To clone or not to clone plant QTLs: present and future challenges

QTLs and Genes for Salt Stress Tolerance: A Journey from Seed to Seed Continued

Rice (Oryza sativa L.) is a crucial crop contributing to global food security; however, its production is susceptible to salinity, a significant abiotic stressor that negatively impacts plant germination, vigour, and yield, degrading crop production. Due to the presence of exchangeable sodium ions (Na+), the affected plants sustain two-way damage resulting in initial osmotic stress and subsequent ion toxicity in the plants, which alters the cell's ionic homeostasis and physiological status. To adapt to salt stress, plants sense and transfer osmotic and ionic signals into their respective cells, which results in alterations of their cellular properties. No specific Na+ sensor or receptor has been identified in plants for salt stress other than the SOS pathway. Increasing productivity under salt-affected soils necessitates conventional breeding supplemented with biotechnological interventions. However, knowledge of the genetic basis of salinity stress tolerance in the breeding pool is somewhat limited because of the complicated architecture of salinity stress tolerance, which needs to be expanded to create salt-tolerant variants with better adaptability. A comprehensive study that emphasizes the QTLs, genes and governing mechanisms for salt stress tolerance is discussed in the present study for future research in crop improvement.

Hotspot Regions of Quantitative Trait Loci and Candidate Genes for Ear-Related Traits in Maize: A Literature Review

In this study, hotspot regions, QTL clusters, and candidate genes for eight ear-related traits of maize (ear length, ear diameter, kernel row number, kernel number per row, kernel length, kernel width, kernel thickness, and 100-kernel weight) were summarized and analyzed over the past three decades. This review aims to (1) comprehensively summarize and analyze previous studies on QTLs associated with these eight ear-related traits and identify hotspot bin regions located on maize chromosomes and key candidate genes associated with the ear-related traits and (2) compile major and stable QTLs and QTL clusters from various mapping populations and mapping methods and techniques providing valuable insights for fine mapping, gene cloning, and breeding for high-yield and high-quality maize. Previous research has demonstrated that QTLs for ear-related traits are distributed across all ten chromosomes in maize, and the phenotypic variation explained by a single QTL ranged from 0.40% to 36.76%. In total, 23 QTL hotspot bins for ear-related traits were identified across all ten chromosomes. The most prominent hotspot region is bin 4.08 on chromosome 4 with 15 QTLs related to eight ear-related traits. Additionally, this study identified 48 candidate genes associated with ear-related traits. Out of these, five have been cloned and validated, while twenty-eight candidate genes located in the QTL hotspots were defined by this study. This review offers a deeper understanding of the advancements in QTL mapping and the identification of key candidates associated with eight ear-related traits. These insights will undoubtedly assist maize breeders in formulating strategies to develop higher-yield maize varieties, contributing to global food security.

Molecular mechanisms underpinning quantitative resistance to Phytophthora sojae in Glycine max using a systems genomics approach

Expression of quantitative disease resistance in many host-pathogen systems is controlled by genes at multiple loci, each contributing a small effect to the overall response. We used a systems genomics approach to study the molecular underpinnings of quantitative disease resistance in the soybean-Phytophthora sojae pathosystem, incorporating expression quantitative trait loci (eQTL) mapping and gene co-expression network analysis to identify the genes putatively regulating transcriptional changes in response to inoculation. These findings were compared to previously mapped phenotypic (phQTL) to identify the molecular mechanisms contributing to the expression of this resistance. A subset of 93 recombinant inbred lines (RILs) from a Conrad × Sloan population were inoculated with P. sojae isolate 1.S.1.1 using the tray-test method; RNA was extracted, sequenced, and the normalized read counts were genetically mapped from tissue collected at the inoculation site 24 h after inoculation from both mock and inoculated samples. In total, more than 100,000 eQTLs were mapped. There was a switch from predominantly cis-eQTLs in the mock treatment to an almost entirely nonoverlapping set of predominantly trans-eQTLs in the inoculated treatment, where greater than 100-fold more eQTLs were mapped relative to mock, indicating vast transcriptional reprogramming due to P. sojae infection occurred. The eQTLs were organized into 36 hotspots, with the four largest hotspots from the inoculated treatment corresponding to more than 70% of the eQTLs, each enriched for genes within plant-pathogen interaction pathways. Genetic regulation of trans-eQTLs in response to the pathogen was predicted to occur through transcription factors and signaling molecules involved in plant-pathogen interactions, plant hormone signal transduction, and MAPK pathways. Network analysis identified three co-expression modules that were correlated with susceptibility to P. sojae and associated with three eQTL hotspots. Among the eQTLs co-localized with phQTLs, two cis-eQTLs with putative functions in the regulation of root architecture or jasmonic acid, as well as the putative master regulators of an eQTL hotspot nearby a phQTL, represent candidates potentially underpinning the molecular control of these phQTLs for resistance.

Characterization and fine mapping analysis of a major stable QTL qKnps-4A for kernel number per spike in wheat

KEY MESSAGE

A major stable QTL for kernel number per spike was narrowed down to a 2.19-Mb region containing two potential candidate genes, and its effects on yield-related traits were characterized. Kernel number per spike (KNPS) in wheat is a key yield component. Dissection and characterization of major stable quantitative trait loci (QTLs) for KNPS would be of considerable value for the genetic improvement of yield potential using molecular breeding technology. We had previously reported a major stable QTL controlling KNPS, qKnps-4A. In the current study, primary fine-mapping analysis, based on the primary mapping population, located qKnps-4A to an interval of approximately 6.8-Mb from 649.0 to 655.8 Mb on chromosome 4A refering to 'Kenong 9204' genome. Further fine-mapping analysis based on a secondary mapping population narrowed qKnps-4A to an approximately 2.19-Mb interval from 653.72 to 655.91 Mb. Transcriptome sequencing, gene function annotation analysis and homologous gene related reports showed that TraesKN4A01HG38570 and TraesKN4A01HG38590 were most likely to be candidate genes of qKnps-4A. Phenotypic analysis based on paired near-isogenic lines in the target region showed that qKnps-4A increased KNPS mainly by increasing the number of central florets per spike. We also evaluated the effects of qKnps-4A on other yield-related traits. Moreover, we dissected the QTL cluster of qKnps-4A and qTkw-4A and proved that the phenotypic effects were probably due to close linkage of two or more genes rather than pleiotropic effects of a single gene. This study provides molecular marker resource for wheat molecular breeding designed to improve yield potential, and lay the foundation for gene functional analysis of qKnps-4A.

