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Inferring the chronological and biological age of individuals is fundamental to population ecology and our understanding of ageing itself, its evolution, and the biological processes that affect or even cause ageing. Epigenetic clocks based on DNA methylation (DNAm) at specific CpG sites show a strong correlation with chronological age in humans, and discrepancies between inferred and actual chronological age predict morbidity and mortality. Recently, a growing number of epigenetic clocks have been developed in non‐model animals and we here review these studies. We also conduct a meta‐analysis to assess the effects of different aspects of experimental protocol on the performance of epigenetic clocks for non‐model animals. Two measures of performance are usually reported, the R2 of the association between the predicted and chronological age, and the mean/median absolute deviation (MAD) of estimated age from chronological age, and we argue that only the MAD reflects accuracy. R2 for epigenetic clocks based on the HorvathMammalMethylChip4 was higher and the MAD scaled to age range lower, compared with other DNAm quantification approaches. Scaled MAD tended to be lower among individuals in captive populations, and decreased with an increasing number of CpG sites. We conclude that epigenetic clocks can predict chronological age with relatively high accuracy, suggesting great potential in ecological epigenetics. We discuss general aspects of epigenetic clocks in the hope of stimulating further DNAm‐based research on ageing, and perhaps more importantly, other key traits. [ABSTRACT FROM AUTHOR]

The classification of cells in non-model organisms has lagged behind the classification of cells in model organisms that have established cluster of differentiation marker sets. To reduce fish diseases, research is needed to better understand immune-related cells, or hemocytes, in non-model organisms like shrimp and other marine invertebrates. In this study, we used Drop-seq to examine how virus infection affected the populations of hemocytes in kuruma shrimp, Penaeus japonicus, which had been artificially infected with a virus. The findings demonstrated that virus infection reduced particular cell populations in circulating hemolymph and inhibited the expression of antimicrobial peptides. We also identified the gene sets that are likely to be responsible for this reduction. Additionally, we identified functionally unknown genes as novel antimicrobial peptides, and we supported this assumption by the fact that these genes were expressed in the population of hemocytes that expressed other antimicrobial peptides. In addition, we aimed to improve the operability of the experiment by conducting Drop-seq with fixed cells as a source and discussed the impact of methanol fixation on Drop-seq data in comparison to previous results obtained without fixation. These results not only deepen our understanding of the immune system of crustaceans but also demonstrate that single-cell analysis can accelerate research on non-model organisms. [ABSTRACT FROM AUTHOR]

The degree to which host, pathogen, and environmental characteristics determine fitness outcomes in response to infection across the tree of life is a key question in ecoimmunology. Because infection experiments require large sample sizes and careful controls, studies have generally been limited to lab‐adapted organisms.Photinus pyralis is a charismatic firefly that is abundant during its annual summer emergence in the Eastern United States. Here, we assess the importance of host condition, pathogen identity and dose, and pre‐infection environment on survival outcomes in response to bacterial infection in wild‐caught adult male P. pyralis.Although survival after sterile saline injection was not statistically different from survival of uninjected controls, survival kinetics support sterile saline injection as the most appropriate control.Serratia marcescens and Providencia rettgeri infections increased mortality, especially at high doses. In contrast to fruit fly studies, Providencia sneebia, Pseudomonas aeruginosa, and Enterococcus faecalis infections did not. Infection with higher doses of P. rettgeri had an increased risk of death for fireflies caught later in the season than those captured earlier, but seasonality did not significantly interact with dose to impact mortality with any of the other bacterial species.These results highlight the importance of considering host, pathogen, and environmental factors when investigating infection outcomes in wild‐caught, non‐model systems. The differences in survival between fireflies and fruit flies emphasise that further studies in a broad array of organisms are needed to explore the diversity of infection responses across the tree of life. [ABSTRACT FROM AUTHOR]

