Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

During the last three decades, QTL analysis in wheat has been conducted for a variety of individual traits, so that thousands of QTL along with the linked markers, their genetic positions and contribution to phenotypic variation (PV) for concerned traits are now known. However, no exhaustive database for wheat QTL is currently available at a single platform. Therefore, the present database was prepared which is an exhaustive information resource for wheat QTL data from the published literature till May, 2020. QTL data from both interval mapping and genome-wide association studies (GWAS) have been included for the following classes of traits: (i) morphological traits, (ii) N and P use efficiency, (iii) traits for biofortification (Fe, K, Se, and Zn contents), (iv) tolerance to abiotic stresses including drought, water logging, heat stress, pre-harvest sprouting and salinity, (v) resistance to biotic stresses including those due to bacterial, fungal, nematode and insects, (vi) quality traits, and (vii) a variety of physiological traits, (viii) developmental traits, and (ix) yield and its related traits. For the preparation of the database, literature was searched for data on QTL/marker-trait associations (MTAs), curated and then assembled in the form of WheatQTLdb. The available information on metaQTL, epistatic QTL and candidate genes, wherever available, is also included in the database. Information on QTL in this WheatQTLdb includes QTL names, traits, associated markers, parental genotypes, crosses/mapping populations, association mapping panels and other useful information. To our knowledge, WheatQTLdb prepared by us is the largest collection of QTL (11,552), epistatic QTL (107) and metaQTL (330) data for hexaploid wheat to be used by geneticists and plant breeders for further studies involving fine mapping, cloning, and marker-assisted selection (MAS) during wheat breeding.

Download full-text PDF

Source
http://dx.doi.org/10.1007/s00438-021-01796-9DOI Listing

Publication Analysis

Top Keywords

qtl
10
traits
10
database wheat
8
wheat qtl
8
qtl data
8
stresses including
8
epistatic qtl
8
wheat
6
database
5
wheatqtldb
4

Similar Publications

Plasma membrane maize Gγ protein MGG4 positively regulates seed size mainly through influencing kernel width.

Plant Cell Rep

September 2025

Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genetics and Physiology, College of Agriculture, Yangzhou University, Yangzhou, 225009, China.

Plasma membrane Gγ protein MGG4, the candidate for maize yield QTL, positively regulates seed size mainly through affecting kernel width.

View Article and Find Full Text PDF

Insulin resistance is a heritable risk factor for many chronic diseases; however, the genetic drivers remain elusive. In seeking these, we performed genetic mapping of insulin sensitivity in 670 chow-fed Diversity Outbred in Australia (DOz) mice and identified a genome-wide significant locus (QTL) on chromosome 8 encompassing 17 defensin genes. By taking a systems genetics approach, we identified alpha-defensin 26 (Defa26) as the causal gene in this region.

View Article and Find Full Text PDF

Global wheat (Triticum aestivum L.) production faces significant challenges due to the destructive nature of leaf (Puccinia triticina; leaf rust [Lr]), stem (Puccinia graminis; stem rust [Sr]), and stripe (Puccinia striiformis; stripe rust [Yr]) rust diseases. Despite ongoing efforts to develop resistant varieties, these diseases remain a persistent challenge due to their highly evolving nature.

View Article and Find Full Text PDF

Systematic Exploration of Potential Druggable Genes for Ischemic Stroke Employing Genome-Wide Mendelian Randomization Analysis.

Brain Behav

September 2025

Department of Thoracic Surgery II, Department of Lung Transplantation, Organ Transplantation Center, the First Hospital of Jilin University, Changchun, China.

Background: Ischemic stroke (IS) treatment remains a significant challenge. This study aimed to identify potential druggable genes for IS using a systematic druggable genome-wide Mendelian Randomization (MR) analysis.

Methods: Two-sample MR analysis was conducted to identify the causal association between potential druggable genes and IS.

View Article and Find Full Text PDF

Legumes are essential for agriculture and food security. Biotic and abiotic stresses pose significant challenges to legume production, lowering productivity levels. Most legumes must be genetically improved by introducing alleles that give pest and disease resistance, abiotic stress adaptability, and high yield potential.

View Article and Find Full Text PDF