What Makes Us Human: Insights from the Evolution and Development of the Human Neocortex.

"What makes us human?" is a central question of many research fields, notably anthropology. In this review, we focus on the development of the human neocortex, the part of the brain with a key role in cognition, to gain neurobiological insight toward answering this question. We first discuss cortical stem and progenitor cells and human-specific genes that affect their behavior. We thus aim to understand the molecular foundation of the expansion of the neocortex that occurred in the course of human evolution, as this expansion is generally thought to provide a basis for our unique cognitive abilities. We then review the emerging evidence pointing to differences in the development of the neocortex between present-day humans and Neanderthals, our closest relatives. Finally, we discuss human-specific genes that have been implicated in neuronal circuitry and offer a perspective for future studies addressing the question of what makes us human.

scCTS: identifying the cell type-specific marker genes from population-level single-cell RNA-seq.

Single-cell RNA-sequencing (scRNA-seq) provides gene expression profiles of individual cells from complex samples, facilitating the detection of cell type-specific marker genes. In scRNA-seq experiments with multiple donors, the population level variation brings an extra layer of complexity in cell type-specific gene detection, for example, they may not appear in all donors. Motivated by this observation, we develop a statistical model named scCTS to identify cell type-specific genes from population-level scRNA-seq data. Extensive data analyses demonstrate that the proposed method identifies more biologically meaningful cell type-specific genes compared to traditional methods.

Computational recognition of regulator genes and signature for ferroptosis with implications on immunological properties and clinical management of atopic dermatitis.

Background: Atopic dermatitis (AD) is a common chronic dermatitis of autoimmune origin that considerably affects the quality of life of patients. Ferroptosis, a newly regulated form of cell death, is essential for inflammation-related damage-associated molecular patterns (DAMPs). In this study, we aimed to identify ferroptosis regulators relevant to AD pathogenesis and reveal the mechanisms by which ferroptosis regulates the pathogenesis of AD. Methods: We analyzed the GEO AD cohorts (GSE16161, GSE32924, GSE107361, and GSE120721), identifying AD-related differentially expressed genes (DEGs) using edgeR. Co-expression and STRING database analyses were used to elucidate the interactions between DEGs and ferroptosis markers. Through functional enrichment analysis, we defined potential biological functions within the protein-protein interaction (PPI) network and developed FerrSig using LASSO regression. The utility of FerrSig in guiding the clinical management of AD was evaluated using the GSE32473 cohort. Subsequently, our in silico findings were confirmed, and mechanistic insights were expanded through both in vitro and in vivo studies, validating the relevance of FerrSig. Results: In the GEO AD cohort, 278 DEGs were identified, including seven ferroptosis signature genes. Co-expression analysis and STRING database review revealed a 63-node PPI network linked to cell cycle and pro-inflammatory pathways. Four ferroptosis genes (ALOXE3, FABP4, MAP3K14, and EGR1) were selected to create FerrSig, which was significantly downregulated in samples collected from patients with AD. In addition, immune-related signaling pathways were significantly differentially enriched between the stratifications of samples collected from patients with AD with high and low ferritin levels, whereas in the GSE32473 cohort, FerrSig was significantly increased in cohorts effectively treated with pimecrolimus or betamethasone. Finally, in vitro and in vivo models showed a notable FerrSig decrease in patients with AD versus healthy control. Treatment with betamethasone and tacrolimus restored FerrSig, and the magnitude of the increase in FerrSig was higher in samples collected from patients with AD with better efficacy assessments. In addition, FerrSig was significantly positively correlated with the ferroptosis inhibitors GPX4 and SLC7A11 and negatively correlated with reactive oxygen species (ROS) levels and p-STAT3/STAT3. This implies that the FerrSig signature genes may regulate ferroptosis through the JAK/STAT3 signaling pathway. Conclusion: Our study further explored the pathogenesis of AD, and FerrSig could serve as a potential biomarker for identifying AD morbidity risks and determining treatment efficacy.

Expression patterns of housekeeping genes and tissue-specific genes in black goats across multiple tissues.

