Mapping of QTL associated with chilling tolerance during reproductive growth in soybean

Low temperatures in summer bring about drastic reduction in seed yield of soybean [Glycine max (L.) Merr.]. To identify quantitative trait loci (QTL) associated with chilling tolerance during the reproductive growth in soybean, a recombinant inbred line (RIL) population consisting of 104 F₆-derived lines was created from a cross between two cultivars, chilling-tolerant Hayahikari and chilling-sensitive Toyomusume. The RIL were genotyped with 181 molecular and phenotypic markers and were scored with regard to chilling tolerance, which was evaluated by comparison of seed-yielding abilities in two artificial climatic environments at chilling and usual temperatures. Three QTL were detected for chilling tolerance in seed-yielding ability. Two of them, qCTTSW1 and qCTTSW2, were mapped near QTL for flowering time, and the latter had an epistatic interaction with a marker locus located near another QTL for flowering time, where no significant QTL for chilling tolerance was detected. The analysis of an F₂ population derived from the cross between Hayahikari and an RIL of the Hayahikari genotype at all QTL for flowering time confirmed the effect of the third QTL, qCTTSW3, on chilling tolerance and suggested that qCTTSW1 was basically independent of the QTL for flowering time. The findings and QTL found in this study may provide useful information for marker-assisted selection (MAS) and further genetic studies on soybean chilling tolerance.     

Marker-assisted selection for early-season cold tolerance in sorghum: QTL validation across populations and environments

Sorghum [Sorghum bicolor (L.) Moench] landraces from China generally exhibit excellent emergence and seedling vigor under cool conditions, and are being used as sources of genes for improvement of seedling cold tolerance in other cultivars. Marker-assisted selection (MAS) could expedite the introgression of genes from landraces into elite lines, however, only a few studies have empirically demonstrated efficacy of MAS for quantitatively inherited agronomic traits. In a preceding study we identified quantitative trait loci (QTL) for early-season performance in a recombinant inbred (RI) population, one parent of which was a cold-tolerant Chinese line, ‘Shan Qui Red’ (SQR). In this study, three SSR markers (Xtxp43, Xtxp51, and Xtxp211), each representing a QTL, were tested in two new populations: (Tx2794 × SQR F₃) and (Wheatland × SQR BC₁F₃). Individual families were genotyped, and early-season field performance was measured for two years. Statistical analyses showed that the SQR allele of Xtxp43 had favorable effects on seedling vigor in both populations, and on emergence in the Tx2794 population. A large positive effect of the SQR allele of Xtxp51 was observed in the Tx2794 population for vigor and emergence. Slight genotype by environment interaction was observed for Xtxp51 in the Wheatland population. Marker Xtxp211 had small but significant effects on seedling vigor and emergence in both populations. Various interactions between loci were also significant. This study validated QTL markers in various genetic backgrounds, and demonstrated the utility of MAS for a quantitative trait, early-season cold tolerance, evaluated in the field.     

Quantitative trait loci involved in regulating seed oil composition in <Emphasis Type="Italic">Arabidopsis thaliana</Emphasis> and their evolutionary implications

Fatty acid composition is an important determinant of seed oil quality. Overall, 72 QTL for 12 fatty acid traits that control seed oil composition were identified in four recombinant inbred line (RIL) populations (Ler-0 × Sha, Ler-0 × Col-4, Ler-2 × Cvi, Ler-0 × No-0) of Arabidopsis thaliana. The identified QTL explained 3.2–79.8% of the phenotypic variance; 33 of the 59 QTL identified in the Ler-0 × Sha and the Ler-0 × Col RIL populations co-located with several a priori candidate genes for seed oil composition. QTL for fatty acids 18:1, 18:2, 22:1, and fatty acids synthesized in plastids was identified in both Ler-0 × Sha and Ler-0 × Col-4 RIL populations, and QTL for 16:0 was identified in the Ler-0 × Sha and Ler-0 × No-0 RIL populations providing strong support for the importance of these QTL in determining seed oil composition. We identified melting point QTL in three RIL populations, and fatty acid QTL collocated with two of them, suggesting that the loci could be under selection for altering the melting point of seed oils to enhance adaptation and could be useful for breeding purposes. Nuclear-cytoplasmic interactions and epistasis were rare. Analysis of the genetic correlations between these loci and other fatty acids indicated that these correlations would tend to strongly enhance selection for desirable fatty acids.     

