Regional Association Analysis Research Articles

Global and regional genetic association analysis of ulcerative colitis and type 2 diabetes mellitus and causal validation analysis of two-sample two-way Mendelian randomization.

Clinical co-occurrence of UC (Ulcerative Colitis) and T2DM (Type 2 Diabetes Mellitus) is observed. The aim of this study is to investigate the potential causal relationship between Ulcerative Colitis (UC) and Type 2 Diabetes Mellitus (T2DM) using LDSC and LAVA analysis, followed by genetic verification through TSMR, providing insights for clinical prevention and treatment. Genetic loci closely related to T2DM were extracted as instrumental variables from the GWAS database, with UC as the outcome variable, involving European populations. The UC data included 27,432 samples and 8,050,003 SNPs, while the T2DM data comprised 406,831 samples and 11,914,699 SNPs. LDSC and LAVA were used for quantifying genetic correlation at both global (genome-wide) and local (genomic regions) levels. MR analysis was conducted using IVW, MR-Egger regression, Weighted median, and Weighted mode, assessing the causal relationship between UC and diabetes with OR values and 95% CI. Heterogeneity and pleiotropy were tested using Egger-intercept, MR-PRESSO, and sensitivity analysis through the "leave-one-out" method and Cochran Q test. Subsequently, a reverse MR operation was conducted using UC as the exposure data and T2DM as the outcome data for validation. Univariable and bivariable LDSC calculated the genetic correlation and potential sample overlap between T2DM and UC, resulting in rg = -0.0518, se = 0.0562, P = 0.3569 with no significant genetic association found for paired traits. LAVA analysis identified 9 regions with local genetic correlation, with 6negative and 3 positive associations, indicating a negative correlation between T2DM and UC. MR analysis, with T2DM as the exposure and UC as the outcome, involved 34 SNPs as instrumental variables. The OR values and 95% CI from IVW, MR-Egger, Weighted median, and Weighted mode were 0.917 (0.848~0.992), 0.949 (0.800~1.125), 0.881 (0.779~0.996), 0.834(0.723~0.962) respectively, with IVW P-value < 0.05, suggesting a negative causal relationship between T2DM and UC. MR-Egger regression showed an intercept of -0.004 with a standard error of 0.009, P = 0.666, and MR-PRESSO Global Test P-value > 0.05, indicating no pleiotropy and no outliers detected. Heterogeneity tests showed no heterogeneity, and the "leave-one-out" sensitivity analysis results were stable. With UC as the exposure and T2DM as the outcome, 32 SNPs were detected, but no clear causal association was found. There is a causal relationship between T2DM and UC, where T2DM reduces the risk of UC, while no significant causal relationship was observed from UC to T2DM.

Host genetic variation at a locus near CHD1L impacts HIV sequence diversity in a South African population.

It has been previously shown that genetic variants near CHD1L on chromosome 1 are associated with reduced HIV VL in African populations. However, the impact of these variants on viral diversity and how they restrict viral replication are unknown. We report on a regional association analysis in a South African population and show evidence of selective pressure by variants near CHD1L on HIV RT and gag. Our findings provide further insight into how genetic variability at this locus contributes to host control of HIV in a South African population.

Causal links of α-thalassemia indices and cardiometabolic traits and diabetes: MR study.

Our study aimed to investigate if genetic variants around 16p13.3's HBA1 locus, associated with erythrocyte indices and HbA1c levels, predict α-thalassemia-related erythrocyte indices, cardiometabolic traits, and diabetes risk in Taiwanese individuals. We analyzed Taiwan Biobank data, including whole-genome sequencing from 1,493 participants and genotyping arrays from 129,542 individuals. First, we performed regional association analysis using whole-genome sequencing data to identify genetic variants significantly associated with erythrocyte indices, confirming their linkage disequilibrium with the α0 thalassemia --SEA deletion mutation, a common cause of α-thalassemia in Southeast Asian populations. Deletion mutation sequencing further validated these variants' association with α-thalassemia. Subsequently, we analyzed genotyping array data, revealing associations between specific genetic variants and cardiometabolic traits, including lipid profiles, HbA1c levels, bilirubin levels, and diabetes risk. Using Mendelian randomization, we established causal relationships between α-thalassemia-related erythrocyte indices and cardiometabolic traits, elucidating their role in diabetes susceptibility. Our findings highlight genetic variants around the α-globin genes as surrogate markers for common α-thalassemia mutations in Taiwan, emphasizing the causal links between α-thalassemia-related erythrocyte indices, cardiometabolic traits, and heightened diabetes risk.

