Treatment of donor cells with recombinant KDM4D protein improves preimplantation development of cloned ovine embryos

Incomplete epigenetic reprogramming is one of the major factors affecting the development of embryos cloned by somatic cell nuclear transfer (SCNT). Histone 3 lysine 9 (H3K9) trimethylation has been identified as a key barrier to efficient reprogramming by SCNT. The aim of this study was to explore a method of downregulating H3K9me3 levels in donor cells by using histone lysine demethylase (KDM) protein. When sheep fetal fibroblast cells were treated with recombinant human KDM4D protein (rhKDM4D), the levels of H3K9 trimethylation and dimethylation were both significantly decreased. After SCNT, rhKDM4D-treated donor cells supported significantly higher percentage of cloned embryos developing into blastocysts as compared to non-treated control cells. Moreover, the blastocyst quality was also improved by rhKDM4D treatment of donor cells, as assessed by the total cell number in blastocysts and the expression of developmental genes including SOX2, NANOG and CDX2. These results indicate that treatment of donor cells with recombinant KDM4D protein can downregulate the levels of H3K9 trimethylation and dimethylation and improve the developmental competence of SCNT embryos. This strategy may be convenient to be used in KDM4-assisted SCNT procedure for improving the efficiency of cloning.     

Knockout of <Emphasis Type="Italic">CTNNB1</Emphasis> by CRISPR-Cas9 technology inhibits cell proliferation through the Wnt/β-catenin signaling pathway

Objective

To study the effects of CTNNB1 gene knockout by CRISPR-Cas9 technology on cell adhesion, proliferation, apoptosis, and Wnt/β-catenin signaling pathway.

Results

CTNNB1 gene of HEK 293T cells was knocked out by CRISPR-Cas9. This was confirmed by sequencing and western blotting. Methylthiazolyl-tetrazolium bromide assays indicated that deletion of β-catenin significantly weakened adhesion ability and inhibited proliferation rate (P < 0.01) of HEK 293T cells. Nevertheless, deletion of β-catenin did not affect apoptosis of HEK 293T cells, which was analyzed by flow cytometry with Annexin V-fluorescein isothiocyanate/propidium iodide double staining. In addition, expression level of GSK-3β, CCND1, and CCNE1 detected by qPCR and expression level of N-Cadherin and cyclin D1 detected by western blotting were significantly decreased (P < 0.01) while expression of γ-catenin detected by western blotting was significantly increased (P < 0.001).

Conclusions

Knockout of CTNNB1 disturbed Wnt/β-catenin signaling pathway and significantly inhibited adhesion and proliferation of HEK 293T cells.

     

Genomic analyses based on pulmonary adenocarcinoma in situ reveal early lung cancer signature

Background

Non-small cell lung cancer (NSCLC) represents more than about 80% of the lung cancer. The early stages of NSCLC can be treated with complete resection with a good prognosis. However, most cases are detected at late stage of the disease. The average survival rate of the patients with invasive lung cancer is only about 4%. Adenocarcinoma in situ (AIS) is an intermediate subtype of lung adenocarcinoma that exhibits early stage growth patterns but can develop into invasion.

Methods

In this study, we used RNA-seq data from normal, AIS, and invasive lung cancer tissues to identify a gene module that represents the distinguishing characteristics of AIS as AIS-specific genes. Two differential expression analysis algorithms were employed to identify the AIS-specific genes. Then, the subset of the best performed AIS-specific genes for the early lung cancer prediction were selected by random forest. Finally, the performances of the early lung cancer prediction were assessed using random forest, support vector machine (SVM) and artificial neural networks (ANNs) on four independent early lung cancer datasets including one tumor-educated blood platelets (TEPs) dataset.

Results

Based on the differential expression analysis, 107 AIS-specific genes that consisted of 93 protein-coding genes and 14 long non-coding RNAs (lncRNAs) were identified. The significant functions associated with these genes include angiogenesis and ECM-receptor interaction, which are highly related to cancer development and contribute to the smoking-free lung cancers. Moreover, 12 of the AIS-specific lncRNAs are involved in lung cancer progression by potentially regulating the ECM-receptor interaction pathway. The feature selection by random forest identified 20 of the AIS-specific genes as early stage lung cancer signatures using the dataset obtained from The Cancer Genome Atlas (TCGA) lung adenocarcinoma samples. Of the 20 signatures, two were lncRNAs, BLACAT1 and CTD-2527I21.15 which have been reported to be associated with bladder cancer, colorectal cancer and breast cancer. In blind classification for three independent tissue sample datasets, these signature genes consistently yielded about 98% accuracy for distinguishing early stage lung cancer from normal cases. However, the prediction accuracy for the blood platelets samples was only 64.35% (sensitivity 78.1%, specificity 50.59%, and AUROC 0.747).

