AI Article Synopsis

Article Abstract

To identify the genomic regions for yield and NUE of rice genotypes and lines with promising yield under low N, a recombinant inbred population (RIL) developed between BPT5204 (a mega variety known for its quality) and PTB1 (variety with high NUE) was evaluated for consecutive wet and dry seasons under low nitrogen (LN) and recommended nitrogen (RN) field conditions. A set of 291 RILs were characterized for 24 traits related to leaf, agro-morphological, yield, N content and nitrogen use efficiency indices. More than 50 RILs were found promising with grain yield >10 g under LN. Parental polymorphism survey with 297 SSRs and selective genotyping revealed five genomic regions associated with yield under LN, which were further saturated with polymorphic SSRs. Thirteen promising SSRs were identified out of 144 marker trait associations under LN using single marker analysis. Composite interval mapping showed 37 QTL under LN with five pleiotropic QTL. A major stable pleiotropic (RM13201-RM13209) from PTB1 spanning 825.4 kb region associated with straw N % (SNP) in both treatments across seasons and yield and yield related traits in WS appears to be promising for the MAS. Another major QTL (RM13181-RM13201) was found to be associated with only relative trait parameters of biomass, grain and grain nitrogen. These two major pleiotropic QTL (RM13201-RM13209 and RM13181-RM13201) on chromosome 2 were characterized for their positive allele effect and could be deployed for the development of rice varieties with NUE.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7575116PMC
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0240854PLOS

Publication Analysis

Top Keywords

pleiotropic qtl
12
major pleiotropic
8
yield
8
nitrogen field
8
field conditions
8
genomic regions
8
nitrogen
6
qtl
5
major
4
qtl identified
4

Similar Publications

Quantitative trait loci (QTL) are genomic regions that influence essential traits in livestock. Understanding QTL distribution and density across species' genomes is crucial for animal genetics research. This study explored the QTLome of cattle, pigs, sheep, and chickens by analyzing QTL distribution and evaluating the correlation between QTL, gene density, and chromosome size with the aim to identify QTL-enriched genomic regions.

View Article and Find Full Text PDF

Unravelling the genetic architecture of soybean tofu quality traits.

Mol Breed

January 2025

Institute of Plant Breeding, Seed Science and Population Genetics, University of Hohenheim, 70599 Stuttgart, Germany.

Unlabelled: Tofu is a popular soybean ( (L.) Merr.) food with a long tradition in Asia and rising popularity worldwide, including Central Europe.

View Article and Find Full Text PDF

Meta-assembly of genomic associations to identify cattle fat depot candidate genes and pleiotropic effects.

BMC Genomics

December 2024

School of Animal and Veterinary Sciences, The University of Adelaide, Roseworthy Campus, Roseworthy, South Australia, 5371, Australia.

Background: Fat traits in cattle are considered important due to their contribution to beef eating quality and carcass economic value. Discovering the genes controlling fat traits in cattle will enable better selection of these traits, but identifying these genes in individual experiments has proven difficult. Compared to individual experiments, meta-analyses allow greater statistical power for detecting quantitative trait loci and identifying genes that influence single and multiple economically important fat traits.

View Article and Find Full Text PDF

The present study investigated the linkage between days to flowering (DTF) and growth habit (GH) in pigeonpea using QTL mapping, QTL-seq, and GWAS approaches. The linkage map developed here is the largest to date, spanning 1825.56 cM with 7987 SNP markers.

View Article and Find Full Text PDF

Background: Antifungal drug resistance presents one of the major concerns for global public health, and hybridization allows the development of high fitness organisms that can better survive in restrictive conditions or in presence of antifungal agents. Hence, understanding how allelic variation can influence antifungal susceptibility in hybrid organisms is important for the development of targeted treatments. Here, we exploited recent advances in multigenerational breeding of hemiascomycete hybrids to study the impact of hybridisation on antifungal resistance and identify quantitative trait loci responsible for the phenotype.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!