Identification of QTL for maize grain yield and kernel-related traits

Grain yield (GY) is one of the most important and complex quantitative traits in maize (Zea mays L.) breeding practice. Quantitative trait loci (QTLs) for GY and three kernel-related traits were detected in a set of recombinant inbred lines (RILs). One hundred and seven simple sequence repeats (SSRs) and 168 insertion/deletion polymorphism markers (Indels) were used to genotype RILs. Eight QTLs were found to be associated with four yield-related traits: GY, 100-kernel weight (HKW), 10-kernel length (KL), and 10-kernel length width (KW). Each QTL explained between 5.96 (qKL2-1) and 13.05 (qKL1-1) per cent of the phenotypic variance. Notably, one common QTL, located at the marker interval between bnlg1893 and chr2-236477 (chromosomal bin 2.09) simultaneously controlled GY and HKW; another common QTL, at bin 2.03 was simultaneously responsible for HKW and KW. Of the QTLs identified, only one pair of significant epistatic interaction involved in chromosomal region at bin 2.03 was detected for HKW; no significant QTL × environment interactions were observed. These results provide the common QTLs and for marker-assisted breeding.     

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.

Abstract

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 F_5:6, F_5:7, and F_5:8 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.     

Genetic variants in root architecture-related genes in a Glycine soja accession,a potential resource to improve cultivated soybean

Background

Root system architecture is important for water acquisition and nutrient acquisition for all crops. In soybean breeding programs, wild soybean alleles have been used successfully to enhance yield and seed composition traits, but have never been investigated to improve root system architecture. Therefore, in this study, high-density single-feature polymorphic markers and simple sequence repeats were used to map quantitative trait loci (QTLs) governing root system architecture in an inter-specific soybean mapping population developed from a cross between Glycine max and Glycine soja.

Results

Wild and cultivated soybean both contributed alleles towards significant additive large effect QTLs on chromosome 6 and 7 for a longer total root length and root distribution, respectively. Epistatic effect QTLs were also identified for taproot length, average diameter, and root distribution. These root traits will influence the water and nutrient uptake in soybean. Two cell division-related genes (D type cyclin and auxin efflux carrier protein) with insertion/deletion variations might contribute to the shorter root phenotypes observed in G. soja compared with cultivated soybean. Based on the location of the QTLs and sequence information from a second G. soja accession, three genes (slow anion channel associated 1 like, Auxin responsive NEDD8-activating complex and peroxidase), each with a non-synonymous single nucleotide polymorphism mutation were identified, which may also contribute to changes in root architecture in the cultivated soybean. In addition, Apoptosis inhibitor 5-like on chromosome 7 and slow anion channel associated 1-like on chromosome 15 had epistatic interactions for taproot length QTLs in soybean.

Conclusion

Rare alleles from a G. soja accession are expected to enhance our understanding of the genetic components involved in root architecture traits, and could be combined to improve root system and drought adaptation in soybean.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1334-6) contains supplementary material, which is available to authorized users.     

