KEGG orthology prediction of bacterial proteins using natural language processing

BACKGROUND

The advent of high-throughput technologies has led to an exponential increase in uncharacterized bacterial protein sequences, surpassing the capacity of manual curation. A large number of bacterial protein sequences remain unannotated by Kyoto Encyclopedia of Genes and Genomes (KEGG) orthology, making it necessary to use auto annotation tools. These tools are now indispensable in the biological research landscape, bridging the gap between the vastness of unannotated sequences and meaningful biological insights.

RESULTS

In this work, we propose a novel pipeline for KEGG orthology annotation of bacterial protein sequences that uses natural language processing and deep learning. To assess the effectiveness of our pipeline, we conducted evaluations using the genomes of two randomly selected species from the KEGG database. In our evaluation, we obtain competitive results on precision, recall, and F1 score, with values of 0.948, 0.947, and 0.947, respectively.

CONCLUSIONS

Our experimental results suggest that our pipeline demonstrates performance comparable to traditional methods and excels in identifying distant relatives with low sequence identity. This demonstrates the potential of our pipeline to significantly improve the accuracy and comprehensiveness of KEGG orthology annotation, thereby advancing our understanding of functional relationships within biological systems.

A revamped rat reference genome improves the discovery of genetic diversity in laboratory rats

The seventh iteration of the reference genome assembly for Rattus norvegicus-mRatBN7.2-corrects numerous misplaced segments and reduces base-level errors by approximately 9-fold and increases contiguity by 290-fold compared with its predecessor. Gene annotations are now more complete, improving the mapping precision of genomic, transcriptomic, and proteomics datasets. We jointly analyzed 163 short-read whole-genome sequencing datasets representing 120 laboratory rat strains and substrains using mRatBN7.2. We defined ∼20.0 million sequence variations, of which 18,700 are predicted to potentially impact the function of 6,677 genes. We also generated a new rat genetic map from 1,893 heterogeneous stock rats and annotated transcription start sites and alternative polyadenylation sites. The mRatBN7.2 assembly, along with the extensive analysis of genomic variations among rat strains, enhances our understanding of the rat genome, providing researchers with an expanded resource for studies involving rats.

The chromosome-level genome assembly of the giant dobsonfly Acanthacorydalis orientalis (McLachlan, 1899)

Acanthacorydalis orientalis (McLachlan, 1899) (Megaloptera: Corydalidae) is an important freshwater-benthic invertebrate species that serves as an indicator for water-quality biomonitoring and is valuable for conservation from East Asia. Here, a high-quality reference genome for A. orientalis was constructed using Oxford Nanopore sequencing and High throughput Chromosome Conformation Capture (Hi-C) technology. The final genome size is 547.98 Mb, with the N50 values of contig and scaffold being 7.77 Mb and 50.53 Mb, respectively. The longest contig and scaffold are 20.57 Mb and 62.26 Mb in length, respectively. There are 99.75% contigs anchored onto 13 pseudo-chromosomes. Benchmarking Universal Single-Copy Orthologs (BUSCO) analysis showed that the completeness of the genome assembly is 99.01%. There are 10,977 protein-coding genes identified, of which 84.00% are functionally annotated. The genome contains 44.86% repeat sequences. This high-quality genome provides substantial data for future studies on population genetics, aquatic adaptation, and evolution of Megaloptera and other related insect groups.

A chromosome-level genome assembly of the spider mite Tetranychus piercei McGregor

Despite the rapid advances in sequencing technology, limited genomic resources are currently available for phytophagous spider mites, which include many important agricultural pests. One of these pests is Tetranychus piercei (McGregor), a serious banana pest in East Asia exhibiting remarkable tolerance to high temperature. In this study, we assembled a high-quality genome of T. piercei using a combination of PacBio long reads and Illumina short reads sequencing. With the assistance of chromatin conformation capture technology, 99.9% of the contigs were anchored into three pseudochromosomes with a total size of 86.02 Mb. Repetitive elements, accounting for 14.16% of this genome (12.20 Mb), are predominantly composed of long-terminal repeats (30.7%). By combining evidence of ab initio prediction, transcripts, and homologous proteins, we annotated 11,881 protein-coding genes. Both the genome and proteins have high BUSCO completeness scores (>94%). This high-quality genome, along with reliable annotation, provides a valuable resource for investigating the high-temperature tolerance of this species and exploring the genomic basis that underlies the host range evolution of spider mites.

Yak genome database: a multi-omics analysis platform

BACKGROUND

The yak (Bos grunniens) is a large ruminant species that lives in high-altitude regions and exhibits excellent adaptation to the plateau environments. To further understand the genetic characteristics and adaptive mechanisms of yak, we have developed a multi-omics database of yak including genome, transcriptome, proteome, and DNA methylation data.

DESCRIPTION

The Yak Genome Database ( http://yakgenomics.com/ ) integrates the research results of genome, transcriptome, proteome, and DNA methylation, and provides an integrated platform for researchers to share and exchange omics data. The database contains 26,518 genes, 62 transcriptomes, 144,309 proteome spectra, and 22,478 methylation sites of yak. The genome module provides access to yak genome sequences, gene annotations and variant information. The transcriptome module offers transcriptome data from various tissues of yak and cattle strains at different developmental stages. The proteome module presents protein profiles from diverse yak organs. Additionally, the DNA methylation module shows the DNA methylation information at each base of the whole genome. Functions of data downloading and browsing, functional gene exploration, and experimental practice were available for the database.

CONCLUSION

This comprehensive database provides a valuable resource for further investigations on development, molecular mechanisms underlying high-altitude adaptation, and molecular breeding of yak.

Genome assembly and annotation of the mermithid nematode Mermis nigrescens

Genetic studies of nematodes have been dominated by Caenorhabditis elegans as a model species. A lack of genomic resources has limited the expansion of genetic research to other groups of nematodes. Here, we report a draft genome assembly of a mermithid nematode, Mermis nigrescens. Mermithidae are insect parasitic nematodes with hosts including a wide range of terrestrial arthropods. We sequenced, assembled, and annotated the whole genome of M. nigrescens using nanopore long reads and 10X Chromium link reads. The assembly is 524 Mb in size consisting of 867 scaffolds. The N50 value is 2.42 Mb, and half of the assembly is in the 30 longest scaffolds. The assembly BUSCO score from the eukaryotic database (eukaryota_odb10) indicates that the genome is 86.7% complete and 5.1% partial. The genome has a high level of heterozygosity (6.6%) with a repeat content of 83.98%. mRNA-seq reads from different sized nematodes (≤2 cm, 3.5-7 cm, and >7 cm body length) representing different developmental stages were also generated and used for the genome annotation. Using ab initio and evidence-based gene model predictions, 12,313 protein-coding genes and 24,186 mRNAs were annotated. These genomic resources will help researchers investigate the various aspects of the biology and host-parasite interactions of mermithid nematodes.