Rapid identification of a major locus qPRL-C06 affecting primary root length in Brassica napus by QTL-seq

BACKGROUND AND AIMS

Brassica napus is one of the most important oilseed crops worldwide. Seed yield of B. napus significantly correlates with the primary root length (PRL). The aims of this study were to identify quantitative trait loci (QTLs) for PRL in B. napus.

METHODS

QTL-seq and conventional QTL mapping were jointly used to detect QTLs associated with PRL in a B. napus double haploid (DH) population derived from a cross between 'Tapidor' and 'Ningyou 7'. The identified major locus was confirmed and resolved by an association panel of B. napus and an advanced backcross population. RNA-seq analysis of two long-PRL lines (Tapidor and TN20) and two short-PRL lines (Ningyou 7 and TN77) was performed to identify differentially expressed genes in the primary root underlying the target QTLs.

KEY RESULTS

A total of 20 QTLs impacting PRL in B. napus grown at a low phosphorus (P) supply were found by QTL-seq. Eight out of ten QTLs affecting PRL at a low P supply discovered by conventional QTL mapping could be detected by QTL-seq. The locus qPRL-C06 identified by QTL-seq was repeatedly detected at both an optimal P supply and a low P supply by conventional QTL mapping. This major constitutive QTL was further confirmed by regional association mapping. qPRL-C06 was delimited to a 0.77 Mb genomic region on chromosome C06 using an advanced backcross population. A total of 36 candidate genes within qPRL-C06 were identified that showed variations in coding sequences and/or exhibited significant differences in mRNA abundances in primary root between the long-PRL and short-PRL lines, including five genes involved in phytohormone biosynthesis and signaling.

CONCLUSIONS

These results both demonstrate the power of the QTL-seq in rapid QTL detection for root traits and will contribute to marker-assisted selective breeding of B. napus cultivars with increased PRL.

Molecular mapping of genomic regions and identification of possible candidate genes associated with gynoecious sex expression in bitter gourd

Bitter gourd is an important vegetable crop grown throughout the tropics mainly because of its high nutritional value. Sex expression and identification of gynoecious trait in cucurbitaceous vegetable crops has facilitated the hybrid breeding programme in a great way to improve productivity. In bitter gourd, gynoecious sex expression is poorly reported and detailed molecular pathways involve yet to be studied. The present experiment was conducted to study the inheritance, identify the genomic regions associated with gynoecious sex expression and to reveal possible candidate genes through QTL-seq. Segregation for the gynoecious and monoecious sex forms in the F₂ progenies indicated single recessive gene controlling gynoecious sex expression in the genotype, PVGy-201. Gynoecious parent, PVGy-201, Monoecious parent, Pusa Do Mausami (PDM), and two contrasting bulks were constituted for deep-sequencing. A total of 10.56, 23.11, 15.07, and 19.38 Gb of clean reads from PVGy-201, PDM, gynoecious bulk and monoecious bulks were generated. Based on the ΔSNP index, 1.31 Mb regions on the chromosome 1 was identified to be associated with gynoecious sex expression in bitter gourd. In the QTL region 293,467 PVGy-201 unique variants, including SNPs and indels, were identified. In the identified QTL region, a total of 1019 homozygous variants were identified between PVGy1 and PDM genomes and 71 among them were non-synonymous variants (SNPS and INDELs), out of which 11 variants (7 INDELs, 4 SNPs) were classified as high impact variants with frame shift/stop gain effect. In total twelve genes associated with male and female gametophyte development were identified in the QTL-region. Ethylene-responsive transcription factor 12, Auxin response factor 6, Copper-transporting ATPase RAN1, CBL-interacting serine/threonine-protein kinase 23, ABC transporter C family member 2, DEAD-box ATP-dependent RNA helicase 1 isoform X2, Polygalacturonase QRT3-like isoform X2, Protein CHROMATIN REMODELING 4 were identified with possible role in gynoecious sex expression. Promoter region variation in 8 among the 12 genes indicated their role in determining gynoecious sex expression in bitter gourd genotype, DBGy-1. The findings in the study provides insight about sex expression in bitter gourd and will facilitate fine mapping and more precise identification of candidate genes through their functional validation.

QTL analysis of important agronomic traits and metabolites in foxtail millet (Setaria italica) by RIL population and widely targeted metabolome

As a bridge between genome and phenotype, metabolome is closely related to plant growth and development. However, the research on the combination of genome, metabolome and multiple agronomic traits in foxtail millet (Setaria italica) is insufficient. Here, based on the linkage analysis of 3,452 metabolites via with high-quality genetic linkage maps, we detected a total of 1,049 metabolic quantitative trait loci (mQTLs) distributed in 11 hotspots, and 28 metabolite-related candidate genes were mined from 14 mQTLs. In addition, 136 single-environment phenotypic QTL (pQTLs) related to 63 phenotypes were identified by linkage analysis, and there were 12 hotspots on these pQTLs. We futher dissected 39 candidate genes related to agronomic traits through metabolite-phenotype correlation and gene function analysis, including Sd1 semidwarf gene, which can affect plant height by regulating GA synthesis. Combined correlation network and QTL analysis, we found that flavonoid-lignin pathway maybe closely related to plant architecture and yield in foxtail millet. For example, the correlation coefficient between apigenin 7-rutinoside and stem diameter reached 0.98, and they were co-located at 41.33-44.15 Mb of chromosome 5, further gene function analysis revealed that 5 flavonoid pathway genes, as well as Sd1, were located in this interval . Therefore, the correlation and co-localization between flavonoid-lignins and plant architecture may be due to the close linkage of their regulatory genes in millet. Besides, we also found that a combination of genomic and metabolomic for BLUP analysis can better predict plant agronomic traits than genomic or metabolomic data, independently. In conclusion, the combined analysis of mQTL and pQTL in millet have linked genetic, metabolic and agronomic traits, and is of great significance for metabolite-related molecular assisted 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.

Genome-wide meta-analysis of QTL for morphological related traits of flag leaf in bread wheat

Flag leaf is an important organ for photosynthesis of wheat plants, and a key factor affecting wheat yield. In this study, quantitative trait loci (QTL) for flag leaf morphological traits in wheat reported since 2010 were collected to investigate the genetic mechanism of these traits. Integration of 304 QTLs from various mapping populations into a high-density consensus map composed of various types of molecular markers as well as QTL meta-analysis discovered 55 meta-QTLs (MQTL) controlling morphological traits of flag leaves, of which 10 MQTLs were confirmed by GWAS. Four high-confidence MQTLs (MQTL-1, MQTL-11, MQTL-13, and MQTL-52) were screened out from 55 MQTLs, with an average confidence interval of 0.82 cM and a physical distance of 9.4 Mb, according to the definition of hcMQTL. Ten wheat orthologs from rice (7) and Arabidopsis (3) that regulated leaf angle, development and morphogenesis traits were identified in the hcMQTL region using comparative genomics, and were speculated to be potential candidate genes regulating flag leaf morphological traits in wheat. The results from this study provides valuable information for fine mapping and molecular markers assisted selection to improve morphological characters in wheat flag leaf.

Identification and characterization of genes for drought tolerance in upland rice cultivar 'Banglami' of North East India

INTRODUCTION

Rice is a major crop in Assam, North East (NE) India. The rice accessions belonging to NE India possess unique traits of breeder's interest, i.e., tolerant to biotic and abiotic stresses. In the present research programme, the stress responsive genes were identified within the QTLs associated with drought tolerance. The differential expression profiling of genes were performed under drought stress and control conditions. Thus, the 'candidate genes' associated with drought tolerance were recognised and may be deployed in a breeding programme.

METHODS AND RESULTS

A drought-tolerant traditional rice cultivar, Banglami, was crossed with a high-yielding, drought-susceptible variety, Ranjit. The mapping population (F₄) was raised through the single seed descent (SSD) method and used in QTL analysis. Under drought stress, a total of 4752 genes were identified through in-silico mining of QTLs. Among these, only 21 genes primarily associated with the stress response. The maximum of four stress-responsive genes were located within the QTLs, qNOG12.1 and qGY1.1. However, under control conditions, 2088 genes were identified, out of which, only 15 were categorised as the major stress responsive genes. The functional characterization of genes recognized 24 different types of proteins. Among these, peroxidase and heat shock proteins (Hsp) are the principal proteins encoded during stress. In addition to that, OsbZIP23, inorganic pyrophosphatase, universal stress protein, serine threonine kinase, NADPH oxidoreductase, and proteins belonging to the ABC1 family were also produced during stress condition. The differential expression profiling showed a profound expression pattern of three candidate genes under drought stress condition, i.e., OsI_32199 (Ascorbate peroxidase), OsI_37694 (Universal stress protein) and OsI_32167 (Heat shock protein 81 - 1).

CONCLUSION

The novel candidate genes identified for drought tolerance, may be used in the breeding programme for the development of 'climate smart rice varieties'.

Testing candidate genes linked to corolla shape variation of a pollinator shift in Rhytidophyllum (Gesneriaceae)

Floral adaptations to specific pollinators like corolla shape variation often result in reproductive isolation and thus speciation. But despite their ecological importance, the genetic bases of corolla shape transitions are still poorly understood, especially outside model species. Hence, our goal was to identify candidate genes potentially involved in corolla shape variation between two closely related species of the Rhytidophyllum genus (Gesneriaceae family) from the Antilles with contrasting pollination strategies. Rhytidophyllum rupincola has a tubular corolla and is strictly pollinated by hummingbirds, whereas R. auriculatum has more open flowers and is pollinated by hummingbirds, bats, and insects. We surveyed the literature and used a comparative transcriptome sequence analysis of synonymous and non-synonymous nucleotide substitutions to obtain a list of genes that could explain floral variation between R. auriculatum and R. rupincola. We then tested their association with corolla shape variation using QTL mapping in a F₂ hybrid population. Out of 28 genes tested, three were found to be good candidates because of a strong association with corolla shape: RADIALIS, GLOBOSA, and JAGGED. Although the role of these genes in Rhytidophyllum corolla shape variation remains to be confirmed, these findings are a first step towards identifying the genes that have been under selection by pollinators and thus involved in reproductive isolation and speciation in this genus.

Quantitative Trait Locus Mapping and Identification of Candidate Genes Controlling Bolting in Spinach (Spinacia oleracea L.)

Spinach is a typical light-sensitive plant. Long days can induce early bolting, thereby influencing the regional adaptation, quality, and vegetative yield of spinach. However, the genes and genetic mechanisms underlying this trait in spinach remain unclear. In this study, a major quantitative trait locus (QTL) qBT1.1, was mapped on chromosome 1 using a BC₁ population (BC_1a) derived from 12S3 (late-bolting recurrent lines) and 12S4 (early bolting lines) with specific-locus amplified fragment (SLAF) markers and Kompetitive Allele Specific PCR (KASP) markers. The qBT1.1 locus was further confirmed and narrowed down to 0.56 Mb by using a large BC₁ (BC_1b) population and an F₂ population using the above KASP markers and the other 20 KASP markers. Within this region, two putative genes, namely, SpFLC and SpCOL14, were of interest due to their relationship with flower regulatory pathways. For SpCOL14, we found multiple variations in the promoter, and the expression pattern was consistent with bolting stages. SpCOL14 was therefore assumed to the best candidate gene for bolting. Overall, our results provide a basis for understanding the molecular mechanisms of bolting in spinach and contribute to the breeding of diverse spinach germplasms for adaptation to different regions.

