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Dissecting genetic networks underlying complex phenotypes: the theoretical framework.

ABSTRACT: Great progress has been made in genetic dissection of quantitative trait variation during the past two decades, but many studies still reveal only a small fraction of quantitative trait loci (QTLs), and epistasis remains elusive. We integrate contemporary knowledge of signal transduction pathways with principles of quantitative and population genetics to characterize genetic networks underlying complex traits, using a model founded upon one-way functional dependency of downstream genes on upstream regulators (the principle of hierarchy) and mutual functional dependency among related genes (functional genetic units, FGU). Both simulated and real data suggest that complementary epistasis contributes greatly to quantitative trait variation, and obscures the phenotypic effects of many 'downstream' loci in pathways. The mathematical relationships between the main effects and epistatic effects of genes acting at different levels of signaling pathways were established using the quantitative and population genetic parameters. Both loss of function and "co-adapted" gene complexes formed by multiple alleles with differentiated functions (effects) are predicted to be frequent types of allelic diversity at loci that contribute to the genetic variation of complex traits in populations. Downstream FGUs appear to be more vulnerable to loss of function than their upstream regulators, but this vulnerability is apparently compensated by different FGUs of similar functions. Other predictions from the model may account for puzzling results regarding responses to selection, genotype by environment interaction, and the genetic basis of heterosis.

SUBMITTER: Zhang F

PROVIDER: S-EPMC3024316 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature

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Dissecting genetic networks underlying complex phenotypes: the theoretical framework.

Zhang Fan F Zhai Hu-Qu HQ Paterson Andrew H AH Xu Jian-Long JL Gao Yong-Ming YM Zheng Tian-Qing TQ Wu Rong-Ling RL Fu Bin-Ying BY Ali Jauhar J Li Zhi-Kang ZK

PloS one 20110120 1

Great progress has been made in genetic dissection of quantitative trait variation during the past two decades, but many studies still reveal only a small fraction of quantitative trait loci (QTLs), and epistasis remains elusive. We integrate contemporary knowledge of signal transduction pathways with principles of quantitative and population genetics to characterize genetic networks underlying complex traits, using a model founded upon one-way functional dependency of downstream genes on upstre ...[more]

PMID: 21283795

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Project description:BackgroundMany maternal traits are associated with a neonate's gestational duration, birth weight, and birth length. These birth outcomes are subsequently associated with late-onset health conditions. The causal mechanisms and the relative contributions of maternal and fetal genetic effects behind these observed associations are unresolved.Methods and findingsBased on 10,734 mother-infant duos of European ancestry from the UK, Northern Europe, Australia, and North America, we constructed haplotype genetic scores using single-nucleotide polymorphisms (SNPs) known to be associated with adult height, body mass index (BMI), blood pressure (BP), fasting plasma glucose (FPG), and type 2 diabetes (T2D). Using these scores as genetic instruments, we estimated the maternal and fetal genetic effects underlying the observed associations between maternal phenotypes and pregnancy outcomes. We also used infant-specific birth weight genetic scores as instrument and examined the effects of fetal growth on pregnancy outcomes, maternal BP, and glucose levels during pregnancy. The maternal nontransmitted haplotype score for height was significantly associated with gestational duration (p = 2.2 × 10-4). Both maternal and paternal transmitted height haplotype scores were highly significantly associated with birth weight and length (p < 1 × 10-17). The maternal transmitted BMI scores were associated with birth weight with a significant maternal effect (p = 1.6 × 10-4). Both maternal and paternal transmitted BP scores were negatively associated with birth weight with a significant fetal effect (p = 9.4 × 10-3), whereas BP alleles were significantly associated with gestational duration and preterm birth through maternal effects (p = 3.3 × 10-2 and p = 4.5 × 10-3, respectively). The nontransmitted haplotype score for FPG was strongly associated with birth weight (p = 4.7 × 10-6); however, the glucose-increasing alleles in the fetus were associated with reduced birth weight through a fetal effect (p = 2.2 × 10-3). The haplotype scores for T2D were associated with birth weight in a similar way but with a weaker maternal effect (p = 6.4 × 10-3) and a stronger fetal effect (p = 1.3 × 10-5). The paternal transmitted birth weight score was significantly associated with reduced gestational duration (p = 1.8 × 10-4) and increased maternal systolic BP during pregnancy (p = 2.2 × 10-2). The major limitations of the study include missing and heterogenous phenotype data in some data sets and different instrumental strength of genetic scores for different phenotypic traits.ConclusionsWe found that both maternal height and fetal growth are important factors in shaping the duration of gestation: genetically elevated maternal height is associated with longer gestational duration, whereas alleles that increase fetal growth are associated with shorter gestational duration. Fetal growth is influenced by both maternal and fetal effects and can reciprocally influence maternal phenotypes: taller maternal stature, higher maternal BMI, and higher maternal blood glucose are associated with larger birth size through maternal effects; in the fetus, the height- and metabolic-risk-increasing alleles are associated with increased and decreased birth size, respectively; alleles raising birth weight in the fetus are associated with shorter gestational duration and higher maternal BP. These maternal and fetal genetic effects may explain the observed associations between the studied maternal phenotypes and birth outcomes, as well as the life-course associations between these birth outcomes and adult phenotypes.

Dataset Information

Dissecting genetic networks underlying complex phenotypes: the theoretical framework.

Publications

Dissecting genetic networks underlying complex phenotypes: the theoretical framework.

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