SNP-based Genome-wide Association Study Research Articles

Genomic wide association study and selective sweep analysis identify genes associated with improved yield under drought in Turkish winter wheat germplasm

A panel comprising of 84 Turkish winter wheat landraces (LR) and 73 modern varieties (MV) was analyzed with genome wide association study (GWAS) to identify genes/genomic regions associated with increased yield under favorable and drought conditions. In addition, selective sweep analysis was conducted to detect signatures of selection in the winter wheat genome driving the differentiation between LR and MV, to gather an understanding of genomic regions linked to adaptation and yield improvement. The panel was genotyped with 25 K wheat SNP array and phenotyped for agronomic traits for two growing seasons (2018 and 2019) in Konya, Turkey. Year 2018 was treated as drought environment due to very low precipitation prior to heading whereas year 2019 was considered as a favorable season. GWAS conducted with SNPs and haplotype blocks using mixed linear model identified 18 genomic regions in the vicinities of known genes i.e., TaERF3-3A, TaERF3-3B, DEP1-5A, FRIZZY PANICLE-2D, TaSnRK23-1A, TaAGL6-A, TaARF12-2A, TaARF12-2B, WAPO1, TaSPL16-7D, TaTGW6-A1, KAT-2B, TaOGT1, TaSPL21-6B, TaSBEIb, trs1/WFZP-A, TaCwi-A1-2A and TaPIN1-7A associated with grain yield (GY) and yield related traits. Haplotype-based GWAS identified five haplotype blocks (H1A-42, H2A-71, H4A-48, H7B-123 and H7B-124), with the favorable haplotypes showing a yield increase of > 700 kg/ha in the drought season. SNP-based GWAS, detected only one larger effect genomic region on chromosome 7B, in common with haplotype-based GWAS. On an average, the percentage variation (PV) explained by haplotypes was 8.0% higher than PV explained by SNPs for all the investigated traits. Selective sweep analysis detected 39 signatures of selection between LR and MV of which 15 were within proximity of known functional genes controlling flowering (PRR-A1, PPR-D1, TaHd1-6B), GY and GY components (TaSus2-2B, TaGS2-B1, AG1-1A/WAG1-1A, DUO-A1, DUO-B1, AG2-3A/WAG2-3A, TaLAX1, TaSnRK210-4A, FBP, TaLAX1, TaPIL1 and AP3-1-7A/WPA3-7A) and 10 regions underlying various transcription factors and regulatory genes. The study outcomes contribute to utilization of LR in breeding winter wheat.

Five improved sesame reference genomes and genome resequencing unveil the contribution of structural variants to genetic diversity and yield-related traits variation.

Five improved sesame reference genomes and genome resequencing unveil the contribution of structural variants to genetic diversity and yield-related traits variation.

Structural variation (SV)-based pan-genome and GWAS reveal the impacts of SVs on the speciation and diversification of allotetraploid cottons

Structural variations (SVs) have long been described as being involved in the origin, adaption, and domestication of species. However, the underlying genetic and genomic mechanisms are poorly understood. Here, we report a high-quality genome assembly of Gossypium barbadense acc. Tanguis, a landrace that is closely related to formation of extra-long-staple (ELS) cultivated cotton. An SV-based pan-genome (Pan-SV) was then constructed using a total of 182 593 non-redundant SVs, including 2236 inversions, 97 398 insertions, and 82 959 deletions from 11 assembled genomes of allopolyploid cotton. The utility of this Pan-SV was then demonstrated through population structure analysis and genome-wide association studies (GWASs). Using segregation mapping populations produced through crossing ELS cotton and the landrace along with an SV-based GWAS, certain SVs responsible for speciation, domestication, and improvement in tetraploid cottons were identified. Importantly, some of the SVs presently identified as associated with the yield and fiber quality improvement had not been identified in previous SNP-based GWAS. In particular, a 9-bp insertion or deletion was found to associate with elimination of the interspecific reproductive isolation between Gossypium hirsutum and G. barbadense. Collectively, this study provides new insights into genome-wide, gene-scale SVs linked to important agronomic traits in a major crop species and highlights the importance of SVs during the speciation, domestication, and improvement of cultivated crop species.

