Molecular marker assisted breeding and genome composition analysis of Zhengmai 7698, an elite winter wheat cultivar

Genome-wide association study and expression of candidate genes for Fe and Zn concentration in sorghum grains

Sorghum germplasm showed grain Fe and Zn genetic variability, but a few varieties were biofortified with these minerals. This work contributes to narrowing this gap. Fe and Zn concentrations along with 55,068 high-quality GBS SNP data from 140 sorghum accessions were used in this study. Both micronutrients exhibited good variability with respective ranges of 22.09-52.55 ppm and 17.92-43.16 ppm. Significant marker-trait associations were identified on chromosomes 1, 3, and 5. Two major effect SNPs (S01_72265728 and S05_58213541) explained 35% and 32% of Fe and Zn phenotypic variance, respectively. The SNP S01_72265728 was identified in the cytochrome P450 gene and showed a positive effect on Fe accumulation in the kernel, while S05_58213541 was intergenic near Sobic.005G134800 (zinc-binding ribosomal protein) and showed negative effect on Zn. Tissue-specific in silico expression analysis resulted in higher levels of Sobic.003G350800 gene product in several tissues such as leaf, root, flower, panicle, and stem. Sobic.005G188300 and Sobic.001G463800 were expressed moderately at grain maturity and anthesis in leaf, root, panicle, and seed tissues. The candidate genes expressed in leaves, stems, and grains will be targeted to improve grain and stover quality. The haplotypes identified will be useful in forward genetics breeding.

Construction of SNP fingerprint and population genetic analysis of honeysuckle germplasm resources in China

INTRODUCTION

The flower buds of Lonicera japonica Thunb. are widely used in Chinese medicine for their anti-inflammatory properties, and they have played an important role in the fight against SARS COVID-19 and other major epidemics. However, due to the lack of scientific and accurate variety identification methods and national unified standards, scattered and non-standardized management in flower bud production has led to mixed varieties that have caused significant difficulties in the cataloging and preservation of germplasm resources and the identification, promotion, and application of new L. japonica varieties.

METHODS

In this study, we evaluated the population structure, genetic relationships, and genetic fingerprints of 39 germplasm resources of Lonicera in China using simplified genome sequencing technology.

RESULTS

A total of 13,143,268 single nucleotide polymorphisms (SNPs) were identified. Thirty-nine samples of Lonicera were divided into four subgroups, and the population structure and genetic relationships among existing Lonicera germplasm resources were determined using principal component analysis, population structure analysis, and phylogenetic tree analysis. Through several stringent selection criteria, 15 additional streamlined, high-quality DNA fingerprints were filtered out of the validated 50 SNP loci and verified as being able to effectively identify the 39 Lonicera varieties.

DISCUSSION

To our knowledge, this is the first comprehensive study measuring the diversity and population structure of a large collection of Lonicera varieties in China. These results have greatly broadened our understanding of the diversity, phylogeny, and population structure of Lonicera. The results may enhance the future analysis of genetic diversity, species identification, property rights disputes, and molecular breeding by providing a scientific basis and reference data for these efforts.

Quantitative trait loci associated with straighthead-resistance used for marker assisted selection in rice (Oryza sativa L.) RIL populations

Straighthead is a physiological disorder of rice (Oryza sativa L.) that causes dramatic yield loss in susceptible cultivars. This disorder is found worldwide and is reported to increasingly occur in the southern United States. Genetic resistance breeding has been considered as one of the most efficient methods for straighthead prevention because the traditional prevention method wastes water and costs labor. In this study, we analyzed the genetic effects of five straighthead quantitative trait loci (QTLs), namely, AP3858-1 (qSH-8), RM225 (qSH-6), RM2 (qSH-7), RM206 (qSH-11), and RM282 (qSH-3), on the recombinant inbred lines (RILs) developed from Jing185/Cocodrie and Zhe733/R312 populations using our five previously identified markers linked to these QTLs. As a result, recombinant inbred lines (RILs) with four resistant alleles at the four loci (AP3858-1, RM225, RM2, and RM206) exhibited the highest straighthead resistance. This result suggests that the four markers could be efficiently used to select the straighthead-resistant recombinant inbred lines (RILs). Furthermore, by using AP3858-1, we successfully obtained five straighthead-resistant recombinant inbred lines (RILs) with more than 50% genetic similarity to Cocodrie. These markers and recombinant inbred lines (RILs) can be used for future straighthead resistance breeding through marker-assisted selection.

A GBS-Based GWAS Analysis of Leaf and Stripe Rust Resistance in Diverse Pre-Breeding Germplasm of Bread Wheat (Triticum aestivum L.)

Yellow (YR) and leaf (LR) rusts caused by Puccinia striiformis f. sp. tritici (Pst) and Puccinia triticina, respectively, are of utmost importance to wheat producers because of their qualitative and quantitative effect on yield. The search for new loci resistant to both rusts is an ongoing challenge faced by plant breeders and pathologists. Our investigation was conducted on a subset of 168 pre-breeding lines (PBLs) to identify the resistant germplasm against the prevalent local races of LR and YR under field conditions followed by its genetic mapping. Our analysis revealed a range of phenotypic responses towards both rusts. We identified 28 wheat lines with immune response and 85 resistant wheat genotypes against LR, whereas there were only eight immune and 52 resistant genotypes against YR. A GWAS (genome-wide association study) identified 190 marker-trait associations (MTAs), where 120 were specific to LR and 70 were specific to YR. These MTAs were confined to 86 quantitative trait loci (QTLs), where 50 QTLs carried MTAs associated with only LR, 29 QTLs carried MTAs associated with YR, and seven QTLs carried MTAs associated with both LR and YR. Possible candidate genes at the site of these QTLs are discussed. Overall, 70 PBLs carried all seven LR/YR QTLs. Furthermore, there were five PBLs with less than five scores for both LR and YR carrying positive alleles of all seven YR/LR QTLs, which are fit to be included in a breeding program for rust resistance induction.

Association of the Recessive Allele vrn-D1 With Winter Frost Tolerance in Bread Wheat

Winter frost has been considered the primary limiting factor in wheat production. Shimai 12 is an elite wheat cultivar grown in central and southern Hebei province of China, but sensitive to winter frost. In this study, the winter frost tolerant cultivar Lunxuan 103 was bred by introducing the recessive allele vrn-D1 from winter wheat Shijiazhuang 8 (frost tolerance) into Shimai 12 using marker-assisted selection (MAS). Different from Shimai 12, Lunxuan 103 exhibited a winter growth habit with strong winter frost tolerance. In the Shimai 12 × Shijiazhuang 8 population, the winter progenies (vrn-D1vrn-D1) had significantly lower winter-killed seedling/tiller rates than spring progenies (Vrn-D1aVrn-D1a), and the consistent result was observed in an association population. Winter frost damage caused a significant decrease in grain yield and spike number/m2 in Shimai 12, but not in Lunxuan 103 and Shijiazhuang 8. The time-course expression analysis showed that the transcript accumulation levels of the cold-responsive genes were higher in Lunxuan 103 and Shijiazhuang 8 than in Shimai 12. Lunxuan 103 possessed the same alleles as its parents in the loci for plant height, vernalization, and photoperiod, except for the vernalization gene Vrn-D1. An analysis of genomic composition showed that the two parents contributed similar proportions of genetic compositions to Lunxuan 103. This study provides an example of the improvement of winter frost tolerance by introducing the recessive vernalization gene in bread wheat.

Genomics-assisted breeding for successful development of multiple-stress-tolerant, climate-smart rice for southern and southeastern Asia

Rice (Oryza sativa L.) in rainfed marginal environments is prone to multiple abiotic and biotic stresses, which can occur in combination in a single cropping season and adversely affect rice growth and yield. The present study was undertaken to develop high-yielding, climate-resilient rice that can provide tolerance to multiple biotic and abiotic stresses. An assembled first-crossing scheme was employed to transfer 15 quantitative trait loci (QTL) and genes-qDTY_1.1 , qDTY_2.1 , qDTY_3.1 , qDTY_12.1 (drought), Sub1 (submergence), Gm4 (gall midge), Pi9, Pita2 (blast), Bph3, Bph17 (brown plant hoppers), Xa4, xa5, xa13, Xa21, and Xa23 (bacterial leaf blight)-from eight different parents using genomics-assisted breeding. A funnel mating design was employed to assemble all the targeted QTL and genes into a high-yielding breeding line IR 91648-B-1-B-3-1. Gene-based linked markers were used in each generation from intercrossing to the F₆ generation for tracking the presence of desirable alleles of targeted QTL and genes. Single-plant selections were performed from F₂ onwards to select desirable recombinants possessing alleles of interest with suitable phenotypes. Phenotyping of 95 homozygous F₆ lines carrying six to 10 QTL and genes was performed for nonstress, reproductive-stage (RS) drought, blast, bacterial leaf blight (BLB), gall midge (GM), and for grain quality parameters such as chalkiness, amylose content (AC), gelatinization temperature (GT), and head rice recovery (HRR). Finally, 56 F₇ homozygous lines were found promising for multiple-location evaluation for grain yield (GY) and other traits. These multiple-stress-tolerant lines with the desired grain quality profiling can be targeted for varietal release in southern and southeastern Asia through national release systems.

SNP and Haplotype-Based Genomic Selection of Quantitative Traits in Eucalyptus globulus

Eucalyptus globulus (Labill.) is one of the most important cultivated eucalypts in temperate and subtropical regions and has been successfully subjected to intensive breeding. In this study, Bayesian genomic models that include the effects of haplotype and single nucleotide polymorphisms (SNP) were assessed to predict quantitative traits related to wood quality and tree growth in a 6-year-old breeding population. To this end, the following markers were considered: (a) ~14 K SNP markers (SNP), (b) ~3 K haplotypes (HAP), and (c) haplotypes and SNPs that were not assigned to a haplotype (HAP-SNP). Predictive ability values (PA) were dependent on the genomic prediction models and markers. On average, Bayesian ridge regression (BRR) and Bayes C had the highest PA for the majority of traits. Notably, genomic models that included the haplotype effect (either HAP or HAP-SNP) significantly increased the PA of low-heritability traits. For instance, BRR based on HAP had the highest PA (0.58) for stem straightness. Consistently, the heritability estimates from genomic models were higher than the pedigree-based estimates for these traits. The results provide additional perspectives for the implementation of genomic selection in Eucalyptus breeding programs, which could be especially beneficial for improving traits with low heritability.