BACKGROUND: The dazzling phenotypic characteristics of male Indian peafowl (Pavo cristatus) are attractive both to the female of the species and to humans. However, little is known about the evolution of the phenotype and phylogeny of these birds at the whole-genome level. So far, there are no reports regarding the genetic mechanism of the formation of leucism plumage in this variant of Indian peafowl. RESULTS: A draft genome of Indian peafowl was assembled, with a genome size of 1.05 Gb (the sequencing depth is 362×), and contig and scaffold N50 were up to 6.2 and 11.4 Mb, respectively. Compared with other birds, Indian peafowl showed changes in terms of metabolism, immunity, and skeletal and feather development, which provided a novel insight into the phenotypic evolution of peafowl, such as the large body size and feather morphologies. Moreover, we determined that the phylogeny of Indian peafowl was more closely linked to turkey than chicken. Specifically, we first identified that PMEL was a potential causal gene leading to the formation of the leucism plumage variant in Indian peafowl. CONCLUSIONS: This study provides an Indian peafowl genome of high quality, as well as a novel understanding of phenotypic evolution and phylogeny of Indian peafowl. These results provide a valuable reference for the study of avian genome evolution. Furthermore, the discovery of the genetic mechanism for the development of leucism plumage is both a breakthrough in the exploration of peafowl plumage and also offers clues and directions for further investigations of the avian plumage coloration and artificial breeding in peafowl.

BACKGROUND: Lightless caves can harbour a wide range of living organisms. Cave animals have evolved a set of morphological, physiological, and behavioural adaptations known as troglomorphisms, enabling their survival in the perpetual darkness, narrow temperature and humidity ranges, and nutrient scarcity of the subterranean environment. In this study, we focused on adaptations of skull shape and sensory systems in the blind cave salamander, Proteus anguinus, also known as olm or simply proteus-the largest cave tetrapod and the only European amphibian living exclusively in subterranean environments. This extraordinary amphibian compensates for the loss of sight by enhanced non-visual sensory systems including mechanoreceptors, electroreceptors, and chemoreceptors. We compared developmental stages of P. anguinus with Ambystoma mexicanum, also known as axolotl, to make an exemplary comparison between cave- and surface-dwelling paedomorphic salamanders. FINDINGS: We used contrast-enhanced X-ray computed microtomography for the 3D segmentation of the soft tissues in the head of P. anguinus and A. mexicanum. Sensory organs were visualized to elucidate how the animal is adapted to living in complete darkness. X-ray microCT datasets were provided along with 3D models for larval, juvenile, and adult specimens, showing the cartilage of the chondrocranium and the position, shape, and size of the brain, eyes, and olfactory epithelium. CONCLUSIONS: P. anguinus still keeps some of its secrets. Our high-resolution X-ray microCT scans together with 3D models of the anatomical structures in the head may help to elucidate the nature and origin of the mechanisms behind its adaptations to the subterranean environment, which led to a series of troglomorphisms.

BACKGROUND: The globe skimmer dragonfly (Pantala flavescens) is a notable Odonata insect distributed in nature fields and farmlands worldwide, and it is commonly recognized as a natural enemy because it preys on agricultural pests and health pests. As one of the sister groups of winged insects, odonatan species are key to understanding the evolution of insect wings. FINDINGS: We present a high-quality reference genome of P. flavescens, which is the first chromosome-level genome in the Palaeoptera (Odonata and Ephemeroptera). The assembled genome size was 662 Mb, with a contig N50 of 16.2 Mb. Via Hi-C scaffolding, 648 Mb (97.9%) of contig sequences were clustered, ordered, and assembled into 12 large scaffolds, each corresponding to a natural chromosome. The X chromosome was identified by sequence coverage depth. The repetitive sequences and gene density of the X chromosome are similar to those of autosomal sequences, but the X chromosome shows a much lower degree of heterozygosity. Our analysis shows that the effective population size experienced 3 declining events, which may have been caused by climate change and environmental pollution. CONCLUSIONS: The genome of P. flavescens provides more information on the biology and evolution of insects and will help for the use of this species in pest control.