The use of next‐generation sequencing (NGS) data sets has increased dramatically over the last decade, but there have been few systematic analyses quantifying the accuracy of the commonly used variant caller programs. Here we used a familial design consisting of diploid tissue from a single lodgepole pine (Pinus contorta) parent and the maternally derived haploid tissue from 106 full‐sibling offspring, where mismatches could only arise due to mutation or bioinformatic error. Given the rarity of mutation, we used the rate of mismatches between parent and offspring genotype calls to infer the single nucleotide polymorphism (SNP) genotyping error rates of FreeBayes, HaplotypeCaller, SAMtools, UnifiedGenotyper, and VarScan. With baseline filtering HaplotypeCaller and UnifiedGenotyper yielded more SNPs and higher error rates by one to two orders of magnitude, whereas FreeBayes, SAMtools and VarScan yielded lower numbers of SNPs and more modest error rates. To facilitate comparison between variant callers we standardized each SNP set to the same number of SNPs using additional filtering, where UnifiedGenotyper consistently produced the smallest proportion of genotype errors, followed by HaplotypeCaller, VarScan, SAMtools, and FreeBayes. Additionally, we found that error rates were minimized for SNPs called by more than one variant caller. Finally, we evaluated the performance of various commonly used filtering metrics on SNP calling. Our analysis provides a quantitative assessment of the accuracy of five widely used variant calling programs and offers valuable insights into both the choice of variant caller program and the choice of filtering metrics, especially for researchers using non‐model study systems. [ABSTRACT FROM AUTHOR]

Acetogenic bacteria are an increasingly popular choice for producing fuels and chemicals from single carbon (C1) substrates. Eubacterium limosum is a promising acetogen with several native advantages, including the ability to catabolize a wide repertoire of C1 feedstocks and the ability to grow well on agar plates. However, despite its promise as a strain for synthetic biology and metabolic engineering, there are insufficient engineering tools and molecular biology knowledge to leverage its native strengths for these applications. To capitalize on the natural advantages of this organism, here we extended its limited engineering toolbox. We evaluated the copy number of three common plasmid origins of replication and devised a method of controlling copy number and heterologous gene expression level by modulating antibiotic concentration. We further quantitatively assessed the strength and regulatory tightness of a panel of promoters, developing a series of well-characterized vectors for gene expression at varying levels. In addition, we developed a black/white colorimetric genetic reporter assay and leveraged the high oxygen tolerance of E. limosum to develop a simple and rapid transformation protocol that enables benchtop transformation. Finally, we developed two new antibiotic selection markers—doubling the number available for this organism. These developments will enable enhanced metabolic engineering and synthetic biology work with E. limosum. [ABSTRACT FROM AUTHOR]

Purpose: Eating contaminated food continues to cause numerous food-borne diseases globally. Understanding the causes of poor food safety practices is key to preventing food-borne diseases. Therefore, this study aimed to assess the prevalence of food safety practices and associated factors among health extension model and non-model households in Kombolcha, Ethiopia. Methods: A comparative cross-sectional study was conducted among 327 model households and 329 non-model households in Kombolcha. Four kebeles were selected randomly from a total of 12 kebeles, followed by a systematic random sampling method to select a total of 656 households. The data were collected through face-to-face interviews with household heads and observations from April 15 to May 15, 2021. Data were entered into EpiData version 3.1 and analyzed using SPSS version 25.0. Determinants of food safety practices were determined by using multivariable logistic regression model at a p-value < 0.05. Results: The overall prevalence of food safety practices was 44.7% (95% CI: 40.5– 48.4%), of which 57.8% (95% CI: 53.0– 63.1%) were model and 31.6% (95% CI: 26.5– 36.7%) were non-model households, with significant variation among household types. Being a model household (AOR=2.99; 95% CI: 1.98– 4.52), having a female household head (AOR=3.13; 95% CI: 2.13– 4.59), proper solid waste management (AOR=2.32; 95% CI: 1.54– 3.48), good knowledge of food safety (AOR=2.05; 95% CI: 1.43– 3.03), and good attitude (AOR=1.74; 95% CI: 1.22, 2.49) were significant predictors of good food safety practices. Conclusion: The prevalence of good food safety practices was not satisfactory. Being a model household, having a female household head, proper solid waste management, good knowledge, and good attitude were significantly associated with good food safety practices. Therefore, the identified modifiable factors are potential areas of intervention to enhance good food safety practices. [ABSTRACT FROM AUTHOR]

