Genetic variance and heritability estimation of hybridized pepper plants (Capsicum annuum L.) F2 progeny for begomovirus resistance in growth stage

Pepper is widely cultivated as a condiment and cash crop in Indonesia. However, Pepper yellow leaf curl disease (PepYLCD) caused by begomovirus is currently seriously affect the domestic pepper production. Breeding for begomovirus resistance material by crossing is currently necessary to overcome the constraint. The present study is aimed to determine the resistance of pepper (C. annuum) plants F2 progenies to begomovirus infection in the growth stage. Two local C. annuum accessions, BaPep-5 as a resistance donor for pepy-1 begomovirus resistance gene (locally called Perintis) and BaPep-4 as a susceptible parent (locally called Kencana) were crossed to generate F2 progenies. The research was conducted in Agricultural Extension Training Centre (BLPP) Saree and Horticulture Laboratory of Syiah Kuala University from February to July 2020. 500 F2 progenies were transplanted to the field along with 15 plants of each parent as control. The result suggested that plant height and crown width had the highest broad sense heritability value, whereas the dichotomous height, stem diameter, secondary branch, and tertiary branch had the lowest broad sense heritability value. Coefficient of genetic variance and coefficient of phenotypic variance from overall characteristics were relatively low which suggest the narrow sense to slightly narrow sense heritability.

Validation and genetic heritability estimation of known type 2 diabetes related variants in the Korean population

Genome-wide association studies (GWASs) facilitated the discovery of countless disease-associated variants. However, GWASs have mostly been conducted in European ancestry samples. Recent studies have reported that these European-based association results may reduce disease prediction accuracy when applied in non-Europeans. Therefore, previously reported variants should be validated in non-European populations to establish reliable scientific evidence for precision medicine. In this study, we validated known associations with type 2 diabetes (T2D) and related metabolic traits in 125,850 samples from a Korean population genotyped by the Korea Biobank Array (KBA). At the end of December 2020, there were 8,823 variants associated with glycemic traits, lipids, liver enzymes, and T2D in the GWAS catalog. Considering the availability of imputed datasets in the KBA genome data, publicly available East-Asian T2D summary statistics, and the linkage disequilibrium among the variants (r2 < 0.2), 2,900 independent variants were selected for further analysis. Among these, 1,837 variants (63.3%) were statistically significant (p < 0.05). Most of the non-replicated variants (n = 1,063) showed insufficient statistical power and decreased minor allele frequencies compared with the replicated variants. Moreover, known variants showed <10% genetic heritability. These results could provide valuable scientific evidence for future study designs, the current power of GWASs, and future applications in precision medicine in the Korean population.

Estimating heritability of glycaemic response to metformin using nationwide electronic health records and population-sized pedigree

Background Variability of response to medication is a well-known phenomenon, determined by both environmental and genetic factors. Understanding the heritable component of the response to medication is of great interest but challenging due to several reasons, including small study cohorts and computational limitations. Methods Here, we study the heritability of variation in the glycaemic response to metformin, first-line therapeutic agent for type 2 diabetes (T2D), by leveraging 18 years of electronic health records (EHR) data from Israel’s largest healthcare service provider, consisting of over five million patients of diverse ethnicities and socio-economic background. Our cohort consists of 80,788 T2D patients treated with metformin, with an accumulated number of 1,611,591 HbA1C measurements and 4,581,097 metformin prescriptions. We estimate the explained variance of glycated hemoglobin (HbA1c%) reduction due to inheritance by constructing a six-generation population-size pedigree from national registries and linking it to medical health records. Results Using Linear Mixed Model-based framework, a common-practice method for heritability estimation, we calculate a heritability measure of $${h}^{2}=12.6 \%$$ h 2 = 12.6 % (95% CI, $$6.1 \%\! -\!19.1 \%$$ 6.1 % − 19.1 % ) for absolute reduction of HbA1c% after metformin treatment in the entire cohort, $${h}^{2}=21.0 \%$$ h 2 = 21.0 % (95% CI, $$7.8 \%\! -\!34.4 \%$$ 7.8 % − 34.4 % ) for males and $${h}^{2}=22.9 \%$$ h 2 = 22.9 % (95% CI, $$10.0 \%\! -\!35.7 \%$$ 10.0 % − 35.7 % ) in females. Results remain unchanged after adjusting for pre-treatment HbA1c%, and in proportional reduction of HbA1c%. Conclusions To the best of our knowledge, our work is the first to estimate heritability of drug response using solely EHR data combining a pedigree-based kinship matrix. We demonstrate that while response to metformin treatment has a heritable component, most of the variation is likely due to other factors, further motivating non-genetic analyses aimed at unraveling metformin’s action mechanism.

