scholarly journals Pea Breeding for Intercropping With Cereals: Variation for Competitive Ability and Associated Traits, and Assessment of Phenotypic and Genomic Selection Strategies

2021 ◽  
Vol 12 ◽  
Author(s):  
Paolo Annicchiarico ◽  
Nelson Nazzicari ◽  
Tommaso Notario ◽  
Cristina Monterrubio Martin ◽  
Massimo Romani ◽  
...  
Keyword(s):  
Genomic Selection ◽  
Plant Height ◽  
Competitive Ability ◽  
Phenotypic Selection ◽  
Indirect Selection ◽  
Flowering Plant ◽  
Complete Suppression ◽  
Selection Strategies ◽  
A Genome ◽  
Selection For

Mixed stand (MS) cropping of pea with small-grain cereals can produce more productive and environment-friendly grain crops relative to pure stand (PS) crops but may require selection to alleviate the pea competitive disadvantage. This study aimed to assess the pea variation for competitive ability and its associated traits and the efficiency of four phenotypic or genomic selection strategies. A set of 138 semi-leafless, semi-dwarf pea lines belonging to six recombinant inbred line populations and six parent lines were genotyped using genotyping-by-sequencing and grown in PS and in MS simultaneously with one barley and one bread wheat cultivar in two autumn-sown trials in Northern Italy. Cereal companions were selected in a preliminary study that highlighted the paucity of cultivars with sufficient earliness for association. Pea was severely outcompeted in both years albeit with variation for pea proportion ranging from nearly complete suppression (<3%) to values approaching a balanced mixture. Greater pea proportion in MS was associated with greater total yield of the mixture (r ≥ 0.46). The genetic correlation for pea yield across MS and PS conditions slightly exceeded 0.40 in both years. Later onset of flowering and taller plant height at flowering onset displayed a definite correlation with pea yield in MS (r ≥ 0.46) but not in PS, whereas tolerance to ascochyta blight exhibited the opposite pattern. Comparisons of phenotypic selection strategies within or across populations based on predicted or actual yield gains for independent years indicated an efficiency of 52–64% for indirect selection based on pea yield in PS relative to pea yield selection in MS. The efficiency of an indirect selection index including onset of flowering, plant height, and grain yield in PS was comparable to that of pea yield selection in MS. A genome-wide association study based on 5,909 SNP markers revealed the substantial diversity of genomic areas associated with pea yield in MS and PS. Genomic selection for pea yield in MS displayed an efficiency close to that of phenotypic selection for pea yield in MS, and nearly two-fold greater efficiency when also taking into account its shorter selection cycle and smaller evaluation cost.

scholarly journals Context-Specific Genomic Selection Strategies Outperform Phenotypic Selection for Soybean Quantitative Traits in the Progeny Row Stage

Crop Science ◽  
2019 ◽  
Vol 59 (1) ◽  
pp. 54-67 ◽  
Author(s):  
Christopher J. Smallwood ◽  
Arnold M. Saxton ◽  
Jason D. Gillman ◽  
Hem S. Bhandari ◽  
Phillip A. Wadl ◽  
...  
Keyword(s):  
Genomic Selection ◽  
Quantitative Traits ◽  
Phenotypic Selection ◽  
Selection Strategies ◽  
Selection For ◽  
Context Specific

scholarly journals Correlations and path analysis in agronomic traits of soybeans under defoliation

2020 ◽  
Vol 36 (5) ◽  
Author(s):  
Alan Mario Zuffo ◽  
Francisco de Alcântara Neto ◽  
Tiago Zoz ◽  
Rafael Felippe Ratke ◽  
Jorge González Aguilera ◽  
...  
Keyword(s):  
Grain Yield ◽  
Plant Height ◽  
Agronomic Traits ◽  
Block Design ◽  
Indirect Selection ◽  
Additional Treatment ◽  
Leaf Damage ◽  
Thousand Grain Weight ◽  
Randomized Block Design ◽  
Selection For

