Transmission ratio distortion regions in the context of genomic evaluation and their effects on reproductive traits in cattle.

Transmission ratio distortion (TRD), which is a deviation from Mendelian expectations, has been associated with basic mechanisms of life such as sperm and ova fertility and viability at developmental stages of the reproductive cycle. In this study different models including TRD regions were tested for different reproductive traits [days from first service to conception (FSTC), number of services, first service nonreturn rate (NRR), and stillbirth (SB)]. Thus, in addition to a basic model with systematic and random effects, including genetic effects modeled through a genomic relationship matrix, we developed 2 additional models, including a second genomic relationship matrix based on TRD regions, and TRD regions as a random effect assuming heterogeneous variances. The analyses were performed with 10,623 cows and 1,520 bulls genotyped for 47,910 SNPs, 590 TRD regions, and several records ranging from 9,587 (FSTC) to 19,667 (SB). The results of this study showed the ability of TRD regions to capture some additional genetic variance for some traits; however, this did not translate into higher accuracy for genomic prediction. This could be explained by the nature of TRD itself, which may arise in different stages of the reproductive cycle. Nevertheless, important effects of TRD regions were found on SB (31 regions) and NRR (18 regions) when comparing at-risk versus control matings, especially for regions with allelic TRD pattern. Particularly for NRR, the probability of observing nonpregnant cow increases by up to 27% for specific TRD regions, and the probability of observing stillbirth increased by up to 254%. These results support the relevance of several TRD regions on some reproductive traits, especially those with allelic patterns that have not received as much attention as recessive TRD patterns.

Discriminating between allele- and genotype-specific transmission ratio distortion.

Transmission ratio distortion (TRD) is defined as the observed deviation from the expected Mendelian inheritance of alleles from heterozygous parents. This phenomenon is attributed to various biological mechanisms acting on germ cells, embryos or fetuses, or even in early postnatal life. Current statistical approaches typically use two independent parametrizations assuming that TRD relies on allele- or genotype-related mechanisms, although they have never been tested and compared. This study compared allele- and genotype-related TRD models on simulated datasets with 1000 genotyped offspring and real data from 168 sire-dam-offspring beef cattle trios. The analysis of simulated datasets favored the true model of analysis in most cases (>93%), and a low percentage of missidentification occurred under (almost) null dominance (genotype-related model) or similar and moderate-to-low sire- and dam-specific TRD parameters (allele-related model). Moreover, the correlation between simulated and predicted distortion parameters was high (>0.97) under the true model. The comparison of allele- and genotype-related TRD models is an appealing tool to infer the biological source of TRD (i.e. haploid vs. diploid cells) when screening the whole genome. The analysis of beef cattle data corroborated a TRD region previously reported in chromosome 4, although discarding allele-related mechanisms and favoring the genotype-related model as the more reliable one. The results of this study highlight the relevance of implementing and comparing different parametrizations to capture all kinds of TRD, and to compare them using appropriate statistical methods.

Discovering lethal alleles across the turkey genome using a transmission ratio distortion approach.

Deviation from Mendelian inheritance expectations (transmission ratio distortion, TRD) has been observed in several species, including the mouse and humans. In this study, TRD was characterized in the turkey genome using both allelic (specific- and unspecific-parent TRD) and genotypic (additive- and dominance-TRD) parameterizations within a Bayesian framework. In this study, we evaluated TRD for 23 243 genotyped Turkeys across 56 393 autosomal SNPs. The analyses included 500 sires, 2013 dams and 11 047 offspring (trios). Three different haplotype sliding windows of 4, 10 and 20 SNPs were used across the autosomal chromosomes. Based on the genotypic parameterizations, 14 haplotypes showed additive and dominance TRD effects highlighting regions with a recessive TRD pattern. In contrast, the allelic model uncovered 12 haplotype alleles with the allelic TRD pattern which showed an underrepresentation of heterozygous offspring in addition to the absence of homozygous animals. For regions with the allelic pattern, only one particular region showed a parent-specific TRD where the penetrance was high via the dam, but low via the sire. The gene set analysis uncovered several gene ontology functional terms, Reactome pathways and several Medical Subject Headings that showed significant enrichment of genes associated with TRD. Many of these gene ontology functional terms (e.g. mitotic spindle assembly checkpoint, DRM complex and Aneuploidy), Reactome pathways (e.g. Mismatch repair) and Medical Subject Headings (e.g. Adenosine monophosphate) are known to be related to fertility, embryo development and lethality. The results of this study revealed potential novel candidate lethal haplotypes, functional terms and pathways that may enhance breeding programs in Turkeys through reducing mortality and improving reproduction rate.

