Ovis canadensis), pneumonia epidemics caused by Mycoplasma ovipneumoniae have been associated with severe population declines and limited recovery across North America. Adult survivors either clear the infection or act as carriers that continually shed M. ovipneumoniae and expose their susceptible offspring, resulting in high rates of lamb mortality for years following the outbreak event. Here, we investigated the influence of genomic composition on persistent carriage of M. ovipneumoniae in a well‐studied bighorn sheep herd in the Wallowa Mountains of Oregon, USA. Using 10,605 SNPs generated using RADseq technology for 25 female bighorn sheep, we assessed genomic diversity metrics and employed family‐based genome‐wide association methodologies to understand variant association and genetic architecture underlying chronic carriage. We observed no differences among genome‐wide diversity metrics  between groups. However, we identified two variant loci of interest and seven associated candidate genes, which may influence carriage status. Further, we found that the SNP panel explained ~55% of the phenotypic variance (SNP‐based heritability) for M. ovipneumoniae carriage, though there was considerable uncertainty in these estimates. While small sample sizes limit conclusions drawn here, our study represents one of the first to assess the genomic factors influencing chronic carriage of a pathogen in a wild population and lays a foundation for understanding genomic influence on pathogen persistence in bighorn sheep and other wildlife populations. Future research should incorporate additional individuals as well as distinct herds to further explore the genomic basis of chronic carriage.Genetic composition can influence host susceptibility to, and transmission of, pathogens, with potential population‐level consequences. In bighorn sheep ( Bighorn sheep populations impacted by infectious pneumonia may experience long‐term recovery complications due to chronically infected individuals shedding pathogen and suppressing lamb recruitment in years following outbreak events. We investigated genetic associations with the chronic carrier phenotype in bighorn sheep to better understand underlying dynamics influencing pathogen persistence in wild sheep populations. Heterogeneity in these characteristics can produce a subset of individuals that contribute disproportionately to disease dynamics. For example, highly infectious individuals may act as superspreaders, resulting in disproportionately more new infections relative to other less infectious individuals  analyses. Genome‐wide association methods have been used to better understand the underlying architecture of disease  and to identify single nucleotide polymorphisms (SNPs) that may be associated with disease phenotypes  populations across western North America. Specifically, pneumonia epizootics  have caused all‐age die‐off events of varying severities , with the most extreme resulting in 100% mortality and localized extirpation  may play a role in infection clearance  of individuals was periodically recaptured, allowing for assessment of longitudinal infection status. The sampling regime focused on ewes, given the research interests of the study for which these data were collected  in the Lostine herd were baited with alfalfa pellets and captured in a corral trap or chemically immobilized using a jab stick or dart gun. Individuals were aged and given a unique marker for recapture, and samples were collected including skin tissue, blood, and nasal swabs  individuals that tested positive and negative in consecutive captures, that is, infected and recovered, were given the status “intermittent”; and (iii) individuals that tested positive in two consecutive sampling events across two or more years were given the status of “chronic carrier”  individuals that consistently tested negative for r” Table   data were available from a previous parentage study of the Lostine herd, including 52 individuals with longitudinal disease data . Remaining reads were demultiplexed and cleaned using PROCESS_RADTAGS in STACKS v2.2  genome (Oar v4.0) using end‐to‐end alignment methods in Bowtie2 v2.3.5.1  and old (≥14) individuals  class I through III genes are located—on chromosome 20. Ovar‐Mhc SNPs were identified from base 7,166,117 to 27,665,927 spanning the locations of the DYA to OLA genes based on our current understanding of the Ovar‐Mhc region structure and location in domestic sheep  was calculated for each individual using the  Coulon, . The sta2.6M. ovipneumoniae negative  and M. ovipneumoniae carriers  and analyzed using the following model  for each SNP. The p‐value significance threshold was adjusted using Bonferroni correction resulting in a threshold of 4.71 × 10–6. Further, as the Bonferroni method can be overly conservative, we controlled for type I errors by using false discovery rate (FDR) methodology, whereby new significance values  and threshold are defined: in this case, we use α = 0.15   and the domestic sheep genome .Genes with potential for influencing carrier status were identified as any genes located within a 500 kb window (up‐ or down‐ stream) of SNPs associated with persistent carriage. This window is based on linkage decay reported for this RADseq dataset  calculations.We implemented an overrepresentation test using PANTHER , and ϵ is a vector of errors. The BSLMM estimates the proportion of variance in phenotypes explained by the SNPs using xβ and u  and estimates a parameter rho whereby values close to 0 imply a polygenic architecture and values close to 1 imply oligogenic structure  or oligogenic , a Bayesian sparse linear mixed model (BSLMM) was implemented in GEMMA v0.98.1  were identified and included in the genome‐wide association analysis. Of these, n = 151 SNPs occurred within the MHC gene complex, including n = 124 SNPs in the MHC class II region and n = 27 SNPs in the MHC class III region (no SNPs occurred in the MHC class I region). Details regarding final SNP locations and coverage across chromosomes can be found in Data carrier = 1.03, meancontrol = 1.04, t=−0.32, df = 6.03, p = .76). Further, there was no difference in observed population‐level heterozygosity between carrier and control groups for the 10,605 loci , or for loci that fell within the Ovar‐Mhc region . The mean allelic richness across all 10,605 loci was 1.55 (variance 0.14) and 1.55 (variance 0.10) for carrier and control groups, respectively , and mean private allelic richness was 0.17  for both groups when rarefaction subsample size was set to 6. Similarly, no difference in allelic richness was observed across loci within the Ovar‐Mhc region: mean allelic richness across was 1.51 (0.15 variance) and 1.51 (variance 0.12) for carrier and controls , and mean private allelic richness was 0.16 .A total of 98,307 variant loci were identified using genomic data from 52 bighorn sheep (19 carriers and 33 control genotypes). After quality filtering of the sequence data see Data , a total3.2GHSR) on chromosome 1. Further, within the 500 kb up‐ and down‐stream window of this SNP, there were five genes of interest , 1,709 molecular functions, and 879 cellular mechanisms in the human genome. After FDR corrections, no gene ontology terms were found to be overrepresented in any of the three categories.3.4n = 16 SNPs) having a relatively large effect, explaining 45.2%  of phenotypic variance  of the phenotypic variance, with a select few —as assessed by heterozygosity at several microsatellite loci—were found to be more susceptible to gastrointestinal parasites  genome (Oar v4.0). Of these seven, six genes—ECT2, NCEH1, TNFSF10, FNDC3B, GHSR, and SEMA6D—have either been observed at elevated expressions in tumor cells or have been documented acting as oncogenes for specific cancers in humans (genes that can transform cells into tumor cells). Changes in expression of these genes may influence tumor regulation in the bighorn sheep host.Seven candidate genes were identified nearby to the SNPs associated with chronic carrier status, using the annotation of the domestic sheep (M. ovipneumoniae) carriage in the upper respiratory tracts of bighorn sheep in a Colorado population . These findings suggest that sinus tumors may disrupt the host's ability to clear pathogens, allowing for maintenance of chronic infections in the upper respiratory tract and potential prolonged shedding  and neoplasm exudate  , and each of these individuals had sinus tumors Table . The pre4.3M. ovipneumoniae carrier status in bighorn sheep. One variant was located in the 5’ untranslated region  of the growth hormone secretagogue receptor (GHSR) gene. The GHSR gene encodes a G‐protein‐coupled receptor that binds ghrelin, a peptide hormone, and is most widely recognized for its role in energy metabolism and growth .Two SNP variants were identified as being associated with GHSR gene have been of interest for selective breeding potential and quality assessment. Polymorphisms identified in the 5’ untranslated region of the GHSR were associated with increased carcass weight and average daily gain in domestic cattle  suggests the ghrelin/GHSR pathway may have a role in generating or controlling immune response   in the carriage phenotype, with large‐effect variants contributing to approximately 25% of the total phenotypic variance . However, there is considerable uncertainty surrounding both estimates: the number of large‐effect SNPs could not be quantified with confidence, likely due to our relatively small sample sizes. Our results preliminarily suggest that more SNPs may have a large effect on the carrier phenotype than just the two identified in our analysis. However, our confidence intervals were broad, and additional studies with increased sample sizes would be required to fully characterize the genetic architecture of the carrier phenotype. A greater understanding of the numbers and effect sizes of genetic variants that influence resistance would allow managers to better assess the utility of using genomic screening moving forward. Specifically, the presence of few, large‐effect SNPs would allow for more focused carrier screening, as opposed to many, small effect variants spread across the genome.4.5M. ovipneumoniae tests performed per individual may have influenced carriage status. As there is a general U‐shaped trend for chronic carriage and age  technology. We observed no difference in genome‐wide diversity  between phenotypes. However, we did identify two variant loci and seven genes associated with carrier status, and six of these genes have functions related to tumor regulation. This result suggests potential causative links between genomic composition, tumor susceptibility, and pneumonia carriage. Support for this causative association comes from previous studies indicating a connection between paranasal sinus tumors and pneumonia in bighorn sheep. However, we observed no overrepresentation in our gene ontology analysis, and our interpretations are limited by our small sample size. This study provides a starting point for understanding the genomic basis and biological mechanisms underlying inability to clear infection in bighorn sheep, both of which are poorly understood but could provide important insight for understanding factors contributing to chronic pathogen carriage and potentially contributing to effective management strategies to combat pneumonia in bighorn sheep populations.Here, we investigated the influence of genomic composition on persistent carriage of The authors declare no competing interests.Alynn Martin: Conceptualization ; Formal analysis ; Methodology ; Writing‐original draft ; Writing‐review & editing . E. Frances Cassirer: Conceptualization ; Data curation ; Funding acquisition ; Investigation ; Project administration ; Resources ; Writing‐original draft ; Writing‐review & editing . Lisette Waits: Conceptualization ; Data curation ; Funding acquisition ; Project administration ; Resources ; Supervision ; Writing‐review & editing . Raina K Plowright: Conceptualization ; Data curation ; Funding acquisition ; Investigation ; Writing‐review & editing . Paul Cross: Conceptualization ; Resources ; Supervision ; Writing‐review & editing . Kimberly Andrews: Conceptualization ; Data curation ; Formal analysis ; Funding acquisition ; Investigation ; Methodology ; Project administration ; Supervision ; Writing‐original draft ; Writing‐review & editing .Supplementary MaterialClick here for additional data file.


