Non-genetic Effects Research Articles

Association of pedigree indexes and genomic breeding values with the performance of Polish Holstein-Friesian cows.

Pedigree indices (PI) and genomically enhanced breeding values (GBV) of Polish Holstein-Friesian heifers were compared with their future performance. Phenotypes of 15,794 cows from 294 herds were analyzed. The traits evaluated included milk, fat and protein yield, somatic cell score (SCC), stature, overall udder and feet and legs score, heifer conception rate, and longevity. PI and GBV were from official evaluation systems, and performance records were adjusted for non-genetic effects. Correlations between breeding values and adjusted phenotypes were analyzed. Additionally, cows within each herd were divided into quartiles based on their breeding values, and the performance of cows from the top and bottom quartiles was compared. For production traits, similar analyses were conducted separately for high and low milk-producing herds to check for possible genotype by environment interaction. The analyses confirmed the significant correlation between breeding values and cow performance. Incorporating genomic information into PI significantly improved the predictive accuracy for milk, fat, and protein yields, as well as for SCC and stature, with increases ranging from 34 to 64%. Comparisons of cows' performance from the top and bottom quartiles supported these observations for all these traits except protein yield, with differences in performance being 43-92% greater when cows were ranked by GBV instead of PI. In a more productive environment, greater differences in performance were found between the top and bottom quartiles. These findings suggest that Polish breeders can enhance the outcomes of their breeding decisions by using GBV instead of PI. This change offers particular benefits in improving the predictability of future performance for the most economically important traits such as milk yield, fat yield, protein yield, somatic cell score, and stature.

On the Relationship Among Linear Type Traits and Functional Longevity in the Italian Mediterranean Buffalo Using a Weibull Proportional Hazards Model

Weibull proportional hazards model was used to identify the non-genetic effects that affect length of productive life (LPL) of the Italian Mediterranean Buffalo (IMB). Data were provided by the Italian National Association of Buffalo Breeders (ANASB) and included records of reproductive, productive, and linear type traits from 59,943 buffalo with first calving from 2002 to 2019. Data were divided into 4 geographical regions to determine if the relationship between the investigated effects and LPL varied by region. LPL was defined as the number of days from the first calving to culling for those buffaloes that were culled (uncensored) or to the date of the last test-day for those that are still alive (censored). The Weibull model included time-dependent effects of herd-year-season of calving, parity and stage of lactation, production as within-herd deviations, as well as time-independent effects of age at first calving, year of birth, type of reproduction (natural mating vs artificial insemination), classifier and ten linear type traits. The average duration of productive life was 1,604 days. Both year of birth and production level had a significant effect on culling risk. Moreover, culling risk decreased linearly across parities. The reference point for age at first calving relative to other classes was set at 35 months. A significant relationship between linear type traits and relative culling risk was also observed, being highest for buffaloes with the lowest linear scores. The results show that the Weibull model provides consistent and robust risk estimates. Therefore, this model would be recommended for future implementation of the first genetic evaluation of LPL in the Italian Mediterranean Buffalo.

Importance and variability of the paternal component in sow reproductive traits.

Reproductive traits are an integral part of the goals of the breeding programs that contribute to the economic success of production. Reproductive phenotypes such as litter size, number of piglets born alive, or litter weight at birth are mainly attributed to females. Thus, the maternal components can be found by default in quantitative genetics' animal models. Still, paternal contribution to variance components should not be discarded. In this review, we indicate the importance of paternal effects in pig breeding by describing both the biology and genetics of boars' traits, the use of (non-)genetic service sire effects in quantitative genetic models for traits measured on females, and genes involved in male reproduction. We start by describing the important biological traits of boars that have the most important effect on their reproductive abilities, i.e., sexual maturity, sperm quality, and testes parameters. Then we move to the possible environmental effects that could affect those traits of boars (e.g., feed, temperature). The main part of the review in detail describes the genetics of boars' reproductive traits (i.e., heritability) and their direct effect on reproductive traits of females (i.e., genetic correlations). We then move to the use of both genetic and non-genetic service sire effects in quantitative models estimated as their percentage in the total variance of traits, which vary depending on the breed from 1 to 4.5% or from 1 to 2%, respectively. Finally, we focus on the description of candidate genes and confirmed mutations affecting male reproduction success: IGF2, Tgm8, ESR1, ZSWIM7, and ELMO1. In conclusion, the observed variance of paternal effects in female reproduction traits might come from various attributes of boars including biological and genetic aspects. Those attributes of boars should not be neglected as they contribute to the success of female reproductive traits.