Annotation of 2,507 Saccharomyces cerevisiae genomes

Saccharomyces cerevisiae (baker's yeast, budding yeast) is one of the most important model organisms for biological research and is a crucial microorganism in industry. Currently, a huge number of Saccharomyces cerevisiae genome sequences are available at the public domain. However, these genomes are distributed at different websites and a large number of them are released without annotation information. To provide one complete annotated genome data resource, we collected 2,507 Saccharomyces cerevisiae genome assemblies and re-annotated 2,506 assemblies using a custom annotation pipeline, producing a total of 15,407,164 protein-coding gene models. With a custom pipeline, all these gene sequences were clustered into families. A total of 1,506 single-copy genes were selected as marker genes, which were then used to evaluate the genome completeness and base qualities of all assemblies. Pangenomic analyses were performed based on a selected subset of 847 medium-high-quality genomes. Statistical comparisons revealed a number of gene families showing copy number variations among different organism sources. To the authors' knowledge, this study represents the largest genome annotation project of S. cerevisiae so far, providing rich genomic resources for the future studies of the model organism S. cerevisiae and its relatives.IMPORTANCESaccharomyces cerevisiae (baker's yeast, budding yeast) is one of the most important model organisms for biological research and is a crucial microorganism in industry. Though a huge number of Saccharomyces cerevisiae genome sequences are available at the public domain, these genomes are distributed at different websites and most are released without annotation, hindering the efficient reuse of these genome resources. Here, we collected 2,507 genomes for Saccharomyces cerevisiae, performed genome annotation, and evaluated the genome qualities. All the obtained data have been deposited at public repositories and are freely accessible to the community. This study represents the largest genome annotation project of S. cerevisiae so far, providing one complete annotated genome data set for S. cerevisiae, an important workhorse for fundamental biology, biotechnology, and industry.

The genome of the rayed Mediterranean limpet Patella caerulea (Linnaeus, 1758)

Patella caerulea (Linnaeus, 1758) is a mollusc limpet species of the class Gastropoda. Endemic to the Mediterranean Sea, it is considered a keystone species due to its primary role in structuring and regulating the ecological balance of tidal and subtidal habitats. It is currently being used as a bioindicator to assess the environmental quality of coastal marine waters and as a model species to understand adaptation to ocean acidification. Here, we provide a high-quality reference genome assembly and annotation for P. caerulea. We generated ∼30 Gb of Pacific Biosciences high-fidelity data from a single individual and provide a final 749.8 Mb assembly containing 62 contigs, including the mitochondrial genome (14,938 bp). With an N50 of 48.8 Mb and 98% of the assembly contained in the 18 largest contigs, this assembly is near chromosome-scale. Benchmarking Universal Single-Copy Orthologs scores were high (Mollusca, 87.8% complete; Metazoa, 97.2% complete) and similar to metrics observed for other chromosome-level Patella genomes, highlighting a possible bias in the Mollusca database for Patellids. We generated transcriptomic Illumina data from a second individual collected at the same locality and used it together with protein evidence to annotate the genome. A total of 23,938 protein-coding gene models were found. By comparing this annotation with other published Patella annotations, we found that the distribution and median values of exon and gene lengths was comparable with other Patella species despite different annotation approaches. The present high-quality P. caerulea reference genome, available on GenBank (BioProject: PRJNA1045377; assembly: GCA_036850965.1), is an important resource for future ecological and evolutionary studies.

Earl Grey: A Fully Automated User-Friendly Transposable Element Annotation and Analysis Pipeline

Transposable elements (TEs) are major components of eukaryotic genomes and are implicated in a range of evolutionary processes. Yet, TE annotation and characterization remain challenging, particularly for nonspecialists, since existing pipelines are typically complicated to install, run, and extract data from. Current methods of automated TE annotation are also subject to issues that reduce overall quality, particularly (i) fragmented and overlapping TE annotations, leading to erroneous estimates of TE count and coverage, and (ii) repeat models represented by short sections of total TE length, with poor capture of 5' and 3' ends. To address these issues, we present Earl Grey, a fully automated TE annotation pipeline designed for user-friendly curation and annotation of TEs in eukaryotic genome assemblies. Using nine simulated genomes and an annotation of Drosophila melanogaster, we show that Earl Grey outperforms current widely used TE annotation methodologies in ameliorating the issues mentioned above while scoring highly in benchmarking for TE annotation and classification and being robust across genomic contexts. Earl Grey provides a comprehensive and fully automated TE annotation toolkit that provides researchers with paper-ready summary figures and outputs in standard formats compatible with other bioinformatics tools. Earl Grey has a modular format, with great scope for the inclusion of additional modules focused on further quality control and tailored analyses in future releases.

Predicting Protein Functions Based on Heterogeneous Graph Attention Technique

In bioinformatics, protein function prediction stands as a fundamental area of research and plays a crucial role in addressing various biological challenges, such as the identification of potential targets for drug discovery and the elucidation of disease mechanisms. However, known functional annotation databases usually provide positive experimental annotations that proteins carry out a given function, and rarely record negative experimental annotations that proteins do not carry out a given function. Therefore, existing computational methods based on deep learning models focus on these positive annotations for prediction and ignore these scarce but informative negative annotations, leading to an underestimation of precision. To address this issue, we introduce a deep learning method that utilizes a heterogeneous graph attention technique. The method first constructs a heterogeneous graph that covers the protein-protein interaction network, ontology structure, and positive and negative annotation information. Then, it learns embedding representations of proteins and ontology terms by using the heterogeneous graph attention technique. Finally, it leverages these learned representations to reconstruct the positive protein-term associations and score unobserved functional annotations. It can enhance the predictive performance by incorporating these known limited negative annotations into the constructed heterogeneous graph. Experimental results on three species (i.e., Human, Mouse, and Arabidopsis) demonstrate that our method can achieve better performance in predicting new protein annotations than state-of-the-art methods.

An historical "wreck": A transcriptome assembly of the naval shipworm, Teredo navalis Linnaeus, 1978

Historically famous for their negative impact on human-built marine wood structures, mollusc shipworms play a central ecological role in marine ecosystems. Their association with bacterial symbionts, providing cellulolytic and nitrogen-fixing activities, underscores their exceptional wood-eating and wood-boring behaviours, improving energy transfer and the recycling of essential nutrients locked in the wood cellulose. Importantly, from a molecular standpoint, a minute of omic resources are available from this lineage of Bivalvia. Here, we produced and assembled a transcriptome from the globally distributed naval shipworm, Teredo navalis (family Teredinidae). The transcriptome was obtained by sequencing the total RNA from five equidistant segments of the whole body of a T. navalis specimen. The quality of the produced assembly was accessed with several statistics, revealing a highly contiguous (1194 N50) and complete (over 90% BUSCO scores for Eukaryote and Metazoan databases) transcriptome, with nearly 38,000 predicted ORF, more than half being functionally annotated. Our findings pave the way to investigate the unique evolutionary biology of these highly modified bivalves and lay the foundation for an adequate gene annotation of a full genome sequence of the species.

