Univariate Linear Models Research Articles

Usability of the Benford’s law for the results of least square estimation

Benford’s law (BL), also known as the first-digit or significant-digit law, is an intriguing pattern in data sets, considers the frequency of occurrence of the first digits, which are not uniformly distributed as might be expected, conversely follow a specified theoretical distribution. According to BL, the occurrence of first non-zero digit in a numerical data, which is generated or found in nature, depends on a logarithmic distribution. Least square estimation (LSE) method is mostly preferred for the estimation of the unknown parameters from different types of geodetic data. The residuals and the normalized residuals of the LSE method, which follow normal distribution and expected values of them are zero are used in outlier detection problem. In this study, BL is investigated for residuals and the normalized residuals estimated from LSE method. Three types of geodetic data are used: (1) simulated regression models, (2) global positioning system (GPS) data, (3) leveling network. The first group data sets are simulated based on linear regression and univariate models and each simulated group is generated for a number of 100, 1000, and 10,000 samples. To generate second group, an international global navigation satellite system (GNSS) service (IGS) station data (ISTA) is processed by kinematic PPP approach using GIPSY OASIS II v6.4 software. Here, the observation duration of GPS data is 4 days. For the last data, a leveling network with 55 points involving 110 observations of height differences is simulated. BL has been applied to the residuals (v) and normalized residuals (w) estimated from LSE method. Goodness-of-fit test has been implemented to determine whether a population has a specified BL distribution or not. This test is based on how good a fit we have between the frequency of occurrence of residuals and normalized residuals in an observed sample and the expected frequencies obtained from the hypothesized distribution. The results depending on the statistical test show that each data set (residuals and normalized residuals) used in this study follows BL.

Comparison and assessment of large-scale surface temperature in climate model simulations

Abstract. We present a data-driven approach to assess and compare the behavior of large-scale spatial averages of surface temperature in climate model simulations and in observational products. We rely on univariate and multivariate dynamic linear model (DLM) techniques to estimate both long-term and seasonal changes in temperature. The residuals from the DLM analyses capture the internal variability of the climate system and exhibit complex temporal autocorrelation structure. To characterize this internal variability, we explore the structure of these residuals using univariate and multivariate autoregressive (AR) models. As a proof of concept that can easily be extended to other climate models, we apply our approach to one particular climate model (MIROC5). Our results illustrate model versus data differences in both long-term and seasonal changes in temperature. Despite differences in the underlying factors contributing to variability, the different types of simulation yield very similar spectral estimates of internal temperature variability. In general, we find that there is no evidence that the MIROC5 model systematically underestimates the amplitude of observed surface temperature variability on multi-decadal timescales – a finding that has considerable relevance regarding efforts to identify anthropogenic “fingerprints” in observational surface temperature data. Our methodology and results present a novel approach to obtaining data-driven estimates of climate variability for purposes of model evaluation.

Genetic evaluation of a 15-year selection program for high growth in striped catfish Pangasianodon hypophthalmus

This study attempted to make a comprehensive genetic evaluation of a selective breeding program for striped catfish Pangasianodon hypophthalmus selected for high growth over 15 years from 2001 to 2015. Statistical analyses were carried out on 54,259 individual fish that were offspring of 554 sires and 926 dams (955 families in total). Both univariate and bivariate linear animal mixed models were used to estimate variance and covariance components for four groups of traits studied: (i) body traits (harvest body weight and standard length), (ii) carcass traits (fillet weight and fillet yield), (iii) fish body condition (condition index) and (iv) growth survival of each individual during grow-out phase. Medium to high heritability (0.31–0.54) were estimated for body traits, while carcass and condition index had medium heritability (0.17 to 0.20). Phenotypic and genetic correlations among body traits (weight and length) were high and close to one. The growth-related traits showed moderate and positive (i.e., favourable) genetic correlations with fillet yield (0.67–0.92) and condition index (0.28–0.49). Direct response to selection for high growth was 9.3% per generation. The selection program increased fillet weight and growth survival by 8.5% and 7.4%, respectively. However, there was insignificant correlated change in fillet yield (only 1.6%). Collectively, our results showed that there are substantial genetic variations in all traits studied and selection for high growth resulted in beneficial changes in fillet weight, fish body condition and survival during grow-out phase. The improved strain of striped catfish had 13.4% greater growth performance than their wild counterparts of the latest generation, suggesting that culture of the improved striped fish line may enhance productivity and economic return for small householder farmers and commercial producers.

