QTL mapping for the flag leaf-related traits using RILs derived from Trititrigia germplasm line SN304 and wheat cultivar Yannong15 in multiple environments

BACKGROUND

Developing and enriching genetic resources plays important role in the crop improvement. The flag leaf affects plant architecture and contributes to the grain yield of wheat (Triticum aestivum L.). The genetic improvement of flag leaf traits faces problems such as a limited genetic basis. Among the various genetic resources of wheat, Thinopyrum intermedium has been utilized as a valuable resource in genetic improvement due to its disease resistance, large spikes, large leaves, and multiple flowers. In this study, a recombinant inbred line (RIL) population was derived from common wheat Yannong15 and wheat-Th. intermedium introgression line SN304 was used to identify the quantitative trait loci (QTL) for flag leaf-related traits.

RESULTS

QTL mapping was performed for flag leaf length (FLL), flag leaf width (FLW) and flag leaf area (FLA). A total of 77 QTLs were detected, and among these, 51 QTLs with positive alleles were contributed by SN304. Fourteen major QTLs for flag leaf traits were detected on chromosomes 2B, 3B, 4B, and 2D. Additionally, 28 QTLs and 8 QTLs for flag leaf-related traits were detected in low-phosphorus and drought environments, respectively. Based on major QTLs of positive alleles from SN304, we identified a pair of double-ended anchor primers mapped on chromosome 2B and amplified a specific band of Th. intermedium in SN304. Moreover, there was a major colocated QTL on chromosome 2B, called QFll/Flw/Fla-2B, which was delimited to a physical interval of approximately 2.9 Mb and contained 20 candidate genes. Through gene sequence and expression analysis, four candidate genes associated with flag leaf formation and growth in the QTL interval were identified.

CONCLUSION

These results promote the fine mapping of QFll/Flw/Fla-2B, which have pleiotropic effects, and will facilitate the identification of candidate genes for flag leaf-related traits. Additionally, this work provides a theoretical basis for the application of Th. intermedium in wheat breeding.

PySmooth: a Python tool for the removal and correction of genotyping errors

In genetic mapping studies involving many individuals, genome-wide markers such as single nucleotide polymorphisms (SNPs) can be detected using different methods. However, it comes with some errors. Some SNPs associated with diseases can be in regions encoding long noncoding RNAs (lncRNAs). Therefore, identifying the errors in genotype file and correcting them is crucial for accurate genetic mapping studies. We develop a Python tool called PySmooth, that offers an easy-to-use command line interface for the removal and correction of genotyping errors. PySmooth uses the approach of a previous tool called SMOOTH with some modifications. It inputs a genotype file, detects errors and corrects them. PySmooth provides additional features such as imputing missing data, better user-friendly usage, generates summary and visualization files, has flexible parameters, and handles more genotype codes. AVAILABILITY AND IMPLEMENTATION: PySmooth is available at https://github.com/lncRNAAddict/PySmooth .

Recent advances in plant translational genomics for crop improvement

The growing population, climate change, and limited agricultural resources put enormous pressure on agricultural systems. A plateau in crop yields is occurring and extreme weather events and urbanization threaten the livelihood of farmers. It is imperative that immediate attention is paid to addressing the increasing food demand, ensuring resilience against emerging threats, and meeting the demand for more nutritious, safer food. Under uncertain conditions, it is essential to expand genetic diversity and discover novel crop varieties or variations to develop higher and more stable yields. Genomics plays a significant role in developing abundant and nutrient-dense food crops. An alternative to traditional breeding approach, translational genomics is able to improve breeding programs in a more efficient and precise manner by translating genomic concepts into practical tools. Crop breeding based on genomics offers potential solutions to overcome the limitations of conventional breeding methods, including improved crop varieties that provide more nutritional value and are protected from biotic and abiotic stresses. Genetic markers, such as SNPs and ESTs, contribute to the discovery of QTLs controlling agronomic traits and stress tolerance. In order to meet the growing demand for food, there is a need to incorporate QTLs into breeding programs using marker-assisted selection/breeding and transgenic technologies. This chapter primarily focuses on the recent advances that are made in translational genomics for crop improvement and various omics techniques including transcriptomics, metagenomics, pangenomics, single cell omics etc. Numerous genome editing techniques including CRISPR Cas technology and their applications in crop improvement had been discussed.

Genome-Wide Association Analysis Unravels New Quantitative Trait Loci (QTLs) for Eight Lodging Resistance Constituent Traits in Rice (Oryza sativa L.)

Lodging poses a significant challenge to rice yield, prompting the need to identify elite alleles for lodging resistance traits to improve cultivated rice varieties. In this study, a natural population of 518 rice accessions was examined to identify elite alleles associated with plant height (PH), stem diameter (SD), stem anti-thrust (AT/S), and various internode lengths (first (FirINL), second (SecINL), third (ThirINL), fourth (ForINL), and fifth (FifINL) internode lengths). A total of 262 SSR markers linked to these traits were uncovered through association mapping in two environmental conditions. Phenotypic evaluations revealed striking differences among cultivars, and genetic diversity assessments showed polymorphisms across the accessions. Favorable alleles were identified for PH, SD, AT/S, and one to five internode lengths, with specific alleles displaying considerable effects. Noteworthy alleles include RM6811-160 bp on chromosome 6 (which reduces PH) and RM161-145 bp on chromosome 5 (which increases SD). The study identified a total of 42 novel QTLs. Specifically, seven QTLs were identified for PH, four for SD, five for AT/S, five for FirINL, six for SecINL, five for ThirINL, six for ForINL, and four for FifINL. QTLs qAT/S-2, qPH2.1, qForINL2.1, and qFifINL exhibited the most significant phenotypic variance (PVE) of 3.99% for the stem lodging trait. AT/S, PH, ForINL, and FifINL had additive effects of 5.31 kPa, 5.42 cm, 4.27 cm, and 4.27 cm, respectively, offering insights into eight distinct cross-combinations for enhancing each trait. This research suggests the potential for crossbreeding superior parents based on stacked alleles, promising improved rice cultivars with enhanced lodging resistance to meet market demands.

Genetic Dissection of Panicle Morphology Traits in Super High-Yield Hybrid Rice Chaoyou 1000

The morphological characteristics of the rice panicle play a pivotal role in influencing yield. In our research, we employed F2 and F2:3 populations derived from the high-yielding hybrid rice variety Chaoyou 1000. We screened 123 pairs of molecular markers, which were available, to construct the genetic linkage map. Subsequently, we assessed the panicle morphology traits of F2 populations in Lingshui County, Hainan Province, in 2017, and F2:3 populations in Hangzhou City, Zhejiang Province, in 2018. These two locations represent two types of ecology. Hangzhou's climate is characterized by high temperatures and humidity, while Lingshui's climate is characterized by a tropical monsoon climate. In total, 33 QTLs were identified, with eight of these being newly discovered, and two of them were consistently detected in two distinct environments. We identified fourteen QTL-by-environment interactions (QEs), which collectively explained 4.93% to 59.95% of the phenotypic variation. While most of the detected QTLs are consistent with the results of previous tests, the novel-detected QTLs will lay the foundation for rice yield increase and molecular breeding.

Grain yield trade-offs in spike-branching wheat can be mitigated by elite alleles affecting sink capacity and post-anthesis source activity

Introducing variations in inflorescence architecture, such as the 'Miracle-Wheat' (Triticum turgidum convar. compositum (L.f.) Filat.) with a branching spike, has relevance for enhancing wheat grain yield. However, in the spike-branching genotypes, the increase in spikelet number is generally not translated into grain yield advantage because of reduced grains per spikelet and grain weight. Here, we investigated if such trade-offs might be a function of source-sink strength by using 385 recombinant inbred lines developed by intercrossing the spike-branching landrace TRI 984 and CIRNO C2008, an elite durum (T. durum L.) cultivar; they were genotyped using the 25K array. Various plant and spike architectural traits, including flag leaf, peduncle, and spike senescence rate, were phenotyped under field conditions for 2 consecutive years. On chromosome 5AL, we found a new modifier QTL for spike branching, branched headt3 (bht-A3), which was epistatic to the previously known bht-A1 locus. Besides, bht-A3 was associated with more grains per spikelet and a delay in flag leaf senescence rate. Importantly, favourable alleles, viz. bht-A3 and grain protein content (gpc-B1) that delayed senescence, are required to improve grain number and grain weight in the spike-branching genotypes. In summary, achieving a balanced source-sink relationship might minimize grain yield trade-offs in Miracle-Wheat.