Genome-wide linkage mapping of yield-related traits in three Chinese bread wheat populations using high-density SNP markers

Key message

We identified 21 new and stable QTL, and 11 QTL clusters for yield-related traits in three bread wheat populations using the wheat 90 K SNP assay.

Abstract

Identification of quantitative trait loci (QTL) for yield-related traits and closely linked molecular markers is important in order to identify gene/QTL for marker-assisted selection (MAS) in wheat breeding. The objectives of the present study were to identify QTL for yield-related traits and dissect the relationships among different traits in three wheat recombinant inbred line (RIL) populations derived from crosses Doumai?×?Shi 4185 (D?×?S), Gaocheng 8901?×?Zhoumai 16 (G?×?Z) and Linmai 2?×?Zhong 892 (L?×?Z). Using the available high-density linkage maps previously constructed with the wheat 90 K iSelect single nucleotide polymorphism (SNP) array, 65, 46 and 53 QTL for 12 traits were identified in the three RIL populations, respectively. Among them, 34, 23 and 27 were likely to be new QTL. Eighteen common QTL were detected across two or three populations. Eleven QTL clusters harboring multiple QTL were detected in different populations, and the interval 15.5–32.3 cM around the Rht-B1 locus on chromosome 4BS harboring 20 QTL is an important region determining grain yield (GY). Thousand-kernel weight (TKW) is significantly affected by kernel width and plant height (PH), whereas flag leaf width can be used to select lines with large kernel number per spike. Eleven candidate genes were identified, including eight cloned genes for kernel, heading date (HD) and PH-related traits as well as predicted genes for TKW, spike length and HD. The closest SNP markers of stable QTL or QTL clusters can be used for MAS in wheat breeding using kompetitive allele-specific PCR or semi-thermal asymmetric reverse PCR assays for improvement of GY.

     

Mapping and validation of simple sequence repeat markers linked to a major gene controlling seed cadmium accumulation in soybean [Glycine max (L.) Merr]

Daily consumption of cadmium (Cd) contaminated foods poses a risk to human health. Cultivar selection is an important method to limit Cd uptake and accumulation, however, analyzing grain Cd concentration is costly and time-consuming. Developing markers for low Cd accumulation will facilitate marker assisted selection (MAS). Inheritance studies using a threshold value of 0.2 mg kg^?1 for low and high and an F_2:3 population showed that low Cd accumulation in soybean seed is under the control of a major gene (Cda1, proposed name) with the allele for low accumulation being dominant. A recombinant inbred line (RIL) population (F_6:8) derived from the cross AC Hime (high Cd accumulation) and Westag-97 (low Cd accumulation) was used to identify the DNA markers linked to Cda gene(s) or quantitative trait loci (QTLs) controlling low Cd accumulation. We screened 171 simple sequence repeat (SSR) primers that showed polymorphism between parents on the 166 RILs. Of these, 40 primers were newly developed from the soybean genomic DNA sequence. Seven SSR markers, SatK138, SatK139, SatK140 (0.5 cM), SatK147, SacK149, SaatK150 and SattK152 (0.3 cM), were linked to Cda1 in soybean seed. All the linked markers were mapped to the same linkage group (LG) K. The closest flanking SSR markers linked to Cda1 were validated using a parallel population (RILs) involving Leo × Westag-97. Linked markers were also validated with diverse soybean genotypes differing in their seed Cd concentration and showed that SSR markers SatK147, SacK149, and SattK152 clearly differentiated the high and low Cd accumulating genotypes tested. To treat Cd uptake as a quantitative trait, QTL analysis using a linkage map constructed with 161 markers identified a major QTL associated with low Cd concentration in the seeds. The QTL was also mapped to the same location as Cda1 on LG-K. This QTL accounted for 57.3% of the phenotypic variation. Potential candidate genes (genes with known or predicted function that could influence the seed Cd concentration) like protein kinase, putative Adagio-like protein, and plasma membrane H⁺-ATPase were found to be located in the locus of interest. Of the four SSR markers located in the region, SattK152 was localized in the plasma membrane H⁺-ATPase gene. SSR markers closely linked to Cda1 in seeds of soybean were identified and have potential to be used for MAS to develop low Cd accumulating cultivars in a breeding program.     