A pangenome analysis pipeline provides insights into functional gene identification in rice

BackgroundA pangenome aims to capture the complete genetic diversity within a species and reduce bias in genetic analysis inherent in using a single reference genome. However, the current linear format of most plant pangenomes limits the presentation of position information for novel sequences. Graph pangenomes have been developed to overcome this limitation. However, bioinformatics analysis tools for graph format genomes are lacking.ResultsTo overcome this problem, we develop a novel strategy for pangenome construction and a downstream pangenome analysis pipeline (PSVCP) that captures genetic variants’ position information while maintaining a linearized layout. Using PSVCP, we construct a high-quality rice pangenome using 12 representative rice genomes and analyze an international rice panel with 413 diverse accessions using the pangenome as the reference. We show that PSVCP successfully identifies causal structural variations for rice grain weight and plant height. Our results provide insights into rice population structure and genomic diversity. We characterize a new locus (qPH8-1) associated with plant height on chromosome 8 undetected by the SNP-based genome-wide association study (GWAS).ConclusionsOur results demonstrate that the pangenome constructed by our pipeline combined with a presence and absence variation-based GWAS can provide additional power for genomic and genetic analysis. The pangenome constructed in this study and the associated genome sequence and genetic variants data provide valuable genomic resources for rice genomics research and improvement in future.

Sweet Taste Preference: Relationships with Other Tastes, Liking for Sugary Foods and Exploratory Genome-Wide Association Analysis in Subjects with Metabolic Syndrome.

Taste perception and its association with nutrition and related diseases (type 2 diabetes, obesity, metabolic syndrome, cardiovascular, etc.) are emerging fields of biomedicine. There is currently great interest in investigating the environmental and genetic factors that influence sweet taste and sugary food preferences for personalized nutrition. Our aims were: (1) to carry out an integrated analysis of the influence of sweet taste preference (both in isolation and in the context of other tastes) on the preference for sugary foods and its modulation by type 2 diabetes status; (2) as well as to explore new genetic factors associated with sweet taste preference. We studied 425 elderly white European subjects with metabolic syndrome and analyzed taste preference, taste perception, sugary-foods liking, biochemical and genetic markers. We found that type 2 diabetic subjects (38%) have a small, but statistically higher preference for sweet taste (p = 0.021) than non-diabetic subjects. No statistically significant differences (p > 0.05) in preferences for the other tastes (bitter, salty, sour or umami) were detected. For taste perception, type 2 diabetic subjects have a slightly lower perception of all tastes (p = 0.026 for the combined “total taste score”), bitter taste being statistically lower (p = 0.023). We also carried out a principal component analysis (PCA), to identify latent variables related to preferences for the five tastes. We identified two factors with eigenvalues >1. Factor 2 was the one with the highest correlation with sweet taste preference. Sweet taste preference was strongly associated with a liking for sugary foods. In the exploratory SNP-based genome-wide association study (GWAS), we identified some SNPs associated with sweet taste preference, both at the suggestive and at the genome-wide level, especially a lead SNP in the PTPRN2 (Protein Tyrosine Phosphatase Receptor Type N2) gene, whose minor allele was associated with a lower sweet taste preference. The PTPRN2 gene was also a top-ranked gene obtained in the gene-based exploratory GWAS analysis. In conclusion, sweet taste preference was strongly associated with sugary food liking in this population. Our exploratory GWAS identified an interesting candidate gene related with sweet taste preference, but more studies in other populations are required for personalized nutrition.

Genome-wide analysis of copy number variants and normal facial variation in a large cohort of Bantu Africans.

