Uncovering the novel characteristics of Asian honey bee, Apis cerana, by whole genome sequencing

Genome-wide association analysis of grain yield and Striga hermonthica and S. asiatica resistance in tropical and sub-tropical maize populations

BACKGROUND

Genetic improvement for Striga hermonthica (Sh) and S. asiatica (Sa) resistance is the most economical and effective control method to enhance the productivity of maize and other major cereal crops. Hence, identification of quantitative trait loci (QTL) associated with Striga resistance and economic traits will guide the pace and precision of resistance breeding in maize. The objective of this study was to undertake a genome-wide association analysis of grain yield and Sh and Sa resistance among tropical and sub-tropical maize populations to identify putative genetic markers and genes for resistance breeding. 126 maize genotypes were evaluated under controlled environment conditions using artificial infestation of Sh and Sa. The test genotypes were profiled for grain yield (GY), Striga emergence counts at 8 (SEC8) and 10 (SEC10) weeks after planting, and Striga damage rate scores at 8 (SDR8) and 10 (SDR10) weeks after planting. Population structure analysis and genome-wide association mapping were undertaken based on 16,000 single nucleotide polymorphism (SNP) markers.

RESULTS

A linkage disequilibrium (LD) analysis in 798,675 marker pairs revealed that 21.52% of pairs were in significant linkage (P < 0.001). Across the chromosomes, the LD between SNPs decayed below a critical level (r2 = 0.1) at a map distance of 0.19 Mbp. The genome-wide association study identified 50 significant loci associated with Sh resistance and 22 significant loci linked to Sa resistance, corresponding to 39 and 19 candidate genes, respectively.

CONCLUSION

The study found non-significant QTL associated with dual resistance to the two examined Striga species Some of the detected genes reportedly conditioned insect and pathogen resistance, plant cell development, variable senescence, and pollen fertility. The markers detected in the present study for Sa resistance were reported for the first time. The gene Zm00001eb219710 was pleiotropic, and conditioned GY and SEC10, while Zm00001eb165170 affected SDR8 and SDR10, and Zm00001eb112030 conditioned SDR8 and SDR10 associated with Sh resistance. The candidate genes may facilitate simultaneous selection for Sh and Sa resistance and grain yield in maize after further validation and introgression in breeding pipelines. Overall, we recommend breeding maize specifically for resistance to each Striga species using germplasm adapted to the endemic region of each parasite.

Novel resistance loci for quantitative resistance to Septoria tritici blotch in Asian wheat (Triticum aestivum) via genome-wide association study

BACKGROUND

Septoria tritici blotch (STB) disease causes yield losses of up to 50 per cent in susceptible wheat cultivars and can reduce wheat production. In this study, genomic architecture for adult-plant STB resistance in a Septoria Association Mapping Panel (SAMP) having 181 accessions and genomic regions governing STB resistance in a South Asian wheat panel were looked for.

RESULTS

Field experiments during the period from 2019 to 2021 revealed those certain accessions, namely BGD52 (CHIR7/ANB//CHIR1), BGD54 (CHIR7/ANB//CHIR1), IND92 (WH 1218), IND8 (DBW 168), and IND75 (PBW 800), exhibited a high level of resistance. Genetic analysis revealed the presence of 21 stable quantitative trait nucleotides (QTNs) associated with resistance to STB (Septoria tritici blotch) on all wheat chromosomes, except for 2D, 3A, 3D, 4A, 4D, 5D, 6B, 6D, and 7A. These QTNs were predominantly located in chromosome regions previously identified as associated with STB resistance. Three Quantitative Trait Loci (QTNs) were found to have significant phenotypic effects in field evaluations. These QTNs are Q.STB.5A.1, Q.STB.5B.1, and Q.STB.5B.3. Furthermore, it is possible that the QTNs located on chromosomes 1A (Q.STB.1A.1), 2A (Q.STB_DH.2A.1, Q.STB.2A.3), 2B (Q.STB.2B.4), 5A (Q.STB.5A.1, Q.STB.5A.2), and 7B (Q.STB.7B.2) could potentially be new genetic regions associated with resistance.

CONCLUSION

Our findings demonstrate the importance of Asian bread wheat as a source of STB resistance alleles and novel stable QTNs for wheat breeding programs aiming to develop long-lasting and wide-ranging resistance to Zymoseptoria tritici in wheat cultivars.

Tracing the genealogy origin of geographic populations based on genomic variation and deep learning

Assigning a query individual animal or plant to its derived population is a prime task in diverse applications related to organismal genealogy. Such endeavors have conventionally relied on short DNA sequences under a phylogenetic framework. These methods naturally show constraints when the inferred population sources are ambiguously phylogenetically structured, a scenario demanding substantially more informative genetic signals. Recent advances in cost-effective production of whole-genome sequences and artificial intelligence have created an unprecedented opportunity to trace the population origin for essentially any given individual, as long as the genome reference data are comprehensive and standardized. Here, we developed a convolutional neural network method to identify population origins using genomic SNPs. Three empirical datasets (an Asian honeybee, a red fire ant, and a chicken datasets) and two simulated populations are used for the proof of concepts. The performance tests indicate that our method can accurately identify the genealogy origin of query individuals, with success rates ranging from  93 % to 100 %. We further showed that the accuracy of the model can be significantly increased by refining the informative sites through FST filtering. Our method is robust to configurations related to batch sizes and epochs, whereas model learning benefits from the setting of a proper preset learning rate. Moreover, we explained the importance score of key sites for algorithm interpretability and credibility, which has been largely ignored. We anticipate that by coupling genomics and deep learning, our method will see broad potential in conservation and management applications that involve natural resources, invasive pests and weeds, and illegal trades of wildlife products.

Relationship between wooden breast severity in broiler chicken, antioxidant enzyme activity and markers of energy metabolism

This study aims to provide new insight on the association between the development of wooden breast myopathy and mitochondrial and glycolytic activity under oxidative stress. Myopathic muscle had higher oxidative stress together with altered glycolytic metabolism and tricarboxylic acid (TCA) cycle. This was evidenced by significantly elevated antioxidant enzyme activities (catalase, superoxide dismutase, and glutathione peroxidase), decreased citrate synthase activity and postmortem glycolytic potential with increasing wooden breast severity. In addition, affected muscles also exhibited higher initial and ultimate pH values as well as reduced total glucose and lactate contents. Citrate synthase activity was negatively correlated to antioxidant enzyme activities. Taken together, we propose that the development of the wooden breast lesion is a chronic process that may be related to the failure of muscle fibers to defend against the excessively generated oxidative products promoted by mitochondrial damage accompanied by impaired TCA cycle. Furthermore, there was a positive correlation between citrate synthase activity and glycolytic potential, which suggests that the wooden breast condition is linked to the overall altered energy metabolism of the muscle, including the oxidative phosphorylation and glycolytic pathways.

Integrating Phylogenies with Chronology to Assemble the Tree of Life

Reconstructing the global Tree of Life necessitates computational approaches to integrate numerous molecular phylogenies with limited species overlap into a comprehensive supertree. Our survey of published literature shows that individual phylogenies are frequently restricted to specific taxonomic groups due to the expertise of investigators and molecular evolutionary considerations, resulting in any given species present in a minuscule fraction of phylogenies. We present a novel approach, called the chronological supertree algorithm (Chrono-STA), that can build a supertree of species from such data by using node ages in published molecular phylogenies scaled to time. Chrono-STA builds a supertree of organisms by integrating chronological data from molecular timetrees. It fundamentally differs from existing approaches that generate consensus phylogenies from gene trees with missing taxa, as Chrono-STA does not impute nodal distances, use a guide tree as a backbone, or reduce phylogenies to quartets. Analyses of simulated and empirical datasets show that Chrono-STA can combine taxonomically restricted timetrees with extremely limited species overlap. For such data, approaches that impute missing distances or assemble phylogenetic quartets did not perform well. We conclude that integrating phylogenies via temporal dimension enhances the accuracy of reconstructed supertrees that are also scaled to time.

