Genetic components and major QTL confer resistance to bean pyralid (Lamprosema indicata Fabricius) under multiple environments in four RIL populations of soybean

The Identification of a Quantative Trait Loci-Allele System of Antixenosis against the Common Cutworm (Spodoptera litura Fabricius) at the Seedling Stage in the Chinese Soybean Landrace Population

Common cutworm (CCW) is an omnivorous insect causing severe yield losses in soybean crops. The seedling-stage mini-tray identification system with the damaged leaf percentage (DLP) as an indicator was used to evaluate antixenosis against CCW in the Chinese soybean landrace population (CSLRP) under three environments. Using the innovative restricted two-stage multi-locus genome-wide association study procedure (RTM-GWAS), 86 DLP QTLs with 243 alleles (2-11/QTL) were identified, including 66 main-effect loci with 203 alleles and 57 QTL-environment interaction loci with 172 alleles. Among the main-effect loci, 12 large-contribution loci (R2 ≥ 1%) explained 25.45% of the phenotypic variation (PV), and 54 small-contribution loci (R2 < 1%) explained 16.55% of the PV. This indicates that the CSLRP can be characterized with a DLP QTL-allele system complex that has not been found before, except for a few individual QTLs without alleles involved. From the DLP QTL-allele matrix, the recombination potentials expressed in the 25th percentile of the DLP of all possible crosses were predicted to be reduced by 41.5% as the maximum improvement and 14.2% as the maximum transgression, indicating great breeding potential in the antixenosis of the CSLRP. From the QTLs, 62 candidate genes were annotated, which were involved in eight biological function categories as a gene network of the DLP. Changing from susceptible to moderate plus resistant varieties in the CSLRP, 26 QTLs had 32 alleles involved, in which 19 genes were annotated from 25 QTL-alleles, including eight increased negative alleles on seven loci and 11 decreased positive alleles on 11 loci, showing the major genetic constitution changes for the antixenosis enhancement at the seedling stage in the CSLRP.

Molecular and genetic insights into secondary metabolic regulation underlying insect-pest resistance in legumes

Insect pests pose a major threat to agricultural production, resulting in significant economic losses for countries. A high infestation of insects in any given area can severely reduce crop yield and quality. This review examines the existing resources for managing insect pests and highlights alternative eco-friendly techniques to enhance insect pest resistance in legumes. Recently, the application of plant secondary metabolites has gained popularity in controlling insect attacks. Plant secondary metabolites encompass a wide range of compounds such as alkaloids, flavonoids, and terpenoids, which are often synthesized through intricate biosynthetic pathways. Classical methods of metabolic engineering involve manipulating key enzymes and regulatory genes to enhance or redirect the production of secondary metabolites in plants. Additionally, the role of genetic approaches, such as quantitative trait loci mapping, genome-wide association (GWAS) mapping, and metabolome-based GWAS in insect pest management is discussed, also, the role of precision breeding, such as genome editing technologies and RNA interference for identifying pest resistance and manipulating the genome to develop insect-resistant cultivars are explored, highlighting the positive contribution of plant secondary metabolites engineering-based resistance against insect pests. It is suggested that by understanding the genes responsible for beneficial metabolite compositions, future research might hold immense potential to shed more light on the molecular regulation of secondary metabolite biosynthesis, leading to advancements in insect-resistant traits in crop plants. In the future, the utilization of metabolic engineering and biotechnological methods may serve as an alternative means of producing biologically active, economically valuable, and medically significant compounds found in plant secondary metabolites, thereby addressing the challenge of limited availability.

Understandings and future challenges in soybean functional genomics and molecular breeding

Soybean (Glycine max) is a major source of plant protein and oil. Soybean breeding has benefited from advances in functional genomics. In particular, the release of soybean reference genomes has advanced our understanding of soybean adaptation to soil nutrient deficiencies, the molecular mechanism of symbiotic nitrogen (N) fixation, biotic and abiotic stress tolerance, and the roles of flowering time in regional adaptation, plant architecture, and seed yield and quality. Nevertheless, many challenges remain for soybean functional genomics and molecular breeding, mainly related to improving grain yield through high-density planting, maize-soybean intercropping, taking advantage of wild resources, utilization of heterosis, genomic prediction and selection breeding, and precise breeding through genome editing. This review summarizes the current progress in soybean functional genomics and directs future challenges for molecular breeding of soybean.