Identification and validation of a major cadmium accumulation locus and closely associated SNP markers in North Dakota durum wheat cultivars

Durum wheat has the tendency of accumulating more cadmium (Cd), a biotoxic heavy metal, in seeds than other commonly grown cereals, thus posing a serious food safety/public health concern. This could have serious negative impact on the national pasta industry and the international export market of durum wheat. The phenotyping for selecting low Cd lines is expensive and time consuming. The use of markers could be a more sustainable approach for selecting lines with low Cd levels. Here, a RIL population developed from a cross between Grenora (high Cd) × Haurani (low Cd) and two association mapping panels consisting of advanced breeding lines from the North Dakota durum wheat breeding program were used to identify QTL and associated markers for Cd. A major QTL, with Haurani contributing low Cd uptake allele and explaining 54.3 % phenotypic variation, was detected on chromosome 5BL. Association mapping using 2010 collection validated the results of linkage mapping and identified major QTL on 5BL. The 2009 collection, showed the presence of a major QTL on chromosome 2B. The SNP marker associated with major QTL on 5BL was converted to user friendly KASPar assay. The major QTL and associated KASPar marker were further validated using another RIL population developed from a cross of Strongfield (low Cd) and Alkabo (high Cd). The development of suitable marker assay, associated with major Cd uptake QTL, would help the selection for low Cd accumulating lines, minimizing the costly phenotypic evaluation for this important trait.     

Using three overlapped RILs to dissect genetically clustered QTL for fiber strength on Chro.D8 in Upland cotton

Fiber strength is an important trait among cotton fiber qualities due to ongoing changes in spinning technology. Major quantitative trait loci (QTL) for fiber quality enable molecular marker-assisted selection (MAS) to effectively improve fiber quality of cotton cultivars. We previously identified a major QTL for fiber strength derived from 7235 in Upland cotton. In the present study, in order to fine-map fiber strength QTL, we chose three recombinant inbred lines (RIL), 7TR-133, 7TR-132, and 7TR-214, developed from a cross between 7235 and TM-1 for backcrossing to TM-1 to develop three large mapping populations. Phenotypic data for fiber strength traits were collected in Nanjing (JES/NAU) and Xinjiang (BES/XJ) in 2006 and 2007. Three simple sequence repeat (SSR) genetic linkage maps on Chro.24(D8) were constructed using these three backcrossed populations. The SSR genetic maps were constructed using 907 individuals in (7TR-133 × TM-1)F₂ (Pop A), 670 in (7TR-132 × TM-1)F₂ (Pop B), and 940 in (7TR-214 × TM-1)F₂ (Pop C). The average distance between SSR loci was 0.62, 1.7, and 0.56 cM for the three maps. MapQTL 5 software detected five-clustered QTL (2.5 < LOD < 29.8) on Chro.D8 for fiber strength following analysis of three RIL backcrossed F₂/F_2:3 progenies at JES/NAU and BES/XJ over 2 years. Five QTL for fiber strength exhibited a total phenotypic variance (PV) of 28.8–59.6%.     

QTL mapping for maize resistance and yield under infestation with Sesamia nonagrioides

The Mediterranean corn borer (MCB) is the most important maize insect pest in the Mediterranean region. The main objective was to map quantitative trait loci (QTL) for yield performance under infestation with MCB, resistance and agronomic traits in a maize RIL population derived from an inbred cross European flint × Reid. Six QTL for resistance traits were located: one QTL for tunnel length (bin 9.03; p = 19.8 %), one QTL for stalk lodging (bin 3.07, p = 11.5 %), and four QTL for ear resistance (bins 1.07, 5.03/5.05, and 8.04; p = 25–63 %). Twelve QTL for agronomic traits were located: a QTL for yield under infestation (bin 5.03, p = 15 %); two QTL for grain moisture (bins 1.07 and 8.05); two QTL for days to anthesis (bin 1.07 and 8.05); two QTL for days to silking (bins 8.04 and 10.02); three QTL for plant height (bins 5.04, 8.05 and 9.03); and two QTL for ear height (bins 8.05 and 9.03). No genetic correlations between yield and other traits were observed. The cross validation (CV) approach showed that the estimation biases for QTL for resistance traits were higher than those for agronomic traits. This work stresses the importance of the region 9.03 for controlling corn borer resistance and suggests the presence of QTL with small effect on ear-resistance traits. At the same genomic region, there are also genes that control plant and ear height and future works could elucidate whether these genes are the same or are closely linked. The QTL for yield seem to play an important role in MCB tolerance in this genetic background. Large biases observed for QTL effects by CV were mainly due to the small sample size used and were higher for resistance traits due to their larger genetic complexity. We consider that it is more appropriate to select for grain yield under infestation instead of selecting for resistance traits because resistance to MCB could have unfavorable associations with agronomic traits.     

Construction of high-density linkage map and identification of QTLs for resistance to sorghum downy mildew in maize (<Emphasis Type="Italic">Zea mays</Emphasis> L.)

Sorghum downy mildew (SDM), caused by obligate biotrophic fungi Peronosclerospora sorghi, is an economically important disease of maize. The genetics of resistance was reported to be polygenic thereby necessitating identification of QTLs for resistance to SDM to initiate effective marker-assisted selection programs. During post-rainy and winter season of 2012, 645 F_2:3 progeny families from the cross CML153 (susceptible) × CML226 (resistant) were screened for their reaction to SDM. Characterization of QTLs affecting resistance to SDM was undertaken using the genetic linkage map with 319 polymorphic SSR and SNP marker loci and the phenotypic data of F_2:3 families. Three QTLs conferring resistance to SDM were consistently identified on chromosomes 2, 3 and 6 in both seasons. The resistant parent CML226 contributed all the QTL alleles conferring resistance to SDM. The major QTL located on chromosome 2 explained 38.68% of total phenotypic variation in the combined analysis with a LOD score of 9.12. All the three QTL showed partially dominant gene effects in combined analysis. The detection of more than one QTL supports the hypothesis that quantitative genes control resistance to P. sorghi. The generation was advanced to F₆ using markers linked to major QTLs on chromosomes 2 and 3 to derive 33 SDM resistant maize inbred lines.     

Identification and validation of genomic regions that affect shoot fly resistance in sorghum [<Emphasis Type="Italic">Sorghum bicolor</Emphasis> (L.) Moench]

Shoot fly is one of the most important pests affecting the sorghum production. The identification of quantitative trait loci (QTL) affecting shoot fly resistance enables to understand the underlying genetic mechanisms and genetic basis of complex interactions among the component traits. The aim of the present study was to detect QTL for shoot fly resistance and the associated traits using a population of 210 RILs of the cross 27B (susceptible) × IS2122 (resistant). RIL population was phenotyped in eight environments for shoot fly resistance (deadheart percentage), and in three environments for the component traits, such as glossiness, seedling vigor and trichome density. Linkage map was constructed with 149 marker loci comprising 127 genomic-microsatellite, 21 genic-microsatellite and one morphological marker. QTL analysis was performed by using MQM approach. 25 QTL (five each for leaf glossiness and seedling vigor, 10 for deadhearts, two for adaxial trichome density and three for abaxial trichome density) were detected in individual and across environments. The LOD and R ² (%) values of QTL ranged from 2.44 to 24.1 and 4.3 to 44.1%, respectively. For most of the QTLs, the resistant parent, IS2122 contributed alleles for resistance; while at two QTL regions, the susceptible parent 27B also contributed for resistance traits. Three genomic regions affected multiple traits, suggesting the phenomenon of pleiotrophy or tight linkage. Stable QTL were identified for the traits across different environments, and genetic backgrounds by comparing the QTL in the study with previously reported QTL in sorghum. For majority of the QTLs, possible candidate genes were identified. The QTLs identified will enable marker assisted breeding for shoot fly resistance in sorghum.     

