Genome-wide association mapping for high temperature tolerance in wheat through 90k SNP array using physiological and yield traits

Dissecting the genetic basis of physiological and yield traits against tolerance to heat stress is an essential in wheat breeding programs to boost up the wheat yield for sustainable food security. Herein, a genome-wide association study (GWAS) was performed to reveal the genetic basis of heat tolerance using high-density Illumina 90K Infinium SNPs array through physiological and yield indices. These indices were phenotyped on a diverse panel of foreign and domestic genotypes of Pakistan, grown in normal and heat-stressed environments. Based on STRUCTURE analysis, the studied germplasm clustered into four sub-population. Highly significant variations with a range of moderate (58.3%) to high (77.8%) heritability was observed under both conditions. Strong positive correlation existed among physiological and yield related attributes. A total of 320 significant (-log10 P ≥ 3) marker-trait associations (MTAs) were identified for the observed characters. Out of them 169 and 151 MTAs were recorded in normal and heat stress environments, respectively. Among the MTA loci, three (RAC875_c103017_302, Tdurum_contig42087_1199, and Tdurum_contig46877_488 on chromosomes 4B, 6B, and 7B respectively), two (BobWhite_c836_422 and BS00010616_51) and three (Kukri_rep_c87210_361, D_GA8KES401BNLTU_253 and Tdurum_contig1015_131) on chromosomes 5A, 1B, and 3D at the positions 243.59cM, 77.82cM and 292.51cM) showed pleiotropic effects in studied traits under normal, heat-stressed and both conditions respectively. The present study not only authenticated the numerous previously reported MTAs for examined attributes but also revealed novel MTAs under heat-stressed conditions. Identified SNPs will be beneficial in determining the novel genes in wheat to develop the heat tolerant and best yielded genotypes to fulfill the wheat requirement for the growing population.

Characterization and Mapping of retr04, retr05 and retr06 Broad-Spectrum Resistances to Turnip Mosaic Virus in Brassica juncea, and the Development of Robust Methods for Utilizing Recalcitrant Genotyping Data

Turnip mosaic virus (TuMV) induces disease in susceptible hosts, notably impacting cultivation of important crop species of the Brassica genus. Few effective plant viral disease management strategies exist with the majority of current approaches aiming to mitigate the virus indirectly through control of aphid vector species. Multiple sources of genetic resistance to TuMV have been identified previously, although the majority are strain-specific and have not been exploited commercially. Here, two Brassica juncea lines (TWBJ14 and TWBJ20) with resistance against important TuMV isolates (UK 1, vVIR24, CDN 1, and GBR 6) representing the most prevalent pathotypes of TuMV (1, 3, 4, and 4, respectively) and known to overcome other sources of resistance, have been identified and characterized. Genetic inheritance of both resistances was determined to be based on a recessive two-gene model. Using both single nucleotide polymorphism (SNP) array and genotyping by sequencing (GBS) methods, quantitative trait loci (QTL) analyses were performed using first backcross (BC1) genetic mapping populations segregating for TuMV resistance. Pairs of statistically significant TuMV resistance-associated QTLs with additive interactive effects were identified on chromosomes A03 and A06 for both TWBJ14 and TWBJ20 material. Complementation testing between these B. juncea lines indicated that one resistance-linked locus was shared. Following established resistance gene nomenclature for recessive TuMV resistance genes, these new resistance-associated loci have been termed retr04 (chromosome A06, TWBJ14, and TWBJ20), retr05 (A03, TWBJ14), and retr06 (A03, TWBJ20). Genotyping by sequencing data investigated in parallel to robust SNP array data was highly suboptimal, with informative data not established for key BC1 parental samples. This necessitated careful consideration and the development of new methods for processing compromised data. Using reductive screening of potential markers according to allelic variation and the recombination observed across BC1 samples genotyped, compromised GBS data was rendered functional with near-equivalent QTL outputs to the SNP array data. The reductive screening strategy employed here offers an alternative to methods relying upon imputation or artificial correction of genotypic data and may prove effective for similar biparental QTL mapping studies.

