Selection For Traits Research Articles

State and trait predictors of cognitive responses to acute stress and uncertainty

ABSTRACT Stress occurs when conditions burden or exceed an individual’s adaptive resources. Military personnel are often tasked with maintaining peak performance under such stressful conditions. Importantly, the effects of stress are nuanced and may vary as a function of individual traits and states. Recent interdisciplinary research has sought to model and identify such relationships. In two previously reported efforts, Soldiers first completed a comprehensive battery of trait assessments across four general domains thought to be predictive of performance: cognitive, health, physical, and social-emotional, and then completed the Decision-Making under Uncertainty and Stress (DeMUS) virtual reality task that probed spatial cognition, memory, and decision-making under stress and variable uncertainty. The present analysis explores whether cognitive, health, physical, and social-emotional trait assessments, as well as physiological state measures, predict or modulate DeMUS performance outcomes under stress. Multiple regression analyses examined the effect of each trait predictor and stress responsiveness on quantitative task performance outcomes. Results revealed that one measure of state stress reactivity, salivary cortisol, predicted lower recognition memory sensitivity. Further, trait measures of healthy eating, agility, flexibility, cognitive updating, and positive emotion predicted enhanced spatial orienting and decision-making performance and confidence. Together, the results suggest that select individual states and traits may predict cognition under stress. Future research should expand to ecologically relevant military stressors during training and operations.

Multi-model approach for optimizing cold-wave resilient maize selection: unveiling genotype-by-environment interaction and predicting yield stability

Cold waves both significantly reduce yield & damage crops as well; unforeseeable nature of cold waves makes it challenging for farmers to manage risk. Thus, we aim to select maize hybrids that thrive under cold stress (both escaping early cold-waves and tolerating cold snaps); pinpoint stable, high-yielding hybrids ideal for regions prone to cold stress. In this investigation 2 years winter trial in Nepal was appraised on diverse maize hybrids for cold wave tolerant, stable across four stations with a Randomized Complete Block Design & 3 replications at each station. Likewise, this research employed 4 statistical methods both fixed effect and linear mixed model: genotype-environment interactions (AMMI), visually analyzes genotype performance and stability across environments (GGE) breeding values of genotypes for selection (BLUP), multiple traits for selection (MTSI). This scholarship revealed significant (P < 0.001) impacts of genotype, environment, and their interaction (GEI) on yield. This GEI, accounting for 100% of yield variance, was mainly captured by 3 principal components, with the first explaining 49%. Notably, mixed-effects models and biplots identified superior hybrids exhibiting both high average yields and consistent performance. GGE biplot analysis unveiled high-yielding and adaptable: GK3157, NK6607, RMH1899 Super, GK3254, RMH666, Shan 111, DKC9149, and Sweety-1. Further, BLUP and WAASBYY analyses delineated the superior performers and stabilized hybrids for yield, with DKC9141, Uttam 121, NK6607, MM2929, RMH-666, GK 3254, and GK3157, and RMH-1899 super candidates for both high yield and stability. In Nepalgunj, Delta 3333, MM2122, and Shaan 111 excelled in both yield and stability, while Rampur favored Rampur Hybrid 6 and MM2424 for stability. Parwanipur and Tarahara shared similar winners for stability and yield, including MM2122, Shaan 111, and Delta 3333 in Parwanipur, and NK7884, MM2424, and Delta 2222 in Tarahara. Based on Multi genotype ideotype distance (MGDI), 9 hybrids were selected for yield and stability, including MM 2033, NK 6607, Sweety 1 so on; exhibited escape to cold waves whilst GK3254, TMMH-846, and MM-9442, were chosen for cold waves adapted hybrids. Moreover, by identifying cold-tolerant maize hybrids, this study has potential to mitigate risks for farmers (economic burden, crop failure) and bolster food security.

