QTL Mapping by Whole Genome Re-sequencing and Analysis of Candidate Genes for Nitrogen Use Efficiency in Rice

Nitrate-responsive transcriptome analysis of rice RGA1 mutant reveals the role of G-protein alpha subunit in negative regulation of nitrogen-sensitivity and use efficiency

KEY MESSAGE

Nitrate-responsive transcriptomic, phenotypic and physiological analyses of rice RGA1 mutant revealed many novel RGA1-regulated genes/processes/traits related to nitrogen use efficiency, and provided robust genetic evidence of RGA1-regulation of NUE. Nitrogen (N) use efficiency (NUE) is important for sustainable agriculture. G-protein signalling was implicated in N-response/NUE in rice, but needed firm genetic characterization of the role of alpha subunit (RGA1). The knock-out mutant of RGA1 in japonica rice exhibited lesser nitrate-dose sensitivity than the wild type (WT), in yield and NUE. We, therefore, investigated its genomewide nitrate-response relative to WT. It revealed 3416 differentially expressed genes (DEGs), including 719 associated with development, grain yield and phenotypic traits for NUE. The upregulated DEGs were related to photosynthesis, chlorophyll, tetrapyrrole and porphyrin biosynthesis, while the downregulated DEGs belonged to cellular protein metabolism and transport, small GTPase signalling, cell redox homeostasis, etc. We validated 26 nitrate-responsive DEGs across functional categories by RT-qPCR. Physiological validation of nitrate-response in the mutant and the WT at 1.5 and 15 mM doses revealed higher chlorophyll and stomatal length but decreased stomatal density, conductance and transpiration. The consequent increase in photosynthesis and water use efficiency may have contributed to better yield and NUE in the mutant, whereas the WT was N-dose sensitive. The mutant was not as N-dose-responsive as the WT in shoot/root growth, productive tillers and heading date, but equally responsive as WT in total N and protein content. The RGA1 mutant was less impacted by higher N-dose or salt stress in terms of yield, protein content, photosynthetic performance, relative water content, water use efficiency and catalase activity. PPI network analyses revealed known NUE-related proteins as RGA1 interactors. Therefore, RGA1 negatively regulates N-dose sensitivity and NUE in rice.

Genome-wide association study using specific-locus amplified fragment sequencing identifies new genes influencing nitrogen use efficiency in rice landraces

Nitrogen is essential for crop production. It is a critical macronutrient for plant growth and development. However, excessive application of nitrogen fertilizer is not only a waste of resources but also pollutes the environment. An effective approach to solving this problem is to breed rice varieties with high nitrogen use efficiency (NUE). In this study, we performed a genome-wide association study (GWAS) on 419 rice landraces using 208,993 single nucleotide polymorphisms (SNPs). With the mixed linear model (MLM) in the Tassel software, we identified 834 SNPs associated with root surface area (RSA), root length (RL), root branch number (RBN), root number (RN), plant dry weight (PDW), plant height (PH), root volume (RL), plant fresh weight (PFW), root fractal dimension (RFD), number of root nodes (NRN), and average root diameter (ARD), with a significant level of p < 2.39×10^-7. In addition, we found 49 SNPs that were correlated with RL, RBN, RN, PDW, PH, PFW, RFD, and NRN using genome-wide efficient mixed-model association (GEMMA), with a significant level of p < 1×10^-6. Additionally, the final results for eight traits associated with 193 significant SNPs by using multi-locus random-SNP-effect mixed linear model (mrMLM) model and 272 significant SNPs associated with 11 traits by using IIIVmrMLM. Within the linkage intervals of significantly associated SNP, we identified eight known related genes to NUE in rice, namely, OsAMT2;3, OsGS1, OsNR2, OsNPF7.4, OsPTR9, OsNRT1.1B, OsNRT2.3, and OsNRT2.2. According to the linkage disequilibrium (LD) decay value of this population, there were 75 candidate genes within the 150-kb regions upstream and downstream of the most significantly associated SNP (Chr5_29804690, Chr5_29956584, and Chr10_17540654). These candidate genes included 22 transposon genes, 25 expressed genes, and 28 putative functional genes. The expression levels of these candidate genes were measured by real-time quantitative PCR (RT-qPCR), and the expression levels of LOC_Os05g51700 and LOC_Os05g51710 in C347 were significantly lower than that in C117; the expression levels of LOC_Os05g51740, LOC_Os05g51780, LOC_Os05g51960, LOC_Os05g51970, and LOC_Os10g33210 were significantly higher in C347 than C117. Among them, LOC_Os10g33210 encodes a peptide transporter, and LOC_Os05g51690 encodes a CCT domain protein and responds to NUE in rice. This study identified new loci related to NUE in rice, providing new genetic resources for the molecular breeding of rice landraces with high NUE.

QTL mapping and identification of candidate genes for cold tolerance at the germination stage in wild rice

BACKGROUND

Cold damage stress significantly affects rice growth (germination and seedling) and causes serious losses in yield in temperate and high-altitude areas around the globe.

OBJECTIVE

This study aimed to explore the cold tolerance (CT) locus of rice and create new cold-tolerant germplasm. We constructed a chromosome segment substitution line (CSSL) with strong CT and fine mapped quantitative trait loci (QTLs) associated with CT by performing the whole-genome resequencing of CSSL with phenotypes under cold treatment.

