SNP Array Research Articles

Prediction accuracy of genomic estimated breeding values for fruit traits in cultivated tomato (Solanum lycopersicum L.)

BackgroundGenomic selection (GS) is an efficient breeding strategy to improve quantitative traits. It is necessary to calculate genomic estimated breeding values (GEBVs) for GS. This study investigated the prediction accuracy of GEBVs for five fruit traits including fruit weight, fruit width, fruit height, pericarp thickness, and Brix. Two tomato germplasm collections (TGC1 and TGC2) were used as training populations, consisting of 162 and 191 accessions, respectively.ResultsLarge phenotypic variations for the fruit traits were found in these collections and the 51K Axiom™ SNP array generated confident 31,142 SNPs. Prediction accuracy was evaluated using different cross-validation methods, GS models, and marker sets in three training populations (TGC1, TGC2, and combined). For cross-validation, LOOCV was effective as k-fold across traits and training populations. The parametric (RR-BLUP, Bayes A, and Bayesian LASSO) and non-parametric (RKHS, SVM, and random forest) models showed different prediction accuracies (0.594–0.870) between traits and training populations. Of these, random forest was the best model for fruit weight (0.780–0.835), fruit width (0.791–0.865), and pericarp thickness (0.643–0.866). The effect of marker density was trait-dependent and reached a plateau for each trait with 768−12,288 SNPs. Two additional sets of 192 and 96 SNPs from GWAS revealed higher prediction accuracies for the fruit traits compared to the 31,142 SNPs and eight subsets.ConclusionOur study explored several factors to increase the prediction accuracy of GEBVs for fruit traits in tomato. The results can facilitate development of advanced GS strategies with cost-effective marker sets for improving fruit traits as well as other traits. Consequently, GS will be successfully applied to accelerate the tomato breeding process for developing elite cultivars.

Comparison of ddRADseq and EUChip60K SNP genotyping systems for population genetics and genomic selection in Eucalyptus dunnii (Maiden).

Eucalyptus dunnii is one of the most important Eucalyptus species for short-fiber pulp production in regions where other species of the genus are affected by poor soil and climatic conditions. In this context, E. dunnii holds promise as a resource to address and adapt to the challenges of climate change. Despite its rapid growth and favorable wood properties for solid wood products, the advancement of its improvement remains in its early stages. In this work, we evaluated the performance of two single nucleotide polymorphism, (SNP), genotyping methods for population genetics analysis and Genomic Selection in E. dunnii. Double digest restriction-site associated DNA sequencing (ddRADseq) was compared with the EUChip60K array in 308 individuals from a provenance-progeny trial. The compared SNP set included 8,011 and 19,008 informative SNPs distributed along the 11 chromosomes, respectively. Although the two datasets differed in the percentage of missing data, genome coverage, minor allele frequency and estimated genetic diversity parameters, they revealed a similar genetic structure, showing two subpopulations with little differentiation between them, and low linkage disequilibrium. GS analyses were performed for eleven traits using Genomic Best Linear Unbiased Prediction (GBLUP) and a conventional pedigree-based model (ABLUP). Regardless of the SNP dataset, the predictive ability (PA) of GBLUP was better than that of ABLUP for six traits (Cellulose content, Total and Ethanolic extractives, Total and Klason lignin content and Syringyl and Guaiacyl lignin monomer ratio). When contrasting the SNP datasets used to estimate PAs, the GBLUP-EUChip60K model gave higher and significant PA values for six traits, meanwhile, the values estimated using ddRADseq gave higher values for three other traits. The PAs correlated positively with narrow sense heritabilities, with the highest correlations shown by the ABLUP and GBLUP-EUChip60K. The two genotyping methods, ddRADseq and EUChip60K, are generally comparable for population genetics and genomic prediction, demonstrating the utility of the former when subjected to rigorous SNP filtering. The results of this study provide a basis for future whole-genome studies using ddRADseq in non-model forest species for which SNP arrays have not yet been developed.

Genetic Background of Blood β-Hydroxybutyrate Acid Concentrations in Early-Lactating Holstein Dairy Cows Based on Genome-Wide Association Analyses.

Ketosis is a common metabolic disorder in the early lactation of dairy cows. It is typically diagnosed by measuring the concentration of β-hydroxybutyrate (BHB) in the blood. This study aimed to estimate the genetic parameters of blood BHB and conducted a genome-wide association study (GWAS) based on the estimated breeding value. Phenotypic data were collected from December 2019 to August 2023, comprising blood BHB concentrations in 45,617 Holstein cows during the three weeks post-calving across seven dairy farms. Genotypic data were obtained using the Neogen Geneseek Genomic Profiler (GGP) Bovine 100 K SNP Chip and GGP Bovine SNP50 v3 (Illumina Inc., San Diego, CA, USA) for genotyping. The estimated heritability and repeatability values for blood BHB levels were 0.167 and 0.175, respectively. The GWAS result detected a total of ten genome-wide significant associations with blood BHB. Significant SNPs were distributed in Bos taurus autosomes (BTA) 2, 6, 9, 11, 13, and 23, with 48 annotated candidate genes. These potential genes included those associated with insulin regulation, such as INSIG2, and those linked to fatty acid metabolism, such as HADHB, HADHA, and PANK2. Enrichment analysis of the candidate genes for blood BHB revealed the molecular functions and biological processes involved in fatty acid and lipid metabolism in dairy cattle. The identification of novel genomic regions in this study contributes to the characterization of key genes and pathways that elucidate susceptibility to ketosis in dairy cattle.

