Genetic parameters for yearling male reproduction traits in tropical composite cattle population.

Fertility is economically important but is hard to quantify and measure in breeding programs which has led extensive breeding programs to ignore fertility in their selection criteria. While female fertility traits have been extensively researched, male fertility traits have been largely ignored. It is estimated that 20% to 40% of bulls have sub-fertility, reducing the number of calves born and profits, highlighting the importance of investigating bull fertility. The most practical measure of male fertility is a bull breeding soundness evaluation (BBSE) which assesses structure as well as semen quality and quantity. Generally, traits recorded in a BBSE are neither genetically evaluated nor used for selection in breeding programs. All traits recorded during a BBSE were analyzed through a series of univariate and bivariate linear mixed models using a genomic relationship matrix to estimate genetic parameters. All genotype and phenotype data were obtained from a tropical composite commercial cattle population and imputed to 27,638 single-nucleotide polymorphisms (SNPs) with a total of 2,613 genotyped animals with BBSE records ranging from 616 to 826 animals depending on the trait. The heritabilities of the 27 traits recorded during a BBSE ranged from 0.02 to 0.49. Seven of the male fertility traits were recommended to be included in a breeding program based on their heritability and their phenotypic and genetic correlations. These traits are scrotal circumference, percent normal sperm, proximal droplets, distal midpiece reflex, knobbed acrosomes, vacuoles/teratoids, and sheath score. Using these seven traits in a breeding program would result in higher calving rates, increasing production and profitability.

One of the key profit drivers in any animal breeding program is fertility as it contributes directly to the progeny produced. Typically, fertility traits are hard to quantify and lowly heritable so they are often ignored in breeding programs. The inclusion of male fertility traits could allow for selection on heritable traits that are easy to measure and implement in a commercial breeding program. The utilization of male fertility traits could improve overall fertility and production. Bull breeding soundness evaluation traits were heritable, ranging from low to high, allowing for genetic improvement in those traits. Seven traits were recommended as selection criteria in a breeding program, which included two physical traits and five sperm traits. Implementing these seven traits in a breeding program would allow for a higher calving rate and associated increased profits.

Genetic evaluations of dairy goats with few pedigree data: different approaches to use molecular information.

One of the limitations of implementing animal breeding programs in small-scale or extensive production systems is the lack of production records and genealogical records. In this context, molecular markers could help to gain information for the breeding program. This study addresses the inclusion of molecular data into traditional genetic evaluation models as a random effect by molecular pedigree reconstruction and as a fixed effect by Bayesian clustering. The methods were tested for lactation curve traits in 14 dairy goat herds with incomplete phenotypic data and pedigree information. The results showed an increment of 37.3% of the relationships regarding the originals with MOLCOAN and clustering into five genetic groups. Data leads to estimating additive variance, error variance, and heritability with four different models, including pedigree and molecular information. Deviance Information Criterion (DIC) values demonstrate a greater fitting of the models that include molecular information either as fixed (genetic clusters) or as random (molecular matrix) effects. The molecular information of simple markers can complement genetic improvement strategies in populations with little information.

Genetic Parameters for Limousine Interbeef Genetic Evaluation of Calving Traits.

The aim of this study was to estimate across-country genetic correlations for calving traits (birth weight, calving ease) in the Limousine breed. Correlations were estimated for eight populations (Czech Republic, joint population of Denmark, Finland, and Sweden, France, Great Britain, Ireland, Slovenia, Switzerland, and Estonia). An animal model on raw performance accounting for across-country interactions (AMACI) was used. (Co)variance components were estimated for pairwise combinations of countries. Fixed and random effects were defined by each country according to its national genetic evaluation system. The average across-country genetic correlation for the direct genetic effect was 0.85 for birth weight (0.69-0.96) and 0.75 for calving ease (0.62-0.94). The average correlation for the maternal genetic effect was 0.57 for birth weight and 0.61 for calving ease. After the estimation of genetic parameters, the weighted bending procedure was used to compute the full Interbeef genetic correlation matrix. After bending, direct genetic correlations ranged from 0.62 to 0.84 (with an average of 0.73) for birth weight and from 0.58 to 0.82 (with an average of 0.68) for calving ease.