PLMSearch: Protein language model powers accurate and fast sequence search for remote homology

Homologous protein search is one of the most commonly used methods for protein annotation and analysis. Compared to structure search, detecting distant evolutionary relationships from sequences alone remains challenging. Here we propose PLMSearch (Protein Language Model), a homologous protein search method with only sequences as input. PLMSearch uses deep representations from a pre-trained protein language model and trains the similarity prediction model with a large number of real structure similarity. This enables PLMSearch to capture the remote homology information concealed behind the sequences. Extensive experimental results show that PLMSearch can search millions of query-target protein pairs in seconds like MMseqs2 while increasing the sensitivity by more than threefold, and is comparable to state-of-the-art structure search methods. In particular, unlike traditional sequence search methods, PLMSearch can recall most remote homology pairs with dissimilar sequences but similar structures. PLMSearch is freely available at https://dmiip.sjtu.edu.cn/PLMSearch .

A high-quality chromosome-level genome assembly of the Chinese medaka Oryzias sinensis

Oryzias sinensis, also known as Chinese medaka or Chinese ricefish, is a commonly used animal model for aquatic environmental assessment in the wild as well as gene function validation or toxicology research in the lab. Here, a high-quality chromosome-level genome assembly of O. sinensis was generated using single-tube long fragment read (stLFR) reads, Nanopore long-reads, and Hi-C sequencing data. The genome is 796.58 Mb, and a total of 712.17 Mb of the assembled sequences were anchored to 23 pseudo-chromosomes. A final set of 22,461 genes were annotated, with 98.67% being functionally annotated. The Benchmarking Universal Single-Copy Orthologs (BUSCO) benchmark of genome assembly and gene annotation reached 95.1% (93.3% single-copy) and 94.6% (91.7% single-copy), respectively. Furthermore, we also use ATAC-seq to uncover chromosome transposase-accessibility as well as related genome area function enrichment for Oryzias sinensis. This study offers a new improved foundation for future genomics research in Chinese medaka.

From tradition to innovation: conventional and deep learning frameworks in genome annotation

Following the milestone success of the Human Genome Project, the 'Encyclopedia of DNA Elements (ENCODE)' initiative was launched in 2003 to unearth information about the numerous functional elements within the genome. This endeavor coincided with the emergence of numerous novel technologies, accompanied by the provision of vast amounts of whole-genome sequences, high-throughput data such as ChIP-Seq and RNA-Seq. Extracting biologically meaningful information from this massive dataset has become a critical aspect of many recent studies, particularly in annotating and predicting the functions of unknown genes. The core idea behind genome annotation is to identify genes and various functional elements within the genome sequence and infer their biological functions. Traditional wet-lab experimental methods still rely on extensive efforts for functional verification. However, early bioinformatics algorithms and software primarily employed shallow learning techniques; thus, the ability to characterize data and features learning was limited. With the widespread adoption of RNA-Seq technology, scientists from the biological community began to harness the potential of machine learning and deep learning approaches for gene structure prediction and functional annotation. In this context, we reviewed both conventional methods and contemporary deep learning frameworks, and highlighted novel perspectives on the challenges arising during annotation underscoring the dynamic nature of this evolving scientific landscape.

A chromosome-level genome assembly of the pig-nosed turtle (Carettochelys insculpta)

The pig-nosed turtle (Carettochelys insculpta) represents the only extant species within the Carettochelyidae family, is a unique Trionychia member fully adapted to aquatic life and currently facing endangerment. To enhance our understanding of this species and contribute to its conservation efforts, we employed high-fidelity (HiFi) and Hi-C sequencing technology to generate its genome assembly at the chromosome level. The assembly result spans 2.18 Gb, with a contig N50 of 126 Mb, encompassing 34 chromosomes that account for 99.6% of the genome. The assembly has a BUSCO score above 95% with different databases and strong collinearity with Yangtze giant softshell turtles (Rafetus swinhoei), indicating its completeness and continuity. A total of 19,175 genes and 46.86% repetitive sequences were annotated. The availability of this chromosome-scale genome represents a valuable resource for the pig-nosed turtle, providing insights into its aquatic adaptation and serving as a foundation for future turtle research.

Contigs directed gene annotation (ConDiGA) for accurate protein sequence database construction in metaproteomics

BACKGROUND

Microbiota are closely associated with human health and disease. Metaproteomics can provide a direct means to identify microbial proteins in microbiota for compositional and functional characterization. However, in-depth and accurate metaproteomics is still limited due to the extreme complexity and high diversity of microbiota samples. It is generally recommended to use metagenomic data from the same samples to construct the protein sequence database for metaproteomic data analysis. Although different metagenomics-based database construction strategies have been developed, an optimization of gene taxonomic annotation has not been reported, which, however, is extremely important for accurate metaproteomic analysis.

RESULTS

Herein, we proposed an accurate taxonomic annotation pipeline for genes from metagenomic data, namely contigs directed gene annotation (ConDiGA), and used the method to build a protein sequence database for metaproteomic analysis. We compared our pipeline (ConDiGA or MD3) with two other popular annotation pipelines (MD1 and MD2). In MD1, genes were directly annotated against the whole bacterial genome database; in MD2, contigs were annotated against the whole bacterial genome database and the taxonomic information of contigs was assigned to the genes; in MD3, the most confident species from the contigs annotation results were taken as reference to annotate genes. Annotation tools, including BLAST, Kaiju, and Kraken2, were compared. Based on a synthetic microbial community of 12 species, it was found that Kaiju with the MD3 pipeline outperformed the others in the construction of protein sequence database from metagenomic data. Similar performance was also observed with a fecal sample, as well as in silico mixed datasets of the simulated microbial community and the fecal sample.

CONCLUSIONS

Overall, we developed an optimized pipeline for gene taxonomic annotation to construct protein sequence databases. Our study can tackle the current taxonomic annotation reliability problem in metagenomics-derived protein sequence database and can promote the in-depth metaproteomic analysis of microbiome. The unique metagenomic and metaproteomic datasets of the 12 bacterial species are publicly available as a standard benchmarking sample for evaluating various analysis pipelines. The code of ConDiGA is open access at GitHub for the analysis of microbiota samples. Video Abstract.

Enriched atlas of lncRNA and protein-coding genes for the GRCg7b chicken assembly and its functional annotation across 47 tissues

Gene atlases for livestock are steadily improving thanks to new genome assemblies and new expression data improving the gene annotation. However, gene content varies across databases due to differences in RNA sequencing data and bioinformatics pipelines, especially for long non-coding RNAs (lncRNAs) which have higher tissue and developmental specificity and are harder to consistently identify compared to protein coding genes (PCGs). As done previously in 2020 for chicken assemblies galgal5 and GRCg6a, we provide a new gene atlas, lncRNA-enriched, for the latest GRCg7b chicken assembly, integrating "NCBI RefSeq", "EMBL-EBI Ensembl/GENCODE" reference annotations and other resources such as FAANG and NONCODE. As a result, the number of PCGs increases from 18,022 (RefSeq) and 17,007 (Ensembl) to 24,102, and that of lncRNAs from 5789 (RefSeq) and 11,944 (Ensembl) to 44,428. Using 1400 public RNA-seq transcriptome representing 47 tissues, we provided expression evidence for 35,257 (79%) lncRNAs and 22,468 (93%) PCGs, supporting the relevance of this atlas. Further characterization including tissue-specificity, sex-differential expression and gene configurations are provided. We also identified conserved miRNA-hosting genes with human counterparts, suggesting common function. The annotated atlas is available at gega.sigenae.org.

