Genomic Position Research Articles

Research progress on the roles of lncRNAs in plant development and stress responses.

Long non-coding RNAs (lncRNAs) are RNAs of more than 200 nucleotides in length that are not (or very rarely) translated into proteins. In eukaryotes, lncRNAs regulate gene expression at the transcriptional, post-transcriptional, and epigenetic levels. lncRNAs are categorized according to their genomic position and molecular mechanism. This review summarized the characteristics and mechanisms of plant lncRNAs involved in vegetative growth, reproduction, and stress responses. Our discussion and model provide a theoretical basis for further studies of lncRNAs in plant breeding.

Chromosomal Position of Ribosomal Protein Genes Affects Long-Term Evolution of Vibrio cholerae.

It is unclear how gene order within the chromosome influences genome evolution. Bacteria cluster transcription and translation genes close to the replication origin (oriC). In Vibrio cholerae, relocation of s10-spc-α locus (S10), the major locus of ribosomal protein genes, to ectopic genomic positions shows that its relative distance to the oriC correlates to a reduction in growth rate, fitness, and infectivity. To test the long-term impact of this trait, we evolved 12 populations of V. cholerae strains bearing S10 at an oriC-proximal or an oriC-distal location for 1,000 generations. During the first 250 generations, positive selection was the main force driving mutation. After 1,000 generations, we observed more nonadaptative mutations and hypermutator genotypes. Populations fixed inactivating mutations at many genes linked to virulence: flagellum, chemotaxis, biofilm, and quorum sensing. Throughout the experiment, all populations increased their growth rates. However, those bearing S10 close to oriC remained the fittest, indicating that suppressor mutations cannot compensate for the genomic position of the main ribosomal protein locus. Selection and sequencing of the fastest-growing clones allowed us to characterize mutations inactivating, among other sites, flagellum master regulators. Reintroduction of these mutations into the wild-type context led to a ≈10% growth improvement. In conclusion, the genomic location of ribosomal protein genes conditions the evolutionary trajectory of V. cholerae. While genomic content is highly plastic in prokaryotes, gene order is an underestimated factor that conditions cellular physiology and evolution. A lack of suppression enables artificial gene relocation as a tool for genetic circuit reprogramming. IMPORTANCE The bacterial chromosome harbors several entangled processes such as replication, transcription, DNA repair, and segregation. Replication begins bidirectionally at the replication origin (oriC) until the terminal region (ter) organizing the genome along the ori-ter axis gene order along this axis could link genome structure to cell physiology. Fast-growing bacteria cluster translation genes near oriC. In Vibrio cholerae, moving them away was feasible but at the cost of losing fitness and infectivity. Here, we evolved strains harboring ribosomal genes close or far from oriC. Growth rate differences persisted after 1,000 generations. No mutation was able to compensate for the growth defect, showing that ribosomal gene location conditions their evolutionary trajectory. Despite the high plasticity of bacterial genomes, evolution has sculpted gene order to optimize the ecological strategy of the microorganism. We observed growth rate improvement throughout the evolution experiment that occurred at expense of energetically costly processes such the flagellum biosynthesis and virulence-related functions. From the biotechnological point of view, manipulation of gene order enables altering bacterial growth with no escape events.

Nuclear and cytoplasmic lncRNAs in root tips of the model legume Medicago truncatula under control and submergence.

In this study, we aimed to identify long noncoding RNAs (lncRNAs) in root tips of the model legume Medicago truncatula using previously generated nuclear, total polyA, ribosome-associated polyA, and Riboseq RNA datasets, which might shed light on their localization and potential regulatory roles. RNA-seq data were mapped to the version 5 of the M. truncatula A17 genome and analyzed to identify genome annotated lncRNAs and putative new root tip (NRT) lncRNAs. lncRNAs were classified according to their genomic location relative to chromatin accessible regions, protein-coding genes and transposable elements (TE), finding differences between annotated lncRNAs and NRT lncRNAs, both in their genomic position as well as in the type of TEs in their vicinity. We investigated their response to submergence and found a set of regulated lncRNAs that were preferentially upregulated in the nucleus, some of which were located nearby genes of the conserved submergence upregulated gene families, and chromatin accessible regions suggesting a potential regulatory role. Finally, the accumulation of lncRNAs under submergence was validated by reverse transcription quantitative polymerase chain reaction on nuclear RNA, providing additional evidence of their localization, which could ultimately be required for their function.

