De Novo Duplication in the CHD7 Gene Associated With Severe CHARGE Syndrome

CHARGE syndrome is an autosomal dominant developmental disorder associated with a constellation of traits involving almost every organ and sensory system, in particular congenital anomalies, including choanal atresia and malformations of the heart, inner ear, and retina. Variants in CHD7 have been shown to cause CHARGE syndrome. Here, we report the identification of a novel de novo p.Asp2119_Pro2120ins6 duplication variant in a conserved region of CHD7 in a severely affected boy presenting with 3 and 5 of the CHARGE cardinal major and minor signs, respectively, combined with congenital umbilical hernia, congenital hernia at the linea alba, mildly hypoplastic inferior vermis, slight dilatation of the lateral ventricles, prominent metopic ridge, and hypoglycemic episodes.

Expression Levels of Candidate Circulating microRNAs in Early-Onset Neonatal Sepsis Compared With Healthy Newborns

The high mortality rate of neonatal sepsis is directly connected with time-consuming diagnostic methods that have low sensitivity and specificity. The need of the hour is to develop novel diagnostic techniques that are rapid and more specific. In this study, we estimated the expression levels of circulating microRNAs (miRNAs) that are involved in regulating immune response genes and underlying inflammatory responses, which may be used for sepsis diagnosis. The total circulating miRNA was isolated and the candidate miRNAs (miR-132, miR-146a, miR-155, and miR-223) were quantified by real-time polymerase chain reaction technique. Statistical analysis revealed that miR-132 ( P < .01) and miR-223 ( P < .05) were downregulated in septic newborns compared with healthy babies. The decrease in expression of miR-132 and miR-223 may be associated with increased expression of immune-related genes involved in TLR (Toll-like receptor) signaling pathway. Further case-control studies with large sample size are required to identify the potential of miRNAs in neonatal sepsis diagnosis.

Application of the GRADE Approach in the Development of Guidelines and Recommendations in Genomic Medicine

A great deal of ambiguity exists in the development of guidelines for genomic applications used in clinical practice. The GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach has the potential to be applied in the guidelines and recommendations development process in genomics. Here, we discuss whether and how GRADE can be applied to address the challenges posed by the evidence-based guidelines and recommendations development process in genomics. To see how GRADE can complement to the current guidelines development in genomics, we compare and contrast GRADE with other approaches. GRADE differed from other methods by incorporating patient values and preferences and balance of consequences. We conclude that the groups trying to implement genomics into practice may gleam more information from applying the GRADE framework. However, it is not clear yet whether GRADE can address the issue of timeliness in terms of the differences between the time required for guidelines development and the rapid pace of genomics.

Insights Into Upland Cotton (Gossypium hirsutum L.) Genetic Recombination Based on 3 High-Density Single-Nucleotide Polymorphism and a Consensus Map Developed Independently With Common Parents

High-density linkage maps are vital to supporting the correct placement of scaffolds and gene sequences on chromosomes and fundamental to contemporary organismal research and scientific approaches to genetic improvement, especially in paleopolyploids with exceptionally complex genomes, eg, upland cotton ( Gossypium hirsutum L., “2n = 52”). Three independently developed intraspecific upland mapping populations were analyzed to generate 3 high-density genetic linkage single-nucleotide polymorphism (SNP) maps and a consensus map using the CottonSNP63K array. The populations consisted of a previously reported F2, a recombinant inbred line (RIL), and reciprocal RIL population, from “Phytogen 72” and “Stoneville 474” cultivars. The cluster file provided 7417 genotyped SNP markers, resulting in 26 linkage groups corresponding to the 26 chromosomes (c) of the allotetraploid upland cotton (AD)1 arisen from the merging of 2 genomes (“A” Old World and “D” New World). Patterns of chromosome-specific recombination were largely consistent across mapping populations. The high-density genetic consensus map included 7244 SNP markers that spanned 3538 cM and comprised 3824 SNP bins, of which 1783 and 2041 were in the At and Dt subgenomes with 1825 and 1713 cM map lengths, respectively. Subgenome average distances were nearly identical, indicating that subgenomic differences in bin number arose due to the high numbers of SNPs on the Dt subgenome. Examination of expected recombination frequency or crossovers (COs) on the chromosomes within each population of the 2 subgenomes revealed that COs were also not affected by the SNPs or SNP bin number in these subgenomes. Comparative alignment analyses identified historical ancestral At-subgenomic translocations of c02 and c03, as well as of c04 and c05. The consensus map SNP sequences aligned with high congruency to the NBI assembly of Gossypium hirsutum. However, the genomic comparisons revealed evidence of additional unconfirmed possible duplications, inversions and translocations, and unbalance SNP sequence homology or SNP sequence/loci genomic dominance, or homeolog loci bias of the upland tetraploid At and Dt subgenomes. The alignments indicated that 364 SNP-associated previously unintegrated scaffolds can be placed in pseudochromosomes of the NBI G hirsutum assembly. This is the first intraspecific SNP genetic linkage consensus map assembled in G hirsutum with a core of reproducible mendelian SNP markers assayed on different populations and it provides further knowledge of chromosome arrangement of genic and nongenic SNPs. Together, the consensus map and RIL populations provide a synergistically useful platform for localizing and identifying agronomically important loci for improvement of the cotton crop.