An exploratory data analysis on genetic architecture in Bos taurus through miRNAs within QTLs and their target genes

Understanding the genetic architecture is important because it allows us to understand the relationship between molecular markers, like miRNAs, QTLs and SNPs, and traits of interest such as milk yield, lipidic content in milk, heat tolerance etc. In the present study we performed an exploratory analysis that found an association of 480 miRNAs within QTLs related to 155 traits. We also discovered that those 480 miRNAs might modulate the expression of 12.374 genes. The most predominant traits available in the data were milk related, such as milk yield and fatty acids content in milk. Besides, the functional enrichment analysis revealed that some of those genes were linked to sensory perception, olfactory perception, perception of stimulus and chemical stimulus, localization, establishment of localization, transport etc. Furthermore, the discovery of miRNAs within QTLs and their target analysis suggests that they might be associated with characteristics of interest. By analyzing these relationships, we strongly encourage that future QTL studies should include miRNAs analysis. Altogether, our analysis enabled us to explore the association between multiple complex traits, miRNAs within QTLs and their target genes in Bos taurus that might have implications in breeding programs.

Identification of Multiple Genetic Loci Related to Low-Temperature Tolerance during Germination in Maize (Zea maize L.) through a Genome-Wide Association Study

Low-temperature stress during the germination stage is an important abiotic stress that affects the growth and development of northern spring maize and seriously restricts maize yield and quality. Although some quantitative trait locis (QTLs) related to low-temperature tolerance in maize have been detected, only a few can be commonly detected, and the QTL intervals are large, indicating that low-temperature tolerance is a complex trait that requires more in-depth research. In this study, 296 excellent inbred lines from domestic and foreign origins (America and Europe) were used as the study materials, and a low-coverage resequencing method was employed for genome sequencing. Five phenotypic traits related to low-temperature tolerance were used to assess the genetic diversity of maize through a genome-wide association study (GWAS). A total of 14 SNPs significantly associated with low-temperature tolerance were detected (-log10(P) > 4), and an SNP consistently linked to low-temperature tolerance in the field and indoors during germination was utilized as a marker. This SNP, 14,070, was located on chromosome 5 at position 2,205,723, which explained 4.84-9.68% of the phenotypic variation. The aim of this study was to enrich the genetic theory of low-temperature tolerance in maize and provide support for the innovation of low-temperature tolerance resources and the breeding of new varieties.

QTLs and Candidate Loci Associated with Drought Tolerance Traits of Kaybonnet x ZHE733 Recombinant Inbred Lines Rice Population

Rice is the most important staple crop for the sustenance of the world's population, and drought is a major factor limiting rice production. Quantitative trait locus (QTL) analysis of drought-resistance-related traits was conducted on a recombinant inbred line (RIL) population derived from the self-fed progeny of a cross between the drought-resistant tropical japonica U.S. adapted cultivar Kaybonnet and the drought-sensitive indica cultivar ZHE733. K/Z RIL population of 198 lines was screened in the field at Fayetteville (AR) for three consecutive years under controlled drought stress (DS) and well-watered (WW) treatment during the reproductive stage. The effects of DS were quantified by measuring morphological traits, grain yield components, and root architectural traits. A QTL analysis using a set of 4133 single nucleotide polymorphism (SNP) markers and the QTL IciMapping identified 41 QTLs and 184 candidate genes for drought-related traits within the DR-QTL regions. RT-qPCR in parental lines was used to confirm the putative candidate genes. The comparison between the drought-resistant parent (Kaybonnet) and the drought-sensitive parent (ZHE733) under DS conditions revealed that the gene expression of 15 candidate DR genes with known annotations and two candidate DR genes with unknown annotations within the DR-QTL regions was up-regulated in the drought-resistant parent (Kaybonnet). The outcomes of this research provide essential information that can be utilized in developing drought-resistant rice cultivars that have higher productivity when DS conditions are prevalent.

Haplotype analysis of QTLs governing early seedling vigor-related traits under dry-direct-seeded rice (Oryza sativa L.) conditions

BACKGROUND

The eventual shifting of cultivation method from puddle transplanted rice to direct-seeded rice (DSR) to save water prompted researchers to develop DSR-suitable varieties. To achieve this, identification of molecular markers associated with must-have traits for DSR, especially early seedling vigour related traits is crucial.

METHODS AND RESULTS

In the present investigation, the haplotype analysis using flanking markers of three important quantitative trait loci (QTLs) for early seedling vigour-related traits viz., qSV-6a (RM204 and RM402) for root length; qVI (RM20429 and RM3) for seedling vigour index; qGP-6 (RM528 and RM400) for germination percentage revealed that the marker alleles were found to show significant associations with qVI and qGP-6 QTLs. The majority of genotypes with high early seedling vigour are with qVIHap-1 (220 and 160 bp) and qGPHap-1 (290 and 290 bp). The rice genotypes with superior haplotypes for early seedling vigour are BMF536, BMF540, BMF525, MM129 and MDP2.

CONCLUSIONS

In conclusion, here we demonstrated that the markers RM20429 and RM3 are associated with seedling vigour index whereas RM528 and RM400 are associated with germination percentage. Therefore, these markers can be utilized to develop varieties suitable for DSR conditions through haplotype-based breeding. In addition, the rice genotypes with superior haplotypes can be of immense value to use as donors or can be released as varieties also under DSR conditions.

Genetic and molecular understanding for the development of methionine-rich maize: a holistic approach

Maize (Zea mays) is the most important coarse cereal utilized as a major energy source for animal feed and humans. However, maize grains are deficient in methionine, an essential amino acid required for proper growth and development. Synthetic methionine has been used in animal feed, which is costlier and leads to adverse health effects on end-users. Bio-fortification of maize for methionine is, therefore, the most sustainable and environmental friendly approach. The zein proteins are responsible for methionine deposition in the form of δ-zein, which are major seed storage proteins of maize kernel. The present review summarizes various aspects of methionine including its importance and requirement for different subjects, its role in animal growth and performance, regulation of methionine content in maize and its utilization in human food. This review gives insight into improvement strategies including the selection of natural high-methionine mutants, molecular modulation of maize seed storage proteins and target key enzymes for sulphur metabolism and its flux towards the methionine synthesis, expression of synthetic genes, modifying gene codon and promoters employing genetic engineering approaches to enhance its expression. The compiled information on methionine and essential amino acids linked Quantitative Trait Loci in maize and orthologs cereals will give insight into the hotspot-linked genomic regions across the diverse range of maize germplasm through meta-QTL studies. The detailed information about candidate genes will provide the opportunity to target specific regions for gene editing to enhance methionine content in maize. Overall, this review will be helpful for researchers to design appropriate strategies to develop high-methionine maize.

Multivariate analysis and genetic dissection of staygreen and stem reserve mobilisation under combined drought and heat stress in wheat (Triticum aestivum L.)

Introduction: Abiotic stresses significantly reduce crop yield by adversely affecting many physio-biochemical processes. Several physiological traits have been targeted and improved for yield enhancement in limiting environmental conditions. Amongst them, staygreen and stem reserve mobilisation are two important mutually exclusive traits contributing to grain filling under drought and heat stress in wheat. Henceforth, the present study was carried out to identify the QTLs governing these traits and to identify the superiors' lines through multi-trait genotype-ideotype distance index (MGIDI) Methods: A mapping population consisting of 166 recombinant inbred lines (RILs) developed from a cross between HD3086 and HI1500 was utilized in this study. The experiment was laid down in alpha lattice design in four environmental conditions viz. Control, drought, heat and combined stress (heat and drought). Genotyping of parents and RILs was carried out with 35 K Axiom® array (Wheat breeder array). Results and Discussion: Medium to high heritability with a moderate to high correlation between traits was observed. Principal component analysis (PCA) was performed to derive latent variables in the original set of traits and the relationship of these traits with latent variables.From this study, 14 QTLs were identified, out of which 11, 2, and 1 for soil plant analysis development (SPAD) value, leaf senescence rate (LSR), and stem reserve mobilisation efficiency (SRE) respectively. Quantitative trait loci (QTLs) for SPAD value harbored various genes like Dirigent protein 6-like, Protein FATTY ACID EXPORT 3, glucan synthase-3 and Ubiquitin carboxyl-terminal hydrolase, whereas QTLs for LSR were found to contain various genes like aspartyl protease family protein, potassium transporter, inositol-tetrakisphosphate 1-kinase, and DNA polymerase epsilon subunit D-like. Furthermore, the chromosomal region for SRE was found to be associated with serine-threonine protein kinase. Serine-threonine protein kinases are involved in many signaling networks such as ABA mediated ROS signaling and acclimation to environmental stimuli. After the validation of QTLs in multilocation trials, these QTLs can be used for marker-assisted selection (MAS) in breeding programs.