Setophaga townsendi and Setophaga occidentalis hybridize in a stable hybrid zone, following a period of geographic separation. Genomic differentiation accumulated during geographic isolation can be homogenized by introgression at secondary contact, whereas genetic regions that cause low hybrid fitness can be shielded from such introgression. Here, we examined the genomic underpinning of speciation by investigating (1) the genetic basis of divergent pigmentation traits between species, (2) variation in differentiation across the genome, and (3) the evidence for selection maintaining differentiation in the pigmentation genes. Using tens of thousands of single nucleotide polymorphisms (SNPs) genotyped in hundreds of individuals within and near the hybrid zone, genome‐wide association mapping revealed a single SNP associated with cheek, crown, breast coloration, and flank streaking, reflecting pleiotropy (one gene affecting multiple traits) or close physical linkage of different genes affecting different traits. This SNP is within an intron of the RALY gene, hence we refer to it as the RALY SNP. We then examined between‐species genomic differentiation, using both genotyping‐by‐sequencing and whole genome sequencing. We found that the RALY SNP is within one of the highest peaks of differentiation, which contains three genes known to influence pigmentation: ASIP, EIF2S2, and RALY (the ASIP‐RALY gene block). Heterozygotes at this gene block are likely of reduced fitness, as the geographic cline of the RALY SNP has been narrow over two decades. Together, these results reflect at least one barrier to gene flow within this narrow (∼200 kb) genomic region that modulates plumage difference between species. Despite extensive gene flow between species across the genome, this study provides evidence that selection on a phenotype‐associated genomic region maintains a stable species boundary.Speciation is one of the most important processes in biology, yet the study of the genomic changes underlying this process is in its infancy. North American warbler species  Speciation is a very important process generating the diversity of lifeforms. However, study of the genomic basis underlying speciation is still in its infancy. Here, we took advantage of a natural hybrid zone (where diverged/diverging lineages interbreed) between two wood warbler species in the Pacific Northwest to uncover the genomic basis underlying species‐specific plumage variation, which is known to be used in social signaling within and between species. We found a 0.2‐Mb gene block, including three pigmentation genes ASIP, EIF2S2, and RALY, significantly explains variation in four of the seven plumage traits that differ between species. This region is also one of the most differentiated peaks in the genome, whereas the rest of the genome is mostly similar between species. Further tracking this gene block across the hybrid zone over two decades revealed selection against hybrids within this gene block that could be one of the predominant evolutionary forces maintaining the species boundary between these hybridizing sister species.Speciation involving partial geographic isolation commonly occurs in nature, yet we are just beginning to understand the genomic changes underlying this process  while controlling for overall genomic differentiation between species  and Setophaga occidentalis  along the Cascade mountains in North America. These closely related species of wood‐warblers started diverging an estimated 400,000 years ago  in hundreds of individuals from the hybrid zone. We also examined patterns of genomic differentiation between these species, using a smaller set of individuals far from the zone. We asked the following specific questions: (1) Are there individual SNPs and/or islands of differentiation strongly associated with species‐specific features ; (2) Is cheek darkening influenced largely by an allele of dominant effect, consistent with the inference made two decades ago by Rohwer and Wood , 250 of them were involved in our previous work in this system , which includes historical specimens at the Burke Museum of Natural History and Culture  collected in 1987–1994  LAB color space. LAB color space is a three‐dimensional space consisting of three distinct, perpendicular axes: (1) Luminosity (L) ranging from black (0) to white (100), (2) “A” ranging from green (–100) to red (100), and (3) “B” ranging from blue (–100) to yellow  in automatic mode for plumage analysis. We took three pictures from different angles: (1) frontal with head tilted up (for bib and breast measurements), (2) profile , and (3) from above (crown) . Instead of scoring species‐specific plumage variation as discrete variables  and averaged the pixels to record the values, respectively. The intensity of bib black was captured in the “L” axis. The intensity of green coloration on the back was captured by the “A” axis. The coloration on crown, cheek, and breast was captured by the “B” axis. For the cheek, we selected and averaged the entire area from above the eye (but excluding the eye) to the bib, and from the base of the bill to the back. To measure the extent of yellow on the breast, we used the program Analyzing Digital Images  is important for social signaling Endler . IdeallyWe acknowledge that without spectral analysis, we do not incorporate UV reflectance, which is a common aspect of signaling in avian systems  from our previous study  from the genomic data assuming that randomly selected markers from the genome are not associated with the trait (after controlling for population structure). We then used λ to correct the test statistic χ2 of each association test, so that the test is relative to the null hypothesis of no phenotype‐genotype association  and the lack of independence among sets of SNPs due to linkage. Genes associated with the candidate SNPs  were retrieved from Ensembl Zebra Finch (Taeniopygia guttata)  and five samples from inland townsendi in Tok, AK  for whole genome resequencing. For DNA extraction, we used 2 mm3 of tissue digested in buffer ATL and AL and washed with AW1 and AW2 of the Qiagen DNeasy Blood and Tissue kit—following the tissue extraction procedure—and separated DNA using UPrep spin columns (Genesee). We standardized DNA concentrations after quantifying concentrations with a Qubit fluorometer, and then generated sequencing libraries with the Illumina TruSeq Nano kit—which includes an eight‐cycle PCR enrichment—selecting 350 bp insert sizes. We individually indexed each sample and sequenced the combined libraries across a single lane of an Illumina NextSeq 500 using the paired‐end 150 bp sequencing chemistry. We combined these 10 samples with other wood warblers from other projects, and consistently included 24 individuals per sequencing lane to generate the target depth of 4–5× across samples.To sample genetic variation at a greater resolution (more SNPs per genetic region) along chromosomes compared to the GBS data, we selected five samples from FST  and occidentalis . This was done for each of the filtered SNPs, and then a genome‐wide weighted average was calculated according to Weir and Cockerham  data, we calculated ockerham . We focuWhitlock  have shoFST (with ANGSD) for each of the nonoverlapping 10‐kb windows.The genomic landscape of differentiation based on the GBS data was compared to that based on the WGS data. The reads from the WGS data were aligned to the same Zebra Finch reference (version 3.2.4)  was significantly associated with multiple plumage landmarks, we investigated whether this locus shows a signature of selection  by tracking the spatial and temporal variation in this locus relative to the plumage hybrid index and rest of the genome  is less than expected under neutral diffusion. In the present study, we applied this method to the RALY clines. In addition, we included the genomic clines and plumage clines (of 1987–1994 and 2015–2016) from our previous study .Across the Cascade mountain range, the pes Fig. . GWAS reOnly two other SNPs were found to be significantly associated with our phenotypic traits. The first is on chr 4A at nucleotide location 5588235, inside an ortholog of the mammal Immunoglobulin Binding Protein 1 (IGBP1) gene, explaining 33% of the variation in the intensity of yellow on the breast Fig. . The sech) of the O allele for each phenotype asZ¯OO, Z¯OT, and Z¯TT denotes the mean phenotype of OO, OT, and TT, respectively. To estimate confidence intervals, we conducted 10,000 iterations of bootstrap resampling of individuals, calculating the mean phenotypes and h each time, and thereby generating a bootstrap distribution of h. An h = 0.5 (Z¯OT = [Z¯TT + Z¯OO]/2) would correspond to complete additivity, h = 0 to complete recessivity of the O allele (Z¯OT = Z¯TT), whereas h = 1 to complete dominance of the O allele (Z¯OT = Z¯OO). Partial recessivity of the O allele would correspond to 0 < h < 0.5, and partial dominance of the O allele to 0.5 < h < 1. The estimated h is 0.810 for crown darkening , 0.908 for cheek darkening , 0.557 for breast yellow intensity , and 0.345 for flank streaking .We estimated the dominance coefficient . However, four high regions of differentiation (FST > 0.6) were found , chr 5 , chr 20 , and chr Z . SNPs in the vicinity of the RALY SNP did not show as strong a differentiation  in the GBS data, whereas most of the genome is not very differentiated (genome‐wide FST = 0.03)  than the genomic cline  in 2015–2016 (Table S5). The RALY cline center was at 1216.35 km in 1987–1994  Fig. . Second,03) Fig. . The RAL994 Fig. .w22015‐2016 – w21987‐1994: –38,573.70 to 1179.23 km2) than the plumage cline (95% CI of w22015‐2016 – w21987‐1994: –3978.35 to 7536.59 km2)   .Furthermore, the increase of the width of the RALY cline was less (95% CI of m2) Fig.  for explSetophaga townsendi and S. occidentalis different species?” a big part of the answer must involve the ASIP‐RALY gene block. Below, we discuss the evidence in support of this conclusion.Hybrid zones have long been considered “laboratories for the study of speciation” Hewitt . For manVariation in the RALY SNP explains  up to 60% of the variation in four out of seven plumage traits that differ between our two study species. A low‐resolution sequencing approach such as GBS, which sequences less than 1% of the genome, would be unlikely to detect a SNP that is directly mechanistically causing variation in the phenotype. It is more likely that the RALY SNP is closely linked to one or more directly causal DNA variants (SNPs or other variants) affecting phenotypic differences. It is also possible that multiple linked SNPs in this region are responsible for the variation in different phenotypic traits, such that the apparent pleiotropic effect  of the RALY SNP might be due to separate causal genes that are closely linked. For these reasons, we consider the three genes in the same narrow differentiation peak as the RALY SNP, as well as regulatory sequences near these genes, to be candidates for the specific sites that directly influence the phenotypes.Each of the three genes in the ASIP‐RALY island of differentiation has been invoked as being associated with color in other species. EIF2S2 has been associated with human skin pigmentation  in SCARF2 in our study of a species pair of the same genus. Instead, we found that the ASIP‐RALY gene block on chr 20 shows the main association with both carotenoid and melanin pigment patches.A previous genome‐wide association study in a hybrid zone between On top of the strong ASIP‐RALY association with various plumage traits, there are very likely other regions of the genome contributing to further refinement of species‐specific coloration in this system. Specifically, other SNPs on chr 4A and chr 1 are significantly associated with intensity and extent of breast coloration. In addition, there might be narrow but important genetic regions that this GBS dataset did not cover. However, the GBS and WGS datasets produced broadly similar overall genomic differentiation landscapes. That, together with the finding of strong associations between some GBS‐identified SNPs and plumage, gives us confidence in using GBS‐based GWAS to reveal the key regions underlying traits differentiating species.h = 0.908). Moreover, we observed partial dominance of the O allele . Such “opposing genetic dominance”  affecting a suite of pigmentation traits. Segregating supergenes can underpin differentiation of a set of traits, facilitating divergence among closely related species , heterozygotes of the RALY SNP may demonstrate patchy plumage ancestries leading to signal interference and disadvantage at territorial combat. Future study should test in more detail the role of these plumage signals in mate preference and social competition within the hybrid zone. Such further investigation would be important, in that genetic evidence for pleiotropic loci that influence both selected traits and reproductive isolation has been scarce  differs diagnostically between these species and is likely under some form of selection (discussed above) that maintains the stable and narrow hybrid zone at the species boundary , suggesting stability of the two forms and substantial independence going forward. This is particularly true for the ASIP‐RALY gene region and perhaps those few other genomic peaks of differentiation .All the sequence data in this study are provided on SRA . The metadata sheets involved in the analysis and figure production are deposited  frontal with head tilted up showing throat badge and breast measurements), 2) profile showing the cheek, and 3) from above showing the crown.Fig. S2 Pairwise scatterplots among 7 plumage variables  in the GWAS.Fig. S3 Weir and Cockerham STF scan of the WGS data, in which each dot represents a 10kb non‐overlapping window (A), where peaks were found on chromosome 1A (B), 4 (C), 5 (D), 20 (E), and Z (F).Table S1 Sample size  involved in the GWAS for each sampling period and population range .Table S2 Sample size of the 7 plumage variables  in which the intersect of the pairwise plumage variables were shown in off diagonal.Table S3 Allele frequencies of SNPs between RALY and ASIP in hybrid zone and parental zones based on the GBS dataset.Table S4 SNPs (in the GBS dataset) with STF > 0.6 and their position, association to genes and molecular functions.Table S5 Center and width of the RALY cline, plumage cline, and genomic cline of historical (1987‐94) versus recent (2015‐16) sampling.Click here for additional data file.


