Genetic variation and association of yield, yield components, and carbon storage in sorghum (Sorghum bicolor [L.] Moench) genotypes.

Trait heritability and the response to selection depend on genetic variation, a prerequisite to developing sorghum varieties with desirable agronomic traits and high carbon sequestration for sustainable crop production and soil health. The present study aimed to assess the extent of genetic variability and associations among agronomic and carbon storage traits in selected sorghum genotypes to identify the best candidates for production or breeding. Fifty genotypes were evaluated at Ukulinga, Bethlehem and Silverton sites in South Africa during the 2022/23 growing season. The following agronomic and carbon storage traits were collected: days to 50% heading (DTH), days to 50% maturity (DTM), plant height (PH), total plant biomass (PB), shoot biomass (SB), root biomass (RB), root-to-shoot biomass ratio (RS), grain yield (GY), harvest index (HI), shoot carbon content (SCc), root carbon content (RCc), grain carbon content (GCc), total plant carbon stock (PCs), shoot carbon stock (SCs), root carbon stock (RCs), and root-to-shoot carbon stock ratio (RCs/SCs), and grain carbon stock (GCs). Higher genotypic coefficient of variations (GCVs) were recorded for GY at 45.92%, RB (39.24%), RCs/SCs (38.45), and RCs (34.62). Higher phenotypic coefficient of variations (PCVs) were recorded for PH (68.91%), followed by GY (51.8%), RB (50.51%), RS (41.96%), RCs/SCs (44.90%), and GCs (41.90%). High broad-sense heritability and genetic advance were recorded for HI (83.76 and 24.53%), GY (78.59 and 9.98%), PB (74.14 and 13.18%) and PCs (53.63 and 37.57%), respectively, suggesting a marked genetic contribution to the traits. Grain yield exhibited positive association with HI (r = 0.76; r = 0.79), DTH (r = 0.13; r = 0.31), PH (r = 0.1; r = 0.27), PB (r = 0.01; r = 0.02), RB (r = 0.05; r = 0.06) based on genotypic and phenotypic correlations, respectively. Further, the path analysis revealed significant positive direct effects of SB (0.607) and RB (0.456) on GY. The RS exerted a positive and significant indirect effect (0.229) on grain yield through SB. The study revealed that PB, SB, RB, RS, RCs, and RCs/SCs are the principal traits when selecting sorghum genotypes with high yield and carbon storage capacity.

Adult Offspring of Deer Mouse Breeding Pairs Selected for Normal and Compulsive-Like Large Nesting Expression Invariably Show the Same Behavior Without Prior In-Breeding.

Obsessive-compulsive disorder is a neuropsychiatric condition with notable genetic involvement. Against this background, laboratory-housed deer mice of both sexes varyingly present with excessive and persistent large nesting behavior (LNB), which has been validated for its resemblance of clinical compulsivity. Although LNB differs from normal nesting behavior (NNB) on both a biological and cognitive level, it is unknown to what extent the expression of LNB and NNB is related to familial background. Here, we randomly selected 14 NNB- and 14 LNB-expressing mice (equally distributed between sexes) to constitute 7 breeding pairs of each phenotype. Pairs were allowed to breed two successive generations of offspring, which were raised until adulthood (12 weeks) and assessed for nesting expression. Remarkably, our findings show that offspring from LNB-expressing pairs build significantly larger nests compared to offspring from NNB-expressing pairs and the nesting expression of the offspring of each breeding pair, irrespective of parental phenotype or litter, is family specific. Collectively, the results of this investigation indicate that LNB can be explored for its potential to shed light on heritable neurocognitive mechanisms that may underlie the expression of specific persistent behavioral phenotypes.

Basal plasma oxytocin & fecal cortisol concentrations are highly heritable and associated with individual differences in behavior & cognition in dog puppies.

