Modelling female fertility traits in beef cattle using linear and non-linear models.

Female fertility traits are key components of the profitability of beef cattle production. However, these traits are difficult and expensive to measure, particularly under extensive pastoral conditions, and consequently, fertility records are in general scarce and somehow incomplete. Moreover, fertility traits are usually dominated by the effects of herd-year environment, and it is generally assumed that relatively small margins are kept for genetic improvement. New ways of modelling genetic variation in these traits are needed. Inspired in the methodological developments made by Prof. Daniel Gianola and co-workers, we assayed linear (Gaussian), Poisson, probit (threshold), censored Poisson and censored Gaussian models to three different kinds of endpoints, namely calving success (CS), number of days from first calving (CD) and number of failed oestrus (FE). For models involving FE and CS, non-linear models overperformed their linear counterparts. For models derived from CD, linear versions displayed better adjustment than the non-linear counterparts. Non-linear models showed consistently higher estimates of heritability and repeatability in all cases (h2  < 0.08 and r < 0.13, for linear models; h2  > 0.23 and r > 0.24, for non-linear models). While additive and permanent environment effects showed highly favourable correlations between all models (>0.789), consistency in selecting the 10% best sires showed important differences, mainly amongst the considered endpoints (FE, CS and CD). In consequence, endpoints should be considered as modelling different underlying genetic effects, with linear models more appropriate to describe CD and non-linear models better for FE and CS.

Genetic parameters of objectionable fibers and of their associations with fleece traits in Corriedale sheep.

The aim of this research was to assess the variability and genetic relationships among binary traits denoting the presence or absence of objectionable fibers, namely pigmented (BINPPF), medullated (BINPMED), and kemp fibers (BINPK), and of fleece traits (fiber diameter [FD] and clean fleece weight [CFW]) in Corriedale sheep. Additionally, the total response to selection against objectionable fibers and indirect responses when selecting for fleece traits were evaluated. Fiber records from 679 animals and fleece records from 795 animals obtained from 2 experimental flocks (from 2005 to 2007) were used; the pedigree file included a total of 3,792 animals. Heritability and genetic correlations among the traits were estimated with a multivariate animal model under a Bayesian setting. Heritability estimates (posterior SD) for BINPPF, BINPMED, and BINPK were 0.35 (0.08), 0.37 (0.10), and 0.63 (0.09), respectively; for CFW and FD, estimates were 0.42 (0.09) and 0.43 (0.08), respectively. The genetic correlations between CFW and the 3 types of objectionable fibers were very low (i.e., <0.2). Thus selection for CFW is not expected to affect the number of such fibers in any direction. The same occurred for the genetic correlation between BINPK and FD. Genetic correlations between FD and BINPMED and FD and BINPPF were positive and favorable (0.50 and 0.56, respectively). Selecting for lower FD would decrease the numbers of objectionable fibers. The expected correlated responses in BINPPF, BINPMED, and BINPK when selecting for CFW were -0.03 (0.11), 0.03 (0.11), and -0.05 (0.18), respectively; when selecting for FD, the correlated responses were -0.26 (0.11), -0.26 (0.11), and -0.14 (0.16). Overall, this study reports novel information on genetic parameters for the presence of objectionable fibers and their associations with fleece traits in sheep. Our findings suggest that it could be possible to improve FD while at the same time reducing the content of BINPMED and BINPPF in wool; however, improvements in CFW are likely to have no effect on the numbers of objectionable fibers.

Activation of the PI3K/AKT pathway by microRNA-22 results in CLL B-cell proliferation.