Genome-Wide Association Studies Reveal Novel Loci for Herbivore Resistance in Wild Soybean (Glycine soja)

The production of soybean [Glycine max (L.) Merr.] is seriously threatened by various leaf-feeding insects, and wild soybean [Glycine soja Sieb. & Zucc.] has a greater resistance capacity and genetic diversity. In this study, a natural population consisting of 121 wild soybean accessions was used for detecting insect resistance genes. The larval weight (LW) of the common cutworm (CCW), the resistance level (RL) and the index of damaged leaf (IDL) were evaluated as resistance indicators to herbivores. An association synonymous SNP AX-94083016 located in the coding region of the respiratory burst oxidase gene GsRbohA1 was identified by genome-wide association study (GWAS) analyses. The overexpression of GsRbohA1 in soybean hairy roots enhanced resistance to CCW. One SNP in the promoter region cosegregated with AX-94083016 contributing to soybean resistance to CCW by altering GsRbohA1 gene expression and reactive oxygen species (ROS) accumulation. Two major haplotypes, GsRbohA1^A and GsRbohA1^G, were identified based on the SNP. The resistant haplotype GsRbohA1^A predominates in wild soybeans, although it has been gradually lost in landraces and cultivars. The nucleotide diversity around GsRbohA1 is much lower in landraces and cultivars than in its ancestors. In conclusion, a new resistant haplotype, GsRbohA1^A, was identified in wild soybean, which will be a valuable gene resource for soybean insect resistance breeding through introducing into improvement lines, and it offers a strategy for exploring resistance gene resources from its wild relatives.

Methylome and transcriptome analyses of soybean response to bean pyralid larvae

BACKGROUND

Bean pyralid is one of the major leaf-feeding insects that affect soybean crops. DNA methylation can control the networks of gene expressions, and it plays an important role in responses to biotic stress. However, at present the genome-wide DNA methylation profile of the soybean resistance to bean pyralid has not been reported so far.

RESULTS

Using whole-genome bisulfite sequencing (WGBS) and RNA-sequencing (RNA-seq), we analyzed the highly resistant material (Gantai-2-2, HRK) and highly susceptible material (Wan82-178, HSK), under bean pyralid larvae feeding 0 h and 48 h, to clarify the molecular mechanism of the soybean resistance and explore its insect-resistant genes. We identified 2194, 6872, 39,704 and 40,018 differentially methylated regions (DMRs), as well as 497, 1594, 9596 and 9554 differentially methylated genes (DMGs) in the HRK0/HRK48, HSK0/HSK48, HSK0/HRK0 and HSK48/HRK48 comparisons, respectively. Through the analysis of global methylation and transcription, 265 differentially expressed genes (DEGs) were negatively correlated with DMGs, there were 34, 49, 141 and 116 negatively correlated genes in the HRK0/HRK48, HSK0/HSK48, HSK0/HRK0 and HSK48/HRK48, respectively. The MapMan cluster analysis showed that 114 negatively correlated genes were clustered in 24 pathways, such as protein biosynthesis and modification; primary metabolism; secondary metabolism; cell cycle, cell structure and component; RNA biosynthesis and processing, and so on. Moreover, CRK40; CRK62; STK; MAPK9; L-type lectin-domain containing receptor kinase VIII.2; CesA; CSI1; fimbrin-1; KIN-14B; KIN-14 N; KIN-4A; cytochrome P450 81E8; BEE1; ERF; bHLH25; bHLH79; GATA26, were likely regulatory genes involved in the soybean responses to bean pyralid larvae. Finally, 5 DMRs were further validated that the genome-wide DNA data were reliable through PS-PCR and 5 DEGs were confirmed the relationship between DNA methylation and gene expression by qRT-PCR. The results showed an excellent agreement with deep sequencing.

CONCLUSIONS

Genome-wide DNA methylation profile of soybean response to bean pyralid was obtained for the first time. Several specific DMGs which participated in protein kinase, cell and organelle, flavonoid biosynthesis and transcription factor were further identified to be likely associated with soybean response to bean pyralid. Our data will provide better understanding of DNA methylation alteration and their potential role in soybean insect resistance.