Bioprospecting of soil-borne microorganisms and chemical dereplication of their anti-microbial constituents with the aid of UPLC-QTOF-MS and molecular networking approach

Due to the emergence of drug-resistant microorganisms, the search for broad-spectrum antimicrobial compounds has become extremely crucial. Natural sources like plants and soils have been explored for diverse metabolites with antimicrobial properties. This study aimed to identify microorganisms from agricultural soils exhibiting antimicrobial effects against known human pathogens, and to highlight the chemical space of the responsible compounds through the computational metabolomics-based bioprospecting approach. Herein, bacteria were extracted from soil samples and their antimicrobial potential was measured via the agar well diffusion method. Methanolic extracts from the active bacteria were analyzed using the liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) technique, and the subsequent data was further analyzed through molecular networking approach which aided in identification of potential anti-microbial compounds. Furthermore, 16S rRNA gene sequencing enabled identification of the active bacterial isolates, where isolate 1 and 2 were identified as strains of Bacillus pumilus, whilst isolate 3 was found to be Bacillus subtilis. Interestingly, isolate 3 (Bacillus subtilis) displayed wide-ranging antimicrobial activity against the tested human pathogens. Molecular networking revealed the presence of Diketopiperazine compounds such as cyclo (D-Pro-D-Leu), cyclo (L-Tyr-L-Pro), cyclo (L-Pro-D-Phe), and cyclo (L-Pro-L-Val), alongside Surfactin C, Surfactin B, Pumilacidin E, and Isarrin D in the Bacillus strains as the main anti-microbial compounds. The application of the molecular networking approach represents an innovation in the field of bio-guided bioprospection of microorganisms and has proved to be an effective and feasible towards unearthing potent antimicrobial compounds. Additionally, the (computational metabolomics-based) approach accelerates the discovery of bioactive compounds and isolation of strains which offer a promising avenue for discovering new clinical antimicrobials. Finally, soil microbial flora could serve an alternative source of anti-microbial compounds which can assist in the fight against emergence of multi-drug resistance bacterial pathogens.

Sex-biased gene expression precedes sexual dimorphism in the agonadal annelid Platynereis dumerilii

Gametogenesis is the process by which germ cells differentiate into mature sperm and oocytes, cells essential for sexual reproduction. The sex-specific molecular programs that drive spermatogenesis and oogenesis can also serve as sex identification markers. Platynereis dumerilii is a research organism that has been studied in many areas of developmental biology. However investigations often disregard sex, as P. dumerilii juveniles lack sexual dimorphism. The molecular mechanisms of gametogenesis in the segmented worm P. dumerilii are also largely unknown. In this study, we used RNA sequencing to investigate the transcriptomic profiles of gametogenesis in P. dumerilii juveniles. Our analysis revealed that sex-biased gene expression becomes increasingly pronounced during the advanced developmental stages, particularly during the meiotic phases of gametogenesis. We identified conserved genes associated with spermatogenesis, such as dmrt1, and a novel gene psmt, that is associated with oogenesis. Additionally, putative long non-coding RNAs were upregulated in both male and female gametogenic programs. This study provides a foundational resource for germ cell research in P. dumerilii, markers for sex identification, and offers comparative data to enhance our understanding of the evolution of gametogenesis mechanisms across species.

Expression of honey bee (Apis mellifera) sterol homeostasis genes in food jelly producing glands of workers

Adult workers of Western honey bees (Apis mellifera L.) acquire sterols from their pollen diet. These food sterols are transported by the hemolymph to peripheral tissues such as the mandibular and the hypopharyngeal glands in the worker bees' heads that secrete food jelly which is fed to developing larvae. As sterols are obligatory components of biological membranes and essential precursors for molting hormone synthesis in insects, they are indispensable to normal larval development. Thus, the study of sterol delivery to larvae is important for a full understanding of honey bee larval nutrition and development. Whereas hypopharyngeal glands only require sterols for their membrane integrity, mandibular glands add sterols, primarily 24-methylenecholesterol, to its secretion. For this, sterols must be transported through the glandular epithelial cells. We have analyzed for the first time in A. mellifera the expression of genes which are involved in intracellular movement of sterols. Mandibular and hypopharyngeal glands were dissected from newly emerged bees, 6-day-old nurse bees that feed larvae and 26-day-old forager bees. The expression of seven genes involved in intracellular sterol metabolism was measured with quantitative real-time PCR. Relative transcript abundance of sterol metabolism genes was significantly influenced by the age of workers and specific genes but not by gland type. Newly emerged bees had significantly more transcripts for six out of seven genes than older bees indicating that the bulk of the proteins needed for sterol metabolism are produced directly after emergence.

Cliffy: robust 16S rRNA classification based on a compressed LCA index

Taxonomic sequence classification is a computational problem central to the study of metagenomics and evolution. Advances in compressed indexing with the r -index enable full-text pattern matching against large sequence collections. But the data structures that link pattern sequences to their clades of origin still do not scale well to large collections. Previous work proposed the document array profiles, which use 𝒪 ( rd ) words of space where r is the number of maximal-equal letter runs in the Burrows-Wheeler transform and d is the number of distinct genomes. The linear dependence on d is limiting, since real taxonomies can easily contain 10,000s of leaves or more. We propose a method called cliff compression that reduces this size by a large factor, over 250x when indexing the SILVA 16S rRNA gene database. This method uses Θ( r log d ) words of space in expectation under a random model we propose here. We implemented these ideas in an open source tool called Cliffy that performs efficient taxonomic classification of sequencing reads with respect to a compressed taxonomic index. When applied to simulated 16S rRNA reads, Cliffy's read-level accuracy is higher than Kraken2's by 11-18%. Clade abundances are also more accurately predicted by Cliffy compared to Kraken2 and Bracken. Overall, Cliffy is a fast and space-economical extension to compressed full-text indexes, enabling them to perform fast and accurate taxonomic classification queries.

2012 ACM Subject Classification

Applied computing → Computational genomics.

Whole-genome resequencing reveals genetic diversity and adaptive evolution in Chinese honeybee (Apis cerana cerana) in Guizhou, China

Introduction: Guizhou Province, characterized by complex and diverse geographic and climatic environments, has rich genetic resources for the Chinese honeybee (Apis cerana cerana) and is one of the main bee-producing areas in China. However, research on the genetic diversity of Chinese honeybee in the Guizhou region is very limited, despite implications for conservation of biodiversity. Methods: In this study, we analyzed the genetic diversity, differentiation, and selection signals based on 116 Chinese honeybees from 12 regions in Guizhou Province using whole-genome sequencing. Results: We identified 1,400,430 high-quality SNPs across all samples. A population structure analysis revealed two independent genetic subgroups of Chinese honeybees in Guizhou, a Yunnan-Guizhou Plateau population in western Guizhou and a hilly-mountainous population in eastern Guizhou. The average nucleotide diversity (Pi) ranged from 0.00138 to 0.00161 and average expected heterozygosity (He) ranged from 0.2592 to 0.2604. The average genetic differentiation index (F ST) for Chinese honeybees in pairwise comparisons of 12 regions ranged from 0.0094 to 0.0293. There was clear genetic differentiation between the western plateau and the eastern hilly mountainous areas of Guizhou; however, F ST values between the eastern and western populations ranged from 0.0170 to 0.0293, indicating a low degree of differentiation. A genome-wide scan revealed a number of genes under selection in the Yunnan-Guizhou Plateau environment. These genes were related to growth and development, reproduction, and cold resistance, and several candidate genes involved in environmental adaptation were identified, including CTR, MAPK, MAST, HSF, and MKKK. Discussion: The results of the present study provide important theoretical bases for the conservation, evaluation, development, and utilization of genetic resources for Chinese honeybees in the Guizhou region and for further investigations of environmental adaptation and underlying mechanisms in the species.

Super-enhancer interactomes from single cells link clustering and transcription

Regulation of gene expression hinges on the interplay between enhancers and promoters, traditionally explored through pairwise analyses. Recent advancements in mapping genome folding, like GAM, SPRITE, and multi-contact Hi-C, have uncovered multi-way interactions among super-enhancers (SEs), spanning megabases, yet have not measured their frequency in single cells or the relationship between clustering and transcription. To close this gap, here we used multiplexed imaging to map the 3D positions of 376 SEs across thousands of mammalian nuclei. Notably, our single-cell images reveal that while SE-SE contacts are rare, SEs often form looser associations we termed "communities". These communities, averaging 4-5 SEs, assemble cooperatively under the combined effects of genomic tethers, Pol2 clustering, and nuclear compartmentalization. Larger communities are associated with more frequent and larger transcriptional bursts. Our work provides insights about the SE interactome in single cells that challenge existing hypotheses on SE clustering in the context of transcriptional regulation.

Serial founder effects slow range expansion in an invasive social insect

Invasive populations often experience founder effects: a loss of genetic diversity relative to the source population, due to a small number of founders. Even where these founder effects do not impact colonization success, theory predicts they might affect the rate at which invasive populations expand. This is because secondary founder effects are generated at advancing population edges, further reducing local genetic diversity and elevating genetic load. We show that in an expanding invasive population of the Asian honey bee (Apis cerana), genetic diversity is indeed lowest at range edges, including at the complementary sex determiner, csd, a locus that is homozygous-lethal. Consistent with lower local csd diversity, range edge colonies had lower brood viability than colonies in the range centre. Further, simulations of a newly-founded and expanding honey bee population corroborate the spatial patterns in mean colony fitness observed in our empirical data and show that such genetic load at range edges will slow the rate of population expansion.