Mapping of a Major-Effect Quantitative Trait Locus for Seed Dormancy in Wheat.

The excavation and utilization of dormancy loci in breeding are effective endeavors for enhancing the resistance to pre-harvest sprouting (PHS) of wheat varieties. CH1539 is a wheat breeding line with high-level seed dormancy. To clarify the dormant loci carried by CH1539 and obtain linked molecular markers, in this study, a recombinant inbred line (RIL) population derived from the cross of weak dormant SY95-71 and strong dormant CH1539 was genotyped using the Wheat17K single-nucleotide polymorphism (SNP) array, and a high-density genetic map covering 21 chromosomes and consisting of 2437 SNP markers was constructed. Then, the germination percentage (GP) and germination index (GI) of the seeds from each RIL were estimated. Two QTLs for GP on chromosomes 5A and 6B, and four QTLs for GI on chromosomes 5A, 6B, 6D and 7A were identified. Among them, the QTL on chromosomes 6B controlling both GP and GI, temporarily named QGp/Gi.sxau-6B, is a major QTL for seed dormancy with the maximum phenotypic variance explained of 17.66~34.11%. One PCR-based diagnostic marker Ger6B-3 for QGp/Gi.sxau-6B was developed, and the genetic effect of QGp/Gi.sxau-6B on the RIL population and a set of wheat germplasm comprising 97 accessions was successfully confirmed. QGp/Gi.sxau-6B located in the 28.7~30.9 Mbp physical position is different from all the known dormancy loci on chromosomes 6B, and within the interval, there are 30 high-confidence annotated genes. Our results revealed a novel QTL QGp/Gi.sxau-6B whose CH1539 allele had a strong and broad effect on seed dormancy, which will be useful in further PHS-resistant wheat breeding.

Genomic imbalance analysis provides new insight into prognostic factors in adult and pediatric T-ALL

AbstractGiven the poor outcome of refractory and relapsing T-cell acute lymphoblastic leukemia (T-ALL), identifying prognostic markers is still challenging. Using single nucleotide polymorphism (SNP) array analysis, we provide a comprehensive analysis of genomic imbalances in a cohort of 317 newly diagnosed patients with T-ALL including 135 children and 182 adults with respect to clinical and biological features and outcomes. SNP array results identified at least 1 somatic genomic imbalance in virtually all patients with T-ALL (∼96%). Del(9)(p21) (∼70%) and UPD(9)p21)/CDKN2A/B (∼28%) were the most frequent genomic imbalances. Unexpectedly del(13)(q14)/RB1/DLEU1 (∼14%) was the second most frequent copy number variant followed by del(6)(q15)/CASP8AP2 (∼11%), del(1)(p33)/SIL-TAL1 (∼11%), del(12)(p13)ETV6/CDKN1B (∼9%), del(18)(p11)/PTPN2 (∼9%), del(1)(p36)/RPL22 (∼9%), and del(17)(q11)/NF1/SUZ12 (∼8%). SNP array also revealed distinct profiles of genomic imbalances according to age, immunophenotype, and oncogenetic subgroups. In particular, adult patients with T-ALL demonstrated a significantly higher incidence of del(1)(p36)/RPL22, and del(13)(q14)/RB1/DLEU1, and lower incidence of del(9)(p21) and UPD(9p21)/CDKN2A/B. We determined a threshold of 15 genomic imbalances to stratify patients into high- and low-risk groups of relapse. Survival analysis also revealed the poor outcome, despite the low number of affected cases, conferred by the presence of chromothripsis (n = 6, ∼2%), del(16)(p13)/CREBBP (n = 15, ∼5%) as well as the newly-identified recurrent gain at 6q27 involving MLLT4 (n = 10, ∼3%). Genomic complexity, del(16)(p13)/CREBBP and gain at 6q27 involving MLLT4, maintained their significance in multivariate analysis for survival outcome. Our study thus demonstrated that whole genome analysis of imbalances provides new insights to refine risk stratification in T-ALL. This trial was registered at www.ClinicalTrials.gov as #NCT00222027 and #NCT00327678, and as #FRALLE 2000T trial.