Oxytocin and cortisol are hormones that can influence cognition and behavior, but the relationships between endogenous concentrations and individual differences in cognitive and behavioral phenotypes remain poorly understood. Across mammals, oxytocin has important roles in diverse social behaviors, and in dogs, it has been implicated in human-oriented behaviors such as social gaze and point-following. Cortisol, an end-product of the hypothalamic-pituitary-adrenal (HPA) axis, is often studied in relation to temperament and emotional reactivity, but it is also known to modulate executive functions. In this study, we measured basal fecal cortisol (n = 247) and plasma oxytocin (n = 249) in dog puppies from a pedigreed population (Canine Companions ®). We collected cognitive and behavioral data from these subjects (n = 247), including measures of human-oriented social cognition, memory, inhibitory control, perceptual discriminations, and temperament. Oxytocin concentrations were estimated to be very highly heritable (h2 = 0.90-0.99) and cortisol concentrations were estimated to be moderately-highly heritable (h2 = 0.43-0.47). Bayesian mixed models controlling for relatedness revealed that oxytocin concentrations were positively associated with spatial working memory and displayed a negative quadratic relationship with behavioral laterality, but no credible associations were seen for social measures. Cortisol concentrations exhibited a negative linear relationship with performance on an inhibitory control task and a negative quadratic relationship with bold behavioral reactions to a novel object. Collectively, our results suggest that individual differences in oxytocin and cortisol concentrations are under strong genetic control in dogs and are associated with phenotypic variation in aspects of temperament, behavioral laterality, and executive function.

Soybean pod shattering resistance allele pdh1 and marker-assisted selection.

Pod shattering is a major production constraint of soybean [Glycine max (L.)]. The objectives of this study were to (i) estimate heritability for pod shattering resistance, (ii) determine the frequency of the pod shattering resistance allele pdh1 in the International Institute for Tropical Agriculture (IITA) soybean germplasm and Zambian commercial varieties, and (iii) determine the effectiveness of the DNA marker for the pod shattering resistance allele pdh1. A total of 59 genotypes were evaluated for pod shattering in field trials conducted in Malawi and Zambia and genotyped with a marker for pdh1. TGx2002-8FM and TGx2002-9FM were the most resistant among genotypes in early and medium maturity classes and can be used for genetic enhancement of pod shattering resistance in these specific maturity classes. Narrow sense heritability estimates for pod shattering ranged from 0.27 to 0.80. Of the 59 genotypes, 57 (96.6%) carried the resistance allele pdh1 while only two genotypes (3.6%) carried the susceptible allele, suggesting near-fixation of the resistance allele pdh1 in the IITA germplasm. The marker for pdh1 was highly effective in selecting resistant genotypes.

Genetic effects on the skin methylome in healthy older twins.

Whole-skin DNA methylation variation has been implicated in several diseases, including melanoma, but its genetic basis has not yet been fully characterized. Using bulk skin tissue samples from 414 healthy female UK twins, we performed twin-based heritability and methylation quantitative trait loci (meQTL) analyses for >400,000 DNA methylation sites. We find that the human skin DNA methylome is on average less heritable than previously estimated in blood and other tissues (mean heritability: 10.02%). meQTL analysis identified local genetic effects influencing DNA methylation at 18.8% (76,442) of tested CpG sites, as well as 1,775 CpG sites associated with at least one distal genetic variant. As a functional follow-up, we performed skin expression QTL (eQTL) analyses in a partially overlapping sample of 604 female twins. Colocalization analysis identified over 3,500 shared genetic effects affecting thousands of CpG sites (10,067) and genes (4,475). Mediation analysis of putative colocalized gene-CpG pairs identified 114 genes with evidence for eQTL effects being mediated by DNA methylation in skin, including in genes implicating skin disease such as ALOX12 and CSPG4. We further explored the relevance of skin meQTLs to skin disease and found that skin meQTLs and CpGs under genetic influence were enriched for multiple skin-related genome-wide and epigenome-wide association signals, including for melanoma and psoriasis. Our findings give insights into the regulatory landscape of epigenomic variation in skin.

Methodological approaches to assessing the genetic predisposition of osteochondrosis of the tarsocrural joint in the Pura Raza Española horses.