Genetic control of mRNA splicing as a potential mechanism for incomplete penetrance of rare coding variants

Exonic variants present some of the strongest links between genotype and phenotype. However, these variants can have significant inter-individual pathogenicity differences, known as variable penetrance. In this study, we propose a model where genetically controlled mRNA splicing modulates the pathogenicity of exonic variants. By first cataloging exonic inclusion from RNA-sequencing data in GTEx V8, we find that pathogenic alleles are depleted on highly included exons. Using a large-scale phased whole genome sequencing data from the TOPMed consortium, we observe that this effect may be driven by common splice-regulatory genetic variants, and that natural selection acts on haplotype configurations that reduce the transcript inclusion of putatively pathogenic variants, especially when limiting to haploinsufficient genes. Finally, we test if this effect may be relevant for autism risk using families from the Simons Simplex Collection, but find that splicing of pathogenic alleles has a penetrance reducing effect here as well. Overall, our results indicate that common splice-regulatory variants may play a role in reducing the damaging effects of rare exonic variants.

Quantitative trait loci mapping of polyphenol metabolites from a 'Latham' x 'Glen Moy' red raspberry (Rubus idaeus L) cross

OBJECTIVE

The objective of this study was to investigate the genetic control of polyphenol accumulation in red raspberry (Rubus idaeus L).

METHODS

The levels of total anthocyanins and 37 individual polyphenol metabolites were measured over three years in a raspberry biparental mapping population. Quantitative trait loci (QTLs) for these traits were mapped onto a high-density SNP linkage map.

RESULTS

At least one QTL was detected for each trait, with good consistency among the years. On four linkage groups (LG), there were major QTLs affecting several metabolites. On LG1, a QTL had large effects on anthocyanins and flavonols containing a rutinoside or rhamnose group. On LG4, a QTL had large effects on several flavonols and on LG5 and LG6 QTLs had large effects on ellagic acid derivatives. Smaller QTLs were found on LG2 and LG3.

CONCLUSION

The identification of robust QTLs for key polyphenols in raspberry provides great potential for marker-assisted breeding for improved levels of potentially health beneficial components.

Metabolic-GWAS provides insights into genetic architecture of seed metabolome in buckwheat

BACKGROUND

Buckwheat (Fagopyrum spp.), belonging to the Polygonaceae family, is an ancient pseudo-cereal with high nutritional and nutraceutical properties. Buckwheat proteins are gluten-free and show balanced amino acid and micronutrient profiles, with higher content of health-promoting bioactive flavonoids that make it a golden crop of the future. Plant metabolome is increasingly gaining importance as a crucial component to understand the connection between plant physiology and environment and as a potential link between the genome and phenome. However, the genetic architecture governing the metabolome and thus, the phenome is not well understood. Here, we aim to obtain a deeper insight into the genetic architecture of seed metabolome in buckwheat by integrating high throughput metabolomics and genotyping-by-sequencing applying an array of bioinformatics tools for data analysis.

RESULTS

High throughput metabolomic analysis identified 24 metabolites in seed endosperm of 130 diverse buckwheat genotypes. The genotyping-by-sequencing (GBS) of these genotypes revealed 3,728,028 SNPs. The Genome Association and Prediction Integrated Tool (GAPIT) assisted in the identification of 27 SNPs/QTLs linked to 18 metabolites. Candidate genes were identified near 100 Kb of QTLs, providing insights into several metabolic and biosynthetic pathways.

CONCLUSIONS

We established the metabolome inventory of 130 germplasm lines of buckwheat, identified QTLs through marker trait association and positions of potential candidate genes. This will pave the way for future dissection of complex economic traits in buckwheat.

Marker-assisted selection for transfer of QTLs to a promising line for drought tolerance in wheat (Triticum aestivum L.)

Wheat crop is subjected to various biotic and abiotic stresses, which affect crop productivity and yield. Among various abiotic stresses, drought stress is a major problem considering the current global climate change scenario. A high-yielding wheat variety, HD3086, has been released for commercial cultivation under timely sown irrigated conditions for the North Western Plain Zone (NWPZ) and North Eastern Plain Zone NEPZ of India. Presently, HD3086 is one of the highest breeder seed indented wheat varieties and has a stable yield over the years. However, under moisture deficit conditions, its potential yield cannot be achieved. The present study was undertaken to transfer drought-tolerant QTLs in the background of the variety HD3086 using marker-assisted backcross breeding. QTLs governing Biomass (BIO), Canopy Temperature (CT), Thousand Kernel Weight (TKW), Normalized Difference Vegetation Index (NDVI), and Yield (YLD) were transferred to improve performance under moisture deficit conditions. In BC1F1, BC2F1, and BC2F2 generations, the foreground selection was carried out to identify the plants with positive QTLs conferring drought tolerance and linked to traits NDVI, CT, TKW, and yield. The positive homozygous lines for targeted QTLs were advanced from BC2F2 to BC2F4 via the pedigree-based phenotypic selection method. Background analysis was carried out in BC2F5 and obtained 78-91% recovery of the recurrent parent genome in the improved lines. Furthermore, the advanced lines were evaluated for 2 years under drought stress to assess improvement in MABB-derived lines. Increased GWPS, TKW, and NDVI and reduced CT was observed in improved lines. Seven improved lines were identified with significantly higher yields in comparison to HD3086 under stress conditions.

Genome-Wide Association Study of Xian Rice Grain Shape and Weight in Different Environments

Drought is one of the key environmental factors affecting the growth and yield potential of rice. Grain shape, on the other hand, is an important factor determining the appearance, quality, and yield of rice grains. Here, we re-sequenced 275 Xian accessions and then conducted a genome-wide association study (GWAS) on six agronomic traits with the 404,411 single nucleotide polymorphisms (SNPs) derived by the best linear unbiased prediction (BLUP) for each trait. Under two years of drought stress (DS) and normal water (NW) treatments, a total of 16 QTLs associated with rice grain shape and grain weight were detected on chromosomes 1, 2, 3, 4, 5, 7, 8, 11, and 12. In addition, these QTLs were analyzed by haplotype analysis and functional annotation, and one clone (GSN1) and five new candidate genes were identified in the candidate interval. The findings provide important genetic information for the molecular improvement of grain shape and weight in rice.

Joint QTL Mapping and Transcriptome Sequencing Analysis Reveal Candidate Seed-Shattering-Related Genes in Common Buckwheat

Common buckwheat (Fagopyrum esculentum M.) is an important traditional miscellaneous grain crop. However, seed-shattering is a significant problem in common buckwheat. To investigate the genetic architecture and genetic regulation of seed-shattering in common buckwheat, we constructed a genetic linkage map using the F₂ population of Gr (green-flower mutant and shattering resistance) and UD (white flower and susceptible to shattering), which included eight linkage groups with 174 loci, and detected seven QTLs of pedicel strength. RNA-seq analysis of pedicel in two parents revealed 214 differentially expressed genes DEGs that play roles in phenylpropanoid biosynthesis, vitamin B6 metabolism, and flavonoid biosynthesis. Weighted gene co-expression network analysis (WGCNA) was performed and screened out 19 core hub genes. Untargeted GC-MS analysis detected 138 different metabolites and conjoint analysis screened out 11 DEGs, which were significantly associated with differential metabolites. Furthermore, we identified 43 genes in the QTLs, of which six genes had high expression levels in the pedicel of common buckwheat. Finally, 21 candidate genes were screened out based on the above analysis and gene function. Our results provided additional knowledge for the identification and functions of causal candidate genes responsible for the variation in seed-shattering and would be an invaluable resource for the genetic dissection of common buckwheat resistance-shattering molecular breeding.