A new interspecific, <Emphasis Type="Italic">Gossypium hirsutum</Emphasis> × <Emphasis Type="Italic">G. barbadense,</Emphasis> RIL population: towards a unified consensus linkage map of tetraploid cotton

We report the development of a new interspecific cotton recombinant inbred line (RIL) population of 140 lines deriving from an interspecific cross between Gossypium hirsutum (Gh) and G. barbadense (Gb), using the same two parents that have served for the construction of a BC₁ map and for the marker-assisted backcross selection program underway at CIRAD. Two marker systems, microsatellites and AFLPs, were used. An important feature of the RIL population was its marked segregation distortion with a genome-wide bias to Gh alleles (parental genome ratio is 71/29). The RIL map displays an excellent colinearity with the BC₁ map, although it is severely contracted in terms of map size. Existence of 255 loci in common (between 6 and 14 per chromosome) allowed the integration of the two data sets. A consensus BC₁–RIL map based upon 215 individuals (75 BC1 + 140 RIL) was built. It consisted of 1,745 loci, spanned 3,637 cM, intermediate between the sizes of the two component maps, and constituted a solid framework to cross align cotton maps using common markers. The new RIL population will be further exploited for fiber property QTL mapping and eQTL mapping. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Identification of the quantitative trait loci (QTL) underlying water soluble protein content in soybean

Water soluble protein content (SPC) plays an important role in the functional efficacy of protein in food products. Therefore, for the identification of quantitative trait loci (QTL) associated with SPC, 212 F_2:9 lines of the recombinant inbred line (RIL) population derived from the cross of ZDD09454 × Yudou12 were grown along with the parents, in six different environments (location × year) to determine inheritance and map solubility-related genes. A linkage map comprising of 301 SSR markers covering 3,576.81 cM was constructed in the RIL population. Seed SPC was quantified with a macro-Kjeldahl procedure in samples collected over multiple years from three locations (Nantong in 2007 and 2008, Zhengzhou in 2007 and 2008, and Xinxiang in 2008 and 2009). SPC demonstrated transgressive segregation, indicating a complementary genetic structure between the parents. Eleven putative QTL were associated with SPC explaining 4.5–18.2 % of the observed phenotypic variation across the 6 year/location environments. Among these, two QTL (qsp8-4, qsp8-5) near GMENOD2B and Sat_215 showed an association with SPC in multiple environments, suggesting that they were key QTL related to protein solubility. The QTL × environment interaction demonstrated the complex genetic mechanism of SPC. These SPC-associated QTL and linked markers in soybean will provide important information that can be utilized by breeders to improve the functional quality of soybean varieties.     

Mapping the dominant wound healing and soft tissue regeneration QTL in MRL × CAST

We have used a mouse ear punch model and the QTL (quantitative trait loci) mapping technique to identify genes that are responsible for soft tissue regeneration. In the early studies, we have identified several QTL and have shown that the inheritance of ear healing was additive in one cross (MRL × SJL), and recessive in another cross (DBA × 129). Because CAST mice are genetically distinct and have a different genetic background, CAST would facilitate the identification of common and novel QTL when crossed with common inbred lines. We made a cross between super healer MRL and poor healer CAST and collected ear punch phenotype and marker genotype data from F₂. Ear punch healing exhibited a dominant mode of inheritance in this cross. There were three main QTL on Chromosomes 4, 9, and 17, and two suggestive QTL on Chromosomes 1 (new) and 7. Taken together, these QTL accounted for about 29% of total F₂ variance of MRL × CAST. Compared with another study using the same cross, we found a totally different set of QTL. Two QTL interactions were identified by a full QTL model: Chromosomes 4 × 17 and 9 × 17; the latter reached to a statistical level at p < 0.05. These interactions explained about 4% of the F₂ phenotypic variance. We conclude that soft tissue regeneration is controlled by multiple genes and locus vs. locus interactions. This work was supported by Assistance Award No. DAMD17-99-1-9571. The U.S. Army Medical Research Acquisition Activity, Fort Detrick, MD, is the awarding and administering acquisition office. The information contained in this publication does not necessarily reflect the position or policy of the U.S. Government and no official endorsement should be inferred.     

