Genetic Selection Research Articles

39 Developing Precision Agriculture Tools to Capture Behavior and Performance in Extensively Managed Sheep

Abstract Rangeland livestock provide a great opportunity to capture resilience traits due to the significant amount of the year spent grazing a resource-limited environment where they are exposed to extreme weather, predators, and varied terrain. Capturing the ability of an individual to cope with these stressors has the potential to improve animal welfare and productivity in the face of climate change. These measurements need to occur over the course of time of an animal in such an environment or capture the sum of the ability of the animal to cope with the environment. To do this, measurements of resilience and efficiency will be a useful tool to make continued improvement in rangeland livestock through genetic selection. However, the high-throughput phenotyping typically required to capture resilience traits is challenged by the remote location, limited or no access to power and internet, and limited manpower for data collection. Therefore, such tools need to be self-sustaining, automated, and cost-effective to be able to capture data on a large number of individuals in a rangeland setting. To this end, we have been exploring the use of precision livestock tools to capture sheep performance in a rangeland environment. We are currently working on developing a portable walk-over-weighing system to automatically capture an individual’s weight that uses a combination of solar powered portable batteries and an RFID system with the aim to make a compact weighing system that can easily be transported in rough mountainous terrain. This system can be used to capture longitudinal weights in challenging environments, which can be used to develop indicators of resilience, such as the variability in weight over time or changes in weight due to chronic environmental stressors such as a heat wave. Because it is RFID-based, the data can also be used to take stock inventory to track possible predation events or other stock losses. We are also using low-cost commercial-off-the-shelf GPS units to capture animal behavior in these environments. These data can be used to derive a multitude of traits relating to land-use behavior, including water usage and daily distance traveled. The data can also be used to capture social interactions, such as ewe-lamb relationships. While the information content is high for these datatypes, there are also challenges associated with missing or unreliable data. We are currently exploring methods to combat these challenges to provide robust measurements of performance. Through these data, we aim to develop traits that integrate animal performance and behavior to identify animals that are better suited to a rangeland environment. We expect that breeding of such animals will result in a positive impact on productivity, a reduced impact on the ecosystem, and lower mortality rates, thereby improving the sustainability of livestock production systems.

PSVI-13 Dietary Milk Fat Globule Membrane Improves Neonatal Piglet Intestinal Architecture and Enhances Mucosal Diamine Oxidase Activity Following Lipopolysaccharide Challenge

Abstract Early life stressors alter the trajectory of gut development and impair nutrient utilization, barrier function, and animal performance throughout life. Gastrointestinal (GI) maladies increase morbidity and mortality in neonates, and dietary nutrients are essential in supporting GI function. Although maternal milk is the gold-standard for yielding developmental benefits to offspring, genetic selection in the modern sow has resulted in large litter size and milk yield potentially insufficient to achieve the high biological growth potential in sow-reared piglets. Research into milk quality has led to the identification of many bioactive nutrients important in neonatal development. Components of the milk fat globule membrane (MFGM) contribute immensely to neonatal nutrition and gut health. However, mechanisms of actions are still being defined. The objective is to define the effect of MFGM supplementation on neonatal piglet intestinal health. We hypothesize dietary MFGM will enhance piglet intestinal architecture and tight junction (TJ) protein abundance, attenuating systemic lipopolysaccharide (LPS)-induced intestinal barrier disruption. One-day-old piglets (n = 32) were assigned to soy (CON) or MFGM phospholipid supplemented diet (0.75% wt/wt) ± LPS (100 µg/kg body weight) challenge in a 2 × 2 factorial design (n = 8/diet/challenge). Piglets were fed for 21 d and 8 animals/diet received saline or LPS injections 4 h before euthanasia. Piglet weights and feed intake were recorded daily to calculate performance. Intestinal tissues were collected to assess villus height (VH) and crypt depth (CD) by hematoxylin and eosin staining. Two biomarkers of intestinal integrity, intestinal fatty acid-binding protein (I-FABP) and diamine oxidase (DAO), were measured in serum or tissue. Protein abundance of claudin-1 and occludin in ileal and colonic mucosa were detected by Western blot. Data were analyzed by 2 × 2 factorial arrangement of traetments using the PROC MIXED. Dietary MFGM had no adverse impact on growth performance or TJ proteins (P > 0.05). Dietary MFGM increased VH (CON: 348.8 and MFGM: 427.0 ± 26.79 µm) and decreased CD (CON: 166.3 and MFGM: 147.4 ± 8.42 µm) in ileum, thereby increasing the VH: CD ratio (CON: 2.2; MFGM: 3.1 ± 0.13; P < 0.05). Further, LPS treatment increased serum I-FABP by 4.4-fold and decreased jejunal mucosal DAO by 0.5-fold compared with saline treatment (P < 0.05). Additionally, there was a 93.1 % increase in colon DAO activity with MFGM diet compared with soy-fed pigs, regardless of LPS challenge (P < 0.05). Dietary MFGM improved neonatal piglet ileum architecture and increased colon DAO activity, potentially attenuating the intestinal barrier disruption following LPS challenge.