Abstract 2418: Copy number variation status of DNA in extracellular vesicles as novel biomarkers of high-grade serous ovarian carcinoma

Abstract Objective: Ovarian cancer is a gynecologic malignancy with a dismal prognosis due to the lack of accurate methods for early diagnosis methods and effective therapies. High-grade serous ovarian carcinoma (HGSOC) is the most common subtype and copy number variations (CNVs) are the dominant genomic events in HGSOC. Extracellular vesicles (EVs) circulate in body fluids and carry pathological genomic information positively. In this study, we evaluated the significance of EV-DNA as novel biomarkers for HGSOC patients. Methods: A total of 124 samples from HGSOC patients and cell lines were analyzed. EVs were isolated using the ultracentrifuge method. Comprehensive CNV statuses were analyzed by whole genome sequencing (WGS) and SNP array. In reference to the Ovarian Cancer Moon Shot database, 30 dominant CNVs in HGSOC were selected as dominant targets for analysis by droplet digital PCR (ddPCR). For predicting the response to PARP inhibitors, HGSOC patients who were treated with olaparib were collected, and DNA was extracted from FFPE tissue at the time of surgery. Results: NTA assays and cryo-electron microscopic analyses showed that the EVs were successfully isolated from all samples. Both WGS and SNP arrays detected correlating CNVs in cell-DNA and EV-DNA for cell lines, and in tissue-DNA and EV-DNA in ascites for patients. The CNV status was also accurately measured by ddPCR. Copy numbers of RAD51, BRCA1, AKT2, CCNE1, and MSH6 were significantly higher in malignant tissue than in benign tissue (p<0.0001, p<0.0001, p=0.0012, p=0.002. p=0.0328, respectively), and were detectable in EV-DNA from ascites. Additionally, the amount of DNA in malignant ascites was significantly higher than in benign ascites (p=0.016), and increased DNA in ascites itself suggested the presence of malignancy. Furthermore, EV-DNA more accurately reflected the CNV status of tumor DNA than cell-free DNA in ascites. Regarding the prediction of PARP inhibitor response, the CNV status in EV-DNA from patients who were treated with olaparib, a PARP inhibitor, demonstrated a marked difference between responders and non-responders. The equation calculated based on the combination of six genes (RB1, GABRA6, CTNNB1, MYC, RAD51, BARD1) could predict the response to olaparib (AUC: 1.0). The selected genes were validated in vitro using EV-DNA, and responders could be identified using the prediction equation calculated from CNV status of the selected genes in EV-DNA from ascites. Conclusion: CNV status of EV-DNA was correctly evaluated and can serve as novel diagnostic and prognostic biomarkers for HGSOC. Citation Format: Ryosuke Uekusa, Akira Yokoi, Kosuke Yoshida, Juntaro Matsuazki, Yusuke Yamamoto, Hiroaki Kajiyama. Copy number variation status of DNA in extracellular vesicles as novel biomarkers of high-grade serous ovarian carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2418.

Aneuploidy is frequent in heterozygous diploid and triploid hydatidiform moles

Hydatidiform moles are abnormal conceptuses. Many hydatidiform moles are diploid androgenetic, and of these, most are homozygous in all loci. Additionally, most hydatidiform moles are euploid. Using Single Nucleotide Polymorphism (SNP) array analysis, in two studies a higher frequency of aneuploidy was observed in diploid androgenetic heterozygous conceptuses, than in their homozygous counterparts. In the Danish Mole Project, we analyze conceptuses suspected to be hydatidiform moles due to the clinical presentation, using karyotyping and Short Tandem Repeat (STR) analysis. Among 278 diploid androgenetic conceptuses, 226 were homozygous in all loci and 52 (18.7%) were heterozygous in several loci. Among 142 triploid diandric conceptuses, 141 were heterozygous for paternally inherited alleles in several loci. Here we show that the frequencies of aneuploidy in diploid androgenetic heterozygous and triploid diandric heterozygous conceptuses were significantly higher than the frequency of aneuploidy in diploid androgenetic homozygous conceptuses. In diploid androgenetic and triploid diandric conceptuses that are heterozygous for paternally inherited alleles, the two paternally inherited sets of genomes originate in two spermatozoa. Each spermatozoon provides one pair of centrioles to the zygote. The presence of two pairs of centrioles may cause an increased risk of aneuploidy.

