Unraveling the Genetic Basis of Key Agronomic Traits of Wrinkled Vining Pea (Pisum sativum L.) for Sustainable Production

Estimating the allelic variation and exploring the genetic basis of quantitatively inherited complex traits are the two foremost breeding scenarios for sustainable crop production. The current study utilized 188 wrinkled vining pea genotypes comprising historical varieties and breeding lines to evaluate the existing genetic diversity and to detect molecular markers associated with traits relevant to vining pea production, such as wrinkled vining pea yield (YTM100), plant height (PH), earliness (ERL), adult plant resistance to downy mildew (DM), pod length (PDL), numbers of pods per plant (PDP), number of peas per pod (PPD), and percent of small wrinkled vining peas (PSP). Marker-trait associations (MTAs) were conducted using 6902 quality single nucleotide polymorphism (SNP) markers generated from the diversity arrays technology sequencing (DArTseq) and Genotyping-by-sequencing (GBS) sequencing methods. The best linear unbiased prediction (BLUP) values were estimated from the two-decadeslong (1999–2020) unbalanced phenotypic data sets recorded from two private breeding programs, the Findus and the Birds eye, now owned by Nomad Foods. Analysis of variance revealed a highly significant variation between genotypes and genotype-byenvironment interactions for the ten traits. The genetic diversity and population structure analyses estimated an intermediate level of genetic variation with two optimal subgroups within the current panel. A total of 48 significant (P < 0.0001) MTAs were identified for eight different traits, including five for wrinkled vining pea yield on chr2LG1, chr4LG4, chr7LG7, and scaffolds (two), and six for adult plant resistance to downy mildew on chr1LG6, chr3LG5 (two), chr6LG2, and chr7LG7 (two). We reported several novel MTAs for different crucial traits with agronomic importance in wrinkled vining pea production for the first time, and these candidate markers could be easily validated and integrated into the active breeding programs for marker-assisted selection

Haplotype-tagged SNPs improve genomic prediction accuracy for Fusarium head blight resistance and yield-related traits in wheat

Genomic prediction is a powerful tool to enhance genetic gain in plant breeding. However, the method is accompanied by various complications leading to low prediction accuracy. One of the major challenges arises from the complex dimensionality of marker data. To overcome this issue, we applied two pre-selection methods for SNP markers viz. LD-based haplotype-tagging and GWAS-based trait-linked marker identification. Six different models were tested with preselected SNPs to predict the genomic estimated breeding values (GEBVs) of four traits measured in 419 winter wheat genotypes. Ten different sets of haplotype-tagged SNPs were selected by adjusting the level of LD thresholds. In addition, various sets of trait-linked SNPs were identified with different scenarios from the training-test combined and only from the training populations. The BRR and RR-BLUP models developed from haplotype-tagged SNPs had a higher prediction accuracy for FHB and SPW by 0.07 and 0.092, respectively, compared to the corresponding models developed without marker pre-selection. The highest prediction accuracy for SPW and FHB was achieved with tagged SNPs pruned at weak LD thresholds (r

Exploring GWAS and genomic prediction to improve Septoria tritici blotch resistance in wheat

Septoria tritici blotch (STB) is a destructive foliar diseases threatening wheat grain yield. Wheat breeding for STB disease resistance has been identifed as the most sustainable and environmentfriendly approach. In this work, a panel of 316 winter wheat breeding lines from a commercial breeding program were evaluated for STB resistance at the seedling stage under controlled conditions followed by genome-wide association study (GWAS) and genomic prediction (GP). The study revealed a signifcant genotypic variation for STB seedling resistance, while disease severity scores exhibited a normal frequency distribution. Moreover, we calculated a broad-sense heritability of 0.62 for the trait. Nine single- and multi-locus GWAS models identifed 24 marker-trait associations grouped into 20 quantitative trait loci (QTLs) for STB seedling-stage resistance. The seven QTLs located on chromosomes 1B, 2A, 2B, 5B (two), 7A, and 7D are reported for the frst time and could potentially be novel. The GP cross-validation analysis in the RR-BLUP model estimated the genomic-estimated breeding values (GEBVs) of STB resistance with a prediction accuracy of 0.49. Meanwhile, the GWAS assisted wRR-BLUP model improved the accuracy to 0.58. The identifed QTLs can be used for markerassisted backcrossing against STB in winter wheat. Moreover, the higher prediction accuracy recorded from the GWAS-assisted GP analysis implies its power to successfully select superior candidate lines based on their GEBVs for STB resistance

Single- and multi-trait genomic prediction and genome-wide association analysis of grain yield and micronutrient-related traits in ICARDA wheat under drought environment

Globally, over 2 billion people suffer from malnutrition due to inadequate intake of micronutrients. Genomic-assisted breeding is identified as a valuable method to facilitate developing new improved plant varieties targeting grain yield and micronutrient-related traits. In this study, a genome-wide association study (GWAS) and single- and multi-trait-based genomic prediction (GP) analysis was conducted using a set of 252 elite wheat genotypes from the International Center for Agricultural Research in Dry Areas (ICARDA). The objective was to identify linked SNP markers, putative candidate genes and to evaluate the genomic estimated breeding values (GEBVs) of grain yield and micronutrient-related traits.. For this purpose, a field trial was conducted at a drought-prone station, Merchouch, Morocco for 2 consecutive years (2018 and 2019) followed by GWAS and genomic prediction analysis with 10,173 quality SNP markers. The studied genotypes exhibited a significant genotypic variation in grain yield and micronutrient-related traits. The GWAS analysis identified highly significantly associated markers and linked putative genes on chromosomes 1B and 2B for zinc (Zn) and iron (Fe) contents, respectively. The genomic predictive ability of selenium (Se) and Fe traits with the multi-trait-based GP GBLUP model was 0.161 and 0.259 improving by 6.62 and 4.44%, respectively, compared to the corresponding single-trait-based models. The identified significantly linked SNP markers, associated putative genes, and developed GP models could potentially facilitate breeding programs targeting to improve the overall genetic gain of wheat breeding for grain yield and biofortification of micronutrients via marker-assisted (MAS) and genomic selection (GS) methods

Genome-Wide Association Analysis and Genomic Prediction for Adult-Plant Resistance to Septoria Tritici Blotch and Powdery Mildew in Winter Wheat

Septoria tritici blotch (STB) caused by the fungal pathogen Zymoseptoria tritici and powdery mildew (PM) caused by Blumeria graminis f.sp tritici (Bgt) are among the forefront foliar diseases of wheat that lead to a significant loss of grain yield and quality. Resistance breeding aimed at developing varieties with inherent resistance to STB and PM diseases has been the most sustainable and environment-friendly approach. In this study, 175 winter wheat landraces and historical cultivars originated from the Nordic region were evaluated for adult-plant resistance (APR) to STB and PM in Denmark, Estonia, Lithuania, and Sweden. Genome-wide association study (GWAS) and genomic prediction (GP) were performed based on the adult-plant response to STB and PM in field conditions using 7,401 single-nucleotide polymorphism (SNP) markers generated by 20K SNP chip. Genotype-by-environment interaction was significant for both disease scores. GWAS detected stable and environment-specific quantitative trait locis (QTLs) on chromosomes 1A, 1B, 1D, 2B, 3B, 4A, 5A, 6A, and 6B for STB and 2A, 2D, 3A, 4B, 5A, 6B, 7A, and 7B for PM adult-plant disease resistance. GP accuracy was improved when assisted with QTL from GWAS as a fixed effect. The GWAS-assisted GP accuracy ranged within 0.53-0.75 and 0.36-0.83 for STB and PM, respectively, across the tested environments. This study highlights that landraces and historical cultivars are a valuable source of APR to STB and PM. Such germplasm could be used to identify and introgress novel resistance genes to modern breeding lines

Multi-model genome-wide association and genomic prediction analysis of 16 agronomic, physiological and quality related traits in ICARDA spring wheat

Identification and exploration of the genetic architecture of traits related to yield, quality, and drought and heat tolerance is important for yield and quality improvement of wheat through marker-assisted selection. One hundred and ninety-two spring wheat genotypes were tested at two heat-stress locations in Sudan (Wad Medani and Dongula), a drought stress site in Morocco (Marchouch) and a site with high yield potential in Egypt (Sids) in replicated trials during the 2015-2016 and 2016-2017 cropping seasons. A total of 10,577 single nucleotide polymorphism markers identified from the 15 K wheat SNP assay were used in a genome-wide association (GWA) study and genomic prediction for 16 phenotypic traits related to yield, quality and drought and heat tolerance. Significant marker-trait associations were detected across GWAS models for all traits. Most detected marker-trait associations (MTAs) were environment-specific, signifying the presence of high quantitative trait loci-by-environment (QTL x E) interaction. Chromosome arm 5AL had significant multi-model MTAs for grain yield and yield-related traits at the heat-stress locations. Highly significant QTLs were detected on chromosome 2D for waxiness. Homoeologous group 2 and 6 chromosomes were with significant MTAs for grain protein content, gluten content, alveograph strength and Zeleny sedimentation test while chromosome arm 3BL was significant for both Z and W traits. Genomic prediction analysis with ridge regression-best linear unbiased prediction model estimated the breeding values of the studied traits with prediction accuracies ranging from 0.16 for leaf rolling to 0.72 for peduncle length. The identified QTLs could be targeted for marker-assisted selection or further studies aimed at fine mapping and cloning the causative genes and detecting favorable haplotypes with positive effects for agronomic, physiological or quality-related traits

Tuberculosis Laboratory Diagnosis Quality Assurance among Public Health Facilities in West Amhara Region, Ethiopia.

Reliable smear microscopy is an important component of Directly Observed Treatment Scheme (DOTS) strategy for TB control program in countries with limited resources. Despite external quality assessment is established in Ethiopia, there is lower TB detection rate (48%) in Amhara region compared to the World Health Organization (WHO) estimate (70%). This highlights the quality of smear microscopy needs to be evaluated. Therefore, the aim of this study was to assess the quality of sputum smear microscopy performance among health center laboratories in West Amhara region, Ethiopia.A cross sectional study was conducted from July 08, 2013 to July 07, 2014. Data were collected from 201 public health center laboratories using a structured questionnaire. Slides were collected based on Lot Quality Assurance Sampling (LQAS) method and rechecked blindly by trained laboratory technologists. The data were entered into EPI info V.7 and smear quality indicators and AFB results were analyzed by SPSS version 20.Among 201 laboratories enrolled in this study, 47 (23.4%) laboratories had major errors. Forty one (20.4%) laboratories had a total of 67 false negative and 29 (14.4%) laboratories had a total of 68 false positive results. Specimen quality, smear thickness and evenness were found poor in 134 (66.7%), 133 (66.2%) and 126 (62.7%) laboratories, respectively. Unavailability of microscope lens cleaning solution (AOR: 2.90; 95% CI: 1.25-6.75; P: 0.013) and dirty smears (AOR: 2.65; 95% CI: 1.14-6.18; P: 0.024) were correlated with false negative results whereas no previous EQA participation (AOR: 3.43; 95% CI: 1. 39-8.45; P: 0.007) was associated with false positive results.The performance of health facilities for sputum smear microscopy was relatively poor in West Amhara region. Hence, strengthening the EQA program and technical support on sputum smear microscopy are recommended to ensure quality tuberculosis diagnostic service

Analysis of malaria surveillance data in Ethiopia: what can be learned from the Integrated Disease Surveillance and Response System?

Background\ud Routine malaria surveillance data is useful for assessing incidence and trends over time, and in stratification for targeting of malaria control. The reporting completeness and potential bias of such data needs assessment.\ud \ud Methods\ud Data on 17 malaria indicators were extracted from the Integrated Disease Surveillance and Response System database for July 2004 to June 2009 (Ethiopian calendar reporting years 1997 to 2001). Reporting units were standardized over time with 2007 census populations. The data were analysed to show reporting completeness, variation in risk by reporting unit, and incidence trends for malaria indicators.\ud \ud Results\ud Reporting completeness, estimated as product of unit-month and health facility reporting, was over 80% until 2009, when it fell to 56% during a period of reorganization in the Ministry of Health. Nationally the average estimated annual incidence of reported total malaria for the calendar years 2005 to 2008 was 23.4 per 1000 persons, and of confirmed malaria was 7.6 per 1,000, with no clear decline in out-patient cases over the time period. Reported malaria in-patient admissions and deaths (averaging 6.4 per 10,000 and 2.3 per 100,000 per year respectively) declined threefold between 2005 and 2009, as did admissions and deaths reported as malaria with severe anaemia. Only 8 of 86 reporting units had average annual estimated incidence of confirmed malaria above 20 per 1,000 persons, while 26 units were consistently below five reported cases per 1,000 persons per year.\ud \ud Conclusion\ud The Integrated Disease Surveillance and Response System functioned well over the time period mid 2004 to the end of 2008. The data suggest that the scale up of interventions has had considerable impact on malaria in-patient cases and mortality, as reported from health centres and hospitals. These trends must be regarded as relative (over space and time) rather than absolute. The data can be used to stratify areas for improved targeting of control efforts to steadily reduce incidence. They also provide a baseline of incidence estimates against which to gauge future progress towards elimination. Inclusion of climate information over this time period and extension of the dataset to more years is needed to clarify the impact of control measures compared to natural cycles on malaria

Performance of sputum smears microscopy in West Amhara Region, 2014.

<p>HFN: High False Negative; HFP: High False Positive; LFP: Low False Positive; LFN: Low False Negative; QE: Quantification Error.</p

General characteristics of Laboratories in West Amhara region, 2014.

<p>TB: tuberculosis; EQA: External Quality Assessment; DEE: Diethyl Ether.</p><p>General characteristics of Laboratories in West Amhara region, 2014.</p