Use of different marker pre-selection methods based on single SNP regression in the estimation of Genomic-EBVs

Two methods of SNPs pre-selection based on single marker regression for the estimation of genomic breeding values (G-EBVs) were compared using simulated data provided by the XII QTL-MAS workshop: i) Bonferroni correction of the significance threshold and ii) Permutation test to obtain the reference distribution of the null hypothesis and identify significant markers at P<0.01 and P<0.001 significance thresholds. From the set of markers significant at P<0.001, random subsets of 50% and 25% markers were extracted, to evaluate the effect of further reducing the number of significant SNPs on G-EBV predictions. The Bonferroni correction method allowed the identification of 595 significant SNPs that gave the best G-EBV accuracies in prediction generations (82.80%). The permutation methods gave slightly lower G-EBV accuracies even if a larger number of SNPs resulted significant (2,053 and 1,352 for 0.01 and 0.001 significance thresholds, respectively). Interestingly, halving or dividing by four the number of SNPs significant at P<0.001 resulted in an only slightly decrease of G-EBV accuracies. The genetic structure of the simulated population with few QTL carrying large effects, might have favoured the Bonferroni method

GPGPU for track finding in High Energy Physics

The LHC experiments are designed to detect large amount of physics events produced with a very high rate. Considering the future upgrades, the data acquisition rate will become even higher and new computing paradigms must be adopted for fast data-processing: General Purpose Graphics Processing Units (GPGPU) is a novel approach based on massive parallel computing. The intense computation power provided by Graphics Processing Units (GPU) is expected to reduce the computation time and to speed-up the low-latency applications used for fast decision taking. In particular, this approach could be hence used for high-level triggering in very complex environments, like the typical inner tracking systems of the multi-purpose experiments at LHC, where a large number of charged particle tracks will be produced with the luminosity upgrade. In this article we discuss a track pattern recognition algorithm based on the Hough Transform, where a parallel approach is expected to reduce dramatically the execution time.Comment: 6 pages, 4 figures, proceedings prepared for GPU-HEP 2014 conference, submitted to DESY-PROC-201

Short communication: Pure-breeding with sexed semen and crossbreeding with semen from double-muscled sires to improve beef production from dairy herds: Weight and value of calves.

The use of sexed semen to produce purebred replacement heifers allows a large proportion of dairy cows to be mated to double-muscled sires and for quantitative and qualitative improvements to be made to beef production from dairy herds. A survey of 1,285 crossbred calves showed that they are destined not only for veal production (like purebred dairy calves) but also for beef production. Crossbred calves obtained from Belgian Blue sires (sold on average at 34 d of age and 64 kg of weight) had a higher market value (€363/calf) than those obtained from double-muscled INRA 95 sires (€297/calf, used for veal production) and from Limousin sires (€216/calf for veal and €271/calf for beef production). As a sire breed, Simmental did not differ significantly from Belgian Blue, but as a dam breed, the crossbred calves fetched a higher price (€5.11/kg) than when Holstein was the dam breed (€4.50/kg). Compared with heifer calves, crossbred bull calves at sale were younger (34.1 vs. 37.2 d) and heavier (64.0 vs. 62.6 kg of live weight), fetched a higher price (€5.13 vs. €4.99/kg), and had a greater value (€328 vs. €312/calf). As the value of purebred dairy calves was about €80 to €100/calf, we are able to confirm that the combined use of sexed semen for pure-breeding and conventional beef semen for terminal crossbreeding can increase the income from dairy farms, especially when the sires are double-muscled beef bulls

High performance computation of landscape genomic models integrating local indices of spatial association

Since its introduction, landscape genomics has developed quickly with the increasing availability of both molecular and topo-climatic data. The current challenges of the field mainly involve processing large numbers of models and disentangling selection from demography. Several methods address the latter, either by estimating a neutral model from population structure or by inferring simultaneously environmental and demographic effects. Here we present Sam$\beta$ada, an integrated approach to study signatures of local adaptation, providing rapid processing of whole genome data and enabling assessment of spatial association using molecular markers. Specifically, candidate loci to adaptation are identified by automatically assessing genome-environment associations. In complement, measuring the Local Indicators of Spatial Association (LISA) for these candidate loci allows to detect whether similar genotypes tend to gather in space, which constitutes a useful indication of the possible kinship relationship between individuals. In this paper, we also analyze SNP data from Ugandan cattle to detect signatures of local adaptation with Sam$\beta$ada, BayEnv, LFMM and an outlier method (FDIST approach in Arlequin) and compare their results. Sam$\beta$ada is an open source software for Windows, Linux and MacOS X available at \url{http://lasig.epfl.ch/sambada}Comment: 1 figure in text, 1 figure in supplementary material The structure of the article was modified and some explanations were updated. The methods and results presented are the same as in the previous versio