 Stress events or leaf damage can alter the redistribution of photoassimilates and modify the morphological traits directly related to grain yield. This study aimed to evaluate the influence of agronomic traits on grain yield in soybean crop in function of leaf defoliation. The experiment consisted of a randomized block design with three replications, arranged in a 6 x 3 + 1 factorial scheme. The factors were composed by six reprodutive stages (R1, R2, R3, R4, R5, and R6) and three defoliation levels (33%, 66%, and 99%), and one additional treatment without defoliation (control). The following traits were evaluated: plant height, number of pods per plant, number of grains per pod, thousand grain weight, and grain yield. The magnitudes of the correlations between the same traits showed high oscillation according to the defoliation level. Results revealed the potential for the indirect selection for grain yield by the traits plant height and number of grains per pods under 0% of defoliation and by the trait number of pods per plant under 33% of defoliation.

Indirect selection for lower deoxynivalenol (DON) content in grain in a winter wheat population

2007 ◽  
Vol 87 (4) ◽  
pp. 931-936 ◽  
Author(s):  
L. Tamburic-Ilincic ◽  
A. W. Schaafsma ◽  
D. E. Falk
Keyword(s):  
Winter Wheat ◽  
Plant Height ◽  
Fusarium Graminearum ◽  
Heading Date ◽  
Indirect Selection ◽  
Wheat Breeding ◽  
Head Blight ◽  
Wheat Population ◽  
Fhb Resistance ◽  
Selection For

Selection for Fusarium head blight (FHB) resistance and lower deoxynivalenol (DON) content is an important goal in many wheat-breeding programs worldwide. Preliminary screening for less severe FHB symptoms in the early segregating generations can be an important tool to assist breeders in determining which lines to advance to homozygosity. The objectives of this study were: (1) to test influence of plant height, heading date, presence of awns and number of spikelets per spike on FHB index and DON content and (2) to estimate the reliability of indirect selection for lower DON content based on FHB index. A Ruby × Frontana winter wheat population was spray inoculated with a spore suspension of Fusarium graminearum in 2001 and 2002. Plant height was significantly associated with DON content in both years; taller lines accumulated less DON than shorter ones. The moderately resistant lines, based on FHB index after in oculation, had a statistically lower DON accumulation compared with the highly susceptible ones (17.7 ppm vs. 20.6 ppm and 0.6 ppm vs. 2.0 ppm in 2001 and 2002) respectively. The results from this study suggest that selection for FHB resistance can be an indirect selection method for lowering DON accumulation in wheat grain. A breeder can identify and discard those early generation lines that are highly susceptible to FHB as they likely would have higher DON levels. Key words: Fusarium graminearum (Schwabe), morphology, resistance, Triticum aestivum L.

scholarly journals Genome-wide association study and genomic selection for yield and related traits in soybean

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0255761
Author(s):  
Waltram Ravelombola ◽  
Jun Qin ◽  
Ainong Shi ◽  
Qijian Song ◽  
Jin Yuan ◽  
...  
Keyword(s):  
Association Study ◽  
Genomic Selection ◽  
Plant Height ◽  
Seed Weight ◽  
Genome Wide Association Study ◽  
Agronomic Traits ◽  
Snp Markers ◽  
Genome Wide Association ◽  
Genome Wide ◽  
A Genome

Soybean [Glycine max (L.) Merr.] is a crop of great interest worldwide. Exploring molecular approaches to increase yield genetic gain has been one of the main challenges for soybean breeders and geneticists. Agronomic traits such as maturity, plant height, and seed weight have been found to contribute to yield. In this study, a total of 250 soybean accessions were genotyped with 10,259 high-quality SNPs postulated from genotyping by sequencing (GBS) and evaluated for grain yield, maturity, plant height, and seed weight over three years. A genome-wide association study (GWAS) was performed using a Bayesian Information and Linkage Disequilibrium Iteratively Nested Keyway (BLINK) model. Genomic selection (GS) was evaluated using a ridge regression best linear unbiased predictor (rrBLUP) model. The results revealed that 20, 31, 37, and 23 SNPs were significantly associated with maturity, plant height, seed weight, and yield, respectively; Many SNPs were mapped to previously described maturity and plant height loci (E2, E4, and Dt1) and a new plant height locus was mapped to chromosome 20. Candidate genes were found in the vicinity of the two SNPs with the highest significant levels associated with yield, maturity, plant height, seed weight, respectively. A 11.5-Mb region of chromosome 10 was associated with both yield and seed weight. Overall, the accuracy of GS was dependent on the trait, year, and population structure, and high accuracy indicates that these agronomic traits can be selected in molecular breeding through GS. The SNP markers identified in this study can be used to improve yield and agronomic traits through the marker-assisted selection and GS in breeding programs.

