Next-generation sequencing identifies novel genes with rare variants in total anomalous pulmonary venous connection

Identification of novel candidate genes in heterotaxy syndrome patients with congenital heart diseases by whole exome sequencing

Heterotaxy syndrome (HS) involves dysfunction of multiple systems resulting from abnormal left-right (LR) body patterning. Most HS patients present with complex congenital heart diseases (CHD), the disability and mortality of HS patients are extremely high. HS has great heterogeneity in phenotypes and genotypes, which have rendered gene discovery challenging. The aim of this study was to identify novel genes that underlie pathogenesis of HS patients with CHD. Whole exome sequencing was performed in 25 unrelated HS cases and 100 healthy controls; 19 nonsynonymous variants in 6 novel candidate genes (FLNA, ITGA1, PCNT, KIF7, GLI1, KMT2D) were identified. The functions of candidate genes were further analyzed in zebrafish model by CRISPR/Cas9 technique. Genome-editing was successfully introduced into the gene loci of flna, kmt2d and kif7, but the phenotypes were heterogenous. Disruption of each gene disturbed normal cardiac looping while kif7 knockout had a more prominent effect on liver budding and pitx2 expression. Our results revealed three potential HS pathogenic genes with probably different molecular mechanisms.

Identification of Post-myocardial Infarction Blood Expression Signatures Using Multiple Feature Selection Strategies

Myocardial infarction (MI) is a type of serious heart attack in which the blood flow to the heart is suddenly interrupted, resulting in injury to the heart muscles due to a lack of oxygen supply. Although clinical diagnosis methods can be used to identify the occurrence of MI, using the changes of molecular markers or characteristic molecules in blood to characterize the early phase and later trend of MI will help us choose a more reasonable treatment plan. Previously, comparative transcriptome studies focused on finding differentially expressed genes between MI patients and healthy people. However, signature molecules altered in different phases of MI have not been well excavated. We developed a set of computational approaches integrating multiple machine learning algorithms, including Monte Carlo feature selection (MCFS), incremental feature selection (IFS), and support vector machine (SVM), to identify gene expression characteristics on different phases of MI. 134 genes were determined to serve as features for building optimal SVM classifiers to distinguish acute MI and post-MI. Subsequently, functional enrichment analyses followed by protein-protein interaction analysis on 134 genes identified several hub genes (IL1R1, TLR2, and TLR4) associated with progression of MI, which can be used as new diagnostic molecules for MI.

In Silico Analysis Identifies Differently Expressed lncRNAs as Novel Biomarkers for the Prognosis of Thyroid Cancer

Background

Thyroid cancer (TC) is one of the most common type of endocrine tumors. Long noncoding RNAs had been demonstrated to play key roles in TC. Material and Methods. The lncRNA expression data were downloaded from Co-lncRNA database. The raw data was normalized using the limma package in R software version 3.3.0. The differentially expressed mRNA and lncRNAs were identified by the linear models for the microarray analysis (Limma) method. The DEGs were obtained with thresholds of ∣logFC∣ > 1.5 and P < 0.001. The hierarchical cluster analysis of differentially expressed mRNAs and lncRNAs was performed using CLUSTER 3.0, and the hierarchical clustering heat map was visualized by Tree View.

Results

In the present study, we identified 6 upregulated and 85 downregulated lncRNAs in TC samples. Moreover, we for the first time identified 16 downregulated lncRNAs was correlated to longer disease-free survival time in patients with TC, including ATP1A1-AS1, CATIP-AS1, FAM13A-AS1, LINC00641, LINC00924, MIR22HG, NDUFA6-AS1, RP11-175K6.1, RP11-727A23.5, RP11-774O3.3, RP13-895J2.2, SDCBP2-AS1, SLC26A4-AS1, SNHG15, SRP14-AS1, and ZNF674-AS1.

Conclusions

Bioinformatics analysis revealed these lncRNAs were involved in regulating the RNA metabolic process, cell migration, organelle assembly, tRNA modification, and hormone levels. This study will provide useful information to explore the potential candidate biomarkers for diagnosis, prognosis, and drug targets for TC.

Identification of rare variants in novel candidate genes in pulmonary atresia patients by next generation sequencing

Pulmonary atresia (PA) is a rare congenital heart defect (CHD) with complex manifestations and a high mortality rate. Since the genetic determinants in the pathogenesis of PA remain elusive, a thorough identification of the genetic factors through whole exome sequencing (WES) will provide novel insights into underlying mechanisms of PA. We performed WES data from PA/VSD (n = 60), PA/IVS (n = 20), TOF/PA (n = 20) and 100 healthy controls. Rare variants and novel genes were identified using variant-based association and gene-based burden analysis. Then we explored the expression pattern of our candidate genes in endothelium cell lines, pulmonary artery tissues, and embryonic hearts. 56 rare damage variants of 7 novel candidate genes (DNAH10, DST, FAT1, HMCN1, HNRNPC, TEP1, and TYK2) were certified to have function in PA pathogenesis for the first time. In our research, the genetic pattern among PA/VSD, PA/IVS and TOF/PA were different to some degree. Taken together, our findings contribute new insights into the molecular basis of this rare congenital birth defect.

HMGA Genes and Proteins in Development and Evolution

HMGA (high mobility group A) (HMGA1 and HMGA2) are small non-histone proteins that can bind DNA and modify chromatin state, thus modulating the accessibility of regulatory factors to the DNA and contributing to the overall panorama of gene expression tuning. In general, they are abundantly expressed during embryogenesis, but are downregulated in the adult differentiated tissues. In the present review, we summarize some aspects of their role during development, also dealing with relevant studies that have shed light on their functioning in cell biology and with emerging possible involvement of HMGA1 and HMGA2 in evolutionary biology.

Research Progress in Pathogenesis of Total Anomalous Pulmonary Venous Connection

Congenital heart defect (CHD) is one of the most common birth defects and the leading course of infant mortality. Total anomalous pulmonary venous connection (TAPVC) is a rare type of cyanotic which accounting for approximately 1-3% of congenital heart disease cases. Based on where the anomalous veins drain, TAPVC can be divided into four subtypes: supracardiac, cardiac, infracardiac, and mixed. In TAPVC, all pulmonary veins fail to link to the left atrium correctly but make abnormal connections to the right atrium or systemic venous system. The mortality of TAPVC patients without proper intervention is nearly 80% in the first year of life and 50% of them died within 3 months after birth. However, the pathogenesis and mechanism of TAPVC remains elusive. In this chapter, we systematically review the epidemiology, anatomy, and pathophysiology of TAPVC and give an overview of the research progress of TAPVC pathogenesis.