Main-effect Quantitative Trait Loci Research Articles

QTL Mapping Combined With Comparative Analyses Identified Candidate Genes for Reduced Shattering in Setaria italica.

Setaria (L.) P. Beauv is a genus of grasses that belongs to the Poaceae (grass) family, subfamily Panicoideae. Two members of the Setaria genus, Setaria italica (foxtail millet) and S. viridis (green foxtail), have been studied extensively over the past few years as model species for C4-photosynthesis and to facilitate genome studies in complex Panicoid bioenergy grasses. We exploited the available genetic and genomic resources for S. italica and its wild progenitor, S. viridis, to study the genetic basis of seed shattering. Reduced shattering is a key trait that underwent positive selection during domestication. Phenotyping of F2:3 and recombinant inbred line (RIL) populations generated from a cross between S. italica accession B100 and S. viridis accession A10 identified the presence of additive main effect quantitative trait loci (QTL) on chromosomes V and IX. As expected, enhanced seed shattering was contributed by the wild S. viridis. Comparative analyses pinpointed Sh1 and qSH1, two shattering genes previously identified in sorghum and rice, as potentially underlying the QTL on Setaria chromosomes IX and V, respectively. The Sh1 allele in S. italica was shown to carry a PIF/Harbinger MITE in exon 2, which gave rise to an alternatively spliced transcript that lacked exon 2. This MITE was universally present in S. italica accessions around the world and absent from the S. viridis germplasm tested, strongly suggesting a single origin of foxtail millet domestication. The qSH1 gene carried two MITEs in the 5′UTR. Presence of one or both MITEs was strongly associated with cultivated germplasm. If the MITE insertion(s) in qSH1 played a role in reducing shattering in S. italica accessions, selection for the variants likely occurred after the domestication of foxtail millet.

Identification of QTL hot spots for malting quality in two elite breeding lines with distinct tolerance to abiotic stress

BackgroundBarley (Hordeum vulgare) is an important crop cultivated across the world. Drought is a major abiotic factor compromising barley yield worldwide, therefore in modern spring barley cultivars superior seed and malting quality characteristics should be combined with reasonable level of drought tolerance. Previously we have identified a number of barley lines demonstrating the superior yield performance under drought conditions. The aim of this work was to perform a QTL analysis of malting quality traits in a doubled haploid (DH) mapping population of two elite barley lines that differ in their reaction pattern to drought stress.ResultsA population of DH lines was developed by crossing two drought-tolerant elite breeding lines, Victoriana and Sofiara, exploiting distinct mechanism of drought tolerance, sustaining assimilation vs remobilization. The mapping population was assayed under field conditions at four distinct locations that differed in precipitation rate. DH lines were genotyped with the Illumina 9 K iSelect assay, and linkage map including 1782 polymorphic markers and covering a total map length of 1140 cM was constructed. The result of quantitative trait loci (QTL) analysis showed that majority of the traits were affected by several main effect QTL and/or QTL x environment (QE) interactions. In total, 57, 41, and 5 QTL were associated with yield-related traits, malting quality traits and seed quality traits, respectively. 11 and 29 of mapped QTL explained more than 10 and 5% of phenotypic variation, respectively. In several chromosomal regions co-localization between QTL for various traits were observed. The largest clusters were detected on chromosomes 3H and 4H.ConclusionsOur QTL mapping results revealed several novel consistent genomic regions controlling malting quality which could be exploited in marker assisted selection. In this context, the complex QTL region on chromosome 3H seems of particular interest, as it harbors several large effect QTL.

Identification of Quantitative Trait Loci for Vigorous Root Development under Water-Deficiency Conditions in Rice

Seedling vigor in drought stress conditions is an important characteristic of the dry direct-seeded rice system. The drought stress in the seedling stage disrupts seed germination and delays the establishment of seedlings. However, little is known about the genetic mechanism of seedling vigor in drought conditions. The identification of quantitative trait loci (QTL) was conducted using 162 recombinant inbred lines (RILs) derived from a cross between two rice varieties―a Tongil-type Milyang23 and a temperate japonica Tong88-7. The seedling vigor of these RILs was characterized by measuring 10 morphological traits of the seedlings grown under drought conditions. The Tong88-7 seedlings showed significantly higher values than the Milyang23 seedlings for all traits. The genotyping-by-sequencing method was used to construct a map of 6140 single nucleotide polymorphisms. Six main-effect QTLs (M-QTLs) associated with seedling vigor traits under drought stress were identified on chromosomes 9 and 11. In particular, five out of these six QTLs were located on chromosome 11, explaining the phenotypic variances of 4.3% through 10.1%. In addition, 21 epistatic QTLs (E-QTLs) were detected, and the 27 loci involved in this interaction were distributed on 11 chromosomes. Both M-QTLs and E-QTLs detected in this study would be useful in breeding programs to develop elite rice varieties especially adapted to dry direct-seeded rice system.

High-density genetic map using whole-genome resequencing for fine mapping and candidate gene discovery for disease resistance in peanut.

SummaryWhole‐genome resequencing (WGRS) of mapping populations has facilitated development of high‐density genetic maps essential for fine mapping and candidate gene discovery for traits of interest in crop species. Leaf spots, including early leaf spot (ELS) and late leaf spot (LLS), and Tomato spotted wilt virus (TSWV) are devastating diseases in peanut causing significant yield loss. We generated WGRS data on a recombinant inbred line population, developed a SNP‐based high‐density genetic map, and conducted fine mapping, candidate gene discovery and marker validation for ELS, LLS and TSWV. The first sequence‐based high‐density map was constructed with 8869 SNPs assigned to 20 linkage groups, representing 20 chromosomes, for the ‘T’ population (Tifrunner × GT‐C20) with a map length of 3120 cM and an average distance of 1.45 cM. The quantitative trait locus (QTL) analysis using high‐density genetic map and multiple season phenotyping data identified 35 main‐effect QTLs with phenotypic variation explained (PVE) from 6.32% to 47.63%. Among major‐effect QTLs mapped, there were two QTLs for ELS on B05 with 47.42% PVE and B03 with 47.38% PVE, two QTLs for LLS on A05 with 47.63% and B03 with 34.03% PVE and one QTL for TSWV on B09 with 40.71% PVE. The epistasis and environment interaction analyses identified significant environmental effects on these traits. The identified QTL regions had disease resistance genes including R‐genes and transcription factors. KASP markers were developed for major QTLs and validated in the population and are ready for further deployment in genomics‐assisted breeding in peanut.

Discovery and validation of genomic regions associated with resistance to maize lethal necrosis in four biparental populations

In sub-Saharan Africa, maize is the key determinant of food security for smallholder farmers. The sudden outbreak of maize lethal necrosis (MLN) disease is seriously threatening the maize production in the region. Understanding the genetic basis of MLN resistance is crucial. In this study, we used four biparental populations applied linkage mapping and joint linkage mapping approaches to identify and validate the MLN resistance-associated genomic regions. All populations were genotyped with low to high density markers and phenotyped in multiple environments against MLN under artificial inoculation. Phenotypic variation for MLN resistance was significant and heritability was moderate to high in all four populations for both early and late stages of disease infection. Linkage mapping revealed three major quantitative trait loci (QTL) on chromosomes 3, 6, and 9 that were consistently detected in at least two of the four populations. Phenotypic variance explained by a single QTL in each population ranged from 3.9% in population 1 to 43.8% in population 2. Joint linkage association mapping across three populations with three biometric models together revealed 16 and 10 main effect QTL for MLN-early and MLN-late, respectively. The QTL identified on chromosomes 3, 5, 6, and 9 were consistent with the QTL identified by linkage mapping. Ridge regression best linear unbiased prediction with five-fold cross-validation revealed high accuracy for prediction across populations for both MLN-early and MLN-late. Overall, the study discovered and validated the presence of major effect QTL on chromosomes 3, 6, and 9 which can be potential candidates for marker-assisted breeding to improve the MLN resistance.

Genetic analysis and gene mapping of a low stigma exposed mutant gene by high-throughput sequencing.