Omics: a tool for resilient rice genetic improvement strategies

Rice is pivotal pyramid of about half of the world population. Bearing small genome size and worldwide utmost food crop rice has been known as ideal cereal crop for genome research. Currently, decreasing water table and soil fatigue are big challenges and intense consequences in changing climate. Whole sequenced genome of rice sized 389 Mb of which 95% is covered with excellent mapping order. Sequenced rice genome helps in molecular biology and transcriptomics of cereals as it provides whole genome sequence of indica and japonica sub species. Through rice genome sequencing and functional genomics, QTLs or genes, genetic variability and halophyte blocks for agronomic characters were identified which have proved much more useful in molecular breeding and direct selection. There are different numbers of genes or QTLs identified for yield related traits i.e., 6 QTLs/genes for plant architecture, 6 for panicle characteristics, 4 for grain number, 1 gene/QTL for tiller, HGW, grain filling and shattering. QTLS/genes for grain quality, biotic stresses and for abiotic stresses are 7, 23 and 13 respectively. Low yield, inferior quality and susceptibility to biotic and abiotic stresses of a crop is due to narrow genetic background of new evolving rice verities. Wild rice provides genetic resources for improvement of these characters, molecular and genomics tool at different stages can overcome these stresses and improve yield and quality of rice crop.

Fine Mapping and Functional Analysis of the Gene PcTYR, Involved in Control of Cap Color of Pleurotus cornucopiae

Oyster mushrooms have a high biological efficiency and are easy to cultivate, which is why they are produced all over the world. Cap color is an important commercial trait for oyster mushrooms. Little is known about the genetic mechanism of the cap color trait in oyster mushrooms, which limits molecular breeding for the improvement of cap color-type cultivars. In this study, a 0.8-Mb major quantitative trait locus (QTL) region controlling cap color in the oyster mushroom Pleurotus cornucopiae was mapped on chromosome 7 through bulked-segregant analysis sequencing (BSA-seq) and extreme-phenotype genome-wide association studies (XP-GWAS). Candidate genes were further selected by comparative transcriptome analysis, and a tyrosinase gene (PcTYR) was identified as the highest-confidence candidate gene. Overexpression of PcTYR resulted in a significantly darker cap color, while the cap color of RNA interference (RNAi) strains for this gene was significantly lighter than that of the wild-type (WT) strains, suggesting that PcTYR plays an essential role in cap color formation. This is the first report about fine mapping and functional verification of a gene controlling cap color in oyster mushrooms. This will enhance our understanding of the genetic basis for cap color formation in oyster mushrooms and will facilitate molecular breeding for cap color. IMPORTANCE Oyster mushrooms are widely cultivated and consumed over the world for their easy cultivation and high biological efficiency (mushroom fresh weight/substrate dry weight × 100%). Fruiting bodies with dark caps are more and more popular according to consumer preferences, but dark varieties are rarely seen on the market. Little is known about the genetic mechanism of the cap color trait in oyster mushrooms, which limits molecular breeding for the improvement of cap color-type cultivars. A major QTL of cap color in oyster mushroom P. cornucopiae was fine mapped by using bulked-segregant analysis (BSA) and extreme-phenotype genome-wide association study (XP-GWAS) analysis. A candidate gene PcTYR coding tyrosinase was further identified with the help of comparative transcriptome analysis. qPCR analysis and genetic transformation tests proved that PcTYR played an essential role in cap color formation. This study will contribute to revealing the genetic mechanism of cap color formation in mushrooms, thereby facilitating molecular breeding for cap color trait.

Identifying Quantitative Trait Loci and Candidate Genes Conferring Resistance to Soybean Mosaic Virus SC7 by Quantitative Trait Loci-Sequencing in Soybean

Soybean mosaic virus (SMV) is detrimental to soybean (Glycine max) breeding, seed quality, and yield worldwide. Improving the basic resistance of host plants is the most effective and economical method to reduce damage from SMV. Therefore, it is necessary to identify and clone novel SMV resistance genes. Here, we report the characterization of two soybean cultivars, DN50 and XQD, with different levels of resistance to SMV. Compared with XQD, DN50 exhibits enhanced resistance to the SMV strain SC7. By combining bulked-segregant analysis (BSA)-seq and fine-mapping, we identified a novel resistance locus, R _SMV -11, spanning an approximately 207-kb region on chromosome 11 and containing 25 annotated genes in the reference Williams 82 genome. Of these genes, we identified eleven with non-synonymous single-nucleotide polymorphisms (SNPs) or insertion-deletion mutations (InDels) in their coding regions between two parents. One gene, GmMATE68 (Glyma.11G028900), harbored a frameshift mutation. GmMATE68 encodes a multidrug and toxic compound extrusion (MATE) transporter that is expressed in all soybean tissues and is induced by SC7. Given that MATE transporter families have been reported to be linked with plant disease resistance, we suggest that GmMATE68 is responsible for SC7 resistance in DN50. Our results reveal a novel SMV-resistance locus, improving understanding of the genetics of soybean disease resistance and providing a potential new tool for marker-assisted selection breeding in soybean.

Perspectives and recent progress of genome-wide association studies (GWAS) in fruits

BACKGROUND

Earlier next-generation sequencing technologies are being vastly used to explore, administer, and investigate the gene space with accurate profiling of nucleotide variations in the germplasm. OVERVIEW AND PROGRESS: Recently, novel advancements in high-throughput sequencing technologies allow a genotyping-by-sequencing approach that has opened up new horizons for extensive genotyping exploiting single-nucleotide-polymorphisms (SNPs). This method acts as a bridge to support and minimize a genotype to phenotype gap allowing genetic selection at the genome-wide level, named genomic selection that could facilitate the selection of traits also in the pomology sector. In addition to this, genome-wide genotyping is a prerequisite for genome-wide association studies that have been used successfully to discover the genes, which control polygenic traits including the genetic loci, associated with the trait of interest in fruit crops.

AIMS AND PROSPECTS

This review article emphasizes the role of genome-wide approaches to unlock and explore the genetic potential along with the detection of SNPs affecting the phenotype of fruit crops and highlights the prospects of genome-wide association studies in fruits.

Whole-Genome Sequencing of 117 Chromosome Segment Substitution Lines for Genetic Analyses of Complex Traits in Rice

Rice is one of the most important food crops in Asia. Genetic analyses of complex traits and molecular breeding studies in rice greatly rely on the construction of various genetic populations. Chromosome segment substitution lines (CSSLs) serve as a powerful genetic population for quantitative trait locus (QTL) mapping in rice. Moreover, CSSLs containing target genomic regions can be used as improved varieties in rice breeding. In this study, we developed a set of CSSLs consisting of 117 lines derived from the recipient 'Huanghuazhan' (HHZ) and the donor 'Basmati Surkb 89-15' (BAS). The 117 lines were extensively genotyped by whole-genome resequencing, and a high-density genotype map was constructed for the CSSL population. The 117 CSSLs covered 99.78% of the BAS genome. Each line contained a single segment, and the average segment length was 6.02 Mb. Using the CSSL population, we investigated three agronomic traits in Shanghai and Hangzhou, China, and a total of 25 QTLs were detected in both environments. Among those QTLs, we found that RFT1 was the causal gene for heading date variance between HHZ and BAS. RFT1 from BAS was found to contain a loss-of-function allele based on yeast two-hybrid assay, and its causal variation was a P to S change in the 94th amino acid of the RFT1 protein. The combination of high-throughput genotyping and marker-assisted selection (MAS) is a highly efficient way to construct CSSLs in rice, and extensively genotyped CSSLs will be a powerful tool for the genetic mapping of agronomic traits and molecular breeding for target QTLs/genes.

Entailing the Next-Generation Sequencing and Metabolome for Sustainable Agriculture by Improving Plant Tolerance

Crop production is a serious challenge to provide food for the 10 billion individuals forecasted to live across the globe in 2050. The scientists' emphasize establishing an equilibrium among diversity and quality of crops by enhancing yield to fulfill the increasing demand for food supply sustainably. The exploitation of genetic resources using genomics and metabolomics strategies can help generate resilient plants against stressors in the future. The innovation of the next-generation sequencing (NGS) strategies laid the foundation to unveil various plants' genetic potential and help us to understand the domestication process to unmask the genetic potential among wild-type plants to utilize for crop improvement. Nowadays, NGS is generating massive genomic resources using wild-type and domesticated plants grown under normal and harsh environments to explore the stress regulatory factors and determine the key metabolites. Improved food nutritional value is also the key to eradicating malnutrition problems around the globe, which could be attained by employing the knowledge gained through NGS and metabolomics to achieve suitability in crop yield. Advanced technologies can further enhance our understanding in defining the strategy to obtain a specific phenotype of a crop. Integration among bioinformatic tools and molecular techniques, such as marker-assisted, QTLs mapping, creation of reference genome, de novo genome assembly, pan- and/or super-pan-genomes, etc., will boost breeding programs. The current article provides sequential progress in NGS technologies, a broad application of NGS, enhancement of genetic manipulation resources, and understanding the crop response to stress by producing plant metabolites. The NGS and metabolomics utilization in generating stress-tolerant plants/crops without deteriorating a natural ecosystem is considered a sustainable way to improve agriculture production. This highlighted knowledge also provides useful research that explores the suitable resources for agriculture sustainability.

Recent Advances for Drought Stress Tolerance in Maize (Zea mays L.): Present Status and Future Prospects

Drought stress has severely hampered maize production, affecting the livelihood and economics of millions of people worldwide. In the future, as a result of climate change, unpredictable weather events will become more frequent hence the implementation of adaptive strategies will be inevitable. Through utilizing different genetic and breeding approaches, efforts are in progress to develop the drought tolerance in maize. The recent approaches of genomics-assisted breeding, transcriptomics, proteomics, transgenics, and genome editing have fast-tracked enhancement for drought stress tolerance under laboratory and field conditions. Drought stress tolerance in maize could be considerably improved by combining omics technologies with novel breeding methods and high-throughput phenotyping (HTP). This review focuses on maize responses against drought, as well as novel breeding and system biology approaches applied to better understand drought tolerance mechanisms and the development of drought-tolerant maize cultivars. Researchers must disentangle the molecular and physiological bases of drought tolerance features in order to increase maize yield. Therefore, the integrated investments in field-based HTP, system biology, and sophisticated breeding methodologies are expected to help increase and stabilize maize production in the face of climate change.

Combining QTL-seq and linkage mapping to uncover the genetic basis of single vs. paired spikelets in the advanced populations of two-ranked maize×teosinte

BACKGROUND

Teosinte ear bears single spikelet, whereas maize ear bears paired spikelets, doubling the number of grains in each cupulate during maize domestication. In the past 20 years, genetic analysis of single vs. paired spikelets (PEDS) has been stagnant. A better understanding of genetic basis of PEDS could help fine mapping of quantitative trait loci (QTL) and cloning of genes.

RESULTS

In this study, the advanced mapping populations (BC₃F₂ and BC₄F₂) of maize × teosinte were developed by phenotypic recurrent selection. Four genomic regions associated with PEDS were detected using QTL-seq, located on 194.64-299.52 Mb, 0-162.80 Mb, 12.82-97.17 Mb, and 125.06-157.01 Mb of chromosomes 1, 3, 6, and 8, respectively. Five QTL for PEDS were identified in the regions of QTL-seq using traditional QTL mapping. Each QTL explained 1.12-38.05% of the phenotypic variance (PVE); notably, QTL qPEDS3.1 with the average PVE of 35.29% was identified in all tests. Moreover, 14 epistatic QTL were detected, with the total PVE of 47.57-66.81% in each test. The QTL qPEDS3.1 overlapped with, or was close to, one locus of 7 epistatic QTL. Near-isogenic lines (NILs) of QTL qPEDS1.1, qPEDS3.1, qPEDS6.1, and qPEDS8.1 were constructed. All individuals of NIL-qPEDS6.1(MT1) and NIL-qPEDS8.1(MT1) showed paired spikelets (PEDS = 0), but the flowering time was 7 days shorter in the NIL-qPEDS8.1(MT1). The ratio of plants with PEDS > 0 was low (1/18 to 3/18) in the NIL-qPEDS1.1(MT1) and NIL-qPEDS3.1(MT1), maybe due to the epistatic effect.

CONCLUSION

Our results suggested that major QTL, minor QTL, epistasis and photoperiod were associated with the variation of PEDS, which help us better understand the genetic basis of PEDS and provide a genetic resource for fine mapping of QTL.

