Species concepts have been defined through a number of lenses, but are almost entirely empirical in nature. Fundamentally linked to various existing species concepts, an interpretation of genomic data through a species classification filter based upon a theoretical genotype-phenotype map with a monophyly requirement is discussed.

Loss of heterozygosity (LOH) is a mitotic recombination event that converts heterozygous loci to homozygous loci. This mutation event is widespread in organisms that have asexual reproduction like budding yeasts, and is also an important and frequent mutation event in tumorigenesis. Mutation accumulation studies have demonstrated that LOH occurs at a rate higher than the point mutation rate, and can impact large portions of the genome. Laboratory evolution experiments of heterozygous yeasts have revealed that LOH often unmasks beneficial recessive alleles that can confer large fitness advantages. Here, I highlight advances in understanding dominance, fitness, and phenotypes in laboratory evolved heterozygous yeast strains. I discuss best practices for detecting LOH in intraspecific and interspecific evolved clones and populations. Utilizing heterozygous strain backgrounds in laboratory evolution experiments offers an opportunity to advance our understanding of this important mutation type in shaping adaptation and genome evolution in wild, domesticated, and clinical populations.

The standard genetic code determines that in most species, including viruses, there are 20 amino acids that are coded by 61 codons, while the other three codons are stop triplets. Considering the whole proteome each species features its own amino acid frequencies, given the slow rate of change, closely related species display similar GC content and amino acids usage. In contrast, distantly related species display different amino acid frequencies. Furthermore, within certain multicellular species, as mammals, intragenomic differences in the usage of amino acids are evident. In this communication, we shall summarize some of the most prominent and well-established factors that determine the differences found in the amino acid usage, both across evolution and intragenomically.

Adaptive evolution navigates a balance between chance and determinism. The stochastic processes of mutation and drift generate phenotypic variation; however, once mutations reach an appreciable frequency in the population, their fate is governed by the deterministic action of selection, enriching for favorable genotypes and purging the less-favorable ones. The net result is that replicate populations will traverse similar-but not identical-pathways to higher fitness. This parallelism in evolutionary outcomes can be leveraged to identify the genes and pathways under selection. However, distinguishing between beneficial and neutral mutations is challenging because many beneficial mutations will be lost due to drift and clonal interference, and many neutral (and even deleterious) mutations will fix by hitchhiking. Here, we review the best practices that our laboratory uses to identify genetic targets of selection from next-generation sequencing data of evolved yeast populations. The general principles for identifying the mutations driving adaptation will apply more broadly.

In recent years, evolutionary biologists have developed an increasing interest in the use of barcoding strategies to study eco-evolutionary dynamics of lineages within evolving populations and communities. Although barcoded populations can deliver unprecedented insight into evolutionary change, barcoding microbes presents specific technical challenges. Here, strategies are described for barcoding populations of the model bacterium Pseudomonas fluorescens SBW25, including the design and cloning of barcoded regions, preparation of libraries for amplicon sequencing, and quantification of resulting barcoded lineages. In so doing, we hope to aid the design and implementation of barcoding methodologies in a broad range of model and non-model organisms.

Cancer, a disease due to uncontrolled cell proliferation is as ancient as multicellular organisms. A 255-million-years-old fossilized forerunner mammal gorgonopsian is probably the oldest evidence of cancer, to date. Cancer seems to have evolved by adapting to the microenvironment occupied by immune sentinel, modulating the cellular behavior from cytotoxic to regulatory, acquiring resistance to chemotherapy and surviving hypoxia. The interaction of genes with environmental carcinogens is central to cancer onset, seen as a spectrum of cancer susceptibility among human population. Cancer occurs in life forms other than human also, although their exposure to environmental carcinogens can be different. Role of genetic etiology in cancer in multiple species can be interesting with regard to not only cancer susceptibility, but also genetic conservation and adaptation in speciation. The widely used model organisms for cancer research are mouse and rat which are short-lived and reproduce rapidly. Research in these cancer prone animal models has been valuable as these have led to cancer therapy. However, another rewarding area of cancer research can be the cancer-resistant animal species. The Peto's paradox and G-value paradox are evident when natural cancer resistance is observed in large mammals, like elephant and whale, small rodents viz. Naked Mole Rat and Blind Mole Rat, and Bat. The cancer resistance remains to be explored in other small or large and long-living animals like giraffe, camel, rhinoceros, water buffalo, Indian bison, Shire horse, polar bear, manatee, elephant seal, walrus, hippopotamus, turtle and tortoise, sloth, and squirrel. Indeed, understanding the molecular mechanisms of avoiding neoplastic transformation across various life forms can be potentially having translational value for human cancer management. Adapted and Modified from (Hanahan and Weinberg 2011).