Runs of homozygosity and selection signature analyses reveal putative genomic regions for artificial selection in layer breeding

BackgroundThe breeding of layers emphasizes the continual selection of egg-related traits, such as egg production, egg quality and eggshell, which enhance their productivity and meet the demand of market. As the breeding process continued, the genomic homozygosity of layers gradually increased, resulting in the emergence of runs of homozygosity (ROH). Therefore, ROH analysis can be used in conjunction with other methods to detect selection signatures and identify candidate genes associated with various important traits in layer breeding.ResultsIn this study, we generated whole-genome sequencing data from 686 hens in a Rhode Island Red population that had undergone fifteen consecutive generations of intensive artificial selection. We performed a genome-wide ROH analysis and utilized multiple methods to detect signatures of selection. A total of 141,720 ROH segments were discovered in whole population, and most of them (97.35%) were less than 3 Mb in length. Twenty-three ROH islands were identified, and they overlapped with some regions bearing selection signatures, which were detected by the De-correlated composite of multiple signals methods (DCMS). Sixty genes were discovered and functional annotation analysis revealed the possible roles of them in growth, development, immunity and signaling in layers. Additionally, two-tailed analyses including DCMS and ROH for 44 phenotypes of layers were conducted to find out the genomic differences between subgroups of top and bottom 10% phenotype of individuals. Combining the results of GWAS, we observed that regions significantly associated with traits also exhibited selection signatures between the high and low subgroups. We identified a region significantly associated with egg weight near the 25 Mb region of GGA 1, which exhibited selection signatures and has higher genomic homozygosity in the low egg weight subpopulation. This suggests that the region may be play a role in the decline in egg weight.ConclusionsIn summary, through the combined analysis of ROH, selection signatures, and GWAS, we identified several genomic regions that associated with the production traits of layers, providing reference for the study of layer genome.

Identifying indirect selection traits to improve winter hardiness in barley

Identifying indirect selection traits to improve winter hardiness in barley

Unraveling the complexities of drought stress in cotton: a multifaceted analysis of selection criteria and breeding approaches

Abiotic stress tolerance breeding programs present a spectrum of perspectives, yet definitive solutions remain elusive, with each approach carrying its own set of advantages and disadvantages. This study systematically evaluates extant methodologies, comparing plant performance across varied genotypes and selection traits under optimal and stress conditions. The objective is to elucidate prevailing ambiguities. Ten homozygous lines (F8 generation) were assessed using a randomized block design alongside five control varieties, with four replicates cultivated under well-watered and deficit water conditions. It is noteworthy that six of the ten homozygous lines were cultivated exclusively under well-watered conditions (F3 to F7), while four lines experienced deficit water conditions (F3 to F7). All five control varieties underwent cultivation under both conditions. These findings underscore the necessity for tailored breeding programs attuned to specific environmental exigencies, recognizing that individual traits manifest divergent responses to varying conditions. It is evident that certain traits exhibit marked disparities under well-watered conditions, while others evince heightened differentiation under water deficit conditions. Significantly, our analysis reveals a pronounced interaction between irrigation regimes and selection traits, which serves to underscore the nuanced interplay between genotype and environmental stress.

Identification of Drought Tolerant Fenugreek Mutants at Seedling Stage Through Multi-Trait Genotype-Ideotype Distance Index (MGIDI)

The top-performing mutants from the M2 generation, induced by a combination of γ radiation and EMS treatment, underwent screening for drought tolerance at the seedling stage in the M3 generation under controlled laboratory conditions. This investigation aimed to assess their potential for drought tolerance. The top 15 high-yielding mutants were assessed under both normal (control) and induced drought conditions (10% PEG solution). Utilizing the MGIDI method, the evaluation provided valuable insights into selection traits and identified mutants with potential drought tolerance. Under normal conditions, mutants M3-181 and M3-149 exhibited superior performance in seedling growth traits, with M3-149 being the top performer under induced drought conditions, followed by M3-181. Their proximity to the red-cutline suggests promising potential that warrants further investigation. Furthermore, these findings indicate that mutant lines displayed superior multi-trait performance compared to the parent cultivar. Specifically, mutants M3-181, M3-149, and M3-29 ranked higher than the parent cultivar under normal conditions, while mutants M3-149, M3-181, and M3-168 surpassed the parent cultivar RMt-1 under induced drought conditions. This underscores the effectiveness of mutation breeding, particularly through the induction of mutations using γ radiation and EMS, as an efficient strategy not only for generating genetic diversity but also for producing variants superior to the parent cultivar. To the best of our knowledge, this is first report made on mutant selection in fenugreek for drought tolerance at seedling stage, using the MGIDI approach.

