Genetic mapping of an autosomal recessive postaxial polydactyly type A to chromosome 13q13.3–q21.2 and screening of the candidate genes

Postaxial Polydactyly (PAP) is characterized by fifth digit duplication in hands and/or feet. Two types of PAP including PAP-A, representing the development of well-formed extra digit, and PAP-B, representing the presence of rudimentary fifth digit, have been described. Both isolated and syndromic forms of PAP have been reported. Isolated forms of PAP usually segregate as an autosomal dominant trait and to date four loci have been identified. In the present study, we have described mapping of the first locus of autosomal recessive PAP type A on chromosome 13q13.3–13q21.2 in a consanguineous Pakistani family. Using polymorphic microsatellite markers, the disease locus was mapped to a 17.87-cM (21.13 Mb) region flanked by markers D13S1288 and D13S632, on chromosome 13q13.3–13q21.2. A maximum multipoint LOD score of 3.84 was obtained with several markers along the disease interval. DNA sequence analysis of exons and splice-junction sites of ten candidate genes (CHM-I, TSC22D1, FOXO1, DIAPH3, CCDC122, CKAP2, SUGT1, RANKL, LPAR6, C13ORF31) did not reveal potentially causal variants.     

MotViz: a tool for sequence motif prediction in parallel to structural visualization and analyses

Linking similar proteins structurally is a challenging task that may help in finding the novel members of a protein family. In this respect, identification of conserved sequence can facilitate understanding and classifying the exact role of proteins. However, the exact role of these conserved elements cannot be elucidated without structural and physiochemical information. In this work, we present a novel desktop application MotViz designed for searching and analyzing the conserved sequence segments within protein structure. With MotViz, the user can extract a complete list of sequence motifs from loaded 3D structures, annotate the motifs structurally and analyze their physiochemical properties. The conservation value calculated for an individual motif can be visualized graphically. To check the efficiency, predicted motifs from the data sets of 9 protein families were analyzed and MotViz algorithm was more efficient in comparison to other online motif prediction tools. Furthermore, a database was also integrated for storing, retrieving and performing the detailed functional annotation studies. In summary, MotViz effectively predicts motifs with high sensitivity and simultaneously visualizes them into 3D strucures. Moreover, MotViz is user-friendly with optimized graphical parameters and better processing speed due to the inclusion of a database at the back end. MotViz is available at http://www.fi-pk.com/motviz.html.     

A genome-wide study of cytogenetic changes in colorectal cancer using SNP microarrays: opportunities for future personalized treatment

In colorectal cancer (CRC), chromosomal instability (CIN) is typically studied using comparative-genomic hybridization (CGH) arrays. We studied paired (tumor and surrounding healthy) fresh frozen tissue from 86 CRC patients using Illumina's Infinium-based SNP array. This method allowed us to study CIN in CRC, with simultaneous analysis of copy number (CN) and B-allele frequency (BAF)--a representation of allelic composition. These data helped us to detect mono-allelic and bi-allelic amplifications/deletion, copy neutral loss of heterozygosity, and levels of mosaicism for mixed cell populations, some of which can not be assessed with other methods that do not measure BAF. We identified associations between CN abnormalities and different CRC phenotypes (histological diagnosis, location, tumor grade, stage, MSI and presence of lymph node metastasis). We showed commonalities between regions of CN change observed in CRC and the regions reported in previous studies of other solid cancers (e.g. amplifications of 20q, 13q, 8q, 5p and deletions of 18q, 17p and 8p). From Therapeutic Target Database, we identified relevant drugs, targeted to the genes located in these regions with CN changes, approved or in trials for other cancers and common diseases. These drugs may be considered for future therapeutic trials in CRC, based on personalized cytogenetic diagnosis. We also found many regions, harboring genes, which are not currently targeted by any relevant drugs that may be considered for future drug discovery studies. Our study shows the application of high density SNP arrays for cytogenetic study in CRC and its potential utility for personalized treatment.     

Modifying bio-catalytic properties of enzymes for efficient biocatalysis: a review from immobilization strategies viewpoint

Enzyme-based catalysis has become one of the most important disciplines in organic synthesis and plays a noteworthy role in the establishment of many chemical industries, e.g. fine chemicals, food or energy, textiles, agricultural, cosmeceutical, medicinal and pharmaceutical industries. However, pristine enzymes fail to demonstrate requisite functionalities for an industrial setting where extremely specific and stable catalysts are required. Immobilization enhances the catalytic stability and activity of enzymes and trims the overall cost burden of the enzyme. Therefore, it widely endeavours for proficient, sustainable, and environmentally responsive catalytic processes. Amongst several immobilization strategies, e.g. (1) supports-assisted, i.e. physical or covalent coupling and (2) supports-free techniques, i.e. cross-linked enzyme crystals (CLECs) or aggregates are the most promising ones and widely pursued for enzyme immobilization purposes. This perspective review focuses on up-to-date developments in the area of enzyme immobilization and presents their potentialities to upgrade and/or modify enzyme properties. Both types of immobilization strategies, i.e. supports-assisted and supports-free techniques are discussed with particular reference to CLECs or aggregates and protein-coated microcrystals. Also, several useful traits achieved after immobilization are also discussed in the second half of the review.     