Similarity in facial characteristics between relatives suggests a strong genetic component underlies facial variation. While there have been numerous studies of the genetics of facial abnormalities and, more recently, single nucleotide polymorphism (SNP) genome-wide association studies (GWASs) of normal facial variation, little is known about the role of genetic structural variation in determining facial shape. In a sample of Bantu African children, we found that only 9% of common copy number variants (CNVs) and 10-kb CNV analysis windows are well tagged by SNPs (r2 ≥ 0.8), indicating that associations with our internally called CNVs were not captured by previous SNP-based GWASs. Here, we present a GWAS and gene set analysis of the relationship between normal facial variation and CNVs in a sample of Bantu African children. We report the top five regions, which had p values ≤ 9.35 × 10−6 and find nominal evidence of independent CNV association (p < 0.05) in three regions previously identified in SNP-based GWASs. The CNV region with strongest association (p = 1.16 × 10−6, 55 losses and seven gains) contains NFATC1, which has been linked to facial morphogenesis and Cherubism, a syndrome involving abnormal lower facial development. Genomic loss in the region is associated with smaller average lower facial depth. Importantly, new loci identified here were not identified in a SNP-based GWAS, suggesting that CNVs are likely involved in determining facial shape variation. Given the plethora of SNP-based GWASs, calling CNVs from existing data may be a relatively inexpensive way to aid in the study of complex traits.

Admixture mapping identifies novel regions influencing Alzheimer disease in African Americans.

African Americans (AA) are substantially underrepresented in Alzheimer's disease (AD) genetic studies, yet their admixed genetic ancestry (African and European) provides a unique opportunity to identify novel genetic factors associated with AD related to genetic ancestry. Admixture mapping (AM) provides a more powerful approach than SNP-based genome-wide association studies (GWAS) in admixed populations in part due to the lower multiple testing burden. In this study we used AM to identify regions associated with AD in AA individuals. Our analyses included 10,271 individuals from 17 AD Sequencing Project and AD Genetics Consortium cohorts. We estimated global ancestry (GA) using the GENESIS software. To infer local ancestry (LA), the target AA dataset was combined with appropriate reference-population samples from HGDP reference panel, and LA was estimated using SHAPEIT followed by RFMix. Then, we performed AM using the GENESIS software separately on each cohort. We meta-analyzed the AM results with the random effect approach (RE2). We calculated the significance threshold using STEAM software. Finally, we performed logistic regression of genotype on affection status for variants across the prioritized regions from AM for fine-mapping. The regression model included LA and genotype as main effects and term for their interaction, along with GA, sex and age as covariates, and used permutation-based testing approach for multiple test correction (N=10,000). AM identified two genome-wide significant loci on chromosomes 17p13.2 (pv=2.2 x10-5 ) and 18q21.33 (pv=1.22x10-5 ). 17p13.2 region was identified as a genome-wide significant in two previous studies in non-Hispanic White population. To fine map this region we conducted ancestry-aware regression analysis. LA x genotype interaction model found the MINK1 gene (rs72835013) on the 17p13.2 region significantly associated with AD (pv = 1x10-4 ). Our results confirmed an AD associated region on the chromosome 17p13.2 and showed that the 17p13.2 region increases AD risk in AA individuals with the European LA. This region includes genes previously indicated in AD such as SCIMP through association studies and the MINK1 and SLC25A11 genes through brain expression studies.

A SNP-based GWAS and functional haplotype-based GWAS of flag leaf-related traits and their influence on the yield of bread wheat (Triticum aestivum L.).