QTL consistency and meta-analysis for grain yield components in three generations in maize

Grain yield is the most important and complex trait in maize. In this study, a total of 258 F₉ recombinant inbred lines (RIL), derived from a cross between dent corn inbred Dan232 and popcorn inbred N04, were evaluated for eight grain yield components under four environments. Quantitative trait loci (QTL) and their epistatic interactions were detected for all traits under each environment and in combined analysis. Meta-analysis was used to integrate genetic maps and detected QTL across three generations (RIL, F_2:3 and BC₂F₂) derived from the same cross. In total, 103 QTL, 42 pairs of epistatic interactions and 16 meta-QTL (mQTL) were detected. Twelve out of 13 QTL with contributions (R ²) over 15% were consistently detected in 3–4 environments (or in combined analysis) and integrated in mQTL. Only q100GW-7-1 was detected in all four environments and in combined analysis. 100qGW-1-1 had the largest R ² (19.3–24.6%) in three environments and in combined analysis. In contrast, 35 QTL for 6 grain yield components were detected in the BC₂F₂ and F_2:3 generations, no common QTL across three generations were located in the same marker intervals. Only 100 grain weight (100GW) QTL on chromosome 5 were located in adjacent marker intervals. Four common QTL were detected across the RIL and F_2:3 generations, and two between the RIL and BC₂F₂ generations. Each of five important mQTL (mQTL7-1, mQTL10-2, mQTL4-1, mQTL5-1 and mQTL1-3) included 7–12 QTL associated with 2–6 traits. In conclusion, we found evidence of strong influence of genetic structure and environment on QTL detection, high consistency of major QTL across environments and generations, and remarkable QTL co-location for grain yield components. Fine mapping for five major QTL (q100GW-1-1, q100GW-7-1, qGWP-4-1, qERN-4-1 and qKR-4-1) and construction of single chromosome segment lines for genetic regions of five mQTL merit further studies and could be put into use in marker-assisted breeding.     

Population development by phenotypic selection with subsequent marker-assisted selection for line extraction in cucumber (<Emphasis Type="Italic">Cucumis sativus</Emphasis> L.)

Cucumber (Cucumis sativus L.; 2n=2x=14) has a narrow genetic base, and commercial yield of US processing cucumber has plateaued in the last 15 years. Yield may be increased by altering plant architecture to produce unique early flowering (days to flower, DTF), female (gynoecious, GYN), highly branched (multiple lateral branching, MLB), long-fruited (length:diameter ratio, L:D) cultivars with diverse plant statures. The genetic map position of QTL conditioning these quantitatively inherited yield component traits is known, and linked molecular markers may have utility in marker-assisted selection (MAS) programs to increase selection efficiency, and effectiveness. Therefore, a base population (C₀), created by intermating four unique but complementary lines, was subjected to three cycles (C₁–C₃) of phenotypic (PHE) mass selection for DTF, GYN, MLB, and L:D. In tandem, two cycles of marker-assisted backcrossing for these traits began with selected C₂ progeny (C_2S) to produce families (F₁[i.e., C_2S × C_2S], and BC₁ [i.e., F₁ × C_2S]) for line extraction, and for comparative analysis of gain from selection by PHE selection, and MAS. Frequencies of marker loci were used to monitor selection-dependent changes during PHE selection, and MAS. Similar gain from selection was detected as a result of PHE selection, and MAS for MLB (~0.3 branches/cycle), and L:D (~0.1 unit increase/cycle) with concomitant changes in frequency at linked marker loci. Although genetic gain was not realized for GYN during PHE selection, the percentage of female flowers of plants subjected to MAS was increased (5.6–9.8% per cycle) depending upon the BC₁ population examined. Selection-dependent changes in frequency were also detected at marker loci linked to female sex expression during MAS. MAS operated to fix favorable alleles that were not exploited by PHE selection in this population, indicating that MAS could be applied for altering plant architecture in cucumber to improve its yield potential. The cost of publishing this paper was defrayed in part by the payment of page charges. Under postal regulations, this paper therefore must be hereby, marked advertisement solely to indicate this fact. Mention of a trade name, proprietary product, or specific equipment does not constitute a guarantee or warranty by the USDA and does not imply its approval to the exclusion of other products that may be suitable.     

