Mosaic tetrasomy 12p. Identical nature of the Pallister syndrome, the Teschler-Nicola/Killian syndrome and mosaic tetrasomy 21

In two cases, first interpreted as mosaic tetrasomy 21, the R banding and the gene dosage studies lead us to conclude to a mosaic tetrasomy 12 p. In Pallister mosaic syndrome and in Teschler-Nicola/Killian syndrome, the very similar clinical signs and the identical abnormal chromosome, missing in leucocytes, led us to conclude that Pallister and Teschler-Nicola/Killian syndrome, as well as mosaic tetrasomy 21 are one and the same syndrome tetrasomy 12 p. This tissue limited mosaic is probably more frequent than it is assumed. Prenatal diagnosis can be made since the supernumerary chromosome is found in amniocytes. The distinctive tissue distribution is probably a selective process due to cellular differentiation gene, CD9 (or Alb 6) located to 12 p.     

Identification of differentially expressed genes related to metabolic syndrome induced with high-fat diet in E3 rats

Understanding the genes differentially expressing in aberrant organs of metabolic syndrome (MetS) facilitates the uncovering of molecular mechanisms and the identification of novel therapeutic targets for the disease. This study aimed to identify differentially expressed genes related to MetS in livers of E3 rats with high-fat-diet-induced metabolic syndrome (HFD-MetS). E3 rats were fed with high-fat diet for 24 weeks to induce MetS. Then, suppression subtractive hybridization (SSH) technology was used to identify the genes differentially expressed between HFD-MetS and control E3 rat livers. Twenty positive recombinant clones were chosen randomly from forward subtractive library and sent to sequence. BLAST analysis in GenBank database was used to determine the property of each cDNA fragment. In total, 11 annotated genes, 3 ESTs, and 2 novel gene fragments were identified by SSH technology. The expression of four genes (Alb, Pip4k2a, Scd1, and Tf) known to be associated with MetS and other five genes (Eif1, Rnase4, Rps12, Rup2, and Tmsb4) unknown to be relevant to MetS was significantly up-regulated in the livers of HFD-MetS E3 rats compared with control rats using real-time quantitative PCR (RT-qPCR). By analyzing the correlations between the expression of these nine genes and serum concentrations of TG, Tch, HDL-C, and LDL-C, we found that there were significant positive correlations between TG and the expression of five genes (Alb, Eif1, Pip4k2a, Rps12, and Tmsb4x), Tch and three genes (Rnase4, Scd1, and Tmsb4x), and LDL-C and two genes (Rnase4 and Scd1), as well there were significant negative correlations between HDL-C and the expression of three genes (Rup2, Scd1, and Tf). This study provides important clues for unraveling the molecular mechanisms of MetS.     

Skin Transcriptome Profiles Associated with Skin Color in Chickens

Nutritional and medicinal benefits have been attributed to the consumption of tissues from the black-boned chickens in oriental countries. Lueyang black-boned chicken is one of the native chicken breeds. However, some birds may instead have white or lighter skin, which directly causes economic losses every year. Previous studies of pigmentation have focused on a number of genes that may play important roles in coat color regulation. Illumina2000 sequencing technology was used to catalog the global gene expression profiles in the skin of the Lueyang chicken with white versus black skin. A total of 18,608 unigenes were assembled from the reads obtained from the skin of the white and black chickens. A total of 649 known genes were differentially expressed in the black versus white chickens, with 314 genes that were up regulated and 335 genes that were down-regulated, and a total of 162 novel genes were differentially expressed in the black versus white chickens, consisting of 73 genes that were up-regulated (including 4 highly expressed genes that were expressed exclusively in the skin of the black chickens) and 89 genes that were down-regulated. There were also a total of 8 known coat-color genes expressed in previous studies (ASIP, TYR, KIT, TYRP1, OCA2, KITLG, MITF and MC1R). In this study, 4 of which showed greater expression in the black chickens, and several were up-regulated, such as KIT, ASIP, TYR and OCA2. To our surprise, KITLG, MITF and MC1R showed no significant difference in expression between the black- and white-skinned chickens, and the expression of TYRP1 was not detected in either skin color. The expression of ASIP, TYR, KIT, TYRP1, OCA2, KITLG, MITF and MC1R was validated by real-time quantitative polymerase chain reaction (qPCR), and the results of the qPCR were consistent with the RNA-seq. This study provides several candidate genes that may be associated with the development of black versus white skin. More importantly, the fact that the MC1R gene showed no significant difference in expression between the black and white chickens is of particular interest for future studies that aim to elucidate its functional role in the regulation of skin color.     

Emergence of differentially regulated pathways associated with the development of regional specificity in chicken skin

Background

Regional specificity allows different skin regions to exhibit different characteristics, enabling complementary functions to make effective use of the integumentary surface. Chickens exhibit a high degree of regional specificity in the skin and can serve as a good model for when and how these regional differences begin to emerge.

Results

We used developing feather and scale regions in embryonic chickens as a model to gauge the differences in their molecular pathways. We employed cosine similarity analysis to identify the differentially regulated and co-regulated genes. We applied low cell techniques for expression validation and chromatin immunoprecipitation (ChIP)-based enhancer identification to overcome limited cell availabilities from embryonic chicken skin.We identified a specific set of genes demonstrating a high correlation as being differentially expressed during feather and scale development and maturation. Some members of the WNT, TGF-beta/BMP, and Notch family known to be involved in feathering skin differentiation were found to be differentially regulated. Interestingly, we also found genes along calcium channel pathways that are differentially regulated. From the analysis of differentially regulated pathways, we used calcium signaling pathways as an example for further verification. Some voltage-gated calcium channel subunits, particularly CACNA1D, are expressed spatio-temporally in the skin epithelium. These calcium signaling pathway members may be involved in developmental decisions, morphogenesis, or epithelial maturation. We further characterized enhancers associated with histone modifications, including H3K4me1, H3K27ac, and H3K27me3, near calcium channel-related genes and identified signature intensive hotspots that may be correlated with certain voltage-gated calcium channel genes.

