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The roles of chance, contingency, and necessity in evolution are unresolved because they have never been assessed in a single system or on timescales relevant to historical evolution. We combined ancestral protein reconstruction and a new continuous evolution technology to mutate and select proteins in the B-cell lymphoma-2 (BCL-2) family to acquire protein–protein interaction specificities that occurred during animal evolution. By replicating evolutionary trajectories from multiple ancestral proteins, we found that contingency generated over long historical timescales steadily erased necessity and overwhelmed chance as the primary cause of acquired sequence variation; trajectories launched from phylogenetically distant proteins yielded virtually no common mutations, even under strong and identical selection pressures. Chance arose because many sets of mutations could alter specificity at any timepoint; contingency arose because historical substitutions changed these sets. Our results suggest that patterns of variation in BCL-2 sequences – and likely other proteins, too – are idiosyncratic products of a particular and unpredictable course of historical events., eLife digest One of the most fundamental and unresolved questions in evolutionary biology is whether the outcomes of evolution are predictable. Is the diversity of life we see today the expected result of organisms adapting to their environment throughout history (also known as natural selection) or the product of random chance? Or did chance events early in history shape the paths that evolution could take next, determining the biological forms that emerged under natural selection much later? These questions are hard to study because evolution happened only once, long ago. To overcome this barrier, Xie, Pu, Metzger et al. developed an experimental approach that can evolve reconstructed ancestral proteins that existed deep in the past. Using this method, it is possible to replay evolution multiple times, from various historical starting points, under conditions similar to those that existed long ago. The end products of the evolutionary trajectories can then be compared to determine how predictable evolution actually is. Xie, Pu, Metzger et al. studied proteins belonging to the BCL-2 family, which originated some 800 million years ago. These proteins have diversified greatly over time in both their genetic sequences and their ability to bind to specific partner proteins called co-regulators. Xie, Pu, Metzger et al. synthesized BCL-2 proteins that existed at various times in the past. Each ancestral protein was then allowed to evolve repeatedly under natural selection to acquire the same co-regulator binding functions that evolved during history. At the end of each evolutionary trajectory, the genetic sequence of the resulting BCL-2 proteins was recorded. This revealed that the outcomes of evolution were almost completely unpredictable: trajectories initiated from the same ancestral protein produced proteins with very different sequences, and proteins launched from different ancestral starting points were even more dissimilar. Further experiments identified the mutations in each trajectory that caused changes in coregulator binding. When these mutations were introduced into other ancestral proteins, they did not yield the same change in function. This suggests that early chance events influenced each protein’s evolution in an unpredictable way by opening and closing the paths available to it in the future. This research expands our understanding of evolution on a molecular level whilst providing a new experimental approach for studying evolutionary drivers in more detail. The results suggest that BCL-2 proteins, in all their various forms, are unique products of a particular, unpredictable course of history set in motion by ancient chance events.

Dysfunctional dopaminergic neurotransmission is central to movement disorders and mental diseases. The dopamine transporter (DAT) regulates extracellular dopamine levels, but the genetic and mechanistic link between DAT function and dopamine-related pathologies is not clear. Particularly, the pathophysiological significance of monoallelic missense mutations in DAT is unknown. Here, we use clinical information, neuroimaging, and large-scale exome-sequencing data to uncover the occurrence and phenotypic spectrum of a DAT coding variant, DAT-K619N, which localizes to the critical C-terminal PSD-95/Discs-large/ZO-1 homology-binding motif of human DAT (hDAT). We identified the rare but recurrent hDAT-K619N variant in exome-sequenced samples of patients with neuropsychiatric diseases and a patient with early-onset neurodegenerative parkinsonism and comorbid neuropsychiatric disease. In cell cultures, hDAT-K619N displayed reduced uptake capacity, decreased surface expression, and accelerated turnover. Unilateral expression in mouse nigrostriatal neurons revealed differential effects of hDAT-K619N and hDATWT on dopamine-directed behaviors, and hDAT-K619N expression in Drosophila led to impairments in dopamine transmission with accompanying hyperlocomotion and age-dependent disturbances of the negative geotactic response. Moreover, cellular studies and viral expression of hDAT-K619N in mice demonstrated a dominant-negative effect of the hDAT-K619N mutant. Summarized, our results suggest that hDAT-K619N can effectuate dopamine dysfunction of pathological relevance in a dominant-negative manner.

