A molecular genome scan and positional candidate gene analysis for important economic traits in the pig

Meat quality contributes considerably to the profit involved in pork production. The main objectives of this study were to identify the chromosomal locations for growth, body composition and meat quality related traits in pigs and to identify genes that control quantitative traits of economic importance. Genome scans were employed to identify these chromosomal regions. A three-generation resource family was developed using two Berkshire grand sires and nine Yorkshire grand dams. Data for 40 traits (growth, body composition and meat quality) were collected from 525 F2 progeny. Linkage analysis and regression interval mapping based on 125 microsatellite markers were used for QTL detection. Significance thresholds were determined by permutation tests. Significant QTL at the chromosome wise 5% level were detected for a total of over 100 growth (chromosomes 1, 2, 3, 4, 6, 7, 8, 9, 11, 13, 14, X), backfat (chromosomes 1, 4, 5, 6, 7, 10, 13, 14) and meat quality traits (chromosomes 1, 2, 4, 5, 6, 8, 10, 11, 12, 13, 14, 15, 17, 18, X). Five genes (ACACB, PPP1CC, GPR49, DUSP6, ATP2B1 ) from human chromosome 12 were chosen as possible candidate genes for QTL detected on chromosome 5. These genes were successfully mapped by physical and genetic methods. Two genes (DUSP6, ATP2B1) were considered for further positional candidate gene analysis. A ATP2B1-Afl III polymorphism revealed significant associations with growth, body composition, and meat quality traits (glycogen content and potential, and ham and loin pH) in the BxY F2 population, but only with light reflectance of ham in a commercial line. A DUSP6-Pst1 Polymorphism was associated with fat traits, which was consistent in the QTL analysis and association studies in the BxY family and in two commercial lines. The identified ATP2B1 and DUSP6 polymorphisms could potentially be used as a markers to track associated QTL and to discover the causative DNA differences

Steady State In A Markov Process

It is well known that a Markov process whose transition matrix is regular approaches a steady-state distribution, or equilibrium distribution. To find these steady-state probabilities requires the solution of a system of linear homogenous equations. However, the matrix of this system is singular and thus the system has infinitely many solutions. This obstacle is overcome by replacing one of the equations of the linear homogenous system by the linear non-homogeneous equation that simply expresses the requirement that the steady-state probabilities sum to one. But which equation of the original system should be chosen to be the one replaced. This brief article demonstrates that any of the equations of the original linear system can be selected as the one to be replaced; no matter which one is selected for replacement; the revised linear system will have the same unique solution

Association of INOS, TRAIL, TGF-b2, TGF-b3, and IgL Genes with Response to Salmonella enteritidis in Poultry

Several candidate genes were selected, based on their critical roles in the host’s response to intracellular bacteria, to study the genetic control of the chicken response to Salmonella enteritidis (SE). The candidate genes were: inducible nitric oxide synthase (INOS), tumor necrosis factor related apoptosis inducing ligand (TRAIL), transforming growth factor b2 (TGF-b2), transforming growth factor b3 (TGF-b3), and immunoglobulin G light chain (IgL). Responses to pathogenic SE colonization or to SE vaccination were measured in the Iowa Salmonella response resource population (ISRRP). Outbred broiler sires and three diverse, highly inbred dam lines produced 508 F1 progeny, which were evaluated as young chicks for either bacterial load isolated from spleen or cecum contents after pathogenic SE inoculation, or the circulating antibody level after SE vaccination. Fragments of each gene were sequenced from the founder lines of the resource population to identify genomic sequence variation. Single nucleotide polymorphisms (SNP) were identified, then PCR-RFLP techniques were developed to genotype the F1 resource population. Linear mixedmodels were used for statistical analyses. Because the inbred dam lines always contributed one copy of the same allele, the heterozygous sire allele effects could be assessed in the F1 generation. Association analyses revealed significant effects of the sire allele of TRAIL-StyI on the spleen (P \u3c 0:07) and cecum (P \u3c 0:0002) SE bacterial load. Significant effects (P \u3c 0:04) were found on the cecum bacterial load for TGF-b3-BsrI. Varied and moderate association was found for SE vaccine antibody response for all genes. This is the first reported study on the association of SNP in INOS, TRAIL, TGF-b2, TGF-b3, and IgL with the chicken response to SE. Identification of candidate genes to improve the immune response may be useful for marker-assisted selection to enhance disease resistance

Recovery of Low-Rank Matrices under Affine Constraints via a Smoothed Rank Function