Osteochondrosis (OC) is a developmental orthopaedic disease of significant concern in numerous sport horse breeds, with significant international relevance. Using digital radiographs, we assessed the occurrence of hock (tarsocrural joint) OC in 3 048 Pura Raza Española (PRE) horses which took part in a morpho-functional test, in three specific locations in the tarsus limbs: the Distal Intermediate Ridge of the Tibia (DIRT), the lateral trochlear ridges of the talus (LTT), and the medial trochlear ridges of the talus (MTT). An incidence rate of 13.3% was found for hock OC in the analysed sample, with the highest incidence rate observed in DIRT (10.0%) and the lowest in MTT (0.2%). Estimates of genetic predisposition to hock OC were carried out using three genetic approaches: 1a) a binomial threshold model based on the presence or absence of OC, 1b) a multinomial threshold model, on a scale from 0 (absence) to 3 (maximum), and 2) a linear model. The effects considered in the models included sex, genetic origin and stud class. All the analyses were based on the Bayesian inference methodology, using the THRGIBBS3F90 software. The binomial threshold model yielded the most suitable results, with an estimated heritability for Overall hock OC of 0.71 ± 0.055 on the underlying scale (0.53 on the observed scale), ranging in different locations from 0.48 ± 0.087 (LTT) to 0.66 ± 0.063 (DIRT) on the underlying scale (0.10 and 0.38 on the observed scale, respectively). The highest significative genetic correlation was observed between Overall and DIRT (0.97) for approach 1a, and the lowest significant genetic correlation was between Overall and LTT (0.49), for approach 2. This study contributes valuable insights into the genetic predisposition towards, as well as for the potential for selective breeding against, hock OC in PRE horses, and provides a basis for future research and breeding programmes aimed at minimising the occurrence of hock OC and promoting the overall health of this breed.

A twin analysis to estimate genetic and environmental factors contributing to variation in weighted gene co-expression network module eigengenes.

Multivariate network-based analytic methods such as weighted gene co-expression network analysis are frequently applied to human and animal gene-expression data to estimate the first principal component of a module, or module eigengene (ME). MEs are interpreted as multivariate summaries of correlated gene-expression patterns and network connectivity across genes within a module. As such, they have the potential to elucidate the mechanisms by which molecular genomic variation contributes to individual differences in complex traits. Although increasingly used to test for associations between modules and complex traits, the genetic and environmental etiology of MEs has not been empirically established. It is unclear if, and to what degree, individual differences in blood-derived MEs reflect random variation versus familial aggregation arising from heritable or shared environmental influences. We used biometrical genetic analyses to estimate the contribution of genetic and environmental influences on MEs derived from blood lymphocytes collected on a sample of N = 661 older male twins from the Vietnam Era Twin Study of Aging (VETSA) whose mean age at assessment was 67.7 years (SD = 2.6 years, range = 62-74 years). Of the 26 detected MEs, 14 (56%) had statistically significant additive genetic variation with an average heritability of 44% (SD = 0.08, range = 35%-64%). Despite the relatively small sample size, this demonstration of significant family aggregation including estimates of heritability in 14 of the 26 MEs suggests that blood-based MEs are reliable and merit further exploration in terms of their associations with complex traits and diseases.

Genetic analysis of a maternal assistance score in sheep.

Maternal behaviour is important for lamb survival, as ewes perform many behaviours that affect the chances of a lamb surviving. Collecting maternal behaviour data directly at lambing is time-consuming and not considered suitable for acquiring the large volumes of data that would be required for using as selection criteria within commercial breeding flocks. The aim of this study was to investigate if a simple scoring system is heritable and assesses the expression of behaviours that reduce the probability of lamb mortality. Ewe behaviour was scored on a 3-point Maternal Assistance Score (MAS): (1) the ewe shows a high level of maternal interest (assumed if no intervention required); (2) the ewe shows limited interest in her lamb; and (3) the ewe shows no interest in her lamb. A total of 19 453 MAS were collected over 12 years, across 24 farms (including both indoor and outdoor lambing systems) and 12 different breed lines that make up the Innovis breeding programme. Ewe parity, breed, number of lambs carried, flock, lambing batch, lambing day within flock and pre-mating weight all had a significant effect on MAS (P < 0.05). The maternal assistance score was shown to be heritable (h2 = 0.05) and repeatable (0.10), positively genetically correlated to lambing difficulty (rg = 0.29) and amount of assistance the lamb required to suckle from the ewe (rg = 0.88), and negatively genetically correlated with the number of lambs successfully reared (rg = 0.49). This study shows that an easy-to-measure score can be used by shepherds with large breeding flocks, based on whether the ewe requires further assistance to support her lamb rearing. The score could be used in breeding programmes to select for lamb rearing ability in the future and potentially lead to an improvement in lamb welfare through a reduction in mortality.