Identification and Validation of Major QTLs, Epistatic Interactions, and Candidate Genes for Soybean Seed Shape and Weight Using Two Related RIL Populations

Understanding the genetic mechanism underlying seed size, shape, and weight is essential for enhancing soybean cultivars. High-density genetic maps of two recombinant inbred line (RIL) populations, LM6 and ZM6, were evaluated across multiple environments to identify and validate M-QTLs as well as identify candidate genes behind major and stable quantitative trait loci (QTLs). A total of 239 and 43 M-QTLs were mapped by composite interval mapping (CIM) and mixed-model-based composite interval mapping (MCIM) approaches, from which 180 and 18, respectively, are novel QTLs. Twenty-two QTLs including four novel major QTLs were validated in the two RIL populations across multiple environments. Moreover, 18 QTLs showed significant AE effects, and 40 pairwise of the identified QTLs exhibited digenic epistatic effects. Thirty-four QTLs associated with seed flatness index (FI) were identified and reported here for the first time. Seven QTL clusters comprising several QTLs for seed size, shape, and weight on genomic regions of chromosomes 3, 4, 5, 7, 9, 17, and 19 were identified. Gene annotations, gene ontology (GO) enrichment, and RNA-seq analyses of the genomic regions of those seven QTL clusters identified 47 candidate genes for seed-related traits. These genes are highly expressed in seed-related tissues and nodules, which might be deemed as potential candidate genes regulating the seed size, weight, and shape traits in soybean. This study provides detailed information on the genetic basis of the studied traits and candidate genes that could be efficiently implemented by soybean breeders for fine mapping and gene cloning, and for marker-assisted selection (MAS) targeted at improving these traits individually or concurrently.

Identification of Additive-Epistatic QTLs Conferring Seed Traits in Soybean Using Recombinant Inbred Lines

Seed weight and shape are important agronomic traits that affect soybean quality and yield. In the present study, we used image analysis software to evaluate 100-seed weight and seed shape traits (length, width, perimeter, projection area, length/width, and weight/projection area) of 155 novel recombinant inbred soybean lines (NJRISX) generated by crossing "Su88-M21" and "XYXHD". We examined quantitative trait loci (QTLs) associated with the six traits (except seed weight per projection area), and identified 42 additive QTLs (5-8 QTLs per trait) accounting for 24.9-37.5% of the phenotypic variation (PV). Meanwhile, 2-4 epistatic QTL pairs per trait out of a total of 18 accounted for 2.5-7.2% of the PV; and unmapped minor QTLs accounted for the remaining 35.0-56.7% of the PV. A total of 28 additive and 11 epistatic QTL pairs were concentrated in nine joint QTL segments (JQSs), indicating that QTLs associated with seed weight and shape are closely related and interacted. An interaction was also detected between additive and epistatic QTL pairs and environment, which made significant contributions of 1.4-9.5% and 0.4-0.8% to the PV, respectively. We annotated 18 candidate genes in the nine JQSs, which were important for interpreting the close relationships among the six traits. These findings indicate that examining the interactions between closely related traits rather than only analyzing individual trait provides more useful insight into the genetic system of the interrelated traits for which there has been limited QTL information.

Influence of Perfluorobutanoic Acid (PFBA) on the Developmental Cycle and Damage Potential of the Beet Armyworm Spodoptera exigua (Hübner) (Insecta: Lepidoptera: Noctuidae)

Perfluorobutanoic acid (PFBA), one of the short-chain replacement perfluoroalkyl substances, has been shown to accumulate in plants. The potential of PFBA to modulate the developmental cycle of the beet armyworm, Spodoptera exigua, a polyphagous pest, was investigated. Second-instar larvae were fed with PFBA-spiked artificial diets and leaves from soybean plants grown with PFBA-spiked irrigation water. Spiked PFBA concentrations were 200 μg/kg for the artificial diet, whereas 405 to 15,190 ng/kg accumulated in the soybean leaves. The larvae fed with the PFBA-spiked diet showed a significant increase in weight gain compared with the controls over a 7-day exposure period. A similar weight gain trend was observed with larvae fed with the PFBA-containing soybean leaves, with the dose-response data fitting into a Brain-Cousens hormesis model with a 57% stimulation over controls. The artificial diet treatments showed 66.7% metamorphosed larva to pupa at 9 days after exposure (dpe) compared with 33.3% of the controls. The adult emergence at 16-dpe followed a similar trend with 57.7% and 33.3%, respectively, for the exposed and control groups. The duration of transition from larvae to adults was more symmetrical and 0.5 day faster for the exposed groups over controls. The beet armyworm caused more damage on leaves from the PFBA exposed plants in a nonmonotonic dose-response manner. The results suggest PFBA may have a stimulatory impact on some hormonal signaling pathways at low doses.