The genetic architecture of five flag leaf morphology traits was dissected by the functional haplotype-based GWAS and a standard SNP-based GWAS in a diverse population consisting of 197 varieties. Flag leaf morphology (FLM) is a critical factor affecting plant architecture and grain yield in wheat. The genetic architecture of FLM traits has been extensively studied with QTL mapping in bi-parental populations, while few studies exploited genome-wide association studies (GWAS) in diverse populations. In this study, a panel of 197 elite and historical varieties from China was evaluated for five FLM traits including the length (FLL), width (FLW), ratio (FLR), area (FLA) and angle (FLANG) as well as yield in nine environments. Based on the phenotypic correlation between yield and FLL (-0.43), FLA (- 0.32) and FLW (0.11), an empirical FLM index combining the three FLM traits proved to be a good predictor for yield. Two GWAS approaches were applied to dissect the genetic architecture of five FLM traits with a Wheat660K SNP array. The functional haplotype-based GWAS revealed 6, 5 and 7 QTL for FLANG, FLL and FLR, respectively, whereas two QTL for FLW and one for FLR were identified by the standard SNP-based GWAS. Due to co-localization, there were 18 independent QTL and 10 of them were close to known ones. One co-localized QTL on chromosome 5A was associated with FLL, FLANG and FLR. Moreover, both GWAS approaches identified a novel QTL for FLR on chromosome 6B which was not reported in previous studies. This study provides new insights into the relationship between FLM and yield and broadens our understanding of the genetic architecture of FLM traits in wheat.

Genome-wide association studies for production, respiratory disease, and immune-related traits in Landrace pigs

Identification of a quantitative trait locus (QTL) related to a chronic respiratory disease such as Mycoplasmal pneumonia of swine (MPS) and immune-related traits is important for the genetic improvement of disease resistance in pigs. The objective of this study was to detect a novel QTL for a total of 22 production, respiratory disease, and immune-related traits in Landrace pigs. A total of 874 Landrace purebred pigs, which were selected based on MPS resistance, were genotyped using the Illumina PorcineSNP60 BeadChip. We performed single nucleotide polymorphism (SNP)-based and haplotype-based genome-wide association studies (GWAS) to detect a novel QTL and to evaluate the possibility of a pleiotropic QTL for these traits. SNP-based GWAS detected a total of six significant regions in backfat thickness, ratio of granular leucocytes to lymphatic cells, plasma concentration of cortisol at different ages, and complement alternative pathway activity in serum. The significant region detected by haplotype-based GWAS was overlapped across the region detected by SNP-based GWAS. Most of these detected QTL regions were novel regions with some candidate genes located in them. With regard to a pleiotropic QTL among traits, only three of these detected QTL regions overlapped among traits, and many detected regions independently affected the traits.

Gene-based association analysis identified a novel gene associated with systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is a complex autoimmune disease with strong genetic predisposition. Genome-wide association studies (GWAS) of SLE have identified more than 50 robust susceptibility loci. However, traditional individual SNP-based GWAS have made it difficult to identify variants with small effects. Moreover, variants revealed by GWAS only explain a limited disease heritability, suggesting that many susceptibility genes remain uncovered. We first curated the published SLE GWAS data from 1047 SLE patients and 1205 healthy controls of Chinese ancestry and performed a gene-based association study. Then quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was conducted to verify novel genes identified above. Gene-based association study identified 10 SLE-associated genes, nine of which were reported by previous GWAS, the other one, ILRUN, is a newly identified gene and was further validated by qRT-PCR. Gene expression analysis of Gene Expression Omnibus (GEO) datasets also showed that the expression of ILRUN in patients with SLE was lower than that in normal subjects. In this study, gene-based association study and qRT-PCR identified that ILRUN is a novel susceptibility gene of SLE. ILRUN may regulate inflammation and antiviral response through its effect on the transcription of type I interferons )I-IFN, and participate in the pathogenesis of SLE.

Haplotype- and SNP-Based GWAS for Growth and Wood Quality Traits in Eucalyptus cladocalyx Trees under Arid Conditions.

The agricultural and forestry productivity of Mediterranean ecosystems is strongly threatened by the adverse effects of climate change, including an increase in severe droughts and changes in rainfall distribution. In the present study, we performed a genome-wide association study (GWAS) to identify single-nucleotide polymorphisms (SNPs) and haplotype blocks associated with the growth and wood quality of Eucalyptus cladocalyx, a tree species suitable for low-rainfall sites. The study was conducted in a progeny-provenance trial established in an arid site with Mediterranean patterns located in the southern Atacama Desert, Chile. A total of 87 SNPs and 3 haplotype blocks were significantly associated with the 6 traits under study (tree height, diameter at breast height, slenderness coefficient, first bifurcation height, stem straightness, and pilodyn penetration). In addition, 11 loci were identified as pleiotropic through Bayesian multivariate regression and were mainly associated with wood hardness, height, and diameter. In general, the GWAS revealed associations with genes related to primary metabolism and biosynthesis of cell wall components. Additionally, associations coinciding with stress response genes, such as GEM-related 5 and prohibitin-3, were detected. The findings of this study provide valuable information regarding genetic control of morphological traits related to adaptation to arid environments.