Direct inference of the distribution of fitness effects of spontaneous mutations from recombinant inbred C. elegans mutation accumulation lines.

The distribution of fitness effects (DFE) of new mutations plays a central role in evolutionary biology. Estimates of the DFE from experimental Mutation Accumulation (MA) lines are compromised by the complete linkage disequilibrium (LD) between mutations in different lines. To reduce LD, we constructed two sets of recombinant inbred lines from a cross of two C. elegans MA lines. One set of lines ("RIAILs") was intercrossed for ten generations prior to ten generations of selfing; the second set of lines ("RILs") omitted the intercrossing. Residual LD in the RIAILs is much less than in the RILs, which affects the inferred DFE when the sets of lines are analyzed separately. The best-fit model estimated from all lines (RIAILs + RILs) infers a large fraction of mutations with positive effects (∼40%); models that constrain mutations to have negative effects fit much worse. The conclusion is the same using only the RILs. For the RIAILs, however, models that constrain mutations to have negative effects fit nearly as well as models that allow positive effects. When mutations in high LD are pooled into haplotypes, the inferred DFE becomes increasingly negative-skewed and leptokurtic. We conclude that the conventional wisdom - most mutations have effects near zero, a handful of mutations have effects that are substantially negative and mutations with positive effects are very rare - is likely correct, and that unless it can be shown otherwise, estimates of the DFE that infer a substantial fraction of mutations with positive effects are likely confounded by LD.

Parent of origin genetic effects on milk production traits in a population of Iranian Holstein cows.

The aim was to estimate the relative contribution of imprinting effects from both paternal and maternal sides to phenotypic variation in milk production traits including 305 days milk yield (MY), average daily milk production (ADM), fat percentage (F%), protein percentage (P%), 305 days fat yield (FY), 305 days protein yield (PY), ratio of fat percentage to protein percentage (F:P) and somatic cell score (SCS) in Iranian Holstein cows. To do this, each trait was analysed with a series of four animal models, which were identical for fixed and additive genetic effects but differed for combinations of paternal and maternal imprinting effects. The log-likelihood ratio test (LRT) and Akaike's information criteria (AIC) were used to select the best model for each trait. Correlations between traits due to additive and imprinting effects were estimated by bivariate analyses. For all traits studied, fitting the imprinting effect led to a better data fit. Also, it resulted in a noticeable decrease in additive genetic variance from 8% (SCS) to 28% (F:P). A significant maternal imprinting effect was detected on all traits studied. Estimates of maternal imprinting heritability ( h mi 2 $$ {h}_{\mathrm{mi}}^2 $$ ) were 0.07 ± 0.02, 0.04 ± 0.01, 0.06 ± 0.01, 0.05 ± 0.01, 0.5 ± 0.01, 0.09 ± 0.02, 0.07 ± 0.02 and 0.06 ± 0.01 for MY, ADM, F%, P%, FY, PY, F:P and SCS, respectively. For F:P, in addition to the maternal imprinting effect, a significant paternal imprinting component was also detected with a 7% contribution to phenotypic variance of F:P. Estimates of direct heritability ( h a 2 $$ {h}_{\mathrm{a}}^2 $$ ) were 0.29 ± 0.02, 0.17 ± 0.01, 0.22 ± 0.02, 0.11 ± 0.01, 0.18 ± 0.02, 0.22 ± 0.02, 0.15 ± 0.04 and 0.06 ± 0.01 for MY, ADM, F%, P%, FY, PY, F:P and SCS, respectively. Maternal imprinting correlations (rmi) were in a wide range between -0.75 ± 0.15 (P%-SCS) and 0.95 ± 0.11 (MY-ADM). Additive genetic correlations (ra) ranged between -0.54 ± 0.05 (MY-P%) and 0.99 ± 0.01 (MY-ADM) and phenotypic correlations (rp) ranged from -0.30 ± 0.01 (MY-F%) to 0.93 ± 0.01 (MY-ADM). The Spearman's correlation between additive breeding values including and excluding imprinting effects deviated from unity especially for top-ranked animals implying re-ranking of top animals following the inclusion of imprinting effects in the model. Since including imprinting effects in the model resulted in better data fit and re-ranking of top animals, including these effects in the genetic evaluation models for milk production traits was recommended.

