Current Genomics (v.16, #3)

Meet the Editorial Board Members: by Joao Pedro de Magalhaes, Girdhar K. Pandey (139-140).

Tetralogy of Fallot and Hypoplastic Left Heart Syndrome – Complex Clinical Phenotypes Meet Complex Genetic Networks by Harald Lahm, Patric Schon, Stefanie Doppler, Martina Dreßen, Julie Cleuziou, Marcus-Andre Deutsch, Peter Ewert, Rudiger Lange, Markus Krane (141-158).
In many cases congenital heart disease (CHD) is represented by a complex phenotype and an array of several functional and morphological cardiac disorders. These malformations will be briefly summarized in the first part focusing on two severe CHD phenotypes, hypoplastic left heart syndrome (HLHS) and tetralogy of Fallot (TOF). In most cases of CHD the genetic origin remains largely unknown, though the complexity of the clinical picture strongly argues against a dysregulation which can be attributed to a single candidate gene but rather suggests a multifaceted polygenetic origin with elaborate interactions. Consistent with this idea, genome-wide approaches using whole exome sequencing, comparative sequence analysis of multiplex families to identify de novo mutations and global technologies to identify single nucleotide polymorphisms, copy number variants, dysregulation of the transcriptome and epigenetic variations have been conducted to obtain information about genetic alterations and potential predispositions possibly linked to the occurrence of a CHD phenotype. In the second part of this review we will summarize and discuss the available literature on identified genetic alterations linked to TOF and HLHS.

Management of Incidental Findings in the Era of Next-generation Sequencing by Heather L. Blackburn, Bradley Schroeder, Clesson Turner, Craig D. Shriver, Darrell L. Ellsworth, Rachel E. Ellsworth (159-174).
Next-generation sequencing (NGS) technologies allow for the generation of whole exome or whole genome sequencing data, which can be used to identify novel genetic alterations associated with defined phenotypes or to expedite discovery of functional variants for improved patient care. Because this robust technology has the ability to identify all mutations within a genome, incidental findings (IF)- genetic alterations associated with conditions or diseases unrelated to the patient's present condition for which current tests are being performed- may have important clinical ramifications. The current debate among genetic scientists and clinicians focuses on the following questions: 1) should any IF be disclosed to patients, and 2) which IF should be disclosed – actionable mutations, variants of unknown significance, or all IF—Policies for disclosure of IF are being developed for when and how to convey these findings and whether adults, minors, or individuals unable to provide consent have the right to refuse receipt of IF. In this review, we detail current NGS technology platforms, discuss pressing issues regarding disclosure of IF, and how IF are currently being handled in prenatal, pediatric, and adult patients.

Epigenomic-Basis of Preemptive Medicine for Neurodevelopmental Disorders by Takeo Kubota, Kunio Miyake, Natsuyo Hariya, Kazuki Mochizuki (175-182).
Neurodevelopmental disorders (NDs) are currently thought to be caused by either genetic defects or various environmental factors. Recent studies have demonstrated that congenital NDs can result not only from changes in DNA sequence in neuronal genes but also from changes to the secondary epigenomic modifications of DNA and histone proteins. Thus, epigenomic assays, as well as genomic assays, are currently performed for diagnosis of the congenital NDs. It is recently known that the epigenomic modifications can be altered by various environmental factors, which potentially cause acquired NDs. Furthermore these alterations can potentially be restored taking advantage of use of reversibility in epigenomics. Therefore, epigenome-based early diagnosis and subsequent intervention, by using drugs that restore epigenomic alterations, will open up a new era of preemptive medicine for congenital and acquired NDs.

Syndactyly, webbing of adjacent digits with or without bony fusion, is one of the most common hereditary limb malformations. It occurs either as an isolated abnormality or as a component of more than 300 syndromic anomalies. There are currently nine types of phenotypically diverse nonsyndromic syndactyly. Non-syndromic syndactyly is usually inherited as an autosomal dominant trait, although the more severe presenting types and subtypes may show autosomal recessive or X-linked pattern of inheritance. The phenotype appears to be not only caused by a main gene, but also dependant on genetic background and subsequent signaling pathways involved in limb formation. So far, the principal genes identified to be involved in congenital syndactyly are mainly involved in the zone of polarizing activity and sonic hedgehog pathway. This review summarizes the recent progress made in the molecular genetics, including known genes and loci responsible for non-syndromic syndactyly, and the signaling pathways those genetic factors involved in, as well as clinical features and animal models. We hope our review will contribute to the understanding of underlying pathogenesis of this complicated disorder and have implication on genetic counseling.

In this paper the detection of rare variants association with continuous phenotypes of interest is investigated via the likelihood-ratio based variance component test under the framework of linear mixed models. The hypothesis testing is challenging and nonstandard, since under the null the variance component is located on the boundary of its parameter space. In this situation the usual asymptotic chisquare distribution of the likelihood ratio statistic does not necessarily hold. To circumvent the derivation of the null distribution we resort to the bootstrap method due to its generic applicability and being easy to implement. Both parametric and nonparametric bootstrap likelihood ratio tests are studied. Numerical studies are implemented to evaluate the performance of the proposed bootstrap likelihood ratio test and compare to some existing methods for the identification of rare variants. To reduce the computational time of the bootstrap likelihood ratio test we propose an effective approximation mixture for the bootstrap null distribution. The GAW17 data is used to illustrate the proposed test.

Detecting the Genomic Signature of Divergent Selection in Presence of Gene Flow by M. J. Rivas, S. Dominguez-Garcia, A. Carvajal-Rodriguez (203-212).
The study of local adaptation is a main focus of evolutionary biology since it may contribute to explain the current species diversity. The genomic scan procedures permit for the first time to study the connection between specific DNA patterns and processes as natural selection, genetic drift, recombination, mutation and gene flow. Accordingly, the information on genomes from non-model organisms increases and the interest on detecting the signal of natural selection in the DNA sequences of different populations also raises. The main goal of the present work is to explore a sequence-based method for detecting natural selection in divergent populations connected by migration. In doing so, we rely on a recently published statistic based upon the definition of haplotype allelic classes (HAC). The original measure was modified to be more sensitive to intermediate frequencies in non-model species. A linkagedisequilibrium- based method was also assayed and individual-based simulations were performed to test the methods. The results suggest that the HAC-based methods and, specifically, the new proposed method are quite powerful for detecting the footprint of moderate divergent selection. They are also robust to reasonable model misspecification. One obvious advantage of the new algorithm is that it does not require knowledge of the allelic state.