Dissection of genetic associations with language-related traits in population-based cohorts.
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ABSTRACT:
SUBMITTER: Paracchini S
PROVIDER: S-EPMC3230763 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe future productivity of wheat (T. aestivum L.) as the most grown crop worldwide is of utmost importance for global food security. Thousand kernel weight (TKW) in wheat is closely associated with grain architecture-related traits, e.g. kernel length (KL), kernel width (KW), kernel area (KA), kernel diameter ratio (KDR), and factor form density (FFD). Discovering the genetic architecture of natural variation in these traits, identifying QTL and candidate genes are the main aims of this study. Therefore, grain architecture-related traits in 261 worldwide winter accessions over three field-year experiments were evaluated.ResultsGenome-wide association analysis using 90K SNP array in FarmCPU model revealed several interesting genomic regions including 17 significant SNPs passing false discovery rate threshold and strongly associated with the studied traits. Four of associated SNPs were physically located inside candidate genes within LD interval e.g. BobWhite_c5872_589 (602,710,399 bp) found to be inside TraesCS6A01G383800 (602,699,767-602,711,726 bp). Further analysis reveals the four novel candidate genes potentially involved in more than one grain architecture-related traits with a pleiotropic effects e.g. TraesCS6A01G383800 gene on 6A encoding oxidoreductase activity was associated with TKW and KA. The allelic variation at the associated SNPs showed significant differences betweeen the accessions carying the wild and mutated alleles e.g. accessions carying C allele of BobWhite_c5872_589, TraesCS6A01G383800 had significantly higher TKW than the accessions carying T allele. Interestingly, these genes were highly expressed in the grain-tissues, demonstrating their pivotal role in controlling the grain architecture.ConclusionsThese results are valuable for identifying regions associated with kernel weight and dimensions and potentially help breeders in improving kernel weight and architecture-related traits in order to increase wheat yield potential and end-use quality.
| S-EPMC8431894 | biostudies-literature
Project description:Insulin resistance, broadly defined as the reduced ability of insulin to exert its biological action, has been associated with depression and cognitive dysfunction in observational studies. However, it is unclear whether these associations are causal and whether they might be underpinned by other shared factors. To address this knowledge gap, we capitalized on the stability of genetic biomarkers through the lifetime, and on their unidirectional relationship with depression and cognition. Specifically, we determined the association between quantitative measures of cognitive function and depression and genetic instruments of insulin resistance traits in two large-scale population samples, the Generation Scotland: Scottish Family Health Study (GS: SFHS; N = 19,994) and in the UK Biobank (N = 331,374). In the GS:SFHS, the polygenic risk score (PRS) for fasting insulin was associated with verbal intelligence and depression while the PRS for the homeostasis model assessment of insulin resistance was associated with verbal intelligence. Despite this overlap in genetic architecture, Mendelian randomization analyses in the GS:SFHS and in the UK Biobank samples did not yield evidence for causal associations from insulin resistance traits to either depression or cognition. These findings may be due to weak genetic instruments, limited cognitive measures and insufficient power but they may also indicate the need to identify other biological mechanisms that may mediate the relationship from insulin resistance to depression and cognition.
| S-EPMC6503941 | biostudies-literature
Project description:We estimated broad heritabilities (H(2)) and narrow heritabilities (h(2)) and conducted genomewide screens, using a novel association-based mapping approach for 20 quantitative trait loci (QTLs) among the Hutterites, a founder population that practices a communal lifestyle. Heritability estimates ranged from.21 for diastolic blood pressure (DBP) to.99 for whole-blood serotonin levels. Using a multipoint method to detect association under a recessive model we found evidence of major QTLs for six traits: low-density lipoprotein (LDL), triglycerides, lipoprotein (a) (Lp[a]), systolic blood pressure (SBP), serum cortisol, and whole-blood serotonin. Second major QTLs for Lp(a) and for cortisol were identified using a single-point method to detect association under a general two-allele model. The heritabilities for these six traits ranged from.37 for triglycerides to.99 for serotonin, and three traits (LDL, SBP, and serotonin) had significant dominance variances (i.e., H(2) > h(2)). Surprisingly, there was little correlation between measures of heritability and the strength of association on a genomewide screen (P>.50), suggesting that heritability estimates per se do not identify phenotypes that are influenced by genes with major effects. The present study demonstrates the feasibility of genomewide association studies for QTL mapping. However, even in this young founder population that has extensive linkage disequilibrium, map densities <<5 cM may be required to detect all major QTLs.
