The effect of family structure on the still-missing heritability and genomic prediction accuracy of type 2 diabetes

This study aims to assess the effect of familial structures on the still-missing heritability estimate and prediction accuracy of Type 2 Diabetes (T2D) using pedigree estimated risk values (ERV) and genomic ERV. We used 11,818 individuals (T2D cases: 2,210) with genotype (649,932 SNPs) and pedigree information from the ongoing periodic cohort study of the Iranian population project. We considered three different familial structure scenarios, including (i) all families, (ii) all families with ≥ 1 generation, and (iii) families with ≥ 1 generation in which both case and control individuals are presented. Comprehensive simulation strategies were implemented to quantify the difference between estimates of [Formula: see text] and [Formula: see text]. A proportion of still-missing heritability in T2D could be explained by overestimation of pedigree-based heritability due to the presence of families with individuals having only one of the two disease statuses. Our research findings underscore the significance of including families with only case/control individuals in cohort studies. The presence of such family structures (as observed in scenarios i and ii) contributes to a more accurate estimation of disease heritability, addressing the underestimation that was previously overlooked in prior research. However, when predicting disease risk, the absence of these families (as seen in scenario iii) can yield the highest prediction accuracy and the strongest correlation with Polygenic Risk Scores. Our findings represent the first evidence of the important contribution of familial structure for heritability estimations and genomic prediction studies in T2D.</p

Identification of Reference Genes for Quantitative Gene Expression Studies in a Non-Model Tree Pistachio (Pistacia vera L.).

The tree species, Pistacia vera (P. vera) is an important commercial product that is salt-tolerant and long-lived, with a possible lifespan of over one thousand years. Gene expression analysis is an efficient method to explore the possible regulatory mechanisms underlying these characteristics. Therefore, having the most suitable set of reference genes is required for transcript level normalization under different conditions in P. vera. In the present study, we selected eight widely used reference genes, ACT, EF1α, α-TUB, β-TUB, GAPDH, CYP2, UBQ10, and 18S rRNA. Using qRT-PCR their expression was assessed in 54 different samples of three cultivars of P. vera. The samples were collected from different organs under various abiotic treatments (cold, drought, and salt) across three time points. Several statistical programs (geNorm, NormFinder, and BestKeeper) were applied to estimate the expression stability of candidate reference genes. Results obtained from the statistical analysis were then exposed to Rank aggregation package to generate a consensus gene rank. Based on our results, EF1α was found to be the superior reference gene in all samples under all abiotic treatments. In addition to EF1α, ACT and β-TUB were the second best reference genes for gene expression analysis in leaf and root. We recommended β-TUB as the second most stable gene for samples under the cold and drought treatments, while ACT holds the same position in samples analyzed under salt treatment. This report will benefit future research on the expression profiling of P. vera and other members of the Anacardiaceae family

The distribution of gene expression levels of eight candidate reference genes in different subsets.

<p>The boxes represent mean Ct values and bars correspond to the standard deviation from various subset including: leaf subset (a), root subset (b), control subset (c), cold subset (d), drought subset (e), and salt subset (f).</p

List of the selected widely used reference genes.

<p>List of the selected widely used reference genes.</p

Candidate reference genes rank in term of their expression stability as computed by BestKeeper.

<p>Candidate reference genes rank in term of their expression stability as computed by BestKeeper.</p

Pipeline for determination of suitable reference gene under different conditions in pistachio.

<p>Two organ types (leaf and root) of three pistachio cultivars (<i>P</i>. <i>vera</i> L. cultivars Sarakhs, Badami, and Ghazvini) under three abiotic treatments (salt, drought, cold) across three time points (0, 3, 6 days after treatment) in three biological replicates were used in this study. Following the RNA extraction, cDNA synthesis and quantitative real-time PCR were conducted. Several statistical programs were applied to rank the reference genes. Different obtained reference gene ranks were subjected in RankAggreg package for attaining a consensus gene rank.</p

Primer sequences for quantitative real-time PCR of selected reference genes.

<p>Primer sequences for quantitative real-time PCR of selected reference genes.</p

Candidate reference genes rank in term of their expression stability as computed by geNorm.

<p>Candidate reference genes rank in term of their expression stability as computed by geNorm.</p

Summary of the different conditions comprising the cultivar, organ, and abiotic treatment, time course and whole dataset were used in present study.

<p>Each experiment was performed in triplicate.</p

Mean of the cycle threshold (Ct) and their standard error (SE) for the eight reference genes in different organs (A and B) under various conditions (C, D, E and F) as well as whole dataset (G).

<p>Mean of the cycle threshold (Ct) and their standard error (SE) for the eight reference genes in different organs (A and B) under various conditions (C, D, E and F) as well as whole dataset (G).</p