and constraints on cell growth in colonies. We show in silico how mechanical constraints generate characteristic patterns of growth rate inhomogeneity in growing cell colonies. Next, we develop a simple one-dimensional model which predicts that coupling the repressilator to this pattern of growth rate via protein dilution generates travelling waves of gene expression. We show that the dynamics of these spatio-temporal patterns are determined by two parameters; the protein degradation and maximum expression rates of the repressors. We derive simple relations between these parameters and the key characteristics of the travelling wave patterns: firstly, wave speed is determined by protein degradation and secondly, wavelength is determined by maximum gene expression rate. Our analytical predictions and numerical results were in close quantitative agreement with detailed individual based simulations of growing cell colonies. Confirming published experimental results we also found that static ring patterns occur when protein stability is high. Our results show that this pattern can be induced simply by growth rate dilution and does not require transition to stationary phase as previously suggested. Our method generalizes easily to other genetic circuit architectures thus providing a framework for multi-scale rational design of spatio-temporal patterns from genetic circuits. We use this method to generate testable predictions for the synthetic biology design-build-test-learn cycle.

bioengineering↗

bioRxiv2020

Genetic information insecurity as state of the art

Genetic information is being generated at an increasingly rapid pace, offering advances in science and medicine that are paralleled only by the threats and risk present within the responsible ecosystem. Human genetic information is identifiable and contains sensitive information, but genetic data security is only recently gaining attention. Genetic data is generated in an evolving and distributed cyber-physical ecosystem, with multiple systems that handle data and multiple partners that utilize the data. This paper defines security classifications of genetic information and discusses the threats, vulnerabilities, and risk found throughout the entire genetic information ecosystem. Laboratory security was found to be especially challenging, primarily due to devices and protocols that were not designed with security in mind. Likewise, other industry standards and best practices threaten the security of the ecosystem. A breach or exposure anywhere in the ecosystem can compromise sensitive information. Extensive development will be required to realize the potential of this emerging field while protecting the bioeconomy and all of its stakeholders.

genomics↗

bioRxiv2020

Genetic Diversity and Structure of Oryza rufipogon Griff. Populations in the Philippines

Oryza rufipogon Griff. or Rufi is the wild progenitor of the cultivated rice, Oryza sativa L. In the Philippines, Rufi was previously known to be found only in Lake Apo, Bukidnon. However, a new population was identified in Lake Napalit in the same province. Based on previous morphological diversity assessment, both populations are unique for at least three characters, i.e., leaf, culm, and awn lengths. Environmental parameters such as rainfall and air temperature also differed between the two lakes. With these, an assessment of Rufis genetic diversity at the molecular level is beneficial to further ascertain its usefulness in rice breeding and gain insights on its conservation status. Thus, this study estimated the degree of genetic diversity and determined the population structure of 41 samples of natural Rufi populations in the Philippines using SSR markers. A total of 98 genome wide polymorphic SSR markers were selected to examine the genetic diversity and structure of Rufi populations, along with seven rice cultivars for comparison. Results showed that Philippine Rufi populations have lower genetic diversity compared to cultivated rice accessions and other Rufi populations in Southeast Asia and China. This low genetic diversity suggested that Rufi populations might be in a genetic bottleneck, perhaps due to observed unsustainable farming practices near their habitat and lack of awareness of their importance. A significant population structure and differentiation were determined using the STRUCTURE and phylogenetic analyses. Population differentiation might be due to geographic isolation which prevented gene flow between the two populations and the unique climatic conditions between the two lakes.