Haplotype-based genome-wide association increases the predictability of leaf rust (Puccinia triticina) resistance in wheat.

Resistance breeding is crucial for sustainable control of wheat leaf rust and single nucleotide polymorphism (SNP)-based genome-wide association studies (GWAS) are widely used to dissect leaf rust resistance. Unfortunately, GWAS based on SNPs often explained only a small proportion of the genetic variation. We compared SNP-based GWAS with a method based on functional haplotypes (FH) considering epistasis in a comprehensive hybrid wheat mapping population composed of 133 parents plus their 1574 hybrids and characterized with 626 245 high-quality SNPs. In total, 2408 and 1 139 828 significant associations were detected in the mapping population by using SNP-based and FH-based GWAS, respectively. These associations mapped to 25 and 69 candidate regions, correspondingly. SNP-based GWAS highlighted two already-known resistance genes, Lr22a and Lr34-B, while FH-based GWAS detected associations not only on these genes but also on two additional genes, Lr10 and Lr1. As revealed by a second hybrid wheat population for independent validation, the use of detected associations from SNP-based and FH-based GWAS reached predictabilities of 11.72% and 22.86%, respectively. Therefore, FH-based GWAS is not only more powerful for detecting associations, but also improves the accuracy of marker-assisted selection compared with the SNP-based approach.

A SNP-Based Genome-Wide Association Study to Mine Genetic Loci Associated to Salinity Tolerance in Mungbean (Vigna radiata L.).

Mungbean (Vigna radiata (L.) R. Wilzeck var. radiata) is a protein-rich short-duration legume that fits well as a rotation crop into major cereal production systems of East and South-East Asia. Salinity stress in arid areas affects mungbean, being more of a glycophyte than cereals. A significant portion of the global arable land is either salt or sodium affected. Thus, studies to understand and improve salt-stress tolerance are imminent. Here, we conducted a genome-wide association study (GWAS) to mine genomic loci underlying salt-stress tolerance during seed germination of mungbean. The World Vegetable Center (WorldVeg) mungbean minicore collection representing the diversity of mungbean germplasm was utilized as the study panel and variation for salt stress tolerance was found in this germplasm collection. The germplasm panel was classed into two agro-climatic groups and showed significant differences in their germination abilities under salt stress. A total of 5288 SNP markers obtained through genotyping-by-sequencing (GBS) were used to mine alleles associated with salt stress tolerance. Associated SNPs were identified on chromosomes 7 and 9. The associated region at chromosome 7 (position 2,696,072 to 2,809,200 bp) contains the gene Vradi07g01630, which was annotated as the ammonium transport protein (AMT). The associated region in chromosome 9 (position 19,390,227 bp to 20,321,817 bp) contained the genes Vradi09g09510 and Vradi09g09600, annotated as OsGrx_S16-glutaredoxin subgroup II and dnaJ domain proteins respectively. These proteins were reported to have functions related to salt-stress tolerance.

