Individual Selection Research Articles

Rapid and High Throughput Hydroponics Phenotyping Method for Evaluating Chickpea Resistance to Phytophthora Root Rot

Phytophthora root rot (PRR) is a major constraint to chickpea production in Australia. Management options for controlling the disease are limited to crop rotation and avoiding high risk paddocks for planting. Current Australian cultivars have partial PRR resistance, and new sources of resistance are needed to breed cultivars with improved resistance. Field- and glasshouse-based PRR resistance phenotyping methods are labour intensive, time consuming, and provide seasonally variable results; hence, these methods limit breeding programs’ abilities to screen large numbers of genotypes. In this study, we developed a new space saving (400 plants/m2), rapid (<12 days), and simplified hydroponics-based PRR phenotyping method, which eliminated seedling transplant requirements following germination and preparation of zoospore inoculum. The method also provided post-phenotyping propagation all the way through to seed production for selected high-resistance lines. A test of 11 diverse chickpea genotypes provided both qualitative (PRR symptoms) and quantitative (amount of pathogen DNA in roots) results demonstrating that the method successfully differentiated between genotypes with differing PRR resistance. Furthermore, PRR resistance hydroponic assessment results for 180 recombinant inbred lines (RILs) were correlated strongly with the field-based phenotyping, indicating the field phenotype relevance of this method. Finally, post-phenotyping high-resistance genotypes were selected. These were successfully transplanted and propagated all the way through to seed production; this demonstrated the utility of the rapid hydroponics method (RHM) for selection of individuals from segregating populations. The RHM will facilitate the rapid identification and propagation of new PRR resistance sources, especially in large breeding populations at early evaluation stages.

Evaluation of performance of genoSCORETM for predicting onset of Alzheimer’s disease in a Japanese population

AbstractBackgroundThe development of diagnostic tools to identify disease risk is critical to enable selection of suitable individuals for inclusion in clinical trials, cohort studies and ultimately to identify patients most likely to benefit from newly approved therapies. Cytox has developed and validated a polygenic risk scoring (PRS) algorithm, genoSCORETM, for predicting the Late Onset Alzheimer’s disease (AD) based on the work pioneered by Escott‐Price, Williams et al 1. However, both training and testing has been performed in study populations containing primarily individuals with Caucasian ethnicity. To ensure that genoSCORE can equally be applicable to all ethnic groups, we have conducted an initial evaluation to understand predictive accuracy for the onset of AD in a Japanese population.MethodsThe PRS approach used in this study is built from a sum of weighted contributions of over 100,000s SNPs associated with disease2. Due to the limited SNP coverage of existing genetic data, we only used 63,499 SNPs and utilized the core genoSCORE algorithm to calculate PRS in a cohort of 2,081 AD and 2,327 CN Japanese subjects from J‐ADNI3 and Niigata University.ResultsThe preliminary result shows an AUC of 0.659 (0.643‐0.675, 95% CI) between AD and CN subjects while PRS presents a bimodal distribution, but the main distribution trend is comparable to a normal distribution of PRS of the ADNI (US) subjects. Although this is significantly less than that seen for Caucasian individuals in the ADNI study, it compares well with the results generated when the reduced number of SNPs are used only in the ADNI cohort subjects (AUC = 0.691).ConclusionsThe preliminary results show the potential use of genoSCORE in the Japanese population. However, the results are likely affected by the limited SNP coverage from the available genetic data for the Japanese population. To determine the true performance of the genoSCORE algorithm in a Japanese population, genotyping samples from this study using our proprietary variaTECTTM II array providing full SNP coverage is in progress. We will then determine the performance and make adjustments to the algorithm if required in a Japanese population of suitably characterized Alzheimer’s disease patients and age‐matched healthy controls.

Phenoptosis and the Various Types of Natural Selection.

In the first description of evolution, the fundamental mechanism is the natural selection favoring the individuals best suited for survival and reproduction (selection at the individual level or classical Darwinian selection). However, this is a very reductive description of natural selection that does not consider or explain a long series of known phenomena, including those in which an individual sacrifices or jeopardizes his life on the basis of genetically determined mechanisms (i.e., phenoptosis). In fact, in addition to (i) selection at the individual level, it is essential to consider other types of natural selection such as those concerning: (ii) kin selection and some related forms of group selection; (iii) the interactions between the innumerable species that constitute a holobiont; (iv) the origin of the eukaryotic cell from prokaryotic organisms; (v) the origin of multicellular eukaryotic organisms from unicellular organisms; (vi) eusociality (e.g., in many species of ants, bees, termites); (vii) selection at the level of single genes, or groups of genes; (viii) the interactions between individuals (or more precisely their holobionts) of the innumerable species that make up an ecosystem. These forms of natural selection, which are all effects and not violations of the classical Darwinian selection, also show how concepts as life, species, individual, and phenoptosis are somewhat not entirely defined and somehow arbitrary. Furthermore, the idea of organisms selected on the basis of their survival and reproduction capabilities is intertwined with that of organisms also selected on the basis of their ability to cooperate and interact, even by losing their lives or their distinct identities.