To study unknown proteins on a large scale, a reference system has been set up for the three better studied eukaryotic kingdoms, built with 36 proteomes as taxonomically diverse as possible. Proteins from 362 other eukaryotic proteomes with no known homologue in this set were then analyzed, focusing noteworthy on singletons, that is, on such proteins with no known homologue in their own proteome. Consistently, for a given species, no more than 12% of the singletons thus found are known at the protein level, according to Uniprot. In addition, since they rely on the information found in the alignment of homologous sequences, predictions of AlphaFold2 for their tridimensional structure are poor. In the case of metazoan species, the number of singletons rarely exceeds 1000 for the species the closest to the reference system (divergence times below 75 Myr). Interestingly, in the cases of viridiplantae and fungi, larger amounts of singletons are found for such species, as if the timescale on which singletons are added to proteomes were different in metazoa and in other eukaryotic kingdoms. In order to confirm this phenomenon, further studies of proteomes closer to those of the reference system are, however, needed.

Random DNA barcodes are a versatile tool for tracking cell lineages, with applications ranging from development to cancer to evolution. Here, we review and critically evaluate barcode designs as well as methods of barcode sequencing and initial processing of barcode data. We first demonstrate how various barcode design decisions affect data quality and propose a new design that balances all considerations that we are currently aware of. We then discuss various options for the preparation of barcode sequencing libraries, including inline indices and Unique Molecular Identifiers (UMIs). Finally, we test the performance of several established and new bioinformatic pipelines for the extraction of barcodes from raw sequencing reads and for error correction. We find that both alignment and regular expression-based approaches work well for barcode extraction, and that error-correction pipelines designed specifically for barcode data are superior to generic ones. Overall, this review will help researchers to approach their barcoding experiments in a deliberate and systematic way.

The long-term evolution experiment (LTEE) with Escherichia coli began in 1988 and it continues to this day, with its 12 populations having recently reached 75,000 generations of evolution in a simple, well-controlled environment. The LTEE was designed to explore open-ended questions about the dynamics and repeatability of phenotypic and genetic evolution. Here I discuss various aspects of the LTEE's experimental design that have enabled its stability and success, including the choices of the culture regime, growth medium, ancestral strain, and statistical replication. I also discuss some of the challenges associated with a long-running project, such as handling procedural errors (e.g., cross-contamination) and managing the expanding collection of frozen samples. The simplicity of the experimental design and procedures have supported the long-term stability of the LTEE. That stability-along with the inherent creativity of the evolutionary process and the emergence of new genomic technologies-provides a platform that has allowed talented students and collaborators to pose questions, collect data, and make discoveries that go far beyond anything I could have imagined at the start of the LTEE.

The advent of next generation sequencing technologies (NGS) has greatly accelerated our understanding of critical aspects of organismal biology from non-model organisms. Bats form a particularly interesting group in this regard, as genomic data have helped unearth a vast spectrum of idiosyncrasies in bat genomes associated with bat biology, physiology, and evolution. Bats are important bioindicators and are keystone species to many eco-systems. They often live in proximity to humans and are frequently associated with emerging infectious diseases, including the COVID-19 pandemic. Nearly four dozen bat genomes have been published to date, ranging from drafts to chromosomal level assemblies. Genomic investigations in bats have also become critical towards our understanding of disease biology and host-pathogen coevolution. In addition to whole genome sequencing, low coverage genomic data like reduced representation libraries, resequencing data, etc. have contributed significantly towards our understanding of the evolution of natural populations, and their responses to climatic and anthropogenic perturbations. In this review, we discuss how genomic data have enhanced our understanding of physiological adaptations in bats (particularly related to ageing, immunity, diet, etc.), pathogen discovery, and host pathogen co-evolution. In comparison, the application of NGS towards population genomics, conservation, biodiversity assessment, and functional genomics has been appreciably slower. We reviewed the current areas of focus, identifying emerging topical research directions and providing a roadmap for future genomic studies in bats.