125 Implementing a Genetic Evaluation Program for Acute Hepatopancreatic Necrosis Disease Resistance in Penaeus Vannamei (Pacific White Shrimp)

Abstract This study aims to evaluate the feasibility of a genomic evaluation program for Acute hepatopancreatic necrosis disease (AHPND) resistance in a commercial population of Penaeus vannamei. AHPND is caused by a strain of Vibrio parahaemolyticus (VpAHPND) producing a binary toxin. It is a World Organization for Animal Health (WOAH, Paris, France)-listed bacterial disease that has caused severe economic losses to the shrimp industry worldwide in recent years. The working hypothesis of this study is that the genetic variation in a commercial P. vannamei population allows an efficient genetic and genomic selection program. To investigate the genetic parameters for AHPND resistance, a controlled challenge experiment was performed at the Shrimp Improvement System biosafety laboratory in Miami, Florida, following an immersion challenge protocol using 4.95 × 107 CFU/ mL bacteria and Specific Pathogen Free (SPF) P. vannamei post larvae (n = 2,400) representing 40 selected families. The bioassay was terminated at 3 days post-challenge. Each family consisted of 60 animals, with one-half of the families (n = 20) representing a fast-growth (FG) line and the remaining one-half (n = 20) representing a slow-growth (SG) line. Survival was recorded as a binary of dead or alive at the end of the three days challenge experiment. Variance components were estimated under an animal threshold binary model using a Gibbs sampler. Estimation of genetic parameters was done within lines and by combining all data records. The average hazard risk ratio (HRR) of survival was 80% greater for the FG line (average mortality 40%) than the SG line (average mortality 20%, P < 0.05) based on survival analysis with a 31% mortality rate combining all data records. The posterior mean estimates of heritabilities were 0.14 (± 0.06) for FG, 0.16 (± 0.07) for SG, and 0.38 (± 0.08), combining all records. Estimated breeding values (EBVs) based on the animal threshold binary model ranged from -0.76 to 1.01 on the liability scale. Spearmans’ rank correlation coefficient between the average EBV of parents and the average mortality rates of corresponding families was 0.98. The results suggest that a breeding program for AHPND resistance is feasible. Moreover, the heritabilities suggest that both lines will respond to mass selection due to the presence of additive genetic variation for APHND-survivability. The next step of this project is to genotype animals from every family and implement a genomic selection program. Additionally, high throughput laboratory results and histopathology scores will be introduced in the genetic evaluation as correlated traits.

89 Physiological Mechanisms Related to Feed Efficiency of Beef Cattle

Abstract Improving feed efficiency is essential for the sustainability of the US beef production system. However, achieving this goal is challenging due to various factors such as diet types, genetics, environments, and industry segmentation. To address these difficulties, it is critical to have a fundamental understanding of what contributes to efficient nutrient utilization and feed resources, which can guide future genetic selection and production practices. Despite recent progress, the regulation of feed intake in growing and finishing cattle remains incompletely understood, hindering advances in feed efficiency. Recent research has aimed to advance the hepatic oxidation theory to growing and finishing cattle fed high-concentrate diets and explored the control of appetite by gut peptide hormones. Other factors contributing to variation in feed efficiency include nutrient metabolism and hormonal control of metabolism. Previous research is limited by a lack of in-depth analysis of metabolism due to the inability to time sample collection relative to feed consumption and account for correlations among metabolites. The role of fat metabolism in the rumen has been associated with epithelial inflammation, while inflammation of the gut has been identified as a contributing factor to inefficiencies in nutrient utilization. However, there is still a need to further understand the role of fatty acid metabolism in the induction of inflammation. An issue that limits the further understanding of efficiency is that a wide variety of feedstuffs are utilized by the industry and small changes in the nutrient composition of a diet can have large impacts on efficiency. Therefore, it is important to consider the utilization efficiency of specific nutrients rather than general feed efficiency. Nitrogen utilization efficiency is becoming increasingly important due to the significant economic and environmental ramifications of inefficiencies in nitrogen utilization. There is growing evidence that precision feeding of protein to match requirements can reduce nitrogen excretion without compromising growth and efficiency. In conclusion, a better understanding of the underlying biology contributing to nutrient utilization is crucial for improving feed utilization efficiency in the US beef production system, which will enhance the sustainability of the US beef production system.