Conclusion

We demonstrated the applicability of cosine similarity analysis for identifying novel regulatory pathways that are differentially regulated during development. Our study concerning the effects of signaling pathways and histone signatures on enhancers suggests that voltage-gated calcium signaling may be involved in early skin development. This work lays the foundation for studying the roles of these gene pathways and their genomic regulation during the establishment of skin regional specificity.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-014-1202-9) contains supplementary material, which is available to authorized users.     

BMP9 Mutations Cause a Vascular-Anomaly Syndrome with Phenotypic Overlap with Hereditary Hemorrhagic Telangiectasia

Hereditary hemorrhagic telangiectasia (HHT), the most common inherited vascular disorder, is caused by mutations in genes involved in the transforming growth factor beta (TGF-β) signaling pathway (ENG, ACVRL1, and SMAD4). Yet, approximately 15% of individuals with clinical features of HHT do not have mutations in these genes, suggesting that there are undiscovered mutations in other genes for HHT and possibly vascular disorders with overlapping phenotypes. The genetic etiology for 191 unrelated individuals clinically suspected to have HHT was investigated with the use of exome and Sanger sequencing; these individuals had no mutations in ENG, ACVRL1, and SMAD4. Mutations in BMP9 (also known as GDF2) were identified in three unrelated probands. These three individuals had epistaxis and dermal lesions that were described as telangiectases but whose location and appearance resembled lesions described in some individuals with RASA1-related disorders (capillary malformation-arteriovenous malformation syndrome). Analyses of the variant proteins suggested that mutations negatively affect protein processing and/or function, and a bmp9-deficient zebrafish model demonstrated that BMP9 is involved in angiogenesis. These data confirm a genetic cause of a vascular-anomaly syndrome that has phenotypic overlap with HHT.     

Diagnostic Application of Targeted Resequencing for Familial Nonsyndromic Hearing Loss

Identification of causative genes for hereditary nonsyndromic hearing loss (NSHL) is important to decide treatment modalities and to counsel the patients. Due to the genetic heterogeneity in sensorineural genetic disorders, the high-throughput method can be adapted for the efficient diagnosis. To this end, we designed a new diagnostic pipeline to screen all the reported candidate genes for NSHL. For validation of the diagnostic pipeline, we focused upon familial NSHL cases that are most likely to be genetic, rather than to be infectious or environmental. Among the 32 familial NSHL cases, we were able to make a molecular genetic diagnosis from 12 probands (37.5%) in the first stage by their clinical features, characteristic inheritance pattern and further candidate gene sequencing of GJB2, SLC26A4, POU3F4 or mitochondrial DNA. Next we applied targeted resequencing on 80 NSHL genes in the remaining 20 probands. Each proband carried 4.8 variants that were not synonymous and had the occurring frequency of less than three among the 20 probands. These variants were then filtered out with the inheritance pattern of the family, allele frequency in normal hearing 80 control subjects, clinical features. Finally NSHL-causing candidate mutations were identified in 13(65%) of the 20 probands of multiplex families, bringing the total solve rate (or detection rate) in our familial cases to be 78.1% (25/32) Damaging mutations discovered by the targeted resequencing were distributed in nine genes such as WFS1, COCH, EYA4, MYO6, GJB3, COL11A2, OTOF, STRC and MYO3A, most of which were private. Despite the advent of whole genome and whole exome sequencing, we propose targeted resequencing and filtering strategy as a screening and diagnostic tool at least for familial NSHL to find mutations based upon its efficacy and cost-effectiveness.     

Detection of Clinically Relevant Genetic Variants in Autism Spectrum Disorder by Whole-Genome Sequencing

Autism Spectrum Disorder (ASD) demonstrates high heritability and familial clustering, yet the genetic causes remain only partially understood as a result of extensive clinical and genomic heterogeneity. Whole-genome sequencing (WGS) shows promise as a tool for identifying ASD risk genes as well as unreported mutations in known loci, but an assessment of its full utility in an ASD group has not been performed. We used WGS to examine 32 families with ASD to detect de novo or rare inherited genetic variants predicted to be deleterious (loss-of-function and damaging missense mutations). Among ASD probands, we identified deleterious de novo mutations in six of 32 (19%) families and X-linked or autosomal inherited alterations in ten of 32 (31%) families (some had combinations of mutations). The proportion of families identified with such putative mutations was larger than has been previously reported; this yield was in part due to the comprehensive and uniform coverage afforded by WGS. Deleterious variants were found in four unrecognized, nine known, and eight candidate ASD risk genes. Examples include CAPRIN1 and AFF2 (both linked to FMR1, which is involved in fragile X syndrome), VIP (involved in social-cognitive deficits), and other genes such as SCN2A and KCNQ2 (linked to epilepsy), NRXN1, and CHD7, which causes ASD-associated CHARGE syndrome. Taken together, these results suggest that WGS and thorough bioinformatic analyses for de novo and rare inherited mutations will improve the detection of genetic variants likely to be associated with ASD or its accompanying clinical symptoms.