Bias and Correction in RNA-seq Data for Marine Species

Significance of NKX2-1 as a biomarker for clinical prognosis, immune infiltration, and drug therapy in lung squamous cell carcinoma

Background

This study was performed to determine the biological processes in which NKX2-1 is involved and thus its role in the development of lung squamous cell carcinoma (LUSC) toward improving the prognosis and treatment of LUSC.

Methods

Raw RNA sequencing (RNA-seq) data of LUSC from The Cancer Genome Atlas (TCGA) were used in bioinformatics analysis to characterize NKX2-1 expression levels in tumor and normal tissues. Survival analysis of Kaplan-Meier curve, the time-dependent receiver operating characteristic (ROC) curve, and a nomogram were used to analyze the prognosis value of NKX2-1 for LUSC in terms of overall survival (OS) and progression-free survival (PFS). Then, differentially expressed genes (DEGs) were identified, and Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and Gene Set Enrichment Analysis (GSEA) were used to clarify the biological mechanisms potentially involved in the development of LUSC. Moreover, the correlation between the NKX2-1 expression level and tumor mutation burden (TMB), tumor microenvironment (TME), and immune cell infiltration revealed that NKX2-1 participates in the development of LUSC. Finally, we studied the effects of NKX2-1 on drug therapy. To validate the protein and gene expression levels of NKX2-1 in LUSC, we employed immunohistochemistry(IHC) datasets, The Gene Expression Omnibus (GEO) database, and qRT-PCR analysis.

Results

NKX2-1 expression levels were significantly lower in LUSC than in normal lung tissue. It significantly differed in gender, stage and N classification. The survival analysis revealed that high expression of NKX2-1 had shorter OS and PFS in LUSC. The multivariate Cox regression hazard model showed the NKX2-1 expression as an independent prognostic factor. Then, the nomogram predicted LUSC prognosis. There are 51 upregulated DEGs and 49 downregulated DEGs in the NKX2-1 high-level groups. GO, KEGG and GSEA analysis revealed that DEGs were enriched in cell cycle and DNA replication.The TME results show that NKX2-1 expression was positively associated with mast cells resting, neutrophils, monocytes, T cells CD4 memory resting, and M2 macrophages but negatively associated with M1 macrophages. The TMB correlated negatively with NKX2-1 expression. The pharmacotherapy had great sensitivity in the NKX2-1 low-level group, the immunotherapy is no significant difference in the NKX2-1 low-level and high-level groups. The analysis of GEO data demonstrated concurrence with TCGA results. IHC revealed NKX2-1 protein expression in tumor tissues of both LUAD and LUSC. Meanwhile qRT-PCR analysis indicated a significantly lower NKX2-1 expression level in LUSC compared to LUAD. These qRT-PCR findings were consistent with co-expression analysis of NKX2-1.

Conclusion

We conclude that NKX2-1 is a potential biomarker for prognosis and treatment LUSC. A new insights of NKX2-1 in LUSC is still needed further research.

Lipid metabolism-related long noncoding RNA RP11-817I4.1 promotes fatty acid synthesis and tumor progression in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common types of tumors. The influence of lipid metabolism disruption on the development of HCC has been demonstrated in published studies.

AIM

To establish an HCC prognostic model for lipid metabolism-related long non-coding RNAs (LMR-lncRNAs) and conduct in-depth research on the specific role of novel LMR-lncRNAs in HCC.

METHODS

Correlation and differential expression analyses of The Cancer Genome Atlas data were used to identify differentially expressed LMR-lncRNAs. Quantitative real-time polymerase chain reaction analysis was used to evaluate the expression of LMR-lncRNAs. Nile red staining was employed to observe intracellular lipid levels. The interaction between RP11-817I4.1, miR-3120-3p, and ATP citrate lyase (ACLY) was validated through the performance of dual-luciferase reporter gene and RIP assays.

RESULTS

Three LMR-lncRNAs (negative regulator of antiviral response, RNA transmembrane and coiled-coil domain family 1 antisense RNA 1, and RP11-817I4.1) were identified as predictive markers for HCC patients and were utilized in the construction of risk models. Additionally, proliferation, migration, and invasion were reduced by RP11-817I4.1 knockdown. An increase in lipid levels in HCC cells was significantly induced by RP11-817I4.1 through the miR-3120-3p/ACLY axis.

CONCLUSION

LMR-lncRNAs have the capacity to predict the clinical characteristics and prognoses of HCC patients, and the discovery of a novel LMR-lncRNAs, RP11-817I4.1, revealed its role in promoting lipid accumulation, thereby accelerating the onset and progression of HCC.

