Dataset Information

Identification of small effect quantitative trait loci of plant architectural, flowering, and early maturity traits in reciprocal interspecific introgression population in cotton.

ABSTRACT: Plant architecture, flowering time and maturity traits are important determinants of yield and fiber quality of cotton. Genetic dissection of loci determining these yield and quality components is complicated by numerous loci with alleles conferring small differences. Therefore, mapping populations segregating for smaller numbers and sizes of introgressed segments is expected to facilitate dissection of these complex quantitative traits. At an advanced stage in the development of reciprocal advanced backcross populations from crosses between elite Gossypium hirsutum cultivar 'Acala Maxxa' (GH) and G. barbadense 'Pima S6' (GB), we undertook mapping of plant architectural traits, flowering time and maturity. A total of 284 BC₄F₁ and BC₄F₂ progeny rows, 120 in GH and 164 in GB background, were evaluated for phenotype, with only 4 and 3 (of 7) traits showing significant differences among progenies. Genotyping by sequencing yielded 3,186 and 3,026 SNPs, respectively, that revealed a total of 27 QTLs in GH background and 22 in GB, for plant height, days to flowering, residual flowering at maturity and maturity. More than of 90% QTLs identified in both backgrounds had small effects (%PV < 10), supporting the merit of this population structure to reduce background noise and small effect QTLs. Germplasm developed in this study may serve as potential pre-breeding material to develop improved cotton cultivars.

SUBMITTER: Chandnani R

PROVIDER: S-EPMC9433993 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of small effect quantitative trait loci of plant architectural, flowering, and early maturity traits in reciprocal interspecific introgression population in cotton.

Chandnani Rahul R Kim Changsoo C Patel Jinesh D JD Guo Hui H Shehzad Tariq T Wallace Jason G JG He Daohua D Zhang Zhengsheng Z Adhikari Jeevan J Khanal Sameer S Chee Peng W PW Paterson Andrew H AH

Frontiers in plant science 20220818

Plant architecture, flowering time and maturity traits are important determinants of yield and fiber quality of cotton. Genetic dissection of loci determining these yield and quality components is complicated by numerous loci with alleles conferring small differences. Therefore, mapping populations segregating for smaller numbers and sizes of introgressed segments is expected to facilitate dissection of these complex quantitative traits. At an advanced stage in the development of reciprocal adva ...[more]

PMID: 36061803

Similar Datasets

Project description:Key messageBackground-independent (BI) and stably expressed (SE) quantitative trait loci (QTLs) were identified using two sets of introgression lines across multiple environments. Genetic background more greatly affected fiber quality traits than environmental factors. Sixty-one SE-QTLs, including two BI-QTLs, were novel and 48 SE-QTLs, including seven BI-QTLs, were previously reported. Cotton fiber quality traits are controlled by QTLs and are susceptible to environmental influence. Fiber quality improvement is an essential goal in cotton breeding but is hindered by limited knowledge of the genetic basis of fiber quality traits. In this study, two sets of introgression lines of Gossypium hirsutum × G. barbadense were used to dissect the QTL stability of three fiber quality traits (fiber length, strength and micronaire) across environments using 551 simple sequence repeat markers selected from our high-density genetic map. A total of 76 and 120 QTLs were detected in the CCRI36 and CCRI45 backgrounds, respectively. Nine BI-QTLs were found, and 78 (41.71%) of the detected QTLs were reported previously. Thirty-nine and 79 QTLs were SE-QTLs in at least two environments in the CCRI36 and CCRI45 backgrounds, respectively. Forty-eight SE-QTLs, including seven BI-QTLs, were confirmed in previous reports, and 61 SE-QTLs, including two BI-QTLs, were considered novel. These results indicate that genetic background more strongly impacts on fiber quality traits than environmental factors. Twenty-three clusters with BI- and/or SE-QTLs were identified, 19 of which harbored favorable alleles from G. barbadense for two or three fiber quality traits. This study is the first report using two sets of introgression lines to identify fiber quality QTLs across environments in cotton, providing insights into the effect of genetic backgrounds and environments on the QTL expression of fiber quality and important information for the genetic basis underlying fiber quality traits toward QTL cloning and molecular breeding.

Project description:Harvesting high quality lint, a long-awaited breeding goal-accomplished partly, can be achieved by identifying DNA markers which could be used for diagnosing cotton plants containing the desired traits. In the present studies, a total of 185 cotton genotypes exhibiting diversity for lint traits were selected from a set of 546 genotypes evaluated for fiber traits in 2009. These genotypes were extensively studied for three consecutive years (2011-2013) at three different locations. Significant genetic variations were found for average boll weight, ginning out turn (GOT), micronaire value, staple length, fiber bundle strength, and uniformity index. IR-NIBGE-3701 showed maximum GOT (43.63%). Clustering of genotypes using Ward's method was found more informative than that of the clusters generated by principal component analysis. A total of 382 SSRs were surveyed on 10 Gossypium hirsutum genotypes exhibiting contrasting fiber traits. Out of these, 95 polymorphic SSR primer pairs were then surveyed on 185 genotypes. The gene diversity averaged 0.191 and the polymorphic information content (PIC) averaged 0.175. Unweighted pair group method with arithmetic mean (UPGMA), principal coordinate analysis (PCoA), and STRUCTURE software grouped these genotypes into four major clusters each. Genetic distance within the clusters ranged from 0.0587 to 0.1030. A total of 47 (25.41%) genotypes exhibited shared ancestry. In total 6.8% (r2 ≥ 0.05) and 4.4% (r2 ≥ 0.1) of the marker pairs showed significant linkage disequilibrium (LD). A number of marker-trait associations (in total 75) including 13 for average boll weight, 18 for GOT percentage, eight for micronaire value, 18 for staple length, three for fiber bundle strength, and 15 for uniformity index were calculated. Out of these, MGHES-51 was associated with all the traits. Most of the marker-trait associations were novel while few validated the associations reported in the previous studies. High frequency of favorable alleles in cultivated varieties is possibly due to fixation of desirable alleles by domestication. These favorable alleles can be used in marker assisted breeding or for gene cloning using next generation sequencing tools. The present studies would set a stage for harvesting high quality lint without compromising the yield potential-ascertaining natural fiber security.

Project description:BACKGROUND: Cotton (Gossypium spp.) is the largest producer of natural fibers for textile and is an important crop worldwide. Crop production is comprised primarily of G. hirsutum L., an allotetraploid. However, elite cultivars express very small amounts of variation due to the species monophyletic origin, domestication and further bottlenecks due to selection. Conversely, wild cotton species harbor extensive genetic diversity of prospective utility to improve many beneficial agronomic traits, fiber characteristics, and resistance to disease and drought. Introgression of traits from wild species can provide a natural way to incorporate advantageous traits through breeding to generate higher-producing cotton cultivars and more sustainable production systems. Interspecific introgression efforts by conventional methods are very time-consuming and costly, but can be expedited using marker-assisted selection. RESULTS: Using transcriptome sequencing we have developed the first gene-associated single nucleotide polymorphism (SNP) markers for wild cotton species G. tomentosum, G. mustelinum, G. armourianum and G. longicalyx. Markers were also developed for a secondary cultivated species G. barbadense cv. 3-79. A total of 62,832 non-redundant SNP markers were developed from the five wild species which can be utilized for interspecific germplasm introgression into cultivated G. hirsutum and are directly associated with genes. Over 500 of the G. barbadense markers have been validated by whole-genome radiation hybrid mapping. Overall 1,060 SNPs from the five different species have been screened and shown to produce acceptable genotyping assays. CONCLUSIONS: This large set of 62,832 SNPs relative to cultivated G. hirsutum will allow for the first high-density mapping of genes from five wild species that affect traits of interest, including beneficial agronomic and fiber characteristics. Upon mapping, the markers can be utilized for marker-assisted introgression of new germplasm into cultivated cotton and in subsequent breeding of agronomically adapted types, including cultivar development.

Project description:BackgroundTo continue to meet the increasing demands of soybean worldwide, it is crucial to identify key genes regulating flowering and maturity to expand the cultivated regions into short season areas. Although four soybean genes have been successfully utilized in early maturity breeding programs, new genes governing maturity are continuously being identified suggesting that there remains as yet undiscovered loci governing agronomic traits of interest. The objective of this study was to identify novel loci and genes involved in a diverse set of early soybean maturity using genome-wide association (GWA) analyses to identify loci governing days to maturity (DTM), flowering (DTF) and pod filling (DTPF), as well as yield and 100 seed weight in Canadian environments. To do so, soybean plant introduction lines varying significantly for maturity, but classified as early varieties, were used. Plants were phenotyped for the five agronomic traits for five site-years and GWA approaches used to identify candidate loci and genes affecting each trait.ResultsGenotyping using genotyping-by-sequencing and microarray methods identified 67,594 single nucleotide polymorphisms, of which 31,283 had a linkage disequilibrium < 1 and minor allele frequency > 0.05 and were used for GWA analyses. A total of 9, 6, 4, 5 and 2 loci were detected for GWA analyses for DTM, DTF, DTPF, 100 seed weight and yield, respectively. Regions of interest, including a region surrounding the E1 gene for flowering and maturity, and several novel loci, were identified, with several loci having pleiotropic effects. Novel loci affecting maturity were identified on chromosomes five and 13 and reduced maturity by 7.2 and 3.3 days, respectively. Novel loci for maturity and flowering contained genes orthologous to known Arabidopsis flowering genes, while loci affecting yield and 100 seed weight contained genes known to cause dwarfism.ConclusionsThis study demonstrated substantial variation in soybean agronomic traits of interest, including maturity and flowering dates as well as yield, and the utility of GWA analyses in identifying novel genetic factors underlying important agronomic traits. The loci and candidate genes identified serve as promising targets for future studies examining the mechanisms underlying the related soybean traits.

Dataset Information

Identification of small effect quantitative trait loci of plant architectural, flowering, and early maturity traits in reciprocal interspecific introgression population in cotton.

Publications

Identification of small effect quantitative trait loci of plant architectural, flowering, and early maturity traits in reciprocal interspecific introgression population in cotton.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets