Dynamic Quantitative Trait Loci Mapping for Plant Height in Recombinant Inbred Line Population of Upland Cotton

Abstract

Plant height (PH) is a key plant architecture trait for improving the biological productivity of cotton. Ideal PH of cotton is conducive to lodging resistance and mechanized harvesting. To detect quantitative trait loci (QTL) and candidate genes of PH in cotton, a genetic map was constructed with a recombinant inbred line (RIL) population of upland cotton. PH phenotype data under nine environments and three best linear unbiased predictions (BLUPs) were used for QTL analyses. Based on restriction-site-associated DNA sequence (RAD-seq), the genetic map contained 5,850 single-nucleotide polymorphism (SNP) markers, covering 2,747.12 cM with an average genetic distance of 0.47 cM. Thirty-seven unconditional QTL explaining 1.03–12.50% of phenotypic variance, including four major QTL and seven stable QTL, were identified. Twenty-eight conditional QTL explaining 3.27–28.87% of phenotypic variance, including 1 major QTL, were identified. Importantly, five QTL, including 4 stable QTL, were both unconditional and conditional QTL. Among the 60 PH QTL (including 39 newly identified), none of them were involved in the whole period of PH growth, indicating that QTL related to cotton PH development have dynamic expression characteristics. Based on the functional annotation of Arabidopsis homologous genes and transcriptome data of upland cotton TM-1, 14 candidate genes were predicted within 10 QTL. Our research provides valuable information for understanding the genetic mechanism of PH development, which also increases the economic production of cotton.

Dynamic QTL mapping revealed primarily the genetic structure of photosynthetic traits in castor (Ricinus communis L.)

“…Confidence intervals for all QTLs were determined at 95% confidence degree. The adjacent QTLs with overlapped confidence intervals and positions within 5 cM were regarded as the same QTL 50 , 51 . The QTLs underlying the same trait detected simultaneously in different populations or at different stages were defined as the stable QTL.…”

“…QTLs were named according to the rule of “q + trait abbreviation + linkage group serial number + QTL serial number on the linkage group”. In order to distinguish the QTLs identified in different populations, the capitals F and B were prefixed the QTLs detected in populations F 2 and BC 1 respectively, no any prefix before stable QTLs 51 . The co-located QTLs were additionally named as “q + Co-locatedQTL + linkage group serial number + QTL serial number”.…”

Canopy Laser Interception Compensation Mechanism—UAV LiDAR Precise Monitoring Method for Cotton Height

“…The results of this study have important practical implications for improving the efficiency of cotton breeding research, especially in breeding experiments involving thousands of samples. The data for each community in traditional breeding experiments are usually determined by manual sampling [4], which requires many labor costs, and the results are greatly affected by human factors. The method used in this study can generate a mean value of the overall height of each community, which is more representative than manual sampling results (Figure 19), and the data collection efficiency is multiplied.…”

“…Cotton is the main raw material of the textile industry and an important cash crop. Plant height is a significant phenotypic trait of cotton that serves as a crucial predictor in yield estimation [2], biomass estimation [3], and lodging resistance [4]. Therefore, it is of great significance to obtain the height of cotton crops in a large area.…”