Table_2_Identification of a novel immune-related gene signature for prognosis and the tumor microenvironment in patients with uveal melanoma combining single-cell and bulk sequencing data.xlsx

IntroductionUveal melanoma (UVM) is the most invasive intraocular malignancy in adults with a poor prognosis. Growing evidence revealed that immune-related gene is related to tumorigenesis and prognosis. This study aimed to construct an immune-related prognostic signature for UVM and clarify the molecular and immune classification.MethodsBased on The Cancer Genome Atlas (TCGA) database, single-sample gene set enrichment (ssGSEA) and hierarchical clustering analysis were performed to identify the immune infiltration pattern of UVM and classify patients into two immunity clusters. Then, we proposed univariate and multivariate Cox regression analysis to identify immune-related genes that related to overall survival (OS) and validated in the Gene Expression Omnibus (GEO) external validation cohort. The molecular and immune classification in the immune-related gene prognostic signature defined subgroups were analyzed.ResultsThe immune-related gene prognostic signature was constructed based on S100A13, MMP9, and SEMA3B genes. The prognostic value of this risk model was validated in three bulk RNA sequencing datasets and one single-cell sequencing dataset. Patients in the low-risk group had better OS than those in the high-risk group. The receiver-operating characteristic (ROC) analysis revealed its strong predictive ability for UVM patients. Lower expression of immune checkpoint genes was presented in the low-risk group. Functional studies showed that S100A13 knockdown via siRNA inhibited UVM cell proliferation, migration, and invasion in vitro, with the increased expression of reactive oxygen species (ROS) related markers in UVM cell lines.DiscussionThe immune-related gene prognostic signature is an independent predictive factor for the survival of patients with UVM and provides new information about cancer immunotherapy in UVM.</p

Table_7_Identification of a novel immune-related gene signature for prognosis and the tumor microenvironment in patients with uveal melanoma combining single-cell and bulk sequencing data.xlsx

IntroductionUveal melanoma (UVM) is the most invasive intraocular malignancy in adults with a poor prognosis. Growing evidence revealed that immune-related gene is related to tumorigenesis and prognosis. This study aimed to construct an immune-related prognostic signature for UVM and clarify the molecular and immune classification.MethodsBased on The Cancer Genome Atlas (TCGA) database, single-sample gene set enrichment (ssGSEA) and hierarchical clustering analysis were performed to identify the immune infiltration pattern of UVM and classify patients into two immunity clusters. Then, we proposed univariate and multivariate Cox regression analysis to identify immune-related genes that related to overall survival (OS) and validated in the Gene Expression Omnibus (GEO) external validation cohort. The molecular and immune classification in the immune-related gene prognostic signature defined subgroups were analyzed.ResultsThe immune-related gene prognostic signature was constructed based on S100A13, MMP9, and SEMA3B genes. The prognostic value of this risk model was validated in three bulk RNA sequencing datasets and one single-cell sequencing dataset. Patients in the low-risk group had better OS than those in the high-risk group. The receiver-operating characteristic (ROC) analysis revealed its strong predictive ability for UVM patients. Lower expression of immune checkpoint genes was presented in the low-risk group. Functional studies showed that S100A13 knockdown via siRNA inhibited UVM cell proliferation, migration, and invasion in vitro, with the increased expression of reactive oxygen species (ROS) related markers in UVM cell lines.DiscussionThe immune-related gene prognostic signature is an independent predictive factor for the survival of patients with UVM and provides new information about cancer immunotherapy in UVM.</p

Table_4_Identification of a novel immune-related gene signature for prognosis and the tumor microenvironment in patients with uveal melanoma combining single-cell and bulk sequencing data.xlsx

IntroductionUveal melanoma (UVM) is the most invasive intraocular malignancy in adults with a poor prognosis. Growing evidence revealed that immune-related gene is related to tumorigenesis and prognosis. This study aimed to construct an immune-related prognostic signature for UVM and clarify the molecular and immune classification.MethodsBased on The Cancer Genome Atlas (TCGA) database, single-sample gene set enrichment (ssGSEA) and hierarchical clustering analysis were performed to identify the immune infiltration pattern of UVM and classify patients into two immunity clusters. Then, we proposed univariate and multivariate Cox regression analysis to identify immune-related genes that related to overall survival (OS) and validated in the Gene Expression Omnibus (GEO) external validation cohort. The molecular and immune classification in the immune-related gene prognostic signature defined subgroups were analyzed.ResultsThe immune-related gene prognostic signature was constructed based on S100A13, MMP9, and SEMA3B genes. The prognostic value of this risk model was validated in three bulk RNA sequencing datasets and one single-cell sequencing dataset. Patients in the low-risk group had better OS than those in the high-risk group. The receiver-operating characteristic (ROC) analysis revealed its strong predictive ability for UVM patients. Lower expression of immune checkpoint genes was presented in the low-risk group. Functional studies showed that S100A13 knockdown via siRNA inhibited UVM cell proliferation, migration, and invasion in vitro, with the increased expression of reactive oxygen species (ROS) related markers in UVM cell lines.DiscussionThe immune-related gene prognostic signature is an independent predictive factor for the survival of patients with UVM and provides new information about cancer immunotherapy in UVM.</p

Table_3_Identification of a novel immune-related gene signature for prognosis and the tumor microenvironment in patients with uveal melanoma combining single-cell and bulk sequencing data.xlsx

IntroductionUveal melanoma (UVM) is the most invasive intraocular malignancy in adults with a poor prognosis. Growing evidence revealed that immune-related gene is related to tumorigenesis and prognosis. This study aimed to construct an immune-related prognostic signature for UVM and clarify the molecular and immune classification.MethodsBased on The Cancer Genome Atlas (TCGA) database, single-sample gene set enrichment (ssGSEA) and hierarchical clustering analysis were performed to identify the immune infiltration pattern of UVM and classify patients into two immunity clusters. Then, we proposed univariate and multivariate Cox regression analysis to identify immune-related genes that related to overall survival (OS) and validated in the Gene Expression Omnibus (GEO) external validation cohort. The molecular and immune classification in the immune-related gene prognostic signature defined subgroups were analyzed.ResultsThe immune-related gene prognostic signature was constructed based on S100A13, MMP9, and SEMA3B genes. The prognostic value of this risk model was validated in three bulk RNA sequencing datasets and one single-cell sequencing dataset. Patients in the low-risk group had better OS than those in the high-risk group. The receiver-operating characteristic (ROC) analysis revealed its strong predictive ability for UVM patients. Lower expression of immune checkpoint genes was presented in the low-risk group. Functional studies showed that S100A13 knockdown via siRNA inhibited UVM cell proliferation, migration, and invasion in vitro, with the increased expression of reactive oxygen species (ROS) related markers in UVM cell lines.DiscussionThe immune-related gene prognostic signature is an independent predictive factor for the survival of patients with UVM and provides new information about cancer immunotherapy in UVM.</p

Table_6_Identification of a novel immune-related gene signature for prognosis and the tumor microenvironment in patients with uveal melanoma combining single-cell and bulk sequencing data.xlsx

IntroductionUveal melanoma (UVM) is the most invasive intraocular malignancy in adults with a poor prognosis. Growing evidence revealed that immune-related gene is related to tumorigenesis and prognosis. This study aimed to construct an immune-related prognostic signature for UVM and clarify the molecular and immune classification.MethodsBased on The Cancer Genome Atlas (TCGA) database, single-sample gene set enrichment (ssGSEA) and hierarchical clustering analysis were performed to identify the immune infiltration pattern of UVM and classify patients into two immunity clusters. Then, we proposed univariate and multivariate Cox regression analysis to identify immune-related genes that related to overall survival (OS) and validated in the Gene Expression Omnibus (GEO) external validation cohort. The molecular and immune classification in the immune-related gene prognostic signature defined subgroups were analyzed.ResultsThe immune-related gene prognostic signature was constructed based on S100A13, MMP9, and SEMA3B genes. The prognostic value of this risk model was validated in three bulk RNA sequencing datasets and one single-cell sequencing dataset. Patients in the low-risk group had better OS than those in the high-risk group. The receiver-operating characteristic (ROC) analysis revealed its strong predictive ability for UVM patients. Lower expression of immune checkpoint genes was presented in the low-risk group. Functional studies showed that S100A13 knockdown via siRNA inhibited UVM cell proliferation, migration, and invasion in vitro, with the increased expression of reactive oxygen species (ROS) related markers in UVM cell lines.DiscussionThe immune-related gene prognostic signature is an independent predictive factor for the survival of patients with UVM and provides new information about cancer immunotherapy in UVM.</p

DataSheet_1_Identification of a novel immune-related gene signature for prognosis and the tumor microenvironment in patients with uveal melanoma combining single-cell and bulk sequencing data.docx

IntroductionUveal melanoma (UVM) is the most invasive intraocular malignancy in adults with a poor prognosis. Growing evidence revealed that immune-related gene is related to tumorigenesis and prognosis. This study aimed to construct an immune-related prognostic signature for UVM and clarify the molecular and immune classification.MethodsBased on The Cancer Genome Atlas (TCGA) database, single-sample gene set enrichment (ssGSEA) and hierarchical clustering analysis were performed to identify the immune infiltration pattern of UVM and classify patients into two immunity clusters. Then, we proposed univariate and multivariate Cox regression analysis to identify immune-related genes that related to overall survival (OS) and validated in the Gene Expression Omnibus (GEO) external validation cohort. The molecular and immune classification in the immune-related gene prognostic signature defined subgroups were analyzed.ResultsThe immune-related gene prognostic signature was constructed based on S100A13, MMP9, and SEMA3B genes. The prognostic value of this risk model was validated in three bulk RNA sequencing datasets and one single-cell sequencing dataset. Patients in the low-risk group had better OS than those in the high-risk group. The receiver-operating characteristic (ROC) analysis revealed its strong predictive ability for UVM patients. Lower expression of immune checkpoint genes was presented in the low-risk group. Functional studies showed that S100A13 knockdown via siRNA inhibited UVM cell proliferation, migration, and invasion in vitro, with the increased expression of reactive oxygen species (ROS) related markers in UVM cell lines.DiscussionThe immune-related gene prognostic signature is an independent predictive factor for the survival of patients with UVM and provides new information about cancer immunotherapy in UVM.</p

Table_5_Identification of a novel immune-related gene signature for prognosis and the tumor microenvironment in patients with uveal melanoma combining single-cell and bulk sequencing data.xlsx

IntroductionUveal melanoma (UVM) is the most invasive intraocular malignancy in adults with a poor prognosis. Growing evidence revealed that immune-related gene is related to tumorigenesis and prognosis. This study aimed to construct an immune-related prognostic signature for UVM and clarify the molecular and immune classification.MethodsBased on The Cancer Genome Atlas (TCGA) database, single-sample gene set enrichment (ssGSEA) and hierarchical clustering analysis were performed to identify the immune infiltration pattern of UVM and classify patients into two immunity clusters. Then, we proposed univariate and multivariate Cox regression analysis to identify immune-related genes that related to overall survival (OS) and validated in the Gene Expression Omnibus (GEO) external validation cohort. The molecular and immune classification in the immune-related gene prognostic signature defined subgroups were analyzed.ResultsThe immune-related gene prognostic signature was constructed based on S100A13, MMP9, and SEMA3B genes. The prognostic value of this risk model was validated in three bulk RNA sequencing datasets and one single-cell sequencing dataset. Patients in the low-risk group had better OS than those in the high-risk group. The receiver-operating characteristic (ROC) analysis revealed its strong predictive ability for UVM patients. Lower expression of immune checkpoint genes was presented in the low-risk group. Functional studies showed that S100A13 knockdown via siRNA inhibited UVM cell proliferation, migration, and invasion in vitro, with the increased expression of reactive oxygen species (ROS) related markers in UVM cell lines.DiscussionThe immune-related gene prognostic signature is an independent predictive factor for the survival of patients with UVM and provides new information about cancer immunotherapy in UVM.</p

Analysis of Heterosis and Quantitative Trait Loci for Kernel Shape Related Traits Using Triple Testcross Population in Maize

<div><p>Kernel shape related traits (KSRTs) have been shown to have important influences on grain yield. The previous studies that emphasize kernel length (KL) and kernel width (KW) lack a comprehensive evaluation of characters affecting kernel shape. In this study, materials of the basic generations (B73, Mo17, and B73 × Mo17), 82 intermated B73 × Mo17 (IBM) individuals, and the corresponding triple testcross (TTC) populations were used to evaluate heterosis, investigate correlations, and characterize the quantitative trait loci (QTL) for six KSRTs: KL, KW, length to width ratio (LWR), perimeter length (PL), kernel area (KA), and circularity (CS). The results showed that the mid-parent heterosis (MPH) for most of the KSRTs was moderate. The performance of KL, KW, PL, and KA exhibited significant positive correlation with heterozygosity but their Pearson’s R values were low. Among KSRTs, the strongest significant correlation was found between PL and KA with R values was up to 0.964. In addition, KW, PL, KA, and CS were shown to be significant positive correlation with 100-kernel weight (HKW). 28 QTLs were detected for KSRTs in which nine were augmented additive, 13 were augmented dominant, and six were dominance × additive epistatic. The contribution of a single QTL to total phenotypic variation ranged from 2.1% to 32.9%. Furthermore, 19 additive × additive digenic epistatic interactions were detected for all KSRTs with the highest total <i>R²</i> for KW (78.8%), and nine dominance × dominance digenic epistatic interactions detected for KL, LWR, and CS with the highest total <i>R²</i> (55.3%). Among significant digenic interactions, most occurred between genomic regions not mapped with main-effect QTLs. These findings display the complexity of the genetic basis for KSRTs and enhance our understanding on heterosis of KSRTs from the quantitative genetic perspective.</p></div

The genetic effect and contribution of epistatic QTL for KSRTs detected in <i>Z1</i> and <i>Z2</i>.

<p>** <i>P</i>≤0.01.</p><p>^a<i>a</i>_<i>i</i> and <i>a</i>_<i>j</i> represent the main effect of the loci <i>i</i> and <i>j</i>, and <i>a</i>_<i>ij</i> represents the epistatic effect between loci <i>i</i> and <i>j</i>.</p><p>^b<i>R</i>^<i>2</i>_<i>i</i>, <i>R</i>^<i>2</i>_<i>j</i>, <i>R</i>^<i>2</i>_<i>ij</i>, and <i>R</i>^<i>2</i> represent the genetic contribution via the percentage of the total variation explained by the <i>a</i>_<i>i</i>, <i>a</i>_<i>j</i>, <i>a</i>_<i>ij</i> and the total interactions for KSRTs respectively.</p><p>^{c, d} indicate marker intervals mapped to more than one QTL.</p><p>The genetic effect and contribution of epistatic QTL for KSRTs detected in <i>Z1</i> and <i>Z2</i>.</p

Mean values and heterosis based on the three blocks.

<p>* <i>P</i>≤0.05,</p><p>** <i>P</i>≤0.01.</p><p>^a Comparison between B73 and Mo17 using <i>t</i> test.</p><p>^b Comparison between MP and F1 using <i>t</i> test.</p><p>Mean values and heterosis based on the three blocks.</p