Abstract 4849: Mosaic chromosomal alterations in a prospective cohort of Mexican Americans for cancer risk and genetic insights

Abstract Introduction: In this study, we aim to explore mosaic chromosomal alterations (mCA) and their implications in cancer risk among Mexican Americans (MA) - an expanding yet historically underrepresented ethnic minority in the U.S. In addition, we propose to develop a novel method that identifies high mutant cell fraction (MCF) copy-neutral Loss of heterozygosity (cn-LOH). At sufficiently high MCF, these will look like runs of homozygosity (ROH) and may be missed by current mCA detection techniques that rely on identified germline heterozygote genotypes. Our preliminary findings revealed frequent and widespread homozygosity across the genome, predominantly in short regions (<10 Mb), although some exceeded 100 Mb. Our objective is to advance mCA detection techniques, differentiating cn-LOH from ROH, to deepen our understanding of mCA. Methods: We analyzed SNP array data from blood and saliva samples of 1657 individuals, focusing on cancer and chronic disease risk ages, from the Mano a Mano Mexican American Cohort Study. We applied hapLOH and MoChA, both haplotype-based methods, to detect mCA. To identify high-MCF cn-LOH, we first scanned for observed ROH using PLINK. Separately, we develop a statistical framework through simulations to differentiate high-MCF cn-LOH from ROH. We considered multiple methods; initially, we built a statistical framework using a hypothesis-testing approach (H0: ROH; H1: cn-LOH), where we compared the “B allele” frequency information within observed ROH. To split this information and obtain our groups, we used population genetic principles. Secondly, we classified our events, calculating the likelihood ratio of our statistical hypotheses. Finally, we explored a haplotype-based imputation approach that leverages flanking diploid region information. Results: We identified numerous mCA, predominantly in individuals without cancer. Simulations showed effective classification in larger homozygosity regions (>10 Mb), guiding our methodological focus on detecting shorter high-MCF regions. Not surprisingly, extremely high MCFs (0.99-1) presented challenges in accurate identification. Conclusion and Future Directions: To improve our mCA results description, we will thoroughly characterize and study their association with cancer phenotypes and environmental exposures. We are in the process of genotyping the entire cohort, which consists of over 25,000 participants. To date, our cohort includes 909 cancer cases, of which 262 are hematological malignancies. We sought to design a unique method that differentiates high-MCF cn-LOH from observed ROH, improving current mCA discovery. Our focus is on small regions as they provide limited information to infer event types. Our next step is to characterize and validate our results, especially in pathologically normal samples, as a way of identifying potential biomarkers of interest. Citation Format: Jessica Valdebenito, Justin Wong, Dahwei Chang, Henry Gomez, Kevin T Nead, Yasminka Jakubek, Paul Scheet. Mosaic chromosomal alterations in a prospective cohort of Mexican Americans for cancer risk and genetic insights [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4849.

Abstract 6618: Pleiotropic GATA3 locus is associated with multiple childhood cancers: harnessing the existing data from the St. Jude Lifetime Cohort and the Childhood Cancer Survivor Study for genetic etiology research

Abstract Background: A genetic variant (rs3824662) at GATA3 was previously associated with risk of Philadelphia chromosome-like acute lymphoblastic leukemia (Ph-like ALL) and relapse. Our recently published childhood Hodgkin lymphoma (HL) study identified a genome-wide significant association for another genetic variant (rs3781093) in high linkage disequilibrium (D’=1.0, R2=0.91) with rs3824662. We hypothesize that GATA3 is a pleiotropic locus associated with multiple childhood cancers. Methods: The study was performed by combining 3 cohorts of childhood cancer survivors: the St Jude Lifetime Cohort Study (SJLIFE), the original and expansion cohorts of the Childhood Cancer Survivor Study (CCSS). The CCSS original cohort had SNP array genotyping and imputation, and the SJLIFE and CCSS expansion cohort underwent whole-genome sequencing. Associations between the variants mapped to GATA3 and risks of different cancer types were analyzed (a specific cancer type was selected as the case group and all other unselected cancer types served as controls, then repeated for 13 cancer types). Summary statistics were subsequently analyzed with the ASSET (Association analysis for SubSETs) method which is powerful for pooling association signals across multiple cancer types when true effects may exist only in a subset and be in opposite directions across cancer types. Results: Genotype data were available for 11623 childhood cancer survivors (5325 from the CCSS original cohort, 2428 from the CCSS expansion cohort, and 3870 from the SJLIFE, all European ancestry) were initially considered. After excluding individuals with dual enrollment or as outliers in the principal components analysis (n=667), a total of 10956 individuals remained for genetic association analysis. We identified a bi-directional association for a subset of childhood cancers with rs3781093 (2-sided P value of 6.22 × 10−19): the same effect allele (C) was associated with increased risk of ALL or soft tissue sarcoma [STS] (OR=1.21; 95% CI=1.13-1.29; P=7.4 × 10−9), and was associated with decreased risk of HL (OR=0.66; 95% CI=0.59-074; P=1.80 × 10−12). The frequencies of the effect allele (C) for rs3781093 in ALL cases (17.9%), STS cases (17.8%) and HL cases (12.5%) relative to non-cancer community controls in the SJLIFE (15.6%) and non-cancer gnomAD samples (14.9%) corroborate this finding. In our combined dataset, there were 1380 Hodgkin lymphoma cases, 2961 ALL cases and 692 STS cases. Conclusion: We discovered a novel variant in the GATA3 locus exhibiting pleiotropy with both tumor-promoting and protective effects, suggesting a shared mechanistic pathway involving GATA3 may underlie the carcinogenesis for ALL, STS and HL. Conducting systematic searches for childhood cancer pleiotropy represents an important research direction. Citation Format: Cheng Chen, Xijun Zhang, Qian Dong, Heather L. Mulder, John Easton, Xiaotu Ma, Jinghui Zhang, Jun Yang, Kim E. Nichols, Gregory T. Armstong, Kirsten K. Ness, Melissa M. Hudson, Hui Wang, Nilanjan Chatterjee, Cindy Im, Zhaoming Wang. Pleiotropic GATA3 locus is associated with multiple childhood cancers: harnessing the existing data from the St. Jude Lifetime Cohort and the Childhood Cancer Survivor Study for genetic etiology research [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6618.