Genetic insights into agronomic and morphological traits of drug-type cannabis revealed by genome-wide association studies

Cannabis sativa L., previously concealed by prohibition, is now a versatile and promising plant, thanks to recent legalization, opening doors for medical research and industry growth. However, years of prohibition have left the Cannabis research community lagging behind in understanding Cannabis genetics and trait inheritance compared to other major crops. To address this gap, we conducted a comprehensive genome-wide association study (GWAS) of nine key agronomic and morphological traits, using a panel of 176 drug-type Cannabis accessions from the Canadian legal market. Utilizing high-density genotyping-by-sequencing (HD-GBS), we successfully generated dense genotyping data in Cannabis, resulting in a catalog of 800 K genetic variants, of which 282 K common variants were retained for GWAS analysis. Through GWAS analysis, we identified 18 markers significantly associated with agronomic and morphological traits. Several identified markers exert a substantial phenotypic impact, guided us to putative candidate genes that reside in high linkage-disequilibrium (LD) with the markers. These findings lay a solid foundation for an innovative cannabis research, leveraging genetic markers to inform breeding programs aimed at meeting diverse needs in the industry.

Intersection of coral molecular responses to a localized mortality event and ex situ deoxygenation

In July 2016, East Bank of Flower Garden Banks (FGB) National Marine Sanctuary experienced a localized mortality event (LME) of multiple invertebrate species that ultimately led to reductions in coral cover. Abiotic data taken directly after the event suggested that acute deoxygenation contributed to the mortality. Despite the large impact of this event on the coral community, there was no direct evidence that this LME was driven by acute deoxygenation, and thus we explored whether gene expression responses of corals to the LME would indicate what abiotic factors may have contributed to the LME. Gene expression of affected and unaffected corals sampled during the mortality event revealed evidence of the physiological consequences of the LME on coral hosts and their algal symbionts from two congeneric species (Orbicella franksi and Orbicella faveolata). Affected colonies of both species differentially regulated genes involved in mitochondrial regulation and oxidative stress. To further test the hypothesis that deoxygenation led to the LME, we measured coral host and algal symbiont gene expression in response to ex situ experimental deoxygenation (control = 6.9 ± 0.08 mg L-1, anoxic = 0.083 ± 0.017 mg L-1) in healthy O. faveolata colonies from the FGB. However, this deoxygenation experiment revealed divergent gene expression patterns compared to the corals sampled during the LME and was more similar to a generalized coral environmental stress response. It is therefore likely that while the LME was connected to low oxygen, it was a series of interconnected stressors that elicited the unique gene expression responses observed here. These in situ and ex situ data highlight how field responses to stressors are unique from those in controlled laboratory conditions, and that the complexities of deoxygenation events in the field likely arise from interactions between multiple environmental factors simultaneously.

Odorant Receptors Expressing and Antennal Lobes Architecture Are Linked to Caste Dimorphism in Asian Honeybee, Apis cerana (Hymenoptera: Apidae)

Insects heavily rely on the olfactory system for food, mating, and predator evasion. However, the caste-related olfactory differences in Apis cerana, a eusocial insect, remain unclear. To explore the peripheral and primary center of the olfactory system link to the caste dimorphism in A. cerana, transcriptome and immunohistochemistry studies on the odorant receptors (ORs) and architecture of antennal lobes (ALs) were performed on different castes. Through transcriptomesis, we found more olfactory receptor genes in queens and workers than in drones, which were further validated by RT-qPCR, indicating caste dimorphism. Meanwhile, ALs structure, including volume, surface area, and the number of glomeruli, demonstrated a close association with caste dimorphism. Particularly, drones had more macroglomeruli possibly for pheromone recognition. Interestingly, we found that the number of ORs and glomeruli ratio was nearly 1:1. Also, the ORs expression distribution pattern was very similar to the distribution of glomeruli volume. Our results suggest the existence of concurrent plasticity in both the peripheral olfactory system and ALs among different castes of A. cerana, highlighting the role of the olfactory system in labor division in insects.

Post-invasion selection acts on standing genetic variation despite a severe founding bottleneck

Invasive populations often have lower genetic diversity relative to the native-range populations from which they derive.1,2 Despite this, many biological invaders succeed in their new environments, in part due to rapid adaptation.3,4,5,6 Therefore, the role of genetic bottlenecks in constraining the adaptation of invaders is debated.7,8,9,10 Here, we use whole-genome resequencing of samples from a 10-year time-series dataset, representing the natural invasion of the Asian honey bee (Apis cerana) in Australia, to investigate natural selection occurring in the aftermath of a founding event. We find that Australia's A. cerana population was founded by as few as one colony, whose arrival was followed by a period of rapid population expansion associated with an increase of rare variants.11 The bottleneck resulted in a steep loss of overall genetic diversity, yet we nevertheless detected loci with signatures of positive selection during the first years post-invasion. When we investigated the origin of alleles under selection, we found that selection acted primarily on the variation introduced by founders and not on the variants that arose post-invasion by mutation. In all, our data highlight that selection on standing genetic variation can occur in the early years post-invasion, even where founding bottlenecks are severe.

The genome of the blind bee louse fly reveals deep convergences with its social host and illuminates Drosophila origins

Social insects' nests harbor intruders known as inquilines,1 which are usually related to their hosts.2,3 However, distant non-social inquilines may also show convergences with their hosts,4,5 although the underlying genomic changes remain unclear. We analyzed the genome of the wingless and blind bee louse fly Braula coeca, an inquiline kleptoparasite of the western honey bee, Apis mellifera.6,7 Using large phylogenomic data, we confirmed recent accounts that the bee louse fly is a drosophilid8,9 and showed that it had likely evolved from a sap-breeder ancestor associated with honeydew and scale insects' wax. Unlike many parasites, the bee louse fly genome did not show significant erosion or strict reliance on an endosymbiont, likely due to a relatively recent age of inquilinism. However, we observed a horizontal transfer of a transposon and a striking parallel evolution in a set of gene families between the honey bee and the bee louse fly. Convergences included genes potentially involved in metabolism and immunity and the loss of nearly all bitter-tasting gustatory receptors, in agreement with life in a protective nest and a diet of honey, pollen, and beeswax. Vision and odorant receptor genes also exhibited rapid losses. Only genes whose orthologs in the closely related Drosophila melanogaster respond to honey bee pheromone components or floral aroma were retained, whereas the losses included orthologous receptors responsive to the anti-ovarian honey bee queen pheromones. Hence, deep genomic convergences can underlie major phenotypic transitions during the evolution of inquilinism between non-social parasites and their social hosts.

A Spatial Multi-Modal Dissection of Host-Microbiome Interactions within the Colitis Tissue Microenvironment

The intricate and dynamic interactions between the host immune system and its microbiome constituents undergo dynamic shifts in response to perturbations to the intestinal tissue environment. Our ability to study these events on the systems level is significantly limited by in situ approaches capable of generating simultaneous insights from both host and microbial communities. Here, we introduce Microbiome Cartography (MicroCart), a framework for simultaneous in situ probing of host features and its microbiome across multiple spatial modalities. We demonstrate MicroCart by comprehensively investigating the alterations in both gut host and microbiome components in a murine model of colitis by coupling MicroCart with spatial proteomics, transcriptomics, and glycomics platforms. Our findings reveal a global but systematic transformation in tissue immune responses, encompassing tissue-level remodeling in response to host immune and epithelial cell state perturbations, and bacterial population shifts, localized inflammatory responses, and metabolic process alterations during colitis. MicroCart enables a deep investigation of the intricate interplay between the host tissue and its microbiome with spatial multiomics.

