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

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.

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.

Identify Candidate Genes Associated with the Weight and Egg Quality Traits in Wenshui Green Shell-Laying Chickens by the Copy Number Variation-Based Genome-Wide Association Study

Copy number variation (CNV), as an essential source of genetic variation, can have an impact on gene expression, genetic diversity, disease susceptibility, and species evolution in animals. To better understand the weight and egg quality traits of chickens, this paper aimed to detect CNVs in Wenshui green shell-laying chickens and conduct a copy number variation regions (CNVRs)-based genome-wide association study (GWAS) to identify variants and candidate genes associated with their weight and egg quality traits to support related breeding efforts. In our paper, we identified 11,035 CNVRs in Wenshui green shell-laying chickens, which collectively spanned a length of 13.1 Mb, representing approximately 1.4% of its autosomal genome. Out of these CNVRs, there were 10,446 loss types, 491 gain types, and 98 mixed types. Notably, two CNVRs showed significant correlations with egg quality, while four CNVRs exhibited significant associations with body weight. These significant CNVRs are located on chromosome 4. Further analysis identified potential candidate genes that influence weight and egg quality traits, including FAM184B, MED28, LAP3, ATOH8, ST3GAL5, LDB2, and SORCS2. In this paper, the CNV map of the Wenshui green shell-laying chicken genome was constructed for the first time through population genotyping. Additionally, CNVRs can be employed as molecular markers to genetically improve chickens' weight and egg quality traits.

Advancements in copy number variation screening in herbivorous livestock genomes and their association with phenotypic traits

Copy number variations (CNVs) have garnered increasing attention within the realm of genetics due to their prevalence in human, animal, and plant genomes. These structural genetic variations have demonstrated associations with a broad spectrum of phenotypic diversity, economic traits, environmental adaptations, epidemics, and other essential aspects of both plants and animals. Furthermore, CNVs exhibit extensive sequence variability and encompass a wide array of genomes. The advancement and maturity of microarray and sequencing technologies have catalyzed a surge in research endeavors pertaining to CNVs. This is particularly prominent in the context of livestock breeding, where molecular markers have gained prominence as a valuable tool in comparison to traditional breeding methods. In light of these developments, a contemporary and comprehensive review of existing studies on CNVs becomes imperative. This review serves the purpose of providing a brief elucidation of the fundamental concepts underlying CNVs, their mutational mechanisms, and the diverse array of detection methods employed to identify these structural variations within genomes. Furthermore, it seeks to systematically analyze the recent advancements and findings within the field of CNV research, specifically within the genomes of herbivorous livestock species, including cattle, sheep, horses, and donkeys. The review also highlighted the role of CNVs in shaping various phenotypic traits including growth traits, reproductive traits, pigmentation and disease resistance etc., in herbivorous livestock. The main goal of this review is to furnish readers with an up-to-date compilation of knowledge regarding CNVs in herbivorous livestock genomes. By integrating the latest research findings and insights, it is anticipated that this review will not only offer pertinent information but also stimulate future investigations into the realm of CNVs in livestock. In doing so, it endeavors to contribute to the enhancement of breeding strategies, genomic selection, and the overall improvement of herbivorous livestock production and resistance to diseases.

Genome-wide investigation to assess copy number variants in the Italian local chicken population

BACKGROUND

Copy number variants (CNV) hold significant functional and evolutionary importance. Numerous ongoing CNV studies aim to elucidate the etiology of human diseases and gain insights into the population structure of livestock. High-density chips have enabled the detection of CNV with increased resolution, leading to the identification of even small CNV. This study aimed to identify CNV in local Italian chicken breeds and investigate their distribution across the genome.