Selenium-binding proteins represent a ubiquitous protein family and recently SBP1 was described as a new stress response regulator in plants. SBP1 has been characterized as a methanethiol oxidase, however its exact role remains unclear. Moreover, in mammals, it is involved in the regulation of anti-carcinogenic growth and progression as well as reduction/oxidation modulation and detoxification. In this work, we delineate the functional potential of certain motifs of SBP in the context of evolutionary relationships. The phylogenetic profiling approach revealed the absence of SBP in the fungi phylum as well as in most non eukaryotic organisms. The phylogenetic tree also indicates the differentiation and evolution of characteristic SBP motifs. Main evolutionary events concern the CSSC motif for which Acidobacteria, Fungi and Archaea carry modifications. Moreover, the CC motif is harbored by some bacteria and remains conserved in Plants, while modified to CxxC in Animals. Thus, the characteristic sequence motifs of SBPs mainly appeared in Archaea and Bacteria and retained in Animals and Plants. Our results demonstrate the emergence of SBP from bacteria and most likely as a methanethiol oxidase.

The yeast Saccharomyces cerevisiae has a long and esteemed history as a model system for laboratory selection experiments. The majority of yeast evolution experiments begin with an isogenic ancestor, impose selection as cells divide asexually, and track mutations that arise and accumulate over time. Within the last decade, the popularity of S. cerevisiae as a model system for exploring the evolution of standing genetic variation has grown considerably. As a facultatively sexual microbe, it is possible to initiate experiments with populations that harbor diversity and also to maintain that diversity by promoting sexual recombination as the experiment progresses. These experimental choices expand the scope of evolutionary hypotheses that can be tested with yeast. And, in this review, I argue that yeast is one of the best model systems for testing such hypotheses relevant to eukaryotic species. Here, I compile a list of yeast evolution experiments that involve standing genetic variation, initially and/or by implementing protocols that induce sexual recombination in evolving populations. I also provide an overview of experimental methods required to set up such an experiment and discuss the unique challenges that arise in this type of research. Throughout the article, I emphasize the best practices emerging from this small but growing niche of the literature.

Tea, which is processed by the tender shoots or leaves of tea plant (Camellia sinensis), is one of the most popular nonalcoholic beverages in the world and has numerous health benefits for humans. Along with new progress in biotechnologies, the refined chromosome-scale reference tea genomes have been achieved, which facilitates great promise for the understanding of fundamental genomic architecture and evolution of the tea plants. Here, we summarize recent achievements in genome sequencing in tea plants and review the new progress in origin and evolution of tea plants by population sequencing analysis. Understanding the genomic characterization of tea plants is import to improve tea quality and accelerate breeding in tea plants.

Cancer originates from somatic cells that have accumulated mutations. These mutations alter the phenotype of the cells, allowing them to escape homeostatic regulation that maintains normal cell numbers. The emergence of malignancies is an evolutionary process in which the random accumulation of somatic mutations and sequential selection of dominant clones cause cancer cells to proliferate. The development of technologies such as high-throughput sequencing has provided a powerful means to measure subclonal evolutionary dynamics across space and time. Here, we review the patterns that may be observed in cancer evolution and the methods available for quantifying the evolutionary dynamics of cancer. An improved understanding of the evolutionary trajectories of cancer will enable us to explore the molecular mechanism of tumorigenesis and to design tailored treatment strategies.

