DataSheet_1_Association between subclinical hyperthyroidism and a PRKAR1A gene variant in Carney complex patients: A case report and systematic review.doc

Background and ObjectivesIt is currently controversial whether subclinical hyperthyroidism is associated with PRKAR1A gene variants. We describe a man with subclinical hyperthyroidism and a PRKAR1A gene variant who was diagnosed with Carney complex (CNC), and we performed a systematic review of published studies to assess the association between PRKAR1A gene variants and the risk of subclinical hyperthyroidism.Design and MethodsThe PubMed, EMBASE, OVID, Science Direct, and gray literature electronic databases were searched for articles published from January 2002 to May 2021 using predefined keywords and inclusion and exclusion criteria. Data on thyroid function from selected studies were extracted and analyzed.ResultsWe identified a CNC patient with a subclinical hyperthyroidism phenotype combined with multiple components and genetic sequenced data. In a subsequent systematic review, twenty selected studies (14 case studies and 6 series studies) enrolling 23 individuals were included in the final analysis. The patient’s thyroid function data were qualitative in 11 cases and quantitative in 12 cases. The prevalence of subclinical hyperthyroidism in the CNC patients with a PRKAR1A gene variant, including our patient, was markedly higher than that in the normal population (12.5% vs. 2%)ConclusionsThe findings of this systematic review provide helpful evidence that PRKAR1A gene variants and subclinical hyperthyroidism are related and suggest that subclinical hyperthyroidism may be a neglected phenotype of PRKAR1A gene variants and a novel component of CNC patients.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO, identifier CRD42021197655.</p

Cyclometalated Iridium Complex-Based Label-Free Photoelectrochemical Biosensor for DNA Detection by Hybridization Chain Reaction Amplification

Photoactive material is the most crucial factor which intimately determines analytical performances of the photoelectrochemical sensor. On the basis of the high affinity of dipyrido [3,2-a:2′,3′-c] phenazine (dppz) with DNA helix, a novel photoactive intercalator, [(ppy)₂Ir­(dppz)]⁺PF₆^–(ppy = 2-phenylpyridine and dppz = dipyrido [3,2-a:2′,3′-c] phenazine) was prepared and characterized by UV–vis absorption spectroscopy, fluorescence spectroscopy, and cyclic voltammetry. The photoelectrochemical properties of the as-prepared iridium­(III) complex immobilized on the ITO electrode was investigated. Either cathodic or anodic photocurrent generation can be observed when triethanolamine (TEOA) or dissolved O₂ is used as a sacrificial electron donor/acceptor, respectively. The probable photocurrent-generation mechanisms are speculated. A highly sensitive iridium­(III) complex-based photoelectrochemical sensor was proposed for DNA detection via hybridization chain reaction (HCR) signal amplification. Under optimal conditions, the biosensor was found to be linearly proportional to the logarithm of target DNA concentration in the range from 0.025 to 100 pmol L^–1 with a detection limit of 9.0 fmol L^–1 (3σ). Moreover, the proposed sensor displayed high selectivity and good reproducibility, demonstrating efficient and stable photoelectric conversion ability of the Ir­(III) complex

SNPs called from Tongcheng pool and seven Chinese wild boars

This table includes the genome-wide SNP data called from Tongcheng pool and seven Chinese wild boars. column 1 & 2: chromosome and position according to Sscrofa 10.2 assembly. column 3: the reference allele according to Sscrofa 10.2 assembly. column 4: the variant allele identified from sequencing data. column 5-11: genotypes of Chinese wild boars, and “00”means the missing genotype. column 12: count of reference allele reads identified from the Tongcheng sequencing pool. column 13: count of variant allele reads identified fromthe Tongcheng sequencing poo

SNPs called from 54 individually sequenced pigs at 102.3-102.675 Mb on chromosome 13