Genetic mapping of QTLs conditioning soybean sprout yield and quality

Soybean sprouts have been used as a food in the Orient since ancient times. In this study, 92 restriction fragment length polymorphism (RFLP) loci and two morphological markers (W1 and T) were used to identify quantitative trait loci (QTLs) associated with soybean sprout-related traits in 100 F₂-derived lines from the cross of ’Pureunkong’×’Jinpumkong 2’. The genetic map consisted of 76 loci which covered about 756 cM and converged into 20 linkage groups. Eighteen markers remained unlinked. Phenotypic data were collected in 1996 and 1997 for hypocotyl length, percentage of abnormal seedlings, and sprout yield 6 days after germination at 20°C. Hypocotyl length was determined as the average length from the point of initiation of the first secondary root to the point of attachment of the cotyledons. The number of decayed seeds and seedlings, plus the number of stunted seedlings (less than 2-cm growth), was recorded a s abnormal seedlings. Seed weight was determined based on the 50-seed sample. Sprout yield was recorded as the total fresh weight of soybean sprouts produced from the 50-seed sample divided by the dry weight of the 50-seed sample. Four QTLs were associated with sprout yield in the combined analysis across 2 years. For the QTL linked to L154 on the Linkage Group (LG) G the positive allele was derived from Pureunkong (R ² = 0.19), whereas at the other three QTLs (A089 on LG B1, A668n on LG K and B046 on LG L) the positive alleles were from Jinpumkong 2. QTLs conditioning seed weight were linked to markers A802n (LG B1), A069 (LG E), Cr321 (LG F) and A235 (LG G). At these four markers, the Jinpumkong allele increased seed weight. Markers K011n on LG B1, W1 on LG F and A757 on LG L were linked to QTLs conditioning hypocotyl length; and Bng119, K455n and K418n to QTLs conditioning the abnormal seedlings. The QTLs conditioning sprout yield were in the same genomic locations as the QTLs for seed weight identified in this population or from previously published research, indicating that QTLs for sprout yield are genetically linked to seed-weight QTLs or else that seed-weight QTLs pleiotropically condition sprout yield. These data demonstrate that effective marker-assisted selection may be feasible for enhancing sprout yield in a soybean. The transgressive segregation of sprout yield, as well as the existence of two QTLs conditioning greater than 10% of the phenotypic variation in sprout yields provides an opportunity to select for progeny lines with a greater sprout yield than currently preferred cultivars such as Pureunkong. Received: 23 August 2000 / Accepted: 23 January 2001     

Development of Chromosome Segment Substitution Lines Derived from Backcross between Two Sequenced Rice Cultivars, <Emphasis Type="Italic">Indica</Emphasis> Recipient 93-11 and <Emphasis Type="Italic">Japonica</Emphasis> Donor Nipponbare

Chromosome segment substitution lines (CSSLs) are powerful tools for detecting and precisely mapping quantitative trait loci (QTLs) and evaluating gene action as a single factor. In this study, 103 CSSLs were produced using two sequenced rice cultivars: 93-11, an elite restorer indica cultivar as recipient, and Nipponbare, a japonica cultivar, as donor. Each CSSL carried a single chromosome substituted segment. The total length of the substituted segments in the CSSLs was 2,590.6 cM, which was 1.7 times of the rice genome. To evaluate the potential application of these CSSLs for QTL detection, phenotypic variations of seed shattering, grain length and grain width in 10 CSSLs were observed. Two QTLs for seed shattering and three for grain length and grain width were identified and mapped on rice chromosomes. The results demonstrate that CSSLs are excellent genetic materials for dissecting complex traits into a set of monogenic loci. These CSSLs are of great potential value for QTL mapping and plant marker-assisted breeding (MAB).     

Genetic control of soybean seed oil: II. QTL and genes that increase oil concentration without decreasing protein or with increased seed yield

Soybean [Glycine max (L.) Merrill] seed oil is the primary global source of edible oil and a major renewable and sustainable feedstock for biodiesel production. Therefore, increasing the relative oil concentration in soybean is desirable; however, that goal is complex due to the quantitative nature of the oil concentration trait and possible effects on major agronomic traits such as seed yield or protein concentration. The objectives of the present study were to study the relationship between seed oil concentration and important agronomic and seed quality traits, including seed yield, 100-seed weight, protein concentration, plant height, and days to maturity, and to identify oil quantitative trait loci (QTL) that are co-localized with the traits evaluated. A population of 203 F_4:6 recombinant inbred lines, derived from a cross between moderately high oil soybean genotypes OAC Wallace and OAC Glencoe, was developed and grown across multiple environments in Ontario, Canada, in 2009 and 2010. Among the 11 QTL associated with seed oil concentration in the population, which were detected using either single-factor ANOVA or multiple QTL mapping methods, the number of QTL that were co-localized with other important traits QTL were six for protein concentration, four for seed yield, two for 100-seed weight, one for days to maturity, and one for plant height. The oil-beneficial allele of the QTL tagged by marker Sat_020 was positively associated with seed protein concentration. The oil favorable alleles of markers Satt001 and GmDGAT2B were positively correlated with seed yield. In addition, significant two-way epistatic interactions, where one of the interacting markers was solely associated with seed oil concentration, were identified for the selected traits in this study. The number of significant epistatic interactions was seven for yield, four for days to maturity, two for 100-seed weight, one for protein concentration, and one for plant height. The identified molecular markers associated with oil-related QTL in this study, which also have positive effects on other important traits such as seed yield and protein concentration, could be used in the soybean marker breeding programs aimed at developing either higher seed yield and oil concentration or higher seed protein and oil concentration per hectare. Alternatively, selecting complementary parents with greater breeding values due to positive epistatic interactions could lead to the development of higher oil soybean cultivars.     

