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1 ase, and resistance to fungal infection is a complex trait.
2 that harbor functional genetic variants of a complex trait.
3 coding variant in BRCA1 associated with any complex trait.
4 y explain the 'missing heritability' of this complex trait.
5 each set controls a biological process or a complex trait.
6 livestock that was driven by selection on a complex trait.
7 t of genetic markers (genomic feature) and a complex trait.
8 ive trait nucleotides (QTNs) associated with complex traits.
9 hat has emerged as a model for Mendelian and complex traits.
10 tools for the study of the genetic basis of complex traits.
11 strated a major role for GxE interactions in complex traits.
12 ) were identified by GWAS as associated with complex traits.
13 a role for rare variants in the etiology of complex traits.
14 new insight into the genetic architecture of complex traits.
15 el insights into the genetic architecture of complex traits.
16 ve been widely used in genetic dissection of complex traits.
17 sights into the shared genetic basis of many complex traits.
18 nd insights into the allelic architecture of complex traits.
19 sease risk factors and biomedically relevant complex traits.
20 ess and can facilitate the evolution of more complex traits.
21 s like sorghum to study the genetic basis of complex traits.
22 s for the source of missing heritability for complex traits.
23 genotype expression across a range of human complex traits.
24 dentifying genetic variants underlying human complex traits.
25 to shed light on the genetic architecture of complex traits.
26 y, thereby increasing understanding of these complex traits.
27 e to gain insights into the genetic basis of complex traits.
28 ent of methylation may have a causal role in complex traits.
29 linked, co-evolving genes that often control complex traits.
30 contributes to variation in quantitative and complex traits.
31 identify some of the missing heritability of complex traits.
32 but common features of a range of high-level complex traits.
33 and to facilitate the genetic dissection of complex traits.
34 of heritable phenotypic variance in diverse complex traits.
35 ay contribute to the missing heritability in complex traits.
36 s for the identification of genes underlying complex traits.
37 cis-regulated expression is associated with complex traits.
38 etect associations between rare variants and complex traits.
39 exhausted their potential, particularly for complex traits.
40 help understand the genetic architecture of complex traits.
41 im to identify rare variants contributing to complex traits.
42 and the genetic basis of gene expression and complex traits.
43 genetic underpinnings of the heritability of complex traits.
44 is designed to improve genomic prediction of complex traits.
45 e an important source of variation for human complex traits.
46 identified many genetic variants underlying complex traits.
47 functionally validated as being relevant for complex traits.
48 associated with multiple diseases and other complex traits.
49 may be associated with monogenic disease or complex traits.
50 s and unraveling the genetic architecture of complex traits.
51 irs, virtually all published twin studies of complex traits.
52 ousands of variants robustly associated with complex traits.
53 overed, leading to a deeper understanding of complex traits.
54 ss the role of epigenetic variation in human complex traits.
55 s light on miRNA involvement in a variety of complex traits.
56 uence genetic studies and contribute to many complex traits.
57 ucidate the role of microRNA as mediators of complex traits.
58 these traits being two independent polygenic complex traits.
59 echanisms that lead to relationships between complex traits.
60 t MPB is less genetically complex than other complex traits.
61 for fine mapping and association mapping of complex traits.
62 ve TF sets governing biological processes or complex traits.
63 ommon variants on cell types contributing to complex traits.
64 r characterizing the genetic architecture of complex traits.
65 mportant in unravelling the genetic basis of complex traits.
66 uired to dissect the genetic architecture of complex traits.
67 vel discoveries and insights into biology of complex traits.
68 proach for identifying new genes involved in complex traits.
69 ng the involvement of RVs in the etiology of complex traits.
70 enetic variation involved in the etiology of complex traits.
71 r further understanding the etiology of many complex traits.
72 t role in the etiology of human diseases and complex traits.
73 o characterizing the genetic architecture of complex traits.
74 r genes and their targets in both simple and complex traits.
75 r further discovery of genes associated with complex traits, a study design with SNP arrays followed
78 ed for over 600,000 SNPs we used Genome-wide Complex Trait Analysis (GCTA) to estimate the proportion
81 following: same-sample bivariate genome-wide complex trait analysis (GCTA)-GREML; independent samples
82 e genetic technique in a century-Genome-wide Complex Trait Analysis (GCTA)-which estimates genetic in
84 mate SNP-based heritability, the genome-wide complex trait analysis procedure was applied to two larg
87 y between unrelated individuals (genome-wide complex trait analysis) indicate that the genotyped func
89 ential SNPs are correlated with a particular complex trait and are important to the prediction of the
90 host susceptibility to HFD-induced T2D is a complex trait and controlled by multiple genetic factors
91 (GWASs) have used microbiome variation as a complex trait and have uncovered human genetic variants
93 ic correlation between gene expression and a complex trait and utilize it to estimate the genetic cor
94 ink biologically meaningful sets of genes to complex traits and at the same time reveal the molecular
95 l fraction of phenotypic variation for human complex traits and contributes little to the missing nar
96 and rare (MAF </= 1%) variants contribute to complex traits and disease in the general population is
97 panels to study the genetic architecture of complex traits and disease in the general population.