This table includes the SNP data at 102.3-102.675 Mb on chromosome 13, and the variants are called from 54 individually sequenced pigs from 11 populations. “00” indicates the missing genotype. column 1 & 2: chromosome and position according to Sscrofa 10.2 assembly. column 3: the reference allele according to Sscrofa 10.2 assembly. column 4: the variant allele identified from sequencing data. column 5- 8: genotypes of four Duroc pigs. column 9-12: genotypes of four Meishan pigs. column 13-19 genotypes of seven Chinese wild boars. column 20-22 genotypes of three Jinhua pigs. column 23-28 genotypes of six Landrace pigs. column 29-42 genotypes of 14 Large White pigs. column 43-45 genotypes of three Neijiang pigs. column 46-48 genotypes of three Penzhou pigs. column 49-52 genotypes of four Tongcheng pigs. column 53-55 genotypes of three Wujin pigs. column 56-58 genotypes of three Yanan pig

SNPs called from 54 individually sequenced pigs at 32.475-32.775 Mb on chromosome 3

This table includes the SNP data at 32.475-32.775 Mb on chromosome 3, and the variants are called from 54 individually sequenced pigs from 11 populations. “00” indicates the missing genotype. column 1 & 2: chromosome and position according to Sscrofa 10.2 assembly. column 3: the reference allele according to Sscrofa 10.2 assembly. column 4: the variant allele identified from sequencing data. column 5- 8: genotypes of four Duroc pigs. column 9-12: genotypes of four Meishan pigs. column 13-19 genotypes of seven Chinese wild boars. column 20-22 genotypes of three Jinhua pigs. column 23-28 genotypes of six Landrace pigs. column 29-42 genotypes of 14 Large White pigs. column 43-45 genotypes of three Neijiang pigs. column 46-48 genotypes of three Penzhou pigs. column 49-52 genotypes of four Tongcheng pigs. column 53-55 genotypes of three Wujin pigs. column 56-58 genotypes of three Yanan pig

SNPs called from 54 individually sequenced pigs at 60-109.95 Mb on chromosome X

This table includes the SNP data at 60-109.95 Mb on chromosome X, and the variants are called from 54 individually sequenced pigs from 11 populations. “00” indicates the missing genotype. column 1 & 2: chromosome and position according to Sscrofa 10.2 assembly. column 3: the reference allele according to Sscrofa 10.2 assembly. column 4: the variant allele identified from sequencing data. column 5- 8: genotypes of four Duroc pigs. column 9-12: genotypes of four Meishan pigs. column 13-19 genotypes of seven Chinese wild boars. column 20-22 genotypes of three Jinhua pigs. column 23-28 genotypes of six Landrace pigs. column 29-42 genotypes of 14 Large White pigs. column 43-45 genotypes of three Neijiang pigs. column 46-48 genotypes of three Penzhou pigs. column 49-52 genotypes of four Tongcheng pigs. column 53-55 genotypes of three Wujin pigs. column 56-58 genotypes of three Yanan pig

Table_3_Deciphering the underlying immune network of the potato defense response inhibition by Phytophthora infestans nuclear effector Pi07586 through transcriptome analysis.xls

Phytophthora infestans, a highly destructive plant oomycete pathogen, is responsible for causing late blight in potatoes worldwide. To successfully infect host cells and evade immunity, P. infestans secretes various effectors into host cells and exclusively targets the host nucleus. However, the precise mechanisms by which these effectors manipulate host gene expression and reprogram defenses remain poorly understood. In this study, we focused on a nuclear-targeted effector, Pi07586, which has been implicated in immune suppression. Quantitative real-time PCR (qRT-PCR) analysis showed Pi07586 was significant up-regulation during the early stages of infection. Agrobacterium-induced transient expression revealed that Pi07586 localized in the nucleus of leaf cells. Overexpression of Pi07586 resulted in increased leaf colonization by P. infestans. RNA-seq analysis revealed that Pi07586 effectively suppressed the expression of PR-1C-like and photosynthetic antenna protein genes. Furthermore, high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS) analysis indicated that Pi07586 overexpression led to a substantial decrease in abscisic acid (ABA), jasmonic acid (JA), and jasmonoyl-isoleucine (JA-Ile) levels, while not affecting salicylic acid (SA) and indole-3-acetic acid (IAA) production. These findings shed new light on the modulation of plant immunity by Pi07586 and enhance our understanding of the intricate relationship between P. infestans and host plants.</p

