Genetic Analysis of Stripe Rust Resistance in the Chinese Wheat Cultivar Luomai 163 DOI
Zimeng Li,

Chan Yuan,

Shunda Li

и другие.

Plant Disease, Год журнала: 2024, Номер unknown

Опубликована: Июль 26, 2024

Stripe or yellow rust (YR) caused by Puccinia striiformis tritici (Pst) is an important foliar disease affecting wheat production globally. Resistant varieties are the most economically and environmentally effective way to manage this disease. The common winter (Triticum aestivum L.) cultivar Luomai 163 exhibited resistance Pst races CYR32 CYR33 at seedling stage showed a high level of adult plant in field. To understand genetic basis YR cultivar, 142 F 5 recombinant inbred lines (RILs) derived from cross Apav#1 × LM163 both parents were genotyped with 16K SNP array bulked segregant analysis sequencing. detected major gene, YrLM163, associated 1BL.1RS translocation. Additionally, three genes for on chromosome arms 1BL (Lr46/Yr29/Pm39/Sr58), 6BS, 6BL 163, whereas contributed quantitative trait locus (QTL) 2BL. These QTL explained severity variations ranging 6.9 54.8%. kompetitive allele-specific PCR (KASP) markers KASP-2BL, KASP-6BS, KASP-6BL novel loci QYr.hzau-2BL, QYr.hzau-6BS, QYr.hzau-6BL developed validated. QYr.hzau-1BL, QYr.hzau-6BS varying degrees when present individually combination based genotype phenotype panel 570 accessions. Six RILs combining alleles all QTL, showing higher field than severities 10.7 16.0%, germplasm resources breeding programs develop YR-resistant good agronomic traits.

Язык: Английский

Genomics, Phenomics, and Machine Learning in Transforming Plant Research: Advancements and Challenges DOI Creative Commons
Sheikh Mansoor,

E.M.B.M. Karunathilake,

Thai Thanh Tuan

и другие.

Horticultural Plant Journal, Год журнала: 2024, Номер unknown

Опубликована: Фев. 1, 2024

Advances in gene editing and natural genetic variability present significant opportunities to generate novel alleles select sources of variation for horticulture crop improvement. The improvement crops enhance their resilience abiotic stresses new pests due climate change is essential future food security. field genomics has made strides over the past few decades, enabling us sequence analyze entire genomes. However, understanding complex relationship between genes expression phenotypes - observable characteristics an organism requires a deeper phenomics. Phenomics seeks link information with biological processes environmental factors better understand traits diseases. Recent breakthroughs this include development advanced imaging technologies, artificial intelligence algorithms, large-scale data analysis techniques. These tools have enabled explore relationships genotype, phenotype, environment unprecedented detail. This review explores importance phenotypes. Integration efficient high throughput plant phenotyping as well potential machine learning approaches genomic phenomics trait discovery.

Язык: Английский

Процитировано

16
Integrating high‐throughput phenotyping and genome‐wide association studies for enhanced drought resistance and yield prediction in wheat DOI Creative Commons
Zhen Zhang,

Yunfeng Qu,

Feifei Ma

и другие.

New Phytologist, Год журнала: 2024, Номер 243(5), С. 1758 - 1775

Опубликована: Июль 11, 2024

Summary Drought, especially terminal drought, severely limits wheat growth and yield. Understanding the complex mechanisms behind drought response in is essential for developing drought‐resistant varieties. This study aimed to dissect genetic architecture high‐yielding ideotypes under drought. An automated high‐throughput phenotyping platform was used examine 28 392 image‐based digital traits (i‐traits) different conditions during flowering stage of a natural population. Of i‐traits examined, 17 073 were identified as drought‐related. A genome‐wide association (GWAS) 5320 drought‐related significant single‐nucleotide polymorphisms (SNPs) 27 SNP clusters. notable hotspot region controlling tolerance discovered, which TaPP2C6 shown be an important negative regulator response. The tapp2c6 knockout lines exhibited enhanced resistance without yield penalty. haplotype analysis revealed favored allele that significantly correlated with resistance, affirming its potential value breeding programs. We developed advanced prediction model using 24 analyzed by machine learning. In summary, this provides comprehensive insights into ideotype approach rapid wheat.

Язык: Английский

Процитировано

11
3D Reconstruction of Wheat Plants by Integrating Point Cloud Data and Virtual Design Optimization DOI Creative Commons

Wenxuan Gu,

Weiliang Wen, Sheng Wu

и другие.

Agriculture, Год журнала: 2024, Номер 14(3), С. 391 - 391

Опубликована: Фев. 29, 2024

The morphology and structure of wheat plants are intricate, containing numerous tillers, rich details, significant cross-obscuration. Methods effectively reconstructing three-dimensional (3D) models that reflects the varietal architectural differences using measured data is challenging in plant phenomics functional–structural models. This paper proposes a 3D reconstruction technique for integrates point cloud virtual design optimization. approach extracted single stem number, growth position, length, inclination angle from plant. It then built an initial mesh model by integrating phytomer template database with variety resolution. Diverse were subsequently virtually designed iteratively modifying leaf azimuth, based on model. Using as overall constraint setting minimum Chamfer distance between optimization objective, we obtained optimal result through continuous iterative calculation. method was validated 27 winter plants, nine varieties three replicates each. R2 values reconstructed 0.80, 0.73, 0.90, 0.69 height, crown width, area, coverage, respectively. Additionally, Normalized Root Mean Squared Errors (NRMSEs) 0.10, 0.12, 0.08, 0.17, Absolute Percentage (MAPEs) used to investigate vertical spatial distribution clouds ranged 4.95% 17.90%. These results demonstrate exhibits satisfactory consistency data, including phenotype distribution, accurately characteristics architecture utilized cultivars. provides technical support research phenotyping analysis.

Язык: Английский

Процитировано

8
Gene editing and GWAS for digital imaging analysis of wheat grain weight, size and shape are inevitable to enhance the yield DOI
Muhammad Jamil, W.A.M Wan Ahmad,

Muhammad Sanwal

и другие.

Cereal Research Communications, Год журнала: 2025, Номер unknown

Опубликована: Фев. 15, 2025

Язык: Английский

Процитировано

1
Standard Framework Construction of Technology and Equipment for Big Data in Crop Phenomics DOI Creative Commons
Weiliang Wen, Shenghao Gu, Ying Zhang

и другие.

Engineering, Год журнала: 2024, Номер unknown

Опубликована: Июнь 1, 2024

Crop phenomics has rapidly progressed in recent years due to the growing need for crop functional genomics, digital breeding, and smart cultivation. Despite this advancement, lack of standards creation usage technology equipment become a bottleneck, limiting industry's high-quality development. This paper begins with an overview phenotyping industry presents industrial mapping big data phenomics. It analyzes necessity current state constructing standard framework phenotyping. Furthermore, proposes intended organizational structure goals framework. details essentials research development hardware equipment, acquisition, storage management data. Finally, it discusses promoting construction evaluation framework, aiming provide ideas developing

Язык: Английский

Процитировано

3
Advances in Crop Improvement through High-Throughput Phenotyping DOI

J Padhy,

Ratan Sarkar, Sourav Ranjan Mohapatra

и другие.

CABI eBooks, Год журнала: 2025, Номер unknown, С. 194 - 215

Опубликована: Фев. 18, 2025

Язык: Английский

Процитировано

0
Chromatin loops gather targets of upstream regulators together for efficient gene transcription regulation during vernalization in wheat DOI Creative Commons
Yanyan Liu, Xiangdong Xu, Chao He

и другие.

Genome biology, Год журнала: 2024, Номер 25(1)

Опубликована: Дек. 2, 2024

Язык: Английский

Процитировано

2
Evaluation of wheat drought resistance using hyperspectral and chlorophyll fluorescence imaging DOI Creative Commons

Yucun Yang,

Xinran Liu, Yuqing Zhao

и другие.

Plant Physiology and Biochemistry, Год журнала: 2024, Номер 219, С. 109415 - 109415

Опубликована: Дек. 17, 2024

Язык: Английский

Процитировано

2
Integrated VIS/NIR Spectrum and Genome-Wide Association Study for Genetic Dissection of Cellulose Crystallinity in Wheat Stems DOI Open Access
Jianguo Li,

Peimin Zhao,

Liyan Zhao

и другие.

International Journal of Molecular Sciences, Год журнала: 2024, Номер 25(5), С. 3028 - 3028

Опубликована: Март 6, 2024

Cellulose crystallinity is a crucial factor influencing stem strength and, consequently, wheat lodging. However, the genetic dissection of cellulose less reported due to difficulty its measurement. In this study, VIS/NIR spectra and were measured for accession panel with diverse backgrounds. We developed reliable model high determination coefficient (R2) (0.95) residual prediction deviation (RPD) (4.04), enabling rapid screening samples. A GWAS in 326 accessions revealed 14 significant SNPs 13 QTLs. Two candidate genes, TraesCS4B03G0029800 TraesCS5B03G1085500, identified. summary, study establishes an efficient method measurement stems provides basis enhancing lodging resistance wheat.

Язык: Английский

Процитировано

1
Genome-wide association study for seedling heat tolerance under two temperature conditions in bread wheat (Triticum aestivum L.) DOI Creative Commons
Chao Fu, Ying Zhou,

Ankui Liu

и другие.

BMC Plant Biology, Год журнала: 2024, Номер 24(1)

Опубликована: Май 21, 2024

Abstract Background As the greenhouse effect intensifies, global temperatures are steadily increasing, posing a challenge to bread wheat ( Triticum aestivum L.) production. It is imperative comprehend mechanism of high temperature tolerance in and implement breeding programs identify develop heat-tolerant germplasm cultivars. Results To quantitative trait loci (QTL) related heat stress (HST) at seedling stage wheat, panel 253 accessions which were re-sequenced used conduct genome-wide association studies (GWAS) using factored spectrally transformed linear mixed models (FaST-LMM). For most accessions, growth seedlings was found be inhibited under stress. Analysis phenotypic data revealed that conditions, main root length, total shoot length decreased by 47.46%, 49.29%, 15.19%, respectively, compared those normal conditions. However, 17 varieties identified as tolerant germplasm. Through GWAS analysis, 115 QTLs detected both Furthermore, 15 stable QTL-clusters associated with response identified. By combining gene expression, haplotype annotation information within physical intervals QTL-clusters, two novel candidate genes, TraesCS4B03G0152700/TaWRKY74-B TraesCS4B03G0501400/TaSnRK3.15-B , responsive potential regulators HST stage. Conclusions This study conducted detailed genetic analysis successfully genes potentially stage, laying foundation further dissect regulatory underlying Our finding could serve genomic landmarks for aimed improving adaptation face climate change.

Язык: Английский

Процитировано

1