Mulberry is admired for its landscaping and possesses high development prospects and scientific research value. Mitochondria are the plants' powerhouse that produces energy to carry out life processes. In this study, the mt genome of Morus L(M. atropurpurea and M. multicaulis)were annotated and assembled. The circular mt genome of M. multicaulis has a length of 361,546bp, contains 54 genes, including 31 protein-coding genes, 20 tRNA genes, and 3 rRNA genes and composition of A(27.38%), T (27.20%), C (22.63%) and G (22.79%). The sequence repeats, RNA editing gene and migration from cp to mt and was observed in M. multicaulis mt genome. Phylogenetic analysis based on the complete mt genomes of Morus and other 28 species reflects an exact evolutionary and taxonomic status. Furthermore, we investigation on mt genome size, organization, and plastomes at the global level and pi analysis of Morus genome was investigated and compared to other land plants. The results indicate that the exist mt genome's variation in plants. We reported the mt genome assembly and annotation of a halophytic model plant, M. multicaulis, and subsequent analysis, which provided us with a comprehensive understanding of the Morus mt genome.

The E1 and E2 genes of the human papillomavirus encode the so-called early proteins, their sequences are conserved, and regulatory functions are associated with the viral oncoproteins. The purpose of this study is to determine the HPV16 E1 and E2 mutations appearing in the female population of southern Poland, depending on the severity of cervical pathological changes. We also take into account the number of E1 and E2 mutations detected in the E6 gene variant (350G or 350T). This publication is one of the first in the Central and Eastern Europe to deal with this topic. We identified 4 mutations in the E1 gene and 24 mutations in the E2 gene that have not been described so far. In three cases of squamous cell carcinoma a C3409T mutation occurred, which is widely described as oncogenic. This mutation lies in the 3243-3539 area of the E2 hinge region. Statistical analyses show a possible relationship of mutations in this area with oncogenesis. The discovered dependencies may be important in the context of oncogenesis, however, a study with a larger group of patients is needed in order to confirm this view.

Architectural stripes tend to form at genomic regions harboring genes with salient roles in cell identity and function. Therefore, the accurate identification and quantification of these features is essential for the understanding of lineage-specific gene regulation. Here, we present Stripenn, an algorithm rooted in computer vision to systematically detect and quantitate architectural stripes from chromatin conformation measurements of various technologies. We demonstrate that Stripenn outperforms existing methods, highlight its biological applications in the context of B and T lymphocytes, and examine the role of sequence variation on architectural stripes by studying the conservation of these features in inbred strains of mice. In summary, Stripenn is a computational method which borrows concepts from widely used image processing techniques for demarcation and quantification of architectural stripes.

Recent publications have highlighted the emergence of mutations in the M1 gene of both influenza A H1N1pdm09 and H3N2 subtypes affecting the performance of commercial RT-PCR assays. Respiratory samples from the 2018/2019 season positive by our in-house RT-PCR for influenza A were analysed for the prevalence and impact of any M1 gene mutations. Sequence information was used to re-design primers for our routine assay and their performance assessed. Forty-five samples, consisting of 11 H1N1pdm09 and 34 H3N2 subtypes, together with the NIBSC H1N1 control were sequenced. All samples displayed the core mutations for H1N1 M1(C154T; G174A and G238A) and for H3N2 M1(C153T; C163T and G189T); three of the H1N1pdm09 viruses also showed a small number of point mutations. None of the mutations appeared to affect either the sensitivity or efficiency of the RT-PCR when compared to the re-designed primers. Although the mutations we found agreed with those in the publications cited we did not encounter any problems with our routine diagnostic assay and no improvements were found when the primers were modified to suit those mutations. However, it is likely that the influenza A virus M1 gene will accumulate further mutations that could impact RT-PCR assays and, therefore, it would be prudent to implement routine sequencing of samples during the influenza seasons to ensure no loss in assay performance.

Recent studies have shown the role of mitochondrial DNA (mtDNA) variants in the pathogenesis of both psoriasis (Ps) and type 2 diabetes (T2D) amongst different ethnicities. However, no studies have investigated the mtDNA variants present in patients with Ps, T2D, and both Ps and T2D (Ps-T2D) in the Arab population. The entire mitochondrial genomes of Kuwaiti subjects with Ps, T2D, Ps-T2D and healthy controls were sequenced using Ion Torrent next-generation sequencing. A total of 36 novel mutations and 51 previously reported mutations were identified in the patient groups that were absent in the controls. Amongst the novel mutations, eight were non-synonymous and exhibited amino acid changes. Of these, two missense mutations (G5262A and A12397G) in the ND genes were detected in the Ps group and a C15735T missense mutation in the CYB gene was detected in Ps-T2D. Other known sequence variations were seen more frequently in all or certain patient groups compared with the controls (P

Since 1992 PredictProtein (https://predictprotein.org) is a one-stop online resource for protein sequence analysis with its main site hosted at the Luxembourg Centre for Systems Biomedicine (LCSB) and queried monthly by over 3,000 users in 2020. PredictProtein was the first Internet server for protein predictions. It pioneered combining evolutionary information and machine learning. Given a protein sequence as input, the server outputs multiple sequence alignments, predictions of protein structure in 1D and 2D (secondary structure, solvent accessibility, transmembrane segments, disordered regions, protein flexibility, and disulfide bridges) and predictions of protein function (functional effects of sequence variation or point mutations, Gene Ontology (GO) terms, subcellular localization, and protein-, RNA-, and DNA binding). PredictProtein’s infrastructure has moved to the LCSB increasing throughput; the use of MMseqs2 sequence search reduced runtime five-fold; user interface elements improved usability, and new prediction methods were added. PredictProtein recently included predictions from deep learning embeddings (GO and secondary structure) and a method for the prediction of proteins and residues binding DNA, RNA, or other proteins. PredictProtein.org aspires to provide reliable predictions to computational and experimental biologists alike. All scripts and methods are freely available for offline execution in high-throughput settings.AvailabilityFreely accessible webserverPredictProtein.org; Source and docker images: github.com/rostlab

Sensitive and reproducible diagnostics are fundamental to containing the spread of existing and emerging pathogens. Despite the reliance of clinical virology on qPCR, technical challenges persist that compromise their reliability for sustainable epidemic containment as sequence instability in probe-binding regions produces false-negative results. We systematically violated canonical qPCR design principles to develop a Pan-Degenerate Amplification and Adaptation (PANDAA), a point mutation assay that mitigates the impact of sequence variation on probe-based qPCR performance. Using HIV-1 as a model system, we optimized and validated PANDAA to detect HIV drug resistance mutations (DRMs). Ultra-degenerate primers with 3’ termini overlapping the probe-binding site adapt the target through site-directed mutagenesis during qPCR to replace DRM-proximal sequence variation. PANDAA-quantified DRMs present at frequency ≥5% (2 h from nucleic acid to result) with a sensitivity and specificity of 96.9% and 97.5%, respectively. PANDAA is an innovative advancement with applicability to any pathogen where target-proximal genetic variability hinders diagnostic development., Iain MacLeod et al. develop the Pan-Degenerate Amplification and Adaptation (PANDAA) point mutation assay to detect HIV drug resistance mutations. This method can be applied to any pathogen where target-proximal genetic variability hinders diagnostic development.

