Haplotype-based Genome-wide Association Study Research Articles

Genome-wide association study of Verticillium longisporum resistance in Brassica genotypes.

Verticillium stripe, caused by Verticillium longisporum, presents an emerging threat to Canadian canola (Brassica napus). Initially detected in Manitoba in 2014, the presence of this pathogen has since been confirmed across western Canada. Infections by V. longisporum can result in yield losses of up to 50%, which is a cause for concern given the susceptibility of most commercial Canadian canola cultivars. The objective of this study was to screen a collection of 211 Brassica genotypes for their reactions to V. longisporum, and to use genome-wide association study (GWAS) to identify single nucleotide polymorphism (SNP) markers for resistance. The plant material consisted of 110 rutabaga (B. napus ssp. napobrassica), 35 canola, 40 Brassica rapa, and 15 Brassica oleracea accessions or cultivars, alongside 11 hosts of the European Clubroot Differential (ECD) set. These materials were screened for resistance under greenhouse conditions and were genotyped using a 19K Brassica SNP array. Three general linear models (GLM), four mixed linear models (MLM), and three GWAS methods were employed to evaluate the markers. Eleven non-commercial Brassica accessions and 9 out of 35 commercial canola cultivars displayed a low normalized area under the disease progress curve (AUDPCnorm.). The non-commercial accessions could prove valuable as potential sources of resistance against V. longisporum. Forty-five SNP markers were identified to be significantly associated with V. longisporum resistance using single-SNP based GWAS analysis. In comparison, haplotype-based GWAS analyses identified 10 to 25 haplotype blocks to be significantly associated with V. longisporum resistance. Between 20% and 56% of QTLs identified by the more conventional single-SNP based GWAS analysis were also detected by the haplotype-based GWAS analysis. The overlapping genomic regions identified by the two GWAS methods present promising hotspots for marker-assisted selection in the future development of Verticillium stripe-resistant canola.

Haplotype-based association mapping of genomic regions associated with Zymoseptoria tritici resistance using 217 diverse wheat genotypes

BackgroundSeptoria tritici blotch (STB) is considered to be one of the most destructive foliar wheat diseases and is caused by Zymoseptoria tritici. The yield losses are severe and in Northwestern Europe can reach up to 50%. The efficacy of fungicides is diminishing due to changes in the genetic structure of the pathogen. Therefore, resistance breeding is the most effective strategy of disease management. Recently, genome-wide association studies (GWAS) have become more popular due to their robustness in dissecting complex traits, including STB resistance in wheat. This was made possible by the use of large mapping populations and new sequencing technologies. High-resolution mapping benefits from historical recombination and greater allele numbers in GWAS.ResultsIn our study, 217 wheat genotypes of diverse origin were phenotyped against five Z. tritici isolates (IPO323, IPO88004, IPO92004, IPO86036 and St1-03) and genotyped on the DArTseq platform. In polytunnel tests two disease parameters were evaluated: the percentage of leaf area covered by necrotic lesions (NEC) and the percentage of leaf area covered by lesions bearing pycnidia (PYC). The disease escape parameters heading date (Hd) and plant height (Ht) were also measured. Pearson’s correlation showed a positive effect between disease parameters, providing additional information. The Structure analysis indicated four subpopulations which included from 28 (subpopulation 2) to 79 genotypes (subpopulation 3). All of the subpopulations showed a relatively high degree of admixture, which ranged from 60% of genotypes with less than 80% of proportions of the genome attributed to assigned subpopulation for group 2 to 85% for group 4. Haplotype-based GWAS analysis allowed us to identify 27 haploblocks (HBs) significantly associated with analysed traits with a p-value above the genome-wide significance threshold (5%, which was –log10(p) > 3.64) and spread across the wheat genome. The explained phenotypic variation of identified significant HBs ranged from 0.2% to 21.5%. The results of the analysis showed that four haplotypes (HTs) associated with disease parameters cause a reduction in the level of leaf coverage by necrosis and pycnidia, namely: Chr3A_HB98_HT2, Chr5B_HB47_HT1, Chr7B_HB36_HT1 and Chr5D_HB10_HT3.ConclusionsGWAS analysis enabled us to identify four significant chromosomal regions associated with a reduction in STB disease parameters. The list of valuable HBs and wheat varieties possessing them provides promising material for further molecular analysis of resistance loci and development of breeding programmes.