Wear of resin denture teeth in partial removable dental prostheses

PurposeTo investigate occlusal wear of resin denture teeth in partial removable dental prostheses worn by partially edentulous patients. MethodsThirty patients with partial removable dental prostheses were included in the study. Thirty-two patients with complete dentures served as a reference group. Occlusal wear after two years was evaluated indirectly using gypsum casts and a three-dimensional laser-scanner device. Overall wear of complete occlusal surfaces and maximum wear of occlusal contact areas were measured. Patient and prosthesis data were analyzed using univariate and multiple linear mixed models. ResultsOverall wear of denture teeth in partial removable dental prostheses was 91 (SD 85) μm, and maximum wear of occlusal contact areas was 329 (SD 204) μm (means and standard deviations). Average and maximum wear values for teeth in complete dentures were both lower than those for teeth in partial removable dental prostheses. However, differences between wear of different types of denture did not reach statistical significance after adjustment for gender, type of tooth, dental status of the opposing jaw, and antagonist material. Statistical analysis revealed that wear was greater for denture teeth occluding with ceramic crowns and/or fixed partial dentures as antagonists. ConclusionsResin denture teeth in partial removable and complete dental prostheses are subjected to clinically important occlusal wear that might destabilize occlusion and cause further problems. Patient-related factors and dental status affect wear behavior and should be taken into consideration when treating patients with removable dentures.

Efficient multivariate analysis algorithms for longitudinal genome-wide association studies.

Current dynamic phenotyping system introduces time as an extra dimension to genome-wide association studies (GWAS), which helps to explore the mechanism of dynamical genetic control for complex longitudinal traits. However, existing methods for longitudinal GWAS either ignore the covariance among observations of different time points or encounter computational efficiency issues. We herein developed efficient genome-wide multivariate association algorithms for longitudinal data. In contrast to existing univariate linear mixed model analyses, the proposed method has improved statistic power for association detection and computational speed. In addition, the new method can analyze unbalanced longitudinal data with thousands of individuals and more than ten thousand records within a few hours. The corresponding time for balanced longitudinal data is just a few minutes. A software package to implement the efficient algorithm named GMA (https://github.com/chaoning/GMA) is available freely for interested users in relevant fields. Supplementary data are available at Bioinformatics online.

Facial photogrammetric profile measurements and sagittal dental occlusion in the young Congolese Bantu Adult (DRC)

The aim of the present study was to determine, according to the kind of dental occlusion, the profile photogrammetric characteristics of the young Congolese Bantu adult (DRC Congo). It was a cross-sectional study, including 302 young Congolese Bantu adults (161 males and 141 females), aged between 18-30 years old. All were in full permanent dentition, out of which 157 in dental normocclusion, 74 in distocclusion, and 71 in mesiocclusion. The included subjects were subjected to anthropometric measurements performed using a photographic tool. The recorded data was analysed using the SPSS 20.0 statistic software for Windows. A general linear univariate model was established to compare the photogrammetric variables according to the gender and the type of dental occlusion. A post-hoc test was performed to specify the level of differentiation between the groups. The level of significance was fixed at P<0.05. The gender dimorphism was observed for eight out of the seventeen variables, namely the facial angle, the FMA, the naso-labial angle, the Z angle, the convexity angle, E/Ls, E/Li, and H/Li. The majority of the observed differences were found in the dental normocclusion situations. In Class III situation, there was almost no difference between males and females, except for variable E/Ls. The photogrammetric measurements of the face captured the morphological specificities related to the type of dental occlusion and to the gender dimorphism. The expressiveness of the gender dimorphism was more pronounced in the subgroup of subjects in dental normoclusion, a little less in distocclusion, and almost none in dental mesiocclusion. Therefore, profile photographs may be a viable alternative to determine normative values for the facial skin profile of the Congolese subject, and may be used as a reference for the diagnostic and treatment approach.