Despite their suitability for studying evolution, many conifer species have large and repetitive giga‐genomes (16–31 Gbp) that create hurdles to producing high coverage SNP data sets that capture diversity from across the entirety of the genome. Due in part to multiple ancient whole genome duplication events, gene family expansion and subsequent evolution within Pinaceae, false diversity from the misalignment of paralog copies creates further challenges in accurately and reproducibly inferring evolutionary history from sequence data. Here, we leverage the cost‐saving benefits of pool‐seq and exome‐capture to discover SNPs in two conifer species, Douglas‐fir (Pseudotsuga menziesii var. menziesii (Mirb.) Franco, Pinaceae) and jack pine (Pinus banksiana Lamb., Pinaceae). We show, using minimal baseline filtering, that allele frequencies estimated from pooled individuals show a strong, positive correlation with those estimated by sequencing the same population as individuals (r >.948), on par with such comparisons made in model organisms. Further, we highlight the utility of haploid megagametophyte tissue for identifying sites that are probably due to misaligned paralogs. Together with additional minor filtering, we show that it is possible to remove many of the loci with large frequency estimate discrepancies between individual and pooled sequencing approaches, improving the correlation further (r >.973). Our work addresses bioinformatic challenges in non‐model organisms with large and complex genomes, highlights the use of megagametophyte tissue for the identification of paralogous artefacts, and suggests the combination of pool‐seq and exome capture to be robust for further evolutionary hypothesis testing in these systems. [ABSTRACT FROM AUTHOR]

EnTAP (Eukaryotic Non‐Model Transcriptome Annotation Pipeline) was designed to improve the accuracy, speed, and flexibility of functional gene annotation for de novo assembled transcriptomes in non‐model eukaryotes. This software package addresses the fragmentation and related assembly issues that result in inflated transcript estimates and poor annotation rates of protein‐coding transcripts. Following filters applied through assessment of true expression and frame selection, open‐source tools are leveraged to functionally annotate the reduced set of translated proteins. Downstream features include fast similarity search across five repositories, protein domain assignment, orthologous gene family assessment, and Gene Ontology (GO) term assignment. The final annotation integrates across multiple databases and selects an optimal assignment from a combination of weighted metrics describing similarity search score, taxonomic relationship, and informativeness. Researchers have the option to include additional filters to identify and remove contaminants, identify associated pathways, and prepare the transcripts for enrichment analysis. This fully featured pipeline is easy to install, configure, and runs significantly faster than comparable annotation packages. EnTAP is optimized to generate extensive functional information for the gene space of organisms with limited or poorly characterized genomic resources. [ABSTRACT FROM AUTHOR]

Planktonic copepods are a diverse and abundant group of small (~mm sized) aquatic animals that play a critical role in linking the base of the food chain with higher trophic levels. These invertebrates are a primary food source for marine fish larvae. Their ubiquitous presence is thus of vital importance for recruitment of fish stocks and also as promising live feed for finfish production in aquaculture. This paper reviews the application of molecular approaches to understanding copepod physiology, particularly in non-parasitic species. The review includes both targeted gene approaches and untargeted transcriptomic approaches, with suggestions for best practices in each case. Issues particularly relevant to studies of copepods include heterogeneity within species, morphologically cryptic species, experimental artifacts associated with sample handling, and limited annotation of copepod genes and transcripts. The emergence of high-throughput sequencing and associated increased availability of genomic and transcriptomic databases have presented a huge opportunity to advance knowledge of copepod physiology. The research community can leverage this opportunity through efforts to maintain or improve data accessibility, database annotation, and documentation of analytical pipelines. Unlabelled Image [ABSTRACT FROM AUTHOR]

Knowledge of how individuals are related is important in many areas of research, and numerous methods for inferring pairwise relatedness from genetic data have been developed. However, the majority of these methods were not developed for situations where data are limited. Specifically, most methods rely on the availability of population allele frequencies, the relative genomic position of variants and accurate genotype data. But in studies of non‐model organisms or ancient samples, such data are not always available. Motivated by this, we present a new method for pairwise relatedness inference, which requires neither allele frequency information nor information on genomic position. Furthermore, it can be applied not only to accurate genotype data but also to low‐depth sequencing data from which genotypes cannot be accurately called. We evaluate it using data from a range of human populations and show that it can be used to infer close familial relationships with a similar accuracy as a widely used method that relies on population allele frequencies. Additionally, we show that our method is robust to SNP ascertainment and applicable to low‐depth sequencing data generated using different strategies, including resequencing and RADseq, which is important for application to a diverse range of populations and species. [ABSTRACT FROM AUTHOR]