BACKGROUND: Alternative polyadenylation (APA) causes shortening or lengthening of the 3'-untranslated region (3'-UTR) of genes (APA genes) in diverse cellular processes such as cell proliferation and differentiation. To identify cell-type-specific APA genes in scRNA-Seq data, current bioinformatic methods have several limitations. First, they assume certain read coverage shapes in the scRNA-Seq data, which can be violated in multiple APA genes. Second, their identification is limited between 2 cell types and not directly applicable to the data of multiple cell types. Third, they do not control undesired source of variance, which potentially introduces noise to the cell-type-specific identification of APA genes. FINDINGS: We developed a combination of a computational change-point algorithm and a statistical model, single-cell Multi-group identification of APA (scMAPA). To avoid the assumptions on the read coverage shape, scMAPA formulates a change-point problem after transforming the 3' biased scRNA-Seq data to represent the full-length 3'-UTR signal. To identify cell-type-specific APA genes while adjusting for undesired source of variation, scMAPA models APA isoforms in consideration of the cell types and the undesired source. In our novel simulation data and data from human peripheral blood mononuclear cells, scMAPA outperforms existing methods in sensitivity, robustness, and stability. In mouse brain data consisting of multiple cell types sampled from multiple regions, scMAPA identifies cell-type-specific APA genes, elucidating novel roles of APA for dividing immune cells and differentiated neuron cells and in multiple brain disorders. CONCLUSIONS: scMAPA elucidates the cell-type-specific function of APA events and sheds novel insights into the functional roles of APA events in complex tissues.

BACKGROUND: "Functional" [18F]-fluorodeoxyglucose positron emission tomography (FDG-fPET) is a new approach for measuring glucose uptake in the human brain. The goal of FDG-fPET is to maintain a constant plasma supply of radioactive FDG in order to track, with high temporal resolution, the dynamic uptake of glucose during neuronal activity that occurs in response to a task or at rest. FDG-fPET has most often been applied in simultaneous BOLD-fMRI/FDG-fPET (blood oxygenation level-dependent functional MRI fluorodeoxyglucose functional positron emission tomography) imaging. BOLD-fMRI/FDG-fPET provides the capability to image the 2 primary sources of energetic dynamics in the brain, the cerebrovascular haemodynamic response and cerebral glucose uptake. FINDINGS: In this Data Note, we describe an open access dataset, Monash DaCRA fPET-fMRI, which contrasts 3 radiotracer administration protocols for FDG-fPET: bolus, constant infusion, and hybrid bolus/infusion. Participants (n = 5 in each group) were randomly assigned to each radiotracer administration protocol and underwent simultaneous BOLD-fMRI/FDG-fPET scanning while viewing a flickering checkerboard. The bolus group received the full FDG dose in a standard bolus administration, the infusion group received the full FDG dose as a slow infusion over the duration of the scan, and the bolus-infusion group received 50% of the FDG dose as bolus and 50% as constant infusion. We validate the dataset by contrasting plasma radioactivity, grey matter mean uptake, and task-related activity in the visual cortex. CONCLUSIONS: The Monash DaCRA fPET-fMRI dataset provides significant reuse value for researchers interested in the comparison of signal dynamics in fPET, and its relationship with fMRI task-evoked activity.

