The novel flightless-I gene brings together two gene families, actin- binding proteins related to gelsolin and leucine-rich-repeat proteins involved in Ras signal transduction

The Drosophila melanogaster gene flightless-I, involved in gastrulation and muscle degeneration, has Caenorhabditis elegans and human homologues. In these highly conserved genes, two previously known gene families have been brought together, families encoding the actin- binding proteins related to gelsolin and the leucine-rich-repeat (LRR) group of proteins involved in protein-protein interactions. Both these gene families exhibit characteristics of molecular changes involving replication slippage and exon shuffling. Phylogenetic analyses of 19 amino acid sequences of 6 related protein types indicate that actin- associated proteins related to gelsolin are monophyletic to a common ancestor and include flightless proteins. Conversely, comparison of 24 amino acid sequences of LRR proteins including the flightless proteins indicates that flightless proteins are members of a structurally related subgroup. Included in the flightless cluster are human and mouse rsp-1 proteins involved in suppressing v-Ras transformation of cells and the membrane-associated yeast (Saccharomyces cerevisae) adenylate cyclase whose analogous LRRs are required for interaction with Ras proteins. There is a strong possibility that ligands for this group could be related and that flightless may have a similar role in Ras signal transduction. It is hypothesized that an ancestral monomeric gelsolin precursor protein has undergone at least four independent gene reorganization events to account for the structural diversity of the extant family of gelsolin-related proteins and that gene duplication and exon shuffling events occurred prior to or at the beginning of multicellular life, resulting in the evolution of some members of the family soon after the appearance of actin-type proteins.      

Magnesium-induced inner membrane aggregation in heart mitochondria: prevention and reversal by carboxyatractyloside and bongkrekic acid

Mg(2+) at an optimal concentration of 2mM (ph 6.5) induces large increases (up to 30 percent) in the optical density of bovine heart mitochondria incubated under conditions of low ionic strength (< approx. 0.01). The increases are associated with aggregation (sticking together) of the inner membranes and are little affected by changes in the energy status of the mitochondria. Virtually all of a number of other polyvalent cations tested and Ag(+) induce increases in mitochondrial optical density similar to those induced by Mg(2+), their approximate order of concentration effectiveness in respect to Mg(2+) being: La(3+) > Pb(2+) = Cu(2+) > Cd(2+) > Zn(2+) > Ag(+) > Mn(2+) > Ca(2+) > Mg(2+). With the exception of Mg(2+), all of these cations appear to induce swelling of the mitochondria concomitant with inner membrane aggregation. The inhibitors of the adenine nucleotide transport reaction carboxyatratyloside and bongkrekic acid are capable of preventing and reversing Mg(2+)-induced aggregation at the same low concentration required for complete inhibition of phosphorylating respiration, suggesting that they inhibit the aggregation by binding to the adenine nucleotide carrier. The findings are interpreted to indicate (a) that the inner mitochondrial membrane is normally prevented from aggregating by virtue of its net negative outer surface change, (b) that the cations induce the membrane to aggregate by binding at its outer surface, decreasing the net negative charge, and (c) that carboxyatractyloside and bongkrekic acid inhibit the aggregation by binding to the outer surface of the membrane, increasing the net negative charge.     

Rates and patterns of mitochondrial DNA sequence evolution in fringilline finches (fringilla spp.) and the greenfinch (Carduelis chloris)

Rates and patterns of evolution in partial sequences of five mitochondrial genes (cytochrome b, ATPase 6, NADH dehydrogenase subunit 5, tRNA(Glu), and the control region) were compared among taxa in the passerine bird genera Fringilla and Carduelis. Rates of divergence do not vary significantly among genes, even in comparisons with the control region. Rate variation among lineages is significant only for the control region and NADH dehydrogenase subunit 5, and patterns of variation are consistent with the expectations of neutral theory. Base composition is biased in all genes but is stationary among lineages, and there is evidence for directional mutation pressure only in the control region. Despite these similarities, patterns of substitution differ among genes, consistent with alternative regimes of selective constraint. Rates of nonsynonymous substitution are higher in NADH dehydrogenase subunit 5 than in other protein-coding genes, and transitions exist in elevated proportions relative to transversions. Transitions appear to accumulate linearly with time in tRNA(Glu), and despite exhibiting the highest overall rate of divergence among species, there are no transversional changes in this gene. Finally, for resolving phylogenetic relationships among Fringilla taxa, the combined protein-coding data are broadly similar to those of the control region in terms of phylogenetic informativeness and statistical support.      