The mammalian skin exhibits a rich spectrum of evolutionary adaptations. The pilosebaceous unit, composed of the hair shaft, follicle, and the sebaceous gland, is the most striking synapomorphy. The evolutionary diversification of mammals across different ecological niches was paralleled by the appearance of an ample variety of skin modifications. Pangolins, order Pholidota, exhibit keratin-derived scales, one of the most iconic skin appendages. This formidable armor is intended to serve as a deterrent against predators. Surprisingly, while pangolins have hair on their abdomens, the occurrence of sebaceous and sweat glands is contentious. Here, we explore various molecular modules of skin physiology in four pangolin genomes, including that of sebum production. We show that genes driving wax monoester formation, Awat1/2, show patterns of inactivation in the stem pangolin branch, while the triacylglycerol synthesis gene Dgat2l6 seems independently eroded in the African and Asian clades. In contrast, Elovl3 implicated in the formation of specific neutral lipids required for skin barrier function is intact and expressed in the pangolin skin. An extended comparative analysis shows that genes involved in skin pathogen defense and structural integrity of keratinocyte layers also show inactivating mutations: associated with both ancestral and independent pseudogenization events. Finally, we deduce that the suggested absence of sweat glands is not paralleled by the inactivation of the ATP-binding cassette transporter Abcc11, as previously described in Cetacea. Our findings reveal the sophisticated and complex history of gene retention and loss as key mechanisms in the evolution of the highly modified mammalian skin phenotypes.

Copy number variants (CNVs), comprising gene amplifications and deletions, are a pervasive class of heritable variation. CNVs play a key role in rapid adaptation in both natural, and experimental, evolution. However, despite the advent of new DNA sequencing technologies, detection and quantification of CNVs in heterogeneous populations has remained challenging. Here, we summarize recent advances in the use of CNV reporters that provide a facile means of quantifying de novo CNVs at a specific locus in the genome, and nanopore sequencing, for resolving the often complex structures of CNVs. We provide guidance for the engineering and analysis of CNV reporters and practical guidelines for single-cell analysis of CNVs using flow cytometry. We summarize recent advances in nanopore sequencing, discuss the utility of this technology, and provide guidance for the bioinformatic analysis of these data to define the molecular structure of CNVs. The combination of reporter systems for tracking and isolating CNV lineages and long-read DNA sequencing for characterizing CNV structures enables unprecedented resolution of the mechanisms by which CNVs are generated and their evolutionary dynamics.

Type IB topoisomerases relax the torsional stress associated with DNA metabolism in the nucleus and mitochondria and constitute important molecular targets of anticancer drugs. Vertebrates stand out among eukaryotes by having two Type IB topoisomerases acting specifically in the nucleus (TOP1) and mitochondria (TOP1MT). Despite their major importance, the origin and evolution of these paralogues remain unknown. Here, we examine the molecular evolutionary processes acting on both TOP1 and TOP1MT in Chordata, taking advantage of the increasing number of available genome sequences. We found that both TOP1 and TOP1MT evolved under strong purifying selection, as expected considering their essential biological functions. Critical active sites, including those associated with resistance to anticancer agents, were found particularly conserved. However, TOP1MT presented a higher rate of molecular evolution than TOP1, possibly related with its specialized activity on the mitochondrial genome and a less critical role in cells. We could place the duplication event that originated the TOP1 and TOP1MT paralogues early in the radiation of vertebrates, most likely associated with the first round of vertebrate tetraploidization (1R). Moreover, our data suggest that cyclostomes present a specialized mitochondrial Type IB topoisomerase. Interestingly, we identified two missense mutations replacing amino acids in the Linker region of TOP1MT in Neanderthals, which appears as a rare event when comparing the genome of both species. In conclusion, TOP1 and TOP1MT differ in their rates of evolution, and their evolutionary histories allowed us to better understand the evolution of chordates.

The phrase "survival of the fittest" has become an iconic descriptor of how natural selection works. And yet, precisely measuring fitness, even for single-celled microbial populations growing in controlled laboratory conditions, remains a challenge. While numerous methods exist to perform these measurements, including recently developed methods utilizing DNA barcodes, all methods are limited in their precision to differentiate strains with small fitness differences. In this study, we rule out some major sources of imprecision, but still find that fitness measurements vary substantially from replicate to replicate. Our data suggest that very subtle and difficult to avoid environmental differences between replicates create systematic variation across fitness measurements. We conclude by discussing how fitness measurements should be interpreted given their extreme environment dependence. This work was inspired by the scientific community who followed us and gave us tips as we live tweeted a high-replicate fitness measurement experiment at #1BigBatch.