Allelic contribution of Nrxn1α to autism-relevant behavioral phenotypes in mice.

Copy number variations (CNVs) in the Neurexin 1 (NRXN1) gene, which encodes a presynaptic protein involved in neurotransmitter release, are some of the most frequently observed single-gene variants associated with autism spectrum disorder (ASD). To address the functional contribution of NRXN1 CNVs to behavioral phenotypes relevant to ASD, we carried out systematic behavioral phenotyping of an allelic series of Nrxn1 mouse models: one carrying promoter and exon 1 deletion abolishing Nrxn1α transcription, one carrying exon 9 deletion disrupting Nrxn1α protein translation, and one carrying an intronic deletion with no observable effect on Nrxn1α expression. We found that homozygous loss of Nrxn1α resulted in enhanced aggression in males, reduced affiliative social behaviors in females, and significantly altered circadian activities in both sexes. Heterozygous or homozygous loss of Nrxn1α affected the preference for social novelty in male mice, and notably, enhanced repetitive motor skills and motor coordination in both sexes. In contrast, mice bearing an intronic deletion of Nrxn1 did not display alterations in any of the behaviors assessed. These findings demonstrate the importance of Nrxn1α gene dosage in regulating social, circadian, and motor functions, and the variables of sex and genomic positioning of CNVs in the expression of autism-related phenotypes. Importantly, mice with heterozygous loss of Nrxn1, as found in numerous autistic individuals, show an elevated propensity to manifest autism-related phenotypes, supporting the use of models with this genomic architecture to study ASD etiology and assess additional genetic variants associated with autism.

Comparative analysis of histopathological parameters, genome-wide copy number alterations, and variants in genes involved in cell cycle regulation in chordomas of the skull base and sacrum.

Chordomas are rare tumors of the axial skeleton that are refractory to conventional therapy. Few studies have compared the morphological and molecular characteristics of chordomas according to the skull base and sacral locations. Histopathological data and changes revealed by array comparative genomic hybridization (CGH) and next-generation sequencing (NGS) of cell cycle regulation genes were analyzed for 28 skull base (SBCs) and 15 sacral (SC) chordomas. All cases were conventional chordomas. SBCs were significantly more frequent in patients aged <40 years and SCs predominated in patients aged >60 years. Mitotic indices ≥2 mitoses/10 high-power fields were correlated with high degrees of nuclear atypia and Ki67 labeling indices ≥6%. We identified 321 genomic positions, and copy number variation losses were more frequent than gain. Moreover, we report a panel of 85 genetic variants of cell cycle genes and the presence of molecular clusters for chordoma as well in CGH as in NGS. These new data strengthen the view that the chordoma should not be considered as a single molecular entity.

Insights into the Key Genes in Cucumis melo and Cucurbita moschata ToLCNDV Resistance

Tomato leaf curl New Delhi virus (ToLCNDV, family Geminiviridae, genus Begomovirus) is a whitefly-transmitted virus that causes widespread damage in Cucurbitaceae and Solaneceae crops worldwide. The Spanish strain, ToLCNDV-ES, affects mainly cucurbit crops and has spread through the Mediterranean basin since its first detection in 2013 in the south of Spain. The control of the virus has been based on the adoption of measures to control the vector, which have not been sufficient to reduce production losses. Therefore, the identification of key genes for ToLCNDV resistance is essential for the development of resistant plants. Regarding genetic control of resistance in cucurbit crops, one major locus on chromosome 11 and two additional regions in chromosomes 12 and 2 of C. melo linked to ToLCNDV resistance have been described recently. Concerning C. moschata, a major QTL was also identified on chromosome 8 that resulted in synteny with a QTL on chromosome 11 of C. melo. In this work, we investigated the molecular basis of ToLCNDV resistance in contrasting accessions of C. melo and C. moschata by transcriptional characterization of 10 different candidate genes controlling host factors related to proviral or antiviral mechanisms. Two proviral factor genes, ARP4 in C. melo and SYTA in C. moschata, showed clear differences in expression levels when the susceptible and resistant accessions were compared. The knowledge of proviral factors associated with resistance could be used to screen an active mutagenesis TILLING platform. This is the case of C. pepo, in which no ToLCNDV resistance has been described to date. The relationship between the regulation of the genes ARP4 and SYTA, as well as the genome position of the described loci related to ToLCNDV resistance, is also discussed.