RESULTS

Copy number variants were mainly distributed across the first six chromosomes and primarily associated with loss type CNV. The majority of CNV in the investigated breeds were of types 0 and 1, and the minimum length of CNV was significantly larger than that reported in previous studies. Interestingly, a high proportion of the length of chromosome 16 was covered by copy number variation regions (CNVR), with the major histocompatibility complex being the likely cause. Among the genes identified within CNVR, only those present in at least five animals across breeds (n = 95) were discussed to reduce the focus on redundant CNV. Some of these genes have been associated to functional traits in chickens. Notably, several CNVR on different chromosomes harbor genes related to muscle development, tissue-specific biological processes, heat stress resistance, and immune response. Quantitative trait loci (QTL) were also analyzed to investigate potential overlapping with the identified CNVR: 54 out of the 95 gene-containing regions overlapped with 428 QTL associated to body weight and size, carcass characteristics, egg production, egg components, fat deposition, and feed intake.

CONCLUSIONS

The genomic phenomena reported in this study that can cause changes in the distribution of CNV within the genome over time and the comparison of these differences in CNVR of the local chicken breeds could help in preserving these genetic resources.

Genome-wide association studies for economically important traits in mink using copy number variation

Copy number variations (CNVs) are structural variants consisting of duplications and deletions of DNA segments, which are known to play important roles in the genetics of complex traits in livestock species. However, CNV-based genome-wide association studies (GWAS) have remained unexplored in American mink. Therefore, the purpose of the current study was to investigate the association between CNVs and complex traits in American mink. A CNV-based GWAS was performed with the ParseCNV2 software program using deregressed estimated breeding values of 27 traits as pseudophenotypes, categorized into traits of growth and feed efficiency, reproduction, pelt quality, and Aleutian disease tests. The study identified a total of 10,137 CNVs (6968 duplications and 3169 deletions) using the Affymetrix Mink 70K single nucleotide polymorphism (SNP) array in 2986 American mink. The association analyses identified 250 CNV regions (CNVRs) associated with at least one of the studied traits. These CNVRs overlapped with a total of 320 potential candidate genes, and among them, several genes have been known to be related to the traits such as ARID1B, APPL1, TOX, and GPC5 (growth and feed efficiency traits); GRM1, RNASE10, WNT3, WNT3A, and WNT9B (reproduction traits); MYO10, and LIMS1 (pelt quality traits); and IFNGR2, APEX1, UBE3A, and STX11 (Aleutian disease tests). Overall, the results of the study provide potential candidate genes that may regulate economically important traits and therefore may be used as genetic markers in mink genomic breeding programs.

Genetic Architecture of Abdominal Fat Deposition Revealed by a Genome-Wide Association Study in the Laying Chicken

Fat has a high energy density, and excessive fatness has been recognized as a problem for egg production and the welfare of chickens. The identification of a genetic polymorphism controlling fat deposition would be helpful to select against excessive fatness in the laying hen. This study aimed to estimate genomic heritability and identify the genetic architecture of abdominal fat deposition in a population of chickens from a Dongxiang blue-shelled local breed crossbred with the White Leghorn. A genome-wide association study was conducted on abdominal fat percentage, egg production and body weights using a sample of 1534 hens genotyped with a 600 K Chicken Genotyping Array. The analysis yielded a heritability estimate of 0.19 ± 0.04 for abdominal fat percentage; 0.56 ± 0.04 for body weight at 72 weeks; 0.11 ± 0.03 for egg production; and 0.24 ± 0.04 for body weight gain. The genetic correlation of abdominal fat percentage with egg production between 60 and 72 weeks of age was -0.35 ± 0.18. This implies a potential trade-off between these two traits related to the allocation of resources. Strong positive genetic correlations were found between fat deposition and weight traits. A promising locus close to COL12A1 on chromosome 3, associated with abdominal fat percent, was found in the present study. Another region located around HTR2A on chromosome 1, where allele substitution was predicted to be associated with body weight gain, accounted for 2.9% of phenotypic variance. Another region located on chromosome 1, but close to SOX5, was associated with egg production. These results may be used to influence the balanced genetic selection for laying hens.