BACKGROUND: Ensete glaucum (2n = 2x = 18) is a giant herbaceous monocotyledonous plant in the small Musaceae family along with banana (Musa). A high-quality reference genome sequence assembly of E. glaucum is a resource for functional and evolutionary studies of Ensete, Musaceae, and the Zingiberales. FINDINGS: Using Oxford Nanopore Technologies, chromosome conformation capture (Hi-C), Illumina and RNA survey sequence, supported by molecular cytogenetics, we report a high-quality 481.5 Mb genome assembly with 9 pseudo-chromosomes and 36,836 genes. A total of 55% of the genome is composed of repetitive sequences with predominantly LTR-retroelements (37%) and DNA transposons (7%). The single 5S ribosomal DNA locus had an exceptionally long monomer length of 1,056 bp, more than twice that of the monomers at multiple loci in Musa. A tandemly repeated satellite (1.1% of the genome, with no similar sequence in Musa) was present around all centromeres, together with a few copies of a long interspersed nuclear element (LINE) retroelement. The assembly enabled us to characterize in detail the chromosomal rearrangements occurring between E. glaucum and the x = 11 species of Musa. One E. glaucum chromosome has the same gene content as Musa acuminata, while others show multiple, complex, but clearly defined evolutionary rearrangements in the change between x= 9 and 11. CONCLUSIONS: The advance towards a Musaceae pangenome including E. glaucum, tolerant of extreme environments, makes a complete set of gene alleles, copy number variation, and a reference for structural variation available for crop breeding and understanding environmental responses. The chromosome-scale genome assembly shows the nature of chromosomal fusion and translocation events during speciation, and features of rapid repetitive DNA change in terms of copy number, sequence, and genomic location, critical to understanding its role in diversity and evolution.

BACKGROUND: Traditional biomonitoring approaches have delivered a basic understanding of biodiversity, but they cannot support the large-scale assessments required to manage and protect entire ecosystems. This study used DNA metabarcoding to assess spatial and temporal variation in species richness and diversity in arthropod communities from 52 protected areas spanning 3 Canadian ecoregions. RESULTS: This study revealed the presence of 26,263 arthropod species in the 3 ecoregions and indicated that at least another 3,000-5,000 await detection. Results further demonstrate that communities are more similar within than between ecoregions, even after controlling for geographical distance. Overall α-diversity declined from east to west, reflecting a gradient in habitat disturbance. Shifts in species composition were high at every site, with turnover greater than nestedness, suggesting the presence of many transient species. CONCLUSIONS: Differences in species composition among their arthropod communities confirm that ecoregions are a useful synoptic for biogeographic patterns and for structuring conservation efforts. The present results also demonstrate that metabarcoding enables large-scale monitoring of shifts in species composition, making it possible to move beyond the biomass measurements that have been the key metric used in prior efforts to track change in arthropod communities.

BACKGROUND: The sequencing of the wheat (Triticum aestivum) genome has been a methodological challenge for many years owing to its large size (15.5 Gb), repeat content, and hexaploidy. Many initiatives aiming at obtaining a reference genome of cultivar Chinese Spring have been launched in the past years and it was achieved in 2018 as the result of a huge effort to combine short-read sequencing with many other resources. Reference-quality genome assemblies were then produced for other accessions, but the rapid evolution of sequencing technologies offers opportunities to reach high-quality standards at lower cost. RESULTS: Here, we report on an optimized procedure based on long reads produced on the Oxford Nanopore Technology PromethION device to assemble the genome of the French bread wheat cultivar Renan. CONCLUSIONS: We provide the most contiguous chromosome-scale assembly of a bread wheat genome to date. Coupled with an annotation based on RNA-sequencing data, this resource will be valuable for the crop community and will facilitate the rapid selection of agronomically important traits. We also provide a framework to generate high-quality assemblies of complex genomes using ONT.

BACKGROUND: Huanglongbing, a devastating disease of citrus, is caused by the obligate, intracellular bacterium "Candidatus Liberibacter asiaticus" (CLas). CLas is transmitted by Diaphorina citri, the Asian citrus psyllid. Development of transmission-blocking strategies to manage huanglongbing relies on knowledge of CLas and D. citri interactions at the molecular level. Prior transcriptome analyses of D. citri point to changes in psyllid biology due to CLas infection but have been hampered by incomplete versions of the D. citri genome, proper host plant controls, and/or a lack of a uniform data analysis approach. In this work, we present lessons learned from a quantitative transcriptome analysis of excised heads, salivary glands, midguts, and bacteriomes from CLas-positive and CLas-negative D. citri using the chromosomal length D. citri genome assembly. RESULTS: Each organ had a unique transcriptome profile and response to CLas infection. Though most psyllids were infected with the bacterium, CLas-derived transcripts were not detected in all organs. By analyzing the midgut dataset using both the Diaci_v1.1 and v3.0 D. citri genomes, we showed that improved genome assembly led to significant and quantifiable differences in RNA-sequencing data interpretation. CONCLUSIONS: Our results support the hypothesis that future transcriptome studies on circulative, vector-borne pathogens should be conducted at the tissue-specific level using complete, chromosomal-length genome assemblies for the most accurate understanding of pathogen-induced changes in vector gene expression.