Low genome-wide homozygosity in 11 Spanish ovine breeds.

The population of Spanish sheep has decreased from 24 to 15 million heads in the last 75 years due to multiple social and economic factors. Such a demographic reduction might have caused an increase in homozygosity and inbreeding, thus limiting the viability of local breeds with excellent adaptations to harsh ecosystems. The main goal of our study was to investigate the homozygosity patterns of 11 Spanish ovine breeds and to elucidate the relationship of these Spanish breeds with reference populations from Europe, Africa and the Near East. By using Ovine SNP50 BeadChip data retrieved from previous publications, we have found that the majority of studied Spanish ovine breeds have close genetic relatedness with other European populations; the one exception is the Canaria de Pelo breed, which is similar to North African breeds. Our analysis has also demonstrated that, with few exceptions, the genomes of Spanish sheep harbor fewer than 50 runs of homozygosity (ROH) with a total length of less than 350 Mb. Moreover, the frequencies of very long ROH (>30 Mb) are very low, and the inbreeding coefficients (FROH ) are generally small (FROH  < 0.10), ranging from 0.008 (Rasa Aragonesa) to 0.086 (Canaria de Pelo). The low levels of homozygosity observed in the 11 Spanish sheep under analysis might be due to their extensive management and the high number of small to medium farms.

Implementation of Bayesian methods to identify SNP and haplotype regions with transmission ratio distortion across the whole genome: TRDscan v.1.0.

Realized deviations from the expected Mendelian inheritance of alleles from heterozygous parents have been previously reported in a broad range of organisms (i.e., transmission ratio distortion; TRD). Various biological mechanisms affecting gametes, embryos, fetuses, or even postnatal offspring can produce patterns of TRD. However, knowledge about its prevalence and potential causes in livestock species is still scarce. Specific Bayesian models have been recently developed for the analyses of TRD for biallelic loci, which accommodated a wide range of population structures, enabling TRD investigation in livestock populations. The parameterization of these models is flexible and allows the study of overall (parent-unspecific) TRD and sire- and dam-specific TRD. This research aimed at deriving Bayesian models for fitting TRD on the basis of haplotypes, testing the models for both haplotype- and SNP-based methods in simulated data and actual Holstein genotypes, and developing a specific software for TRD analyses. Results obtained on simulated data sets showed that the statistical power of the analysis increased with sample size of trios (n), proportion of heterozygous parents, and the magnitude of the TRD. On the other hand, the statistical power to detect TRD decreased with the number of alleles at each loci. Bayesian analyses showed a strong Pearson correlation coefficient (≥0.97) between simulated and estimated TRD that reached the significance level of Bayes factor ≥10 for both single-marker and haplotype analyses when n ≥ 25. Moreover, the accuracy in terms of the mean absolute error decreased with the increase of the sample size and increased with the number of alleles at each loci. Using real data (55,732 genotypes of Holstein trios), SNP- and haplotype-based distortions were detected with overall TRD, sire-TRD, or dam-TRD, showing different magnitudes of TRD and statistical relevance. Additionally, the haplotype-based method showed more ability to capture TRD compared with individual SNP. To discard possible random TRD in real data, an approximate empirical null distribution of TRD was developed. The program TRDscan v.1.0 was written in Fortran 2008 language and provides a powerful statistical tool to scan for TRD regions across the whole genome. This developed program is freely available at http://www.casellas.info/files/TRDscan.zip.

On individual-specific prediction of hidden inbreeding depression load.

Inbreeding depression is caused by increased homozygosity in the genome and merges two genetic mechanisms, a higher impact from recessive mutations and the waste of overdominance contributions. It is of major concern for the conservation of endangered populations of plants and animals, as major abnormalities are more frequent in inbred families than in outcrosses. Nevertheless, we lack appropriate analytical methods to estimate the hidden inbreeding depression load (IDL) in the genome of each individual. Here, a new mixed linear model approach has been developed to account for the inbreeding depression-related background of each individual in the pedigree. Within this context, inbred descendants contributed relevant information to predict the IDL contained in the genome of a given ancestor; moreover, known relationships spread these predictions to the remaining individuals in the pedigree, even if not contributing inbred offspring. Results obtained from the analysis of weaning weight in the MARET rabbit population demonstrated that the genetic background of inbreeding depression distributed heterogeneously across individuals and inherited generation by generation. Moreover, this approach was clearly preferred in terms of model fit and complexity when compared with classical approaches to inbreeding depression. This methodology must be viewed as a new tool for a better understanding of inbreeding in domestic and wild populations.

Bayesian analysis of parent-specific transmission ratio distortion in seven Spanish beef cattle breeds.

Transmission ratio distortion (TRD) is the departure from the expected Mendelian ratio in offspring, a poorly investigated biological phenomenon in livestock species. Given the current availability of specific parametric methods for the analysis of segregation data, this study focused on the screening of TRD in 602 402 single nucleotide polymorphisms covering all autosomal chromosomes in seven Spanish beef cattle breeds. On average, 0.13% (n = 786) and 0.01% (n = 29) of genetic markers evidenced sire- or dam-specific TRD respectively. There were no single nucleotide polymorphisms accounting for both sire- and dam-specific TRD at the same time, and only one marker (rs43147474) accounted for (sire-specific) TRD in all seven breeds. It must be noted that rs43147474 is located in the fourth intronic region of the GTP-binding protein 10 gene, and this locus has been previously linked to the maintenance of mitochondria and nucleolar architectures. Alternatively, other candidate genes surround this hot-spot for sire-specific TRD in the cattle genome, and they are related to embryonic and postnatal lethality as well as prostate cancer, among others. This research characterized the distribution of TRD in the bovine genome, highlighting heterogeneous results when comparing across breeds.

Technical note: PaGELL v.1.5: A flexible parametric program for the Bayesian analysis of longevity data within the context of animal breeding.

This technical note presents the program PaGELL v.1.5 (Parametric Genetic Evaluation of Lifespan in Livestock), a flexible software program to analyze (right-censored) longevity data in livestock populations, with a special emphasis on the genetic evaluation of the breeding stock. This software relies on a parametric generalization of the proportional hazard model; more specifically, the baseline hazard function follows a Weibull process and flexibility is gained by including an additional time-dependent effect with the number of change points defined by the user. The program can accommodate 3 different sources of variation (i.e., systematic, permanent environmental, and additive genetic effects) and both fixed and time-dependent patterns (only for systematic and permanent environmental effects). Analyses are performed within a Bayesian context by sampling from the joint posterior distribution of the model, and model fit can be easily determined by the calculation of the deviance information criterion. Although this software has already been used on field data sets, its performance has been double-checked on simulated data set, and results are presented in this technical note. PaGELL v.1.5 was written in Fortran 95 language and, after compiling with the GNU Fortran Compiler v.4.7 and later, it has been tested in Windows, Linux, and MacOS operating systems (both 32- and 64-bit platforms). This program is available at http://www.casellas.info/files/pageII.zip.

Genetic and environmental relationships of detailed milk fatty acids profile determined by gas chromatography in Brown Swiss cows.