Conclusions

The comparison of AIS with normal and invasive tumor revealed diseases-specific genes and offered new insights into the mechanism underlying AIS progression into an invasive tumor. These genes can also serve as the signatures for early diagnosis of lung cancer with high accuracy. The expression profile of gene signatures identified from tissue cancer samples yielded remarkable early cancer prediction for tissues samples, however, relatively lower accuracy for boold platelets samples.

     

Identification of cancer subtypes from single-cell RNA-seq data using a consensus clustering method

Background

Human cancers are complex ecosystems composed of cells with distinct molecular signatures. Such intratumoral heterogeneity poses a major challenge to cancer diagnosis and treatment. Recent advancements of single-cell techniques such as scRNA-seq have brought unprecedented insights into cellular heterogeneity. Subsequently, a challenging computational problem is to cluster high dimensional noisy datasets with substantially fewer cells than the number of genes.

Methods

In this paper, we introduced a consensus clustering framework conCluster, for cancer subtype identification from single-cell RNA-seq data. Using an ensemble strategy, conCluster fuses multiple basic partitions to consensus clusters.

Results

Applied to real cancer scRNA-seq datasets, conCluster can more accurately detect cancer subtypes than the widely used scRNA-seq clustering methods. Further, we conducted co-expression network analysis for the identified melanoma subtypes.

Conclusions

Our analysis demonstrates that these subtypes exhibit distinct gene co-expression networks and significant gene sets with different functional enrichment.

     

润楠属植物叶片和枝条水力特征的协同关系

以润楠属(Machilus) 7种植物成年个体为材料,对其进行生理指标测定,并对它们的叶片水分供需关系以及木质部纹孔特征和导水效率之间的关联进行分析。结果显示,润楠属7种植物相比原始被子植物具有更高的叶脉密度(VD),叶脉密度为9.8～14.1 mm/mm~2;气孔密度(SD)与叶脉密度呈显著正相关,说明叶片水分供需存在协同关系;气孔密度与气孔大小(GLC)呈负相关;气孔越大的叶片其膨压丧失点(TLP)的绝对值越低。枝条边材比导率(Ks)较低,为0.13～1.87 kg·m~(-1)·s~(-1)·MPa~(-1),且种间差异较大。叶脉和气孔密度均与边材比导率呈正相关。边材比导率与纹孔膜面积、纹孔口面积以及纹孔口长短轴比例相关性不显著。研究结果表明润楠属植物虽然叶脉密度较高,且木质部水分供应和叶片结构具有协同关系,但木质部解剖结构较为原始,导管多具梯形穿孔板,导水效率低,只能适应比较湿润的生境。     

Molecular evolution of maize catalases and their relationship to other eukaryotic and prokaryotic catalases

We have compared the nucleotide and protein sequences of the three maize catalase genes with other plant catalases to reconstruct the evolutionary relationship among these catalases. These sequences were also compared with other eukaryotic and prokaryotic catalases. Phylogenies based on distances and parsimony analysis show that all plant catalases derive from a common ancestral catalase gene and can be divided into three distinct groups. The first, and major, group includes maizeCatl, barleyCat1, riceCatB and most of the dicot catalases. The second group is an apparent dicot-specific catalase group encompassing the tobaccoCat2 and tomatoCat. The third is a monocot-specific catalase class including the maize Cat3, barley Cat2, and riceCatA. The maize Cat2 gene is loosely related to the first group. The distinctive features of monocot-specific catalases are their extreme high codon bias at the third position and low degree of sequence similarity to other plant catalases. Similarities in the intron positions for several plant catalase genes support the conclusion of derivation from a common ancestral gene. The similar intron position between bean catalases and human catalase implies that the animal and plant catalases might have derived from a common progenitor gene sequence. Correspondence to: J.G. Scandalios