Differential Effects of ABCG5/G8 Gene Region Variants on Lipid Profile, Blood Pressure Status, and Gallstone Disease History in Taiwan.

ABCG5 and ABCG8 are two key adenosine triphosphate-binding cassette (ABC) proteins that regulate whole-body sterol trafficking. This study aimed to elucidate the association between ABCG5/G8 gene region variants and lipid profile, cardiometabolic traits, and gallstone disease history in Taiwan. A total of 1494 Taiwan Biobank participants with whole-genome sequencing data and 117,679 participants with Axiom Genome-Wide CHB Array data were enrolled for analysis. Using genotype-phenotype and stepwise linear regression analyses, we found independent associations of four Asian-specific ABCG5 variants, rs119480069, rs199984328, rs560839317, and rs748096191, with total, low-density lipoprotein (LDL), and non-high-density lipoprotein (HDL) cholesterol levels (all p ≤ 0.0002). Four other variants, which were in nearly complete linkage disequilibrium, exhibited genome-wide significant associations with gallstone disease history, and the ABCG8 rs11887534 variant showed a trend of superiority for gallstone disease history in a nested logistic regression model (p = 0.074). Through regional association analysis of various other cardiometabolic traits, two variants of the PLEKHH2, approximately 50 kb from the ABCG5/G8 region, exhibited significant associations with blood pressure status (p < 10-6). In conclusion, differential effects of ABCG5/G8 region variants were noted for lipid profile, blood pressure status, and gallstone disease history in Taiwan. These results indicate the crucial role of individualized assessment of ABCG5/G8 variants for different cardiometabolic phenotypes.

A quantitative trait GWAS on lens thickness identifies novel risk loci on PTPRM in the narrow angle individuals susceptible to PACG.

PACG is one of the leading causes of blindness where lens thickness is a major risk factor for narrow-angle individuals. To our knowledge, no literature has been reported on candidate gene for lens thickness as a quantitative trait (QT). Here, we performed a genome-wide association analysis on lens thickness in the narrow-angle individuals. We conducted a genome-wide association study (GWAS) in the narrow angle individuals to investigate comprehensive genetic insights on lens thickness. In QT-GWAS, we identified 145 genome-wide suggestive significant loci in the discovery cohort. Subsequently, we observed 13 SNPs that showed statistical significance around the region of PTRRM. Regional association analysis for top significant genotyped variants identified PTPRM as the most likely candidate for increased LT. Integrative bioinformatic analyses confirmed that the associated genomic region has potential regulatory roles for modulating transcription as enhancers. In the replication cohort, the sentinel genotype SNP was further associated significantly (P-value =0.000448) with high LT individuals. In both cohorts, the T allele of rs1941137 in the PTPRM gene indicates as a risk allele for the increased LT. In this study, we discovered evidence of a genomic association between chromosomal areas around the PTPRM and increased lens thickness, resulting in a narrow angle. The regulatory components corresponding to PTPRM variations might have a role in the thicker lens. We report that the genomic region near PTPRM, a gene of potential interest, is associated with increased lens thickness.

Genetic mapping and regional association analysis revealed a CYTOKININ RESPONSE FACTOR 10 gene controlling flowering time in Brassica napus L.

Oilseed rape (Brassica napus L.), as an important source of renewable energy and an industrial crop, has received extensive attention. Breeding cultivars with appropriate flowering time (FT) is of high significance for crop yields, but it is currently impeded by incomplete understanding of genetic control for flowering time in B. napus. In this study, ebm, an ethyl methanesulfonate mutagenesis (EMS) mutant with early blooming, was derived from B. napus cv. Zhongshuang9 (ZS9). Genetic analysis showed that the early blooming of ebm was controlled by a dominant nuclear gene. The Ebm locus was delimitated in a 905-kb region on chromosome A02 by bulked segregant analysis sequencing and fine mapping. Based on the expression and variation analysis of the genes in the candidate region, and gene conservation analysis in pan-genome, a potential gene BnaA02.CRF10 was pinpointed, which encodes a cytokinin response factor involved in the cytokinin signaling pathway. Regional association and haplotype analyses of the initial and blooming FT in a worldwide bio-panel of 263 re-sequenced B. napus accessions further confirmed the candidate gene and mined favorable allelic variations. Additionally, differentially expressed genes (DEGs) related to ethylene and cytokinin genetic factors were significantly induced in the ebm mutant by comparative transcriptome analysis. Moreover, phylogenetic and synteny network analyses provided strong evidence for the phylogenetic conservation of the CRF subfamily during the evolutionary history from Chlorophyta to dicotyledonous plants. Taken together, a novel conserved gene with favorable alleles conferring early flowering trait in B. napus was identified, which lays a foundation for the genetic improvement and cultivar breeding of this important crop with shortened growth periods in the future.

Transcriptome and Regional Association Analyses Reveal the Effects of Oleosin Genes on the Accumulation of Oil Content in Brassica napus.

Rapeseed stores lipids in the form of oil bodies. Oil bodies in the seeds of higher plants are surrounded by oleosins. Adjusting oleosin protein levels can prevent the fusion of oil bodies and maintain oil body size during seed development. However, oil contents are affected by many factors, and studies on the complex molecular regulatory mechanisms underlying the variations in seed oil contents of B. napus are limited. In this study, a total of 53 BnOLEO (B. napus oleosin) genes were identified in the genome of B. napus through a genome-wide analysis. The promoter sequences of oleosin genes consisted of various light-, hormone-, and stress-related cis-acting elements, along with transcription factor (TF) binding sites, for 25 TF families in 53 BnOLEO genes. The differentially expressed oleosin genes between two high- and two low-oil-content accessions were explored. BnOLEO3-C09, BnOLEO4-A02, BnOLEO4-A09, BnOLEO2-C04, BnOLEO1-C01, and BnOLEO7-A03 showed higher expressions in the high-oil-content accessions than in low-oil-content accessions, at 25, 35, and 45 days after pollination (DAP) in two different environments. A regional association analysis of 50 re-sequenced rapeseed accessions was used to further analyze these six BnOLEO genes, and it revealed that the nucleotide variations in the BnOLEO1-C01 and BnOLEO7-A03 gene regions were related to the phenotypic variations in seed oil content. Moreover, a co-expression network analysis revealed that the BnOLEO genes were directly linked to lipid/fatty acid metabolism, TF, lipid transport, and carbohydrate genes, thus forming a molecular network involved in seed oil accumulation. These favorable haplotypes can be utilized in molecular marker-assisted selection in order to further improve seed oil contents in rapeseed.

Regional association and transcriptome analysis revealed candidate genes controlling plant height in Brassica napus.

The online version contains supplementary material available at 10.1007/s11032-022-01337-1.

Genetic Variants at the APOE Locus Predict Cardiometabolic Traits and Metabolic Syndrome: A Taiwan Biobank Study.

Several apolipoprotein genes are located at the APOE locus on chromosome 19q13.32. This study explored the genetic determinants of cardiometabolic traits and metabolic syndrome at the APOE locus in a Taiwanese population. A total of 81,387 Taiwan Biobank (TWB) participants were enrolled to undergo genotype–phenotype analysis using data from the Axiom Genome-Wide CHB arrays. Regional association analysis with conditional analysis revealed lead single-nucleotide variations (SNVs) at the APOE locus: APOE rs7412 and rs429358 for total, low-density lipoprotein (LDL), and high-density lipoprotein (HDL) cholesterol levels; CLPTM1 rs3786505 and rs11672748 for LDL and HDL cholesterol levels; and APOC1 rs438811 and APOE-APOC1 rs439401 for serum triglyceride levels. Genotype–phenotype association analysis revealed a significant association of rs429358 and rs438811 with metabolic syndrome and of rs7412, rs438811, and rs439401 with serum albumin levels (p < 0.0015). Stepwise regression analysis indicated that CLPTM1 variants were independently associated with LDL and HDL cholesterol levels (p = 3.10 × 10−15 for rs3786505 and p = 1.48 × 10−15 for rs11672748, respectively). APOE rs429358 and APOC1 rs438811 were also independently associated with metabolic syndrome (p = 2.29 × 10−14) and serum albumin levels (p = 3.80 × 10−6), respectively. In conclusion, in addition to APOE variants, CLPTM1 is a novel candidate locus for LDL and HDL cholesterol levels at the APOE gene region in Taiwan. Our data also indicated that APOE and APOC1 variants were independently associated with metabolic syndrome and serum albumin levels, respectively. These results revealed the crucial role of genetic variants at the APOE locus in predicting cardiometabolic traits and metabolic syndrome.