Pure-breeding with sexed semen and crossbreeding with semen of double-muscled sires to improve beef production from dairy herds: Factors affecting heifer and cow fertility and the sex ratio

Using sexed semen to produce purebred replacement heifers makes it possible to mate a large proportion of dairy cows to double-muscled sires and to quantitatively and qualitatively improve beef production and increase the income from dairy herds. Net profit first depends on changes in the farm's overall fertility rate. The objective of this study was to analyze the conception rate in herds using a combination of conventional dairy semen (for pure- and crossbreeding), X-sorted dairy semen (to produce purebred replacement heifers), and conventional beef semen (for terminal crossbreeding). Data were obtained from 50,785 inseminations of 15,580 dairy cows (78% Holstein-Friesian, 15% Brown Swiss, 2% Simmental, and 5% crossbreds) from 106 dairy farms (average milk yield 35.1 ± 9.4 kg/d, with 3.76 ± 0.83% fat and 3.32 ± 0.39% protein contents). To account for the main potential confounders, we used separate generalized linear mixed-effects models for cows and virgin heifers. The results showed that the odds ratio of conception improved (1.00 to 1.34) with an increase in the average milk yield of the herd but worsened (1.12 to 0.70) with an increase in the milk yield of individual cows within herd. The summer months showed a strong reduction in the odds ratio of conception in cows (0.56 in July and August) but not in virgin heifers. Multiparous cows had a lower odds ratio of conception (0.85) than primiparous cows (1.00). The order of insemination did not affect the fertility of the cows or heifers, whereas the odds ratio of conception improved with advancing lactation (1.00 to 2.12). The Simmental cows were more fertile than Holstein-Friesians (1.37 vs. 1.00), whereas the fertility of the heifers was not affected by breed. Taking all these possible confounders into account simultaneously, in pure-breeding the odds ratio of conception using sexed semen did not differ from that using conventional dairy semen in cows (0.90 vs. 1.00) or in virgin heifers (0.95 vs. 1.00). However, crossbreeding using conventional beef and dairy semen improved the odds ratio of conception (1.10 and 1.17, respectively) in cows (1.37 using beef semen) and heifers (1.25 using dairy semen). The proportion of newborn heifer calves was ≥90% using sexed dairy semen. The combined use of sexed semen, especially on heifers, to produce purebred replacement females and beef semen to produce terminal crossbred calves was shown to have the potential to increase overall herd fertility, which could be further improved using sexed dairy semen to produce dairy crossbreds instead of purebred replacement heifers

Population Structure and Genetic Diversity of Italian Beef Breeds as a Tool for Planning Conservation and Selection Strategies

The aim was to investigate the population structure of eight beef breeds: three local Tuscan breeds under extinction, Calvana (CAL), Mucca Pisana (MUP), and Pontremolese (PON); three local unselected breeds reared in Sardinia, Sarda (SAR), Sardo Bruna (SAB), and Sardo Modicana (SAM); and two cosmopolitan breeds, Charolais (CHA) and Limousine (LIM), reared in the same regions. An effective population size ranges between 14.62 (PON) to 39.79 (SAM) in local breeds, 90.29 for CHA, and 135.65 for LIM. The average inbreeding coefficients were higher in Tuscan breeds (7.25%, 5.10%, and 3.64% for MUP, CAL, and PON, respectively) compared to the Sardinian breeds (1.23%, 1.66%, and 1.90% in SAB, SAM, and SAR, respectively), while for CHA and LIM they were <1%. The highest rates of mating between half-siblings were observed for CAL and MUP (~9% and 6.5%, respectively), while the highest rate of parent–offspring mating was ~8% for MUP. Our findings describe the urgent situation of the three Tuscan breeds and support the application of conservation measures and/or the development of breeding programs. Development of breeding strategies is suggested for the Sardinian breeds

Genomic diversity and signatures of selection in meat and fancy rabbit breeds based on high-density marker data

