Implication of next-generation sequencing on association studies

Siu, Hoicheong; Zhu, Yun; Li, Jin; Xiong, Momiao

doi:10.1186/1471-2164-12-322

Cited by 19 publications

(15 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…One of the limitations of current GWAS technology is its limited ability to detect low-frequency variants. A study by Siu et al 32 found that GWAS coverage of rare variants was still inadequate despite using chips designed to detect them. In addition, the quality of imputed low-frequency and, especially, rare variants in these studies is generally lower than that for common variants.…”

Section: Discussionmentioning

confidence: 99%

“…37 Next-generation sequencing is also increasingly helping to improve the understanding of genetic association studies. 32 Projects such as ENCODE are likely to provide new insights into GWAS associations in non-coding regions of the genome. 38 Together, these multiple approaches will help us identify additional genetic associations and understand their functional implications.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

A systematic review of cancer GWAS and candidate gene meta-analyses reveals limited overlap but similar effect sizes

et al. 2013

View full text Add to dashboard Cite

Candidate gene and genome-wide association studies (GWAS) represent two complementary approaches to uncovering genetic contributions to common diseases. We systematically reviewed the contributions of these approaches to our knowledge of genetic associations with cancer risk by analyzing the data in the Cancer Genome-wide Association and Meta Analyses database (Cancer GAMAdb). The database catalogs studies published since January 1, 2000, by study and cancer type. In all, we found that meta-analyses and pooled analyses of candidate genes reported 349 statistically significant associations and GWAS reported 269, for a total of 577 unique associations. Only 41 (7.1%) associations were reported in both candidate gene meta-analyses and GWAS, usually with similar effect sizes. When considering only noteworthy associations (defined as those with false-positive report probabilities r0.2) and accounting for indirect overlap, we found 202 associations, with 27 of those appearing in both meta-analyses and GWAS. Our findings suggest that meta-analyses of well-conducted candidate gene studies may continue to add to our understanding of the genetic associations in the post-GWAS era.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

A systematic review of cancer GWAS and candidate gene meta-analyses reveals limited overlap but similar effect sizes

et al. 2013

View full text Add to dashboard Cite

show abstract

“…Different values of ρ correspond to different levels of LD, with ρ = 0 indicating linkage equilibrium (LE) and greater ρ indicating stronger LD between neighboring variants. LD between common and rare variants and among rare variants is generally weak [16–17], but LD among common variants could be strong. We, therefore, considered 2 different LD structures among all CVs and LCVs: (1) the CVs and LCVs are in linkage equilibrium ( ρ = 0); (2) the CVs and LCVs are situated in regions of moderate LD ( ρ = 0.5).…”

Section: Simulation Studiesmentioning

confidence: 99%

Two-Stage Extreme Phenotype Sequencing Design for Discovering and Testing Common and Rare Genetic Variants: Efficiency and Power

Kang

Lin²,

Hákonarson³

et al. 2012

Hum Hered

View full text Add to dashboard Cite

Next-generation sequencing technology provides an unprecedented opportunity to identify rare susceptibility variants. It is not yet financially feasible to perform whole-genome sequencing on a large number of subjects, and a two-stage design has been advocated to be a practical option. In stage I, variants are discovered by sequencing the whole genomes of a small number of carefully selected individuals. In stage II, the discovered variants of a large number of individuals are genotyped to assess associations. Individuals with extreme phenotypes are typically selected in stage I. Using simulated data for unrelated individuals, we explore two important aspects of this two-stage design: the efficiency of discovering common and rare single-nucleotide polymorphisms (SNPs) in stage I and the impact of incomplete SNP discovery in stage I on the power of testing associations in stage II. We applied a sum test and a sum of squared score test for gene-based association analyses evaluating the power of the two-stage design. We obtained the following results from extensive simulation studies and analysis of the GAW17 dataset. When individuals with trait values more extreme than the 99.7–99th quantile were included in stage I, the two-stage design could achieve the same power as or even higher than the one-stage design if the rare causal variants had large effect sizes. In such design, fewer than half of the total SNPs including more than half of the causal SNPs were discovered, which included nearly all SNPs with minor allele frequencies (MAFs) ≥5%, more than half of the SNPs with MAFs between 1% and 5%, and fewer than half of the SNPs with MAFs <1%. Although a one-stage design may be preferable to identify multiple rare variants having small to moderate effect sizes, our observations support using the two-stage design as a cost-effective option for next-generation sequencing studies.

show abstract

“…This is referred to as next-generation GWAS [43]. With this approach, variants down to a population frequency of 1 % are found.…”

Section: The Experts’ Perspectivementioning

confidence: 99%

Future possibilities in migraine genetics

2012

View full text Add to dashboard Cite

Migraine with and without aura (MA and MO, respectively) have a strong genetic basis. Different approaches using linkage-, candidate gene- and genome-wide association studies have been explored, yielding limited results. This may indicate that the genetic component in migraine is due to rare variants; capturing these will require more detailed sequencing in order to be discovered. Next-generation sequencing (NGS) techniques such as whole exome and whole genome sequencing have been successful in finding genes in especially monogenic disorders. As the molecular genetics research progresses, the technology will follow, rendering these approaches more applicable in the search for causative migraine genes in MO and MA. To date, no studies using NGS in migraine genetics have been published. In order to gain insight into the future possibilities of migraine genetics, we have looked at NGS studies in other diseases and have interviewed three experts in the field of genetics and complex traits. The experts’ ideas suggest that the preferred NGS approach depends on the expected effect size and the frequency of the variants of interest. Family-specific variants can be found by sequencing a small number of individuals, while a large number of unrelated cases are needed to find common and rare variants. NGS is currently hampered by high cost and technical problems concurrent with analyzing large amounts of data generated, especially by whole genome sequencing. As genome-wide association chips, exome sequencing and whole genome sequencing gradually become more affordable, these approaches will be used on a larger scale. This may reveal new risk variants in migraine which may offer previously unsuspected biological insights.

show abstract

Implication of next-generation sequencing on association studies

Cited by 19 publications

References 19 publications

A systematic review of cancer GWAS and candidate gene meta-analyses reveals limited overlap but similar effect sizes

A systematic review of cancer GWAS and candidate gene meta-analyses reveals limited overlap but similar effect sizes

Two-Stage Extreme Phenotype Sequencing Design for Discovering and Testing Common and Rare Genetic Variants: Efficiency and Power

Future possibilities in migraine genetics

Contact Info

Product

Resources

About