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Additional file 1: Figure S1. Average correlations between $${\widehat{\mathbf{m}}}_{\mathbf{p}}$$ m ^ p ( $$\widehat{\mathbf{m}}$$ m ^ using a partial dataset) and $${\widehat{\mathbf{m}}}_{\mathbf{w}}$$ m ^ w ( $$\widehat{\mathbf{m}}$$ m ^ using the whole dataset) for the CG design, and their SD as error bars. Figure S2. Average correlations between $${(\widehat{\mathbf{a}+\mathbf{m}})}_{\mathbf{p}}$$ ( a + m ^ ) p and $${(\widehat{\mathbf{a}+\mathbf{m}})}_{\mathbf{w}}$$ ( a + m ^ ) w for CG designs, and their SD as error bars. Figure S3. Results of microbiome wide association analyses using back solving of BLUP solutions between operational taxonomic units and residual feed intake (RFI), feed conversion ratio (FCR), daily feed intake (DFI), average daily gain (ADG) and back fat thickness (BFT).

Additional file 6: Figure S3. Manhattan plots for GWAS of RFI trait in global, HRFI line or LRFI line populations. The plot shows the − log10(p-values) for all SNPs in the analysis against their genomic position. Changes in color represent different chromosomes. The dashed line represents the threshold for genome wide significance (threshold of -log10(p-value) = 4.5).

Additional file 6: Figure S3. Manhattan plots for GWAS of RFI trait in global, HRFI line or LRFI line populations. The plot shows the − log10(p-values) for all SNPs in the analysis against their genomic position. Changes in color represent different chromosomes. The dashed line represents the threshold for genome wide significance (threshold of -log10(p-value) = 4.5).

Table S1. Variableâ s contributions to the first two dimensions of the PCA. Variables that contributed to more than 10% to one axis are underlined. (PDF 35 kb)

Figure S1. PCA variables’ correlogram. Correlations of each variable to the first two dimensions of the PCA are shown. CTL, CD8αhi cytotoxic T lymphocytes. (PDF 129 kb)

Box-plot representation of NR3C1 and TGFB2 expression in fetuses with different genotypes at 90 (d90) and 110 day (d110) of gestation. (PDF 120 kb)

Concentration of blood parameters from umbilical cord of purebred fetuses (LW or MS) and crossbred fetuses (LWMS and MSLW) at 90 and 110 days of gestation [68–71]. (PDF 351 kb)

Primer sequences used for qRT-PCR. PPIA, peptidylprolyl isomerase A; TBP, TATA box binding protein; CCL2, C-C motif chemokine ligand 2; CIRBP, cold inducible RNA binding protein; FABP1, fatty acid binding protein 1; GBP1, guanylate binding protein 1; G6PC, Glucose 6 phosphatase; PPARGC1A, peroxisome proliferator-activated receptor gamma coactivator 1-alpha. (PDF 160 kb)

PCA analysis of the additive model, the gestational age model and the fetal genotype model. (a) For the gestational age model, the PC1 explained 30.0% of the total variance and segregated data from fetuses according to their age. (b) For the genotype model, the data from purebred LW and MS fetuses were clearly separated along the PC1 (24.3%) while the data from crossbred fetuses segregated on the PC3 (10.5%). (c) The gestational age segregation was also clear cut in PC1 (24.4%) of the additive model, while the purebred fetuses segregated on PC2 (16.2%). (PDF 153 kb)

Box-plot representation of the seven tested genes in qPCR compared to their microarray expression. (PDF 359 kb)

Distribution of the rank of the significant adjusted P -values in the tests for DE transcripts between t = 0 and t = + 1, t = 0 and t = + 4 and t = 0 and t = + 24 ‘.pdf’ file. P-values are smaller at t=+1 and t=+4 than at t=+24 implying that the transcripts were overall more differentially expressed between t=0 and t=+1 and between t=0 and t=+4 than between t=0 and t=+24. (PDF 4 kb)

Figure S2. Gating strategy for non B-lymphocyte subsets analysis. Representative flow cytometry profile is shown. Nucleated single cells were identified as DRAQ5-positive cells. Among SSC-Alo cells, CD4/CD8α/CD3 co-staining allowed the determination of 6 lymphocyte subsets as mentioned on the plots. (PDF 935 kb)

Additional file 3: Figure S1. Correlations between true and imputed genotypes for animals genotyped on 60K, 70K or 650K SNPs chip. For each analysis, correlations were estimated setting 5000 SNPs as missing (5 batches of 1000 SNPs) on one chip among SNPs in common between the two arrays used. Animals are sorted and colored by generation. Correlations between true and imputed genotypes (a) for the 286 animals genotyped with the 60K SNPs chip using animals with 70K genotypes as reference population, and (b) for the 1346 animals genotyped with the 70K SNPs chip using animals with 60K genotypes as reference. (c) Correlations between true and imputed genotypes after imputation to 650K SNPs from the imputed medium density genotypes. (d) Correlations between true and imputed genotypes based on the leave-one-out cross-validation.

Additional file 4: Figure S2. Proportion of certain expected genotypes per animal, per SNP and in relation to the MAF of the SNPs. The proportion of certain genotypes corresponds to expected genotypes from parents which are homozygous for the same allele or homozygous for opposite alleles, and half of the genotypes from matings of two heterozygous parents were also taken into account. This proportion was studied per individual for the 66,988 SNPs of the 60K SNPs chip (a), per SNP for the 2426 pigs (b) and finally per SNP while taking into account the MAF of each SNP (c).

Figure S2. Gating strategy for non B-lymphocyte subsets analysis. Representative flow cytometry profile is shown. Nucleated single cells were identified as DRAQ5-positive cells. Among SSC-Alo cells, CD4/CD8α/CD3 co-staining allowed the determination of 6 lymphocyte subsets as mentioned on the plots. (PDF 935 kb)

Additional file 4: Figure S2. Proportion of certain expected genotypes per animal, per SNP and in relation to the MAF of the SNPs. The proportion of certain genotypes corresponds to expected genotypes from parents which are homozygous for the same allele or homozygous for opposite alleles, and half of the genotypes from matings of two heterozygous parents were also taken into account. This proportion was studied per individual for the 66,988 SNPs of the 60K SNPs chip (a), per SNP for the 2426 pigs (b) and finally per SNP while taking into account the MAF of each SNP (c).

Additional file 3: Figure S1. Correlations between true and imputed genotypes for animals genotyped on 60K, 70K or 650K SNPs chip. For each analysis, correlations were estimated setting 5000 SNPs as missing (5 batches of 1000 SNPs) on one chip among SNPs in common between the two arrays used. Animals are sorted and colored by generation. Correlations between true and imputed genotypes (a) for the 286 animals genotyped with the 60K SNPs chip using animals with 70K genotypes as reference population, and (b) for the 1346 animals genotyped with the 70K SNPs chip using animals with 60K genotypes as reference. (c) Correlations between true and imputed genotypes after imputation to 650K SNPs from the imputed medium density genotypes. (d) Correlations between true and imputed genotypes based on the leave-one-out cross-validation.