Quantitative Trait Loci For Yield Research Articles

OsGELP77, a QTL for broad-spectrum disease resistance and yield in rice, encodes a GDSL-type lipase.

Lipids and lipid metabolites have essential roles in plant-pathogen interactions. GDSL-type lipases are involved in lipid metabolism modulating lipid homeostasis. Some plant GDSLs modulate lipid metabolism altering hormone signal transduction to regulate host-defence immunity. Here, we functionally characterized a rice lipase, OsGELP77, promoting both immunity and yield. OsGELP77 expression was induced by pathogen infection and jasmonic acid (JA) treatment. Overexpression of OsGELP77 enhanced rice resistance to both bacterial and fungal pathogens, while loss-of-function of osgelp77 showed susceptibility. OsGELP77 localizes to endoplasmic reticulum and is a functional lipase hydrolysing universal lipid substrates. Lipidomics analyses demonstrate that OsGELP77 is crucial for lipid metabolism and lipid-derived JA homeostasis. Genetic analyses confirm that OsGELP77-modulated resistance depends on JA signal transduction. Moreover, population genetic analyses indicate that OsGELP77 expression level is positively correlated with rice resistance against pathogens. Three haplotypes were classified based on nucleotide polymorphisms in the OsGELP77 promoter where OsGELP77Hap3 is an elite haplotype. Three OsGELP77 haplotypes are differentially distributed in wild and cultivated rice, while OsGELP77Hap3 has been broadly pyramided for hybrid rice development. Furthermore, quantitative trait locus (QTL) mapping and resistance evaluation of the constructed near-isogenic line validated OsGELP77, a QTL for broad-spectrum disease resistance. In addition, OsGELP77-modulated lipid metabolism promotes JA accumulation facilitating grain yield. Notably, the hub defence regulator OsWRKY45 acts upstream of OsGELP77 by initiating the JA-dependent signalling to trigger immunity. Together, OsGELP77, a QTL contributing to immunity and yield, is a candidate for breeding broad-spectrum resistant and high-yielding rice.

Identification of robust yield quantitative trait loci derived from cultivated emmer for durum wheat improvement.

Durum wheat (Triticum turgidum ssp. durum L.) is an important world food crop used to make pasta products. Compared to bread wheat (Triticum aestivum L.), fewer studies have been conducted to identify genetic loci governing yield-component traits in durum wheat. A potential source of diversity for durum is its immediate progenitor, cultivated emmer (T. turgidum ssp. dicoccum). We evaluated two biparental populations of recombinant inbred lines (RILs) derived from crosses between the durum lines Ben and Rusty and the cultivated emmer wheat accessions PI 41025 and PI 193883, referred to as the Ben×PI 41025 (BP025) and Rusty×PI 193883 (RP883) RIL populations, respectively. Both populations were evaluated under field conditions in three seasons with an aim to identify quantitative trait loci (QTLs) associated with yield components and seed morphology that were expressed in multiple environments. A total of 44 and 34 multi-environment QTLs were identified in the BP025 and RP883 populations, respectively. As expected, genetic loci known to govern domestication and development were associated with some of the QTLs, but novel QTLs derived from the cultivated emmer parents and associated with yield components including spikelet number, grain weight, and grain size were identified. These QTLs offer new target loci for durum wheat improvement, and toward that goal, we identified five RILs with increased grain weight and size compared to the durum parents. These materials along with the knowledge of stable QTLs and associated markers can help to expedite the development of superior durum varieties.

Mapping QTL for Yield and Its Component Traits Using Wheat (Triticum aestivum L.) RIL Mapping Population from TAM 113 × Gallagher

Understanding genetic architectures of yield and yield-related traits of wheat (Triticum aestivum L.) grown under dryland or irrigated conditions is pivotal for developing modern high-yielding germplasm and cultivars. The objectives of this study were to detect quantitative trait loci (QTL) linked to yield and yield components using a mapping population derived from ‘TAM 113’/‘Gallagher’, including 191 recombinant inbred lines (RILs). The population was grown in McGregor, College Station, and Bushland, Texas, for three consecutive years from 2019 to 2021. A high-density genetic map covering all 21 chromosomes was constructed using a set of 8,075 single nucleotide polymorphisms (SNPs) obtained using genotyping-by-sequencing (GBS). A total of 147 QTLs for 16 yield-related traits were identified, which included 16 QTLs consistently detected in multiple experiments and 8 QTLs that showed pleiotropic effects. Of them, five pleiotropic QTLs overlapped with the consistent QTL. They increased grain yield (YLD) up to 37.64 g m−2, thousand kernel weight (TKW) up to 1.33 g, harvest (HI) up to 0.97%, kernel length up to 0.08 mm, and kernel width up to 0.04 mm with Gallagher alleles and increased YLD up to 22.21 g m−2, kernels spike−1 up to 1.77, TKW up to 1.14 g, and HI up to 3.72% with TAM 113 alleles. One major and consistent QTL on chromosome 2D at 34.4 Mbp overlapped with the major photoperiod gene Ppd-D1 and was affected by multiple traits, including kernel diameter (DIAM), TKW, kernel hardness index (KHI), heading date (HD), and plant height (PH). Another QTL cluster region on 7D between 52 and 66 Mbp, encompassing one consistent and three pleiotropic QTLs. One of the pleiotropic QTLs at 52 Mbp increased YLD up to 24.16 g m−2, HI up to 1%, and DIAM up to 0.03 mm. This study dissected genetic loci associated with yield and yield-related traits, providing valuable information on wheat improvement using marker-assisted selection (MAS).

Inheritance and Quantitative Trait Loci Mapping of Aromatic Compounds from Clementine (Citrus × clementina Hort. ex Tan.) and Sweet Orange (C. × sinensis (L.) Osb.) Fruit Essential Oils.

Despite their importance in food processing, perfumery and cosmetics, the inheritance of sweet orange aromatic compounds, as well as their yield in the fruit peel, has been little analyzed. In the present study, the segregation of aromatic compounds was studied in an F1 population of 77 hybrids resulting from crosses between clementine and blood sweet orange. Fruit-peel essential oils (PEOs) extracted by hydrodistillation were analyzed by gas chromatography coupled with flame ionization detection. Genotyping by sequencing was performed on the parents and the hybrids. The resulting "clementine × sweet blood orange" genetic map consists of 710 SNP markers distributed in nine linkage groups (LGs), representing the nine citrus chromosomes, and spanning 1054 centimorgans. Twenty quantitative trait loci (QTLs) were identified, explaining between 20.5 and 55.0% of the variance of the major aromatic compounds and PEO yield. The QTLs for monoterpenes and aliphatic aldehydes predominantly colocalized on LGs 5 and 8, as did the two QTLs for PEO yield. The sesquiterpene QTLs were located on LGs 1, 3, 6 and 8. The detection of major QTLs associated with the synthesis of aliphatic aldehydes, known for their strong aromatic properties, open the way for marker-assisted selection.

A physical map of traits of agronomic importance based on potato and tomato genome sequences.

Potato, tomato, pepper, and eggplant are worldwide important crop and vegetable species of the Solanaceae family. Molecular linkage maps of these plants have been constructed and used to map qualitative and quantitative traits of agronomic importance. This research has been undertaken with the vision to identify the molecular basis of agronomic characters on the one hand, and on the other hand, to assist the selection of improved varieties in breeding programs by providing DNA-based markers that are diagnostic for specific agronomic characters. Since 2011, whole genome sequences of tomato and potato became available in public databases. They were used to combine the results of several hundred mapping and map-based cloning studies of phenotypic characters between 1988 and 2022 in physical maps of the twelve tomato and potato chromosomes. The traits evaluated were qualitative and quantitative resistance to pathogenic oomycetes, fungi, bacteria, viruses, nematodes, and insects. Furthermore, quantitative trait loci for yield and sugar content of tomato fruits and potato tubers and maturity or earliness were physically mapped. Cloned genes for pathogen resistance, a few genes underlying quantitative trait loci for yield, sugar content, and maturity, and several hundred candidate genes for these traits were included in the physical maps. The comparison between the physical chromosome maps revealed, in addition to known intrachromosomal inversions, several additional inversions and translocations between the otherwise highly collinear tomato and potato genomes. The integration of the positional information from independent mapping studies revealed the colocalization of qualitative and quantitative loci for resistance to different types of pathogens, called resistance hotspots, suggesting a similar molecular basis. Synteny between potato and tomato with respect to genomic positions of quantitative trait loci was frequently observed, indicating eventual similarity between the underlying genes.