GATA4 and estrogen receptor alpha bind at SNPs rs9921222 and rs10794639 to regulate AXIN1 expression in osteoblasts.

Osteoporosis is a serious public health problem that affects 200 million people worldwide. Genome-wide association studies have revealed the association between several single nucleotide polymorphisms (SNPs) near WNT/β-catenin signaling genes and bone mineral density (BMD). The activation of β-catenin by WNT ligands is required for osteoblast differentiation. SNP rs9921222 is an intronic variant of AXIN1 (a scaffold protein in the destruction complex that regulates β-catenin signaling) that correlates with BMD. However, the biological mechanism of SNP rs9921222 has never been reported. Here, we show that the genotype of SNP rs9921222 correlates with the expression of AXIN1 in human osteoblasts. RNA and genomic DNA were analyzed from primary osteoblasts from 111 different individuals. Homozygous TT at rs9921222 correlates with a higher expression of AXIN1 than homozygous CC. Regional association analysis showed that rs9921222 is in high linkage disequilibrium (LD) with SNP rs10794639. In silico transcription factor analysis predicted that rs9921222 is within a GATA4 motif and rs10794639 is adjacent to an estrogen receptor alpha (ERα) motif. Mechanistically, GATA4 and ERα bind at SNPs rs9921222 and rs10794639 as detected by ChIP-qPCR. Luciferase assays demonstrate that rs9921222 is the causal SNP to alter ERα and GATA4 binding. GATA4 promoted the expression, and in contrast, ERα suppressed the expression of AXIN1 via the histone deacetylase complex member SIN3A. Functionally, the level of AXIN1 negatively correlates with the level of transcriptionally active β-catenin. In summary, we have discovered a molecular mechanism of the SNP rs9921222 to regulate AXIN1 through GATA4 and ERα binding in human osteoblasts.

Differential Genetic and Epigenetic Effects of the KLF14 Gene on Body Shape Indices and Metabolic Traits.

The KLF14 gene is a key metabolic transcriptional transregulator with monoallelic maternal expression. KLF14 variants are only associated with adipose tissue gene expression, and KLF14 promoter methylation is strongly associated with age. This study investigated whether age, sex, and obesity mediate the effects of KLF14 variants and DNA methylation status on body shape indices and metabolic traits. In total, the data of 78,742 and 1636 participants from the Taiwan Biobank were included in the regional plot association analysis for KLF14 variants and KLF14 methylation, respectively. Regional plot association studies revealed that the KLF14 rs4731702 variant and the nearby strong linkage disequilibrium polymorphisms were the lead variants for lipid profiles, blood pressure status, insulin resistance surrogate markers, and metabolic syndrome mainly in female participants and for body shape indices mainly in obese women. Significant age-dependent associations between KLF14 promoter methylation levels and body shape indices, and metabolic traits were also noted predominantly in female participants. KLF14 variants and KLF14 hypermethylation status were associated with metabolically healthy and unhealthy phenotypes, respectively, in obese individuals, and only the KLF14 variants demonstrated a significant association with both higher adiposity and lower cardiometabolic risk in the same allele, revealing uncoupled excessive adiposity from its cardiometabolic comorbidities, especially in obese women. Variations of KLF14 are associated with body shape indices, metabolic traits, insulin resistance, and metabolically healthy status. Differential genetic and epigenetic effects of KLF14 are age-, sex- and obesity-dependent. These results provided a personalized reference for the management of cardiometabolic diseases in precision medicine.

