Identification of new genes and quantitative trait locis associated with growth curve parameters in F2 chicken population using genome-wide association study.

The markers which are correlated with the growth curve parameters help in understanding the characteristics of individual growth during the rearing of livestock. This study aimed to identify a set of biomarkers through a GWAS for growth curve parameters in crossbred chickens using the Illumnia 60K chicken SNP Beadchip. Growth data were collected from a total of 301 birds from cross of a broiler line and native chickens. Using the Gompertz-Laird model, two growth curve parameters, the instantaneous growth rate per day (L) and the coefficient of relative growth or maturing index (k), were estimated. The L and k were used to estimate five derived parameters, namely asymptotic (mature) body weight, body weight at inflection point, age at the inflection point, average growth rate and maximum growth rate. These parameters were considered as phenotypic values in the GWAS based on generalized linear models. The results of the GWAS indicated 21 significant markers, which were located near or within 46 genes. A number of these genes, such as GH, RET, GRB14, FTSJ3 and CCK, are important for growth and meat quality in chickens, and some of them are growth related in other species such as sheep and cattle (GPI, XIRP2, GALNTL6, BMS1, THSD4, TRHDE, SHISA9, ACSL6 and DYNC1LI2). The other genes are associated with developmental biological pathways. These genes are particuarly related to body weight, average daily gain and growth QTL. The results of this study can shed light on the genetic mechanism of biological functions of growth factors in broiler chickens, which is useful for developing management practices and accelerating genetic progress in breeding programs.

BosFinder: a novel pre-microRNA gene prediction algorithm in Bos taurus.

MicroRNAs (miRNAs) are small non-coding RNAs that modulate gene expression transcriptionally (transcriptional activation or inactivation) and/or post-transcriptionally (translation inhibition or degradation of their target mRNAs). This phenomenon has significant roles in growth and developmental processes in plants and animals. Bos taurus is one of the most important livestock animals, having great importance in food and economical sciences and industries. However, limited information is available on Bos taurus constituent miRNAs because its whole genome assembly has been only recently published. Therefore, computational methods have been essential tools in miRNA gene prediction and discovery. Among these, machine-learning-based approaches are used to characterize genome scale pre-miRNAs from expressed sequence tags (ESTs). In this study, a support vector machine model was used to classify 33 structural and thermodynamic features of pre-miRNA genes. Public bovine EST data were obtained from different tissues in various developmental stages. A new algorithm, called BosFinder, was developed to identify and annotate the whole genome's derived pre-miRNAs. We found 18 776 highly potential pre-miRNA sequences. This is the first genome survey report of Bos taurus based on a machine-learning method for pre-miRNA gene finding. The bosfinder program is freely available at http://lbb.ut.ac.ir/Download/LBBsoft/BosFinder/.

Cuckoo search epistasis: a new method for exploring significant genetic interactions.

The advent of high-throughput sequencing technology has resulted in the ability to measure millions of single-nucleotide polymorphisms (SNPs) from thousands of individuals. Although these high-dimensional data have paved the way for better understanding of the genetic architecture of common diseases, they have also given rise to challenges in developing computational methods for learning epistatic relationships among genetic markers. We propose a new method, named cuckoo search epistasis (CSE) for identifying significant epistatic interactions in population-based association studies with a case-control design. This method combines a computationally efficient Bayesian scoring function with an evolutionary-based heuristic search algorithm, and can be efficiently applied to high-dimensional genome-wide SNP data. The experimental results from synthetic data sets show that CSE outperforms existing methods including multifactorial dimensionality reduction and Bayesian epistasis association mapping. In addition, on a real genome-wide data set related to Alzheimer's disease, CSE identified SNPs that are consistent with previously reported results, and show the utility of CSE for application to genome-wide data.

Building blocks of biological networks: a review on major network motif discovery algorithms.

In recent years, there has been a great interest in studying different aspects of complex networks in a range of fields. One important local property of networks is network motifs, recurrent and statistically significant sub-graphs or patterns, which assists researchers in the identification of functional units in the networks. Although network motifs may provide a deep insight into the network's functional abilities, their detection is computationally challenging. Therefore several algorithms have been introduced to resolve this computationally hard problem. These algorithms can be classified under various paradigms such as exact counting methods, sampling methods, pattern growth methods and so on. Here, the authors will give a review on computational aspects of major algorithms and enumerate their related benefits and drawbacks from an algorithmic perspective.

Transfer of rye chromosome segments to wheat by a gametocidal system.

A gametocidal chromosome derived from Aegilops triuncialis (3C) induces chromosome mutations in gametes lacking the 3C chromosome in common wheat (Triticum aestivum L.). We combined 3C with chromosome 1R of rye (Secale cereale L.) in a common wheat line to know how efficiently 3C induces transfers of small 1R segments to wheat. In the 811 progeny of this wheat line, we found five wheat chromosomes (2A, 2D, 3D, 5D and 7D) carrying segments of the 1R satellite. Wheat plants carrying these translocations were tested for the presence of a storage protein locus Sec-1 and a cluster of resistance genes for wheat rust diseases, Sr31, Lr26 and Yr9. The 2A and 2D translocations had the Sec-1 and three rust resistance loci. The 3D and 5D translocations had Sr31, Lr26 and Yr9 but not Sec-1. The 7D translocation lacked Sec-1, Lr26 and Yr9, but the presence of Sr31 in this translocation was not determined. This showed that the translocation points fell into three regions of the 1R satellite, namely, proximal to Sec-1, between Sec-1 and the rust resistance loci, and distal to the rust resistance loci. Thus, the 3C gametocidal system was demonstrated to be effective in transferring small rye chromosome segments.