BACKGROUND: As databases grow larger, it becomes harder to fully control their collection, and they frequently come with missing values. These large databases are well suited to train machine learning models, e.g., for forecasting or to extract biomarkers in biomedical settings. Such predictive approaches can use discriminative-rather than generative-modeling and thus open the door to new missing-values strategies. Yet existing empirical evaluations of strategies to handle missing values have focused on inferential statistics. RESULTS: Here we conduct a systematic benchmark of missing-values strategies in predictive models with a focus on large health databases: 4 electronic health record datasets, 1 population brain imaging database, 1 health survey, and 2 intensive care surveys. Using gradient-boosted trees, we compare native support for missing values with simple and state-of-the-art imputation prior to learning. We investigate prediction accuracy and computational time. For prediction after imputation, we find that adding an indicator to express which values have been imputed is important, suggesting that the data are missing not at random. Elaborate missing-values imputation can improve prediction compared to simple strategies but requires longer computational time on large data. Learning trees that model missing values-with missing incorporated attribute-leads to robust, fast, and well-performing predictive modeling. CONCLUSIONS: Native support for missing values in supervised machine learning predicts better than state-of-the-art imputation with much less computational cost. When using imputation, it is important to add indicator columns expressing which values have been imputed.

BACKGROUND: Genome-wide gene function annotations are useful for hypothesis generation and for prioritizing candidate genes potentially responsible for phenotypes of interest. We functionally annotated the genes of 18 crop plant genomes across 14 species using the GOMAP pipeline. RESULTS: By comparison to existing GO annotation datasets, GOMAP-generated datasets cover more genes, contain more GO terms, and are similar in quality (based on precision and recall metrics using existing gold standards as the basis for comparison). From there, we sought to determine whether the datasets across multiple species could be used together to carry out comparative functional genomics analyses in plants. To test the idea and as a proof of concept, we created dendrograms of functional relatedness based on terms assigned for all 18 genomes. These dendrograms were compared to well-established species-level evolutionary phylogenies to determine whether trees derived were in agreement with known evolutionary relationships, which they largely are. Where discrepancies were observed, we determined branch support based on jackknifing then removed individual annotation sets by genome to identify the annotation sets causing unexpected relationships. CONCLUSIONS: GOMAP-derived functional annotations used together across multiple species generally retain sufficient biological signal to recover known phylogenetic relationships based on genome-wide functional similarities, indicating that comparative functional genomics across species based on GO data holds promise for generating novel hypotheses about comparative gene function and traits.

BACKGROUND: CRISPR-Cas systems have expanded the possibilities for gene editing in bacteria and eukaryotes. There are many excellent tools for designing CRISPR-Cas guide RNAs (gRNAs) for model organisms with standard Cas enzymes. GuideMaker is intended as a fast and easy-to-use design tool for challenging projects with (i) non-standard Cas enzymes, (ii) non-model organisms, or (iii) projects that need to design a panel of gRNA for genome-wide screens. FINDINGS: GuideMaker can rapidly design gRNAs for gene targets across the genome using a degenerate protospacer-adjacent motif (PAM) and a genome. The tool applies hierarchical navigable small world graphs to speed up the comparison of guide RNAs and optionally provides on-target and off-target scoring. This allows the user to design effective gRNAs targeting all genes in a typical bacterial genome in ∼1-2 minutes. CONCLUSIONS: GuideMaker enables the rapid design of genome-wide gRNA for any CRISPR-Cas enzyme in non-model organisms. While GuideMaker is designed with prokaryotic genomes in mind, it can efficiently process eukaryotic genomes as well. GuideMaker is available as command-line software, a stand-alone web application, and a tool in the CyCverse Discovery Environment. All versions are available under a Creative Commons CC0 1.0 Universal Public Domain Dedication.