Recycling of parental histones preserves the epigenetic landscape during embryonic development.

Epigenetic inheritance during DNA replication requires an orchestrated assembly of nucleosomes from parental and newly synthesized histones. We analyzed Drosophila HisC mutant embryos harboring a deletion of all canonical histone genes, in which nucleosome assembly relies on parental histones from cell cycle 14 onward. Lack of new histone synthesis leads to more accessible chromatin and reduced nucleosome occupancy, since only parental histones are available. This leads to up-regulated and spurious transcription, whereas the control of the developmental transcriptional program is partially maintained. The genomic positions of modified parental histone H2A, H2B, and H3 are largely restored during DNA replication. However, parental histones with active marks become more dispersed within gene bodies, which is linked to transcription. Together, the results suggest that parental histones are recycled to preserve the epigenetic landscape during DNA replication in vivo.

Integrating top-down and bottom-up approaches to understand the genetic architecture of speciation across a monkeyflower hybrid zone.

Understanding the phenotypic and genetic architecture of reproductive isolation is a long-standing goal of speciation research. In several systems, large-effect loci contributing to barrier phenotypes have been characterized, but such causal connections are rarely known for more complex genetic architectures. In this study, we combine "top-down" and "bottom-up" approaches with demographic modelling toward an integrated understanding of speciation across a monkeyflower hybrid zone. Previous work suggests that pollinator visitation acts as a primary barrier to gene flow between two divergent red- and yellow-flowered ecotypes of Mimulus aurantiacus. Several candidate isolating traits and anonymous single nucleotide polymorphism loci under divergent selection have been identified, but their genomic positions remain unknown. Here, we report findings from demographic analyses that indicate this hybrid zone formed by secondary contact, but that subsequent gene flow was restricted by widespread barrier loci across the genome. Using a novel, geographic cline-based genome scan, we demonstrate that candidate barrier loci are broadly distributed across the genome, rather than mapping to one or a few "islands of speciation." Quantitative trait locus (QTL) mapping reveals that most floral traits are highly polygenic, with little evidence that QTL colocalize, indicating that most traits are genetically independent. Finally, we find little evidence that QTL and candidate barrier loci overlap, suggesting that some loci contribute to other forms of reproductive isolation. Our findings highlight the challenges of understanding the genetic architecture of reproductive isolation and reveal that barriers to gene flow other than pollinator isolation may play an important role in this system.

Effect of reduced genomic representation on using runs of homozygosity for inbreeding characterization.

Genomic measures of inbreeding based on identical-by-descent (IBD) segments are increasingly used to measure inbreeding and mostly estimated on SNP arrays and whole-genome sequencing (WGS) data. However, some softwares recurrently used for their estimation assume that genomic positions which have not been genotyped are nonvariant. This might be true for WGS data, but not for reduced genomic representations and can lead to spurious IBD segments estimation. In this project, we simulated the outputs of WGS, two SNP arrays of different sizes and RAD-sequencing for three populations with different sizes and histories. We compare the results of IBD segments estimation with two softwares: runs of homozygosity (ROHs) estimated with PLINK and homozygous-by-descent (HBD) segments estimated with RZooRoH. We demonstrate that to obtain meaningful estimates of inbreeding, RZooRoH requires a SNPs density 11 times smaller compared to PLINK: ranks of inbreeding coefficients were conserved among individuals above 22 SNPs/Mb for PLINK and 2 SNPs/Mb for RZooRoH. We also show that in populations with simple demographic histories, distribution of ROHs and HBD segments are correctly estimated with both SNP arrays and WGS. PLINK correctly estimated distribution of ROHs with SNP densities above 22 SNPs/Mb, while RZooRoH correctly estimated distribution of HBD segments with SNPs densities above 11 SNPs/Mb. However, in a population with a more complex demographic history, RZooRoH resulted in better distribution of IBD segments estimation compared to PLINK even with WGS data. Consequently, we advise researchers to use either methods relying on excess homozygosity averaged across SNPs or model-based HBD segments calling methods for inbreeding estimations.

Genome-Wide Identification and Phylogenetic and Expression Analyses of the PLATZ Gene Family in Medicago sativa L.

The PLATZ family is a novel class of plant-specific zinc finger transcription factors with important roles in plant growth and development and abiotic stress responses. PLATZ members have been identified in many plants, including Oryza sativa, Zea mays, Triticum aestivum, Fagopyrum tataricum, and Arabidopsis thaliana; however, due to the complexity of the alfalfa reference genome, the members of the PLATZ gene family in alfalfa (Medicago sativa L.) have not been systematically identified and analyzed. In this study, 55 Medicago sativa PLATZ genes (MsPLATZs) were identified in the alfalfa "Xinjiangdaye" reference genome. Basic bioinformatic analysis was performed, including the characterization of sequence lengths, protein molecular weights, genomic positions, and conserved motifs. Expression analysis reveals that 7 MsPLATZs are tissue-specifically expressed, and 10 MsPLATZs are expressed in all examined tissues. The transcriptomic expression of these genes is obvious, indicating that these MsPLATZs have different functions in the growth and development of alfalfa. Based on transcriptome data analysis and real-time quantitative PCR (RT-qPCR), we identified 22, 22, and 21 MsPLATZ genes that responded to salt, cold, and drought stress, respectively, with 20 MsPLATZs responding to all three stresses. This study lays a foundation for further exploring the functions of MsPLATZs, and provides ideas for the improvement of alfalfa varieties and germplasm innovation.

Genome-wide identification of germin-like proteins in peanut (Arachis hypogea L.) and expression analysis under different abiotic stresses.

Peanut is an important food and feed crop, providing oil and protein nutrients. Germins and germin-like proteins (GLPs) are ubiquitously present in plants playing numerous roles in defense, growth and development, and different signaling pathways. However, the GLP members have not been comprehensively studied in peanut at the genome-wide scale. We carried out a genome-wide identification of the GLP genes in peanut genome. GLP members were identified comprehensively, and gene structure, genomic positions, motifs/domains distribution patterns, and phylogenetic history were studied in detail. Promoter Cis-elements, gene duplication, collinearity, miRNAs, protein-protein interactions, and expression were determined. A total of 84 GLPs (AhGLPs ) were found in the genome of cultivated peanut. These GLP genes were clustered into six groups. Segmental duplication events played a key role in the evolution of AhGLPs, and purifying selection pressure was underlying the duplication process. Most AhGLPs possessed a well-maintained gene structure and motif organization within the same group. The promoter regions of AhGLPs contained several key cis-elements responsive to 'phytohormones', 'growth and development', defense, and 'light induction'. Seven microRNAs (miRNAs) from six families were found targeting 25 AhGLPs. Gene Ontology (GO) enrichment analysis showed that AhGLPs are highly enriched in nutrient reservoir activity, aleurone grain, external encapsulating structure, multicellular organismal reproductive process, and response to acid chemicals, indicating their important biological roles. AhGLP14, AhGLP38, AhGLP54, and AhGLP76 were expressed in most tissues, while AhGLP26, AhGLP29, and AhGLP62 showed abundant expression in the pericarp. AhGLP7, AhGLP20, and AhGLP21, etc., showed specifically high expression in embryo, while AhGLP12, AhGLP18, AhGLP40, AhGLP78, and AhGLP82 were highly expressed under different hormones, water, and temperature stress. The qRT-PCR results were in accordance with the transcriptome expression data. In short, these findings provided a foundation for future functional investigations on the AhGLPs for peanut breeding programs.

Deciphering Hierarchical Chromatin Domains and Preference of Genomic Position Forming Boundaries in Single Mouse Embryonic Stem Cells.

The exploration of single-cell 3D genome maps reveals that chromatin domains are indeed physical structures presenting in single cells, and domain boundaries vary from cell to cell. However, systematic analysis of the association between regulatory factor binding and elements and the formation of chromatin domains in single cells has not yet emerged. To this end, a hierarchical chromatin domain structure identification algorithm (named as HiCS) is first developed from individual single-cell Hi-C maps, with superior performance in both accuracy and efficiency. The results suggest that in addition to the known CTCF-cohesin complex, Polycomb, TrxG, pluripotent protein families, and other multiple factors also contribute to shaping chromatin domain boundaries in single embryonic stem cells. Different cooperation patterns of these regulatory factors drive genomic position categories with differential preferences forming boundaries, and the most extensive six types of retrotransposons are differentially distributed in these genomic position categories with preferential localization. The above results suggest that these different retrotransposons within genomic regions interplay with regulatory factors navigating the preference of genomic positions forming boundaries, driving the formation of higher-order chromatin structures, and thus regulating cell functions in single mouse embryonic stem cells.

Novel SNP Markers and Their Application in Low-Cyanide Cassava (Manihot esculenta crantz) Breeding Program

The major flaw of cassava is its indigenous cyanide. Traditional breeding program for diminishing cyanide in cassava take a long waiting time for harvesting cassava tubers to assess cyanide content. Genetic markers are useful for selection of good agricultural traits, which also applied in low-cyanide cassava breeding programs by detecting gene associate with cyanide content in cassava. Therefore, the objective of this study was to develop SNP markers to detect low cyanide trait in cassava. Genotype analysis was carried out using Genotyping by Sequencing (GBS) technology assembling with phenotype analysis. Then, the SNP markers associated with cyanide content were found. Afterward, the primers of SNP marker associated with cyanide content 2 positions were developed using tetra-primer ARMS-PCR techniques. S16_640082 and S16_735381 SNP markers on chromosome 16 showed potential ability of the selection of cassava varieties with cyanide content less than 250 mg HCN/kg fresh weight. The selection accuracy of S16_640082 and S16_735381 SNP markers was 73.33 and 76.64 %, respectively. These markers could be used in marker assisted selection (MAS) in cassava seedling. It substantially reduces cassava breeding programs cost and time. HIGHLIGHTS The major flaw of cassava is its indigenous cyanide. Up to our knowledge, there is rarely report on SNP marker related to cyanide content in Thai cassava population By performing genome wide association mapping (GWAS) to characterize the genome position related to HCN, 2 novel SNP markers associated with cyanide content were found The primers to detect the SNP markers were developed using tetra-primer ARMS-PCR techniques The markers showed ability of the selection of cassava varieties with cyanide content less than 250 mg HCN/kg fresh weight GRAPHICAL ABSTRACT

Transgene insertion into the plastid genome alters expression of adjacent native chloroplast genes at the transcriptional and translational levels.

In plant biotechnology and basic research, chloroplasts have been used as chassis for the expression of various transgenes. However, potential unintended side effects of transgene insertion and high-level transgene expression on the expression of native chloroplast genes are often ignored and have not been studied comprehensively. Here, we examined expression of the chloroplast genome at both the transcriptional and translational levels in five transplastomic tobacco (Nicotiana tabacum) lines carrying the identical aadA resistance marker cassette in diverse genomic positions. Although none of the lines exhibits a pronounced visible phenotype, the analysis of three lines that contain the aadA insertion in different locations within the petL-petG-psaJ-rpl33-rps18 transcription unit demonstrates that transcriptional read-through from the aadA resistance marker is unavoidable, and regularly causes overexpression of downstream sense-oriented chloroplast genes at the transcriptional and translational levels. Investigation of additional lines that harbour the aadA intergenically and outside of chloroplast transcription units revealed that expression of the resistance marker can also cause antisense effects by interference with transcription/transcript accumulation and/or translation of downstream antisense-oriented genes. In addition, we provide evidence for a previously suggested role of genomically encoded tRNAs in chloroplast transcription termination and/or transcript processing. Together, our data uncover principles of neighbouring effects of chloroplast transgenes and suggest general strategies for the choice of transgene insertion sites and expression elements to minimize unintended consequences of transgene expression on the transcription and translation of native chloroplast genes.

Genome-wide analysis of aberrant position and sequence of plasma DNA fragment ends in patients with cancer.