Sequencing-based technology reveals popping characteristics in maize, establishing a benchmark for popcorn genetics, and supporting a gradual selection process for popping traits. Zea mays L. var. Everta) is the most ancient type of cultivated maize. However, there is little known about the genetics of popping-related traits based on genotyping-by-sequencing (GBS) technology. Here, we characterized the phenotypic variation for seven popping-related traits in maize kernels among 526 CIMMYT inbred lines (CMLs). In total, 155 083 high-quality single nucleotide polymorphism (SNP) markers were identified by a GBS approach. Several trait-associated loci were detected by genome-wide association study for color, popping expansion volume, shape, pericarp, flotation index, floury/vitreous, and protein content, explaining a majority of the observed phenotypic variance, and these were validated by a diverse panel comprising 764 tropical landrace accessions. Sixty two of the identified loci were recognized to have undergone selection. On average, there was a 55.27% frequency for alleles that promote popping in CMLs. Our work not only pinpoints previously unknown loci for popping-related traits, but also reveals that many of these loci have undergone selection. Beyond establishing a new benchmark for the genetics of popcorn, our study provides a foundation for gene discovery and breeding. It also presents evidence to investigate the role of a gradual loss of popping ability as a by-product of diversification of culinary uses throughout the evolution of teosinte–to–modern maize.Popcorn ( Zea species), and are known for their ability to pop (Zea mays L. var. Everta) from Mexico is considered to be the most ancient maize type, and its genome sequence should contain the most comprehensive sample of genomic variation of maize  shows that genomic structural variation is enriched near the regions associated with traits , and 200 kernels  or 25 ml peanut oil  and 900 W power . In these studies, both the restricted diversity of the parents and low marker density limited a comprehensive dissection of popcorn genetic variation. Current sequencing technologies are both high throughput and highly accurate, thus providing an opportunity to more thoroughly dissect the popcorn genome, and reveal the genomic variation that underlies the evolution and domestication of maize. Here we apply conventional genotyping-by-sequencing (cGBS), which is a technically simple, highly multiplexed approach  markers  conducted GWAS on seven popping-related traits in 526 CIMMYT  inbred lines (CMLs) using 155 083 high-quality cGBS SNPs; (ii) validated the expansion-volume-related loci in a diverse set of 764 tropical landrace populations; and (iii) tested if the loci associated with popping-related traits had undergone selection. The results of this study create a new resource for popcorn genetics to dissect the origin and evolution of maize.http://hdl.handle.net/11529/10246) was used as an association mapping panel. Field experiments were conducted at Mexico, including those at Agua Fria, El Batan, HA, Palmira, RL, and Tlaltizapan, based on the adaptation groups. Each accession was planted in a single 1 m row with 30 cm spacing between rows (http://hdl.handle.net/11529/10423). In total, there were 955 690 SNPs retained, and their physical coordinates were derived from the maize reference genome version B73 AGPv2 (https://www.maizegdb.org/genome/genome_assembly/B73%20RefGen_v2). Imputation was performed with Beagle  mg ml-1]. Floury/Vitreous was defined as the ratio of floury to vitreous endosperm types. Six kernels per replicate were randomly selected for scanning. The resulting images were analyzed and the areas of floury and vitreous endosperm were measured by WinSEEDLE (Regent Instruments Canada Inc.). As a result, the ratio of the area of floury versus vitreous endosperm was calculated for each kernel, and the average value was used for further analyses. The percentage of protein was evaluated using a near-infrared spectrometer (NIRs) FOSS 6500 . Spectra were collected between 400 nm and 2500 nm, registering the absorbance values log(1/R) at 4 nm intervals for each sample  cream or (2) white  were calculated by fitting the following random model using the “lme4” package in R  of each trait was estimated as:where orrplot” . Variancr is the number of replications (=2 in this study).where Fixed and random model Circulating Probability Unification , was used for the association analysis, where the first three principal component analysis (PCA) values (eigenvectors) were included as fixed effects in the mixed model to correct for stratification  threshold of 6.46 was used for an experimental type I error rate of 0.05. To balance the false positives and false negatives, the whole-genome –log10 significance cutoff was finally set at 5. The total phenotypic variation explained by all of the significant SNPs was estimated by the coefficient of determination R2 from multiple linear models using the “lm” function in R . Based on the genome annotation, SNPs were categorized as being located in coding regions (i.e. overlapping with a coding exon), splice sites (within 2 bp of a splicing junction), 5′ UTRs and 3′ UTRs, intron, upstream and downstream regions, and intergenic regions. SNPs in coding regions were further grouped into synonymous SNPs (not causing amino acid changes) or non-synonymous SNPs . Functional enrichment analysis of the annotated genes was performed using the ClueGO plug-in for Cytoscape 3.6.1  , could be estimated by regressing each SNP for a selected eigenvector. To exclude the effect of genetic drift in selection loci mapping, the p-value was adjusted by a genomic control factor , and consequently the corrected p-value, PGC, was used for detecting the loci under selection. The SNPs with the top 5% of PGC values (i.e. PGC<0.0266) were considered to have undergone selection.Identification of potential selective signals during maize domestication and improvement through genome-wide association studies of eigenvectors was implemented using the bottom-up searching strategy EigenGWAS . The origins of these landraces represent diverse ecological regions including lowland tropical, sub-tropical/mid-altitude, and highland tropical subgroups, which were planted in Celaya and Tlaltizapan in 2016 . Of the 3 713 115 tGBS SNPs, 65 540 were retained after filtering for MAF and heterozygosity. The 65 540 tGBS SNPs were imputed without a reference panel using Beagle (V4.1). To further capture the genetic variation across the maize genome, the 65 540 SNPs from tGBS were also imputed to 359 618 high-quality SNPs using maize HapMap V3 as a reference panel (https://www.maizegdb.org/genome/genome_assembly/B73%20RefGen_v3). Finally, the union of the two SNP sets (N=414 124 SNPs) was filtered by MAF and heterozygosity under the same criteria as aforementioned, resulting in 355 442 high-quality SNPs which were retained for validation.In total, 0.31 terabases (Tb) of sequence data from 2.5 billion quality-trimmed reads were generated via tGBSNspI and BfuCI were used to digest the genomic DNA; while the single restriction enzyme ApeKI had been used to generate the cGBS data (http://ensembl.gramene.org/Oryza_sativa/Tools/AssemblyConverter?db=core. An extended haplotype homozygosity (EHH) test was conducted for the target SNPs within a 2 Mb region, identifying long and frequent haplotypes as implemented in the R package “rehh”  was 0.22 and the heterozygosity was 0.02. The heterozygosity of more than 98% of the SNPs was lower than 0.05 (r2 of 0.1)  . Princip of 0.1) : the pan of 0.1) . The tro of 0.1) . The pasr=0.50, P<0.01) and popcorn shape , and significantly and negatively correlated with IF , Floury/Vitreous , and protein content , confirming previously reported correlations between PEV and kernel quality traits (H2) of the seven popping-related traits ranged from 0.63 for floury/vitreous to 1 for color , encoding a phytoene synthase. PSY1 has been previously reported to reduce the carotenoid pigment content in maize endosperm, owing to a 378 bp InDel upstream of its transcription start site, and an SNP in its fifth exon that results in a Thr-to-Asn substitution . Subsequently, a GWAS was performed independently for each of the seven examined traits  using FarmCPU based on 155 083 SNPs . There w2.25E-38 , Fig. S510P>5) associated with popping-related traits with P-values ranging from 9.88E-06 to 2.25E-38 (n=101) have not been defined  and cryptochrome 1 (CRY1) affect PEV; and UWM10642, which encodes an F-box protein, is associated with protein content , PEV and protein , and floury/vitreous and pericarp . PEV was connected to pericarp and protein content by SNPs S2_96341835 and S2_217692527. These results suggest that the popping-related traits might be genetically co-regulated.Pleiotropic genes play important roles in understanding correlations among phenotypes , but locTo better understand the popping-related traits, we estimated the proportion of the phenotypic variance explained by significant SNPs, which averaged 43% across the seven traits, ranging from 28–83% . For then=58), and protein content, the lowest  was conducted in the set of 764 landrace populations. We narrowed down the candidate region on chromosome 2 to a 7 Mb region with 16 genes from 91 435 963 bp to 98 827 228 bp by linkage disequilibrium analysis . We eval1S1) derived from popcorn and dent maize parents, and detected four QTLs related to PEV on chromosomes 1, 3, and 5. Using a total of 101 SSR markers to detect QTLs in 194 F3 plants derived from the popcorn inbred A-1–6 and flint maize inbred V273, 2:3 and 220 BC2F2 derived from popcorn inbred N04 and dent corn inbred Dan232 , zea agamous-like1 (ZAGL1), sugary1 (SU1), and waxy 1 (WX1), existed in the ancestral state, sharply contrasting with the ubiquity of derived alleles in extant landraces. Their findings suggest that much of the evolution during domestication has been gradual, and they encourage further paleogenomic research to address provocative questions about the world’s most productive cereal. The most ancient form of maize was a popcorn (Zea mays L. var. Everta), and as such it is an ideal material for researchers to access a vast archive of paleogenomic data, permitting detailed investigations of prehistoric, as well as recent, selective pressures, and ultimately achieving a new understanding of the formation of maize landraces and improved maize lines. To further understand the history and spread of maize, Recently, To improve the analysis, in this study a comprehensive, quantitative measurement of kernel traits was performed. As a result, we were able to identify 162 SNPs associated with the kernel traits that we measured, of which 62 (38%) exhibit evidence of having been under selection. For seven traits, more than 30% of the significant SNPs exhibit evidence of selection, except for the percentage of pericarps. Those traits (and the percentage of SNPs) are color (46%), PEV (48%), shape (40%), IF (38%), protein (33%), and floury/vitreous 31%; . Given tIn this study, the 162 identified loci that we identified incorporated all of the previously known loci associated with popping-related traits. Beyond that, 147 loci were reported here for the first time. We discovered that non-popcorn inbreds (CMLs) contain variation for alleles that promote popping. Thus, our study represents a new benchmark for genetics in popcorn, and moving forward, should be helpful in dissecting both evolutionary and functional hypotheses. Specifically, it will guide efforts to determine the genetic basis of popcorn physiology, evolution, and history, assist gene discovery and breeding, and provide a more detailed understanding of the role of gradual popcorn domestication during the evolution of teosinte–to–popcorn-to-diversified modern maize. Genome sequences contain all kinds of information that control and influence biological functions. In this study, genetic variation was aligned to the B73 reference genome which has its own unique selection history. The development of the other gold-standard temperate maize genomes, Mo17  decay over physical distance. Fig. S3. Principal component analysis (PCA) of 155 083 SNPs based on 526 CMLs for GWAS.Fig. S4. The phenotypic distribution of the seven traits. Fig. S5. Manhattan plots and QQ (Quantile-Quantile) plots for six traits. Fig. S6. Prediction of the observed performance for six traits using the significant SNPs associated with the corresponding traits. Fig. S7. Prediction of the observed performance for seven traits using the common significant SNPs identified by GWAS and EigenGWAS. Fig. S8. The frequency distribution of popping-related SNPs that promote popping in CMLs.Table S1. Summary of the popping-related loci identified in previous studies.Table S2. The information on the seven traits measured in two replications for 526 CMLs.Table S3. The information and phenotype for the 764 maize tropical landrace populations.Table S4. Estimates of variance components for six traits in this study.Table S5. The significant SNPs associated with popping-related traits in 526 CMLs.eraa480_suppl_Supplementary_TableClick here for additional data file.eraa480_suppl_Supplementary_FigureClick here for additional data file.