Exploring the Drought Tolerant Quantitative Trait Loci in Spring Wheat.

Drought-induced stress poses a significant challenge to wheat throughout its growth, underscoring the importance of identifying drought-stable quantitative trait loci (QTLs) for enhancing grain yield. Here, we evaluated 18 yield-related agronomic and physiological traits, along with their drought tolerance indices, in a recombinant inbred line population derived from the XC7 × XC21 cross. These evaluations were conducted under both non-stress and drought-stress conditions. Drought stress significantly reduced grain weight per spike and grain yield per plot. Genotyping the recombinant inbred line population using the wheat 90K single nucleotide polymorphism array resulted in the identification of 131 QTLs associated with the 18 traits. Drought stress also exerted negative impacts on grain formation and filling, directly leading to reductions in grain weight per spike and grain yield per plot. Among the identified QTLs, 43 were specifically associated with drought tolerance across the 18 traits, with 6 showing direct linkages to drought tolerance in wheat. These results provide valuable insights into the genetic mechanisms governing wheat growth and development, as well as the traits contributing to the drought tolerance index. Moreover, they serve as a theoretical foundation for the development of new wheat cultivars having exceptional drought tolerance and high yield potentials under both drought-prone and drought-free conditions.

Unlocking the genetic diversity and population structure of the newly introduced two-row spring European HerItage Barley collecTion (ExHIBiT).

In the last century, breeding programs have traditionally favoured yield-related traits, grown under high-input conditions, resulting in a loss of genetic diversity and an increased susceptibility to stresses in crops. Thus, exploiting understudied genetic resources, that potentially harbour tolerance genes, is vital for sustainable agriculture. Northern European barley germplasm has been relatively understudied despite its key role within the malting industry. The European Heritage Barley collection (ExHIBiT) was assembled to explore the genetic diversity in European barley focusing on Northern European accessions and further address environmental pressures. ExHIBiT consists of 363 spring-barley accessions, focusing on two-row type. The collection consists of landraces (~14%), old cultivars (~18%), elite cultivars (~67%) and accessions with unknown breeding history (~1%), with 70% of the collection from Northern Europe. The population structure of the ExHIBiT collection was subdivided into three main clusters primarily based on the accession's year of release using 26,585 informative SNPs based on 50k iSelect single nucleotide polymorphism (SNP) array data. Power analysis established a representative core collection of 230 genotypically and phenotypically diverse accessions. The effectiveness of this core collection for conducting statistical and association analysis was explored by undertaking genome-wide association studies (GWAS) using 24,876 SNPs for nine phenotypic traits, four of which were associated with SNPs. Genomic regions overlapping with previously characterised flowering genes (HvZTLb) were identified, demonstrating the utility of the ExHIBiT core collection for locating genetic regions that determine important traits. Overall, the ExHIBiT core collection represents the high level of untapped diversity within Northern European barley, providing a powerful resource for researchers and breeders to address future climate scenarios.

The genetic landscape of autism spectrum disorder in the Middle Eastern population.

Introduction: Autism spectrum disorder (ASD) is characterized by aberrations in social interaction and communication associated with repetitive behaviors and interests, with strong clinical heterogeneity. Genetic factors play an important role in ASD, but about 75% of ASD cases have an undetermined genetic risk. Methods: We extensively investigated an ASD cohort made of 102 families from the Middle Eastern population of Qatar. First, we investigated the copy number variations (CNV) contribution using genome-wide SNP arrays. Next, we employed Next Generation Sequencing (NGS) to identify de novo or inherited variants contributing to the ASD etiology and its associated comorbid conditions in families with complete trios (affected child and the parents). Results: Our analysis revealed 16 CNV regions located in genomic regions implicated in ASD. The analysis of the 88 ASD cases identified 41 genes in 39 ASD subjects with de novo (n = 24) or inherited variants (n = 22). We identified three novel de novo variants in new candidate genes for ASD (DTX4, ARMC6, and B3GNT3). Also, we have identified 15 de novo variants in genes that were previously implicated in ASD or related neurodevelopmental disorders (PHF21A, WASF1, TCF20, DEAF1, MED13, CREBBP, KDM6B, SMURF1, ADNP, CACNA1G, MYT1L, KIF13B, GRIA2, CHM, and KCNK9). Additionally, we defined eight novel recessive variants (RYR2, DNAH3, TSPYL2, UPF3B KDM5C, LYST, and WNK3), four of which were X-linked. Conclusion: Despite the ASD multifactorial etiology that hinders ASD genetic risk discovery, the number of identified novel or known putative ASD genetic variants was appreciable. Nevertheless, this study represents the first comprehensive characterization of ASD genetic risk in Qatar's Middle Eastern population.

Abstract P525: Polygenic Risk Scores for Morning Chronotype and Longer Sleep Duration Are Associated With Weight and Glycemic Outcomes in the Multi-Ethnic Study of Atherosclerosis (MESA)

Introduction: Circadian rhythms regulate key physiological processes, including sleep-wake. Alterations in the circadian rhythm have been associated with greater risk of metabolic diseases. Genome-wide association studies (GWAS) have revealed genes variants associated with sleep phenotypes. Hypothesis: Polygenic risk scores (PRS) for significant SNPs reported in GWAS of chronotype (C), sleep duration (SD), and short sleep (SS, <7/h) are associated with metabolic parameters. Methods: We carried out a longitudinal analysis in 6,814 adults (aged 45-84 y at baseline) from the Multi-Ethnic Study of Atherosclerosis (MESA). Glucose, insulin, insulin resistance (HOMA-IR), body mass index (BMI) and waist circumference (WC) were assessed at baseline (2000-2002) and 16-18 y follow-up (Exam 6, N=3,303). DNA was extracted from whole blood, and genotyping data were obtained by the Affymetrix 6.0 SNP array. PRS for the following phenotypes were constructed as weight sum of genoma-wide significant alleles: 1) chronotype [PRS-C]; 2) continuous SD [PRS-SD]; and 3) SS duration [PRS-SS]. Multivariable linear regression models adjusted by sociodemographic, obesity, smoking, Mediterranean diet, physical activity and antidiabetic drugs were performed to assess associations between PRS and study outcomes (fasting glucose and insulin, HOMA-IR, hemoglobin A1c, BMI, and WC) cross-sectionally and longitudinally. Results: At baseline, none of the PRS were associated with glucose, insulin or HOMA-IR (p>0.05). A significant positive association was detected for PRS-C with BMI and WC: greater genetically determined morningness was associated with lower BMI (β=-20.0±3.0; p<0.001) and smaller WC (β=-44.1±8.0; p<0.001). Similar results were observed with PRS-SD (BMI: β=-0.1±0.0; p=0.005; WC: β=-0.3±0.1; p=0.008) and PRS-SS (BMI: β=9.3±2.8; p<0.001; WC: β=19.8±7.4; p=0.007). In longitudinal analyses, we observed prospective associations between PRS-C with BMI (β=-43.5±12.2; p<0.001), WC (β=-116.0.1±29.1; p<0.001), and glucose (β=-204.7±90.0; p=0.024). PRS-SS was longitudinally associated with HOMA-IR (β=214.1±88.0; p=0.017) and a trend was observed for hemoglobin A1c (β=-6.6±3.4; p=0.053), but not with anthropometrics parameters. No associations were noted for PRS-SD with obesity and glycemic outcomes in longitudinal analyses. Conclusion: In the MESA population, PRS for chronotype, sleep duration, and short sleep are associated with anthropometric but not with glycemic measures in cross-sectional analyses. However, PRS for chronotype and short sleep was associated with anthropometric and glycemic parameters in longitudinal analyses, suggesting the importance of genetic predisposition for morningness and adequate sleep duration for metabolic health.

Selection Signatures Reveal Candidate Genes for the Cornish Rex Breed-Specific Phenotype.

Many coat color, behavioral and morphological traits are specific and fixed across cat breeds, with several variants influencing these traits being common among different breeds. In the domestic cat, rexoid mutations have been documented in several breeds. In the Cornish Rex, four bp deletion in the LPAR6 gene has been found to cause a frame shift and a premature stop codon. In addition to the rexoid coat, Cornish Rex cats also have a characteristic head, ear shape and body type. Analysis of the selection signatures in the Cornish Rex genome revealed several regions that are under selective pressure. One of these is located in CFA B4, in the region where the ALX1 gene is located. The ALX1 gene in Burmese cats disrupts the cranial morphogenesis and causes brachycephaly in the heterozygous state. In our study, we confirmed the presence of a deletion in LPAR6 in 20 Cornish Rex and in four F1 hybrids between Cornish Rex and domestic cat. However, we did not confirm the presence of the deletion in ALX1 in Cornish Rex cats. Genome-wide selection signature analysis was performed using ROH islands and integrated haplotype score (iHS) statistics based on publicly available SNP array data of 11 Cornish Rex cats. The selection signatures were detected on chromosomes A1, A3, C2, B1, B4 and D1.