Establishment of a prognostic model toward lung squamous cell carcinoma based on m7G-related genes in the cancer genome atlas

Lung squamous cell carcinoma (LUSC) is a non-small cell lung cancer with a poor prognosis owing to late diagnosis. New molecular markers are urgently needed to improve the diagnosis and prognosis of LUSC. 7-Methylguanosine (m7G) modifications, a tRNA modification, are common in eubacteria, eukaryotes, and a few archaea. These modifications promote the turnover and stability of some mRNAs to prevent mRNA decay, improve translation efficiency, and reduce ribosomal pausing but are associated with poor survival in human cancer cells. However, expression of m7G-related genes in LUSC and their association with prognosis remain unclear. In the present study, we identified nine differentially expressed genes related to prognosis by comparing the expression profiles of tumor tissues (502 LUSC reports) with normal tissues (49 adjacent nontumor lung tissue reports). The genes included six upregulated genes (KLK7, LCE3E, AREG, KLK6, ZBED2, and MAPK4) and three downregulated genes (ADH1C, NTS, and ERLIN2). Based on these nine genes, patients with LUSC were classified into low- and high-risk groups to analyze the trends in prognosis. We found that the nine m7G-related genes play important roles in immune regulation, hormone regulation, and drug sensitivity through pathways including antigen processing and presentation, adherent plaques, extracellular matrix receptor interactions, drug metabolism of cytochrome P-450, and metabolism of cytochrome P-450 to xenobiotics; the functions of these genes are likely accomplished in part by m6A modifications. The effect of m7G-related genes on the diagnosis and prognosis of LUSC was further indicated by population analysis.NEW & NOTEWORTHY Based on the differential expression of 7-methylguanosine (m7G) modification-associated genes between normal and lung squamous cell carcinoma (LUSC) tissues, and considering the performance of our m7G-related gene risk profiles as independent risk factors in predicting overall survival, we conclude that m7G modification is closely linked to the development of LUSC. In addition, this study offers a new genetic marker for predicting the prognosis of patients with LUSC and presents a crucial theoretical foundation for future investigations on the relationship between m7G modification-related genes, immunity, and drug sensitivity in LUSC.

Transcriptome Analysis Reveals the Response Mechanism of Frl-Mediated Resistance to Fusarium oxysporum f. sp. radicis-lycopersici (FORL) Infection in Tomato

Tomato Fusarium crown and root rot (FCRR) is an extremely destructive soil-borne disease. To date, studies have shown that only plants with tomato mosaic virus (TMV) resistance exhibit similar resistance to tomato Fusarium oxysporum f. sp. radicis-lycopersici (FORL) and have identified a single relevant gene, Frl, in Peruvian tomato. Due to the relative lack of research on FCRR disease-resistance genes in China and elsewhere, transcriptome data for FORL-resistant (cv. ‘19912’) and FORL-susceptible (cv. ‘Moneymaker’) tomato cultivars were analysed for the first time in this study. The number of differentially expressed genes (DEGs) was higher in Moneymaker than in 19912, and 189 DEGs in the ‘plant–pathogen interaction’ pathway were subjected to GO and KEGG enrichment analyses. MAPK and WRKY genes were enriched in major metabolic pathways related to plant disease resistance; thus, we focused on these two gene families. In the early stage of tomato infection, the content of JA and SA increased, but the change in JA was more obvious. Fourteen genes were selected for confirmation of their differential expression levels by qRT-PCR. This study provides a series of novel disease resistance resources for tomato breeding and genetic resources for screening and cloning FORL resistance genes.

Identification of a novel autophagy-related prognostic signature and small molecule drugs for glioblastoma by bioinformatics

OBJECTIVE

To explore the autophagy-related prognostic signature (ARPs) via data mining in gene expression profiles for glioblastoma (GBM).

METHODS

Using the Cancer Genome Atlas (TCGA) database, we obtained 156 GBM samples and 5 adjacent normal samples, and denoted them as discovery cohort. Univariate Cox regression analysis was used to screen autophagy genes that related to GBM prognosis. Then, the least absolute shrinkage and selection operator Cox regression model was used to construct an autophagy-based ARPs, which was validated in an external cohort containing 80 GBM samples. The patients in the above-mentioned cohorts were divided into low-risk group and high-risk group according to the median prognostic risk score, and the diagnostic performance of the model was assessed by receiver operating characteristic curve analyses. The gene ontology and Kyoto encyclopedia of genes and genomes pathway enrichment analyses were performed between the high-risk and low-risk patients. Additionally, the genetic features of ARPs, such as genetic variation profiles, correlations with tumor-infiltrating lymphocytes (TILs), and potential drug sensitivity, were further assessed in the TCGA-GBM data set.