Abstract LB-174: Genome-wide association meta-analysis identifies novel GP2 gene risk variants for pancreatic cancer in the Japanese population

Abstract Pancreatic cancer is one of the most challenging malignancies because of its dismal prognosis, largely unknown etiology, and absence of early detection method. Here we report the results of a meta-analysis of three genome-wide association studies (GWAS) involving 2039 pancreatic cancer cases and 32592 control subjects, which represent the largest sample size in the Japanese population. To complement the SNP-based GWAS, we performed a gene-based GWAS using MAGMA. Given the pleiotropic effects observed for the top variants, we performed a Mendelian randomization (MR) analysis to address the possible causal relationship between type-2 diabetes (T2D) and pancreatic cancer risk, using 82 T2D-related SNPs and 25 hemoglobin A1c (HbA1c)-related SNPs as instrumental variables. We identified 3 (13q12.2, 13q22.1, and 16p12.3) genome-wide significant loci (P&amp;lt;5.0×10-8), as well as 4 loci with suggestive evidence of association (P&amp;lt;1.0×10-6) for pancreatic cancer. Of the identified risk loci, 16p12.3 is novel; the lead SNP maps to rs78193826 (OR=1.46, 95%CI=1.29-1.66, P=4.28×10-9), an Asian-specific, non-synonymous variant of glycoprotein 2 (GP2) predicted to be highly deleterious. Additionally, gene-based GWAS identified a novel gene, KRT8, which is linked to exocrine pancreatic and liver diseases. The identified variants in the GP2 gene exhibited pleiotropic effects on multiple traits, including type 2 diabetes, Hemoglobin A1c (HbA1c) levels, and pancreatic cancer. MR analysis suggested that genetically increased HbA1c levels may be causally associated with increased pancreatic cancer risk. Further fine mapping and functional characterization are required to elucidate the effects of common GP2 gene variants on pancreatic cancer susceptibility. Moreover, our findings highlight genetic susceptibility factors shared between T2D and pancreatic cancer. Citation Format: Yingsong Lin, Masahiro Nakatochi, Hidemi Ito, Yoichiro Kamatani, Hiromi Sakamoto, Hiroshi Ishii, Naoki Sasahira, Makoto Ueno, Naoto Egawa, Mitsuru Mori, Haruhisa Nakao, Yasushi Adachi, Kenji Wakai, Shoichiro Tsugane, Masayuki Yamamoto, Atsushi Shimizu, Takashi Kadowaki, Teruhiko Yoshida, Fumihiko Matsuda, Michiaki Kubo, Shogo Kikuchi, Keitaro Matsuo. Genome-wide association meta-analysis identifies novel GP2 gene risk variants for pancreatic cancer in the Japanese population [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr LB-174.

Shared genes between Alzheimer's disease and ischemic stroke.

SummaryAimsAlthough converging evidence from experimental and epidemiological studies indicates Alzheimer's disease (AD) and ischemic stroke (IS) are related, the genetic basis underlying their links is less well characterized. Traditional SNP‐based genome‐wide association studies (GWAS) have failed to uncover shared susceptibility variants of AD and IS. Therefore, this study was designed to investigate whether pleiotropic genes existed between AD and IS to account for their phenotypic association, although this was not reported in previous studies.MethodsTaking advantage of large‐scale GWAS summary statistics of AD (17,008 AD cases and 37,154 controls) and IS (10,307 IS cases and 19,326 controls), we performed gene‐based analysis implemented in VEGAS2 and Fisher's meta‐analysis of the set of overlapped genes of nominal significance in both diseases. Subsequently, gene expression analysis in AD‐ or IS‐associated expression datasets was conducted to explore the transcriptional alterations of pleiotropic genes identified.Results16 AD‐IS pleiotropic genes surpassed the cutoff for Bonferroni‐corrected significance. Notably, MS4A4A and TREM2, two established AD‐susceptibility genes showed remarkable alterations in the spleens and brains afflicted by IS, respectively. Among the prioritized genes identified by virtue of literature‐based knowledge, most are immune‐relevant genes (EPHA1, MS4A4A, UBE2L3 and TREM2), implicating crucial roles of the immune system in the pathogenesis of AD and IS.ConclusionsThe observation that AD and IS had shared disease‐associated genes offered mechanistic insights into their common pathogenesis, predominantly involving the immune system. More importantly, our findings have important implications for future research directions, which are encouraged to verify the involvement of these candidates in AD and IS and interpret the exact molecular mechanisms of action.

Association of Copy Number Variation at Intron 3 of HMGA2 With Navel Length in Bos indicus.