Identification of homologous protein models via 3D comparisons using predicted structures

Recent advances in protein structure prediction enable 3D homology alignment and domain annotation using tertiary structures. Here, we present a protocol to identify homologous structures and annotate protein domains through in silico comparisons using the AlphaFold database. We describe steps for downloading and installing PyMOL software, preparing the query structure, and conducting a 3D homology search. The example provided highlights the application of this protocol in reevaluating an mpox viral protein annotation. For complete details on the use and execution of this protocol, please refer to Pan et al. (2023).1.

Genome Sequence Analysis of Calcifying Bacteria Bacillus paranthracis CT5 and Its Biomineralization Efficacy to Improve the Strength and Durability Properties of Civil Structures

Bacteria producing urea amidohydrolases (UA) and carbonic anhydrases (CA) are of great importance in civil engineering as these enzymes are responsible for microbially induced calcium carbonate precipitation (MICCP). In this investigation, genomic insights of Bacillus paranthracis CT5 and the expression of genes underlying in MICCP were studied. B. paranthracis produced a maximum level of UA (669.3 U/ml) and CA (125 U/ml) on 5th day of incubation and precipitated 197 mg/100 ml CaCO3 after 7 days of incubation. After 28 days of curing, compressive strength of bacterial admixed and bacterial cured (B-B) specimens was 13.7% higher compared to water-mixed and water-cured (W-W) specimens. A significant decrease in water absorption was observed in bacterial-cured specimens compared to water-cured specimens after 28 days of curing. For genome analysis, reads were assembled de novo producing 5,402,771 bp assembly with N50 of 273,050 bp. RAST annotation detected six amidohydrolase and three carbonic anhydrase genes. Among 5700 coding sequences found in genome, COG gene annotation grouped 4360 genes into COG categories with highest number of genes to transcription (435 genes), amino acid transport and metabolism (362 genes) along with cell wall/membrane/envelope biogenesis and ion transport and metabolism. KEGG functional classification predicted 223 pathways consisting of 1,960 genes and the highest number of genes belongs to two-component system (101 genes) and ABC transporter pathways (98 genes) enabling bacteria to sense and respond to environmental signals and actively transport various minerals and organic molecules, which facilitate the active transport of molecules required for MICCP.

A draft genome of the neritid snail Theodoxus fluviatilis

The neritid snail Theodoxus fluviatilis is found across habitats differing in salinity, from shallow waters along the coast of the Baltic Sea to lakes throughout Europe. Living close to the water surface makes this species vulnerable to changes in salinity in their natural habitat, and the lack of a free-swimming larval stage limits this species' dispersal. Together, these factors have resulted in a patchy distribution of quite isolated populations differing in their salinity tolerances. In preparation for investigating the mechanisms underlying the physiological differences in osmoregulation between populations that cannot be explained solely by phenotypic plasticity, we present here an annotated draft genome assembly for T. fluviatilis, generated using PacBio long reads, Illumina short reads, and transcriptomic data. While the total assembly size (1045 kb) is similar to those of related species, it remains highly fragmented (N scaffolds = 35,695; N50 = 74 kb) though moderately high in complete gene content (BUSCO single copy complete: 74.3%, duplicate: 2.6%, fragmented: 10.6%, missing: 12.5% using metazoa n = 954). Nevertheless, we were able to generate gene annotations of 21,220 protein-coding genes (BUSCO single copy complete: 65.1%, duplicate: 16.7%, fragmented: 9.1%, missing: 9.1% using metazoa n = 954). Not only will this genome facilitate comparative evolutionary studies across Gastropoda, as this is the first genome assembly for the basal snail family Neritidae, it will also greatly facilitate the study of salinity tolerance in this species. Additionally, we discuss the challenges of working with a species where high molecular weight DNA isolation is very difficult.

Whole-genome sequence and annotation of Penstemon davidsonii

Penstemon is the most speciose flowering plant genus endemic to North America. Penstemon species' diverse morphology and adaptation to various environments have made them a valuable model system for studying evolution. Here, we report the first full reference genome assembly and annotation for Penstemon davidsonii. Using PacBio long-read sequencing and Hi-C scaffolding technology, we constructed a de novo reference genome of 437,568,744 bases, with a contig N50 of 40 Mb and L50 of 5. The annotation includes 18,199 gene models, and both the genome and transcriptome assembly contain over 95% complete eudicot BUSCOs. This genome assembly will serve as a valuable reference for studying the evolutionary history and genetic diversity of the Penstemon genus.

High-quality assembled and annotated genomes of Nicotiana tabacum and Nicotiana benthamiana reveal chromosome evolution and changes in defense arsenals

Nicotiana tabacum and Nicotiana benthamiana are widely used models in plant biology research. However, genomic studies of these species have lagged. Here we report the chromosome-level reference genome assemblies for N. benthamiana and N. tabacum with an estimated 99.5% and 99.8% completeness, respectively. Sensitive transcription start and termination site sequencing methods were developed and used for accurate gene annotation in N. tabacum. Comparative analyses revealed evidence for the parental origins and chromosome structural changes, leading to hybrid genome formation of each species. Interestingly, the antiviral silencing genes RDR1, RDR6, DCL2, DCL3, and AGO2 were lost from one or both subgenomes in N. benthamiana, while both homeologs were kept in N. tabacum. Furthermore, the N. benthamiana genome encodes fewer immune receptors and signaling components than that of N. tabacum. These findings uncover possible reasons underlying the hypersusceptible nature of N. benthamiana. We developed the user-friendly Nicomics (http://lifenglab.hzau.edu.cn/Nicomics/) web server to facilitate better use of Nicotiana genomic resources as well as gene structure and expression analyses.

Chromosome-Level Assembly and Annotation of the Pearly Heath Coenonympha arcania Butterfly Genome

We present the first chromosome-level genome assembly and annotation of the pearly heath Coenonympha arcania, generated with a PacBio HiFi sequencing approach and complemented with Hi-C data. We additionally compare synteny, gene, and repeat content between C. arcania and other Lepidopteran genomes. This reference genome will enable future population genomics studies with Coenonympha butterflies, a species-rich genus that encompasses some of the most highly endangered butterfly taxa in Europe.

Genome Assembly and Annotation of the Dark-Branded Bushbrown Butterfly Mycalesis mineus (Nymphalidae: Satyrinae)

We report a high-quality genome draft assembly of the dark-branded bushbrown, Mycalesis mineus, a member of the Satyrinae subfamily of nymphalid butterflies. This species is emerging as a promising model organism for investigating the evolution and development of phenotypic plasticity. Using 45.99 Gb of long-read data (N50 = 11.11 kb), we assembled a genome size of 497.4 Mb for M. mineus. The assembly is highly contiguous and nearly complete (96.8% of Benchmarking Universal Single-Copy Orthologs lepidopteran genes were complete and single copy). The genome comprises 38.71% of repetitive elements and includes 20,967 predicted protein-coding genes. The assembled genome was super-scaffolded into 28 pseudo-chromosomes using a closely related species, Bicyclus anynana, with a chromosomal-level genome as a template. This valuable genomic tool will advance both ongoing and future research focused on this model organism.