RESULTS

A signature of ARPs including NDUFB9, BAK1, SUPT3H, GAPDH, CDKN1B, CHMP6, and EGFR were detected and validated. We identified a autophagy-related prognosis 7-gene signature correlated survival prognosis, immune infiltration, level of cytokines, and cytokine receptor in tumor microenvironment. Furthermore, the signature was tested in several pathways related to disorders of tumor microenvironment, as well as cancer-related pathways. Additionally, a range of small molecular drugs, shown to have a potential therapeutic effect on GBM.

CONCLUSIONS

We constructed an autophagy-based 7-gene signature, which could serve as an independent prognostic indicator for cases of GBM and sheds light on the role of autophagy as a potential therapeutic target in GBM.

Deciphering the Pyroptosis-Related Prognostic Signature and Immune Cell Infiltration Characteristics of Colon Cancer

Background: Colon cancer (CC) remains one of the most common malignancies with a poor prognosis. Pyroptosis, referred to as cellular inflammatory necrosis, is thought to influence tumor development. However, the potential effects of pyroptosis-related regulators (PRRs) on the CC immune microenvironment remain unknown.

Methods: In this study, 27 PRRs reported in the previous study were used to cluster the 1,334 CC samples into three pyroptosis-related molecular patterns. Through subtype pattern differential analysis and structure network mining using Weighted Gene Co-expression Network Analysis (WGCNA), 854 signature genes associated with the PRRs were discovered. Further LASSO-penalized Cox regression of these genes established an eight-gene assessment model for predicting prognosis.

Results: The CC patients were subtyped based on three distinct pyroptosis-related molecular patterns. These pyroptosis-related patterns were correlated with different clinical outcomes and immune cell infiltration characteristics in the tumor microenvironment. The pyroptosis-related eight-signature model was established and used to assess the prognosis of CC patients with medium-to-high accuracy by employing the risk scores, which was named “PRM-scores.” Greater inflammatory cell infiltration was observed in tumors with low PRM-scores, indicating a potential benefit of immunotherapy in these patients.

Conclusions: This study suggests that PRRs have a significant effect on the tumor immune microenvironment and tumor development. Evaluating the pyroptosis-related patterns and related models will promote our understanding of immune cell infiltration characteristics in the tumor microenvironment and provide a theoretical basis for future research targeting pyroptosis in cancer.

Integrative Analysis of Biomarkers Through Machine Learning Identifies Stemness Features in Colorectal Cancer

Background: Cancer stem cells (CSCs), which are characterized by self-renewal and plasticity, are highly correlated with tumor metastasis and drug resistance. To fully understand the role of CSCs in colorectal cancer (CRC), we evaluated the stemness traits and prognostic value of stemness-related genes in CRC.

Methods: In this study, the data from 616 CRC patients from The Cancer Genome Atlas (TCGA) were assessed and subtyped based on the mRNA expression-based stemness index (mRNAsi). The correlations of cancer stemness with the immune microenvironment, tumor mutational burden (TMB), and N6-methyladenosine (m6A) RNA methylation regulators were analyzed. Weighted gene co-expression network analysis (WGCNA) was performed to identify the crucial stemness-related genes and modules. Furthermore, a prognostic expression signature was constructed using the Lasso-penalized Cox regression analysis. The signature was validated via multiplex immunofluorescence staining of tissue samples in an independent cohort of 48 CRC patients.

Results: This study suggests that high-mRNAsi scores are associated with poor overall survival in stage IV CRC patients. Moreover, the levels of TMB and m6A RNA methylation regulators were positively correlated with mRNAsi scores, and low-mRNAsi scores were characterized by increased immune activity in CRC. The analysis identified 34 key genes as candidate prognosis biomarkers. Finally, a three-gene prognostic signature (PARPBP, KNSTRN, and KIF2C) was explored together with specific clinical features to construct a nomogram, which was successfully validated in an external cohort.

Conclusion: There is a unique correlation between CSCs and the prognosis of CRC patients, and the novel biomarkers related to cell stemness could accurately predict the clinical outcomes of these patients.