Quantitative trait loci analysis of seed oil content and composition of wild and cultivated soybean

BACKGROUND

Soybean oil is a major source of edible oil, and the domestication of wild soybean has resulted in significant changes in oil content and composition. Extensive efforts have been made to identify genetic loci that are related to soybean oil traits. The objective of this study was to identify quantitative trait loci (QTLs) related to soybean seed oil and compare the fatty acid composition between wild and cultivated soybean.

RESULTS

Using the specific-locus amplified fragment sequencing (SLAF-seq) method, a total of 181 recombinant inbred lines (RILs) derived from a cross between wild soybean ZYD00463 (Glycine soja) and cultivated soybean WDD01514 (Glycine max) were genotyped. Finally, a high-density genetic linkage map comprising 11,398 single-nucleotide polymorphism (SNP) markers on 20 linkage groups (LGs) was constructed. Twenty-four stable QTLs for seed oil content and composition were identified by model-based composite interval mapping (CIM) across multiple environments. Among these QTLs, 23 overlapped with or were adjacent to previously reported QTLs. One QTL, qPA10_1 (5.94-9.98 Mb) on Chr. Ten is a novel locus for palmitic acid. In the intervals of stable QTLs, some interesting genes involved in lipid metabolism were detected.

CONCLUSIONS

We developed 181 RILs from a cross between wild soybean ZYD00463 and cultivated soybean WDD01514 and constructed a high-density genetic map using the SLAF-seq method. We identified 24 stable QTLs for seed oil content and compositions, which includes qPA10_1 on Chr. 10, a novel locus for palmitic acid. Some interesting genes in the QTL regions were also detected. Our study will provide useful information for scientists to learn about genetic variations in lipid metabolism between wild and cultivated soybean.

Genome-Wide Detection of Major and Epistatic Effect QTLs for Seed Protein and Oil Content in Soybean Under Multiple Environments Using High-Density Bin Map

Seed protein and oil content are the two important traits determining the quality and value of soybean. Development of improved cultivars requires detailed understanding of the genetic basis underlying the trait of interest. However, it is prerequisite to have a high-density linkage map for precisely mapping genomic regions, and therefore the present study used high-density genetic map containing 2267 recombination bin markers distributed on 20 chromosomes and spanned 2453.79 cM with an average distance of 1.08 cM between markers using restriction-site-associated DNA sequencing (RAD-seq) approach. A recombinant inbred line (RIL) population of 104 lines derived from a cross between Linhefenqingdou and Meng 8206 cultivars was evaluated in six different environments to identify main- and epistatic-effect quantitative trait loci (QTLs)as well as their interaction with environments. A total of 44 main-effect QTLs for protein and oil content were found to be distributed on 17 chromosomes, and 15 novel QTL were identified for the first time. Out of these QTLs, four were major and stable QTLs, viz., qPro-7-1, qOil-8-3, qOil-10-2 and qOil-10-4, detected in at least two environments plus combined environment with R² values >10%. Within the physical intervals of these four QTLs, 111 candidate genes were screened for their direct or indirect involvement in seed protein and oil biosynthesis/metabolism processes based on gene ontology and annotation information. Based on RNA sequencing (RNA-seq) data analysis, 15 of the 111 genes were highly expressed during seed development stage and root nodules that might be considered as the potential candidate genes. Seven QTLs associated with protein and oil content exhibited significant additive and additive × environment interaction effects, and environment-independent QTLs revealed higher additive effects. Moreover, three digenic epistatic QTLs pairs were identified, and no main-effect QTLs showed epistasis. In conclusion, the use of a high-density map identified closely linked flanking markers, provided better understanding of genetic architecture and candidate gene information, and revealed the scope available for improvement of soybean quality through marker assisted selection (MAS).

