MOESM1 of Empirical determination of breed-of-origin of alleles in three-breed cross pigs

Additional file 1. Allele assignment (%) per chromosome (Chr) to synthetic boar (S), Landrace (LR), or Large White (LW) as breed-of-origin when using pedigree information and a relaxation factor of 20 %. The data provided represent the percentage of allele assignment to each purebred line as breed-of-origin per chromosome when using pedigree information and a relaxation factor of 20 %

Additional file 3: Table S4. of Accuracy of imputation using the most common sires as reference population in layer chickens

Animal-specific imputation accuracy (rcorrected) on GGA8 for different MAF classes and different reference sizes in G0, G1 and G2

MOESM1 of Assigning breed origin to alleles in crossbred animals

Additional file 1. Table S1: Percentages of alleles correctly assigned a breed origin (%correct), incorrectly assigned (%incorrect), or unassigned (%unknown) for a BC crossbred animal for the chromosome 1. Results are averages (SD) across the 10 replicates. Table S2: Percentages of alleles correctly assigned a breed origin (%correct), incorrectly assigned (%incorrect), or unassigned (%unknown) for a BC crossbred animal for the chromosome 2. Results are averages (SD) across the 10 replicates. Table S3: Percentages of alleles correctly assigned a breed origin (%correct), incorrectly assigned (%incorrect), or unassigned (%unknown) for a A(BC) crossbred animal for chromosome 1. Results are averages (SD) across the 10 replicates. Table S4: Percentages of alleles correctly assigned a breed origin (%correct), incorrectly assigned (%incorrect), or unassigned (%unknown) for a A(BC) crossbred animal for chromosome 2. Results are averages (SD) across the 10 replicates. Table S5: Percentages of BC and A(BC) animals having at least 80 % of assigned alleles, and Spearman rank correlations between the order of the phasing analyses obtained from the forward selection and a predefined order of the same phasing analyses for the A(BC) animals, with a relaxation factor equal to 10 %. Results are averages (SD) across the 10 replicates. Table S6: Percentages of assigned alleles of the chromosomes SSC2 and SSC18 for an EF or a D(EF) animal, and percentages of EF and D(EF) animals having at least 80 % of assigned alleles, with a relaxation factor equal to 10 %. Table S7: Average (SD) percentages of assigned alleles of the chromosomes SSC2 and SSC18 for an EF or a D(EF) animal. Table S8: Percentages of alleles correctly assigned a breed origin (%correct) and incorrectly assigned (%incorrect), for the chromosome 2 with 9 phasing analyses with, or without, the additional rules. Results are averages (SD) across the 10 replicates

Additional file 4: Table S1. of Accuracy of imputation using the most common sires as reference population in layer chickens

Total number of SNPs masked for different MAF classes in 48K to 60K scenario

MOESM1 of The impact of genome editing on the introduction of monogenic traits in livestock

Additional file 1. Simulation_genome_editing.R. This file presents the simulation program in R to create the simulation scenarios presented

MOESM1 of The impact of genome editing on the introduction of monogenic traits in livestock

Additional file 1. Simulation_genome_editing.R. This file presents the simulation program in R to create the simulation scenarios presented

MOESM1 of Weighted single-step GWAS and gene network analysis reveal new candidate genes for semen traits in pigs

Additional file 1: Table S1. Variance components and standard errors (in parenthesis) for semen traits. The data provided represent the values of variance components (additive genetic, environmental and residual) and the respective standard errors for each semen trait and pig line

MOESM2 of Weighted single-step GWAS and gene network analysis reveal new candidate genes for semen traits in pigs

Additional file 2: Table S2. The three SNP windows that explained the highest proportion of genetic variance of each semen trait in L1. The data provided represent the chromosome, average window position (in basepairs) and the percentage of variance explained by the three SNP windows that explained the highest proportion of genetic variance for each semen trait in L1

Parque Eólico Offshore: Rota

El presente proyecto tiene como objeto la descripción de las obras e instalaciones necesarias para llevar a cabo la construcción del Parque Eólico offshore “Rota” (Cádiz). España se encuentra, dentro del ámbito internacional, entre los primeros países en el desarrollo e instalaciones de parques eólicos terrestres, siendo en Europa sólo superada por Alemania. Sin embargo, no contamos con instalaciones de parques eólicos marinos como tales en nuestro país, debido a la importante inversión que supone la construcción de las cimentaciones y a que se necesitan unas determinadas batimetrías con una separación de la costa establecida por ley, que limita la posibilidad real de construir parques eólicos offshore, con las técnicas actuales, en las costas gallegas y la costa del golfo de Cádiz, donde la plataforma continental atlántica no es tan abrupta

Additional file 1: of A nonsense mutation in B3GALNT2 is concordant with hydrocephalus in Friesian horses

Sanger DNA sequencing results for the nonsense mutation. A table with information on all horses that have been sequenced for the nonsense mutation. (DOCX 20 kb