32 Feeding Gilts and Sows to Maximize Their Mammary Development

Abstract The task of feeding growing replacement gilts, gestating gilts and sows to maximize their future milk yield is not easy. Yet, this is particularly important when considering the great demands made by the large litters of our current hyperprolific sow genetic lines. One aspect that needs to be considered is the effect of feeding on mammary development taking place before the onset of lactation, which is a major determinant of potential milk yield. One can only attempt to stimulate mammogenesis during periods with rapid mammary development. In swine, these periods are from three months of age until puberty, from 90 days of gestation until farrowing, and throughout lactation. Early studies showed that a 20% or 26% feed restriction from 90 days of age until puberty drastically reduces mammary parenchymal tissue mass. However, in a more recent study, sow milk yield was not altered following a 10% or 20% feed restriction, or a 25% dietary fiber addition (diluting dietary energy by 5%) from 90 days of age to breeding. This absence of effect may be due to the greater feed intake of control gilts in that recent study compared with the older studies. Such a difference in feed intake was likely brought about by genetic selection for faster growing pigs, and it appeared that feed intake of growing gilts can be reduced to 2.7 kg/day without detrimental effects on their future milk yield. During prepuberty, inclusion of the phytoestrogen genistein (2.3 g/day) in the diet increases the number of mammary parenchymal cells. During late gestation, feeding very high energy levels (10.5 Mcal ME/day) may have detrimental effects on mammary development and subsequent milk production. Furthermore, feed intake throughout gestation is important because of its effect on body condition. Gilts that are too thin (< 16 mm backfat thickness) in late gestation have reduced mammary development. A 40% increase in SID Lys via inclusion of additional soybean meal to the diet of gilts from days 90 to 110 of gestation increased mammary parenchymal mass by 44%. On the other hand, providing the same 40% increase in dietary SID Lys to multiparous sows during late gestation had no significant effect on mammary parenchymal mass. These findings therefore support the use of phase-feeding during gestation of gilts only. Increasing circulating concentrations of the growth factor IGF-1 during late gestation also increased mammary parenchymal mass by 22%. Current data clearly demonstrate that feeding management before lactation can be used to improve sow milk yield.

134 Estimating the Heritability of Nitrogen and Carbon Isotopes in the Tail Hair of Beef Cattle

Abstract The natural abundance of nitrogen isotopes (δ15N) in animal tissues is related to the ability of cattle to lose less nitrogen in the urine and has been used to estimate nitrogen use efficiency and feed efficiency. Carbon isotope enrichment (δ13C) has also been used to estimate feed conversion ratio and grazing behavior in beef cattle. There are significant variations between the individual beef cattle in the same environment for δ15N and δ13C of the tail hair. Thus, the objective was to determine the heritability of δ15N and δ13C in the tail hair of tropically adapted beef cattle to further validate their use in genetic breeding programs. A total of 497 Bos indicus steers (269 Brahman and 228 Droughtmaster) were used, and the steers had reliable pedigree information for three generations as they were part of the beef cattle genetic evaluation system in Australia. Two single, mixed breed, contemporary groups of steers are used including the steers weaned in 2019 (n = 254) and steers weaned in 2020 (n = 243). Samples of tail switch hair representing hair segments growing during the dry season were collected and analyzed for δ15N and δ13C. Fixed effects fitted in the linear regression model were age, breed, year (as contemporary groups), and average daily gain during the different seasons. The heritabilities of δ15N and δ13C in the tail hair were estimated at 0.43 ± 0.14, and 0.41 ± 0.15, respectively, which indicates both are moderately heritable traits. The genetic correlation between δ15N and δ13C was negative at -0.78 ± 0.16, and the phenotypic one was -0.40 ± 0.04. The negative correlation can be explained by the contrasting isotope fractionation in the urine of cattle, as urine has less δ15N and more δ13C than the diet. The findings of this study have shown for the first time that both δ15N and δ13C in the tail hair of cattle are heritable traits. These results support the feasibility of utilizing tail hair isotopes as a promising approach for identifying cattle with greater nitrogen use efficiency, which is a key trait in low-protein diets. Moreover, genetic selection for nitrogen-efficient cattle can reduce the environmental impact of beef production.

40 Genetic Selection for Water Intake in Beef Cattle

Abstract The amount of water consumed daily by beef cattle is a heritable trait, but one that likely has varying levels of importance across the US and the world. Results from a USDA-funded water intake and adaptability to water restriction (as a proxy for reduced consumption due to poor water quality) project will be presented.

144 Using Digital Twin Simulations to Optimize Genetic Selection in an Admixed Beef Herd

Abstract Polled cattle, or those that are naturally hornless, are highly advantageous from both an economic and animal welfare perspective. While there are a number of different mutations that result in a polled phenotype, a duplication on bovine chromosome 1, referred to as the Celtic mutation, is the most common within beef cattle. Tropically adapted beef cattle typically have some degree of indicine influence, which are all naturally horned breeds. Polled genes must therefore be introgressed into tropically adapted cattle from naturally polled breeds, such as Angus, carrier of the Celtic mutation. However, Angus are not as well suited for hot, humid climates and introgression cannot happen at the expense of productivity or adaptation. Therefore, strategies must be developed to balance the introgression of poll alleles into a population with continued genetic improvement for economically important traits. This study utilized a privately owned, commercial population of admixed cattle to address this challenge. These cattle (n = ~3,000; single year cohort) were previously genotyped and SNP effects were estimated for heifer pregnancy as part of the internal genetic evaluation of the private enterprise. Management and selection of male and female replacements were modelled using actual production parameters in a digital twin framework. Four different breeding systems, multi-sire natural service, artificial insemination, and invitro fertilization collecting either five or 10 oocytes, were modelled and compared with account for differences in selection intensity. Selection index weighting of poll vs heifer pregnancy was modelled in eight different combinations. Genetic crosses were then simulated using the real genotypes in the genomicSimulation package in R for 5, 10, and 30 years of crosses to evaluate long and short-term consequences. We found that this approach of combining digital twin modelling with simulated crosses can be used to identify the selection strategy that should be applied to optimally balance selection for poll and economically important traits, such as fertility. This modelling approach provides a framework that may be customized to fit specific production parameters or genetic populations representing individual operations. More generally, this particular study used cattle and management practices representative of the northern Australian beef industry, and may be used as a reference for producers in that production system of strategies for increasing the rate of polled animals in their herds. Furthermore, this approach may be applied to the selection for or against other single gene traits, such as many genetic disorders. The USDA is an equal opportunity provider and employer.

PSVII-2 The Impact of Genomic Information Inclusion on Breeding Value Prediction for a Novel Parasite Resistance Indicator Trait in Brazilian Anglo-Nubian Goats: a Pilot Study

Abstract Infection by Haemonchus contortus is the gastrointestinal parasitosis of greatest economic and social importance in the production of goats, being the leading cause of mortality in the Brazilian goat industry. Genetic selection for resistance to parasites in Anglo-Nubian goats has proven to be a viable alternative to traditional methods of controlling gastrointestinal nematodes, producing animals genetically superior in resistance to parasites. This study aimed to evaluate the impact of including genomic information on the estimation of variance components, genetic parameters, and predictive accuracy of genetic values for the new trait Parasitic Resistance (PR) in Anglo-Nubian goats. The PR is generated by measuring Body Condition Score, FAMACHA chart (ranging from 1 to 5), and Fecal Egg Count on a regular scale. These three traits were used as input variables in the CAPRIOVI software, which uses fuzzy logic to create the PR score, ranging from 0 to 10. Animals with lower scores are more likely to be parasitized and require treatment, while animals with higher scores are less likely to be infected. We used information from 352 animals, totaling 3,855 repeated measurements of PR over the years (2001 to 2020) and 1,500 animals in the pedigree. Animals with less than three measurements for any of the three input traits were removed from the dataset. Contemporary groups were built from information from the year of birth, data collection season, birth season, and physiological stage of the animal, considered as fixed effects, and age at the time of data collection as a covariate in an animal repeatability model. A total of 89 animals were genotyped using the Bead Chip Goats SNP50. After quality control, the remaining 38,659 SNPs (Table 1) were used to build the hybrid matrix (H). The variance components (VC) were estimated using the Bayesian Gibbs Sampling method, and breeding values were predicted using the Best Linear Unbiased Prediction (BLUP) and single-step Best Linear Unbiased Prediction (ssGBLUP) methods. The additive genetic variance and heritability estimation ranged from 0.13 to 0.14 and 0.04 to 0.05, respectively (Table 2). The accuracies obtained for PR with BLUP and ssGBLUP were 0.12 and 0.14, respectively, representing a gain of 16.7%. The genomic information (25 % of all animals with phenotypes) with the repeated records improved the predictive model capability based on accuracy. It also improved the VC estimation for PR in Anglo-Nubian goats raised in the Brazilian semi-arid region. These results highlight the positive impact of genetic evaluation of goats for PR, even with few phenotypes and genotyped animals. In addition to elucidating the additive genetic influence of parasite resistance, it can be a great source of information on the selection and production of Anglo-Nubian goats.

PSII-5 Evaluating Haemonchus Contortus Resistance in Hair Sheep Lambs Under Divergent Selection for Reduced Fecal Egg Count

Abstract The gastrointestinal nematode (GIN) Haemonchus contortus is a major threat to global sheep production, a problem exacerbated by increasing levels of anthelmintic resistance. Genetic selection of sheep for reduced fecal egg count (FEC) is hypothesized to improve parasite resistance. This study measured the biological response and worm burden of Dorper x White Dorper (DWD) with high (average = +37.8) or low (average = -12.0) post-weaning FEC estimated breeding values (EBV) and Barbados Blackbelly x Mouflon (BBM) following oral inoculation with 10,000 H. contortus larvae. Lambs (aged 8 months) were grouped by breed and EBV (DWD+, DWD-, BBM) and treatment (inoculated or non-inoculated control) into 6 groups (n = 4/grp). At d 0 and 21, blood samples were collected to measure packed-cell volume (PCV) and serum IgG via enzyme linked immunosorbent assay and at d 21 FEC were additionally recorded. Lambs were subsequently harvested and adult H. contortus counts for each lamb were captured from the abomasum. Data analysis was performed in SAS v 9.4 and significance was set at P < 0.05. In the inoculated lambs, no difference was observed in PCV at d 21, but DWD+ had a greater mean FEC (1,400 + 297 epg) than both DWD- (263 + 167; P = 0.0157) and BBM (50 + 21; P = 0.004). Total serum IgG (ug/mL) was greater in DWD- than DWD+ lambs at both d 0 (686.37 + 50.7 v. 486.15 + 51.25; P = 0.0321) and d 21 (287.16 + 14.33 v. 197.24 + 12.82; P = 0.0034). In BBM, there was no difference in IgG from d 0 (172.80 + 22.44) to d 21 (185.08 ± 4.25). While BBM had reduced IgG at d 0 than both DWD groups, there was no difference between BBM and DWD+ at d 21 (P = 0.4026). Following harvest, inoculated DWD+ had greater worm burden than DWD- (1,330 + 76 v. 818 + 165; P = 0.0308) and both DWD groups were greater than BBM (263 + 120; P = 0.0003). These data confirm previous findings that BBM are more resistant to H. contortus than DWD, and selection for decreased FEC EBV decreased fecal egg output and worm burden within the DWD breed. Future studies will include RNA-sequencing of abomasal epithelial tissue from inoculated and control lambs in an effort to elucidate gene expression differences between divergently selected DWD and BBM sheep infected with H. contortus.

139 Genomic-Based Genetic Parameters of Behavioral Ethogram Traits in Lactating Sows Under Heat Stress Conditions and Their Relationship with Direct Indicators of Heat Tolerance

Abstract Increased global temperatures pose challenges to livestock agriculture. Domestic swine are particularly sensitive to hotter environments due to their inability to sweat, litter bearing nature, difficulty in expressing natural cooling behaviors, and intense genetic selection for production traits. Since animal welfare is central to livestock production as a matter vital to efficiency as much as ethics, developing novel traits that may be genetically related to heat tolerance may assist in improving and sustaining animal welfare. The objective of this study was to develop novel traits of behavior using an ethogram designed for efficiency in production settings, estimate the variance components, and correlate these traits with indicators of heat tolerance and maternal ability. This study considered 1,312 individual Landrace-Large White cross production sows between 6 and 19 days of lactation. Animals were housed in farrowing crates in a commercial setting in southern North Carolina in June and July of 2021, an environment susceptible to potential heat stress. These sows were subjected to a standardized procedure involving a person removing hair from both hips using an electric clipper while an observer was positioned in front of the sow to record behaviors. Scores were later applied to the variations in behavior both for changes in positions and types of vocalizations displayed by the animals during handling. Genotypes were obtained from hair follicles and captured by a 50K porcine SNP panel. Variance components for novel behavior traits were obtained using the BLUPF90+ programs and genomic relationship matrix to estimate genetic correlations of behavior with several indicators of heat tolerance and maternal ability. Heritabilities for behavior traits ranged from 0.131 for vocalization score to 0.072 for shaving time, while heritabilities for heat tolerance and maternal ability ranged from 0.15 to 0.03 for vaginal temperature and respiration efficiency, respectively. The maternal ability traits were based on the single current litter and had the lowest heritabilities ranging from 0.101 to 0.04 for number born alive and number of mummies, respectively. High and positive genetic correlations indicate a potential for coupled selection for both fewer mummified piglets and a greater number of liveborn using the behavior trait of vocalization score. These correlations between favorable maternal traits and behavior traits suggest the potential that one or more complex biological pathways exist that share relevancy between these traits. However, genetic correlations between the behavior traits and heat tolerance indicators were low to negligible, most with a magnitude falling below 0.10, revealing the need for other traits to be used as selection parameters for heat tolerance. Further studies may be able to capture additional environmental effects to improve models of behavior and create indirect measures more obtainable than direct measures of heat tolerance.

A Critical Review of the Effectiveness of Machine Learning & Deep Learning Approaches in Forecasting Stock Market Trends

For a long time, traders as well as researchers have been actively interested in financial market forecasting. A financial market prediction has an interest for investors & researchers since long time. An existing method for predicting stock prices often rely on technical and fundamental analysis, which have limitations in handling the complexity and volume of financial data. To handle complex data sets for forecasting the value of stock using new emerging learning techniques. The most commonly used approach such as artificial neural networks (ANN), neural network techniques, SVM, decision trees algorithm, and random forests. These techniques can capture complex nonlinear relationships between variables and adjust to changing market conditions. The machine learning & deep learning analyze the trend for the future values of stock prediction and provides observation for making decision. The importance of feature selection and data preprocessing are used for improving the prediction accuracy of stock value. The genetic method feature selection concept can reduce the dimensionality of the data and remove irrelevant features, while data preprocessing techniques such as normalization and scaling can improve the stability and convergence of the algorithms. Sentiment analysis of social media data can capture market sentiment and investor behavior, while news articles can provide insights into company performance and industry trends. The accuracy of predictions tends to decrease as the prediction horizon increases and the prediction accuracy varies across different stock markets. A lot of significant work, the most recent stock market-related prediction system includes multiple limitations. Now the conclusion, the projection of stock markets is a hybrid approach & certain parameters for stock market forecasting should be as accurate as possible.

Fecal Microbiome Analysis Distinguishes Bacterial Taxa Biomarkers Associated with Red Fillet Color in Rainbow Trout.

The characteristic reddish-pink fillet color of rainbow trout is an important marketing trait. The gastrointestinal microbiome is vital for host health, immunity, and nutrient balance. Host genetics play a crucial role in determining the gut microbiome, and the host-microbiome interaction impacts the host's phenotypic expression. We hypothesized that fecal microbiota could be used to predict fillet color in rainbow trout. Fish were fed Astaxanthin-supplemented feed for six months, after which 16s rDNA sequencing was used to investigate the fecal microbiome composition in rainbow trout families with reddish-pink fillet coloration (red fillet group, average saturation index = 26.50 ± 2.86) compared to families with pale white fillet color (white fillet group, average saturation index = 21.21 ± 3.53). The linear discriminant analysis effect size (LEFse) tool was used to identify bacterial biomarkers associated with fillet color. The alpha diversity measure shows no difference in the red and white fillet groups. Beta diversity principal component analysis showed clustering of the samples along the white versus red fillet group. The red fillet group has enrichment (LDA score > 1.5) of taxa Leuconostoc lactis, Corynebacterium variabile, Jeotgalicoccus halotolerans, and Leucobacter chromiireducens. In contrast, the white fillet group has an enriched presence of mycoplasma, Lachnoclostridium, and Oceanobacillus indicireducens. The enriched bacterial taxa in the red fillet group have probiotic functions and can generate carotenoid pigments. Bacteria taxa enriched in the white fillet group are either commensal, parasitic, or capable of reducing indigo dye. The study identified specific bacterial biomarkers differentially abundant in fish families of divergent fillet color that could be used in genetic selection to improve feed carotenoid retention and reddish-pink fillet color. This work extends our understanding of carotenoid metabolism in rainbow trout through the interaction between gut microbiota and fillet color.

