Main-effect Quantitative Trait Loci Research Articles

Combined genome and transcriptome analysis of elite fiber quality in Gossypium barbadense.

Gossypium barbadense, which is one of several species of cotton, is well-known for its superior fiber quality. However, the genetic basis of its high-quality fiber remains largely unexplored. Here, we re-sequenced 269 G. barbadense accessions. Phylogenetic structure analysis showed that the set of accessions were clustered into three groups, G1 and G2 mainly included modern cultivars from Xinjiang, China, and G3 was related to widely introduced accessions in different regions worldwide. A genome-wide association study of five fiber quality traits across multiple field environments identified a total of 512 qtls (main effect QTLs) and 94 qtlEs (QTL-by-environment interactions) related to fiber quality, of which 292 qtls and 57 qtlEs co-located with previous studies. We extracted the genes located in these loci and performed expression comparison, local association analysis, and introgression segment identification. The results showed that high expression of hormone-related genes during fiber development, introgressions from G. hirsutum, and the recombination of domesticated elite allelic variation, were three major contributors to improve fiber quality of G. barbadense. In total, 839 candidate genes with encoding region variation associated with elite fiber quality were mined. We confirmed that haplotype GB_D03G0092H traced from G. hirsutum introgression, with a 1-bp deletion leading to a frameshift mutation compared with GB_D03G0092B, significantly improved fiber quality. GB_D03G0092H localized in the plasma membrane, while GB_D03G0092B in both the nucleus and plasma membrane. Overexpression of GB_D03G0092H in Arabidopsis (Arabidopsis thaliana) significantly improved the elongation of longitudinal cells. Our study systematically reveals the genetic basis of the superior fiber quality of G. barbadense and provides elite segments and gene resources for breeding high-quality cotton cultivars.

Inheritance and genetic mapping of the first CPMMV tolerance locus in common bean

AbstractAlthough cowpea mild mottle virus (CPMMV) has been reported in Brazil since 1983, it has only become a significant concern for researchers and farmers in recent years. The objective of this work was to investigate the genetic basis of CPMMV tolerance, mapping and reporting the first loci associated with this trait in common bean (cv. BRS Sublime). Phenotypic assays were carried out on 180 individual plants (F2 generation) and 180 F2:3 progenies comprising 12 plants per family and their parents (BRS Sublime, tolerant parent × CNFCT 16207, susceptible parent). CPMMV was mechanically inoculated and symptoms were evaluated at 35 days after inoculation, using a 1–5 scoring scale. A linkage map was constructed using 1695 single‐nucleotide polymorphism (SNP) and SilicoDArT markers that segregated in the F2 and F2:3 generations as expected. Markers were distributed across 11 common bean chromosomes, resulting in a total length of 2864 cM, with an average distance between markers of 1.8 cM. Phenotypic observations revealed that tolerance in cv. BRS Sublime is controlled by a single dominant gene. The main effect quantitative trait locus (QTL; CPMMV.Pv08) associated with CPMMV tolerance was identified in the terminal region on chromosome 8 (Pv08). This QTL explained approximately 77% of phenotypic variation, indicating that the inheritance of tolerance to CPMMV is monogenic, controlled by a major locus. As far as we know, this study represents the first investigation into the inheritance and genetic mapping of CPMMV tolerance in common bean, with potential for the development of elite lines with multiple virus resistance/tolerance.

Mapping of QTLs and meta-QTLs for Heterodera avenae Woll. resistance in common wheat (Triticum aestivum L.)