Genetic architecture and accuracy of predicted genomic breeding values for sea lice resistance in the St John River aquaculture strain of North American Atlantic salmon

Sea lice infections cause significant economic losses in Atlantic salmon (Salmo salar) farming. The objectives of this study were to (1) estimate the heritability of resistance to sea lice in the USDA's breeding program for North American (N.A.) Atlantic salmon; (2) elucidate the genetic architecture of sea lice resistance; and (3) assess the accuracy and bias of predicted breeding values for sea lice resistance using cross-validation analysis (CVA) and progeny testing of selection candidates (PTSC). Fish from year-class (YC) 2014 n=967 and YC 2018 n=941 were challenged with sea lice (Lepeophtheirus salmonis) and genotyped with the new USDA 50K SNP chip developed for the N.A. Atlantic salmon. Heritability estimates for sea lice count in the two year-classes were between 0.07 and 0.10. GWAS with weighted ssGBLUP (wssGBLUP) highlighted the polygenic architecture of the trait. With CVA, the genomic prediction methods x¯=0.54 had higher accuracy of predictions than the pedigree-based method x¯=0.43; and ssGBLUP had the highest accuracy of BV predictions (0.50–0.62) among the genomic prediction methods. With PTSC approach, the pedigree-based method PBLUP had higher estimated accuracy than the genomic prediction methods (0.48 vs. 0.30). Bias of BV predictions with CVA x¯=0.87range0.57−1.06 was lower than with PTSC x¯=1.22range0.44−2.35. Our retrospective assessment of the accuracy of indirect sib-based selection to improve sea lice resistance in the St John River aquaculture stock that is commonly used for farming of Atlantic salmon in North America demonstrated that substantial genetic gains can be obtained. Due to the polygenic architecture of the trait, the estimated accuracy of the ssGBLUP model was better than the wssGBLUP model. In our assessment, a larger training sample size will be needed to achieve optimal results with the whole genome-enabled selective breeding method due to the polygenic architecture of sea lice resistance coupled with low heritability of the trait.

Identifying QTL for grain protein content independent from grain yield-related traits in durum wheat

Grain protein content (GPC) is a crucial quality trait determining the nutritional, rheological, and end-use properties characteristics of wheat. Breeding programs for GPC were hindered by complex genetic control, the strong influence of environmental factors, and the negative correlation between GPC and grain yield. To identify stable quantitative trait loci (QTL) associated with increased GPC without decreasing grain yield, a recombinant inbred lines population of durum wheat was genotyped with a 25K SNP array and evaluated for GPC and yield-related traits in four field trials. Six QTL for GPC were identified on chromosomes 1B, 2B (two loci), 4B, 5A, and 6A, consistently expressed across environments, four of which had antagonistic effects on grain yield per spike (GYS). Two QTL (QGpc.mgb-5A and QGpc/TKW.mgb-2B.2) on 2B and 5A chromosomes were independent of GYS variations and could be used in marker-assisted selection (MAS) for GPC improvement. Identifying and utilizing beneficial QTL/genes for wheat improvement requires careful consideration of the inverse relationship between GPC and yield-related traits, and phenotypic data collected across multiple environments. MAS or genomic selection techniques can effectively target favorable alleles for GPC enhancement while minimizing the impact on grain yield.

Investigating the Association of Polygenic Risk Scores With Thyroid Cancer Susceptibility in a Han Chinese Population.

Thyroid cancer, the leading endocrine tumor with a rising global incidence, especially in women, is influenced by both genetic and environmental factors. This study examines the relationship between polygenic risk scores (PRS) and thyroid cancer susceptibility in the Han Chinese population, as well as the impact of genetic variants on clinical outcomes. Analyzing data from 57 257 participants in the Taiwan Precision Medicine Initiative, the study employed the Affymetrix Genome-Wide TWB 2.0 SNP Array for genotyping. PRS were calculated using single nucleotide polymorphisms (SNPs) from prior genome-wide association studies, specifically PGS000087 and PGS000797, and correlated with clinical parameters like age, sex, comorbidities, and treatment methods. Among 4063 participants with thyroid tumors (839 malignant, 3224 benign), higher PRS quartiles correlated significantly with increased thyroid cancer incidence. The highest quartile showed a 1.15-fold (PGS000797) and 1.14-fold (PGS000087) greater risk than the lowest quartile. Key findings included an association between higher PRS quartiles and younger onset age, along with a notable link to chronic kidney disease and thyroid hormone levels in specific SNPs. The study demonstrates PRS's utility in predicting thyroid cancer risk in the Han Chinese population, with higher PRS associated with increased risk and distinct clinical features. While this study focuses on the Han Chinese population, we recognize the importance of comparing PRS performance across different ancestries to fully understand ethnic genetic diversity in cancer risk assessment. Future studies should aim to include such comparative analysis.