| S-EPMC1274354 | biostudies-literature
Project description:PurposeThe purpose of this study was to describe the genetic relationship between smoking and glaucoma.MethodsWe used summary-level genetic data for smoking initiation, smoking intensity (cigarettes per day [CPD]), intraocular pressure (IOP), vertical cup-disc ratio, and open-angle glaucoma (OAG) to estimate global genetic correlations (rg) and perform two-sample Mendelian randomization (MR) experiments that explored relations between traits. Finally, we examined associations between smoking genetic risk scores (GRS) and smoking traits with measured IOP and OAG in Rotterdam Study participants.ResultsWe identified weak inverse rg between smoking- and glaucoma-related traits that were insignificant after Bonferroni correction. However, MR analysis revealed that genetically predicted smoking initiation was associated with lower IOP (-0.18 mm Hg per SD, 95% confidence interval [CI] = -0.30 to -0.06, P = 0.003). Furthermore, genetically predicted smoking intensity was associated with decreased OAG risk (odds ratio [OR] = 0.74 per SD, 95% CI = 0.61 to 0.90, P = 0.002). In the Rotterdam Study, the smoking initiation GRS was associated with lower IOP (-0.09 mm Hg per SD, 95% CI = -0.17 to -0.01, P = 0.04) and lower odds of OAG (OR = 0.84 per SD, 95% CI = 0.73 to 0.98, P = 0.02) in multivariable-adjusted analyses. In contrast, neither smoking history nor CPD was associated with IOP (P ≥ 0.38) or OAG (P ≥ 0.54). Associations between the smoking intensity GRS and glaucoma traits were null (P ≥ 0.13).ConclusionsMR experiments and GRS generated from Rotterdam Study participants support an inverse relationship between smoking and glaucoma.Translational relevanceUnderstanding the genetic drivers of the inverse relationship between smoking and glaucoma could yield new insights into glaucoma pathophysiology.
| S-EPMC9932549 | biostudies-literature
Project description:Heritability, genetic correlation, and genetic associations estimated from samples of unrelated individuals are often perceived as confirmation that genotype causes the phenotype(s). However, these estimates can arise from indirect mechanisms due to population phenomena including population stratification, dynastic effects, and assortative mating. We introduce these, describe how they can bias or inflate genotype-phenotype associations, and demonstrate methods that can be used to assess their presence. Using data on educational achievement and parental socioeconomic position as an exemplar, we demonstrate that both heritability and genetic correlation may be biased estimates of the causal contribution of genotype. These results highlight the limitations of genotype-phenotype estimates obtained from samples of unrelated individuals. Use of these methods in combination with family-based designs may offer researchers greater opportunities to explore the mechanisms driving genotype-phenotype associations and identify factors underlying bias in estimates.
| S-EPMC7159920 | biostudies-literature
Project description:Genetic dissection kernel weight-related traits is of great significance for improving wheat yield potential. As one of the three major yield components of wheat, thousand kernel weight (TKW) was mainly affected by grain length (GL) and grain width (GW). To uncover the key loci for these traits, we carried out a quantitative trait loci (QTL) analysis of an F6 recombinant inbred lines (RILs) population derived from a cross of Henong 5290 (small grain) and 06Dn23 (big grain) with a 50 K single nucleotide polymorphism (SNP) array. A total of 17 stable and big effect QTL, including 5 for TKW, 8 for GL and 4 for GW, were detected on the chromosomes 1B, 2A, 2B, 2D, 4B, 5A, 6A and 6D, respectively. Among these, there were two co-located loci for three traits that were mapped on the chromosome 4BS and 6AL. The QTL on 6AL was the most stable locus and explained 15.4-24.8%, 4.1-8.8% and 15.7-24.4% of TKW, GW and GL variance, respectively. In addition, two more major QTL of GL were located on chromosome arm 2BL and 2DL, accounting for 9.7-17.8% and 13.6-19.8% of phenotypic variance, respectively. In this study, we found one novel co-located QTL associated with GL and TKW in 2DL, QGl.haaf-2DL.2/QTkw.haaf-2DL.2, which could explain 13.6-19.8% and 9.8-10.7% phenotypic variance, respectively. Genetic regions and linked markers of these stable QTL will help to further refine mapping of the corresponding loci and marker-assisted selection (MAS) breeding for wheat grain yield potential improvement.
| S-EPMC8103506 | biostudies-literature
Project description:An optimized plant architecture (PA) is fundamental for high-yield breeding but the genetic control of the important trait is largely unknown in rapeseed. Here plant architecture factors (PAFs) were proposed to consist of main inflorescence length proportion (MILP), branch height proportion (BHP), and branch segment proportion (BSP). Comparison of different genotypes in a DH population grown in diverse environments showed that an optimized PAF performance with MILP and BHP between 0.3-0.4 was important for high yield potential. In total, 163 unique quantitative trait loci (QTLs) for PA- and plant yield (PY)-related traits were mapped onto a high-density genetic map. Furthermore, 190 PA-related candidate genes for 91 unique PA QTLs and 2350 PY epistatic interaction loci-pairs were identified, which explain 2.8-51.8% and 5.2-23.6% of phenotypic variation, respectively. Three gene categories, transcription factor, auxin/IAA, and gibberellin, comprise the largest proportions of candidate genes for PA-related QTLs. The effectiveness of QTL candidate genes prediction was demonstrated by cloning of three candidate genes, Bna.A02.CLV2, Bna.A09.SLY2, and Bna.C07.AHK4. The study thus outlines a gene network for control of PA-related traits and provides novel information for understanding the establishment of ideal PA and for developing effective breeding strategies for yield improvement in rapeseed and other crops.