Navel injuries caused by friction against the pasture can promote infection, reproductive problems and costly treatments in beef cattle raised in extensive systems. A haplotype-based genome-wide association study (GWAS) was performed for visual scores of navel length at yearling in Nellore cattle (Bos indicus) using data from 2,016 animals and 503,088 single nucleotide polymorphism (SNP) markers. The strongest signal (p = 1.01 × 10-9) was found on chromosome 5 spanning positions 47.9–48.2 Mbp. This region contains introns 3 and 4 and exons 4 and 5 of the high mobility group AT-hook 2 gene (HMGA2). Further inspection of the region with whole genome sequence data of 21 Nellore bulls revealed correlations between counts of the significant haplotype and copy number gains of a ∼6.2 kbp segment of intron 3 of HMGA2. Analysis of genome sequences from five African B. indicus and four European Bos taurus breeds revealed that the copy number variant (CNV) is indicine-specific. This intronic CNV was then validated through quantitative polymerase chain reaction (qPCR) using Angus animals as copy neutral controls. Importantly, the CNV was not detectable by means of conventional SNP-based GWAS or SNP probe intensity analyses. Given that HMGA2 affects the expression of the insulin-like growth factor 2 gene (IGF2) together with the pleomorphic adenoma gene 1 (PLAG1), and that the latter has been repeatedly shown to be associated with quantitative traits of economic importance in cattle, these findings highlight the emerging role of variants impacting the insulin-like growth factor pathway to cattle breeding.

Discovery of QTL Alleles for Grain Shape in the Japan-MAGIC Rice Population Using Haplotype Information.

A majority of traits are determined by multiple quantitative trait loci (QTL) that can have pleiotropic effects. A multi-parent advanced generation inter-cross (MAGIC) population is well suited for genetically analyzing the effects of multiple QTL on traits of interest because it contains a higher number of QTL alleles than a biparental population. We previously produced the JAPAN-MAGIC (JAM) population, derived from eight rice (Oryza sativa L.) cultivars with high yield and biomass in Japan, and developed the method of genome-wide association study (GWAS) using haplotype information on the JAM lines. This method was effective for identifying major genes such as Waxy for eating quality and Sd1 for culm length. Here, we show that haplotype-based GWAS is also effective for the evaluation of multiple QTL with small effects on rice grain shape in the JAM lines. Although both the haplotype- and SNP-based GWAS identified multiple QTL for grain length and width, the sum of the estimated trait values of each allele for the QTL detected by haplotype-based GWAS had higher correlation with observed values than those detected by SNP-based GWAS, indicating high-accuracy QTL detection in the haplotype-based GWAS. Furthermore, the study revealed pleiotropic effects of some QTL regions in regulation of grain shape, suggesting that the haplotype-based GWAS using the JAM lines is an effective means to evaluate the main and side effects of haplotypes at each QTL. Information on the pleiotropic effects of haplotypes on various traits will be useful for designing ideal lines in a breeding program.

Gene-based GWAS analysis for consecutive studies of GEFOS.

Single-nucleotide polymorphism (SNP)-based genome-wide association studies (GWASs) have already identified about 100 loci associated with bone mineral density (BMD), but these loci only explain a small proportion of heritability to osteoporosis risk. In the present study, we performed a gene-based analysis of the largest GWASs in the bone field to identify additional BMD-associated genes. BMD-associated genes were identified by combining the summary statistic P values of SNPs across individual genes in the two consecutive meta-analyses of GWASs from the Genetic Factors for Osteoporosis (GEFOS) studies. The potential functionality of these genes to bone was partially assessed by differential gene expression analysis. Additionally, the consistency of the identification of potential bone mineral density (BMD)-associated variants were evaluated by estimating the correlation of the P values of the same single-nucleotide polymorphisms (SNPs)/genes between the two consecutive Genetic Factors for Osteoporosis Studies (GEFOS) with largely overlapping samples. Compared to the SNP-based analysis, the gene-based strategy identified additional BMD-associated genes with genome-wide significance and increased their mutual replication between the two GEFOS datasets. Among these BMD-associated genes, three novel genes (UBTF, AAAS, and C11orf58) were partially validated at the gene expression level. The correlation analysis presented a moderately high between-study consistency of potential BMD-associated variants. Gene-based analysis as a supplementary strategy to SNP-based genome-wide association studies, when applied here, is shown that it helped identify some novel BMD-associated genes. In addition to its empirically increased statistical power, gene-based analysis also provides a higher testing stability for identification of BMD genes.