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.

Haplotype-Based Genome-Wide Association Analysis Using Exome Capture Assay and Digital Phenotyping Identifies Genetic Loci Underlying Salt Tolerance Mechanisms in Wheat.

Soil salinity can impose substantial stress on plant growth and cause significant yield losses. Crop varieties tolerant to salinity stress are needed to sustain yields in saline soils. This requires effective genotyping and phenotyping of germplasm pools to identify novel genes and QTL conferring salt tolerance that can be utilised in crop breeding schemes. We investigated a globally diverse collection of 580 wheat accessions for their growth response to salinity using automated digital phenotyping performed under controlled environmental conditions. The results show that digitally collected plant traits, including digital shoot growth rate and digital senescence rate, can be used as proxy traits for selecting salinity-tolerant accessions. A haplotype-based genome-wide association study was conducted using 58,502 linkage disequilibrium-based haplotype blocks derived from 883,300 genome-wide SNPs and identified 95 QTL for salinity tolerance component traits, of which 54 were novel and 41 overlapped with previously reported QTL. Gene ontology analysis identified a suite of candidate genes for salinity tolerance, some of which are already known to play a role in stress tolerance in other plant species. This study identified wheat accessions that utilise different tolerance mechanisms and which can be used in future studies to investigate the genetic and genic basis of salinity tolerance. Our results suggest salinity tolerance has not arisen from or been bred into accessions from specific regions or groups. Rather, they suggest salinity tolerance is widespread, with small-effect genetic variants contributing to different levels of tolerance in diverse, locally adapted germplasm.

A genome-wide association study of freezing tolerance in red clover (Trifolium pratense L.) germplasm of European origin.

Improvement of persistency is an important breeding goal in red clover (Trifolium pratense L.). In areas with cold winters, lack of persistency is often due to poor winter survival, of which low freezing tolerance (FT) is an important component. We conducted a genome wide association study (GWAS) to identify loci associated with freezing tolerance in a collection of 393 red clover accessions, mostly of European origin, and performed analyses of linkage disequilibrium and inbreeding. Accessions were genotyped as pools of individuals using genotyping-by-sequencing (pool-GBS), generating both single nucleotide polymorphism (SNP) and haplotype allele frequency data at accession level. Linkage disequilibrium was determined as a squared partial correlation between the allele frequencies of pairs of SNPs and found to decay at extremely short distances (< 1 kb). The level of inbreeding, inferred from the diagonal elements of a genomic relationship matrix, varied considerably between different groups of accessions, with the strongest inbreeding found among ecotypes from Iberia and Great Britain, and the least found among landraces. Considerable variation in FT was found, with LT50-values (temperature at which 50% of the plants are killed) ranging from -6.0°C to -11.5°C. SNP and haplotype-based GWAS identified eight and six loci significantly associated with FT (of which only one was shared), explaining 30% and 26% of the phenotypic variation, respectively. Ten of the loci were found within or at a short distance (<0.5 kb) from genes possibly involved in mechanisms affecting FT. These include a caffeoyl shikimate esterase, an inositol transporter, and other genes involved in signaling, transport, lignin synthesis and amino acid or carbohydrate metabolism. This study paves the way for a better understanding of the genetic control of FT and for the development of molecular tools for the improvement of this trait in red clover through genomics assisted breeding.

Evaluation of Fusarium Head Blight Resistance Effects by Haplotype-Based Genome-Wide Association Study in Winter Wheat Lines Derived by Marker Backcrossing Approach.