ecology↗

bioRxiv2020

Balancing selection maintains ancient genetic diversity in C. elegans

Across diverse taxa, selfing species have evolved independently from outcrossing species thousands of times. The transition from outcrossing to selfing significantly decreases the effective population size, effective recombination rate, and heterozygosity within a species. These changes lead to a reduction in genetic diversity, and therefore adaptive potential, by intensifying the effects of random genetic drift and linked selection. Within the nematode genus Caenorhabditis, selfing has evolved at least three times and all three species, including in the model organism Caenorhabditis elegans, show substantially reduced genetic diversity relative to outcrossing species. Selfing and outcrossing Caenorhabditis species are often found in the same niches, but we still do not know how selfing species with limited genetic diversity can adapt to these environments. Here, we examine the whole-genome sequences from 609 wild C. elegans strains isolated worldwide and show that genetic variation is concentrated in punctuated hyper-divergent regions that cover 20% of the C. elegans reference genome. These regions are enriched in environmental response genes that mediate sensory perception, pathogen response, and xenobiotic stress response. Population genomic evidence suggests that genetic diversity in these regions has been maintained by long-term balancing selection. Using long-read genome assemblies for 15 wild strains, we show that hyper-divergent haplotypes contain unique sets of genes and show levels of divergence comparable to levels found between Caenorhabditis species that diverged millions of years ago. These results provide an example for how species can avoid the evolutionary "dead end" associated with selfing.

evolutionary biology↗

bioRxiv2020

Quantitative trait locus mapping reveals an independent genetic basis for joint divergence in leaf function, life-history, and floral traits between scarlet monkeyflower (Mimulus cardinalis) populations

PREMISEAcross taxa, vegetative and floral traits that vary along a fast-slow life-history axis are often correlated with leaf functional traits arrayed along the leaf economics spectrum, suggesting a constrained set of adaptive trait combinations. Such broad-scale convergence may arise from genetic constraints imposed by pleiotropy (or tight linkage) within species, or from natural selection alone. Understanding the genetic basis of trait syndromes and their components is key to distinguishing these alternatives and predicting evolution in novel environments. METHODSWe used a line-cross approach and quantitative trait locus (QTL) mapping to characterize the genetic basis of twenty leaf functional/physiological, life history, and floral traits in hybrids between annualized and perennial populations of scarlet monkeyflower (Mimulus cardinalis). RESULTSWe mapped both single and multi-trait QTLs for life history, leaf function and reproductive traits, but found no evidence of genetic co-ordination across categories. A major QTL for three leaf functional traits (thickness, photosynthetic rate, and stomatal resistance) suggests that a simple shift in leaf anatomy may be key to adaptation to seasonally dry habitats. CONCLUSIONSOur results suggest that the co-ordination of resource-acquisitive leaf physiological traits with a fast life history and more selfing mating system results from environmental selection rather than functional or genetic constraint. Independent assortment of distinct trait modules, as well as a simple genetic basis to leaf physiological traits associated with drought escape, may facilitate adaptation to changing climates.

plant biology↗

bioRxiv2020

High Throughput Computational Mouse Genetic Analysis

BackgroundGenetic factors affecting multiple biomedical traits in mice have been identified when GWAS data that measured responses in panels of inbred mouse strains was analyzed using haplotype-based computational genetic mapping (HBCGM). Although this method was previously used to analyze one dataset at a time; but now, a vast amount of mouse phenotypic data is now publicly available, which could lead to many more genetic discoveries. ResultsHBCGM and a whole genome SNP map covering 53 inbred strains was used to analyze 8462 publicly available datasets of biomedical responses (1.52M individual datapoints) measured in panels of inbred mouse strains. As proof of concept, causative genetic factors affecting susceptibility for eye, metabolic and infectious diseases were identified when structured automated methods were used to analyze the output. One analysis identified a novel genetic effector mechanism; allelic differences within the mitochondrial targeting sequence affected the subcellular localization of a protein. We also found allelic differences within the mitochondrial targeting sequences of many murine and human proteins, and these could affect a wide range of biomedical phenotypes. ImplicationsThese initial results indicate that genetic factors affecting biomedical responses could be identified through analysis of very large datasets, and they provide an early indication of how this type of augmented intelligence can facilitate genetic discovery.

bioinformatics↗

bioRxiv2020

Prevalence of genetically similar Flavobacterium columnare phages across aquaculture environments reveals a strong potential for pathogen control

Intensive aquaculture conditions expose fish to bacterial infections, leading to significant financial losses, extensive antibiotic use and risk of antibiotic resistance in target bacteria. Flavobacterium columnare causes columnaris disease in aquaculture worldwide. To develop a bacteriophage-based control of columnaris disease, we isolated and characterized 126 F. columnare strains and 63 phages against F. columnare from Finland and Sweden. Bacterial isolates were virulent on rainbow trout (Oncorhynchus mykiss) and fell into four previously described genetic groups A, C, E and G, with genetic groups C and E being the most virulent. Phage host range studied against a collection of 228 bacterial isolates demonstrated modular infection patterns based on host genetic group. Phages infected contemporary and previously isolated bacterial hosts, but bacteria isolated most recently were generally resistant to previously isolated phages. Despite large differences in geographical origin, isolation year or host range of the phages, whole genome sequencing of 56 phages showed high level of genetic similarity to previously isolated F. columnare phages (Ficleduovirus, Myoviridae). Altogether, this phage collection demonstrates a potential to be used in phage therapy. Significance StatementBacteriophages were discovered already over a century ago, and used widely in treatment of bacterial diseases before the era of antibiotics. Due to harmful effects of antibiotic leakage into environment, aquaculture is a potential target for phage therapy. However, the development of efficient phage therapy approach requires detailed characterization of bacterial pathogen virulence and phage host range. Here, we describe phage-bacterium interactions in the fish pathogen Flavobacterium columnare. We found that genetically similar phages are found from different fish farms, and their infectivity cluster according to genetic group of bacteria. In addition, phages were able to infect bacterial hosts from other farms, which is a preferable trait considering phage therapy approach. However, the most recently isolated phages had broader host range than the previously isolated phages, suggesting a response in the phage community to evolution of resistance in the bacteria. These results show that designing phage therapy for aquaculture (and other) systems needs consideration of both temporal and geographical aspects of the phage-bacterium interaction.

microbiology↗

bioRxiv2020

Temporal stability and genetic diversity of 48-year old T-series phages

T-series phages have been model organisms for molecular biology since the 1940s. Given that these phages have been stocked, distributed, and propagated for decades across the globe, there exists the potential for genetic drift to accumulate between stocks over time. Here we compared the temporal stability and genetic relatedness of laboratory-maintained phage stocks with a T-series collection from 1972. Only the T-even phages produced viable virions. We obtained complete genomes of these T-even phages, along with two contemporary T4 stocks. Performing comparative genomics, we found 12 and 16 nucleotide variations, respectively, in the genomes of T2 and T6; whereas there were ~172 nucleotide variations between T4-sublines when compared with NCBI RefSeq genome. To account for the possibility of artefacts in the NCBI RefSeq, we used the 1972 T4 stock as a reference and compared genetic and phenotypic variations between T4-sublines. Genomic analysis predicted nucleotide variations in genes associated with DNA metabolism and structural proteins. We did not however, observe any differences in growth characteristics or host range between the T4-sublines. Our study highlights the potential for genetic drift between individually maintained T-series phage stocks, yet after 48-years, this has not resulted in phenotypic alternations in these important model organisms. ImportanceT-series bacteriophages have been used throughout the world for various molecular biology researches, which were critical for establishing the fundamentals of molecular biology - from the structure of DNA to advanced gene-editing tools. These model bacteriophages help keep research data consistent and comparable between laboratories. However, we observed genetic variability when compared contemporary sublines of T4-phages to a 48-year old stock of T4. This may have effects in the comparability of results obtained using T4 phage. Here, we highlighted the genomic differences between T4 sublines and examined phenotypic differences in phage replication parameters. We observed limited genomic changes but no phenotypic variations between T4 sublines. Our research highlights the possibility of genetic drift in model bacteriophages.

microbiology↗

bioRxiv2020

Understanding the genetic diversity of the guayabillo (Psidium galapageium), an endemic plant of the Galapagos Islands

Oceanic archipelagos are known to host a variety of endemic plant species. The genetic diversity and structure of these species is an important indicator of their evolutionary history and can inform appropriate conservation strategies that mitigate the risks to which theyre exposed, including invasive species and environmental disturbances. A comprehensive consideration of the role of their natural history, as well as the landscape features and the geological history of the islands themselves is required to adequately understand any emerging patterns. Such is the case for the guayabillo (Psidium galapageium), an understudied endemic plant from the Galapagos Islands with important ecological and economic roles. In this study we designed and evaluated 13 informative SSR markers and used them to investigate the genetic diversity, population structure and connectivity of the guayabillo populations from San Cristobal, Isabela and Santa Cruz islands. A total of 208 guayabillo individuals were analyzed, revealing a strong population structure between islands and two distinct genetic lineages for the Santa Cruz population. Overall, the guayabillo genetic diversity is relatively high, an unusual pattern for an insular endemic species which is possibly explained by its polyploidy and the geographical features of the islands. These include their broad altitudinal ranges and habitat heterogeneity. For populations displaying a lower genetic diversity such as San Cristobal, the history of human disturbance could be an important factor explaining these observations. Some similarities between individuals in Santa Cruz and the San Cristobal population could be explained by population differentiation or distinct natural histories of separate lineages. Our findings highlight the complex population dynamics that shape the genetic diversity of species like the guayabillo and emphasize the need to explore the currently unresolved questions about this Galapagos endemic plant.