Preliminary outcomes on phenotypic and genetic parameter estimates for body weight of indigenous Tswana goats in Botswana

The aims of this study were to estimate the genetic and phenotypic parameters for growth traits and evaluate genetic trends on 585 indigenous Tswana goats. The population was maintained under low input production system at the Department of Agricultural Research in Lesego ranch, Botswana, from 2005 to 2008. Data included birth weight (BW), weaning weight (WW), weight at 8 months (PW), yearling weight (YW), pre-weaning average daily gain (ADG) and two post weaning average daily gains (ADG2 and ADGYW). Data was analysed using general linear model of SAS to determine non-genetic effects. Estimation of genetic and phenotypic parameters were estimated using ASREML fitting an animal model that accounted for fixed effect of parity, sex, type of birth and year of birth. Least squares means for BW, WW, PW and YW were 2.88 ± 0.03, 12.15 ± 0.17, 16.52 ± 0.28 and 21.04 ± 0.32Kg, respectively, while those for ADG, ADG2 and ADGYW were 74.52 ± 1.41, 28.78 ± 1.55 and 33.66 ± 2.28 g/day, respectively. Estimates of heritability for BW, WW, PW and YW were 0.79 ± 0.11, 0.63 ± 0.14, 0.32 ± 0.13 and 0.48 ± 0.16, respectively. The genetic correlations for all the traits studied were positive and moderate to high (0.48 to 0.82) whilst phenotypic correlations ranged from 0.21 to 0.72. Positive average genetic trends of 12.32% (WW), 13.39% (PW) and 7.38% (YW) were attained. The results have demonstrated the potential of this breed to be improved through selection.

Estimation of Genetic Parameters for Milk Production Rate and Its Stability in Holstein Population.

Milk production rate (MPR) refers to the rate of milk secretion per hour (kg/h), calculated from the harvested milk yield and milking interval, and it is considered an appropriate measure to evaluate the production potential of cows. The objective of this study was to estimate the phenotypic and genetic parameters of milk production rate traits. In this study, the milking records of 4760 Holstein cows were collected, and four milk yield traits and six milk production rate traits were defined. The MIXED procedure was used to detect the impacts of non-genetic effects on milk yield and milk production rate traits, including parity, measured season and lactation stage. Variance and covariance components for milk yield and milk production rate traits were estimated using a univariate linear repeatability model. Parity, measurement season and lactation stage had significant effects (p < 0.01) on milk yield, milk production rate and its stability. Milk yield and milk production traits had high heritability, and ranged from 0.25 to 0.39. The stability of milk production rate had low heritability (0.04~0.05). Milk production rate is beneficial for the devolving novel trait in dairy breeding and provides new insights for herd management and genetic selection of production performance of dairy cattle.

313 Many farmers want a prediction of future performance, not necessarily breeding potential

Abstract High heritability is a characteristic of many performance traits in cattle translating to a relatively strong correlation between an (accurate) estimated breeding value for an animal and its (future) production potential. However, the broad sense heritability (i.e., numerator in the formula includes both additive and non-additive genetic variance) is often larger than the narrow sense heritability (i.e., numerator includes only the additive genetic variance) especially for low heritability traits like reproductive performance. Moreover, the repeatability of a trait can be greater again, the difference between the heritability and repeatability is the inclusion of a permanent environmental variance in the numerator. Accurate and pertinent omic-based animal-level features can contribute to an increase in narrow sense heritability owing to a possible reduction in the residual variance; such data can also provide insights into both non-additive genetic variance and the permanent environmental variance. Even at the level of the contemporary group, omic-level data from the likes of bulk blood/saliva/milk sample, can improve how systematic environmental effects are modeled in the mixed model equations thus also reducing the residual variance. The greater heritability will contribute to a strengthening of the correlation between future phenotypic performance potential and estimated additive genetic merit. Importantly, omic measures for individual animals can help predict the permanent environmental effect of that animal capturing the yet untapped contributor to phenotypic variance. Irrespective, predictions need to be replaced by prescriptions; end users are inundated with data yet crave actionable information. Animal breeders have a lush (pardon the pun!) history of distilling estimates of genetic merit for a plethora of traits into a single value per animal (i.e., breeding indexes); this is the first step in transitioning from predictions to prescriptions. Given the familiarity of end users with breeding indexes, the potential exists to develop production indexes to rank commercial animals on future expected performance taking cognizance of genetic and non-genetic effects. Such production indexes align well with the associated breeding index but where the estimates of genetic merit for the traits in question are replaced by estimates of production merit; these estimated production values are the sum of the additive genetic, non-additive genetic and permanent environmental effects. The weighting factors in the production indexes are more short-term using current costs and prices as opposed to breeding indexes which are longer term. In comparison with the breeding indexes, the production indexes can include ancillary information like gender, age, and month of calving/birth. Like breeding indexes, they are updated in real time. Examples of the application of genome-enabled production indexes are guides for valuing animals for purchase or culling.