Aquaporins (AQPs) are integral membrane proteins responsible for water transport across cellular membranes in both prokaryotes and eukaryotes. A subfamily of AQPs, known as aquaglyceroporins (AQGPs), facilitate the transport of small solutes such as glycerol, water, and other solutes across cellular membranes. These proteins are involved in a variety of physiological processes, such as organogenesis, wound healing, and hydration. Although AQPs have been studied extensively in different species, their conservation patterns, phylogenetic relationships, and evolution in mammals remain unexplored. In the present study, 119 AQGP coding sequences from 31 mammalian species were analysed to identify conserved residues, gene organisation, and most importantly, the nature of AQGP gene selection. Repertoire analysis revealed the absence of AQP7, 9, and 10 genes in certain species of Primates, Rodentia, and Diprotodontia, although not all three genes were absent in a single species. Two Asparagine-Proline-Alanine (NPA) motifs located at the N- and C-terminal ends, aspartic acid (D) residues, and the ar/R region were conserved in AQP3, 9, and 10. Six exons encoding the functional MIP domain of AQGP genes were found to be conserved across mammalian species. Evolutionary analysis indicated signatures of positive selection in AQP7, 9, and 10 amongst different mammalian lineages. Furthermore, substitutions of certain amino acids located close to critical residues may alter AQGP functionality, which is crucial for substrate selectivity, pore formation, and transport efficiency required for the maintenance of homeostasis in different mammalian species.

The fitness of a genotype is defined as its lifetime reproductive success, with fitness itself being a composite trait likely dependent on many underlying phenotypes. Measuring fitness is important for understanding how alteration of different cellular components affects a cell's ability to reproduce. Here, we describe an improved approach, implemented in Python, for estimating fitness in high throughput via pooled competition assays.

Pooled sequencing-based fitness assays are a powerful and widely used approach to quantifying fitness of thousands of genetic variants in parallel. Despite the throughput of such assays, they are prone to biases in fitness estimates, and errors in measurements are typically larger for deleterious fitness effects, relative to neutral effects. In practice, designing pooled fitness assays involves tradeoffs between the number of timepoints, the sequencing depth, and other parameters to gain as much information as possible within a feasible experiment. Here, we combined simulations and reanalysis of an existing experimental dataset to explore how assay parameters impact measurements of near-neutral and deleterious fitness effects using a standard fitness estimator. We found that sequencing multiple timepoints at relatively modest depth improved estimates of near-neutral fitness effects, but systematically biased measurements of deleterious effects. We showed that a fixed total number of reads, deeper sequencing at fewer timepoints improved resolution of deleterious fitness effects. Our results highlight a tradeoff between measurement of deleterious and near-neutral effect sizes for a fixed amount of data and suggest that fitness assay design should be tuned for fitness effects that are relevant to the specific biological question.

Chlorophyllide a oxygenase (CAO) is responsible for converting chlorophyll a to chlorophyll b in a two-step oxygenation reaction. CAO belongs to the family of Rieske-mononuclear iron oxygenases. Although the structure and reaction mechanism of other Rieske monooxygenases have been described, a member of plant Rieske non-heme iron-dependent monooxygenase has not been structurally characterized. The enzymes in this family usually form a trimeric structure and electrons are transferred between the non-heme iron site and the Rieske center of the adjoining subunits. CAO is supposed to form a similar structural arrangement. However, in Mamiellales such as Micromonas and Ostreococcus, CAO is encoded by two genes where non-heme iron site and Rieske cluster localize on the distinct polypeptides. It is not clear if they can form a similar structural organization to achieve the enzymatic activity. In this study, the tertiary structures of CAO from the model plant Arabidopsis thaliana and the Prasinophyte Micromonas pusilla were predicted by deep learning-based methods, followed by energy minimization and subsequent stereochemical quality assessment of the predicted models. Furthermore, the chlorophyll a binding cavity and the interaction of ferredoxin, which is the electron donor, on the surface of Micromonas CAO were predicted. The electron transfer pathway was predicted in Micromonas CAO and the overall structure of the CAO active site was conserved even though it forms a heterodimeric complex. The structures presented in this study will serve as a basis for understanding the reaction mechanism and regulation of the plant monooxygenase family to which CAO belongs.