Genome-Wide Association Mapping for Yield and Yield-Related Traits in Rice (Oryza Sativa L.) Using SNPs Markers

Rice (Oryza sativa L.) is a staple food for more than 50% of the world's population. Rice cultivar improvement is critical in order to feed the world's growing population. Improving yield is one of the main aims of rice breeders. However, yield is a complex quantitative trait controlled by many genes. The presence of genetic diversity is the key factor to improve the yield hence, the presence of diversity in any germplasm is important for yield improvement. In the current study, the rice germplasm was collected from Pakistan and the United States of America and a panel of 100 diverse genotypes was utilized to identify important yield and yield-related traits. For this, a genome-wide association study (GWAS) was performed to identify the genetic loci related to yield. The GWAS on the diverse germplasm will lead to the identification of new genes which can be utilized in the breeding program for improvement of yield. For this reason, firstly, the germplasm was phenotypically evaluated in two growing seasons for yield and yield-related traits. The analysis of variance results showed significant differences among traits which showed the presence of diversity in the current germplasm. Secondly, the germplasm was also genotypically evaluated using 10K SNP. Genetic structure analysis showed the presence of four groups which showed that enough genetic diversity was present in the rice germplasm to be used for association mapping analysis. The results of GWAS identified 201 significant marker trait associations (MTAs. 16 MTAs were identified for plant height, 49 for days to flowering, three for days to maturity, four for tillers per plant, four for panicle length, eight for grains per panicle, 20 unfilled grains per panicle, 81 for seed setting %, four for thousand-grain weight, five for yield per plot and seven for yield per hectare. Apart from this, some pleiotropic loci were also identified. The results showed that panicle length (PL) and thousand-grain weight (TGW) were controlled by a pleiotropic locus OsGRb23906 on chromosome 1 at 10,116,371 cM. The loci OsGRb25803 and OsGRb15974 on chromosomes 4 and 8 at the position of 14,321,111 cM and 6,205,816 cM respectively, showed pleiotropic effects for seed setting % (SS) and unfilled grain per panicle (UG/P). A locus OsGRb09180 on chromosome 4 at 19,850,601 cM was significantly linked with SS and yield/ha. Furthermore, gene annotation was performed, and results indicated that the 190 candidate genes or QTLs that closely linked with studied traits. These candidate genes and novel significant markers could be useful in marker-assisted gene selection and QTL pyramiding to improve rice yield and the selection of potential parents, recombinants and MTAs which could be used in rice breeding programs to develop high-yielding rice varieties for sustainable food security.

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 5,471.55 cM. 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 (qg_s6-2 and qGY6-1), while co-localized QTLs for stomatal conductance and transpiration rate were identified on chr 7 (qg_s7-1 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.

Candidate genes affecting stomatal density in rice (Oryza sativa L.) identified by genome-wide association

Stomata regulate photosynthesis and water loss. They have been an active subject of research for centuries, but our knowledge of the genetic components that regulate stomatal development in crops remains very limited in comparison to the model plant Arabidopsis thaliana. Leaf stomatal density was found to vary by over 2.5-fold across a panel of 235 rice accessions. Using GWAS, we successfully identified five different QTLs associated with stomatal density on chromosomes 2, 3, 9, and 12. Forty-two genes were identified within the haplotype blocks corresponding to these QTLs. Of these, nine genes contained haplotypes that were associated with different stomatal densities. These include a gene encoding a trehalose-6-phosphate synthase, an enzyme that has previously been associated with altered stomatal density in Arabidopsis, and genes encoding a B-BOX zinc finger family protein, a leucine-rich repeat family protein, and the 40 S ribosomal protein S3a, none of which have previously been linked to stomatal traits. We investigated further and show that a closely related B-BOX protein regulates stomatal development in Arabidopsis. The results of this study provide information on genetic associations with stomatal density in rice. The QTLs and candidate genes may be useful in future breeding programs for low or high stomatal density and, consequently, improved photosynthetic capacity, water use efficiency, or drought tolerance.

Current Progress and Future Prospect of Wheat Genetics Research towards an Enhanced Nitrogen Use Efficiency

To improve the yield and quality of wheat is of great importance for food security worldwide. One of the most effective and significant approaches to achieve this goal is to enhance the nitrogen use efficiency (NUE) in wheat. In this review, a comprehensive understanding of the factors involved in the process of the wheat nitrogen uptake, assimilation and remobilization of nitrogen in wheat were introduced. An appropriate definition of NUE is vital prior to its precise evaluation for the following gene identification and breeding process. Apart from grain yield (GY) and grain protein content (GPC), the commonly recognized major indicators of NUE, grain protein deviation (GPD) could also be considered as a potential trait for NUE evaluation. As a complex quantitative trait, NUE is affected by transporter proteins, kinases, transcription factors (TFs) and micro RNAs (miRNAs), which participate in the nitrogen uptake process, as well as key enzymes, circadian regulators, cross-talks between carbon metabolism, which are associated with nitrogen assimilation and remobilization. A series of quantitative genetic loci (QTLs) and linking markers were compiled in the hope to help discover more efficient and useful genetic resources for breeding program. For future NUE improvement, an exploration for other criteria during selection process that incorporates morphological, physiological and biochemical traits is needed. Applying new technologies from phenomics will allow high-throughput NUE phenotyping and accelerate the breeding process. A combination of multi-omics techniques and the previously verified QTLs and molecular markers will facilitate the NUE QTL-mapping and novel gene identification.

Breeding and Genomic Approaches towards Development of Fusarium Wilt Resistance in Chickpea

Chickpea is an important leguminous crop with potential to provide dietary proteins to both humans and animals. It also ameliorates soil nitrogen through biological nitrogen fixation. The crop is affected by an array of biotic and abiotic factors. Among different biotic stresses, a major fungal disease called Fusarium wilt, caused by Fusarium oxysporum f. sp. ciceris (FOC), is responsible for low productivity in chickpea. To date, eight pathogenic races of FOC (race 0, 1A, and 1B/C, 2-6) have been reported worldwide. The development of resistant cultivars using different conventional breeding methods is very time consuming and depends upon the environment. Modern technologies can improve conventional methods to solve these major constraints. Understanding the molecular response of chickpea to Fusarium wilt can help to provide effective management strategies. The identification of molecular markers closely linked to genes/QTLs has provided great potential for chickpea improvement programs. Moreover, omics approaches, including transcriptomics, metabolomics, and proteomics give scientists a vast viewpoint of functional genomics. In this review, we will discuss the integration of all available strategies and provide comprehensive knowledge about chickpea plant defense against Fusarium wilt.

Genome-Wide Association Study for Seed Dormancy Using Re-Sequenced Germplasm under Multiple Conditions in Rice

Seed dormancy is a key factor used to determine seed germination in rice production. So far, only a few genes controlling seed dormancy have been reported, and the genetic mechanism of rice seed dormancy is still elusive. In this study, a population of 195 diverse re-sequenced accessions from 40 countries was evaluated for the seed germination rate (GR) without dormancy breaking (WDB) as a control and under dry heating (DH) and gibberellic acid (GA) treatments, as dormancy breaking agents to identify QTLs for seed dormancy. Phenotypic assessment revealed that these accessions had abundant variations in seed dormancy. GWAS using 1,120,223 high-quality single nucleotide polymorphisms (SNPs) and a mixed linear model (MLM) incorporating both principal components (PCs) and kinship (K) identified 30 QTLs on 10 chromosomes, accounting for 7.3-20.4% of the phenotypic variance in GR. Ten of the QTLs were located in the regions of previously reported QTLs, while the rest were novel ones. Thirteen high-confidence candidate genes were predicted for the four QTLs detected in two or three conditions (qGR4-4, qGR4-5, qGR8 and qGR11-4) and one QTL with a large effect (qGR3). These genes were highly expressed during seed development and were significantly regulated by various hormone treatments. This study provides new insights into the genetic and molecular basis of rice seed dormancy/germination. The accessions with moderate and strong dormancy and markers for the QTLs and candidate genes are useful for attaining a proper level of seed dormancy.

Genome-Wide Urea Response in Rice Genotypes Contrasting for Nitrogen Use Efficiency

Rice is an ideal crop for improvement of nitrogen use efficiency (NUE), especially with urea, its predominant fertilizer. There is a paucity of studies on rice genotypes contrasting for NUE. We compared low urea-responsive transcriptomes of contrasting rice genotypes, namely Nidhi (low NUE) and Panvel1 (high NUE). Transcriptomes of whole plants grown with media containing normal (15 mM) and low urea (1.5 mM) revealed 1497 and 2819 differentially expressed genes (DEGs) in Nidhi and Panvel1, respectively, of which 271 were common. Though 1226 DEGs were genotype-specific in Nidhi and 2548 in Panvel1, there was far higher commonality in underlying processes. High NUE is associated with the urea-responsive regulation of other nutrient transporters, miRNAs, transcription factors (TFs) and better photosynthesis, water use efficiency and post-translational modifications. Many of their genes co-localized to NUE-QTLs on chromosomes 1, 3 and 9. A field evaluation under different doses of urea revealed better agronomic performance including grain yield, transport/uptake efficiencies and NUE of Panvel1. Comparison of our urea-based transcriptomes with our previous nitrate-based transcriptomes revealed many common processes despite large differences in their expression profiles. Our model proposes that differential involvement of transporters and TFs, among others, contributes to better urea uptake, translocation, utilization, flower development and yield for high NUE.

Genetics and breeding of phenolic content in tomato, eggplant and pepper fruits

Phenolic acids and flavonoids are large groups of secondary metabolites ubiquitous in the plant kingdom. They are currently in the spotlight due to the numerous health benefits associated with their consumption, as well as for their vital roles in plant biological processes and in plant-environment interaction. Tomato, eggplant and pepper are in the top ten most consumed vegetables in the world, and their fruit accumulation profiles have been extensively characterized, showing substantial differences. A broad array of genetic and genomic tools has helped to identify QTLs and candidate genes associated with the fruit biosynthesis of phenolic acids and flavonoids. The aim of this review was to synthesize the available information making it easily available for researchers and breeders. The phenylpropanoid pathway is tightly regulated by structural genes, which are conserved across species, along with a complex network of regulatory elements like transcription factors, especially of MYB family, and cellular transporters. Moreover, phenolic compounds accumulate in tissue-specific and developmental-dependent ways, as different paths of the metabolic pathway are activated/deactivated along with fruit development. We retrieved 104 annotated putative orthologues encoding for key enzymes of the phenylpropanoid pathway in tomato (37), eggplant (29) and pepper (38) and compiled 267 QTLs (217 for tomato, 16 for eggplant and 34 for pepper) linked to fruit phenolic acids, flavonoids and total phenolics content. Combining molecular tools and genetic variability, through both conventional and genetic engineering strategies, is a feasible approach to improve phenolics content in tomato, eggplant and pepper. Finally, although the phenylpropanoid biosynthetic pathway has been well-studied in the Solanaceae, more research is needed on the identification of the candidate genes behind many QTLs, as well as their interactions with other QTLs and genes.

Quantitative trait loci associated with amino acid concentration and in vitro protein digestibility in pea (Pisum sativum L.)

With the expanding interest in plant-based proteins in the food industry, increasing emphasis is being placed on breeding for protein concentration and quality. Two protein quality traits i.e., amino acid profile and protein digestibility, were assessed in replicated, multi-location field trials from 2019 to 2021 in pea recombinant inbred line population PR-25. This RIL population was targeted specifically for the research of protein related traits and its parents, CDC Amarillo and CDC Limerick, had distinct variations in the concentration of several amino acids. Amino acid profile was determined using near infrared reflectance analysis, and protein digestibility was through an in vitro method. Several essential amino acids were selected for QTL analysis, including lysine, one of the most abundant essential amino acids in pea, and methionine, cysteine, and tryptophan, the limiting amino acids in pea. Based on phenotypic data of amino acid profiles and in vitro protein digestibility of PR-25 harvested in seven location-years, three QTLs were associated with methionine + cysteine concentration, among which, one was located on chromosome 2 (R² = 17%, indicates this QTL explained 17% phenotypic variation of methionine + cysteine concentration within PR-25), and two were located on chromosome 5 (R² = 11% and 16%). Four QTLs were associated with tryptophan concentration and are located on chromosome 1 (R² = 9%), chromosome 3 (R² = 9%), and chromosome 5 (R² = 8% and 13%). Three QTLs were associated with lysine concentration, among which, one was located on chromosome 3 (R² = 10%), the other two were located on chromosome 4 (R² = 15% and 21%). Two QTLs were associated with in vitro protein digestibility, one each located on chromosomes 1 (R² = 11%) and 2 (R² = 10%). QTLs associated with in vitro protein digestibility, and methionine + cysteine concentration on chromosome 2 were identified to be co-localized with known QTL for total seed protein concentration in PR-25. QTLs associated with tryptophan and methionine + cysteine concentration co-localized on chromosome 5. The identification of QTLs associated with pea seed quality is an important step towards marker-assisted selection of breeding lines with improved nutritional quality, which will further boost the competitiveness of pea in plant-based protein markets.

Identification of QTLs and Putative Candidate Genes for Plant Architecture of Lotus Revealed by Regional Association Mapping

The lotus (Nelumbo Adans.) is one of the most economically relevant ornamental aquatic plants. Plant architecture (PA) is an important trait for lotus classification, cultivation, breeding, and applications. However, the underlying genetic and molecular basis controlling PA remains poorly understood. In this study, an association study for PA-related traits was performed with 93 genome-wide microsatellite markers (simple sequence repeat, SSR) and 51 insertion-deletion (InDel) markers derived from the candidate regions using a panel of 293 lotus accessions. Phenotypic data analysis of the five PA-related traits revealed a wide normal distribution and high heritability from 2013 to 2016, which indicated that lotus PA-related traits are highly polygenic traits. The population structure (Q-matrix) and the relative kinships (K-matrix) of the association panels were analyzed using 93 SSR markers. The mixed linear model (MLM) taking Q-matrix and K-matrix into account was used to estimate the association between markers and the traits. A total of 26 markers and 65 marker-trait associations were identified by considering associations with p < 0.001 and Q < 0.05. Based on the significant markers, two QTLs on Chromosome 1 were identified, and two candidate genes were preliminarily determined. The results of our study provided useful information for the lotus breeding aiming at different PA phenotypes using a molecular-assisted selection (MAS) method and also laid the foundation for the illustration of the molecular mechanism underlying the major QTL and key markers associated with lotus PA.

Genome-wide association study revealed suggestive QTLs for production and reproduction traits in Indian Murrah buffalo

The present study was aimed to identify the genome-wide SNPs associated with production and reproduction traits in 96 Indian Murrah buffalo genotyped based on ddRAD approach using Genome-Wide Association Study (GWAS) along with phenotypes of contemporary animals using mixed linear model for production and reproduction traits. A total of 27,735 SNPs identified using ddRAD approach in 96 Indian Murrah buffaloes were used for GWAS. A total of 28 SNPs were found to be associated with production and reproductive traits. Among these, 14 SNPs were present in the intronic region of AK5, BACH2, DIRC2, ECPAS, MPZL1, MYO16, QRFPR, RASGRF1, SLC9A4, TANC1, and TRIM67 genes and one SNP in long non-coding region of LOC102414911. Out of these 28 SNPs, 9 SNPs were found to have pleiotropic effect over milk production traits and were present in chromosome number BBU 1, 2, 4, 6, 9, 10, 12, 19, and 20. SNPs in the intronic region of AK5, TRIM67 genes were found to be associated with milk production traits. Eleven and five SNPs in the intergenic region were associated with milk production and reproduction traits respectively. The above genomic information may be used for selection of Murrah animals for genetic improvement.

Flooding tolerance in Rice: adaptive mechanism and marker-assisted selection breeding approaches

Natural and man-made ecosystems worldwide are subjected to flooding, which is a form of environmental stress. Genetic variability in the plant response to flooding involves variations in metabolism, architecture, and elongation development that are related with a low oxygen escape strategy and an opposing quiescence scheme that enables prolonged submergence endurance. Flooding is typically associated with a decrease in O₂ in the cells, which is especially severe when photosynthesis is absent or limited, leading to significant annual yield losses globally. Over the past two decades, considerable advancements have been made in understanding of mechanisms of rice adaptation and tolerance to flooding/submergence. The mapping and identification of Sub1 QTL have led to the development of marker-assisted selection (MAS) breeding approach to improve flooding-tolerant rice varieties in submergence-prone ecosystems. The Sub1 incorporated in rice varieties showed tolerance during flash flood, but not during stagnant conditions. Hence, gene pyramiding techniques can be applied to combine/stack multiple resistant genes for developing flood-resilient rice varieties for different types of flooding stresses. This review contains an update on the latest advances in understanding the molecular mechanisms, metabolic adaptions, and genetic factors governing rice flooding tolerance. A better understanding of molecular genetics and adaptation mechanisms that enhance flood-tolerant varieties under different flooding regimes was also discussed.

A Compendium for Novel Marker-Based Breeding Strategies in Eggplant

The worldwide production of eggplant is estimated at about 58 Mt, with China, India and Egypt being the major producing countries. Breeding efforts in the species have mainly focused on increasing productivity, abiotic and biotic tolerance/resistance, shelf-life, the content of health-promoting metabolites in the fruit rather than decreasing the content of anti-nutritional compounds in the fruit. From the literature, we collected information on mapping quantitative trait loci (QTLs) affecting eggplant's traits following a biparental or multi-parent approach as well as genome-wide association (GWA) studies. The positions of QTLs were lifted according to the eggplant reference line (v4.1) and more than 700 QTLs were identified, here organized into 180 quantitative genomic regions (QGRs). Our findings thus provide a tool to: (i) determine the best donor genotypes for specific traits; (ii) narrow down QTL regions affecting a trait by combining information from different populations; (iii) pinpoint potential candidate genes.

A chromosome-level genome assembly for Erianthus fulvus provides insights into its biofuel potential and facilitates breeding for improvement of sugarcane

Erianthus produces substantial biomass, exhibits a good Brix value, and shows wide environmental adaptability, making it a potential biofuel plant. In contrast to closely related sorghum and sugarcane, Erianthus can grow in degraded soils, thus releasing pressure on agricultural lands used for biofuel production. However, the lack of genomic resources for Erianthus hinders its genetic improvement, thus limiting its potential for biofuel production. In the present study, we generated a chromosome-scale reference genome for Erianthus fulvus Nees. The genome size estimated by flow cytometry was 937 Mb, and the assembled genome size was 902 Mb, covering 96.26% of the estimated genome size. A total of 35 065 protein-coding genes were predicted, and 67.89% of the genome was found to be repetitive. A recent whole-genome duplication occurred approximately 74.10 million years ago in the E. fulvus genome. Phylogenetic analysis showed that E. fulvus is evolutionarily closer to S. spontaneum and diverged after S. bicolor. Three of the 10 chromosomes of E. fulvus formed through rearrangements of ancestral chromosomes. Phylogenetic reconstruction of the Saccharum complex revealed a polyphyletic origin of the complex and a sister relationship of E. fulvus with Saccharum sp., excluding S. arundinaceum. On the basis of the four amino acid residues that provide substrate specificity, the E. fulvus SWEET proteins were classified as mono- and disaccharide sugar transporters. Ortho-QTL genes identified for 10 biofuel-related traits may aid in the rapid screening of E. fulvus populations to enhance breeding programs for improved biofuel production. The results of this study provide valuable insights for breeding programs aimed at improving biofuel production in E. fulvus and enhancing sugarcane introgression programs.

Diet can alter the cost of resistance to a natural parasite in Caenorhabditis elegans

Resistance to parasites confers a fitness advantage, yet hosts show substantial variation in resistance in natural populations. Evolutionary theory indicates that resistant and susceptible genotypes can coexist if resistance is costly, but there is mixed evidence that resistant individuals have lower fitness in the absence of parasites. One explanation for this discrepancy is that the cost of resistance varies with environmental context. We tested this hypothesis using Caenorhabditis elegans and its natural microsporidian parasite, Nematocida ironsii. We used multiple metrics to compare the fitness of two near-isogenic host genotypes differing at regions associated with resistance to N. ironsii. To quantify the effect of the environment on the cost associated with these known resistance regions, we measured fitness on three microbial diets. We found that the cost of resistance varied with both diet and the measure of fitness. We detected no cost to resistance, irrespective of diet, when fitness was measured as fecundity. However, we detected a cost when fitness was measured in terms of population growth, and the magnitude of this cost varied with diet. These results provide a proof of concept that, by mediating the cost of resistance, environmental context may govern the rate and nature of resistance evolution in heterogeneous environments.

Linkage and association mapping of ovule number per ovary (ON) in oilseed rape (Brassica napus L.)

Ovule number (ON) produced during flower development determines the maximum number of seeds per silique and thereby affects crop productivity; however, the genetic basis of ON remains poorly understood in oilseed rape (Brassica napus). In this study, we genetically dissected the ON variations in a double haploid (DH) population and in natural population (NP) by linkage mapping and genome-wide association analysis. Phenotypic analysis showed that ON displayed normal distribution in both populations with the broad-sense heritability of 0.861 (DH population) and 0.930 (natural population). Linkage mapping identified 5 QTLs related to ON, including qON-A03, qON-A07, qON-A07-2, qON-A10, and qON-C06. Genome-wide association studies (GWAS) revealed 214, 48, and 40 significant single-nucleotide polymorphisms (SNPs) by individually using the single-locus model GLM and the multiple-locus model MrMLM and FASTMrMLM. The phenotypic variation explained (PVE) by these QTLs and SNPs ranged from 2.00-17.40% to 5.03-7.33%, respectively. Integration of the results from both strategies identified four consensus genomic regions associated with ON from the chromosomes A03, A07, and A10. Our results preliminarily resolved the genetic basis of ON and provides useful molecular markers for plant yield improvement in B. napus.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01355-7.

Digitalizing breeding in plants: A new trend of next-generation breeding based on genomic prediction

As the world's population grows and food needs diversification, the demand for cereals and horticultural crops with beneficial traits increases. In order to meet a variety of demands, suitable cultivars and innovative breeding methods need to be developed. Breeding methods have changed over time following the advance of genetics. With the advent of new sequencing technology in the early 21st century, predictive breeding, such as genomic selection (GS), emerged when large-scale genomic information became available. GS shows good predictive ability for the selection of individuals with traits of interest even for quantitative traits by using various types of the whole genome-scanning markers, breaking away from the limitations of marker-assisted selection (MAS). In the current review, we briefly describe the history of breeding techniques, each breeding method, various statistical models applied to GS and methods to increase the GS efficiency. Consequently, we intend to propose and define the term digital breeding through this review article. Digital breeding is to develop a predictive breeding methods such as GS at a higher level, aiming to minimize human intervention by automatically proceeding breeding design, propagating breeding populations, and to make selections in consideration of various environments, climates, and topography during the breeding process. We also classified the phases of digital breeding based on the technologies and methods applied to each phase. This review paper will provide an understanding and a direction for the final evolution of plant breeding in the future.

Genome-Wide Association Study of Rice Grain Shape and Chalkiness in a Worldwide Collection of Xian Accessions

Rice (Oryza sativa L.) appearance quality, which is mainly defined by grain shape and chalkiness, is an important target in rice breeding. In this study, we first re-sequenced 137 indica accessions and then conducted a genome-wide association study (GWAS) for six agronomic traits with the 2,998,034 derived single nucleotide polymorphisms (SNPs) by using the best linear unbiased prediction (BLUP) values for each trait. The results revealed that 195 SNPs had significant associations with the six agronomic traits. Based on the genome-wide linkage disequilibrium (LD) blocks, candidate genes for the target traits were detected within 100 kb upstream and downstream of the relevant SNP loci. Results indicate that six quantitative trait loci (QTLs) significantly associated with six traits (qTGW4.1, qTGW4.2, qGL4.1, qGL12.1, qGL12.2, qGW2.1, qGW4.1, qGW6.1, qGW8.1, qGW8.2, qGW9.1, qGW11.1, qGLWR2.1, qGLWR2.2, qGLWR4.2, qPGWC5.1 and qDEC6.1) were identified for haplotype analysis. Among these QTLs, two (qTGW4.2 and qGW6.1), were overlapped with FLO19 and OsbZIP47, respectively, and the remaining four were novel QTLs. These candidate genes were further validated by haplotype block construction.