METHODS

A chromosome CSSL, including 271 lines from a cross between the cold-tolerant wild rice Y11 (Oryza rufipogon Griff.) and the cold-sensitive rice variety GH998, was developed to map QTLs conferring CT at the germination stage. The whole-genome resequencing was performed on CSSL for mapping QTLs of associated with CT at the germination stage.

RESULTS

A high-density linkage map of the CSSLs was developed using the whole-genome resequencing of 1484 bins. The QTL analysis using 615,466 single-nucleotide polymorphisms (SNPs) led to the identification of 2 QTLs related to germination rate at low-temperature on chromosome 8 (qCTG-8) and chromosome 11 (qCTG-11). The qCTG-8 and qCTG-11 explained 14.55% and 14.31% of the total phenotypic variation, respectively. We narrowed down qCTG-8 and qCTG-11 to 195.5 and 78.83-kb regions, respectively. The expression patterns of important candidate genes in different tissues, and of RNA-sequencing (RNA-seq) in CSSLs, were identified based on gene sequences in qCTG-8 and qCTG-11 cold-induced expression analysis. LOC_Os08g01120 and LOC_Os08g01390 were identified as candidate genes in qCTG-8, and LOC_Os11g32880 was identified as a candidate gene in qCTG-11.

CONCLUSIONS

This study demonstrated a general method that could be used to identify useful loci and genes in wild rice and aid in the future cloning of candidate genes of qCTG-8 and qCTG-11. The CSSLs with strong CT were supported for breeding cold-tolerant rice varieties.

Effects of concentration-dependent graphene on maize seedling development and soil nutrients

The long-term use of chemical fertilizers to maintain agricultural production has had various harmful effects on farmland and has greatly impacted agriculture's sustainable expansion. Graphene, a unique and effective nanomaterial, is used in plant-soil applications to improve plant nutrient uptake, reduce chemical fertilizer pollution by relieving inadequate soil nutrient conditions and enhance soil absorption of nutrient components. We investigated the effects of graphene amendment on nutrient content, maize growth, and soil physicochemical parameters. In each treatment, 5 graphene concentration gradients (0, 25, 50, 100, and 150 g kg^-1) were applied in 2 different types (single-layer and few-layers, SL and FL). Soil aggregates, soil accessible nutrients, soil enzyme activity, plant nutrients, plant height, stem diameter, dry weight, and fresh weight were all measured throughout the maize growth to the V3 stage. Compared to the control (0 g kg^-1), we found that graphene increased the percentage of large agglomerates (0.25-10 mm) in the soil and significantly increased the geometric mean diameter (GMD) and mean weight diameter (MWD) values of > 0.25 mm water-stable agglomerates as the increase of concentration. Soil available nutrient content (AN, AP, and AK) increased, peaking at 150 g kg^-1. Graphene boosted nutrient absorption by maize plants, and aboveground total nitrogen (TN), total phosphorus (TP), and total potassium (TK) contents rose with the increasing application, which raised aboveground fresh weight, dry weight, plant height, and stalk thickness. The findings above confirmed our prediction that adding graphene to the soil may improve maize plant biomass by enhancing soil fertility and improving the soil environment. Given the higher manufacturing cost of single-layer graphene and the greater effect of few-layer graphene on soil and maize plants at the same concentration, single-layer graphene and few-layer graphene at a concentration of 50 g kg^-1 were the optimal application rates.

Functional Bph14 from Rathu Heenati promotes resistance to BPH at the early seedling stage of rice (Oryza sativa L.) as revealed by QTL-seq

A QTL associated with BPH resistance at the early seedling stage was identified on chromosome 3. Functional Bph14 in Rathu Heenati was associated with BPH resistance at the early seedling stage. Brown planthopper (BPH; Nilaparvata lugens Stål) is considered the most important rice pest in many Asian countries. Several BPH resistance genes have previously been identified. However, there are few reports of genes specific for BPH resistance at the early seedling stage, a crucial stage for direct-seeding cultivation. In this study, we performed a QTL-seq analysis using two bulks (20 F₂ lines in each bulk) of the F₂ population (n = 300) derived from a cross of Rathu Heenati (RH) × HCS-1 to identify QTL/genes associated with BPH resistance at the early seedling stage. An important QTL was identified on chromosome 3 and Bph14 was identified as a potential candidate gene based on the differences in gene expression and sequence variation when compared with the two parents. All plants in the resistant bulks possessed the functional Bph14 from RH and all plants in the susceptible bulk and HCS-1 contained a large deletion (2703 bp) in Bph14. The functional Bph14 gene of RH appears to be important for BPH resistance at the early seedling stage of rice and could be used in conjunction with other BPH resistance genes in rice breeding programs that confer resistance to BPH at the early and later growth stages.