Mutations of DNA organisms are introduced by replication errors. However, SARS-CoV-2, as an RNA virus, is additionally subjected to rampant RNA editing by hosts. Both resources contributed to SARS-CoV-2 mutation and evolution, but the relative prevalence of the two origins is unknown. We performed comparative genomic analyses at intra-species (world-wide SARS-CoV-2 strains) and inter-species (SARS-CoV-2 and RaTG13 divergence) levels. We made prior predictions of the proportion of each mutation type (nucleotide substitution) under different scenarios and compared the observed versus the expected. C-to-T alteration, representing C-to-U editing, is far more abundant that all other mutation types. Derived allele frequency (DAF) as well as novel mutation rate of C-to-T are the highest in SARS-CoV-2 population, and C-T substitution dominates the divergence sites between SARS-CoV-2 and RaTG13. This is compelling evidence suggesting that C-to-U RNA editing is the major source of SARS-CoV-2 mutation. While replication errors serve as a baseline of novel mutation rate, the C-to-U editing has elevated the mutation rate for orders of magnitudes and accelerates the evolution of the virus.

TenA thiamin-degrading enzymes are commonly found in prokaryotes, plants, fungi and algae and are involved in the thiamin salvage pathway. The gut symbiont Bacteroides thetaiotaomicron (Bt) produces a TenA protein (BtTenA) which is packaged into its extracellular vesicles. An alignment of BtTenA protein sequence with proteins from different databases using the basic local alignment search tool (BLAST) and the generation of a phylogenetic tree revealed that BtTenA is related to TenA-like proteins not only found in a small number of intestinal bacterial species but also in some aquatic bacteria, aquatic invertebrates, and freshwater fish. This is, to our knowledge, the first report describing the presence of TenA-encoding genes in the genome of members of the animal kingdom. By searching metagenomic databases of diverse host-associated microbial communities, we found that BtTenA homologues were mostly represented in biofilms present on the surface of macroalgae found in Australian coral reefs. We also confirmed the ability of a recombinant BtTenA to degrade thiamin. Our study shows that BttenA-like genes which encode a novel sub-class of TenA proteins are sparingly distributed across two kingdoms of life, a feature of accessory genes known for their ability to spread between species through horizontal gene transfer.

HUA ENHANCER 1 (HEN1) is a pivotal mediator in protecting sRNAs from 3'-end uridylation and 3' to 5' exonuclease-mediated degradation in plants. Here, we investigated the pattern of the HEN1 protein family evolutionary history and possible relationships in the plant lineages using protein sequence analyses and conserved motifs composition, functional domain identification, architecture, and phylogenetic tree reconstruction and evolutionary history inference. According to our results, HEN1 protein sequences bear several highly conserved motifs in plant species retained during the evolution from their ancestor. However, several motifs are present only in Gymnosperms and Angiosperms. A similar trend showed for their domain architecture. At the same time, phylogenetic analysis revealed the grouping of the HEN1 proteins in the three main super clads. In addition, the Neighbor-net network analysis result provides some nodes have multiple parents indicating a few conflicting signals in the data, which is not the consequence of sampling error, the effect of the selected model, or the estimation method. By reconciling the protein and species tree, we considered the gene duplications in several given species and found 170 duplication events in the evolution of HEN1 in the plant lineages. According to our analysis, the main HEN1 superclass mostly showed orthologous sequences that illustrate the vertically transmitting of HEN1 to the main lines. However, in both orthologous and paralogs, we predicted insignificant structural deviations. Our analysis implies that small local structural changes that occur continuously during the folds can moderate the changes created in the sequence. According to our results, we proposed a hypothetical model and evolutionary trajectory for the HEN1 protein family in the plant kingdom.