Bos grunniens; YAK), and Bali (Bos javanicus) based on dense SNP data. In general, moderate genetic diversity levels were observed in most cattle populations. The proportion of polymorphic SNP ranged from 0.197 (YAK) to 0.992 (Mongolian cattle). Observed and expected heterozygosity ranged from 0.023 (YAK) to 0.366 , and from 0.021 (YAK) to 0.358 (SH), respectively. The overall average inbreeding (±SD) was: 0.118 ± 0.028, 0.228 ± 0.059, 0.194 ± 0.041, and 0.021 ± 0.004 based on the observed versus expected number of homozygous genotypes, excess of homozygosity, correlation between uniting gametes, and runs of homozygosity (ROH), respectively. Signatures of selection based on multiple scenarios and methods  revealed important genomic regions and candidate genes. The candidate genes identified are related to various biological processes and pathways such as heat-shock proteins, oxygen transport, anatomical traits, mitochondrial DNA maintenance, metabolic activity, feed intake, carcass conformation, fertility, and reproduction. This highlights the large number of biological processes involved in thermal tolerance and thus, the polygenic nature of climatic resilience. A comprehensive description of genetic diversity measures in Chinese cattle and YAK was carried out and compared to 24 worldwide cattle breeds to avoid potential biases. Numerous genomic regions under positive selection were detected using three signature of selection methods and candidate genes potentially under positive selection were identified. Enriched function analyses pinpointed important biological pathways, molecular function and cellular components, which contribute to a better understanding of the biological mechanisms underlying thermal tolerance in cattle. Based on the large number of genomic regions identified, thermal tolerance has a complex polygenic inheritance nature, which was expected considering the various mechanisms involved in thermal stress response.Understanding the biological mechanisms of climatic adaptation is of paramount importance for the optimization of breeding programs and conservation of genetic resources. The aim of this study was to investigate genetic diversity and unravel genomic regions potentially under selection for heat and/or cold tolerance in thirty-two worldwide cattle breeds, with a focus on Chinese local cattle breeds adapted to divergent climatic conditions, Datong yak ( Bos taurus) breeds to local environments is of paramount importance for the design and optimization of breeding programs and conservation of genetic resources  and Bos taurus indicus (mainly in the South of China) or hybrids between both subspecies  and Bali cattle  have a substantial economic and social role in their respective habitat. In the mountainous regions of Asia, Datong yak (YAK) provides milk, meat, fiber and hide, and transportation  statistics , and Bali (Bos javanicus) populations. To our best knowledge, no signatures of selection have been reported in the literature for some important Chinese cattle breeds , which are unique genetic resources adapted to divergent climatic conditions. Furthermore, adding outgroups (closely related species) to the analyses can contribute to a better understanding of evolutive processes related to climatic adaptation that shaped cattle speciation, which has not been well investigated due to previous lack of genomic datasets.Several statistical methods have been proposed to identify signatures of selection, such as the fixation index  breeds, Datong yak (Bos grunniens) and Bali (Bos javanicus) were included in this study (Bos genus (YAK and BLI) datasets are the genomic datasets, in which genotyping platforms developed for cattle (a closely related Bovidae species) were used. This might have resulted in ascertainment bias . In summary, a total of 986 animals from 32 different cattle (is study . Three sis study  were dowis study . A limitent bias  in the rent bias . The nument bias .HO) per animal and within population was calculated based on the number of heterozygotes divided by the total number of genotypes. HO values were compared to the expected heterozygosity under Hardy Weinberg Equilibrium (HE). Both metrics were calculated using the – hardy flag , (2) genomic inbreeding based on excess of homozygosity (FHOM), (3) correlation between uniting gametes (FU), and (4) ROH-based inbreeding (FROH). FEH, FHOM, and FU were calculated using all genotyped animals and SNP that remained after the QC performed individually for each population. FROH was calculated as the genome length covered by ROH divided by the total genome length covered by SNPs across all 29 autosomes. Different inbreeding metrics are expected to differ as they capture complementary populational diversity characteristics  based on the observed versus expected number of homozygous genotypes (eristics .r2) was calculated for each breed group using the –r2 flag  − f(A)∗f(B)]2. Within-population quality control was used to calculate LD (or r2) for each breed. The LD decay was then analyzed for the following different genetic distance classes between SNP pairs .where f(AB), f(A), f(a), f(B), and f(b) are observed frequencies of AB, A, a, B, and b, respectively, and r2) and assigning the appropriate sign based on the calculated disequilibrium (D) metric, as used in the calculation of LD. The D values were calculated using the –dprime-signed option  corresponds to a value of t generations in the past. This value was calculated as Ne in generation 5 was assumed as the recent Ne and ancient Ne was investigated up to 500 generations in the past.where, as t=12c . The Ne For all the above-mentioned metrics 35,505 SNPs from 312 individuals from eight Chinese cattle breeds  and YAK population were used. These metrics were only calculated to these populations as all the other datasets were extracted from public databases and similar studies have been published elsewhere e.g., .n = 986) from the 34 populations (–pca flag (For the PCA and genomic population tree (described below) all individuals were considered . In order to identify putative genomic regions under selection, the analyses were performed by grouping the cattle breeds in divergent clusters defined as heat, mild cold, and extreme cold tolerant populations. Preliminary analyses with balanced number of individuals per group were performed, but similar results were observed (results not shown). Therefore, the results with the complete datasets are presented here. Genomic regions under a mean plus four SD threshold were considered as candidate regions. To identify putative genome regions under selection, the analyses were performed under four scenarios of contrasting models:To identify population-specific loci under positive selection, (1)FST1):Groups based on climate adaptation ( The groups (n = 3) included all populations and were created based on climate adaptation: heat adaptation , mild cold/thermoneutral adaptation  and harsh cold adaptation .(2)FST2):Groups based on climate adaptation and breeding purpose excluding YAK and BLI populations ( The groups (n = 3) included all populations mentioned for FST1, but YAK and BLI were excluded.(3)FST3):Most climatic-divergent individual breeds ( The three most climatic-divergent populations (one for each group described above) based on FST values were compared against each other. The populations were DH (heat group), HOL , and YAKU (harsh cold group).The hapFLK method was used for calculation of distance matrices and the estimation of hapFLK as described by FST, ROH, and HapFLK analyses were mapped using the Biomart tool  and YAK population. As previously mentioned, these metrics were only calculated to these populations as all the other datasets were extracted from public databases and similar studies have been published elsewhere e.g., .HO ranged from 0.023 (YAK) to 0.366 (SH). The average HO was lower than the HE for DH, DC, Wannam, and MG populations, indicating slightly lower genetic diversity levels than expected.PSNP was high in all analyzed populations (ranged from 0.659 to 0.992), except in YAK (0.197). The distribution of SNP percentage by MAF range is shown in The D ranged from 0.016 (YAK) to 0.290 (MG) . Higher FHOM), 0.250 ± 0.051 (FEH), 0.194 ± 0.041(FU), and 0.021 ± 0.004 (FROH). The average inbreeding coefficients differed among cattle breeds and YAK had the highest values for FHOM, FU, and FROH metrics. FEH and FHOM, which surprisingly had a negative correlation (−0.71).Four different approaches to estimate genomic inbreeding coefficients were used. The average genomic inbreeding coefficients estimated using different approaches are shown in The proportion of ROH segments in each length category for the nine populations are shown in A descriptive summary of ROH is presented in The LD decay pattern for all populations is shown in As an example, the consistency of gametic phase between DH and SH with the other Chinese cattle breeds are shown in Ne ranged from 3,032 (MG breed) at 500 generations ago to 47 (KZK) at five generations ago. The Ne five generations ago (considered as recent Ne) were quite variable across populations, ranging from 147 (DC) to 47 (KZK). YAK had the smallest Ne 500 generations ago (Ne = 195) and 66 five generation ago. The Ne values from 5 to 500 generations ago are shown in The historical Bos indicus; ZBO, ZFU, ZMA, and EAZ) and another group of Chinese cattle breeds adapted to heat , which have small contributions from Bos taurus indicus from crossing over centuries ago. The PCA plots considering only the 32 cattle populations are shown in The genetic relationship among 32 cattle breeds, YAK and BLI populations revealed by PCA are shown in Bos taurus indicus × Bos taurus taurus), taurine (Bos taurus taurus) or indicine (Bos taurus indicus) breeds were clustered separately. Also, populations with similar development background were clustered together .The genomic population tree (constructed based on whole-genome SNPs) for 32 cattle breeds is presented in FST values indicate potential positive selection while low FST values suggest negative or neutral selection. Considering 32 cattle breeds, YAK and BLI populations there were several genomic regions potentially under selection in at least one of the populations studied. These selective sweeps were distributed on all 29 autosomal chromosomes. In scenario 1 (FST1), where we contrasted climate adaptation groups (n = 3), we observed 303 significant SNP and 3 shared SNP were found between the groups . The highest number of SNP identified was on BTA1 (15 SNP) in the harsh cold adapted group and the lowest was on BTA1 (1 SNP) in the cold adapted group. In FST2, which contrasted climate adaptation groups (n = 3), but excluding YAK and BLI from the comparison, 858 significant SNP were identified. Thirty-one SNP were shared between harsh cold and the heat adapted group, and a total of 827 unique SNP were observed. The highest number of SNP identified was on BTA1 (40 SNP) in the harsh cold adapted group and one SNP were found to be significant in BTA 3 in the cold/thermoneutral group. For FST3, where the most climatic-divergent breeds were compared, 987 significant SNP were observed. For the mild cold/thermoneutral and heat groups there were seven overlapping SNP, 37 between heat and harsh cold groups and 11 between mild cold/thermoneutral and harsh cold groups. The highest number of SNP identified was on BTA2 (62 SNP) in DH and the lowest was on BTA28 (7 SNP) in the MG population. As an example of the FST process, FST1, considering climate adaptation and including YAK and BLI genotypes. FST2 and FST3, respectively.High p-values < 0.005 were considered significant. These peaks were located in BTA3, BTA4, BTA10, and BTA14, for the first scenario, using YAK as an outgroup. In the second scenario, which had BLI population as outgroup, peaks were also found on BTA3, BTA4, BTA10, and BTA14, as well as on BTA15. In the third scenario, which considered only the 32 cattle populations and no outgroup, there were also significant peaks in BTA3, BTA4, BTA10, and BTA14. The highest peaks for the three scenarios were located on BTA10. The haplotype based hapFLK metric and −log  for the whole genome are shown in The hapFLK method enables the identification of genomic regions of outlying differentiation between populations while accounting for their hierarchical structure . SignifiThe highest number of ROH segments in the cattle populations were found for XIN and Weiling Humped  and the lowest (36) was found in KZK. The highest number of ROH segments were observed in BTA6 in XIN (179 ROH segments) and BTA1 in the Weiling Humped (153 ROH segments). The lowest number of ROH segments was observed in BTA28 in the DC, SH, and MG breeds (2 ROH segments). No ROH segments were found for KZK in BTA7, BTA15, BTA16, BTA18, BTA19, BTA26, BTA27, BTA28 and BTA29. The number of ROH segments observed in YAK was substantially greater  in comparison to the cattle populations. The number of ROH segments per chromosome in YAK ranged from 145 (BTA25) to 487 (BTA5).FST values greater than the mean plus four SD for FST1, FST2, and FST3; hapFLK p-values smaller than 0.005, and regions in ROH were further investigated to identify potential genes under positive selection for thermal tolerance. A summary of the number of regions identified and the number of genes for each method and scenario is presented in FST1, 8,702 and 1,206 candidate genes, respectively. On the other hand, the lowest number (30) was found for hapFLK when considering YAK as an outgroup. Some of the genes located in at least two different metrics were considered as relevant genes for further investigation. For instance, some of these genes are related to heat shock proteins , oxygen transport  and PIF1 (BTA10: 45.27–45.27 Mb)] and one was present only in MG cattle [ATG16L2 (BTA15: 52.35–52.36 Mb)]. These same two candidate genes present in YAK were identified between FST2 and hapFLK. Two novel candidate genes were also identified based on hapFLK and FST3, including OAZ2 (BTA10: 45.36–45.37 Mb) and CSNK1G1 (BTA10: 45.66–45.81 Mb). Larger number of overlapping regions were identified when comparing scenarios based either on FST or hapFLK to the ROH-based approach. For instance, the gene SNORA70 (BTA11: 99.006–99.007 Mb) was identified in DC cattle based on ROH and FST1. All genomic regions and candidate genes are reported in Several novel candidate genes were found when combining different methods. Two candidate genes were identified in YAK , myosin complex (GOTERM_CC), myosin (UP_KEYWORDS), steroid hormone receptor and nuclear hormone receptor [ligand-binding-core (INTERPRO)], steroid hormone receptor activity (GOTERM_MF), collagen triple helix repeat and collagen trimer (INTERPRO and GOTERM_CC), collagen (UP_KEYWORDS) and respiratory chain (UP_KEYWORDS).The functionally enriched categories of candidate genes are shown in Considering the third scenario (SCEN3), where candidate genes identified in the signatures of selection analyses in the cold adaptation groups were analyzed, 36 significantly enriched functional categories were identified including myosin head [motor domain (INTERPRO)], myosin complex (GOTERM_CC), innate immunity and innate immune response (UP_KEYWORDS and GOTERM_BP), immunity (UP_KEYWORDS), cell–cell adhesion and cell–cell adherens junction (GOTERM_BP and GOTERM_CC), and immunoglobulin I-set and immunoglobulin V-set (INTERPRO). Lastly, we analyzed candidate genes identified in the signatures of selection analyses for YAK (SCEN4) and 35 significantly enriched functional categories were identified including salivary secretion and gastric acid secretion (KEGG_PATHWAY), oxygen binding (GOTERM_MF), hemoglobin complex (GOTERM_CC), oxygen transport (UP_KEYWORDS), oxygen transport activity (GOTERM_MF), immunoglobulin subtype 2 and immunoglobulin-like domain (INTERPRO), myosin head [motor domain (INTERPRO)], myosin complex (GOTERM_CC), secondary metabolites biosynthesis, transport, and catabolism (COG_ONTOLOGY), steroid hormone receptor and steroid hormone receptor activity (INTERPRO and GOTERM_MF), and prolactin signaling pathway (KEGG_PATHWAY).PSNP was high in the majority of the eight Chinese cattle breeds  and YAK population studied in this section  also found high PSNP (0.952). YAK was an exception, both for the distribution of SNP percentage and for the proportion of polymorphic SNP. These differences between YAK and the cattle breeds may be due to the fact that YAK was not included in the development of the SNP chip panel and the fact that YAK and cattle are different species (Bos gruniens and Bos taurus), even though closely related in the evolutionary tree. To minimize and avoid this potential issue, a SNP chip panel could be developed specifically for YAKs. Alternatively, genotyping-by-sequencing (GBS) could be employed  and MG (HO = 0.331 and HE = 0.332) cattle breeds. Similar heterozygosity values (HO = 0.340 and HE = 0.341) compared to those found for taurine breeds in this study have been reported in Australian HOL cattle , which generated very relevant results  and between FROH and FU (0.15), which are similar to the findings in this study. A similar correlation to our study (−0.07 versus −0.10) were found between FHOM and FU in Danish Red cattle and a negative correlation, but higher than found here (−0.07 versus −0.44), was observed between FHOM and FU in Danish HOL cattle bulls . High correlation between FHOM and FROH (0.85) has also been reported in other Chinese cattle breeds  similar to the ones found in this study for DC, DH, Weiling Humped, and WN cattle. There was an increase in Ne for YAK in the most recent generations (∼50 generations ago), which is probably due to the introduction of outbred animals or a high level of crossbreeding with other populations. To ensure a long-term viable genetic diversity, a threshold of Ne equals to 100 has been suggested  were identified in ROH and were demonstrated by previous studies  and brite  adipocytes, that in the case of exposure to cold can differentiate into cells capable of expressing uncoupling protein 1, producing heat by lipid oxidation  may also be positively selected for lipid metabolism in warm environments. The gene TMC6, identified for mild cold/thermoneutral group based on FST3 and ROH, has been reported to influence milk quality in cold environment in Northern China breeds (COL27A1 (found here in FST2 and ROH), which has been proposed to be involved in cartilage calcification, which is another important aspect in cold climates. Studying signatures of selection for candidate genes for body temperature maintenance under the cold stress in Siberian cattle populations, GRIA4 contribute to cold-stress resistance due to indirect involvement in body thermoregulation. In our study a gene from the same family (GRIA1) was found for YAK in the FST3 and ROH scenarios. This indicates that GRIA1 may also be involved in cattle adaptation to cold climates. RASA1) and ion regulation , which were also identified in our study for scenarios FST2 and ROH (RASA1), and FST3 and ROH (CACNG3), FST3 and ROH (SLC22A23), and FST1 and ROH (TRPC4).The candidate gene a breeds . Thus, tHBM and HBG, related with oxygen transportation were identified for YAK in FST1, FST2, and ROH (HBM) and in hapFLK and ROH (HBG). These genes were previous identified by HBM and HBG were suppressed in the presence of heat stress. The fact that these genes were found here as under positive selection in YAK highlights the importance of these genes in oxygen transportation in harsh and high-altitude environments.High altitudes, where YAKs are raised, might result in hematopoiesia, where the reduced oxygen tension leads to an increase of erythrocytes as an adaptive mechanism to low oxygen levels . The canSLC38A4, AGXT2, STEAP3, CSMD3, ABCB4, ZDBF2, and LAMA2 identified in FST1 and ROH, were previously reported in a study of functional characterization of mammalian genes involved in adaptation to Arctic or Antarctic environments (SLC38A4), mammoth and polar bear , mammoth, whale, and polar bear (ZDBF2), and human and mammoth (LAMA2). The gene SLC38A4 encodes a transporter protein that is expressed predominantly in the liver and participates in the transfer of amino acids  in the metabolism and resistance of animals exposed to harsh environments .The genes ronments  and had no acids  and is pno acids . Regardin humans  and relan humans . The posHSPE1, which regulates maintenance of metabolic activity and survival  identified based on FST1, FST3, and ROH in DH were previous reported to harbor selective sweeps for environmental adaptation in EAZ  to maintain protein folding under heat stress  were previously reported to be related to fertility traits in cattle  was previously reported to be associated with fat deposition  might contribute to improved production and reproduction under heat stress conditions.Two genes identified between n cattle . NRXN3 hn cattle . CACNB2  in cows . Reverteposition , feed inposition  phenotypoduction  and SLC9n humans . Anotherronments . Taye etd intake . The aboFST1 and ROH (LEF1 and MLST8), and FST2, FST3, and ROH (SMYD3). LEF1, MLST8, and SMYD3 are genes related with immune and anti−infectious response in Mediterranean cattle breeds. LEF1 could be a strong candidate gene to heat adaptation since it is also related to thermotolerance and ultra-violet protection, as suggested by its central role in hair pigmentation  are involved in antigen recognition and related to the development of immune response in West African cattle  in WN and SEN, breeds with short coat hair. This finding in WN might be linked to thermotolerance in this cattle breed, an adaptation to high temperature environment. Another important trait in thermal tolerance adaptation in livestock is coat color  in some cattle breeds (PMEL) with thermotolerance.A slick coat is associated to higher thermotolerance and higher milk production on crossbred animals under tropical environment and can be considered as an indicator or indirect phenotype to some highly important production traits . A deletEN breed . The PRLat color . Cows wiat color . The gene breeds . The posDNAJA1, DNAJB1, HSPH1, and HSPA4). DNAJA1 and DNAJB1) that regulates the ATPase activity of HSP70 (HSPH1 and HSPA4) by interacting with the J domain of the HSP70 proteins and also conferring thermo-tolerance to cells on exposure to heat stress  were clustered in the “oxygen binding” molecular function that was identified for YAK in scenarios SCEN1 and SCEN4. At high altitudes, where YAKs are raised, immediate means of acclimatization such as hyperventilation, hemoconcentration, and erythropoiesis are initiated to increase total oxygen carrying capacity  were grouped into two groups related to folate receptor and folic acid transporter activity. The high number of genes identified in our study  makes itcapacity . In suchcapacity . In addiNDUFS3, NDUFB6, CYCS, and CYCT) were clustered together and are related to respiratory chain. BSP1, BSP3, and BSP5) related to fertilization and sperm capacitation were identified in scenario SCEN2, based on the heat adaptation candidate genes group. Heat stress can be considered as cytotoxic, as it alters biological molecules, disturbs cell functions, modulates metabolic reactions, induces oxidative cell damage, and activates both apoptosis and necrosis pathways . Four geThe large number of genomic regions and candidate genes identified in this study was not unexpected. As there are multiple mechanisms involved in cold and heat stress response, natural and artificial selection are expected to cause weak selection pressure at many sites across the genome. The weak selection pressure is due to the small effect of each of the many variants or QTL underlying the phenotype, which results in small changes to allele frequencies at the many loci, but which result in the adaptation response observed across breeds .The information reported here will be useful for the implementation of genomic selection and other genomic studies in local Chinese cattle populations and YAK. Genomic selection is expected to increase the genetic gain along with the decrease in generation interval . Due to Lastly, some of the potential limitations of this study should be highlighted. Having additional breeds from the same subspecies, but adapted to different climatic conditions, would be beneficial. Ascertainment bias might have influenced the estimates due the fact the SNP array design did not include all the cattle populations evaluated and especially any population of YAK or BLI. Moreover, due to the large number of candidate genes identified, additional studies should prioritize specific genes for more in-depth studies for validation purposes.FST, hapFLK, and ROH). Various candidate genes were identified as potentially under selection for thermal tolerance based on multiple methods and scenarios. Enrichment analyses identified important biological pathways, molecular function and cellular components, which greatly contribute to our understanding of the genetic background of thermal tolerance in cattle and Datong yak. These results highlight the diversity and complexity of mechanisms that are involved in response to harsh environmental conditions. Further studies are needed to validate these results by using larger and independent populations, additional methods for specific thermal stress indicators , and other tools such as whole-genome sequencing. These novel findings are useful for the conservation of genetic resources, especially under global climate changes, and contribute to the potential discovery of functional genes and genetic mechanisms related to thermal tolerance in cattle, Datong yak, and Bali populations.A comprehensive description of genetic diversity measures in thirty-two worldwide cattle populations , Datong yak, and Bali populations is presented. Moderate genetic diversity was observed within each population, but optimal contribution strategies should be adopted to avoid further reduction in the genetic diversity of these populations. The breeds adapted to heat seems to be moderately related to each other and the same was observed for those adapted to cold environments. This study provides a high-confidence map of positive selection signatures for thermal tolerance in cattle, and Datong yak using three alternative methods (http://widde.toulouse.inra.fr/widde/widde/main.do;jsessionid=73509E5BFFDDE224635B91CA70E9FC82?module=cattle.All relevant information supporting the results of this article are included within the article and its additional files. Public genotypic data used for our analysis can be found at WIDDE database: LB, YW, QX, and FS participated in the design of the study. PF performed all the analyses and results interpretation, was involved in the discussions, and wrote the first draft of the manuscript. LB provided training to the first author, contributed to the analyses and results interpretation, was involved in all the discussions, and edited all the versions of the manuscript. YW and YZ provided the cattle genotypes, while PY provided the YAK genotypes used for the study. HO participated in the results interpretation, was involved in the discussions and gave editorial assistance. FS, YW, QX, and PY edited the final version of the manuscript and provided valuable suggestions. All authors have approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Recent developments in solar thermal systems have aroused considerable interest in several countries with high solar potential. One of the most promising solar driven technologies is the solar thermal dish-Stirling system. One of the main issues of the solar dish–Stirling system is thermal losses from its components. The majority of the thermal losses of the system occur through its receiver before the thermal energy is converted to electrical energy by the Stirling engine. The goal of this investigation is to analyze the thermal performance of the receiver of a standalone pilot solar dish–Stirling system installed in Kerman City, Iran, to be used in remote off-grid areas of the Kerman Province. An analytical model was developed to predict the input energy, thermal losses, and thermal efficiency of the receiver. The receiver thermal model was first validated by comparing simulation results to experimental measurements for the EuroDish project. Then, the incident flux intensity intercepted by the receiver aperture, the thermal losses through the receiver , and the power output during daytime hours (average day of each month for a year) were predicted. The results showed that the conduction loss was small, while the convection and radiation losses played major roles in the total thermal losses through the receiver. The convection loss is dominant during the early morning and later evening hours, while radiation loss reaches its highest value near midday. Finally, the thermal efficiency of the receiver and the power output for each working hour throughout the year were calculated. The maximum performance of the system occurred at midday in the middle of July, with a predicted power output of 850 W, and a receiver efficiency of about 60%. At this time, a conduction loss of about 266 W, a convection loss of 284 W, and a radiation loss of about 2000 W were estimated. To date, several types of solar thermal technologies have been developed to produce electricity from solar energy. Currently, a parabolic solar dish–Stirling system is one of the types of concentrating solar power plants considered as one of the most efficient proven solar thermal technologies .A parabolic solar dish–Stirling system has a solar collector that consists of a solar parabolic dish and a thermal receiver through which thermal energy is provided to drive a Stirling engine . The par2 year. The solar hours in this area are almost 2800 h/year [This system is classified as the most efficient model, exceeding the total efficacy of any other solar conversion technology ; hence, So far, several investigations have been conducted to design and analyze a standalone dish Stirling module. One of the main issues being addressed by designers is the performance of the different parts of the system. Hence, a number of investigations have focused on modeling and improving solar dish–Stirling modules, in particular, the solar receiver.The performance of a parabolic solar dish–Stirling system was examined by Wu et al. , who repThe present paper proposes an approach for analysis of the thermal efficiency, taking into account the thermal losses through the receiver of the standalone Kerman pilot dish–Stirling system under the specific meteorological conditions in Kerman City. The power is to be used in remote off-grid desert areas of Kerman Province. An analytical model was used to predict the conduction, convection, and radiation losses through the receiver. The calculations were performed for the daytime hours of an average day in each month of a year . Then, uThe main objective of the study is to present a practical methodology for predicting the performance of each part of the solar dish–Stirling system, and then, to demonstrate that the methodology provides the necessary elements to design the system modules. This approach shows the impact and importance of each thermal mechanism on the efficiency of the receiver at different periods of time.f/dd). This shape can also be defined by the rim angle. A schematic of the system is illustrated in The shape of a parabolic concentrator and the location of its focal point can be defined by the dish focal distance to diameter ratio f=dd4The rim angle must be determined before sizing the aperture because it influences the maximum concentration ratio (CR), collector slope error, and losses due to convection and radiation . ψ) between 0° and the rim angle is calculated as: The distance between the surface of the concentrator and the focal point of the aperture at any angle Q˙conThe natural convective heat transfer coefficient, which refers to transfer through the receiver cavity, depends on the aperture and receiver diameters, and the cavity location on a specific day and at a specific time. To estimate this coefficient, the Nusselt number can be calculated as below :(5)NunatThe forced convective heat transfer coefficient of the receiver cavity can be expressed as a function of the wind speed, as follows : (6)hforThe total convective heat transfer coefficient and total convection losses through the receiver cavity are calculated using the following equations :(7)htotaThe radiation loss from the receiver is a considerable part of the total thermal losses of the receiver. It consists of two radiation mechanisms: the emitted radiation and the reflected radiation. The emitted and reflected radiation heat transfer from the receiver cavity is calculated with the following equations, respectively:It is seen that the radiation loss reflected from the cavity surfaces depends on the effective absorptance of the cavity receiver, which is defined as The total thermal loss from the receiver is calculated as below:The receiver efficiency can be calculated as a function of the total thermal loss, the entrance solar energy, and the concentrator efficiency as follows:The heat rate transferred to the Stirling engine is assumed to be equal to the heat rate supplied by the receiver. Therefore, the thermal power input received by the Stirling engine can be estimated as below:concη), the receiver efficiency (recη), the Stirling engine efficiency (SEη), and the generator efficiency (genη) as below: The total efficiency of the system is equal to the product of the concentrator efficiency (Finally, the power output of the system can be expressed as a product of the total input energy and the total efficiency as follows:In order to calculate