Аксиологическая неоднозначность социального отбора в образовании

The relevance of the problem is caused by the need for young people to make a conscious choice of life priorities and guidelines. The purpose of this article is to study the value foundations of individual choice and social selection in education. Different approaches to understanding the significance of the selection function of educational activity are presented. A classification of the priorities of professional and social choice, as well as criteria for choosing the optimal method of individual development, has been completed. The factors that determine the meaning of education in historical retrospect are studied. The internal mechanisms of the professional and educational structure of society, making it a channel of social mobility, are considered. At the same time, a position is presented that shows the ambiguity of the influence of one or another mechanism on the future — some events can simultaneously contribute to both vertical and horizontal mobility. The author also strives to identify the axiological principles of establishing the boundaries of attributing a particular case to different social elevators. The question is raised about the moral choice of a teacher when organizing teaching activities that take into account the abilities and prospects of students. The ambivalence of this situation in relation to the influence on the further activity of the subject is pointed out, and in this sense, both the inconsistency and the dialectical unity of social selection and personal choice are established.

Participatory tree selection and fruit morphological characterization ofPhoebe cooperiana(U.N Kanjilal ex A. Das) in the Eastern Himalayas of India

AbstractSelection of desirable phenotypes and characterization of variability in economically important traits are essential for domestication of indigenous fruit trees (IFTs). Currently, participatory tree selection is a widely accepted approach in IFT domestication wherein farmers' knowledge and preferences are included in tree selection processes. In Arunachal Pradesh, India, fruits ofPhoebe cooperianaare extensively consumed by people and traded across the state. In this study, we employed a selection index to screen trees for superior fruit traits from a base population of 45 farmer-identified trees ofP. cooperianain Arunachal Pradesh. Based on fruit diameter length ratio, pulp fruit ratio and yield, 19 trees were selected for superior fruit traits. The per cent improvement for 10 fruit and seed traits ranged from 0.16 to 14.56% compared to the base population. Significant variation for all fruit and seed parameters was observed among the 19 trees with coefficient of variation values ranging between 1.92% for fruit diameter and 8.26% for seed weight. There was significant positive association between economic traits including fruit weight with pulp weight, fruit diameter length ratio with fruit weight and pulp thickness with pulp weight. Principal component analysis revealed that variability was largely contributed by fruit weight (0.49), pulp weight (0.46), seed weight (0.45) and fruit diameter (0.42). Cluster analysis grouped phenotypes into seven groups with no clear clustering of individuals from the same area. The study highlights the significance of participatory tree selection approach and the benefits of individual tree selection in capturing wider variation and locating extreme phenotypes in IFT domestication.

Edge Detection Algorithm for Infrared Images of Power Equipment Based on Improved Grey Wolf Algorithm and Corrosion Algorithm

The enhanced grey wolf algorithm is merged with the corrosion algorithm, and a grey wolf corrosion optimization algorithm is proposed to precisely identify the boundaries within infrared images of power equipment. The refined grey wolf algorithm employs exponential entropy as its fitness function and incorporates an individual wolf selection mechanism, enabling binary segmentation with adaptively chosen thresholds and high resemblance to the original image. Simulation results of actual infrared images captured in substations reveal that, compared to conventional edge detection algorithms such as Sobel, Roberts, Prewitt, Log, and Canny, the algorithm proposed in this paper yields comprehensive and well-defined boundaries with a high degree of conformity to the original infrared image. This proposed algorithm demonstrates significant applicability in the domain of infrared image processing and target recognition for power equipment.