Toxic effects of the heavy metal Cd on Apis cerana cerana (Hymenoptera: Apidae): Oxidative stress, immune disorders and disturbance of gut microbiota

Cadmium (Cd) is a toxic non-essential metal element that can enter the honey bee body through air, water and soil. Currently, there is a lack of sufficient research on the effects of Cd on A. cerana cerana, especially the potential risks of long-term exposure to sublethal concentrations. In order to ascertain the toxicological effects of the heavy metal Cd on bees, we performed laboratory-based toxicity experiments on worker bees and conducted analyses from three distinctive facets: antioxidative, immunological, and gut microbiota. The results showed that exposure of bees to high concentrations of Cd resulted in acute mortality, and the increase in mortality was concentration dependent. In long-term exposure to sublethal concentrations, Cd reduced the number of transcripts of antioxidant genes (AccSOD1, AccTPx3 and AccTPx4) and superoxide dismutase activity, causing an increase in malondialdehyde content. Simultaneously, the transcription of immune-related genes (AccAbaecin and AccApidaecin) and acetylcholinesterase activities was inhibited. Furthermore, Cd changes the structural characteristics of bacterial and fungal communities in the gut, disrupting the balance of microbial communities. In conclusion, the health and survival of honey bees are affected by Cd. This study provides a scientific basis for investigating the toxicological mechanisms and control strategies of the heavy metal Cd on honey bees, while facilitating a better understanding and protection of these valuable honey bees.

Data-driven detection of age-related arbitrary monotonic changes in single-cell gene expression distributions

Identification of genes whose expression increases or decreases with age is central to understanding the mechanisms behind aging. Recent scRNA-seq studies have shown that changes in single-cell expression profiles with aging are complex and diverse. In this study, we introduce a novel workflow to detect changes in the distribution of arbitrary monotonic age-related changes in single-cell expression profiles. Since single-cell gene expression profiles can be analyzed as probability distributions, our approach uses information theory to quantify the differences between distributions and employs distance matrices for association analysis. We tested this technique on simulated data and confirmed that potential parameter changes could be detected in a set of probability distributions. Application of the technique to a public scRNA-seq dataset demonstrated its potential utility as a straightforward screening method for identifying aging-related cellular features.

The evolution and functional divergence of 10 Apolipoprotein D-like genes in Nilaparvata lugens

Apolipoprotein D (ApoD), a member of the lipocalin superfamily of proteins, is involved in lipid transport and stress resistance. Whereas only a single copy of the ApoD gene is found in humans and some other vertebrates, there are typically several ApoD-like genes in insects. To date, there have been relatively few studies that have examined the evolution and functional differentiation of ApoD-like genes in insects, particularly hemi-metabolous insects. In this study, we identified 10 ApoD-like genes (NlApoD1-10) with distinct spatiotemporal expression patterns in Nilaparvata lugens (BPH), which is an important pest of rice. NlApoD1-10 were found to be distributed on 3 chromosomes in a tandem array of NlApoD1/2, NlApoD3-5, and NlApoD7/8, and show sequence and gene structural divergence in the coding regions, indicating that multiple gene duplication events occurred during evolution. Phylogenetic analysis revealed that NlApoD1-10 can be clustered into 5 clades, with NlApoD3-5 and NlApoD7/8 potentially evolving exclusively in the Delphacidae family. Functional screening using an RNA interference approach revealed that only NlApoD2 was essential for BPH development and survival, whereas NlApoD4/5 are highly expressed in testes, and might play roles in reproduction. Moreover, stress response analysis revealed that NlApoD3-5/9, NlApoD3-5, and NlApoD9 were up-regulated after treatment with lipopolysaccharide, H2 O2 , and ultraviolet-C, respectively, indicating their potential roles in stress resistance.

Gut Microbiota of Apis mellifera at Selected Ontogenetic Stages and Their Immunogenic Potential during Summer

Honeybees (Apis mellifera) are pollinating agents of economic importance. The role of the gut microbiome in honeybee health has become increasingly evident due to its relationship with immune function, growth, and development. Although their dynamics at various developmental stages have been documented, their dynamics during the era of colony collapse disorder and immunogenic potential, which are connected to the antagonistic immune response against pathogens, need to be elucidated. Using 16S rRNA gene Illumina sequencing, the results indicated changes in the gut microbiota with the developmental stage. The bacterial diversity of fifth stage larva was significantly different among the other age groups, in which Fructobacillus, Escherichia-Shigella, Bombella, and Tyzzerella were unique bacteria. In addition, the diversity of the worker bee microbiome was distinct from that of the younger microbiome. Lactobacillus and Gilliamella remained conserved throughout the developmental stages, while Bifidobacterium colonized only worker bees. Using an in silico approach, the production potential of lipopolysaccharide-endotoxin was predicted. Forager bees tend to have a higher abundance rate of Gram-negative bacteria. Our results revealed the evolutionary importance of some microbiome from the larval stage to the adult stage, providing insight into the potential dynamics of disease response and susceptibility. This finding provides a theoretical foundation for furthering the understanding of the function of the gut microbiota at various developmental stages related to probiotic development and immunogenic potential.

Modeling the neuroimmune system in Alzheimer's and Parkinson's diseases

Parkinson's disease (PD) and Alzheimer's disease (AD) are neurodegenerative disorders caused by the interaction of genetic, environmental, and familial factors. These diseases have distinct pathologies and symptoms that are linked to specific cell populations in the brain. Notably, the immune system has been implicated in both diseases, with a particular focus on the dysfunction of microglia, the brain's resident immune cells, contributing to neuronal loss and exacerbating symptoms. Researchers use models of the neuroimmune system to gain a deeper understanding of the physiological and biological aspects of these neurodegenerative diseases and how they progress. Several in vitro and in vivo models, including 2D cultures and animal models, have been utilized. Recently, advancements have been made in optimizing these existing models and developing 3D models and organ-on-a-chip systems, holding tremendous promise in accurately mimicking the intricate intracellular environment. As a result, these models represent a crucial breakthrough in the transformation of current treatments for PD and AD by offering potential for conducting long-term disease-based modeling for therapeutic testing, reducing reliance on animal models, and significantly improving cell viability compared to conventional 2D models. The application of 3D and organ-on-a-chip models in neurodegenerative disease research marks a prosperous step forward, providing a more realistic representation of the complex interactions within the neuroimmune system. Ultimately, these refined models of the neuroimmune system aim to aid in the quest to combat and mitigate the impact of debilitating neuroimmune diseases on patients and their families.

A reference genome of Commelinales provides insights into the commelinids evolution and global spread of water hyacinth (Pontederia crassipes)

Commelinales belongs to the commelinids clade, which also comprises Poales that includes the most important monocot species, such as rice, wheat, and maize. No reference genome of Commelinales is currently available. Water hyacinth (Pontederia crassipes or Eichhornia crassipes), a member of Commelinales, is one of the devastating aquatic weeds, although it is also grown as an ornamental and medical plant. Here, we present a chromosome-scale reference genome of the tetraploid water hyacinth with a total length of 1.22 Gb (over 95% of the estimated size) across 8 pseudochromosome pairs. With the representative genomes, we reconstructed a phylogeny of the commelinids, which supported Zingiberales and Commelinales being sister lineages of Arecales and shed lights on the controversial relationship of the orders. We also reconstructed ancestral karyotypes of the commelinids clade and confirmed the ancient commelinids genome having 8 chromosomes but not 5 as previously reported. Gene family analysis revealed contraction of disease-resistance genes during polyploidization of water hyacinth, likely a result of fitness requirement for its role as a weed. Genetic diversity analysis using 9 water hyacinth lines from 3 continents (South America, Asia, and Europe) revealed very closely related nuclear genomes and almost identical chloroplast genomes of the materials, as well as provided clues about the global dispersal of water hyacinth. The genomic resources of P. crassipes reported here contribute a crucial missing link of the commelinids species and offer novel insights into their phylogeny.

ToxCodAn-Genome: an automated pipeline for toxin-gene annotation in genome assembly of venomous lineages

BACKGROUND

The rapid development of sequencing technologies resulted in a wide expansion of genomics studies using venomous lineages. This facilitated research focusing on understanding the evolution of adaptive traits and the search for novel compounds that can be applied in agriculture and medicine. However, the toxin annotation of genomes is a laborious and time-consuming task, and no consensus pipeline is currently available. No computational tool currently exists to address the challenges specific to toxin annotation and to ensure the reproducibility of the process.

RESULTS

Here, we present ToxCodAn-Genome, the first software designed to perform automated toxin annotation in genomes of venomous lineages. This pipeline was designed to retrieve the full-length coding sequences of toxins and to allow the detection of novel truncated paralogs and pseudogenes. We tested ToxCodAn-Genome using 12 genomes of venomous lineages and achieved high performance on recovering their current toxin annotations. This tool can be easily customized to allow improvements in the final toxin annotation set and can be expanded to virtually any venomous lineage. ToxCodAn-Genome is fast, allowing it to run on any personal computer, but it can also be executed in multicore mode, taking advantage of large high-performance servers. In addition, we provide a guide to direct future research in the venomics field to ensure a confident toxin annotation in the genome being studied. As a case study, we sequenced and annotated the toxin repertoire of Bothrops alternatus, which may facilitate future evolutionary and biomedical studies using vipers as models.