Multiple Testing in the Context of Gene Discovery in Sickle Cell Disease Using Genome-Wide Association Studies

The issue of multiple testing, also termed multiplicity, is ubiquitous in studies where multiple hypotheses are tested simultaneously. Genome-wide association study (GWAS), a type of genetic association study that has gained popularity in the past decade, is most susceptible to the issue of multiple testing. Different methodologies have been employed to address the issue of multiple testing in GWAS. The purpose of the review is to examine the methodologies employed in dealing with multiple testing in the context of gene discovery using GWAS in sickle cell disease complications.

Exon Mapping in Long Noncoding RNAs Using Digital Filters

Long noncoding RNAs (lncRNAs) which were initially dismissed as “transcriptional noise” have become a vital area of study after their roles in biological regulation were discovered. Long noncoding RNAs have been implicated in various developmental processes and diseases. Here, we perform exon mapping of human lncRNA sequences (taken from National Center for Biotechnology Information GenBank) using digital filters. Antinotch digital filters are used to map out the exons of the lncRNA sequences analyzed. The period 3 property which is an established indicator for locating exons in genes is used here. Discrete wavelet transform filter bank is used to fine-tune the exon plots by selectively removing the spectral noise. The exon locations conform to the ranges specified in GenBank. In addition to exon prediction, G-C concentrations of lncRNA sequences are found, and the sequences are searched for START and STOP codons as these are indicators of coding potential.

Inferring Orthologs: Open Questions and Perspectives

With the increasing number of sequenced genomes and their comparisons, the detection of orthologs is crucial for reliable functional annotation and evolutionary analyses of genes and species. Yet, the dynamic remodeling of genome content through gain, loss, transfer of genes, and segmental and whole-genome duplication hinders reliable orthology detection. Moreover, the lack of direct functional evidence and the questionable quality of some available genome sequences and annotations present additional difficulties to assess orthology. This article reviews the existing computational methods and their potential accuracy in the high-throughput era of genome sequencing and anticipates open questions in terms of methodology, reliability, and computation. Appropriate taxon sampling together with combination of methods based on similarity, phylogeny, synteny, and evolutionary knowledge that may help detecting speciation events appears to be the most accurate strategy. This review also raises perspectives on the potential determination of orthology throughout the whole species phylogeny.

SNP Marker Discovery in Pima Cotton (Gossypium barbadense L.) Leaf Transcriptomes

The objective of this study was to explore the known narrow genetic diversity and discover single-nucleotide polymorphic (SNP) markers for marker-assisted breeding within Pima cotton ( Gossypium barbadense L.) leaf transcriptomes. cDNA from 25-day plants of three diverse cotton genotypes [Pima S6 (PS6), Pima S7 (PS7), and Pima 3-79 (P3-79)] was sequenced on Illumina sequencing platform. A total of 28.9 million reads (average read length of 138 bp) were generated by sequencing cDNA libraries of these three genotypes. The de novo assembly of reads generated transcriptome sets of 26,369 contigs for PS6, 25,870 contigs for PS7, and 24,796 contigs for P3-79. A Pima leaf reference transcriptome was generated consisting of 42,695 contigs. More than 10,000 single-nucleotide polymorphisms (SNPs) were identified between the genotypes, with 100% SNP frequency and a minimum of eight sequencing reads. The most prevalent SNP substitutions were C–-T and A–-G in these cotton genotypes. The putative SNPs identified can be utilized for characterizing genetic diversity, genotyping, and eventually in Pima cotton breeding through marker-assisted selection.