Chronic lymphocytic leukemia (CLL) is characterized by accumulation of clonal B cells arrested in G0/G1 stages that coexist, in different proportions, with proliferative B cells. Understanding the crosstalk between the proliferative subsets and their milieu could provide clues on CLL biology. We previously identified one of these subpopulations in the peripheral blood from unmutated patients that appears to be a hallmark of a progressive disease. Aiming to characterize the molecular mechanism underlying this proliferative behavior, we performed gene expression analysis comparing the global mRNA and microRNA expression of this leukemic subpopulation, and compared it with their quiescent counterparts. Our results suggest that proliferation of this fraction depend on microRNA-22 overexpression that induces phosphatase and tensin homolog downregulation and phosphoinositide 3-kinase (PI3K)/AKT pathway activation. Transfection experiments demonstrated that miR-22 overexpression in CLL B cells switches on PI3K/AKT, leading to downregulation of p27(-Kip1) and overexpression of Survivin and Ki-67 proteins. We also demonstrated that this pathway could be triggered by microenvironment signals like CD40 ligand/interleukin-4 and, more importantly, that this regulatory loop is also present in lymph nodes from progressive unmutated patients. Altogether, these results underline the key role of PI3K/AKT pathway in the generation of the CLL proliferative pool and provide additional rationale for the usage of PI3K inhibitors.

Identifying associations between amino acid changes and meta information in alignments.

MOTIVATION: We present a method that identifies associations between amino acid changes in potentially significant sites in an alignment (taking into account several amino acid properties) with phenotypic data, through the phylogenetic mixed model. The latter accounts for the dependency of the observations (organisms). It is known from previous studies that the pathogenic aspect of many organisms may be associated with a single or just few changes in amino acids, which have a strong structural and/or functional impact on the protein. Discovering these sites is a big step toward understanding pathogenicity. Our method is able to discover such sites in proteins responsible for the pathogenic character of a group of bacteria. RESULTS: We use our method to predict potentially significant sites in the RpoS protein from a set of 209 bacteria. Several sites with significant differences in biological relevant regions were found. AVAILABILITY: Our tool is publicly available on the CRAN network at http://cran.r-project.org/ CONTACT: naya@pasteur.edu.uy SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Assessment of Poisson, probit and linear models for genetic analysis of presence and number of black spots in Corriedale sheep.

Black skin spots are associated with pigmented fibres in wool, an important quality fault. Our objective was to assess alternative models for genetic analysis of presence (BINBS) and number (NUMBS) of black spots in Corriedale sheep. During 2002-08, 5624 records from 2839 animals in two flocks, aged 1 through 6 years, were taken at shearing. Four models were considered: linear and probit for BINBS and linear and Poisson for NUMBS. All models included flock-year and age as fixed effects and animal and permanent environmental as random effects. Models were fitted to the whole data set and were also compared based on their predictive ability in cross-validation. Estimates of heritability ranged from 0.154 to 0.230 for BINBS and 0.269 to 0.474 for NUMBS. For BINBS, the probit model fitted slightly better to the data than the linear model. Predictions of random effects from these models were highly correlated, and both models exhibited similar predictive ability. For NUMBS, the Poisson model, with a residual term to account for overdispersion, performed better than the linear model in goodness of fit and predictive ability. Predictions of random effects from the Poisson model were more strongly correlated with those from BINBS models than those from the linear model. Overall, the use of probit or linear models for BINBS and of a Poisson model with a residual for NUMBS seems a reasonable choice for genetic selection purposes in Corriedale sheep.

Predictive ability of direct genomic values for lifetime net merit of Holstein sires using selected subsets of single nucleotide polymorphism markers.

