Error minimization explains the codon usage of highly expressed genes in Escherichia coli

Different organisms use synonymous codons with different preferences. Several measures have been introduced to compute the extent of codon usage bias within a gene or genome, among which the codon adaptation index (CAI) has been shown to be well correlated with mRNA levels of Escherichia coli. In this work an error adaptation index (eAI) is introduced, which estimates the level at which a gene can tolerate the effects of mistranslations. It is shown that the eAI has a strong correlation with CAI, as well as with mRNA levels, which suggests that the codons of highly expressed genes are selected so that mistranslation would have the minimum possible effect on the structure and function of the related proteins.     

OCC-1D regulates Wnt signaling pathway: potential role of long noncoding RNA in colorectal cancer

Molecular Biology Reports - Aberrant activation of the Wnt signaling pathway is observed in most colorectal cancers (CRC). OCC-1D is a splice variant of OCC-1 gene which is considered as a long...     

Molecular and morphological evaluation of transgenic Persian walnut plants harboring Fld gene under osmotic stress condition

Molecular Biology Reports - Soil drought stress is a limiting factor of productivity in walnut (Juglans regia L). Ferredoxin (Fd) level decreases under adverse environmental stress. Functional...     

Copper (II) complexes with N,S donor pyrazole-based ligands as anticancer agents

BioMetals - A group of bidentate nitrogen and sulfur donor pyrazole derivative ligands abbreviated as Na[RNCS(Pz)], Na[RNCS(PzMe2)], Na[RNCS(PzMe3)], Na[RNCS(PzPhMe)], Na[RNCS(PzPh2)], where...     

Property evaluation of two anticancer candidate platinum complexes with N-isobutyl glycine ligand against human colon cancer

BioMetals - Small molecules have potential usage in cancer therapy due to their remarkable potency of disarranging the natural structure of nucleic acids. In this study, two complexes...     

A structural approach reveals how neighbouring C2H2 zinc fingers influence DNA binding specificity

Development of an accurate protein–DNA recognition code that can predict DNA specificity from protein sequence is a central problem in biology. C₂H₂ zinc fingers constitute by far the largest family of DNA binding domains and their binding specificity has been studied intensively. However, despite decades of research, accurate prediction of DNA specificity remains elusive. A major obstacle is thought to be the inability of current methods to account for the influence of neighbouring domains. Here we show that this problem can be addressed using a structural approach: we build structural models for all C₂H₂-ZF–DNA complexes with known binding motifs and find six distinct binding modes. Each mode changes the orientation of specificity residues with respect to the DNA, thereby modulating base preference. Most importantly, the structural analysis shows that residues at the domain interface strongly and predictably influence the binding mode, and hence specificity. Accounting for predicted binding mode significantly improves prediction accuracy of predicted motifs. This new insight into the fundamental behaviour of C₂H₂-ZFs has implications for both improving the prediction of natural zinc finger-binding sites, and for prioritizing further experiments to complete the code. It also provides a new design feature for zinc finger engineering.     

Concurrent Whole-Genome Haplotyping and Copy-Number Profiling of Single Cells

Methods for haplotyping and DNA copy-number typing of single cells are paramount for studying genomic heterogeneity and enabling genetic diagnosis. Before analyzing the DNA of a single cell by microarray or next-generation sequencing, a whole-genome amplification (WGA) process is required, but it substantially distorts the frequency and composition of the cell’s alleles. As a consequence, haplotyping methods suffer from error-prone discrete SNP genotypes (AA, AB, BB) and DNA copy-number profiling remains difficult because true DNA copy-number aberrations have to be discriminated from WGA artifacts. Here, we developed a single-cell genome analysis method that reconstructs genome-wide haplotype architectures as well as the copy-number and segregational origin of those haplotypes by employing phased parental genotypes and deciphering WGA-distorted SNP B-allele fractions via a process we coin haplarithmisis. We demonstrate that the method can be applied as a generic method for preimplantation genetic diagnosis on single cells biopsied from human embryos, enabling diagnosis of disease alleles genome wide as well as numerical and structural chromosomal anomalies. Moreover, meiotic segregation errors can be distinguished from mitotic ones.