Table_1_Deciphering the underlying immune network of the potato defense response inhibition by Phytophthora infestans nuclear effector Pi07586 through transcriptome analysis.xlsx

Phytophthora infestans, a highly destructive plant oomycete pathogen, is responsible for causing late blight in potatoes worldwide. To successfully infect host cells and evade immunity, P. infestans secretes various effectors into host cells and exclusively targets the host nucleus. However, the precise mechanisms by which these effectors manipulate host gene expression and reprogram defenses remain poorly understood. In this study, we focused on a nuclear-targeted effector, Pi07586, which has been implicated in immune suppression. Quantitative real-time PCR (qRT-PCR) analysis showed Pi07586 was significant up-regulation during the early stages of infection. Agrobacterium-induced transient expression revealed that Pi07586 localized in the nucleus of leaf cells. Overexpression of Pi07586 resulted in increased leaf colonization by P. infestans. RNA-seq analysis revealed that Pi07586 effectively suppressed the expression of PR-1C-like and photosynthetic antenna protein genes. Furthermore, high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS) analysis indicated that Pi07586 overexpression led to a substantial decrease in abscisic acid (ABA), jasmonic acid (JA), and jasmonoyl-isoleucine (JA-Ile) levels, while not affecting salicylic acid (SA) and indole-3-acetic acid (IAA) production. These findings shed new light on the modulation of plant immunity by Pi07586 and enhance our understanding of the intricate relationship between P. infestans and host plants.</p

Table_2_Deciphering the underlying immune network of the potato defense response inhibition by Phytophthora infestans nuclear effector Pi07586 through transcriptome analysis.xlsx

Phytophthora infestans, a highly destructive plant oomycete pathogen, is responsible for causing late blight in potatoes worldwide. To successfully infect host cells and evade immunity, P. infestans secretes various effectors into host cells and exclusively targets the host nucleus. However, the precise mechanisms by which these effectors manipulate host gene expression and reprogram defenses remain poorly understood. In this study, we focused on a nuclear-targeted effector, Pi07586, which has been implicated in immune suppression. Quantitative real-time PCR (qRT-PCR) analysis showed Pi07586 was significant up-regulation during the early stages of infection. Agrobacterium-induced transient expression revealed that Pi07586 localized in the nucleus of leaf cells. Overexpression of Pi07586 resulted in increased leaf colonization by P. infestans. RNA-seq analysis revealed that Pi07586 effectively suppressed the expression of PR-1C-like and photosynthetic antenna protein genes. Furthermore, high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS) analysis indicated that Pi07586 overexpression led to a substantial decrease in abscisic acid (ABA), jasmonic acid (JA), and jasmonoyl-isoleucine (JA-Ile) levels, while not affecting salicylic acid (SA) and indole-3-acetic acid (IAA) production. These findings shed new light on the modulation of plant immunity by Pi07586 and enhance our understanding of the intricate relationship between P. infestans and host plants.</p

MOESM4 of Uncoordinated expression of DNA methylation-related enzymes in human cancer

Additional file 4: Table S2. Correlations among DNA methylation-related enzymes in 26 human tissues. The RNA-Seq gene expression data of 7 DNA methylation-related enzymes were obtained from the GTEx dataset. The correlations among the expression levels of the 7 enzymes in 26 human tissues are analyzed and shown. A multiple-testing correction was done by using Benjamini–Hochberg procedure. The corrected p value is shown only when the p value was changed from < 0.05 to > 0.05 after the correction