Rice is one of the main food crops and several studies have examined the molecular mechanism of the exposure of the rice plant stigma. The improvement in the exposure of the stigma in female parent hybrid combinations can enhance the efficiency of hybrid breeding. In the present study, a mutant plant with low exposed stigma (lesr) was discovered among the descendants of the indica thermo-sensitive sterile line 115S. The ES% rate of the mutant decreased by 70.64% compared with the wild type variety. The F2 population was established by genetic analysis considering the mutant as the female parent and the restorer line 93S as the male parent. The results indicated a normal F1 population, while a clear division was noted for the high and low exposed stigma groups, respectively. This process was possible only by a ES of 25% in the F2 population. This was in agreement with the ratio of 3:1, which indicated that the mutant was controlled by a recessive main-effect QTL locus, temporarily named as LESR. Genome-wide comparison of the SNP profiles between the early, high and low production bulks were constructed from F2 plants using bulked segregant analysis in combination with high-throughput sequencing technology. The results demonstrated that the candidate loci was located on the chromosome 10 of the rice. Following screening of the recombinant rice plants with newly developed molecular markers, the genetic region was narrowed down to 0.25 Mb. This region was flanked by InDel-2 and InDel-2 at the physical location from 13.69 to 13.94 Mb. Within this region, 7 genes indicated base differences between parents. A total of 2 genes exhibited differences at the coding region and upstream of the coding region, respectively. The present study aimed to further clone the LESR gene, verify its function and identify the stigma variation.

Mapping Main-effect and Epistatic QTL for Hard Seededness in Soybean

Mapping Main-effect and Epistatic QTL for Hard Seededness in Soybean

QTL mapping for Q-enzyme activity during grain development in rice

Q-enzyme is important for the synthesis of rice grain starch and vital for grain filling. In this study, QTL (Quantitative trait locus) analysis for Q-enzyme activity during grain filling was carried out using recombinant inbred line population derived from the super rice Xieyou 9308. The activity of Qenzyme was greatest at 15 days after heading. In addition, the Q-enzyme activity in early stage (Q10 and Q15) showed significant correlation with the grain filling rate of each stage as well as the average grain filling rate. Nine maineffect QTLs for grain Q-enzyme activity were identified through QTL analysis, they were distributed on chromosome 2, 3, 5, 6 and 7, and the proportion of phenotypic variation explained (R2) by individual QTLs ranged from 5.68% to 11.59%. Among them, qQ10-3 and qQ15-3-2 are located in the same region of RM282-RM6283 on chromosome 3. qQ10-7-1 was detected in two years with an average R2 of 8.86%, and significant epistasis effect with environment was also identified. These results enhance our understanding of the genetic bases of Q-enzyme activity in rice grain.

Main and epistatic QTL analyses for Sclerotinia Head Rot resistance in sunflower.

Sclerotinia Head Rot (SHR), a disease caused by Sclerotinia sclerotiorum, is one of the most limiting factors in sunflower production. In this study, we identified genomic loci associated with resistance to SHR to support the development of assisted breeding strategies. We genotyped 114 Recombinant Inbred Lines (RILs) along with their parental lines (PAC2 –partially resistant–and RHA266 –susceptible–) by using a 384 single nucleotide polymorphism (SNP) Illumina Oligo Pool Assay to saturate a sunflower genetic map. Subsequently, we tested these lines for SHR resistance using assisted inoculations with S. sclerotiorum ascospores. We also conducted a randomized complete-block assays with three replicates to visually score disease incidence (DI), disease severity (DS), disease intensity (DInt) and incubation period (IP) through four field trials (2010–2014). We finally assessed main effect quantitative trait loci (M-QTLs) and epistatic QTLs (E-QTLs) by composite interval mapping (CIM) and mixed-model-based composite interval mapping (MCIM), respectively. As a result of this study, the improved map incorporates 61 new SNPs over candidate genes. We detected a broad range of narrow sense heritability (h2) values (1.86–59.9%) as well as 36 M-QTLs and 13 E-QTLs along 14 linkage groups (LGs). On LG1, LG10, and LG15, we repeatedly detected QTLs across field trials; which emphasizes their putative effectiveness against SHR. In all selected variables, most of the identified QTLs showed high determination coefficients, associated with moderate to high heritability values. Using markers shared with previous Sclerotinia resistance studies, we compared the QTL locations in LG1, LG2, LG8, LG10, LG11, LG15 and LG16. This study constitutes the largest report of QTLs for SHR resistance in sunflower. Further studies focusing on the regions in LG1, LG10, and LG15 harboring the detected QTLs are necessary to identify causal alleles and contribute to unraveling the complex genetic basis governing the resistance.