Fusarium head blight (FHB) of wheat caused by Fusarium species is a destructive disease, causing grain yield and quality losses. Developing FHB-resistant cultivars is crucial to minimize the extent of the disease. The first objective of this study was incorporation of Fhb1 from a resistant donor into five Polish wheat breeding lines with good agronomical traits and different origins. We also performed a haplotype-based GWAS to identify chromosome regions in derived wheat families associated with Fusarium head blight resistance. As a result of marker-assisted backcrossing (MABC), five wheat combinations were obtained. Fungal inoculation and disease assessment were conducted for two years, 2019 and 2020. In 2019 the average phenotypic response of type II resistance was 2.2, whereas in 2020 it was 2.1. A haploblock-based GWAS performed on 10 phenotypic traits (related to type of resistance, year of experiment and FHB index) revealed nine marker-trait associations (MTA), among which six belong to chromosome 2D, two to 3B and one to 7D. Phenotypic variation (R2) explained by the identified haplotypes in haploblocks ranged from 6% to 49%. Additionally, an association weight matrix (AWM) was created, giving the partial correlation-information theory (PCIT) pipeline of 171 edges and 19 nodes. The resultant data and high level of explained phenotypic variance of MTA create the opportunity for data utilization in MAS.

Failing the four-gamete test enables exact phasing: the Corners’ Algorithm

BackgroundFailing the four-gamete test for two polymorphic DNA markers is an indication that two or three rather than four haplotypes segregate in the population. The objective of this paper is to show that when just three haplotypes are segregating, all three haplotypes can be fully and unambiguously phase-resolved.Theory and methodsThe Corners’ Algorithm tests the four corners in a 3 × 3 table of two-locus genotypes. If one of the four corners is filled with zeroes, then the missing haplotype is identified and the phases of all three haplotypes can be unambiguously resolved for all individuals. Three applications of this method are proposed when the four-gamete test fails: (1) direct estimation of linkage disequilibrium (LD), (2) haplotype-based genome-wide association studies (GWAS) of three haplotypes (single-marker GWAS tests for two out of three haplotypes only), and (3) haplotyping of chromosomal regions that are comprised of pairs of single nucleotide polymorphisms (SNPs) that consist of just three haplotypes. An example based on 435 sows with performance records for total number of piglets born is used to illustrate the methods.ResultsOf 20,339 SNPs, approximately 50% of the pairs of flanking SNPs failed the four-gamete test. For those, the expectation maximization (EM) algorithm gave the same results. The average of the absolute value of the difference in r2 between flanking SNPs across the genome between the two methods was 0.00082. Single-marker GWAS (using two of three haplotypes) detected significant associations for total number of piglets born on chromosomes 1, 2, 6, 9, 10, 12, 13, 14, 15, and 18. Haplotype-based GWAS using the third haplotype resolved with the Corners’ Algorithm detected additional significant associations for total number of piglets born on chromosomes 2, 5, 10, 13, 14, 15, and 18. Estimated substitution effects ranged from 0.40 to 1.35 piglets. Haplotyping of chromosomal regions that failed the four-gamete test for any pair of SNPs covered 961 Mb out of the 2249 Mb by the SNP array.ConclusionsThe Corner’s Algorithm allows to fully phase haplotypes when the four-gamete test fails. Longer haplotypes in chromosomal regions in which the four-gamete test fails for any pair of SNPs can be used as a multi-allelic marker with increased polymorphism information content.

Exploiting single-marker and haplotype-based genome-wide association studies to identify QTL for the number of teats in Italian Duroc pigs

The number of teats is a morphological trait of high economic relevance for the pig industry. Here, to dissect the genomic architecture of this trait in the Italian Duroc pig population, we present the results of genome-wide association studies in this Italian heavy pig breed. A total of 1,162 pigs, for which the number of teats was recorded, was genotyped with two high-throughput single nucleotide polymorphism (SNP) genotyping platforms (60 K and 70 K). Genome-wide association analyses were based on a single-marker approach and on a haplotype-based approach. Two quantitative trait loci (QTL) affecting the number of teats were identified. The most significant QTL, identified by the single-marker analysis and confirmed by the haplotype-based method, was located on Sus scrofa chromosome (SSC) 7, in the region of the vertnin (VRTN) gene. Suggestively associated markers (SNPs and haplotypes) were located on SSC10, in the region of the FERM domain containing 4A (FRMD4A) gene, the second identified QTL. These findings confirm previous results obtained in a few other Duroc populations. Overall, this study further supported the important role of variability in the VRTN gene region in affecting the number of teats in pigs. Moreover, the results also indicated that this trait in the Italian Duroc breed, as in many other pig breeds, is affected by few QTL, with the contribution of many other genetic factors with small effects, following the classical theory of quantitative traits.

GWAS Case Studies in Wheat.

With the advancements in next-generation sequencing technologies, leading to millions of single nucleotide polymorphisms in all crop species including wheat, genome-wide association study (GWAS) has become a leading approach for trait dissection. In wheat, GWAS has been conducted for a plethora of traits and more and more studies are being conducted and reported in journals. While application of GWAS has become a routine in wheat using the standardized approaches, there has been a great leap forward using newer models and combination of GWAS with other sets of data. This chapter has reviewed all these latest advancements in GWAS in wheat by citing the most important studies and their outputs. Specially, we have focused on studies that conducted meta-GWAS, multilocus GWAS, haplotype-based GWAS, Environmental- and Eigen-GWAS, and/or GWAS combined with gene regulatory network and pathway analyses or epistatic interactions analyses; all these have taken the association mapping approach to new heights in wheat.

Further host-genomic characterization of total antibody response to PRRSV vaccination and its relationship with reproductive performance in commercial sows: genome-wide haplotype and zygosity analyses

BackgroundThe possibility of using antibody response (S/P ratio) to PRRSV vaccination measured in crossbred commercial gilts as a genetic indicator for reproductive performance in vaccinated crossbred sows has motivated further studies of the genomic basis of this trait. In this study, we investigated the association of haplotypes and runs of homozygosity (ROH) and heterozygosity (ROHet) with S/P ratio and their impact on reproductive performance.ResultsThere was no association (P-value ≥ 0.18) of S/P ratio with the percentage of ROH or ROHet, or with the percentage of heterozygosity across the whole genome or in the major histocompatibility complex (MHC) region. However, specific ROH and ROHet regions were significantly associated (P-value ≤ 0.01) with S/P ratio on chromosomes 1, 4, 5, 7, 10, 11, 13, and 17 but not (P-value ≥ 0.10) with reproductive performance. With the haplotype-based genome-wide association study (GWAS), additional genomic regions associated with S/P ratio were identified on chromosomes 4, 7, and 9. These regions harbor immune-related genes, such as SLA-DOB, TAP2, TAPBP, TMIGD3, and ADORA. Four haplotypes at the identified region on chromosome 7 were also associated with multiple reproductive traits. A haplotype significantly associated with S/P ratio that is located in the MHC region may be in stronger linkage disequilibrium (LD) with the quantitative trait loci (QTL) than the previously identified single nucleotide polymorphism (SNP) (H3GA0020505) given the larger estimate of genetic variance explained by the haplotype than by the SNP.ConclusionsSpecific ROH and ROHet regions were significantly associated with S/P ratio. The haplotype-based GWAS identified novel QTL for S/P ratio on chromosomes 4, 7, and 9 and confirmed the presence of at least one QTL in the MHC region. The chromosome 7 region was also associated with reproductive performance. These results narrow the search for causal genes in this region and suggest SLA-DOB and TAP2 as potential candidate genes associated with S/P ratio on chromosome 7. These results provide additional opportunities for marker-assisted selection and genomic selection for S/P ratio as genetic indicator for litter size in commercial pig populations.

SNP- and Haplotype-Based GWAS of Flowering-Related Traits in Brassica napus.