Genome-wide fragmentation patterns in cell-free DNA (cfDNA) in plasma are strongly influenced by cellular origin due to variation in chromatin accessibility across cell types. Such differences between healthy and cancer cells provide the opportunity for development of novel cancer diagnostics. Here, we investigated whether analysis of cfDNA fragment end positions and their surrounding DNA sequences reveals the presence of tumor-derived DNA in blood. We performed genome-wide analysis of cfDNA from 521 samples and analyzed sequencing data from an additional 2147 samples, including healthy individuals and patients with 11 different cancer types. We developed a metric based on genome-wide differences in fragment positioning, weighted by fragment length and GC content [information-weighted fraction of aberrant fragments (iwFAF)]. We observed that iwFAF strongly correlated with tumor fraction, was higher for DNA fragments carrying somatic mutations, and was higher within genomic regions affected by copy number amplifications. We also calculated sample-level means of nucleotide frequencies observed at genomic positions spanning fragment ends. Using a combination of iwFAF and nine nucleotide frequencies from three positions surrounding fragment ends, we developed a machine learning model to differentiate healthy individuals from patients with cancer. We observed an area under the receiver operative characteristic curve (AUC) of 0.91 for detection of cancer at any stage and an AUC of 0.87 for detection of stage I cancer. Our findings remained robust with as few as 1 million fragments analyzed per sample, demonstrating that analysis of fragment ends can become a cost-effective and accessible approach for cancer detection and monitoring.

Evaluation and limitations of different approaches among COVID-19 fatal cases using whole-exome sequencing data

BackgroundCOVID-19 caused by the SARS-CoV-2 infection may result in various disease symptoms and severity, ranging from asymptomatic, through mildly symptomatic, up to very severe and even fatal cases. Although environmental, clinical, and social factors play important roles in both susceptibility to the SARS-CoV-2 infection and progress of COVID-19 disease, it is becoming evident that both pathogen and host genetic factors are important too. In this study, we report findings from whole-exome sequencing (WES) of 27 individuals who died due to COVID-19, especially focusing on frequencies of DNA variants in genes previously associated with the SARS-CoV-2 infection and the severity of COVID-19.ResultsWe selected the risk DNA variants/alleles or target genes using four different approaches: 1) aggregated GWAS results from the GWAS Catalog; 2) selected publications from PubMed; 3) the aggregated results of the Host Genetics Initiative database; and 4) a commercial DNA variant annotation/interpretation tool providing its own knowledgebase. We divided these variants/genes into those reported to influence the susceptibility to the SARS-CoV-2 infection and those influencing the severity of COVID-19. Based on the above, we compared the frequencies of alleles found in the fatal COVID-19 cases to the frequencies identified in two population control datasets (non-Finnish European population from the gnomAD database and genomic frequencies specific for the Slovak population from our own database). When compared to both control population datasets, our analyses indicated a trend of higher frequencies of severe COVID-19 associated risk alleles among fatal COVID-19 cases. This trend reached statistical significance specifically when using the HGI-derived variant list. We also analysed other approaches to WES data evaluation, demonstrating its utility as well as limitations.ConclusionsAlthough our results proved the likely involvement of host genetic factors pointed out by previous studies looking into severity of COVID-19 disease, careful considerations of the molecular-testing strategies and the evaluated genomic positions may have a strong impact on the utility of genomic testing.

Comparative bioinformatics analysis of the biosynthetic pathways and key candidate genes of three species, Vitis vinifera, Fragaria vesca and Olea europaea, furnish enzyme sets for the production of pharmaceutically valuable terpenes in heterologous hosts

Plants represent a rich repository of taxonomically restricted, yet chemically diverse, secondary metabolites that are synthesised via specific metabolic pathways. Enzyme specificity and biosynthetic gene clustering are the bottleneck of secondary metabolite evolution. As economically important food crops, grape, strawberry, and olive produce many pharmaceutically important molecules; however, their specific biosynthetic pathways remain inaccessible. Our genomic-based analysis of these three species reveal the biosynthetic diversity of their specialised secondary metabolites. We found over 20 BGCs predicted, most of which were characterised in two species, grape and strawberry. Gene annotation of the biosynthetic candidate genes predicted the production of many medically and industrially important compounds including cycloartenol, nerolidol, farnesene and valencene. Although most of the predicted clusters are concentrated in specific genomic positions, some have shown gene duplications in their clusters, which is suggestive of pseudogenes or misassembled genomes. Our genome mining and putative functional analysis of the biosynthetic genes annotated in the three species indicated the evolutionary processes that have shaped their current genetic structure and the structural diversity of their chemical compositions. Revealing the biogenetic background of these natural molecules is a step forward towards the expansion of their chemical diversification via engineering their biosynthetic genes heterologously, as well as the identification of their role in the interaction between those plants and their biotic and abiotic conditions.

Deep-sequencing of viral genomes from a large and diverse cohort of treatment-naive HIV-infected persons shows associations between intrahost genetic diversity and viral load.

Infection with human immunodeficiency virus type 1 (HIV) typically results from transmission of a small and genetically uniform viral population. Following transmission, the virus population becomes more diverse because of recombination and acquired mutations through genetic drift and selection. Viral intrahost genetic diversity remains a major obstacle to the cure of HIV; however, the association between intrahost diversity and disease progression markers has not been investigated in large and diverse cohorts for which the majority of the genome has been deep-sequenced. Viral load (VL) is a key progression marker and understanding of its relationship to viral intrahost genetic diversity could help design future strategies for HIV monitoring and treatment. We analysed deep-sequenced viral genomes from 2,650 treatment-naive HIV-infected persons to measure the intrahost genetic diversity of 2,447 genomic codon positions as calculated by Shannon entropy. We tested for associations between VL and amino acid (AA) entropy accounting for sex, age, race, duration of infection, and HIV population structure. We confirmed that the intrahost genetic diversity is highest in the env gene. Furthermore, we showed that mean Shannon entropy is significantly associated with VL, especially in infections of >24 months duration. We identified 16 significant associations between VL (p-value<2.0x10-5) and Shannon entropy at AA positions which in our association analysis explained 13% of the variance in VL. Finally, equivalent analysis based on variation in HIV consensus sequences explained only 2% of VL variance. Our results elucidate that viral intrahost genetic diversity is associated with VL and could be used as a better disease progression marker than HIV consensus sequence variants, especially in infections of longer duration. We emphasize that viral intrahost diversity should be considered when studying viral genomes and infection outcomes. Samples included in this study were derived from participants who consented in the clinical trial, START (NCT00867048) (23), run by the International Network for Strategic Initiatives in Global HIV Trials (INSIGHT). All the participant sites are listed here: http://www.insight-trials.org/start/my_phpscript/participating.php?by=site.

Dynamic, adaptive sampling during nanopore sequencing using Bayesian experimental design

Nanopore sequencers can select which DNA molecules to sequence, rejecting a molecule after analysis of a small initial part. Currently, selection is based on predetermined regions of interest that remain constant throughout an experiment. Sequencing efforts, thus, cannot be re-focused on molecules likely contributing most to experimental success. Here we present BOSS-RUNS, an algorithmic framework and software to generate dynamically updated decision strategies. We quantify uncertainty at each genome position with real-time updates from data already observed. For each DNA fragment, we decide whether the expected decrease in uncertainty that it would provide warrants fully sequencing it, thus optimizing information gain. BOSS-RUNS mitigates coverage bias between and within members of a microbial community, leading to improved variant calling; for example, low-coverage sites of a species at 1% abundance were reduced by 87.5%, with 12.5% more single-nucleotide polymorphisms detected. Such data-driven updates to molecule selection are applicable to many sequencing scenarios, such as enriching for regions with increased divergence or low coverage, reducing time-to-answer.

Copy Number Variation and Allele Ratio Analysis in Candida albicans Using Whole Genome Sequencing Data.

Whole genome sequencing of human fungal pathogens has revolutionized the speed and accuracy in which sequence variants that cause antifungal resistance can be identified. Genome rearrangements resulting in copy number variation (CNV) are a significant source of acquired antifungal drug resistance across diverse fungal species. Some CNVs are transient in nature, while other CNVs are stable and well tolerated even in the absence of antifungal drugs. By visualizing whole genome sequencing read depth as a function of genomic location, CNVs and CNV breakpoints (genomic positions where the copy number changes occur relative to the rest of the genome) are rapidly identified. A similar analysis can be used to visualize allele ratio changes that occur across the genomes of heterozygous fungal species, both in the presence and absence of CNVs. This protocol walks through the bioinformatic analysis of CNVs and allele ratios utilizing free, open-source visualization tools. We provide code to use with an example dataset (matched antifungal drug-sensitive and drug-resistant Candida albicans isolates) and notes on how to expand this protocol to other fungal genomes.