Improving Quantitative Traits in Self-Pollinated Crops Using Simulation-Based Selection With Minimal Crossing

Genomic selection and marker-assisted recurrent selection have been applied to improve quantitative traits in many cross-pollinated crops. However, such selection is not feasible in self-pollinated crops owing to laborious crossing procedures. In this study, we developed a simulation-based selection strategy that makes use of a trait prediction model based on genomic information to predict the phenotype of the progeny for all possible crossing combinations. These predictions are then used to select the best cross combinations for the selection of the given trait. In our simulated experiment, using a biparental initial population with a heritability set to 0.3, 0.6, or 1.0 and the number of quantitative trait loci set to 30 or 100, the genetic gain of the proposed strategy was higher or equal to that of conventional recurrent selection method in the early selection cycles, although the number of cross combinations of the proposed strategy was considerably reduced in each cycle. Moreover, this strategy was demonstrated to increase or decrease seed protein content in soybean recombinant inbred lines using SNP markers. Information on 29 genomic regions associated with seed protein content was used to construct the prediction model and conduct simulation. After two selection cycles, the selected progeny had significantly higher or lower seed protein contents than those from the initial population. These results suggest that our strategy is effective in obtaining superior progeny over a short period with minimal crossing and has the potential to efficiently improve the target quantitative traits in self-pollinated crops.

Download Full-text

A RECURRENT SELECTION SCHEME FOR FABA BEAN

Canadian Journal of Plant Science ◽

10.4141/cjps87-009 ◽

1987 ◽

Vol 67 (1) ◽

pp. 79-85 ◽

Cited By ~ 1

Author(s):

G. G. ROWLAND

Keyword(s):

Protein Content ◽

Vicia Faba ◽

Seed Yield ◽

Faba Bean ◽

Recurrent Selection ◽

Seed Protein ◽

Random Mating ◽

Seed Protein Content ◽

Selection Scheme ◽

Seed Protein Concentration

A recurrent selection method for use in faba bean (Vicia faba) was evaluated over a 10-yr period. The method consists of growing superior lines in open-pollinated random mating nurseries (RMN), selecting heavily podded plants from these lines, evaluating the offspring for yield and seed protein concentration, and replacing inferior lines in the RMN with selections deemed superior. Two types of RMN were established, one for yield (RMY) and the other for both yield and seed protein content (RMP). The criterion for entry of a line into the RMY was a seed yield in the top 3 % of a yield trial while entry into the RMP required a line to be in the top 5% for seed yield and 3% for protein content. A positive increase in seed yield of the selected lines from both RMNs was found over time, but no increase in seed protein content was noted.Key words: Vicia faba, recurrent selection, breeding method, faba bean

Download Full-text

SNP marker association for incrementing soybean seed protein content

Agronomy Science and Biotechnology ◽

10.33158/asb.r107.v6.2020 ◽

2020 ◽

Vol 6 ◽

pp. 1-11

Author(s):

Arthur Bernardeli ◽

Aluízio Borem ◽

Rodrigo Lorenzoni ◽

Rafael Aguiar ◽

Jessica Nayara Basilio Silva ◽

...

Keyword(s):

Protein Content ◽

Seed Protein ◽

Recombinant Inbred Lines ◽

Soybean Seed ◽

Snp Markers ◽

Snp Marker ◽

Seed Protein Content ◽

Single Marker Analysis ◽

Soybean Breeding ◽

Single Marker

Soybean seed protein content (SPC) has been decreasing throughout last decades and DNA marker association has shown its usefulness to improve this trait even in soybean breeding programs that focus primarily on soybean yield and seed oil content (SOC). Aiming to elucidate the association of two SNP markers (ss715630650 and ss715636852) to the SPC, a soybean population of 264 F5-derived recombinant inbred lines (RILs) from a bi-parental cross was tested in four environments. Through the single-marker analysis, the additive effect () and the portion of SPC variation due to the SNPs () for single and multi-environment data were assessed, and transgressive RILs for SPC were observed. The estimates revealed the association of both markers to SPC in most of environments. The marker ss715636852 was more frequently associated to SPC, including multi-environment data, and contributed up to = 1.30% for overall SPC, whereas ss715630650 had significant association just in two locations, with contributions of = 0.76% and = 0.74% to overall SPC in Vic1 and Cap1, respectively. The RIL 84-13 was classified as an elite genotype due to its favorable alleles and high SPC means, which reached 53.78% in Cap1, and 46.33% in MET analysis. Thus, these results confirm the usefulness of the SNP marker ss715636852 in a soybean breeding program for SPC.

Download Full-text

Genetic mapping high protein content QTL from soybean ‘Nanxiadou 25’ and candidate gene analysis

BMC Plant Biology ◽

10.1186/s12870-021-03176-2 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Jia Wang ◽

Lin Mao ◽

Zhaoqiong Zeng ◽

Xiaobo Yu ◽

Jianqiu Lian ◽

...

Keyword(s):

Qtl Mapping ◽

Protein Content ◽

Candidate Genes ◽

Seed Protein ◽

Recombinant Inbred Lines ◽

High Protein ◽

Quality Trait ◽

Seed Protein Content ◽

High Protein Content ◽

Major Qtl

Abstract Background Soybean is a globally important legume crop that provides a primary source of high-quality vegetable protein and oil. Seed protein content (SPC) is a valuable quality trait controlled by multiple genes in soybean. Results In this study, we performed quantitative trait loci (QTL) mapping, QTL-seq, and RNA sequencing (RNA-seq) to reveal the genes controlling protein content in the soybean by using the high protein content variety Nanxiadou 25. A total of 50 QTL for SPC distributed on 14 chromosomes except chromosomes 4, 12, 14, 17, 18, and 19 were identified by QTL mapping using 178 recombinant inbred lines (RILs). Among these QTL, the major QTL qSPC_20–1 and qSPC_20–2 on chromosome 20 were repeatedly detected across six tested environments, corresponding to the location of the major QTL detected using whole-genome sequencing-based QTL-seq. 329 candidate DEGs were obtained within the QTL region of qSPC_20–1 and qSPC_20–2 via gene expression profile analysis. Nine of which were associated with SPC, potentially representing candidate genes. Clone sequencing results showed that different single nucleotide polymorphisms (SNPs) and indels between high and low protein genotypes in Glyma.20G088000 and Glyma.16G066600 may be the cause of changes in this trait. Conclusions These results provide the basis for research on candidate genes and marker-assisted selection (MAS) in soybean breeding for seed protein content.

Download Full-text

Shikimate Dehydrogenase ‐1 2 Allozyme as a Marker for High Seed Protein Content in Rice

Crop Science ◽

10.2135/cropsci1990.0011183x003000040036x ◽

1990 ◽

Vol 30 (4) ◽

pp. 937-940 ◽

Cited By ~ 5

Author(s):

V. V. Shenoy ◽

D. V. Seshu ◽

J. K. S. Sachan

Keyword(s):

Protein Content ◽

Seed Protein ◽

Seed Protein Content ◽

Shikimate Dehydrogenase

Download Full-text

Modeling the Competitive Effect of Euphorbia dracunculoides and Astragalus sp. in Zero Input Rainfed Chickpea

Planta Daninha ◽

10.1590/s0100-83582018360100021 ◽

2018 ◽

Vol 36 (0) ◽

Author(s):

R.M. IKRAM ◽

A. TANVEER ◽

R. MAQBOOL ◽

M.A. NADEEN

Keyword(s):

Protein Content ◽

Critical Period ◽

Field Experiments ◽

Seed Protein ◽

Yield Loss ◽

Seed Protein Content ◽

Yield Losses ◽

Competition Period ◽

Crop Competition ◽

Weed Removal

ABSTRACT: Brown chickpea (Cicer arietinum L.) is one of the two chickpea types grown in Pakistan and other countries. The critical period for weed removal in a rainfed chickpea system is an important consideration in devising weed management strategies. Field experiments were conducted in the winter season of 2011 and 2012 to determine the extent of yield loss with different periods of weed crop competition. Seven weed crop competition periods (0, 45, 60, 75, 90, 105 and 160 days after sowing - DAS) were used to identify the critical period for weed removal in rainfed chickpea. Experimental plots were naturally infested with Euphorbia dracunculoides and Astragalus sp. in both years. Individual, composite density and dry weights of E. dracunculoides and Astragalussp. increased significantly with an increase in the competition period. However, yield and yield-contributing traits of chickpea significantly decreased with an increase in the competition period. Chickpea seed yield loss was 11-53% in different weed crop competition periods. Euphorbia dracunculoides and Astragalus sp. removed 39.9 and 36.9 kg ha-1 of N, 9.61 and 7.27 kg ha-1 of P and 38.3 and 36.9 kg ha-1 of K, respectively. Season long weed competition (160 days after sowing) resulted in 19.5% seed protein content compared with 24.5% seed protein content in weed-free chickpea. A Logistic equation was fitted to yield data in response to increasing periods of weed crop competition. The critical timing of weed removal at 5 and 10% acceptable yield losses were 26 and 39 DAS, respectively. The observed critical period suggests that in rainfed chickpea, a carefully timed weed removal could prevent grain yield losses.

Download Full-text