Formation of the synaptonemal complex in a gynogenetic allodiploid hybrid fish.

Introduction: The correct pairing and separation of homologous chromosomes during meiosis is crucial to ensure both genetic stability and genetic diversity within species. In allodiploid organisms, synapsis often fails, leading to sterility. However, a gynogenetic allodiploid hybrid clone line (GDH), derived by crossing red crucian carp (Carassius auratus ♀) and common carp (Cyprinus carpio ♂), stably produces diploid eggs. Because the GDH line carries 100 chromosomes with 50 chromosomes from the red crucian carp (RCC; ♀, 2n = 2x = 100) and 50 chromosomes from the common carp (CC; C. carpio L., ♂, 2n = 2x = 100), it is interesting to study the mechanisms of homologous chromosome pairing during meiosis in GDH individuals. Methods: By using fluorescence in situ hybridization (FISH) with a probe specific to the red crucian carp to label homologous chromosomes, we identified the synaptonemal complex via immunofluorescence assay of synaptonemal complex protein 3 (SCP3). Results: FISH results indicated that, during early ovarian development, the GDH oogonium had two sets of chromosomes with only one set from Carassius auratus, leading to the failure formation of normal bivalents and the subsequently blocking of meiosis. This inhibition lasted at least 5 months. After this long period of inhibition, pairs of germ cells fused, doubling the chromosomes such that the oocyte contained two sets of chromosomes from each parent. After chromosome doubling at 10 months old, homologous chromosomes and the synaptonemal complex were identified. Discussion: Causally, meiosis proceeded normally and eventually formed diploid germ cells. These results further clarify the mechanisms by which meiosis proceeds in hybrids.

Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST.

Spatially resolved transcriptomics involves a set of emerging technologies that enable the transcriptomic profiling of tissues with the physical location of expressions. Although a variety of methods have been developed for data integration, most of them are for single-cell RNA-seq datasets without consideration of spatial information. Thus, methods that can integrate spatial transcriptomics data from multiple tissue slides, possibly from multiple individuals, are needed. Here, we present PRECAST, a data integration method for multiple spatial transcriptomics datasets with complex batch effects and/or biological effects between slides. PRECAST unifies spatial factor analysis simultaneously with spatial clustering and embedding alignment, while requiring only partially shared cell/domain clusters across datasets. Using both simulated and four real datasets, we show improved cell/domain detection with outstanding visualization, and the estimated aligned embeddings and cell/domain labels facilitate many downstream analyses. We demonstrate that PRECAST is computationally scalable and applicable to spatial transcriptomics datasets from different platforms.

Immunoglobulin heavy-chain loci in ancient allotetraploid goldfish.

As an ancient allotetraploid species, goldfish (Carassius auratus) have two sets of subgenomes. In this study, immunoglobulin heavy-chain (IGH) genes were cloned from the red crucian carp (Carassius auratus red var.), and the corresponding loci were identified in the gynogenetic diploid red crucian carp (GRCC) genome as well as the genomes of three other goldfish strains (Wakin, G-12, and CaTCV-1). Examination showed that each goldfish strain possessed two sets of parallel IGH loci: a complete IGHA locus and a degenerated IGHB locus that was nearly 40 × smaller. In the IGHA locus, multiple τ chain loci were arranged in tandem between the µ&δ chain locus and the variable genes, but no τ-like genes were found in the IGHB locus.

A Novel Allotriploid Hybrid Derived From Female Goldfish × Male Bleeker's Yellow Tail.

Hybridization is a traditional and effective strategy to alter the genotypes and phenotypes of the offspring, and distant hybridization is a useful strategy to generate polyploids in fish. In this study, goldfish (Carassius auratus, GF, 2n = 100) and Bleeker's yellow tail (Xenocypris davidi Bleeker, YT, 2n = 48), which belong to different subfamilies, were crossed with each other. The cross of female GF × male YT successfully obtained hybrid offspring (GFYT hybrids), while the cross of female YT × male GF was lethal, and all the fertilized eggs stopped developing before the neurula stage of embryogenesis. All GFYT hybrids possessed 124 chromosomes (3n = 124) with two sets from GF and one set from YT. The measurable and countable traits of GFYT hybrids were identified, and the genetic characteristics of 5S rDNA between GFYT hybrids and their parents were also revealed. There were, respectively, four and three different 5S rDNA types in GF (assigned as GF-Ⅰ∼Ⅳ) and YT (assigned as YT-Ⅰ∼Ⅲ), and GFYT hybrids specifically inherited YT-Ⅰ and YT-Ⅱ 5S rDNA types from YT and GF-Ⅲ and GF-Ⅳ from GF. In addition, there were only testis-like and fat-like gonads been found in GFYT hybrids. Interestingly, there were pyknotic and heteromorphous chromatin and invaginated cell membrane observed in the spermatids of testis-like gonads, but no mature sperm were found. Furthermore, TUNEL assays indicated that, compared with control, apparent apoptotic signals, which were mainly distributed around spermatid regions, were detected in the testis-like gonads, and the expression of apoptosis pathway-related genes including p53, bcl-2, bax, and caspase9 was significantly upregulated. Moreover, the expression of meiosis-related genes including spo11, dmc1, and rad51 showed an abnormally high expression, but mns1 and meig1, two key genes involved in the maturation of spermatid, were extremely downregulated. In brief, this is the first report of allotriploid via distant hybridization between GF and YT that possessing different chromosome numbers in vertebrates. The obtainment of GFYT hybrids not only harbors potential benefits and application in aquaculture but also further extends the understanding of the influence of hybridization and polyploidization on the genomic constitution of the hybrid offspring. Furthermore, they can be used as a model to test the origin and consequences of polyploidization and served as a proper resource to study the underlying mechanisms of spermatogenesis dysfunctions.

Regression-based heterogeneity analysis to identify overlapping subgroup structure in high-dimensional data.

Heterogeneity is a hallmark of complex diseases. Regression-based heterogeneity analysis, which is directly concerned with outcome-feature relationships, has led to a deeper understanding of disease biology. Such an analysis identifies the underlying subgroup structure and estimates the subgroup-specific regression coefficients. However, most of the existing regression-based heterogeneity analyses can only address disjoint subgroups; that is, each sample is assigned to only one subgroup. In reality, some samples have multiple labels, for example, many genes have several biological functions, and some cells of pure cell types transition into other types over time, which suggest that their outcome-feature relationships (regression coefficients) can be a mixture of relationships in more than one subgroups, and as a result, the disjoint subgrouping results can be unsatisfactory. To this end, we develop a novel approach to regression-based heterogeneity analysis, which takes into account possible overlaps between subgroups and high data dimensions. A subgroup membership vector is introduced for each sample, which is combined with a loss function. Considering the lack of information arising from small sample sizes, an l2$l_2$ norm penalty is developed for each membership vector to encourage similarity in its elements. A sparse penalization is also applied for regularized estimation and feature selection. Extensive simulations demonstrate its superiority over direct competitors. The analysis of Cancer Cell Line Encyclopedia data and lung cancer data from The Cancer Genome Atlas show that the proposed approach can identify an overlapping subgroup structure with favorable performance in prediction and stability.

Robust structured heterogeneity analysis approach for high-dimensional data.

Revealing relationships between genes and disease phenotypes is a critical problem in biomedical studies. This problem has been challenged by the heterogeneity of diseases. Patients of a perceived same disease may form multiple subgroups, and different subgroups have distinct sets of important genes. It is hence imperative to discover the latent subgroups and reveal the subgroup-specific important genes. Some heterogeneity analysis methods have been proposed in the recent literature. Despite considerable successes, most of the existing studies are still limited as they cannot accommodate data contamination and ignore the interconnections among genes. Aiming at these shortages, we develop a robust structured heterogeneity analysis approach to identify subgroups, select important genes as well as estimate their effects on the phenotype of interest. Possible data contamination is accommodated by employing the Huber loss function. A sparse overlapping group lasso penalty is imposed to conduct regularization estimation and gene identification, while taking into account the possibly overlapping cluster structure of genes. This approach takes an iterative strategy in the similar spirit of K-means clustering. Simulations demonstrate that the proposed approach outperforms alternatives in revealing the heterogeneity and selecting important genes for each subgroup. The analysis of Cancer Cell Line Encyclopedia data leads to biologically meaningful findings with improved prediction and grouping stability.

A Penalization Method for Estimating Heterogeneous Covariate Effects in Cancer Genomic Data.

In high-throughput profiling studies, extensive efforts have been devoted to searching for the biomarkers associated with the development and progression of complex diseases. The heterogeneity of covariate effects associated with the outcomes across subjects has been noted in the literature. In this paper, we consider a scenario where the effects of covariates change smoothly across subjects, which are ordered by a known auxiliary variable. To this end, we develop a penalization-based approach, which applies a penalization technique to simultaneously select important covariates and estimate their unique effects on the outcome variables of each subject. We demonstrate that, under the appropriate conditions, our method shows selection and estimation consistency. Additional simulations demonstrate its superiority compared to several competing methods. Furthermore, applying the proposed approach to two The Cancer Genome Atlas datasets leads to better prediction performance and higher selection stability.

Robust nonparametric integrative analysis to decipher heterogeneity and commonality across subgroups using sparse boosting.

In many biomedical problems, data are often heterogeneous, with samples spanning multiple patient subgroups, where different subgroups may have different disease subtypes, stages, or other medical contexts. These subgroups may be related, but they are also expected to have differences with respect to the underlying biology. The heterogeneous data presents a precious opportunity to explore the heterogeneities and commonalities between related subgroups. Unfortunately, effective statistical analysis methods are still lacking. Recently, several novel methods based on integrative analysis have been proposed to tackle this challenging problem. Despite promising results, the existing studies are still limited by ignoring data contamination and making strict assumptions of linear effects of covariates on response. As such, we develop a robust nonparametric integrative analysis approach to identify heterogeneity and commonality, as well as select important covariates and estimate covariate effects. Possible data contamination is accommodated by adopting the Cauchy loss function, and a nonparametric model is built to accommodate nonlinear effects. The proposed approach is based on a sparse boosting technique. The advantages of the proposed approach are demonstrated in extensive simulations. The analysis of The Cancer Genome Atlas data on glioblastoma multiforme and lung adenocarcinoma shows that the proposed approach makes biologically meaningful findings with satisfactory prediction.

A novel NK-lysin in hybrid crucian carp can exhibit cytotoxic activity in fish cells and confer protection against Aeromonas hydrophila infection in comparison with Carassius cuvieri and Carassius auratus red var.

NK-lysin, an effector of natural killer (NK) cells and cytotoxic T lymphocytes (CTLs), not only exhibits cytotoxic effect in fish cells, but also participates in the immune defense against pathogenic infection. In this study, ORF sequences of RCC-NK-lysin, WCC-NK-lysin and WR-NK-lysin were 369 bp. Tissue-specific analysis revealed that the highest expressions of RCC-NK-lysin and WCC-NK-lysin were observed in gill, while the peaked level of WR-NK-lysin mRNA was observed in spleen. A. hydrophila infection sharply increased RCC-NK-lysin, WCC-NK-lysin and WR-NK-lysin mRNA expression in liver, trunk kidney and spleen. In addition, elevated levels of NK-lysin mRNA were observed in cultured fin cell lines of red crucian carp (RCC), white crucian carp (WCC) and their hybrid offspring (WR) after Lipopolysaccharide (LPS) challenge. RCC-NK-lysin, WCC-NK-lysin and WR-NK-lysin exerted regulatory roles in inducing ROS generation, modulating mitochondrial membrane potential, decreasing fish cell viability and antagonizing survival signalings, respectively. RCC/WCC/WR-NK-lysin-overexpressing fish could up-regulate expressions of inflammatory cytokines and decrease bacterial loads in spleen. These results indicated that NK-lysin in hybrid fish contained close sequence similarity to those of its parents, possessing the capacities of cytotoxicity and immune defense against bacterial infection.

Effect of Lipopolysaccharide (LPS) stimulation on apoptotic process and oxidative stress in fibroblast cell of hybrid crucian carp compared with those of Carassius cuvieri and Carassius auratus red var.