Versatile mapping-by-sequencing with Easymap v.2

Mapping-by-sequencing combines Next Generation Sequencing (NGS) with classical genetic mapping by linkage analysis to establish gene-to-phenotype relationships. Although numerous tools have been developed to analyze NGS datasets, only a few are available for mapping-by-sequencing. One such tool is Easymap, a versatile, easy-to-use package that performs automated mapping of point mutations and large DNA insertions. Here, we describe Easymap v.2, which also maps small insertion/deletions (InDels), and includes workflows to perform QTL-seq and variant density mapping analyses. Each mapping workflow can accommodate different experimental designs, including outcrossing and backcrossing, F₂, M₂, and M₃ mapping populations, chemically induced mutation and natural variant mapping, input files containing single-end or paired-end reads of genomic or complementary DNA sequences, and alternative control sample files in FASTQ and VCF formats. Easymap v.2 can also be used as a variant analyzer in the absence of a mapping algorithm and includes a multi-threading option.

Transcriptome and Small RNA Sequencing Reveal the Mechanisms Regulating Harvest Index in Brassica napus

Harvest index (HI), the ratio of harvested seed weight to total aboveground biomass weight, is an economically critical value reflecting the convergence of complex agronomic traits. HI values in rapeseed (Brassica napus) remain much lower than in other major crops, and the underlying regulatory network is largely unknown. In this study, we performed mRNA and small RNA sequencing to reveal the mechanisms shaping HI in B. napus during the seed-filling stage. A total of 8,410 differentially expressed genes (DEGs) between high-HI and low-HI accessions in four tissues (silique pericarp, seed, leaves, and stem) were identified. Combining with co-expression network, 72 gene modules were identified, and a key gene BnaSTY46 was found to participate in retarded establishment of photosynthetic capacity to influence HI. Further research found that the genes involved in circadian rhythms and response to stimulus may play important roles in HI and that their transcript levels were modulated by differentially expressed microRNAs (DEMs), and we identified 903 microRNAs (miRNAs), including 46 known miRNAs and 857 novel miRNAs. Furthermore, transporter activity-related genes were critical to enhancing HI in good cultivation environments. Of 903 miRNAs, we found that the bna-miR396-Bna.A06SRp34a/Bna.A01EMB3119 pair may control the seed development and the accumulation of storage compounds, thus contributing to higher HI. Our findings uncovered the underlying complex regulatory network behind HI and offer potential approaches to rapeseed improvement.

Fine-mapping and identification of a candidate gene controlling seed coat color in melon (Cucumis melo L. var. chinensis Pangalo)

MELO3C019554 encoding a homeobox protein (PHD transcription factor) is a candidate gene that involved in the formation of seed coat color in melon. Seed coat color is related to flavonoid content which is closely related to seed dormancy. According to the genetic analysis of a six-generation population derived from two parents (IC2508 with a yellow seed coat and IC2518 with a brown seed coat), we discovered that the yellow seed coat trait in melon is controlled by a single dominant gene, named CmBS-1. Bulked segregant analysis sequencing (BSA-Seq) revealed that the gene is located at 11,860,000-15,890,000 bp (4.03 Mb) on Chr 6. The F₂ population was genotyped using insertion-deletions (InDels), from which cleaved amplified polymorphic sequence (dCAPS) markers were derived to construct a genetic map. The gene was then fine-mapped to a 233.98 kb region containing 12 genes. Based on gene sequence analysis with two parents, we found that the MELO3C019554 gene encoding a homeobox protein (PHD transcription factor) had a nonsynonymous single nucleotide polymorphism (SNP) mutation in the coding sequence (CDS), and the SNP mutation resulted in the conversion of an amino acid (A → T) at residue 534. In addition, MELO3C019554 exhibited lower relative expression levels in the yellow seed coat than in the brown seed coat. Furthermore, we found that MELO3C019554 is related to 12 flavonoid metabolites. Thus, we predicted that MELO3C019554 is a candidate gene controlling seed coat color in melon. The study lays a foundation for further cloning projects and functional analysis of this gene, as well as marker-assisted selection breeding.

CRISPR/Cas9 gene editing and natural variation analysis demonstrate the potential for HvARE1 in improvement of nitrogen use efficiency in barley

Nitrogen is a major determinant of grain yield and quality. As excessive use of nitrogen fertilizer leads to environmental pollution and high production costs, improving nitrogen use efficiency (NUE) is fundamental for a sustainable agriculture. Here, we dissected the role of the barley abnormal cytokinin response1 repressor 1 (HvARE1) gene, a candidate for involvement in NUE previously identified in a genome-wide association study, through natural variation analysis and clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9)-mediated gene editing. HvARE1 was predominantly expressed in leaves and shoots, with very low expression in roots under low nitrogen conditions. Agrobacterium-mediated genetic transformation of immature embryos (cv. Golden Promise) with single guide RNAs targeting HvARE1 generated 22 T₀ plants, from which four T₁ lines harbored missense and/or frameshift mutations based on genotyping. Mutant are1 lines exhibited an increase in plant height, tiller number, grain protein content, and yield. Moreover, we observed a 1.5- to 2.8-fold increase in total chlorophyll content in the flag leaf at the grain filling stage. Delayed senescence by 10-14 d was also observed in mutant lines. Barley are1 mutants had high nitrogen content in shoots under low nitrogen conditions. These findings demonstrate the potential of ARE1 in NUE improvement in barley.