Abstract IA007: Design of next generation precision medicine trials using artificial intelligence

Abstract A better understanding of cancer biology has enabled the development of molecularly targeted therapies matching molecular alterations that induce tumor proliferation and metastases. Over the last decades, dozens of drugs were approved in various cancer types based on molecular alterations, often producing prolonged efficacy. More recently, some molecular alterations were found to be relevent across cancer types, such as NTRK translocations, thereby defining novel ontologies of cancer populations that are no longer defined by their cancer type but only a molecular alteration/signature. Although drug development is being challenged by these novel ontologies, patient stratification remains quite straightforward with unidimentional treatment algorithms (1 drug for 1 alteration, across or within cancer types). However, the relevance of some other alterations present in several cancer types sometimes differs across cancer types, but also among patients with a same cancer type, highlithing the issue of cancer heterogeneity. This later much more frequent situation supports a precision medicine approach that takes into account comprehensive molecular profiling. What I will try to explain during my talk is that the move from stratified medicine to precision medicine, defined as the individual selection of a treatment based on comprehensive molecular profiling, can only be done by using artificial intelligence. In order to illustrate this provocative statemen, I will review some initiatives that have used artificail intelligence in their study designs. I will finish by presenting the SENTIER project (Strategies to Expedite and Navigate Therapeutic Innovations through patient-centric and knowledge-Enhanced Research), an integrated research platform for early drug development that pursues the aim to accelerate drug development by connecting data from different early phase clinical trials in order to accelerate drug development. Citation Format: Christophe Le Tourneau. Design of next generation precision medicine trials using artificial intelligence [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr IA007.

ASXL1 Mutation and Leukocytosis Undermine Spleen Response to Pacritinib in Myelofibrosis

Background: Non-transplant treatment options in myelofibrosis (MF) are palliative in scope and include JAK2 inhibitors (JAKi): ruxolitinib, fedratinib, pacritinib, and momelotinib. All four JAKi are effective in reducing spleen size and alleviating symptoms. In addition, pacritinib and momelotinib exhibit erythropoietic effect, attributed to alleviation of ineffective erythropoiesis through inhibition of activin A receptor type-I. In the current study, we sought to identify molecular or clinical predictors of response to pacritinib in MF patients treated outside of clinical trials. Methods: The current study was conducted under an institutional review board approved minimum risk protocol that allowed retrospective collection and analysis of data from patient records (Mayo Clinic, Rochester, MN; Scottsdale, AZ; and Jacksonville, FL). Anemia response assignment was restricted to patients with baseline hemoglobin level of <10 g/dL and required, for transfusion dependent cases, achieving transfusion independence and, for transfusion-independent cases, an increase in hemoglobin of ≥1.5 g/dL, both sustained for a minimum 2 months; spleen response was clinically vetted but was also supported by radiologic imaging when available and required a ≥50% decrease in palpable splenomegaly for spleen size >10 cm or the spleen becoming not palpable for a spleen size 5-10 cm at base line. Symptom response was adjudicated by central review and required a marked or moderate improvement to qualify as response; because of the retrospective nature of the study, symptom burden assessment by formal criteria was not attempted. Leukocyte cutoff level used for response analysis was determined by receiver operating characteristic curve analysis. Conventional statistical methods were applied using JMP Pro 16.0.0 software (SAS Institute, Cary, NC, USA). Results: We identified 36 NGS-annotated patients with MF who received pacritinib therapy between April,2022 and June,2023 (median age 66 years; 56% males). Twenty-five (69%) patients had failed previous JAKi therapy while 11 (31%) were JAKi-naïve. Eighteen (50%) patients were transfusion-dependent while the median (range) counts were 106 x 10(9)/L (14-578) for platelets, 6.6 x 10(9)/L (1.2-112.8) for leukocytes, and 9 x 10(9)/L (5-12.4) for hemoglobin; leukocyte count was ≥15 x 10(9)/L in 11 (31%) patients and hemoglobin <10 g/dL in 29 (81%). Karyotype was unfavorable in 12 (34%) patients. Driver mutation distribution was JAK2 55%, CALR 27%, MPL 11%, and triple-negative 5%. NGS revealed mutations involving ASXL1 36%, U2AF1 13%, IDH1 13%, SF3B1 13%, K/NRAS 5%, SRSF2 8%, and EZH2 5%. Pacritinib was started at 200 mg BID in 9 (25%) patients and at lower doses in the remaining. Median duration of pacritinib therapy was 4 months (range 1-15). Anemia response was documented in 5 (17%) of the 29 patients with baseline hemoglobin <10 g/dL, spleen response in 12 of 28 evaluable (42%) and symptom response in 18 (50%). Improvement in symptoms was always accompanied by both anemia (p=0.008) and spleen (p=0.01) response; by contrast, there was no significant correlation between anemia and spleen responses (p=0.9) (Table 1). Significant correlations with molecular or clinical variables were mostly apparent for spleen response, which was more likely to occur in the absence of ASXL1 mutation (61% vs 10%; p=0.006), with leukocyte count <15 x 10 (9)/L (55% vs 0%; p=0.005), and in JAKi-naïve vs previously-exposed cases (75% vs 30%; p=0.03; Table 1); significance was sustained by all three risk factors during multivariable analysis; the prognostic impact of ASXL1 (p=0.02 vs 0.01) and leukocytosis (p=0.01 vs 0.07) was apparent in both JAKi-naïve vs JAKi-exposed cases. Anemia response was non-significantly (p=0.27) higher in transfusion-independent (27%) vs dependent (11%) cases, at baseline, and was more likely (p=0.04) to occur in patients starting at lower dose levels. Treatment-emergent adverse events included diarrhea 44%, nausea/vomiting 19%, and grade-3/4 thrombocytopenia 38% or neutropenia (11%). Conclusions: ASXL1 mutation and leukocytosis (>15 x 10 9/L) are independently associated with inferior spleen response to pacritinib, in both JAKi-naïve and JAKi-exposed myelofibrosis. These observations are important for individualized treatment selection.