Genomic Analyses of Visual Cognition: Perceptual Rivalry and Top-Down Control.

Visual cognition in humans has traditionally been studied with cognitive behavioral methods and brain imaging, but much less with genetic methods. Perceptual rivalry, an important phenomenon in visual cognition, is the spontaneous perceptual alternation that occurs between two distinct interpretations of a physically constant visual stimulus (e.g., binocular rivalry stimuli) or a perceptually ambiguous stimulus (e.g., the Necker cube). The switching rate varies dramatically across individuals and can be voluntarily modulated by observers. Here, we adopted a genomic approach to systematically investigate the genetics underlying binocular rivalry, Necker cube rivalry and voluntary modulation of Necker cube rivalry in young Chinese adults (Homo sapiens, 81% female, 20 ± 1 years old) at multiple levels, including common single nucleotide polymorphism (SNP)-based heritability estimation, SNP-based genome-wide association study (GWAS), gene-based analysis, and pathway analysis. We performed a pilot GWAS in 2441 individuals and replicated it in an independent cohort of 943 individuals. Common SNP-based heritability was estimated to be 25% for spontaneous perceptual rivalry. SNPs rs184765639 and rs75595941 were associated with voluntary modulation, and imaging data suggested genotypic difference of rs184765639 in the surface area of the left caudal-middle frontal cortex. Additionally, converging evidence from multilevel analyses associated genes such as PRMT1 with perceptual switching rate, and MIR1178 with voluntary modulation strength. In summary, this study discovered specific genetic contributions to perceptual rivalry and its voluntary modulation in human beings. These findings may promote our understanding of psychiatric disorders, as perceptual rivalry is a potential psychiatric biomarker.SIGNIFICANCE STATEMENT Perceptual rivalry is an important visual phenomenon in which our perception of a physically constant visual input spontaneously switches between two different states. There are individual variations in perceptual switching rate and voluntary modulation strength. Our genomic analyses reveal several loci associated with these two kinds of variation. Because perceptual rivalry is thought to be relevant to and potentially an endophenotype for psychiatric disorders, these results may help understand not only visual cognition, but also psychiatric disorders.

A combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence

Intelligence, or general cognitive function, is phenotypically and genetically correlated with many traits, including a wide range of physical, and mental health variables. Education is strongly genetically correlated with intelligence (rg = 0.70). We used these findings as foundations for our use of a novel approach—multi-trait analysis of genome-wide association studies (MTAG; Turley et al. 2017)—to combine two large genome-wide association studies (GWASs) of education and intelligence, increasing statistical power and resulting in the largest GWAS of intelligence yet reported. Our study had four goals: first, to facilitate the discovery of new genetic loci associated with intelligence; second, to add to our understanding of the biology of intelligence differences; third, to examine whether combining genetically correlated traits in this way produces results consistent with the primary phenotype of intelligence; and, finally, to test how well this new meta-analytic data sample on intelligence predicts phenotypic intelligence in an independent sample. By combining datasets using MTAG, our functional sample size increased from 199,242 participants to 248,482. We found 187 independent loci associated with intelligence, implicating 538 genes, using both SNP-based and gene-based GWAS. We found evidence that neurogenesis and myelination—as well as genes expressed in the synapse, and those involved in the regulation of the nervous system—may explain some of the biological differences in intelligence. The results of our combined analysis demonstrated the same pattern of genetic correlations as those from previous GWASs of intelligence, providing support for the meta-analysis of these genetically-related phenotypes.