The aim of this study was to characterize the profile of 47 fatty acids, including conjugated linoleic acid (CLA), 13 fatty acid groups, and 5 Δ(9)-desaturation indices in milk samples from Brown Swiss cows. The genetic variation was assessed and the statistical relevance of the genetic background for each trait was evaluated using the Bayes factor test. The additive genetic, herd-date, and residual relationships were also estimated among all single fatty acids and groups of fatty acids. Individual milk samples were collected from 1,158 Italian Brown Swiss cows and a detailed analysis of fat percentages and milk fatty acid compositions was performed by gas chromatography. Bayesian animal models were used for (co)variance components estimation. Exploitable genetic variation was observed for most of the de novo synthesized fatty acids and saturated fatty acids, except for C4:0 and C6:0, whereas long-chain fatty acids and unsaturated fatty acids (including CLA) were mainly influenced by herd-date effects. Herd-date effect explained large portions of the total phenotypic variance for C18:2 cis-9,cis-12 (0.668), C18:3 cis-9,cis-12,cis-15 (0.631), and the biohydrogenation and elongation products of these fatty acids. The desaturation ratios showed higher heritability estimates than the individual fatty acids, except for CLA desaturation index (0.098). Among the medium-chain fatty acids, C12:0 had greater heritability than C14:0 (0.243 vs. 0.097, respectively). Both C14:0 and C16:0 showed negative additive genetic correlations with the main monounsaturated and polyunsaturated fatty acids of milk fat, suggesting that their synthesis in the mammary gland may be influenced by the presence of unsaturated fatty acids. No correlation was observed between C4:0 and the other short-chain fatty acids (except for C6:0), confirming the independence of C4:0 from de novo mammary fatty acid synthesis. Among the genetic correlations dealing with potentially beneficial fatty acids, C18:0 was positively correlated with vaccenic and rumenic acids and negatively with linoleic acid. Finally, fatty acids C6:0 through C14:0 showed relevant correlations due to unknown environmental effects, suggesting the potential existence of genetic variances in micro-environmental sensitivity. This study allowed us to acquire new knowledge about the genetic and the environmental relationships among fatty acids. Likewise, the existence of genetic variation for most of de novo synthetized fatty acids and saturated fatty acids was also observed. Overall, these results provide useful information to combine feeding with genetic selection strategies for obtaining a desirable milk fatty acids profile, depending on the origin of fatty acids in milk.

Application of the microarray technology to the transcriptional analysis of muscle phenotypes in pigs.

The transcriptome refers to the collection of all transcripts present in a cell. Gene expression has a very dynamic nature; it acts as a bridge between epigenetic marks, DNA sequence and proteins and changes to accommodate the requirements of the cell at each given time. Recent technological advances have created new opportunities to study complex phenotypes from a global point of view. From an animal production perspective, muscle transcriptomics has been investigated in relation to muscle growth, carcass fattening and meat quality traits. In this review, we discuss the impact of nutritional, anatomical and genetic factors on muscle gene expression and meat quality of pigs assessed by microarray technologies. Altogether, several common themes have been revealed by the in-depth analysis of the current body of knowledge, for instance, the involvement of genes related to energy balance and substrate turnover in the oxidative/glycolytic phenotype of red/white muscle fibre types and in the storage of intramuscular fat. The review also covers recent advances in the discovery of expression QTL and regulatory RNAs in porcine breeds as well as technical developments in the field of deep-sequencing technologies that are expected to substantially increase our knowledge about the genetic architecture of meat quality and production traits.

Classification of light Yorkshire pigs at different production stages using ordinary least squares and machine learning methods.

Pig homogeneity and growth are major concerns for the pig industry today. Variability in pigs' size has a strong impact on profitability as uniformity plays a key role in the overall economic value of pigs produced. This research focused on statistical methods to identify pigs at risk of growth retardation at different stages of production. Data from 125 083 Yorkshire pigs at weaning (18-28 d), 59 533 pigs at the end of the nursery period (70-82 d) and 48 862 pigs at slaughter (155-170 d) were analyzed under three different cut-points (lowest 10, 20 and 30%) to characterize light animals. Records were randomly split into 2:1 training:testing sets, and each training data set was analyzed through an ordinary least squares approach and four machine learning algorithms (decision tree, random forest, and two alternative boosting approaches). A wide range of weighting functions were applied to give increased relevance to lighter pigs. Each resulting classification norm was used to classify light pigs in the testing data set. Both sensitivity and specificity were retained to construct the receiver operating characteristic curve, and the statistical performance of each analytical approach was evaluated by the area under the curve (AUC). In all production stages and cut-points, the random forest machine learning algorithm provided the highest AUC, closely followed by boosting procedures. For weaning BW (WW), factors related to birth BW and litter size accounted for more than 75% of the important prediction factors for light pigs. BW at the end of the nursery period and slaughter BW analyses revealed a similar pattern where WW and BW at the end of the nursery period accounted for more than 40 and 50% of statistical importance among the prediction factors, respectively. Machine learning algorithms are useful tools to easily evaluate the risk factors affecting the efficiency and homogeneity in swine. Since the BW at birth and weaning are key factors, sow nutrition and feeding management during gestation and lactation, along with piglet management during lactation, are identified as important influences on pig weight variability.

Genetics of serum and muscle lipids in pigs.