The objective of the present study was to assess the predictive ability of subsets of single nucleotide polymorphism (SNP) markers for development of low-cost, low-density genotyping assays in dairy cattle. Dense SNP genotypes of 4,703 Holstein bulls were provided by the USDA Agricultural Research Service. A subset of 3,305 bulls born from 1952 to 1998 was used to fit various models (training set), and a subset of 1,398 bulls born from 1999 to 2002 was used to evaluate their predictive ability (testing set). After editing, data included genotypes for 32,518 SNP and August 2003 and April 2008 predicted transmitting abilities (PTA) for lifetime net merit (LNM$), the latter resulting from progeny testing. The Bayesian least absolute shrinkage and selection operator method was used to regress August 2003 PTA on marker covariates in the training set to arrive at estimates of marker effects and direct genomic PTA. The coefficient of determination (R(2)) from regressing the April 2008 progeny test PTA of bulls in the testing set on their August 2003 direct genomic PTA was 0.375. Subsets of 300, 500, 750, 1,000, 1,250, 1,500, and 2,000 SNP were created by choosing equally spaced and highly ranked SNP, with the latter based on the absolute value of their estimated effects obtained from the training set. The SNP effects were re-estimated from the training set for each subset of SNP, and the 2008 progeny test PTA of bulls in the testing set were regressed on corresponding direct genomic PTA. The R(2) values for subsets of 300, 500, 750, 1,000, 1,250, 1,500, and 2,000 SNP with largest effects (evenly spaced SNP) were 0.184 (0.064), 0.236 (0.111), 0.269 (0.190), 0.289 (0.179), 0.307 (0.228), 0.313 (0.268), and 0.322 (0.291), respectively. These results indicate that a low-density assay comprising selected SNP could be a cost-effective alternative for selection decisions and that significant gains in predictive ability may be achieved by increasing the number of SNP allocated to such an assay from 300 or fewer to 1,000 or more.

Small RNAs analysis in CLL reveals a deregulation of miRNA expression and novel miRNA candidates of putative relevance in CLL pathogenesis.

MicroRNAs (miRNAs) are a novel class of small noncoding RNA molecules that regulate gene expression by inducing degradation or translational inhibition of target mRNAs. There are more than 500 miRNA genes reported in the human genome, constituting one of the largest classes of regulatory genes. Increasing experimental evidence supports the idea of aberrant miRNA expression in cancer pathogenesis. We analyzed the pattern of miRNA expression in chronic lymphocytic leukemia (CLL) cells and our results showed a global reduction in miRNA expression levels in CLL cells associated to a consistent underexpression of miR-181a, let-7a and miR-30d. We observed overexpression of miR-155 and a set of five miRNAs that are differentially expressed between patients with different clinical outcomes. Five novel miRNA candidates cloned from leukemic cells are reported. Surprisingly, predicted mRNA targets for these novel miRNA revealed a high proportion of targets located in a small region of chromosome 1, which is frequently altered in human cancer. Additionally, several targets were shared by at least two of miRNA candidates. Predicted targets included several genes recently described as tumor suppressors. These data could afford new avenues for exploring innovative pathways in CLL biology and therapy.

Genetic variability in calving success in Aberdeen Angus cows under extensive recording.

Data from 2032 Uruguayan Aberdeen Angus cows under extensive management and recording practices were analysed with Bayesian threshold-liability sire models, to assess genetic variability in calving success (CS), defined as a different binary trait for each of the second (CS2), third (CS3) and fourth (CS4) calving opportunities. Sire (herd) variances ranged from 0.08 to 0.11 (0.10 to 0.20) and heritability from 0.27 to 0.35, with large credibility intervals. Correlations between herd effects on CS at different calving opportunities were positive. Genetic correlation between CS2 and CS4 was positive (0.68), whereas those involving adjacent calving opportunities (CS2-CS3 and CS3-CS4) were negative, at -0.39 and -0.54, respectively. The residual correlation CS2-CS3 was negative (-0.32). The extent of uncertainty associated with the posterior estimates of the parameters was further evaluated through simulation, assuming different true values (-0.4, -0.2, +0.2 and +0.4) for the genetic correlations and changes in the degree of belief parameters of the inverse Wishart priors for the sire covariance matrix. Although inferences were not sharp enough, CS appears to be moderately heritable. The quality of data recording should be improved, in order to effect genetic improvement in female fertility.

Translational selection shapes codon usage in the GC-rich genome of Chlamydomonas reinhardtii.

In unicellular species codon usage is determined by mutational biases and natural selection. Among prokaryotes, the influence of these factors is different if the genome is skewed towards AT or GC, since in AT-rich organisms translational selection is absent. On the other hand, in AT-rich unicellular eukaryotes the two factors are present. In order to understand if GC-rich genomes display a similar behavior, the case of Chlamydomonas reinhardtii was studied. Since we found that translational selection strongly influences codon usage in this species, we conclude that there is not a common pattern among unicellular organisms.