Genome-Wide Association Study of Leaf Chlorophyll Content Using High-Density SNP Array in Peanuts (Arachis hypogaea L.)

The content of chlorophyll, a fundamental component required for photosynthesis in plants, has been widely studied across crop species. In this study, we aimed to evaluate the genetic diversity of 453 peanut accessions. We evaluated the evolutionary relationships using a genome-wide association study (GWAS) of leaf color data based on chlorophyll content analysis using the Axiom_Arachis array containing 58K single-nucleotide polymorphisms (SNPs). We identified seven SNPs as being significantly associated with leaf chlorophyll content on the chromosomes Aradu.A02, Aradu.A08, Araip.B02, Araip.B05, Araip.B06, and Araip.B08 in a GAPIT analysis. The SNP AX-176820297 on Araip.B05 was significantly linked with leaf chlorophyll content across the seasons. The Arahy.SDG4EV gene was detected to be in linkage disequilibrium (LD) with the significant SNPs, and its expression was significantly correlated with leaf chlorophyll content. The results of the current study provide useful and fundamental information with which to assess genetic variations in chlorophyll content and can be utilized for further genetic and genomic studies and breeding programs in peanuts.

A Combination of Leaf Rust Resistance Genes, Including Lr34 and Lr46, Is the Key to the Durable Resistance of the Canadian Wheat Cultivar, Carberry

The hexaploid spring wheat cultivar, Carberry, was registered in Canada in 2009, and has since been grown over an extensive area on the Canadian Prairies. Carberry has maintained a very high level of leaf rust (Puccinia triticina Eriks.) resistance since its release. To understand the genetic basis of Carberry’s leaf rust resistance, Carberry was crossed with the susceptible cultivar, Thatcher, and a doubled haploid (DH) population of 297 lines was generated. The DH population was evaluated for leaf rust in seven field environments at the adult plant stage. Seedling and adult plant resistance (APR) to multiple virulence phenotypes of P. triticina was evaluated on the parents and the progeny population in controlled greenhouse studies. The population was genotyped with the wheat 90 K iSelect single nucleotide polymorphism (SNP) array, and quantitative trait loci (QTL) analysis was performed. The analysis using field leaf rust response indicated that Carberry contributed nine QTL located on chromosomes 1B, 2B (2 loci), 2D, 4A, 4B, 5A, 5B, and 7D. The QTL located on 1B, 2B, 5B, and 7D chromosomes were observed in two or more environments, whereas the remainder were detected in single environments. The resistance on 1B, detected in five environments, was attributed to Lr46 and on 7D, detected in seven environments to Lr34. The first 2B QTL corresponded with the adult plant gene, Lr13, while the second QTL corresponded with Lr16. The seedling analysis showed that Carberry carries Lr2a, Lr16, and Lr23. Five epistatic effects were identified in the population, with synergistic interactions being observed for Lr34 with Lr46, Lr16, and Lr2a. The durable rust resistance of Carberry is attributed to Lr34 and Lr46 in combination with these other resistance genes, because the resistance has remained effective even though the P. triticina population has evolved virulent to Lr2a, Lr13, Lr16, and Lr23.

Joint copy number and mutation phylogeny reconstruction from single-cell amplicon sequencing data

Reconstructing the history of somatic DNA alterations that occurred in a tumour can help understand its evolution and predict its resistance to treatment. Single-cell DNA sequencing (scDNAseq) can be used to investigate clonal heterogeneity and to inform phylogeny reconstruction. However, existing phylogenetic methods for scDNAseq data are designed either for point mutations or for large copy number variations, but not for both types of events simultaneously. Here, we develop COMPASS, a computational method for inferring the joint phylogeny of mutations and copy number alterations from targeted scDNAseq data. We evaluate COMPASS on simulated data and show that it outperforms existing methods. We apply COMPASS to a large cohort of 123 patients with acute myeloid leukemia (AML) and detect copy number alterations, including subclonal ones, which are in agreement with current knowledge of AML development. We further used bulk SNP array data to orthogonally validate or findings.

Genome-Wide Association Analysis To Delineate High-Quality Snps For Seed Micronutrient Density In Chickpea (Cicer Arietinum L.)

Chickpea is the most important nutrient rich grain legume crop in the world. A diverse core set of 147 chickpea genotypes was genotyped with 50K Cicer SNP array and trait phenotyped in two different environments for four seed micro-nutrients (Cu, Fe, Mn, and Zn). The trait data and high-throughput 50K SNP genotypic data was used for genome-wide association study (GWAS) that led the discovery of gene/QTLs for seed Cu, Fe, Mn, and Zn concentrations in chickpea. The analysis of seed micronutrient data revealed significant differences for all the four micronutrient concentrations (P ≤ 0.05). The mean concentration of seed Fe, Zn, Cu, and Mn pooled over two-year data was 146.1 ppm, 45.9 ppm, 63.8 ppm and 27.0 ppm respectively. The analysis of results led to the identification of 35 SNPs significantly associated with seed Zn, Cu, Fe and Mn concentrations. Among these 35 MTAs, 5 were stable (consistently identified in different environments), 6 were major (explain more than 15% phenotypic variation for an individual trait) and 3 were both major and stable MTAs. The stable and major MTAs identified during the present study shall prove useful in molecular breeding programs aimed at enhancing seed nutrient density of chickpea.

Patients with polyclonal hepatocellular carcinoma are at a high risk of early recurrence and have a poor recurrence-free survival period

Background/purpose of the study Tumor heterogeneity based on copy number variations is associated with the evolution of cancer and its clinical grade. Clonal composition (CC) represents the number of clones based on the distribution of B-allele frequency (BAF) obtained from a genome-wide single nucleotide polymorphism (SNP) array. A higher CC number represents a high degree of heterogeneity. We hypothesized and evaluated that the CC number in hepatocellular carcinoma (HCC) tissues might be associated with the clinical outcomes of patients. Methods Somatic mutation, whole transcriptome, and CC number based on copy number variations of 36 frozen tissue samples of operably resected HCC tissues were analyzed by targeted deep sequencing, transcriptome analysis, and SNP array. Results The samples were classified into the heterogeneous tumors as poly-CC (n = 26) and the homogeneous tumors as mono-CC (n = 8). The patients with poly-CC had a higher rate of early recurrence and a significantly shorter recurrence-free survival period than the mono-CC patients (7.0 months vs. not reached, p = 0.0084). No differences in pathogenic non-synonymous mutations, such as TP53, were observed between the two groups when targeted deep sequencing was applied. A transcriptome analysis showed that cell cycle-related pathways were enriched in the poly-CC tumors, compared to the mono-CC tumors. Poly-CC HCC is highly proliferative and has a high risk of early recurrence. Conclusion CC is a possible candidate biomarker for predicting the risk of early postoperative recurrence and warrants further investigation.

Association Mapping of Agronomic traits in Bread Wheat using a high Density 90k SNP Array

A genome-wide association study (GWAS) was performed using a high-density infinium 90K SNP array. We identified a total markers traits associations (MTAs) (p ?0.000) for the following plant traits; days taken to 50% heading(DH), days to 50% maturity (DM), plant height (Ph) cm, flag leaf area cm2 (FLA), tillers number per plant, spike length (SL) cm and grain yield per plant (GP) g. Most of the SNPs were identified in the A and B genome as compared to the D genome. The significant associated SNPs were mainly distributed on the chromosome 2B, 3B, 5A, and 5B. Nine SNPs on chromosome 5A, 2B and 2D were identified having pleiotropic effects The correlation analysis showed a significant positive association among SL, NT, GP. Which depicted that these traits are promising for breeding high yielding wheat cultivars. This study provided useful information of the valuable genetic loci for marker-assisted breeding.