Heat stress tolerance in peas (Pisum sativum L.): Current status and way forward

In the era of climate change, the overall productivity of pea (Pisum sativum L.) is being threatened by several abiotic stresses including heat stress (HS). HS causes severe yield losses by adversely affecting several traits in peas. A reduction in pod yield has been reported from 11.1% to 17.5% when mean daily temperature increase from 1.4 to 2.2°C. High-temperature stress (30.5-33°C) especially during reproductive phase is known to drastically reduce both seed yield and germination. HS during germination and early vegetative stage resulted in poor emergence and stunted plant growth along with detrimental effects on physiological functions of the pea plant. To combat HS and continue its life cycle, plants use various defense strategies including heat escape, avoidance or tolerance mechanisms. Ironically, the threshold temperatures for pea plant and its responses are inconsistent and not yet clearly identified. Trait discovery through traditional breeding such as semi leaflessness (afila), upright growing habit, lodging tolerance, lower canopy temperature and small seeded nature has highlighted their utility for greater adaptation under HS in pea. Screening of crop gene pool and landraces for HS tolerance in a targeted environment is a simple approach to identify HS tolerant genotypes. Thus, precise phenotyping using modern phenomics tools could lead to increased breeding efficiency. The NGS (next generation sequencing) data can be associated to find the candidate genes responsible for the HS tolerance in pea. In addition, genomic selection, genome wide association studies (GWAS) and marker assisted selection (MAS) can be used for the development of HS tolerant pea genotypes. Additionally, development of transgenics could be an alternative strategy for the development of HS tolerant pea genotypes. This review comprehensively covers the various aspects of HS tolerance mechanisms in the pea plant, screening protocols, omic advances, and future challenges for the development of HS tolerant genotypes.

Inheritance of Fruit Red-Flesh Patterns in Peach

Fruit color is an important trait in peach from the point of view of consumer preference, nutritional content, and diversification of fruit typologies. Several genes and phenotypes have been described for peach flesh and skin color, and although peach color knowledge has increased in the last few years, some fruit color patterns observed in peach breeding programs have not been carefully described. In this work, we first describe some peach mesocarp color patterns that have not yet been described in a collection of commercial peach cultivars, and we also study the genetic inheritance of the red dots present in the flesh (RDF) and red color around the stone (CAS) in several intra- and interspecific segregating populations for both traits. For RDF, we identified a QTL at the beginning of G5 in two intraspecific populations, and for CAS we identified a major QTL in G4 in both an intraspecific and an interspecific population between almond and peach. Finally, we discuss the interaction between these QTLs and some other genes previously identified in peach, such as dominant blood flesh (DBF), color around the stone (Cs), subacid (D) and the maturity date (MD), and the implications for peach breeding. The results obtained here will help peach germplasm curators and breeders to better characterize their plant materials and to develop an integrated system of molecular markers to select these traits.

Molecular Mapping of Biofortification Traits in Bread Wheat (Triticum aestivum L.) Using a High-Density SNP Based Linkage Map

A set of 188 recombinant inbred lines (RILs) derived from a cross between a high-yielding Indian bread wheat cultivar HD2932 and a synthetic hexaploid wheat (SHW) Synthetic 46 derived from tetraploid Triticum turgidum (AA, BB 2n = 28) and diploid Triticum tauschii (DD, 2n = 14) was used to identify novel genomic regions associated in the expression of grain iron concentration (GFeC), grain zinc concentration (GZnC), grain protein content (GPC) and thousand kernel weight (TKW). The RIL population was genotyped using SNPs from 35K Axiom^® Wheat Breeder's Array and 34 SSRs and phenotyped in two environments. A total of nine QTLs including five for GPC (QGpc.iari_1B, QGpc.iari_4A, QGpc.iari_4B, QGpc.iari_5D, and QGpc.iari_6B), two for GFeC (QGfec.iari_5B and QGfec.iari_6B), and one each for GZnC (QGznc.iari_7A) and TKW (QTkw.iari_4B) were identified. A total of two stable and co-localized QTLs (QGpc.iari_4B and QTkw.iari_4B) were identified on the 4B chromosome between the flanking region of Xgwm149-AX-94559916. In silico analysis revealed that the key putative candidate genes such as P-loop containing nucleoside triphosphatehydrolase, Nodulin-like protein, NAC domain, Purine permease, Zinc-binding ribosomal protein, Cytochrome P450, Protein phosphatase 2A, Zinc finger CCCH-type, and Kinesin motor domain were located within the identified QTL regions and these putative genes are involved in the regulation of iron homeostasis, zinc transportation, Fe, Zn, and protein remobilization to the developing grain, regulation of grain size and shape, and increased nitrogen use efficiency. The identified novel QTLs, particularly stable and co-localized QTLs are useful for subsequent use in marker-assisted selection (MAS).

fulvum

Earliness in crop plants has a vital role in prevention of heat-induced drought stress and in combating global warming, which is predicted to exacerbate in the near future. Furthermore, earliness may expand production into northern areas or higher altitudes, having relatively shorter growing season and may also expand arable lands to meet global food demands. The primary objective of the present study was to investigate quantitative trait loci (QTLs) for super-earliness and important agro-morphological traits in a recombinant inbred line (RIL) population derived from an interspecific cross. A population of 114 RILs developed through single-seed descent from an interspecific cross involving Pisum sativum L. and P. fulvum Sibth. et Sm. was evaluated to identify QTLs for super-earliness and important agro-morphological traits. A genetic map was constructed with 44 SSRs markers representing seven chromosomes with a total length of 262.6 cM. Of the 14 QTLs identified, two were for super-earliness on LG2, one for plant height on LG3, six for number of pods per plant on LG2, LG4, LG5 and LG6, one for number of seeds per pod on LG6, one for pod length on LG4 and three for harvest index on LG3, LG5, and LG6. AA205 and AA372-1 flanking markers for super-earliness QTLs were suggested for marker-assisted selection (MAS) in pea breeding programs due to high heritability of the trait. This is the first study to map QTLs originating from P. sativum and P. fulvum recently identified species with super-earliness character and the markers (AA205 and AA372-1) linked to QTLs were valuable molecular tools for pea breeding.

Association Mapping of Amylose Content in Maize RIL Population Using SSR and SNP Markers

The ratio of amylose to amylopectin in maize kernel starch is important for the appearance, structure, and quality of food products and processing. This study aimed to identify quantitative trait loci (QTLs) controlling amylose content in maize through association mapping with simple sequence repeat (SSR) and single-nucleotide polymorphism (SNP) markers. The average value of amylose content for an 80-recombinant-inbred-line (RIL) population was 8.8 ± 0.7%, ranging from 2.1 to 15.9%. We used two different analyses-Q + K and PCA + K mixed linear models (MLMs)-and found 38 (35 SNP and 3 SSR) and 32 (29 SNP and 3 SSR) marker-trait associations (MTAs) associated with amylose content. A total of 34 (31 SNP and 3 SSR) and 28 (25 SNP and 3 SSR) MTAs were confirmed in the Q + K and PCA + K MLMs, respectively. This study detected some candidate genes for amylose content, such as GRMZM2G118690-encoding BBR/BPC transcription factor, which is used for the control of seed development and is associated with the amylose content of rice. GRMZM5G830776-encoding SNARE-interacting protein (KEULE) and the uncharacterized marker PUT-163a-18172151-1376 were significant with higher R2 value in two difference methods. GRMZM2G092296 were also significantly associated with amylose content in this study. This study focused on amylose content using a RIL population derived from dent and waxy inbred lines using molecular markers. Future studies would be of benefit for investigating the physical linkage between starch synthesis genes using SNP and SSR markers, which would help to build a more detailed genetic map and provide new insights into gene regulation of agriculturally important traits.

Mapping QTL for Phenological and Grain-Related Traits in a Mapping Population Derived from High-Zinc-Biofortified Wheat

Genomic regions governing days to heading (DH), days to maturity (DM), plant height (PH), thousand-kernel weight (TKW), and test weight (TW) were investigated in a set of 190 RILs derived from a cross between a widely cultivated wheat-variety, Kachu (DPW-621-50), and a high-zinc variety, Zinc-Shakti. The RIL population was genotyped using 909 DArTseq markers and phenotyped in three environments. The constructed genetic map had a total genetic length of 4665 cM, with an average marker density of 5.13 cM. A total of thirty-seven novel quantitative trait loci (QTL), including twelve for PH, six for DH, five for DM, eight for TKW and six for TW were identified. A set of 20 stable QTLs associated with the expression of DH, DM, PH, TKW, and TW were identified in two or more environments. Three novel pleiotropic genomic-regions harboring co-localized QTLs governing two or more traits were also identified. In silico analysis revealed that the DArTseq markers were located on important putative candidate genes such as MLO-like protein, Phytochrome, Zinc finger and RING-type, Cytochrome P450 and pentatricopeptide repeat, involved in the regulation of pollen maturity, the photoperiodic modulation of flowering-time, abiotic-stress tolerance, grain-filling duration, thousand-kernel weight, seed morphology, and plant growth and development. The identified novel QTLs, particularly stable and co-localized QTLs, will be validated to estimate their effects in different genetic backgrounds for subsequent use in marker-assisted selection (MAS).