open6noThe study was funded by the PSRN (Programma di Sviluppo Rurale Nazionale) Cun-Fu and Cun-Fu 2 projects (co-funded by the European Agricultural Fund for Rural Development of the European Union and by the Italian Ministry of Agriculture, Food and Forestry—MiPAAF) and by the University of Bologna RFO 2019 programme.Background: Domestication of the rabbit (Oryctolagus cuniculus) has led to a multi-purpose species that includes many breeds and lines with a broad phenotypic diversity, mainly for external traits (e.g. coat colours and patterns, fur structure, and morphometric traits) that are valued by fancy rabbit breeders. As a consequence of this human-driven selection, distinct signatures are expected to be present in the rabbit genome, defined as signatures of selection or selective sweeps. Here, we investigated the genome of three Italian commercial meat rabbit breeds (Italian Silver, Italian Spotted and Italian White) and 12 fancy rabbit breeds (Belgian Hare, Burgundy Fawn, Champagne d’Argent, Checkered Giant, Coloured Dwarf, Dwarf Lop, Ermine, Giant Grey, Giant White, Rex, Rhinelander and Thuringian) by using high-density single nucleotide polymorphism data. Signatures of selection were identified based on the fixation index (FST) statistic with different approaches, including single-breed and group-based methods, the latter comparing breeds that are grouped based on external traits (different coat colours and body sizes) and types (i.e. meat vs. fancy breeds). Results: We identified 309 genomic regions that contained signatures of selection and that included genes that are known to affect coat colour (ASIP, MC1R and TYR), coat structure (LIPH), and body size (LCORL/NCAPG, COL11A1 and HOXD) in rabbits and that characterize the investigated breeds. Their identification proves the suitability of the applied methodologies for capturing recent selection events. Other regions included novel candidate genes that might contribute to the phenotypic variation among the analyzed breeds, including genes for pigmentation-related traits (EDNRA, EDNRB, MITF and OCA2) and body size, with a strong candidate for dwarfism in rabbit (COL2A1). Conclusions: We report a genome-wide view of genetic loci that underlie the main phenotypic differences in the analyzed rabbit breeds, which can be useful to understand the shift from the domestication process to the development of breeds in O. cuniculus. These results enhance our knowledge about the major genetic loci involved in rabbit external traits and add novel information to understand the complexity of the genetic architecture underlying body size in mammals.openBallan, Mohamad; Bovo, Samuele; Schiavo, Giuseppina; Schiavitto, Michele; Negrini, Riccardo; Fontanesi, LucaBallan, Mohamad; Bovo, Samuele; Schiavo, Giuseppina; Schiavitto, Michele; Negrini, Riccardo; Fontanesi, Luc

Comparative analysis of genomic inbreeding parameters and runs of homozygosity islands in several fancy and meat rabbit breeds

Runs of homozygosity (ROH) are defined as long stretches of DNA homozygous at each polymorphic position. The proportion of genome covered by ROH and their length are indicators of the level and origin of inbreeding. In this study, we analysed SNP chip datasets (obtained using the Axiom OrcunSNP Array) of a total of 702 rabbits from 12 fancy breeds and four meat breeds to identify ROH with different approaches and calculate several genomic inbreeding parameters. The highest average number of ROH per animal was detected in Belgian Hare (~150) and the lowest in Italian Silver (~106). The average length of ROH ranged from 4.001 ± 0.556 Mb in Italian White to 6.268 ± 1.355 Mb in Ermine. The same two breeds had the lowest (427.9 ± 86.4 Mb, Italian White) and the highest (921.3 ± 179.8 Mb, Ermine) average values of the sum of all ROH segments. More fancy breeds had a higher level of genomic inbreeding (as defined by ROH) than meat breeds. Several ROH islands contain genes involved in body size, body length, pigmentation processes, carcass traits, growth, and reproduction traits (e.g.: AOX1, GPX5, IFRD1, ITGB8, NELL1, NR3C1, OCA2, TRIB1, TRIB2). Genomic inbreeding parameters can be useful to overcome the lack of information in the management of rabbit genetic resources. ROH provided information to understand, to some extent, the genetic history of rabbit breeds and to identify signatures of selection in the rabbit genome

Movement Analysis Could Help in the Assessment of Chronic Low Back Pain Patients: Results from a Preliminary Explorative Study

Introduction: This study aimed to assess the reliability of a qualitative scoring system based on the movement analysis of the spine in different populations and after usual care rehabilitative intervention. If proven true, the results could further future research development in quantitative indexes, leading to a possible subclassification of chronic low back pain (cLBP). Methods: This was a preliminary exploratory observational study. Data of an optoelectronic spine movement analysis from a pathological population (cLBP population, 5 male, 5 female, age 58 ± 16 years) were compared to young healthy participants (5M, 5F, age 22 ± 1) and were analysed via a new qualitative score of the pattern of movement. Internal consistency was calculated. Two independent assessors (experienced and inexperienced) assessed the blinded data, and we calculated inter- and intrarater reliability. We performed an analysis for cLBP pre and post a ten session group rehabilitation program between and within groups. Results: Internal consistency was good for all movements (α = 0.84-0.88). Intra-rater reliability (Intraclass correlation coefficient-ICC) was excellent for overall scores of all movements (ICC(1,k) = 0.95-0.99), while inter-rater reliability was poor to moderate (ICC(1,k) = 0.39-0.78). We found a significant difference in the total movement scores between cLBP and healthy participants (p = 0.001). Within-group comparison (cLBP) showed no significant difference in the total movement score in pre and post-treatment. Conclusion: The perception of differences between normal and pathological movements has been confirmed through the proposed scoring system, which proved to be able to distinguish different populations. This study has many limitations, but these results show that movement analysis could be a useful tool and open the door to quantifying the identified parameters through future studies