Descriptive Statistics and Genome-Wide Copy Number Analysis of Milk Production Traits of Jiangsu Chinese Holstein Cows

Milk production traits are the most important quantitative economic traits in dairy cow production; improving the yield and quality of milk is an important way to ensure the production efficiency of the dairy industry. This study carried out a series of in-depth statistical genetics studies and molecular analyses on the Chinese Holstein cows in the Jiangsu Province, such as descriptive statistics and copy number variation analysis. A genetic correlation, phenotypic correlation, and descriptive statistical analysis of five milk production traits (milk yield, milk fat percentage, milk fat yield, milk protein percentage, and milk protein yield) of the dairy cows were analyzed using the SPSS and DMU software. Through quality control, 4173 cows and their genomes were used for genomic study. Then, SNPs were detected using DNA chips, and a copy number variation (CNV) analysis was carried out to locate the quantitative trait loci (QTL) of the milk production traits by Perl program software Penn CNV and hidden Markov model (HMM). The phenotypic means of the milk yield, milk fat percentage, milk fat mass, milk protein percentage, and milk protein mass at the first trimester were lower than those at the other trimesters by 8.821%, 1.031%, 0.930%, 0.003%, and 0.826%, respectively. The five milk production traits showed a significant phenotypic positive correlation (p < 0.01) and a high genetic positive correlation among the three parities. Based on the GGPBovine 100 K SNP data, QTL-detecting research on the fist-parity milk performance of dairy cows was carried out via the CNV. We identified 1731 CNVs and 236 CNVRs in the 29 autosomes of 984 Holstein dairy cows, and 19 CNVRs were significantly associated with the milk production traits (p < 0.05). These CNVRs were analyzed via a bioinformatics analysis; a total of 13 gene ontology (GO) terms and 20 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were significantly enriched (p < 0.05), and these terms and pathways are mainly related to lipid metabolism, amino acid metabolism, and cellular catabolic processes. This study provided a theoretical basis for the molecular-marker-assisted selection of dairy cows by developing descriptive statistics on the milk production traits of dairy cows and by locating the QTL and functional genes that affect the milk production traits of first-born dairy cows. The results describe the basic status of the milk production traits of the Chinese Holstein cows in Jiangsu and locate the QTL and functional genes that affect the milk production traits of the first-born cows, providing a theoretical basis for the molecular-marker-assisted selection of dairy cows.

Genome wide copy number variations using Porcine 60K SNP Beadchip in Landlly pigs

In the present study, Porcine 60K SNP genotype data from 69 Landlly pigs were used to explore Copy Number Variations (CNVs) across the autosomes. A total of 386 CNVs were identified using Hidden Markov Model (HMM) in PennCNV software, which were subsequently aggregated to 115 CNV regions (CNVRs). Among the total detected CNVRs, 58 gain, 49 were loss type while remaining 8 events were both gain and loss types. Identified CNVRs covered 12.5 Mb (0.55%) of Sus scrofa reference 11.1 genome. Comparison of our results with previous investigations on pigs revealed that approximately 75% CNVRs were novel, which may be due to differences in genetic background, environment and implementation of artificial selection in Landlly pigs. Functional annotation and pathway analysis showed the significant enrichment of 267 well-annotated Sus scrofa genes in CNVRs. These genes were involved in different biological functions like sensory perception, meat quality traits, back fat thickness and immunity. Additionally, KIT and FUT1 were two major genes detected on CNVR in our population. This investigation provided a comprehensive overview of CNV distribution in the Indian porcine genome for the first time, which may be useful for further investigating the association of important quantitative traits in Landlly pigs.Highlights115 CNVRs were identified in 69 Landlly pig population.Approximately 75% detected CNVRs were novel for Landlly population.Significant enrichment of 267 well-annotated Sus scrofa genes observed in these CNVRs.These genes were involved in different biological functions like sensory perception, meat quality traits, back fat thickness and immunity.Comprehensive CNV map in the Indian porcine genome developed for the first time.

Genetic Association Analysis of Copy Number Variations for Meat Quality in Beef Cattle

Meat quality is an economically important trait for global food production. Copy number variations (CNVs) have been previously implicated in elucidating the genetic basis of complex traits. In this article, we detected a total of 112,198 CNVs and 10,102 CNV regions (CNVRs) based on the Bovine HD SNP array. Next, we performed a CNV-based genome-wide association analysis (GWAS) of six meat quality traits and identified 12 significant CNV segments corresponding to eight candidate genes, including PCDH15, CSMD3, etc. Using region-based association analysis, we further identified six CNV segments relevant to meat quality in beef cattle. Among these, TRIM77 and TRIM64 within CNVR4 on BTA29 were detected as candidate genes for backfat thickness (BFT). Notably, we identified a 34 kb duplication for meat color (MC) which was supported by read-depth signals, and this duplication was embedded within the keratin gene family including KRT4, KRT78, and KRT79. Our findings will help to dissect the genetic architecture of meat quality traits from the aspects of CNVs, and subsequently improve the selection process in breeding programs.

Genome-Wide Detection of Copy Number Variations Associated with Miniature Features in Horses

Copy number variations (CNVs) are crucial structural genomic variants affecting complex traits in humans and livestock animals. The current study was designed to conduct a comprehensive comparative copy number variation analysis among three breeds, Debao (DB), Baise (BS), and Warmblood (WB), with a specific focus on identifying genomic regions associated with miniature features in horses. Using whole-genome next-generation resequencing data, we identified 18,974 CNVs across 31 autosomes. Among the breeds, we found 4279 breed-specific CNV regions (CNVRs). Baise, Debao, and Warmblood displayed 2978, 986, and 895 distinct CNVRs, respectively, with 202 CNVRs shared across all three breeds. After removing duplicates, we obtained 1545 CNVRs from 26 horse genomes. Functional annotation reveals enrichment in biological functions, including antigen processing, cell metabolism, olfactory conduction, and nervous system development. Debao horses have 970 genes overlapping with CNVRs, possibly causing their small size and mountainous adaptations. We also found that the genes GHR, SOX9, and SOX11 may be responsible for the miniature features of the Debao horse by analyzing their overlapping CNVRs. Overall, this study offers valuable insights into the widespread presence of CNVs in the horse genome. The findings contribute to mapping horse CNVs and advance research on unique miniature traits observed in the Debao horse.

Detection distribution of CNVs of SNX29 in three goat breeds and their associations with growth traits

As a member of the SNX family, the goat sorting nexin 29 (SNX29) is initially identified as a myogenesis gene. Therefore, this study aimed to examine the polymorphism in the SNX29 gene and its association with growth traits. In this study, we used an online platform to predict the structures of the SNX29 protein and used quantitative real-time PCR to detect potential copy number variation (CNV) in Shaanbei white cashmere (SBWC) goats (n = 541), Guizhou black (GB) goats (n = 48), and Nubian (NB) goats (n = 39). The results showed that goat SNX29 protein belonged to non-secretory protein. Then, five CNVs were detected, and their association with growth traits was analyzed. In SBWC goats, CNV1, CNV3, CNV4, and CNV5 were associated with chest width and body length (P < 0.05). Among them, the CNV1 individuals with gain and loss genotypes were superior to those individuals with a median genotype, but CNV4 and CNV5 of individuals with the median genotype were superior to those with the loss and gain genotypes. In addition, individuals with the gain genotype had superior growth traits in CNV3. In brief, this study suggests that the CNV of SNX29 can be used as a molecular marker in goat breeding.

