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The syndrome of multiple morphological abnormalities of the sperm flagella (MMAF) is a specific kind of asthenoteratozoospermia with a mosaic of flagellar morphological abnormalities (absent, short, bent, coiled, and irregular flagella). MMAF was proposed in 2014 and has attracted increasing attention; however, it has not been clearly understood. In this review, we elucidate the definition of MMAF from a systematical view, the difference between MMAF and other conditions with asthenoteratozoospermia or asthenozoospermia (such as primary mitochondrial sheath defects and primary ciliary dyskinesia), the knowledge regarding its etiological mechanism and related genetic findings, and the clinical significance of MMAF for intracytoplasmic sperm injection and genetic counseling. This review provides the basic knowledge for MMAF and puts forward some suggestions for further investigations.

Cardiomyopathy is a group of disease characterized by structural and functional damage to the myocardium. The etiologies of cardiomyopathies are diverse, spanning from genetic mutations impacting fundamental myocardial functions to systemic disorders that result in widespread cardiac damage. Many specific gene mutations cause primary cardiomyopathy. Environmental factors and metabolic disorders may also lead to the occurrence of cardiomyopathy. This review provides an in‐depth analysis of the current understanding of the pathogenesis of various cardiomyopathies, highlighting the molecular and cellular mechanisms that contribute to their development and progression. The current therapeutic interventions for cardiomyopathies range from pharmacological interventions to mechanical support and heart transplantation. Gene therapy and cell therapy, propelled by ongoing advancements in overarching strategies and methodologies, has also emerged as a pivotal clinical intervention for a variety of diseases. The increasing number of causal gene of cardiomyopathies have been identified in recent studies. Therefore, gene therapy targeting causal genes holds promise in offering therapeutic advantages to individuals diagnosed with cardiomyopathies. Acting as a more precise approach to gene therapy, they are gradually emerging as a substitute for traditional gene therapy. This article reviews pathogenesis and therapeutic interventions for different cardiomyopathies. Cardiomyopathy is a group of diseases characterized by structural and functional damage to the myocardium. Many specific gene mutations, environmental factors, and metabolic disorders may cause cardiomyopathy. Traditional therapeutic includes drug and surgery. With the growing comprehension of the molecular mechanisms underlying cardiomyopathy. Gene therapy and cell therapy has become a tool for the clinical treatment of disease.

High-throughput genomic technologies yield about 20,000 variants in the protein-coding exome of each individual. A commonly used approach to select candidate disease-causing variants is to test whether the associated gene has been previously reported to be disease-causing. In the absence of known disease-causing genes, it can be challenging to associate candidate genes with specific genetic diseases. To facilitate the discovery of novel gene-disease associations, we determined the putative biologically closest known genes and their associated diseases for 13,005 human genes not currently reported to be disease-associated. We used these data to construct the closest disease-causing genes (CDG) server, which can be used to infer the closest genes with an associated disease for a user-defined list of genes or diseases. We demonstrate the utility of the CDG server in five immunodeficiency patient exomes across different diseases and modes of inheritance, where CDG dramatically reduced the number of candidate genes to be evaluated. This resource will be a considerable asset for ascertaining the potential relevance of genetic variants found in patient exomes to specific diseases of interest. The CDG database and online server are freely available to non-commercial users at: http://lab.rockefeller.edu/casanova/CDG.

Background Prediction of pathogenic genes is crucial for disease prevention, diagnosis, and treatment. But traditional genetic localization methods are often technique-difficulty and time-consuming. With the development of computer science, computational biology has gradually become one of the main methods for finding candidate pathogenic genes. Methods We propose a pathogenic genes prediction method based on network embedding which is called Multipath2vec. Firstly, we construct an heterogeneous network which is called GP −network. It is constructed based on three kinds of relationships between genes and phenotypes, including correlations between phenotypes, interactions between genes and known gene-phenotype pairs. Then in order to embedding the network better, we design the multi-path to guide random walk in GP −network. The multi-path includes multiple paths between genes and phenotypes which can capture complex structural information of heterogeneous network. Finally, we use the learned vector representation of each phenotype and protein to calculate the similarities and rank according to the similarities between candidate genes and the target phenotype. Results We implemented Multipath2vec and four baseline approaches (i.e., CATAPULT, PRINCE, Deepwalk and Metapath2vec) on many-genes gene-phenotype data, single-gene gene-phenotype data and whole gene-phenotype data. Experimental results show that Multipath2vec outperformed the state-of-the-art baselines in pathogenic genes prediction task. Conclusions We propose Multipath2vec that can be utilized to predict pathogenic genes and experimental results show the higher accuracy of pathogenic genes prediction.

