P-values 1.49e-08 to 1.01e-08) within introns of the gene adhesion G protein-coupled receptor B3 (ADGRB3) associated with lower fecal egg counts. With linear regression, four significant SNPs  were identified within the first intron of the gene EGF-like repeats and discoidin domains 3 (EDIL3). These identified SNPs were in very high linkage disequilibrium (r2 of 0.996–1), and animals with alternate homozygous genotypes had significantly higher median weaning tFEC phenotypes compared to all other genotypes. Significant SNPs were queried through public databases to identify putative transcription factor binding site (TFBS) and potential lncRNA differences between reference and alternate alleles. Changes in TFBS were predicted at two SNPs, and one significant SNP was found to be within a predicted lncRNA sequence with greater than 90% similarity to a known lncRNA in the bovine genome. The gene EDIL3 has been described in other species for its roles in the inhibition and resolution of inflammation. Potential changes of EDIL3 expression mediated through lncRNA expression and/or transcription factor binding may impact the overall immune response and reduce the ability of Katahdin sheep to control GIN infection. This study lays the foundation for further research of EDIL3 and ADGRB3 towards understanding genetic mechanisms of susceptibility to GIN, and suggests these SNPs may contribute to genetic strategies for improving parasite resistance traits in sheep.Gastrointestinal nematodes (GIN) pose a severe threat to sheep production worldwide. Anthelmintic drug resistance coupled with growing concern regarding potential environmental effects of drug use have demonstrated the necessity of implementing other methods of GIN control. The aim of this study was to test for genetic variants associated with resistance or susceptibility to GIN in Katahdin sheep to improve the current understanding of the genetic mechanisms responsible for host response to GIN. Linear regression and case-control genome-wide association studies were conducted with high-density genotype data and cube-root transformed weaning fecal egg counts (tFEC) of 583 Katahdin sheep. The case-control GWAS identified two significant SNPs ( Gastrointestinal nematodes (GIN) are arguably considered to be one of the greatest health and economic threats to small ruminant production worldwide . GIN infThe lifecycles of GIN parasites are similar and can be divided between a free-living environmental stage and a parasitic stage within the specific gastrointestinal niche. Sheep that are susceptible to GIN may harbor thousands of worms and contribute to the continued contamination of parasite eggs into the environment ; dependiHair sheep are generally considered to be more tolerant of GIN infection than conventional wool breeds and are capable of maintaining higher packed cell volumes and lower fecal egg counts (FEC) during parasite challenge . The Kath2 of 0.2–0.3), although there are differences in parasite resistance both between and within breeds  was performed with high-density (HD) genotype data and weaning FEC of 583 Katahdin sheep. The reference DNA sequences associated with significant SNPs were queried through public functional databases for putative transcription factor binding sites (TFBSs) and sequence identity to known non-coding RNA. These predictive analyses were conducted in order to evaluate possible functional consequences of significant SNPs towards building a better understanding of the potential genetic mechanisms that differentiate susceptible from resistant sheep.n = 275 male, n = 308 female) were used in the current study. To ensure representative exposure to GIN, animals were sampled from 20 different Katahdin flocks located in 12 states across the US  (n = 282), 2018 (n = 209) or 2017 or earlier (n = 92). Stool samples were collected directly from the rectum of animals at weaning (70.24 ± 11.04 days of age). Weaning FEC were quantified by a certified parasitology laboratory using the modified McMaster technique (Louisiana State University School of Veterinary Medicine and the Virginia-Maryland College of Veterinary Medicine). From previous work, the GIN infections present on most farms used in the current study were expected to be mixed populations of H. contortus, Trichostrongylus spp., and to a lesser extent, Teladorsagia spp., Cooperia spp. and Oesophagostomum spp  . All paromum spp .n = 119), the maximum was 38 (n = 1) and the median was 8 (n = 23)  .Blood samples were collected by the participating sheep producers and stored on blood cards until genotyping. Sample DNA were extracted from blood cards and genotyped with the high-density (HD) Illumina 600 K SNP BeadChip  comprised of 606,006 markers. All DNA extraction and genotyping were conducted at Neogen Corporation—GeneSeek Operations, Lincoln, NE, USA. DNA was extracted by Neogen using the MagMAX™ DNA Multi-Sample Ultra Kit (Thermo Fisher Scientific Cat. A25598).All samples had a genotypic call rate (CR) > 90%: genotype markers with GenCall score <0.15 were initially excluded, followed by non-autosomal markers, markers with CR < 90%, minor allele frequency <1% or Hardy-Weinberg Equilibrium P-value < 1.0e-06. Redundant markers were filtered such that the marker with the highest CR per genomic location was retained for analyses. Following quality control, 505,914 high-quality autosomal markers and 583 samples were used for analyses.ww.goldenhelix.com) using the Efficient Mixed-Model eXpedited (EMMAX) (n = 119). In all tests a genomic relationship matrix was fitted as a random effect and variables with significant relationship to tFEC were fitted as fixed effects. These variables included birth month, birth/rear type  and flock; year was also significant   with addnificant  but was https://zzz.bwh.harvard.edu/plink/perm.shtml#aperm). Other parameters included alpha (0), beta (0.001), intercept (1) and slope (0.001). Permutation testing achieved a minimum empirical P-value of 1.00e-06; therefore, genome-wide significance was set to P-values < 1.00e-06. Any significant SNPs identified were further analyzed with the Kruskal-Wallis test (weaning tFEC ∼ SNP) and visualized with the package ggpubr in R version 3.6.3 . LD was reported using the r2 statistic as it is thought to be more robust than the D’ statistic and is generally more favored in the context of association studies (The linkage disequilibrium (LD) of significant SNPs identified in the LR recessive model were evaluated. LD was estimated using the composite haplotype method in the SNP and Variation SuiteTM v8.9.0 software  were queried through RNAcentral with the SNP reference and alternative allele . Due to The search tool ConSite was used to analyze input sequences against a TFBS profile collection drawn from the JASPAR database . For eacP-values from expected P-values. The QQ plots of the recessive models indicated the best control of type I/type II error  plots were constructed for each model to visualize the deviation of observed II error .EDIL3), also known as developmental endothelial locus-1 (DEL-1) , followed by rs417983470  and rs416102123 . The alternate alleles of significant SNPs identified were observed at a frequency of 35% in this study population. The proportion of weaning tFEC phenotypic variance explained by significant SNPs were 5.4%, 5.4%, 5.2%, and 5.1%, respectively -like repeats and discoidin domains 3 ( (DEL-1) . All fouectively .P-value = 1.49e-08 and 5.7% proportion of variance explained. This SNP is positioned within the first intron of the PALM2 and AKAP2 fusion gene (PALM2AKAP2). The annotation of this gene is unclear, as PALM2 and AKAP2 have been previously annotated as separate genes  (The results of the LR additive and dominant GWAS models were similar. Both of these models identified the significant SNP rs428768700 with te genes . No anim(PCDH17) .P-value = 1.01E-08 and 5.8% proportion of variance explained and rs421657777 with P-value = 5.81E-08 and 5.2% proportion of variance explained (ADGRB3). Marker rs421657777 is positioned within intron 17 and marker rs416881989 is positioned within intron 26 of ADGRB3. Although G protein-coupled receptors are involved in many physiological processes . The LD between SNPs rs405327900, rs413712238 and rs416102123 was r2 = 1, indicating perfect LD, while the LD of rs417983470 to all others was r2 = 0.996, indicating high LD. Given the strength of correlations between these SNPs, the frequencies at which these alleles occurred were determined within the sample population. The majority of samples were either homozygous for the alternate alleles (11.8% of samples), homozygous for the reference alleles (41.9% of samples) or were entirely heterozygous (46.1% of samples) at all four SNPs , SNPs rs405327900, rs416102123 and rs413712238 all exhibited identical Kruskal-Wallis test results, with overall p = 0.00018. The homozygous alternate genotypes  were significantly different when compared to heterozygous  (p = 2.3e-05) and homozygous reference genotypes  (p = 0.00091), respectively. Again based on the Kruskal-Wallis test, with an overall p = 0.00023, the homozygous alternate genotype (GG) for SNP rs417983470 significantly differed from the heterozygous (AG) (p = 3.1e-05) and homozygous reference (AA) (p = 0.001) genotypes. For all four SNPs, the homozygous alternate genotype was found to have a significantly higher median weaning tFEC than all other genotypes  (Bos taurus genome (Bos_taurus_UMD_3.1/bosTau6 assembly). The reference allele query matched at 289 positions and the alternate allele query matched at 290 positions of the target RNA sequence  were located within a region with previously reported RNA-seq reads , NCBI  scaled) . These S scaled) . The seqsequence .EDIL3 intronic variants, significant SNPs were examined for putative TFBSs. The SNPs rs405327900, rs413712238 and rs416102123 were located within predicted TFBS sequences. TFBS matrix score differences between alternate and reference alleles were observed for two of the three SNPs. The SNP rs405327900 was predicted within the transcription factors T-box transcription factor T  and proto-oncogene c-Fos (c-Fos). Whereas the alternate allele introduced a TFBS for c-Fos which was not present at the reference allele, the binding score prediction for TBXT was greater with the reference allele compared to the alternate allele. Regarding SNP rs416102123, a sequence of 10 nucleotides matched with transcription factors belonging to the Rel/NF-κB family: Rel class, proto-oncogene c-Rel (c-Rel) and transcription factor p65 . These TFBS were predicted to have greater scores with the alternate allele vs. reference allele. A TFBS for interferon regulatory factor 1 (IRF1) was identified with rs416102123 reference and lost with alternate allele sequence  within sequence near EDIL3, including EDIL3, respectively. None of the aforementioned studies tested the four SNPs significant in the present study, as these SNPs are unique to the HD array and could not be investigated in studies that utilize 50K array data.This GWAS is the first to identify significant associations with the gene EDIL3 encodes the protein epidermal growth factor (EGF)-like repeat and discoidin I-like domain-containing protein 3, a secreted glycoprotein which acts as an integrin ligand and has non-redundant roles in multiple stages of the immune response, including myelopoiesis, anti-inflammatory regulation of neutrophil infiltration and resolution of inflammation  expression has been found to correlate with the expression of nearby genes  and lncRr2 = 0.996–1) and genotypes were observed at high frequencies in the study population. Animals that possessed the homozygous alternate genotype at each significant SNP were likely more susceptible to GIN, as indicated by significantly higher median weaning tFEC phenotypes. These animals were predicted to match the lncRNA NONBTAT023693.2 with a greater identity score, possess a TFBS for c-Fos and lack a TFBS for IRF1. Animals with either homozygous reference or heterozygous genotypes were likely less susceptible to GIN infection when compared to animals with homozygous alternate genotypes. Animals that possessed homozygous reference genotypes at each significant SNP had lower predicted identity to NONBTAT023693.2 lncRNA, lacked c-Fos TFBS and possessed IRF1 TFBS. Animals that were heterozygous at significant SNPs possessed a combination of reference and alternate allele genetic attributes, but were phenotypically similar to animals with only reference alleles. These results suggest that the presence of c-Fos TFBS on both strands within EDIL3, either in conjunction with or independent of the presence of intronic lncRNA, might influence gene expression towards a more susceptible immune response to GIN. Conversely, the presence of IRF1 TFBS on one or both strands may influence a less susceptible response to GIN.The significant SNPs identified in this study were in high LD ; upregulation of TGF-β may be associated with an effective immune response to GIN in mammalian hosts (EDIL3 may have on the immune response to GIN in Katahdin sheep.It may be hypothesized that suppression of an hosts , and earan hosts . FurtherEDIL3 that were significantly associated with weaning tFEC in Katahdin sheep. Furthermore, animals with alternate homozygous genotypes at significant SNPs were found to have significantly greater median weaning tFEC phenotypes, indicating that these genotypes incur greater risk for susceptibility to GIN. Significant SNPs may have functional consequences through altered TFBS and/or lncRNA sequence, thereby affecting EDIL3 gene expression. Further work is needed to elucidate causative variants and precise functional mechanisms as well as to confirm the presence of predicted TFBS and lncRNA. To the best of our knowledge, this is the first study to associate the immune gene EDIL3 with response to parasites in sheep.In this study, four SNPs were identified within the first intron of


The detection of single nucleotide polymorphisms (SNPs) is of great significance in the early diagnosis of diseases and the rational use of drugs. Thus, a novel biosensor based on the quenching effect of fluorescence-embedded SYBR Green I (SG) dye and graphene oxide (GO) was introduced in this study. The probe DNA forms a double helix structure with perfectly complementary DNA (pcDNA) and 15 single-base mismatch DNA (smDNA) respectively. SG is highly intercalated with perfectly complementary dsDNA (pc-dsDNA) and exhibits strong fluorescence emission. Single-base mismatch dsDNA (SNPs) has a loose double-stranded structure and exhibits poor SG intercalation and low fluorescence sensing. At this time, the sensor still showed poor SNP discrimination. GO has a strong effect on single-stranded DNA (ssDNA), which can reduce the fluorescence response of probe DNA and eliminate background interference. And competitively combined with ssDNA in SNPs, quenching the fluorescence of SG/SNP, while the fluorescence value of pc-dsDNA was retained, increasing the signal-to-noise ratio. At this time, the sensor has obtained excellent SNP resolution. Different SNPs detect different intensities of fluorescence in the near-infrared region to evaluate the sensor's identification of SNPs. The experimental parameters such as incubation time, incubation temperature and salt concentration were optimized. Under optimal conditions, 1 nM DNA with 0–10 nM linear range and differentiate 5% SNP were achieved. The detection method does not require labeling, is low cost, simple in operation, exhibits high SNP discrimination and can be distinguished by SNP at room temperature. So as to clearly distinguish the SNPs in the DNA sequence. (Single nucleotide polymorphisms (SNPs) are extremely important genetic variations in human genes . SNPs reequence. . Using Sequence. . But onlSYBR Green I (SG) is a dye with green excitation wavelength that binds to all dsDNA double helix minor groove regions, and has a very high affinity with dsDNA . In the In this study, a novel biosensor based on the quenching effect of fluorescence-embedded SYBR Green I (SG) dye  and grap2HPO4, NaCl, and KH2PO4 .DNA oligomers were purchased from Shanghai Biotech Biotechnology Co. (Shanghai China). All of the DNA oligomers were purified by high performance liquid chromatography (HPLC). These sequences are shown in Fluorescence emission spectra were performed using a F-4500 fluorescence spectrophotometer  with a scan rate at 1,200 nm/min. The slits for excitation and emission were set at 5 nm/5 nm.In a typical experiment, 10 μl of probe DNA (10 μM) and 10 μl of target DNA (10 μM) were hybridized in 20 μl of 10 mM phosphate buffer  for 30 min at room temperature. The mixture of 4 μl hybridization solution and 10 μl SG (×10) was placed in a fluorescence colorimetric plate, and then 986 μl water was added. The resultant solution was then added 5 μl of graphene solution (500 μg/ml) and was carried out immediately after mixing to ensure that the detection time was consistent after each addition of graphene solution, generally 15 s. During the detection, the excitation wavelength was 497 nm, and the scanning range was 507–650 nm. Each sample was measured five times.The experimental principle of the biosensor is illustrated in SG specifically embeds dsDNA, and the fluorescence value of SG/dsDNA is much higher than that of SG alone. Hence, SG is widely used in gel electrophoresis and PCR technology. This study examined 15-base SNPs, and base mismatches occurred every two bases, as shown in This study further analyzed the dynamic changes of fluorescence values of SNPs with mismatched bases at positions 5, 8, and 11 over time after adding 2.5 μg/ml GO. As shown in λ = 525 nm. According to the detection procedure optimized for salt concentration, the following results were obtained. The results in pc-dsDNA/FSNP-8 (>68) were much higher than Fpc-dsDNA/FSNP-5 (<52), which illustrated that different positions of the smDNAs’ mismatched bases (pc-dsDNA/FSNP-5-T (52) or Fpc-dsDNA/FSNP-5-G (48) was higher than Fpc-dsDNA/FSNP-5-A (8) at 0.2 mM NaCl. This shows that different mismatched bases in the same position had also different discrimination. Therefore, SNPs from pcDNA could be easily detected when NaCl concentration at 0.2 mM NaCl, at which point the good Fpc-dsDNA/FSNPs (>20) was enough for SNP discrimination  was investigated. Under the best experimental conditions, the sensitivity of this method to detect SNPs was analyzed. As shown in In the proposed detection system, the final concentration of the probe DNA was 10 nM, and the total concentration of pcDNA and the detected smDNA  was 10 nM. The ratio of pcDNA/(pcDNA + smDNA) was 0, 5, 10, 20, 40, 60, 80, and 100%. Analysis was performed under experimental conditions of 25°C and 0.2 mM NaCl concentration, and the results shown in In summary, a new, fast, simple, ultra-highly sensitive and selective biosensor for detecting SNPs was developed here. All above detection results confirm that our biosensor indeed work as we expect. 1) The sensor requires no fluorescent labeling, is simple and inexpensive. 2) SG has specificity for the intercalation strength of each dsDNA, but the specificity is not high enough. Perfectly complementary dsDNA expresses high fluorescence emission due to the high intercalation of SG, while SNP is relatively low. After adding GO, the interaction between GO and SNP is much greater than that between GO and pc-dsDNA. The fluorescence emitted by SG/SNP is quickly quenched by GO, and the fluorescence value is almost zero. However, the fluorescence of SG/pc-dsDNA is still high. At this time, the fluorescence ratio of SG/pc-dsDNA to SG/SNP is up to 120 times, and the signal-to-noise ratio is very high. 3) Under optimized conditions, we could detect 1 nM DNA with 0–10 nM linear range and differentiate 5% SNP, with a response time of only 15 s. The sensor is expected to make a significant contribution to pharmacogenomics and medical diagnosis.