Digital Phenotyping: A Game Changer for the Broiler Industry

In response to escalating global demand for poultry, the industry grapples with an array of intricate challenges, from enhancing productivity to improving animal welfare and attenuating environmental impacts. This comprehensive review explores the transformative potential of digital phenotyping, an emergent technological innovation at the cusp of dramatically reshaping broiler production. The central aim of this study is to critically examine digital phenotyping as a pivotal solution to these multidimensional industry conundrums. Our investigation spotlights the profound implications of 'digital twins' in the burgeoning field of broiler genomics, where the production of exact digital counterparts of physical entities accelerates genomics research and its practical applications. Further, this review probes into the ongoing advancements in the research and development of a context-sensitive, multimodal digital phenotyping platform, custom-built to monitor broiler health. This paper critically evaluates this platform's potential in revolutionizing health monitoring, fortifying the resilience of broiler production, and fostering a harmonious balance between productivity and sustainability. Subsequently, the paper provides a rigorous assessment of the unique challenges that may surface during the integration of digital phenotyping within the industry. These span from technical and economic impediments to ethical deliberations, thus offering a comprehensive perspective. The paper concludes by highlighting the game-changing potential of digital phenotyping in the broiler industry and identifying potential future directions for the field, underlining the significance of continued research and development in unlocking digital phenotyping's full potential. In doing so, it charts a course towards a more robust, sustainable, and productive broiler industry. The insights garnered from this study hold substantial value for a broad spectrum of stakeholders in the broiler industry, setting the stage for an imminent technological evolution in poultry production.

Comparative analysis of genomic inbreeding parameters and runs of homozygosity islands in several fancy and meat rabbit breeds

Runs of homozygosity (ROH) are defined as long stretches of DNA homozygous at each polymorphic position. The proportion of genome covered by ROH and their length are indicators of the level and origin of inbreeding. In this study, we analysed SNP chip datasets (obtained using the Axiom OrcunSNP Array) of a total of 702 rabbits from 12 fancy breeds and four meat breeds to identify ROH with different approaches and calculate several genomic inbreeding parameters. The highest average number of ROH per animal was detected in Belgian Hare (~150) and the lowest in Italian Silver (~106). The average length of ROH ranged from 4.001 ± 0.556 Mb in Italian White to 6.268 ± 1.355 Mb in Ermine. The same two breeds had the lowest (427.9 ± 86.4 Mb, Italian White) and the highest (921.3 ± 179.8 Mb, Ermine) average values of the sum of all ROH segments. More fancy breeds had a higher level of genomic inbreeding (as defined by ROH) than meat breeds. Several ROH islands contain genes involved in body size, body length, pigmentation processes, carcass traits, growth, and reproduction traits (e.g.: AOX1, GPX5, IFRD1, ITGB8, NELL1, NR3C1, OCA2, TRIB1, TRIB2). Genomic inbreeding parameters can be useful to overcome the lack of information in the management of rabbit genetic resources. ROH provided information to understand, to some extent, the genetic history of rabbit breeds and to identify signatures of selection in the rabbit genome.

Comprehensive analysis of structural variants in chickens using PacBio sequencing

Structural variants (SVs) are one of the main sources of genetic variants and have a greater impact on phenotype evolution, disease susceptibility, and environmental adaptations than single nucleotide polymorphisms (SNPs). However, SVs remain challenging to accurately type, with several detection methods showing different limitations. Here, we explored SVs from 10 different chickens using PacBio technology and detected 49,501 high-confidence SVs. The results showed that the PacBio long-read detected more SVs than Illumina short-read technology genomes owing to some SV sites on chromosomes, which are related to chicken growth and development. During chicken domestication, some SVs beneficial to the breed or without any effect on the genomic function of the breed were retained, whereas deleterious SVs were generally eliminated. This study could facilitate the analysis of the genetic characteristics of different chickens and provide a better understanding of their phenotypic characteristics at the SV level, based on the long-read sequencing method. This study enriches our knowledge of SVs in chickens and improves our understanding of chicken genomic diversity.