Identification of main effect and epistatic quantitative trait loci for morphological and yield-related traits in peanut (Arachis hypogaea L.)

An effort was made in the present study to identify the main effect and epistatic quantitative trait locus (QTL) for the morphological and yield-related traits in peanut. A recombinant inbred line (RIL) population derived from TAG 24 × GPBD 4 was phenotyped in seven environments at two locations. QTL analysis with available genetic map identified 62 main-effect QTLs (M-QTLs) for ten morphological and yield-related traits with the phenotypic variance explained (PVE) of 3.84–15.06%. Six major QTLs (PVE > 10%) were detected for PLHT, PPP, YPP, and SLNG. Stable M-QTLs appearing in at least two environments were detected for PLHT, LLN, YPP, YKGH, and HSW. Five M-QTLs governed two traits each, and 16 genomic regions showed co-localization of two to four M-QTLs. Intriguingly, a major QTL reported to be linked to rust resistance showed pleiotropic effect for yield-attributing traits like YPP (15.06%, PVE) and SLNG (13.40%, PVE). Of the 24 epistatic interactions identified across the traits, five interactions involved six M-QTLs. Three interactions were additive × additive and remaining two involved QTL × environment (QE) interactions. Only one major M-QTL governing PLHT showed epistatic interaction. Overall, this study identified the major M-QTLs for the important productivity traits and also described the lack of epistatic interactions for majority of them so that they can be conveniently employed in peanut breeding.

Dissection of Resistance Genes to Pseudomonas syringae pv. phaseolicola in UI3 Common Bean Cultivar.

Few quantitative trait loci have been mapped for resistance to Pseudomonas syringae pv. phaseolicola in common bean. Two F2 populations were developed from the host differential UI3 cultivar. The objective of this study was to further characterize the resistance to races 1, 5, 7 and 9 of Psp included in UI3. Using a QTL mapping approach, 16 and 11 main-effect QTLs for pod and primary leaf resistance were located on LG10, explaining up to 90% and 26% of the phenotypic variation, respectively. The homologous genomic region corresponding to primary leaf resistance QTLs detected tested positive for the presence of resistance-associated gene cluster encoding nucleotide-binding and leucine-rich repeat (NL), Natural Resistance Associated Macrophage (NRAMP) and Pentatricopeptide Repeat family (PPR) proteins. It is worth noting that the main effect QTLs for resistance in pod were located inside a 3.5 Mb genomic region that included the Phvul.010G021200 gene, which encodes a protein that has the highest sequence similarity to the RIN4 gene of Arabidopsis, and can be considered an important candidate gene for the organ-specific QTLs identified here. These results support that resistance to Psp from UI3 might result from the immune response activated by combinations of R proteins, and suggest the guard model as an important mechanism in pod resistance to halo blight. The candidate genes identified here warrant functional studies that will help in characterizing the actual defense gene(s) in UI3 genotype.

Conditional and unconditional QTLs mapping of gluten strength in common wheat (Triticum aestivum L.)

AbstractDissecting the genetic relationships among gluten-related traits is important for high quality wheat breeding. Quantitative trait loci (QTLs) analysis for gluten strength, as measured by sedimentation volume (SV) and gluten index (GI), was performed using the QTLNetwork 2.0 software. Recombinant inbred lines (RILs) derived from the winter wheat varieties Shannong 01-35×Gaocheng 9411 were used for the study. A total of seven additive QTLs for gluten strength were identified using an unconditional analysis. QGi1D-13 and QSv1D-14 were detected through unconditional and conditional QTLs mapping, which explained 9.15–45.08% of the phenotypic variation. QTLs only identified under conditional QTL mapping were located in three marker intervals: WPT-3743–GLU-D1 (1D), WPT-7001–WMC258 (1B), and WPT-8682–WPT-5562 (1B). Six pairs of epistatic QTLs distributed nine chromosomes were identified. Of these, two main effect QTLs (QGi1D-13 and QSv1D-14) and 12 pairs of epistatic QTLs were involved in interactions with the environment. The results indicated that chromosomes 1B and 1D are important for the improvement of gluten strength in common wheat. The combination of conditional and unconditional QTLs mapping could be useful for a better understanding of the interdependence of different traits at the QTL molecular level.