Black goats are a significant meat breed in southern China. To investigate the expression patterns and biological functions of genes in various tissues of black goats, we analyzed housekeeping genes (HKGs), tissue-specific genes (TSGs), and hub genes (HUBGs) across 23 tissues. Additionally, we analyzed HKGs in 13 tissues under different feeding conditions. We identified 2968 HKGs, including six important ones. Interestingly, HKGs in grazing black goats demonstrated higher and more stable expression levels. We discovered a total of 9912 TSGs, including 134 newly identified ones. The number of TSGs for mRNA and lncRNA were nearly equal, with 127 mRNA TSGs expressed solely in one tissue. Additionally, the predicted functions of tissue-specific long non-coding RNAs (lncRNAs) targeting mRNAs corresponded with the physiological functions of the tissues.Weighted gene co-expression network analysis (WGCNA) constructed 30 modules, where the dark grey module consists almost entirely of HKGs, and TSGs are located in modules most correlated with their respective tissues. Additionally, we identified 289 HUBGs, which are involved in regulating the physiological functions of their respective tissues. Overall, these identified HKGs, TSGs, and HUBGs provide a foundation for studying the molecular mechanisms affecting the genetic and biological processes of complex traits in black goats.

Pan-genome analysis reveals novel chromosomal markers for multiplex PCR-based specific detection of Bacillus anthracis.

BACKGROUND: Bacillus anthracis is a highly pathogenic bacterium that can cause lethal infection in animals and humans, making it a significant concern as a pathogen and biological agent. Consequently, accurate diagnosis of B. anthracis is critically important for public health. However, the identification of specific marker genes encoded in the B. anthracis chromosome is challenging due to the genetic similarity it shares with B. cereus and B. thuringiensis. METHODS: The complete genomes of B. anthracis, B. cereus, B. thuringiensis, and B. weihenstephanensis were de novo annotated with Prokka, and these annotations were used by Roary to produce the pan-genome. B. anthracis exclusive genes were identified by Perl script, and their specificity was examined by nucleotide BLAST search. A local BLAST alignment was performed to confirm the presence of the identified genes across various B. anthracis strains. Multiplex polymerase chain reactions (PCR) were established based on the identified genes. RESULT: The distribution of genes among 151 whole-genome sequences exhibited three distinct major patterns, depending on the bacterial species and strains. Further comparative analysis between the three groups uncovered thirty chromosome-encoded genes exclusively present in B. anthracis strains. Of these, twenty were found in known lambda prophage regions, and ten were in previously undefined region of the chromosome. We established three distinct multiplex PCRs for the specific detection of B. anthracis by utilizing three of the identified genes, BA1698, BA5354, and BA5361. CONCLUSION: The study identified thirty chromosome-encoded genes specific to B. anthracis, encompassing previously described genes in known lambda prophage regions and nine newly discovered genes from an undefined gene region to the best of our knowledge. Three multiplex PCR assays offer an accurate and reliable alternative method for detecting B. anthracis. Furthermore, these genetic markers have value in anthrax vaccine development, and understanding the pathogenicity of B. anthracis.

Screening Wheat Genotypes for Specific Genes Linked to Drought Tolerance.

Drought stress, which significantly affects growth and reduces grain yield, is one of the main problems for wheat crops. Producing promising drought-tolerant wheat cultivars with high yields is one of the main targets for wheat breeders. In this study, a total of seven drought-tolerant wheat genotypes were screened for the presence of 19 specific drought tolerance genes. The genotypes were tested under normal and drought conditions for two growing seasons. Four spike traits, namely, spike length (SPL), grain number per spike (GNPS), number of spikelets per spike (NSPS), and grain yield per spike (GYPS), were scored. The results revealed that drought stress decreased the SPL, GNPS, NSPS, and GYPS, with ranges ranging from 2.14 (NSPS) to 13.92% (GNPS) and from 2.40 (NSPS) to 11.09% (GYPS) in the first and second seasons, respectively. ANOVA revealed high genetic variation among the genotypes for each trait under each treatment. According to the drought tolerance indices, Omara 007 presented the highest level of drought tolerance (average of sum ranks = 3), whereas both Giza-36 genotypes presented the lowest level of drought tolerance (average of sum ranks = 4.8) among the genotypes tested. Among the 19 genes tested, 11 were polymorphic among the selected genotypes. Omara 007 and Omara 002 presented the greatest number of specific drought tolerance genes (nine) tested in this study, whereas Sohag-5, Giza-36, and PI469072 presented the lowest number of drought tolerance genes (four). The number of different genes between each pair of genotypes was calculated. Seven different genes were found between Omara 007 and Giza-36, Omara 007 and Sohag-5, and Omara 002 and PI469072. The results of this study may help to identify the best genotypes for crossing candidate genotypes, and not merely to genetically improve drought tolerance in wheat.

