scholarly journals Variation for Photoperiod and Temperature Sensitivity in the Global Mini Core Collection of Sorghum

2021 ◽  
Vol 12 ◽  
Author(s):  
Hari D. Upadhyaya ◽  
M. Vetriventhan ◽  
Vania C. R. Azevedo

Information on photoperiod and temperature sensitivity of sorghum germplasm is important to identify appropriate sources for developing cultivars with a broad adaptation. The sorghum mini core collection consisting of 242 accessions along with three control cultivars were evaluated for days to 50% flowering (DFL) and plant height in two long-day rainy and two short-day post-rainy seasons, and for grain yield and 100-seed weight in the two post-rainy seasons. Differences in DFL and cumulative growing degree days (CGDD) in the rainy and post-rainy seasons were used to classify the accessions for photoperiod and temperature sensitivity. Results revealed 18 mini core landraces as photoperiod and temperature insensitive (PTINS), 205 as photoperiod sensitive and temperature insensitive (PSTINS), and 19 as photoperiod and temperature-sensitive (PTS) sources. The 19 PTS sources and 80 PSTINS sources took less DFL in the long-day rainy seasons than in the short-day post-rainy season indicating their adaptation to the rainy season and a possible different mechanism than that trigger flowering in the short-day sorghums. In all three groups, several accessions with desirable combinations of agronomic traits were identified for use in the breeding programs to develop climate-resilient cultivars and for genomic studies to identify genes responsible for the photoperiod and temperature responses.

Plant Disease ◽  
2010 ◽  
Vol 94 (4) ◽  
pp. 439-444 ◽  
Author(s):  
Rajan Sharma ◽  
V. P. Rao ◽  
H. D. Upadhyaya ◽  
V. Gopal Reddy ◽  
R. P. Thakur

Grain mold and downy mildew are important biotic constraints to grain sorghum (Sorghum bicolor) production worldwide and are best managed through host plant resistance. A sorghum mini-core collection composed of 242 germplasm accessions developed from a core collection of 2,246 landrace accessions from 58 countries was evaluated to identify sources of grain mold and downy mildew resistance. Of the 242 accessions, 140 that flowered during the rainy season (the other 102 accessions were photoperiod sensitive) were screened for grain mold resistance in a grain mold nursery under field epiphytotic conditions during 2007 and 2008. All 242 accessions were screened for downy mildew in the greenhouse using a sandwich inoculation technique. Fifty accessions were resistant to grain mold (≤10% mean severity). These resistant accessions represented four basic and six intermediate races of sorghum that originated from 21 countries and exhibited considerable diversity for agronomic and morphological traits. Downy mildew resistance (mean incidence ≤10%) was observed only in six (IS 28747, IS 31714, IS 23992, IS 27697, IS 28449, and IS 30400) of the 242 accessions. One accession, IS 23992, exhibited resistance to both the diseases. The morphologically and agronomically diverse accessions that are resistant to grain mold or downy mildew should be useful to sorghum disease resistance breeding programs.


2020 ◽  
Author(s):  
Shuai Liu ◽  
Hua Zhong ◽  
Xiaoxi Meng ◽  
Tong Sun ◽  
Yangsheng Li ◽  
...  

Abstract BackgroundRice is an important human staple food vulnerable to heavy metal contamination leading to serious concerns. High yield with low heavy metal contamination is a common but highly challenging goal for rice breeders worldwide due to lack of genetic knowledge and markers. ResultsTo identify candidate QTLs and develop molecular markers for rice yield and heavy metal content, a total of 191 accessions from the USDA Rice mini-core collection with over 3.2 million SNPs were employed to investigate the QTLs. Sixteen ionomic and thirteen agronomic traits were analyzed utilizing two univariate (GLM and MLM) and two multivariate (MLMM and FarmCPU) GWAS methods. 106, 47, and 97 QTLs were identified for ionomics flooded, ionomics unflooded, and agronomic traits, respectively, with the criterium of p-value <1.53×10-8, which was determined by the Bonferroni correction for p-value of 0.05. While 49 (~20%) of the 250 QTLs were coinciding with previous reported QTLs/genes, about 201 (~80%) were new. In addition, several new candidate genes involved in ionomic and agronomic traits control were identified by analyzing the DNA sequence, gene expression, and the homologs of the QTL regions. Our results further showed that each of the four GWAS methods can identify unique as well as common QTLs, suggesting that using multiple GWAS methods can complement each other in QTL identification, especially by combining univariate and multivariate methods. ConclusionsWhile 49 previously reported QTLs/genes were rediscovered, over 200 new QTLs for ionomic and agronomic traits were found in the rice genome. Moreover, multiple new candidate genes for agronomic and ionomic traits were identified. This research provides novel insights into the genetic basis of both ionomic and agronomic variations in rice, establishing the foundation for marker development in breeding and further investigation on reducing heavy-metal contamination and improving crop yields. Finally, the comparative analysis of the GWAS methods showed that each method has unique features and different methods can complement each other.


2011 ◽  
Vol 9 (01) ◽  
pp. 45-58 ◽  
Author(s):  
Hari D. Upadhyaya ◽  
Mahendar Thudi ◽  
Naresh Dronavalli ◽  
Neha Gujaria ◽  
Sube Singh ◽  
...  

Chickpea is the third most important grain legume grown in the arid and semi-arid regions of the world. In spite of vast germplasm accessions available in different genebanks, there has been very limited use of these accessions in genetic enhancement of chickpea. However, in recent years, specialized germplasm subsets such as global composite collection, core collection, mini core collection and reference set have been developed. In parallel, significant genomic resources such as molecular markers including simple sequence repeats (SSRs), single nucleotide polymorphisms (SNPs), diversity arrays technology (DArT) and transcript sequences, e.g. expressed sequence tags, short transcript reads, have been developed. By using SSR, SNP and DArT markers, integrated genetic maps have been developed. It is anticipated that the use of genomic resources and specialized germplasm subsets such as mini core collection and reference set will facilitate identification of trait-specific germplasm, trait mapping and allele mining for resistance to biotic and abiotic stresses and for agronomic traits. Advent of the next generation sequencing technologies coupled with advances in bioinformatics offers the possibility of undertaking large-scale sequencing of germplasm accessions so that modern breeding approaches such as genomic selection and breeding by design can be realized in near future for chickpea improvement.


2021 ◽  
Author(s):  
Kehu Li ◽  
Yongyi Ge ◽  
Lily Yan Wang

Abstract The USDA rice mini-core collection was established to capture the diversity of an entire collection of over 18,700 accessions of global origins for efficient germplasm evaluation and exploration. Previous studies have investigated its genetic diversity and population structure using genome-wide SSR markers. Many important agronomic traits that are fundamental to rice breeding programs, however, remain to be explored. Functional markers can be developed based on polymorphic sites within genes affecting phenotypic variation in, e.g., starch physicochemical properties, nutritional qualities and biotic resistance. These markers can be used for genotyping and hence differentiating phenotypes among rice accessions. In this study, we employed 12 pairs of functional markers (SNP and Indel) to genotype all 217 accessions constituting the USDA rice mini-core. These markers are highly associated with starch physicochemical properties (intron 1 G/C SNP, 23bp duplication in exon 2, exon 6 C/A SNP, exon 10 C/T SNP of Waxy gene, GC/TT SNPs of SSIIa gene, G/C SNP of SBE3 gene), glutelin content (3.5 kb deletion in Lgc1 gene), grain length (C/A SNP in GS3 gene), brown planthopper resistance (InDel in Bph 14 gene) and rice blast resistance (InDel in Pi54 and Pit gene). Using these functional markers, all the 217 accessions of the mini-core are characterized for aforementioned agronomic traits associated alleles/genes. The results of this study will help breeders select parental materials with desirable allele/gene combinations and phenotypes among mini-core accessions for rice breeding programs.


2013 ◽  
Vol 38 (6) ◽  
pp. 935-946 ◽  
Author(s):  
Li HUANG ◽  
Xiao-Ping REN ◽  
Xiao-Jie ZHANG ◽  
Yu-Ning CHEN ◽  
Hui-Fang JIANG

2005 ◽  
Vol 191 (4) ◽  
pp. 255-262 ◽  
Author(s):  
T. Han ◽  
C. Wu ◽  
R. S. Mentreddy ◽  
J. Zhao ◽  
X. Xu ◽  
...  

Author(s):  
Rongkui Han ◽  
Dean Lavelle ◽  
Maria José Truco ◽  
Richard Michelmore

Abstract Key message A population of lettuce that segregated for photoperiod sensitivity was planted under long-day and short-day conditions. Genetic mapping revealed two distinct sets of QTLs controlling daylength-independent and photoperiod-sensitive flowering time. Abstract The molecular mechanism of flowering time regulation in lettuce is of interest to both geneticists and breeders because of the extensive impact of this trait on agricultural production. Lettuce is a facultative long-day plant which changes in flowering time in response to photoperiod. Variations exist in both flowering time and the degree of photoperiod sensitivity among accessions of wild (Lactuca serriola) and cultivated (L. sativa) lettuce. An F6 population of 236 recombinant inbred lines (RILs) was previously developed from a cross between a late-flowering, photoperiod-sensitive L. serriola accession and an early-flowering, photoperiod-insensitive L. sativa accession. This population was planted under long-day (LD) and short-day (SD) conditions in a total of four field and screenhouse trials; the developmental phenotype was scored weekly in each trial. Using genotyping-by-sequencing (GBS) data of the RILs, quantitative trait loci (QTL) mapping revealed five flowering time QTLs that together explained more than 20% of the variation in flowering time under LD conditions. Using two independent statistical models to extract the photoperiod sensitivity phenotype from the LD and SD flowering time data, we identified an additional five QTLs that together explained more than 30% of the variation in photoperiod sensitivity in the population. Orthology and sequence analysis of genes within the nine QTLs revealed potential functional equivalents in the lettuce genome to the key regulators of flowering time and photoperiodism, FD and CONSTANS, respectively, in Arabidopsis.


2020 ◽  
Author(s):  
Shuai Liu ◽  
Hua Zhong ◽  
Xiaoxi Meng ◽  
Tong Sun ◽  
Yangsheng Li ◽  
...  

Abstract Background: Rice is an important human staple food vulnerable to heavy metal contamination due to its unique physiology and growth environment. High yield with low heavy metal contamination is a common but highly challenging goal for rice breeders worldwide due to lack of genetic knowledge. To identify candidate QTLs for rice yield and heavy metal content, sixteen ionomic traits and thirteen agronomic traits of the USDA Rice mini-core collection were analyzed using both univariate and multivariate GWAS methods in this study. The USDA Rice Mini-Core Collection contains about 1% of the whole Rice Collection of the National Small Grains Collection (NSGC), USA.Results: Using the p-value <1.53×10-8, this criterium p-value was determined by the Bonferroni correction for p-value of 0.05, 106, 47, and 97 QTLs were identified for ionomics in flooded environment, unflooded environment, and agronomic traits, respectively. A large number of QTLs coincide well with previous report results while many of the QTLs are new QTLs, suggesting the efficiency of GWAS methods and the reliability of this study. Our results further showed that each of the four GWAS methods can identify unique as well as common QTLs. When univariate methods failed to identify QTLs for a trait, the multivariate methods frequently detected QTLs. However, when many QTLs were detected by univariate methods, the number of QTLs detected by multivariate methods were reduced in many cases. These analyses suggest that using multiple GWAS methods can complement each other in QTL identification. In addition, several candidate genes involved in ionomic and agronomic traits control were identified by analyzing the sequences of the candidate QTL regions.Conclusions: Significant QTLs for heavy metal, mineral, and agronomic traits are presented in the rice genome and some of them have been fine mapped in the rice genome in this study. This research provides novel insights into the genetic basis of both ionomic and agronomic variations in rice, establishing an important foundation for further studies on reducing heavy-metal contamination and improving crop yields. In addition, the comparison analysis of the GAWS methods showed that each method has unique feature and different method can complement each other.


Sign in / Sign up

Export Citation Format

Share Document