QTL mapping of antixenosis resistance to common cutworm (Spodoptera litura Fabricius) in wild soybean (Glycine soja)

The common cutworm (CCW; Spodoptera litura Fabricius) is a serious herbivorous insect pest of soybean (Glycine max) in Asia and Oceania. Previously, we identified quantitative trait loci (QTLs) for CCW-antibiosis-resistance, CCW-1 and CCW-2, and antixenosis-resistance, qRslx1 and qRslx2, in the cultivar 'Himeshirazu'. The effects of these QTLs are useful in the breeding of CCW-resistant cultivars. In this study, we conducted an antixenosis bioassay on CCW using recombinant inbred lines derived from a cross between a wild soybean (Glycine soja) and the leading cultivar 'Fukuyutaka' to identify CCW-resistance genes in G. soja. The QTL analysis revealed six and four novel antixenosis-resistance QTLs in 2012 and 2013, respectively. Among them, the QTLs on chromosomes 2 and 7, designated qRslx4 and qRslx3, respectively, were stably detected in both years. qRslx3 exhibited the largest effect in both years, suggesting that qRslx3 can be exploited in the breeding of CCW-resistant soybean. Furthermore, qRslx3 and qRslx4 can be used, along with previously reported QTLs from 'Himeshirazu', to enhance the CCW-resistance of soybean cultivars because their chromosomal positions are unique. These new CCW-resistance QTLs from G. soja should play important roles in the breeding of CCW-resistant soybean cultivars.

Comparative transcriptome analysis of soybean response to bean pyralid larvae

BACKGROUND

Soybean is one of most important oilseed crop worldwide, however, its production is often limited by many insect pests. Bean pyralid is one of the major soybean leaf-feeding insects in China. To explore the defense mechanisms of soybean resistance to bean pyralid, the comparative transcriptome sequencing was completed between the leaves infested with bean pyralid larvae and no worm of soybean (Gantai-2-2 and Wan82-178) on the Illumina HiSeq™ 2000 platform.

RESULTS

In total, we identified 1744 differentially expressed genes (DEGs) in the leaves of Gantai-2-2 (1064) and Wan82-178 (680) fed by bean pyralid for 48 h, compared to 0 h. Interestingly, 315 DEGs were shared by Gantai-2-2 and Wan82-178, while 749 and 365 DEGs specifically identified in Gantai-2-2 and Wan82-178, respectively. When comparing Gantai-2-2 with Wan82-178, 605 DEGs were identified at 0 h feeding, and 468 DEGs were identified at 48 h feeding. Gene Ontology (GO) annotation analysis revealed that the DEGs were mainly involved in the metabolic process, single-organism process, cellular process, responses to stimulus, catalytic activities and binding. Pathway analysis showed that most of the DEGs were associated with the plant-pathogen interaction, phenylpropanoid biosynthesis, phenylalanine metabolism, flavonoid biosynthesis, peroxisome, plant hormone signal transduction, terpenoid backbone biosynthesis, and so on. Finally, we used qRT-PCR to validate the expression patterns of several genes and the results showed an excellent agreement with deep sequencing.

CONCLUSIONS

According to the comparative transcriptome analysis results and related literature reports, we concluded that the response to bean pyralid feeding might be related to the disturbed functions and metabolism pathways of some key DEGs, such as DEGs involved in the ROS removal system, plant hormone metabolism, intracellular signal transduction pathways, secondary metabolism, transcription factors, biotic and abiotic stresses. We speculated that these genes may have played an important role in synthesizing substances to resist insect attacks in soybean. Our results provide a valuable resource of soybean defense genes that will benefit other studies in this field.

Proteomic analysis by iTRAQ-MRM of soybean resistance to Lamprosema Indicate

BACKGROUND

Lamprosema indicate is a major leaf feeding insect pest to soybean, which has caused serious yield losses in central and southern China. To explore the defense mechanisms of soybean resistance to Lamprosema indicate, a highly resistant line (Gantai-2-2) and a highly susceptible line (Wan 82-178) were exposed to Lamprosema indicate larval feedings for 0 h and 48 h, and the differential proteomic analyses of these two lines were carried out.

RESULTS

The results showed that 31 differentially expressed proteins (DEPs) were identified in the Gantai-2-2 when comparing 48 h feeding with 0 h feeding, and 53 DEPs were identified in the Wan 82-178. 28 DEPs were identified when comparing Gantai-2-2 with Wan 82-178 at 0 h feeding. The bioinformatic analysis results showed that most of the DEPs were associated with ribosome, linoleic acid metabolism, flavonoid biosynthesis, phenylpropanoid biosynthesis, peroxisome, stilbenoid, diarylheptanoid and gingerol biosynthesis, glutathione metabolism, pant hormone signal transduction, and flavone and flavonol biosynthesis, as well as other resistance related metabolic pathways. The MRM analysis showed that the iTRAQ results were reliable.