Identification and Validation of a QTL for Bacterial Leaf Streak Resistance in Rice (Oryza sativa L.) against Thai Xoc Strains

Rice is one of the most important food crops in the world and is of vital importance to many countries. Various diseases caused by fungi, bacteria and viruses constantly threaten rice plants and cause yield losses. Bacterial leaf streak disease (BLS) caused by Xanthomonas oryzae pv. oryzicola (Xoc) is one of the most devastating rice diseases. However, most modern rice varieties are susceptible to BLS. In this study, we applied the QTL-seq approach using an F2 population derived from the cross between IR62266 and Homcholasit (HSC) to rapidly identify the quantitative trait loci (QTL) that confers resistance to BLS caused by a Thai Xoc isolate, SP7-5. The results showed that a single genomic region at the beginning of chromosome 5 was highly associated with resistance to BLS. The gene xa5 was considered a potential candidate gene in this region since most associated single nucleotide polymorphisms (SNPs) were within this gene. A Kompetitive Allele-Specific PCR (KASP) marker was developed based on two consecutive functional SNPs in xa5 and validated in six F2 populations inoculated with another Thai Xoc isolate, 2NY2-2. The phenotypic variance explained by this marker (PVE) ranged from 59.04% to 70.84% in the six populations. These findings indicate that xa5 is a viable candidate gene for BLS resistance and may help in breeding programs for BLS resistance.

Identification of genomic loci conferring broad-spectrum resistance to multiple nematode species in exotic soybean accession PI 567305

KEY MESSAGE

Genetic analysis identified a unique combination of major QTL for resistance to important soybean nematodes concurrently present in a single soybean accession, which has not been reported earlier. An exotic soybean [Glycine max (L.) Merr.] accession, PI 567305, was reported to be highly resistant to three important nematode species, soybean cyst (SCN), root-knot (RKN), and reniform (RN) nematodes. However, genetic basis controlling broad-spectrum resistance in this germplasm has not been investigated. We report results of genetic analysis to identify genomic loci conferring resistance to these nematode species. A bi-parental population consisting of 242 F8-derived recombinant inbred lines (RILs) was developed from a cross of a nematode susceptible cultivar, Magellan, and resistant accession, PI 567305. The RILs were phenotyped for nematode resistance to three SCN HG types. They were genotyped using the Infinium SoySNP6K BeadChips and genotype-by-sequencing (GBS) methods in an attempt to evaluate the cost-effectiveness and efficiency of these two genotyping platforms. Genetic analysis confirmed the major QTL on chromosomes (Chrs) 10 and 18 with broad-spectrum resistance to the three nematodes present in this germplasm. Haplotype and copy number variation analyses of SCN resistance QTL indicated that PI 567305 has a different haplotype, which is associated with likely a unique SCN resistance mechanism different from Peking- or PI 88788-type resistance. The evaluations of both Infinium Beadchip- and GBS-based genotyping technologies provided comprehensive insights for researchers to choose a cost-effective and efficient platform for QTL mapping and for other genomic studies in soybeans.

Evolutionarily informed machine learning enhances the power of predictive gene-to-phenotype relationships

Inferring phenotypic outcomes from genomic features is both a promise and challenge for systems biology. Using gene expression data to predict phenotypic outcomes, and functionally validating the genes with predictive powers are two challenges we address in this study. We applied an evolutionarily informed machine learning approach to predict phenotypes based on transcriptome responses shared both within and across species. Specifically, we exploited the phenotypic diversity in nitrogen use efficiency and evolutionarily conserved transcriptome responses to nitrogen treatments across Arabidopsis accessions and maize varieties. We demonstrate that using evolutionarily conserved nitrogen responsive genes is a biologically principled approach to reduce the feature dimensionality in machine learning that ultimately improved the predictive power of our gene-to-trait models. Further, we functionally validated seven candidate transcription factors with predictive power for NUE outcomes in Arabidopsis and one in maize. Moreover, application of our evolutionarily informed pipeline to other species including rice and mice models underscores its potential to uncover genes affecting any physiological or clinical traits of interest across biology, agriculture, or medicine.

Identification of alkali-tolerant candidate genes using the NGS-assisted BSA strategy in rice

Rice (Oryza sativa L.) is a saline-alkali-sensitive crop. Saline-alkali environments can seriously affect the growth, development, and yield of rice. The mechanisms of salt tolerance and alkali tolerance in rice are different; thus, it is very important to study and explore the alkali-tolerant gene loci to improve the saline-alkali tolerance of rice varieties. In this study, the japonica rice varieties Dongnong 425 (DN425) and Changbai 10 (CB10) and a hybridized recombinant inbred line (RIL) population were used as materials to be irrigated with Na2CO3 solution under field test conditions. A resistant pool (R-pool) and a sensitive pool (S-pool) were constructed by selecting the lines with extremely high and extremely low 1000-grain weight (TGW), respectively, from the RIL population under alkali treatment. Four candidate TGW regions on chromosomes (Chr.) 2 and 3 were associated using the bulked segregant analysis (BSA) strategy assisted by next-generation sequencing (NGS) technology (NGS-assisted BSA). Using the linkage analysis, QTL-qATGW2-2 in the candidate region was mapped within a range of 116 Kb between the SSR marker RM13592 and the Indel marker Indel3 of Chr. 2, which contained 18 predictive genes. The BSA sequencing results showed that Os02g39884 contained a nonsynonymous substitution mutation SNP (nsSNP), leading to the transformation of a residue from arginine (cGg) to glutamine (cAg); thus, Os02g39884 was inferred to be the candidate gene of qATGW2-2. The results of the qRT-PCR analysis also confirmed this. This paper provides important information for the rapid and accurate identification of the alkali-tolerant gene loci in rice.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01228-x.