CONCLUSIONS

ToxCodAn-Genome is suitable to perform toxin annotation in the genome of venomous species and may help to improve the reproducibility of further studies. ToxCodAn-Genome and the guide are freely available at https://github.com/pedronachtigall/ToxCodAn-Genome.

Isolation, Quantification, and Visualization of Extracellular Membrane Vesicles in Rhizobia Under Free-Living Conditions

Rhizobia are a group of soil proteobacteria that are able to establish a symbiotic interaction with legumes. These bacteria are capable to fix atmospheric nitrogen into ammonia within specific plant root organs called nodules. The rhizobia-legume interaction is established by a complex molecular dialogue that starts with flavonoids exudated by the plant roots. In response, signaling molecules known as Nod factors (NFs) are secreted by the bacteria. These factors are sensed by specific plant receptors that trigger a downstream signaling cascade leading to rhizobium-specific intracellular colonization of the root hair via the formation of infection threads and the eventual development of nodules on roots. In these organs, rhizobia can fix nitrogen from the atmosphere for the plant in exchange for photosynthates and the appropriate environment for nitrogen fixation. Recently, it has been demonstrated that extracellular membrane vesicles (EMVs) produced by some rhizobia carry NFs. EMVs are proteolipidic structures that are secreted to the milieu from the bacterial membranes and are involved in several important biological processes, including intercellular communication. Thus far, little is known about rhizobia vesicles, and further studies are needed to understand their functions, including their role as transporting vessels of signaling molecules during the process of symbiosis. Here, we present a detailed protocol to isolate high-purity EMVs from free-living cultured rhizobia, test their integrity, and quantify their abundance.

Promoters and Synthetic Promoters in Trichoderma reesei

Trichoderma reesei holds immense promise for large-scale protein production, rendering it an excellent subject for deeper exploration using genetic engineering methods to achieve a comprehensive grasp of its cellular physiology. Understanding the genetic factors governing its intrinsic regulatory network is crucial, as lacking this knowledge could impede the expression of target genes. Prior and ongoing studies have concentrated on advancing new expression systems grounded in synthetic biology principles. These methodologies involve utilizing established potent promoters or engineered variations. Genomic and transcriptomic analyses have played a pivotal role in identifying robust promoters and expression systems, including light-responsive, copper-inducible, L-methionine-inducible, and Tet-On systems, among others. This chapter seeks to highlight various research endeavors focusing on tunable and constitutive promoters, the impact of different promoters on both native and foreign protein expression, the discovery of fresh promoters, and strategies conducive to future research aimed at refining and enhancing protein expression in T. reesei. Characterizing new promoters and adopting innovative expression systems hold the potential to significantly expand the molecular toolkit accessible for genetically engineering T. reesei strains. For instance, modifying potent inducible promoters such as Pcbh1 by replacing transcriptional repressors (cre1, ace1) with activators (xyr1, ace2, ace3, hap2/3/5) and integrating synthetic expression systems can result in increased production of crucial enzymes such as endoglucanases (EGLs), β-glucosidases (BGLs), and cellobiohydrolases (CBHs). Similarly, robust constitutive promoters such as Pcdna1 can be converted into synthetic hybrid promoters by incorporating activation elements from potent inducible promoters, facilitating cellulase induction and expression even under repressive conditions. Nevertheless, further efforts are necessary to uncover innovative promoters and devise novel expression strategies to enhance the production of desired proteins on an industrial scale.

Sc-TUSV-ext: Single-cell clonal lineage inference from single nucleotide variants (SNV), copy number alterations (CNA) and structural variants (SV)

Clonal lineage inference ("tumor phylogenetics") has become a crucial tool for making sense of somatic evolution processes that underlie cancer development and are increasingly recognized as part of normal tissue growth and aging. The inference of clonal lineage trees from single cell sequence data offers particular promise for revealing processes of somatic evolution in unprecedented detail. However, most such tools are based on fairly restrictive models of the types of mutation events observed in somatic evolution and of the processes by which they develop. The present work seeks to enhance the power and versatility of tools for single-cell lineage reconstruction by making more comprehensive use of the range of molecular variant types by which tumors evolve. We introduce Sc-TUSV-ext, an integer linear programming (ILP) based tumor phylogeny reconstruction method that, for the first time, integrates single nucleotide variants (SNV), copy number alterations (CNA) and structural variations (SV) into clonal lineage reconstruction from single-cell DNA sequencing data. We show on synthetic data that accounting for these variant types collectively leads to improved accuracy in clonal lineage reconstruction relative to prior methods that consider only subsets of the variant types. We further demonstrate the effectiveness on real data in resolving clonal evolution in the presence of multiple variant types, providing a path towards more comprehensive insight into how various forms of somatic mutability collectively shape tissue development.

Potential use of iPSCs for disease modeling, drug screening, and cell-based therapy for Alzheimer's disease

Alzheimer's disease (AD) is a chronic illness marked by increasing cognitive decline and nervous system deterioration. At this time, there is no known medication that will stop the course of Alzheimer's disease; instead, most symptoms are treated. Clinical trial failure rates for new drugs remain high, highlighting the urgent need for improved AD modeling for improving understanding of the underlying pathophysiology of disease and improving drug development. The development of induced pluripotent stem cells (iPSCs) has made it possible to model neurological diseases like AD, giving access to an infinite number of patient-derived cells capable of differentiating neuronal fates. This advance will accelerate Alzheimer's disease research and provide an opportunity to create more accurate patient-specific models of Alzheimer's disease to support pathophysiological research, drug development, and the potential application of stem cell-based therapeutics. This review article provides a complete summary of research done to date on the potential use of iPSCs from AD patients for disease modeling, drug discovery, and cell-based therapeutics. Current technological developments in AD research including 3D modeling, genome editing, gene therapy for AD, and research on familial (FAD) and sporadic (SAD) forms of the disease are discussed. Finally, we outline the issues that need to be elucidated and future directions for iPSC modeling in AD.

Influence of social lifestyles on host-microbe symbioses in the bees

Microbiomes are increasingly recognised as critical for the health of an organism. In eusocial insect societies, frequent social interactions allow for high-fidelity transmission of microbes across generations, leading to closer host-microbe coevolution. The microbial communities of bees with other social lifestyles are less studied, and few comparisons have been made between taxa that vary in social structure. To address this gap, we leveraged a cloud-computing resource and publicly available transcriptomic data to conduct a survey of microbial diversity in bee samples from a variety of social lifestyles and taxa. We consistently recover the core microbes of well-studied corbiculate bees, supporting this method's ability to accurately characterise microbial communities. We find that the bacterial communities of bees are influenced by host location, phylogeny and social lifestyle, although no clear effect was found for fungal or viral microbial communities. Bee genera with more complex societies tend to harbour more diverse microbes, with Wolbachia detected more commonly in solitary tribes. We present a description of the microbiota of Euglossine bees and find that they do not share the "corbiculate core" microbiome. Notably, we find that bacteria with known anti-pathogenic properties are present across social bee genera, suggesting that symbioses that enhance host immunity are important with higher sociality. Our approach provides an inexpensive means of exploring microbiomes of a given taxa and identifying avenues for further research. These findings contribute to our understanding of the relationships between bees and their associated microbial communities, highlighting the importance of considering microbiome dynamics in investigations of bee health.

Whole-genome SNP markers reveal runs of homozygosity in indigenous cattle breeds of Pakistan

The runs of homozygosity (ROH) were identified in 14 Pakistani cattle breeds (n = 105) by genotyping with the Illumina 50 K SNP BeadChip. These breeds were categorized into Dairy, Dual, and Draft breeds based on their utility and production performance. We identified a total of 10,936 ROHs which mainly consisted of a high number of shorter segments (1-4 Mb). Dairy group exhibited the highest level of inbreeding (FROH: 0.078 ± 0.028) while the lowest (FROH: 0.002 ± 0.008) was observed in Dual group. In 48 genomic regions identified with a high frequency of ROH, 207 genes were detected in the three breed groups. A substantially higher number of ROH islands detected in dairy breeds indicated the impact of the positive selection pressure over the years. Important candidate genes and QTL were detected in the ROH islands associated with economic traits like milk production, reproduction, meat, carcass, and health traits in dairy cattle.