Monoclonal Gammopathy of Undetermined Significance and the Risk of Thrombotic Events: Results from Istopmm, a Population-Based Screening Study in Iceland

Introduction: Multiple myeloma (MM), Waldenström's macroglobulinemia (WM), and related disorders have been associated with excess risk of thrombosis. Furthermore, medications used to treat these disorders, in particular immunomodulatory agents, have been associated with excess thrombotic risk. Monoclonal gammopathy of undetermined significance (MGUS), the asymptomatic precursor of MM, WM, and related disorders, has also been associated with arterial and venous thrombosis. However, prior studies have been based on cohorts where MGUS was diagnosed as part of the work-up for other unrelated medical disorders. We have shown that these cohort have biased selection of individuals with chronic disease, including autoimmune disease, heart failure, endocrine disorders and more. This selection bias may have led to false associations or overestimation of the relationship of MGUS and thrombotic events. Aim: To evaluate the relationship of MGUS and thrombosis in a screened cohort of individuals with MGUS. Methods: Data were obtained from the Iceland screens, treats, or prevents multiple myeloma study (iStopMM), a population-based screening study for MGUS and a randomized trial of follow-up strategies with the aim of evaluating the benefits and harms of MGUS screening. As part of the study 75,422 Icelandic residents 40 years and older (54% of the underlying population) have provided their informed consent for the study and were screened by serum protein electrophoresis (SPEP) and free light chain (FLC) assay. The cohort was crosslinked to population-based Icelandic government registries that includes all diagnoses made in the universal healthcare system, recorded as international classification of diseases (ICD) 10 codes. The study exposure was MGUS at screening and the outcome was venous and arterial thrombosis, defined as recorded ICD-10 codes. Events recorded within 90 days of each other were considered the same event. We further analyzed subgroups of M protein isotype and light chain (LC) MGUS. We followed participants prospectively after the date of screening to arterial and venous thrombosis as the endpoint and censoring at death, progression to MM, WM, and related disorders, or end of follow-up. Hazard ratios (HR) for time to first thrombotic event were estimated using Cox regression models, while hazard ratios for recurrent thrombotic events were estimated using mixed-effects Cox regression models with a random intercept. Both prospective analyses were adjusted for age as a non-linear variable and sex. In a secondary analysis, M-protein concentration was included as a non-linear variable into similar models that were restricted to those with MGUS with an M-protein. Results: Of the 75,422 screened, 3,353 had MGUS with an M-protein, here termed heavy chain (HC) MGUS, and 315 had LC MGUS. Over a median follow-up of 3.67 to 3.90 years, depending on the outcome of interest, 263 and 3,557 arterial events (20.4 and 13.5 per 1,000 person years) and 260 and 3,092 venous events (20.2 and 11.7 per 1,000 person years) were observed in those with and without MGUS respectively. MGUS was found to be associated with venous thrombotic events (HR: 1.31; 95% CI: 1.08-1.57), in particular deep vein thrombosis (HR:1.46; 95% CI: 1.12-1.90). Of the different MGUS subtypes, this association was only observed in non-IgM MGUS. The results were similar in the recurrent events analysis. IgM MGUS was found to be associated with a higher of peripheral arterial embolic events (HR: 2.86; 95% 1.04-7.85) but this association was not observed in the recurrent event analysis. M-protein concentration was not correlated with the risk of thrombotic events. Discussion: In this large population-based study including more than 75,000 individuals screened for MGUS, we found that MGUS, and particularly non-IgM MGUS, was associated with venous thrombotic events. Interestingly, the size of the M-protein spike was not associated with a higher risk for thromboembolic events. Further studies are needed to identify the underlying mechanisms with the goal of identifying subgroups of the MGUS population that may require interventions to prevent thrombotic events, potentially improving the survival and quality of life of those with MGUS.