Transcriptome sequencing analysis of the role of miR-499-5p and SOX6 in chicken skeletal myofiber specification

MicroRNAs (miRNAs) might play critical roles in skeletal myofiber specification. In a previous study, we found that chicken miR-499-5p is specifically expressed in slow-twitch muscle and that its potential target gene is SOX6. In this study, we performed RNA sequencing to investigate the effects of SOX6 and miR-499-5p on the modulation and regulation of chicken muscle fiber type and its regulatory mechanism. The expression levels of miR-499-5p and SOX6 demonstrated opposing trends in different skeletal muscles and were associated with muscle fiber type composition. Differential expression analysis revealed that miR-499-5p overexpression led to significant changes in the expression of 297 genes in chicken primary myoblasts (CPMs). Myofiber type-related genes, including MYH7B and CSRP3, showed expression patterns similar to those in slow-twitch muscle. According to functional enrichment analysis, differentially expressed genes were mostly associated with muscle development and muscle fiber-related processes. SOX6 was identified as the target gene of miR-499-5p in CPM using target gene mining and luciferase reporter assays. SOX6 knockdown resulted in upregulation of the slow myosin genes and downregulation of fast myosin genes. Furthermore, protein-protein interaction network analysis revealed that MYH7B and RUNX2 may be the direct targets of SOX6. These results indicated that chicken miR-499-5p may promote slow-twitch muscle fiber formation by repressing SOX6 expression. Our study provides a dataset that can be used as a reference for animal meat quality and human muscle disease studies.

Genome-wide detection of copy number variation in American mink using whole-genome sequencing

BACKGROUND

Copy number variations (CNVs) represent a major source of genetic diversity and contribute to the phenotypic variation of economically important traits in livestock species. In this study, we report the first genome-wide CNV analysis of American mink using whole-genome sequence data from 100 individuals. The analyses were performed by three complementary software programs including CNVpytor, DELLY and Manta.

RESULTS

A total of 164,733 CNVs (144,517 deletions and 20,216 duplications) were identified representing 5378 CNV regions (CNVR) after merging overlapping CNVs, covering 47.3 Mb (1.9%) of the mink autosomal genome. Gene Ontology and KEGG pathway enrichment analyses of 1391 genes that overlapped CNVR revealed potential role of CNVs in a wide range of biological, molecular and cellular functions, e.g., pathways related to growth (regulation of actin cytoskeleton, and cAMP signaling pathways), behavior (axon guidance, circadian entrainment, and glutamatergic synapse), lipid metabolism (phospholipid binding, sphingolipid metabolism and regulation of lipolysis in adipocytes), and immune response (Wnt signaling, Fc receptor signaling, and GTPase regulator activity pathways). Furthermore, several CNVR-harbored genes associated with fur characteristics and development (MYO5A, RAB27B, FGF12, SLC7A11, EXOC2), and immune system processes (SWAP70, FYN, ORAI1, TRPM2, and FOXO3).

CONCLUSIONS

This study presents the first genome-wide CNV map of American mink. We identified 5378 CNVR in the mink genome and investigated genes that overlapped with CNVR. The results suggest potential links with mink behaviour as well as their possible impact on fur quality and immune response. Overall, the results provide new resources for mink genome analysis, serving as a guideline for future investigations in which genomic structural variations are present.

Genome-wide evaluation of copy gain and loss variations in three Afghan sheep breeds