The structure and function of human leucocyte antigen (HLA-A) is well known and is an extremely variable protein. From the public HLA-A database, we chose 26 high frequency HLA-A alleles (45% of sequenced alleles). Using five arbitrary references from these alleles, we analyzed synonymous mutations at the third codon position (sSNP3) and non-synonymous mutations (NSM). Both mutation types showed non-random locations of 29 sSNP3 codons and 71 NSM codons in the five reference lists. Most sSNP3 codons show identical mutation types with many mutations resulting from cytosine deamination. We proposed 23 ancestral parents of sSNP3 in five reference sequences using conserved parents in five unidirectional codons and 18 majority parents in reciprocal codons. These 23 proposed ancestral parents show exclusive codon usage of G3 or C3 parents located on both DNA strands that mutate to A3 or T3 variants mostly (76%) by cytosine deamination The sSNP3 and NSM show clear separation of the two variant types with most sSNP3 located in conserved areas in exons 2, 3 and 4, compared to most NSM appearing in two Variable Areas with no sSNP3 in the latter parts of exons 2 (α1) and 3 (α2). The Variable Areas contain NSM (polymorphic) residues at the center of the groove that bind the foreign peptide. We find distinctly different mutation patterns in NSM codons from those of sSNP3. Namely, G-C to A-T mutation frequency was much smaller, suggesting that evolutional pressures of deamination and other mechanisms applied to the two areas are significantly different.

Genetic integrity of an accession should be preserved in the conservation of germplasm. Characterization of diverse germplasm based on a molecular basis enhances its conservation and use in breeding programs. The aim of this study was to assess the genetic diversity of 169 sorghum accessions using a total of 6977 SNP markers. The polymorphic information content of the markers was 0.31 which is considered to be moderately high. Structure analysis using ADMIXTURE program revealed a total of 10 subpopulations. Neighbor-joining tree revealed the presence of six main clusters among these subpopulations whereas in principal component analysis, seven clusters were identified. Cluster analysis grouped most populations depending on source of collection although other accessions originating from the same source were grouped under different clusters. Analysis of molecular variance (AMOVA) revealed 30% and 70% of the variation occurred within and among accessions, respectively. Gene flow within the populations was, however, limited indicating high differentiation within the subpopulation. Observed heterozygosity among accessions varied from 0.03 to 0.06 with a mean of 0.05 since sorghum is a self-pollinating crop. High genetic diversity among the subpopulations can be further explored for superior genes to develop new sorghum varieties.

Following the completion of an adaptive evolution experiment, fitness evaluations are routinely conducted to assess the magnitude of adaptation. In doing so, proper consideration should be given when determining the appropriate methods as trade-offs may exist between accuracy and throughput. Here, we present three instances in which small changes in the framework or execution of fitness evaluations significantly impacted the outcomes. The first case illustrates that discrepancies in fitness conclusions can arise depending on the approach to evaluating fitness, the culture vessel used, and the sampling method. The second case reveals that variations in environmental conditions can occur associated with culture vessel material. Specifically, these subtle changes can greatly affect microbial physiology leading to changes in the culture pH and distorting fitness measurements. Finally, the last case reports that heterogeneity in CFU formation time can result in inaccurate fitness conclusions. Based on each case, considerations and recommendations are presented for future adaptive evolution experiments.

About 90% of people infected with Human T lymphotropic virus type-1 (HTLV-1) virus are asymptomatic, so it can be said that the prevalence of this virus is not completely clear. During chronic infection, the expression of programmed cell death-1 (PD-1) protein increases and causes exhausted phenotype in T cells. Considering the role of host genetics and immune responses in HTLV-1 infection, in this case-control study, included 81 asymptomatic carriers (ACs) and 162 healthy controls (HCs), rs11568821 and rs41386349 polymorphisms of PD-1 gene were evaluated by Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method which investigated by one primer pair for both polymorphisms also, proviral load (PVL) measured by quantitative real-time PCR (Q-RT-PCR). The results showed that the mutant allele of rs11568821 (A) and rs41386349 (T) polymorphisms is associated with an increase in HTLV-1 infection significantly (p = 0.019 and p = 0.000 respectively). But there was no significant relationship between PVL and polymorphisms.