100 Identifying genetic correlations between complex traits and diseases can provide useful etiologic
101 eral and can be applied to GWAS data for all complex traits and diseases in humans and to such data i
106 lts data to estimate the SNP heritability of complex traits and diseases, partition this heritability
107 e identified thousands of risk loci for many complex traits and diseases, the causal variants and gen
108 rogeneity in genetic architecture underlying complex traits and diseases, while broadly acknowledged,
120 potential to elucidate the genetic basis of complex traits and further our understanding of transcri
121 ariants pleiotropically associated with both complex traits and gene expression, to identify variants
122 ate the contribution of mQTL to variation in complex traits and infer that methylation may have a cau
124 used to dissect the genetic architecture of complex traits and predict phenotypes for marker-assiste
125 opulations to dissect the genetic control of complex traits and present a set of candidate genes for
126 istical power to assess associations between complex traits and relevant intermediate phenotypes, has
127 y, but GBS outperformed low-density SNPs for complex traits and simple traits evaluated under stress
128 d to understand the role of rare variants in complex traits and to advance the goals of precision med
129 studies to identify genetic risk factors in complex traits and to predict evolution under selection.
130 ntify novel genetic variants associated with complex traits and to shed new insights on underlying bi
132 insights into the genetic correlation among complex traits and will facilitate future soybean functi
133 arget gene networks on the genetics of human complex traits, and provided resources which should cont
134 lucidate the genetic portions of these truly complex traits, and this knowledge can then be mined for
136 ss-nation differences in the mean values for complex traits are common, but the reasons for these dif
140 As the majority of mutations associated with complex traits are located outside the exome, it is cruc
141 n genome-wide association studies (GWASs) of complex traits are thought to act by affecting gene regu
143 el has proven to be useful for prediction of complex traits as well as estimation of population genet
145 ), designed to improve the power for mapping complex-trait-associated loci in a minority population b
146 only have a number of important disease and complex trait association findings emerged, but our coll
147 s of isolated populations can boost power in complex-trait association studies, and an in-depth under
150 Here we analyzed summary statistics from 56 complex traits (average N = 101,401) by extending strati
151 ation studies are widely utilized to analyze complex traits but their ability to disclose genetic arc
152 nderstand the genetic mechanisms governing a complex trait, but may not be directly relevant to plant
153 iants play a central role in the genetics of complex traits, but we still lack a full understanding o
156 Our findings show that the regulation of complex traits can be highly dependent on the developmen
157 ta to perform accurate genetic prediction of complex traits can facilitate genomic selection in anima
158 endeavor to associate genetic variation with complex traits, closely related taxa are particularly fr
159 ts into GWAS transferability, we developed a complex trait coalescent-based simulation framework cons
160 he contribution of low-frequency variants in complex traits, demonstrate the advantage of including p
161 associated with GWAS variants for a range of complex traits, demonstrating the utility of this approa
164 ed model analysis confirmed the advantage of complex trait dissection using an integrated approach.
165 than 90% of common variants associated with complex traits do not affect proteins directly, but inst
166 his goal has proven difficult since NUE is a complex trait encompassing physiological and development
167 of microRNA (miRNA) on the genetics of human complex traits, especially in the context of miRNA-targe
170 e method to the GWAS results of the 18 human complex traits from >1.75 million subjects, and identifi
171 esults indicate that genetic dissection of a complex trait, functional annotation of new genes, and t
172 perspective and highlight the usefulness of complex trait genetic studies in isolated populations.
175 overies it has facilitated in population and complex-trait genetics, the biology of diseases, and tra
177 ediction performance, prediction accuracy of complex traits (grain yield) were consistently lower tha
178 a small proportion of heritability for each complex trait has been explained by identified genetic v
179 olite variation) in populations that vary in complex traits, has proven effective for dissecting the
181 h genome-wide association studies (GWAS) for complex traits have discovered a large number of trait-
183 arge sets of variants to the heritability of complex traits have yielded important insights into the
184 between summed runs of homozygosity and four complex traits: height, forced expiratory lung volume in
188 traits in two species, and to predict eight complex traits in a human cohort.Genetic prediction of c
191 ated that integrated molecular dissection of complex traits in different population types can enable
193 allele sharing may be useful for studies of complex traits in founder populations, where hidden rela
194 y to jointly predict phenotypes for multiple complex traits in human genetic epidemiology as well as
197 ever, many sequence variants associated with complex traits in maize have small effects and low repea
202 TLs that were reported to be associated with complex traits in prior genome-wide association studies,
204 bottlenecks impeding the genetic analysis of complex traits in rodents are access to mapping populati
205 EML-LDMS) to estimate heritability for human complex traits in unrelated individuals using whole-geno
206 y (677C > T polymorphism) increases risk for complex traits, including neuropsychiatric disorders.