Nucleotide Diversity of the Maize ZmCNR13 Gene and Association With Ear Traits

The maize (Zea mays L.) ZmCNR13 gene, encoding a protein of fw2.2-like (FWL) family, has been demonstrated to be involved in cell division, expansion, and differentiation. In the present study, the genomic sequences of the ZmCNR13 locus were re-sequenced in 224 inbred lines, 56 landraces and 30 teosintes, and the nucleotide polymorphism and selection signature were estimated. A total of 501 variants, including 415 SNPs and 86 Indels, were detected. Among them, 51 SNPs and 4 Indels were located in the coding regions. Although neutrality tests revealed that this locus had escaped from artificial selection during the process of maize domestication, the population of inbred lines possesses lower nucleotide diversity and decay of linkage disequilibrium. To estimate the association between sequence variants of ZmCNR13 and maize ear characteristics, a total of ten ear-related traits were obtained from the selected inbred lines. Four variants were found to be significantly associated with six ear-related traits. Among them, SNP2305, a non-synonymous mutation in exon 2, was found to be associated with ear weight, ear grain weight, ear diameter and ear row number, and explained 4.59, 4.61, 4.31, and 8.42% of the phenotypic variations, respectively. These results revealed that natural variations of ZmCNR13 might be involved in ear development and can be used in genetic improvement of maize ear-related traits.

Mapping of QTL for agronomic traits using high-density SNPs with an RIL population in maize

BACKGROUND

Genome wide association studies (GWAS) have been widely used to identify QTLs underlying quantitative traits in humans and animals, and they have also become a popular method of mapping QTLs in many crops, including maize. Advances in high-throughput genotyping technologies enable construction of high-density linkage maps using SNP markers.

OBJECTIVES

High-density genetic mapping must precede to find molecular markers associated with a particular trait. The objectives of this study were to (1) construct a high-density linkage map using SNP markers and (2) detect the QTLs for grain yield and quality related traits of the Mo17/KW7 RIL population.

METHODS

In this study, two parental lines, Mo17 (normal maize inbred line) and KW7 (waxy inbred line) and 80 F_7:8 lines in the Mo17/KW7 RIL population were genotyped using the MaizeSNP50 BeadChip, an Illumina BeadChip array of 56,110 maize SNPs. Marker integration and detection of QTLs was performed using the inclusive composite interval mapping (ICIM) method within the QTL IciMapping software.

RESULTS

This study was genotyped using the Illumina MaizeSNP50 BeadChip for maize Mo17/KW7 recombinant inbred line (RIL) population. The 2904 SNP markers were distributed along all 10 maize chromosomes. The total length of the linkage map was 3553.7 cm, with an average interval of 1.22 cm between SNPs. A total of 18 QTLs controlling eight traits were detected in the Mo17/KW7 RIL population. Three QTLs for plant height (PH) were detected on chromosomes 4 and 8 and showed from 16.01% (qPH8) to 19.85% (qPH4a) of phenotypic variance. Five QTLs related to ear height (EH) were identified on chromosomes 3, 4, and 6 and accounted for 3.79% (qEH6) to 27.57% (qEH4b) of phenotypic variance. Five QTLs related to water content (WC) on chromosomes 1, 4, 8, and 9 accounted for 9.55% (qWC8b) to 23.30% (qWC4) of phenotypic variance. One QTL (qAC9) relating to amylose content (AC) on chromosome 9 showed 82.10% of phenotypic variance.

CONCLUSIONS

The high-density linkage map and putative QTLs of the maize RIL population detected in this study can be effectively utilized in waxy and normal maize breeding programs to facilitate the selection process through marker-assisted selection (MAS) breeding programs.

GBS-SNP and SSR based genetic mapping and QTL analysis for drought tolerance in upland cotton

A recombinant inbred line mapping population of intra-species upland cotton was generated from a cross between the drought-tolerant female parent (AS2) and the susceptible male parent (MCU13). A linkage map was constructed deploying 1,116 GBS-based SNPs and public domain-based 782 SSRs spanning a total genetic distance of 28,083.03 cM with an average chromosomal span length of 1,080.12 cM with inter-marker distance of 10.19 cM.A total of 19 quantitative trait loci (QTLs) were identified in nine chromosomes for field drought tolerance traits. Chromosomes 3 and 8 harbored important drought tolerant QTLs for chlorophyll stability index trait while for relative water content trait, three QTLs on chromosome 8 and one QTL each on chromosome 4, 12 were identified. One QTL on each chromosome 8, 5, and 7, and two QTLs on chromosome 15 linking to proline content were identified. For the nitrate reductase activity trait, two QTLs were identified on chromosome 3 and one on each chromosome 8, 13, and 26. To complement our QTL study, a meta-analysis was conducted along with the public domain database and resulted in a consensus map for chromosome 8. Under field drought stress, chromosome 8 harbored a drought tolerance QTL hotspot with two in-house QTLs for chlorophyll stability index (qCSI01, qCSI02) and three public domain QTLs (qLP.FDT_1, qLP.FDT_2, qCC.ST_3). Identified QTL hotspot on chromosome 8 could play a crucial role in exploring abiotic stress-associated genes/alleles for drought trait improvement.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12298-021-01041-y.

Rapid Identification of QTL for Mesocotyl Length in Rice Through Combining QTL-seq and Genome-Wide Association Analysis

Mesocotyl is a crucial organ for pushing buds out of soil, which plays a vital role in seedling emergence and establishment in direct-seeded rice. Thus, the identification of quantitative trait loci (QTL) associated with mesocotyl length (ML) could accelerate genetic improvement of rice for direct seeding cultivation. In this study, QTL sequencing (QTL-seq) applied to 12 F₂ populations identified 14 QTL for ML, which were distributed on chromosomes 1, 3, 4, 5, 6, 7, and 9 based on the Δ(SNP-index) or G-value statistics. Besides, a genome-wide association study (GWAS) using two diverse panels identified five unique QTL on chromosomes 1, 8, 9, and 12 (2), respectively, explaining 5.3–14.6% of the phenotypic variations. Among these QTL, seven were in the regions harboring known genes or QTLs, whereas the other 10 were potentially novel. Six of the QTL were stable across two or more populations. Eight high-confidence candidate genes related to ML were identified for the stable loci based on annotation and expression analyses. Association analysis revealed that two PCR gel-based markers for the loci co-located by QTL-seq and GWAS, Indel-Chr1:18932318 and Indel-Chr7:15404166 for loci qML1.3 and qML7.2 respectively, were significantly associated with ML in a collection of 140 accessions and could be used as breeder-friendly markers in further breeding.