Pork meat is one of the most important sources of animal protein in the human diet. Its nutritional properties are partly determined by intramuscular fat content and composition, with existing general consensus about the detrimental effects of cholesterol and saturated fat on cardiovascular health in humans. Because of their physiological resemblance, pigs can be also used as a valuable animal model to study the genetics of human diseases such as atherosclerosis, obesity and dyslipidaemias. Heritability estimates and QTL maps of porcine muscle and serum lipid traits evidence that a considerable amount of genetic variance determining these phenotypes exists, but its molecular basis remains mostly unknown. The recent advent of high-throughput genotyping and sequencing technologies has revolutionised the field of animal genomics. With these powerful tools, finding needles in the genomic haystack has become increasingly feasible. However, these methodological advances should not be deemed as magic bullets. The goal of identifying the many polymorphisms that shape the variability of lipid phenotypes is so challenging that success can be achieved only under the scope of large international consortia.

Transcriptional analysis of intramuscular fatty acid composition in the longissimus thoracis muscle of Iberian × Landrace back-crossed pigs.

This study aimed at identifying differential gene expression conditional on the fatty acid profile of the longissimus thoracis (Lt) muscle, a prime cut of economic relevance for fresh and cured pork production. A population of 110 Iberian (25%) × Landrace (75%) back-crossed pigs was used, because these two breeds exhibit extreme profiles of intramuscular saturated fatty acid, monounsaturated fatty acid (MUFA) and polyunsaturated fatty acid (PUFA) contents. Total RNA from Lt muscle was individually hybridized to GeneChip Porcine Genome arrays (Affymetrix). A principal component analysis was performed with data from the 110 animals to select 40 extreme animals based on the total fatty acid profile and the MUFA composition (MAP). Comparison of global transcription levels between extreme fatty acid profile pigs (n = 40) resulted in 219 differentially expressed probes (false discovery rate <0.10). Gene ontology, pathway and network analysis indicated that animals with higher percentages of PUFA exhibit a shift toward a more oxidative muscular metabolism state, with a raise in mitochondria function (PPARGC1A, ATF2), fatty acid uptake and oxidation (FABP5, MGLL). On the other hand, 87 probes were differentially expressed between MUFA composition groups (n = 40; false discovery rate <0.10). In particular, muscles rich in n-7 MUFA expressed higher levels of genes involved in lipid metabolism (GLUL, CRAT, PLA2G15) and lower levels of fatty acid elongation genes (ELOVL5). Moreover, the chromosomal position of FABP5, PAQR3, MGLL, PPARGC1A, GLUL and ELOVL5 co-localized with very relevant QTL for fat deposition and composition described in the same resource population. This study represents a complementary approach to identifying genes underlying these QTL effects.

Genetic analysis of rennet coagulation time, curd-firming rate, and curd firmness assessed over an extended testing period using mechanical and near-infrared instruments.

The aims of this study were (1) to analyze rennet coagulation time (RCT), curd-firming rate, and curd firmness obtained by extending the standard 30-min testing time to 45 min; (2) to estimate heritabilities of the aforementioned traits determined by mechanical (Formagraph; Foss Electric, Hillerød, Denmark) and near-infrared optical (Optigraph; Ysebaert, Frépillon, France) instruments, and to assess the statistical relevance of their genetic background by using the Bayes factor procedure, the deviance information criterion, and the mean squared error; (3) to estimate phenotypic and genetic relationships between instruments within trait and between traits within instrument; and (4) to obtain correlations for sire rankings based on the used instruments. Individual milk samples were collected from 913 Brown Swiss cows reared in 63 herds located in Trento Province (Italy). Milk coagulation properties (MCP) were measured using 2 different instruments: Formagraph and Optigraph. Both instruments were housed in the same laboratory and operated by the same technician. Each sample was analyzed simultaneously on each instrument. All experimental conditions (milk temperature and the concentration and type of rennet) were identical. For the analysis, univariate and bivariate animal models were implemented using Bayesian methods. Univariate analyses were conducted to test the hypothesis that the traits showed additive genetic determination. Deviance information criterion, Bayes factor, and mean squared error were used as model choice criteria. The main results were that (1) RCT could be measured on all samples by extending the observation time to 45 min, and its genetic parameters (h(2)=0.23) and breeding values could be estimated while avoiding the bias of noncoagulating samples; (2) curd-firming rate could be measured on almost all milk samples, and its genetic parameters could be estimated for the first time on a field data set (h(2)=0.21); (3) for the first time, genetic parameters of curd firmness 45 min after rennet addition (h(2)=0.12) were estimated, and they were compared with curd firmness 30 min after rennet addition (h(2)=0.17); and (4) MCP estimated using the Optigraph appeared to be genetically different from those determined by Formagraph, with the partial exception of RCT (genetic correlation=0.97). Breeding strategies for the improvement of MCP must be planned with caution. Currently, the high throughput, ease of use, and reduced costs of analysis make predictions obtained from mid-infrared spectroscopy (MIRS) on untreated milk samples a promising alternative to produce relevant data at the population level. The use of mechanical lactodynamographs to establish reference data for MIRS calibrations have been already studied, whereas the use of near-infrared optical lactodynamographs as a reference method for MIRS calibrations needs to be investigated.