Genetic diversity and natural selection of apical membrane antigen-1 (ama-1) in Cameroonian Plasmodium falciparum isolates

Antigenic variation associated with genetic diversity in global Plasmodium falciparum apical membrane antigen-1 (PfAMA-1) is a major impediment to designing an effective malaria vaccine. Here, we report the first study on genetic diversity and natural selection of the Pfama-1 gene in P. falciparum isolates from Cameroon. A total of 328 P. falciparum positive samples collected during 2016 and 2019 from five localities of Cameroon were analysed. The ectodomain coding fragment of Pfama-1 gene was amplified for polymorphism profiling and natural selection analysis. A total of 108 distinct haplotypes were found in 203 P. falciparum isolates with considerable nucleotide diversity (π = 0.016) and haplotype diversity (Hd = 0.976). Most amino acid substitutions detected were scattered in ectodomain-I and few specific mutations viz P145L, K148Q, K462I, L463F, N471K, S482L, E537G, K546R and I547F were seen only in Cameroonian isolates. A tendency of natural selection towards positive diversifying selection was observed (Taj-D = 2.058). Five positively selected codon sites (P145L, S283L, Q308E/K, P330S and I547F) were identified, which overlapped with predicted B-cell epitopes and red blood cell (RBC) binding sites, suggesting their potential implication in host immune pressure and parasite-RBC binding complex modulation. The Cameroonian P. falciparum populations indicated a moderate level of genetic differentiation when compared with global sequences, with few exceptions from Vietnam and Venezuela. Our findings provide baseline data on existing Pfama-1 gene polymorphisms in Cameroonian field isolates, which will be useful information for malaria vaccine design.

Effects of genetic selection for fast growth on the development of wooden breast myopathy in broilers

ABSTRACT 1. This study investigated the physiological and molecular mechanisms leading to wooden breast (WB) by comparing growth parameters, oxygen consumption rate, thyroid hormone and gene expression patterns in fast- versus slow-growing broiler lines (Cobb500 and L1986, respectively). 2. WB was observed in Cobb500 broilers only and was first diagnosed on d 21 post-hatch. Compared to the slow-growing L1986, Cobb500 showed a significantly higher growth rate, relative breast weight, breast thickness, meat pH and water-retention capacity (drip loss). Correspondingly, there was significantly lower relative heart weight, relative right ventricular weight, triiodothyronine and thyroxine concentrations and oxygen consumption rate. 3. Compared to No-WB Cobb500, the WB-affected samples exhibited higher relative breast weight, breast thickness and drip loss and lower plasma total thyroxine (T4) concentrations. 4. Selection for fast growth was associated with differential expression of genes involved in hypoxia (PLOD2), energy metabolism (FABP3, FABP4, CD36, and LPL), endoplasmic reticulum stress, muscle regeneration (CSRP3) and fibre-type switching (ANKRD1). WB-affected samples exhibited an upregulation of CSRP3, PLOD2 and ANKRD1, while CD36 was downregulated. Taken together, selection for fast growth and muscle gain is not matched by adequate cardiac and metabolic support systems.

Study of genes polymorphisms in RANK/RANKL/OPG and WNT signaling pathways and their associations with bone parameters in broiler chicken

Limb problems are one of the most common problems with fast-growing meat-type chickens. Various bone abnormalities, which can lead to limping, bone weakness, or even fractures, bring overall discomfort to birds and a loss of production. Genetic aspects are often associated with these side effects on bone stability and are also cited as the dominant cause. These points to a close negative relationship of genetic selection for rapid growth with traits involved in bone integrity. Due to the assumption of an additive genetic background, improvements through genetic tools can be used. Our study is focused on selected genes of important signaling pathways for bone metabolism. We tried to detect polymorphisms that would show associations with selected bone parameters in a total of 48 broilers. Those were fast-growing Ross 308 hybrids and slow-growing Hubbard M22BxJA87A hybrids. The TNFRSF11A and WISP1 genes were tested. A total of fourteen polymorphisms were found, three of them were synonymous and five in the intron. In the case of four polymorphisms found in exons of the TNFRSF11A gene (c.11G > T, c.31G > A, c.37C > G, c.514G > A), associations with the observed bone parameters (bone strength, bone dimensions and bone mass) were demonstrated. The genetic architecture of bone traits is not fully understood, therefore the present study and the knowledge gained can help to increase the potential in poultry breeding processes and thus reduce the death of individuals.

Integrating genome-wide association study into genomic selection for the prediction of agronomic traits in rice (Oryza sativa L.)

Accurately identifying varieties with targeted agronomic traits was thought to contribute to genetic selection and accelerate rice breeding progress. Genomic selection (GS) is a promising technique that uses markers covering the whole genome to predict the genomic-estimated breeding values (GEBV), with the ability to select before phenotypes are measured. To choose the appropriate GS models for breeding work, we analyzed the predictability of nine agronomic traits measured from a population of 459 diverse rice varieties. By the comparison of eight representative GS models, we found that the prediction accuracies ranged from 0.407 to 0.896, with reproducing kernel Hilbert space (RKHS) having the highest predictive ability in most traits. Further results demonstrated the predictivity of GS is altered by several factors. Moreover, we assessed the method of integrating genome-wide association study (GWAS) into various GS models. The predictabilities of GS combined peak-associated markers generated from six different GWAS models were significantly different; a recommendation of Mixed Linear Model (MLM)-RKHS was given for the GWAS-GS-integrated prediction. Finally, based on the above result, we experimented with applying the P-values obtained from optimal GWAS models into ridge regression best linear unbiased prediction (rrBLUP), which benefited the low predictive traits in rice.