Combining QTL and candidate gene analysis with phenotypic model to unravel the relationship between lodging and related traits in soybean

Lodging is one of the major influencing factors of yield and quality in soybean [Glycine max (L.) Merr.] and other crops. To dissect the genetic basis of lodging in soybean, a recombinant inbred line population consisting of 165 lines was used to evaluate lodging percentage and eight related traits (branch number, internode length, number of nodes, plant height, stem diameter, stem strength, root length, and root weight) in three environments. Regression analysis indicated that plant height and root weight, which explain more than 55% of the variation in lodging percentage, might be the key factors influencing lodging in soybean. Nine consensus quantitative trait locus (QTLs) of lodging percentage were detected in one to three environments. Of which, eight consensus QTLs were colocated with 16 consensus QTLs of lodging-related traits by meta-analysis. In addition, seven candidate genes with the biological functions of shoot branching, root development, internode elongation, and lignin biosynthesis were identified on four pleiotropic QTL regions (oq.13-1, oq.13-2, oq.19-2, and oq.19-3) for lodging percentage and related traits. These findings showed that the consensus QTLs of lodging percentage might result from the pleiotropic QTLs affecting the lodging-related traits. Soybean lodging is determined by the cumulative effect of many traits/processes of growth and development. The combination of MAS, statistical model, and phenotypic selection will provide a powerful breeding strategy for lodging resistance in soybean.     

Chromosome segment detection for seed size and shape traits using an improved population of wild soybean chromosome segment substitution lines

Size and shape of soybean seeds are closely related to seed yield and market value. Annual wild soybeans have the potential to improve cultivated soybeans, but their inferior seed characteristics should be excluded. To detect quantitative trait loci (QTLs)/segments of seed size and shape traits in annual wild soybean, its chromosome segment substitution lines (CSSLs) derived from NN1138-2 (recurrent parent, Glycine max) and N24852 (donor parent, Glycine soja) and then modified 2 iterations (coded SojaCSSLP3) were improved further to contain more lines (diagonal segments) and less heterozygous and missing portions. The new population (SojaCSSLP4) composed of 195 CSSLs was evaluated under four environments, and 11, 13, 7, 15 and 14 QTLs/segments were detected for seed length (SL), seed width (SW), seed roundness (SR), seed perimeter (SP) and seed cross section area (SA), respectively, with all 60 wild allele effects negative. Among them, 16 QTLs/segments were shared by 2–5 traits, respectively, but 0–3 segments for each of the 5 traits were independent. The non-shared Satt274 and shared Satt305, Satt540 and Satt239 were major segments, along with other segments composed of two different but related sets of genetic systems for SR and the other 4 traits, respectively. Compared with the literature, 7 SL, 5 SW and 2 SR QTLs/segments were also detected in cultivated soybeans; allele distinction took place between cultivated and wild soybeans, and also among cultivated parents. The present mapping is understood as macro-segment mapping, the segments may be further dissected into smaller segments as well as corresponding QTLs/genes.     