A niche-based evolutionary algorithm with dual cooperative archive for solving constrained multi-objective optimization problems

Constrained multi-objective optimization problems (CMOPs) are commonly encountered in engineering practice. The key to effectively solving these problems lies in achieving a timely balance between convergence, diversity, and feasibility during iterations. Furthermore, the appropriate utilization of infeasible solutions is crucial for identifying potential feasible regions. In order to accomplish this comprehensive objective, we propose a novel dual-stage constrained multi-objective evolutionary algorithm (CMOEA) called NACMOEA in this paper. It can be characterized by the following features: 1) Introducing a novel niche-based individual selection and infeasible solution utilization strategy to enhance convergence, diversity, and feasibility. 2) Presenting a cooperative search strategy assisted by dual archives to approximate the constrained Pareto front (CPF) from both feasible and infeasible perspectives, thereby improving the efficiency of obtaining the complete CPF. 3) Designing a new stage switch method based on non-dominant coverage rate to ensure proper completion of search stage switching. Extensive experiments demonstrate that NACMOEA exhibits competitive comprehensive performance when compared with other advanced CMOEAs.

Genomic predictions and GWAS for heat tolerance in pigs based on reaction norm models with performance records and data from public weather stations considering alternative temperature thresholds.

Genetic improvement of livestock productivity has resulted in greater production of metabolic heat and potentially greater susceptibility to heat stress. Various studies have demonstrated that there is genetic variability for heat tolerance and genetic selection for more heat tolerant individuals is possible. The rate of genetic progress tends to be greater when genomic information is incorporated into the analyses as more accurate breeding values can be obtained for young individuals. Therefore, this study aimed (1) to evaluate the predictive ability of genomic breeding values for heat tolerance based on routinely recorded traits, and (2) to investigate the genetic background of heat tolerance based on single-step genome-wide association studies for economically important traits related to body composition, growth and reproduction in Large White pigs. Pedigree information was available for 265,943 animals and genotypes for 8686 animals. The studied traits included ultrasound backfat thickness (BFT), ultrasound muscle depth (MDP), piglet weaning weight (WW), off-test weight (OTW), interval between farrowing (IBF), total number of piglets born (TNB), number of piglets born alive (NBA), number of piglets born dead (NBD), number of piglets weaned (WN) and weaning-to-estrus interval (IWE). The number of phenotypic records ranged from 6059 (WN) to 172,984 (TNB). Single-step genomic reaction norm predictions were used to calculate the genomic estimated breeding values for each individual. Predictions of breeding values for the validation population individuals were compared between datasets containing phenotypic records measured in the whole range of temperatures (WR) and datasets containing only phenotypic records measured when the weather station temperature was above 10°C (10C) or 15°C (15C), to evaluate the usefulness of these datasets that may better reflect the within-barn temperature. The use of homogeneous or heterogeneous residual variance was found to be trait-dependent, where homogeneous variance presented the best fit for MDP, BFT, OTW, TNB, NBA, WN and IBF, while the other traits (WW and IWE) had better fit with heterogeneous variance. The average prediction accuracy, dispersion and bias values considering all traits for WR were 0.36 ± 0.05, -0.07 ± 0.13 and 0.76 ± 0.10, respectively; for 10C were 0.39 ± 0.02, -0.05 ± 0.07 and 0.81 ± 0.05, respectively; and for 15C were 0.32 ± 0.05, -0.05 ± 0.11 and 0.84 ± 0.10, respectively. Based on the studied traits, using phenotypic records collected when the outside temperature (from public weather stations) was above 10°C provided better predictions for most of the traits. Forty-three and 62 candidate genomic regions were associated with the intercept (overall performance level) and slope term (specific biological mechanisms related to environmental sensitivity), respectively. Our results contribute to improve genomic predictions using existing datasets and better understand the genetic background of heat tolerance in pigs. Furthermore, the genomic regions and candidate genes identified will contribute to future genomic studies and breeding applications.