BackgroundIn hexaploid wheat, quantitative trait loci (QTL) and meta-QTL (MQTL) analyses were conducted to identify genomic regions controlling resistance to cereal cyst nematode (CCN), Heterodera avenae. A mapping population comprising 149 RILs derived from the cross HUW 468 × C 306 was used for composite interval mapping (CIM) and inclusive composite interval mapping (ICIM).ResultsEight main effect QTLs on three chromosomes (1B, 2A and 3A) were identified using two repeat experiments. One of these QTLs was co-localized with a previously reported wheat gene Cre5 for resistance to CCN. Seven important digenic epistatic interactions (PVE = 5% or more) were also identified, each involving one main effect QTL and another novel E-QTL. Using QTLs earlier reported in literature, two meta-QTLs were also identified, which were also used for identification of 57 candidate genes (CGs). Out of these, 29 CGs have high expression in roots and encoded the following proteins having a role in resistance to plant parasitic nematodes (PPNs): (i) NB-ARC,P-loop containing NTP hydrolase, (ii) Protein Kinase, (iii) serine-threonine/tyrosine-PK, (iv) protein with leucine-rich repeat, (v) virus X resistance protein-like, (vi) zinc finger protein, (vii) RING/FYVE/PHD-type, (viii) glycosyl transferase, family 8 (GT8), (ix) rubisco protein with small subunit domain, (x) protein with SANT/Myb domain and (xi) a protein with a homeobox.ConclusionIdentification and selection of resistance loci with additive and epistatic effect along with two MQTL and associated CGs, identified in the present study may prove useful for understanding the molecular basis of resistance against H. avenae in wheat and for marker-assisted selection (MAS) for breeding CCN resistant wheat cultivars.

Genetic dissection of cold tolerance at the budding stage of rice in an indica-japonica recombination inbred line population

Rice is highly cold-sensitive, and thus, the promotion of cold resistance in buds is essential. In this study, we conducted a mapping analysis to identify quantitative trait loci (QTLs) associated with cold tolerance in buds. The analysis was performed using a recombinant inbred line (RIL) population consisting of 192 lines derived from the cold-tolerant strain 02428 and the cold-sensitive strain YZX. Seven additive loci on chromosomes 1, 4, 5, and 6 were identified, of which loci 3 and 7 were found in two crop seasons, indicating stability. Three epistatic interactions, one present over two seasons, were found. Loci 3 and 7 pyramided with two main-effect QTLs observed to control the rate of low-temperature germination in our previous study. Two materials with good cold resistance at the germination and bud stages were obtained, namely, G93 and G146. Transcriptome sequencing analysis of the two parent buds after cold treatment found that genes expressed differentially between the two parents were related to photosynthesis, energy metabolism, and reactive oxygen scavenging. Five candidate genes, namely, Os01g0385400, Os01g0388000, Os06g0287700, Os06g0289200, and Os06g0291100, were selected in the two stable intervals based on gene expression profiles and annotations. These genetic loci exhibit strong potential as targets for breeding cold tolerance in buds and require additional investigation. In conclusion, this work provides valuable genetic resources that can be utilized to improve the cold tolerance of rice.

Genetic mapping identified major main-effect and three co-localized quantitative trait loci controlling high iron and zinc content in groundnut.

Malnutrition is a major challenge globally, and groundnut is a highly nutritious self-pollinated legume crop blessed with ample genomic resources, including the routine deployment of genomic-assisted breeding. This study aimed to identify genomic regions and candidate genes for high iron (Fe) and zinc (Zn) content, utilizing a biparental mapping population (ICGV 00440×ICGV 06040;). Genetic mapping and quantitative trait locus (QTL) analysis (474 mapped single-nucleotide polymorphism loci; 1536.33cM) using 2 seasons of phenotypic data together with genotypic data identified 5 major main-effect QTLs for Fe content. These QTLs exhibited log-of-odds (LOD) scores ranging from 6.5 to 7.4, explaining phenotypic variation (PVE) ranging from 22% (qFe-Ah01) to 30.0% (qFe-Ah14). Likewise, four major main effect QTLs were identified for Zn content, with LOD score ranging from 4.4 to 6.8 and PVE ranging from 21.8% (qZn-Ah01) to 32.8% (qZn-Ah08). Interestingly, three co-localized major and main effect QTLs (qFe-Ah01, qZn-Ah03, and qFe-Ah11) were identified for both Fe and Zn contents. These genomic regions harbored key candidate genes, including zinc/iron permease transporter, bZIP transcription factor, and vacuolar iron transporter which likely play pivotal roles in the accumulation of Fe and Zn contents in seeds. The findings of this study hold potential for fine mapping and diagnostic marker development for high Fe and Zn contents in groundnut.