Mapping soybean aphid resistance genes in PI 567598B

The soybean aphid (Aphis glycines Matsumura) has been a major pest of soybean [Glycine max (L.) Merr.] in North America since it was first reported in 2000. Our previous study revealed that the strong aphid resistance of plant introduction (PI) 567598B was controlled by two recessive genes. The objective of this study was to locate these two genes on the soybean genetic linkage map using molecular markers. A mapping population of 282 F_4:5 lines derived from IA2070 × E06902 was evaluated for aphid resistance in a field trial in 2009 and a greenhouse trial in 2010. Two quantitative trait loci (QTLs) were identified using the composite and multiple interval mapping methods, and were mapped on chromosomes 7 (linkage group M) and 16 (linkage group J), respectively. E06902, a parent derived from PI 567598B, conferred resistance at both loci. In the 2010 greenhouse trial, each of the two QTLs explained over 30 % of the phenotypic variation. Significant epistatic interaction was also found between these two QTLs. However, in the 2009 field trial, only the QTL on chromosome 16 was found and it explained 56.1 % of the phenotypic variation. These two QTLs and their interaction were confirmed with another population consisting of 94 F_2:5 lines in the 2008 and 2009 greenhouse trials. For both trials in the alternative population, these two loci explained about 50 and 80.4 % of the total phenotypic variation, respectively. Our study shows that soybean aphid isolate used in the 2009 field trial defeated the QTL found on chromosome 7. Presence of the QTL on chromosome 16 conferred soybean aphid resistance in all trials. The markers linked to the aphid-resistant QTLs in PI 567598B or its derived lines can be used in marker-assisted breeding for aphid resistance.     

Seed quality QTLs identified in a molecular map of early maturing soybean

This study identified QTLs influencing seed quality characters in a cross of two early maturing soybean (Glycine max [L.] Merr.) cultivars (Ma.Belle and Proto) adapted to the short growing seasons of Central Europe. A molecular linkage map was constructed by using 113 SSR, 6 RAPD and 1 RFLP markers segregating in 82 individuals of an F₂ population. The map consists of 23 linkage groups and corresponds wellto previously published soybean maps. Using phenotypic data of the F₂-derived lines grown in five environments, four markers for protein content, three for oil content and eight for seed weight were identified. Four from fifteen seed quality QTL-regions identified in the present study were also found by other authors. Markers associated with seed weight QTLs were consistent across all environments and proved to have effects large enough to be useful in a marker-assisted breeding program, whereas protein and oil QTLs showed environmental interactions. Received: 9 October 2000 / Accepted: 26 February 2001     

甘蓝型油菜千粒重性状的QTL初步定位研究

千粒重是油菜重要的产量相关性状之一,构建油菜遗传连锁图谱是研究其产量性状基因的前提。本研究利用小孢子培养技术,选育出了甘蓝型油菜大粒品系(G-42)和小粒品系(7-9)的纯合DH系DH-G-42和DH-7-9,其千粒重分别为6.24 g和2.42 g,二者比值达2.58。以DH-G-42为母本、DH-7-9为父本,构建了含190个单株的F2遗传作图群体,利用SSR和SRAP标记技术绘制遗传连锁图谱,该图谱共包含20个连锁群,涉及128个SSR标记和100个SRAP标记,图谱总长1546.6cM,标记间平均图距为6.78cM。本研究共检测到3个与千粒重性状相关的QTL,分别位于A9和C1连锁群,其中qSW-A9-1和qSW-A9-2贡献率分别达到10.98%和27.45%,均可视为控制粒重的主效QTL。本研究为后续进行油菜千粒重性状QTL的精细定位分析、分子标记辅助选择育种及新基因的克隆等奠定了基础。     

QTL mapping and epistatic interaction analysis of field resistance to sudden death syndrome (<Emphasis Type="Italic">Fusarium virguliforme</Emphasis>) in soybean

Key message

Two interactive quantitative trait loci (QTLs) controlled the field resistance to sudden death syndrome (SDS) in soybean. The interaction between them was confirmed.