Copy number variation (CNV) is one of the main sources of variation between different individuals that has recently attracted much researcher interest as a major source for heritable variation in complex traits. The aim of this study was to identify CNVs in Afghan indigenous sheep consisting of three Arab, Baluchi, and Gadik breeds using genomic arrays containing 53,862 single nucleotide polymorphism (SNP) markers. Data were analyzed using the Hidden Markov Model (HMM) of PennCNV software. In this study, out of 45 sheep studied, 97.8% (44 animals) have shown CNVs. In total, 411 CNVs were observed for autosomal chromosomes and the entire sequence length of around 144 Mb was identified across the genome. The average number of CNVs per each sheep was 9.13. The identified CNVs for Arab, Baluchi, and Gadik breeds were 306, 62, and 43, respectively. After merging overlapped regions, a total of 376 copy number variation regions (CNVR) were identified, which are 286, 50, and 40 for Arab, Baluchi, and Gadik breeds, respectively. Bioinformatics analysis was performed to identify the genes and QTLs reported in these regions and the biochemical pathways involved by these genes. The results showed that many of these CNVRs overlapped with the genes or QTLs that are associated with various pathways such as immune system development, growth, reproduction, and environmental adaptions. Furthermore, to determine a genome-wide pattern of selection signatures in Afghan sheep breeds, the unbiased estimates of FST was calculated and the results indicated that 37 of the 376 CNVRs (~ 10%) have been also under selection signature, most of those overlapped with the genes influencing production, reproduction and immune system. Finally, the statistical methods used in this study was applied in an external dataset including 96 individuals of the Iranian sheep breed. The results indicated that 20 of the 114 CNVRs (18%) identified in Iranian sheep breed were also identified in our study, most of those overlapped with the genes influencing production, reproduction and immune system. Overall, this is the first attempts to develop the genomic map of loss and gain variation in the genome of Afghan indigenous sheep breeds, and may be important to shed some light on the genomic regions associated with some economically important traits in these breeds.

CNV detection and their association with growth, efficiency and carcass traits in Santa Inês sheep

Copy number variations (CNV) are an important source of genetic variation. CNV has been increasingly studied and frequently associated with diseases and productive traits in livestock animals. However, CNV-based genome-wide association studies (GWAS) in Santa Inês sheep, one of the principal sheep breeds in Brazil, have not yet been reported. Thus, the aim of this study was to investigate the association between CNV and growth, efficiency and carcass traits in sheep. The Illumina OvineSNP50 BeadChip array was used to detect CNV in 491 Santa Inês individuals. Then, CNV-based GWAS was performed with a linear mixed model approach considering a genomic relationship matrix, for ten traits: (1) growth: body weight at three (W3) and six (W6) months of age; (2) efficiency: residual feed intake (RFI) and feed efficiency (FE) and (3) carcass: external carcass length (ECL), leg length (LL), carcass yield (CY), commercial cuts weight (CCW), loin eye area (LEA) and subcutaneous fat thickness (SFT). We identified 1,167 autosomal CNV in 438 sheep, with 294 non-redundant CNV, ranging from 21.8 to 861.9 kb, merged into 216 distinct copy number variation regions (CNVRs). One significant CNV segment (p_FDR -value<0.05) in OAR3 was associated with CY, while another significant CNV in OAR6 was associated with RFI. Additionally, another 5 CNV segments were considered relevant for investigation in the future studies. The significant segments overlapped 4 QTLs and spanned 8 genes, including the SPAST, TGFA and ADGRL3 genes, involved in cell differentiation and energy metabolism. Therefore, the results of the present study increase knowledge about CNV in sheep, their possible impacts on productive traits, and provide information for future investigations, being especially useful for those interested in structural variations in the sheep genome.

SAP30 Gene Is a Probable Regulator of Muscle Hypertrophy in Chickens

Animals with muscle hypertrophy phenotype are targeted by the broiler industry to increase the meat production and the quality of the final product. Studies characterizing the molecular machinery involved with these processes, such as quantitative trait loci studies, have been carried out identifying several candidate genes related to this trait; however, validation studies of these candidate genes in cell culture is scarce. The aim of this study was to evaluate SAP30 as a candidate gene for muscle development and to validate its function in cell culture in vitro. The SAP30 gene was downregulated in C2C12 muscle cell culture using siRNA technology to evaluate its impact on morphometric traits and gene expression by RNA-seq analysis. Modulation of SAP30 expression increased C2C12 myotube area, indicating a role in muscle hypertrophy. RNA-seq analysis identified several upregulated genes annotated in muscle development in treated cells (SAP30-knockdown), corroborating the role of SAP30 gene in muscle development regulation. Here, we provide experimental evidence of the involvement of SAP30 gene as a regulator of muscle cell hypertrophy.