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The objective of the present study was to discover the genetic variants, functional candidate genes, biological processes and molecular functions underlying the negative genetic correlation observed between body weight (BW) and egg number (EN) traits in female broilers. To this end, first a bivariate genome-wide association and second stepwise conditional-joint analyses were performed using 2586 female broilers and 240 k autosomal SNPs. The aforementioned analyses resulted in a total number of 49 independent cross-phenotype (CP) significant SNPs with 35 independent markers showing antagonistic action i.e., positive effects on one trait and negative effects on the other trait. A number of 33 independent CP SNPs were located within 26 and 14 protein coding and long non-coding RNA genes, respectively. Furthermore, 26 independent markers were situated within 44 reported QTLs, most of them related to growth traits. Investigation of the functional role of protein coding genes via pathway and gene ontology analyses highlighted four candidates ( CPEB3, ACVR1, MAST2 and CACNA1H ) as most plausible pleiotropic genes for the traits under study. Three candidates ( CPEB3, MAST2 and CACNA1H ) were associated with antagonistic pleiotropy, while ACVR1 with synergistic pleiotropic action. Current results provide a novel insight into the biological mechanism of the genetic trade-off between growth and reproduction, in broilers.

Elucidating the genetic variation and structure of Lemnos and Lesvos sheep is critical for maintaining local genetic diversity, ecosystem integrity and resilience of local food production of the two North Aegean islands. In the present study, we explored genetic diversity and differentiation as well as population structure of the Lemnos and Lesvos sheep. Furthermore, we sought to identify a small panel of markers with the highest discriminatory power to assign animals across islands. A total number of n = 424 (n = 307, Lemnos and n = 117, Lesvos) ewes, sampled from n = 24 herds dispersed at different geographic regions on the two islands, were genotyped with the 50K SNP array. Mean observed heterozygosity was higher (but not statistically significantly different) in Lesvos than in Lemnos population (0.384 vs. 0.377) while inbreeding levels were higher in Lemnos than Lesvos herds (0.065 vs. 0.031). Results of principal components along with that of admixture analysis and estimated genetic distances revealed genetic clusters corresponding to Lesvos and Lemnos origin and the existence of infrastructure within islands that were associated with geographical isolation and genetic history of the studied populations. In particular, genetic analyses highlighted three geographically isolated herds in Lemnos that are located at mountainous areas of the island and are characterized as representatives of the local sheep by historic data and reports. Admixture analysis also showed a shared genetic background between Lemnos and Lesvos sheep attributable to past gene flow. Little overall genetic differentiation was detected between the two island sheep populations, while 150 discriminatory SNPs could accurately assign animals to their origin. Present results are comparable with those reported in the worldwide sheep breeds, suggesting geography related genetic patterns across and within islands and the existence of the local Lemnos sheep.

In Greece, a number of local sheep breeds are raised in a wide range of ecological niches across the country. These breeds can be used for the identification of genetic variants that contribute to local adaptation. To this end, 50k genotypes of 90 local sheep from mainland Greece (Epirus, n = 35 and Peloponnesus, n = 55) were used, as well as 147 genotypes of sheep from insular Greece (Skyros, n = 21), Lemnos, n = 36 and Lesvos, n = 90). Principal components and phylogenetic analysis along with admixture and spatial point patterns analyses suggested genetic differentiation of ‘mainland-island’ populations. Genome scans for signatures of selection and genome-wide association analysis (GWAS) pointed to one highly differentiating marker on OAR4 (F ST = 0.39, FLK = 21.93, FDR p-value = 0.10) that also displayed genome wide significance (FDR p-value = 0.002) during GWAS. A total number of 6 positional candidate genes ( LOC106990429 , ZNF804B , TEX47 , STEAP4 , SRI and ADAM22 ) were identified within 500 kb flanking regions around the significant marker. In addition, two QTLs related to fat tail deposition are reported in genomic regions 800 kb downstream the significant marker. Based on gene ontology analysis and literature evidence, the identified candidate genes possess biological functions relevant to local adaptation that worth further investigation.

