Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 5 de 5
Filtrar
Mais filtros

Base de dados
Ano de publicação
Tipo de documento
País de afiliação
Intervalo de ano de publicação
1.
Physiol Plant ; 176(3): e14396, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38887929

RESUMO

Phosphorus (P) is a crucial macronutrient required for normal plant growth. Its effective uptake from the soil is a trait of agronomic importance. Natural variation in maize (339 accessions) root traits, namely root length and number of primary, seminal, and crown roots, root and shoot phosphate (Pi) contents, and root-to-shoot Pi translocation (root: shoot Pi) under normal (control, 40 ppm) and low phosphate (LP, 1 ppm) conditions, were used for genome-wide association studies (GWAS). The Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) model of GWAS provided 23 single nucleotide polymorphisms (SNPs) and 12 relevant candidate genes putatively linked with root Pi, root: shoot Pi, and crown root number (CRN) under LP. The DNA-protein interaction analysis of Zm00001d002842, Zm00001d002837, Zm00001d002843 for root Pi, and Zm00001d044312, Zm00001d045550, Zm00001d025915, Zm00001d044313, Zm00001d051842 for root: shoot Pi, and Zm00001d031561, Zm00001d001803, and Zm00001d001804 for CRN showed the presence of potential binding sites of key transcription factors like MYB62, bZIP11, ARF4, ARF7, ARF10 and ARF16 known for induction/suppression of phosphate starvation response (PHR). The in-silico RNA-seq analysis revealed up or down-regulation of candidate genes along with key transcription factors of PHR, while Uniprot analysis provided genetic relatedness. Candidate genes that may play a role in P uptake and root-to-shoot Pi translocation under LP are proposed using common PHR signaling components like MYB62, ARF4, ARF7, ARF10, ARF16, and bZIP11 to induce changes in root growth in maize. Candidate genes may be used to improve low P tolerance in maize using the CRISPR strategy.


Assuntos
Estudo de Associação Genômica Ampla , Fosfatos , Raízes de Plantas , Polimorfismo de Nucleotídeo Único , Zea mays , Zea mays/genética , Zea mays/crescimento & desenvolvimento , Zea mays/metabolismo , Raízes de Plantas/genética , Raízes de Plantas/crescimento & desenvolvimento , Raízes de Plantas/metabolismo , Polimorfismo de Nucleotídeo Único/genética , Fosfatos/metabolismo , Fosfatos/deficiência , Regulação da Expressão Gênica de Plantas , Proteínas de Plantas/genética , Proteínas de Plantas/metabolismo , Desequilíbrio de Ligação/genética
2.
Physiol Mol Biol Plants ; 30(9): 1449-1462, 2024 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-39310699

RESUMO

Seed size is an important agronomic trait that indicates seed quality. In legumes, pods with equal and larger seeds remain the first preference of farmers and consumers. Genetic understanding related to seed size including seed allometric traits has been limited in the case of peas. To fill this void the findings presented here used the genome-wide association studies (GWAS) to identify novel candidate gene(s) putatively linked with seed size in Pisum sativum L. The study was conducted on 240 Pea Single Plant Plus Collection (PSPPC) panels of pea germplasm. Allometric traits measured included seed_length, seed_width, seed_thickness, seed_volume, seed_biomass, and seed_biomass by volume (SB_V). GWAS was performed using the Genome Association and Prediction Integrated Tool (GAPIT) on R-studio. The Bayesian information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) model provided significant single nucleotide polymorphisms (SNPs) linked with all the seed allometric traits. When analyzed the genomic regions of these SNPs provided a list of candidate genes that may be related to seed size. The present study thus provides a list of significant SNPs and relevant genes viz. Psat2g072000 for seed_length, Psat4g104320 for seed_width, Psat6g125800 and Psat6g125840 for seed_thickness, Psat6g228320 for seed_volume, Psat2g143920 for seed_biomass, and Psat2g120400 for SB_V which may prove useful in the improvement of pea seed size using breeding programs or CRISPR intervention. Understanding the genetic basis of seed size could lead to crop development with desirable seed characteristics, such as equal and larger-sized seeds with maximum yield and higher nutritional content. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-024-01499-6.