No impact of hygienic behavior and viral coinfection on the development of European foulbrood in honey bee (Apis mellifera) colonies during blueberry pollination in Michigan

European foulbrood (EFB) is a severe disease of honey bee (Apis mellifera) larvae caused by the bacterium Linnaeus [Hymenoptera: Apidae]) Melissococcus plutonius (ex White) Bailey and Collins (Lactobacillales: Enterococcaceae). Many beekeepers in North America report severe EFB following blueberry pollination, but it is not clear what factors during pollination are related to clinical disease. Additionally, the impact that other factors such as viral load and hygienic behavior have on EFB has not been studied. In Spring of 2020 we enrolled 60 commercial honey bee colonies in a prospective cohort study. Colonies were inspected 3 times over the season with hive metrics and samples taken for viral testing. Each colony was tested for hygienic behavior twice and the score was averaged. Viral loads were determined by qPCR for deformed wing virus (DWV) A and B. We found no statistical difference in the EFB prevalence or severity between the 2 yards at any timepoint; 50% (n = 16) of the colonies in the holding yard and 63% (n = 17) in blueberry developed moderate to severe EFB over the study period. When colonies from both yards were pooled, we found no relationship between viral load or hygienic behavior and development of EFB. These results suggest that other factors may be responsible for driving EFB virulence and hygienic behavior is not likely helpful in managing this disease.

Prevalent bee venom genes evolved before the aculeate stinger and eusociality

BACKGROUND

Venoms, which have evolved numerous times in animals, are ideal models of convergent trait evolution. However, detailed genomic studies of toxin-encoding genes exist for only a few animal groups. The hyper-diverse hymenopteran insects are the most speciose venomous clade, but investigation of the origin of their venom genes has been largely neglected.

RESULTS

Utilizing a combination of genomic and proteo-transcriptomic data, we investigated the origin of 11 toxin genes in 29 published and 3 new hymenopteran genomes and compiled an up-to-date list of prevalent bee venom proteins. Observed patterns indicate that bee venom genes predominantly originate through single gene co-option with gene duplication contributing to subsequent diversification.

CONCLUSIONS

Most Hymenoptera venom genes are shared by all members of the clade and only melittin and the new venom protein family anthophilin1 appear unique to the bee lineage. Most venom proteins thus predate the mega-radiation of hymenopterans and the evolution of the aculeate stinger.

AlexandrusPS: A User-Friendly Pipeline for the Automated Detection of Orthologous Gene Clusters and Subsequent Positive Selection Analysis

The detection of adaptive selection in a system approach considering all protein-coding genes allows for the identification of mechanisms and pathways that enabled adaptation to different environments. Currently, available programs for the estimation of positive selection signals can be divided into two groups. They are either easy to apply but can analyze only one gene family at a time, restricting system analysis; or they can handle larger cohorts of gene families, but require considerable prerequisite data such as orthology associations, codon alignments, phylogenetic trees, and proper configuration files. All these steps require extensive computational expertise, restricting this endeavor to specialists. Here, we introduce AlexandrusPS, a high-throughput pipeline that overcomes technical challenges when conducting transcriptome-wide positive selection analyses on large sets of nucleotide and protein sequences. The pipeline streamlines 1) the execution of an accurate orthology prediction as a precondition for positive selection analysis, 2) preparing and organizing configuration files for CodeML, 3) performing positive selection analysis using CodeML, and 4) generating an output that is easy to interpret, including all maximum likelihood and log-likelihood test results. The only input needed from the user is the CDS and peptide FASTA files of proteins of interest. The pipeline is provided in a Docker image, requiring no program or module installation, enabling the application of the pipeline in any computing environment. AlexandrusPS and its documentation are available via GitHub (https://github.com/alejocn5/AlexandrusPS).

Omics analyses of Rehmannia glutinosa dedifferentiated and cambial meristematic cells reveal mechanisms of catalpol and indole alkaloid biosynthesis

BACKGROUND

Rehmannia glutinosa is a rich source of terpenoids with a high medicinal reputation. The present study compared dedifferentiated cells (DDCs) and cambial meristematic cells (CMCs) cell cultures of R. glutinosa for terpenoid (catalpol) and indole alkaloid (IA) biosynthesis. In this regard, we used widely targeted metabolomics and transcriptome sequencing approaches together with the comparison of cell morphology, cell death (%), and catalpol production at different time points.

RESULTS

We were able to identify CMCs based on their morphology and hypersensitivity to zeocin. CMCs showed higher dry weight content and better catalpol production compared to DDCs. The metabolome analysis revealed higher concentrations of IA, terpenoids, and catalpol in CMCs compared to DDCs. The transcriptome sequencing analysis showed that a total of 27,201 genes enriched in 139 pathways were differentially expressed. The higher catalpol concentration in CMCs is related to the expression changes in genes involved in acetyl-CoA and geranyl-PP biosynthesis, which are precursors for monoterpenoid biosynthesis. Moreover, the expressions of the four primary genes involved in monoterpenoid biosynthesis (NMD, CYP76A26, UGT6, and CYP76F14), along with a squalene monooxygenase, exhibit a strong association with the distinct catalpol biosynthesis. Contrarily, expression changes in AADC, STR, and RBG genes were consistent with the IA biosynthesis. Finally, we discussed the phytohormone signaling and transcription factors in relation to observed changes in metabolome.

CONCLUSIONS

Overall, our study provides novel data for improving the catalpol and IA biosynthesis in R. glutinosa.

Light signaling as cellular integrator of multiple environmental cues in plants

Plants being sessile need to rapidly adapt to the constantly changing environment through modifications in their internal clock, metabolism, and gene expression. They have evolved an intricate system to perceive and transfer the signals from the primary environmental factors namely light, temperature and water to regulate their growth development and survival. Over past few decades rigorous research using molecular genetics approaches, especially in model plant Arabidopsis, has resulted in substantial progress in discovering various photoreceptor systems and light signaling components. In parallel several molecular pathways operating in response to other environmental cues have also been elucidated. Interestingly, the studies have shown that expression profiles of genes involved in photomorphogenesis can undergo modulation in response to other cues from the environment. Recently, the photoreceptor, PHYB, has been shown to function as a thermosensor. Downstream components of light signaling pathway like COP1 and PIF have also emerged as integrating hubs for various kinds of signals. All these findings indicate that light signaling components may act as central integrator of various environmental cues to regulate plant growth and development processes. In this review, we present a perspective on cross talk of signaling mechanisms induced in response to myriad array of signals and their integration with the light signaling components. By putting light signals on the central stage, we propose the possibilities of enhancing plant resilience to the changing environment by fine-tuning the genetic manipulation of its signaling components in the future.

Genetic differentiation and local adaptation of the Japanese honeybee, Apis cerana japonica

We examine the population genetic structure and divergence among the regional populations of the Japanese honeybee, Apis cerana japonica, by re-sequencing the genomes of 105 individuals from the three main Japanese islands with diverse climates. The genetic structure results indicated that these individuals are distinct from the mainland Chinese A. cerana samples. Furthermore, population structure analyses have identified three genetically distinct geographic regions in Japan: Northern (Tohoku-Kanto-Chubu districts), Central (Chugoku district), and Southern (Kyushu district). In some districts, "possible non-native" individuals, likely introduced from other regions in recent years, were discovered. Then, genome-wide scans were conducted to detect candidate genes for adaptation by two different approaches. We performed a population branch statistics (PBS) analysis to identify candidate genes for population-specific divergence. A latent factor mixed model (LFMM) was used to identify genes associated with climatic variables along a geographic gradient. The PBSmax analysis identified 25 candidate genes for population-specific divergence whereas the LFMM analysis identified 73 candidate genes for adaptation to climatic variables along a geographic gradient. However, no common genes were identified by both methods.

Evolution of five environmentally responsive gene families in a pine-feeding sawfly, Neodiprion lecontei (Hymenoptera: Diprionidae)

A central goal in evolutionary biology is to determine the predictability of adaptive genetic changes. Despite many documented cases of convergent evolution at individual loci, little is known about the repeatability of gene family expansions and contractions. To address this void, we examined gene family evolution in the redheaded pine sawfly Neodiprion lecontei, a noneusocial hymenopteran and exemplar of a pine-specialized lineage evolved from angiosperm-feeding ancestors. After assembling and annotating a draft genome, we manually annotated multiple gene families with chemosensory, detoxification, or immunity functions before characterizing their genomic distributions and molecular evolution. We find evidence of recent expansions of bitter gustatory receptor, clan 3 cytochrome P450, olfactory receptor, and antimicrobial peptide subfamilies, with strong evidence of positive selection among paralogs in a clade of gustatory receptors possibly involved in the detection of bitter compounds. In contrast, these gene families had little evidence of recent contraction via pseudogenization. Overall, our results are consistent with the hypothesis that in response to novel selection pressures, gene families that mediate ecological interactions may expand and contract predictably. Testing this hypothesis will require the comparative analysis of high-quality annotation data from phylogenetically and ecologically diverse insect species and functionally diverse gene families. To this end, increasing sampling in under-sampled hymenopteran lineages and environmentally responsive gene families and standardizing manual annotation methods should be prioritized.