Background The study explored the accuracy and biases of genomic selection in two commercial Pekin duck lines, focusing on their performance under real-world breeding practices. A dataset of 26 K duck records with phenotype and imputed genotype information (60 K chip) was analysed for growth, welfare, and primary feather length traits. Mixed linear models with relationship matrices from pedigree (BLUP) or markers (GBLUP) were used to estimate variance components and breeding values. We then assessed selection accuracies and biases to determine the most appropriate models. Results Results showed high imputation accuracies of 0.93 for line A and 0.92 for line D. Heritability estimates from pedigree were generally higher than those from genomic markers. For example, juvenile weight (JW) heritability ranged from 0.22 in line A and 0.25 in line D using markers, to 0.39 and 0.50, respectively, using the pedigree. Slaughter body weight (BW) had similar trends. Gait heritability was low (0.07) using markers in both lines, while breast muscle depth (BD) also had lower estimates (0.15–0.16). For line A, genomic prediction accuracies were higher with the G-matrix, especially for BW (r 2 =0.68-0.70) and JW with r 2 of 0.49. Estimates for gait and foot pad dermatitis (FPD) improved using the G-matrix at 0.58 vs. 0.24 and 0.68 vs. 0.44, respectively, compared to pedigree information. Similar improvements were found for line D, with BD estimates improving from 0.50 to 0.71 using the G-matrix. Line A showed minimal bias (0.01-0.19) with the G-matrix compared to 0.02-0.41 with the A-matrix; the highest bias was for JW. Line D had lower biases with the G-matrix (0.02-0.17) than in line A with markers, while higher biases were observed using pedigree (0.01-0.37). Conclusions These findings indicate that all traits were heritable with higher prediction accuracies and lower biases using GBLUP compared to BLUP. This study demonstrates the effectiveness of GBLUP in improving prediction accuracy and reducing bias in selection traits of Pekin ducks, particularly for traits with low heritability.

Average daily gain (ADG), body weight (BW), primary feather length (PRF) and breast depth (BD) are economically important traits in duck production, and understanding the genetic architecture of these traits remains limited. Genome-wide association studies (GWAS) can provide insight into the genetic mechanism underlying these traits. Increasing the power of GWAS by applying approaches such as genotype imputation can improve the ability to detect quantitative trait loci associations with polygenic traits. To increase the power of detecting marker-trait associations in this study, we also exploited imputed data and on a larger sample size. The objective of this study was to investigate marker-trait associations for ADG, BW, PRF and BD in ducks. First, we conducted univariate GWA analyses using chip data (hence medium density data) using 45 K autosomal SNPs and 1445 ducks from single breeding line. Second, we exploited imputed data with a larger sample size (13020) from the same line and performed univariate analyses. Comparison of SNP signals between the medium density and imputed data identified 63 common SNPs that were co-localized on chromosome 4. Several functional candidate genes such as PPARGC1A , LDB2 and LCORL were found within or close to the identified region. Indeed, the LCORL-NCAPG region has been reported in many mammalian species to be related to growth. Considering results from both analyses, current findings propose novel putative pleiotropic candidate quantitative trait loci (QTL) with the associated genes for the traits we analysed while identifying the most promising QTL region on chromosome 4.

Aim of the present study was to investigate whether body weight (BW) in broilers is associated with functional modular genes. To this end, first a GWAS for BW was conducted using 6,598 broilers and the high density SNP array. The next step was to search for positional candidate genes and QTLs within strong LD genomic regions around the significant SNPs. Using all positional candidate genes, a network was then constructed and community structure analysis was performed. Finally, functional enrichment analysis was applied to infer the functional relevance of modular genes. A total number of 645 positional candidate genes were identified in strong LD genomic regions around 11 genome-wide significant markers. 428 of the positional candidate genes were located within growth related QTLs. Community structure analysis detected 5 modules while functional enrichment analysis showed that 52 modular genes participated in developmental processes such as skeletal system development. An additional number of 14 modular genes ( GABRG1, NGF, APOBEC2, STAT5B, STAT3, SMAD4, MED1, CACNB1, SLAIN2, LEMD2, ZC3H18, TMEM132D, FRYL and SGCB ) were also identified as related to body weight. Taken together, current results suggested a total number of 66 genes as most plausible functional candidates for the trait examined.

Digital dermatitis (DD) is an endemic infectious hoof disease causing lameness in dairy cattle. The aim of the present study was to investigate the genetic profile of DD development using phenotypic and genotypic data on 2192 Holstein cows. The feet of each cow were clinically examined four times: pre-calving, shortly after calving, near peak of milk production, and in late lactation. Presence or absence of disease and proportion of healthy feet per cow constituted two DD phenotypes of study. For each phenotype and timepoint of clinical examination, we conducted single-step genome-wide association analyses to identify individual markers and genomic regions linked to DD. We focused on the ten 1-Mb windows that explained the largest proportion of the total genetic variance as well as windows that enclosed significant markers. Functional enrichment analysis was also applied to determine functional candidate genes for DD. Significant ( P  < 0.05) genomic heritability estimates were derived ranging from 0.21 to 0.25. Results revealed two markers on chromosomes 7 and 15 that were related to both disease phenotypes. Furthermore, we identified three genomic windows on chromosome 14 and one window on chromosome 7 each explaining more than 1% of the trait additive genetic variance. Functional enrichment analysis revealed multiple promising candidate genes implicated in hoof health, wound healing, and inflammatory skin diseases. Collectively, our results provide novel insights into the biological mechanism of host resistance to DD development in dairy cattle and support genomic selection towards improving foot health.

Background Aim of the present study was first to identify genetic variants associated with egg number (EN) in female broilers, second to describe the mode of their gene action (additive and/or dominant) and third to provide a list with implicated candidate genes for the trait. A number of 2586 female broilers genotyped with the high density (~ 600 k) SNP array and with records on EN (mean = 132.4 eggs, SD = 29.8 eggs) were used. Data were analyzed with application of additive and dominant multi-locus mixed models. Results A number of 7 additive, 4 dominant and 6 additive plus dominant marker-trait significant associations were detected. A total number of 57 positional candidate genes were detected within 50 kb downstream and upstream flanking regions of the 17 significant markers. Functional enrichment analysis pinpointed two genes ( BHLHE40 and CRTC1 ) to be involved in the ‘entrainment of circadian clock by photoperiod’ biological process. Gene prioritization analysis of the positional candidate genes identified 10 top ranked genes ( GDF15, BHLHE40, JUND, GDF3, COMP, ITPR1, ELF3, ELL, CRLF1 and IFI30). Seven prioritized genes ( GDF15, BHLHE40, JUND, GDF3, COMP, ELF3, CRTC1) have documented functional relevance to reproduction, while two more prioritized genes ( ITPR1 and ELL ) are reported to be related to egg quality in chickens. Conclusions Present results have shown that detailed exploration of phenotype-marker associations can disclose the mode of action of genetic variants and help in identifying causative genes associated with reproductive traits in the species.

Digital dermatitis (DD) is a global infectious hoof disease causing lameness in cattle. The condition has been studied extensively in milking cows. The present study deployed data from repeated clinical examinations of young heifers to develop DD phenotypes reflecting the disease prevalence and progression. The newly defined traits were then subjected to single-step genome-wide association analyses to assess their genetic profile. Data were collected during four monthly clinical examinations of 921 Holstein heifers aged less than 15 months. The M-score system was used to assess hoof health, and four phenotypes were developed on each animal: two binary traits considering the presence or absence of DD within each examination (BINR) and across all examinations (BINA) and two disease progression traits (TP1 and TP2) throughout the examination period. The latter two phenotypes were derived on heifers that were healthy at first examination (n = 625). Pedigree and genome-wide genotypes were available on these animals. For each trait, the ten 1-Mb windows that explained the largest proportion of the total genetic variance were used to search for positional candidate genes. Functional enrichment analysis was carried out to determine the functional candidates. All traits were significantly (P < 0.05) heritable with heritability estimates ranging from 0.22 for TP2 to 0.32 for BINA. Our findings revealed common genomic regions between traits distributed across eight chromosomes (7, 8, 11, 12, 13, 20, 23 and 24). Functional enrichment analysis revealed multiple candidate genes including DOCK2 and SRF that are known for involvement in immune response. Results provide novel insights into the genetic mechanism for DD development and progression in young dairy heifers.