Genetic mapping identified three hotspot genomic regions and candidate genes controlling heat tolerance-related traits in groundnut.

Groundnut productivity and quality have been impeded by rising temperatures in semi-arid environments. Hence, understanding the effects and molecular mechanisms of heat stress tolerance will aid in tackling yield losses. In this context, a recombinant inbred line (RIL) population was developed and phenotyped for eight seasons at three locations for agronomic, phenological, and physiological traits under heat stress. A genetic map was constructed using genotyping-by-sequencing with 478 single-nucleotide polymorphism (SNP) loci spanning a map distance of 1,961.39 cM. Quantitative trait locus (QTL) analysis using phenotypic and genotypic data identified 45 major main-effect QTLs for 21 traits. Intriguingly, three QTL clusters (Cluster-1-Ah03, Cluster-2-Ah12, and Cluster-3-Ah20) harbor more than half of the major QTLs (30/45, 66.6%) for various heat tolerant traits, explaining 10.4%-38.6%, 10.6%-44.6%, and 10.1%-49.5% of phenotypic variance, respectively. Furthermore, important candidate genes encoding DHHC-type zinc finger family protein (arahy.J0Y6Y5), peptide transporter 1 (arahy.8ZMT0C), pentatricopeptide repeat-containing protein (arahy.4A4JE9), Ulp1 protease family (arahy.X568GS), Kelch repeat F-box protein (arahy.I7X4PC), FRIGIDA-like protein (arahy.0C3V8Z), and post-illumination chlorophyll fluorescence increase (arahy.92ZGJC) were the underlying three QTL clusters. The putative functions of these genes suggested their involvement in seed development, regulating plant architecture, yield, genesis and growth of plants, flowering time regulation, and photosynthesis. Our results could provide a platform for further fine mapping, gene discovery, and developing markers for genomics-assisted breeding to develop heat-tolerant groundnut varieties.

Application of a Novel Quantitative Trait Locus Combination to Improve Grain Shape without Yield Loss in Rice (Oryza sativa L. spp. japonica).

Grain shape is one of the key factors deciding the yield product and the market value as appearance quality in rice (Oryza sativa L.). The grain shape of japonica cultivars in Korea is quite monotonous because the selection pressure of rice breeding programs works in consideration of consumer preference. In this study, we identified QTLs associated with grain shape to improve the variety of grain shapes in Korean cultivars. QTL analysis revealed that eight QTLs related to five tested traits were detected on chromosomes 2, 5, and 10. Among them, three QTLs-qGL2 (33.9% of PEV for grain length), qGW5 (64.42% for grain width), and qGT10 (49.2% for grain thickness)-were regarded as the main effect QTLs. Using the three QTLs, an ideal QTL combination (qGL2P + qGW5P + qGT10B) could be constructed on the basis of the accumulated QTL effect without yield loss caused by the change in grain shape in the population. In addition, three promising lines with a slender grain type were selected as a breeding resource with a japonica genetic background based on the QTL combination. The application of QTLs detected in this study could improve the grain shape of japonica cultivars without any linkage drag or yield loss.