BACKGROUND: The ring-tailed lemur (Lemur catta) is a charismatic strepsirrhine primate endemic to Madagascar. These lemurs are of particular interest, given their status as a flagship species and widespread publicity in the popular media. Unfortunately, a recent population decline has resulted in the census population decreasing to <2,500 individuals in the wild, and the species's classification as an endangered species by the IUCN. As is the case for most strepsirrhine primates, only a limited amount of genomic research has been conducted on L. catta, in part owing to the lack of genomic resources. RESULTS: We generated a new high-quality reference genome assembly for L. catta (mLemCat1) that conforms to the standards of the Vertebrate Genomes Project. This new long-read assembly is composed of Pacific Biosciences continuous long reads (CLR data), Optical Mapping Bionano reads, Arima HiC data, and 10X linked reads. The contiguity and completeness of the assembly are extremely high, with scaffold and contig N50 values of 90.982 and 10.570 Mb, respectively. Additionally, when compared to other high-quality primate assemblies, L. catta has the lowest reported number of Alu elements, which results predominantly from a lack of AluS and AluY elements. CONCLUSIONS: mLemCat1 is an excellent genomic resource not only for the ring-tailed lemur community, but also for other members of the Lemuridae family, and is the first very long read assembly for a strepsirrhine.

Snake venoms represent a danger to human health, but also a gold mine of bioactive proteins that can be harnessed for drug discovery purposes. The evolution of snakes and their venom has been studied for decades, particularly via traditional morphological and basic genetic methods alongside venom proteomics. However, while the field of genomics has matured rapidly over the past 2 decades, owing to the development of next-generation sequencing technologies, snake genomics remains in its infancy. Here, we provide an overview of the state of the art in snake genomics and discuss its potential implications for studying venom evolution and toxinology. On the basis of current knowledge, gene duplication and positive selection are key mechanisms in the neofunctionalization of snake venom proteins. This makes snake venoms important evolutionary drivers that explain the remarkable venom diversification and adaptive variation observed in these reptiles. Gene duplication and neofunctionalization have also generated a large number of repeat sequences in snake genomes that pose a significant challenge to DNA sequencing, resulting in the need for substantial computational resources and longer sequencing read length for high-quality genome assembly. Fortunately, owing to constantly improving sequencing technologies and computational tools, we are now able to explore the molecular mechanisms of snake venom evolution in unprecedented detail. Such novel insights have the potential to affect the design and development of antivenoms and possibly other drugs, as well as provide new fundamental knowledge on snake biology and evolution.

BACKGROUND: Gossypium hirsutum L. is the most widely cultivated cotton species, and a high-quality reference genome would be a huge boost for researching the molecular mechanism of agronomic traits in cotton. FINDINGS: Here, Pacific Biosciences and Hi-C sequencing technologies were used to assemble a new upland cotton genome of the No. 1 Chinese cotton variety CRI-12. We generated a high-quality assembled CRI-12 genome of 2.31 Gb with a contig N50 of 19.65 Mb, which was superior to previously reported genomes. Comparisons between CRI-12 and other reported genomes revealed 7,966 structural variations and 7,378 presence/absence variations. The distribution of the haplotypes among A-genome (Gossypium arboreum), D-genome (Gossypium raimondii), and AD-genome (G. hirsutum and Gossypium barbadense) suggested that many haplotypes were lost and recombined in the process of polyploidization. More than half of the haplotypes that correlated with different tolerances were located on chromosome D13, suggesting that this chromosome may be important for wide adaptation. Finally, it was demonstrated that DNA methylation may provide advantages in environmental adaptation through whole-genome bisulfite sequencing analysis. CONCLUSIONS: This research provides a new reference genome for molecular biology research on Gossypium hirsutum L. and helps decode the broad environmental adaptation mechanisms in the No. 1 Chinese cotton variety CRI-12.