Bemisia tabaci B mitotype was reported in São Paulo state. However, the duration from the time of initial introduction to population upsurges is not known. To investigate whether the 1991 B mitotype outbreaks in Brazil originated in São Paulo or from migrating populations from neighboring introduction sites, country‐wide field samples of B. tabaci archived from 1989–2005 collections were subjected to analysis of mitochondrial cytochrome oxidase I (mtCOI) and nuclear RNA‐binding protein 15 (RP‐15) sequences. The results of mtCOI sequence analysis identified all B. tabaci as the NAFME 8 haplotype of the B mitotype. Phylogenetic analyses of RP‐15 sequences revealed that the B mitotype was likely a hybrid between a B type parent related to a haplotype Ethiopian endemism (NAFME 1–3), and an unidentified parent from the North Africa‐Middle East (NAF‐ME) region. Results provide the first evidence that this widely invasive B mitotype has evolved from a previously undocumented hybridization event. Samples from Rio de Janeiro (1989) and Ceará state (1990), respectively, are the earliest known B mitotype records in Brazil. A simulated migration for the 1989 introduction predicted a dispersal rate of 200–500 km/year, indicating that the population was unlikely to have reached Ceará by 1990. Results implicated two independent introductions of the B mitotype in Brazil in 1989 and 1990, that together were predicted to have contributed to the complete invasion of Brazil in only 30 generations.During 1991, in Brazil, the presence of the exotic  Two independent introductions of the B mitotype in Brazil, in 1989 and 1990, were predicted to have contributed to the complete invasion of Brazil in only 30 generations. Brown laboratory, University of Arizona. The nuclear RNA‐binding protein 15 (RP‐15) gene was PCR‐amplified and sequenced, and analyzed for nucleotide divergence and phylogenetic relationships. The spatio‐temporal patterns of dispersal for the B mitotype was simulated using SPLATCHE 3  insect collection maintained in Brasília, Brazil (Table B. tabaci samples were obtained from the JK Brown laboratory collection (University of Arizona), EN8 from Israel, and Eth3 from Ethiopia, previously shown to group phylogenetically with B mitotype haplotypes NAFME 8 and 3, respectively  whiteflies were selected for all but one sample (40399), which contained only males (1n). Using a flat wood toothpick , individual whiteflies were transferred to a sterile 1.5 ml microfuge tube containing 20 µl CTAB lysis buffer  and ground with a micropestle. The pestle was washed with 600 µl of CTAB lysis buffer to keep all whitefly fragments into the buffer. Proteinase K was added at 0.005 mg/ml, and samples were incubated overnight at 55°C, followed by incubation at 65°C for 15 min to inactivate the Proteinase K. One volume of chloroform was added, and the mix was centrifugated  at 16,000 g for 3 min at 4°C for phase separation. One volume of 100% isopropanol and 40 µg glycogen were added to the supernatant, with incubation for 10 min at 4°C. Total nucleic acids were pelleted by centrifugation at 16,000 g at 4°C for 10 min. The pellet was washed with 70% ethanol, air‐dried, and dissolved in 10 mmol/L Tris‐HCl, pH 8.0.Total DNA was extracted and purified using an optimized protocol  and Eth3 (NAFME 3). The previously published NAFME 1–2 and 4–7 reference sequences  consisting of the 3′‐end of the mtCOI and contiguous tRNAleu of 66 bp was amplified by PCR from samples collected in Brazil and from two of the eight B mitotype haplotypes of B. tabaci samples collected in Brazil and from two of the eight haplotype references for B. tabaci, EN8 (NAFME 8), and Eth3 (NAFME 3). The RP‐15 sequences for NAFME1‐2 and 4–7 were not available for comparison. The RP‐15 fragment was amplified by PCR using the primer pair F‐RP15‐190–5′‐CACCCACTTCATCCTCACCC‐3′ and R‐RP15‐962–5′‐TCACCCCAGGCATCATAAGC‐3′. Cycling parameters were initial denaturation of 95°C for 1 min, followed by 30 cycles of 95°C for 15 s, 55°C for 15 s, 72°C for 1 min, and a final extension at 72°C for 2min.The RP‐15 fragment of 773 bp was amplified by PCR from E. coli DH5α competent cells .The COI and RP‐15 amplicons of the expected size were cloned into the TA cloning vector pGEM‐T Easy  by heat shock‐mediated transformation of B. tabaci haplotypes, NAFME 8 (EN8_1 and EN8_3) and NAFME 3 , respectively, 8–10 cloned RP‐15 amplicons were subjected to DNA sequencing as described above.To amplify additional RP‐15 alleles from the 2.2Sequences were aligned using MUSCLE v3.8.31 Edgar, , implemeB. tabaci exemplar haplotypes, NAFME 1–8 (Table B. tabaci from Israel (EN8_1 and 3) (NAFME 8) and Ethiopia (Eth3‐1 and 2) (NAFME3).The mtCOI sequences from Brazil samples and reference sequence EN8 (NAFME 8), showed minimal to no sequence divergence, therefore representative sequences from Brazil (100% nt similarity), 40339, 40348, 40375, 40399, 40400, and 40415, were selected for phylogenetic analysis. The mtCOI sequences representing –8 Table  were inc–8 Table . The nucBemisia spp., collected from sweet potato plants in Namulonge, Uganda.The mtCOI and RP‐15 sequences for the A mitotype (New World species) from Ecuador, and Q‐like mitotype from Uganda Table , were in6 generations. Trees were sampled every 200th generation. Log‐likelihood scores were plotted with the generations sampled using Tracer v1.6 .Bayesian analysis was carried out using MrBayes v3.2.6  covering Brazil and parts of surrounding South American countries. Each deme represented a surface of ~72 km2 and exchanged migrants with its four neighbors depending on the pre‐defined parameters: (1) carrying capacity, an estimate of the maximum number of whiteflies that could be sustained given predicted resources available in the geographic deme; (2) friction, corresponding to the ease by which whiteflies move from deme to deme; and (3) migration rate, which refers to the percentage of the population likely to spread to a neighboring deme. Maps of land cover and topographic information for Brazil  were obtained from the geographical information system repository (https://www.diva‐gis.org/gdata). The altitude map was coded using distinct friction values for each cell using QGIS v 3.16.3 (http://qgis.osgeo.org). Maps were re‐sized to a layer resolution of 0.08 and exported as ASCII raster layers using the conversion tool available in the “Raster” menu, and unnecessary rows in map headers were removed using a text editor. The “land cover” map consisted of one of 22 vegetation types based on the classification by the Global Land Cover 2000 Project (GLC20000) (https://forobs.jrc.ec.europa.eu/products/glc2000/glc2000.php).Simulations of population expansion were estimated using SPLATCHE v3 . For instance, the largest relative carrying capacities at 100%, were assigned to the following vegetation types: agriculture intensive, mosaic agriculture degraded forests, mosaic agriculture degraded vegetation. The lowest carrying capacity of 0% was assigned to micro‐niches with a vegetation type unlikely to sustain whitefly populations, which are fresh water flooded forests, mangroves, barren bare soil, water bodies, and permanent snow ice.B. tabaci was “least likely” to establish, for example, in bodies of water or dense, humid tropical forested areas, and other ecosystems that are inconsistent with known B mitotype habitats. For altitude, extreme friction was set to values above 600 m a.s.l. and lowland areas were set to anticipate unimpeded flight and dispersal.The likelihood of whitefly migration rate was given as a friction value that ranged from 0 to 1, where 0 was assigned to demes with no impediments for whitefly migration, that is, migration is strong, and 1 corresponded to extreme friction, or when migration is not possible. Friction type was set to 2 to consider barriers to dispersal given by the vegetation type (land cover) and altitude. For the vegetation map, the same criteria used to define carrying capacities were used to assign friction values, with the lowest friction assigned to irrigated agro‐ecosystems  known to vary between host plants , the simulation considered minimum, maximum, and average R0 values of 19.75, 158.24, and 54.30, respectively. The values were corrected (Rc0) using the observed probability of survival in soybean fields of Brazil at 0.177 . The depictions are considered predictors of demographic expansion of the B mitotype, assuming arrival, establishment, and spread from the different predicted sites of introduction in Brazil.Indicators of reproduction, development, and survival were used to model the demographic expansion of the B mitotype in Brazil. Several studies have measured basic demographic parameters under controlled environments . Results of the mtCOI pairwise distance analysis indicated that the B. tabaci B‐mitotype sequences from Brazil diverged from those of the Ethiopia 3  and the NAFME 1–7 haplotypes by 1.8% and 0.5–1.9%, respectively  of the B mitotype analyzed from the 1989–2005 collections were found to harbor two different alleles, which corresponded to the two well‐differentiated BZ‐B1 and BZ‐B2 subclades  (40399), yielded one allele, inadvertently serving as an internal control. The B mitotype  endemic to Israel  also harbored BZ‐B1 and two alleles. In contrast, the nuclear RP‐15 sequences determined for the reference Eth3 (NAFME 3)  from Ethiopia, grouped with the BZ‐B2 subclade only.Based on phylogenetic analysis of the RP‐15 nuclear sequences, females  reference, at 1.5–2.2% pairwise distance, which was 0.1% less than the pairwise distances between the B and Q nuclear types, at 1.6–1.75%.Collectively, these results suggest that the invasive B haplotype associated with the outbreaks in Brazil, identified as NAFME 8, and the reference EN8 (NAFME 8) from Israel, could possibly represent the offspring resulting from a potentially recent hybridization event. Further, results indicate that one parent of hybrid NAFME 8 is most closely related to the B mitotype reference from Ethiopia (NAFME 1–3). The other parental allele(s) did not match any of the RP‐15 alleles determined here and further exploration was beyond the scope of this study Figure .3.2The demographic expansion predictions outward from Rio de Janeiro, the earliest record of the B mitotype presence, indicated that the B mitotype likely dispersed