Ideotype based genotype selection in a multivariate dataset of sweet potato (Ipomoea batatas L.).

The dataset extensively examines the factors considered when choosing sweet potato genotypes, considering various characteristics. Notably, Moz1.15 demonstrated the highest marketable root yield at 46.46 t/ha, H5.ej.10 exhibited the highest beta-carotene level at 48.94 mg/100 g, and Moz1.9 recorded the highest vitamin C content at 23.89 mg/100 g. Moreover, there were significant correlations (ranging from 0.21 to 0.84) among the yield and quality traits studied in sweet potatoes. Principal component analysis (PCA) confirmed the connections among these traits, identifying four distinct clusters of genotypes, each characterized by specific significant combinations of traits. Factor analysis using the multi-trait genotype-ideotype index (MGIDI) highlighted the considerable impact of sweet potato traits across two growing seasons (2020-21 and 2021-22), facilitating the selection of genotypes with potential genetic gains ranging from 1.86 % to 75.4 %. Broad-sense heritability (h2) varied from 64.9 % to 99.8 %. The use of the MGIDI index pinpointed several promising genotypes, with BARI Mistialu-12 and H9.7.12 consistently performing well over both years. These genotypes exhibited both strengths and weaknesses.

Five years of change in adult twins: longitudinal changes of genetic and environmental influence on epigenetic clocks.

BACKGROUND: Epigenetic clocks were known as promising biomarkers of aging, including original clocks trained by individual CpG sites and principal component (PC) clocks trained by PCs of CpG sites. The effects of genetic and environmental factors on epigenetic clocks are still unclear, especially for PC clocks. METHODS: We constructed univariate twin models in 477 same-sex twin pairs from the Chinese National Twin Registry (CNTR) to estimate the heritability of five epigenetic clocks (GrimAge, PhenoAge, DunedinPACE, PCGrimAge, and PCPhenoAge). Besides, we investigated the longitudinal changes of genetic and environmental influences on epigenetic clocks across 5 years in 134 same-sex twin pairs. RESULTS: Heritability of epigenetic clocks ranged from 0.45 to 0.70, and those for PC clocks were higher than those for original clocks. For five epigenetic clocks, the longitudinal stability was moderate to high and was largely due to genetic effects. The genetic correlations between baseline and follow-up epigenetic clocks were moderate to high. Special unique environmental factors emerged both at baseline and at follow-up. PC clocks showed higher longitudinal stability and unique environmental correlations than original clocks. CONCLUSIONS: For five epigenetic clocks, they have the potential to identify aging interventions. High longitudinal stability is mainly due to genetic factors, and changes of epigenetic clocks over time are primarily due to changes in unique environmental factors. Given the disparities in genetic and environmental factors as well as longitudinal stability between PC and original clocks, the results of studies with original clocks need to be further verified with PC clocks.

LDER-GE estimates phenotypic variance component of gene-environment interactions in human complex traits accurately with GE interaction summary statistics and full LD information.

Gene-environment (GE) interactions are essential in understanding human complex traits. Identifying these interactions is necessary for deciphering the biological basis of such traits. In this study, we review state-of-art methods for estimating the proportion of phenotypic variance explained by genome-wide GE interactions and introduce a novel statistical method Linkage-Disequilibrium Eigenvalue Regression for Gene-Environment interactions (LDER-GE). LDER-GE improves the accuracy of estimating the phenotypic variance component explained by genome-wide GE interactions using large-scale biobank association summary statistics. LDER-GE leverages the complete Linkage Disequilibrium (LD) matrix, as opposed to only the diagonal squared LD matrix utilized by LDSC (Linkage Disequilibrium Score)-based methods. Our extensive simulation studies demonstrate that LDER-GE performs better than LDSC-based approaches by enhancing statistical efficiency by ~23%. This improvement is equivalent to a sample size increase of around 51%. Additionally, LDER-GE effectively controls type-I error rate and produces unbiased results. We conducted an analysis using UK Biobank data, comprising 307 259 unrelated European-Ancestry subjects and 966 766 variants, across 217 environmental covariate-phenotype (E-Y) pairs. LDER-GE identified 34 significant E-Y pairs while LDSC-based method only identified 23 significant E-Y pairs with 22 overlapped with LDER-GE. Furthermore, we employed LDER-GE to estimate the aggregated variance component attributed to multiple GE interactions, leading to an increase in the explained phenotypic variance with GE interactions compared to considering main genetic effects only. Our results suggest the importance of impacts of GE interactions on human complex traits.