QTL mapping for nine drought-responsive agronomic traits in bread wheat under irrigated and rain-fed environments.

In bread wheat, QTL interval mapping was conducted for nine important drought responsive agronomic traits. For this purpose, a doubled haploid (DH) mapping population derived from Kukri/Excalibur was grown over three years at four separate locations in India, both under irrigated and rain-fed environments. Single locus analysis using composite interval mapping (CIM) allowed detection of 98 QTL, which included 66 QTL for nine individual agronomic traits and 32 QTL, which affected drought sensitivity index (DSI) for the same nine traits. Two-locus analysis allowed detection of 19 main effect QTL (M-QTL) for four traits (days to anthesis, days to maturity, grain filling duration and thousand grain weight) and 19 pairs of epistatic QTL (E-QTL) for two traits (days to anthesis and thousand grain weight). Eight QTL were common in single locus analysis and two locus analysis. These QTL (identified both in single- and two-locus analysis) were distributed on 20 different chromosomes (except 4D). Important genomic regions on chromosomes 5A and 7A were also identified (5A carried QTL for seven traits and 7A carried QTL for six traits). Marker-assisted recurrent selection (MARS) involving pyramiding of important QTL reported in the present study, together with important QTL reported earlier, may be used for improvement of drought tolerance in wheat. In future, more closely linked markers for the QTL reported here may be developed through fine mapping, and the candidate genes may be identified and used for developing a better understanding of the genetic basis of drought tolerance in wheat.

Identification and validation of major QTLs and epistatic interactions for seed oil content in soybeans under multiple environments based on a high-density map

The seed oil content in soybean is an important trait that drives successful soybean quality. A recombination of inbred lines derived from a cross between the ‘Charleston’ and ‘Dongnong594’ cultivars was planted in one location (HRB) across 13 years and two locations (HXL and JMS) across 6 years in China (25 environments in total), and the genetic effects were partitioned into additive main effects, epistatic main effects and their environmental interaction effects using composite interval mapping and inclusive composite interval mapping models based on a high-density genetic map. Twelve main-effect quantitative trait loci (QTLs) were identified on chromosomes Ch3, Ch4, Ch6, Ch13, Ch15, Ch17, Ch18,Ch19 and Ch20 and detected in more than two environments. Among the intervals of the main-effect QTLs, eleven candidate genes were screened for their involvement in seed oil content and/or fatty acid biosynthesis and metabolism processes based on gene ontology and annotation information, moreover, the main effect QTL were identified in a wild soybean chromosome segment substitution lines population, the phenotype and the QTL fragment showed the identity relationship significantly. Furthermore, an analysis of epistatic interactions showed that four epistatic QTL pairs were detected, and they could explain approximately 70% of the phenotypic variation interaction with environments in total. The additive main-effect QTLs and epistatic QTL pairs contributed to high phenotypic variation under multiple environments, and the results were also validated and corroborated with previous research, indicating that marker-assisted selection can be used to improve soybean oil content and that the candidate genes can also be used as a foundation data set for research on gene functions.

Linkage map construction and QTL identification of P-deficiency tolerance in Oryza rufipogon Griff. at early seedling stage

Low phosphorus availability is a major factor limiting rice productivity. In this study, a population of backcross recombinant inbred lines (BILs) derived from an inter-specific cross (Oryza sativa L. × O. rufipogon Griff.) was used for genetic linkage map construction and quantitative trait locus (QTL) mapping. The results showed that a linkage map consisting of 153 markers was constructed. Twenty-one out of 231 BILs were tolerant of low-phosphorus according to the index to P-deficiency tolerance. Twenty-three QTLs on chromosomes 1, 2, 3, 7, 8, 9 and 11 were detected, of which eight QTLs showed high (22.93–37.32%) contribution to phenotypic variation. In addition, most of QTLs in this study (18 out of 23 QTLs) were located and overlapped on the chromosome 1, 3 and 11, which individually explained 6.07–34.70% phenotypic variation, indicating that there might be multiple main effect QTLs related to P-deficiency tolerance in O. rufipogon, and these QTLs might cluster in the same region. These results would provide helpful information for cloning and utilizing the P-deficiency tolerance-responsive genes from O. rufipogon.