Interferon induced with helicase C domain-containing protein 1 (IFIH1) gene encodes a cytoplasmic RNA helicase otherwise known as melanoma differentiation-associated 5 (MDA5), a RIG-1-like RNA helicase that recognizes viral RNA and is involved in innate immunity through recognition of viral RNA. Upon binding to double-stranded (ds) RNA, MDA5 forms a filamentous assembly along the length of dsRNA and utilizes molecular signatures to discriminate self, versus non-self on the basis of dsRNA length and methylation. Its missense variant rs35667974 is protective for type 1 diabetes, psoriasis, and psoriatic arthritis, but is also found to be associated with an increased risk for ankylosing spondylitis, Crohn's disease, and ulcerative colitis. To gain insight into the complex role of this variant we performed a structural analysis of MDA5 in complex with dsRNA using molecular dynamics simulations. Our data suggest that while the Ile923Val mutation of the rs35667974 variant does not affect binding to native dsRNA significantly, it displays a destabilizing effect in the presence of 2'-O uridine methylation. Thus, the presence of 2'-O-methylation at the dsRNA introduces a sensing signature that leads to selective reduction of the overall MDA catalytic activity. This study represents an evaluation of the role of the shared rs35667974 variant of autoimmune locus IFIH1, reported to lead to selectively reduced catalytic activity of the modified MDA5 phenotype and, as a consequence, reduced negative feedback on cytokine and chemokine signaling and selectively protection against autoimmunity.

Evolutionary processes happen gradually over time and are, thus, considered time dependent. In addition, several evolutionary processes are either adaptations to local habitats or changing habitats, otherwise restricted thereby. Since evolutionary processes driving speciation take place within the landscape of environmental and temporal bounds, several published studies have aimed at providing accurate, fossil-calibrated, estimates of the divergence times of both extant and extinct species. Correct calibration is critical towards attributing evolutionary adaptations and speciation both to the time and paleogeography that contributed to it. Data from more than 4000 studies and nearly 1,50,000 species are available from a central TimeTree resource and provide opportunities of retrieving divergence times, evolutionary timelines, and time trees in various formats for most vertebrates. These data greatly enhance the ability of researchers to investigate evolution. However, there is limited functionality when studying lists of species that require batch retrieval. To overcome this, a PYTHON package termed Python-Automated Retrieval of TimeTree data (PAReTT) was created to facilitate a biologist-friendly interaction with the TimeTree resource. Here, we illustrate the use of the package through three examples that includes the use of timeline data, time tree data, and divergence time data. Furthermore, PAReTT was previously used in a meta-analysis of candidate genes to illustrate the relationship between divergence times and candidate genes of migration. The PAReTT package is available for download from GitHub or as a pre-compiled Windows executable, with extensive documentation on the package available on GitHub wiki pages regarding dependencies, installation, and implementation of the various functions.

Mammalian plasma kallikrein (PK) and coagulation factor XI (fXI) are serine proteases that play in the kinin-kallikrein cascade and in the blood clotting pathway. These proteases share sequence homology and have four apple domains (APDs) and a serine protease domain (SPD) from their N-terminus to C-terminus. No homologs of these proteases are believed to be present in fish species, except for lobe-finned fish. Fish, however, have a unique lectin, named kalliklectin (KL), which is composed of APDs only. In the present study, we found genomic sequences encoding a protein with both APDs and SPD in a few cartilaginous and bony fishes, including the channel catfish Ictalurus punctatus, using bioinformatic analysis. Furthermore, we purified two ~ 70 kDa proteins from the blood plasma of the catfish using mannose-affinity and gel filtration chromatography sequentially. Using de novo sequencing with quadrupole time-of-flight tandem mass spectrometry, several internal amino acid sequences in these proteins were mapped onto possible PK/fXI-like sequences that are thought to be splicing variants. Exploration of APD-containing proteins in the hagfish genome database and phylogenetic analysis suggested that the PK/fXI-like gene originated from hepatocyte growth factor, and that the gene was acquired in a common ancestor of jawed fish. Synteny analysis provided evidence for chromosomal translocation around the PK/fXI-like locus that occurred in the common ancestor of holosteans and teleosts after separation from the lobe-finned fish lineage, or gene duplication into two chromosomes, followed by independent gene losses. This is the first identification of PK/fXI-like proteins in teleosts.