Identification of de novo germline mutations and causal genes for sporadic diseases using trio‐based whole‐exome/genome sequencing

Whole‐genome or whole‐exome sequencing (WGS/WES) of the affected proband together with normal parents (trio) is commonly adopted to identify de novo germline mutations (DNMs) underlying sporadic cases of various genetic disorders. However, our current knowledge of the occurrence and functional effects of DNMs remains limited and accurately identifying the disease‐causing DNM from a group of irrelevant DNMs is complicated. Herein, we provide a general‐purpose discussion of important issues related to pathogenic gene identification based on trio‐based WGS/WES data. Specifically, the relevance of DNMs to human sporadic diseases, current knowledge of DNM biogenesis mechanisms, and common strategies or software tools used for DNM detection are reviewed, followed by a discussion of pathogenic gene prioritization. In addition, several key factors that may affect DNM identification accuracy and causal gene prioritization are reviewed. Based on recent major advances, this review both sheds light on how trio‐based WGS/WES technologies can play a significant role in the identification of DNMs and causal genes for sporadic diseases, and also discusses existing challenges.     

Threat to the point: improving the value of comparative extinction risk analysis for conservation action

Comparative extinction risk analysis is a common approach for assessing the relative plight of biodiversity and making conservation recommendations. However, the usefulness of such analyses for conservation practice has been questioned. One reason for underperformance may be that threats arising from global environmental changes (e.g., habitat loss, invasive species, climate change) are often overlooked, despite being widely regarded as proximal drivers of species’ endangerment. We explore this problem by (i) reviewing the use of threats in this field and (ii) quantitatively investigating the effects of threat exclusion on the interpretation and potential application of extinction risk model results. We show that threat variables are routinely (59%) identified as significant predictors of extinction risk, yet while most studies (78%) include extrinsic factors of some kind (e.g., geographic or bioclimatic information), the majority (63%) do not include threats. Despite low overall usage, studies are increasingly employing threats to explain patterns of extinction risk. However, most continue to employ methods developed for the analysis of heritable traits (e.g., body size, fecundity), which may be poorly suited to the treatment of nonheritable predictors including threats. In our global mammal and continental amphibian extinction risk case studies, omitting threats reduced model predictive performance, but more importantly (i) reduced mechanistic information relevant to management; (ii) resulted in considerable disagreement in species classifications (12% and 5% for amphibians and mammals, respectively, translating to dozens and hundreds of species); and (iii) caused even greater disagreement (20–60%) in a downstream conservation application (species ranking). We conclude that the use of threats in comparative extinction risk analysis is important and increasing but currently in the early stages of development. Priorities for future studies include improving uptake, availability, quality and quantification of threat data, and developing analytical methods that yield more robust, relevant and tangible products for conservation applications.     

Network‐based global inference of human disease genes

Deciphering the genetic basis of human diseases is an important goal of biomedical research. On the basis of the assumption that phenotypically similar diseases are caused by functionally related genes, we propose a computational framework that integrates human protein–protein interactions, disease phenotype similarities, and known gene–phenotype associations to capture the complex relationships between phenotypes and genotypes. We develop a tool named CIPHER to predict and prioritize disease genes, and we show that the global concordance between the human protein network and the phenotype network reliably predicts disease genes. Our method is applicable to genetically uncharacterized phenotypes, effective in the genome‐wide scan of disease genes, and also extendable to explore gene cooperativity in complex diseases. The predicted genetic landscape of over 1000 human phenotypes, which reveals the global modular organization of phenotype–genotype relationships. The genome‐wide prioritization of candidate genes for over 5000 human phenotypes, including those with under‐characterized disease loci or even those lacking known association, is publicly released to facilitate future discovery of disease genes.     

Prioritization of orphan disease-causing genes using topological feature and GO similarity between proteins in interaction networks

Identification of disease-causing genes among a large number of candidates is a fundamental challenge in human disease studies. 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 propose an improved algorithm SPGOranker by integrating the semantic similarity of 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 orphan 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.     

雌激素受体基因和长白猪繁殖性能相关研究

通过检测612头长白母猪共2 239窝ESR基因的PvuⅡ酶切多态性,分析了不同ESR基因型和长白母猪繁殖性状的相关,以确定ESR基因在猪育种应用的可能性.头胎母猪、第2胎母猪和3胎以上母猪的资料分开统计.群体中B等位基因的频率很低,但似然比检验结果显示群体的基因频率处于哈代-温伯格连锁平衡状态.第1胎BB基因型母猪的总产仔数显著高于AA型母猪(12.05±0.82 vs 10.19±0.24)(P＜0.05),但BB基因型母猪的初生仔猪重显著低于AA型母猪(1.23±0.07vs 1.42±0.02)(P＜0.05).第3胎以上资料合并,BB基因型母猪的总产仔数显著多于AA和AB基因型母猪(11.98±0.63 vs10.90±0.48/10.92±0.51)(P＜0.05),产活仔数显著高于AA型母猪(10.31±0.58 vs 9.43±0.45)(P＜0.05);AB基因型母猪初生仔猪重显著低于AA型母猪(1.44±0.04 vs 1.48±0.04)(P＜0.05).所有资料合并,BB基因型母猪的总产仔数极显著高于AB型母猪(11.63±0.52 VS 10.63±0.42)(P＜0.01),显著高于AA型母猪(11.63±0.52 vs 10.70±0.40)(P＜0.05);BB基因型母猪的产活仔数显著高于AB和AA基因型母猪(10.15±0.50 vs 9.33±0.39/9.41±0.41)(P＜0.05).其余情况下各基因型母猪间繁殖性状间差异不显著(P＞0.05).总之,BB基因型母猪的总产仔数和产活仔数优于其他基因型母猪,但仔猪初生重较低.ESR基因可以作为遗传标记,用于本群长白猪产仔数的选择.     

猪肌细胞生成素基因对部分生长性状的影响

采用PCR-SSCP方法对长白猪、大白猪、杜洛克猪、山西黑猪和马身猪的肌细胞生成素（Myogenin,简称MyoG）基因进行单核苷酸多态性检测,并分析MyoG基因对猪的初生重、断奶重、6月龄重和背膘厚的影响。根据猪MyoG基因的DNA序列设计10对引物,发现In2-3引物扩增的片段有多态性。统计结果发现,3种基因型（AA、AB、BB）在各品种中的分布不一致。χ^2独立性检验表明,基因型频率在外来猪种（长白猪、大白猪、杜洛克猪）与地方猪种（山西黑猪、马身猪）间存在显著差异（P〈0．05）。固定效应模型分析结果表明,初生重和背膘厚基因型间差异显著（P〈0．05）,而断奶重和6月龄重基因型间差异不显著（P〉0．05）。最小二乘分析结果表明,BB基因型与其他两种基因型比较有较小的初生重,同AA和AB型比较差异极显著（P〈0．01）,3种基因型在初生重的大小排列顺序为AA〉AB〉BB;AA基因型与其他两种基因型比较有较小的背膘厚,同AB和BB型比较差异极显著（P〈0．01）,3种基因型在背膘厚的大小排列顺序为AA〈AB〈BB。因此,推测基因型对个体的初生重和胴体瘦肉率存在一定的影响,选择带有A等位基因的个体有望提高个体的初生重和胴体的瘦肉率。     

Myogenin基因的分子生物学综述

对肌细胞生成素(myogenin,MyoG)的作用机制及其基因的定位、结构、遗传变异及其与经济性状的关系等进行了综述。     

Functional and association studies of the cholesteryl ester transfer protein (CETP) gene in a Wannan Black pig model

Some polymorphisms of the human CETP gene are causally and significantly associated with serum lipids levels; however, the information regarding this gene in pigs is sparse. To evaluate the effects of CETP on blood lipid traits and fat deposition in pig, porcine CETP tissue expression patterns were observed by quantitative real‐time polymerase chain reaction (qPCR) first. High expression was detected in liver, spleen, gluteus medius (GM) muscle and backfat. A de novo polymorphism (AF333037:g.795C>T) in the intron 1 region of porcine CETP was identified. This polymorphism was further genotyped by direct sequencing of the PCR products of 390 Wannan Black pigs, a Chinese native breed population. Association analyses at 45 and 300 days of age revealed highly significant associations between CETP genotypes and serum lipid traits. Furthermore, this polymorphism was proved to be associated with differences in liver CETP mRNA levels: pigs at 300 days of age with the TT genotype had higher levels than did those with other genotypes (P = 0.021). Additionally, analysis at 300 days of age showed that GM CETP mRNA expression correlated positively with serum lipids levels as well as with carcass backfat thickness and intramuscular fat content in GM. These results indicate that CETP is involved in serum, adipose and muscle lipid metabolism in pigs. The mechanisms underlying such relationships and their functional implications are worthy of further research.     