Identification of genes for drought resistance and prediction of gene candidates in soybean seedlings based on linkage and association mapping

Drought is one of the primary abiotic stress factors affecting the yield, growth, and development of soybeans. In extreme cases, drought can reduce yield by more than 50%. The seedling stage is an important determinant of soybean growth: the number and vigor of seedlings will affect growth and yield at harvest. Therefore, it is important to study the drought resistance of soybean seedlings. In this study, a recombinant inbred line (RIL) population comprising 234 F6:10 lines (derived from Zhonghuang 35 × Jindou 21) and a panel of 259 soybean accessions was subjected to drought conditions to identify the effects on phenotypic traits under these conditions. Using a genetic map constructed by single nucleotide polymorphism (SNPs) markers, 18 quantitative trait loci (QTL) on 7 soybean chromosomes were identified in two environments. This included 9 QTL clusters identified in the RIL population. Fifty-three QTL were identified in 19 soybean chromosomes by genome-wide association analysis (GWAS) in the panel of accessions, including 69 significant SNPs (−log10 (P) ≥ 3.97). A combination of the two populations revealed that two SNPs (−log10 (P) ≥ 3.0) fell within two of the QTL (qPH7-4 and qPH7-6) confidence intervals. We not only re-located several previously reported drought-resistance genes in soybean and other crops but also identified several non-synonymous stress-related mutation site differences between the two parents, involving Glyma.07g093000, Glyma.07g093200, Glyma.07g094100 and Glyma.07g094200. One previously unreported new gene related to drought stress, Glyma.07g094200, was found by regional association analysis. The significant SNP CHR7-17619 (G/T) was within an exon of the Glyma.07g094200 gene. In the RIL population, the DSP value of the “T” allele of CHR7-17619 was significantly (P < 0.05) larger than the “G” allele in different environments. The results of our study lay the groundwork for cloning and molecular marker-assisted selection of drought-resistance genes in soybeans at the seedling stage.

Regional association analysis coupled with transcriptome analyses reveal candidate genes affecting seed oil accumulation in Brassica napus.

Regional association analysis of 50 re-sequenced Chinese semi-winter rapeseed accessions in combination with co-expression analysis reveal candidate genes affecting oil accumulation in Brassica napus. One of the breeding goals in rapeseed production is to enhance the seed oil content to cater to the increased demand for vegetable oils due to a growing global population. To investigate the genetic basis of variation in seed oil content, we used 60K Brassica Infinium SNP array along with phenotype data of 203 Chinese semi-winter rapeseed accessions to perform a genome-wide analysis of haplotype blocks associated with the oil content. Nine haplotype regions harbouring lipid synthesis/transport-, carbohydrate metabolism- and photosynthesis-related genes were identified as significantly associated with the oil content and were mapped to chromosomes A02, A04, A05, A07, C03, C04, C05, C08 and C09, respectively. Regional association analysis of 50 re-sequenced Chinese semi-winter rapeseed accessions combined with transcriptome datasets from 13 accessions was further performed on these nine haplotype regions. This revealed natural variation in the BnTGD3-A02 and BnSSE1-A05 gene regions correlated with the phenotypic variation of the oil content within the A02 and A04 chromosome haplotype regions, respectively. Moreover, co-expression network analysis revealed that BnTGD3-A02 and BnSSE1-A05 were directly linked with fatty acid beta-oxidation-related gene BnKAT2-C04, thus forming a molecular network involved in the potential regulation of seed oil accumulation. The results of this study could be used to combine favourable haplotype alleles for further improvement of the seed oil content in rapeseed.

Analysis of copy number variation in dogs implicates genomic structural variation in the development of anterior cruciate ligament rupture.