Hypoxia and hyperthermia are two connected consequences of the ongoing global change and constitute major threats for coastal marine organisms. In the present study, we used a proteomic approach to characterize the changes induced by hypoxia in the great scallop, Pecten maximus, subjected to three different temperatures (10 °C, 18 °C and 25 °C). We did not observe any significant change induced by hypoxia in animals acclimated at 10 °C. At 18 °C and 25 °C, 16 and 11 protein spots were differentially accumulated between normoxia and hypoxia, respectively. Moreover, biochemical data (octopine dehydrogenase activity and arginine assays) suggest that animals grown at 25 °C switched their metabolism towards anaerobic metabolism when exposed to both normoxia and hypoxia, suggesting that this temperature is out of the scallops’ optimal thermal window. The 11 proteins identified with high confidence by mass spectrometry are involved in protein modifications and signaling (e.g., CK2, TBK1), energy metabolism (e.g., ENO3) or cytoskeleton (GSN), giving insights into the thermal-dependent response of scallops to hypoxia.

Non-model plants i.e., the species which have one or all of the characters such as long life cycle, difficulty to grow in the laboratory or poor fecundity, have been schemed out of sequencing projects earlier, due to high running cost of Sanger sequencing. Consequently, the information about their genomics and key biological processes are inadequate. However, the advent of fast and cost effective next generation sequencing (NGS) platforms in the recent past has enabled the unearthing of certain characteristic gene structures unique to these species. It has also aided in gaining insight about mechanisms underlying processes of gene expression and secondary metabolism as well as facilitated development of genomic resources for diversity characterization, evolutionary analysis and marker assisted breeding even without prior availability of genomic sequence information. In this review we explore how different Next Gen Sequencing platforms, as well as recent advances in NGS based high throughput genotyping technologies are rewarding efforts on de-novo whole genome/transcriptome sequencing, development of genome wide sequence based markers resources for improvement of non-model crops that are less costly than phenotyping. [ABSTRACT FROM AUTHOR]

As approaches are sought for more efficient and democratized uses of non-model and expanded model genomics references, ease of integration of genomic feature datasets is especially desirable in multidisciplinary research communities. Valuable conclusions are often missed or slowed when researchers refer experimental results to a single reference sequence that lacks integrated pan-genomic and multi-experiment data in accessible formats. Association of genomic positional information, such as results from an expansive variety of next-generation sequencing experiments, with annotated reference features such as genes or predicted protein binding sites, provides the context essential for conclusions and ongoing research. When the experimental system includes polymorphic genomic inputs, rapid calculation of gene structural and protein translational effects of sequence variation from the reference can be invaluable. Here we present FEATnotator, a lightweight, fast and easy to use open source software program that integrates and reports overlap and proximity in genomic information from any user-defined datasets including those from next generation sequencing applications. We illustrate use of the tool by summarizing whole genome sequence variation of a widely used natural isolate of Arabidopsis thaliana in the context of gene models of the reference accession. Previous discovery of a protein coding deletion influencing root development is replicated rapidly. Appropriate even in investigations of a single gene or genic regions such as QTL, comprehensive reports provided by FEATnotator better prepare researchers for interpretation of their experimental results. The tool is available for download at http://featnotator.sourceforge.net . [ABSTRACT FROM AUTHOR]

Wildlife crime enforcement is increasingly relying on genetic techniques to deliver forensic evidence to investigators. Forensic DNA applications require robust molecular markers, informative at the level of the species, population and individual, in a wide range of taxa. Within species, single-nucleotide polymorphisms (SNPs) have long been recognized as offering many potential advantages over traditional microsatellite markers; however, the best methods for their discovery, validation and genotyping in non-model species remain an area of novel research and much discussion. The potential availability to wildlife geneticists of deep sequencing platforms and high-density genotyping arrays appears to promise an almost infinite source of variable markers for determining the geographic or individual origin of a sample. This study examines the drivers for developing SNP genotyping panels in wildlife forensics and their potential as applied tools, before examining a range of strategies that are being employed to try to unlock this potential and address current questions in wildlife conservation and enforcement. [ABSTRACT FROM AUTHOR]