the annual energy that can be produced by the system, it is necessary to determine the amount of solar irradiance reaching the dish concentrator in a year. Since the aperture of the receiver is much smaller than the reflector, only beam radiation is effectively directed onto the absorbing surface of the receiver ; therefoThe Kerman pilot produced about 0.6 kW of power output in the middle of June at the highest solar radiation, which was in good agreement with the predicted power output of 0.629 kW at the same time. In addition, the receiver thermal model simulation was validated by comparing its results to the measured data from the 10-kW EuroDish project . Under tThe wind speed and the ambient temperature data recorded by the weather bureau of Kerman City throughout the year were used to take into account the effects of meteorological conditions of the site on the simulation results throughout the operating hours of the year. As an example, the data records of Kerman City during the working period of the pilot test on 15 July are reported in Accordingly, the incident flux intensity intercepted by the receiver, the thermal losses, efficiency of the receiver, and system power output in the daytime hours of an average day for each month in a year were calculated. In this section, we report the results from our analysis of the thermal losses of the receiver, including the conduction, convection, and radiation losses. These losses are dependent on the location of the receiver, the receiver cavity temperature, and the time of day.The incident flux intensity values intercepted by the receiver aperture in the daytime hours of an average day for each month in a year are shown in In order to minimize the conduction losses from the receiver cavity and also minimize the shading of the dish, an optimum insulation layer thickness of 75 mm for the high-temperature ceramic fiber insulation was suggested  and usedThe total conduction loss in the working hours of an average day of each month in a year is shown in Convection losses are affected by the orientation of the receiver aperture, the receiver cavity temperature, ambient temperature, and the wind speed. The total convection losses through the receiver cavity in daytime on an average day of each month in a year are shown in It can be seen that the convection loss is highly affected by the time of day. The minimum convection loss occurs at about midday. In addition, in the short period of time around midday, the convection loss changes only slightly with time. In contrast, when the time approaches early morning or late evening, the convection loss increases considerably. The main reason for this is that the orientation of the receiver has the main effect on the convection loss. At midday, the receiver aperture is facing downward, and its orientation is more vertical; whereas, during early morning or later evening, it is oriented more horizontally. Consequently, the receiver is subjected to a more stable convective situation at midday. Moreover, it can be seen that, during the interval of November to February, the convection loss is relatively higher. The main reason for this is that the convection loss is most affected by the time of the year due to changes in the solar incident angle. Consequently, changes in the orientation of the receiver aperture are unavoidable.Radiative heat transfer contributes to thermal losses from the receiver through the aperture. This involves both radiation being emitted from the receiver aperture and radiation being reflected off the receiver cavity surfaces. Both forms of radiation loss are taken into account in the radiation model.Heat transfer mechanisms, including conduction, convection, and radiation, contribute to the total thermal energy losses from the receiver. The conduction loss has the smallest fraction among all of the thermal loss mechanisms. In early morning and late evening, the convection loss is dominant, which results in a considerable decrease in the thermal performance of the receiver while the convection loss decreases considerably during the midday period. In contrast to the trend of the convection loss, in the midday period, the radiation loss is high while it is lower in the early morning and later evening.Finally, the predicted power outputs during the working hours of an average day on each month in a year are shown in The study developed a practical methodology which estimates the performance of the solar dish–Stirling system by calculating the performance of each part of the system. A practical example reflected important conclusions regarding the obtained results for thermal losses through the receiver, its thermal efficiency, and the power output. Thermal modeling and simulations for a standalone pilot parabolic solar dish–Stirling system composed of a 1-kW Stirling engine, a parabolic dish, and a receiver were conducted. The conduction, convection, and radiation heat losses through the receiver and their impact on its thermal efficiency for the selected design of the pilot system were examined. The pilot was set up in Kerman City, Iran. The input energy received by the receiver aperture, thermal losses through the receiver, thermal efficiency of the receiver, and the power output were predicted using an analytical model. The thermal losses resulting from the conduction, convection, and radiation heat transfer were calculated for the daytime hours on an average day of each month in a year. The results demonstrated that the convection loss was primary during early morning and later evening hours, which resulted in a significant decrease in the receiver performance during these periods of time. In contrast, the radiation loss played a more significant role in reducing the receiver performance during the midday period. The conduction loss also made the smallest contribution among all of the thermal losses. The receiver thermal efficiency values in the working hours on an average day of each month in a year were also calculated. Results showed that during early morning and later evening, the receiver efficiencies were minimal. It was found that during these periods, the convection losses were considerably higher, while the incident flux intensity values intercepted by the receiver aperture were comparatively lower. This resulted in poor receiver efficiency. For the given ambient conditions throughout the year, a maximum receiver efficiency of about 60% was estimated. The power output also reached a maximum of 850 W. It can be concluded that the approach presented in this study is useful to illustrate the influence of each of the thermal mechanisms contributing to thermal losses from the receiver, on its performance at different periods throughout a year. The methodology provided a comprehensive design procedure by taking into account thermal mechanisms, the efficiency of each element of the system, and the power output at different periods of time. As perspectives, the work presented a practical design approach that was able to make a whole-year simulation. The methodology can also be used to design more efficient and feasible systems.


NCAPG and LCORL genes was associated with all skeletal traits in the Limousin population and with wither height in the Angus. Other than that, little overlap existed in detected QTLs for the skeletal type traits in the other breeds. Only two QTLs overlapped the beef and dairy breeds; both QTLs were located on BTA5 and were associated with height in both the Angus and the Holstein-Friesian, despite the difference in age at assessment. Several detected QTLs in the present study overlapped with QTLs documented elsewhere that are associated with carcass traits, feed intake, and calving difficulty. While most breeding programs select for the macro-traits like carcass weight, carcass conformation, and feed intake, the higher degree of granularity with selection on the individual linear type traits in a multi-trait index underpinning the macro-level goal traits, presents an opportunity to help resolve genetic antagonisms among morphological traits in the pursuit of the animal with optimum performance metrics.Linear type traits describing the skeletal characteristics of an animal are moderately to strongly genetically correlated with a range of other performance traits in cattle including feed intake, reproduction traits and carcass merit; thus, type traits could also provide useful insights into the morphological differences among animals underpinning phenotypic differences in these complex traits. The objective of the present study was to identify genomic regions associated with five subjectively scored skeletal linear traits, to determine if these associated regions are common in multiple beef and dairy breeds, and also to determine if these regions overlap with those proposed elsewhere to be associated with correlated performance traits. Analyses were carried out using linear mixed models on imputed whole genome sequence data separately in 1,444 Angus, 1,129 Hereford, 6,433 Charolais, 8,745 Limousin, 1,698 Simmental, and 4,494 Holstein-Friesian cattle, all scored for the linear type traits. There was, on average, 18 months difference in age at assessment of the beef versus the dairy animals. While the majority of the identified quantitative trait loci (QTL), and thus genes, were both trait-specific and breed-specific, a large-effect pleiotropic QTL on BTA6 containing the  Linear type traits have been used in both beef and dairy cattle since the early 20th century to characterize the skeletal characteristics of an animal . These tWhile many genomic studies have been carried out on stature in both beef and dairy cattle , few stu1.Animal Care and Use Committee approval was not obtained for the present study as the data were obtained from the existing Irish Cattle Breeding Federation (ICBF) national databaseRoutine scoring of linear type traits is carried out on both registered and commercial beef herds by trained classifiers from the Irish Cattle Breeding Federation as part of the Irish national beef breeding program . Five skAnimals were discarded from the dataset if the sire, dam, herd, or classifier was unknown. Only data from classifiers that scored ≥ 100 animals since the year 2000 were kept. Animals were also discarded from the dataset if the parity of the dam was unknown; parity of the dam was subsequently recoded into 1, 2, 3, 4, and ≥ 5. Contemporary group was defined as herd-by-scoring date generated separately per breed. Each contemporary group had to have at least five records. Following edits, data were available on 81,200 animals, aged between 6 and 16 months, consisting of 3,356 AA, 31,049 CH, 3,004 HE, 35,159 LM, and 8,632 SI.Scoring of linear type traits in the Irish dairy herd is undertaken by trained classifiers from the Irish Holstein-Friesian Association . For theAnimals were discarded from the dataset if the sire, dam, herd, or classifier was unknown. Records were also discarded from the data set if scored after 10 months of lactation. Only data from classifiers that scored > 100 animals since the year 2000 were retained. Contemporary group was defined as herd-by-scoring date and each contemporary group had to have at least five records. Following edits, data were available on 117,151 primiparous Holstein-Friesian cows (HF) aged between 23 and 42 months at scoring.Prior to inclusion in the analysis, all beef cattle phenotypes were adjusted, within breed, in ASREML  using thyijklm = μ + HSDm + Sexj + AMk + DPl + animali + eijklmyijklm is the linear type trait, μ represents the population mean, HSDm is the fixed effect of herd-by-scoring date , Sexj is jth sex of the animal , AMk is the fixed effect of the age in months of the animal (k = 11 classes from 6 to 16 months), DPl