A molecular marker linked to the mollis gene conferring soft-seediness for marker-assisted selection applicable to a wide range of crosses in lupin (Lupinus angustifolius L.) breeding

To broaden the gene pool of domesticated commercial cultivars of narrow-leafed lupin (Lupinus angustifolius L.), wild accessions are used as parents in crossing in lupin breeding. Among the progenies from wild × domesticated (W × D) crosses, the soft-seediness gene mollis is the most difficult domestication gene to be selected by conventional breeding methods, where molecular marker-assisted selection (MAS) is highly desirable. MAS in plant breeding requires markers to be cost-effective and high-throughput, and be applicable to a wide range of crosses in a breeding program. In this study, representative plants from an F8 recombinant inbred line (RIL) population derived from a W × D cross, together with four cultivars and four wild types, were used in DNA fingerprinting by microsatellite-anchored fragment length polymorphisms (MFLP). Two co-dominant MFLP polymorphisms were identified as candidate markers linked to the mollis gene, and one of the candidate markers was selected and converted into a co-dominant, sequence-specific PCR marker. This marker, designated MoLi, showed a perfect match with phenotypes of seed coat permeability on a segregating population consisting of 115 F8 RILs, confirming the close genetic linkage to the mollis gene. Validation tests showed that the banding pattern of marker MoLi is consistent with all the 25 historical and current commercial cultivars released in Australia, and is consistent with mollis genotypes in 119 of the 125 accessions in the Australian L. angustifolius core collection. Marker MoLi provides a cost-effective way to select the mollis gene in a wide range of W × D crosses in lupin breeding.     

Quantitative trait loci and candidate genes underlying genotype by environment interaction in the response of Arabidopsis thaliana to drought

Drought stress was imposed on two sets of Arabidopsis thaliana genotypes grown in sand under short‐day conditions and analysed for several shoot and root growth traits. The response to drought was assessed for quantitative trait locus (QTL) mapping in a genetically diverse set of Arabidopsis accessions using genome‐wide association (GWA) mapping, and conventional linkage analysis of a recombinant inbred line (RIL) population. Results showed significant genotype by environment interaction (G×E) for all traits in response to different watering regimes. For the RIL population, the observed G×E was reflected in 17 QTL by environment interactions (Q×E), while 17 additional QTLs were mapped not showing Q×E. GWA mapping identified 58 single nucleotide polymorphism (SNPs) associated with loci displaying Q×E and an additional 16 SNPs associated with loci not showing Q×E. Many candidate genes potentially underlying these loci were suggested. The genes for RPS3C and YLS7 were found to contain conserved amino acid differences when comparing Arabidopsis accessions with strongly contrasting drought response phenotypes, further supporting their candidacy. One of these candidate genes co‐located with a QTL mapped in the RIL population.     

Quantitative trait locus analysis of a recombinant inbred line population derived from a Lycopersicon esculentum x Lycopersicon cheesmanii cross

Quantitative trait loci influencing fruit traits were identified by restriction fragment length polymorphism (RFLP) analysis in a population of recombinant inbred lines (RIL) derived from a cross of the cultivated tomato, Lycopersicon esculentum with a related wild species Lycopersicon cheesmanii. One hundred thirty-two polymorphic RFLP loci spaced throughout the tomato genome were scored for 97 F₈ RIL families. Fruit weight and soluble solids were measured in replicated trials during 1991 and 1992. Seed weight was measured in 1992. Significant (P<0.01 level) quantitative trait locus (QTL) associations of marker loci were identified for each trait. A total of 73 significant marker locus-trait associations were detected for the three traits measured. Fifty-three of these associations were for fruit weight and soluble solids, many of which involved marker loci signficantly associated with both traits. QTL with large effects on all three traits were detected on chromosome 6. Greater homozygosity at many loci in the RIL population as compared to F₂ populations and greater genomic coverage resulted in increased precision in the estimation of QTL effects, and large proportions of the total phenotypic variance were explained by marker class variation at significant marker loci for many traits. The RIL population was effective in detecting and discriminating among QTL for these traits previously identified in other investigations despite skewed segregation ratios at many marker loci. Large additive effects were measured at significant marker loci. Lower fruit weight, higher soluble solids, and lower seed weight were generally associated with RFLP alleles from theL. cheesmanii parent.     