QTL Mapping of Growth Traits in Yellow River Carp (Cyprinus carpio haematopterus) at 5–17 Months after Hatching

To screen the quantitative trait loci (QTL) and genes related to the growth of Yellow River carp (Cyprinus carpio haematopterus) after removing the maternal effect, we established a family of these carps. Four growth-related traits (body length, height, thickness, and weight) of the family at 5 and 17 months after hatching (MAH) were measured. Analysis of QTL mapping for the four growth-related traits was conducted using the genetic linkage map constructed in our laboratory. We identified 47 QTL that were related to the four growth traits and three consensus QTL (cQTL). A total of 10, 14, 10, and 13 QTL were associated with body length, height, thickness, and weight, respectively; cQTL-1, cQTL-2, and cQTL-3 contained 11, 2, and 2 QTL, respectively. We detected 17 growth-related candidate genes within 50 Kb upstream and downstream of the five main-effect QTL (phenotypic variation explained > 10%, logarithm of odds > 5.5). Two genes (cbfa2t2 and neca1) that may be affected by maternal effects were identified by comparing the main-effect QTL at 17 and 5–17 MAH. This study was the first attempt to eliminate growth-related QTL and genes affected by maternal effects in Yellow River carp. These results can be used in molecular marker-assisted breeding and provide valuable genomic resources for the genetic mechanisms underlying growth in Yellow River carp.

QTL analysis for nitrogen use efficiency in wheat (Triticum aestivum L.)

The genetic architecture of nitrogen use efficiency (NUE) and its two component traits i.e. NUpE (N uptake efficiency) and NUtE (N utilization efficiency) was studied using a bi-parental RIL mapping population derived from a cross HUW468 (high NUE)/C306 (low NUE). The mapping population, two parental genotypes and three check genotypes were evaluated under four different N levels (0, 60, 120, and 180 kg/ha) over three years. A genetic map containing 456 SNP markers (2571.38 cM length) was used for QTL analysis. Thirty six main effect QTLs (17 QTLs for NUE, 13 NUpE and 6 QTLs for NUtE) distributed on 12 chromosomes (1B, 1D, 2A, 2B, 3A, 4B, 5A, 5B, 5D, 6A, 6D, and 7A) were identified at 2.52–9.27 LOD scores. Individual QTLs explained 6.65–22.89% phenotypic variation. Multi-traits QTLs (Mt-QTLs) and epistatic QTLs involving first-order epistatic (QTL × QTL) interactions were also discovered. Candidate genes (CGs, as many as 737) were mined from QTL regions which were mainly involved in metabolic process, cellular process and catalytic activity, etc.; differential expression was observed for 49 CGs in roots and 34 in shoots. The CGs encoded important transcription factors, transporters, etc. having a role in NUE. QTLs and CGs reported in this study enriched the available knowledge. Seven QTLs (including three Mt-QTLs) and QTLs involved in six epistatic interactions are recommended for MAS for improvement of NUE in wheat.

Genomic Mapping, Molecular Marker and Marker Assisted Selection in Rice: A Review

Increased agricultural output is necessary to feed a growing world population, yet crop yield growth rates are currently slowing down. Therefore, qualities related to yield, stability, and sustainability should take center stage in plant breeding initiatives. Durable disease resistance, abiotic stress tolerance, and effective nutrition and water usage are a few of these characteristics. On several rice chromosomes, various resistance genes have been discovered, mapped, and tightly connected DNA markers have been created. The following qualities were chosen as potential molecular marker candidates: fragrance, disease resistance to bacterial, blast, and sheath blights, grain extension while cooking, chalkiness propensity, gelatinization temperature, minor aroma components, and seedling vigor/early establishment. With the help of developments in genetics and genomics, it is now feasible to go into the history of rice domestication and identify the precise genetic processes that were influenced by human selection. Agronomic main effect quantitative trait loci (QTLs) may contribute cumulatively to genetic variation, with hybrids showing stronger effects and comparatively fewer contributions from epistatic effects.