Complimentary Methods for Multivariate Genome-Wide Association Study Identify New Susceptibility Genes for Blood Cell Traits.

Genome-wide association studies (GWAS) have found hundreds of novel loci associated with full blood count (FBC) phenotypes. However, most of these studies were performed in a single phenotype framework without putting into consideration the clinical relatedness among traits. In this work, in addition to the standard univariate GWAS, we also use two different multivariate methods to perform the first multiple traits GWAS of FBC traits in ∼7000 individuals from the Ugandan General Population Cohort (GPC). We started by performing the standard univariate GWAS approach. We then performed our first multivariate method, in this approach, we tested for marker associations with 15 FBC traits simultaneously in a multivariate mixed model implemented in GEMMA while accounting for the relatedness of individuals and pedigree structures, as well as population substructure. In this analysis, we provide a framework for the combination of multiple phenotypes in multivariate GWAS analysis and show evidence of multi-collinearity whenever the correlation between traits exceeds the correlation coefficient threshold of r2 >=0.75. This approach identifies two known and one novel loci. In the second multivariate method, we applied principal component analysis (PCA) to the same 15 correlated FBC traits. We then tested for marker associations with each PC in univariate linear mixed models implemented in GEMMA. We show that the FBC composite phenotype as assessed by each PC expresses information that is not completely encapsulated by the individual FBC traits, as this approach identifies three known and five novel loci that were not identified using both the standard univariate and multivariate GWAS methods. Across both multivariate methods, we identified six novel loci. As a proof of concept, both multivariate methods also identified known loci, HBB and ITFG3. The two multivariate methods show that multivariate genotype-phenotype methods increase power and identify novel genotype-phenotype associations not found with the standard univariate GWAS in the same dataset.

Vascular Access Choice, Complications, and Outcomes in Children on Maintenance Hemodialysis: Findings From the International Pediatric Hemodialysis Network (IPHN) Registry

Arteriovenous fistulas (AVFs) have been recommended as the preferred vascular access for pediatric patients on maintenance hemodialysis (HD), but data comparing AVFs with other access types are scant. We studied vascular access choice, placement, complications, and outcomes in children. Prospective observational cohort study. 552 children and adolescents from 27 countries on maintenance HD followed up prospectively by the International Pediatric HD Network (IPHN) Registry between 2012 and2017. Type of vascular access: AVF, central venous catheter (CVC), or arteriovenous graft. Infectious and noninfectious vascular access complication rates, dialysis performance, biochemical and hematologic parameters, and clinical outcomes. Univariate and multivariable linear mixed models, generalized linear mixed models, and proportional hazards models; cumulative incidence functions. During 314 cumulative patient-years, 628 CVCs, 225 AVFs, and 17 arteriovenous grafts were placed. One-third of the children with an AVF required a temporary CVC until fistula maturation. Vascular access choice was associated with age and expectations for early transplantation. There was a 3-fold higher living related transplantation rate and lower median time to transplantation of 14 (IQR, 6-23) versus 20 (IQR, 14-36) months with CVCs compared with AVFs. Higher blood flow rates and Kt/Vurea were achieved with AVFs than with CVCs. Infectious complications were reported only with CVCs (1.3/1,000 catheter-days) and required vascular access replacement in 47%. CVC dysfunction rates were 2.5/1,000 catheter-days compared to 1.2/1,000 fistula-days. CVCs required 82% more revisions and almost 3-fold more vascular access replacements to a different site than AVFs (P<0.001). Clinical rather than population-based data. CVCs are the predominant vascular access choice in children receiving HD within the IPHN. Age-related anatomical limitations and expected early living related transplantation were associated with CVC use. CVCs were associated with poorer dialysis efficacy, higher complication rates, and more frequent need for vascular access replacement. Such findings call for a re-evaluation of pediatric CVC use and practices.

An Artificial Neural Networks‐Based Tree Ring Width Proxy System Model for Paleoclimate Data Assimilation

AbstractConstructing suitable tree ring width (TRW) proxy system models (PSMs) is an emerging research focus in paleoclimate data assimilation (PDA). Currently, however, it is unknown as to which TRW PSMs are optimal for practical PDA applications. This study proposes an artificial neural networks (ANN)‐based TRW PSM and compares its performance with those of existing TRW PSMs, including linear univariate model, linear multivariate model, and physically based VS‐Lite model. The results show that ANN‐based TRW PSM is more suitable for practical PDA applications than other three TRW PSMs in terms of performance and universality. Overall, the performances of the four TRW PSMs in PDA can be ranked as follows (from best to worst): ANN, linear multivariate model, linear univariate model, and physically based VS‐Lite model. In addition, the results of our study not only indicate that the ANN model is a really effective tool for constructing TRW PSM in practical PDA applications but also imply that the ANN model has the potential to provide new insights into the construction of other types of PSMs (e.g., speleothem δ18O PSM) when physics of the climate‐proxy relationships cannot be described fully in advance.

CFTR Modulator Use Is Associated with Higher Hemoglobin Levels in Individuals with Cystic Fibrosis.

Understanding how cystic fibrosis transmembrane conductance regulator (CFTR) modulators influence comorbid conditions like anemia is of great interest to the cystic fibrosis community. To test the hypothesis that CFTR modulators are associated with higher hemoglobin (Hgb) levels. Annualized Hgb and other laboratory, demographic, and anthropometric data were abstracted from the U.S. CF Foundation Patient Registry for adult and pediatric registrants before and after therapy with ivacaftor (IVA) or lumacaftor/ivacaftor (LUM/IVA) between January 2010 and December 2016. Univariate and multivariate linear mixed models were used to examine the effect of IVA on Hgb in patients with G551D-CFTR, and the effect of LUM/IVA on Hgb in F508del-CFTR homozygotes. Linear regression was used to characterize change in mean Hgb over time. A total of 1,347 registrants (707 males and 640 females) with G551D-CFTR and 12,582 F508del-CFTR homozygotes (6,640 males and 5,942 females) who had never undergone lung transplant and had contemporaneous data regarding Hgb and CFTR modulator use were identified. IVA was associated with average Hgb increases of 0.54 gm/dl (95% confidence interval [CI], 0.39-0.69; P < 0.0001) and 0.18 gm/dl (95% CI, 0.01-0.35; P = 0.037) for males and females, respectively, with G551D-CFTR. LUM/IVA was associated with average Hgb increases of 0.58 gm/dl (95% CI, 0.48-0.68; P < 0.0001) and 0.26 gm/dl (95% CI, 0.20-0.33; P < 0.0001) for male and female F508del-CFTR homozygotes, respectively. In multivariate models, IVA positively affected Hgb in males but not females, and LUM/IVA positively affected Hgb in both sexes. IVA and LUM/IVA use are both associated with higher Hgb levels in patients with CF.

Anchorage loss assessment of the indirect anchor tooth during adjunctive orthodontic treatment.

This study quantitatively assessed movement of anchor teeth connected to a miniscrew (indirect anchor tooth) and investigated factors affecting movement during adjunctive orthodontic treatment. Dental plaster models of 28 patients whose treatment included an indirect anchor tooth on one side were collected before and after treatment. The casts were digitally scanned, and 2 groups were constituted: the indirect anchor teeth (experimental group; n=52) and the untreated teeth (control group; the first and second premolars opposing the indirect anchor tooth to which no orthodontic force was applied; n=55). Pretreatment and posttreatment models were superimposed and the amount and direction of indirect anchor tooth movement were evaluated with the use of a univariate linear mixed model. Possible factors affecting movement of the indirect anchor tooth and its significance were also evaluated with the use of a multiple linear mixed model. The indirect anchor tooth moved 0.91±0.50mm and did not exhibit significant differences in the transverse, vertical, or sagittal directions. The location of the indirect anchor tooth affected movement and the tooth moved significantly more in the mandible than in the maxilla. The indirect anchor tooth can move during adjunctive orthodontic treatment and thus requires careful monitoring for occlusal changes.