Phase separation is emerging as a universal principle for how cells use dynamic subcompartmentalization to organize biochemical reactions in time and space1,2. Yet, whether the emergent physical properties of these biomolecular condensates are important for their biological function remains unclear. The intrinsically disordered protein PopZ forms membraneless condensates at the poles of the bacterium Caulobacter crescentus and selectively sequesters kinase-signaling cascades to regulate asymmetric cell division3–5. By dissecting the molecular grammar underlying PopZ phase separation, we find that unlike many eukaryotic examples, where unstructured regions drive condensation6,7, a structured domain of PopZ drives condensation, while conserved repulsive features of the disordered region modulate material properties. By generating rationally designed PopZ mutants, we find that the exact material properties of PopZ condensates directly determine cellular fitness, providing direct evidence for the physiological importance of the emergent properties of biomolecular condensates. Our work codifies a clear set of design principles illuminating how sequence variation in a disordered domain alters the function of a widely conserved bacterial condensate. We used these insights to repurpose PopZ as a modular platform for generating synthetic condensates of tunable function in human cells.

We determined the complete chloroplast genome sequences of Aconitum austrokoreense Koidz., an endangered endemic species in Korea. The chloroplast DNA is 155,682 bp in length and encodes 37 tRNAs, 8 rRNAs, and 86 protein-coding genes. Phylogenetic analysis and sequence comparison of protein-coding genes with those in other Ranunculaceae chloroplast DNAs showed that the chloroplast genome of A. austrokoreense is closely related to that of A. chiisanense and large sequence variations identified in rps16, matK, and rpl20 are specific to these two species.

The ESKAPEE pathogens are the leading cause of health care-associated infections worldwide. Two-component systems (TCSs) can be used as effective targets against pathogenic bacteria since they are ubiquitous and manage various vital functions such as antibiotic resistance, virulence, biofilms, quorum sensing, and pH balance, among others., The two-component system (TCS) helps bacteria sense and respond to environmental stimuli through histidine kinases and response regulators. TCSs are the largest family of multistep signal transduction processes, and they are involved in many important cellular processes such as antibiotic resistance, pathogenicity, quorum sensing, osmotic stress, and biofilms. Here, we perform the first comprehensive study to highlight the role of TCSs as potential drug targets against ESKAPEE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter spp., and Escherichia coli) pathogens through annotation, mapping, pangenomic status, gene orientation, and sequence variation analysis. The distribution of the TCSs is group specific with regard to Gram-positive and Gram-negative bacteria, except for KdpDE. The TCSs among ESKAPEE pathogens form closed pangenomes, except for Pseudomonas aeruginosa. Furthermore, their conserved nature due to closed pangenomes might make them good drug targets. Fitness score analysis suggests that any mutation in some TCSs such as BaeSR, ArcBA, EvgSA, and AtoSC, etc., might be lethal to the cell. Taken together, the results of this pangenomic assessment of TCSs reveal a range of strategies deployed by the ESKAPEE pathogens to manifest pathogenicity and antibiotic resistance. This study further suggests that the conserved features of TCSs might make them an attractive group of potential targets with which to address antibiotic resistance. IMPORTANCE The ESKAPEE pathogens are the leading cause of health care-associated infections worldwide. Two-component systems (TCSs) can be used as effective targets against pathogenic bacteria since they are ubiquitous and manage various vital functions such as antibiotic resistance, virulence, biofilms, quorum sensing, and pH balance, among others. This study provides a comprehensive overview of the pangenomic status of the TCSs among ESKAPEE pathogens. The annotation and pangenomic analysis of TCSs show that they are significantly distributed and conserved among the pathogens, as most of them form closed pangenomes. Furthermore, our analysis also reveals that the removal of the TCSs significantly affects the fitness of the cell. Hence, they may be used as promising drug targets against bacteria.