High-quality genome assembly of a C. crossoptilon and related functional and genetics data resources

There are four species in the Crossoptilon genus inhibiting at from very low to very high altitudes across China, and they are in varying levels of danger of extinction. To better understand the genetic basis of adaptation to high altitudes and genetic changes due to bottleneck, we assembled the genome (~1.02 Gb) of a white eared pheasant (WT) (Crossoptilon crossoptilon) inhibiting at high altitudes (3,000~7,000 m) in northwest of Yunnan province, China, using a combination of Illumina short reads, PacBio long reads and Hi-C reads, with a contig N50 of 19.63 Mb and only six gaps. To further provide resources for gene annotation as well as functional and population genetics analyses, we sequenced transcriptomes of 20 major tissues of the WT individual and re-sequenced another 10 WT individuals and a blue eared pheasant (Crossoptilon auritum) individual inhabiting at intermediate altitudes (1,500~3,000 m). Our assembled WT genome, transcriptome data, and DNA sequencing data can be valuable resources for studying the biology, evolution and developing conservation strategies of these endangered species.

Chromosome-level genome assembly and annotation of the Yunling cattle with PacBio and Hi-C sequencing data

Yunling cattle is a new breed of beef cattle bred in Yunnan Province, China. It is bred by crossing the Brahman, the Murray Grey and the Yunnan Yellow cattle. Yunling cattle can adapt to the tropical and subtropical climate environment, and has good reproductive ability and growth speed under high temperature and high humidity conditions, it also has strong resistance to internal and external parasites and with good beef performance. In this study, we generated a high-quality chromosome-level genome assembly of a male Yunling cattle using a combination of short reads sequencing, PacBio HiFi sequencing and Hi-C scaffolding technologies. The genome assembly(3.09 Gb) is anchored to 31 chromosomes(29 autosomes plus one X and Y), with a contig N50 of 35.97 Mb and a scaffold N50 of 112.01 Mb. It contains 1.62 Gb of repetitive sequences and 20,660 protein-coding genes. This first construction of the Yunling cattle genome provides a valuable genetic resource that will facilitate further study of the genetic diversity of bovine species and accelerate Yunling cattle breeding efforts.

De Novo Genome Assembly of the Whitespot Parrotfish (Scarus forsteni): A Valuable Scaridae Genomic Resource

Scarus forsteni, a whitespot parrotfish from the Scaridae family, is a herbivorous fish inhabiting coral reef ecosystems. The deterioration of coral reefs has highly affected the habitats of the parrotfish. The decline in genetic diversity of parrotfish emphasizes the critical importance of conserving their genetic variability to ensure the resilience and sustainability of marine ecosystems for future generations. In this study, a genome of S. forsteni was assembled de novo through using Illumina and Nanopore sequencing. The 1.71-Gb genome of S. forsteni, was assembled into 544 contigs (assembly level: contig). It exhibited an N50 length of 17.97 Mb and a GC content percentage of 39.32%. Our BUSCO analysis revealed that the complete protein of the S. forsteni genome had 98.10% integrity. Combined with structure annotation data, 34,140 (74.81%) genes were functionally annotated out of 45,638 predicted protein-coding genes. Upon comparing the genome size and TE content of teleost fishes, a roughly linear relationship was observed between these two parameters. However, TE content is not a decisive factor in determining the genome size of S. forsteni. Population history analysis results indicate that S. forsteni experienced two major population expansions, both of which occurred before the last interglacial period. In addition, through a comparative genomic analysis of the evolutionary relationship of other species, it was found that S. forsteni had the closest relationship with Cheilinus undulatus, another member of the Labridae family. Our expansion and contraction analysis of the gene family showed that the expansion genes were mainly associated with immune diseases, organismal systems, and cellular processes. At the same time, cell transcription and translation, sex hormone regulation, and other related pathways were also more prominent in the positive selection genes. The genomic sequence of S. forsteni offers valuable resources for future investigations on the conservation, evolution, and behavior of fish species.

Chromosome-level genome assembly and annotation of rare and endangered tropical bivalve, Tridacna crocea

Tridacna crocea is an ecologically important marine bivalve inhabiting tropical coral reef waters. High quality and available genomic resources will help us understand the population structure and genetic diversity of giant clams. This study reports a high-quality chromosome-scale T. crocea genome sequence of 1.30 Gb, with a scaffold N50 and contig N50 of 56.38 Mb and 1.29 Mb, respectively, which was assembled by combining PacBio long reads and Hi-C sequencing data. Repetitive sequences cover 71.60% of the total length, and a total of 25,440 protein-coding genes were annotated. A total of 1,963 non-coding RNA (ncRNA) were determined in the T. crocea genome, including 62 micro RNA (miRNA), 58 small nuclear RNA (snRNA), 83 ribosomal RNA (rRNA), and 1,760 transfer RNA (tRNA). Phylogenetic analysis revealed that giant clams diverged from oyster about 505.7 Mya during the evolution of bivalves. The genome assembly presented here provides valuable genomic resources to enhance our understanding of the genetic diversity and population structure of giant clams.

Chromosome-scale genome assembly of Lepus oiostolus (Lepus, Leporidae)

Lepus oiostolus (L. oiostolus) is a species endemic to the Qinghai-Tibet Plateau. However, the absence of a reference genome limits genetic studies. Here, we reported a high-quality L. oiostolus genome assembly, with scaffolds anchored to 24 chromosomes and a total assembled length of 2.80 Gb (contig N50 = 64.25 Mb). Genomic annotation uncovered 22,295 protein-coding genes and identified 49.84% of the sequences as transposable elements. Long interspersed nuclear elements (LINEs) constitute a high proportion of the genome. Our study is at the first time to report the chromosome-scale genome for the species of the L. oiostolus. It provides a valuable genomic resource for future research on the evolution of the Leporidae.

A method to estimate the contribution of rare coding variants to complex trait heritability

It has been postulated that rare coding variants (RVs; MAF < 0.01) contribute to the "missing" heritability of complex traits. We developed a framework, the Rare variant heritability (RARity) estimator, to assess RV heritability (h2RV) without assuming a particular genetic architecture. We applied RARity to 31 complex traits in the UK Biobank (n = 167,348) and showed that gene-level RV aggregation suffers from 79% (95% CI: 68-93%) loss of h2RV. Using unaggregated variants, 27 traits had h2RV > 5%, with height having the highest h2RV at 21.9% (95% CI: 19.0-24.8%). The total heritability, including common and rare variants, recovered pedigree-based estimates for 11 traits. RARity can estimate gene-level h2RV, enabling the assessment of gene-level characteristics and revealing 11, previously unreported, gene-phenotype relationships. Finally, we demonstrated that in silico pathogenicity prediction (variant-level) and gene-level annotations do not generally enrich for RVs that over-contribute to complex trait variance, and thus, innovative methods are needed to predict RV functionality.