Mapping of a major QTL controlling plant height using a high-density genetic map and QTL-seq methods based on whole-genome resequencing in Brassica napus

Plant height is a crucial element related to plant architecture that influences the seed yield of oilseed rape (Brassica napus L.). In this study, we isolated a natural B. napus mutant, namely a semi-dwarf mutant (sdw-e), which exhibits a 30% reduction in plant height compared with Zhongshuang 11-HP (ZS11-HP). Quantitative trait locus sequencing (QTL-seq) was conducted using two extreme DNA bulks in F₂ populations in Wuchang-2017 derived from ZS11-HP × sdw-e to identify QTLs associated with plant height. The result suggested that two QTL intervals were located on chromosome A10. The F₂ population consisting of 200 individuals in Yangluo-2018 derived from ZS11-HP × sdw-e was used to construct a high-density linkage map using whole-genome resequencing. The high-density linkage map harbored 4323 bin markers and covered a total distance of 2026.52 cM with an average marker interval of 0.47 cM. The major QTL for plant height named qPHA10 was identified on linkage group A10 by interval mapping and composite interval mapping methods. The major QTL qPHA10 was highly consistent with the QTL-seq results. And then, we integrated the variation sites and expression levels of genes in the major QTL interval to predict the candidate genes. Thus, the identified QTL and candidate genes could be used in marker-assisted selection for B. napus breeding in the future.

Identification of a major-effect QTL associated with pre-harvest sprouting in cucumber (Cucumis sativus L.) using the QTL-seq method

Background

Cucumber (Cucumis sativus L.) is cultivated worldwide, and it is essential to produce enough high-quality seeds to meet demand. Pre-harvest sprouting (PHS) in cucumber is a critical problem and causes serious damage to seed production and quality. Nevertheless, the genetic basis and molecular mechanisms underlying cucumber PHS remain unclear. QTL-seq is an efficient approach for rapid quantitative trait loci (QTL) identification that simultaneously takes advantage of bulked-segregant analysis (BSA) and whole-genome resequencing. In the present research, QTL-seq analysis was performed to identify QTLs associated with PHS in cucumber using an F₂ segregating population.

Results

Two QTLs that spanned 7.3 Mb on Chromosome 4 and 0.15 Mb on Chromosome 5 were identified by QTL-seq and named qPHS4.1 and qPHS5.1, respectively. Subsequently, SNP and InDel markers selected from the candidate regions were used to refine the intervals using the extended F₂ populations grown in the 2016 and 2017 seasons. Finally, qPHS4.1 was narrowed to 0.53 Mb on chromosome 4 flanked by the markers SNP-16 and SNP-24 and was found to explain 19–22% of the phenotypic variation in cucumber PHS. These results reveal that qPHS4.1 is a major-effect QTL associated with PHS in cucumber. Based on gene annotations and qRT-PCR expression analyses, Csa4G622760 and Csa4G622800 were proposed as the candidate genes.

Conclusions

These results provide novel insights into the genetic mechanism controlling PHS in cucumber and highlight the potential for marker-assisted selection of PHS resistance breeding.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07548-8.

Genetic and molecular control of grain yield in maize

Understanding the genetic and molecular basis of grain yield is important for maize improvement. Here, we identified 49 consensus quantitative trait loci (cQTL) controlling maize yield-related traits using QTL meta-analysis. Then, we collected yield-related traits associated SNPs detected by association mapping and identified 17 consensus significant loci. Comparing the physical positions of cQTL with those of significant SNPs revealed that 47 significant SNPs were located within 20 cQTL regions. Furthermore, intensive reviews of 31 genes regulating maize yield-related traits found that the functions of many genes were conservative in maize and other plant species. The functional conservation indicated that some of the 575 maize genes (orthologous to 247 genes controlling yield or seed traits in other plant species) might be functionally related to maize yield-related traits, especially the 49 maize orthologous genes in cQTL regions, and 41 orthologous genes close to the physical positions of significant SNPs. In the end, we prospected on the integration of the public sources for exploring the genetic and molecular mechanisms of maize yield-related traits, and on the utilization of genetic and molecular mechanisms for maize improvement.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01214-3.

Identification and Validation of a Novel Locus Controlling Spikelet Number in Bread Wheat (Triticum aestivum L.)

Spikelet number is an important target trait for wheat yield improvement. Thus, the identification and verification of novel quantitative trait locus (QTL)/genes controlling spikelet number are essential for dissecting the underlying molecular mechanisms and hence for improving grain yield. In the present study, we constructed a high-density genetic map for the Kechengmai1/Chuanmai42 doubled haploid (DH) population using 13,068 single-nucleotide polymorphism (SNP) markers from the Wheat 55K SNP array. A comparison between the genetic and physical maps indicated high consistence of the marker orders. Based on this genetic map, a total of 27 QTLs associated with total spikelet number per spike (TSN) and fertile spikelet number per spike (FSN) were detected on chromosomes 1B, 1D, 2B, 2D, 3D, 4A, 4D, 5A, 5B, 5D, 6A, 6B, and 7D in five environments. Among them, five QTLs on chromosome 2D, 3D, 5A, and 7D were detected in multiple environments and combined QTL analysis, explaining the phenotypic variance ranging from 3.64% to 23.28%. Particularly, QTsn/Fsn.cib-3D for TSN and FSN [phenotypic variation explained (PVE) = 5.97-23.28%, limit of detection (LOD) = 3.73-18.51] is probably a novel locus and located in a 4.5-cM interval on chromosome arm 3DL flanking by the markers AX-110914105 and AX-109429351. This QTL was further validated in other two populations with different genetic backgrounds using the closely linked Kompetitive Allele-Specific PCR (KASP) marker KASP_AX-110914105. The results indicated that QTsn/Fsn.cib-3D significantly increased the TSN (5.56-7.96%) and FSN (5.13-9.35%), which were significantly correlated with grain number per spike (GNS). We also preliminary analyzed the candidate genes within this locus by sequence similarity, spatial expression patterns, and collinearity analysis. These results provide solid foundation for future fine mapping and cloning of QTsn/Fsn.cib-3D. The developed and validated KASP markers could be utilized in molecular breeding aiming to increase the grain yield in wheat.