Since the beginning of the Human Genome Project, sequencing of the human genome has driven the development of technologies and methods to discover the variation within it. While the cost of sequencing the original human haploid consensus reference genome was approximately $2.7 billion US dollars, the subsequent development of better and more efficient sequencing machines and methodologies, such as massively parallel next-generation sequencing technologies, dramatically reduced both the cost and time to sequence personal human genomes and apply these technologies for research and in the clinic. In addition, the development and refinement of targeted capture methods and reagents for exome sequencing resulted in a rapid increase in the number of human exomes sequenced and analyzed, dramatically expanding our knowledge of human coding variation. Concurrently, bioinformatic algorithms and tools have been developed to manage and analyze the tremendous amount of genomic data generated. This chapter aims to give an overview of the methodologies used to interrogate the human genome focusing mainly on genomic sequencing from Sanger sequencing to single-molecule DNA sequencing. Additionally, an overview of the analyses performed to identify medically relevant sequence variation and how these have been applied to successfully elucidate the molecular causes of rare diseases is provided. Finally, the application of genomic sequencing in the clinic and the limitations of the approach are discussed.

Snake venoms contain many protein and peptide isoforms with high levels of sequence variation, even within a single species. In this review, we highlight several examples, from both published and unpublished work in our lab, demonstrating how a combined venom gland transcriptome and proteome methodology allows for comprehensive characterization of venoms, including those from understudied rear-fanged snake species, and we provide recommendations for using these approaches. When characterizing venoms, peptide mass fingerprinting using databases built predominately from protein sequences originating from model organisms can be disadvantageous, especially when the intention is to document protein diversity. Therefore, the use of species-specific venom gland transcriptomes corrects for the absence of these unique peptide sequences in databases. The integration of transcriptomics and proteomics improves the accuracy of either approach alone for venom profiling.

In rabies diagnosis, it is essential to count on a rapid test to give a quick response. The combined sensitivity and robustness of the TaqMan RT-PCR assays (qRT-PCR) have made these methods a valuable alternative for rabies virus (RABV) detection. We conducted a study to compare the applicability of two widely used qRT-PCR assays targeting the nucleoprotein gene (LysGT1 assay) and leader sequences (LN34 qRT-PCR assay) of RABV genomes, in all variants circulating in Argentina. A total of 44 samples obtained from bats, dogs, cattle, and horses, that were previously tested for rabies by FAT and conventional RT-PCR, were used in the study. All variants were successfully detected by the pan-lyssavirus LN34 qRT-PCR assay. The LysGT1 assay failed to detect three bat-related variants. We further sequenced the region targeted by LysGT1 and demonstrated that the presence of three or more mismatches with respect to the primers and probe sequences precludes viral detection. We conclude that the LysGT1 assay is prone to yield variant-dependent false-negative test results, and in consequence, the LN34 assay would ensure more effective detection of RABV in Argentina.

Long-read analysis of 36 individual genomes revealed extensive structural diversity within human centromeric repeat arrays., Our understanding of centromere sequence variation across human populations is limited by its extremely long nested repeat structures called higher-order repeats that are challenging to sequence. Here, we analyzed chromosomes 11, 17, and X using long-read sequencing data for 36 individuals from diverse populations including a Han Chinese trio and 21 Japanese. We revealed substantial structural diversity with many previously unidentified variant higher-order repeats specific to individuals characterizing rapid, haplotype-specific evolution of human centromeric arrays, while frequent single-nucleotide variants are largely conserved. We found a characteristic pattern shared among prevalent variants in human and chimpanzee. Our findings pave the way for studying sequence evolution in human and primate centromeres.

Non-alcoholic or recently re-defined metabolic associated fatty liver disease (MAFLD), a spectrum of progressive hepatic disease, has become a public health issue in obese children and adolescents. MAFLD is a complex metabolic disease strongly associated with obesity and insulin resistance. It is not known why not every obese subject will develop MAFLD. Different ethnic/racial groups display differences in MAFLD prevalence, indicating genetic factor plays a role. In the past two decades, sequence variations in genetic loci, including PNPLA3, TM6SF2, GCKR, MBOAT7, HSD17B13, etc. have been shown to confer susceptibility to MAFLD in children and adults. This review article provides an updated viewpoint of genetic predictors related to pediatric MAFLD. We discuss whether these susceptible genes can be clinically used for risk stratification and personalized care. Understanding human genetics and molecular mechanisms can give important information not only for prediction of risk but also on how to design drugs. In view of current epidemic of MAFLD worldwide, it is necessary to identify which children with MAFLD progress rapidly and need earlier intervention. In the future, a comprehensive analysis of individualized genetic and environmental factors may help assess the risk of children with MAFLD and personalize their treatment.