Identification of QTLs associated with seed protein concentration in two diverse recombinant inbred line populations of pea.

Improving the seed protein concentration (SPC) of pea (Pisum sativum L.) has turned into an important breeding objective because of the consumer demand for plant-based protein and demand from protein fractionation industries. To support the marker-assisted selection (MAS) of SPC towards accelerated breeding of improved cultivars, we have explored two diverse recombinant inbred line (RIL) populations to identify the quantitative trait loci (QTLs) associated with SPC. The two RIL populations, MP 1918 × P0540-91 (PR-30) and Ballet × Cameor (PR-31), were derived from crosses between moderate SPC × high SPC accessions. A total of 166 and 159 RILs of PR-30 and PR-31, respectively, were genotyped using an Axiom® 90K SNP array and 13.2K SNP arrays, respectively. The RILs were phenotyped in replicated trials in two and three locations of Saskatchewan, Canada in 2020 and 2021, respectively, for agronomic assessment and SPC. Using composite interval mapping, we identified three QTLs associated with SPC in PR-30 and five QTLs in PR-31, with the LOD value ranging from 3.0 to 11.0. A majority of these QTLs were unique to these populations compared to the previously known QTLs for SPC. The QTL SPC-Ps-5.1 overlapped with the earlier reported SPC associated QTL PC-QTL-3. Three QTLs, SPC-Ps-4.2, SPC-Ps-5.1, and SPC-Ps-7.2 with LOD scores of 7.2, 7.9, and 11.3, and which explained 14.5%, 11.6%, and 11.3% of the phenotypic variance, respectively, can be used for marker-assisted breeding to increase SPC in peas. Eight QTLs associated with the grain yield were identified with LOD scores ranging from 3.1 to 8.2. Two sets of QTLs, SPC-Ps-2.1 and GY-Ps-2.1, and SPC-Ps-5.1 and GY-Ps-5.3, shared the QTL/peak regions. Each set of QTLs contributed to either SPC or grain yield depending on which parent the QTL region is derived from, thus confirming that breeding for SPC should take into consideration the effects on grain yield.

Genetic diversity of variants involved in drug response among Tunisian and Italian populations toward personalized medicine

Adverse drug reactions (ADR) represent a significant contributor to morbidity and mortality, imposing a substantial financial burden. Genetic ancestry plays a crucial role in drug response. The aim of this study is to characterize the genetic variability of selected pharmacogenes involved with ADR in Tunisians and Italians, with a comparative analysis against global populations. A cohort of 135 healthy Tunisians and 737 Italians were genotyped using a SNP array. Variants located in 25 Very Important Pharmacogenes implicated in ADR were extracted from the genotyping data. Distribution analysis of common variants in Tunisian and Italian populations in comparison to 24 publicly available worldwide populations was performed using PLINK and R software. Results from Principle Component and ADMIXTURE analyses showed a high genetic similarity among Mediterranean populations, distinguishing them from Sub-Saharan African and Asian populations. The Fst comparative analysis identified 27 variants exhibiting significant differentiation between the studied populations. Among these variants, four SNPs rs622342, rs3846662, rs7294, rs5215 located in SLC22A1, HMGCR, VKORC1 and KCNJ11 genes respectively, are reported to be associated with ethnic variability in drug responses. In conclusion, correlating the frequencies of genotype risk variants with their associated ADRs would enhance drug outcomes and the implementation of personalized medicine in the studied populations.

Microduplication and Microdeletion Syndromes Diagnosed Prenatally Using Single Nucleotide Polymorphism Array.

We present a series of microdeletion and microduplication syndromes (MMSs) observed in our clinical practice over a three-year period from 2020 to 2023. Microdeletion and microduplication syndromes, characterized by chromosomal deletions or duplications of less than five megabases, pose challenges in terms of diagnosis, especially prenatal and clinical management. Clinically, MMSs encompass a broad spectrum of manifestations, ranging from intellectual disability and developmental delays to congenital anomalies, facial dysmorphisms, and neurobehavioral abnormalities. Notable examples include well-characterized syndromes such as DiGeorge syndrome (22q11.2 deletion), Prader-Willi syndrome (15q11-q13 deletion), and Williams syndrome (7q11 deletion). Our study focuses on the genetic foundations and prenatal ultrasound findings of these syndromes, with an emphasis on cases associated with intellectual disability. Using SNP array technology, we delve into the evolving landscape of diagnostic methods, providing a nuanced understanding of copy number variations (CNVs) and their implications. Prenatal diagnosis allows for the early detection of MMSs, enabling parents and healthcare providers to make informed decisions about the pregnancy and plan for appropriate medical care and interventions. Beyond theoretical considerations, our article bridges the gap between research and practical application by offering insights derived from clinical cases. Through the presentation of specific cases, we aim to contribute valuable data to the broader discourse on MMSs, fostering knowledge exchange and enhancing the medical community's awareness of these complex genetic conditions.