Genomic Architecture of Yield Performance of an Elite Rice Hybrid Revealed by its Derived Recombinant Inbred Line and Their Backcross Hybrid Populations

BackgroundSince its development and wide adoption in China, hybrid rice has reached the yield plateau for more than three decades. To understand the genetic basis of heterosis in rice and accelerate hybrid rice breeding, the yield performances of the elite rice hybrid, Quan-you-si-miao (QYSM) were genetically dissected by whole-genome sequencing, large-scale phenotyping of 1061 recombined inbred lines (RILs) and 1061 backcross F1 (BCF1) hybrids derived from QYSM’s parents across three environments and gene-based analyses.ResultsGenome-wide scanning of 13,847 segregating genes between the parents and linkage mapping based on 855 bins across the rice genome and phenotyping experiments across three environments resulted in identification of large numbers of genes, 639 main-effect QTLs (M-QTLs) and 2736 epistatic QTLs with significant additive or heterotic effects on the trait performances of the combined population consisting of RILs and BCF1 hybrids, most of which were environment-specific. The 324 M-QTLs affecting yield components included 32.7% additive QTLs, 38.0% over-dominant or dominant ones with strong and positive effects and 29.3% under-dominant or incomplete recessive ones with significant negative heterotic effects.63.6% of 1403 genes with allelic introgression from subspecies japonica/Geng in the parents of QYSM may have contributed significantly to the enhanced yield performance of QYSM.ConclusionsThe parents of QYSM and related rice hybrids in China carry disproportionally more additive and under-dominant genes/QTLs affecting yield traits. Further focus in indica/Xian rice breeding should shift back to improving inbred varieties, while breaking yield ceiling of Xian hybrids can be achieved by one or combinations of the three strategies: (1) by pyramiding favorable alleles of additive genes, (2) by eliminating or minimizing under-dominant loci, and (3) by pyramiding overdominant/dominant genes polymorphic, particularly those underlying inter-subspecific heterosis.

WheatQTLdb V2.0: a supplement to the database for wheat QTL.

We recently developed a database for hexaploid wheat QTL (WheatQTLdb; www.wheatqtldb.net), which included 11,552 QTL affecting various traits of economic importance. However, that database did not include valuable QTL from other wheat species and/or progenitors of hexaploidwheat. Therefore, an updated and improved version of wheat QTL database (WheatQTLdb V2.0) was developed, which now includes information on hexaploid wheat (Triticum aestivum) and the following seven other related species: T. durum, T. turgidum, T. dicoccoides, T. dicoccum, T. monococcum, T. boeoticum, and Aegilops tauschii. WheatQTLdb V2.0 includes a much-improved list of QTL, including 27,518 main effect QTL, 202 epistatic QTL, and 1321 metaQTL. This newly released WheatQTLdb V2.0 also has additional valuable options to search and choose the QTL, category-wise, and trait-wise data for their use inresearch or breeding programs.

A novel procedure for identifying a hybrid QTL-allele system for hybrid-vigor improvement, with a case study in soybean (Glycine max) yield

“Breeding by design” for pure lines may be achieved by construction of an additive QTL-allele matrix in a germplasm panel or breeding population, but this option is not available for hybrids, where both additive and dominance QTL-allele matrices must be constructed. In this study, a hybrid-QTL identification approach, designated PLSRGA, using partial least squares regression (PLSR) for model fitting integrated with a genetic algorithm (GA) for variable selection based on a multi-locus, multi-allele model is described for additive and dominance QTL-allele detection in a diallel hybrid population (DHP). The PLSRGA was shown by simulation experiments to be superior to single-marker analysis and was then used for QTL-allele identification in a soybean DPH yield experiment with eight parents. Twenty-eight main-effect QTL with 138 alleles and nine QTL × environment QTL with 46 alleles were identified, with respective contributions of 61.8% and 23.5% of phenotypic variation. Main-effect additive and dominance QTL-allele matrices were established as a compact form of the DHP genetic structure. The mechanism of heterosis superior-to-parents (or superior-to-parents heterosis, SPH) was explored and might be explained by a complementary locus-set composed of OD+ (showing positive over-dominance, most often), PD+ (showing positive partial-to-complete dominance, less often) and HA+ (showing positive homozygous additivity, occasionally) loci, depending on the parental materials. Any locus-type, whether OD+, PD + and HA+, could be the best genotype of a locus. All hybrids showed various numbers of better or best genotypes at many but not necessarily all loci, indicating further SPH improvement. Based on the additive/dominance QTL-allele matrices, the best hybrid genotype was predicted, and a hybrid improvement approach is suggested. PLSRGA is powerful for hybrid QTL-allele detection and cross-SPH improvement.

Genetic mechanism of heterosis for rice milling and appearance quality in an elite rice hybrid

Development of hybrid rice with high yield and grain quality is a goal of rice breeding. To investigate the genetic mechanism of heterosis for rice milling and appearance quality in indica/xian rice, QTL mapping was conducted using 1061 recombinant inbred lines (RILs) derived from a cross of the xian rice cultivars Quan9311B (Q9311B) and Wu-shan-si-miao (WSSM), and a backcross F1 (BC1F1) population developed by crossing the RILs with Quan9311A (Q9311A), combined with phenotyping in two environments. The F1 hybrid (Q9311A × WSSM) showed various degrees of heterosis for milling and appearance quality. A total of 142 main-effect QTL (M-QTL) and 407 pairs of epistatic QTL (E-QTL) were identified for five milling and appearance quality traits and grain yield per plant (GYP) in the RIL, BC1F1 and mid-parental heterosis (HMP) populations. Differential detection of QTL in three populations revealed that most additive loci detected in the RILs did not show heterotic effects, but some of them did contribute to BC1F1 trait performance. Unlike heterosis of GYP, single-locus overdominance and epistasis were the main contributors to heterosis for milling and appearance quality. Epistasis contributed more to the heterosis for milling quality than to that for appearance quality. Three (four) QTL regions harboring opposite (consistent) directions of favorable allele effects for GYP and grain quality were identified, indicating the presence of partial genetic overlaps between GYP and grain quality. Three strategies are proposed to develop hybrid rice with high yield and good grain quality: 1) pyramiding favorable alleles with consistent directions of gene effects for GYP and grain quality at the M-QTL on different chromosomes; 2) introgressing favorable alleles for GYP and grain quality into the parents and then pyramiding and fixing these additive effects in hybrids; and 3) pyramiding overdominant and dominant loci and minimizing or eliminating underdominant loci from the parents.

Genetic Dissection of Rice Ratooning Ability Using an Introgression Line Population and Substitution Mapping of a Pleiotropic Quantitative Trait Locus qRA5.

Ratooning ability is a key factor that influences ratoon rice yield, in the area where light and temperature are not enough for second season rice. In the present study, an introgression line population derived from Minghui 63 as the recipient parent and 02428 as the donor parent was developed, and a high-density bin map containing 4568 bins was constructed. Nine ratooning-ability-related traits were measured, including maximum tiller number, panicle number, and grain yield per plant in the first season and ratoon season, as well as three secondary traits, maximum tiller number ratio, panicle number ratio, and grain yield ratio. A total of 22 main-effect QTLs were identified and explained for 3.26–18.63% of the phenotypic variations in the introgression line population. Three genomic regions, including 14.12–14.65 Mb on chromosome 5, 4.64–5.76 Mb on chromosome 8, and 10.64–15.52 Mb on chromosome 11, were identified to simultaneously control different ratooning-ability-related traits. Among them, qRA5 in the region of 14.12–14.65 Mb on chromosome 5 was validated for its pleiotropic effects on maximum tiller number and panicle number in the first season, as well as its maximum tiller number ratio, panicle number ratio, and grain yield ratio. Moreover, qRA5 was independent of genetic background and delimited into a 311.16 kb region by a substitution mapping approach. These results will help us better understand the genetic basis of rice ratooning ability and provide a valuable gene resource for breeding high-yield ratoon rice varieties.

Main effect and epistatic QTL affecting spike shattering and association with plant height revealed in two spring wheat (Triticum aestivum L.) populations

Key messageA major QTL on chromosome arm 4BS was associated with reduced spike shattering and reduced plant height in coupling phase, and a second major QTL associated with reduced spike shattering was detected on chromosome arm 5AL in the same wheat variety Carberry.Spike shattering can cause severe grain yield loss in wheat. Development of cultivars with reduced shattering but having easy mechanical threshability is the target of wheat breeding programs. This study was conducted to determine quantitative trait loci (QTL) associated with shattering resistance, and epistasis among QTL in the populations Carberry/AC Cadillac and Carberry/Thatcher. Response of the populations to spike shattering was evaluated near Swift Current, SK, in four to five environments. Plant height data recorded in different locations and years were used to determine the relationship of the trait with spike shattering. Each population was genotyped and mapped with the wheat 90 K Illumina iSelect SNP array. Main effect QTL were analyzed by MapQTL 6, and epistatic interactions between main effect QTL were determined by QTLNetwork 2.0. Correlations between height and shattering ranged from 0.15 to 0.49. Carberry contributed two major QTL associated with spike shattering on chromosome arms 4BS and 5AL, detected in both populations. Carberry also contributed two minor QTL on 7AS and 7AL. AC Cadillac contributed five minor QTL on 1AL, 2DL, 3AL, 3DL and 7DS. Nine epistatic QTL interactions were identified, out of which the most consistent and synergistic interaction, that reduced the expression of shattering, occurred between 4BS and 5AL QTL. The 4BS QTL was consistently associated with reduced shattering and reduced plant height in the coupling phase. The present findings shed light on the inheritance of shattering resistance and provide genetic markers for manipulating the trait to develop wheat cultivars.

Genetic mapping of tolerance to iron deficiency chlorosis in peanut (Arachis hypogaea L.)

Iron deficiency chlorosis (IDC) under calcareous and alkaline soils is a significant abiotic stress affecting the growth and yield of peanut. In this study, the genomic regions governing IDC tolerance were mapped using a recombinant inbred line (RIL) population derived from TMV 2 (susceptible to IDC) and TMV 2-NLM (tolerant to IDC), which was phenotyped during the rainy seasons of 2019 and 2020 in the iron-deficient calcareous plots. The best linear unbiased prediction (BLUP) values for IDC tolerance traits like visual chlorotic rating (VCR), and SPAD chlorophyll meter reading (SCMR) were used for QTL analysis along with a genetic map carrying 700 GBS-derived SNP, AhTE and SSR markers. In total, 11 and 12 main-effect QTLs were identified for VCR and SCMR, respectively. Among them three QTLs were major with the phenotypic variance explained (PVE) of 10.3–34.4% for VCR, and two QTL were major for SCMR with PVE of 11.5–11.7%. A region (159.3–178.3 cM) on chromosome Ah13 carrying two QTLs (one each for VCR and SCMR) was consistent with the previous report. A SNP marker, Ah14_138037990 identified from single marker analysis for VCR was located in the intronic region of the gene Arahy.QA0C1, which is important for protein-binding. Overall, this study identified new QTLs and also validated QTL for IDC tolerance. These genomic resources could be useful for genomics-assisted breeding of peanut for IDC tolerance.

Integrative QTL Identification, Fine Mapping and Candidate Gene Analysis of a Major Locus qLTG3a for Seed Low-Temperature Germinability in Rice

Low-temperature germinability (LTG) is an important agronomic trait that can affect the planting time, planting area, and grain yield of staple crops, such as rice. However, the genetic mechanism of LTG is still unclear. In this study, a multi-parental permanent population with 208 single segment substitution lines (SSSLs) was used to conduct a genetic dissection for LTG across four cropping seasons. LTG was a typical quantitative trait with a high combined broad-sense heritability of 0.71. By comparison with the recipient parent, Huajingxian74, 24 SSSLs were identified as carrying LTG QTLs, which were further merged into integrated QTLs with shorter genetic distances by substitution mapping. Finally, 14 LTG QTLs were mapped on ten chromosomes, including seven positive-effect and seven negative-effect QTLs, with additive effect contributions ranging from 19.2 to 39.9%. qLTG3a, a main-effect and novel QTL, was confirmed by bulk segregant analysis using an F2 segregating population, and five key recombinants were selected to develop F3 populations for progeny testing. Marker-trait association analysis fine mapped qLTG3a to a 332.7-kb physical region between markers M6026 and M6341. Within this interval, 40 annotated genes were revealed, and three genes (Os03g0213300, Os03g0214400, and Os03g0214600) were considered as pivotal candidate genes for qLTG3a based on their sequence variations and expression patterns. Besides low temperature, qLTG3a can also enhance seed germination under standard temperature and osmotic stress. In summary, this study identified some genetic factors regulating LTG and opened a new window for breeding elite direct-seeded rice varieties. It will help reduce the climate risk in the production process of rice, which is of great significance to ensuring food security.

Epistatic QTLsPlay a Major Role in Nitrogen Use Efficiency and Its Component Traits in Indian Spring Wheat

Nitrogen use efficiency (NUE) in wheat may significantly reduce the excessive use of N fertilizers. However, being a quantitative trait, understanding its genetic basis is required for efficient wheat breeding. The present study was carried out to dissect the complex trait through the mapping of quantitative trait locus (QTLs) related to NUE component traits in Indian wheat. A linkage map was constructed using F2 population derived from two parents contrasting for nitrogen-responsive traits using simple sequence repeat (SSR) markers. Phenotyping for root dry weight, N uptake and utilization were carried out under a high nitrogen environment. Twenty-seven main effect QTLs for eight traits and 26 interaction QTLs for three traits were detected. The main effect QTLs explained a significant amount of phenotypic variance up to the extent of 11.18%. The QTLs were also found to have significant epistatic interactions governed by both additive and non-additive gene action. In particular, chromosome 2A harbours QTLs for many traits viz. SDW, RDW, TDW, R:S, %N, NUtE, and NUpE, including epistasis and interaction QTLs that were flanked by markers Xwmc728-Xwmc473 and Xwmc779-Xgwm249. Taken together, the genomic regions on 2A, 4A, and 7A were found to contain QTLs for a majority of the studied NUE traits that can be potentially exploited in future wheat breeding programmes.

Genotyping-by-Sequencing Based Genetic Mapping Identified Major and Consistent Genomic Regions for Productivity and Quality Traits in Peanut.

With an objective of identifying the genomic regions for productivity and quality traits in peanut, a recombinant inbred line (RIL) population developed from an elite variety, TMV 2 and its ethyl methane sulfonate (EMS)-derived mutant was phenotyped over six seasons and genotyped with genotyping-by-sequencing (GBS), Arachis hypogaea transposable element (AhTE) and simple sequence repeats (SSR) markers. The genetic map with 700 markers spanning 2,438.1 cM was employed for quantitative trait loci (QTL) analysis which identified a total of 47 main-effect QTLs for the productivity and oil quality traits with the phenotypic variance explained (PVE) of 10–52% over the seasons. A common QTL region (46.7–50.1 cM) on Ah02 was identified for the multiple traits, such as a number of pods per plant (NPPP), pod weight per plant (PWPP), shelling percentage (SP), and test weight (TW). Similarly, a QTL (7.1–18.0 cM) on Ah16 was identified for both SP and protein content (PC). Epistatic QTL (epiQTL) analysis revealed intra- and inter-chromosomal interactions for the main-effect QTLs and other genomic regions governing these productivity traits. The markers identified by a single marker analysis (SMA) mapped to the QTL regions for most of the traits. Among the five potential candidate genes identified for PC, SP and oil quality, two genes (Arahy.7A57YA and Arahy.CH9B83) were affected by AhMITE1 transposition, and three genes (Arahy.J5SZ1I, Arahy.MZJT69, and Arahy.X7PJ8H) involved functional single nucleotide polymorphisms (SNPs). With major and consistent effects, the genomic regions, candidate genes, and the associated markers identified in this study would provide an opportunity for gene cloning and genomics-assisted breeding for increasing the productivity and enhancing the quality of peanut.