The Impact of Genetic Architecture on Genome-Wide Evaluation Methods

The rapid increase in high-throughput single-nucleotide polymorphism data has led to a great interest in applying genome-wide evaluation methods to identify an individual''s genetic merit. Genome-wide evaluation combines statistical methods with genomic data to predict genetic values for complex traits. Considerable uncertainty currently exists in determining which genome-wide evaluation method is the most appropriate. We hypothesize that genome-wide methods deal differently with the genetic architecture of quantitative traits and genomes. A genomic linear method (GBLUP), and a genomic nonlinear Bayesian variable selection method (BayesB) are compared using stochastic simulation across three effective population sizes and a wide range of numbers of quantitative trait loci (N_QTL). GBLUP had a constant accuracy, for a given heritability and sample size, regardless of N_QTL. BayesB had a higher accuracy than GBLUP when N_QTL was low, but this advantage diminished as N_QTL increased and when N_QTL became large, GBLUP slightly outperformed BayesB. In addition, deterministic equations are extended to predict the accuracy of both methods and to estimate the number of independent chromosome segments (M_e) and N_QTL. The predictions of accuracy and estimates of M_e and N_QTL were generally in good agreement with results from simulated data. We conclude that the relative accuracy of GBLUP and BayesB for a given number of records and heritability are highly dependent on M_e, which is a property of the target genome, as well as the architecture of the trait (N_QTL).THE rapid progress and reducing costs of genome sequencing and high-throughput DNA techniques have led to a great interest in applying genome-wide evaluation methods to identify individuals of high genetic merit. Genome-wide evaluation uses associations of a large number of SNP (single nucleotide polymorphism) markers across the whole genome with phenotypes to produce accurate estimates of breeding values (EBVs) for candidates to selection (Meuwissen et al. 2001). The accuracy of genome-wide selection (i.e., selection based on genomic EBVs) is expected to be substantially higher than that of traditional best linear unbiased prediction (BLUP) selection, which is based on pedigree and phenotypic data (Daetwyler et al. 2008; Goddard 2009; Hayes et al. 2009c). In addition, genome-wide selection has the potential to reduce inbreeding rates because of the increased emphasis on own rather than family information (Woolliams et al. 2002; Daetwyler et al. 2007; Dekkers 2007). Furthermore, the application of genome-wide evaluation approaches can significantly aid our understanding of quantitative trait genetic architecture.The genome-wide evaluation methods suggested to date can be broadly categorized into groups according to whether there is an assortment of the SNP by magnitude of effect or contribution to the variance. One group treats SNP homogeneously and includes variants of genomic best linear unbiased prediction (GBLUP). This group includes a form of ridge regression (Meuwissen et al. 2001) and the use of a realized relationship matrix computed from the markers instead of the traditional pedigree matrix (NejatiJavaremi et al. 1997; Villanueva et al. 2005; Hayes et al. 2009c). Both approaches have been shown to be equivalent (Habier et al. 2007; Goddard 2009). A second group provides for heterogeneity among SNP contributions to the variance, with some contributions permitted to be large while the remainder are small, possibly zero. This assortment is helped by Bayesian approaches, which place priors on numbers of SNP with major contributions (e.g., BayesA and BayesB; see Meuwissen et al. 2001, 2009; Lee et al. 2008), or with some penalty based on functions of the magnitude of effect for each SNP (e.g., Lasso; see Tibshirani 1996; Yi and Xu 2008) or with other smoothing metrics (Long et al. 2007). A third group attempts to reduce dimensionality by using principal components or partial least squares (Raadsma et al. 2008; Solberg et al. 2009) to identify an informative subset of SNP genotypes. The main two methods currently used in real data sets are a linear prediction method, GBLUP, and variants of nonlinear Bayesian variable selection approaches such as BayesB.In most simulated published data, the accuracy of BayesB outperformed that of GBLUP (e.g., Meuwissen et al. 2001; Habier et al. 2007; Lund et al. 2009). However, real data results have not consistently supported this conclusion. Two reviews of empirical results in dairy cattle to date have shown that GBLUP and BayesB result in very similar accuracies for most traits (Hayes et al. 2009a; Vanraden et al. 2009). One reason for the disagreement between simulated and real data results could be that the genetic architecture simulated is significantly different from what is found in real populations. Most studies published to date that compare methods using simulated architectures have considered only 50 or fewer QTL affecting the trait (e.g., Meuwissen et al. 2001; Habier et al. 2007; Lund et al. 2009). In this article we hypothesize that the relative utility of genome-wide evaluation methods depends significantly on both the genomic structure of the population and the genetic trait architecture.The main objective of this study was to compare a linear method, GBLUP, and a nonlinear variable selection method, BayesB, using simulated data across a range of population and trait genetic architectures to further understand the mechanics of genome-wide evaluation methods. An important secondary objective was to extend deterministic prediction models to predict the accuracy of both methods. Theoretical models complement stochastic simulation by helping the understanding of the factors involved in genome-wide evaluation performance and, in return, stochastic simulation is used to confirm theoretical derivations.     

Comparison of linkage disequilibrium and haplotype diversity on macro- and microchromosomes in chicken

Background

Toll like receptors (TLR) play the central role in the recognition of pathogen associated molecular patterns (PAMPs). Mutations in the TLR1, TLR2 and TLR4 genes may change the ability to recognize PAMPs and cause altered responsiveness to the bacterial pathogens.

Results

The study presents association between TLR gene mutations and increased susceptibility to Mycobacterium avium subsp. paratuberculosis (MAP) infection. Novel mutations in TLR genes (TLR1- Ser150Gly and Val220Met; TLR2 – Phe670Leu) were statistically correlated with the hindrance in recognition of MAP legends. This correlation was confirmed subsequently by measuring the expression levels of cytokines (IL-4, IL-8, IL-10, IL-12 and IFN-γ) in the mutant and wild type moDCs (mocyte derived dendritic cells) after challenge with MAP cell lysate or LPS. Further in silico analysis of the TLR1 and TLR4 ectodomains (ECD) revealed the polymorphic nature of the central ECD and irregularities in the central LRR (leucine rich repeat) motifs.

Conclusion

The most critical positions that may alter the pathogen recognition ability of TLR were: the 9^th amino acid position in LRR motif (TLR1–LRR10) and 4^th residue downstream to LRR domain (exta-LRR region of TLR4). The study describes novel mutations in the TLRs and presents their association with the MAP infection.     

THE EXPRESSION OF APELIN AND ITS RECEPTOR APJ DURING DIFFERENT PHYSIOLOGICAL STAGES IN THE BOVINE OVARY

Recent studies implicate that apelin and its receptor APJ may have important role for the modulation of angiogenesis. The aim of this study was to further characterise the regulation of apelin/APJ system in bovine ovary. Experiment 1: corpora lutea (CL) were assigned to the following stages: days 1-2, 3-4, 5-7, 8-12, 13-16, >18 (after regression) of oestrous cycle and of gravidity (month <3, 3-5, 6-7 and >8). Experiment 2: Follicles during maturation were divided into granulosa cells (GC) and theca interna (TI) and were examined separately. Classification of follicles occurred by follicle size and oestradiol-17β (E2) concentration in the follicular fluid (FF) (<0.5 ng/ml, 0.5-5 ng/ml; 5-40 ng/ml; 40-180 ng/ml; >180 ng/ml). Real-time RT-PCR (qPCR) was applied to investigate mRNA expression of examined factors. In general, the expression level of apelin during the oestrous cycle was significantly higher compared to the one during pregnancy. Apelin mRNA levels were always high during the cycle with a tendency of decrease after CL regression. The APJ mRNA in the CL was significantly up regulated on days 5-7 and 8-12 followed by a decrease on days 13-16, and further on days >18. The expression of APJ does not show any significant regulation in the CL throughout pregnancy. The expression of apelin and APJ was not statistically regulated in GC, but was significantly up regulated in follicles with an E2 concentration of more than 5 ng/ml and showed an increase according to growth and maturation of follicles. In conclusion, our data suggest that apelin/APJ system is involved in the mechanism regulating angiogenesis during follicle maturation as well as during CL formation and function in the bovine ovary.     

Genes and spacers of cloned sea urchin histone DNA analyzed by sequencing

A cloned histone gene cluster of the highly reiterated type from the sea urchin Psammechinus miliaris was analyzed by DNA sequencing. More than half of the 6 kb repeat was sequenced, including coding regions of all five histones, some prelude and trailing sequences lying adjacent to the structural genes, and segments of the AT-rich spacer DNA. The gene cluster does not code for gonad-specific histone variants but may instead be active in early sea urchin development, as indicated by comparison to reference histones. The encoded histones seem not to be derived from longer precursor proteins, nor is there any evidence for insert sequences within the coding regions. Sequence similarities exist among the putative ribosome-binding sites adjacent to the initiator codons of individual genes. The AT-rich spacer segments between the genes differ from each other, are made up from relatively simple nucleotide arrangements, but are not repetitious, and apparently do not code for additional large proteins.