CONCLUSIONS

According to the analysis of the DEPs results, the soybean defended or resisted the Lamprosema indicate damage by the induction of a synthesis of anti-digestive proteins which inhibit the growth and development of insects, reactive oxygen species scavenging, signaling pathways, secondary metabolites synthesis, and so on.

Development of INDEL Markers for Genetic Mapping Based on Whole Genome Resequencing in Soybean

Soybean [Glycine max (L.) Merrill] is an important crop worldwide. In this study, a Chinese local soybean cultivar, Hedou 12, was resequenced by next generation sequencing technology to develop INsertion/DELetion (INDEL) markers for genetic mapping. 49,276 INDEL polymorphisms and 242,059 single nucleotide polymorphisms were detected between Hedou 12 and the Williams 82 reference sequence. Of these, 243 candidate INDEL markers ranging from 5-50 bp in length were chosen for validation, and 165 (68%) of them revealed polymorphisms between Hedou 12 and Williams 82. The validated INDEL markers were also tested in 12 other soybean cultivars. The number of polymorphisms in the pairwise comparisons of 14 soybean cultivars varied from 27 to 165. To test the utility of these INDEL markers, they were used to perform genetic mapping of a crinkly leaf mutant, and the CRINKLY LEAF locus was successfully mapped to a 360 kb region on chromosome 7. This research shows that high-throughput sequencing technologies can facilitate the development of genome-wide molecular markers for genetic mapping in soybean.

QTL Analysis of Head Splitting Resistance in Cabbage (Brassica oleracea L. var. capitata) Using SSR and InDel Makers Based on Whole-Genome Re-Sequencing

Head splitting resistance (HSR) in cabbage is an important trait closely related to both quality and yield of head. However, the genetic control of this trait remains unclear. In this study, a doubled haploid (DH) population derived from an intra-cross between head splitting-susceptible inbred cabbage line 79-156 and resistant line 96-100 was obtained and used to analyze inheritance and detect quantitative trait loci (QTLs) for HSR using a mixed major gene/polygene inheritance analysis and QTL mapping. HSR can be attributed to additive-epistatic effects of three major gene pairs combined with those of polygenes. Negative and significant correlations were also detected between head Hsr and head vertical diameter (Hvd), head transverse diameter (Htd) and head weight (Hw). Using the DH population, a genetic map was constructed with simple sequence repeat (SSR) and insertion-deletion (InDel) markers, with a total length of 1065.9 cM and average interval length of 4.4 cM between adjacent markers. Nine QTLs for HSR were located on chromosomes C3, C4, C7, and C9 based on 2 years of phenotypic data using both multiple-QTL mapping and inclusive composite interval mapping. The identified QTLs collectively explained 39.4 to 59.1% of phenotypic variation. Three major QTLs (Hsr 3.2, 4.2, 9.2) showing a relatively larger effect were robustly detected in different years or with different mapping methods. The HSR trait was shown to have complex genetic mechanisms. Results from QTL mapping and classical genetic analysis were consistent. The QTLs obtained in this study should be useful for molecular marker-assisted selection in cabbage breeding and provide a foundation for further research on HSR genetic regulation.

Marker-assisted breeding for transgressive seed protein content in soybean [Glycine max (L.) Merr]