scholarly journals Genotypic Selection for Soybean Earliness

2020 ◽  
Vol 12 (11) ◽  
pp. 169
Author(s):  
Flaviane O. Ribeiro ◽  
Adriano T. Bruzi ◽  
Mariane C. Bianchi ◽  
Igor O. Soares ◽  
Karina B. Silva
Keyword(s):  
Plant Height ◽  
Flowering Plant ◽  
High Yield ◽  
Correlated Response ◽  
Early Maturity ◽  
Days To Flowering ◽  
Lattice Design ◽  
Early Maturing ◽  
Superior Genotypes ◽  
Selection For

Obtaining early-maturing soybean cultivars with high yield performance has long been the focus of breeding programs. Obtaining the estimates of genetic and phenotypic parameters can assist breeders at selecting the superior genotypes. Therefore, the aim was to estimate the genetic and phenotypic parameters of progenies throughout the recurrent selection for early maturity in soybeans and to select progenies with superior agronomic traits. S0:1 progenies were evaluated in one site during the 2015/2016 harvest using a 12 × 12 lattice design, with one 2-meter row plot with two replicates. The S0:2 progenies were evaluated during the 2016/2017 harvest using an 8 × 8 lattice design, with one 3-meter row plot with three replicates. The S0:3 progenies were evaluated during the 2017/2018 harvest using a 5 × 5 lattice design, with two 3-meter rows plots with three replicates. Both S0:2 and S0:3 progenies were evaluated in three different sites. The days to flowering, full maturity, first pod insertion height, plant height, lodging index and grain yield traits was evaluated. The data were analyzed using a mixed model approach. The genetic and phenotypic parameters, expected gain with selection, realized heritability, correlated response and the frequency distributions of the adjusted means were estimated. The estimates of the variance components have evidenced variability among the progenies, enabling the selection of superior genotypes. All the evaluated progenies showed good agronomic performance, combining early maturity and productive performance. When early-maturing progenies were selected, there was a reduction in days to flowering, plant height, first pod insertion height, lodging and yield.

Recurrent Phenotypic Selection for Resistance to Brown Leaf Spot in Smooth Bromegrass 1

Crop Science ◽  
1986 ◽  
Vol 26 (3) ◽  
pp. 533-536 ◽  
Author(s):  
Clyde C. Berg ◽  
Robert T. Sherwood ◽  
Kenneth E. Zeiders
Keyword(s):  
Leaf Spot ◽  
Phenotypic Selection ◽  
Smooth Bromegrass ◽  
Brown Leaf Spot ◽  
Brown Leaf ◽  
Selection For

scholarly journals Prediction Accuracies of Genomic Selection for Nine Commercially Important Traits in the Portuguese Oyster (Crassostrea angulata) Using DArT-Seq Technology

Genes ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 210
Author(s):  
Sang V. Vu ◽  
Cedric Gondro ◽  
Ngoc T. H. Nguyen ◽  
Arthur R. Gilmour ◽  
Rick Tearle ◽  
...  
Keyword(s):  
Moisture Content ◽  
Genomic Selection ◽  
Shell Length ◽  
Prediction Accuracy ◽  
Genomic Information ◽  
Morphometric Traits ◽  
Shell Weight ◽  
Shell Width ◽  
Crassostrea Angulata ◽  
Selection For