3.
Physiol Mol Biol Plants ; 28(6): 1311-1321, 2022 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-35910442

RESUMO

The phenotyping of plant roots is a challenging task and poses a major lacuna in plant root research. Roots rhizospheric zone is affected by several environmental cues among which salinity, drought, heavy metal and soil pH are key players. Among biological factors, fungal, nematode and bacterial interactions with roots are vital for improving nutrient uptake efficiency in plants. The subterranean nature of a plant root and the limited number of approaches for root phenotyping offers a great challenge to the plant breeders to select a desirable root trait under different stress conditions. Identification of key root traits can provide a basic understanding for generating crop plants with enhanced ability to withstand various biotic or abiotic stresses. For instance, crops with improved soil exploration potential, phosphate uptake efficiency, water use efficiency and others. Laboratory methods such as hydroponics, rhizotron, rhizoslide and luminescence observatory for roots do not provide precise and desired root quantification attributes. Though 3D imaging by X-ray computed tomography (X-ray-CT) and magnetic resonance imaging techniques are complex, however, it provides the most applicable and practically relevant data for quantifying root system architecture traits. This review outlines the current developments in root studies including recent approaches viz. X-ray-CT, MRI, thermal infrared imaging and minirhizotron. Although root phenotyping is a laborious procedure, it offers multiple advantages by removing discrepancies and providing the actual practical significance of plant roots for breeding programs.

4.
Plants (Basel) ; 13(3)2024 Feb 05.
Artigo em Inglês | MEDLINE | ID: mdl-38337989

RESUMO

Phosphate (P) is a crucial macronutrient for normal plant growth and development. The P availability in soils is a limitation factor, and understanding genetic factors playing roles in plant adaptation for improving P uptake is of great biological importance. Genome-wide association studies (GWAS) have become indispensable tools in unraveling the genetic basis of complex traits in various plant species. In this study, a comprehensive GWAS was conducted on diverse tomato (Solanum lycopersicum L.) accessions grown under normal and low P conditions for two weeks. Plant traits such as shoot height, primary root length, plant biomass, shoot inorganic content (SiP), and root inorganic content (RiP) were measured. Among several models of GWAS tested, the Bayesian-information and linkage disequilibrium iteratively nested keyway (BLINK) models were used for the identification of single nucleotide polymorphisms (SNPs). Among all the traits analyzed, significantly associated SNPs were recorded for PB, i.e., 1 SNP (SSL4.0CH10_49261145) under control P, SiP, i.e., 1 SNP (SSL4.0CH08_58433186) under control P and 1 SNP (SSL4.0CH08_51271168) under low P and RiP i.e., 2 SNPs (SSL4.0CH04_37267952 and SSL4.0CH09_4609062) under control P and 1 SNP (SSL4.0CH09_3930922) under low P condition. The identified SNPs served as genetic markers pinpointing regions of the tomato genome linked to P-responsive traits. The novel candidate genes associated with the identified SNPs were further analyzed for their protein-protein interactions using STRING. The study provided novel candidate genes, viz. Solyc10g050370 for PB under control, Solyc08g062490, and Solyc08g062500 for SiP and Solyc09g010450, Solyc09g010460, Solyc09g010690, and Solyc09g010710 for RiP under low P condition. These findings offer a glimpse into the genetic diversity of tomato accessions' responses to P uptake, highlighting the potential for tailored breeding programs to develop P-efficient tomato varieties that could adapt to varying soil conditions, making them crucial for sustainable agriculture and addressing global challenges, such as soil depletion and food security.

5.
Research (Wash D C) ; 7: 0491, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-39371687

RESUMO

Precise and timely detection of a crop's nutrient requirement will play a crucial role in assuring optimum plant growth and crop yield. The present study introduces a reliable deep learning platform called "Deep Learning-Crop Platform" (DL-CRoP) for the identification of some commercially grown plants and their nutrient requirements using leaf, stem, and root images using a convolutional neural network (CNN). It extracts intrinsic feature patterns through hierarchical mapping and provides remarkable outcomes in identification tasks. The DL-CRoP platform is trained on the plant image dataset, namely, Jammu University-Botany Image Database (JU-BID), available at https://github.com/urfanbutt. The findings demonstrate implementation of DL-CRoP-cases A (uses shoot images) and B (uses leaf images) for species identification for Solanum lycopersicum (tomato), Vigna radiata (Vigna), and Zea mays (maize), and cases C (uses leaf images) and D (uses root images) for diagnosis of nitrogen deficiency in maize. The platform achieved a higher rate of accuracy at 80-20, 70-30, and 60-40 splits for all the case studies, compared with established algorithms such as random forest, K-nearest neighbor, support vector machine, AdaBoost, and naïve Bayes. It provides a higher accuracy rate in classification parameters like recall, precision, and F1 score for cases A (90.45%), B (100%), and C (93.21), while a medium-level accuracy of 68.54% for case D. To further improve the accuracy of the platform in case study C, the CNN was modified including a multi-head attention (MHA) block. It resulted in the enhancement of the accuracy of classifying the nitrogen deficiency above 95%. The platform could play an important role in evaluating the health status of crop plants along with a role in precise identification of species. It may be used as a better module for precision crop cultivation under limited nutrient conditions.

SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA