Genome-wide detection of CNVs associated with beak deformity in chickens using high-density 600K SNP arrays

Genome-wide association study of copy number variations with shank traits in a F2 crossbred chicken population

Copy number variations (CNVs) are large-scale changes in the DNA sequence that can affect the genetic structure and phenotype of an organism. The purpose of this study was to investigate the existing CNVs and their associations with the shank diameter (ShD) and shank length (ShL) traits using data from an F2 crossbred chicken population. To carry out the study, 312 chickens were genotyped using the Illumina 60k SNP Beadchip. The shank traits of the birds were measured from day 1 to 12 weeks of age. penncnv and cnvruler tools were used to find copy numbers and regions with copy number changes (CNVR), respectively. The CNVRanger package was used to perform a genome-wide association study between shank traits and CNVs. Gene ontology research in CNVRs was carried out using the david database. In this investigation, 966 CNVs and 606 regions with copy number changes were discovered. The copy number states and variations were randomly distributed along the length of the autosomal chromosomes. Weeks 1-4, 9 and 12 of growth revealed a significant association of copy number variations with shank traits, false discovery rate (FDR-corrected p-value < 0.01), and the majority of CNVs that were statistically significant were found on chromosomes 1-3. These CNV segments are nearby genes such as KCNJ12, FGF6 and MYF5, which are fundamental to growth and development. In addition, gene set analyses revealed terms related to muscle physiology, regulation of cellular processes and potassium channels.

Copy number variations affecting growth curve parameters in a crossbred chicken population

Copy number variations (CNVs) are key structural variations in the genome and may contribute to phenotypic differences. In this study, we used a F2 chicken population created from reciprocal crossing between fast-growing Arian broiler line and Urmia native chickens. The chickens were genotyped by 60 K SNP BeadChip, and PennCNV algorithm was used to detect genome-wide CNVs. The growth curve parameters of W0, k, L, Wf, Wi, ti and average GR were used as phenotypic data. The association between CNV and growth curve parameters was carried out using the CNVRanger R/Bioconductor package. Five CNV regions (CNVRs) were chosen for the validation experiment using qPCR. Gene enrichment analysis was done using WebGestalt. The STRING database was used to search for significant pathways. The results identified 966 CNVs and 600 CNVRs including 468 gains, 67 losses, and 65 both events on autosomal chromosomes. Validation of the CNVRs obtained from the qPCR assay were 79 % consistent with the prediction by PennCNV. A total of 43 significant CNVs were obtained for the seven growth curve parameters. The 416 genes annotated for significant CNVs. Six genes out of 416 genes were most related to growth curve parameters. These genes were LCP2, Dock2, CD80, CYFIP1, NIPA1 and NIPA2. Some of these genes in their biological process were associated with the growth, reproduction and development of cells or organs that ultimately lead to the growth of the body. The results of the study could pave the way for better understanding the molecular process of CNVs and growth curve parameters in birds.

How structural variants shape avian phenotypes: Lessons from model systems

Despite receiving significant recent attention, the relevance of structural variation (SV) in driving phenotypic diversity remains understudied, although recent advances in long-read sequencing, bioinformatics and pangenomic approaches have enhanced SV detection. We review the role of SVs in shaping phenotypes in avian model systems, and identify some general patterns in SV type, length and their associated traits. We found that most of the avian SVs so far identified are short indels in chickens, which are frequently associated with changes in body weight and plumage colouration. Overall, we found that relatively short SVs are more frequently detected, likely due to a combination of their prevalence compared to large SVs, and a detection bias, stemming primarily from the widespread use of short-read sequencing and associated analytical methods. SVs most commonly involve non-coding regions, especially introns, and when patterns of inheritance were reported, SVs associated primarily with dominant discrete traits. We summarise several examples of phenotypic convergence across different species, mediated by different SVs in the same or different genes and different types of changes in the same gene that can lead to various phenotypes. Complex rearrangements and supergenes, which can simultaneously affect and link several genes, tend to have pleiotropic phenotypic effects. Additionally, SVs commonly co-occur with single-nucleotide polymorphisms, highlighting the need to consider all types of genetic changes to understand the basis of phenotypic traits. We end by summarising expectations for when long-read technologies become commonly implemented in non-model birds, likely leading to an increase in SV discovery and characterisation. The growing interest in this subject suggests an increase in our understanding of the phenotypic effects of SVs in upcoming years.

Analysis of DNA Methylation Profiles in Mandibular Condyle of Chicks With Crossed Beaks Using Whole-Genome Bisulfite Sequencing

Crossed beaks have been observed in at least 12 chicken strains around the world, which severely impairs their growth and welfare. To explore the intrinsic factor causing crossed beaks, this study measured the length of bilateral mandibular ramus of affected birds, and investigated the genome-wide DNA methylation profiles of normal and affected sides of mandibular condyle. Results showed that the trait was caused by impaired development of unilateral mandibular ramus, which is extended through calcification of mandibular condyle. The methylation levels in the CG contexts were higher than that of CHG and CHH, with the highest methylation level of gene body region, followed by transcription termination sites and downstream. Subsequently, we identified 1,568 differentially methylated regions and 1,317 differentially methylated genes in CG contexts. Functional annotation analysis of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes showed that these genes were involved in bone mineralization and bone morphogenesis. Furthermore, by combining the WGBS and previous RNA-Seq data, 11 overlapped genes were regulated by both long non-coding RNA and DNA methylation. Among them, FIGNL1 is an important gene in calcification of mandibular condyle. Generally, because the affected genes play key roles in maintaining mandibular calcification, these changes may be pivotal factors of crossed beaks.

Genome-wide detection of CNVs and their association with performance traits in broilers

Background

Copy number variations (CNVs) are a major type of structural genomic variants that underlie genetic architecture and phenotypic variation of complex traits, not only in humans, but also in livestock animals. We identified CNVs along the chicken genome and analyzed their association with performance traits. Genome-wide CNVs were inferred from Affymetrix® high density SNP-chip data for a broiler population. CNVs were concatenated into segments and association analyses were performed with linear mixed models considering a genomic relationship matrix, for birth weight, body weight at 21, 35, 41 and 42 days, feed intake from 35 to 41 days, feed conversion ratio from 35 to 41 days and, body weight gain from 35 to 41 days of age.

Results

We identified 23,214 autosomal CNVs, merged into 5042 distinct CNV regions (CNVRs), covering 12.84% of the chicken autosomal genome. One significant CNV segment was associated with BWG on GGA3 (q-value = 0.00443); one significant CNV segment was associated with BW35 (q-value = 0.00571), BW41 (q-value = 0.00180) and BW42 (q-value = 0.00130) on GGA3, and one significant CNV segment was associated with BW on GGA5 (q-value = 0.00432). All significant CNV segments were verified by qPCR, and a validation rate of 92.59% was observed. These CNV segments are located nearby genes, such as KCNJ11, MyoD1 and SOX6, known to underlie growth and development. Moreover, gene-set analyses revealed terms linked with muscle physiology, cellular processes regulation and potassium channels.

Conclusions

Overall, this CNV-based GWAS study unravels potential candidate genes that may regulate performance traits in chickens. Our findings provide a foundation for future functional studies on the role of specific genes in regulating performance in chickens.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07676-1.

Phenotype characterization of crossed beaks in Beijing-You chickens based on morphological observation