Genotyping of red tilapia strains in Central Luzon Philippines targeting ESR1 gene

Tilapia is an economically important commodity worldwide. Marker-assisted selection (MAS) has been practiced in livestock culture to ensure the selection of a specific trait that will benefit the culture system. This study assessed the allelic variation in six red tilapia strains in Central Luzon, Philippines. Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) was done to evaluate the genotypes of six strains of red tilapia using intron one portion of the chromosome one of the estrogen receptor 1 (ESR1) gene. The target gene was amplified using primers designed in previous study and then subjected to RFLP using PvuII restriction enzyme. Single Nucleotide Polymorphisms (SNPs) were also evaluated in six DNA sequences. Results showed that 18 red tilapia samples were found to be of the AA genotype. Aligned sequences of the 122 bp ESR1 gene revealed that among six red tilapia strains, there are 117 identical pairs, three transversional pairs, and three transitional pairs. The SNPs observed can be used to identify restriction enzymes that discriminate different genotypes in the target gene. Association studies can be done to determine the genotypes that are linked to specific traits in cultured animals.

Genome-Wide Association Study Reveals Novel Candidate Genes Influencing Semen Traits in Landrace Pigs.

Artificial insemination plays a crucial role in pig production, particularly in enhancing the genetic potential of elite boars. To accelerate genetic progress for semen traits in pigs, it is vital to understand and identify the underlying genetic markers associated with desirable traits. Herein, we genotyped 1238 Landrace boars with GeneSeek Porcine SNP50 K Bead chip and conducted genome-wide association studies to identify genetic regions and candidate genes associated with 12 semen traits. Our study identified 38 SNPs associated with the analyzed 12 semen traits. Furthermore, we identified several promising candidate genes, including HIBADH, DLG1, MED1, APAF1, MGST3, MTG2, and ZP4. These candidate genes have the potential function to facilitate the breeding of boars with improved semen traits. By further investigating and understanding the roles of these genes, we can develop more effective breeding strategies that contribute to the overall enhancement of pig production. The results of our study provide valuable insights for the pig-breeding industry and support ongoing research efforts to optimize genetic selection for superior semen traits.

Conversion of superior bread wheat genotype HD3209 carrying Lr19/Sr25 into CMS line for development of rust-resistant wheat hybrids

Hybrid development is one of the most promising strategies for boosting crop yields. Parental lines used to create hybrids must have good per se performance and disease resistance for developing superior hybrids. Indian wheat line HD3209 was developed by introducing the rust resistance genes Lr19/Sr25 into the background of popular wheat variety HD2932. The wheat line HD3209 carrying Lr19/Sr25 has been successfully and rapidly converted to the CMS line A-HD3209, with 96.01% background genome recovery, based on selection for agro-morphological traits, rust resistance, pollen sterility, and foreground and background analyses utilizing SSR markers. The converted CMS line A-HD3209 was completely sterile and nearly identical to the recurrent parent HD3209. Based on high per se performance and rust resistance, the study concludes that the derived CMS line A-HD3209 is promising and can be employed successfully in hybrid development.