Genetic factors influencing milk and fat yields in tropically adapted dairy cattle: insights from quantitative trait loci analysis and gene associations.

The objective of this study was to identify genes associated with 305-day milk yield (MY) and fat yield (FY) that also influence the adaptability of the Thai multibreed dairy cattle population to tropical conditions. A total of 75,776 imputed and actual single nucleotide polymorphisms (SNPs) from 2,661 animals were used to identify genomic regions associated with MY and FY using the single-step genomic best linear unbiased predictions. Fixed effects included herd-yearseason, breed regression, heterosis regression and calving age regression effects. Random effects were animal additive genetic and residual. Individual SNPs with a p-value smaller than 0.05 were selected for gene mapping, function analysis, and quantitative trait loci (QTL) annotation analysis. A substantial number of QTLs associated with MY (9,334) and FY (8,977) were identified by integrating SNP genotypes and QTL annotations. Notably, we discovered 17 annotated QTLs within the health and exterior QTL classes, corresponding to nine unique genes. Among these genes, Rho GTPase activating protein 15 (ARHGAP15) and catenin alpha 2 (CTNNA2) have previously been linked to physiological traits associated with tropical adaptation in various cattle breeds. Interestingly, these two genes also showed signs of positive selection, indicating their potential role in conferring tolerance to trypanosomiasis, a prevalent tropical disease. Our findings provide valuable insights into the genetic basis of MY and FY in the Thai multibreed dairy cattle population, shedding light on the underlying mechanisms of tropical adaptation. The identified genes represent promising targets for future breeding strategies aimed at improving milk and fat production while ensuring resilience to tropical challenges. This study significantly contributes to our understanding of the genetic factors influencing milk production and adaptability in dairy cattle, facilitating the development of sustainable genetic selection strategies and breeding programs in tropical environments.

Variable Selection for Recurrent Events Using Heuristic Approaches: Identifying Informative Variables for Rehospitalization in Schizophrenia Patients

Introduction: Recurrent event data, as a generalization of survival data, are frequently observed in various areas of medical research, including sequential hospitalizations in patients with schizophrenia. As experiencing multiple relapses during schizophrenia can have many implications, such as self-harm or harm to others, loss of education or employment, or other adverse outcomes, identifying and determining the most critical factors related to relapses in this disorder is essential. This study aimed to utilize heuristic approaches for selecting predictor variables in the field of recurrent events with an application to schizophrenia disorder
 Methods: A two-step algorithm was employed to apply a combination of two variable selection methods, recursive feature elimination (RFE) and genetic algorithm feature selection (GAFS), and four modeling techniques: Gradient boosting (GB), artificial neural network (ANN), random forest (RF), and support vector machine (SVM) to simulated recurrent event datasets.
 Results: In most simulation scenarios, the results indicated that the combination of RFE and RF applied to the deviance residual (DR) outperforms the other methods. The RFE-RF-DR selected the following predictor variables: Number of children, age, marital status, and history of substance abuse.
 Conclusion: Our findings revealed that the proposed machine learning-based model is a promising technique for selecting predictor variables associated with a recurrent outcome when analyzing multivariate time-toevent data with recurrent events.

The impacts of thermal heterogeneity across microhabitats on post-settlement selection of intertidal mussels

Rapid genetic selection is critical for allowing natural populations to adapt to different thermal environments such as those that occur across intertidal microhabitats with high degrees of thermal heterogeneity. To address the question of how thermal regimes influence selection and adaptation in the intertidal black mussel Mytilisepta virgata, we continuously recorded environmental temperatures in both tidal pools and emergent rock microhabitats and then assessed genetic differentiation, gene expression patterns, RNA editing level, and cardiac performance. Our results showed that the subpopulations in the tidal pool and on emergent rocks had different genetic structures and exhibited different physiological and molecular responses to high-temperature stress. These results indicate that environmental heterogeneity across microhabitats is important for driving genetic differentiation and shed light on the importance of post-settlement selection for adaptively modifying the genetic composition and thermal responses of these intertidal mussels.