westwardly, unimpeded, at a speed rate of 200–500 km/year, reaching São Paulo in only 15 generations by 1990, but would have been unable in this same year to reach Ceará, the site of second oldest archived B mitotype sample (record) in Brazil Figure  were linB. tabaci to establish, consisting of micro‐niches in the Caatinga and transitional palm forest that surrounds Icapuí, Ceará, or “tropical vegetation,” from where B. tabaci samples were collected in 1990 , indicated that populations invading from this locale migrated at a slower rate than the those from Rio de Janeiro, at 100–300 km/year. The slower rate can likely be attributed to the climatic conditions there, which are unfavorable for 0 Figure . Based o0 Figure .3.3® (https://www.tropicos.org). The B. tabaci samples were collected during 1989–2005 from the following eight plant species, broccoli Brassica oleracea var. italica Plenk (n = 4), cabbage B. oleracea var. capitata L. (Brassicaceae) (n = 5), cucumber Cucumis sativus L. (n = 2), muskmelon C. melo L. (Cucurbitaceae) (n = 4), soybean Glycine max L. (Fabaceae) (n = 2), wild Solanum spp. (Solanaceae) (n = 5), unidentified Cucurbita spp. (Cucurbitaceae) (n = 2), unidentified weed species (n = 4), followed by one observation on Abelmoschus esculentus (L.) Moench , Citrullus lanatus (Thunb.) Mansf. (Cucurbitaceae), Gossypium sp. , Solanum lycopersicum (L.) H. Karst. (Solanaceae), Nicotiana tabacum L. (Solanaceae), Phaseolus sp., P. vulgaris L. (Fabaceae), and Spondias mombin L. (Anacardiaceae).The plant species binomial names were corroborated using the botanical database TropicosB. tabaci B mitotype in Brazil, was collected from broccoli plants, B. oleracea var italica, one of several host plant species not preferred by B. tabaci endemic to Brazil or elsewhere in the Americas , the oldest known museum archive of the s Brown, . The B m4B. tabaci outbreaks in São Paulo, Brazil based on the silver‐leaf symptoms observed there in pumpkin plants , and genotyped using the RP‐15 gene as a nuclear marker , a region where melon was reported to be heavily infested by B. tabaci resulting in feeding damage and outbreaks of whitefly‐transmitted viruses , in 2 years or less. The rapid geographic expansion of B. tabaci from the two independent introductions, traceable to 1989 and 1990, respectively, led to the two migrating populations to coalesce and establish a nearly country‐wide infestation by ~1991. By comparison, invasion of the US by the B mitotype, including the suspect initial sites of introduction first in Hawaii and then in Florida, required approximately 4–5 years (1986–1991) , harbored two alleles, BZ‐B1 and BZ‐B2. Further, only one of the two alleles, BZ‐B2, was recovered from the Eth3 reference (NAFME 3) from Ethiopia, suggesting the B haplotype that invaded Brazil (and elsewhere) represents a potentially recent, intra‐specific hybridization event. The NAFME region is the predicted center of origin of the B mitotype Brown, , and recRickettsia, Wolbachia, and Cardinium , suggests the possibility of unidirectional gene flow as a potential driver of selection that favored the hybridization event. Unidirectional gene flow is well‐known to be associated with increased competitive advantage of a dominant parent over a less dominant one, which can result in asymmetric mating ; Data curation ; Formal analysis ; Investigation ; Methodology ; Software ; Visualization ; Writing – original draft ; Writing – review & editing . Muriel Rizental: Conceptualization ; Data curation ; Formal analysis ; Investigation ; Methodology ; Writing – original draft . Eliane Dias Quintela: Conceptualization ; Funding acquisition ; Investigation ; Methodology ; Project administration ; Resources ; Supervision ; Validation ; Writing – review & editing . Aluana Gonçalves de Abreu: Conceptualization ; Data curation ; Investigation ; Methodology ; Resources ; Supervision ; Writing – review & editing . Judith K. Brown: Conceptualization (lead); Funding acquisition ; Investigation ; Methodology ; Project administration ; Resources ; Supervision ; Validation ; Writing – original draft ; Writing – review & editing .Table S1Click here for additional data file.


Tilapia is one of the most abundant species in aquaculture. Hypoxia is known to depress growth rate, but the genetic mechanism by which this occurs is unknown. In this study, two groups consisting of 3140 fish that were raised in either aerated (normoxia) or non-aerated pond . During grow out, fish were sampled five times to determine individual body weight (BW) gains. We applied a genome-wide association study to identify SNPs and genes associated with the hypoxic and normoxic environments in the 16th generation of a Genetically Improved Farmed Tilapia population.igf1rb, rora, efna3 and aurk were also associated with growth in the later stage in the hypoxic environment. Conversely, 13 linkage groups containing 29 unique significant and suggestive SNPs were found across the whole growth period under the normoxic environment. A meta-analysis showed that 33 SNPs were significantly associated with BW across the two environments, indicating a shared effect independent of hypoxic or normoxic environment. Functional pathways were involved in nervous system development and organ growth in the early stage, and oocyte maturation in the later stage.In the hypoxic environment, 36 SNPs associated with at least one of the five body weight measurements (BW1 till BW5), of which six, located between 19.48 Mb and 21.04 Mb on Linkage group (LG) 8, were significant for body weight in the early growth stage (BW1 to BW2). Further significant associations were found for BW in the later growth stage (BW3 to BW5), located on LG1 and LG8. Analysis of genes within the candidate genomic region suggested that MAPK and VEGF signalling were significantly involved in the later growth stage under the hypoxic environment. Well-known hypoxia-regulated genes such as There are clear genotype-growth associations in both normoxic and hypoxic environments, although genome architecture involved changed over the growing period, indicating a transition in metabolism along the way. The involvement of pathways important in hypoxia especially at the later growth stage indicates a genotype-by-environment interaction, in which MAPK and VEGF signalling are important components.The online version contains supplementary material available at 10.1186/s12864-021-07486-5. Tilapia is one of the most important species in aquaculture noted for their relative ease of culture and rapid growth. Tilapia is currently cultured in over 120 countries, mainly in the tropics and sub-tropics, with a production from 0.3 million tonnes in 1987 to closely 7 million tonnes in 2018, which makes it the second largest aquaculture species in the world , 5. The Response to hypoxia is a highly complicated biological process that has received considerable scientific attention, both in fishes and in land vertebrates . Most of these response processes happen very early at the onset of hypoxia through the activation of pathways depending on proteins that are already present . But in has1) influenced the production of hyaluronan, which can directly effect on hypoxia tolerance.Genetic adaptation to hypoxia is important for survival in many aquatic species, since variation in oxygen availability in water can vary far more, and far more rapidly, than in terrestrial ecosystems. Hypoxia is an important cause of economic losses in aquaculture. Understanding the genomic architecture of hypoxia adaptation could help to improve resilience through breeding programs for economically important species. So far, hypoxia tolerance has been studied in a limited number of fish species, including catfish , 14, AtlThere are only a few studies that focused on genetic bases of either hypoxia tolerance or growth in Nile tilapia , 19, howFish fry was produced from generation 15 of the GIFT breeding program. The experiment was carried out in an aerated (normoxic) and non-aerated  ponds, each producing 1026 and 1037 fish that were involved in the analysis. Body weight of growing fish was measured at five time points (Table The estimated phenotypic correlations for body weight between different time points in the two environments are shown in Table Oreochromis niloticus genome (GenBank accession GCF_001858045).In total 27,090 SNPs that passed SNP minor allele frequency, genotype and individuate call rate criteria, were used for subsequent analysis. Those SNPs were found to be randomly distributed across the genome with a density of approximately 28 SNP per Mb. The highest number of SNPs (4344) on LG3 while LG11 had the lowest number of SNPs (630) ) and 5.52 (−log10(0.05/16504)), respectively.Significant SNPs were detected with a univariate GWAS by implementing a linear mixed model. We observed that sex and hapa effects can explain part of the difference in body weight. Thus, these were treated as fixed factors in our analysis. Overall, five association analyses, one for each time point where body weight was measured, were performed for each environment. The Manhattan plots for each of the five time points in the hypoxic and normoxic environments are shown in Fig. In the hypoxic environment, the analyses showed 10 significant and 26 suggestive SNPs associated with BW1 to BW5 , were associated with body weight from BW3 to BW5. Moreover, two SNPs on LG8  were significant at BW4 and BW5. Notably, those SNPs located on LG8 were found at a different region compared to SNPs on the same LG in hypoxic GWAS. Hence, associations for BW1 to BW2 were different from BW4 to BW5, although BW3 shows both overlap to early and late growth stages, which could indicate that a transition in the pathways involved occurred around this stage.A meta-analysis GWAS that considered the effects of 27,090 SNPs in common in the hypoxic and normoxic environments was performed, and the results are shown in Fig. raraa, rarab, bahcc1) were significant for BW1 and BW2 for both single and across environmental GWAS.Based on the SNP association pattern for five measurements across the whole growth stage, we defined the early stage as BW1 and BW2, while the later stage is BW3 to BW5. Through gene identification within the associated genomic regions, the functional processes and pathways were subsequently enriched for single