Prioritization of candidate genes for attention deficit hyperactivity disorder by computational analysis of multiple data sources

Attention deficit hyperactivity disorder (ADHD) is a common, highly heritable psychiatric disorder characterized by hyperactivity, inattention and increased impulsivity. In recent years, a large number of genetic studies for ADHD have been published and related genetic data has been accumulated dramatically. To provide researchers a comprehensive ADHD genetic resource, we previously developed the first genetic database for ADHD (ADHDgene). The abundant genetic data provides novel candidates for further study. Meanwhile, it also brings new challenge for selecting promising candidate genes for replication and verification research. In this study, we surveyed the computational tools for candidate gene prioritization and selected five tools, which integrate multiple data sources for gene prioritization, to prioritize ADHD candidate genes in ADHDgene. The prioritization analysis resulted in 16 prioritized candidate genes, which are mainly involved in several major neurotransmitter systems or in nervous system development pathways. Among these genes, nervous system development related genes, especially SNAP25, STX1A and the gene-gene interactions related with each of them deserve further investigations. Our results may provide new insight for further verification study and facilitate the exploration of pathogenesis mechanism of ADHD.     

Polymorphism of growth hormone gene and its association with seminal and sexual behavioral traits in crossbred cattle

The decline in the male reproductive ability in terms of sexual behavior and seminal traits might lead to nonavailability of required number of bulls in a progeny testing program. The present study was conducted in 493 crossbred cattle (Bos taurus × Bos indicus) bulls to study polymorphisms of growth hormone (GH) gene and its association with seminal and sexual behavioral characteristics. A 428-base pair fragment of GH gene spanning over the fourth exon, fourth intron, and fifth exon was amplified and digested with AluI restriction enzyme. Bulls were found to be polymorphic, with two variants, LL and LV, and higher genotypic frequency for LL being 0.88. Twelve nucleotide changes and a single nonsynonymous substitution of Leucine by Valine were observed from GH1 (L) to GH2 (V). Statistical analysis revealed that the genotype of the GH gene had a significant effect on libido score, reaction time, Flehmen response, requirement of mounting stimulus, sperm mass activity, number of semen doses per collection, individual fresh sperm motility, postthaw sperm motility, acrosome integrity, hypo-osmotic swelling test, live and dead count, total morphological abnormality, and head abnormality of sperm in crossbred bulls. Growth hormone gene might be considered a candidate gene for seminal and sexual behavioral traits in crossbred cattle.     

Impact of selection on genes involved in regulatory network: a modelling study

Complex phenotypes are often controlled by many interacting genes. One question emerging from such organization is how selection, acting at the phenotypic level, shapes the evolution of genes involved in regulatory networks controlling the phenotypes. We studied this issue through a matrix model of such networks. In a population submitted to selection, we simulated the evolution of a quantitative trait controlled by a set of loci that regulate each other through positive or negative interactions. Investigating several levels of selection intensity on the trait, we studied the evolution of regulation intensity between the genes and the evolution of the genetic diversity of those genes as an indirect measure of the strength of selection acting on them. We show that an increasing intensity of selection on the phenotype leads to an increased level of regulation between the loci. Moreover, we found that the genes responding more strongly to selection within the network were those evolving towards stronger regulatory action on the other genes and/or those that are the less regulated by the other genes. This observation is strongest for an intermediate level of selection. This may explain why several experimental studies have shown evidence of selection on regulatory genes inside gene networks.     

Estimating myostatin gene effect on milk performance traits using estimated gene content for a large number of non-genotyped cows

The objective of this study was to estimate the myostatin (mh) gene's effect on milk, protein and fat yield in a large heterogeneous cow population, of which only a small portion was genotyped. For this purpose, a total of 13 992 889 test-day records derived from 799 778 cows were available. The mh gene effect was estimated via BLUP using a multi-lactation, multi-trait random regression test-day model with an additional fixed regression on mh gene content. As only 1416 animals, (of which 1183 cows had test-day records) were genotyped, more animals of additional breeds with assumed known genotype were added to estimate the genotype (gene content) of the remaining cows more reliably. This was carried out using the conventional pedigree information between genotyped animals and their non-genotyped relatives. Applying this rule, mean estimated gene content over all cows with test-day records was 0.104, showing that most cows were homozygous +/+. In contrast, when gene content estimation was only based on genotyped animals, mean estimated gene content over all cows with test-day records was with 1.349 overestimated. Therefore, the applied method for gene content estimation in large populations needs additional genotype assumptions about additional animals representing genetic diversity when the breed composition in the complete population is heterogeneous and only a few animals from predominantly one breed are genotyped. Concerning allele substitution effects for one copy of the 'mh' gene variant, significant decreases of -76.1 kg milk, -3.6 kg fat and -2.8 kg protein/lactation were obtained on average when gene content estimation was additionally based on animals with assumed known genotype. Based on this result, knowledge of the mh genotypes and their effects has the potential to improve milk performance traits in cattle.     

肌细胞生成素基因的研究进展

本文综述了肌细胞生成素（myogenin,MYOG）基因在位置、结构、多态性及检测方法上的研究现状,并初步探讨了MYOG基因与经济性状的关系。 Abstract: In this paper we briefly introduced the location, structure, polymorphisms of myogenin gene, and discussed the relationships of myogenin gene with economic traits.     