Chromosome level genome assembly of the Etruscan shrew Suncus etruscus

Suncus etruscus is one of the world's smallest mammals, with an average body mass of about 2 grams. The Etruscan shrew's small body is accompanied by a very high energy demand and numerous metabolic adaptations. Here we report a chromosome-level genome assembly using PacBio long read sequencing, 10X Genomics linked short reads, optical mapping, and Hi-C linked reads. The assembly is partially phased, with the 2.472 Gbp primary pseudohaplotype and 1.515 Gbp alternate. We manually curated the primary assembly and identified 22 chromosomes, including X and Y sex chromosomes. The NCBI genome annotation pipeline identified 39,091 genes, 19,819 of them protein-coding. We also identified segmental duplications, inferred GO term annotations, and computed orthologs of human and mouse genes. This reference-quality genome will be an important resource for research on mammalian development, metabolism, and body size control.

Two chromosome-level genomes of Smittia aterrima and Smittia pratorum (Diptera, Chironomidae)

Chironomids are one of the most abundant aquatic insects and are widely distributed in various biological communities. However, the lack of high-quality genomes has hindered our ability to study the evolution and ecology of this group. Here, we used Nanopore long reads and Hi-C data to produce two chromosome-level genomes from mixed genomic data. The genomes of Smittia aterrima (SateA) and Smittia pratorum (SateB) were assembled into three chromosomes, with sizes of 78.45 Mb and 71.56 Mb, scaffold N50 lengths of 25.73 and 23.53 Mb, and BUSCO completeness of 98.5% and 97.8% (n = 1,367), 5.68 Mb (7.24%) and 1.94 Mb (2.72%) of repetitive elements, and predicted 12,330 (97.70% BUSCO completeness) and 11,250 (97.40%) protein-coding genes, respectively. These high-quality genomes will serve as valuable resources for comprehending the evolution and environmental adaptation of chironomids.

Chromosome-level genome assembly of Acrossocheilus fasciatus using PacBio sequencing and Hi-C technology

Acrossocheilus fasciatus (Cypriniformes, Cyprinidae) is emerged as a newly commercial stream fish in the south of China with high economic and ornamental value. In this study, a chromosome-level reference genome of A. fasciatus was assembled using PacBio, Illumina and Hi-C sequencing technologies. As a result, a high-quality genome was generated with a size of 879.52 Mb (accession number: JAVLVS000000000), scaffold N50 of 32.7 Mb, and contig N50 of 32.7 Mb. The largest and smallest scafford was 60.57 Mb and 16 kb, respectively. BUSCO analysis showed a completeness score of 98.3%. Meanwhile, the assembled sequences were anchored to 25 pseudo-chromosomes with an integration efficiency of 96.95%. Additionally, we found approximately 390.91 Mb of repetitive sequences that accounting for 44.45% of the assembled genome, and predicted 24,900 protein-coding genes. The available genome reported in the present study provided a crucial resource to further investigate the regulation mechanism of genetic diversity, sexual dimorphism and evolutionary histories.

Chromosome-level genome assembly and annotation of eel goby (Odontamblyopus rebecca)

The eel gobies fascinate researchers with many important features, including its unique body structure, benthic lifestyle, and degenerated eyes. However, genome assembly and exploration of the unique genomic composition of the eel gobies are still in their infancy. This has severely limited research progress on gobies. In this study, multi-platform sequencing data were generated and used to assemble and annotate the genome of O. rebecca at the chromosome-level. The assembled genome size of O. rebecca is 918.57 Mbp, which is similar to the estimated genome size (903.03 Mbp) using 17-mer. The scaffold N50 is 41.67 Mbp, and 23 chromosomes were assembled using Hi-C technology with a mounting rate of 99.96%. Genome annotation indicates that 53.29% of the genome is repetitive sequences, and 22,999 protein-coding genes are predicted, of which 21,855 have functional annotations. The chromosome-level genome of O. rebecca will not only provide important genomic resources for comparative genomic studies of gobies, but also expand our knowledge of the genetic origin of their unique features fascinating researchers for decades.

Chromosome level genome assembly of endangered medicinal plant Anisodus tanguticus

Anisodus tanguticus is a medicinal herb that belongs to the Anisodus genus of the Solanaceae family. This endangered herb is mainly distributed in Qinghai-Tibet Plateau. In this study, we combined the Illumina short-read, Nanopore long-read and high-throughput chromosome conformation capture (Hi-C) sequencing technologies to de novo assemble the A. tanguticus genome. A high-quality chromosomal-level genome assembly was obtained with a genome size of 1.26 Gb and a contig N50 of 25.07 Mb. Of the draft genome sequences, 97.47% were anchored to 24 pseudochromosomes with a scaffold N50 of 51.28 Mb. In addition, 842.14 Mb of transposable elements occupying 66.70% of the genome assembly were identified and 44,252 protein-coding genes were predicted. The genome assembly of A. tanguticus will provide genetic repertoire to understand the adaptation strategy of Anisodus species in the plateau, which will further promote the conservation of endangered A. tanguticus resources.

Reference transcriptome assembly of a protogynous sex change fish, harlequin sandsmelt (Parapercis pulchella)

The harlequin sandsmelt (Parapercis pulchella) is a female-to-male sex change fish in which functional females possess ovotestes that consist of both ovarian and testicular tissues. These features indicate that this species could be an excellent model for studying the flexibility of sex differentiation in vertebrates. However, genetic resources in this species have so far been limited. Therefore, in this study, the reference transcriptome of this fish was constructed through RNA-sequencing, de novo transcriptome assembly, superTranscripts construction, and functional annotations. To obtain as many genes as possible, RNA was extracted from various tissues (brains, gills, hearts, livers, guts, and gonads) and various sexual stages (females, individuals during sex change, and males) and then subjected to sequencing and downstream analyses. As a result, 91,884 representative transcripts with 32,627 protein-coding sequences were generated. 72.2% of protein-coding sequences (23,566 sequences) were functionally annotated. Also, our analysis shows that the superTranscripts method effectively removes redundant sequences from raw-assembled data compared with other strategies. The resultant dataset is a valuable resource for future molecular developmental studies on sex change in P. pulchella.

Genome assembly and microsatellite marker development using Illumina and PacBio sequencing in Persicaria maackiana (Polygonaceae) from Korea

BACKGROUND

Persicaria maackiana (Regel) is a potential medicinal plant that exerts anti-diabetic effects. However, the lack of genomic information on P. maackiana hinders research at the molecular level.

OBJECTIVE

Herein, we aimed to construct a draft genome assembly and obtain comprehensive genomic information on P. maackiana using high-throughput sequencing tools PacBio Sequel II and Illumina.

METHODS

Persicaria maackiana samples from three natural populations in Gaecheon, Gichi, and Uiryeong reservoirs in South Korea were used to generate genomic DNA libraries, perform genome de novo assembly, gene ontology analysis, phylogenetic tree analysis, genotyping, and identify microsatellite markers.

