Association of Genetic Variants of ELMO1 Gene With Diabetic Nephropathy in the North Indian Population

Diabetic nephropathy (DN) is a major cause of renal failure globally including chronic kidney disease and end-stage renal disease (ESRD). Using comprehensive linkage disequilibrium mapping, we genotyped five polymorphisms from engulfment and cell motility 1 (ELMO1) gene (rs741301, rs7799004, rs1882080, rs11769038 and rs1345365) to evaluate its association with DN. BMI was observed to be low in DN cases as compared to the control groups, which is the result of haemodialysis and high doses of medication. Physical inactivity, lipid profile, urea and creatinine were observed to be the confounding factors correlated with DN. This study comprehensively evaluated ELMO1 in DN patients, T2D without Nephropathy and healthy controls from North Indian population and revealed significant association with DN. Haplotypes G-G-C-C and G-A-T-T provided ~2-fold risk towards DN development. In conclusion, the present study suggests the significant role of ELMO1 gene polymorphisms in the pathophysiology of DN in North-Indian population.

Joint linkage and association mapping of complex traits in shrub willow (Salix purpurea L.)

Background and Aims Increasing energy demands and the necessity to reduce greenhouse gas emissions are key motivating factors driving the development of lignocellulosic crops as an alternative to non-renewable energy sources. The effects of global climate change will require a better understanding of the genetic basis of complex adaptive traits to breed more resilient bioenergy feedstocks, like willow (Salix spp.). Shrub willow is a sustainable and dedicated bioenergy crop, bred to be fast-growing and high-yielding on marginal land without competing with food crops. In a rapidly changing climate, genomic advances will be vital for the sustained improvement of willow and other non-model bioenergy crops. Here, joint genetic mapping was used to exploit genetic variation garnered from both recent and historical recombination events in S. purpurea. Methods A panel of North American naturalized S. purpurea accessions and full-sib F2S. purpurea population were genotyped and phenotyped for a suite of morphological, physiological, pest and disease resistance, and wood chemical composition traits, collected from multi-environment and multi-year replicated field trials. Controlling for population stratification and kinship in the association panel and spatial variation in the F2, a comprehensive mixed model analysis was used to dissect the complex genetic architecture and plasticity of these important traits. Key Results Individually, genome-wide association (GWAS) models differed in terms of power, but the combined approach, which corrects for yearly and environmental co-factors across datasets, improved the overall detection and resolution of associated loci. Although there were few significant GWAS hits located within support intervals of QTL for corresponding traits in the F2, many large-effect QTL were identified, as well as QTL hotspots. Conclusions This study provides the first comparison of linkage analysis and linkage disequilibrium mapping approaches in Salix, and highlights the complementarity and limits of these two methods for elucidating the genetic architecture of complex bioenergy-related traits of a woody perennial breeding programme.

Patient HLA Germline Variation and Transplant Survivorship

Purpose HLA mismatching increases mortality after unrelated donor hematopoietic cell transplantation. The role of the patient’s germline variation on survival is not known. Patients and Methods We previously identified 12 single nucleotide polymorphisms within the HLA region as markers of transplantation determinants and tested these in an independent cohort of 1,555 HLA-mismatched unrelated transplants. Linkage disequilibrium mapping across class II identified candidate susceptibility features. The candidate gene was confirmed in an independent cohort of 3,061 patients. Results Patient rs429916AA/AC was associated with increased transplantation-related mortality compared with rs429916CC (hazard ratio [HR], 1.39; 95% CI, 1.12 to 1.73; P = .003); rs429916A positivity was a proxy for DOA*01:01:05. Mortality increased with one (HR, 1.17; 95% CI, 1.0 to 1.36; P = .05) and two (HR, 2.51; 95% CI, 1.41 to 4.45; P = .002) DOA*01:01:05 alleles. HLA-DOA*01:01:05 was a proxy for HLA-DRB1 alleles encoding FEY ( P < 10E-15) and FDH ( P < 10E-15) amino acid substitutions at residues 26/28/30 that influence HLA-DRβ peptide repertoire. FEY- and FDH-positive alleles were positively associated with rs429916A ( P < 10E-15); FDY-positive alleles were negatively associated. Mortality was increased with FEY (HR, 1.66; 95% CI, 1.29 to 2.13; P = .00008) and FDH (HR, 1.40; 95% CI, 1.02 to 1.93; P = .04), whereas FDY was protective (HR, 0.88; 95% CI, 0.78 to 0.98; P = .02). Of the three candidate motifs, FEY was validated as the susceptibility determinant for mortality (HR, 1.29; 95% CI, 1.00 to 1.67; P = .05). Although FEY was found frequently among African and Hispanic Americans, it increased mortality independently of ancestry. Conclusion Patient germline HLA-DRB1 alleles that encode amino acid substitutions that influence the peptide repertoire of HLA-DRβ predispose to increased death after transplantation. Patient germline variation informs transplantation outcomes across US populations and may provide a means to reduce risks for high-risk patients through pretransplantation screening and evaluation.

Association analysis of agronomic traits with microsatellites in maize inbred lines

Association analysis or linkage disequilibrium mapping is a method for identification of quantitative trait loci (QTLs) in a panel of divergent unrelated individuals based on historical recombinations during a crop?s domestication and selection. It should account for the population structure, which can be the result of adaptation to local conditions or selection, to reduce the possibility of declaring false-positive associations. The aim of this study was to determine potentially significant and consistent associations between markers and agronomic important maize (Zea mays L.) traits using association analysis in a diverse breeding material that can be ultimately implemented in maize selection. To this end, 96 maize inbred lines were evaluated in field trials at three locations in Serbia for eleven agronomic traits and analysed with microsatellite markers. Twenty five microsatellites were used to assess the population structure using Bayesian model-based clustering method and to test the significance of associations between the markers and the traits with general (GLM) and mixed linear (MLM) models. The cluster analysis divided maize inbred lines in four subpopulations, corresponding to the BSSS (Iowa Stiff Stalk Synthetic), LSC (Lancaster Sure Crop), Iodent heterotic groups and exotic and independent germplasm. The models identified associations between twenty five microsatellite markers and eleven agronomic traits, resulting in 133 and 71 associations across the environments for GLM and MLM, respectively. Some of the identified marker-trait associations were significant and consistent in several environments. The associations stable in several environments were identified between the markers bnlg1067 and two flowering traits; nc005 and bnlg434 and plant height, bnlg434 and ear height; bnlg1643 and umc1127 and leaf number, bnlg1360 and ear diameter; umc1019 and umc1506 and number of rows per ear; bnlg2305 and bnlg1451 and ear length, and between bnlg1175 and thousand-kernel weight. The results of this study indicate that these microsatellites could be used in marker-assisted selection of inbred lines, after validation of the marker-trait associations and testing combining abilities of the inbreds during hybrid development.