Quantitative Trait Loci Controlling Agronomic and Biochemical Traits in Cannabis sativa

Understanding the genetic basis of complex traits is a fundamental goal of evolutionary genetics. Yet, the genetics controlling complex traits in many important species such as hemp (Cannabis sativa) remain poorly investigated. Because hemp’s change in legal status with the 2014 and 2018 U.S. Federal Farm Bills, interest in the genetics controlling its numerous agriculturally important traits has steadily increased. To better understand the genetics of agriculturally important traits in hemp, we developed an F₂ population by crossing two phenotypically distinct hemp cultivars (Carmagnola and USO31). Using whole-genome sequencing, we mapped quantitative trait loci (QTL) associated with variation in numerous agronomic and biochemical traits. A total of 69 loci associated with agronomic (34) and biochemical (35) trait variation were identified. We found that most QTL co-localized, suggesting that the phenotypic distinctions between Carmagnola and USO31 are largely controlled by a small number of loci. We identified TINY and olivetol synthase as candidate genes underlying co-localized QTL clusters for agronomic and biochemical traits, respectively. We functionally validated the olivetol synthase candidate by expressing the alleles in yeast. Gas chromatography-mass spectrometry assays of extracts from these yeast colonies suggest that the USO31 olivetol synthase is functionally less active and potentially explains why USO31 produces lower cannabinoids compared to Carmagnola. Overall, our results help modernize the genomic understanding of complex traits in hemp.

Characteristics of Metabolites by Seed-Specific Inhibition of FAD2 in Brassica napus L

Fatty acid desaturase-2 (FAD2) is a key enzyme in the production of polyunsaturated fatty acids in plants. RNAi technology can reduce the expression of FAD2 genes in Brassica napus seeds and acquire transgenic B. napus plants with a high oleic acid content, but the effect of seed-specific inhibition of FAD2 expression on B. napus seed metabolites is not clear. Here we use widely targeted metabolomics to investigate the metabolites of normal-oleic-acid rapeseed (OA) and high-oleic-acid rapeseed (HOA) seeds, resulting in a total of 726 metabolites being detected. Among them, 24 differential metabolites were significantly downregulated and 88 differential metabolites were significantly upregulated in HOA rapeseed. In further lipid profile experiments, more lipids in B. napus seeds were accurately quantified. The contents of glycolipids and phospholipids that contain C18:1 increased significantly and C18:2 decreased because FAD2 expression was inhibited. The changes in the expression of key genes in related pathways were also consistent with the changes in metabolites. The insertion site of the ihpRNA plant expression vector was reconfirmed through genomewide resequencing, and the transgenic event did not change the sequence of FAD2 genes. There was no significant difference in the germination rate and germination potential between OA and HOA rapeseed seeds because the seed-specific ihpRNA plant expression vector did not affect other stages of plant growth. This work provides a theoretical and practical guidance for subsequent molecular breeding of high OA B. napus.

Understanding Omics Driven Plant Improvement and de novo Crop Domestication: Some Examples

In the current era, one of biggest challenges is to shorten the breeding cycle for rapid generation of a new crop variety having high yield capacity, disease resistance, high nutrient content, etc. Advances in the "-omics" technology have revolutionized the discovery of genes and bio-molecules with remarkable precision, resulting in significant development of plant-focused metabolic databases and resources. Metabolomics has been widely used in several model plants and crop species to examine metabolic drift and changes in metabolic composition during various developmental stages and in response to stimuli. Over the last few decades, these efforts have resulted in a significantly improved understanding of the metabolic pathways of plants through identification of several unknown intermediates. This has assisted in developing several new metabolically engineered important crops with desirable agronomic traits, and has facilitated the de novo domestication of new crops for sustainable agriculture and food security. In this review, we discuss how "omics" technologies, particularly metabolomics, has enhanced our understanding of important traits and allowed speedy domestication of novel crop plants.

Genomic resources in plant breeding for sustainable agriculture

Climate change during the last 40 years has had a serious impact on agriculture and threatens global food and nutritional security. From over half a million plant species, cereals and legumes are the most important for food and nutritional security. Although systematic plant breeding has a relatively short history, conventional breeding coupled with advances in technology and crop management strategies has increased crop yields by 56 % globally between 1965-85, referred to as the Green Revolution. Nevertheless, increased demand for food, feed, fiber, and fuel necessitates the need to break existing yield barriers in many crop plants. In the first decade of the 21st century we witnessed rapid discovery, transformative technological development and declining costs of genomics technologies. In the second decade, the field turned towards making sense of the vast amount of genomic information and subsequently moved towards accurately predicting gene-to-phenotype associations and tailoring plants for climate resilience and global food security. In this review we focus on genomic resources, genome and germplasm sequencing, sequencing-based trait mapping, and genomics-assisted breeding approaches aimed at developing biotic stress resistant, abiotic stress tolerant and high nutrition varieties in six major cereals (rice, maize, wheat, barley, sorghum and pearl millet), and six major legumes (soybean, groundnut, cowpea, common bean, chickpea and pigeonpea). We further provide a perspective and way forward to use genomic breeding approaches including marker-assisted selection, marker-assisted backcrossing, haplotype based breeding and genomic prediction approaches coupled with machine learning and artificial intelligence, to speed breeding approaches. The overall goal is to accelerate genetic gains and deliver climate resilient and high nutrition crop varieties for sustainable agriculture.