In this paper, the problem of matrix rank minimization under affine constraints is addressed. The state-of-the-art algorithms can recover matrices with a rank much less than what is sufficient for the uniqueness of the solution of this optimization problem. We propose an algorithm based on a smooth approximation of the rank function, which practically improves recovery limits on the rank of the solution. This approximation leads to a non-convex program; thus, to avoid getting trapped in local solutions, we use the following scheme. Initially, a rough approximation of the rank function subject to the affine constraints is optimized. As the algorithm proceeds, finer approximations of the rank are optimized and the solver is initialized with the solution of the previous approximation until reaching the desired accuracy. On the theoretical side, benefiting from the spherical section property, we will show that the sequence of the solutions of the approximating function converges to the minimum rank solution. On the experimental side, it will be shown that the proposed algorithm, termed SRF standing for Smoothed Rank Function, can recover matrices which are unique solutions of the rank minimization problem and yet not recoverable by nuclear norm minimization. Furthermore, it will be demonstrated that, in completing partially observed matrices, the accuracy of SRF is considerably and consistently better than some famous algorithms when the number of revealed entries is close to the minimum number of parameters that uniquely represent a low-rank matrix.Comment: Accepted in IEEE TSP on December 4th, 201

DOA Estimation in Partially Correlated Noise Using Low-Rank/Sparse Matrix Decomposition

We consider the problem of direction-of-arrival (DOA) estimation in unknown partially correlated noise environments where the noise covariance matrix is sparse. A sparse noise covariance matrix is a common model for a sparse array of sensors consisted of several widely separated subarrays. Since interelement spacing among sensors in a subarray is small, the noise in the subarray is in general spatially correlated, while, due to large distances between subarrays, the noise between them is uncorrelated. Consequently, the noise covariance matrix of such an array has a block diagonal structure which is indeed sparse. Moreover, in an ordinary nonsparse array, because of small distance between adjacent sensors, there is noise coupling between neighboring sensors, whereas one can assume that nonadjacent sensors have spatially uncorrelated noise which makes again the array noise covariance matrix sparse. Utilizing some recently available tools in low-rank/sparse matrix decomposition, matrix completion, and sparse representation, we propose a novel method which can resolve possibly correlated or even coherent sources in the aforementioned partly correlated noise. In particular, when the sources are uncorrelated, our approach involves solving a second-order cone programming (SOCP), and if they are correlated or coherent, one needs to solve a computationally harder convex program. We demonstrate the effectiveness of the proposed algorithm by numerical simulations and comparison to the Cramer-Rao bound (CRB).Comment: in IEEE Sensor Array and Multichannel signal processing workshop (SAM), 201

Successive Concave Sparsity Approximation for Compressed Sensing

In this paper, based on a successively accuracy-increasing approximation of the $\ell_0$ norm, we propose a new algorithm for recovery of sparse vectors from underdetermined measurements. The approximations are realized with a certain class of concave functions that aggressively induce sparsity and their closeness to the $\ell_0$ norm can be controlled. We prove that the series of the approximations asymptotically coincides with the $\ell_1$ and $\ell_0$ norms when the approximation accuracy changes from the worst fitting to the best fitting. When measurements are noise-free, an optimization scheme is proposed which leads to a number of weighted $\ell_1$ minimization programs, whereas, in the presence of noise, we propose two iterative thresholding methods that are computationally appealing. A convergence guarantee for the iterative thresholding method is provided, and, for a particular function in the class of the approximating functions, we derive the closed-form thresholding operator. We further present some theoretical analyses via the restricted isometry, null space, and spherical section properties. Our extensive numerical simulations indicate that the proposed algorithm closely follows the performance of the oracle estimator for a range of sparsity levels wider than those of the state-of-the-art algorithms.Comment: Submitted to IEEE Trans. on Signal Processin

Detection of imprinted QTL in the Berkshire x Yorkshire cross

Genome scans have enabled the detection of regions on chromosomes that contain genes that affect economic traits, so-called quantitative trait loci (QTL). An example is the genome scan that was conducted at ISU in an F2 cross between the Berkshire and Yorkshire breeds (Malek et al. 2001a,b). This study identified many QTL related to growth performance and meat quality. But this analysis only considered QTL with a Mendelian mode of expression. This implies that an effect of the Berkshire allele on the trait was assumed to be the same whether it was inherited from the F1 sire or from the F1 dam (see Figure 1). As a result, the two heterozygotes (BY and YB) are assumed to have the same effect (d). There is, however, evidence that the expression of some genes depends on their parental origin. For example, with paternal expression, a Berkshire gene for increased meat quality would only be expressed in the F2 progeny if it was inherited from the sire (Figure 2). In that case, individuals with QTL genotype BB and BY are expected to have the same genetic value (Figure 2), as do individuals with genotypes YB and YY. The inheritance mechanism for maternal expression is illustrated in Figure 3. In this case, genotype BB has the same value as YB, as do BY and YY