MotivationIt is computationally challenging to detect variation by aligning long reads from single-molecule sequencing (SMS) instruments, or megabase-scale contigs from SMS assemblies. One approach to efficiently align long sequences is sparse dynamic programming (SDP), where exact matches are found between the sequence and the genome, and optimal chains of matches are found representing a rough alignment. Sequence variation is more accurately modeled when alignments are scored with a gap penalty that is a convex function of the gap length. Because previous implementations of SDP used a linear-cost gap function that does not accurately model variation, and implementations of alignment that have a convex gap penalty are either inefficient or use heuristics, we developed a method, lra, that uses SDP with a convex-cost gap penalty. We use lra to align long-read sequences from PacBio and Oxford Nanopore (ONT) instruments as well asde novoassembly contigs.ResultsAcross all data types, the runtime of lra is between 52-168% of the state of the art aligner minimap2 when generating SAM alignment, and 9-15% of an alternative method, ngmlr. This alignment approach may be used to provide additional evidence of SV calls in PacBio datasets, and an increase in sensitivity and specificity on ONT data with current SV detection algorithms. The number of calls discovered using pbsv with lra alignments are within 98.3-98.6% of calls made from minimap2 alignments on the same data, and give a nominal 0.2-0.4% increase in F1 score by Truvari analysis. On ONT data with SV called using Sniffles, the number of calls made from lra alignments is 3% greater than minimap2-based calls, and 30% greater than ngmlr based calls, with a 4.6-5.5% increase in Truvari F1 score. When applied to calling variation from de novo assembly contigs, there is a 5.8% increase in SV calls compared to minimap2+paftools, with a 4.3% increase in Truvari F1 score.Availability and implementationAvailable in bioconda:https://anaconda.org/bioconda/lraand github:https://github.com/ChaissonLab/LRAContactmchaisso@usc.edu,jingwenr@usc.edu

A rapid increase in fuel consumption has been seen due to a sudden increase in the usage of automotive vehicles. This results in an increase in air pollution. Due to which a stricter regulation applied by the federal government to decrease air pollution. To escape from the pollution penalty innovations are been pushed. The industry has been looking at many innovative manufacturing processes like electric assisted manufacturing, single point incremental forming, high-speed forming, and many. All these innovative processes promise more uniform deformation and increases formability in the part. One such process is tube hydroforming for tubular parts. Tube hydroforming is the successful manufacturing process to create a variety of shapes using fluid pressure. The fluid medium can be water with preventive additives, oil, or viscous liquid. In this process, the tube was filled with the fluid medium and further pressurized to deform to various shapes. Tube hydroforming is categorized into three types: high pressure, pressure sequencing and low-pressure tube hydroforming. Ferrous and non-ferrous metals are formed using these processes. Due to uniform thinning in the formed part, the parts can be lower weight and thus proven to be the technology to create light-weight parts for automotive and aerospace industries to increase the fuel economy. Tube hydroforming has gained popularity due to its many advantages such as part consolidation, quality of the formed part and the possibility of unique shapes with indents or angles. This paper focuses on low-pressure tube hydroforming. In low-pressure tube hydroforming, during the closing of the die the tube is marginally pressurized to a fixed volume. The previous study which was published in IMECE2019 was focused on investigating the deformation mechanics of the tube due to variation in the process sequence during low-pressure tube hydroforming. In the second part of this research focus on how the thickness of the tube affect the deformation mechanics in the variation of the process sequence during low-pressure tube hydroforming. The circular tube was formed in a square shape. The four sides of die edges were considered as individual edges and the motion of these edges will be varied to achieve the final shape. The deformation mechanics in each condition was presented and analyzed. The relative thickness and strain distribution were studied. The change of tube profile pattern from the start to the end of the process were presented and compared. It was found that the deformation mechanics was mostly influenced by the variation of movement by punch and die side with no internal pressure case. The buckling in the tube wall also depended on which side of the die moves to deform the tube.