Bacterial LPS is a heat-stable endotoxin and wall components of gram negative bacteria, which can exhibit a toxicological effect on physiology and biochemical activities of fish. In this study, we investigated the effect of LPS exposure on cell viability, oxidative stress, caspase activity and immune-related gene expressions in cultured fin cell lines of red crucian carp, white crucian carp and their hybrid offspring. LPS stimulation could reduce fish cell viability, whereas gene expression levels and promoter activities in inflammatory signals increased dramatically. Moreover, enhanced levels of intracellular oxidative stress and decreased levels of mitochondrial membrane potential (MMP) were observed in LPS-induced fish cells. N-Acetyl-L-cysteine (NAC) could alleviate LPS-stimulated reactive oxygen species (ROS) generation and caspase-3 activity in fish cells. These results suggested that ROS-mediated cytotoxic stress was involved in LPS-induced inflammation and mitochondrial damage in cultured fish cells.

Biomarker-guided heterogeneity analysis of genetic regulations via multivariate sparse fusion.

Heterogeneity is a hallmark of many complex diseases. There are multiple ways of defining heterogeneity, among which the heterogeneity in genetic regulations, for example, gene expressions (GEs) by copy number variations (CNVs), and methylation, has been suggested but little investigated. Heterogeneity in genetic regulations can be linked with disease severity, progression, and other traits and is biologically important. However, the analysis can be very challenging with the high dimensionality of both sides of regulation as well as sparse and weak signals. In this article, we consider the scenario where subjects form unknown subgroups, and each subgroup has unique genetic regulation relationships. Further, such heterogeneity is "guided" by a known biomarker. We develop a multivariate sparse fusion (MSF) approach, which innovatively applies the penalized fusion technique to simultaneously determine the number and structure of subgroups and regulation relationships within each subgroup. An effective computational algorithm is developed, and extensive simulations are conducted. The analysis of heterogeneity in the GE-CNV regulations in melanoma and GE-methylation regulations in stomach cancer using the TCGA data leads to interesting findings.

Chimeric ferritin H in hybrid crucian carp exhibits a similar down-regulation in lipopolysaccharide-induced NF-κB inflammatory signal in comparison with Carassius cuvieri and Carassius auratus red var.

Ferritin H can participate in the regulation of teleostean immunity. ORF sequences of RCC/WCC/WR-ferritin H were 609 bp, while WR-ferritin H gene possessed chimeric fragments or offspring-specific mutations. In order to elucidate regulation of immune-related signal transduction, three fibroblast-like cell lines derived from caudal fin of red crucian carp (RCC), white crucian carp (WCC) and their hybrid offspring (WR) were characterized and designated as RCCFCs, WCCFCs and WRFCs. A sharp increase of ferritin H mRNA was observed in RCCFCs, WCCFCs and WRFCs following lipopolysaccharide (LPS) challenge. Overexpression of RCC/WCC/WR-ferritin H can decrease MyD88-IRAK4 signal and antagonize NF-κB, TNFα promoter activity in RCCFCs, WCCFCs and WRFCs, respectively. These results indicated that ferritin H in hybrid offspring harbors highly-conserved domains with a close sequence similarity to those of its parents, playing a regulatory role in inflammatory signals.

Antibacterial and immunoregulatory activity of a novel hepcidin homologue in diploid hybrid fish (Carassius auratus cuvieri ♀ × Carassius auratus red var ♂).

Hepcidin, a multifunctional hormone oligopeptide, not only exhibits a regulatory role in iron metabolism, but also participates in the regulation of teleostean immunity. In this study, ORF sequence of WR-hepcidin was 258 bp and encoded 85 amino acid residues. Tissue-specific analysis revealed that the highest expression of WR-hepcidin was observed in liver. Aeromonas hydrophila challenge can sharply increased WR-hepcidin mRNA expression in liver, trunk kidney and spleen. The purified WR-hepcidin fusion peptide can directly bind to A. hydrophila and Streptococcus agalactiae, reduce the relative bacterial activity, limit bacterial growth and attenuate their dissemination to tissues in vivo. In addition, the treatment of WR-hepcidin fusion protein can diminish the production of pro-inflammatory cytokines. These results indicated that WR-hepcidin can play a negative regulatory role in bacteria-stimulated pro-inflammatory cytokines production and MyD88-IRAK4 activation.