Carcass traits are crucial characteristics of broilers. However, the underlying genetic mechanisms are not well understood. In the current study, significant loci and major-effect candidate genes affecting nine carcass traits related to meat production were analyzed in 873 purebred broilers using an imputation-based genome-wide association study.
 
  The heritability estimates of nine carcass traits, including carcass weight, thigh muscle weight, and thigh muscle percentage, were moderate to high and ranged from 0.21 to 0.39. Twelve genome-wide significant SNPs and 118 suggestively significant SNPs of 546,656 autosomal variants were associated with carcass traits. All SNPs for six weight traits (body weight at 42 days of age, carcass weight, eviscerated weight, whole thigh weight, thigh weight, and thigh muscle weight) were clustered around the 24.08 Kb region (GGA24 5.73-5.75 Mb) and contained only one candidate gene (
  ). The most significant SNP, rs15226023, accounted for 4.85-7.71% of the estimated genetimajor-effect candidate gene for carcass composition traits. Our results supply essential information for causative mutation identification of carcass traits in broilers.Mutually exclusive splicing is an important mechanism for expanding protein diversity. An extreme example is the Down syndrome cell adhesion molecular (Dscam1) gene of insects, containing four clusters of variable exons (exons 4, 6, 9, and 17), which potentially generates tens of thousands of protein isoforms through mutually exclusive splicing, of which regulatory mechanisms are still elusive. Here, we systematically analyzed the variable exon 4, 6, and 9 clusters of Dscam1 in Coleoptera species. Through comparative genomics and RNA secondary structure prediction, we found apparent evidence that the evolutionarily conserved RNA base pairing mediates mutually exclusive splicing in the Dscam1 exon 4 cluster. In contrast to the fly exon 6, most exon 6 selector sequences in Coleoptera species are partially located in the variable exon region. Besides, bidirectional RNA-RNA interactions are predicted to regulate the mutually exclusive splicing of variable exon 9 of Dscam1. Although the docking sites in exon 4 and 9 clusters are clade specific, the docking sites-selector base pairing is conserved in secondary structure level. In short, our result provided a mechanistic framework for the application of long-range RNA base pairings in regulating the mutually exclusive splicing of Coleoptera Dscam1.Determining mechanisms regulating complex traits in pigs is essential to improve the production efficiency of this globally important protein source. MicroRNAs (miRNAs) are a class of non-coding RNAs known to post-transcriptionally regulate gene expression affecting numerous phenotypes, including those important to the pig industry. To facilitate a more comprehensive understanding of the regulatory mechanisms controlling growth, carcass composition, and meat quality phenotypes in pigs, we integrated miRNA and gene expression data from longissimus dorsi muscle samples with genotypic and phenotypic data from the same animals. We identified 23 miRNA expression Quantitative Trait Loci (miR-eQTL) at the genome-wide level and examined their potential effects on these important production phenotypes through miRNA target prediction, correlation, and colocalization analyses. One miR-eQTL miRNA, miR-874, has target genes that colocalize with phenotypic QTL for 12 production traits across the genome including backfat thickness, dressing percentage, muscle pH at 24 h post-mortem, and cook yield. The results of our study reveal genomic regions underlying variation in miRNA expression and identify miRNAs and genes for future validation of their regulatory effects on traits of economic importance to the global pig industry.Interrupted exons in the pre-mRNA transcripts are ligated together through RNA splicing, which plays a critical role in the regulation of gene expression. Exons with a length ≤ 30 nt are defined as microexons that are unique in identification. However, microexons, especially those shorter than 8 nt, have not been well studied in many organisms due to difficulties in mapping short segments from sequencing reads. Here, we analyzed mRNA-seq data from a variety of Drosophila samples with a newly developed bioinformatic tool, ce-TopHat. In addition to the Flybase annotated, 465 new microexons were identified. Differentially alternatively spliced (AS) microexons were investigated between the Drosophila tissues (head, body, and gonad) and genders. Most of the AS microexons were found in the head and two AS microexons were identified in the sex-determination pathway gene fruitless.Eukaryotic genomes are wrapped around nucleosomes and organized into different levels of chromatin structure. Chromatin organization has a crucial role in regulating all cellular processes involving DNA-protein interactions, such as DNA transcription, replication, recombination and repair. Histone post-translational modifications (HPTMs) have a prominent role in chromatin regulation, acting as a sophisticated molecular code, which is interpreted by HPTM-specific effectors. Here, we review the role of histone lysine methylation changes in regulating the response to radiation-induced genotoxic damage in mammalian cells. We also discuss the role of histone methyltransferases (HMTs) and histone demethylases (HDMs) and the effects of the modulation of their expression and/or the pharmacological inhibition of their activity on the radio-sensitivity of different cell lines.  https://www.selleckchem.com/ALK.html  Finally, we provide a bioinformatic analysis of published datasets showing how the mRNA levels of known HMTs and HDMs are modulated in different cell lines by exposure to different irradiation conditions.Classification is widely used in gene expression data analysis. Feature selection is usually performed before classification because of the large number of genes and the small sample size in gene expression data. In this article, a novel feature selection algorithm using approximate conditional entropy based on fuzzy information granule is proposed, and the correctness of the method is proved by the monotonicity of entropy. Firstly, the fuzzy relation matrix is established by Laplacian kernel. Secondly, the approximately equal relation on fuzzy sets is defined. And then, the approximate conditional entropy based on fuzzy information granule and the importance of internal attributes are defined. Approximate conditional entropy can measure the uncertainty of knowledge from two different perspectives of information and algebra theory. Finally, the greedy algorithm based on the approximate conditional entropy is designed for feature selection. Experimental results for six large-scale gene datasets show that our algorithm not only greatly reduces the dimension of the gene datasets, but also is superior to five state-of-the-art algorithms in terms of classification accuracy.