Similar alteration for mental and physical aspects in health-related quality of life over 5 to 8\u2009years in 1347 patients with early arthritis and early inflammatory back pain

IntroductionHealth-related quality of life (HRQoL) is a priority for patients. The objectives were to describe the changes in HRQoL over 5–8 years in patients with early arthritis (EA) or early inflammatory back pain (IBP) and to explore factors associated to HRQoL.Patients and methodsIn 2 prospective observational French cohorts (ESPOIR for EA patients and DESIR for early IBP patients), HRQoL was assessed regularly over 5–8 years, using the SF36 physical and mental composite scores (PCS and MCS, range 0–100). Disease activity was assessed by DAS28-ESR and ASDAS-CRP. Univariate and multivariate linear mixed-effect models and trajectory-based mapping were applied.ResultsIn all, 1347 patients (701 EA and 646 early IBP) were analysed: mean age 48.4 ± 12.2 and 33.9 ± 8.7 years respectively; mean disease duration 3.4 ± 1.7 and 18.2 ± 10.8 months; and 76.3% and 55.0% females. At baseline, in EA, mean PCS and MCS were respectively 40.2 ± 9.1 and 40.4 ± 11.2 and, in early IBP, were respectively 38.5 ± 8.5 and 39.8 ± 10.9. Over follow-up, HRQoL mean levels improved mostly over the first 6 months (p < 0.001). Two trajectories were evidenced in both diseases. The ‘good HRQoL’ trajectory groups, i.e. 54–61% of patients, reached levels of HRQoL close to population norms. DAS28-ESR and ASDAS-CRP over time were related to PCS (range of explained variance 9–43%, p < 0.001 in the mixed models) but not to MCS.ConclusionHRQoL was altered similarly for both physical and mental aspects in EA and early IBP. Disease activity only partly explained HRQoL: the drivers of HRQoL should be further explored.

Suitability of LF-NMR to analysis water state and predict dielectric properties of Chinese yam during microwave vacuum drying

The feasibility of low-field nuclear magnetic resonance (LF-NMR) was investigated to predict the dielectric properties of Chinese yam slices. Changes in relaxation behaviors and dielectric properties (at 915 and 2450 MHz) of samples during microwave vacuum drying as well as their relationship were studied. Results showed that the total moisture content decreases gradually over drying time, and the free water was removed first, followed by the immobile water and bound water. Correspondingly, the dielectric constant (ε′) gradually decreased till to reach a relative and stable low value; while the loss factor (ε″) changed slightly first, then decreased gradually and also reached a low value finally. Univariate linear models showed that the signal intensity of free water peak (A23) and the transverse relaxation time of immobile water (T22) had good correlation with dielectric properties. Furthermore, partial least squares regression (PLSR) models with four NMR parameters as variables gave better results with R2P of 0.946, 0.936, 0.962 and 0.921 for ε′ and ε″ at 915 MHz and ε′ and ε″ at 2450 MHz, respectively. The overall results revealed that LF-NMR is suitable for predicting the dielectric properties as a rapid and noninvasive method.

Genome-wide study to detect single nucleotide polymorphisms associated with visceral and subcutaneous fat deposition in Holstein dairy cows

Excessive abdominal fat might be associated with more severe metabolic disorders in Holstein cows. Our hypothesis was that there are genetic differences between cows with low and high abdominal fat deposition and a normal cover of subcutaneous adipose tissue. The objective of this study was to assess the genetic basis for variation in visceral adiposity in US Holstein cows. The study included adult Holstein cows sampled from a slaughterhouse (Green Bay, WI, USA) during September 2016. Only animals with a body condition score between 2.75 and 3.25 were considered. The extent of omental fat at the level of the insertion of the lesser omentum over the pylorus area was assessed. A group of 100 Holstein cows with an omental fold <5 mm in thickness and minimum fat deposition throughout the entire omentum, and the second group of 100 cows with an omental fold ⩾20 mm in thickness and with a marked fat deposition observed throughout the entire omentum were sampled. A small piece of muscle from the neck was collected from each cow into a sterile container for DNA extraction. Samples were submitted to a commercial laboratory for interrogation of genome-wide genomic variation using the Illumina BovineHD Beadchip. Genome-Wide association analysis was performed to test potential associations between fat deposition and genomic variation. A univariate mixed linear model analysis was performed using genome-wide efficient mixed model association to identify single nucleotide polymorphisms (SNPs) significantly associated with variation in a visceral fat deposition. The chip heritability was 0.686 and the estimated additive genetic and residual variance components were 0.427 and 0.074, respectively. In total, 11 SNPs defining four quantitative trait locus (QTL) regions were found to be significantly associated with visceral fat deposition (P<0.00001). Among them, two of the QTL were detected with four and five significantly associated SNPs, respectively; whereas, the QTLs detected on BTA12 and BTA19 were each detected with only one significantly associated SNP. No enriched gene ontology terms were found within the gene networks harboring these genes when supplied to DAVID using either theBos taurus or human gene ontology databases. We conclude that excessive omental fat in Holstein cows with similar body condition scores is not caused by a single Mendelian locus and that the trait appears to be at least moderately heritable; consequently, selection to reduce excessive omental fat is potentially possible, but would require the generation of predicted transmitting abilities from larger and random samples of Holstein cattle.

Spatial analysis and temporal trends of antimicrobial use in Danish pig herds following the introduction of the Yellow Card scheme

Spatial analysis and temporal trends of antimicrobial use in Danish pig herds following the introduction of the Yellow Card scheme

Empirical estimation of the power of test in outlier detection problem

Classical outlier detection test methods such as Baarda test and Pope test are generally preferred in geodetic problems. They depend on the Least Square Estimation (LSE) and LSE is very sensitive to the variations of the model. The capacity of the LSE changes depending on the different significance level, different type of outlier, the number of outlier, magnitude of outlier, number of observations and the number of unknowns. In statistics, the power of test is the probability of rejecting the null hypothesis when the null hypothesis is false. It is a theoretical assumption and depends on the significance level α (Type I error) and β (Type II error). The different types of the outliers, such as random or non-random, affect the results of the test methods; but the power of test is the same for all different types of the outliers. In this study, empirical estimation of the power of test is presented as Mean Success Rate (MSR). The theoretical power of test and empirical MSR have been estimated for univariate model and linear model by using Baarda test; according to the obtained results, MSR can be used as empirical value of the power of test and capacity of the test models. Also, MSR reflects more realistic results than the theoretical power of test.

Mobility analysis of AmpuTees (MAAT 5): Impact of five common prosthetic ankle-foot categories for individuals with diabetic/dysvascular amputation.

IntroductionDiabetes and vascular disease represent the most common etiologies for lower limb amputations. In lower limb loss rehabilitation, the prosthetic ankle-foot mechanism is the most common major component needed to restore function. The purpose of this study was to examine the impact of five common prosthetic ankle-foot mechanisms on functional mobility in a large sample of individuals with amputation due to diabetes/dysvascular disease.MethodsA retrospective analysis of the Prosthetic Limb Users' Survey of Mobility (PLUS-M®) captured in the patient care setting. A total of 738 individuals were included and subsequently subdivided into five groups based on the ankle-foot mechanism of their current prosthesis. Groups were compared using a general linear univariate model with age, body mass index, comorbid health status, time since amputation, and amputation level entered as covariates.ResultsThe microprocessor ankle-foot group had the highest mobility (F4,728 = 3.845, p=0.004), which was followed by the vertical loading pylon type ankle-foot, the hydraulic ankle-foot, the flex-walk-type ankle-foot, and lastly the flex-foot-type ankle-foot.ConclusionThese results demonstrate that the selection of different prosthetic ankle-foot technology directly impacts functional mobility for the patient with an amputation due to diabetes and/or vascular disease.