Empirical comparison and analysis of machine learning-based approaches for druggable protein identification

Efficiently and precisely identifying drug targets is crucial for developing and discovering potential medications. While conventional experimental approaches can accurately pinpoint these targets, they suffer from time constraints and are not easily adaptable to high-throughput processes. On the other hand, computational approaches, particularly those utilizing machine learning (ML), offer an efficient means to accelerate the prediction of druggable proteins based solely on their primary sequences. Recently, several state-of-the-art computational methods have been developed for predicting and analyzing druggable proteins. These computational methods showed high diversity in terms of benchmark datasets, feature extraction schemes, ML algorithms, evaluation strategies and webserver/software usability. Thus, our objective is to reexamine these computational approaches and conduct a comprehensive assessment of their strengths and weaknesses across multiple aspects. In this study, we deliver the first comprehensive survey regarding the state-of-the-art computational approaches for in silico prediction of druggable proteins. First, we provided information regarding the existing benchmark datasets and the types of ML methods employed. Second, we investigated the effectiveness of these computational methods in druggable protein identification for each benchmark dataset. Third, we summarized the important features used in this field and the existing webserver/software. Finally, we addressed the present constraints of the existing methods and offer valuable guidance to the scientific community in designing and developing novel prediction models. We anticipate that this comprehensive review will provide crucial information for the development of more accurate and efficient druggable protein predictors.

Common as well as unique methylation-sensitive DNA regulatory elements in three mammalian SLC9C1 genes

The SLC9C1 gene (which encodes the NHE10 protein) is essential for male fertility in both mice and humans, however the epigenetic mechanisms regulating its testis/sperm-specific gene expression have yet to be studied. Here we identify and characterize DNA regulatory elements of the SLC9C1 gene across three mammalian species: mouse, rat, and human. First, in silico analysis of these mammalian SLC9C1 genes identified a CpG island located upstream of the transcription start site in the same relative position in all three genes. Further analysis reveals that this CpG island behaves differently, with respect to gene regulatory activity, in the mouse SLC9C1 gene than it does in the rat and human SLC9C1 gene. The mouse SLC9C1 CpG island displays strong promoter activity by itself and seems to have a stronger gene regulatory effect than either the rat or human SLC9C1 CpG islands. While the function of the upstream SLC9C1 CpG island may be divergent across the three studied species, it appears that the promoters of these three mammalian SLC9C1 genes share similar DNA methylation-sensitive regulatory mechanisms. All three SLC9C1 promoter regions are differentially methylated in lung and testis, being more hypermethylated in lung relative to the testis, and DNA sequence alignments provide strong evidence of primary sequence conservation. Luciferase assays reveal that in vitro methylation of constructs containing different elements of the three SLC9C1 genes largely exhibit methylation-sensitive promoter activity (reduced promoter activity when methylated) in both HEK 293 and GC-1spg cells. In total, our data suggest that the DNA methylation-sensitive elements of the mouse, rat, and human SLC9C1 promoters are largely conserved, while the upstream SLC9C1 CpG island common to all three species seems to perform a different function in mouse than it does in rat and human. This work provides evidence that while homologous genes can all be regulated by DNA methylation-dependent epigenetic mechanisms, the location of the specific cis-regulatory elements responsible for this regulation can differ across species.

SNP-Slice Resolves Mixed Infections: Simultaneously Unveiling Strain Haplotypes and Linking Them to Hosts

Multi-strain infection is a common yet under-investigated phenomenon of many pathogens. Currently, biologists analyzing SNP information have to discard mixed infection samples, because existing downstream analyses require monogenomic inputs. Such a protocol impedes our understanding of the underlying genetic diversity, co-infection patterns, and genomic relatedness of pathogens. A reliable tool to learn and resolve the SNP haplotypes from polygenomic data is an urgent need in molecular epidemiology. In this work, we develop a slice sampling Markov Chain Monte Carlo algorithm, named SNP-Slice, to learn not only the SNP haplotypes of all strains in the populations but also which strains infect which hosts. Our method reconstructs SNP haplotypes and individual heterozygosities accurately without reference panels and outperforms the state of art methods at estimating the multiplicity of infections and allele frequencies. Thus, SNP-Slice introduces a novel approach to address polygenomic data and opens a new avenue for resolving complex infection patterns in molecular surveillance. We illustrate the performance of SNP-Slice on empirical malaria and HIV datasets and provide recommendations for the practical use of the method.

The evolutionary history of bees in time and space

Bees are the most significant pollinators of flowering plants. This partnership began ca. 120 million years ago, but the uncertainty of how and when bees spread across the planet has greatly obscured investigations of this key mutualism. We present a novel analysis of bee biogeography using extensive new genomic and fossil data to demonstrate that bees originated in Western Gondwana (Africa and South America). Bees likely originated in the Early Cretaceous, shortly before the breakup of Western Gondwana, and the early evolution of any major bee lineage is associated with either the South American or African land masses. Subsequently, bees colonized northern continents via a complex history of vicariance and dispersal. The notable early absences from large landmasses, particularly in Australia and India, have important implications for understanding the assembly of local floras and diverse modes of pollination. How bees spread around the world from their hypothesized Southern Hemisphere origin parallels the histories of numerous flowering plant clades, providing an essential step to studying the evolution of angiosperm pollination syndromes in space and time.

Natural products of pentacyclic triterpenoids: from discovery to heterologous biosynthesis

Covering: up to 2022Pentacyclic triterpenoids are important natural bioactive substances that are widely present in plants and fungi. They have significant medicinal efficacy, play an important role in reducing blood glucose and protecting the liver, and have anti-inflammatory, anti-oxidation, anti-fatigue, anti-viral, and anti-cancer activities. Pentacyclic triterpenoids are derived from the isoprenoid biosynthetic pathway, which generates common precursors of triterpenes and steroids, followed by cyclization with oxidosqualene cyclases (OSCs) and decoration via cytochrome P450 monooxygenases (CYP450s) and glycosyltransferases (GTs). Many biosynthetic pathways of triterpenoid saponins have been elucidated by studying their metabolic regulation network through the use of multiomics and identifying their functional genes. Unfortunately, natural resources of pentacyclic triterpenoids are limited due to their low content in plant tissues and the long growth cycle of plants. Based on the understanding of their biosynthetic pathway and transcriptional regulation, plant bioreactors and microbial cell factories are emerging as alternative means for the synthesis of desired triterpenoid saponins. The rapid development of synthetic biology, metabolic engineering, and fermentation technology has broadened channels for the accumulation of pentacyclic triterpenoid saponins. In this review, we summarize the classification, distribution, structural characteristics, and bioactivity of pentacyclic triterpenoids. We further discuss the biosynthetic pathways of pentacyclic triterpenoids and involved transcriptional regulation. Moreover, the recent progress and characteristics of heterologous biosynthesis in plants and microbial cell factories are discussed comparatively. Finally, we propose potential strategies to improve the accumulation of triterpenoid saponins, thereby providing a guide for their future biomanufacturing.

Characterizing the circadian connectome of Ocimum tenuiflorum using an integrated network theoretic framework

Across the three domains of life, circadian clock is known to regulate vital physiological processes, like, growth, development, defence etc. by anticipating environmental cues. In this work, we report an integrated network theoretic methodology comprising of random walk with restart and graphlet degree vectors to characterize genome wide core circadian clock and clock associated raw candidate proteins in a plant for which protein interaction information is available. As a case study, we have implemented this framework in Ocimum tenuiflorum (Tulsi); one of the most valuable medicinal plants that has been utilized since ancient times in the management of a large number of diseases. For that, 24 core clock (CC) proteins were mined in 56 template plant genomes to build their hidden Markov models (HMMs). These HMMs were then used to identify 24 core clock proteins in O. tenuiflorum. The local topology of the interologous Tulsi protein interaction network was explored to predict the CC associated raw candidate proteins. Statistical and biological significance of the raw candidates was determined using permutation and enrichment tests. A total of 66 putative CC associated proteins were identified and their functional annotation was performed.