Abstract

Sudden death syndrome (SDS), caused by Fusarium virguliforme, is a major disease of soybean [Glycine max (L.) Merr.] in the United States. Breeding for soybean resistance to SDS is the most cost-effective method to manage the disease. The objective of this study was to identify and characterize quantitative trait loci (QTLs) underlying field resistance to SDS in a recombinant inbred line population from the cross GD2422?×?LD01-5907. This population was genotyped with 1786 polymorphic single nucleotide polymorphisms (SNPs) using SoySNP6 K iSelect BeadChip and evaluated for SDS resistance in a naturally infested field. Four SDS resistance QTLs were mapped on Chromosomes 4, 8, 12 and 18. The resistant parent, LD01-5907, contributed the resistance alleles for the QTLs on Chromosomes 8 and 18 (qSDS-8 and qSDS-18), while the other parent, GD2422, provided the resistance alleles for the QTLs on Chromosomes 4 and 12 (qSDS-4 and qSDS-12). The minor QTL on Chromosome 12 (qSDS-12) is novel. The QTL on Chromosomes 8 and 18 (qSDS-8 and qSDS-18) overlapped with two soybean cyst nematode resistance-related loci, Rhg4 and Rhg1, respectively. A significant interaction between qSDS-8 and qSDS-18 was detected by disease incidence. Individual effects together with the interaction effect explained around 70% of the phenotypic variance. The epistatic interaction of qSDS-8 and qSDS-18 was confirmed by the field performance across multiple years. Furthermore, the resistance alleles at qSDS-8 and qSDS-18 were demonstrated to be recessive. The SNP markers linked to these QTLs will be useful for marker-assisted breeding to enhance the SDS resistance.

     

Dissecting Quantitative Trait Loci for Boron Efficiency across Multiple Environments in Brassica napus

High yield is the most important goal in crop breeding, and boron (B) is an essential micronutrient for plants. However, B deficiency, leading to yield decreases, is an agricultural problem worldwide. Brassica napus is one of the most sensitive crops to B deficiency, and considerable genotypic variation exists among different cultivars in response to B deficiency. To dissect the genetic basis of tolerance to B deficiency in B. napus, we carried out QTL analysis for seed yield and yield-related traits under low and normal B conditions using the double haploid population (TNDH) by two-year and the BQDH population by three-year field trials. In total, 80 putative QTLs and 42 epistatic interactions for seed yield, plant height, branch number, pod number, seed number, seed weight and B efficiency coefficient (BEC) were identified under low and normal B conditions, singly explaining 4.15–23.16% and 0.53–14.38% of the phenotypic variation. An additive effect of putative QTLs was a more important controlling factor than the additive-additive effect of epistatic interactions. Four QTL-by-environment interactions and 7 interactions between epistatic interactions and the environment contributed to 1.27–4.95% and 1.17–3.68% of the phenotypic variation, respectively. The chromosome region on A2 of SYLB-A2 for seed yield under low B condition and BEC-A2 for BEC in the two populations was equivalent to the region of a reported major QTL, BE1. The B. napus homologous genes of Bra020592 and Bra020595 mapped to the A2 region and were speculated to be candidate genes for B efficiency. These findings reveal the complex genetic basis of B efficiency in B. napus. They provide a basis for the fine mapping and cloning of the B efficiency genes and for breeding B-efficient cultivars by marker-assisted selection (MAS).     

Construction of Chromosome Segment Substitution Lines in Peanut (Arachis hypogaea L.) Using a Wild Synthetic and QTL Mapping for Plant Morphology

Chromosome segment substitution lines (CSSLs) are powerful QTL mapping populations that have been used to elucidate the molecular basis of interesting traits of wild species. Cultivated peanut is an allotetraploid with limited genetic diversity. Capturing the genetic diversity from peanut wild relatives is an important objective in many peanut breeding programs. In this study, we used a marker-assisted backcrossing strategy to produce a population of 122 CSSLs from the cross between the wild synthetic allotetraploid (A. ipaënsis×A. duranensis)^4x and the cultivated Fleur11 variety. The 122 CSSLs offered a broad coverage of the peanut genome, with target wild chromosome segments averaging 39.2 cM in length. As a demonstration of the utility of these lines, four traits were evaluated in a subset of 80 CSSLs. A total of 28 lines showed significant differences from Fleur11. The line×trait significant associations were assigned to 42 QTLs: 14 for plant growth habit, 15 for height of the main stem, 12 for plant spread and one for flower color. Among the 42 QTLs, 37 were assigned to genomic regions and three QTL positions were considered putative. One important finding arising from this QTL analysis is that peanut growth habit is a complex trait that is governed by several QTLs with different effects. The CSSL population developed in this study has proved efficient for deciphering the molecular basis of trait variations and will be useful to the peanut scientific community for future QTL mapping studies.     