Transposable elements contribute to tissue-specific gene regulation in humans.

BACKGROUND: Transposable elements (TEs) contribute to approximately half of the human genome, and along with many other functions, they have been known to play a role in gene regulation in the genome. With TEs' active/repressed states varying across tissue and cell types, they have the potential to regulate gene expression in a tissue-specific manner. OBJECTIVE AND METHODS: To provide a systematic analysis of TEs' contribution in tissue-specific gene regulation, we examined the regulatory elements and genes in association with TE-derived regulatory sequences in 14 human cell lines belonging to 10 different tissue types using the functional genomics data from the ENCODE project. Specifically, we separately analyzed regulatory regions identified by three different approaches (DNase hypersensitive sites (DHS), histone active sites (HA), and histone repressive sites (HR)). RESULTS: These regulatory regions showed to be distinct from each other by sharing less than 2.5% among all three types and more than 95% showed to be cell line-specific. Despite a lower total TE content overall than the genome average, each regulatory sequence type showed enrichment for one or two specific TE type(s): DHS for long terminal repeats (LTRs) and DNA transposons, HA for short interspersed nucleotide elements (SINEs), and HR for LTRs. In contrast, SINE was shown to be overrepresented in all three types of regulatory sequences located in gene-neighboring regions. TE-regulated genes were mostly shown to have cell line specific pattern, and tissue-specific genes (TSGs) showed higher usage of TE regulatory sequences in the tissue of their expression. While TEs in the regulatory sequences showed to be older than their genome-wide counterparts, younger TEs were shown to be more likely used in cell line specific regulatory sequences. CONCLUSIONS: Collectively, our study provided further evidence enforcing an important contribution of TEs to tissue-specific gene regulation in humans.

A Comparative Full-Length Transcriptome Analysis Using Oxford Nanopore Technologies (ONT) in Four Tissues of Bovine Origin.

The transcriptome complexity and splicing patterns in male and female cattle are ambiguous, presenting a substantial obstacle to genomic selection programs that seek to improve productivity, disease resistance, and reproduction in cattle. A comparative transcriptomic analysis using Oxford Nanopore Technologies (ONT) was conducted in bovine testes (TESTs), ovaries (OVAs), muscles (MUSCs), and livers (LIVs). An average of 5,144,769 full-length reads were obtained from each sample. The TESTs were found to have the greatest number of alternative polyadenylation (APA) events involved in processes such as sperm flagellum development and fertilization in male reproduction. In total, 438 differentially expressed transcripts (DETs) were identified in the LIVs in a comparison of females vs. males, and 214 DETs were identified in the MUSCs between females and males. Additionally, 14,735, 36,347, and 33,885 DETs were detected in MUSC vs. LIV, MUSC vs. TEST, and OVA vs. TEST comparisons, respectively, revealing the complexity of the TEST. Gene Set Enrichment Analysis (GSEA) showed that these DETs were mainly involved in the "spermatogenesis", "flagellated sperm motility", "spermatid development", "reproduction", "reproductive process", and "microtubule-based movement" KEGG pathways. Additional studies are necessary to further characterize the transcriptome in different cell types, developmental stages, and physiological conditions in bovines and ascertain the functions of the novel transcripts.

Transcriptomic Analysis Reveals Adaptive Evolution and Conservation Implications for the Endangered Magnolia lotungensis.

Magnolia lotungensis is an extremely endangered endemic tree in China. To elucidate the genetic basis of M. lotungensis, we performed a comprehensive transcriptome analysis using a sample integrating the plant's bark, leaves, and flowers. De novo transcriptome assembly yielded 177,046 transcripts and 42,518 coding sequences. Notably, we identified 796 species-specific genes enriched in organelle gene regulation and defense responses. A codon usage bias analysis revealed that mutation bias appears to be the primary driver of selection in shaping the species' genetic architecture. An evolutionary analysis based on dN/dS values of paralogous and orthologous gene pairs indicated a predominance of purifying selection, suggesting strong evolutionary constraints on most genes. A comparative transcriptomic analysis with Magnolia sinica identified approximately 1000 ultra-conserved genes, enriched in essential cellular processes such as transcriptional regulation, protein synthesis, and genome stability. Interestingly, only a limited number of 511 rapidly evolving genes under positive selection were detected compared to M. sinica and Magnolia kuangsiensis. These genes were enriched in metabolic processes associated with adaptation to specific environments, potentially limiting the species' ability to expand its range. Our findings contribute to understanding the genetic architecture of M. lotungensis and suggest that an insufficient number of adaptive genes contribute to its endangered status.

Tight Junction Component Occludin Binds to FIP5 to Regulate Endosome Trafficking and Mitotic Spindle Function.

The genetic basis of vertebrate emergence during metazoan evolution has remained largely unknown. Understanding vertebrate-specific genes, such as the tight junction protein Occludin (Ocln), may help answer this question. Here, it is shown that mammary glands lacking Ocln exhibit retarded epithelial branching, owing to reduced cell proliferation and surface expansion. Interestingly, Ocln regulates mitotic spindle orientation and function, and its loss leads to a range of defects, including prolonged prophase and failed nuclear and/or cytoplasmic division. Mechanistically, Ocln binds to the RabGTPase-11 adaptor FIP5 and recruits recycling endosomes to the centrosome to participate in spindle assembly and function. FIP5 loss recapitulates Ocln null, leading to prolonged prophase, reduced cell proliferation, and retarded epithelial branching. These results identify a novel role in OCLN-mediated endosomal trafficking and potentially highlight its involvement in mediating membranous vesicle trafficking and function, which is evolutionarily conserved and essential.

Identification and validation of a novel predictive signature based on hepatocyte-specific genes in hepatocellular carcinoma by integrated analysis of single-cell and bulk RNA sequencing.

BACKGROUND: Hepatocellular carcinoma represents a significant global burden in terms of cancer-related mortality, posing a substantial risk to human health. Despite the availability of various treatment modalities, the overall survival rates for patients with hepatocellular carcinoma remain suboptimal. The objective of this study was to explore the potential of novel biomarkers and to establish a novel predictive signature utilizing multiple transcriptome profiles. METHODS: The GSE115469 and CNP0000650 cohorts were utilized for single cell analysis and gene identification. The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets were utilized in the development and evaluation of a predictive signature. The expressions of hepatocyte-specific genes were further validated using the GSE135631 cohort. Furthermore, immune infiltration results, immunotherapy response prediction, somatic mutation frequency, tumor mutation burden, and anticancer drug sensitivity were analyzed based on various risk scores. Subsequently, functional enrichment analysis was performed on the differential genes identified in the risk model. Moreover, we investigated the expression of particular genes in chronic liver diseases utilizing datasets GSE135251 and GSE142530. RESULTS: Our findings revealed hepatocyte-specific genes (ADH4, LCAT) with notable alterations during cell maturation and differentiation, leading to the development of a novel predictive signature. The analysis demonstrated the efficacy of the model in predicting outcomes, as evidenced by higher risk scores and poorer prognoses in the high-risk group. Additionally, a nomogram was devised to forecast the survival rates of patients at 1, 3, and 5 years. Our study demonstrated that the predictive model may play a role in modulating the immune microenvironment and impacting the anti-tumor immune response in hepatocellular carcinoma. The high-risk group exhibited a higher frequency of mutations and was more likely to benefit from immunotherapy as a treatment option. Additionally, we confirmed that the downregulation of hepatocyte-specific genes may indicate the progression of hepatocellular carcinoma and aid in the early diagnosis of the disease. CONCLUSION: Our research findings indicate that ADH4 and LCAT are genes that undergo significant changes during the differentiation of hepatocytes into cancer cells. Additionally, we have created a unique predictive signature based on genes specific to hepatocytes.

PLS-based gene subset augmentation and tumor-specific gene identification.

In the study of tumor disease pathogenesis, the identification of genes specifically expressed in disease states is pivotal, yet challenges arise from high-dimensional datasets with limited samples. Conventional gene (feature) selection methods often fall short of capturing the complexity of gene-phenotype and gene-gene interactions, necessitating a more robust analysis method. To address these challenges, a gene subset augmentation strategy is proposed in this paper. Our approach introduces diverse perturbation mechanisms to generate distinct gene subsets. The partial least squares-based multiple gene measurement algorithm considers gene-phenotype and gene-gene correlations, identifying differentially expressed genes, including those with weak signals. The constructed gene networks derived from the augmented subsets unveil regulatory patterns, enabling association analysis to explore gene associations comprehensively. Our algorithm excels in identifying small-sized gene subsets with strong discriminative power, surpassing traditional methods that yield a single gene subset. Unlike conventional approaches, our algorithm reveals a spectrum of different gene subsets and their weakly differentially expressed genes. This nuanced perspective aids in unraveling the molecular characteristics and specific expression patterns of tumor genes. The versatility of our approach not only contributes to the advancement of tumor-specific gene identification but also holds promise for addressing challenges in various fields characterized by high-dimensional datasets and limited samples. The Python implementation is available at http://github.com/wenjieyou/PLSGSA.

Analysis of twelve genomes of the bacterium Kerstersia gyiorum from brown-throated sloths (Bradypus variegatus), the first from a non-human host.

Kerstersia gyiorum is a Gram-negative bacterium found in various animals, including humans, where it has been associated with various infections. Knowledge of the basic biology of K. gyiorum is essential to understand the evolutionary strategies of niche adaptation and how this organism contributes to infectious diseases; however, genomic data about K. gyiorum is very limited, especially from non-human hosts. In this work, we sequenced 12 K. gyiorum genomes isolated from healthy free-living brown-throated sloths (Bradypus variegatus) in the Parque Estadual das Fontes do Ipiranga (São Paulo, Brazil), and compared them with genomes from isolates of human origin, in order to gain insights into genomic diversity, phylogeny, and host specialization of this species. Phylogenetic analysis revealed that these K. gyiorum strains are structured according to host. Despite the fact that sloth isolates were sampled from a single geographic location, the intra-sloth K. gyiorum diversity was divided into three clusters, with differences of more than 1,000 single nucleotide polymorphisms between them, suggesting the circulation of various K. gyiorum lineages in sloths. Genes involved in mobilome and defense mechanisms against mobile genetic elements were the main source of gene content variation between isolates from different hosts. Sloth-specific K. gyiorum genome features include an IncN2 plasmid, a phage sequence, and a CRISPR-Cas system. The broad diversity of defense elements in K. gyiorum (14 systems) may prevent further mobile element flow and explain the low amount of mobile genetic elements in K. gyiorum genomes. Gene content variation may be important for the adaptation of K. gyiorum to different host niches. This study furthers our understanding of diversity, host adaptation, and evolution of K. gyiorum, by presenting and analyzing the first genomes of non-human isolates.

The genome of Citrus australasica reveals disease resistance and other species specific genes.

BACKGROUND: The finger lime (Citrus australasica), one of six Australian endemic citrus species shows a high natural phenotypic diversity and novel characteristics. The wide variation and unique horticultural features have made this lime an attractive candidate for domestication. Currently no haplotype resolved genome is available for this species. Here we present a high quality, haplotype-resolved reference genome for this species using PacBio HiFi and Hi-C sequencing. RESULTS: Hifiasm assembly and SALSA scaffolding resulted in a collapsed genome size of 344.2 Mb and 321.1 Mb and 323.2 Mb size for the two haplotypes. The nine pseudochromosomes of the collapsed genome had an N50 of 35.2 Mb, 99.1% genome assembly completeness and 98.9% gene annotation completeness (BUSCO). A total of 41,304 genes were predicted in the nuclear genome. Comparison with C. australis revealed that 13,661 genes in pseudochromosomes were unique in C. australasica. These were mainly involved in plant-pathogen interactions, stress response, cellular metabolic and developmental processes, and signal transduction. The two genomes showed a syntenic arrangement at the chromosome level with large structural rearrangements in some chromosomes. Genetic variation among five C. australasica cultivars was analysed. Genes related to defense, synthesis of volatile compounds and red/yellow coloration were identified in the genome. A major expansion of genes encoding thylakoid curvature proteins was found in the C. australasica genome. CONCLUSIONS: The genome of C. australasica present in this study is of high quality and contiguity. This genome helps deepen our understanding of citrus evolution and reveals disease resistance and quality related genes with potential to accelerate the genetic improvement of citrus.

Tissue-Targeted Transcriptomics Reveals SEMA3D Control of Hypoglossal Nerve Projection to Mouse Tongue Primordia.

The mouse hypoglossal nerve originates in the occipital motor nuclei at embryonic day (E)10.5 and projects a long distance, reaching the vicinity of the tongue primordia, the lateral lingual swellings, at E11.5. However, the details of how the hypoglossal nerve correctly projects to the primordia are poorly understood. To investigate the molecular basis of hypoglossal nerve elongation, we used a novel transcriptomic approach using the ROKU method. The ROKU algorithm identified 3825 genes specific for lateral lingual swellings at E11.5, of which 34 genes were predicted to be involved in axon guidance. Ingenuity Pathway Analysis-assisted enrichment revealed activation of the semaphorin signaling pathway during tongue development, and quantitative PCR showed that the expressions of Sema3d and Nrp1 in this pathway peaked at E11.5. Immunohistochemistry detected NRP1 in the hypoglossal nerve and SEMA3D as tiny granules in the extracellular space beneath the epithelium of the tongue primordia and in lateral and anterior regions of the mandibular arch. Fewer SEMA3D granules were localized around hypoglossal nerve axons and in the space where they elongated. In developing tongue primordia, tissue-specific regulation of SEMA3D might control the route of hypoglossal nerve projection via its repulsive effect on NRP1.

Genomic screening of fish-specific genes in gnathostomes and their functions in fin development.

In this study, we comprehensively searched for fish-specific genes in gnathostomes that contribute to development of the fin, a fish-specific trait. Many previous reports suggested that animal group-specific genes are often important for group-specific traits. Clarifying the roles of fish-specific genes in fin development of gnathostomes, for example, can help elucidate the mechanisms underlying the formation of this trait. We first identified 91 fish-specific genes in gnathostomes by comparing the gene repertoire in 16 fish and 35 tetrapod species. RNA-seq analysis narrowed down the 91 candidates to 33 genes that were expressed in the developing pectoral fin. We analyzed the functions of approximately half of the candidate genes by loss-of-function analysis in zebrafish. We found that some of the fish-specific and fin development-related genes, including fgf24 and and1/and2, play roles in fin development. In particular, the newly identified fish-specific gene qkia is expressed in the developing fin muscle and contributes to muscle morphogenesis in the pectoral fin as well as body trunk. These results indicate that the strategy of identifying animal group-specific genes is functional and useful. The methods applied here could be used in future studies to identify trait-associated genes in other animal groups.

Signature construction and molecular subtype identification based on liver-specific genes for prediction of prognosis, immune activity, and anti-cancer drug sensitivity in hepatocellular carcinoma.

BACKGROUND: Liver specific genes (LSGs) are crucial for hepatocyte differentiation and maintaining normal liver function. A deep understanding of LSGs and their heterogeneity in hepatocellular carcinoma (HCC) is necessary to provide clues for HCC diagnosis, prognosis, and treatment. METHODS: The bulk and single-cell RNA-seq data of HCC were downloaded from TCGA, ICGC, and GEO databases. Through unsupervised cluster analysis, LSGs-based HCC subtypes were identified in TCGA-HCC samples. The prognostic effects of the subtypes were investigated with survival analyses. With GSVA and Wilcoxon test, the LSGs score, stemness score, aging score, immune score and stromal score of the samples were estimated and compared. The HCC subtype-specific genes were identified. The subtypes and their differences were validated in ICGC-HCC samples. LASSO regression analysis was used for key gene selection and risk model construction for HCC overall survival. The model performance was estimated and validated. The key genes were validated for their heterogeneities in HCC cell lines with quantitative real-time PCR and at single-cell level. Their dysregulations were investigated at protein level. Their correlations with HCC response to anti-cancer drugs were estimated in HCC cell lines. RESULTS: We identified three LSGs-based HCC subtypes with different prognosis, tumor stemness, and aging level. The C1 subtype with low LSGs score and high immune score presented a poor survival, while the C2 subtype with high LSGs score and immune score indicated an enduring survival. Although no significant survival difference between C2 and C3 HCCs was shown, the C2 HCCs presented higher immune score and stroma score. The HCC subtypes and their differences were confirmed in ICGC-HCC dataset. A five-gene prognostic signature for HCC survival was constructed. Its good performance was shown in both the training and validation datasets. The five genes presented significant heterogeneities in different HCC cell lines and hepatocyte subclusters. Their dysregulations were confirmed at protein level. Furthermore, their significant associations with HCC sensitivities to anti-cancer drugs were shown. CONCLUSIONS: LSGs-based HCC subtype classification and the five-gene risk model might provide useful clues not only for HCC stratification and risk prediction, but also for the development of more personalized therapies for effective HCC treatment.