Cyanotoxins, biosynthetic gene clusters, and factors modulating cyanotoxin biosynthesis

Cyanobacterial harmful algal blooms (CHABs) are a global environmental concern that encompasses public health issues, water availability, and water quality owing to the production of various secondary metabolites (SMs), including cyanotoxins in freshwater, brackish water, and marine ecosystems. The frequency, extent, magnitude, and duration of CHABs are increasing globally. Cyanobacterial species traits and changing environmental conditions, including anthropogenic pressure, eutrophication, and global climate change, together allow cyanobacteria to thrive. The cyanotoxins include a diverse range of low molecular weight compounds with varying biochemical properties and modes of action. With the application of modern molecular biology techniques, many important aspects of cyanobacteria are being elucidated, including aspects of their diversity, gene-environment interactions, and genes that express cyanotoxins. The toxicological, environmental, and economic impacts of CHABs strongly advocate the need for continuing, extensive efforts to monitor cyanobacterial growth and to understand the mechanisms regulating species composition and cyanotoxin biosynthesis. In this review, we critically examined the genomic organization of some cyanobacterial species that lead to the production of cyanotoxins and their characteristic properties discovered to date.

Nicotinic Acid Catabolism Modulates Bacterial Mycophagy in Burkholderia gladioli Strain NGJ1

Burkholderia gladioli strain NGJ1 exhibits mycophagous activity on a broad range of fungi, including Rhizoctonia solani, a devastating plant pathogen. Here, we demonstrate that the nicotinic acid (NA) catabolic pathway in NGJ1 is required for mycophagy. NGJ1 is auxotrophic to NA and it potentially senses R. solani as a NA source. Mutation in the nicC and nicX genes involved in NA catabolism renders defects in mycophagy and the mutant bacteria are unable to utilize R. solani extract as the sole nutrient source. As supplementation of NA, but not FA (fumaric acid, the end product of NA catabolism) restores the mycophagous ability of ΔnicC/ΔnicX mutants, we anticipate that NA is not required as a carbon source for the bacterium during mycophagy. Notably, nicR, a MarR-type of transcriptional regulator that functions as a negative regulator of the NA catabolic pathway is upregulated in ΔnicC/ΔnicX mutant and upon NA supplementation the nicR expression is reduced to the basal level in both the mutants. The ΔnicR mutant produces excessive biofilm and is completely defective in swimming motility. On the other hand, ΔnicC/ΔnicX mutants are compromised in swimming motility as well as biofilm formation, potentially due to the upregulation of nicR. Our data suggest that a defect in NA catabolism alters the NA pool in the bacterium and upregulates nicR which in turn suppresses bacterial motility as well as biofilm formation, leading to mycophagy defects. IMPORTANCE Mycophagy is an important trait through which certain bacteria forage over fungal mycelia and utilize fungal biomass as a nutrient source to thrive in hostile environments. The present study emphasizes that nicotinic acid (NA) is important for bacterial motility and biofilm formation during mycophagy by Burkholderia gladioli strain NGJ1. Defects in NA catabolism potentially alter the cellular NA pool, upregulate the expression of nicR, a negative regulator of biofilm, and therefore suppress bacterial motility as well as biofilm formation, leading to mycophagy defects.

Survey Results of Honey Bee Colony Losses in Winter in China (2009-2021)

There is growing concern that massive loss of honey bees can cause serious negative effects on biodiversity and ecosystems. Surveys of colony losses have been performed worldwide to monitor the dynamic changes and health status of honey bee colonies. Here, we present the results of surveys regarding winter colony losses from 21 provinces in China from 2009 to 2021, with a total of 1,744,324 colonies managed by 13,704 beekeepers. The total colony losses were low (9.84%; 95% Confidence Interval (CI): 9.60-10.08%) but varied among years, provinces, and scales of apiaries. As little is known about the overwintering mortality of Apis cerana, in this study, we surveyed and compared the loss rates between Apis mellifera and A. cerana in China. We found colonies of A. mellifera suffered significantly lower losses than A. cerana in China. Larger apiaries resulted in higher losses in A. mellifera, whereas the opposite was observed in A. cerana. Furthermore, we used generalized linear mixed-effects models (GLMMs) to evaluate the effects of potential risk factors on winter colony losses and found that the operation size, species, migration, migration×species interaction, and queen problems were significantly related to the loss rates. New queens can increase their colony overwintering survival. Migratory beekeepers and large operations reported lower loss rates.

Two novel endophytic Tolypocladium species identified from native pines in south Florida

This study investigated the incidence and diversity of Tolypocladium within trunks of south Florida slash pines (Pinus densa). Thirty-five isolates were recovered from trunk tissue including living phloem, cambium, and sapwood. Two novel species of Tolypocladium (T. subtropicale and T. trecense) are described here based on morphological and molecular analysis of concatenated LSU, ITS, tef-1, tub, and RPB1 sequences. Our findings expand our understanding of the distribution, diversity, and ecology of this genus and confirm that it is widely spread as an endophyte across ecosystems and hosts. Strains collected in this survey will be used in future bioassays to determine their potential ecological roles as mycoparasites or entomopathogens. Citation: Soares JM, Karlsen-Ayala E, Salvador-Montoya CA, Gazis R (2023). Two novel endophytic Tolypocladium species identified from native pines in south Florida. Fungal Systematics and Evolution 11: 51-61. doi: 10.3114/fuse.2023.11.04.

Fulgor: A fast and compact k-mer index for large-scale matching and color queries

The problem of sequence identification or matching - determining the subset of references from a given collection that are likely to contain a query nucleotide sequence - is relevant for many important tasks in Computational Biology, such as metagenomics and pan-genome analysis. Due to the complex nature of such analyses and the large scale of the reference collections a resourceefficient solution to this problem is of utmost importance. The reference collection should therefore be pre-processed into an index for fast queries. This poses the threefold challenge of designing an index that is efficient to query, has light memory usage, and scales well to large collections. To solve this problem, we describe how recent advancements in associative, order-preserving, k-mer dictionaries can be combined with a compressed inverted index to implement a fast and compact colored de Bruijn graph data structure. This index takes full advantage of the fact that unitigs in the colored de Bruijn graph are monochromatic (all k-mers in a unitig have the same set of references of origin, or "color"), leveraging the order-preserving property of its dictionary. In fact, k-mers are kept in unitig order by the dictionary, thereby allowing for the encoding of the map from k-mers to their inverted lists in as little as 1+o(1) bits per unitig. Hence, one inverted list per unitig is stored in the index with almost no space/time overhead. By combining this property with simple but effective compression methods for inverted lists, the index achieves very small space. We implement these methods in a tool called Fulgor. Compared to Themisto, the prior state of the art, Fulgor indexes a heterogeneous collection of 30,691 bacterial genomes in 3.8× less space, a collection of 150,000 Salmonella enterica genomes in approximately 2× less space, is at least twice as fast for color queries, and is 2 - 6× faster to construct.

Exploring Conflicts in Whole Genome Phylogenetics: A Case Study Within Manakins (Aves: Pipridae)

Some phylogenetic problems remain unresolved even when large amounts of sequence data are analyzed and methods that accommodate processes such as incomplete lineage sorting are employed. In addition to investigating biological sources of phylogenetic incongruence, it is also important to reduce noise in the phylogenomic dataset by using appropriate filtering approach that addresses gene tree estimation errors. We present the results of a case study in manakins, focusing on the very difficult clade comprising the genera Antilophia and Chiroxiphia. Previous studies suggest that Antilophia is nested within Chiroxiphia, though relationships among Antilophia+Chiroxiphia species have been highly unstable. We extracted more than 11,000 loci (ultra-conserved elements and introns) from whole genomes and conducted analyses using concatenation and multispecies coalescent methods. Topologies resulting from analyses using all loci differed depending on the data type and analytical method, with 2 clades (Antilophia+Chiroxiphia and Manacus+Pipra+Machaeopterus) in the manakin tree showing incongruent results. We hypothesized that gene trees that conflicted with a long coalescent branch (e.g., the branch uniting Antilophia+Chiroxiphia) might be enriched for cases of gene tree estimation error, so we conducted analyses that either constrained those gene trees to include monophyly of Antilophia+Chiroxiphia or excluded these loci. While constraining trees reduced some incongruence, excluding the trees led to completely congruent species trees, regardless of the data type or model of sequence evolution used. We found that a suite of gene metrics (most importantly the number of informative sites and likelihood of intralocus recombination) collectively explained the loci that resulted in non-monophyly of Antilophia+Chiroxiphia. We also found evidence for introgression that may have contributed to the discordant topologies we observe in Antilophia+Chiroxiphia and led to deviations from expectations given the multispecies coalescent model. Our study highlights the importance of identifying factors that can obscure phylogenetic signal when dealing with recalcitrant phylogenetic problems, such as gene tree estimation error, incomplete lineage sorting, and reticulation events. [Birds; c-gene; data type; gene estimation error; model fit; multispecies coalescent; phylogenomics; reticulation].