MyoG基因对金华猪繁殖性状的影响

用PCR-RFLP方法对金华猪I系（109头）、II系（15头）、III系（25头）的MyoG基因的第二内含子内（PCR1- MspⅠ-RFLP）和3'-端（PCR2- MspⅠ-RFLP）位点进行了多态性分析。结果表明：PCR1- MspⅠ-RFLP位点有3种基因型（AA、AB、BB）,其基因型频率分别为0.1544,0.3826,0.4631;PCR2- MspⅠ-RFLP位点只有2种基因型（MM、MN）,其基因型频率分别为0.9953和0.0047。采用SPSS程序分析MyoG基因对金华猪繁殖性状的影响。结果表明：MyoG基因对金华母猪初胎的总产仔数、二胎的产活仔数影响显著（P<0.05）,而对其他胎次组合的总产仔数、产活仔数以及初生窝重没有显著影响（P<0.05）。     

Commentary: When does understanding phenotypic evolution require identification of the underlying genes?

Adaptive evolution is fundamentally a genetic process. Over the past three decades, characterizing the genes underlying adaptive phenotypic change has revealed many important aspects of evolutionary change. At the same time, natural selection is often fundamentally an ecological process that can often be studied without identifying the genes underlying the variation on which it acts. This duality has given rise to disagreement about whether, and under what circumstances, it is necessary to identify specific genes associated with phenotypic change. This issue is of practical concern, especially for researchers who study nonmodel organisms, because of the often enormous cost and labor required to “go for the genes.” We here consider a number of situations and questions commonly addressed by researchers. Our conclusion is that although gene identification can be crucial for answering some questions, there are others for which definitive answers can be obtained without finding underlying genes. It should thus not be assumed that considerations of “empirical completeness” dictate that gene identification is always desirable.     

基于节点-模块置信度及局部模块度双重约束挖掘前列腺癌候选疾病模块

前列腺癌病因及发病机理研究有助于前列腺癌预防和治疗.目前,前列腺癌生化试验研究方法成本高、耗时,而基于网络计算方法容易受基因表达谱数据不完整、噪声高及实验样本数量少等约束.为此,本文提出一种基于节点-模块置信度及局部模块度的双重约束算法(命名为NMCOM),挖掘前列腺癌候选疾病模块.NMCOM算法不依赖基因表达谱数据,采用候选基因与致病表型之间一致性得分,候选基因与致病基因之间语义相似性得分融合排序策略,选取起始节点,并基于节点-模块置信度及局部模块度双重约束挖掘前列腺癌候选疾病模块.通过对挖掘出的模块进行富集分析,最终得到18个有显著意义的候选疾病基因模块.与单一打分排序方法及随机游走重开始方法相比,NMCOM融合排序策略的平均排名比小、AUC值大,且挖掘出结果明显优于其他模块挖掘算法,模块生物学意义显著.NMCOM算法不仅能准确有效地挖掘前列腺癌候选疾病模块,且可扩展挖掘其他疾病候选模块.     

Nucleotide variants in prion-related protein (testis-specific) gene (PRNT) and effects on Chinese and Mongolian sheep phenotypes

ABSTRACT

Studies of the ovine prion-related protein (testis-specific) gene (PRNT), including studies of genetic diversity, have highlighted its potential relationship to scrapie infection and economically important ovine traits. PRNT was previously reported to be highly polymorphic in Portuguese sheep. To characterize genetic polymorphisms in this gene in Asian sheep, a direct sequencing method was used to detect polymorphic loci in PRNT in 285 individual sheep from four Chinese and one Mongolian breeds. Seven SNP variants in PRNT were identified, including three novel variants (g.93G>A, g.162G>T, and g.190A>G) and four previously reported variants (g.17 C>T, g.112G>C, g.129C>T, and g.144A>G). In the five breeds that we analyzed, the mutation frequencies of g.190A>G in Lanzhou Fat-tail sheep (LFTS) and g.129C>T in the other four varieties were high (F>0.5). Moreover, thirteen different haplotypes that had a comparable distribution in the tested breeds were also identified; ‘C-G-G-C-A-G-A’ occurred at the highest frequency in the five sheep breeds. Additionally, we previously explored the significance of relationships between polymorphisms in PRNP or PRND and ovine growth performance. Here, we also performed correlation analysis in all tested loci. These loci polymorphisms were significantly associated with ten different growth traits (P<0.05), except for g.93G>A. Meanwhile, in contrast to a previous study, there was no significant association between the seven SNP loci analyzed and our previously reported sheep PRND or PRNP insertion/deletion mutations. Our findings may provide new insights into polymorphic variation in ovine PRNT, which may contribute to genetic improvements in economic traits that are important for sheep breeding.