Clinical Application of Chromosomal Microarray Analysis in Fetuses with Congenital Heart Disease

Background: Congenital heart disease (CHD) is an important birth defect, but its mechanism is still unclear. In recent years, genetic causes including chromosomal abnormalities are associated with the occurrence of congenital heart disease. In this study, CMA technology is applied to explore the genetic causes of congenital heart disease, so as to further clarify the correlation between genotype and phenotype and prepare for late pregnancy intervention and postnatal diagnosis and treatment.Objective: To explore the chromosomal abnormalities and copy number variation (CNVs) of fetuses with CHD by CMA technology, and to clarify the clinical application value of CMA technology as a detection method of first-tier antenatal CHD.Methods: Amniotic fluid sample from 155 pregnant women diagnosed with fetus CHD by prenatal ultrasound from 2018 to 2021 are collected for SNP-array detection and karyotype analysis. According to the detected CNVs results, FISH, CMA or karyotype analysis are further selected for parental verification.Results: Among the 155 fetuses with CHD, a total of 32 (20.6%) cases of chromosomal abnormalities are detected, of which 31.3% are chromosome number abnormalities. CNVs of likely pathogenicity and unknown significance are 2.5% and 5.2% respectively. The detection rate of chromosomal abnormalities in CHD of different subtypes is different, among which the high detection rate is complex CHD (31.2%), right ventricular outflow tract obstruction (30.7%) and conotruncal defects (25%). The detection rate of chromosomal abnormalities in CHD with extracardiac structural abnormalities is significantly higher than that in isolated CHD (52.4% vs 11.3%, p<0.05). In addition, the detection rate of CHD with abnormal extracardiac structure is significantly higher than that of CHD with soft markers (52.4% vs 17.8%, p<0.05), which is statistically significant. There is no significant difference in detection rate between CHD with soft markers and isolated CHD (17.8% vs 11.3%). Of the 155 pregnant women with fetus CHD, 59 chose to terminate their pregnancies, some of which were terminated according to the results of SNP-array, and some of which were terminated according to the severity of CHD.Conclusion: SNP-array technology can be used to detect chromosomal abnormalities of first-tier antenatal CHD fetuses, with high resolution, short reporting period and high efficiency. Meanwhile, pregnancy intervention can be taken according to the results.

Genome-Wide Association Analysis of Stable Stripe Rust Resistance Loci in a Chinese Wheat Landrace Panel Using the 660K SNP Array

Stripe rust (caused by Puccinia striiformis f. sp. tritici) is one of the most severe diseases affecting wheat production. The disease is best controlled by developing and growing resistant cultivars. Chinese wheat (Triticum aestivum) landraces have excellent resistance to stripe rust. The objectives of this study were to identify wheat landraces with stable resistance and map quantitative trait loci (QTL) for resistance to stripe rust from 271 Chinese wheat landraces using a genome-wide association study (GWAS) approach. The landraces were phenotyped for stripe rust responses at the seedling stage with two predominant Chinese races of P. striiformis f. sp. tritici in a greenhouse and the adult-plant stage in four field environments and genotyped using the 660K wheat single-nucleotide polymorphism (SNP) array. Thirteen landraces with stable resistance were identified, and 17 QTL, including eight associated to all-stage resistance and nine to adult-plant resistance, were mapped on chromosomes 1A, 1B, 2A, 2D, 3A, 3B, 5A, 5B, 6D, and 7A. These QTL explained 6.06–16.46% of the phenotypic variation. Five of the QTL, QYrCL.sicau-3AL, QYrCL.sicau-3B.4, QYrCL.sicau-3B.5, QYrCL.sicau-5AL.1 and QYrCL.sicau-7AL, were likely new. Five Kompetitive allele specific PCR (KASP) markers for four of the QTL were converted from the significant SNP markers. The identified wheat landraces with stable resistance to stripe rust, significant QTL, and KASP markers should be useful for breeding wheat cultivars with durable resistance to stripe rust.