Identification and validation of an immune-related prognostic signature and key gene in papillary thyroid carcinoma

BACKGROUND

Papillary thyroid carcinoma (PTC) is the most common pathological type of thyroid cancer. The effect of traditional anti-tumor therapy is not ideal for the patients with recurrence, metastasis and radioiodine resistance. The abnormal expression of immune-related genes (IRGs) has critical roles in the etiology of PTC. However, the effect of IRGs on PTC prognosis remains unclear.

METHODS

Based on The Cancer Genome Atlas (TCGA) and ImmPort databases, we integrated IRG expression profiles and progression-free intervals (PFIs) of PTC patients. First, we identified the differentially expressed IRGs and transcription factors (TFs) in PTC. Subsequently, an IRG model that can predict the PFI was constructed by using univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analyses of the differentially expressed IRGs in the TCGA. Additionally, a protein-protein interaction (PPI) network showed the interactions between the differentially expressed genes (DEGs), and the top 30 genes with the highest degree were extracted from the network. Then, the key IRG was identified by the intersection analysis of the PPI network and univariate Cox regression, which was verified the differential expression of by western blotting and immunohistochemistry (IHC). ssGSEA was performed to understand the correlation between the key IRG expression level and immune activity.

RESULTS

A total of 355 differentially expressed IRGs and 43 differentially expressed TFs were identified in PTC patients. Then, eight IRGs were finally utilized to construct an IRG model. The respective areas under the curve (AUCs) of the IRG model reached 0.948, 0.820, and 0.831 at 1, 3 and 5 years in the training set. In addition, lactotransferrin (LTF) was determined as the key IRG related to prognosis. The expression level of LTF in tumor tissues was significantly lower than that in normal tissues. And the results of ssGSEA showed the expression level of LTF is closely related to immune activity.

CONCLUSIONS

These findings show that the prognostic model and key IRG may become promising molecular markers for the prognosis of PTC patients.

Identification of Genes Related to Immune Infiltration in the Tumor Microenvironment of Cutaneous Melanoma

Cutaneous melanoma (CM) is the leading cause of skin cancer deaths and is typically diagnosed at an advanced stage, resulting in a poor prognosis. The tumor microenvironment (TME) plays a significant role in tumorigenesis and CM progression, but the dynamic regulation of immune and stromal components is not yet fully understood. In the present study, we quantified the ratio between immune and stromal components and the proportion of tumor-infiltrating immune cells (TICs), based on the ESTIMATE and CIBERSORT computational methods, in 471 cases of skin CM (SKCM) obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) were analyzed by univariate Cox regression analysis, least absolute shrinkage, and selection operator (LASSO) regression analysis, and multivariate Cox regression analysis to identify prognosis-related genes. The developed prognosis model contains ten genes, which are all vital for patient prognosis. The areas under the curve (AUC) values for the developed prognostic model at 1, 3, 5, and 10 years were 0.832, 0.831, 0.880, and 0.857 in the training dataset, respectively. The GSE54467 dataset was used as a validation set to determine the predictive ability of the prognostic signature. Protein–protein interaction (PPI) analysis and weighted gene co-expression network analysis (WGCNA) were used to verify “real” hub genes closely related to the TME. These hub genes were verified for differential expression by immunohistochemistry (IHC) analyses. In conclusion, this study might provide potential diagnostic and prognostic biomarkers for CM.

The novel immune-related genes predict the prognosis of patients with hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the main causes of cancer deaths globally. Immunotherapy is becoming increasingly important in the cure of advanced HCC. Thus it is essential to identify biomarkers for treatment response and prognosis prediction. We searched publicly available databases and retrieved 465 samples of genes from The Cancer Genome Atlas (TCGA) database and 115 tumor samples from Gene Expression Omnibus (GEO). Meanwhile, we used the ImmPort database to determine the immune-related genes as well. Weighted gene correlation network analysis, Cox regression analysis and least absolute shrinkage and selection operator (LASSO) analysis were used to identify the key immune related genes (IRGs) which are closely related to prognosis. Gene set enrichment analysis (GSEA) was implemented to explore the difference of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway between Immune high- and low-risk score groups. Finally, we made a prognostic nomogram including Immune-Risk score and other clinicopathologic factors. A total of 318 genes from prognosis related modules were identified through weighted gene co-expression network analysis (WGCNA). 46 genes were strongly linked to prognosis after univariate Cox analysis. We constructed a seven genes prognostic signature which showed powerful prediction ability in both training cohort and testing cohort. 16 significant KEGG pathways were identified between high- and low- risk score groups using GSEA analysis. This study identified and verified seven immune-related prognostic biomarkers for the patients with HCC, which have potential value for immune modulatory and therapeutic targets.