RESULTS

The assembled P. maackiana genome yielded 32,179 contigs. Assessment of assembly integrity revealed 1503 (93.12%) complete Benchmarking Universal Single-Copy Orthologs. A total of 64,712 protein-coding genes were predicted and annotated successfully in the protein database. In the Kyoto Encyclopedia of Genes and Genomes (KEGG) orthologs, 13,778 genes were annotated into 18 categories. Genes that activated AMPK were identified in the KEGG pathway. A total of 316,992 microsatellite loci were identified, and primers targeting the flanking regions were developed for 292,059 microsatellite loci. Of these, 150 primer sets were randomly selected for amplification, and 30 of these primer sets were identified as polymorphic. These primers amplified 3-9 alleles. The mean observed and expected heterozygosity were 0.189 and 0.593, respectively. Polymorphism information content values of the markers were 0.361-0.754.

CONCLUSION

Collectively, our study provides a valuable resource for future comparative genomics, phylogeny, and population studies of P. maackiana.

NCAD v1.0: a database for non-coding variant annotation and interpretation

The application of whole genome sequencing is expanding in clinical diagnostics across various genetic disorders, and the significance of non-coding variants in penetrant diseases is increasingly being demonstrated. Therefore, it is urgent to improve the diagnostic yield by exploring the pathogenic mechanisms of variants in non-coding regions. However, the interpretation of non-coding variants remains a significant challenge, due to the complex functional regulatory mechanisms of non-coding regions and the current limitations of available databases and tools. Hence, we develop the non-coding variant annotation database (NCAD, http://www.ncawdb.net/), encompassing comprehensive insights into 665,679,194 variants, regulatory elements, and element interaction details. Integrating data from 96 sources, spanning both GRCh37 and GRCh38 versions, NCAD v1.0 provides vital information to support the genetic diagnosis of non-coding variants, including allele frequencies of 12 diverse populations, with a particular focus on the population frequency information for 230,235,698 variants in 20,964 Chinese individuals. Moreover, it offers prediction scores for variant functionality, five categories of regulatory elements, and four types of non-coding RNAs. With its rich data and comprehensive coverage, NCAD serves as a valuable platform, empowering researchers and clinicians with profound insights into non-coding regulatory mechanisms while facilitating the interpretation of non-coding variants.

Whole-genome sequence and characterization of a marine red yeast, Rhodosporidium sphaerocarpum GDMCC 60679, featuring the assimilation of ammonia nitrogen

A marine red yeast, Rhodosporidium sphaerocarpum, is generally used for the production of lipids and carotenoids. In a previous study, we demonstrated that a marine-derived R. sphaerocarpum GDMCC 60679 can efficiently remove ammonia nitrogen and exhibit multiple probiotic functions for shrimp, Litopenaeus vannamei. Here, we performed a genome assembly of the strain GDMCC 60679 using a combination of the data from Illumina PE and PacBio CLR reads. The genome has a size of 18.03 Mb and consists of 32 contigs with an N50 length of 1,074,774 bp and GC content of 63 %. The genome was predicted to contain 6092 protein-coding genes, 5962 of which were functionally annotated. Metabolic pathways responsible for the ammonia assimilation and the synthesis of lipids and carotenoids were particularly examined to explore and characterize genes contributing to these functions. Whole-genome sequence and annotation of the strain lays a foundation to reveal the molecular mechanism of its prominent biological functions and will facilitate us to further expand new applications of yeasts in Rhodosporidium.

A Chromosome-Level Genome Assembly and Annotation for the Clouded Apollo Butterfly (Parnassius mnemosyne): A Species of Global Conservation Concern

The clouded apollo (Parnassius mnemosyne) is a palearctic butterfly distributed over a large part of western Eurasia, but population declines and fragmentation have been observed in many parts of the range. The development of genomic tools can help to shed light on the genetic consequences of the decline and to make informed decisions about direct conservation actions. Here, we present a high-contiguity, chromosome-level genome assembly of a female clouded apollo butterfly and provide detailed annotations of genes and transposable elements. We find that the large genome (1.5 Gb) of the clouded apollo is extraordinarily repeat rich (73%). Despite that, the combination of sequencing techniques allowed us to assemble all chromosomes (nc = 29) to a high degree of completeness. The annotation resulted in a relatively high number of protein-coding genes (22,854) compared with other Lepidoptera, of which a large proportion (21,635) could be assigned functions based on homology with other species. A comparative analysis indicates that overall genome structure has been largely conserved, both within the genus and compared with the ancestral lepidopteran karyotype. The high-quality genome assembly and detailed annotation presented here will constitute an important tool for forthcoming efforts aimed at understanding the genetic consequences of fragmentation and decline, as well as for assessments of genetic diversity, population structure, inbreeding, and genetic load in the clouded apollo butterfly.

AnnoPRO: a strategy for protein function annotation based on multi-scale protein representation and a hybrid deep learning of dual-path encoding

Protein function annotation has been one of the longstanding issues in biological sciences, and various computational methods have been developed. However, the existing methods suffer from a serious long-tail problem, with a large number of GO families containing few annotated proteins. Herein, an innovative strategy named AnnoPRO was therefore constructed by enabling sequence-based multi-scale protein representation, dual-path protein encoding using pre-training, and function annotation by long short-term memory-based decoding. A variety of case studies based on different benchmarks were conducted, which confirmed the superior performance of AnnoPRO among available methods. Source code and models have been made freely available at: https://github.com/idrblab/AnnoPRO and https://zenodo.org/records/10012272.

Functional annotation of insecta transcriptomes: A cautionary tale from Lepidoptera

Functional annotation is a critical step in the analysis of genomic data, as it provides insight into the function of individual genes and the pathways in which they participate. Currently, there is no consensus on the best computational approach for assigning functional annotation. This study compares three functional annotation methods (BLAST, eggNOG-Mapper, and InterProScan) in their ability to assign Gene Ontology terms in two species of Insecta with differing levels of annotation, Bombyx mori and Manduca sexta. The methods were compared for their annotation coverage, number of term assignments, term agreement and non-overlapping terms. Here we show that there are large discrepancies in gene ontology term assignment among the three computational methods, which could lead to confounding interpretations of data and non-comparable results. This study provide insight into the strengths and weaknesses of each computational method and highlight the need for more standardized methods of functional annotation.

FunPredCATH: An ensemble method for predicting protein function using CATH

MOTIVATION

The growth of unannotated proteins in UniProt increases at a very high rate every year due to more efficient sequencing methods. However, the experimental annotation of proteins is a lengthy and expensive process. Using computational techniques to narrow the search can speed up the process by providing highly specific Gene Ontology (GO) terms.

METHODOLOGY

We propose an ensemble approach that combines three generic base predictors that predict Gene Ontology (BP, CC and MF) terms from sequences across different species. We train our models on UniProtGOA annotation data and use the CATH domain resources to identify the protein families. We then calculate a score based on the prevalence of individual GO terms in the functional families that is then used as an indicator of confidence when assigning the GO term to an uncharacterised protein.

METHODS

In the ensemble, we use a statistics-based method that scores the occurrence of GO terms in a CATH FunFam against a background set of proteins annotated by the same GO term. We also developed a set-based method that uses Set Intersection and Set Union to score the occurrence of GO terms within the same CATH FunFam. Finally, we also use FunFams-Plus, a predictor method developed by the Orengo Group at UCL to predict GO terms for uncharacterised proteins in the CAFA3 challenge.