Anterior cruciate ligament (ACL) rupture is an important condition of the human knee. Second ruptures are common and societal costs are substantial. Canine cranial cruciate ligament (CCL) rupture closely models the human disease. CCL rupture is common in the Labrador Retriever (5.79% prevalence), ~100-fold more prevalent than in humans. Labrador Retriever CCL rupture is a polygenic complex disease, based on genome-wide association study (GWAS) of single nucleotide polymorphism (SNP) markers. Dissection of genetic variation in complex traits can be enhanced by studying structural variation, including copy number variants (CNVs). Dogs are an ideal model for CNV research because of reduced genetic variability within breeds and extensive phenotypic diversity across breeds. We studied the genetic etiology of CCL rupture by association analysis of CNV regions (CNVRs) using 110 case and 164 control Labrador Retrievers. CNVs were called from SNPs using three different programs (PennCNV, CNVPartition, and QuantiSNP). After quality control, CNV calls were combined to create CNVRs using ParseCNV and an association analysis was performed. We found no strong effect CNVRs but found 46 small effect (max(T) permutation P<0.05) CCL rupture associated CNVRs in 22 autosomes; 25 were deletions and 21 were duplications. Of the 46 CCL rupture associated CNVRs, we identified 39 unique regions. Thirty four were identified by a single calling algorithm, 3 were identified by two calling algorithms, and 2 were identified by all three algorithms. For 42 of the associated CNVRs, frequency in the population was <10% while 4 occurred at a frequency in the population ranging from 10–25%. Average CNVR length was 198,872bp and CNVRs covered 0.11 to 0.15% of the genome. All CNVRs were associated with case status. CNVRs did not overlap previous canine CCL rupture risk loci identified by GWAS. Associated CNVRs contained 152 annotated genes; 12 CNVRs did not have genes mapped to CanFam3.1. Using pathway analysis, a cluster of 19 homeobox domain transcript regulator genes was associated with CCL rupture (P = 6.6E-13). This gene cluster influences cranial-caudal body pattern formation during embryonic limb development. Clustered genes were found in 3 CNVRs on chromosome 14 (HoxA), 28 (NKX6-2), and 36 (HoxD). When analysis was limited to deletion CNVRs, the association was strengthened (P = 8.7E-16). This study suggests a component of the polygenic risk of CCL rupture in Labrador Retrievers is associated with small effect CNVs and may include aspects of stifle morphology regulated by homeobox domain transcript regulator genes.

Genetic analysis of QTLs controlling allelopathic characteristics in sorghum.

Mature sorghum herbage is known to contain several water-soluble secondary metabolites (allelochemicals). In this study, we investigated quantitative trait loci (QTLs) associated with allelochemical characteristics in sorghum using linkage mapping and linkage disequilibrium (LD)-based association mapping. A sorghum diversity research set (SDRS) of 107 accessions was used in LD mapping whereas, F2:3 lines derived from a cross between Japanese and African landraces were used in linkage mapping. The QTLs were further confirmed by positional (targeted) association mapping with Q+K model. The inhibitory effect of water-soluble extracts (WSE) was tested on germination and root length of lettuce seedlings in four concentrations (25%, 50%, 75% and 100%). A Significant range of variations was observed among genotypes in both types of mapping populations (P < 0.05). A total of 181 simple sequence repeats (SSRs) derived from antecedently reported map have been used for genotyping of SDRS. A genetic linkage map of 151 sorghum SSR markers was also developed on 134 F2 individuals. The total map length was 1359.3 cM, with an average distance of 8.2 cM between adjacent markers. LD mapping identified three QTLs for inhibition effect on germination and seven QTLs for root length of lettuce seedlings. Whereas, a total of six QTLs for inhibition of germination and ten QTLs for root length were detected in linkage mapping approach. The percent phenotypic variation explained by individual QTL ranged from 6.9% to 27.3% in SDRS and 9.9% to 35.6% in F2:3 lines. Regional association analysis identified four QTLs, three of them are common in other methods too. No QTL was identified in the region where major gene for sorgoleone (SOR1) has been cloned previously on chromosome 5.

Characterization and fine mapping of qkrnw4, a major QTL controlling kernel row number in maize.

A major QTL controlling kernel row number, qkrnw4, was identified by combining linkage analysis and association mapping. Within qkrnw4, on the basis of its expression and bioinformatics analysis, Zm00001d052910 was supposed to be the candidate gene for kernel row number. Kernel row number (KRN) is an important yield-related trait that affects kernel number in maize. Understanding the genetic basis of KRN is important for increasing maize yields. In the present study, by the use of a near-isogenic line (NIL) that has a B73 background and that consistently displays a low KRN across environments, qkrnw4, a major quantitative trait locus (QTL) associated with KRN within a yield trait-related QTL hotspot in bin 4.08, was finely mapped to an ~ 33-kb interval. Regional association analysis of a nested association mapping population comprising 5000 recombinant inbred lines revealed Zm00001d052910, which encodes a protein with an unknown function, as the important candidate gene responsible for qkrnw4. Different expression levels of this candidate gene in immature ears were detected between the NIL and its recurrent parent. Moreover, the expression of several auxin-related genes was consistent with that of the candidate gene. Furthermore, the potential associations of this candidate gene with well-known inflorescence-related genes were discussed. The results of this study provide important information for the genetic elucidation of KRN variation in maize.

Integrated Genomic Strategies for Cereal Genetic Enhancement: Combining QTL and Association Mapping.

Identification of genetic basis for important agronomic traits is essential for marker-assisted crop improvement. Linkage mapping is one of the most popular approaches utilized for identification of major quantitative trait loci (QTLs) governing important agronomic traits in cereals. However, the identified QTLs usually span large genomic intervals and very few of these are subsequently fine mapped to single major effect gene. This hinders application of these QTLs in marker-aided breeding and crop genetic enhancement. On the contrary, association mapping, another popular approach for identification of QTLs, provides very high resolution but suffers from high level of false positives. Joint linkage-association analysis provides a way to combine advantages and avoid the pitfalls associated with both these methods. In this context, we recently developed MetaQTL specific regional association analysis and demonstrated its utility to rapidly narrow down previously identified QTL intervals to few candidate genes. Here, we describe the detailed step-by-step guide for performing MetaQTL specific regional association analysis to identify important genomic regions and underlying potential major effect genes governing traits of agronomic importance in cereals.

A generalized model for combining dependent SNP-level summary statistics and its extensions to statistics of other levels

Here I propose a fundamentally new flexible model to reveal the association between a trait and a set of genetic variants in a genomic region/gene. This model was developed for the situation when original individual-level phenotype and genotype data are not available, but the researcher possesses the results of statistical analyses conducted on these data (namely, SNP-level summary Z score statistics and SNP-by-SNP correlations). The new model was analytically derived from the classical multiple linear regression model applied for the region-based association analysis of individual-level phenotype and genotype data by using the linear compression of data, where the SNP-by-SNP correlations are among the explanatory variables, and the summary Z score statistics are categorized as the response variables. I analytically show that the regional association analysis methods developed within the framework of the classical multiple linear regression model with additive effects of genetic variants can be reformulated in terms of the new model without the loss of information. The results obtained from the regional association analysis utilizing the classical model and those derived using the proposed model are identical when SNP-by-SNP correlations and SNP-level statistics are estimated from the same genetic data.

Evaluation of WISP1 as a candidate gene for bone mineral density in the Old Order Amish

Wnt1-inducible signaling pathway protein-1 (WISP1) is a novel target of the Wnt pathway for modulating osteogenesis and improving bone strength. However, it is not clear if genetic variants in the WISP1 region are associated with bone mineral density (BMD) in human. The aim of this study is to investigate the role of genetic variation in WISP1 gene as a determinant of BMD in 1,510 Old Order Amish (OOA). We performed regional association analysis of 58 tag variants within 5 kb upstream and downstream to WISP1 with BMD and found 5 variants that were associated with BMD at multiple skeletal sites (P values from 2.89 × 10−6 to 1.62 × 10−2), with some significant associations even after adjustment for multiple comparisons. To replicate these results in an independent dataset, we performed a look-up of BMD associations with these variants in European ancestry subjects from the large GEFOS Consortium and observed the nominal associations of two of these variants with BMD (P values: 0.031 to 0.048). In conclusion, we have demonstrated that genetic variants surrounding WISP1 are associated with BMD at multiple skeletal sites in the OOA, thus influencing osteoporosis risk. These results support a role for the WISP1 gene on influencing variation in BMD.

Use of Genotypes of Common Variants for Genome-Wide Regional Association Analysis

Regional association analysis is a new statistical method which simultaneously considers all variants in a selected genome region. This method was created for the analysis of rare genetic variants, whose genotypes are determined by exome or genome sequencing. The gene is usually considered as a region. It was also proposed to use a regional analysis for testing of the association between a complex trait and a set of common variants genotyped by the panels developed for genome-wide association analysis. In this case, overlapping genome regions (sliding windows) are usually considered as a region. Since the size of such regions can be rather large, there is a risk of overestimation (inflation) of the test statistic and an increase in the type I error. In this work, the effect of the size of the region on the type I error was studied for traits with different heritability. The results of simulating experiments demonstrated that the physical size of the region but not the number of genetic variants in it is a limiting factor. The higher the trait heritability, the greater the type I error differs from the declared value. The analysis of a large number of real traits confirmed these conclusions. It is necessary to take into account these results during the interpretation of the results of regional association analysis conducted on large regions using common genetic variants.