KEY MESSAGE

After two cycles of marker-assisted breeding on three loci, lines with transgressive segregation of 8.22-9.32 % protein content were developed based on four original soybean parents with 35.35-44.83 % protein content. Marker-assisted breeding has been an innovative approach in conventional breeding, which is to be further demonstrated, especially for quantitative traits. A study on continuous transgressive breeding for seed protein content (SPC) in soybean using marker-assisted procedures is reported here. The SPC of the recombinant inbred line (RIL) population XG varied in 38.04-47.54 % under five environments with P 1 of 35.35 %, P 2 of 44.34 % and total heritability of 89.11 %. A transgressive segregant XG30 with SPC 45.53 % was selected for further improvement. The linkage mapping of XG showed its genetic constitution composed of five additive QTL (32.16 % of phenotypic variation or PV) and two pairs of epistatic QTL (2.96 % PV) using 400 SSR markers with the remnant heritability 53.99 % attributed to the undetected collective of minor QTL. Another transgressive segregant WT133 with SPC 48.39 % was selected from the RIL population WT (44.83 % SPC for both parents). XG30 and WT133 were genotyped on the three major additive QTL (Prot-08-1, Prot-14-1 and Prot-19-2) as A 2 A 2 B 2 B 2 L 1 L 1 and A 1 A 1 B 1 B 1 L 2 L 2 , respectively. From WT133×XG30, surprising transgressive progenies were obtained, among which the recombinants with all three positive alleles A 2 _B 2 _L 2 _ performed the highest SPC, especially that of Prot-08-1. The five F 2-derived superior families showed their means higher than the high parent value in F 2:3 and F 2:4 and more transgressive effect in F 2:5:6, with the highest as high as 54.15 %, or 4.82 and 9.32 % more than WT133 and its original high parent, respectively. This study demonstrated the efficiency of marker-assisted procedure in breeding for transgressive segregation of quantitative trait.

Quantitative trait loci mapping and genetic dissection for lint percentage in upland cotton (Gossypium hirsutum)

Lint percentage is an important character of cotton yield components and it is also correlated with cotton fibre development. In this study, we used a high lint percentage variety, Baimian1, and a low lint percentage, TM-1 genetic standard for Gossypium hirsutum, as parents to construct a mapping populations in upland cotton (G. hirsutum). A quantitative trait locus/loci (QTL) analysis of lint percentage was performed by using two mapping procedures; composite interval mapping (CIM), inclusive composite interval mapping (ICIM) and the F2:3 populations in 2 years. Six main-effect QTL (M-QTL) for lint percentage (four significant and two suggestive) were detected in both years by CIM, and were located on chr. 3, chr. 19, chr. 26 and chr. 5/chr. 19. Of the six QTL, marker intervals and favourable gene sources of the significant M-QTL, qLP-3(2010) and qLP-3(2011) were consistent. These QTL were also detected by ICIM, and therefore, should preferentially be used for markerassisted selection (MAS) of lint percentage. Another M-QTL, qLP-19(2010), was detected by two mapping procedures, and it could also be a candidate for MAS. We detected the interaction between two M-QTL and environment, and 11 epistatic QTL (E-QTL) and their interaction with environment by using ICIM. The study also found two EST-SSRs, NAU1187 and NAU1255, linked to M-QTL for lint percentage that could be candidate markers affecting cotton fibre development.

Identification of quantitative trait loci controlling linolenic acid concentration in PI483463 (Glycine soja)

KEY MESSAGE

The QTLs controlling alpha-linolenic acid concentration from wild soybean were mapped on nine soybean chromosomes with various phenotypic variations. New QTLs for alpha-linolenic acid were detected in wild soybean. Alpha-linolenic acid (ALA) is a polyunsaturated fatty acid desired in human and animal diets. Some wild soybean (Glycine soja) genotypes are high in ALA. The objective of this study was to identify quantitative trait loci (QTLs) controlling ALA concentration in a wild soybean accession, PI483463. In total, 188 recombinant inbred lines of F5:6, F5:7, and F5:8 generations derived from a cross of wild soybean PI483463 (~15 % ALA) and cultivar Hutcheson (~9 % ALA) were planted in four environments. Harvested seeds were used to measure fatty acid concentration. Single nucleotide polymorphism markers of the universal soybean linkage panel (USLP 1.0) and simple sequence repeat markers were used for molecular genotyping. Nine putative QTLs were identified that controlled ALA concentration by model-based composite interval mapping and mapped to different soybean chromosomes. The QTLs detected in four environments explained 2.4-7.9 % of the total phenotypic variation (PV). Five QTLs, qALA5_3, qALA6_1, qALA14_1, qALA15_1, and qALA17_1, located on chromosomes 5, 6, 14, 15, and 17 were identified by model-based composite interval mapping and composite interval mapping in two individual environments. Among them, qALA6_1 showed the highest contribution to the PV with 10.0-10.2 % in two environments. The total detected QTLs for additive and epistatic effects explained 52.4 % of the PV for ALA concentration. These findings will provide useful information for understanding genetic structure and marker-assisted breeding programs to increase ALA concentration in seeds derived from wild soybean PI483463.