EVALUATION

We evaluated the methods against the CAFA3 benchmark and DomFun. We used the Precision, Recall and Fmax metrics and the benchmark datasets that are used in CAFA3 to evaluate our models and compare them to the CAFA3 results. Our results show that FunPredCATH compares well with top CAFA methods in the different ontologies and benchmarks.

CONTRIBUTIONS

FunPredCATH compares well with other prediction methods on CAFA3, and the ensemble approach outperforms the base methods. We show that non-IEA models obtain higher Fmax scores than the IEA counterparts, while the models including IEA annotations have higher coverage at the expense of a lower Fmax score.

Chromosome-level genome assembly and annotation of the yellow grouper, Epinephelus awoara

Epinephelus awoara, as known as yellow grouper, is a significant economic marine fish that has been bred artificially in China. However, the genetic structure and evolutionary history of yellow grouper remains largely unknown. Here, this work presents the high-quality chromosome-level genome assembly of yellow grouper using PacBio single molecule sequencing technique (SMRT) and High-through chromosome conformation capture (Hi-C) technologies. The 984.48 Mb chromosome-level genome of yellow grouper was assembled, with a contig N50 length of 39.77 Mb and scaffold N50 length of 41.39 Mb. Approximately 99.76% of assembled sequences were anchored into 24 pseudo-chromosomes with the assistance of Hi-C reads. Furthermore, approximately 41.17% of the genome was composed of repetitive elements. In total, 24,541 protein-coding genes were predicted, of which 22,509 (91.72%) genes were functionally annotated. The highly accurate, chromosome-level reference genome assembly and annotation are crucial to the understanding of population genetic structure, adaptive evolution and speciation of the yellow grouper.

Genomic insights into the endangered white-eared night heron (Gorsachius magnificus)

OBJECTIVES

A genome sequence of a threatened species can provide valuable genetic information that is important for improving the conservation strategies. The white-eared night heron (Gorsachius magnificus) is an endangered and poorly known ardeid bird. In order to support future studies on conservation genetics and evolutionary adaptation of this species, we have reported a de novo assembled and annotated whole-genome sequence of the G. magnificus.

DATA DESCRIPTION

The final draft genome assembly of the G. magnificus was 1.19 Gb in size, with a contig N50 of 187.69 kb and a scaffold N50 of 7,338.28 kb. According to BUSCO analysis, the genome assembly contained 97.49% of the 8,338 genes in the Aves (odb10) dataset. Approximately 10.52% of the genome assembly was composed of repetitive sequences. A total of 14,613 protein-coding genes were predicted in the genome assembly, with functional annotations available for 14,611 genes. The genome assembly exhibited a heterozygosity rate of 0.49 heterozygosity per kilobase pair. This draft genome of G. magnificus provides valuable genomic resources for future studies on conservation and evolution.

Chromosome-level genome assembly of Hippophae gyantsensis

Hippophae gyantsensis, which is a native tree species in China, is ideal for windbreak and sand-fixing forests. It is an economically and ecologically valuable tree species distributed exclusively in the Qinghai-Tibet Plateau in China. In our study, we assembled a chromosome-level genome of H. gyantsensis using Illumina sequencing, Nanopore sequencing and chromosome structure capture technique. The genome was 716.32 Mb in size with scaffold N50 length of 64.84 Mb. A total of 716.25 Mb genome data was anchored and orientated onto 12 chromosomes with a mounting rate of up to 99.99%. Additionally, the genome was found to comprise approximately 56.84% repeat sequences, of which long terminal repeats(LTRs) that accounted for 33.19% of the entire genome. Meanwhile, a total of 32,316 protein-coding genes were predicted, and 91.07% of these genes were functionally annotated. We also completed a series of comparative genomic analyses to provide researchers with useful reference material for future studies on seabuckthorn.

A chromosome-level genome assembly of a deep-sea symbiotic Aplacophora mollusc Chaetoderma sp

The worm-shaped, shell-less Caudofoveata is one of the least known groups of molluscs. As early-branching molluscs, the lack of high-quality genomes hinders our understanding of their evolution and ecology. Here, we report a high-quality chromosome-scale genome of Chaetoderma sp. combining PacBio, Illumina, and high-resolution chromosome conformation capture sequencing. The final assembly has a size of 2.45 Gb, with a scaffold N50 length of 141.46 Mb, and is anchored to 17 chromosomes. Gene annotations showed a high level of accuracy and completeness, with 23,675 predicted protein-coding genes and 94.44% of the metazoan conserved genes by BUSCO assessment. We further present 16S rRNA gene amplicon sequencing of the gut microbiota in Chaetoderma sp., which was dominated by the chemoautotrophic bacteria (phylum Gammaproteobacteria). This chromosome-level genome assembly presents the first genome for the Caudofoveata, which constitutes an important resource for studies ranging from molluscan evolution, symposium, to deep-sea adaptation.

scMMT: a multi-use deep learning approach for cell annotation, protein prediction and embedding in single-cell RNA-seq data

Accurate cell type annotation in single-cell RNA-sequencing data is essential for advancing biological and medical research, particularly in understanding disease progression and tumor microenvironments. However, existing methods are constrained by single feature extraction approaches, lack of adaptability to immune cell types with similar molecular profiles but distinct functions and a failure to account for the impact of cell label noise on model accuracy, all of which compromise the precision of annotation. To address these challenges, we developed a supervised approach called scMMT. We proposed a novel feature extraction technique to uncover more valuable information. Additionally, we constructed a multi-task learning framework based on the GradNorm method to enhance the recognition of challenging immune cells and reduce the impact of label noise by facilitating mutual reinforcement between cell type annotation and protein prediction tasks. Furthermore, we introduced logarithmic weighting and label smoothing mechanisms to enhance the recognition ability of rare cell types and prevent model overconfidence. Through comprehensive evaluations on multiple public datasets, scMMT has demonstrated state-of-the-art performance in various aspects including cell type annotation, rare cell identification, dropout and label noise resistance, protein expression prediction and low-dimensional embedding representation.

Partial order relation-based gene ontology embedding improves protein function prediction

Protein annotation has long been a challenging task in computational biology. Gene Ontology (GO) has become one of the most popular frameworks to describe protein functions and their relationships. Prediction of a protein annotation with proper GO terms demands high-quality GO term representation learning, which aims to learn a low-dimensional dense vector representation with accompanying semantic meaning for each functional label, also known as embedding. However, existing GO term embedding methods, which mainly take into account ancestral co-occurrence information, have yet to capture the full topological information in the GO-directed acyclic graph (DAG). In this study, we propose a novel GO term representation learning method, PO2Vec, to utilize the partial order relationships to improve the GO term representations. Extensive evaluations show that PO2Vec achieves better outcomes than existing embedding methods in a variety of downstream biological tasks. Based on PO2Vec, we further developed a new protein function prediction method PO2GO, which demonstrates superior performance measured in multiple metrics and annotation specificity as well as few-shot prediction capability in the benchmarks. These results suggest that the high-quality representation of GO structure is critical for diverse biological tasks including computational protein annotation.