Genomic Landscape of Mutational Biases in the Pacific Oyster Crassostrea gigas

Mutation is a driving force of evolution that has been shaped by natural selection and is universally biased. Previous studies determined genome-wide mutational patterns for several species and investigated the heterogeneity of mutational patterns at fine-scale levels. However, little evidence of the heterogeneity of mutation rates over large genomic regions was shown. Hence, the mutational patterns of different large-scale genomic regions and their association with selective pressures still need to be explored. As the second most species-rich animal phylum, little is known about the mutational patterns in Mollusca, especially oysters. In this study, the mutational bias patterns are characterized by using whole-genome resequencing data in the Crassostrea gigas genome. I studied the genome-wide relative rates of the pair mutations and found that the predominant mutation is GC -> AT, irrespective of the genomic regions. This analysis reveals that mutational biases were associated with gene expression levels across the C. gigas genome. Genes with higher expression levels and breadth expression patterns, longer coding length, and more exon numbers had relatively higher GC -> AT rates. I also found that genes with larger dN/dS values had relatively higher GC -> AT rates. This work represents the first comprehensive research on the mutational biases in Mollusca species. Here, I comprehensively investigated the relationships between mutational biases with some intrinsic genetic factors and evolutionary indicators and proposed that selective pressures are important forces shaping the mutational biases across the C. gigas genome.

New insights into the Manila clam and PAMPs interaction based on RNA-seq analysis of clam through in vitro challenges with LPS, PGN, and poly(I:C)

Background

Manila clam (Ruditapes philippinarum) is a worldwide commercially important marine bivalve species. In recent years, however, microbial diseases caused high economic losses and have received increasing attention. To understand the molecular basis of the immune response to pathogen-associated molecular patterns (PAMPs) in R. philippinarum, transcriptome libraries of clam hepatopancreas were constructed at 24 h post-injection with Lipopolysaccharide (LPS), peptidoglycan (PGN), and polyinosinic-polycytidylic acid (poly(I:C)) and phosphate-buffered saline (PBS) control by using RNA sequencing technology (RNA-seq).

Results

A total of 832, 839, and 188 differentially expressed genes (DEGs) were found in LPS, PGN, and poly(I:C) challenge group compared with PBS control, respectively. Several immune-related genes and pathways were activated in response to the different PAMPs, suggesting these genes and pathways might specifically participate in the immune response to pathogens. Besides, the analyses provided useful complementary data to compare different PAMPs challenges in vivo. Functional enrichment analysis of DEGs demonstrated that PAMPs responsive signal pathways were related to apoptosis, signal transduction, immune system, and signaling molecules and interaction. Several shared or specific DEGs response to different PAMPs were revealed in R. philippinarum, including pattern recognition receptors (PRRs), antimicrobial peptides (AMPs), interferon-induced proteins (IFI), and some other immune-related genes were found in the present work.

Conclusions

This is the first study employing high throughput transcriptomic sequencing to provide valuable genomic resources and investigate Manila clam response to different PAMPs through in vivo challenges with LPS, PGN, and poly(I:C). The results obtained here provide new insights to understanding the immune characteristics of R. philippinarum response to different PAMPs. This information is critical to elucidate the molecular basis of R. philippinarum response to different pathogens invasion, which potentially can be used to develop effective control strategies for different pathogens.

Identification of Key Genes Related to Lung Squamous Cell Carcinoma Using Bioinformatics Analysis

Lung squamous cell carcinoma (LUSC) is often diagnosed at the advanced stage with poor prognosis. The mechanisms of its pathogenesis and prognosis require urgent elucidation. This study was performed to screen potential biomarkers related to the occurrence, development and prognosis of LUSC to reveal unknown physiological and pathological processes. Using bioinformatics analysis, the lung squamous cell carcinoma microarray datasets from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases were analyzed to identify differentially expressed genes (DEGs). Furthermore, PPI and WGCNA network analysis were integrated to identify the key genes closely related to the process of LUSC development. In addition, survival analysis was performed to achieve a prognostic model that accomplished good prediction accuracy. Three hundred and thirty–seven up–regulated and 119 down-regulated genes were identified, in which four genes have been found to play vital roles in LUSC development, namely CCNA2, AURKA, AURKB, and FEN1. The prognostic model contained 5 genes, which were all detrimental to prognosis. The AUC of the established prognostic model for predicting the survival of patients at 1, 3, and 5 years was 0.692, 0.722, and 0.651 in the test data, respectively. In conclusion, this study identified several biomarkers of significant interest for additional investigation of the therapies and methods of prognosis of lung squamous cell carcinoma.