Traits related to flowering time are the most promising agronomic traits that directly impact the seed yield and oil quality of rapeseed (Brassica napus L.). Developing early flowering and maturity rapeseed varieties is an important breeding objective in B. napus. Many studies have reported on days to flowering, but few have reported on budding, bolting, and the interval between bolting and DTF. Therefore, elucidating the genetic architecture of QTLs and genes regulating flowering time, we presented an integrated investigation on SNP and haplotype-based genome-wide association study of 373 diverse B. napus germplasm, which were genotyped by the 60K SNP array and were phenotyped in the four environments. The results showed that a total of 15 and 37 QTLs were detected from SNP and haplotype-based GWAS, respectively. Among them, seven QTL clusters were identified by haplotype-based GWAS. Moreover, three and eight environmentally stable QTLs were detected by SNP-GWAS and haplotype-based GWAS, respectively. By integrating the above two approaches and by co-localizing the four traits, ten (10) genomic regions were under selection on chromosomes A03, A07, A08, A10, C06, C07, and C08. Interestingly, the genomic regions FT.A07.1, FT.A08, FT.C06, and FT.C07 were identified as novel. In these ten regions, a total of 197 genes controlling FT were detected, of which 14 highly expressed DEGs were orthologous to 13 Arabidopsis thaliana genes after integration with transcriptome results. In a nutshell, the above results uncovered the genetic architecture of important agronomic traits related to flowering time and provided a basis for multiple molecular marker-trait associations in B. napus.

27 Machine Learning Algorithms Based on Haplotype Libraries for Classification of Stillbirth Susceptibility in Holstein Cows

Abstract Reduced fertility is one of the main causes of economic losses in dairy farms. The cost of a stillbirth is estimated in US$ 938 per case in Holstein herds. Machine learning (ML) is gaining popularity in the livestock sector as a mean to identify hidden patterns and due to its potential to address dimensionality problems. Here we investigate the application of ML algorithms for the prediction of cows with higher stillbirth susceptibility in two scenarios: cows with &amp;gt;25% and &amp;gt;33.33% of stillbirths among birth records. These thresholds correspond to percentiles 75 (still_75) and 90 (still_90), respectively. A total of 10,570 cows and 50,541 birth records were collected to perform a haplotype-based genome-wide association study. Five-hundred significant pseudo single nucleotide polymorphisms (pseudo-SNPs) (False-Discovery Rate&amp;lt; 0.05) were used as input features of ML-based predictions to determine if the cow is in the top-75 and top-90 percentiles. Table 1 shows the classification performance of the investigated ML and linear models. The ML models outperformed linear models for both thresholds. In general, still_75 showed higher F1 values compared to still_90, suggesting a lower misclassification ratio when a less stringent threshold is used. We observe that accuracy of the models in our study is higher when compared to ML-based prediction accuracies in other breeds, e.g. compared to the accuracies of 0.46 and 0.67 that were achieved using SNPs for body weight in Brahman and fertility traits in Nellore, respectively. Xgboost algorithm shows the highest balanced accuracy (BA; 0.625), F1-score (0.588) and area under the curve (AUC; 0.688), suggesting that xgboost can achieve the highest predictive performance and the lowest difference in misclassification ratio between classes. The ML applied over haplotype libraries is an interesting approach for the detection of animals with higher susceptibility to stillbirths due to highest predictive accuracy and relatively lower misclassification ratio.

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.

40 Novel Genomic Regions Associated with Igg Antibody Response to PRRSV Vaccination Revealed by Haplotype-based GWAS

Abstract Previous studies on genomics of antibody response, measured as sample-to-positive (S/P) ratio, to Porcine Reproductive and Respiratory Syndrome virus (PRRSV) have reported a major quantitative trait locus (QTL) on the major histocompatibility complex (MHC) on chromosome 7, explaining ~25% of the genetic variance of this trait. S/P ratio following modified live PRRSV vaccination in crossbred commercial gilts has been proposed as genetic indicator for reproductive performance in non-infected purebred sows and PRRSV-vaccinated crossbred sows. This motivated further genomic study for this trait by performing haplotype-based genome-wide association study (GWAS). 906 naïve F1 (Landrace x Large White) had blood samples taken at ~50d after vaccination for measuring PRRSV ELISA S/P ratio and genotyping. Haplotype-based GWAS identified 8 genomic regions on chromosomes 4 (108 Mb), 7 (15, 21, and 24–27 Mb), and 9 (33 Mb) that were associated (q-value &amp;lt; 0.07) with S/P ratio. From those, only the MHC region (chromosome 7; 24 – 26 Mb) had been identified in the SNP based GWAS. The main SNP identified in the SNP based GWAS (H3GA0020505) was not in LD with the haplotype; thus, we added this SNP to the haplotype model. We observed that the haplotype explained more of the genetic variance compared to the H3GA0020505 SNP, indicating that the MHC haplotype is in stronger LD with the QTL than the H3GA0020505 SNP. All the significant regions associated with S/P ratio included immune-related candidate genes, such as SLA-DOB, TAP2, TAPBP, TMIGD3, and ADORA. This study validated the QTL identified on the MHC region, narrowing the search for causal genes in this region, and identified new genomic regions, along with candidate genes associated with S/P ratio. Identifying novel genomic regions provides more resources for marker-assisted selection and genomic prediction of S/P ratio in purebred and commercial pig populations.