Cross-Species Comparison of the Pan-RAF Inhibitor LY3009120's Anti-Tumor Effects in Equine, Canine, and Human Malignant Melanoma Cell Lines.

Malignant melanomas (MMs) are the abnormal proliferation of melanocytes and are one of the lethal skin cancers in humans, equines, and canines. Accordingly, MMs in companion animals can serve as naturally occurring animal models, completing conventional cancer models. The common constitutive activation of the MAPK and PI3K pathways in MMs has been described in all three species. Targeting the related pathways is considered a potential option in comparative oncologic approaches. Herein, we present a cross-species comparative analysis exposing a set of ten melanoma cell lines (one human, three equine, and six canine) derived from primary tumors or metastasis to a pan-RAF and RAF dimer inhibitor (LY3009120). Cellular response (proliferation, biomass, metabolism, early and late apoptosis/necrosis, and morphology) and the presence of pathogenic single-nucleotide variants (SNVs) within the mutational hotspot genes BRAF exon 11 and 15, NRAS exon 2 and 3, KRAS exon 2, and KIT exon 11 were analyzed. This study showed that equine malignant melanoma (EMM) cells (MelDuWi) harbor the KRAS p.Q61H mutation, while canine malignant melanoma (CMM) cells (cRGO1 and cRGO1.2) carry NRAS p.G13R. Except for EMM metastasis cells eRGO6 (wild type of the above-mentioned hotspot genes), all melanoma cell lines exhibited a decrease in dose dependence after 48 and 72 h of exposure to LY3009120, independent of the mutation hotspot landscape. Furthermore, LY3009120 caused significant early apoptosis and late apoptosis/necrosis in all melanoma cell lines except for eRGO6. The anti-tumor effects of LY3009120 were observed in nine melanoma cell lines, indicating the potential feasibility of experimental trials with LY3009120. The present study reveals that the irradiation-resistant canine metastasis cells (cRGO1.2) harboring the NRAS p.G13R mutation are significantly LY3009120-sensitive, while the equine metastases-derived eRGO6 cells show significant resistance to LY3009120, which make them both valuable tools for studying resistance mechanisms in comparative oncology.

Use of methane production data for genetic prediction in beef cattle: A review.

Methane (CH4) is a greenhouse gas that is produced and emitted from ruminant animals through enteric fermentation. Methane production from cattle has an environmental impact and is an energetic inefficiency. In the beef industry, CH4 production from enteric fermentation impacts all three pillars of sustainability: environmental, social, and economic. A variety of factors influence the quantity of CH4 produced during enteric fermentation, including characteristics of the rumen and feed composition. There are several methodologies available to either quantify or estimate CH4 production from cattle, all with distinct advantages and disadvantages. Methodologies include respiration calorimetry, the sulfur-hexafluoride tracer technique, infrared spectroscopy, prediction models, and the GreenFeed system. Published studies assess the accuracy of the various methodologies and compare estimates from different methods. There are advantages and disadvantages of each technology as they relate to the use of these phenotypes in genetic evaluation systems. Heritability and variance components of CH4 production have been estimated using the different CH4 quantification methods. Agreement in both the amounts of CH4 emitted and heritability estimates of CH4 emissions between various measurement methodologies varies in the literature. Using greenhouse gas traits in selection indices along with relevant output traits could provide producers with a tool to make selection decisions on environmental sustainability while also considering productivity. The objective of this review was to discuss factors that influence CH4 production, methods to quantify CH4 production for genetic evaluation, and genetic parameters of CH4 production in beef cattle.

Referral patterns and genetic testing outcomes in a contemporary hereditary renal cancer clinic.