Relationship Among Intron Length, Gene Expression, and Nucleotide Diversity in the Pacific Oyster Crassostrea gigas

Crassostrea gigas is a model mollusk, but its genetic features have not been studied comprehensively. In this study, we used whole-genome resequencing data to identify and characterize nucleotide diversity and population recombination rate in a diverse collection of 21 C. gigas samples. Our analyses revealed that C. gigas harbors both extremely high genetic diversity and recombination rates across the whole genome as compared with those of the other taxa. The noncoding regions, introns, intergenic spacers, and untranslated regions (UTRs) showed a lower level diversity than the synonymous sites. The larger introns tended to have lower diversity. Moreover, we found a negative association of the non-synonymous diversity with gene expression, which suggested that purifying selection played an important role in shaping genetic diversity. The nucleotide diversity at the 100- and 50-kb levels was positively correlated with population recombination rates, which was expected if the diversity was shaped by purifying selection or hitchhiking of advantageous mutants. Our work gives a general picture of the oyster's polymorphism pattern and its association with recombination rates.

Gonadal Transcriptome Analysis of Pacific Abalone Haliotis discus discus: Identification of Genes Involved in Germ Cell Development

Little is known about the molecular mechanisms governing gonadal developmental processes in abalones. Here, we conducted transcriptome analysis of Pacific abalone Haliotis discus discus for gene discovery in the brain, ovary, testis, and unfertilized eggs. Among the annotated unigenes, 48.6% of unigenes were identified by Venn diagram analysis as having universal or tissue-specific expression. Twenty-three genes with gonad-biased gene ontology (GO) terms were first obtained. Secondly, 36 genes were found by screening known gene names related to germ cell development. Finally, 17 genes were obtained by querying the annotated unigene database for zygotically expressed gonadal genes (ovary and testis) and maternally expressed gonadal genes (ovary, testis, and unfertilized eggs) using keywords related to reproduction. To further verify tissue distribution pattern and subcellular localization of these genes, RT-PCR and in situ hybridization were performed using a unigene encoding a germ cell marker, vasa, as control. The results showed that vasa was expressed mainly in the early developmental stages of germ cells in both sexes. One of the candidate genes, vitelline envelope zona pellucida domain protein 12 (ZP12), was expressed in the primordial germ cells of immature gonad and early developmental stages of germ cells of the adult female. The results obtained from the present study suggest that vasa and ZP12 are involved in germ cell development of Pacific abalone and that ZP12 is an especially useful germ cell-specific marker in immature adults. The current gonadal transcriptome profile is an extensive resource for future reproductive molecular biology studies of this species.

Comparative Transcriptome Analysis Reveals Growth-Related Genes in Juvenile Chinese Sea Cucumber, Russian Sea Cucumber, and Their Hybrids

Heterosis is important for sea cucumber breeding, but its molecular mechanism remains largely unexplored. In this study, parental lines of Apostichopus japonicus from Russia (R) and China (C) were used to construct hybrids (CR and RC) by reciprocal crossing. We examined the transcriptional profiles of the hybrids (CR and RC) and the purebreds (CC and RR) at different developmental times. A total of 60.27 Gb of clean data was obtained, and 176,649 unigenes were identified, of which 50,312 unigenes were annotated. A total of 414,536 SNPs were identified. A total of 7011 differentially expressed genes (DEGs) were obtained between the purebreds and hybrids at 45 days after fertilization (DAF), and a total of 8218 DEGs were obtained between the purebreds and hybrids at 75 DAF. In addition, a total of 7652 DEGs were obtained between 45 DAF and 75 DAF. The significant DEGs were mainly involved in the MAPK and FOXO signaling pathways, especially in the Ras-Raf-MEK1/2-ERK module, which may be a key regulator of development and growth in juvenile A. japonicus. In addition, we also identified key growth-related genes, such as fgfs, igfs, megfs and hgfs, which were upregulated in the hybrids (RC and CR); these genes may play important roles in heterosis in A. japonicus. Our study provides fundamental information on the molecular mechanisms underlying heterosis in sea cucumber and might suggest strategies for the selection of rapidly growing strains of sea cucumber in aquaculture.