QTL analysis of cotton fiber length in advanced backcross populations derived from a cross between Gossypium hirsutum and G. mustelinum

QTLs for fiber length mapped in three generations of advanced backcross populations derived from crossing Gossypium hirsutum and Gossypium mustelinum showed opportunities to improve elite cottons by introgression from wild relatives. The molecular basis of cotton fiber length in crosses between Gossypium hirsutum and Gossypium mustelinum was dissected using 21 BC3F2 and 12 corresponding BC3F2:3 and BC3F2:4 families. Sixty-five quantitative trait loci (QTLs) were detected by one-way analysis of variance. The QTL numbers detected for upper-half mean length (UHM), fiber uniformity index (UI), and short fiber content (SFC) were 19, 20, and 26 respectively. Twenty-three of the 65 QTLs could be detected at least twice near adjacent markers in the same family or near the same markers across different families/generations, and 32 QTLs were detected in both one-way variance analyses and mixed model-based composite interval mapping. G. mustelinum alleles increased UHM and UI and decreased SFC for five, one, and one QTLs, respectively. In addition to the main-effect QTLs, 17 epistatic QTLs were detected which helped to elucidate the genetic basis of cotton fiber length. Significant among-family genotypic effects were detected at 18, 16, and 16 loci for UHM, UI, and SFC, respectively. Six, two, and two loci showed genotype × family interaction for UHM, UI and SFC, respectively, illustrating complexities that might be faced in introgression of exotic germplasm into cultivated cotton. Co-location of many QTLs for UHM, UI, and SFC accounted for correlations among these traits, and selection of these QTLs may improve the three traits simultaneously. The simple sequence repeat (SSR) markers associated with G. mustelinum QTLs will assist breeders in transferring and maintaining valuable traits from this exotic source during cultivar development.

Examining two sets of introgression lines reveals background-independent and stably expressed QTL that improve grain appearance quality in rice (Oryza sativa L.)

Key messageA novel QTL cluster for appearance quality on Chr07 was identified using reciprocal introgression populations in different locations in China. Two secondary F2populations validated QTL with significant effect on appearance quality.Appearance quality (AQ) is the main determinants of market value of rice. Identification of QTL affecting AQ is the prerequisite for efficient improvement of AQ through marker-assisted selection (MAS). Two sets of reciprocal introgression lines derived from indica Minghui 63 and japonica 02428 were used to dissect the stability of QTL affecting five AQ traits, including grain length, grain width, length to width ratio, percentage of grains with chalkiness, and degree of endosperm chalkiness using 4568 bin genotype produced from 58,000 SNPs across five different environments. A total of 41 and 30 main-effect QTL were identified in MH63 and 02428 backgrounds, respectively. Among them, 9 background-independent QTL (BI-QTL) were found. There were also 13 and 10 stable-expressed QTL (SE-QTL) across at least two environments in MH63 and 02428 backgrounds, respectively. Two important BI- and SE-QTL regions (BISERs) including BISER-I harboring qPGWC5, qDEC5, qGW5.1, and qLWR5 on chromosome 5 and BISER-II harboring qGL7, qLWR7, qPGWC7, and qDEC7 on chromosome 7 were identified. The BISER-II was newly reported and validated by two secondary F2 populations in the reciprocal backgrounds. Among 59 epistatic QTL (E-QTL) detected in this study, there were only four SE- but no BI-E-QTL detected in different environments, indicating that genetic background has stronger effect on AQ traits than the environmental factors, especially for percentage of grains with chalkiness (PGWC) and degree of endosperm chalkiness (DEC) with lower heritability. BISER-I and BISER-II harboring many BI- and SE-QTL with favorable alleles from slender grain rice are much important for improvement of rice AQ by MAS.