Membrane proteins are of great interest to plant physiologists because of their important function in many physiological processes. However, their study is hampered by their low abundance and poor solubility in aqueous buffers. Proteomics studies of non-model plants are generally restricted to gel-based methods. Unfortunately, all gel-based techniques for membrane proteomics lack resolving power. Therefore, a very stringent enrichment method is needed before protein separation. In this study, protein extraction in a mixture of chloroform and methanol in combination with gel electrophoresis is evaluated as a method to study membrane proteins in non-model plants. Benefits as well as disadvantages of the method are discussed. To demonstrate the pitfalls of working with non-model plants and to give a proof of principle, the method was first applied to whole leaves of the model plant Arabidopsis. Subsequently, a comparison with proteins extracted from leaves of the non-model plant, banana, was made. To estimate the tissue and organelle specificity of the method, it was also applied on banana meristems. Abundant membrane or lipid-associated proteins could be identified in both tissues, with the leaf extract yielding a higher number of membrane proteins. [ABSTRACT FROM AUTHOR]

Fluctuating Thermal Regimes (FTR), where organisms are held at low temperatures with a brief, daily warm pulse, have been shown to increase longevity in adult insects and improve pupa survival while reducing sublethal effects. We used FTR to extend the longevity and thus generation time of the fly species Themira biloba (Diptera: Sepsidae). T. biloba can be maintained in continuous culture and requires an insecticide-free dung substrate for larval growth and development. Our objective was to decrease labor and consumable materials required to maintain insect species in critical scientific collections using FTR. We extended pupation time from 4 days up to 8 weeks with no increase in mortality, and mean adult longevity was increased from 12 days to 50 days. FTR is a valuable tool for reducing the investment required to maintain rare and exotic insects. • Fluctuating temperatures extended pupa development from 4 days to 8 weeks. • Mean adult longevity increased from 12 ± 0.29 days to 50 ± 1.79 days. • This protocol may be used to extend generation time and reduce resource consumption in some non-model species. [ABSTRACT FROM AUTHOR]

For the last century we have relied on model organisms to help understand fundamental biological processes. Now, with advancements in genome sequencing, assembly, and annotation, non-model organisms may be studied with the same advanced bioanalytical toolkit as model organisms. Proteomics is one such technique, which classically relies on predicted protein sequences to catalog and measure complex proteomes across tissues and biofluids. Applying proteomics to non-model organisms can advance and accelerate biomimicry studies, biomedical advancements, veterinary medicine, agricultural research, behavioral ecology, and food safety. In this postmodel organism era, we can study almost any species, meaning that many non-model organisms are, in fact, important emerging model organisms. Herein we specifically focus on eukaryotic organisms and discuss the steps to generate sequence databases, analyze proteomic data with or without a database, and interpret results as well as future research opportunities. Proteomics is more accessible than ever before and will continue to rapidly advance in the coming years, enabling critical research and discoveries in non-model organisms that were hitherto impossible.

Background RNA sequencing (RNA-seq) analyses can benefit from performing a genome-guided and de novo assembly, in particular for species where the reference genome or the annotation is incomplete. However, tools for integrating an assembled transcriptome with reference annotation are lacking. Findings Necklace is a software pipeline that runs genome-guided and de novo assembly and combines the resulting transcriptomes with reference genome annotations. Necklace constructs a compact but comprehensive superTranscriptome out of the assembled and reference data. Reads are subsequently aligned and counted in preparation for differential expression testing. Conclusions Necklace allows a comprehensive transcriptome to be built from a combination of assembled and annotated transcripts, which results in a more comprehensive transcriptome for the majority of organisms. In addition RNA-seq data are mapped back to this newly created superTranscript reference to enable differential expression testing with standard methods. [ABSTRACT FROM AUTHOR]

Hypoxia and hyperthermia are two connected consequences of the ongoing global change and constitute major threats for coastal marine organisms. In the present study, we used a proteomic approach to characterize the changes induced by hypoxia in the great scallop, Pecten maximus, subjected to three different temperatures (10 °C, 18 °C and 25 °C). We did not observe any significant change induced by hypoxia in animals acclimated at 10 °C. At 18 °C and 25 °C, 16 and 11 protein spots were differentially accumulated between normoxia and hypoxia, respectively. Moreover, biochemical data (octopine dehydrogenase activity and arginine assays) suggest that animals grown at 25 °C switched their metabolism towards anaerobic metabolism when exposed to both normoxia and hypoxia, suggesting that this temperature is out of the scallops' optimal thermal window. The 11 proteins identified with high confidence by mass spectrometry are involved in protein modifications and signaling (e.g., CK2, TBK1), energy metabolism (e.g., ENO3) or cytoskeleton (GSN), giving insights into the thermal-dependent response of scallops to hypoxia.