Forecasting cryptocurrencies under model and parameter instability

This paper studies the predictability of cryptocurrency time series. We compare several alternative univariate and multivariate models for point and density forecasting of four of the most capitalized series: Bitcoin, Litecoin, Ripple and Ethereum. We apply a set of crypto-predictors and rely on dynamic model averaging to combine a large set of univariate dynamic linear models and several multivariate vector autoregressive models with different forms of time variation. We find statistically significant improvements in point forecasting when using combinations of univariate models, and in density forecasting when relying on the selection of multivariate models. Both schemes deliver sizable directional predictability.

The genetic architecture of milk ELISA scores as an indicator of Johne's disease (paratuberculosis) in dairy cattle

Johne's disease (or paratuberculosis), caused by Mycobacterium avium ssp. paratuberculosis (MAP) infection, is a globally prevalent disease with severe economic and welfare implications. With no effective treatment available, understanding the role of genetics influencing host infection status is essential to develop selection strategies to breed for increased resistance to MAP infection. The main objectives of this study were to estimate genetic parameters for the MAP-specific antibody response using milk ELISA scores in Canadian Holstein cattle as an indicator of resistance to Johne's disease, and to unravel genomic regions and candidate genes significantly associated with MAP infection. After data editing, 168,987 milk ELISA records from 2,306 herds, obtained from CanWest Dairy Herd Improvement, were used for further analyses. Variance and heritability estimates for MAP infection status were determined using univariate linear animal models under 3 scenarios: (a) SCEN1: the complete data set (all herds); (b) SCEN2: herds with at least one suspect or test-positive animal (ELISA optical density ≥0.07); and (c) SCEN3: herds with at least one test-positive animal (ELISA optical density ≥0.11). Heritability estimates were calculated as 0.066, 0.064, and 0.063 for SCEN1, SCEN2, and SCEN3, respectively. The correlations between estimated breeding values for resistance to MAP infection and other economically important traits, when significant, were favorable and of low magnitude. Genome-wide association analyses identified important genomic regions on Bos taurus autosome (BTA)1, BTA7, BTA9, BTA14, BTA15, BTA17, BTA19, and BTA25 showing significant association with MAP infection status. These regions included 2 single nucleotide polymorphisms located 2 kb upstream of positional candidate genes CD86 and WNT9B, which play key roles in host immune response and tissue homeostasis. This study revealed the genetic architecture of MAP infection in Canadian Holstein cattle as measured by milk ELISA scores by estimating genetic parameters along with the identification of genomic regions potentially influencing MAP infection status. These findings will be of significant value toward implementing genetic and genomic evaluations for resistance to MAP infection in Holstein cattle.

Genome wide association study identifies novel potential candidate genes for bovine milk cholesterol content

This study aimed to identify single nucleotide polymorphisms (SNPs) associated with milk cholesterol (CHL) content via a genome wide association study (GWAS). Milk CHL content was determined by gas chromatography and expressed as mg of CHL in 100 g of fat (CHL_fat) or in 100 mg of milk (CHL_milk). GWAS was performed with 1,183 cows and 40,196 SNPs using a univariate linear mixed model. Two and 20 SNPs were significantly associated with CHL_fat and CHL_milk, respectively. The important regions for CHL_fat and CHL_milk were at 41.9 Mb on chromosome (BTA) 17 and 1.6–3.2 Mb on BTA 14, respectively. DGAT1, PTPN1, INSIG1, HEXIM1, SDS, and HTR5A genes, also known to be associated with human plasma CHL phenotypes, were identified as potential candidate genes for bovine milk CHL. Additional new potential candidate genes for milk CHL were RXFP1, FAM198B, TMEM144, CXXC4, MAML2 and CDH13. Enrichment analyses suggested that identified candidate genes participated in cell-cell signaling processes and are key members in tight junction, focal adhesion, Notch signaling and glycerolipid metabolism pathways. Furthermore, identified transcription factors such as PPARD, LXR, and NOTCH1 might be important in the regulation of bovine milk CHL content. The expression of several positional candidate genes (such as DGAT1, INSIG1 and FAM198B) and their correlation with milk CHL content were further confirmed with RNA sequence data from mammary gland tissues. This is the first GWAS on bovine milk CHL. The identified markers and candidate genes need further validation in a larger cohort for use in the selection of cows with desired milk CHL content.