Comprehensive analyses of 435 goat transcriptomes provides insight into male reproduction.

A systematic analysis of genes related to reproduction is crucial for obtaining a comprehensive understanding of the molecular mechanisms that underlie male reproductive traits in mammals. Here, we utilized 435 goat transcriptome datasets to unveil the testicular tissue-specific genes (TSGs), allele-specific expression (ASE) genes and their uncharacterized transcriptional features related to male goat reproduction. Results showed a total of 1790 TSGs were identified in goat testis, which was the most among all tissues. GO enrichment analyses suggested that testicular TSGs were mainly involved in spermatogenesis, multicellular organism development, spermatid development, and flagellated sperm motility. Subsequently, a total of 95 highly conserved TSGs (HCTSGs), 508 middle conserved TSGs (MCTSGs) and 42 no conserved TSGs (NCTSGs) were identified in goat testis. GO enrichment analyses suggested that the HCTSGs and MCTSGs has a more important association with male reproduction than NCTSGs. Additionally, we identified 644 ASE genes, including 88 tissue-specific ASE (TS-ASE) genes (e.g., FSIP2, TDRD9). GO enrichment analyses indicated that both ASE genes and TS-ASE genes were associated with goat male reproduction. Overall, this study revealed an extensive gene set involved in the regulation of male goat reproduction and their dynamic transcription patterns. Data reported here provide valuable insights for a further improvement of the economic benefits of goats as well as future treatments for male infertility.

Metabolic variations in root tissues and rhizosphere soils of weak host plants potently lead to distinct host status and chemotaxis regulation of Meloidogyne incognita in intercropping.

Root-knot nematodes (RKNs) inflict extensive damage to global agricultural production. Intercropping has been identified as a viable agricultural tool for combating RKNs, but the mechanisms by which intercropped plants modulate RKN parasitism are still not well understood. Here, we focus on the cucumber-amaranth intercropping system. We used a range of approaches, including the attraction assay, in vitro RNA interference (RNAi), untargeted metabolomics, and hairy root transformation, to unveil the mechanisms by which weak host plants regulate Meloidogyne incognita chemotaxis towards host plants and control infection. Amaranth roots showed a direct repellence to M. incognita through disrupting its chemotaxis. The in vitro RNAi assay demonstrated that the Mi-flp-1 and Mi-flp-18 genes (encoding FMRFamide-like peptides) regulated M. incognita chemotaxis towards cucumber and controlled infection. Moreover, M. incognita infection stimulated cucumber and amaranth to accumulate distinct metabolites in both root tissues and rhizosphere soils. In particular, naringenin and salicin, enriched specifically in amaranth rhizosphere soils, inhibited the expression of Mi-flp-1 and Mi-flp-18. In addition, overexpression of genes involved in the biosynthesis of pantothenic acid and phloretin, both of which were enriched specifically in amaranth root tissues, delayed M. incognita development in cucumber hairy roots. Together, our results reveal that both the distinct host status and disruption of chemotaxis contribute to M. incognita inhibition in intercropping.

Predicting cell-type specific disease genes of diabetes with the biological network.

Type 2 diabetes (T2D) is a chronic condition that can lead to significant harm, such as heart disease, kidney disease, nerve damage, and blindness. Although T2D-related genes have been identified through Genome-wide association studies (GWAS) and various computational methods, the biological mechanism of T2D at the cell type level remains unclear. Exploring cell type-specific genes related to T2D is essential to understand the cellular mechanisms underlying the disease. To address this issue, we introduce DiGCellNet (predicting Disease Genes with Cell type specificity based on biological Networks), a model that integrates graph convolutional network (GCN) and multi-task learning (MTL) to predict T2D-associated cell type-specific genes based on the biological network. Our work represents the first attempt to predict cell type-specific disease genes using GCN and MTL. We evaluate our approach by predicting genes specific to four cell types and demonstrate that the proposed DiGCellNet outperforms other models that combine node embeddings with traditional machine learning algorithms. Moreover, DiGCellNet successfully identifies CALM1 as a gene specific to beta cell type in T2D cases, and this association is confirmed using an independent dataset. The code is available at https://github.com/23AIBox/23AIBox-DiGCellNet.