The prevalence of crossed beaks ranging from 0.2 to 7.4% was documented in at least 12 chicken strains. Previous studies focused largely on candidate molecules, whereas the morphological observation was missing. This study reported a detailed phenotype and prevalence of crossed beaks based on morphological observation in nine thousand nine hundred 1-day-old female Beijing-You chicks. Affected chicks were classified into 2 categories based on the direction of the mandibular deformation: left and right. Each category was selected to sacrifice for the measurement of length, width, and thickness of the bilateral mandibular ramus (MR). The normal chicks were used as controls. Paraffin section was made for the bilateral MR of a crossed beak and a normal control for histology analysis. A total of 97 out of 9,900 chickens showed beak deformity including 71 crossed beaks (0.72%) and 26 side beaks (0.26%) for which the upper and lower beak were both bent in the same direction. There was no difference in the direction of the bend of the lower beak in crossed beaks (P > 0.05). The incidence of crossed beaks increased quickly from 0 to 56 d and no new incidence after 56 d. The angle of the crossed beaks was below 5° in the first week and had grown more severe with age until 56 d. The mandible structure showed that condyle served as a growth center for the MR extension. The short-side MR of crossed beaks was thicker than normal ones (P < 0.05) and caused the mandible deviated to the same direction. Meanwhile, the short-side MR prevented the occlusion, leading the jugal arch deformity, which in turn resulted in a bent maxillary horizontally. Similarly, chicks with side beaks also had asymmetry in MR length and the deformities of the jugal arch after dissection. In summary, asymmetric growth of bilateral MR induced crossed beaks and side beaks; the mandibular condyle could be an ideal sample for the related molecular mechanism studies underlying this trait.

Genome-wide characterization of copy number variations in the host genome in genetic resistance to Marek's disease using next generation sequencing

Background

Marek’s disease (MD) is a highly neoplastic disease primarily affecting chickens, and remains as a chronic infectious disease that threatens the poultry industry. Copy number variation (CNV) has been examined in many species and is recognized as a major source of genetic variation that directly contributes to phenotypic variation such as resistance to infectious diseases. Two highly inbred chicken lines, 6₃ (MD-resistant) and 7₂ (MD-susceptible), as well as their F₁ generation and six recombinant congenic strains (RCSs) with varied susceptibility to MD, are considered as ideal models to identify the complex mechanisms of genetic and molecular resistance to MD.

Results

In the present study, to unravel the potential genetic mechanisms underlying resistance to MD, we performed a genome-wide CNV detection using next generation sequencing on the inbred chicken lines with the assistance of CNVnator. As a result, a total of 1649 CNV regions (CNVRs) were successfully identified after merging all the nine datasets, of which 90 CNVRs were overlapped across all the chicken lines. Within these shared regions, 1360 harbored genes were identified. In addition, 55 and 44 CNVRs with 62 and 57 harbored genes were specifically identified in line 6₃ and 7₂, respectively. Bioinformatics analysis showed that the nearby genes were significantly enriched in 36 GO terms and 6 KEGG pathways including JAK/STAT signaling pathway. Ten CNVRs (nine deletions and one duplication) involved in 10 disease-related genes were selected for validation by using quantitative real-time PCR (qPCR), all of which were successfully confirmed. Finally, qPCR was also used to validate two deletion events in line 7₂ that were definitely normal in line 6₃. One high-confidence gene, IRF2 was identified as the most promising candidate gene underlying resistance and susceptibility to MD in view of its function and overlaps with data from previous study.

Conclusions

Our findings provide valuable insights for understanding the genetic mechanism of resistance to MD and the identified gene and pathway could be considered as the subject of further functional characterization.

The Morphology of Cross-Beaks and BMP4 Gene Expression in Huiyang Bearded Chickens

Simple Summary

Recently, the emergence of cross-beaks has been reported in several domestic chickens. Despite several candidate genes, bone morphogenetic protein 4 (BMP4) has been suggested as responsible for chicken cross-beaks. The subtypes of the morphology term, etiopathogenesis, and the relationship of the candidate BMP4 gene to cross-beaks are not yet known. The objective of this study was to describe the subtypes of cross-beaks by left or right and upper and lower jaw bones and to figure out the relationship between BMP4 and the development of craniofacial bones in Huiyang bearded chickens.

Abstract

Bird beaks are important for biological purposes such as food intake, removing parasites, and defining phenotypic attributes. Cross-beaks are a threat to poultry health and are harmful to productivity, wasting some units in the poultry industry. However, there is still limited research on subtypes of cross-beaks and the genetic basis of cross-beaks as well. Here, we described the subtypes of cross-beaks in terms of left or right and upper or lower jaw bones. We evaluated the impact of cross-beaks on craniofacial bones and figured out the relationship between bone morphogenetic protein 4 (BMP4) and the development of craniofacial bones in Huiyang bearded chickens. We identified five typical subtypes of cross-beaks by morphological assessment and X-ray scanning. We found that cross-beaks caused certain changes in the facial bone morphology, including changes to the length and width of the bone around the ocular area (p < 0.05). The relative expressions of BMP4 in lacrimal, mandible, premaxilla, frontal, and parietal bones were significantly higher in the severe cross-beak group, followed by that of the medium cross-beak group, weak cross-beak group, and control group (p < 0.05). Overall, we constructed a generally applicable method to classify cross-beaks in term of the angle. The skeleton around the ocular area was affected by the cross-beak. The expression levels of BMP4 in craniofacial bones may provide insight to potential role of BMP4 in the development of cross-beaks.

Differential proteomic analysis to identify proteins associated with beak deformity in chickens

The beak is the dominant avian facial feature, and beak deformity occurs in 0.5 to 2.5% of some indigenous chicken breeds, resulting in difficulties when eating, drinking, and performing natural behaviors. Previous studies on beak deformity focused largely on candidate molecules associated with skeletogenic development, providing insight into the molecular and genetic underpinnings of beak deformity. The present study was performed to identify candidate proteins related to this malformation in chickens. Three 12-day-old Beijing-You roosters with deformed beaks (D1, D2, and D3) and 3 with normal beaks (N1, N2, and N3) were used, and total beak proteins were isolated and subjected to standard iTRAQ labeling, strong cation-exchange chromatography, and liquid chromatography-tandem mass spectrometry. Mascot 2.3.02 was used to identify and quantitatively analyze proteins. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were used to identify functions and metabolic pathways of differentially expressed proteins, and key proteins were further validated using western blot. A total of 2,370, 2,401, and 2,378 proteins were reliably quantified in 3 biological replicates, among which, 2,345 were common to all, and 92 were differentially expressed between the 2 groups. These included 37 upregulated and 55 downregulated proteins in deformed beaks. Pentraxin-related protein 3, hemopexin, lipoprotein lipase, retinoid-binding protein 7, and biliverdin reductase A were downregulated in all 3 sets, while parvalbumin, peptidyl-prolyl cis-trans isomerase, and ubiquitin-fold modifier 1 were upregulated. Pathway analysis returned no enriched pathways, and western blot validated the iTRAQ results. Parvalbumin and lipoprotein lipase could be firstly selected as key proteins in view of their known functions in regulating the buffering of intracellular free Ca2+ in both cartilage and bone cells and bone mass, respectively. Their potential roles in beak deformity, however, deserve further studies. In summary, the onset of beak deformity could be very complex, and this study will be helpful for future investigation of mechanistic explanation for beak deformity.

Single SNP- and pathway-based genome-wide association studies for beak deformity in chickens using high-density 600K SNP arrays

Background

Beak deformity, typically expressed as the crossing of upper and lower mandibles, is found in several indigenous chicken breeds, including the Beijing-You chickens studied here. Beak deformity severely impairs the birds’ growth and welfare. Although previous studies shed some light on the genetic regulation of this complex trait, the genetic basis of this malformation remains incompletely understood.

Results

In this study, single SNP- and pathway-based genome-wide association studies (GWASs) were performed using ROADTRIPS and SNP ratio test (SRT), respectively. A total of 48 birds with deformed beaks (case) and 48 normal birds (control) were genotyped using Affymetrix 600 K HD genotyping arrays. As a result, 95 individuals and 429,539 SNPs were obtained after quality control. The P-value was corrected by a Bonferroni adjustment based on linkage disequilibrium pruning. The single SNP-based association study identified one associated SNP with 5% genome-wide significance and seven suggestively associated SNPs. Four high-confidence genes, LOC421892, TDRD3, RET, and STMN1, were identified as the most promising candidate genes underlying this complex trait in view of their positions, functions, and overlaps with previous studies. The pathway-based association study highlighted the association of six pathways with beak deformity, including the calcium signaling pathway.

Conclusions

Potentially useful candidate genes and pathways for beak deformity were identified, which should be the subject of further functional characterization.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4882-8) contains supplementary material, which is available to authorized users.