Temperature is a critical abiotic factor shaping the distribution and abundance of species, but the mechanisms that underpin organismal thermal limits remain poorly understood. One possible mechanism underlying these limits is the failure of mitochondrial processes, as mitochondria play a crucial role in animals as the primary site of ATP production. Conventional measures of mitochondrial performance suggest that these organelles can function at temperatures much higher than those that limit whole-organism function, suggesting that they are unlikely to set organismal thermal limits. However, this conclusion is challenged by recent data connecting sequence variation in mitochondrial genes to whole-organism thermal tolerance. Here, we review the current state of knowledge of mitochondrial responses to thermal extremes and ask whether they are consistent with a role for mitochondrial function in shaping whole-organism thermal limits. The available data are fragmentary, but it is possible to draw some conclusions. There is little evidence that failure of maximal mitochondrial oxidative capacity as assessed in vitro sets thermal limits, but there is some evidence to suggest that temperature effects on ATP synthetic capacity may be important. Several studies suggest that loss of mitochondrial coupling is associated with the thermal limits for organismal growth, although this needs to be rigorously tested. Most studies have utilized isolated mitochondrial preparations to assess the effects of temperature on these organelles, and there remain many untapped opportunities to address these questions using preparations that retain more of their biological context to better connect these subcellular processes with whole-organism thermal limits.

High-throughput sequencing such as those provided by Illumina are an efficient way to understand sequence variation within viral populations. However, challenges exist in distinguishing process-introduced error from biological variance, which significantly impacts our ability to identify sub-consensus single-nucleotide variants (SNVs). Here we have taken a systematic approach to evaluate laboratory and bioinformatic pipelines to accurately identify low-frequency SNVs in viral populations. Artificial DNA and RNA &ldquo, populations&rdquo, were created by introducing known SNVs at predetermined frequencies into template nucleic acid before being sequenced on an Illumina MiSeq platform. These were used to assess the effects of abundance and starting input material type, technical replicates, read length and quality, short-read aligner, and percentage frequency thresholds on the ability to accurately call variants. Analyses revealed that the abundance and type of input nucleic acid had the greatest impact on the accuracy of SNV calling as measured by a micro-averaged Matthews correlation coefficient score, with DNA and high RNA inputs (107 copies) allowing for variants to be called at a 0.2% frequency. Reduced input RNA (105 copies) required more technical replicates to maintain accuracy, while low RNA inputs (103 copies) suffered from consensus-level errors. Base errors identified at specific motifs identified in all technical replicates were also identified which can be excluded to further increase SNV calling accuracy. These findings indicate that samples with low RNA inputs should be excluded for SNV calling and reinforce the importance of optimising the technical and bioinformatics steps in pipelines that are used to accurately identify sequence variants.

DNA metabarcoding has become a powerful approach for analysing complex communities from environmental samples, but there are still methodological challenges limiting its full potential. While conserved DNA markers, like 16S and 18S, often are not able to discriminate among closely related species, other more variable markers - like the fungal ITS region, may include considerable intraspecific variation, which can lead to oversplitting of species during DNA metabarcoding analyses. Here we assessed the effects of intraspecific sequence variation in DNA metabarcoding by analysing local populations of eleven fungal species. We investigated the allelic diversity of ITS2 haplotypes using both Sanger sequencing and high throughput sequencing (HTS) coupled with error correction with the software dada2. All the eleven species, except one, included some level of intraspecific variation in the ITS2 region. Overall, we observed a high correspondence between haplotypes generated by Sanger sequencing and HTS, with the exception of a few additional haplotypes detected using either approach. These extra haplotypes, typically occurring in low frequencies, were probably due to PCR and sequencing errors or intragenomic variation in the rDNA region. The presence of intraspecific (and possibly intragenomic) variation in ITS2 suggest that haplotypes (or ASVs) should not be used as basic units in ITS-based fungal community analyses, but an extra clustering step is needed to approach species-level resolution.