is the fixed effect of the parity of the dam , animali is the random additive effect of animal i, and eijklm is the random residual effect. The adjusted phenotype was the raw phenotype less the fixed effect solutions of HSD, Sex, AM, and DP.where The dairy phenotypes were also adjusted in ASREML  using thyijklm = μ + HSDm + AMj + CMk + LSl + animali + eijklmyijklm is the linear type trait, μ represents the population mean, HSDm is the fixed effect of herd-by-scoring date , AMj is the fixed effect of the age in months of the animal at scoring (j = 20 levels from 23 to 42 months), CMk is the fixed effect of the month of calving (k = 12 levels from 1 to 12), LSl if the fixed effect of the stage of lactation of the animals (l = 10 levels from 1 to 10 reflecting number of months of lactation), animali is the random additive effect of animal i, and eijklm is the random residual effect. The adjusted phenotype was the raw phenotype less the fixed effect solutions of HSD, AM, CM, and LS.where n = 5,808; 54,001 SNPs), the Illumina High Density , the Illumina 3k panel , the Illumina LD genotyping panel  or a bespoke genotype panel (IDB) developed in Ireland , version 2  or version 3 . Each animal had a call rate ≥ 90%. Only autosomal SNPs, SNPs with a call rate ≥ 90% and those with a known chromosome and position on UMD 3.1 were retained for imputation.Of the edited dataset of 81,200 beef animals and 117,151 dairy animals with linear type trait information, 23,943 animals from six breeds  also had genotype information available. These genotypes were imputed to whole genome sequence (WGS) as part of a larger dataset of 638,662 genotyped animals from multiple breeds as detailed by  Ireland  which waBos Taurus animals of multiple breeds from Run6.0 of the 1000 Bulls Genomes Project by first phasing all 638,662 imputed HD genotypes using Eagle  ≤ 0.002 were removed and regions of poor WGS imputation accuracy, identified using 147,309 verified parent-progeny relationships as previously described by The association analyses were performed, within each breed separately, using a mixed linear model in Genome-wide Complex Trait Analysis (GCTA) . Autosomy is a vector of preadjusted phenotypes, μ is the overall mean, x is the vector of imputed genotypes, b is the additive fixed effect of the candidate SNP to be tested for association, u ∼ N is the vector of additive genetic effects, where G is the genomic relationship matrix calculated from the imputed HD SNP genotypes, and e ∼ N is the vector of random residual effects, with I representing the identity matrix and where p ≤ 1 × 10–8 and a suggestive threshold of p ≤ 1 × 10–5 was applied genome-wide for each SNP in each trait as per 2 was used to identify if any of the QTLs identified within the present study had previously been associated with any other traits in beef or dairy cattle. To identify QTL regions that were suggestive in more than 1 breed, each chromosome was split into 1 kb genomic windows and windows containing suggestive SNPs (p ≤ 1 × 10–5) were compared across the breeds.A significance threshold of The proportion of genetic variance of a trait explained by a SNP was calculated as:p is the frequency of the minor allele,a is the allele substitution effect and where Z-score method in METAL  (1−Pi/2)Δi, where Φ is the cumulative distribution function, and Pi and Δi are the P-value and direction of effect for breed i, respectively.where Enrichment analysis was carried out among all suggestive and significant SNPs within each trait and each breed separately to estimate if the number of SNPs in each annotation class was greater than what would be expected by chance :a is the number of suggestive and/or significant SNPs in the annotation class of interest, b is the total number of suggestive and/or significant SNPs that were associated, c is the total number of SNPs in the annotation class in the association analysis, and d is the overall number of SNPs included in the association analysis.where p ≤ 1 × 10–8) and/or suggestive (p ≤ 1 × 10–5) SNPs were detected for all of the traits in all six breeds; however, the exact locations of these SNPS, and the direction of the effects of these SNPs, differed by breed.The scale of measurement, number of records, mean, and standard deviation of the linear type traits in each breed is in the NCAPG and LCORL. There were also two suggestive 1 kb windows located at approximately 94.9 Mb on BTA5 common to both the AA and HF.No 1 kb genomic window associated with height was common to all six breeds. There was, however, some overlap in suggestive 1 kb windows between the AA and LM where 79 suggestive windows located on BTA6 were common to both breeds . Six genNCAPG and LCORL genes on BTA6  and significantly associated in the LM (p < 1.29 × 10–12). Interestingly, the positive  allele of these SNPs occurred at similar frequencies (0.08–0.09) in both the AA and LM and had a similar effect size in both breeds. In comparison, while these SNPs were segregating in both the HE and HF, and had similar allele frequencies in the HE as in the AA and LM, none of these SNPs were near significance in either the HE (p > 0.11) or HF (p > 0.88). However, a suggestive association was detected 21 Mb further upstream of LCORL on BTA6 in the HF where the strongest association within this QTL, rs209851496 (p = 1.94 × 10–6), was located 1kb upstream of the CHRNA9 gene.The strongest associations in both the AA and LM were intergenic variants located in QTLs surrounding the  on BTA6  and accoPTPRO gene, were associated with WH in these breeds. The strongest associations in the remaining breeds were all intergenic SNPs, although their location differed by chromosome; the strongest association in the CH was on BTA2 in a 1 Mb QTL containing MSTN; the strongest association in the HE was in BTA7, with the strongest association for the SI located on BTA12.Of the 514 SNPs that were suggestively associated with stature in the HF, 281 were located on BTA5. Both the AA and HF had suggestive associations on this autosome; two intergenic SNPs, rs798298008 (AA) and rs475950607 (HF), located just 17 bp apart and 63 Kb from the ALKBH8 and RAB39A, was the only QTL identified that had not previously been associated with WH in any of the within-breed analyses.There were 1,055 suggestive and 36 significant SNPs associated with WH in the meta-analysis . A singlNCAPG/LCORL complex, contained 34 suggestively associated SNPs, of which the strongest (rs110194711) was in the MEPE gene. A similar genomic region on BTA6 was also associated with CW in the HE, suggesting that the QTL region on BTA6 may harbor an across-breed pleiotropic association since it was also associated with WH in the AA and LM. Although four of the 6 breeds  had QTLs on BTA10 suggestively associated with CW , located on BTA20.There were no 1 kb suggestive windows common to any of the breeds associated with width of hips. The QTL on BTA6 surrounding the e breeds . Of the 31.26 Mb . SeveralIn comparison to WH and CW, the lead variant within the top five QTLs associated with HW in the AA, CH, HE and SI breeds was near fixation . All of FKBP1P, CDH13, HSPB1, DNAAF1, and PSMB9.In the meta-analysis of HW and RW, suggestively associated QTL were located on BTA11, BTA15, BTA18, and BTA23 ; none ofNCAPG and LCORL genes were suggestively associated with BL in both the AA and LM , was an intronic SNP located within NCAPG  units longer on average, than those with two copies of the major allele.The window-based analyses revealed that no 1kb genomic region was suggestively associated with BL in all breeds, but 40 1 kb windows on BTA6 surrounding the A and LM . In totain NCAPG . In totaMSTN gene; these SNPs included the well-known Q204X stop-gain mutation, rs110344317 (p = 2.01 × 10–35). When Q204X was forced into the model as a fixed effect, the most significant of the remaining SNPs on BTA2 generally reduced in significance relative to when Q204X was not included in the model. The most significant SNP on BTA2 after accounting for the variability in the Q204X genotype was rs41638272, an intergenic SNP located 15 kb from the SLC40A1 gene. The QTL associated with BL also overlapped the QTL on BTA2 associated with WH suggesting this QTL may play a major role in affecting the morphology of an animal. No other significant associations with BL were identified in any of the remaining beef breeds.A QTL on BTA2 was significantly associated with BL in the CH; this QTL stretched 10 Mb and contained 1,765 significant and 3,760 suggestive SNPs . Fifty sDNTTIP1, TNNC2, PLTP, and CDH22 while no obvious candidate genes were identified on BTA12.In the meta-analysis of BL, significantly associated QTLs were identified on BTA2 and BTA6, similar to what was identified in the CH and LM breeds, respectively . Other QNCAPG and LCORL genes in LM was significantly associated with any of the breeds for CD , three traits in the SI  and AA , and two in both the CH (WH and BL) and HF . Of the top 140 QTLs associated with the skeletal type traits , 80 of tNCAPG and LCORL genes, the majority of QTLs associated with the skeletal type traits were breed-specific and in many cases, also trait specific. The differences observed in associated QTLs among the breeds may be due to epistatic or gene-by-environment interactions, or simply due to differences in the power to detect significance due to the large differences in population sizes among the breeds  of SNPs associated with any trait were intergenic SNPs; the number of intergenic SNPs and also 3′ UTR and 5′ UTR variants were enriched for the majority of traits they were associated with in each breed, demonstrating the importance of regulatory networks within the genome to the cattle skeletal traits. Inference could also be drawn, therefore, on the contribution of regulatory regions to the correlated traits like carcass merit and feed intake. Downstream and upstream gene variants were also enriched in many of the traits. In general, the SNPs located within, or close to, the genes identified as candidate genes were located within these non-coding or regulatory regions. For example, 22 SNPs that were suggestively or significantly associated with WH in the LM were located within the ic model .NCAPG and LCORL genes was the only QTL associated with more than two traits and in more than one breed. This indicates that while the NCAPG and LCORL genes may affect multiple traits in multiple breeds, the majority of QTLs underlying the skeletal type traits are both trait-specific and breed-specific. This has implications on the perceived usefulness of across-breed genomic evaluations for the component traits as well as possibly for their correlated economically important traits  based solely on purebreds. Many of the QTLs identified in the present study have previously been documented to be associated with a number of other performance traits in cattle, including carcass traits, feed intake and calving difficulty.While many QTLs were identified as being associated with each trait in each breed, a large-effect QTL on BTA6 containing the PRJNA238491, PRJEB9343, PRJNA176557, PRJEB18113, PRNJA343262, PRJNA324822, PRJNA324270, PRJNA277147, PRJNA474946, and PRJEB5462.Sequence variant genotypes were provided by participation in the 1000 Bulls Consortium and a subset of the sequences can be found at NCBI BioProject http://www.icbf.com).Ethical review and approval was not required for the animal study because as the data were obtained from the existing Irish Cattle Breeding Federation (ICBF) national database (JD, DB, RV, and DP participated in the design of the study and were involved in the interpretation of the results. JD performed the analyses and wrote the first draft of the manuscript. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.