Форпост КЛ – первый отечественный сорт ярового рапса, устойчивый к имидазолиноновым гербицидам

A spring rapeseed cultivar Forpost KL has been developed during the period of 2009–2019 by an individual selection method in F2 from ESI-No. 65/2009 × Luch hybrid combination. That was the first Russian spring rapeseed cultivar resistant to imidazolinone herbicides. In 2015–2019, in the competitive crop variety testing conducted in the All-Russian Research Rapeseed Institute, the cultivar Forpost KL exceeded the standard Rif on seed yield by 0.15 t/ha (by 7.6 %), on oil yield – by 0.07 t/ha, and its glucos-inolate content in seeds was lower by 2.6 µmol/g. Forpost KL has been included into the State Register of breeding achievements (Patent No. 12408) and approved for production in the North-West (2), Central (3), Volga-Vyatka (4), Central Black Earth (5), Middle Volga (7), Ural ( 9), West Siberian (10), and East Siberian (11) regions from 2022.

A transformer-based genomic prediction method fused with knowledge-guided module.

Genomic prediction (GP) uses single nucleotide polymorphisms (SNPs) to establish associations between markers and phenotypes. Selection of early individuals by genomic estimated breeding value shortens the generation interval and speeds up the breeding process. Recently, methods based on deep learning (DL) have gained great attention in the field of GP. In this study, we explore the application of Transformer-based structures to GP and develop a novel deep-learning model named GPformer. GPformer obtains a global view by gleaning beneficial information from all relevant SNPs regardless of the physical distance between SNPs. Comprehensive experimental results on five different crop datasets show that GPformer outperforms ridge regression-based linear unbiased prediction (RR-BLUP), support vector regression (SVR), light gradient boosting machine (LightGBM) and deep neural network genomic prediction (DNNGP) in terms of mean absolute error, Pearson's correlation coefficient and the proposed metric consistent index. Furthermore, we introduce a knowledge-guided module (KGM) to extract genome-wide association studies-based information, which is fused into GPformer as prior knowledge. KGM is very flexible and can be plugged into any DL network. Ablation studies of KGM on three datasets illustrate the efficiency of KGM adequately. Moreover, GPformer is robust and stable to hyperparameters and can generalize to each phenotype of every dataset, which is suitable for practical application scenarios.

Genomic selection in Eucalyptus globulus as an assisted selection tool for growth rate and disease resistance

The adoption of genomic selection (GS) in forest tree breeding allows shortening breeding cycles, increasing selection intensity, and improving the accuracy of breeding values, which translate into increased genetic gains. Therefore, the objective of this work was to design a breeding strategy incorporating GS in the Eucalyptus globulus improvement plan of the INIA. Using the single step genomic selection (ssGBLUP) methodology, a multi-trait model of GS was developed considering different ages of evaluation (14 and 21 months), and combination of growth traits (total height and DBH) and heteroblasty (proportion of adult foliage). The model was tested through the predictive capacity (estimated through intra-population cross-validation), the prediction bias (estimated as the regression coefficient between the reference breeding values and those predicted by the model), and the comparison between the rankings of breeding values from the conventional ABLUP and the ssGBLUP (as the proportion of common individuals in the top 10%). The heritabilities in the strict sense for all traits were high, ranging from 0.51 to 0.72. The predictive abilities of the different cross-validations by site and by trait were high, varying from 0.72 to 0.92. The model tends to slightly underestimate DBH and the proportion of adult foliage at some sites and overestimate them at others (bias between 0.88 and 1.19), and overestimate total height in all sites (bias between 0.51 and 0.68). The proportion of common individuals in the top 10% by conventional selection and GS is high for all traits (0.76 - 0.86). These results suggest that the incorporation of GS in the improvement plan of E. globulus would be efficient. It is proposed to include GS in two stages of the breeding cycle: the selection of the best parents for controlled mating, increasing the selection intensity, and the selection of individuals in the nursery, reducing the stage of field evaluation of the selected clones. This strategy will markedly reduce the selection cycle, allowing commercial clones to be obtained in half the time compared to conventional selection.

Indicators of efficiency in operational crosses of Eucalyptus dunnii and hybrids in Montes del Plata: Current progress and challenges

One of the main goals of a tree breeding program is to increase forest productivity, adaptation and profitability of forest plantations. Eucalyptus dunnii is a main species used for pulp production in Uruguay. Montes del Plata (MdP) is one of the largest forest companies in Uruguay and has been focused on the development, testing and deployment of E. dunnii clones to establish commercial plantations in Uruguay. This poster refers to the generation of control-pollinated families, as the starting point of MdP clonal strategy. Control pollination (CP) is a tool in genetic breeding programs that enables to recombine selected genotypes with desired traits to maximize gain in the medium to long term. The selection trait for pulpwood objective is tons of cellulose per tree (ADt); consequently, growth, frost tolerance, health, and wood properties are relevant for parent selection. Ongoing work shows a fruitfully performance of E. dunnii. In the south-east region of Uruguay the species have one flowering period per year, with an average flowering time occurring between the last fortnight of February and the first half of May. Developed protocols for pollen harvesting and methods for crossing are used. The survival of pollinated flowers resulting in fruits has shown to vary with parental species. Average survival rates are 20 to 35%. The main loss of crop happens during the first 4 months after pollinating, weighting —in average— a loss of 40% of the pollinated flowers. The species fruit crop occurs one year after CP. The number of seed per fruit varies with the parental species. E. dunnii × E. dunnii crosses yield in average 6.4 seeds per fruit. However, we have seen a reduction in seeds per fruit in hybrid crosses, where E. dunnii is pollinated with another species, mostly E. globulus, E. grandis and E. dorrigoensis. Seed crops are sawn in the nursery and start an individual clonal selection based on rooting protocols. Clones that fulfill the rooting constraints go to field trials. This is presented in another poster proposal. Main challenges for the future are to maintain a wide genetic diversity in the breeding population, early flowering, and continuous improvement on CP techniques.

The genetics and breeding of the Portuguese oyster, Crassostrea angulata: lessons, experiences, and challenges in Vietnam

Aquaculture mollusc production is predominantly from Asia, with more than 80% of the total biomass produced in China. Vietnam’s annual mollusc production is growing rapidly but is comparatively small given its coastal resources. A significant challenge for future mollusc production, and oysters in particular, is the supply of high-quality spat. Most mollusc spat in Vietnam comes from local wild sources or is imported from China. Particularly in the case of oysters, where wild collection is low and importation of oyster spat into Vietnam from other jurisdictions is not controlled, supply is unreliable and presents a biosecurity risk to the industry. Controlling the life cycle in hatcheries can increase the sustainability and reliability of spat supply with the advantages of genetic enhancement in the long term. Beyond well-established selection methods based on phenotypic data for pedigreed families, the rapid development of genomic technology has enabled innovation in hatchery production based on genetic programs. This technology allows greater insight into oyster genetics in intensive aquaculture production systems. Recent reviews of selection programs demonstrate that inbreeding control via mate selection is an effective strategy for oyster species. Genetic response through combinations of individual and family-based selection can enhance morphometric traits by 10% per generation and disease resistance by 15% per generation in many aquaculture species. Genomic techniques provide information for selecting candidates at an earlier stage and improve prediction accuracy. In this paper, we review the literature on popular genomic tools and breeding techniques used for molluscs, focusing on the Portuguese oyster, Crassostrea angulata. This is to better comprehend how modern quantitative and molecular genetic technologies are being applied in mollusc breeding programs. It considers opportunities for and the feasibility of using genomic-based selection as well as the challenges that are faced in breeding programs transitioning to these new methods.

Hybridization and divergent climatic preferences drive divergence of two allopatric Gentiana species on the Qinghai-Tibet Plateau.

Exploring how species diverge is vital for understanding the drivers of speciation. Factors such as geographical separation and ecological selection, hybridization, polyploidization and shifts in mating system are all major mechanisms of plant speciation, but their contributions to divergence are rarely well understood. Here we test these mechanisms in two plant species, Gentiana lhassica and G. hoae, with the goal of understanding recent allopatric species divergence on the Qinghai-Tibet Plateau (QTP). We performed Bayesian clustering, phylogenetic analysis and estimates of hybridization using 561 302 nuclear genomic single nucleotide polymorphisms (SNPs). We performed redundancy analysis, and identified and annotated species-specific SNPs (ssSNPs) to explore the association between climatic preference and genetic divergence. We also estimated genome sizes using flow cytometry to test for overlooked polyploidy. Genomic evidence confirms that G. lhassica and G. hoae are closely related but distinct species, while genome size estimates show divergence occurred without polyploidy. Gentiana hoae has significantly higher average FIS values than G. lhassica. Population clustering based on genomic SNPs shows no signature of recent hybridization, but each species is characterized by a distinct history of hybridization with congeners that has shaped genome-wide variation. Gentiana lhassica has captured the chloroplast and experienced introgression with a divergent gentian species, while G. hoae has experienced recurrent hybridization with related taxa. Species distribution modelling suggested range overlap in the Last Interglacial Period, while redundancy analysis showed that precipitation and temperature are the major climatic differences explaining the separation of the species. The species differ by 2993 ssSNPs, with genome annotation showing missense variants in genes involved in stress resistance. This study suggests that the distinctiveness of these species on the QTP is driven by a combination of hybridization, geographical isolation, mating system differences and evolution of divergent climatic preferences.