Mapping QTLs for plant height and flowering time in a Chinese summer planting soybean RIL population

Soybean is a primary source of plant oil and protein and has a high nutritional value. Plant height (PH) and flowering time (FT) are two important agronomic traits in breeding programs for soybean. In this study, we mapped QTLs associated with PH and FT in three environments using a population with determinate growth including 236 recombinant inbred lines (NJZY-RIL) derived from a cross between two summer planting varieties, ZXD and NN1138-2. A high-density genetic map with 3255 SLAF-markers was constructed that spanned 2144.85 cM of the soybean genome with an average marker distance of 0.66 cM. Altogether, six QTLs controlling PH and eleven QTLs controlling FT were mapped using mixed-model-based composite interval mapping and composite interval mapping methods. qPH-1-1 and qFT-15-2 were two novel main effect QTLs identified in this study; qFT-6-2, qFT-15-2, qFT-16-1, qPH-1-1, qPH-15-1 and qPH-16-1 were consistently detected across environments and by the two mapping methods. Two pairs of QTLs, qFT-15-2 and qPH-15-1 as well as qFT-16-1 and qPH-16-1, which were located in the same marker interval on chromosomes 15 and 16, respectively, were found to have close linkage or pleiotropy. These results may increase our understanding of the genetic control of PH and FT in soybean and provide support for implementing marker-assisted selection in developing soybean cultivars with high yield and early maturity in summer planting regions.

Exploring the quantitative resistance to Pseudomonas syringae pv. phaseolicola in common bean (Phaseolus vulgaris L.)

Pseudomonas syringae pv. phaseolicola is an important disease that causes halo blight in common bean. The genetic mechanisms underlying quantitative halo blight resistance are poorly understood in this species, as most disease studies have focused on qualitative resistance. The present work examines the genetic basis of quantitative resistance to the nine halo blight races in different organs (primary and trifoliate leaf, stem and pod) of an Andean recombinant inbred line (RIL) progeny. Using a multi-environment quantitative trait locus (QTL) mapping approach, 76 and 101 main-effect and epistatic QTLs were identified, respectively. Most of the epistatic interactions detected were due to loci without detectable QTL additive main effects. Main and epistatic QTLs detected were mainly consistent across the environment conditions. The homologous genomic regions corresponding to 26 of the 76 main-effect detected QTLs were positive for the presence of resistance-associated gene cluster encoding nucleotide-binding and leucine-rich repeat (NL) proteins and known defence genes. Main-effect QTLs for resistance to races 3, 4 and 5 in leaf, stem and pod were located on chromosome 2 within a 3.01-Mb region, where a cluster of nine NL genes was detected. The NL gene Phvul.002G323300 is located in this region, which can be considered an important putative candidate gene for the non-organ-specific QTL identified here. The present research provides essential information not only for the better understanding of the plant-pathogen interaction but also for the application of genomic assisted breeding for halo blight resistance in common bean.

Identification of QTL for Fiber Quality and Yield Traits Using Two Immortalized Backcross Populations in Upland Cotton.

Two immortalized backcross populations (DHBCF1s and JMBCF1s) were developed using a recombinant inbred line (RIL) population crossed with the two parents DH962 and Jimian5 (as the males), respectively. The fiber quality and yield component traits of the two backcross populations were phenotyped at four environments (two locations, two years). One hundred seventy-eight quantitative trait loci (QTL) were detected including 76 for fiber qualities and 102 for yield components, explaining 4.08–17.79% of the phenotypic variation (PV). Among the 178 QTL, 22 stable QTL were detected in more than one environment or population. A stable QTL, qFL-c10-1, was detected in the previous F2 population, a RIL population in 3 environments and the current two BCF1 populations in this study, explaining 5.79–37.09% of the PV. Additionally, 117 and 110 main-effect QTL (M-QTL) and 47 and 191 digenic epistatic QTL (E-QTL) were detected in the DHBCF1s and JMBCF1s populations, respectively. The effect of digenic epistasis played a more important role on lint percentage, fiber length and fiber strength. These results obtained in the present study provided more resources to obtain stable QTL, confirming the authenticity and reliability of the QTL for molecular marker-assisted selection breeding and QTL cloning.