Quantitative trait locus analysis of unsaturated fatty acids in a recombinant inbred population of soybean

Soybean [Glycine max (L.) Merr.] is an important oilseed crop which produces about 30 % of the world’s edible vegetable oil. The quality of soybean oil is determined by its fatty acid composition. Soybean oil high in oleic and low in linolenic fatty acids is desirable for human consumption and other uses. The objectives of this study were to identify quantitative trait loci (QTLs) for unsaturated fatty acids and to evaluate the genetic effects of single QTL and QTL combinations in soybean. A population of recombinant inbred lines derived from the cross of SD02-4-59 × A02-381100 was evaluated for fatty acid content in seven environments. In total, 516 polymorphic single nucleotide polymorphism markers, 477 polymorphic simple sequence repeat markers and three GmFAD3 genes were used to genotype the mapping population. By using the composite interval mapping and/or the interval mapping method, a total of 15 QTLs for the three unsaturated fatty acids were detected in more than two environments. Two QTLs for oleic acid on linkage groups G [chromosome (Chr) 18] (qOLE-G) and J (Chr 16) (qOLE-J), three QTLs for linoleic acid on linkage groups A1 (Chr 5) (qLLE-A1) and G (Chr 18) (qLLE-G-1 and qLLE-G-2), and five QTLs for linolenic acid on linkage groups C2 (Chr 6), D1a (Chr 1), D1b (Chr 2), F (Chr 13) and G (Chr 18) were consistently detected in at least three individual environments and the average data over all environments. Significant QTL × QTL interactions were not detected. However, significant QTL × environment interactions were detected for all the QTLs which were repeatedly detected. Some QTLs reported previously were confirmed, and seven new QTLs (two for oleic acid, two for linoleic acid and three for linolenic acid) were identified in this study. Comparisons of two-locus and three-locus combinations indicated that cumulative effects of QTLs were significant for all the three unsaturated fatty acids. QTL pyramiding by molecular marker-assisted breeding would be an appropriate strategy for the improvement of unsaturated fatty acids in soybean.     

Mapping QTL for Biomass Yield and Its Components in Rice (Oryza sativa L.)

Addicive effects, additive by additive epistatic effects, and their environmental interactions of QTLs are important genetic components of quantitative traits. Genetic architecture underlying rice biomass yield and its two component traits (straw yield and grain yield) were analyzed for a population of 125 DH lines from an inter-subspecific cross of IR64/Azucena. The mixed-model based composite interval mapping approach (MCIM) was used to detect QTLs, There were 12 QTLs detected with additive main effects, 27 QTLs involved in digenic interaction with aa and/or aae effects, and 18 QTLs affected by environments with ae and/or aae effects. It was revealed that epistatic effects and QE interaction effects existed on biomass yield and its component traits in rice. In addition, the genetic basis of relationships among these traits were investigated. Four QTLs and one pair of epistatic QTLs were detected to be responsible for the positive correlation between biomass yield and straw yield. Three QTLs might be responsible for the negative correlation between straw yield and grain yield. This result could partially explain the genetic basis of correlation among the three traits, and provide useful information for genetic improvement of these traits by marker-assisted selection.     

Fine-mapping of QTLs for individual and total isoflavone content in soybean (<Emphasis Type="Italic">Glycine max L.</Emphasis>) using a high-density genetic map

Key message

Fifteen stable QTLs were identified using a high-density soybean genetic map across multiple environments. One major QTL, qIF5-1, contributing to total isoflavone content explained phenotypic variance 49.38, 43.27, 46.59, 45.15 and 52.50%, respectively.