environmental and across environmental GWAS, respectively. Considering that BW3 is the transition point, SNPs that overlapped with the early stage were excluded in the functional annotation for the later stage. The candidate genes derived from single environment and across environment GWAS are shown in Fig. dock5, dock10, dock11, baiap2a, baiap2b, aurka and aurkb strongly interacting with rac1b and ppp3ca, which all are proteins participating in MAPK and VEGF signalling  terms were found to be significantly overrepresented , an orthologue also found in human, mouse and zebrafish, participates in nervous system development [Our results suggest a number of genes and metabolic pathways involved in the adaptation to differences in dissolved oxygen in Nile tilapia. In the hypoxic environment, 14 significantly enriched processes were associated with the early growth stage, including nervous system development and animal organ development. ntiation . In addiebrafish . Mediatoelopment . HoweverHIF-1α, which rapidly accumulates to activate genes involved in a series of responses to hypoxia [igf1ra, identified in this study, codes for IGF-1 receptor-a, a receptor of insulin-like growth factor that was reported to be a primary mediator of growth hormones [efna3) is shown as a key functional mediator of hypoxic microenvironment and is regarded as a therapeutic target for hypoxia-specific disease [rora) was demonstrated to be a key regulator of HIF-1α activities in human [aurka) gene, a serine kinase in neuroblastoma related to cell growth and migration, can up-regulate expression in human BE (2)-C cells under hypoxia [During the later growth stage, the results of pathway enrichment suggest that candidate regions are significantly enriched for adherens junctions, oocyte meiosis, MAPK signalling pathway, VEGF signalling pathway, regulation of actin cytoskeleton and progesterone-mediated oocyte maturation. Among these six pathways, various studies in zebrafish, channel catfish, and sea bass have shown MAPK to be involved in low oxygen tolerance in fish , 33, 34. hypoxia , 36. Thehormones . The eph disease . Retinoiin human . Finally hypoxia . Recentl hypoxia  also fou hypoxia . Additio hypoxia  has repoIn the normoxic environment, six biological processes were significantly enriched for BW1 and BW2, including retinoic acid receptor signalling pathway, apoptotic signalling pathway, liver development, signal transduction, steroid hormone mediated signalling pathway and brain development. Steroid hormone mediated and retinoic acid receptor signalling pathway overlapped with the same stage in the hypoxia environment, which seems mostly involved in general growth and development processes. The overlap in the early growth stage between normoxic and hypoxic environments may result from shared conditions until the first time point. Another possibility is that hypoxia affected small fish less, and there still was sufficient dissolved oxygen as a result of lower overall demand. As fish grew bigger, the metabolic impact of high growth on oxygen consumption and availability may have become more pronounced .mcu) that was reported to be a regulator in skeletal muscle growth and homeostasis [oit3) and MAP 6 domain containing 1 (map 3d1) were both reported to be related with calcium ion binding activity [For the later growth stage, 12 suggestive SNPs tagging regions containing 22 candidate genes were identified. These included the gene coding for mitochondrial calcium uniporter  also showed significance for single GWAS in the normoxic and hypoxic environments, respectively. Prpf38b only showed a major effect in the hypoxic environment. The orthologues of this gene in human, zebrafish and mouse have been shown to have a function in the central nerve system [raraa, rarab, and med24 were significantly associated in the meta-analysis during the later stages. Nucleotide-binding protein 2 (nump2) was reported to be associated with both IGF1 and IGFP3 in a human GWA study [The results from the meta-analysis show that five genes play a major role in growth and development during the early growth stage, namely e system . DevelopWA study . Those rWA study , similarWA study  and cattWA study , it was Moreover, no pathway related to hypoxia tolerance was found in meta-analysis GWAS, which indicates some genes affect body weight in the hypoxic environment while different subset of genes are important for body weight under the normoxic environment  installed in a 500m2 earthen pond, aerated by a paddlewheel. For each hapa, 18 male and 50 female breeders were distributed for stocking, and they were removed from mating hapa after 15 days. Fry were reared in the same hapas for 60 days until they reached a taggable size. The fingerlings from each rearing hapa were tagged and then transferred into two earthen ponds with an equal number. Overall 1570 fish were reared in each pond with stocking density of 3 fish/m2. We managed two ponds with the same feeding management , while aeration was the only different treatment between two ponds.The fish were derived from the Aquaculture Extension Centre of the Malaysian Department of Fisheries at Jitra, Kedah State, Malaysia . Genetically Improved Farmed Tilapia (GIFT) strain was used in this experiment, and it had been selected for growth based on estimating breeding value (EBV) of harvest weight, with the genetic gain ranged from 5 to 15% per generation. The mate allocation strategy has controlled inbreeding and maintained effective population size . The expWe measured DO every 2 h for 24 h with a total of 7 days during the different grow-out periods using EcoSense® DO200A. The average DO measurements for aerated pond (normoxia) and non-aerated pond  are shown in Supplementary Figure DNA extraction and genotyping procedures were described in previous study by Mengistu et al. . In shorhttps://github.com/najoshi/sickle). The quality of each individual was evaluated by FastQC (version 1.6) [Raw sequence reads were trimmed for adaptors and low quality bases with Sickle (ion 1.6) . Sequencion 1.6)  aligningion 1.6)  in a defion 1.6)  with theyij = u + αi + βj + αi ∗ βj + εij, while y is the body weight; u is the population mean; αi is the effect of the ith level of hapa; βj is the effect of the jth level of sex; ε is the random error effect. It suggested that hapa, sex and their interaction were significant with body weight. Therefore, residuals from the fixed effects model were used for the subsequent association analysis [Basic statistics of phenotype data was analysed in R (version 3.5.3). Body weight in our study is not completely following a normal distribution as estimated by Shapiro-Wilk test . Therefoanalysis .P-value were evaluated as 3.03E-06 (0.05/16504) and 6.06E-05 (1/16504), respectively.A principal component analysis (PCA) was performed to estimate population structure before GWAS in Plink (version 1.9) . The topA univariate GWAS was performed by implementing a linear mixed model in GEMMA :\documey is the a vector of observation on body weight; W is a covariate matrix of fixed effects (including top five PCs) used to adjust population structure; α is a vector of the corresponding coefficient including the intercept; x is a vector of the marker genotypes and β is the corresponding vector of marker effects for the phenotypes; μ is a vector of random effects and ε is the random residuals. We performed the Wald statistic for each SNP which means we tested the alternative hypothesis H1: β ≠ 0 compared to null hypothesis H0: β= 0 for each SNP, which is one of common methods in GWAS studies of quantitative traits [In this equation, e traits .i) for ith environment was calculated by the following equation:Meta-analysis is powerful to detect shared genetic architecture across traits and populations . Thus, wi is the standard error of the SNP effect in ith environment GWAS. Then, the effect size and standard error for ith environment GWAS were estimated by the following:Here sThe statistical significance was estimated by a z-score of IVW as bellow:https://cran.r-project.org/web/packages/qqman/). The inflation factor λ was calculated to indicate the influence of population structure in the association analyses. Candidate regions were defined as the genomic regions that located 20 kb upstream and downstream of the genome-wide significant SNPs. In order to identify candidate genes nearby the significant SNPs, we used the Custom Annotations function to create an annotation set with parameters  in Ensembl Variant Effect Predictor (VEP) [p-value of 0.05 was used to define significant enrichment.Manhattan and quantile-quantile (Q-Q) plots were generated through the “qqman” package (or (VEP) . All proor (VEP) . The falAdditional file 1: Supplementary Figure 1. Variation of dissolved oxygen in the normoxic and hypoxic environments during the 24-h cycle.Additional file 2: Supplementary Figure 2. Body weight comparison amongst four hapas in the normoxic and hypoxic environments.Additional file 3: Supplementary Figure 3. Two-dimensional plots of all individuals using SNP markers in the hypoxic environment.Additional file 4: Supplementary Figure 4. Two-dimensional plots of all individuals using SNP markers in the normoxic environment.Additional file 5: Supplementary Figure 5. Quantile-quantile plots through the whole growth stage in the hypoxic environment.Additional file 6: Supplementary Figure 6. Quantile-quantile plots through the whole growth stage in the normoxic environment.Additional file 7: Supplementary Table 1. Measurements of dissolved oxygen in the normoxic and hypoxic environments.Additional file 8: Supplementary Table 2. Information of genome-wide significant and suggestive SNPs in the hypoxic environment.Additional file 9: Supplementary Table 3. Information of genome-wide significant and suggestive SNPs in the normoxic environment.Additional file 10: Supplementary Table 4. Information of genome-wide significant SNPs across the two environments by meta-analysis.Additional file 11: Supplementary Table 5. Functional enrichment for the early stage in the hypoxic environment.Additional file 12: Supplementary Table 6. Functional enrichment for the early stage in the normoxic environment.Additional file 13: Supplementary Table 7. Functional enrichment for the whole growth stage across the two environments by meta-analysis.