Measurement of response to selection in silkworm commercial hybrids against individual selection of parental lines

Measurement of response to selection in silkworm commercial hybrids against individual selection of parental lines

129 The Relationship Between Pulmonary Arterial Pressure Expected Progeny Differences and Methane Emissions

Abstract The objective of this study was to determine the relationship between pulmonary arterial pressure (PAP) expected progeny differences (EPD) and methane emissions. Pulmonary arterial pressure is an indicator of pulmonary arterial hypertension in cattle and is especially relevant at high altitudes, with increasing importance in moderate elevation feedlot and finishing systems. Enteric methane emissions from cattle are increasingly emphasized due to their contribution of greenhouse gases in the agricultural sector. As pulmonary arterial hypertension continues to be an issue in high altitudes and feedlots, understanding relationships with methane emission rates will be useful for both concomitant selection with the goal of improving environmental sustainability. The PAP EPD data were collected on 123 total heifers (n = 37) and steers (n = 86) located on a ranch in southern Wyoming at an elevation of 2,194.56 meters. Gas emissions were collected using a GreenFeed system (C-Lock, Rapid City, South Dakota), which measures the gas fluxes of individual animals at the CSU ARDEC facility at an elevation of 1,557.53 meters. Individual animal methane emissions were measured as grams/day. A generalized linear regression model was used to regress average daily methane emissions (mean = 163.08, SD = 38.74, min = 87.72, max = 247.03) on PAP EPD (mean = -0.464, SD = 1.565, min = -6.382, max = 4.286), pen, and age in days (mean = 258.2, SD = 20.009, min = 200, max = 298). The PAP EPD (P = 0.484) did not account for a significant amount of variation in methane emissions. Additionally, the effect of pen (P < 0.05) and age (P < 0.05) were significant sources of variation for methane production. The effects of pen had a range of 60.916 units of methane emission/day (P < 0.05). Age of the individual was evaluated as a linear covariate and had a solution of 0.678 units of methane emission/day (P < 0.05), suggesting that older individuals had increased methane emissions. These results show no statistical relationship between PAP EPD and methane in these data. While preliminary results suggest that selection for low PAP EPD individuals will have no adverse effects on sustainability metrics, future research is needed to fully understand the relationship between beef cattle production traits and sustainability metrics.

Differences on the level of hepatic transcriptome between two flatfish species in response to liver cancer and environmental pollution levels

Environmental factors can cause cancer in both wild animals and humans. In ecological settings, genetic variation and natural selection can sometimes produce resilience to the negative impacts of environmental change. An increase in oncogenic substances in natural habitats has therefore, unintentionally, created opportunities for using polluted habitats to study cancer defence mechanisms. The Baltic and North Sea are among the most contaminated marine areas, with a long history of pollution. Two flatfish species (flounder, Platichthys flesus and dab, Limanda limanda) are used as ecotoxicological indicator species due to pollution-induced liver cancer. Cancer is more prevalent in dab, suggesting species-specific differences in vulnerability and/or defence mechanisms. We conducted gene expression analyses for 30 flatfishes. We characterize between- and within-species patterns in potential cancer-related mechanisms. By comparing cancerous and healthy fishes, and non-cancerous fishes from clean and polluted sites, we suggest also genes and related physiological mechanisms that could contribute to a higher resistance to pollution-induced cancer in flounders. We discovered changes in transcriptome related to elevated pollutant metabolism, alongside greater tumour suppression mechanisms in the liver tissue of flounders compared to dabs. This suggests either hormetic upregulation of tumour suppression or a stronger natural selection pressure for higher cancer resistance for flounders in polluted environment. Based on gene expression patterns seen in cancerous and healthy fish, for liver cancer to develop in flounders, genetic defence mechanisms need to be suppressed, while in dabs, analogous process is weak or absent. We conclude that wild species could offer novel insights and ideas for understanding the nature and evolution of natural cancer defence mechanisms.