Abstract

Soybeans (Glycine max L.) are a major source of dietary isoflavones. To identify novel quantitative trait loci (QTL) underlying isoflavone content, and to improve the accuracy of marker-assisted breeding in soybean, a valuable mapping population comprised of 196 F_7:8–10 recombinant inbred lines (RILs, Huachun 2 × Wayao) was utilized to evaluate individual and total isoflavone content in plants grown in four different environments in Guangdong. A high-density genetic linkage map containing 3469 recombination bin markers based on 0.2 × restriction site-associated DNA tag sequencing (RAD-seq) technology was used to finely map QTLs for both individual and total isoflavone contents. Correlation analyses showed that total isoflavone content, and that of five individual isoflavone, was significantly correlated across the four environments. Based on the high-density genetic linkage map, a total of 15 stable quantitative trait loci (QTLs) associated with isoflavone content across multiple environments were mapped onto chromosomes 02, 05, 07, 09, 10, 11, 13, 16, 17, and 19. Further, one of them, qIF5-1, localized to chromosomes 05 (38,434,171–39,045,620 bp) contributed to almost all isoflavone components across all environments, and explained 6.37–59.95% of the phenotypic variance, especially explained 49.38, 43.27, 46.59, 45.15 and 52.50% for total isoflavone. The results obtained in the present study will pave the way for a better understanding of the genetics of isoflavone accumulation and reveals the scope available for improvement of isoflavone content through marker-assisted selection.

     

Dynamic Quantitative Trait Loci Analysis of Seed Reserve Utilization during Three Germination Stages in Rice

In this study, one rice population of recombinant inbred lines (RILs) was used to determine the genetic characteristics of seed reserve utilization during the early (day 6), middle (day 10) and late (day 14) germination stages. The seedling dry weight (SDW) and weight of the mobilized seed reserve (WMSR) were increased, while the seed reserve utilization efficiency (SRUE) decreased, during the process of seed germination. The SDW and WMSR were affected by the seed weight, while the SRUE was not affected by the seed weight. A total of twenty unconditional and twenty-one conditional additive QTLs and eight epistatic QTLs were identified at three germination stages, and the more QTLs were expressed at the late germination stage. Among them, twelve additive and three epistatic QTLs for SDW, eight additive and three epistatic QTLs for WMSR and thirteen additive and two epistatic QTLs for SRUE were identified, respectively. The phenotypic variation explained by each additive QTL, epistatic QTL and QTL × development interaction ranged from 6.10 to 23.91%, 1.79 to 6.88% and 0.22 to 2.86%, respectively. Two major additive QTLs qWMSR7.1 and qSRUE4.3 were identified, and each QTL could explain more than 20% of the total phenotypic variance. By comparing the chromosomal positions of these additive QTLs with those previously identified, eleven QTLs might represent novel genes. The best four cross combinations of each trait for the development of RIL populations were selected. The selected RILs and the identified QTLs might be applicable to improve rice seed reserve utilization by the marker-assisted selection approach.     

Identifying <Emphasis Type="Italic">FATB1a</Emphasis> deletion that causes reduced palmitic acid content in soybean N87-2122-4 to develop a functional marker for marker-assisted selection

Palmitic acid is a major saturated fatty acid in soybean oil, and consumption of saturated fat is linked to a risk of coronary diseases. Development of soybean (Glycine max) cultivars with reduced palmitic acid content is an important goal of soybean breeding. The FATB1a gene was previously found to be responsible for reduced palmitic acid in the soybean line N87-2122-4. The objective of this research was to characterize the FATB1a gene identified in N87-2122-4 and develop a breeder-friendly, functional marker to facilitate marker-assisted selection and improve breeding efficiency for reduced palmitic soybeans. With the availability of soybean genetic maps, reference genome, and gene annotations, an approximate 254 kb deleted genomic region, including the FATB1a gene, was identified. Based on the gene deletion information, we developed a TaqMan marker and tested it with a segregating F ₂ population that consisted of 140 individual plants derived from ‘Cook’ × N87-2122-4. The marker performed well and accounted for 57 % of the phenotypic variation. The marker was also validated using a panel of 121 diverse soybean lines with known fatty acid profiles. The result indicated that the marker can be used effectively in marker-assisted breeding for reduced palmitic acid in soybean.