CD226molecule (CD226) and neuropeptide Y (NPY) genes that could be involved in reproductive seasonality were close to the significant SNPs. To validate the results, we sequenced the entire coding region of the NPY gene and four exons of the CD226 gene to search for polymorphisms that could be involved in the phenotypes studied. Two synonymous and two nonsynonymous SNPs in the NPY and CD226 genes, respectively, were genotyped in the whole population. We demonstrated that the AA genotype of the SNP rs404360094 located in exon 3 of the CD226 gene was associated with higher and lower total days of anoestrus and oestrous cycling months, respectively. Therefore, this SNP could be utilized as a genetic marker for assisted selection marker to reduce seasonality.To elucidate the genetic basis of reproductive seasonality in Rasa Aragonesa sheep breed, we performed a genome-wide association study (GWAS) in order to detect single nucleotide polymorphisms (SNPs) or regions associated with traits related to ovarian function and behavioural signs of estrous. The GWAS included 205 ewes with genotypes for 583882 SNPs. Only one SNP overcame the genome-wide significance level. Nine potential SNPs overcame the chromosome-wise significance level (FDR 10%). Gene annotation demonstrated that CD226 molecule (CD226) gene, associated with the three traits. This gene is related to reproductive diseases. Two other SNPs were located close to the neuropeptide Y (NPY) gene, which is involved in circadian rhythms. To validate the GWAS, partial characterization of both genes by Sanger sequencing, and genotyping of two synonymous and two nonsynonymous SNPs in the NPY and CD226 genes, respectively, were performed. SNP association analysis showed that only SNP rs404360094 in the exon 3 of the CD226 gene, which produces an amino acid substitution from asparagine (uncharged polar) to aspartic acid (acidic), was associated with the three seasonality traits. Our results suggest that the CD226 gene may be involved in the reproductive seasonality in Rasa Aragonesa.A genome-wide association study (GWAS) was used to identify genomic regions influencing seasonality reproduction traits in Rasa Aragonesa sheep. Three traits associated with either ovarian function based on blood progesterone levels  or behavioral signs of oestrous (oestrous cycling months) were studied. The GWAS included 205 ewes genotyped using the 50k and 680k Illumina Ovine Beadchips. Only one SNP associated with the progesterone cycling months overcame the genome-wide significance level (rs404991855). Nine SNPs exhibited significant associations at the chromosome level, being the SNPs rs404991855 and rs418191944, that are located in the  Sheep reproduction at temperate latitudes is widely known to exhibit marked seasonality . The phoDifferences in the duration of the breeding season between breeds and between individuals within a breed raised in the same region have been reported ,6. Ewes melatonin receptor subtype 1A (MTNR1A) [arylalkylamine N-acetyltransferase (AANAT) [leptin receptor (LEPR) [MTNR1A gene. Calvo et al. [MTNR1A gene and rs403578195 in exon 8 of the LEPR gene were associated with reproductive seasonality traits in the Rasa Aragonesa sheep breed. AANAT is involved in the biosynthesis of melatonin and controls daily changes in melatonin production. Additional candidate genes involved in seasonal breeding in sheep, such as the aryl hydrocarbon receptor nuclear translocator-like protein (ARNTL), casein kinase 1 epsilon (CSNK1E), clock circadian regulator (CLOCK), cryptochrome circadian regulator 1 (CRY1), period circadian regulator 1 (PER1), period circadian regulator 2 (PER2), and neuronal pas domain protein 4 (NPAS4), have been reported in functional genomic studies of genes associated with circadian and circannual rhythms [Advances in genomic research and high-throughput genotyping techniques have enhanced the ability of researchers to search for mutations that underlie variations in complex traits ,13. Geno(MTNR1A) ,23,24,25 (AANAT) , and lepr (LEPR) . The firo et al.  and Lakho et al.  showed t rhythms ,30,31, aneuropeptide s receptor 1 (NPSR1), heparan sulfate-glucosamine 3-sulfotransferase 5 (HS3ST5), regulatory associated protein of mtor complex 1 (RPTOR), and neuronal pentraxin 1 (NPTX1), which are related to circadian and circannual rhythms. The aims of this study were the following: first, to perform a GWAS with a larger animal sample (205 ewes) using medium (50k) and high-density (680k) arrays from an Illumina Ovine Beadchip to identify new SNPs underlying sheep reproductive seasonality traits. Second, we confirmed the results obtained in the GWAS analysis through partial characterization of the genes located close to significant SNPs with putative functions related to seasonal reproduction and subsequent genotyping of some SNPs identified in these genes for association studies.As an initial attempt to identify genomic regions associated with reproductive seasonality in Rasa Aragonesa, our research group carried out a GWAS using 110 ewes genotyped by the Illumina OvineSNP50 Beadchip . SeveralPhenotypic seasonality data were collected from an experimental flock of Rasa Aragonesa sheep, described by Martinez-Royo et al. . Flock mIn Martinez-Royo et al.  are repohttps://www.usc.es/cegen/; accessed on 19 April 2021) and “Xenetica Fontao” company .The GWAS included 110 ewes genotyped with the OvineSNP50 Infinium Beadchip  designed by the International Sheep Genome Consortium , as emplp-Value < 0.001) were excluded. Next, the two datasets were merged with PLINK 1.9, and the Beagle4.0 program [2 < 0.2 over a window size of 50 SNPs, and a step of 10 SNPs. Genome-wide identity-by-state (IBS) pairwise distances were calculated using all SNPs that remained after pruning. A pairwise population concordance test constraint was applied to the clustering procedure (-ppc option). GWAS was performed using the GCTA  program [2 divided by the expected median χ2.The software Plink1.9  was used program  was used program  running  program . The cho program . To contGenes located within a 500 kb-long interval centered on the significant SNPs associated with the three seasonality traits were obtained according to the sheep genome assembly (Oar_v3.1) and based on Ensembl release 81.CD226 and NPY genes could be involved in reproductive seasonality. The ovine CD226 gene is located on chromosome 23, covering approximately 100.7 kb with 6 exons (GenBank acc. Number NC_040274), whereas the NPY gene is located on chromosome OAR4 and covers approximately 6.8 kb with 4 exons (GenBank acc. Number NC_040255). All exons of the NPY gene were characterized, while four exons were chosen to characterize the CD226 gene. The significant SNPs were located in intron 2 of CD226, approximately 52 and 4 kb from exons 2 and 3, respectively. These exons were selected because they have nonsynonymous polymorphisms in the Ensembl Variation database  of the Oar 3.1 version of the sheep genome. Primer3 software was used to design the primers . Target-specific primers were designed in intron-flanking regions around the targeted exon. 2, 50 mM KCl, 10 mM Tris-HCl, 0.1% Triton X-100, and 1 U Taq polymerase . The following cycling conditions were used for all amplification fragments: an initial denaturation step of 94 °C for 3 min followed by 35 cycles of PCR, with cycling conditions of 30 s at 94 °C, 30 s at annealing temperature, and 30 s at 72 °C, and a final extension step of 72 °C for 5 min.Gene annotation based on the results of GWAS demonstrated that n = 6; intermediate TDA: 56 ± 19.8 days, n = 6; high TDA: 142.3 ± 15.7 days, n = 6) was utilized to look for polymorphisms in the experimental population. The PCR products were purified using the FavorPrep Gel/PCR purification mini kit , and sequenced in both directions by STAB Vida company  using an ABI 3730XL sequencer . Homology searches were performed using BLAST . To align the sequences, BioEdit [http://www.ebi.ac.uk/Tools/msa/clustalo/; accessed on 19 April 2021) were used. The impact of amino acid substitution on the structure and function of the protein was predicted using the PolyPhen-2  [http://www.ensembl.org/Ovisaries/Tools/VEP?db=core; accessed on 19 April 2021) softwares. The locations of SNPs were determined based on the genome version of Ovis aries Oar_v3.1.Direct Sanger sequencing of the PCR products from the 8 exons in 18 ewes with extreme and intermediate values for TDA  following the manufacturer’s instructions: one in exon 2 (rs588529642) and the second in exon 3 (rs404360094). The sequence surrounding the target polymorphism was submitted for assay design to the KASP genotyping provider . Assays were performed in 96-well formats in a 10 μL volume containing 1 µL of DNA , 5 µL of 2X KASP V4.0 master mix standard ROX , 0.14 µL of assay mix  and 3.86 µL nuclease-free water. Reactions were performed in a CFX96 Bio-Rad thermocycler  with conditions as follows: 94 °C for 15 min followed by 9 touchdown cycles of 94 °C for 20 s and 57 °C for 60 s (decreasing −0.6 °C per cycle) followed by 25 additional cycles of 20 s at 94 °C and 60 s at 55 °C. Following PCR, the plate was cooled to 30 °C, and fluorescence was read using a single quantification cycle for 1 s.Genomic DNA was extracted from blood samples of 265 ewes of the flock using standard protocols. Two nonsynonymous SNPs in the NPY gene failed. Therefore, the two synonymous SNPs located in exon 2 of the NPY gene  were genotyped by Sanger sequencing  [CD226 and NPY SNPs were independently analysed with the same statistical model.Haploview software v4.2  was usedil 2021) , includi2 within the CD226 and NPY were estimated. SNPs were phased using the expectation-maximization (E–M) algorithm to assign individual haplotypes with PLINK1.9 [Haploview software v4.2 was used to define blocks of LD based on the 4-gamete rule . D’ and PLINK1.9 . DiplotyAfter the QC was performed on the imputed genotypes, 205 ewes with genotypes for 583882 SNPs distributed on the 27 ovine chromosomes were retained for subsequent analyses. In the MDS analysis, 188633 autosomal SNPs were used to calculate the pairwise IBS distance after SNP pruning. MDS analysis revealed a substructure within the total dataset and identified 4 principal clusters in the analysed population . These cp = 0.07). p < 0.10) with TDA, P4CM, and OCM traits, respectively . The significant SNPs for P4CM in chromosome 4 were located 35 (rs424340754) and 47 kb (rs410373132) from NPY and were completely linked. The SNPs rs404991855 and rs418191944 were located in intron 2 of CD226.Only one significant SNP (rs404991855) for P4CM was found at the genome-wise significance level after Bonferroni correction . In the ectively . Two SNPectively . The sevectively c. Finallectively b. The geNPY gene and four exons of the CD226 gene to search for polymorphisms that could be involved in the phenotypes studied. No deleterious mutations were detected. For the NPY gene, we found two synonymous SNPs in exon 2. One of these mutations was not previously described (OAR4:g.71593018 G > T) (We sequenced the entire coding region of the 8 G > T) . These S8 G > T) . AlthougCD226 gene, three SNPs were detected in exon 2 , and one SNP was detected in exon 3 (rs404360094). Two of these SNPs (rs588529642 and rs404360094) were nonsynonymous substitutions and were selected to be genotyped in the whole population. These SNPs were predicted in silico to be tolerated by VEP and benign by PolyPhen-2, showing that the SNP located in exon 2 (rs588529642) had a lower SIFT value (0.1) (For the ue (0.1) . This SN2 between the pairwise combination of the SNPs in the same chromosome. Very low LD was found. LD indices for SNPs located in the CD226 gene were 0.06 and 0 for D’ and r2, respectively. For SNPs located in the NPY gene, 1 and 0.002 were observed for D’ and r2, respectively. One haplotype block was predicted for SNPs located in exon 2 of the NPY gene.To determine the extent of LD among these markers, we estimated