Genetic linkage mapping and QTL identification for salinity tolerance in Indian mustard (Brassica juncea L. Czern and Coss.) using SSR markers

Soil salinity is one of the major environmental constraints that limits crop yield and nearly 7% of the total area worldwide is affected by salinity. Salinity-induced oxidative stress causes membrane damage during germination and seedling growth. Indian mustard is a major oilseed crop in India and its production and productivity are severely affected by salt stress. Breeding Brassica cultivars for salinity tolerance by conventional means is very difficult and time-consuming. Therefore, understanding the molecular components associated with salt tolerance is needed to facilitate breeding for salt tolerance in Brassica. In this investigation, quantitative trait loci (QTLs) associated with salt tolerance were identified using F2:3 mapping population developed from a cross between CS52 (salinity tolerant) and RH30 (salinity sensitive). Parents and F2:3 were evaluated under controlled and salinity stress conditions for 14 morpho-physiological traits for two consecutive generations (F2 and F2:3), explaining proportion of the phenotypic variance under control condition. Simple sequence repeat (SSR) markers were used for mapping studies. A genetic linkage map based on 42 simple sequence repeats (SSRs) markers was constructed covering 2298.5 ​cM (Haldane) to identify the loci associated with salt tolerance in Brassica juncea. Forty-one SSRs showing polymorphism in the parents (CS52 and RH30) were mapped on 8 linkage groups (C1–C8). One marker (nga 129) did not map to any of the linkage group and was excluded from mapping. Linkage group 5 (C5; 317.9 ​cM) was longest and linkage group 1 (C1, 255.0 ​cM) was shortest. Further, we identified 15 QTLs controlling 8 traits using F2:3 population. These QTLs explained 12.44–60.63% of the phenotypic variation with a LOD score range of 3.62–5.97. Out of these QTLs, QMI4.1 related to membrane injury showed 51.28% phenotypic variance with a LOD score of 3.34. QTL QBYP8.1 related to biological yield per plant showed 60.63% phenotypic variance at a LOD score of 3.62. The highest LOD score of 5.97 was recorded for QTL related to seed yield per plant (QSYP4.1). Major QTLs were QTL for biological yield per plant (QBYP8.1), QTL for siliquae per plant (QSP4.1), QTL for primary branches (QPB4.1), QTLs for seed per siliqua (QSS4.1, QSS4.2), QTL for seed yield per plant (QSYP4.1), and QTL for membrane injury (QMI8.1) which showed more than 50% phenotypic variance. These QTLs identified in our study need to be confirmed in other populations as well so that these can be used in marker-assisted selection and breeding to enhance salt tolerance in Brassica juncea.

Mapping of QTLs for morphophysiological and yield traits under water-deficit stress and well-watered conditions in maize.

Maize productivity is significantly impacted by drought; therefore, improvement of drought tolerance is a critical goal in maize breeding. To achieve this, a better understanding of the genetic basis of drought tolerance is necessary. Our study aimed to identify genomic regions associated with drought tolerance-related traits by phenotyping a mapping population of recombinant inbred lines (RILs) for two seasons under well-watered (WW) and water-deficit (WD) conditions. We also used single nucleotide polymorphism (SNP) genotyping through genotyping-by-sequencing to map these regions and attempted to identify candidate genes responsible for the observed phenotypic variation. Phenotyping of the RILs population revealed significant variability in most of the traits, with normal frequency distributions, indicating their polygenic nature. We generated a linkage map using 1,241 polymorphic SNPs distributed over 10 chromosomes (chrs), covering a total genetic distance of 5,471.55cM. We identified 27 quantitative trait loci (QTLs) associated with various morphophysiological and yield-related traits, with 13 QTLs identified under WW conditions and 12 under WD conditions. We found one common major QTL (qCW2-1) for cob weight and a minor QTL (qCH1-1) for cob height that were consistently identified under both water regimes. We also detected one major and one minor QTL for the Normalized Difference Vegetation Index (NDVI) trait under WD conditions on chr 2, bin 2.10. Furthermore, we identified one major QTL (qCH1-2) and one minor QTL (qCH1-1) on chr 1 that were located at different genomic positions to those identified in earlier studies. We found co-localized QTLs for stomatal conductance and grain yield on chr 6 (qgs6-2 and qGY6-1), while co-localized QTLs for stomatal conductance and transpiration rate were identified on chr 7 (qgs7-1 and qTR7-1). We also attempted to identify the candidate genes responsible for the observed phenotypic variation; our analysis revealed that the major candidate genes associated with QTLs detected under water deficit conditions were related to growth and development, senescence, abscisic acid (ABA) signaling, signal transduction, and transporter activity in stress tolerance. The QTL regions identified in this study may be useful in designing markers that can be utilized in marker-assisted selection breeding. In addition, the putative candidate genes can be isolated and functionally characterized so that their role in imparting drought tolerance can be more fully understood.

Mapping quantitative trait loci for biomass yield and yield-related traits in lowland switchgrass (Panicum virgatum L.) multiple populations.

Switchgrass can be used as an alternative source for bioenergy production. Many breeding programs focus on the genetic improvement of switchgrass for increasing biomass yield. Quantitative trait loci (QTL) mapping can help to discover marker-trait associations and accelerate the breeding process through marker-assisted selection. To identify significant QTL, this study mapped seven hybrid populations and one combined of two hybrid populations (30 to 96 F1s) derived from Alamo and Kanlow genotypes. The populations were evaluated for biomass yield, plant height, and crown size in a simulated-sward plot with two replications at two locations in Tennessee from 2019 to 2021. The populations showed significant genetic variation for the evaluated traits and exhibited transgressive segregation. The 17,251 single nucleotide polymorphisms (SNPs) generated through genotyping-by-sequencing (GBS) were used to construct a linkage map using a fast algorithm for multiple outbred families. The linkage map spanned 1,941 cM with an average interval of 0.11 cM between SNPs. The QTL analysis was performed on evaluated traits for each and across environments (year and location) that identified five QTL for biomass yield (Logarithm of the odds, LOD 3.12 to 4.34), four QTL for plant height (LOD 3.01 to 5.64), and seven QTL for crown size (LOD 3.0 to 4.46) (P ≤ 0.05). The major QTL for biomass yield, plant height, and crown size resided on chromosomes 8N, 6N, and 8 K explained phenotypic variations of 5.6, 5.1, and 6.6%, respectively. SNPs linked to QTL could be incorporated into marker-assisted breeding to maximize the selection gain in switchgrass breeding.

Quantitative Trait Loci for Genotype and Genotype by Environment Interaction Effects for Seed Yield Plasticity to Terminal Water-Deficit Conditions in Canola (Brassica napus L.)

Canola plants suffer severe crop yield and oil content reductions when exposed to water-deficit conditions, especially during the reproductive stages of plant development. There is a pressing need to develop canola cultivars that can perform better under increased water-deficit conditions with changing weather patterns. In this study, we analysed genetic determinants for the main effects of quantitative trait loci (QTL), (Q), and the interaction effects of QTL and Environment (QE) underlying seed yield and related traits utilising 223 doubled haploid (DH) lines of canola in well-watered and water-deficit conditions under a rainout shelter. Moderate water-deficit at the pre-flowering stage reduced the seed yield to 40.8%. Multi-environmental QTL analysis revealed 23 genomic regions associated with days to flower (DTF), plant height (PH) and seed yield (SY) under well-watered and water-deficit conditions. Three seed yield QTL for main effects were identified on chromosomes A09, C03, and C09, while two were related to QE interactions on A02 and C09. Two QTL regions were co-localised to similar genomic regions for flowering time and seed yield (A09) and the second for plant height and chlorophyll content. The A09 QTL was co-located with a previously mapped QTL for carbon isotope discrimination (Δ13C) that showed a positive relationship with seed yield in the same population. Opposite allelic effects for plasticity in seed yield were identified due to QE interactions in response to water stress on chromosomes A02 and C09. Our results showed that QTL's allelic effects for DTF, PH, and SY and their correlation with Δ13C are stable across environments (field conditions, previous study) and contrasting water regimes (this study). The QTL and DH lines that showed high yield under well-watered and water-deficit conditions could be used to manipulate water-use efficiency for breeding improved canola cultivars.

QTL for yield per plant under water deficit and well-watered conditions and drought susceptibility index in soybean (Glycine max (L.) Merr.)