QTL Mapping and Identification of Candidate Genes for Heat Tolerance at the Flowering Stage in Rice

High-temperature stress can cause serious abiotic damage that limits the yield and quality of rice. Heat tolerance (HT) during the flowering stage of rice is a key trait that can guarantee a high and stable yield under heat stress. HT is a complex trait that is regulated by multiple quantitative trait loci (QTLs); however, few underlying genes have been fine mapped and cloned. In this study, the F_2:3 population derived from a cross between Huanghuazhan (HHZ), a heat-tolerant cultivar, and 9311, a heat-sensitive variety, was used to map HT QTLs during the flowering stage in rice. A new major QTL, qHTT8, controlling HT was identified on chromosome 8 using the bulked-segregant analysis (BSA)-seq method. The QTL qHTT8 was mapped into the 3,555,000–4,520,000 bp, which had a size of 0.965 Mb. The candidate region of qHTT8 on chromosome 8 contained 65 predicted genes, and 10 putative predicted genes were found to be associated with abiotic stress tolerance. Furthermore, qRT-PCR was performed to analyze the differential expression of these 10 genes between HHZ and 9311 under high temperature conditions. LOC_Os08g07010 and LOC_Os08g07440 were highly induced in HHZ compared with 9311 under heat stress. Orthologous genes of LOC_Os08g07010 and LOC_Os08g07440 in plants played a role in abiotic stress, suggesting that they may be the candidate genes of qHTT8. Generally, the results of this study will prove useful for future efforts to clone qHTT8 and breed heat-tolerant varieties of rice using marker-assisted selection.

Association genetics of the parameters related to nitrogen use efficiency in Brassica juncea L

Genome wide association studies allowed prediction of 17 candidate genes for association with nitrogen use efficiency. Novel information obtained may provide better understanding of genomic controls underlying germplasm variations for this trait in Indian mustard. Nitrogen use efficiency (NUE) of Indian mustard (Brassica juncea (L.) Czern & Coss.) is low and most breeding efforts to combine NUE with crop performance have not succeeded. Underlying genetics also remain unexplored. We tested 92 SNP-genotyped inbred lines for yield component traits, N uptake efficiency (NUPEFF), nitrogen utilization efficiency (NUTEFF), nitrogen harvest index (NHI) and NUE for two years at two nitrogen doses (N_o without added N and N₁₀₀ added @100 kg/ha). Genotypes IC-2489-88, M-633, MCP-632, HUJM 1080, GR-325 and DJ-65 recorded high NUE at low N. These also showed improved crop performance under high N. One determinate mustard genotype DJ-113 DT-3 revealed maximum NUTEFF. Genome wide association studies (GWAS) facilitated recognition of 17 quantitative trait loci (QTLs). Environment specificity was high. B-genome chromosomes (B02, B03, B05, B07 and B08) harbored many useful loci. We also used regional association mapping (RAM) to supplement results from GWAS. Annotation of the genomic regions around peak SNPs helped to predict several gene candidates for root architecture, N uptake, assimilation and remobilization. CAT9 (At1g05940) was consistently envisaged for both NUE and NUPEFF. Major N transporter genes, NRT1.8 and NRT3.1 were predicted for explaining variation for NUTEFF and NUPEFF, respectively. Most significant amino acid transporter gene, AAP1 appeared associated with NUE under limited N conditions. All these candidates were predicted in the regions of high linkage disequilibrium. Sequence information of the predicted candidate genes will permit development of molecular markers to aid breeding for high NUE.

Biochemical and Genetic Approaches Improving Nitrogen Use Efficiency in Cereal Crops: A Review

Nitrogen is an essential nutrient required in large quantities for the proper growth and development of plants. Nitrogen is the most limiting macronutrient for crop production in most of the world's agricultural areas. The dynamic nature of nitrogen and its tendency to lose soil and environment systems create a unique and challenging environment for its proper management. Exploiting genetic diversity, developing nutrient efficient novel varieties with better agronomy and crop management practices combined with improved crop genetics have been significant factors behind increased crop production. In this review, we highlight the various biochemical, genetic factors and the regulatory mechanisms controlling the plant nitrogen economy necessary for reducing fertilizer cost and improving nitrogen use efficiency while maintaining an acceptable grain yield.