Probabilistic inference of the genetic architecture underlying functional enrichment of complex traits

We develop a Bayesian model (BayesRR-RC) that provides robust SNP-heritability estimation, an alternative to marker discovery, and accurate genomic prediction, taking 22 seconds per iteration to estimate 8.4 million SNP-effects and 78 SNP-heritability parameters in the UK Biobank. We find that only ≤10% of the genetic variation captured for height, body mass index, cardiovascular disease, and type 2 diabetes is attributable to proximal regulatory regions within 10kb upstream of genes, while 12-25% is attributed to coding regions, 32–44% to introns, and 22-28% to distal 10-500kb upstream regions. Up to 24% of all cis and coding regions of each chromosome are associated with each trait, with over 3,100 independent exonic and intronic regions and over 5,400 independent regulatory regions having ≥95% probability of contributing ≥0.001% to the genetic variance of these four traits. Our open-source software (GMRM) provides a scalable alternative to current approaches for biobank data.

Comparing Heritability Estimators under Alternative Structures of Linkage Disequilibrium

SNP heritability of a trait is the proportion of its variance explained by the additive effects of the genome-wide single nucleotide polymorphisms (SNPs). The existing approaches to estimate SNP heritability can be broadly classified into two categories. One set of approaches model the SNP effects as fixed effects and the other treats the SNP effects as random effects. These methods make certain assumptions about the dependency among individuals (familial relationship) as well as the dependency among markers (linkage disequilibrium, LD) to provide consistent estimates of SNP heritability as the number of individuals increases. While various approaches have been proposed to account for such dependencies, it remains unclear which estimates reported in the literature are more robust against various model mis-specifications. Here we investigate the impact of different structures of LD and familial relatedness on heritability estimation. We show that the performance of different methods for heritability estimation depends heavily on the structure of the underlying pattern of LD and the degree of relatedness among sampled individuals. However, contrary to the claim in the current literature, we did not find significant differences in the performance of these fixed-SNP-effects and random-SNP-effects approaches. Moreover, we established the equivalence between the two method-of-moments estimators, one from each of these two lines of approaches.

Genetics of severe hypercholesterolemia in the general population: Insights from the STANISLAS cohort

Background: Severe hypercholesterolemia (SH) is a common condition characterized by increased levels of total and low-density lipoprotein cholesterol (LDLc). Methods: The aim of this study is to screen for prevalence of hypercholesterolemia, perform heritability estimation of circulating lipoproteins and study the association between SH cases and surrogate cardiovascular disease markers among participants of STANISLAS cohort. Gene candidate analyses were utilized to investigate the association between lipid levels, SH and polymorphisms from the three commonly reported genes (APOB, LDLR and PCSK9). Results: Participants with SH (n=102; 6.9%) were older (58 vs. 51yr), had higher total cholesterol (290 vs. 209mg/dL), LDLc (206 vs. 136mg/dL) and triglycerides (114 vs. 88 mg/dL). Despite smoking less, they had carotid plaques more frequently (21.2 vs. 9.3%), higher cIMT (676 vs. 597µm), and had more frequent family history cardiovascular disease. The circulating lipid levels have an important heritability: LDLc 51.6%, HDLc 66.6%, total cholesterol 49.8%, and triglycerides 41.4%. The SNPs located in LDLR gene present the strongest association with LDLc levels: rs55997232, rs17242395, rs1010679, and rs11668477. Conclusion: In a healthy cohort, participants with SH had premature vascular damage. LDLc had an important component of heritability and SNPs linked to the LDLR gene presented a strong association with LDLc. These findings reinforce the need for an early identification and treatment of SH subjects, which is mostly polygenic.