the parameters D’ and rCD226 gene was significantly associated with the three reproductive seasonality traits (see p < 0.01) or GG  genotypes. Similarly, ewes with the AA genotype showed fewer oestrous records than those with AG  or GG (−0.13 ± 0.05). Similar results were observed for the P4CM trait.Association analyses included 265 ewes. NPY gene), and a second block containing the two nonsynonymous SNPs of the CD226 gene (block 2). Three haplotypes were identified for each block (G) had lower TDA and more oestrous records than those without copies . This haplotype contains the G allele of the SNP located in exon 2 (rs418191944), which is associated with lower TDA and higher P4MC and OCM values. Conversely, ewes with 2 copies of haplotype H2 (AA) had more TDA and fewer oestrous records.Haplotype association studies were performed, considering block 1, which was predicted with Haploview , one in an intergenic region approximately 412 kb from the CD226 gene (rs405024177), and one in a different intergenic region in chromosome 23 (rs410842314).Nine potential SNPs reaching the chromosome-wise level of significance were identified to be associated with the TDA, P4CM, and OCM reproductive seasonality traits. Only one SNP (rs404991855) associated with P4CM overcame the genome-wide significance level. The SNPs rs404991855 and rs418191944 on chromosome 23 appeared to be associated with the three traits and were located in intron 2 of the n humans ,47. On tght loss . Three oNPY and CD226 genes have been reported in other studies to be potentially associated with reproductive processes. NPY plays a role in the regulation of the secretion of gonadotropin releasing hormone (GnRH) in rats [NPY stimulates feed consumption and inhibits reproduction in sheep. However, Miner [CD226 gene encodes the glycoprotein CD226, also known as DNAM-1 (DNAX Accessory Molecule-1), which is expressed on the surface of natural killer (NK) cells and is involved in T cell-mediated cytotoxicity against certain tumours [16 and CD56: CD56bright/CD16– functioning to primarily produce cytokines in the circulating blood, and CD56dim/CD16+ performing cytotoxicity in the tissues [56dim/CD16+ NK cells in follicular fluid (FF) in women suffering from idiopathic infertility is significantly higher than that in FF from patients undergoing in vitro fertilization (IVF) for tubal or male factor infertility. Furthermore, Křížan et al. [56bright/CD16– NK cells. Additionally, Fainaru et al. [56bright CD16– NK cells are abundant in maturing ovarian follicles and that their presence correlates with the ovarian response to gonadotropins. These cells have been shown to be proangiogenic through the secretion of such cytokines as vascular endothelial growth factor and placental growth factor [56bright NK cells migrate into the ovarian follicle, supporting follicular angiogenesis and oocyte development [56dim NK cell subset characterized by a lack of expression of DNAM-1. These researchers reported that CD56dimDNAM-1neg NK cells displayed reduced motility, poor proliferation, lower production of interferon-γ, and limited killing capacities compared with CD56bright and CD56dimDNAM-1pos NK cell subsets.The  in rats , rabbits in rats , monkeys in rats , and she in rats ,53. It h in rats . In the  in rats  indicate in rats  reported in rats  noted th in rats . Clarke  in rats  determinr, Miner  showed t tumours . NK cell tumours ,62. NK c tissues ,64. Luka tissues  have shon et al.  reportedu et al.  indicateh factor . In patielopment . Recent elopment  describeCD226 could lead to glycoprotein alteration and could therefore affect follicle development. Additionally, mutations in the NPY gene would explain one of the neuroendocrine and physiological mechanisms that link nutrition and reproduction. Accordingly, the NPY and CD226 genes were selected for validation studies for their possible involvement in seasonal reproduction in sheep. Using 18 ewes with extreme values of TDA, we detected 2 and 4 SNPs in NPY and CD226, respectively . Notably, we did not sequence regulatory regions, such as the promoter or 5’ and 3’ UTR regions. Therefore, we could have missed the responsible mutation, as it was not in LD with the detected mutations. Similarly, no association was found with the SNP located in exon 2 of the CD226 gene. Importantly, no homozygous animals were found for the G allele, and a low MAF was found for this SNP (0.042). However, the analysis demonstrated that the SNP located in exon 3 of CD226 (rs404360094) was associated with the three reproductive seasonality traits. Notably, this SNP is close and in LD with the significant SNPs found in intron 2 in the GWAS analysis . In this sense, the GWAS analysis could have detected the effect found in exon 3 of CD226. Heterozygous and homozygous ewes for the G allele had less TDA and showed more oestrous events than those with the AA genotype (CD226 gene; thus, the observed relationship could indicate that the SNP should be in LD with the true causative mutation.In this study, no association was found with the genotype , which wgenotype . These rCD226 gene reached the chromosome-wise significance threshold on chromosome 23 using the GWAS approach. As noted above, because this gene could be related to follicular angiogenesis and oocyte development in humans, we decided to confirm the GWAS results using a candidate gene approach, determining that the SNP rs404360094 located in exon 3 of the CD226 gene was associated with reproductive seasonality traits in Rasa Aragonesa ewes. Therefore, this SNP could be utilized as a genetic marker for assisted selection to reduce seasonality. These results should be confirmed in more animals and in other breeds.In summary, GWAS results were confirmed using a candidate gene approach. First, two SNPs located in intron 2 of the CD226 gene is associated with lower TDA and higher P4CM, which are both traits related to ovarian function based on blood progesterone levels. This allele was also associated with higher OCM scores, which is an indicator of oestrous behaviour. These findings enabled us to validate the GWAS results and demonstrated the involvement of the genomic region where the CD226 gene is located. This SNP could be utilized as a genetic marker along with other SNPs already characterized in Rasa Aragonesa as being associated with traits related to reproductive efficiency, such as prolificacy or reproductive seasonality.This study employed a GWAS approach to identify genomic regions associated with traits involved in reproductive seasonality in sheep. We demonstrated that the G allele of the SNP rs404360094 located in exon 3 of the


The carcass value of cattle is a function of carcass weight and quality. Given the economic importance of carcass merit to producers, it is routinely included in beef breeding objectives. A detailed understanding of the genetic variants that contribute to carcass merit is useful to maximize the efficiency of breeding for improved carcass merit. The objectives of the present study were two-fold: firstly, to perform genome-wide association analyses of carcass weight, carcass conformation, and carcass fat using copy number variant (CNV) data in a population of 923 Holstein-Friesian, 945 Charolais, and 974 Limousin bulls; and secondly to perform separate association analyses of carcass traits on the same population of cattle using the Log R ratio (LRR) values of 712,555 single nucleotide polymorphisms (SNPs). The LRR value of a SNP is a measure of the signal intensity of the SNP generated during the genotyping process.U6 which encodes a spliceosomal subunit and 5S rRNA which encodes a ribosomal subunit.A total of 13,969, 3,954, and 2,805 detected CNVs were tested for association with the three carcass traits for the Holstein-Friesian, Charolais, and Limousin, respectively. The copy number of 16 CNVs and the LRR of 34 SNPs were associated with at least one of the three carcass traits in at least one of the three cattle breeds. With the exception of three SNPs, none of the quantitative trait loci detected in the CNV association analyses or the SNP LRR association analyses were also detected using traditional association analyses based on SNP allele counts. Many of the CNVs and SNPs associated with the carcass traits were located near genes related to the structure and function of the spliceosome and the ribosome; in particular, The present study demonstrates that CNV data and SNP LRR data can be used to detect genomic regions associated with carcass traits in cattle providing information on quantitative trait loci over and above those detected using just SNP allele counts, as is the approach typically employed in genome-wide association analyses.The online version contains supplementary material available at 10.1186/s12864-021-08075-2. The carcass value of cattle in most jurisdictions is a function of the carcass weight, with additional premia paid for animals that meet particular specifications on age, breed-type, and certain carcass conformation and carcass fat metrics , 2. The 2 of the observed fluorescence intensity of the SNP divided by the expected fluorescence intensity of the SNP [One of the key metrics used to detect CNVs from SNP array data is the normalized fluorescence intensity of the SNP. The fluorescence intensity reported on Illumina genotype platforms is measured by the log R ratio (LRR) value, where the LRR value of a SNP is the log the SNP . The exp the SNP . To the  the SNP  used the the SNP  did, howThe objectives of the present study were two-fold: firstly, to perform association analyses of carcass traits in cattle using CNV copy number, and secondly to perform separate association analyses of carcass traits on the same population of cattle but using SNP LRR values. Of interest for both of these objectives was whether or not any discovered associations could also be detected using only the allele count data for individual SNPs, as this is the approach most commonly undertaken in genome-wide association analyses.Four different association analyses were carried out in the present study, with the models applied differing only by the independent variable in the model. The four models evaluated included each carcass trait as the dependent variable but the independent variable was either the CNV copy number for a given detected CNV, the SNP LRR per SNP or, at a chromosomal level, the proportion of the chromosome with a called CNV or the mean SNP LRR per chromosome. The single CNV and SNP LRR association analyses were used to identify individual CNVs and SNP LRRs associated with carcass traits while both the CNV proportion and mean LRR per chromosome analyses were used to determine if overall CNV burden, or mean LRR as a metric possibly reflective of CNV burden, associated with carcass merit.P = 0.0002) with carcass conformation in the Holstein-Friesians; with this exception, there was no other detected association with the proportion of the chromosome with a called duplication CNV or the proportion of the chromosome with a called deletion CNV. The mean LRR of chromosome 13 was positively associated with carcass conformation in Holstein-Friesians (P = 0.0006); the regression coefficient for the relationship between carcass conformation and mean LRR of chromosome 13 was 1.059 (SE = 0.307). The mean LRR of all other chromosomes was not associated with any of the carcass traits in any breed.The proportion of the chromosome with a called CNV (either deletion or duplication) did not associate with any of the carcass traits in any of the three breeds. The proportion of chromosome 20 with a called duplication CNV was negatively associated  were associated with the carcass trait in question (P > 0.05). The same approach was used to determine if the called allele counts of any SNP located within 500 kb upstream or downstream of associated SNP LRRs (including the SNP itself) were also associated with the trait in question. For each of the associated SNP LRRs, there were between 164 and 