Background Cleft lip (CL) is one of the most common congenital birth defects with complex etiology. While genome-wide association studies (GWAS) have made significant advances in our understanding of mutations and their related genes with potential involvement in the etiology of CL, it remains unknown how these genes are functionally regulated and interact with each other in lip development. Currently, identifying the disease-causing genes in human CL is urgently needed. So far, the causative CL genes have been largely undiscovered, making it challenging to design experiments to validate the functional influence of the mutations identified from large genomic studies such as CL GWAS. Results Transcription factors (TFs) and microRNAs (miRNAs) are two important regulators in cellular system. In this study, we aimed to investigate the genetic interactions among TFs, miRNAs and the CL genes curated from the previous studies. We constructed miRNA-TF co-regulatory networks, from which the critical regulators as putative drivers in CL were examined. Based on the constructed networks, we identified ten critical hub genes with prior evidence in CL. Furthermore, the analysis of partitioned regulatory modules highlighted a number of biological processes involved in the pathology of CL, including a novel pathway “Signaling pathway regulating pluripotency of stem cells”. Our subnetwork analysis pinpointed two candidate miRNAs, hsa-mir-27b and hsa-mir-497 , activating the Wnt pathway that was associated with CL. Our results were supported by an independent gene expression dataset in CL. Conclusions This study represents the first regulatory network analysis of CL genes. Our work presents a global view of the CL regulatory network and a novel approach on investigating critical miRNAs, TFs and genes via combinatory regulatory networks in craniofacial development. The top genes and miRNAs will be important candidates for future experimental validation of their functions in CL.

Identification of disease-causing genes among a large number of candidates is a fundamental challenge in human disease stud- ies. However, it is still time-consuming and laborious to determine the real disease-causing genes by biological experiments. With the advances of the high-throughput techniques, a large number of protein-protein interactions have been produced. Therefore, to address this issue, several methods based on protein interaction network have been proposed. In this paper, we propose a shortest path-based algorithm, named SPranker, to prioritize disease-causing genes in protein interaction networks. Considering the fact that diseases with similar phenotypes are generally caused by functionally related genes, we further pro- pose an improved algorithm SPGOranker by integrating the semantic similarity of gene ontology （GO） annotations. SPGOranker not only considers the topological similarity between protein pairs in a protein interaction network but also takes their functional similarity into account. The proposed algorithms SPranker and SPGOranker were applied to 1598 known or- phan disease-causing genes from 172 orphan diseases and compared with three state-of-the-art approaches, ICN, VS and RWR The experimental results show that SPranker and SPGOranker outperform ICN, VS, and RWR for the prioritization of orphan disease-causing genes. Importantly, for the case study of severe combined immunodeficiency, SPranker and SPGOranker predict several novel causal genes.

This chapter contains sections titled: Introduction A Classic Mendelian Cattle Trait: Presence/Absence of Horns Bovine Mendelian Traits Characterized at the DNA Level A (Mostly) Morbid Map of the Bovine Genome Other Bovine Mendelian Traits Conclusion References

Anorectal malformations (ARM) constitute a heterogeneous group of rare congenital anomalies affecting the cloaca. Although genetic factors are implicated in ARM pathogenesis, our understanding of the underlying molecular mechanisms remains limited for both non-syndromic and syndromic ARM. Despite recent advancements, the genes identified so far account for only about 30% of the diagnostic yield from exome sequencing. Our study aimed to identify potential novel disease-causing mutations associated with ARMs. We performed exome sequencing on 12 patients with ARM and discovered a pathogenic single nucleotide polymorphism (SNP) in the MFHAS1 gene in two individuals with non-syndromic ARM. Additionally, we identified insertion/deletion (INDEL) and splice-site variants in five genes - SOX9, AOC4P, SKA3, KRTAP5-7, and PRSS2. Despite the insights provided by our study regarding the association of these variants with ARM occurrence, further functional and segregation studies in larger cohorts are necessary to validate these findings.