Genomic interventions for sustainable agriculture

Agricultural production faces a Herculean challenge to feed the increasing global population. Food production systems need to deliver more with finite land and water resources while exerting the least negative influence on the ecosystem. The unpredictability of climate change and consequent changes in pests/pathogens dynamics aggravate the enormity of the challenge. Crop improvement has made significant contributions towards food security, and breeding climate-smart cultivars are considered the most sustainable way to accelerate food production. However, a fundamental change is needed in the conventional breeding framework in order to respond adequately to the growing food demands. Progress in genomics has provided new concepts and tools that hold promise to make plant breeding procedures more precise and efficient. For instance, reference genome assemblies in combination with germplasm sequencing delineate breeding targets that could contribute to securing future food supply. In this review, we highlight key breakthroughs in plant genome sequencing and explain how the presence of these genome resources in combination with gene editing techniques has revolutionized the procedures of trait discovery and manipulation. Adoption of new approaches such as speed breeding, genomic selection and haplotype-based breeding could overcome several limitations of conventional breeding. We advocate that strengthening varietal release and seed distribution systems will play a more determining role in delivering genetic gains at farmer's field. A holistic approach outlined here would be crucial to deliver steady stream of climate-smart crop cultivars for sustainable agriculture.

Genome-wide identification of the peptide transporter family in rice and analysis of the PTR expression modulation in two near-isogenic lines with different nitrogen use efficiency

BACKGROUND

Nitrogen (N) is a major nutrient element for crop growth. In plants, the members of the peptide transporter (PTR) gene family may involve in nitrate uptake and transport. Here, we identified PTR gene family in rice and analyzed their expression profile in near-isogenic lines.

RESULTS

We identified 96, 85 and 78 PTR genes in Nipponbare, R498 and Oryza glaberrima, and the phylogenetic trees were similar in Asian cultivated rice and African cultivated rice. The number of PTR genes was higher in peanut (125) and soybean (127). The 521 PTR genes in rice, maize, sorghum, peanut, soybean and Arabidopsis could be classified into 4 groups, and their distribution was different between monocots and dicots. In Nipponbare genome, the 25 PTR genes were distributed in 5 segmental duplication regions on chromosome 1, 2, 3, 4, 5, 7, 8, 9, and 10. The PTR genes in rice have 0-11 introns and 1-12 exons, and 16 of them have the NPF (NRT1/PTR family) domain. The results of RNA-seq showed that the number of differentially expressed genes (DEGs) between NIL15 and NIL19 at three stages were 928, 1467, and 1586, respectively. Under low N conditions, the number of differentially expressed PTR genes increased significantly. The RNA-seq data was analyzed using WGCNA to predict the potential interaction between genes. We classified the genes with similar expression pattern into one module, and obtained 25 target modules. Among these modules, three modules may be involved in rice N uptake and utilization, especially the brown module, in which hub genes were annotated as protein kinase that may regulate rice N metabolism.

CONCLUSIONS

In this study, we comprehensively analyzed the PTR gene family in rice. 96 PTR genes were identified in Nippobare genome and 25 of them were located on five large segmental duplication regions. The Ka/Ks ratio indicated that many PTR genes had undergone positive selection. The RNA-seq results showed that many PTR genes were involved in rice nitrogen use efficiency (NUE), and protein kinases might play an important role in this process. These results provide a fundamental basis to improve the rice NUE via molecular breeding.

Fine mapping and gene cloning in the post-NGS era: advances and prospects

Improvement in traits of agronomic importance is the top breeding priority of crop improvement programs. Majority of these agronomic traits show complex quantitative inheritance. Identification of quantitative trait loci (QTLs) followed by fine mapping QTLs and cloning of candidate genes/QTLs is central to trait analysis. Advances in genomic technologies revolutionized our understanding of genetics of complex traits, and genomic regions associated with traits were employed in marker-assisted breeding or cloning of QTLs/genes. Next-generation sequencing (NGS) technologies have enabled genome-wide methodologies for the development of ultra-high-density genetic linkage maps in different crops, thus allowing placement of candidate loci within few kbs in genomes. In this review, we compare the marker systems used for fine mapping and QTL cloning in the pre- and post-NGS era. We then discuss how different NGS platforms in combination with advanced experimental designs have improved trait analysis and fine mapping. We opine that efficient genotyping/sequencing assays may circumvent the need for cumbersome procedures that were earlier used for fine mapping. A deeper understanding of the trait architectures of agricultural significance will be crucial to accelerate crop improvement.

Nitrogen Use Efficiency in Durum Wheat Under Different Nitrogen and Water Regimes in the Mediterranean Basin