207 al properties of the allelic architecture of complex traits, including the proportion of the heritabl
208 een LeafCutter intron quantifications and 40 complex traits increased the number of associated diseas
211 cohorts (the Gene-Lifestyle Interactions and Complex Traits Involved in Elevated Disease Risk [GLACIE
212 nts from the Gene-Lifestyle Interactions and Complex Traits Involved in Elevated Disease Risk Study.
213 flurry of work revealing size to be a highly complex trait involving the integration of three core as
214 n such that each quantitative trait locus of complex trait is in linkage disequilibrium with at least
219 ment of the contribution of rare variants to complex traits is hampered by low statistical power and
221 sults prove that very accurate prediction of complex traits is possible, and suggest that additional
222 particularly challenging compared with other complex traits is the difficulty of accessing the releva
226 These results suggest genetic influences on complex traits like obesity can vary over time, presumab
227 rse populations can increase power to detect complex trait loci when the underlying causal variants a
229 atory variants mediate the majority of known complex trait loci, we sought to identify gene-by-BMI (G
233 iation studies (GWAS) for genetic mapping of complex traits, most existing GWAS methodologies are sti
235 ful to identify novel susceptibility loci to complex traits not only for ethnicity-specific loci but
237 rsity have used genotypes varying in several complex traits, obscuring the specific phenotypic variat
238 erpret the underlying mechanism regulating a complex trait of interest in each discovered locus, rese
241 variants associated with common diseases and complex traits, only a handful of these variants are val
245 e genome-wide association studies (GWASs) on complex traits, our understanding of their genetic archi
246 e understanding of the genetic regulation of complex traits, particularly in species that carry large
247 cular fluid IL-1beta) and derive periodontal complex traits (PCTs) via principal component analysis.
248 growing evidence of shared risk alleles for complex traits (pleiotropy), including autoimmune and ne
250 leaving an open question of whether accurate complex trait predictions can be achieved in practice.
252 hat can help understand the functionality of complex trait-related single nucleotide polymorphisms (S
254 hese splicing QTLs are major contributors to complex traits, roughly on a par with variants that affe
255 ious studies, we found that similar to other complex traits, schizophrenia risk genes were more likel
256 umulating evidence suggesting that different complex traits share common risk basis, namely pleiotrop
257 s imply that studies of the genetic basis of complex traits should be expanded to include mechanisms
258 en with legumes is a remarkable example of a complex trait spread by horizontal transfer of a few key
259 ant applications such as assembly of protein complexes, trait stacking, and metabolic engineering.
261 rge datasets to dissect the genetic basis of complex traits such as behavior, which are both time-con
262 lation resulted very useful for delving into complex traits such as biomass production and digestibil
264 ected functionalities that can be related to complex traits such as disease progression, drug respons
266 questions about the genetic architecture of complex traits, such as allele frequency and effect size
267 rmatics have enabled breakthroughs for other complex traits, such as cardiovascular disease or asthma
269 sing different data and methods obscures how complex traits, such as epithelia, neurons, and muscles
270 rofile of genetic influences contributing to complex traits, such as social communication difficultie
271 er, we identify shifts associated with other complex traits, suggesting that polygenic adaptation has
272 gnitive impairment in older individuals is a complex trait that in population-based studies most comm
276 growth, wood density, and wood chemistry are complex traits that are hard to improve in long-lived pe
277 estigate the amount of genetic variation for complex traits that can be revealed by single-SNP genome
279 dentified some nucleotide variants affecting complex traits that have been validated with fine-mappin
280 entified thousands of variants associated to complex traits, these variants only explain a small amou
281 titative trait loci (mQTL), although as with complex traits they lack the statistical power to identi
282 tistical power to identify risk variants for complex traits through a joint analysis of multiple GWAS
285 ast set-based association analysis for human complex traits using summary-level data from genome-wide
286 rease the accuracy of genomic prediction for complex traits using this model, provided the genomic fe
291 librium (LD)-dependent architecture of human complex traits, where SNPs with low levels of LD (LLD) h
295 investigation of the genetic basis of other complex traits with overlapping and distinct clinical fe
296 aits in a human cohort.Genetic prediction of complex traits with polygenic architecture has wide appl
298 and fetal brain) to prioritize genes for >40 complex traits with robust GWAS data and found considera
299 te that both adaptability and pleiotropy are complex traits, with extensive heritable differences ari
300 ows that epigenetic mechanisms contribute to complex traits, with implications across many fields of
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