| S-EPMC4754947 | biostudies-literature
Project description:Heterosis contributes a big proportion to hybrid performance in maize, especially for grain yield. It is attractive to explore the underlying genetic architecture of hybrid performance and heterosis. Considering its complexity, different from former mapping method, we developed a series of linear mixed models incorporating multiple polygenic covariance structures to quantify the contribution of each genetic component (additive, dominance, additive-by-additive, additive-by-dominance, and dominance-by-dominance) to hybrid performance and midparent heterosis variation and to identify significant additive and non-additive (dominance and epistatic) quantitative trait loci (QTL). Here, we developed a North Carolina II population by crossing 339 recombinant inbred lines with two elite lines (Chang7-2 and Mo17), resulting in two populations of hybrids signed as Chang7-2 × recombinant inbred lines and Mo17 × recombinant inbred lines, respectively. The results of a path analysis showed that kernel number per row and hundred grain weight contributed the most to the variation of grain yield. The heritability of midparent heterosis for 10 investigated traits ranged from 0.27 to 0.81. For the 10 traits, 21 main (additive and dominance) QTL for hybrid performance and 17 dominance QTL for midparent heterosis were identified in the pooled hybrid populations with two overlapping QTL. Several of the identified QTL showed pleiotropic effects. Significant epistatic QTL were also identified and were shown to play an important role in ear height variation. Genomic selection was used to assess the influence of QTL on prediction accuracy and to explore the strategy of heterosis utilization in maize breeding. Results showed that treating significant single nucleotide polymorphisms as fixed effects in the linear mixed model could improve the prediction accuracy under prediction schemes 2 and 3. In conclusion, the different analyses all substantiated the different genetic architecture of hybrid performance and midparent heterosis in maize. Dominance contributes the highest proportion to heterosis, especially for grain yield, however, epistasis contributes the highest proportion to hybrid performance of grain yield.
| S-EPMC8670227 | biostudies-literature
Project description:Maize yield components including row number, kernel number per row, kernel thickness, kernel width, kernel length, 100-kernel weight, and volume weight affect grain yield directly. Previous studies mainly focused on dissecting the genetic basis of per se performances for yield-related traits, but the genetic basis of general combining ability (GCA) for these traits is still unclear. In the present study, 328 RILs were crossed as males to two testers according to the NCII mating design, resulting in a hybrid panel composed of 656 hybrids. Both the hybrids and parental lines were evaluated in four environments in 2015 and 2016. Correlation analysis showed the performances of GCA effects were significantly correlated to the per se performances of RILs for all yield-related traits (0.17 ≤ r ≤ 0.64, P > 0.01). Only 17 of 95 QTL could be detected for both per se performances of RILs and GCA effects for eight yield-related traits. The QTL qKN7-1 and qHKW1-3, which could explain more than 10% of the variation in the GCA effects of KN and HKW, were also detected for per se performances for the traits. The pleiotropic loci qRN3-1 and qRN6, which together explained 14.92% of the observed variation in GCA effects for RN, were associated with the GCA effects of KW and HKW, but not with per se performances for these traits. In contrast, Incw1, which was related to seed weight in maize, was mapped to the region surrounding MK2567 at the qHKW5-2 locus, but no GCA effect was detected. The QTL identified in present study for per se performances and corresponding GCA effects for yield-related traits might be useful for maize hybrid breeding.
| S-EPMC7387702 | biostudies-literature
Project description:To get additional insight into the phenotype of attentional problems, we examined to what extent genetic and environmental factors explain covariation between lack of dispositional mindfulness and attention-deficit/hyperactivity disorder (ADHD) traits in youth, and explored the incremental validity of these constructs in predicting life satisfaction. We used data from a UK population-representative sample of adolescent twins (N = 1092 pairs) on lack of dispositional mindfulness [Mindful Attention Awareness Scale (MAAS)], ADHD traits [Conners' Parent Rating Scale-Revised (CPRS-R): inattentive (INATT) and hyperactivity/impulsivity (HYP/IMP) symptom dimensions] and life satisfaction (Students' Life Satisfaction Scale). Twin model fitting analyses were conducted. Phenotypic correlations (rp) between MAAS and CPRS-R (INATT: rp = 0.18, HYP/IMP: rp = 0.13) were small, but significant and largely explained by shared genes for INATT (% rp INATT-MAAS due to genes: 93%, genetic correlation rA = 0.37) and HYP/IMP (% rp HYP/IMP-MAAS due to genes: 81%; genetic correlation rA = 0.21) with no significant contribution of environmental factors. MAAS, INATT and HYP/IMP significantly and independently predicted life satisfaction. Lack of dispositional mindfulness, assessed as self-reported perceived lapses of attention (MAAS), taps into an aspect of attentional functioning that is phenotypically and genetically distinct from parent-rated ADHD traits. The clinically relevant incremental validity of both scales implicates that MAAS could be used to explore the underlying mechanisms of an aspect of attentional functioning that uniquely affects life satisfaction and is not captured by DSM-based ADHD scales. Further future research could identify if lack of dispositional mindfulness and high ADHD traits can be targeted by different therapeutic approaches resulting in different effects on life satisfaction.
| S-EPMC6751144 | biostudies-literature