GPCR-MPredictor: multi-level prediction of G protein-coupled receptors using genetic ensemble

G protein-coupled receptors (GPCRs) are transmembrane proteins, which transduce signals from extracellular ligands to intracellular G protein. Automatic classification of GPCRs can provide important information for the development of novel drugs in pharmaceutical industry. In this paper, we propose an evolutionary approach, GPCR-MPredictor, which combines individual classifiers for predicting GPCRs. GPCR-MPredictor is a web predictor that can efficiently predict GPCRs at five levels. The first level determines whether a protein sequence is a GPCR or a non-GPCR. If the predicted sequence is a GPCR, then it is further classified into family, subfamily, sub-subfamily, and subtype levels. In this work, our aim is to analyze the discriminative power of different feature extraction and classification strategies in case of GPCRs prediction and then to use an evolutionary ensemble approach for enhanced prediction performance. Features are extracted using amino acid composition, pseudo amino acid composition, and dipeptide composition of protein sequences. Different classification approaches, such as k-nearest neighbor (KNN), support vector machine (SVM), probabilistic neural networks (PNN), J48, Adaboost, and Naives Bayes, have been used to classify GPCRs. The proposed hierarchical GA-based ensemble classifier exploits the prediction results of SVM, KNN, PNN, and J48 at each level. The GA-based ensemble yields an accuracy of 99.75, 92.45, 87.80, 83.57, and 96.17% at the five levels, on the first dataset. We further perform predictions on a dataset consisting of 8,000 GPCRs at the family, subfamily, and sub-subfamily level, and on two other datasets of 365 and 167 GPCRs at the second and fourth levels, respectively. In comparison with the existing methods, the results demonstrate the effectiveness of our proposed GPCR-MPredictor in classifying GPCRs families. It is accessible at .     

Phytochemicals from the stem wood of Sorbus lanata (D. Don.) Schauer

Three new phenolic compounds, sorlanin (4-(3-(hydroxymethyl)-5-methoxy-7-phenyl-2,3-dihydrobenzo[b][1,4]dioxin-2-yl)-2-methoxyphenol, 1), sorbanin (2-((3,5-dimethoxy-[1,1′-biphenyl]-4-yl)oxy)-1-(4-hydroxy-3-methoxyphenyl)propane-1,3-diol, 2) and sorbalanin (4-(3-(hydroxymethyl)-5,6-dimethoxy-2,3-dihydrobenzo[b][1,4]dioxino[2,3-g]benzofuran-2-yl)-2-methoxyphenol, 3), together with eight known compounds, polystachyol (4), isolariciresinol (5), dihydrodehydrodiconiferyl alcohol (6), tuberculatin (7), ovafolinin E (8), aucuparin (9), 2′-methoxyaucuparin (10), and tetracosyl-3-(3,4-dihydroxyphenyl)acrylate (11), were isolated from Sorbus lanata. The structures of these phytoconstituents were elucidated through extensive spectroscopic techniques, including UV, IR, 1D and 2D NMR, ESI-MS and HRESI-MS experiments. All the compounds except 9 and 10 were isolated for the first time from the genus Sorbus. The isolated compounds were also tested in DPPH radical scavenging reaction where compounds 6, 7, 10 and 11 showed significant activities with IC₅₀ values of 9.2, 11.7, 23.0 and 33.7 μM, respectively.     

Exome sequencing discloses <Emphasis Type="Italic">KALRN</Emphasis> homozygous variant as likely cause of intellectual disability and short stature in a consanguineous pedigree

Background

The recent availability of whole-exome sequencing has opened new possibilities for the evaluation of individuals with genetically undiagnosed intellectual disability.

Results

We report two affected siblings, offspring of first-cousin parents, with intellectual disability, hypotonia, short stature, growth hormone deficiency, and delayed bone age. All members of the nuclear family were genotyped, and exome sequencing was performed in one of the affected individuals. We used an in-house algorithm (CATCH v1.1) that combines homozygosity mapping with exome sequencing results and provides a list of candidate variants. One identified novel homozygous missense variant in KALRN (NM_003947.4:c.3644C>A: p.(Thr1215Lys)) was predicted to be pathogenic by all pathogenicity prediction software used (SIFT, PolyPhen, Mutation Taster). KALRN encodes the protein kalirin, which is a GTP-exchange factor protein with a reported role in cytoskeletal remodeling and dendritic spine formation in neurons. It is known that mice with ablation of Kalrn exhibit age-dependent functional deficits and behavioral phenotypes.

Conclusion

Exome sequencing provided initial evidence linking KALRN to monogenic intellectual disability in man, and we propose that KALRN is the causative gene for the autosomal recessive phenotype in this family.