OBJECTIVES: Multidisciplinary hereditary tumor clinics are a collaborative format to identify and treat patients with genetic cancer predispositions. The hereditary renal cancer clinic at Indiana University is comprised of a urologic oncologist, medical oncologist, clinical geneticist, and genetic counselor. The clinic holds regular tumor board meetings, where patient histories, pedigrees, imaging, pathology, and management plans are collectively reviewed and discussed. Here we report the contemporary experience for our hereditary renal cancer clinic, with description and analysis of referral patterns, patient profiles, and genetic testing outcomes. MATERIALS AND METHODS: A retrospective review of an IRB-approved, prospectively maintained database of patients seen in the hereditary renal cancer clinic was performed. Patient characteristics, genetic testing results, and disease characteristics were reported and analyzed. RESULTS: A total of 142 patients seen in clinics from January 2018 to June 2023 were included. Patient's median age was between 40 and 49 years old, and 88.7% were Caucasian. The most common reasons for referral were early-onset renal tumors (40%), known hereditary renal cancer syndrome (29%), and hereditary renal cancer syndrome screening (13%). Of those with a tissue diagnosis of renal cell carcinoma, 46.2% were clear cell subtype. The presence of nonrenal syndromic features concerning for hereditary renal tumor syndrome was predictive of pathogenic mutation identification (OR 13.45, P < 0.0001). Patient race and presence of multifocal tumors were not predictive of pathogenic mutation identification. When restricting analysis to patients with an established renal malignancy, high-grade tumor histology was predictive of a pathogenic mutation (OR 8.17, P = 0.012), though higher pathologic stage and nonclear cell histology were not. Referral for early-onset renal tumor (age < 45 years) predicted lower likelihood of pathogenic mutations (OR 0.10, P = 0.0002). FH gene mutations were the most commonly identified pathogenic mutations. Genetic testing of family members (cascade testing) was recommended to 9 patients seen in clinic; a pathogenic mutation was subsequently identified in all but one of these families. CONCLUSIONS: These findings are useful for referring physicians and patients in determining patient referral to hereditary cancer clinics, and for counseling patients undergoing genetic testing. Data from non-Caucasian patients and evolving implications of variants of unclear significance (VUS) may represent future research directions for hereditary renal cancer clinics.

SNARE-ing the Reason for Post-Cardiac Surgery Critical Illness-Related Corticosteroid Insufficiency.

Critical illness-related corticosteroid insufficiency (CIRCI) can cause hemodynamic instability in neonates after congenital heart surgery with manifestations that increase morbidity and potential mortality. We retrospectively reviewed neonates who underwent cardiac surgery between August 2018 and July 2020 at a freestanding children's hospital, had next-generation sequencing performed, and had their cortisol levels drawn as standard clinical care after cardiac surgery. The groups were defined as CIRCI (with a cortisol level ≤ 4.5 mcg/dL) and non-CIRCI (level > 4.5 mcg/dL). The CIRCI group (n = 8) had a 100% incidence of heterozygous gene mutation on STX1A with splicing or loss of function, and this mutation was not found in the non-CIRCI group (n = 8). Additional gene mutations were found in the CIRCI group on RAB6A, ABCA3, SIDT2, and LILRB3, with no incidence in the non-CIRCI group. Three additional mutations were found across the CIRCI group in INPPL1 and FAM189A2 (both splicing and missense), with 12-25% of patients in the non-CIRCI group also displaying these mutations. Novel genetic abnormalities were seen in neonates with symptoms of CIRCI with potential cardiac implications from a gene mutation for STX1A. Compounding effects of additional gene mutations need to be confirmed and explored for potential predisposition to hemodynamic instability during times of stress.

Early-infantile developmental and epileptic encephalopathy: the aetiologies, phenotypic differences and outcomes-a prospective observational study.