Effects of brain estrogen receptor on depression and its mechanism of action

Depression is a refractory disease involving multiple pathologic changes, characterized by long-term disease course, low curative rate, and complex symptoms. However, the pathologic mechanism of this disease is incompletely known. Current research mainly focuses on the monoamine neurotransmitter hypothesis, neuroendocrine-related hypothesis, neuroinflammation hypothesis, and brain structure-function hypothesis. An intimate interplay exists between estrogen with the development and progression of depression. Estrogen receptors are widely distributed in the central nervous system, the expression of which can exert genetic and nongenetic effects to improve depression through regulating the level of neurotransmitters, mediating the function of the hypothalamus-pituitarium-adrenal axis, alleviating neuroinflammation, and protecting neurons. This study elaborated on the regulatory effect and mechanism of brain estrogen receptors on depression, hoping to provide new ideas for the clinical treatment of depression.

Investigating the impact of paternal age, paternal heat stress, and estimation of non-genetic paternal variance on dairy cow phenotype

BackgroundLinear models that are commonly used to predict breeding values in livestock species consider paternal influence solely as a genetic effect. However, emerging evidence in several species suggests the potential effect of non-genetic semen-mediated paternal effects on offspring phenotype. This study contributes to such research by analyzing the extent of non-genetic paternal effects on the performance of Holstein, Montbéliarde, and Normande dairy cows. Insemination data, including semen Batch Identifier (BI, a combination of bull identification and collection date), was associated with various traits measured in cows born from the insemination. These traits encompassed stature, milk production (milk, fat, and protein yields), udder health (somatic cell score and clinical mastitis), and female fertility (conception rates of heifers and cows). We estimated (1) the effects of age at collection and heat stress during spermatogenesis, and (2) the variance components associated with BI or Weekly aggregated BI (WBI).ResultsOverall, the non-genetic paternal effect estimates were small and of limited biological importance. However, while heat stress during spermatogenesis did not show significant associations with any of the traits studied in daughters, we observed significant effects of bull age at semen collection on the udder health of daughters. Indeed, cows born from bulls collected after 1500 days of age had higher somatic cell scores compared to those born from bulls collected at a younger age (less than 400 days old) in both Holstein and Normande breeds (+ 3% and + 5% of the phenotypic mean, respectively). In addition, across all breeds and traits analyzed, the estimates of non-genetic paternal variance were consistently low, representing on average 0.13% and 0.09% of the phenotypic variance for BI and WBI, respectively (ranging from 0 to 0.7%). These estimates did not significantly differ from zero, except for milk production traits (milk, fat, and protein yields) in the Holstein breed and protein yield in the Montbéliarde breed when WBI was considered.ConclusionsOur findings indicate that non-genetic paternal information transmitted through semen does not substantially influence the offspring phenotype in dairy cattle breeds for routinely measured traits. This lack of substantial impact may be attributed to limited transmission or minimal exposure of elite bulls to adverse conditions.

From genetic mosaicism to tumorigenesis through indirect genetic effects.

Genetic mosaicism has long been linked to aging, and several hypotheses have been proposed to explain the potential connections between mosaicism and susceptibility to cancer. It has been proposed that mosaicism may disrupt tissue homeostasis by affecting intercellular communications and releasing microenvironmental constraints within tissues. The underlying mechanisms driving these tissue-level influences remain unidentified, however. Here, we present an evolutionary perspective on the interplay between mosaicism and cancer, suggesting that the tissue-level impacts of genetic mosaicism can be attributed to Indirect Genetic Effects (IGEs). IGEs can increase the level of cellular stochasticity and phenotypic instability among adjacent cells, thereby elevating the risk of cancer development within the tissue. Moreover, as cells experience phenotypic changes in response to challenging microenvironmental conditions, these changes can initiate a cascade of nongenetic alterations, referred to as Indirect non-Genetic Effects (InGEs), which in turn catalyze IGEs among surrounding cells. We argue that incorporating both InGEs and IGEs into our understanding of the process of oncogenic transformation could trigger a major paradigm shift in cancer research with far-reaching implications for practical applications.

Uncertainty in the mating strategy of honeybees causes bias and unreliability in the estimates of genetic parameters

BackgroundBreeding queens may be mated with drones that are produced by a single drone-producing queen (DPQ), or a group of sister-DPQs, but often only the dam of the DPQ(s) is reported in the pedigree. Furthermore, datasets may include colony phenotypes from DPQs that were open-mated at different locations, and thus to a heterogeneous drone population.MethodsSimulation was used to investigate the impact of the mating strategy and its modelling on the estimates of genetic parameters and genetic trends when the DPQs are treated in different ways in the statistical evaluation model. We quantified the bias and standard error of the estimates when breeding queens were mated to one DPQ or a group of DPQs, assuming that this information was known or not. We also investigated four alternative strategies to accommodate the phenotypes of open-mated DPQs in the genetic evaluation: excluding their phenotypes, adding a dummy pseudo-sire in the pedigree, or adding a non-genetic (fixed or random) effect to the statistical evaluation model to account for the origin of the mates.ResultsThe most precise estimates of genetic parameters and genetic trends were obtained when breeding queens were mated with drones of single DPQs that are correctly assigned in the pedigree. However, when they were mated with drones from one or a group of DPQs, and this information was not known, erroneous assumptions led to considerable bias in these estimates.Furthermore, genetic variances were considerably overestimated when phenotypes of colonies from open-mated DPQs were adjusted for their mates by adding a dummy pseudo-sire in the pedigree for each subpopulation of open-mating drones. On the contrary, correcting for the heterogeneous drone population by adding a non-genetic effect in the evaluation model produced unbiased estimates.ConclusionsKnowing only the dam of the DPQ(s) used in each mating may lead to erroneous assumptions on how DPQs were used and severely bias the estimates of genetic parameters and trends. Thus, we recommend keeping track of DPQs in the pedigree, and not only of the dams of DPQ(s). Records from DPQ colonies with queens open-mated to a heterogeneous drone population can be integrated by adding non-genetic effects to the statistical evaluation model.

The impact of social-environmental factors on IQ in syndromic intellectual developmental disabilities.

Despite having the same underlying genetic etiology, individuals with the same syndromic form of intellectual developmental disability (IDD) show a large degree of interindividual differences in cognition and IQ. Research indicates that up to 80% of the variation in IQ scores among individuals with syndromic IDDs is attributable to nongenetic effects, including social-environmental factors. In this narrative review, we summarize evidence of the influence that factors related to economic stability (focused on due to its prevalence in existing literature) have on IQ in individuals with syndromic IDDs. We also highlight the pathways through which economic stability is hypothesized to impact cognitive development and drive individual differences in IQ among individuals with syndromic IDDs. We also identify broader social-environmental factors (e.g., social determinants of health) that warrant consideration in future research, but that have not yet been explored in syndromic IDDs. We conclude by making recommendations to address the urgent need for further research into other salient factors associated with heterogeneity in IQ. These recommendations ultimately may shape individual- and community-level interventions and may inform systems-level public policy efforts to promote the cognitive development of and improve the lived experiences of individuals with syndromic IDDs.

Sexual Selection Increases Male Behavioral Consistency in Drosophila melanogaster.

AbstractSexual selection has been suggested to influence the expression of male behavioral consistency. However, despite predictions, direct experimental support for this hypothesis has been lacking. Here, we investigated whether sexual selection altered male behavioral consistency in Drosophila melanogaster-a species with both pre- and postcopulatory sexual selection. We took 1,144 measures of locomotor activity (a fitness-related trait in D. melanogaster) from 286 flies derived from replicated populations that have experimentally evolved under either high or low levels of sexual selection for >320 generations. We found that high sexual selection males were more consistent (decreased within-individual variance) in their locomotor activity than male conspecifics from low sexual selection populations. There were no differences in behavioral consistency between females from the high and low sexual selection populations. Furthermore, while females were more behaviorally consistent than males in the low sexual selection populations, there were no sex differences in behavioral consistency in high sexual selection populations. Our results demonstrate that behavioral plasticity is reduced in males from populations exposed to high levels of sexual selection. Disentangling whether these effects represent an evolved response to changes in the intensity of selection or are manifested through nongenetic parental effects represents a challenge for future research.

Estimation of genetic parameters for bull conception rate and its genetic correlations with semen production traits in Japanese Black bulls

The P of achieving pregnancy is an important trait of bull fertility in beef cattle and is defined as the bull conception rate (BCR). This study aimed to clarify and better understand the genetic architecture of the BCR calculated using artificial insemination and pregnancy diagnosis records from a progeny testing program in Japanese Black bulls. In this study, we estimated the genetic parameters of the BCR and their correlation with semen production traits. In addition, we assessed the correlated responses in BCR by considering the selection of semen production traits. Nine hundred and sixteen Japanese Black bulls were selected based on fertility, with 28 869 pregnancy diagnostic records from the progeny testing program. Our results showed that the heritability estimate was 0.04 in the BCR at the first service and 0.14 in BCR for the three services, and an increase in the inbreeding coefficient led to a significant decrease in BCR. The phenotypic trend of BCR remained almost constant over the years, whereas the genetic trend increased. In addition, the changes in the progeny testing year effect showed a similar tendency to the phenotypic trends, suggesting that the phenotypic trends could be mainly due to non-genetic effects, including progeny testing year effects. The estimated genetic correlation of BCR with sperm motility traits was favorably moderate to high (ranging from 0.49 to 0.97), and those with sperm quantity traits such as semen volume were favorably low to moderate (ranging from 0.23 to 0.51). In addition, the correlated responses in BCR at the first service by selection for sperm motility traits resulted in a higher genetic gain than direct selection. This study provides new insights into the genetic factors affecting BCR and the possibility of implementing genetic selection to improve BCR by selecting sperm motility traits in Japanese Black bulls.

Maternal genetic and non-genetic effects on the development of exploration and anxiety-like behaviours in a native Australian rodent, the fawn-footed mosaic-tailed rat Melomys cervinipes

Abstract Personality in non-human animals has been a popular area of research; however, it is still unknown how genetic and non-genetic factors influence the development of personality in many species. Therefore, we investigated how maternal genetic and non-genetic effects influenced adult offspring personality (exploration and anxiety) in the fawn-footed mosaic-tailed rat Melomys cervinipes. We first measured the amount of maternal care mothers provided to their offspring. Later, we assessed mothers and adult offspring over two testing sessions for exploratory behaviour using open field and novel object tests, and anxiety behaviour in a light/dark test. We calculated repeatability of behaviours and used parent–offspring regressions to assess heritability of behaviours. No measure of maternal care significantly influenced offspring personality. However, exploration of new spaces was constrained by maternal genetic effects. In contrast, anxiety and exploration of novel objects was more flexible, suggesting these behaviours may be more influenced by an individual’s experiences during development.

Investigating pedigree- and SNP-associated components of heritability in a wild population of Soay sheep

Estimates of narrow sense heritability derived from genomic data that contain related individuals may be biased due to the within-family effects such as dominance, epistasis and common environmental factors. However, for many wild populations, removal of related individuals from the data would result in small sample sizes. In 2013, Zaitlen et al. proposed a method to estimate heritability in populations that include close relatives by simultaneously fitting an identity-by-state (IBS) genomic relatedness matrix (GRM) and an identity-by-descent (IBD) GRM. The IBD GRM is identical to the IBS GRM, except relatedness estimates below a specified threshold are set to 0. We applied this method to a sample of 8557 wild Soay sheep from St. Kilda, with genotypic information for 419,281 single nucleotide polymorphisms. We aimed to see how this method would partition heritability into population-level (IBS) and family-associated (IBD) variance for a range of genetic architectures, and so we focused on a mixture of polygenic and monogenic traits. We also implemented a variant of the model in which the IBD GRM was replaced by a GRM constructed from SNPs with low minor allele frequency to examine whether any additive genetic variance is captured by rare alleles. Whilst the inclusion of the IBD GRM did not significantly improve the fit of the model for the monogenic traits, it improved the fit for some of the polygenic traits, suggesting that dominance, epistasis and/or common environment not already captured by the non-genetic random effects fitted in our models may influence these traits.

Exploring definitions of daily enteric methane emission phenotypes for genetic evaluations using a population of indoor-fed multi-breed growing cattle with feed intake data.

