Residual effect of defeated stripe rust resistance genes/QTLs in bread wheat against prevalent pathotypes of Puccinia striiformis f. sp. tritici

Integrated genome-wide association and transcriptomic analysis to identify receptor kinase genes to stripe rust resistance in wheat germplasm from southwestern China

Stripe rust of wheat, caused by Puccinia striiformis f. sp. tritici (Pst), is one of the most important diseases of wheat worldwide. Identification of new and elite Pst-resistance loci or genes has the potential to enhance overall resistance to this pathogen. Here, we conducted an integrated genome-wide association study (GWAS) and transcriptomic analysis to screen for loci associated with resistance to stripe rust in 335 accessions from Yunnan, including 311 landraces and 24 cultivars. Based on the environmental phenotype, we identified 113 protein kinases significantly associated with Pst resistance using mixed linear model (MLM) and generalized linear model (GLM) models. Transcriptomic analysis revealed that 52 of 113 protein kinases identified by GWAS were up and down regulated in response to Pst infection. Among these genes, a total of 15 receptor kinase genes were identified associated with Pst resistance. 11 candidate genes were newly discovered in Yunnan wheat germplasm. Our results revealed that resistance alleles to stripe rust were accumulated in Yunnan wheat germplasm, implying direct or indirect selection for improving stripe rust resistance in elite wheat breeding programs.

Fine mapping of Ae-Ps4.5, a major locus for resistance to pathotype III of Aphanomyces euteiches in pea

KEY MESSAGE

QTL mapping and recombinant screening confirmed the major effect of QTL Ae-Ps4.5 on pea resistance to pathotype III of Aphanomyces euteiches and fine-mapped the QTL to a 3.06-Mb interval. Aphanomyces root rot, caused by Aphanomyces euteiches, is the most important disease of pea (Pisum sativum L.) worldwide. The development of pea-resistant varieties is a major challenge to control the disease. Previous linkage studies identified seven main resistance quantitative trait loci (QTL), including the QTL Ae-Ps4.5 associated with partial resistance in US nurseries infested by the pea pathotype III of A. euteiches. This study aimed to confirm the major effect of Ae-Ps4.5 on A. euteiches pathotype III, refine its interval, and identify candidate genes underlying the QTL. QTL mapping on an updated genetic map from the Puget × 90-2079 pea recombinant inbred line population identified Ae-Ps4.5 in a 0.8-cM confidence interval with a high effect (R2 = 89%) for resistance to the Ae109 reference strain of A. euteiches (pathotype III) under controlled conditions. However, the QTL mapping did not detect Ae-Ps4.5 for resistance to the RB84 reference strain of A. euteiches (pathotype I). Screening 224-pea BC5F2 plant progeny derived from three near-isogenic lines (NILs) carrying the 90-2079 allele at Ae-Ps4.5 in the Puget genetic background with 26 SNP markers identified 15 NILs showing recombination in the QTL interval. Phenotyping of the recombinant lines for resistance to the Ae109 strain of A. euteiches reduced the QTL to a physical interval of 3.06 Mb, containing 50 putative annotated genes on the Caméor pea genome V1a among which three candidate genes highlighted. This study provides closely linked SNP markers and putative candidate genes to accelerate pea breeding for resistant varieties to Aphanomyces root rot.

Quantifying microcyte and macrocyte percentages in archived red blood cell volume histogram images

INTRODUCTION

We sought to quantify percentages of microcytes and macrocytes in archived automated hematology analyzer (AHA) red blood cell (RBC) volume histogram images.

METHODS

In preliminary studies, we demonstrated that an on-line application of Gauss' area formula (SketchAndCalc™) measured percentage areas of 20 segments under a computer-generated normal distribution curve (-3.0 standard deviations [SD] to +3.0 SD) with accuracy and precision (Pearson's correlation of measured areas with corresponding theoretical areas r [20] = 0.9962 [p < 0.0001]). Thus, we used SketchAndCalc™ to quantify percentages of microcytes (50-80 fL) and macrocytes (110-200 fL) in archived AHA histogram images in women with previously untreated iron-deficiency anemia (IDA) and previously untreated hemochromatosis.

RESULTS

Median microcyte percentages in 13 women with IDA and 13 women with hemochromatosis were 63.6% (range 13.5-76.8) and 6.7% (range 3.4-24.8), respectively (p < 0.0001). Mean macrocyte percentages in women with IDA and hemochromatosis were 8.8% ± 6.1 SD and 33.8% ± 11.7 SD, respectively (p < 0.0001). Spearman's correlations of microcyte percentages with macrocyte percentages, mean corpuscular volume, and mean corpuscular hemoglobin in 26 women were rs [26] = -0.9485, rs [26] = -0.9641, and rs [26] = -0.9036, respectively (each p < 0.0001).

CONCLUSIONS

This method of quantifying microcyte and macrocyte percentages could enable other studies of RBC volume subpopulations in archived AHA histogram images.