Distortion of Mendelian segregation across the Angus cattle genome uncovering regions affecting reproduction.

Nowadays, the availability of genotyped trios (sire-dam-offspring) in the livestock industry enables the implementation of the transmission ratio distortion (TRD) approach to discover deleterious alleles in the genome. Various biological mechanisms at different stages of the reproductive cycle such as gametogenesis, embryo development and postnatal viability can induce signals of TRD (i.e., deviation from Mendelian inheritance expectations). In this study, TRD was evaluated using both SNP-by-SNP and sliding windows of 2-, 4-, 7-, 10- and 20-SNP across 92,942 autosomal SNPs for 258,140 genotyped Angus cattle including 7,486 sires, 72,688 dams and 205,966 offspring. Transmission ratio distortion was characterized using allelic (specific- and unspecific-parent TRD) and genotypic parameterizations (additive- and dominance-TRD). Across the Angus autosomal chromosomes, 851 regions were clearly found with decisive evidence for TRD. Among these findings, 19 haplotypes with recessive patterns (potential lethality for homozygote individuals) and 52 regions with allelic patterns exhibiting complete or quasi-complete absence for homozygous individuals in addition to under-representation (potentially reduced viability) of the carrier (heterozygous) offspring were found. In addition, 64 (12) and 20 (4) regions showed significant influence on the trait heifer pregnancy at p-value < 0.05 (after chromosome-wise false discovery rate) and 0.01, respectively, reducing the pregnancy rate up to 15%, thus, supporting the biological importance of TRD phenomenon in reproduction.

Recombination rates across porcine autosomes inferred from high-density linkage maps.

Studies of the variation in recombination rate across the genome provide a better understanding of evolutionary genomics and are also an important step towards mapping and dissecting complex traits in domestic animals. With the recent completion of the porcine genome sequence and the availability of a high-density porcine single nucleotide polymorphism (SNP) array, it is now possible to construct a high-density porcine linkage map and estimate recombination rate across the genome. A total of 416 animals were genotyped with the Porcine SNP60BeadChip, and high-density chromosome linkage maps were constructed using CRI-MAP, assuming the physical order of the Sscrofa10 assembly. The total linkage map length was 2018.79 cM, using 658 meioses and 14,503 SNPs. The estimated average recombination rate across the porcine autosomes was 0.86 cM/Mb. However, a large variation in recombination rate was observed among chromosomes. The estimated average recombination rates (cM/Mb) per chromosome ranged from 0.48 in SSC1 to 1.48 in SSC10, displaying a significant negative correlation with the chromosome sizes. In addition, the analysis of the variation in the recombination rates taking 1-Mb sliding windows has allowed us to demonstrate the variation in recombination rates within chromosomes. In general, a larger recombination rate was observed in the extremes than in the centre of the chromosome. Finally, the ratio between female and male recombination rates was also inferred, obtaining a value of 1.38, with the heterogametic sex having the least recombination.

Colonic stenting as a bridge to surgery in malignant large-bowel obstruction: a report from two large multinational registries.

