The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project–imputed genotype data in up to ~370,000 women, we identify 389 independent signals (P < 5 × 10−8) for age at menarche, a milestone in female pubertal development. In Icelandic data, these signals explain ~7.4% of the population variance in age at menarche, corresponding to ~25% of the estimated heritability. We implicate ~250 genes via coding variation or associated expression, demonstrating significant enrichment in neural tissues. Rare variants near the imprinted genes MKRN3 and DLK1 were identified, exhibiting large effects when paternally inherited. Mendelian randomization analyses suggest causal inverse associations, independent of body mass index (BMI), between puberty timing and risks for breast and endometrial cancers in women and prostate cancer in men. In aggregate, our findings highlight the complexity of the genetic regulation of puberty timing and support causal links with cancer susceptibility.

The Swedish Twin Registry (STR) today contains more than 194,000 twins and more than 75,000 pairs have zygosity determined by an intra-pair similarity algorithm, DNA, or by being of opposite sex. Of these, approximately 20,000, 25,000, and 30,000 pairs are monozygotic, same-sex dizygotic, and opposite-sex dizygotic pairs, respectively. Since its establishment in the late 1950s, the STR has been an important epidemiological resource for the study of genetic and environmental influences on a multitude of traits, behaviors, and diseases. Following large investments in the collection of biological specimens in the past 10 years we have now established a Swedish twin biobank with DNA from 45,000 twins and blood serum from 15,000 twins, which effectively has also transformed the registry into a powerful resource for molecular studies. We here describe the main projects within which the new collections of both biological samples as well as phenotypic measures have been collected. Coverage by year of birth, zygosity determination, ethnic heterogeneity, and influences of in vitro fertilization are also described.

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Glutathione S-transferase (GST) refers to one of the major detoxifying enzymes that plays an important role in different abiotic and biotic stress modulation pathways of plant. The present study aimed to a comprehensive genome-wide functional characterization of GST genes and proteins in tomato (Solanum lycopersicum L.). The whole genome sequence analysis revealed the presence of 90 GST genes in tomato, the largest GST gene family reported till date. Eight segmental duplicated gene pairs might contribute significantly to the expansion of SlGST gene family. Based on phylogenetic analysis of tomato, rice, and Arabidopsis GST proteins, GST family members could be further divided into ten classes. Members of each orthologous class showed high conservancy among themselves. Tau and lambda are the major classes of tomato; while tau and phi are the major classes for rice and Arabidopsis. Chromosomal localization revealed highly uneven distribution of SlGST genes in 13 different chromosomes, where chromosome 9 possessed the highest number of genes. Based on publicly available microarray data, expression analysis of 30 available SlGST genes exhibited a differential pattern in all the analyzed tissues and developmental stages. Moreover, most of the members showed highly induced expression in response to multiple biotic and abiotic stress inducers that could be harmonized with the increase in total GST enzyme activity under several stress conditions. Activity of tomato GST could be enhanced further by using some positive modulators (safeners) that have been predicted through molecular docking of SlGSTU5 and ligands. Moreover, tomato GST proteins are predicted to interact with a lot of other glutathione synthesizing and utilizing enzymes such as glutathione peroxidase, glutathione reductase, glutathione synthetase and γ-glutamyltransferase. This comprehensive genome-wide analysis and expression profiling would provide a rational platform and possibility to explore the versatile role of GST genes in crop engineering.

In order to further illuminate the potential role of dominant genetic variation in the "missing heritability" debate, we investigated the additive (narrow-sense heritability, h(2)) and dominant (δ(2)) genetic variance for 18 human complex traits. Within the same study base (10,682 Swedish twins), we calculated and compared the estimates from classic twin-based structural equation model with SNP-based genomic-relatedness-matrix restricted maximum likelihood [GREML(d)] method. Contributions of δ(2) were evident for 14 traits in twin models (average δ(2)twin = 0.25, range 0.14-0.49), two of which also displayed significant δ(2) in the GREMLd analyses (triglycerides δ(2)SNP = 0.28 and waist circumference δ(2)SNP = 0.19). On average, the proportion of h(2)SNP/h(2)twin was 70% for ADE-fitted traits (for which the best-fitting model included additive and dominant genetic and unique environmental components) and 31% for AE-fitted traits (for which the best-fitting model included additive genetic and unique environmental components). Independent evidence for contribution from shared environment, also in ADE-fitted traits, was obtained from self-reported within-pair contact frequency and age at separation. We conclude that despite the fact that additive genetics appear to constitute the bulk of genetic influences for most complex traits, dominant genetic variation might often be masked by shared environment in twin and family studies and might therefore have a more prominent role than what family-based estimates often suggest. The risk of erroneously attributing all inherited genetic influences (additive and dominant) to the h(2) in too-small twin studies might also lead to exaggerated "missing heritability" (the proportion of h(2) that remains unexplained by SNPs).

Purpose To estimate the heritability of scoliosis in the Swedish Twin Registry. Methods Self-reported data on scoliosis from 64,578 twins in the Swedish Twin Registry were analysed. Prevalence, pair-and probandwise concordances and tetrachoric correlations in mono-and dizygotic same-sex twins were calculated. The relative importance of genetic variance, i.e. the heritability, and unique and shared environmental variance was estimated using structural equation modelling in Mx software. In addition, all twins in the twin registry were matched against the Swedish Inpatient Register on the primary diagnosis idiopathic scoliosis. Results The prevalence of scoliosis was 4%. Pair-and probandwise concordance was 0.11/0.17 for mono-and 0.04/0.08 for same-sex dizygotic twins. The tetrachoric correlation (95% CI) was 0.41 (0.33-0.49) in mono-and 0.18 (0.09-0.29) in dizygotic twins. The most favourable model in the Mx analyses estimated the additive genetic effects (95% CI) to 0.38 (0.18-0.46) and the unique environmental effects to 0.62 (0.54-0.70). Shared environmental effects were not significant. The pairwise/ probandwise concordance for idiopathic scoliosis in the Swedish Inpatient Register was 0.08/0.15 for monozygotic and zero/zero for same-sex dizygotic twins. Conclusion Using self-reported data on scoliosis from the Swedish Twin Registry, we estimate that 38% of the variance in the liability to develop scoliosis is due to additive genetic effects and 62% to unique environmental effects. This is the first study of sufficient size to make heritability estimates of scoliosis.

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In twin studies of cardiovascular disease biomarkers the dizygotic correlations are often estimated to be less than half of monozygotic correlations indicating a potential influence of nonadditive genetic factors. Using a large and homogenous sample, we estimated the additive and dominance genetic influences on levels of high density lipoprotein, low density lipoprotein, apolipoprotein A-I, apolipoprotein B, total cholesterol, triglycerides, glucose, hemoglobin Alc and c-reactive protein, all of which are biomarkers associated with cardiovascular disease. The blood biomarkers were measured on 12,000 Swedish twins born between 1911 and 1958. The large sample allowed us to obtain heritability estimates with considerable precision and provided adequate statistical power for estimation of dominance genetic components. Our study showed complete absence of the shared environment component for the investigated traits. Dominant genetic component was shown to be significant for low density lipoprotein (0.18), glucose (0.31), Hemoglobin Alc (0.55), and c-reactive protein (0.27). To our knowledge, this is the first statistically significant evidence for dominance genetic variance found for low density lipoprotein, glucose, hemoglobin Alc, and c-reactive protein in a population based twin sample. The study highlights the importance of acknowledging nonadditive genes underlying the risk of developing cardiovascular diseases.