Previous work found that the centromeric repeats of the Western European house mouse (Mus musculus domesticus) are composed predominantly of a 120 bp monomer that is shared by the X and autosomes. Polymorphism in length and sequence was also reported. Here I quantified the length and sequence polymorphism of the centromeric repeats found on the X and autosomes. The levels of local and global sequence variation were also compared. I found three length variants: a 64mer, 112mer and 120mer with relative frequencies of 2.4%, 8.6%, and 89%, respectively. There was substantial sequence variation within all three length variants with a rank-order of: 64mer < 120mer < 112mer. The 64mer was never found alone on long Sanger traces, and was arranged predominantly as a 176 bp higher-order repeat composed of a 64/112mer dimer. Reanalysis of archived ChIP-seq reads found that all three length variants were enriched with the foundational centromere protein CENP-A, but the enrichment was far higher for the 120mer. This pattern indicates that only the 120mer contributes substantially to the functional centromeres, i.e., to the kinetochore-binding, centric cores of the centromeric repeat arrays. Despite only moderate sequence divergence among random pairs of 120mers (averaging 5.9%), other measures of sequence diversity were exceptionally high: i) variant richness (numerical diversity) –on average, one new sequence variant was observed every 4th additional monomer randomly sampled (in N = 7.2 × 103 monomers), and ii) variant evenness –all of the nearly 2 × 103 observed sequence variants were at low frequency, with the most common variant having a frequency of only 5.7%. I next used long Sanger trace data from the Mouse Genome Project to assess the pattern of monomer diversity among neighboring 120mers. Unexpectedly, side-by-side monomers were rarely identical in sequence, and sequence divergence between these neighbors was nearly as high as that between random pairs taken from the genome-wide pool of all 120mers. I also used long Sanger traces to determine sequence variation among neighborhoods of 5 contiguous 120 bp monomers. Sequence diversity within these small regions typically spanned most of the entire range of that found genome-wide. Despite high sequence variation within these neighborhoods, the density of monomers with functional binding motifs for CENP-B (i.e., b-boxes with sequence NTTCGNNNNANNCGGGN) was strongly conserved at about 50%. The overarching pattern of monomer structure at the centromeric repeats of this subspecies is: i) high homogeneity in the density CENP-B binding sites, and ii) high heterogeneity in monomer sequence at both local and global levels.

BackgroundCurrent mark release recapture methodologies are limited in their ability to address complex problems in vector biology, such as studying multiple groups overlapping in space and time. Additionally, limited mark retention, reduced post-marking survival, and the large effort in marking, collection and recapture, all complicate effective insect tracking.MethodWe have developed and evaluated a marking method using a fluorescent dye (Smartwater®) combined with synthetic DNA tags to informatively and efficiently mark adult mosquitoes using an airbrush pump and nebulizer. Using handheld UV flashlights, the fluorescent marking enabled quick and simple initial detection of recaptures in a simple, field-ready, and non-destructive approach that when combined with a simple, extraction-free PCR on individual mosquito legs provides potentially unlimited marking information.ResultsThis marking, first tested in the laboratory with Anopheles gambiae s.l. mosquitoes, did not affect survival (median ages 24-28 days, p-adj > 0.25), oviposition (median eggs/female of 28.8, 32.5, 33.3 for water, green, red dyes, respectively, p-adj > 0.44), or Plasmodium competence (mean oocysts 5.56 to 10.6, p-adj > 0.95). DNA and fluorescence had 100% retention up to 3 weeks (longest time point tested) with high intensity, indicating marks would persist longer.ConclusionsWe describe a novel, simple, no/low-impact, and long-lasting marking method that allows separation of multiple insect subpopulations by combining unlimited length and sequence variation in the synthetic DNA tags. This method can be readily deployed in the field for marking multiple groups of mosquitoes or other insects.