Additional file 2 of Genetic diversity and signatures of selection for heat tolerance and immune response in Iranian native chickens

Additional file 2: Figure S1.Venndiagrams summarize unique and common variants among groups. Fig. S2. Theheat map of ChromoPainter’s coancestry matrix. Each row corresponds to therecipient genomes and columns represent the donor individuals. Fig. S3. Cross validationerror (CV) plot from ADMIXTURE. Fig. S4. Box plots of nucleotide diversity, calculated in 50kb sliding window with 20 kb increments across the genome. Fig. S5. Genomic regions with selection signals in nativechickens by π method. (A) Indigenousgroup versus Arian chickens. (B) Indigenous group versus White Leghornchickens. Fig. S6. Haplotype network based on pairwise differenceswithin the selective sweep region (Chr1: 176.34-176.36) inHSPH1

Additional file 1 of Genetic diversity and signatures of selection for heat tolerance and immune response in Iranian native chickens

Additional file 1: Table S1: Sample information for each chicken (72 individuals) used in this study. Table S2. Chromosome-length and number of detected variants before and after filtering. Table S3. Mean number of ROHs longer than different classes (Kb).Table S4. Summary  diversity results. Proportion of polymorphic SNPs (PN ), Observed heterozygosity (Ho), Expected heterozygosity (He), and average inbreeding coefficient (F) for each studied group. Table S5: Positively selected genes (top %5) identified between indigenous group and White-Leghorn identified by FST method. Table S6. Positively selected genes identified by top 1% highest log2 (θπ·Native-ecotypes/θπ·White-Leghorn). Table S7. Positively selected genes (top %5) identified by FST method between indigenous group and Arian. Table S8: Positively selected genes identified by top 1% highest log2 (θπ·Native-ecotypes/θπ·Arian). Table S9. Overrepresented GO categories among genes showing high Fst values between indigenous group and  White-Leghorn. Table S10. Overrepresented GO categories among genes showing high log2 (θπ·Native-ecotypes/θπ·White-Leghorn). Table S11. Overrepresented GO categories among genes showing high Fst values (indigenous group versus Arian). Table S12. Overrepresented GO categories among genes showing high log2 (θπ·Native-ecotypes/θπ·Arian)

Impact of inclusion non-additive effects on genome-wide association and variance’s components in Scottish black sheep

It’s well-documented that most economic traits have a complex genetic structure that is controlled by additive and non-additive gene actions. Hence, knowledge of the underlying genetic architecture of such complex traits could aid in understanding how these traits respond to the selection in breeding and mating programs. Computing and having estimates of the non-additive effect for economic traits in sheep using genome-wide information can be important because; non-additive genes play an important role in the prediction accuracy of genomic breeding values and the genetic response to the selection. This study aimed to assess the impact of non-additive effects (dominance and epistasis) on the estimation of genetic parameters for body weight traits in sheep. This study used phenotypic and genotypic belonging to 752 Scottish Blackface lambs. Three live weight traits considered in this study were included in body weight at 16, 20, and 24 weeks). Three genetic models including additive (AM), additive + dominance (ADM), and additive + dominance + epistasis (ADEM), were used. The narrow sense heritability for weight at 16 weeks of age (BW16) were 0.39, 0.35, and 0.23, for 20 weeks of age (BW20) were 0.55, 0.54, and 0.42, and finally for 24 weeks of age (BW24) were 0.16, 0.12, and 0.02, using the AM, ADM, and ADEM models, respectively. The additive genetic model significantly outperformed the non-additive genetic model (p  The results emphasized that the non-additive genetic effects play an important role in controlling body weight variation at the age of 16–24 weeks in Scottish Blackface lambs. It is expected that using a high-density SNP panel and the joint modeling of both additive and non-additive effects can lead to better estimation and prediction of genetic parameters.</p

Additional file 4 of A genome-wide scan to identify signatures of selection in two Iranian indigenous chicken ecotypes

Additional file 4: Table S4. Summary of GO terms related to biological processes resulting from the analyses of cROH regions, CLR, FST and hapFLK in the Lari and Khazak ecotypes. This table represents gene ontology (GO) terms that are significant (P-value > 0.05), (L: Lari ecotype and K: Khazak ecotype)

Additional file 2 of A genome-wide scan to identify signatures of selection in two Iranian indigenous chicken ecotypes

Additional file 2: Table S2. List of candidate genes that overlap with regions identified by the CLR method in the Lari and Khazak ecotypes

Additional file 6 of A genome-wide scan to identify signatures of selection in two Iranian indigenous chicken ecotypes

Additional file 6: Table S6. List of candidate genes that overlap with regions identified by the ROH method in the Lari and Khazak ecotypes

Additional file 1 of A genome-wide scan to identify signatures of selection in two Iranian indigenous chicken ecotypes

Additional file 1: Table S1. Summary of the distribution of ROH lengths along the genome per animal. An excel file containing the number of ROH, total size of genome covered by ROH (kb) and average of ROH length (kb) per animal

Additional file 8 of A genome-wide scan to identify signatures of selection in two Iranian indigenous chicken ecotypes

Additional file 8: Table S8. List of candidate genes that overlap with regions identified by the hapFLK method

Additional file 3 of A genome-wide scan to identify signatures of selection in two Iranian indigenous chicken ecotypes

Additional file 3: Table S3. List of the genes that were identified simultaneously by at least two of the four applied methods. This table represents the identified common genes shared by at least two of the four methods used, FST, hapFLK, CLR and ROH, (L: Lari ecotype and K: Khazak ecotype)

Additional file 9 of A genome-wide scan to identify signatures of selection in two Iranian indigenous chicken ecotypes

Additional file 9: Table S9. Overlaps between the reported QTL in the QTL database and the detected candidate regions by FST, hapFLK, CLR and ROH analysis. This file presents the overlaps between the traits and the position of the known QTL regions in chicken with the position of the identified putative signatures of selection by the four methods