Drought has historically represented the greatest abiotic stress to adversely affect the stability of soybean (Glycine max (L.) Merr.) yields in non-irrigated field conditions. To investigate the genetic basis underlying drought tolerance in soybean, we screened the seed yield per plant (YP) in a natural diversity panel of 149 accessions under both water deficit (drought-stressed; YP-S) and well-watered (full irrigation; YP-W) conditions in field and greenhouse trials and calculated a drought susceptibility index (DSI) based on the differences in yield between treatments within each accession. A total of 19 quantitative trait loci (QTLs) were identified: eight were significantly associated with YP-W, 10 were associated with YP-S, 2 were associated with DSI and one QTL was associated with both YP-S and DSI. We then compared QTLs identified here with previously reported markers and found that these loci were located in regions associated with yield-related and other agronomic traits. In particular, YP-S-associated single nucleotide polymorphism (SNP) ss246509299 in chromosome (Chr.) 8, and YP-W-associated ss249310678 on Chr. 17 were both previously correlated with canopy wilt. Eight significant QTLs were located within eight genes. Glyma.18g092200, contained ss249600231 and annotated as GmWRKY168, is reportedly responsive to cadmium. This study helps to resolve which loci contribute to yield under drought stress in soybean, and can potentially serve as markers for selection of elite, high-yield and drought tolerant varieties.

Genome-wide association analysis identified consistent QTL for seed yield in a soybean diversity panel tested across multiple environments.

Improving seed yield is one of the main targets of soybean [Glycine max (L.) Merr.] breeding. Identification of loci that influence productivity and understanding their genetic mechanism will help marker-assisted trait introgression. The present study evaluated a diverse panel of 541 soybean genotypes consisting of three maturity groups (MGs III-V) in four environments in Kansas, U.S. Data on seed yield, seed weight, shattering resistance, days to maturity, and plant height showed significant genotype, environmental, and genotype × environment interaction variations. Seed yield and shattering had moderate broad-sense heritability (<85%), while the rest of the traits showed high broad-sense heritability (>90%). The SoySNP50K iSelect BeadChip dataset was used to identify significantly associated loci via genome-wide association studies (GWAS). A total of 19 single-nucleotide polymorphisms (SNPs) were significantly associated with seed yield. Particularly, two stable seed yield quantitative trait loci (QTL) on chromosomes 9 and 17 were consistently detected in at least three out of four environments. Candidate gene analysis surrounding seed yield QTL on chromosome 9 showed that Glyma.09G048900, an oxygen binding protein, was the closest to the QTL peak. Similarly, Glyma.17G090200 and Glyma.17G090400 were within 20-kb region of the seed yield QTL on chromosome 17. The candidate genes warrant further analysis to determine their functional mechanisms and develop markers for seed yield improvement.

Genome-wide analysis of CNVs in three populations of Tibetan sheep using whole-genome resequencing.

Copy number variation (CNV), an important source of genomic structural variation, can disturb genetic structure, dosage, regulation and expression, and is associated with phenotypic diversity and adaptation to local environments in mammals. In the present study, 24 resequencing datasets were used to characterize CNVs in three ecotypic populations of Tibetan sheep and assess CNVs related to domestication and adaptation in Qinghai-Tibetan Plateau. A total of 87,832 CNV events accounting for 0.3% of the sheep genome were detected. After merging the overlapping CNVs, 2777 CNV regions (CNVRs) were obtained, among which 1098 CNVRs were shared by the three populations. The average length of these CNVRs was more than 3 kb, and duplication events were more frequent than deletions. Functional analysis showed that the shared CNVRs were significantly enriched in 56 GO terms and 18 KEGG pathways that were mainly concerned with ABC transporters, olfactory transduction and oxygen transport. Moreover, 188 CNVRs overlapped with 97 quantitative trait loci (QTLs), such as growth and carcass QTLs, immunoglobulin QTLs, milk yield QTLs and fecal egg counts QTLs. PCDH15, APP and GRID2 overlapped with body weight QTLs. Furthermore, Vst analysis showed that RUNX1, LOC101104348, LOC105604082 and PAG11 were highly divergent between Highland-type Tibetan Sheep (HTS) and Valley-type Tibetan sheep (VTS), and RUNX1 and LOC101111988 were significantly differentiated between VTS and Oura-type Tibetan sheep (OTS). The duplication of RUNX1 may facilitate the hypoxia adaptation of OTS and HTS in Qinghai-Tibetan Plateau, which deserves further research in detail. In conclusion, for the first time, we represented the genome-wide distribution characteristics of CNVs in Tibetan sheep by resequencing, and provided a valuable genetic variation resource, which will facilitate the elucidation of the genetic basis underlying the distinct phenotypic traits and local adaptation of Tibetan sheep.

Mapping and identification of QTL in 5601T × U99-310255 RIL population using SNP genotyping: soybean seed quality traits.

Molecular markers have played and will continue to play a major role in the genetic characterization and improvement of soybeans. They have helped identify major loci for tolerance to abiotic stressors, disease resistance, herbicide resistance, soybean seed quality traits, and yield. However, most yield quantitative trait loci (QTL) are specific to a certain population, and the genetic variation found in the specific bi-parental population is not always shared in other populations. A major objective in soybean breeding is to develop high yielding cultivars. Unfortunately, soybean seed yield, as well as protein and oil content, are complex quantitative traits to characterize from the phenotypic and genotypic perspectives. The objectives of this study are to detect soybean genomic regions that increase protein content, while maintaining oil content and seed yield and to successfully identify soybean QTL associated with these seed quality traits. To achieve these objectives, data from the 138 recombinant inbred lines grown in six environments were used to perform QTL detection analyses in search of significant genomic regions affecting soybean seed protein, oil, and yield. A total of 21 QTL were successfully identified for yield, protein, oil, methionine, threonine, lodging, maturity, and meal. Knowledge of their locations and flanking markers will aid in marker assisted selection for plant breeders. This will lead to a more valuable soybean for farmers, processors, and animal nutritionists.

Mapping QTLs for spring green-up, plant vigor, and plant biomass in two lowland switchgrass populations.

The online version contains supplementary material available at 10.1007/s11032-022-01296-7.

Identification and Validation of Quantitative Trait Loci for Wheat Dwarf Virus Resistance in Wheat (Triticum spp.).

Wheat dwarf virus (WDV) is transmitted by the leafhopper Psammotettix alienus. As a major pathogen in wheat and other cereals, WDV causes high yield losses in many European countries. Due to climate change, insect-transmitted viruses will become more important and the restrictions in the use of insecticides efficient against P. alienus renders growing of WDV resistant/tolerant varieties the only effective strategy to control WDV. So far, there is little information about the possible sources of resistance and no known information about the genome regions responsible for the resistance. In a screening for WDV resistance using artificial inoculation in gauze houses, a panel of 500 wheat accessions including cultivars, gene bank accessions, and wild relatives of wheat was phenotyped for virus titer, infection rate, as well as plant height and yield parameters relative to healthy controls of the same genotype. Additionally, 85 T. aestivum-Ae. tauschii intogression lines were tested for WDV resistance in the greenhouse. A subset of 250 hexaploid wheat accessions was genotyped with the 15k iSelect SNP Chip. By genome-wide association study (GWAS), the quantitative trait loci (QTL) for partial WDV resistance were identified. Within these studies, one cultivar was identified showing an average infection rate of only 5.7%. By analyzing single seed descent (SSD) and doubled haploid (DH) populations comprising 153 and 314 individuals for WDV resistance and by genotyping these with the 25k iSelect SNP Chip, QTL for yield per plant, thousand-grain weight, and relative virus titer were validated on chromosomes 1B, 2B, 3B, 4B, 4A, 5A, 6A, and 7A. These results will be the basis for marker-assisted selection for WDV resistance to replacing the laborious, time-consuming, and technically challenging phenotyping with WDV bearing leafhoppers.

Genotyping by sequencing-based linkage map construction and identification of quantitative trait loci for yield-related traits and oil content in Jatropha (Jatropha curcas L.).

Jatropha (Jatropha curcas L.) has been considered as a potential bioenergy crop and its genetic improvement is essential for higher seed yield and oil content which has been hampered due to lack of desirable molecular markers. An F2 population was created using an intraspecific cross involving a Central American line RJCA9 and an Asiatic species RJCS-9 to develop a dense genetic map and for Quantitative trait loci (QTL) identification. The genotyping-by-sequencing (GBS) approach was used to genotype the mapping population of 136 F2 individuals along with the two parental lines for classification of the genotypes based on single nucleotide polymorphism (SNPs). NextSeq 2500 sequencing technology provided a total of 517.23million clean reads, with an average of ~ 3.8million reads per sample. We analysed 411 SNP markers and developed 11 linkage groups. The total length of the genetic map was 4092.3cM with an average marker interval of 10.04cM. We have identified a total of 83 QTLs for various yield and oil content governing traits. The percentage of phenotypic variation (PV) was found to be in the range of 8.81 to 65.31%, and a QTL showed the maximum PV of 65.3% for a total seed number on the 6th linkage group (LG). The QTLs detected in this study for various phenotypic traits will lay down the path for marker-assisted breeding in the future and cloning of genes that are responsible for phenotypic variation.

Genetic Architecture of Grain Yield-Related Traits in Sorghum and Maize.

Grain size, grain number per panicle, and grain weight are crucial determinants of yield-related traits in cereals. Understanding the genetic basis of grain yield-related traits has been the main research object and nodal in crop science. Sorghum and maize, as very close C4 crops with high photosynthetic rates, stress tolerance and large biomass characteristics, are extensively used to produce food, feed, and biofuels worldwide. In this review, we comprehensively summarize a large number of quantitative trait loci (QTLs) associated with grain yield in sorghum and maize. We placed great emphasis on discussing 22 fine-mapped QTLs and 30 functionally characterized genes, which greatly hinders our deep understanding at the molecular mechanism level. This review provides a general overview of the comprehensive findings on grain yield QTLs and discusses the emerging trend in molecular marker-assisted breeding with these QTLs.

Analysis of Genetic Diversity and Survey of QTLs for Grain Yield under Drought Stress in Drought Tolerant Rice Landraces Using DTY QTL-linked Markers

Genetic diversity in a set of 60 rice genotypes were analyzed using 27 random and 13 grain yield under drought (DTY) quantitative trait loci (QTLs)-linked simple sequence repeats (SSR) markers. The average gene diversity polymorphism information content were 0.53 and 0.46, respectively. The presence of DTY QTLs for grain yield under drought stress was predicted using peak marker in comparison to the positive checks. The DTY QTL qDTY12.1, amplified by the peak marker RM 28048, was found in 43.3% of genotypes, and qDTY2.2 was detected in only 6.67 % of genotypes using peak marker RM279. Two germplasm accessions, IC389895 and DT 2, possessed maximum number of DTY QTLs and absent is IC525099. Phylogenetic analysis revealed four distinct clusters within the germplasm. Overall, the evaluated genotypes presented a rich source of diversity and contain valuable DTY QTLs which can be utilized in rice genetic enhancement program for drought tolerance.

Detection of drought tolerance-related QTL in the Plainsman V./Cappelle Desprez doubled haploid wheat population

Drought stress is one of the major abiotic factors that significantly reduces wheat grain yield. Improving drought tolerance is a challenge that plant breeders are facing nowadays. In this study, our goal was to identify quantitative trait loci (QTL) in the Plainsman V./Cappelle Desprez doubled haploid (DH) population under drought induced as decreased irrigation (ds) and well-watered (ww) conditions in glasshouse. In total, 54 QTL were detected across the three years in two water regimes linked to 10 drought tolerance-related agronomic traits. Out of the detected QTL regions several have been previously reported. The QTL on chromosome 1A (wPt-744613-wPt-8016) related to thousand grain weight was detected in both ds and ww conditions, explaining the 12.7–17.4% of the phenotypic variance. QTL for grain yield was detected on chromosomes 1A, and 6B in the ds treatment. Numerous QTL was identified under both irrigation levels.

Genome-wide QTL mapping of yield and agronomic traits in two widely adapted winter wheat cultivars from multiple mega-environments.

Quantitative trait loci (QTL) analysis could help to identify suitable molecular markers for marker-assisted breeding (MAB). A mapping population of 124 F5:7recombinant inbred lines derived from the cross ‘TAM 112’/‘TAM 111’ was grown under 28 diverse environments and evaluated for grain yield, test weight, heading date, and plant height. The objective of this study was to detect QTL conferring grain yield and agronomic traits from multiple mega-environments. Through a linkage map with 5,948 single nucleotide polymorphisms (SNPs), 51 QTL were consistently identified in two or more environments or analyses. Ten QTL linked to two or more traits were also identified on chromosomes 1A, 1D, 4B, 4D, 6A, 7B, and 7D. Those QTL explained up to 13.3% of additive phenotypic variations with the additive logarithm of odds (LOD(A)) scores up to 11.2. The additive effect increased yield up to 8.16 and 6.57 g m−2 and increased test weight by 2.14 and 3.47 kg m−3 with favorable alleles from TAM 111 and TAM 112, respectively. Seven major QTL for yield and six for TW with one in common were of our interest on MAB as they explained 5% or more phenotypic variations through additive effects. This study confirmed previously identified loci and identified new QTL and the favorable alleles for improving grain yield and agronomic traits.