MIMOSA: a resource consisting of improved methylome prediction models increases power to identify DNA methylation-phenotype associations.

Although DNA methylation (DNAm) has been implicated in the pathogenesis of numerous complex diseases, from cancer to cardiovascular disease to autoimmune disease, the exact methylation sites that play key roles in these processes remain elusive. One strategy to identify putative causal CpG sites and enhance disease etiology understanding is to conduct methylome-wide association studies (MWASs), in which predicted DNA methylation that is associated with complex diseases can be identified. However, current MWAS models are primarily trained using the data from single studies, thereby limiting the methylation prediction accuracy and the power of subsequent association studies. Here, we introduce a new resource, MWAS Imputing Methylome Obliging Summary-level mQTLs and Associated LD matrices (MIMOSA), a set of models that substantially improve the prediction accuracy of DNA methylation and subsequent MWAS power through the use of a large summary-level mQTL dataset provided by the Genetics of DNA Methylation Consortium (GoDMC). Through the analyses of GWAS (genome-wide association study) summary statistics for 28 complex traits and diseases, we demonstrate that MIMOSA considerably increases the accuracy of DNA methylation prediction in whole blood, crafts fruitful prediction models for low heritability CpG sites, and determines markedly more CpG site-phenotype associations than preceding methods. Finally, we use MIMOSA to conduct a case study on high cholesterol, pinpointing 146 putatively causal CpG sites.

Genetic Selection Approach for Semen Characteristics in Thai Native Grandparent Roosters (Pradu Hang Dum) Using Random Regression Test-Day Models and Selection Indices.

The aim of this study was to analyze suitable genetic models and selection indices to estimate the genetic parameters and breeding values of native Thai roosters. A total of 3475 records of seven semen traits (mass movement, semen pH, semen color, volume, sperm viability, sperm abnormalities, and sperm concentration) from 242 Thai native grandparent roosters were analyzed. Multiple-trait random regression test-day models with five covariance functions were used to analyze the variance components, genetic parameters, and breeding values. The selection index (SI) was calculated to determine the optimal genetic value for different selection percentages. The results showed that a multiple-trait random regression test-day model with a second-order Legendre polynomial function was the most appropriate genetic model for this population. The estimated heritability values were low to moderate, ranging from 0.110 to 0.112 (mass movement), 0.040 to 0.051 (semen pH), 0.092 to 0.097 (semen color), 0.220 to 0.225 (semen volume), 0.067 to 0.083 (sperm viability), 0.086 to 0.099 (sperm abnormalities), and 0.134 to 0.138 (sperm concentration). The repeatability values exceeded the heritability values and were within the range of 0.133 to 0.688. The genetic correlations among semen traits ranged from -0.332 to 0.677, and phenotypic correlations ranged from -0.260 to 0.460. When considering heritability and genetic correlation values, semen volume, sperm concentration, and mass movement were the top three priority semen traits calculated as selection indices. Finally, the top 10% of the selection index was recommended for creating the next generation. Our findings provide useful information on genetic parameters and an appropriate selection index of semen traits for selecting the genetics of individual Thai native grandparent roosters. The heritability estimates for semen traits reported here suggest an adequate response to selection through a genetic evaluation approach. Our results indicate that it is possible to select grandparent roosters with better reproductive performance.

Fatty Acids in Dry Beans (Phaseolus vulgaris L.): A Contribution to Their Analysis and the Characterization of a Diversity Panel.

Dry bean (Phaseolus vulgaris L.) is a crop of high nutritional interest widespread throughout the world. This research had two objectives. On the one hand, the development and validation of an analytical method to quantify fatty acids in dry beans based on the extraction and derivatization in a single step and later quantification by gas chromatography. On the other, its application to characterize the fatty acid content in a diversity panel consisting of 172 lines. The method was successfully validated in terms of accuracy, precision and robustness. Among the 14 fatty acids that constitute the fatty acid profile of dry bean, the most quantitatively important were linolenic acid, the major fatty acid in all cases, with an average value of 6.7 mg/g, followed by linoleic acid (3.9 mg/g), palmitic acid (2.9 mg/g) and oleic acid (1.5 mg/g). The concentrations of fatty acids in dry bean were influenced by the gene pool, with the Mesoamerican gene pool showing a higher content of palmitic, stearic, linoleic and linolenic acids and the Andean gene pool a higher level of cis-vaccenic acid. Also, the expression of fatty acid content showed high heritability. The information generated constitutes a robust database of interest in food technology, nutrition and breeding programs.

Understanding the Genetic Basis of Blueberry Postharvest Traits to Define Better Breeding Strategies.

Blueberry (Vaccinium spp.) is among the most-consumed soft fruit and has been recognized as an important source of health-promoting compounds. Highly perishable and susceptible to rapid spoilage due to fruit softening and decay during postharvest storage, modern breeding programs are looking to maximize quality and extend the market life of fresh blueberries. However, it is uncertain how genetically controlled postharvest quality traits are in blueberries. This study aimed to investigate the prediction ability and genetic basis of the main fruit quality traits affected during blueberry postharvest to create breeding strategies for developing cultivars with an extended shelf life. To achieve this goal, we carried out target genotyping in a breeding population of 588 individuals and evaluated for several fruit quality traits after one day, one week, three weeks, and seven weeks of postharvest storage at 1 °C. Using longitudinal genome-based methods, we estimated genetic parameters and predicted unobserved phenotypes. Our results showed large diversity, moderate heritability, and consistent predictive accuracies along the postharvest storage for most of the traits. Regarding fruit quality, firmness showed the largest variation during postharvest storage, with a surprising number of genotypes maintaining or increasing their firmness even after seven weeks of cold storage. Our results suggest that we can effectively improve blueberry postharvest quality through breeding and use genomic prediction to maximize the genetic gains in the long term. We also emphasize the potential of using longitudinal genomic prediction models to predict fruit quality at extended postharvest periods by integrating known phenotypic data from harvest.

Familial Resemblance of Bone Health in Maternal Lineage Pairs and Triads: A Scoping Review.

INTRODUCTION: Female bone health is influenced by familial resemblance, health parameters and maturational periods (puberty and menopause); this combination has been researched using familial multi-generational cross-sectional studies. AIM: This scoping review aimed to compile bone health research which uses sexually mature (grandmother-) mother-daughter pairs (and triads) and to determine the trends in its methodologies and familial comparisons. METHODS: The Joanna Briggs Institute methodology for scoping reviews was used. Extraction included study and population characteristics, methodology (with an emphasis on imaging) and family-based results. RESULTS: Twenty-nine studies were included, and their generations were categorized into four developmental categories: late adolescent to young adult, pre-menopause, mixed-menopause, and post-menopause. Eleven different pair/triad combinations were observed; the most common was pre-menopausal daughters and post-menopausal mothers. Dual-energy X-ray absorptiometry (DXA) was the most utilized imaging modality, and the hip was the most imaged region of interest (ROI). Regardless of pairing, imaging modality and ROI, there was often a trend toward significant familial resemblance and heritability (h2 and h2L). CONCLUSION: This scoping review highlights the trends in bone health linked to familial resemblance, as well as the importance of menopause and late adolescence. This review compiles the commonalities and challenges within these studies to inform future research.

Genetics of osteoarthritis.

Osteoarthritis (OA) is the most common form of arthritis with well recognized multifactorial nature. While several environmental factors such as older age, obesity and previous joint injury are strongly associated with its development, a genetic influence on OA has been recognized for over 80 years. Identification of genes associated with OA has received considerable attention over the last two decades, aided by the rapidly evolving genotyping and sequencing technologies. More than 300 genomic loci have been identified to be associated with OA at different joints. These findings are likely to help our better understanding of the pathogenesis of OA and lead to important therapeutic and diagnostic advances in this most common disabling rheumatic disorder. This article will review the data that support the role of genetic factors in common idiopathic OA.