Genomic selection has been widely used in terrestrial animals but has had limited application in aquaculture due to relatively high genotyping costs. Genomic information has an important role in improving the prediction accuracy of breeding values, especially for traits that are difficult or expensive to measure. The purposes of this study were to (i) further evaluate the use of genomic information to improve prediction accuracies of breeding values from, (ii) compare different prediction methods (BayesA, BayesCπ and GBLUP) on prediction accuracies in our field data, and (iii) investigate the effects of different SNP marker densities on prediction accuracies of traits in the Portuguese oyster (Crassostrea angulata). The traits studied are all of economic importance and included morphometric traits (shell length, shell width, shell depth, shell weight), edibility traits (tenderness, taste, moisture content), and disease traits (Polydora sp. and Marteilioides chungmuensis). A total of 18,849 single nucleotide polymorphisms were obtained from genotyping by sequencing and used to estimate genetic parameters (heritability and genetic correlation) and the prediction accuracy of genomic selection for these traits. Multi-locus mixed model analysis indicated high estimates of heritability for edibility traits; 0.44 for moisture content, 0.59 for taste, and 0.72 for tenderness. The morphometric traits, shell length, shell width, shell depth and shell weight had estimated genomic heritabilities ranging from 0.28 to 0.55. The genomic heritabilities were relatively low for the disease related traits: Polydora sp. prevalence (0.11) and M. chungmuensis (0.10). Genomic correlations between whole weight and other morphometric traits were from moderate to high and positive (0.58–0.90). However, unfavourably positive genomic correlations were observed between whole weight and the disease traits (0.35–0.37). The genomic best linear unbiased prediction method (GBLUP) showed slightly higher accuracy for the traits studied (0.240–0.794) compared with both BayesA and BayesCπ methods but these differences were not significant. In addition, there is a large potential for using low-density SNP markers for genomic selection in this population at a number of 3000 SNPs. Therefore, there is the prospect to improve morphometric, edibility and disease related traits using genomic information in this species.

scholarly journals Uncovering genomic regions controlling plant architectural traits in hexaploid wheat using different GWAS models

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ali Muhammad ◽  
Jianguo Li ◽  
Weichen Hu ◽  
Jinsheng Yu ◽  
Shahid Ullah Khan ◽  
...  
Keyword(s):  
Plant Height ◽  
Genome Wide Association Study ◽  
Flag Leaf ◽  
Significant Snps ◽  
Complex Trait ◽  
Leaf Length ◽  
Candidate Snps ◽  
A Genome ◽  
Multiple Environments ◽  
Architectural Traits

AbstractWheat is a major food crop worldwide. The plant architecture is a complex trait mostly influenced by plant height, tiller number, and leaf morphology. Plant height plays a crucial role in lodging and thus affects yield and grain quality. In this study, a wheat population was genotyped by using Illumina iSelect 90K single nucleotide polymorphism (SNP) assay and finally 22,905 high-quality SNPs were used to perform a genome-wide association study (GWAS) for plant architectural traits employing four multi-locus GWAS (ML-GWAS) and three single-locus GWAS (SL-GWAS) models. As a result, 174 and 97 significant SNPs controlling plant architectural traits were detected by ML-GWAS and SL-GWAS methods, respectively. Among these SNP makers, 43 SNPs were consistently detected, including seven across multiple environments and 36 across multiple methods. Interestingly, five SNPs (Kukri_c34553_89, RAC875_c8121_1490, wsnp_Ex_rep_c66315_64480362, Ku_c5191_340, and tplb0049a09_1302) consistently detected across multiple environments and methods, played a role in modulating both plant height and flag leaf length. Furthermore, candidate SNPs (BS00068592_51, Kukri_c4750_452 and BS00022127_51) constantly repeated in different years and methods associated with flag leaf width and number of tillers. We also detected several SNPs (Jagger_c6772_80, RAC875_c8121_1490, BS00089954_51, Excalibur_01167_1207, and Ku_c5191_340) having common associations with more than one trait across multiple environments. By further appraising these GWAS methods, the pLARmEB and FarmCPU models outperformed in SNP detection compared to the other ML-GWAS and SL-GWAS methods, respectively. Totally, 152 candidate genes were found to be likely involved in plant growth and development. These finding will be helpful for better understanding of the genetic mechanism of architectural traits in wheat.

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