Genetic selection has been identified as a promising approach for reducing enteric methane (CH4) emissions; a prerequisite for genetic evaluations; however, these are estimates of the necessary genetic parameters based on a population representative of where the genetic evaluations will be used. The objective of this study was, therefore, to derive genetic parameters for a series of definitions of CH4, carbon dioxide (CO2), and dry matter intake (DMI) as well as genetic correlations between CH4, CO2, and DMI in a bid to address the paucity of studies involving methane emissions measured in beef cattle using GreenFeed systems. Lastly, estimated breeding values (EBV) were generated for nine alternative definitions of CH4 using the derived genetic parameters; the EBV were validated against both phenotypic performance (adjusted for non-genetic effects) and the Legarra and Reverter method comparing EBV generated for a subset of the dataset compared to EBV generated from the entire dataset. Individual animal CH4 and CO2 records were available from a population of 1,508 multi-breed growing beef cattle using 10 GreenFeed Emission Monitoring systems. Nine trait definitions for CH4 and CO2 were derived: individual spot measures, the average of all spot measures within a 3-h, 6-h, 12-h, 1-d, 5-d, 10-d, and 15-d period and the average of all spot measures across the full test period (20 to 114 d on test). Heritability estimates from 1,155 animals, for CH4, increased as the length of the averaging period increased and ranged from 0.09 ± 0.03 for the individual spot measures trait to 0.43 ± 0.11 for the full test average trait; a similar trend existed for CO2 with the estimated heritability ranging from 0.17 ± 0.04 to 0.50 ± 0.11. Enteric CH4 was moderately to strongly genetically correlated with DMI with a genetic correlation of 0.72 ± 0.02 between the spot measures of CH4 and a 1-d average DMI. Correlations, adjusted for heritability, between the adjusted phenotype and (parental average) EBV ranged from 0.56 to 1.14 across CH4 definitions and the slope between the adjusted phenotype and EBV ranged from 0.92 to 1.16 (expectation = 1). Validation results from the Legarra and Reverter regression method revealed a level bias of between -0.81 and -0.45, a dispersion bias of between 0.93 and 1.17, and ratio accuracy (ratio of the partial evaluation accuracies on whole evaluation accuracies) from 0.28 to 0.38. While EBV validation results yielded no consensus, CH4 is a moderately heritable trait, and selection for reduced CH4 is achievable.

The role of gene expression hypoxia-inducible factor-1a and serum level monocyte chemoattractant protein-1 in the incidence of chronic myeloid leukemia in Iraqi patients

Abstract: BACKGROUND: Chronic myeloid leukemia (CML) is a hematopoietic stem cell malignancy described by a translocation between chromosomes 9 and 22. There are many factors genetic or nongenetic effect on disease progression such as growth factors and transcription factors act as oncogenes or tumor suppressor genes. OBJECTIVES: The purpose of this research was to investigate the role of hypoxia-inducible factor (HIF1A) gene expression with CML, as well as the role of monocyte chemoattractant protein-1 (MCP-1) as a predictive biomarker on disease progression. MATERIALS AND METHODS: The current study consists of three groups: first group includes 50 newly diagnosed CML patients (females 22 and males 28), second group consists of 50 CML patients treated with tyrosine kinase inhibitor (TKI) with a complete molecular response (p210 BCR-ABL transcript levels ≤0.1% IS) (female 25 and male 25), and third group included another 50 apparently healthy volunteers (female 20 and male 30). The patients were admitted from the National Center of Hematology/Mustansiriyah University. All patients are diagnosed according to a complete blood count (CBC), a bone marrow examination, and a BCR-ABL gene test. RESULTS: Reverse transcription-quantitative polymerase chain reaction was applied to assess the expression levels of the HIF-1A gene and serum level of MCP1 by enzyme-linked immunosorbent assay. The results displayed downregulated of the HIF1A gene messenger RNA in CML patients in comparison to the controls group, as well as no statistically significant link was discovered when the fold of expression was correlated with the age and gender of CML patients. CONCLUSION: HIF1-alpha gene has an important role in pathological pathways such as angiogenesis. According to this study, HIF1-alpha gene is not an appropriate prognostic biomarker for detecting the risk of CML as well as MCP1 is thought to be a predictor of CML progression.

Estimation of genetic and non-genetic effects on productive life of Iranian Holstein dairy cows.

Understanding the factors that influence the lifespan of dairy cows is crucial for enhancing their productive life (PL). This study aimed to investigate the impact of genetic and environmental effects on the PL of Holstein cows. Data included 82,505 cows from 1952 sires that calved for the first time between 2001 and 2016. PL was defined from first calving to culling. Proportional hazard models, assuming a piecewise Weibull distribution of the baseline hazard function, were utilized to account for time-dependent effects, such as herd size variations, year-season, milk yield, fat and protein contents, and the time-independent fixed effect of age at first calving. Herd-year and sire effects were considered as random effects. All effects showed significant associations with PL (p< 0.001). The relative risk of culling was higher in heifers that calved at an older age and cows that calved during the cold season. Moreover, cows with lower production had a significantly shorter PL compared with high-producing cows. The effective heritability in the absence of censored data was estimated at 0.15. These findings suggest that greater attention should be paid to regular and accurate breeding programs, which are essential for enhancing profitability and the PL of Iranian dairy cows.

Inbreeding Depression and Purging for Meat Performance Traits in German Sheep Breeds.

This study provides estimates on genetic parameters, inbreeding depression and purging for meat performance measures from 25 German sheep breeds. All German meat, merino sheep breeds and breeds of other breeding directions with a sufficient number of pedigree and performance data were included in this study. Phenotypic traits retrieved from the national database OviCap were evaluated: daily weight gain, meatiness score and ultrasound measurements for muscle and fat thickness. We employed animal models to estimate heritability, variance and covariance components for these meat performance traits as well as inbreeding depression and purging. The heritabilities, on average, reached estimates of 0.55, 0.34, 0.53 and 0.61 for daily weight gain, meatiness score and ultrasound measurements for muscle and fat thickness, respectively. We estimated the linear regression slopes for the individual rate of inbreeding, new and ancestral inbreeding, as well as the inbreeding coefficient and its interaction with the inbreeding coefficient of Ballou, employing animal models with non-genetic effects and the additive genetic effect of the animal. Across all breeds, inbreeding was only significant for daily weight gain, whereas for all other traits, estimates were not significant. Within sheep breeds, we found significant inbreeding depression for daily weight gain in German Mutton Merino and German Blackheaded Mutton as well as for the meatiness score in German Whiteheaded Mutton. Significant effects for purging, based on ancestral inbreeding and the interaction effect of the classical inbreeding coefficient with the inbreeding coefficient of Ballou, were not obvious either across or within any sheep breed. A 1% increase in inbreeding significantly decreased the phenotypic trait median of daily weight gain across all sheep breeds by 0.50% and 0.70% of phenotypic and genetic standard deviation, respectively. Purging effects due to ancestral inbreeding were not significant in any breed or across breeds. The results of this study may indicate that inbreeding depression may be more harmful in traits under stronger selection than in traits that exert low selection pressure. The results of this study demonstrate the different effects that result in meat performance traits due to inbreeding. With increasing rates of inbreeding and critical effective population sizes, selection intensity for breeding objectives has to be critically reviewed for each sheep breed. Inbreeding depression and purging should be evaluated in order to prevent a decrease in trait means due to inbreeding and to determine whether detrimental alleles are eliminated.

Sperm specificity and potential paternal effects in gynogenesis in the Amazon Molly (Poecilia formosa)

The Amazon Molly (Poecilia formosa) reproduces by gynogenesis, a relatively rare form of asexual reproduction where sperm is required to trigger embryogenesis, but male genes are not incorporated into the genome of the embryo. Studying gynogenesis could isolate paternal non-genetic effects on reproduction. This study explored which of eleven related species can produce sperm to trigger gynogenesis through natural mating in P. formosa, and whether sympatry affects reproductive success in P. formosa. Reproductive outcomes measured were relative reproductive output (number of offspring in the first brood divided by female standard length), relative embryo output (number of embryos in the first brood divided by female standard length) and combined relative reproductive output (sum of relative reproductive output and relative embryo output). For large (&gt;4 cm) P. formosa, combined relative reproductive output was higher with sympatric Atlantic Molly (Poecilia mexicana) males than with allopatric P. mexicana males. P. formosa produced live offspring or late-stage embryos with all species tested in the genera Poecilia and Limia but did not produce offspring or embryos with males from the genera Gambusia, Girardinus, Heterandria, Poeciliopsis, or Xiphophorus. This information, as well as the limitations characterized in this study, will set a foundation for use of P. formosa as a model for paternal effects and the species specificity of sperm on fertilization, embryogenesis, and reproductive success.