Trait selection strategy in multi-trait GWAS: Boosting SNP discoverability

Since the first Genome-Wide Association Studies (GWAS), thousands of variant-trait associations have been discovered. However, comprehensively mapping the genetic determinant of complex traits through univariate testing can require prohibitive sample sizes. Multi-trait GWAS can circumvent this issue and improve statistical power by leveraging the joint genetic architecture of human phenotypes. Although many methodological hurdles of multi-trait testing have been solved, the strategy to select traits has been overlooked. In this study, we conducted multi-trait GWAS on approximately 20,000 combinations of 72 traits using an omnibus test as implemented in JASS (Joint Analysis of Summary Statistics). We assessed which genetic features of the sets of traits analysed were associated with an increased detection of variants compared to univariate screening. Several features of the set of traits, including the heritability, the number of traits, and the genetic correlation, drive the multi-trait test gain. Using these features jointly in predictive models captures a large fraction of the power gain of the multi-trait test (Pearson's γ between the observed and predicted gain equals 0.43, P < 1.6 x 10-60). Applying an alternative multi-trait approach (MTAG), we identified similar features of interest, but with an overall 70% lower number of new associations. Finally, selecting sets based on our data-driven models systematically outperformed the common strategy of selecting clinically similar traits. This work provides a unique picture of the determinant of multi-trait GWAS statistical power and outline practical strategies for multi-trait testing.

The Phenotypic Variation in Moso Bamboo and the Selection of Key Traits.

This research aimed to explore the diverse phenotypic characteristics of moso bamboo in China and pinpoint essential characteristics of moso bamboo. In this study, 63 grids were selected using the grid method to investigate 28 phenotypic traits of moso bamboo across the entire distribution area of China. The results suggest that the phenotypic traits of moso bamboo exhibit rich diversity, with coefficients of variation ranging from 5.87% to 36.57%. The phenotypic traits of moso bamboo showed varying degrees of correlation. A principal component analysis was used to identify seven main phenotypic trait indicators: diameter at breast height (DBH), leaf area (LA), leaf weight (LW), branch-to-leaf ratio (BLr), leaf moisture content (Lmc), wall-to-cavity ratio (WCr), and node length at breast height (LN), which accounted for 81.64% of the total information. A random forest model was used, which gave good results to validate the results. The average combined phenotypic trait value (D-value) of most germplasm was 0.563. The highest D-value was found in Wuyi 1 moso in Fujian (0.803), while the lowest D-value was observed in Pingle 2 moso in Guangxi (0.317). The clustering analysis of phenotypic traits classified China's moso bamboo germplasm into four groups. Group I had the highest D-value and is an important candidate germplasm for excellent germplasm screening.

Integration of molecular breeding and multi-resistance screening for developing a promising restorer line Guihui5501 with heavy grain, good grain quality, and endurance to biotic and abiotic stresses.

Rice, a critical staple on a global scale, faces escalating challenges in yield preservation due to the rising prevalence of abiotic and biotic stressors, exacerbated by frequent climatic fluctuations in recent years. Moreover, the scorching climate prevalent in the rice-growing regions of South China poses obstacles to the cultivation of good-quality, heavy-grain varieties. Addressing this dilemma requires the development of resilient varieties capable of withstanding multiple stress factors. To achieve this objective, our study employed the broad-spectrum blast-resistant line Digu, the brown planthopper (BPH)-resistant line ASD7, and the heavy-grain backbone restorer lines Fuhui838 (FH838) and Shuhui527 (SH527) as parental materials for hybridization and multiple crossings. The incorporation of molecular markers facilitated the rapid pyramiding of six target genes (Pi5, Pita, Pid2, Pid3, Bph2, and Wxb ). Through a comprehensive evaluation encompassing blast resistance, BPH resistance, cold tolerance, grain appearance, and quality, alongside agronomic trait selection, a promising restorer line, Guihui5501 (GH5501), was successfully developed. It demonstrated broad-spectrum resistance to blast, exhibiting a resistance frequency of 77.33% against 75 artificially inoculated isolates, moderate resistance to BPH (3.78 grade), strong cold tolerance during the seedling stage (1.80 grade), and characteristics of heavy grains (1,000-grain weight reaching 35.64 g) with good grain quality. The primary rice quality parameters for GH5501, with the exception of alkali spreading value, either met or exceeded the second-grade national standard for premium edible rice varieties, signifying a significant advancement in the production of good-quality heavy-grain varieties in the southern rice-growing regions. Utilizing GH5501, a hybrid combination named Nayou5501, characterized by high yield, good quality, and resistance to multiple stresses, was bred and received approval as a rice variety in Guangxi in 2021. Furthermore, genomic analysis with gene chips revealed that GH5501 possessed an additional 20 exceptional alleles, such as NRT1.1B for efficient nitrogen utilization, SKC1 for salt tolerance, and STV11 for resistance to rice stripe virus. Consequently, the restorer line GH5501 could serve as a valuable resource for the subsequent breeding of high-yielding, good-quality, and stress-tolerant hybrid rice varieties.

Whole-genome sequencing analysis of soybean diversity across different countries and selection signature of Korean soybean accession.

Soybean is an important agricultural crop known for its high protein and oil content, contributing to essential nutritional and health benefits for humans. Domesticated in China over 5,000 years ago, soybean has since adapted to diverse environments and spread worldwide. This study aimed to investigate the genomic characteristics and population structures of 2,317 publicly available soybean whole-genome sequences from diverse geographical regions, including China, Korea, Japan, Europe, North America, and South America. We used large-scale whole-genome sequencing data to perform high-resolution analyses to reveal the genetic characteristics of soybean accessions. Soybean accessions from China and Korea exhibited landrace characteristics, indicating higher genetic diversity and adaptation to local environments. On the other hand, soybean accessions from Japan, the European Union, and South America were found to have low genetic diversity due to artificial selection and breeding for agronomic traits. We also identified key variants and genes associated with the ability to adapt to different environments. In Korean soybean accessions, we observed strong selection signals for isoflavone synthesis, an adaptive trait critical for improving soybean adaptability, survival, and reproductive success by mitigating environmental stress. Identifying specific genomic regions showing unique patterns of selective sweeps for genes such as HIDH, CYP73A11, IFS1, and CYP81E11 associated with isoflavone synthesis provided valuable insights into potential adaptation mechanisms. Our research has significantly improved our understanding of soybean diversity at the genetic level. We have identified key genetic variants and genes influencing adaptability, laying the foundation for future advances in genomics-based breeding programs and crop improvement efforts.

Dual-Model GWAS Analysis and Genomic Selection of Maize Flowering Time-Related Traits.

An appropriate flowering period is an important selection criterion in maize breeding. It plays a crucial role in the ecological adaptability of maize varieties. To explore the genetic basis of flowering time, GWAS and GS analyses were conducted using an associating panel consisting of 379 multi-parent DH lines. The DH population was phenotyped for days to tasseling (DTT), days to pollen-shedding (DTP), and days to silking (DTS) in different environments. The heritability was 82.75%, 86.09%, and 85.26% for DTT, DTP, and DTS, respectively. The GWAS analysis with the FarmCPU model identified 10 single-nucleotide polymorphisms (SNPs) distributed on chromosomes 3, 8, 9, and 10 that were significantly associated with flowering time-related traits. The GWAS analysis with the BLINK model identified seven SNPs distributed on chromosomes 1, 3, 8, 9, and 10 that were significantly associated with flowering time-related traits. Three SNPs 3_198946071, 9_146646966, and 9_152140631 showed a pleiotropic effect, indicating a significant genetic correlation between DTT, DTP, and DTS. A total of 24 candidate genes were detected. A relatively high prediction accuracy was achieved with 100 significantly associated SNPs detected from GWAS, and the optimal training population size was 70%. This study provides a better understanding of the genetic architecture of flowering time-related traits and provides an optimal strategy for GS.

Commercial maize hybrids have smaller root systems after 80 Years of breeding

Roots have gained attention for their role in improving plant function in high-stress environments and providing ecosystem services such as soil organic carbon storage. An important step in breeding for enhanced root phenotypes is understanding how root traits have changed historically due to selection for yield and other aboveground traits. However, among the few era panel studies focused on roots, there are conflicting findings about how breeding has altered traits such as root system length and biomass, while other traits such as root depth distribution, root size class distribution, and tissue quality remain largely unexplored. Our aim was to assess breeding-driven changes in root traits that are relevant to resource acquisition and soil carbon sequestration. We grew twelve maize (Zea mays L.) hybrids from the Corteva/Pioneer ERA panel, spanning from 1936 to 2014, in 1.5 m deep mesocosms. At the eight-leaf stage, intact root systems were imaged and analyzed using a custom root phenotyping platform, and roots and shoots were subjected to carbon and nitrogen analysis and Diffuse Reflectance FTIR to assess variation in tissue composition. We found that the newest hybrids produced 40% less root biomass and 36% less root length than the oldest hybrids, with declines of 0.024 g year−1 (s.e.: 0.005, p < 0.01) and 0.86 m year−1 (s.e.: 0.23, p < 0.01) with no changes in maximum rooting depth, which averaged 113 cm (±5.62). , and no directional shifts in chemical composition. We also found a decline in the root-to-shoot ratio from 0.58 g g−1 to 0.46 g g−1 (s.e.: 0.0006, p < 0.05). Our results suggest that selection for yield has indirectly decreased root system size over 80 years of maize breeding. Smaller root systems of modern hybrids may contribute to the higher optimum plant populations and higher yields of modern maize hybrids.

Fine-mapping and candidate gene analysis of tuber eye depth in potato

Eye depth is an important agronomic trait affecting tubers' appearance, quality, and processing suitability. Hence, cultivating varieties with uniform shapes and shallow eye depth are important goals for potato breeding. In this study, based on the primary mapping of the tuber eye-depth locus using a small primary-segregating population, a large secondary-segregating population with 2,100 individuals was used to map the eye-depth locus further. A major quantitative trait locus for eye-depth on chromosome 10 was identified (designated qEyd10.1) using BSA-seq and traditional QTL mapping method. The qEyd10.1 could explain 55.0% of the eye depth phenotypic variation and was further narrowed to a 309.10 kb interval using recombinant analysis. To predict candidate genes, tissue sectioning and RNA-seq of the specific tuber tissues were performed. Genes encoding members of the peroxidase superfamily with likely roles in indole acetic acid regulation were considered the most promising candidates. These results will facilitate marker-assisted selection for the shallow-eye trait in potato breeding and provide a solid basis for eye-depth gene cloning and the analysis of tuber eye-depth regulatory mechanisms.

Improved functional mapping of complex trait heritability with GSA-MiXeR implicates biologically specific gene sets.

While genome-wide association studies are increasingly successful in discovering genomic loci associated with complex human traits and disorders, the biological interpretation of these findings remains challenging. Here we developed the GSA-MiXeR analytical tool for gene set analysis (GSA), which fits a model for the heritability of individual genes, accounting for linkage disequilibrium across variants and allowing the quantification of partitioned heritability and fold enrichment for small gene sets. We validated the method using extensive simulations and sensitivity analyses. When applied to a diverse selection of complex traits and disorders, including schizophrenia, GSA-MiXeR prioritizes gene sets with greater biological specificity compared to standard GSA approaches, implicating voltage-gated calcium channel function and dopaminergic signaling for schizophrenia. Such biologically relevant gene sets, often with fewer than ten genes, are more likely to provide insights into the pathobiology of complex diseases and highlight potential drug targets.

Morpho-physiological and yield traits for selection of drought tolerant Urochloa grass ecotypes.