Genetic Regulation of Biomarkers as Stress Proxies in Dairy Cows

Stress in livestock reduces productivity and is a welfare concern. At a physiological level, stress is associated with the activation of inflammatory responses and increased levels of harmful reactive oxygen species. Biomarkers that are indicative of stress could facilitate the identification of more stress-resilient animals. We examined twenty-one metabolic, immune response, and liver function biomarkers that have been associated with stress in 416 Italian Simmental and 436 Italian Holstein cows which were genotyped for 150K SNPs. Single-SNP and haplotype-based genome-wide association studies were carried out to assess whether the variation in the levels in these biomarkers is under genetic control and to identify the genomic loci involved. Significant associations were found for the plasma levels of ceruloplasmin (Bos taurus chromosome 1—BTA1), paraoxonase (BTA4) and γ-glutamyl transferase (BTA17) in the individual breed analysis that coincided with the position of the genes coding for these proteins, suggesting that their expression is under cis-regulation. A meta-analysis of both breeds identified additional significant associations with paraoxonase on BTA 16 and 26. Finding genetic associations with variations in the levels of these biomarkers suggests that the selection for high or low levels of expression could be achieved rapidly. Whether the level of expression of the biomarkers correlates with the response to stressful situations has yet to be determined.

Haplotype-based genomic analysis reveals novel association of CNTNAP5 genic region with primary angle closure glaucoma

Primary angle closure glaucoma (PACG) is one of the major causes of blindness worldwide. The underlying genetic aetiology is complex in nature and molecular mechanism remains elusive. Here, we identify genomic alterations using haplotype-based genome-wide association study in 148 PACG and 92 anatomically predisposed non-glaucomatous individuals. Logistic regression was performed on each common haplotype (within blocks of 3-8 SNPs) across the genotype and a total of 59 SNPs were found below genome wide suggestive threshold (p <1e-05). We found majority of these SNPs (n = 13) are located in CNTNAP5 genic region. The prioritized rs780010 of CNTNAP5 is also significantly associated with Cup to Disc ratio, which is a clinical parameter directly correlated with glaucomatous neurodegeneration. We further validated rs780010, present in all the significant haplotype blocks with p-value = 2.131e-06 (discovery phase), in a separate replication cohort (PACG, n = 50; control, n = 39) and observed significant association (p = 0.012, per G allele OR = 2.3079; 95 % CI: 1.23-4.33). Bioinformatics analyses also suggested neuronal expression of CNTNAP5 with active chromatin structure. KEGG pathway analysis indicates towards pathways related to apoptosis and neurodegeneration. Overall, these results not only indicate a strong genetic association of CNTNAP5 locus with PACG but also suggest its potential involvement in glaucomatous neurodegeneration.

Haplotype analysis from unmanned aerial vehicle imagery of rice MAGIC population for the trait dissection of biomass and plant architecture.