Genome-wide association study of host resistance to the ectoparasite Ichthyophthirius multifiliis in the Amazon fish Colossoma macropomum

BACKGROUND

Tambaqui, Colossoma macropomum, is the most important native fish species farmed in South America, particularly in Brazil, where its production is limited in the southern and southeastern regions due to disease outbreaks caused by the parasite Ichthyophthirius multifiliis. Therefore, genome level analysis to understand the genetic architecture of the host resistance against I. multifiliis is fundamental to improve this trait in tambaqui. The objective of the present study was to map QTL (quantitative trait loci) associated with resistance to I. multifiliis in tambaqui by GWAS (genome-wide association study).

METHODS AND RESULTS

Individuals belonging to seven families, which were previously submitted to an experimental challenge to assess the natural resistance to the parasite I. multifiliis, were used for genomic analysis. A total of 7717 SNPs were identified in this population by ddRAD (double digest restriction site associated DNA). GWAS revealed four SNPs significantly associated in the LGs (linkage groups) 2, 9, 11 and 20 for the traits time of death and parasite load. The SNPs explained a low proportion of the variance to I. multifiliis resistance for time of death and parasite load (about 0.622% and 0.375%, respectively). The SNPs were close to 11 genes related to the immune system: abcf3, znf830, ccr9, gli3, ackr4, tbata, ndr2, tgfbr3, nhej1, znf644b, and cldn10a.

CONCLUSIONS

In conclusion, the resistance to I. multifiliis is probably under polygenic control in tambaqui, in which different QTLs of low variance can be involved in the immune responses against this ectoparasite.

Quantitative trait loci associated with straighthead-resistance used for marker assisted selection in rice (Oryza sativa L.) RIL populations

Straighthead is a physiological disorder of rice (Oryza sativa L.) that causes dramatic yield loss in susceptible cultivars. This disorder is found worldwide and is reported to increasingly occur in the southern United States. Genetic resistance breeding has been considered as one of the most efficient methods for straighthead prevention because the traditional prevention method wastes water and costs labor. In this study, we analyzed the genetic effects of five straighthead quantitative trait loci (QTLs), namely, AP3858-1 (qSH-8), RM225 (qSH-6), RM2 (qSH-7), RM206 (qSH-11), and RM282 (qSH-3), on the recombinant inbred lines (RILs) developed from Jing185/Cocodrie and Zhe733/R312 populations using our five previously identified markers linked to these QTLs. As a result, recombinant inbred lines (RILs) with four resistant alleles at the four loci (AP3858-1, RM225, RM2, and RM206) exhibited the highest straighthead resistance. This result suggests that the four markers could be efficiently used to select the straighthead-resistant recombinant inbred lines (RILs). Furthermore, by using AP3858-1, we successfully obtained five straighthead-resistant recombinant inbred lines (RILs) with more than 50% genetic similarity to Cocodrie. These markers and recombinant inbred lines (RILs) can be used for future straighthead resistance breeding through marker-assisted selection.

Nitrogen use efficiency-a key to enhance crop productivity under a changing climate

Nitrogen (N) is an essential element required for the growth and development of all plants. On a global scale, N is agriculture's most widely used fertilizer nutrient. Studies have shown that crops use only 50% of the applied N effectively, while the rest is lost through various pathways to the surrounding environment. Furthermore, lost N negatively impacts the farmer's return on investment and pollutes the water, soil, and air. Therefore, enhancing nitrogen use efficiency (NUE) is critical in crop improvement programs and agronomic management systems. The major processes responsible for low N use are the volatilization, surface runoff, leaching, and denitrification of N. Improving NUE through agronomic management practices and high-throughput technologies would reduce the need for intensive N application and minimize the negative impact of N on the environment. The harmonization of agronomic, genetic, and biotechnological tools will improve the efficiency of N assimilation in crops and align agricultural systems with global needs to protect environmental functions and resources. Therefore, this review summarizes the literature on nitrogen loss, factors affecting NUE, and agronomic and genetic approaches for improving NUE in various crops and proposes a pathway to bring together agronomic and environmental needs.

Whole-genome sequence-based association analyses on an eight-breed crossed heterogeneous stock of pigs reveal the genetic basis of skeletal muscle fiber characteristics

Skeletal muscle fiber characteristics (MFCs) have been extensively studied due to their importance to human health and athletic ability, as well as to the quantity and quality of livestock meat production. Hence, we performed a genome-wide association study (GWAS) on nine muscle fiber traits by using whole genome sequence data in an eight-breed crossed heterogeneous stock pig population. This GWAS revealed 67 quantitative trait loci (QTLs) for these traits. The most significant GWAS signal was detected in the region of Sus scrofa chromosome 12 (SSC12) containing the MYH gene family. Notably, we identified a significant SNP rs322008693 (P = 7.52E-09) as the most likely causal mutation for the total number of muscle fibers (TNMF) QTL on SSC1. The results of EMSA and luciferase assays indicated that the rs322008693 SNP resided in a functional element. These findings provide valuable molecular markers for pig meat production selection as well as for deciphering the genetic mechanisms of the muscle fiber physiology.

QTL Detection for Rice Grain Length and Fine Mapping of a Novel Locus qGL6.1

BACKGROUND

Grain length (GL) that is directly associated with appearance quality is a key target of selection in rice breeding. Although abundant quantitative trait locus (QTL) associated with GL have been identified, it was still relatively weak to identify QTL for GL from japonica genetic background, as the shortage of japonica germplasms with long grains. We performed QTLs analysis for GL using a recombinant inbred lines (RILs) population derived from the cross between japonica variety GY8 (short grains) and LX1 (long grains) in four environments.

RESULTS

A total of 197 RILs were genotyped with 285 polymorphic SNP markers. Three QTLs qGL5.3, qGL6.1 and qGL11 were detected to control GL by individual environmental analyses and multi-environment joint analysis. Of these, a major-effect and stable QTL qGL6.1 was identified to be a novel QTL, and its LX1 allele had a positive effect on GL. For fine-mapping qGL6.1, a BC₁F₂ population consisting of 2,487 individuals was developed from a backcross between GY8 and R176, one line with long grain. Eight key informative recombinants were identified by nine kompetitive allele specific PCR (KASP) markers. By analyzing key recombinants, the qGL6.1 locus was narrowed down to a 40.41 kb genomic interval on chromosome 6. One candidate gene LOC_Os06g43304.1 encoding cytochrome P450 (CYP71D55) was finally selected based on the difference in the transcriptional expression and variations in its upstream and downstream region.

CONCLUSIONS

Three QTLs qGL5.3, qGL6.1 and qGL11 were identified to control grain length in rice. One novel QTL qGL6.1 was fine mapped within 40.41 kb region, and LOC_Os06g43304.1 encoding cytochrome P450 (CYP71D55) may be its candidate gene. We propose that the further cloning of the qGL6.1 will facilitate improving appearance quality in japonica varieties.

Physiology and Molecular Breeding in Sustaining Wheat Grain Setting and Quality under Spring Cold Stress

Spring cold stress (SCS) compromises the reproductive growth of wheat, being a major constraint in achieving high grain yield and quality in winter wheat. To sustain wheat productivity in SCS conditions, breeding cultivars conferring cold tolerance is key. In this review, we examine how grain setting and quality traits are affected by SCS, which may occur at the pre-anthesis stage. We have investigated the physiological and molecular mechanisms involved in floret and spikelet SCS tolerance. It includes the protective enzymes scavenging reactive oxygen species (ROS), hormonal adjustment, and carbohydrate metabolism. Lastly, we explored quantitative trait loci (QTLs) that regulate SCS for identifying candidate genes for breeding. The existing cultivars for SCS tolerance were primarily bred on agronomic and morphophysiological traits and lacked in molecular investigations. Therefore, breeding novel wheat cultivars based on QTLs and associated genes underlying the fundamental resistance mechanism is urgently needed to sustain grain setting and quality under SCS.