Background FIGLA is a transcription factor gene which plays a critical role in folliculogenesis. Consistent with this, FIGLA variants have been identified in females with non‐syndromic primary ovarian insufficiency (POI) in both autosomal‐dominant and autosomal‐recessive forms. Case Description We encountered two Japanese sisters who had secondary or primary amenorrhea at 15 years of age. They were diagnosed as having non‐syndromic primary ovarian insufficiency (POI) with hypergonadotropic hypoestrogenism and markedly low serum anti‐Müllerian hormone values. Outcome Whole genome sequencing revealed a novel homozygous missense variant, NM_001004311.3:c.338A>G:p.(Tyr113Cys), in FIGLA essential for folliculogenesis in the two sisters. The parents were heterozygous for this variant, and the heterozygous mother had regular menses at 51 years of age. This variant was extremely rare in public databases, and was invariably assessed as deleterious by six prediction tools. Furthermore, the p.(Tyr113Cys)‐FIGLA protein was assessed as “pathogenic” or “likely pathogenic” by protein structural predictions, and was evaluated as “destabilizing” or “decrease stability” by protein stability predictions Conclusion The results, in conjunction with the data reported in the literature, imply that FIGLA variants account for a small but certain fraction of non‐syndromic POI, and pose a question as to the relevance of FIGLA variants to an autosomal dominant form of POI, although FIGLA variants have been identified in both autosomal dominant and autosomal recessive forms of non‐syndromic POI. FIGLA is a transcription factor gene which is expressed in the very early stage of female germ cells and plays a critical role in folliculogenesis. Here, we report a homozygous FIGLA variant identified in two Japanese sisters with non‐syndromic primary ovarian insufficiency (POI), and review the previously reported autosomal‐dominant and autosomal‐recessive FIGLA variants. The results imply that FIGLA variants account for a small but certain fraction of non‐syndromic POI and pose a question as to the presence of autosomal‐dominant FIGLA variants.

Background Waardenburg syndrome (WS) is a rare genetic disorder mainly characterized by hearing loss and pigmentary abnormalities. Currently, seven causative genes have been identified for WS, but clinical genetic testing results show that 38.9% of WS patients remain molecularly unexplained. In this study, we performed multi-data integration analysis through protein-protein interaction and phenotype-similarity to comprehensively decipher the potential causative factors of undiagnosed WS. In addition, we explored the association between genotypes and phenotypes in WS with the manually collected 443 cases from published literature. Results We predicted two possible WS pathogenic genes ( KIT , CHD7 ) through multi-data integration analysis, which were further supported by gene expression profiles in single cells and phenotypes in gene knockout mouse. We also predicted twenty, seven, and five potential WS pathogenic variations in gene PAX3 , MITF , and SO X10, respectively. Genotype-phenotype association analysis showed that white forelock and telecanthus were dominantly present in patients with PAX3 variants; skin freckles and premature graying of hair were more frequently observed in cases with MITF variants; while aganglionic megacolon and constipation occurred more often in those with SOX10 variants. Patients with variations of PAX3 and MITF were more likely to have synophrys and broad nasal root. Iris pigmentary abnormality was more common in patients with variations of PAX3 and SOX10 . Moreover, we found that patients with variants of SOX10 had a higher risk of suffering from auditory system diseases and nervous system diseases, which were closely associated with the high expression abundance of SOX10 in ear tissues and brain tissues. Conclusions Our study provides new insights into the potential causative factors of WS and an alternative way to explore clinically undiagnosed cases, which will promote clinical diagnosis and genetic counseling. However, the two potential disease-causing genes ( KIT , CHD7 ) and 32 potential pathogenic variants ( PAX3 : 20, MITF : 7, SOX10 : 5) predicted by multi-data integration in this study are all computational predictions and need to be further verified through experiments in follow-up research.