Drought has become more recurrent and causes a substantial decline in forage yields leading to strain on feed resources for livestock production. This has intensified the search for drought-tolerant forages to promote sustainable livestock production. The objective of this study was to identify drought-tolerant Urochloa grasses and to discern their morpho-physiological and yield traits to water stress as well as the relationship between these traits and indices of drought resistance. The results showed that the ecotypes, water regimes and their interaction significantly influenced all the studied morpho-physiological and yield traits. There was a significant decrease in plant height, number of leaves and tillers, dry matter yield, relative water content, photosystem II and efficiency of photosystem II with an increase in non-photochemical quenching. The principal component analysis revealed that the performance of Urochloa grass ecotypes was different under water sufficient (WS) and water deficit conditions. Drought tolerance indicators (mean productivity, geometric mean productivity, tolerance index and stress tolerance index) were most effective in identifying Urochloa ecotypes with high biomass production under both water deficient and WS conditions. Ecotypes K17, K7, Kisii, Busia and Kakamega were the most drought tolerant, Basilisk, K6, K10, K19 and Toledo were moderately tolerant whereas, CIAT6385, CIAT16449, K13, K5 and K9 were drought sensitive. The five drought-tolerant Urochloa ecotypes should be tested for sustainable biomass production under field conditions and used in breeding programmes to develop high-yielding drought-tolerant varieties.

Evaluation of predictive ability of linear type gonadal traits on reproductive capacity of breeding dairy bulls.

Dimensions of linear type traits facilitate selection of livestock for breeding and rearing. To date, use of linear type traits for selection of breeding bulls is highly concentric to scrotal circumference (SC), with probable overlook to other important traits. Present study reported the importance of various gonadal linear type traits on spermatozoa production, age-related changes in gonadal linear type traits of bulls and predictive ability of these traits on bulls' reproductive potentials. Among all gonadal traits, testicular density (TD), scrotal volume (SV), paired testicular weight (PWT) and SC were found most important predictor variables in order, which can discriminate between good/poor breeding bulls, that is, produced frozen semen doses (FSD) or not. Dimensions of gonadal traits increased significantly up to 36 months age and thereafter, development became slow and negligible. In contrast, TD decreased by 30%, 51%, 64%, 68% and 71% at 12, 24, 36, 48 and >49 months age, respectively, from its base value at 6 months. Bulls of lower TD (≤0.88 g/cm3) had significantly higher ejaculate volume (+9%), sperm motility, sperm concentration (+100 million/mL) and sperm output (+26%)/ejaculate as compared to bulls of higher TD (>0.88 g/cm3). Discriminant function was developed using TD, SV, PWT and SC to identify bulls of superior reproductive potentials. It was concluded that among the investigated traits, TD was the strongest to discriminate between FSD and Non-FSD bulls. Therefore, our findings suggested that TD could be more potential trait than SC for dairy bulls' breeding soundness evaluation and assessment of reproductive ability.

Mite non-reproduction is not a consequence of the brood removal behavior of varroa sensitive hygiene honey bee colonies (Apis mellifera).

A sustainable solution to the global threat of the Varroa destructor mite is the selection of varroa-resistant honey bee (Apis mellifera) colonies. Both "mite non-reproduction" (MNR) and "varroa sensitive hygiene" (VSH) appear to be promising selection traits for achieving the goal of a resistant honey bee. MNR describes colonies that have a high number of non-reproductive mites (no offspring, no males, or delayed development of mite offspring). High numbers of non-reproductive mites have been observed in selected colonies, but the mechanism behind this trait has not yet been identified. The specialized hygienic behavior of selected honey bees, called VSH, is the removal of varroa-infested brood. These traits were thought to be linked by VSH bees preferentially removing reproductive varroa females leaving only non-reproductive mites behind in cells and thus creating colonies with high levels of MNR. To further investigate this link, we used an experimental setup and data sets from a four-year selection project designed to breed for MNR and VSH colonies. In addition, we sought to answer the question of whether non-reproductive mites are a direct consequence of worker removal behavior. To test this, we artificially induced removal behavior, and after providing the mite with enough time to re-enter another cell, we opened all capped cells, relocated the mites, and evaluated their reproduction. As shown in previous studies and in this study, VSH had no effect on MNR levels. Also, the induced removal behavior did not lead to non-reproduction in the subsequent reproductive cycle post interruption. We thus concluded that breeding for non-reproductive mites does not automatically breed for VSH behavior and worker removal behavior does not cause subsequent reproductive failure of the mites forced to flee and find a new cell for reproduction.