Improving nitrogen use efficiency (NUE) represents one of the main goals to reduce N input in maximizing crop yield for sustainable agriculture. A NUE key strategy is the exploitation of genetic variation in available germplasm together with the understanding of molecular mechanisms governing this complex trait. Thus, NUE, its components, nitrogen uptake efficiency (NUpE) and nitrogen utilization efficiency (NUtE), and NUE-related traits heritability were evaluated in ancient (Cappelli, Capeiti, Russello, and Mazzancoio) and modern (Messapia, Tiziana, Svevo, and Normanno) wheat genotypes for tackling nitrogen (N) and/or water limitation in both growth chamber and field experiments. Our results exhibited a reduction of NUE, NUpE, and NUtE under water and combined (nitrogen + water) stress in all the genotypes, as expected. The contribution of genetic variability on phenotypic variation was significant for NUtE, harvest index, post-anthesis nitrogen uptake (PANU), and biomass production traits. Moreover, the stress tolerance indexes, calculated and bi-plotted for N and water stresses, exhibited two distinct clusters for many traits as then confirmed by principal component analysis. Although modern varieties showed higher crop yield and NUE under conventional N and water regimes, ancient varieties exhibited best performances to cope with both stresses, mainly under water limitation. Finally, the usage index, which takes into account total biomass increase, underlined that old genotypes were less affected by both stresses during crop cycle. In particular, these genotypes showed the best performances for NUE and its components under both stresses at stem elongation and milk ripening as shown also by PANU. In addition, at these stages, nitrate and ammonium transporter gene expressions in the root were performed, showing the highest activity in ancient varieties. In conclusion, the identification of NUE traits during a specific crop cycle stage, under both N and water limitation, will help in the breeding of more resilient varieties in Mediterranean sustainable agriculture by reducing N supply.

Fine mapping and identification of the fuzzless gene GaFzl in DPL972 (Gossypium arboreum)

The fuzzless gene GaFzl was fine mapped to a 70-kb region containing a GIR1 gene, Cotton_A_11941, responsible for the fuzzless trait in Gossypium arboreum DPL972. Cotton fiber is the most important natural textile resource. The fuzzless mutant DPL972 (Gossypium arboreum) provides a useful germplasm resource to explore the molecular mechanism underlying fiber and fuzz initiation and development. In our previous research, the fuzzless gene in DPL972 was identified as a single dominant gene and named GaFzl. In the present study, we fine mapped this gene using F₂ and BC₁ populations. By combining traditional map-based cloning and next-generation sequencing, we mapped GaFzl to a 70-kb region containing seven annotated genes. RNA-Sequencing and re-sequencing analysis narrowed these candidates to two differentially expressed genes, Cotton_A_11941 and Cotton_A_11942. Sequence alignment uncovered no variation in coding or promoter regions of Cotton_A_11942 between DPL971 and DPL972, whereas two single-base mutations in the promoter region and a TTG insertion in the coding region were detected in Cotton_A_11941 in DPL972. Cotton_A_11941 encoding a homologous gene of GIR1 (GLABRA2-interacting repressor) in Arabidopsis thaliana is thus the candidate gene most likely responsible for the fuzzless trait in DPL972. Our findings should lead to a better understanding of cotton fuzz formation, thereby accelerating marker-assisted selection during cotton breeding.

RDWN6XB, a major quantitative trait locus positively enhances root system architecture under nitrogen deficiency in rice

BACKGROUND

Nitrogen (N) is a major input cost in rice production, in addition to causing severe pollution to agricultural and ecological environments. Root dry weight has been considered the most important component related to crop yields than the other root traits. Therefore, development of rice varieties/lines with low input of N fertilizer and higher root traits are essential for sustainable rice production.

RESULTS

In this context, a main effect quantitative trait locus qRDWN6^XB on the long arm of chromosome 6 which positively confers tolerance to N deficiency in the Indica rice variety XieqingzaoB, was identified using a chromosomal segment substitution line (CSSL) population. qRDWN6^XB was determined to be located near marker InD90 on chromosome 6 based on association analysis of phenotype data from three N levels and 120 polymorphic molecular markers. The target chromosomal segment substitution line CSSL45, which has the higher root dry weight (RDW) than indica cultivar Zhonghui9308 and carry qRDWN6^XB, was selected for further study. A BC₅F_2:3 population derived from a cross between CSSL45 and Zhonghui9308 was constructed. To fine-map qRDWN6^XB, we used the homozygous recombinant plants and ultimately this locus was narrowed to a 52.3-kb between markers ND-4 and RM19771, which contains nine candidate genes in this region. One of these genes, LOC_Os06g15910 as a potassium transporter was considered a strong candidate gene for the RDWN6^XB locus.

CONCLUSIONS

The identification of qRDWN6^XB provides a new genetic resource for breeding rice varieties and a starting point to improve grain yield despite the decreased input of N fertilizers. The newly developed and tightly linked InDel marker ND-4 will be useful to improve the root system architecture under low N by marker-assisted selection (MAS) in rice breeding programs.

Whole Genome Resequencing from Bulked Populations as a Rapid QTL and Gene Identification Method in Rice

Most Quantitative Trait Loci (QTL) and gene isolation approaches, such as positional- or map-based cloning, are time-consuming and low-throughput methods. Understanding and detecting the genetic material that controls a phenotype is a key means to functionally analyzing genes as well as to enhance crop agronomic traits. In this regard, high-throughput technologies have great prospects for changing the paradigms of DNA marker revealing, genotyping, and for discovering crop genetics and genomic study. Bulk segregant analysis, based on whole genome resequencing approaches, permits the rapid isolation of the genes or QTL responsible for the causative mutation of the phenotypes. MutMap, MutMap Gap, MutMap+, modified MutMap, and QTL-seq methods are among those approaches that have been confirmed to be fruitful gene mapping approaches for crop plants, such as rice, irrespective of whether the characters are determined by polygenes. As a result, in the present study we reviewed the progress made by all these methods to identify QTL or genes in rice.