Unmanned aerial vehicles (UAVs) are popular tools for high-throughput phenotyping of crops in the field. However, their use for evaluation of individual lines is limited in crop breeding because research on what the UAV image data represent is still developing. Here, we investigated the connection between shoot biomass of rice plants and the vegetation fraction (VF) estimated from high-resolution orthomosaic images taken by a UAV 10 m above a field during the vegetative stage. Haplotype-based genome-wide association studies of multi-parental advanced generation inter-cross (MAGIC) lines revealed four quantitative trait loci (QTLs) for VF. VF was correlated with shoot biomass, but the haplotype effect on VF was better correlated with that on shoot biomass at these QTLs. Further genetic characterization revealed the relationships between these QTLs and plant spreading habit, final shoot biomass and panicle weight. Thus, genetic analysis using high-throughput phenotyping data derived from low-altitude, high-resolution UAV images during early stages of rice growing in the field provides insights into plant growth, architecture, final biomass, and yield.

Haplotype-Based, Genome-Wide Association Study Reveals Stable Genomic Regions for Grain Yield in CIMMYT Spring Bread Wheat.

We untangled key regions of the genetic architecture of grain yield (GY) in CIMMYT spring bread wheat by conducting a haplotype-based, genome-wide association study (GWAS), together with an investigation of epistatic interactions using seven large sets of elite yield trials (EYTs) consisting of a total of 6,461 advanced breeding lines. These lines were phenotyped under irrigated and stress environments in seven growing seasons (2011–2018) and genotyped with genotyping-by-sequencing markers. Genome-wide 519 haplotype blocks were constructed, using a linkage disequilibrium-based approach covering 14,036 Mb in the wheat genome. Haplotype-based GWAS identified 7, 4, 10, and 15 stable (significant in three or more EYTs) associations in irrigated (I), mild drought (MD), severe drought (SD), and heat stress (HS) testing environments, respectively. Considering all EYTs and the four testing environments together, 30 stable associations were deciphered with seven hotspots identified on chromosomes 1A, 1B, 2B, 4A, 5B, 6B, and 7B, where multiple haplotype blocks were associated with GY. Epistatic interactions contributed significantly to the genetic architecture of GY, explaining variation of 3.5–21.1%, 3.7–14.7%, 3.5–20.6%, and 4.4– 23.1% in I, MD, SD, and HS environments, respectively. Our results revealed the intricate genetic architecture of GY, controlled by both main and epistatic effects. The importance of these results for practical applications in the CIMMYT breeding program is discussed.

Fine mapping genetic variants associated with age at puberty and sow fertility using SowPro90 genotyping array.

Sow fertility traits, such as litter size and the number of lifetime parities produced (reproductive longevity), are economically important. Selection for these traits is difficult because they are lowly heritable and expressed late in life. Age at puberty (AP) is an early indicator of reproductive longevity. Here, we utilized a custom Affymetrix single-nucleotide polymorphisms (SNPs) array (SowPro90) enriched with positional candidate genetic variants for AP and a haplotype-based genome-wide association study to fine map the genetic sources associated with AP and other fertility traits in research (University of Nebraska-Lincoln [UNL]) and commercial sow populations. Five major quantitative trait loci (QTL) located on four Sus scrofa chromosomes (SSC2, SSC7, SSC14, and SSC18) were discovered for AP in the UNL population. Negative correlations (r = -0.96 to -0.10; P < 0.0001) were observed at each QTL between genomic estimated breeding values for AP and reproductive longevity measured as lifetime number of parities (LTNP). Some of the SNPs discovered in the major QTL regions for AP were located in candidate genes with fertility-associated gene ontologies (e.g., P2RX3, NR2F2, OAS1, and PTPN11). These SNPs showed significant (P < 0.05) or suggestive (P < 0.15) associations with AP, reproductive longevity, and litter size traits in the UNL population and litter size traits in the commercial sows. For example, in the UNL population, when the number of favorable alleles of an SNP located in the 3' untranslated region of PTPN11 (SSC14) increased, AP decreased (P < 0.0001), while LTNP increased (P < 0.10). Additionally, a suggestive difference in the observed NR2F2 isoforms usage was hypothesized to be the source of the QTL for puberty onset mapped on SSC7. It will be beneficial to further characterize these candidate SNPs and genes to understand their impact on protein sequence and function, gene expression, splicing process, and how these changes affect the phenotypic variation of fertility traits.