plant biology↗

bioRxiv2020

Within-patient genetic diversity of SARS-CoV-2

SARS-CoV-2, the virus responsible for the current COVID-19 pandemic, is evolving into different genetic variants by accumulating mutations as it spreads globally. In addition to this diversity of consensus genomes across patients, RNA viruses can also display genetic diversity within individual hosts, and co-existing viral variants may affect disease progression and the success of medical interventions. To systematically examine the intra-patient genetic diversity of SARS-CoV-2, we processed a large cohort of 3939 publicly-available deeply sequenced genomes with specialised bioinformatics software, along with 749 recently sequenced samples from Switzerland. We found that the distribution of diversity across patients and across genomic loci is very unbalanced with a minority of hosts and positions accounting for much of the diversity. For example, the D614G variant in the Spike gene, which is present in the consensus sequences of 67.4% of patients, is also highly diverse within hosts, with 29.7% of the public cohort being affected by this coexistence and exhibiting different variants. We also investigated the impact of several technical and epidemiological parameters on genetic heterogeneity and found that age, which is known to be correlated with poor disease outcomes, is a significant predictor of viral genetic diversity. Author SummarySince it arose in late 2019, the new coronavirus (SARS-CoV-2) behind the COVID-19 pandemic has mutated and evolved during its global spread. Individual patients may host different versions, or variants, of the virus, hallmarked by different mutations. We examine the diversity of genetic variants coexisting within patients across a cohort of 3939 publicly accessible samples and 749 recently sequenced samples from Switzerland. We find that a small number of patients carry most of the diversity, and that patients with more diversity tend to be older. We also find that most of the diversity is concentrated in certain regions and positions of the virus genome. In particular, we find that a variant reported to increase infectivity is among the most diverse positions. Our study provides a large-scale survey of within-patient diversity of the SARS-CoV-2 genome.

genomics↗

bioRxiv2020

Genetic-variant hotspots and hotspot clusters in the human genome facilitating adaptation while increasing instability

BackgroundGenetic variants, underlining phenotypic diversity, are known to distribute unevenly in the human genome. A comprehensive understanding of the distributions of different genetic variants is important for insights into genetic functions and disorders. MethodsHerein, a sliding-window scan of regional densities of eight kinds of germline genetic variants, including single-nucleotide-polymorphisms (SNPs) and four size-classes of copy-number-variations (CNVs) in the human genome has been performed. ResultsThe study has identified 44,379 hotspots with high genetic-variant densities, and 1,135 hotspot clusters comprising more than one type of hotspots, accounting for 3.1% and 0.2% of the genome respectively. The hotspots and clusters are found to co-localize with different functional genomic features, as exemplified by the associations of hotspots of middle-size CNVs with histone-modification sites, work with balancing and positive selections to meet the need for diversity in immune proteins, and facilitate the development of sensory-perception and neuroactive ligand-receptor interaction pathways in the function-sparse late-replicating genomic sequences. Genetic variants of different lengths co-localize with retrotransposons of different ages on a long-with-young and short-with-all basis. Hotspots and clusters are highly associated with tumour suppressor genes and oncogenes (p < 10-10), and enriched with somatic tumour CNVs and the trait- and disease-associated SNPs identified by genome-wise association studies, exceeding tenfold enrichment in clusters comprising SNPs and extra-long CNVs. ConclusionsIn conclusion, the genetic-variant hotspots and clusters represent two-edged swords that spearhead both positive and negative genomic changes. Their strong associations with complex traits and diseases also open up a potential Common Disease-Hotspot Variant approach to the missing heritability problem.

genomics↗