In this study, we have evaluated the underlying aetiologies, yield of genetic testing and long-term outcomes in patients with early-infantile developmental and epileptic encephalopathies. We have prospectively studied patients with seizure onset before 3 months of age. Based on the clinical details, neuroimaging, metabolic testing and comprehensive genetic evaluation, patients were classified into different aetiological groups. The phenotypic differences between genetic/unknown groups and remaining aetiologies were compared. Factors that could affect seizure control were also assessed. A total of 80 children (M:F ratio-1.5:1) were recruited. The median seizure onset age was 28 days (range, 1-90 days). The aetiologies were confirmed in 66 patients (83%). The patients were further classified into four aetiological groups: genetic (50%), structural (19%), metabolic (14%; all were vitamin responsive) and unknown (17%). On comparing for the phenotypic differences between the groups, children in the 'genetic/unknown' groups were more frequently observed to have severe developmental delay (Odds Ratio = 57; P < 0.0001), autistic behaviours (Odds Ratio = 37; P < 0.0001), tone abnormalities (Odds Ratio = 9; P = 0.0006) and movement disorder (Odds Ratio = 19; P < 0.0001). Clonic seizures were more common in the vitamin responsive/structural groups (Risk Ratio = 1.36; P = 0.05) as compared to patients with 'genetic/unknown' aetiologies. On the contrary, vitamin responsive/structural aetiology patients were less likely to have tonic seizures (Risk Ratio = 0.66; P = 0.04). Metabolic testing was diagnostic in three out of 41 patients tested (all three had biotinidase deficiency). MRI was abnormal in 35/80 patients (malformation observed in 16/35; 19/35 had non-specific changes that did not contribute to underlying aetiology). A molecular diagnosis was achieved in 53 out of 77 patients tested (69%). Next-generation sequencing had a yield of 51%, while microarray had a yield of 14%. STXBP1 was the most common (five patients) single-gene defect identified. There were 24 novel variants. The mean follow-up period was 30 months (range, 4-72 months). On multivariate logistic regression for the important factors that could affect seizure control (seizure onset age, time lag of first visit to paediatric neurologist and aetiologies), only vitamin responsive aetiology had a statistically significant positive effect on seizure control (P = 0.02). Genetic aetiologies are the most common cause of early-infantile developmental and epileptic encephalopathies. Patients in the genetic/unknown groups had a more severe phenotype. Patients with vitamin responsive epilepsies had the best probability of seizure control.

Updating test-day milk yield factors for use in genetic evaluations and dairy production systems: a comprehensive review.

Various methods have been proposed to estimate daily yield from partial yields, primarily to deal with unequal milking intervals. This paper offers an exhaustive review of daily milk yields, the foundation of lactation records. Seminal advancements in the late 20th century concentrated on two main adjustment metrics: additive additive correction factors (ACF) and multiplicative correction factors (MCF). An ACF model provides additive adjustments to two times AM or PM milk yield, which then becomes the estimated daily yields, whereas an MCF is a ratio of daily yield to the yield from a single milking. Recent studies highlight the potential of alternative approaches, such as exponential regression and other nonlinear models. Biologically, milk secretion rates are not linear throughout the entire milking interval, influenced by the internal mammary gland pressure. Consequently, nonlinear models are appealing for estimating daily milk yields as well. MCFs and ACFs are typically determined for discrete milking interval classes. Nonetheless, large discrete intervals can introduce systematic biases. A universal solution for deriving continuous correction factors has been proposed, ensuring reduced bias and enhanced daily milk yield estimation accuracy. When leveraging test-day milk yields for genetic evaluations in dairy cattle, two predominant statistical models are employed: lactation and test-day yield models. A lactation model capitalizes on the high heritability of total lactation yields, aligning closely with dairy producers' needs because the total amount of milk production in a lactation directly determines farm revenue. However, a lactation yield model without harnessing all test-day records may ignore vital data about the shapes of lactation curves needed for informed breeding decisions. In contrast, a test-day model emphasizes individual test-day data, accommodating various intervals and recording plans and allowing the estimation of environmental effects on specific test days. In the United States, the patenting of test-day models in 1993 used to restrict the use of test-day models to regional and unofficial evaluations by the patent holders. Estimated test-day milk yields have been used as if they were accurate depictions of actual milk yields, neglecting possible estimation errors. Its potential consequences on subsequent genetic evaluations have not been sufficiently addressed. Moving forward, there are still numerous questions and challenges in this domain.

Beyond chromosome analysis: Additional genetic testing practice in a Down syndrome clinic.

Down syndrome (DS) and other genetic conditions have been reported to co-occur in the same person. This study sought to examine the genetic evaluation beyond chromosome analysis of individuals with DS at one DS specialty clinic. Retrospective chart review of genetic testing performed beyond chromosome analysis, the indication for the genetic testing, and the result of the genetic testing from the electronic health record was performed. Demographic information was collected and summary statistics, including mean and frequency, were calculated. The charts of 637 individuals with DS were reviewed. Overall, 146 genetic tests in addition to routine chromosome analysis were performed on 92 individuals with DS. Tests included chromosomal microarray, gene panels, and whole exome sequencing. Tests were performed for the indication of: autism spectrum disorder, celiac disease, dementia, hematologic diseases, and others. Eleven individuals with DS were found to have a second genetic diagnosis. Individuals with DS in one multidisciplinary clinic for DS had a variety of genetic tests beyond chromosomes completed, for varied indications, and with some abnormal results leading to additional diagnoses. Additional genetic testing beyond chromosome analysis is a reasonable consideration for patients with DS who have features suggestive of a secondary diagnosis.

Comparison of different validation methods for single-step genomic evaluations based on a simulated cattle population.

The validation of estimated breeding values from single-step genomic BLUP (ssGBLUP) is an important topic, as more and more countries and animal populations are currently changing their genomic prediction to single-step. The objective of this work was to compare different methods to validate single-step genomic breeding values (GEBV). The investigations were carried out using a simulation study based on the German-Austrian-Czech Fleckvieh population. To test the validation methods under different conditions, several biased and unbiased scenarios were simulated. The application of the widely used Interbull GEBV test to the single-step method is only possible to a limited extent, partly because of genomic preselection, which biases conventional estimated breeding values. Alternative validation methods considered in the study are the linear regression method proposed by Legarra and Reverter, the improved genomic validation including additional regressions as suggested by VanRaden and an adaptation of the Interbull GEBV test using daughter yield deviations (DYD) from ssGBLUP instead of pedigree BLUP. The comparison of the different methods for the different scenarios showed that for males the methods based on GEBV estimate the dispersion more accurate and less biased compared with the GEBV test using DYD from ssGBLUP, whereas the standard Interbull GEBV test is highly affected by genomic preselection for males. For females, the GEBV test using yield deviations from ssGBLUP results in better estimations for the true dispersion.

Genetic evaluation of heat tolerance in Holsteins using test-day production records and NASA POWER weather data.

Heat stress is a prominent issue in livestock production, even for intensively housed dairy herds in Canada. Production records and meteorological data can be combined to assess heat tolerance in dairy cattle. The overall aim of this study was to evaluate the possibility of genetic evaluation for heat tolerance in Canadian dairy cattle. The 2 specific objectives were (1) to estimate the genetic parameters for milk, fat, and protein yield for Holsteins while accounting for high environmental heat loads, and (2) to determine if a genotype-by-environment interaction causes reranking of top-ranked sires between environments with low and high heat loads. A repeatability test-day model with a heat stress function was used to evaluate the genetic merit for milk, fat, and protein yield under heat stress and at thermal comfort for first parity in 5 regions in Canada. The heat stress function for each trait was defined using a specific temperature-humidity index (THI) threshold. The purpose of this function was to quantify the level of heat stress that was experienced by the dairy cattle. The estimated genetic correlation between the general additive genetic effect and the additive effect on the slope of the change in the trait phenotype for milk, fat, and protein yield ranged from -0.16 to -0.30, -0.20 to -0.44, and -0.28 to -0.42, respectively. These negative correlations imply that there is an antagonistic relationship between sensitivity to heat stress and level of production. The heritabilities for milk, fat, and protein yield at 15 units above the THI threshold ranged from 0.15 to 0.27, 0.11 to 0.15, and 0.11 to 0.15, respectively. Finally, the rank correlations between the breeding values from a repeatability model with no heat stress effect and the breeding values accounting for heat stress for the 100 top-ranked bulls indicated possible interaction between milk production traits and THI, resulting in substantial reranking of the top-ranked sires in Canada, especially for milk yield. This is the first study to implement weather data from the NASA POWER database in a genetic evaluation of heat tolerance in dairy cattle. The NASA POWER database is a novel alternative meteorological resource that is potentially more reliable and consistent and with broader coverage than weather station data increasing the number of animals that could be included in a heat stress evaluation.

Variance component estimates, phenotypic characterization, and genetic evaluation of bovine congestive heart failure in commercial feeder cattle.

The increasing incidence of bovine congestive heart failure (BCHF) in feedlot cattle poses a significant challenge to the beef industry from economic loss, reduced performance, and reduced animal welfare attributed to cardiac insufficiency. Changes to cardiac morphology as well as abnormal pulmonary arterial pressure (PAP) in cattle of mostly Angus ancestry have been recently characterized. However, congestive heart failure affecting cattle late in the feeding period has been an increasing problem and tools are needed for the industry to address the rate of mortality in the feedlot for multiple breeds. At harvest, a population of 32,763 commercial fed cattle were phenotyped for cardiac morphology with associated production data collected from feedlot processing to harvest at a single feedlot and packing plant in the Pacific Northwest. A sub-population of 5,001 individuals were selected for low-pass genotyping to estimate variance components and genetic correlations between heart score and the production traits observed during the feeding period. At harvest, the incidence of a heart score of 4 or 5 in this population was approximately 4.14%, indicating a significant proportion of feeder cattle are at risk of cardiac mortality before harvest. Heart scores were also significantly and positively correlated with the percentage Angus ancestry observed by genomic breed percentage analysis. The heritability of heart score measured as a binary (scores 1 and 2 = 0, scores 4 and 5 = 1) trait was 0.356 in this population, which indicates development of a selection tool to reduce the risk of congestive heart failure as an EPD (expected progeny difference) is feasible. Genetic correlations of heart score with growth traits and feed intake were moderate and positive (0.289-0.460). Genetic correlations between heart score and backfat and marbling score were -0.120 and -0.108, respectively. Significant genetic correlation to traits of high economic importance in existing selection indexes explain the increased rate of congestive heart failure observed over time. These results indicate potential to implement heart score observed at harvest as a phenotype under selection in genetic evaluation in order to reduce feedlot mortality due to cardiac insufficiency and improve overall cardiopulmonary health in feeder cattle.

An effective hyper-parameter can increase the prediction accuracy in a single-step genetic evaluation.

The H-matrix best linear unbiased prediction (HBLUP) method has been widely used in livestock breeding programs. It can integrate all information, including pedigree, genotypes, and phenotypes on both genotyped and non-genotyped individuals into one single evaluation that can provide reliable predictions of breeding values. The existing HBLUP method requires hyper-parameters that should be adequately optimised as otherwise the genomic prediction accuracy may decrease. In this study, we assess the performance of HBLUP using various hyper-parameters such as blending, tuning, and scale factor in simulated and real data on Hanwoo cattle. In both simulated and cattle data, we show that blending is not necessary, indicating that the prediction accuracy decreases when using a blending hyper-parameter <1. The tuning process (adjusting genomic relationships accounting for base allele frequencies) improves prediction accuracy in the simulated data, confirming previous studies, although the improvement is not statistically significant in the Hanwoo cattle data. We also demonstrate that a scale factor, α, which determines the relationship between allele frequency and per-allele effect size, can improve the HBLUP accuracy in both simulated and real data. Our findings suggest that an optimal scale factor should be considered to increase prediction accuracy, in addition to blending and tuning processes, when using HBLUP.

Livestock phenomics and genetic evaluation approaches in Africa: current state and future perspectives.

The African livestock sector plays a key role in improving the livelihoods of people through the supply of food, improved nutrition and consequently health. However, its impact on the economy of the people and contribution to national GDP is highly variable and generally below its potential. This study was conducted to assess the current state of livestock phenomics and genetic evaluation methods being used across the continent, the main challenges, and to demonstrate the effects of various genetic models on the accuracy and rate of genetic gain that could be achieved. An online survey of livestock experts, academics, scientists, national focal points for animal genetic resources, policymakers, extension agents and animal breeding industry was conducted in 38 African countries. The results revealed 1) limited national livestock identification and data recording systems, 2) limited data on livestock production and health traits and genomic information, 3) mass selection was the common method used for genetic improvement with very limited application of genetic and genomic-based selection and evaluation, 4) limited human capacity, infrastructure, and funding for livestock genetic improvement programmes, as well as enabling animal breeding policies. A joint genetic evaluation of Holstein-Friesian using pooled data from Kenya and South Africa was piloted. The pilot analysis yielded higher accuracy of prediction of breeding values, pointing to possibility of higher genetic gains that could be achieved and demonstrating the potential power of multi-country evaluations: Kenya benefited on the 305-days milk yield and the age at first calving and South Africa on the age at first calving and the first calving interval. The findings from this study will help in developing harmonized protocols for animal identification, livestock data recording, and genetic evaluations (both national and across-countries) as well as in designing subsequent capacity building and training programmes for animal breeders and livestock farmers in Africa. National governments need to put in place enabling policies, the necessary infrastructure and funding for national and across country collaborations for a joint genetic evaluation which will revolutionize the livestock genetic improvement in Africa.

Estimates of Genetic Parameters for Milk, the Occurrence of and Susceptibility to Clinical Lameness and Claw Disorders in Dairy Goats.

The New Zealand goat industry accesses niche markets for high-value products, mainly formula for infants and young children. This study aimed to estimate the genetic parameters of occurrence and susceptibility of clinical lameness and selected claw disorders and establish their genetic associations with milk production traits. Information on pedigree, lameness, claw disorders, and milk production was collected on three farms between June 2019 and July 2020. The dataset contained 1637 does from 174 sires and 1231 dams. Estimates of genetic and residual (co)variances, heritabilities, and genetic and phenotypic correlations were obtained with uni- and bi-variate animal models. The models included the fixed effects of farm and parity, deviation from the median kidding date as a covariate, and the random effects of animal and residual error. The heritability (h2) estimates for lameness occurrence and susceptibility were 0.07 and 0.13, respectively. The h2 estimates for claw disorder susceptibilities ranged from 0.02 to 0.23. The genotypic correlations ranged from weak to very strong between lameness and milk production traits (-0.94 to 0.84) and weak to moderate (0.23 to 0.84) between claw disorder and milk production traits.

Missing a chance to prevent: disparities in completion of genetic evaluation in high-risk patients with endometrial cancer.

OBJECTIVE: The primary goal of this study is to examine disparities in high-risk endometrial cancer (EC) patients in relation to rates of genetic referrals (GR), testing (GT), and counseling (GC). METHODS: This is a retrospective analysis of patients with newly diagnosed EC between January 1, 2014 and September 1, 2020 at a single institution. Patients were defined as high-risk EC patients when they were 1) diagnosed at 50 years or younger, 2) had a positive family history for cancer or 3) had evidence of loss of mismatch repair protein expression on tumor immunohistochemistry. Rates of GR, GT and GC were analyzed based on race, ethnicity, primary language and insurance status. RESULTS: During the study period, 674 patients were diagnosed with EC and 249 (36.9%) were considered high-risk EC patients. Among high-risk patients, 128 (51.2%) were referred to GT and GC. Of those referred, 103 (80.5%) underwent GT and 85 (66.4%) completed GC. Out of all high-risk patients, 20 (18.4%) were positive for LS on GT and 29 (28.2%) had VUS results. In multivariate analysis, the odds of GT and GC referral were lower among patients who identified as Hispanic (OR=0.40; 95% CI=0.19-0.87; p=0.020). Patients who identified as black were less likely to receive GC when compared to patients of other races (p=0.030). CONCLUSION: It is our hope that through this data we will increase awareness around existing disparities in genetic evaluation for patients with EC and ultimately create strategies to improve equitable access to care for all patients.

Strategies for accommodating gene-edited sires and their descendants in genetic evaluations.

Gene editing has the potential to expedite the rate of genetic gain for complex traits. However, changing nucleotides (i.e., QTN) in the genome can affect the additive genetic relationship among individuals and, consequently, impact genetic evaluations. Therefore, the objectives of this study were to estimate the impact of including gene-edited individuals in the genetic evaluation and investigate modeling strategies to mitigate potential errors. For that, a beef cattle population was simulated for nine generations (N = 13,100). Gene-edited sires (1, 25, or 50) were introduced in generation 8. The number of edited QTN was 1, 3, or 13. Genetic evaluations were performed using pedigree, genomic data, or a combination of both. Relationships were weighted based on the effect of the edited QTN. Comparisons were made using the accuracy, average absolute bias, and dispersion of the estimated breeding values (EBV). In general, the EBV of the first generation of progeny of gene-edited sires were associated with greater average absolute bias and overdispersion than the EBV of the progeny of non-gene-edited sires (P ≤ 0.001). Weighting the relationship matrices increased (P ≤ 0.001) the accuracy of EBV when the gene-edited sires were introduced by 3% and decreased (P ≤ 0.001) the average absolute bias and dispersion for the progeny of gene-edited sires. For the second generation of descendants of gene-edited sires, the absolute bias increased as the number of edited alleles increased; however, the rate of increase in absolute bias was 0.007 for each allele edited when the relationship matrices were weighted compared with 0.10 when the relationship matrices were not weighted. Overall, when gene-edited sires are included in genetic evaluations, error is introduced in the EBV, such that the EBV of progeny of gene-edited sires are underestimated. Hence, the progeny of gene-edited sires would be less likely to be selected to be parents of the next generation than what was expected based on their true genetic merit. Therefore, modeling strategies such as weighting the relationship matrices are essential to avoid incorrect selection decisions if animals that have been edited for QTN underlying complex traits are introduced into genetic evaluations.

Coupling gene editing, a technology with the potential to make specific changes to DNA sequence (e.g., quantitative trait nucleotide, QTN), with genomic selection can generate faster genetic gain in economically important traits. However, gene editing would impact the genetic relationship among individuals and, consequently, genetic evaluations. The objectives of this study were to understand how gene editing impacts genetic prediction and develop strategies to mitigate potential errors in estimated breeding values (EBV). A beef cattle population was simulated (N = 13,100; nine generations) with the introduction of gene-edited sires in generation 8. Genetic evaluations were performed using pedigree and genomic data. Relationships were weighted based on the effect of the edited QTN. In general, the EBV of the first generation of progeny of gene-edited sires were associated with greater average absolute bias and overdispersion than the EBV of the progeny of non-gene-edited sires. Weighting the relationship matrices decreased the average absolute bias and dispersion for the progeny of gene-edited sires. For the second generation of descendants of gene-edited sires, the absolute bias increased by 0.10 for each allele edited. By weighting the relationship matrices, the rate of increase in absolute bias per allele decreased to 0.007. Therefore, when gene-edited sires are included in genetic evaluations, strategies such as weighting the relationship matrices should be considered to avoid incorrect selection decisions.

Impact of age-dependent red blood cell parameters on α-globin gene genotyping in children.

When screening for α-thalassemia in children, adult cut-offs for mean corpuscular volume (MCV) and mean corpuscular hemoglobin (MCH) are generally applied to guide genetic evaluation. However, the normal ranges for MCV and MCH are lower in children than in adults, so we hypothesized that using age-matched cut-offs could lead to a more rational diagnostic strategy. The aim of this study was to evaluate if age-matched cut-offs could be applied advantageously. Data on children referred to a hemoglobin fractionation at the Department of Clinical Biochemistry, Aarhus University Hospital between 2016-2021 were identified in the laboratory information system. α-globin gene (HBA1/HBA2) genotyping was performed using multiplex gap-polymerase chain reaction. A total of 387 children were identified. HBA1/HBA2-genotyping was performed in 207 children (53%), and α-thalassemia was diagnosed in 47 children (23%) with -α3.7/αα being the predominant genotype (13%). We found that 23 children had MCV and MCH levels in the normal age-matched range, and two of these children (9%) were α+ thalassemia carriers with three functional α-globin genes. Using age-specific cut-off levels resulted in a reduction of 23 (11%) genotypes performed. In conclusion, applying age-matched cut-offs for MCV and MCH when screening children for α-thalassemia lead to 11% fewer genotypes performed while 9% carriers of α+ thalassemia (of the medically innocuous genotype -α3.7/αα) would have been overlooked.

Genetic evaluation in phenotypically discordant monozygotic twins with Coats Disease.

PURPOSE: To report the unique case of a pair of phenotypically discordant monozygotic twins, with one of them affected by unilateral Coats disease. CASE REPORT: Both patients underwent a complete ophthalmologic evaluation and were genetically tested with whole-exome sequencing (WES). Any known or unknown potential genetic determinant of Coats disease wasn't found. CONCLUSION: It may suggest a non-genetic etiology for this disorder. This represents, to the best of our knowledge, the first case of genetic analysis of monozygotic twins, one of whom is affected by Coats disease. Further studies are warranted, including performing genetic analysis directly on retinal biopsy tissue.