Estimating the Additive Heritability of Historiometric Eminence in a Super-Pedigree Comprised of Four Prominent Families

By merging analytical approaches from the fields of historiometrics and behavior genetics, a social pedigree-based estimate of the heritability of eminence is generated. Eminent individuals are identified using the Pantheon dataset. A single super-pedigree, comprised of four prominent and interrelated families (including the Wedgwood–Darwin, Arnold–Huxley, Keynes-Baha’u’lláh, and Benn-Rutherford pedigrees) is assembled, containing 30 eminent individuals out of 301 in total. Each eminent individual in the super-pedigree is assigned a relative measure of historical eminence (scaled from 1 to 100) with noneminent individuals assigned a score of 0. Utilizing a Bayesian pedigree-based heritability estimation procedure employing an informed prior, an additive heritability of eminence of .507 (95% CI [.434, .578]) was found. The finding that eminence is additively heritable is consistent with expectations from behavior-genetic studies of factors that are thought to underlie extraordinary accomplishment, which indicate that they are substantially additively heritable. Owing to the limited types of intermarriage present in the data, it was not possible to estimate the impact of nonadditive genetic contributions to heritability. Gene-by-environment interactions could not be estimated in the present analysis either; therefore, the finding that eminence is simply a function of additive genetic and nonshared environmental variance should be interpreted cautiously.

Genomics of Endometriosis: From Genome Wide Association Studies to Exome Sequencing

This review aims at better understanding the genetics of endometriosis. Endometriosis is a frequent feminine disease, affecting up to 10% of women, and characterized by pain and infertility. In the most accepted hypothesis, endometriosis is caused by the implantation of uterine tissue at ectopic abdominal places, originating from retrograde menses. Despite the obvious genetic complexity of the disease, analysis of sibs has allowed heritability estimation of endometriosis at ~50%. From 2010, large Genome Wide Association Studies (GWAS), aimed at identifying the genes and loci underlying this genetic determinism. Some of these loci were confirmed in other populations and replication studies, some new loci were also found through meta-analyses using pooled samples. For two loci on chromosomes 1 (near CCD42) and chromosome 9 (near CDKN2A), functional explanations of the SNP (Single Nucleotide Polymorphism) effects have been more thoroughly studied. While a handful of chromosome regions and genes have clearly been identified and statistically demonstrated as at-risk for the disease, only a small part of the heritability is explained (missing heritability). Some attempts of exome sequencing started to identify additional genes from families or populations, but are still scarce. The solution may reside inside a combined effort: increasing the size of the GWAS designs, better categorize the clinical forms of the disease before analyzing genome-wide polymorphisms, and generalizing exome sequencing ventures. We try here to provide a vision of what we have and what we should obtain to completely elucidate the genetics of this complex disease.

Single-Step Genome Wide Association Study Identifies QTL Signals for Untrimmed and Trimmed Thigh Weight in Italian Crossbred Pigs for Dry-Cured Ham Production

Protected Designation of Origin (PDO) dry-cured ham is the most important product in the Italian pig breeding industry, mainly oriented to produce heavy pig carcasses to obtain hams of the right weight and maturity. Recently, along with the traditional traits swine breeding programs have aimed to include novel carcass traits. The identification at the genome level of quantitative trait loci (QTLs) affecting such new traits helps to reveal their genetic determinism and may provide information to be integrated in prediction models in order to improve prediction accuracy as well as to identify candidate genes underlying such traits. This study aimed to estimate genetic parameters and perform a single step genome wide association studies (ssGWAS) on novel carcass traits such as untrimmed (UTW) and trimmed thigh weight (TTW) in two pig crossbred lines approved for the ham production of the Italian PDO. With this purpose, phenotypes were collected from ~1800 animals and 240 pigs were genotyped with Illumina PorcineSNP60 Beadchip. The single-step genomic BLUP procedure was used for the heritability estimation and to implement the ssGWAS. QTL were characterized based on the variance of 10-SNP sliding window genomic estimated breeding values. Moderate heritabilities were detected and QTL signals were identified on chromosome 1, 4, 6, 7, 11 and 15 for both traits. As expected, the genetic correlation among the two traits was very high (~0.99). The QTL regions encompassed a total of 249 unique candidate genes, some of which were already reported in association with growth, carcass or ham weight traits in pigs. Although independent studies are required to further verify our findings and disentangle the possible effects of specific linkage disequilibrium in our population, our results support the potential use of such new QTL information in future breeding programs to improve the reliability of genomic prediction.