Genomic Regions Associated with Amino Acid Composition in Soybean

Soybean [Glycine max (L.) Merr.] is the single largest source of protein in animal feed. However, few studies have been conducted to evaluate genomic regions controlling amino acid composition in soybean. It is important to study the genetics of amino acid composition to achieve improvements through breeding. The objectives of this study were to determine the ratios between essential to non-essential (E:NE) and essential to total (E:T) amino acids, and to identify genomic regions controlling essential and non-essential amino acid composition in soybean seed. To achieve these objectives, 101 F₆-derived recombinant inbred lines (RIL) developed from a cross of N87-984-16 × TN93-99 were used. Ground soybean seed samples were analyzed for amino acids using a near infrared spectroscopy (NIRS) instrument. A significant (p < 0.01) difference among the RIL was found for amino acid composition. Heritability estimates on an entry mean basis ranged from 0.13 for His to 0.67 for Tyr. A total of 94 polymorphic simple sequence repeat (SSR) molecular genetic markers were screened in DNA from progenies. Single factor ANOVA was used to identify candidate quantitative trait loci (QTL), which were then confirmed by QTL Cartographer. At least one QTL for each amino acid was detected in this population. QTL linked to molecular markers Satt143, Satt168, Satt203, Satt274 and Satt495 were associated with most of the amino acids. Phenotypic variation explained by an individual QTL ranged from 9.4 to 45.3%. QTL detected for amino acids in soybean in this experiment are expected to be useful for future breeding programs targeting development of improved soybean amino acid composition for human and animal nutrition.     

Identification of QTLs Underlying Water-Logging Tolerance in Soybean

Soil water-logging can cause severe damage to soybean [Glycine max (L.) Merr.] and results in significant yield reduction. The objective of this study was to identify quantitative trait loci (QTL) that condition water-logging tolerance (WLT) in soybean. Two populations with 103 and 67 F_6:11 recombinant inbred lines (RILs) from A5403 × Archer (Population 1) and P9641 × Archer (Population 2), respectively, were used as the mapping populations. The populations were evaluated for WLT in manually flooded fields in 2001, 2002, and 2003. Significant variation was observed for WLT among the lines in the two populations. No transgressive tolerant segregants were observed in either population. Broad-sense heritability of WLT for populations 1 and 2 were 0.59 and 0.43, respectively. The tolerant and sensitive RILs from each population were selected to create a tolerant bulk and a sensitive bulk, respectively. The two bulks and the parents of each population were tested with 912 simple sequence repeat (SSR) markers to select candidate regions on the linkage map that were associated with WLT. Markers from the candidate regions were used to genotype the RILs in both populations. Both single marker analysis (SMA) and composite interval mapping (CIM) were used to identify QTL for WLT. Seventeen markers in Population 1 and 15 markers in Population 2 were significantly (p <0.0001) associated with WLT in SMA. Many of these markers were linked to Rps genes or QTL conferring resistance to Phytophthora sojae Kaufmann and Gerdemann. Five markers, Satt599 on linkage group (LG) A1, Satt160, Satt269, and Satt252 on LG F, and Satt485 on LG N, were significant (p <0.0001) for WLT in both populations. With CIM, a WLT QTL was found close to the marker Satt385 on LG A1 in Population 1 in 2003. This QTL explained 10% of the phenotypic variation and the allele that increased WLT came from Archer. In Population 2 in 2002, a WLT QTL was located near the marker Satt269 on LG F. This QTL explained 16% of the phenotypic variation and the allele that increased WLT also came from Archer.