486 SNPs located within the genomic region encompassing 500 kb upstream and downstream of the associated SNP LRR. The alleles of 30 SNPs located between 6.55 Mb and 8.43 Mb were associated with carcass fat in the Charolais; these 30 SNPs were located within 500 kb of two SNPs with LRRs also associated with carcass fat in the Charolais. The allele count of a single SNP located on chromosome 26 at 27.08 Mb was associated with carcass weight in Holstein-Friesians; this SNP was located 284.9 kb downstream of a SNP whose LRR value also associated with carcass weight in the Holstein-Friesians. There were 75 other SNPs located within the 284.9 kb region between the SNP associated by allele count and the SNP associated by LRR; none of these 75 SNPs associated with carcass weight in the Holstein-Friesians by either allele count or LRR. For all other detected SNP LRR associations, there was no SNP within 500 kb associated by allele count with the trait in question.A total of 72 genes overlapped in genomic position with the QTL regions of the 16 associated CNVs. The DAVID algorithm reported that there was no gene-set enrichment in this set of 72 genes. A total of 163 genes overlapped in genomic position with the QTL regions of the associated SNP LRRs, and there was no gene set enrichment in these 163 genes.Carcass weight, carcass conformation, and carcass fat are key components of carcass value and have a direct impact on the profitability of beef farming . ConsideWhile several previous studies have attempted to relate SNP allele count data to carcass traits , 8, 29, In the chromosome-based association analyses, four different analyses were conducted. Within each of these analyses, the 29 autosomal chromosomes were separately tested for an association with each of the three carcass traits in the three different breeds; this amounts to 1,044 individual tests. Given that an association was detected for only two of these tests , it suggests that these results may not reflect true associations but rather were spurious associations due to noise in the data.A single CNV located on chromosome 25 at 15.58 Mb was associated with all three carcass traits but just in Holstein-Friesians (Table P = 3.715 × 10− 6 prior to multiple testing adjustment) was not above the threshold for significance after adjusting for multiple testing albeit there was a strong association. The lack of QTLs shared across the different breeds or traits for either the associated CNVs or the associated SNP LRRs is broadly consistent with the literature using SNP allele count in the association analysis of carcass traits in cattle, where the majority of associated SNPs are only associated with one particular carcass trait within a single breed [Although no SNP LRRs were associated with more than one trait, the SNP LRR with the strongest association with carcass fat in Charolais, located on chromosome 2 at 6.85 Mb, was also the SNP LRR with the strongest association with carcass conformation in the Charolais. However, this association with carcass conformation  subunit of the ribosome [The genes near or nearest to an associated CNV or SNP LRRs were often components of the spliceosome or the ribosome Tables , 3 and 4ribosome , were loU6 and 5S rRNA genes with associated CNVs and SNP LRRs indicates that these genes may be associated with carcass traits in cattle. However, it could be the case that these genes were often located near associated CNVs and SNP LRRs because they are enriched in genomic regions frequently subject to copy number variation, due to the fact that there are multiple copies of these genes in the cattle genome. Other cattle studies have also reported that U6 and 5S rRNA are under positive selection, and are also associated with carcass traits. Both U6 and 5S rRNA genes have been demonstrated to be under positive selection in North African cattle [5S rRNA and U6 may be candidate genes for dry matter intake in a multi-breed population of cattle. Additionally, Wang et al. [U6 may be a candidate gene for average back fat thickness and carcass marbling, and 5S rRNA may be a candidate gene for carcass marbling in a multi-breed population of cattle. In addition to 5S rRNA, other genes related to the structure and function of the ribosome have also been associated with carcass traits in cattle. The RPS20 gene, which encodes a protein that is part of the structure of the ribosome [L27a, a ribosomal subunit, are associated with marbling in Japanese cattle [The close genomic proximity of several distinct copies of n cattle , as welln cattle . Zhang en cattle  reportedg et al.  reportedribosome , is assoribosome . Mutatioe cattle . Similare cattle .Genomic regions associated with carcass traits in cattle were identified using both CNV and SNP LRR data, which, for the vast majority, would not have been detected using traditional genome wide association approaches based on SNP allele counts. Hence SNP allele counts, SNP LRR data, and CNV data could be complementary in detecting genomic regions associated with performance. Although only a small proportion of the genetic variability in the carcass traits was captured with these two new variant types, the same may not be true for other populations or traits; moreover, improvements in the calling of CNVs in particular could possibly improve the strength of the association analyses.All animals were genotyped using the Illumina BovineHD SNP array  ; the positions of all SNPs were taken from the UMD 3.1 build of the bovine genome . Only anEstimated breeding values (EBVs) and associated reliability estimates for carcass weight, carcass fat, and carcass conformation were obtained for each animal from the January 2019 national genetic evaluation of the Irish Cattle Breeding Federation (ICBF) . In Ireland, carcass weight is the weight of the carcass after the head, limbs, hide, internal organs, and visceral fat are removed from the carcass . CarcassDuring the genotyping process, when a DNA molecule complementary to a particular SNP binds to the SNP array it precipitates a fluorescence reaction; the intensity of this reaction is recorded in the log R-ratio (LRR) statistic . The LRRA CNV was considered to have been called by both PennCNV and QuantiSNP when the endpoints of the CNV called by one algorithm, were no more than 1 SNP from the endpoints of the CNV called by the other algorithm. This difference of 1 SNP was allowed for because if there is an error in endpoint demarcation, the true endpoint of the CNV is typically only one SNP away , 67. CopThe population structure for each breed was inferred using the method described by Patterson et al.  using thThe present study consisted of four separate sets of association analyses of carcass weight, carcass fat, and carcass conformation; two were based on aggregate metrics per chromosome with the remaining two being undertaken for individual CNV or SNP. The four separate analyses differed by the independent variable in the model which were: (1) the mean LRR per autosomal chromosome, (2) the proportion of each chromosome that had a called CNV, (3) the CNV copy number, and (4) the SNP LRR value. The proportion of the chromosome that had a called CNV was calculated per animal as the combined genomic length of all CNVs on the chromosome divided by the genomic length of the chromosome. This calculation was also repeated separately using only called deletion CNVs to obtain the proportion of the chromosome with a called deletion CNV; similarly, the proportion of the chromosome with a called duplication CNV was calculated separately using only called duplication CNVs. The genomic length of the chromosome was calculated as the genomic distance between the first and last genotyped SNP on the chromosome.The motivation for the CNV copy number association analysis was to determine if individual CNVs were associated with any of the three carcass traits considered. Similarly, the purpose of the SNP LRR association analysis was to determine if individual SNP LRR data can be used to identify genomic regions associated with carcass traits in cattle. Furthermore, it was of interest to determine if common genomic regions existed between those identified by the CNV copy number and those with SNP LRR, since SNP LRR is an important statistic for detecting CNVs from SNP array data. There may be an association between CNV burden and traits of interest; for example, previous studies in humans have reported associations between CNV burden and both autism spectrum disorders and schizophrenia , 73. TheEach association analysis was undertaken separately for each of the three breeds and each of the three carcass traits using the R package lme4qtl . A lineadEBV was the vector of deregressed EBVs, µ was a vector representing the intercept term, and gi was a vector of the ith independent variable in the model. In the mean LRR value per chromosome analyses, gi was a vector of mean LRR value per animal for the ith chromosome treated as a continuous fixed effect while in the analyses of the proportion of the chromosomes with a called CNV, gi was a vector of the proportion of the chromosome with a called CNV for the ith chromosome treated as a continuous fixed effect. In the CNV association analyses, gi was a vector of the copy number for the ith CNV treated as a categorical fixed effect, while in the SNP LRR association analyses, gi represented a vector of LRR values for the ith SNP treated as a continuous fixed effect. In all models, u represented the polygenic effect of each animal in the population treated as a random effect and e represents a vector of random residual effects. In all models, X and Z were design matrices that related the fixed and random effects to each animal record. In all models, population stratification was accounted for by fitting a direct additive genetic effect via a genomic relationship matrix. Method 1 of VanRaden [u, was assumed to have the distribution N based on the ARS_UCD1.2 build of the bovine genome [For gene-set enrichment analysis, a QTL region flanking each of the associated CNVs and SNP LRRs was specified as the genomic region spanning 500 kb upstream and 500 kb downstream of the associated CNV or SNP. The genomic position of each associated SNP LRR was updated per the ARS_UCD1.2 assembly of the bovine genome . For eace genome . The lise genome . The DAVAdditional file 1:Table S1. The P-value for the association between each of the associated CNVs with each of the three traits across all three breeds. The genomic location column is formatted chromosome, start position bp, end position bp. Where a value of NA is given, the CNV was not tested for the given breed and trait due to insufficient population frequency of the CNV in that population.Additional file 2: Table S2. The number of animals available for each breed and trait, the mean effective record contribution (ERC) per animal, and the sum of the ERCs for all animals available for each breed and trait.Additional file 3: Figure S1. Manhattan plots for copy number variants (CNVs) associated with carcass weight in A) Charolais B) Holstein-Friesians C) Limousins. The red line represents the significance threshold for each of the three breeds.Additional file 4: Figure S2. Manhattan plots for copy number variants (CNVs) associated with carcass fat in A) Charolais B) Holstein-Friesians C) Limousins. The red line represents the significance threshold for each of the three breeds.Additional file 5: Figure S3. Manhattan plots for copy number variants (CNVs) associated with carcass conformation in A) Charolais B) Holstein-Friesians C) Limousins. The red line represents the significance threshold for each of the three breeds.Additional file 6: Table S3. The mean, standard deviation, minimum, and maximum of the deregressed estimated breeding values (EBVs) for each trait for each of the three breeds.Additional file 7: Table S4. Median, mean, and standard deviation of the number of CNVs per animal, referred to as count, and the length of CNVs within breed.