OBJECTIVES: To date, this is the largest prospective series in patients with malignant colorectal obstruction to evaluate the effectiveness and safety of colonic self-expanding metal stents (SEMSs) as an alternative to emergency surgery. SEMSs allow restoration of bowel transit and careful tumor staging in preparation for elective surgery, hence avoiding the high morbidity and mortality associated with emergency surgery and stoma creation. METHODS: This report is on the SEMS bridge-to-surgery subset enrolled in two multicenter international registries. Patients were treated per standard of practice, with documentation of clinical and procedural success, safety, and surgical outcomes. RESULTS: A total of 182 patients were enrolled with obstructive tumor in the left colon (85%), rectum (11%), or splenic flexure (4%). Of these patients, 86% had localized colorectal cancer without metastasis. Procedural success was 98% (177/181). Clinical success was 94% (141/150). Elective surgery was performed in 150 patients (9 stomas) and emergency surgery in 7 patients for treatment of a complication (3 stomas). The overall complication rate was 7.8% (13/167), including perforation in 3% (5/167), stent migration in 1.2% (2/167), bleeding in 0.6% (1/167), persistent colonic obstruction in 1.8% (3/167), and stent occlusion due to fecal impaction in 1.2% (2/167). One patient died from complications related to surgical management of a perforation. CONCLUSIONS: SEMSs provide an effective bridge to surgery treatment with an acceptable complication rate in patients with acute malignant colonic obstruction, restoring luminal patency and allowing elective surgery with primary anastomosis in most patients.

Quantitative trait loci for fatness at growing and reproductive stages in Iberian × Meishan F(2) sows.

A considerable number of fatness QTL have been identified in growing pigs, but there is a lack of knowledge about the genetic architecture of this trait in gilts and sows. We have performed a genome scan, in 255 Iberian × Meishan F(2) sows, for backfat thickness (BF) at 150 (BF(150) ) and 210 (BF(210)) days of age, 30 days after conception (BF(30)) and 7-10 days before farrowing (BF(bf)). We have found one BF150 QTL in SSC6 (120 cM) that was highly significant (P < 0.001) at the chromosome-wide level and suggestive at the genome-wide level (P < 0.1). Ten additional chromosome-wide significant QTL were found for sow BF(150) (SSC1, SSC13), BF(210) (SSC6, SSC8, SSC15), BF(30) (SSC5, SSC6) and BF(bf) (SSC1, SSC6, SSC13). The location of several of the BF QTL varied depending on the growing and reproductive status of the sow, suggesting that part of these genetic effects may have a temporal pattern of phenotypic expression.

Short communication: effect of mutation age on genomic predictions.

Genomic selection relies on the whole-genome evaluation of single nucleotide polymorphisms (SNP), some of them linked to quantitative trait loci (QTL). Although statistical methodology has been developed for the analysis of genomic data, little is known about the performance of SNP association studies when trying to capture variability from QTL mutations of different ages. Within this context, the influence of mutation age was analyzed under a simulation design, assuming presence or absence of selection on mutant QTL alleles. Focusing on a unique chromosome with a single QTL located in the proximal end, the performance of the genomic selection analyses was evaluated in terms of standardized mean square error (MSE). For all simulation scenarios, MSE was highest for the youngest mutations. The MSE was progressively reduced with mutation age under random mating and soft selection, and reached its maximum performance with the oldest mutations. On the other hand, moderate and strong selection caused a quick reduction of the MSE from youngest mutations to mutations arising in generations 920 to 939, thus resulting in a progressive increase for older mutations. In both cases, very young mutations escaped from genomic selection analyses, releasing a relevant amount of genetic variability that could not be captured and used in genomic selection programs. This demonstrated the need for new analytical approaches to model relevant and recent sources of variation; if captured, these young mutations could substantially contribute to current breeding schemes.

Bootstrap test for proportional hazard assumption on time-independent systematic effects of longevity data.

This manuscript focuses on the development of a bootstrap test for validating the proportional hazard (PH) assumption in longevity data, avoiding parametric assumptions on baseline survival and hazard patterns, and subjective interpretations of previously developed graphical tests. Monte Carlo simulations are used to generate new data sets from the estimated Kaplan-Meier survival function, and inferences are then made on the coefficient of variation (CV) of the estimated hazard over time. One-tailed bootstrap intervals can be established, given that the CV could theoretically range between 0 (perfect PH) and +∞ (absolute loss of proportionality between hazard functions). This procedure was tested by simulation, and the obtained results suggested it as a useful statistical tool when Kaplan-Meier assumptions are satisfied. If not, this bootstrap test was robust for medium to large data sets, whereas it could suffer from statistical biases when testing small populations.