Linkage analysis, GWAS, transcriptome analysis to identify candidate genes for rice seedlings in response to high temperature stress

BACKGROUND

Rice plants suffer from the rising temperature which is becoming more and more prominent. Mining heat-resistant genes and applying them to rice breeding is a feasible and effective way to solve the problem.

RESULT

Three main biomass traits, including shoot length, dry weight, and fresh weight, changed after abnormally high-temperature treatment in the rice seedling stage of a recombinant inbred lines and the natural indica germplasm population. Based on a comparison of the results of linkage analysis and genome-wide association analysis, two loci with lengths of 57 kb and 69 kb in qDW7 and qFW6, respectively, were associated with the rice response to abnormally high temperatures at the seedling stage. Meanwhile, based on integrated transcriptome analysis, some genes are considered as important candidate genes. Combining with known genes and analysis of homologous genes, it was found that there are eight genes in candidate intervals that need to be focused on in subsequent research.

CONCLUSIONS

The results indicated several relevant loci, which would help researchers to further discover beneficial heat-resistant genes that can be applied to rice heat-resistant breeding.

Linkage analysis, GWAS, transcriptome analysis to identify candidate genes for rice seedlings in response to high temperature stress

BACKGROUND

Rice plants suffer from the rising temperature which is becoming more and more prominent. Mining heat-resistant genes and applying them to rice breeding is a feasible and effective way to solve the problem.

RESULT

Three main biomass traits, including shoot length, dry weight, and fresh weight, changed after abnormally high-temperature treatment in the rice seedling stage of a recombinant inbred lines and the natural indica germplasm population. Based on a comparison of the results of linkage analysis and genome-wide association analysis, two loci with lengths of 57 kb and 69 kb in qDW7 and qFW6, respectively, were associated with the rice response to abnormally high temperatures at the seedling stage. Meanwhile, based on integrated transcriptome analysis, some genes are considered as important candidate genes. Combining with known genes and analysis of homologous genes, it was found that there are eight genes in candidate intervals that need to be focused on in subsequent research.

CONCLUSIONS

The results indicated several relevant loci, which would help researchers to further discover beneficial heat-resistant genes that can be applied to rice heat-resistant breeding.

Genetic analysis of maize shank length by QTL mapping in three recombinant inbred line populations

In maize, the shank is a unique tissue linking the stem to the ear. Shank length (SL) mainly affects the transport of photosynthetic products to the ear and the dehydration of kernels via regulated husk morphology. The limited studies on SL revealed it is a highly heritable quantitative trait controlled by significant additive and additive-dominance effects. However, the genetic basis of SL remains unclear. In this study, we analyzed three maize recombinant inbred line (RIL) populations to elucidate the molecular mechanism underlying the SL. The data indicated the SL varied among the three RIL populations and was highly heritable. Additionally, the SL was positively correlated with the husk length (HL), husk number (HN), ear length (EL), and ear weight (EW) in the BY815/K22 (BYK) and CI7/K22 (CIK) RIL populations, but was negatively correlated with the husk width (HW) in the BYK RIL population. Moreover, 10 quantitative trait loci (QTL) for SL were identified in the three RIL populations, five of which were large-effect QTL. The percentage of the total phenotypic variation explained by the QTL for SL was 13.67 %, 20.45 %, and 30.81 % in the BY815/DE3 (BYD), BYK, and CIK RIL populations, respectively. Further analyses uncovered some genetic overlap between SL and EL, SL and ear row number (ERN), SL and cob weight (CW), and SL and HN. Unlike the large-effect QTL qSL BYK-2-2, which spanned the centromere, the other four large-effect QTL were delimited to a single peak bin via bin map. Furthermore, 2, 5, 6, and 12 genes associated with SL were identified for qSL BYK-2-1, qSL CIK-2-1, qSL CIK-9-1, and qSL CIK-9-2, respectively. Five of the candidate genes for SL may contribute to the hormone metabolism and sphingolipid biosynthesis regulating cell elongation, division, differentiation, and expansion. These results may be relevant for future studies on the genetic basis of SL and for the molecular breeding of maize based on marker-assisted selection to develop new varieties with an ideal SL.

QTL-seq analysis of powdery mildew resistance in a Korean cucumber inbred line

QTL mapping and RT-PCR analyses identified the CsGy5G015660 as a strong powdery mildew resistance candidate gene and natural variation of CsGy5G015660 allele was observed using 115 core germplasm. Powdery mildew (PM) is among the most serious fungal diseases encountered in the cultivation of cucurbits. The development of PM-resistant inbred lines is thus of considerable significance for cucumber breeding programs. In this study, we applied bulked segregant analysis combined with QTL-seq to identify PM resistance loci using F₂ population derived from a cross between two Korean cucumber inbred lines, PM-R (resistant) and PM-S (susceptible). Genome-wide SNP profiling using bulks of the two extreme phenotypes identified two QTLs on chromosomes 5 and 6, designated pm5.2 and pm6.1, respectively. The two PM resistance loci were validated using molecular marker-based classical QTL analysis: pm5.2 (30% R² at LOD 11) and pm6.1 (11% R² at LOD 3.2). Furthermore, reverse transcriptase-PCR analyses, using genes found to be polymorphic between PM-R and PM-S, were conducted to identify the candidate gene(s) responsible for PM resistance. We found that transcripts of the gene CsGy5G015660, encoding a putative leucine-rich repeat receptor-like serine/threonine-protein kinase (RPK2), showed specific accumulation in PM-R prior to the appearance of disease symptoms, and was accordingly considered a strong candidate gene for PM resistance. In addition, cleaved amplified polymorphic sequence markers from CsGy5G015660 were developed and used to screen 35 inbred lines. Natural variation in the CsGy5G015660 allele was also observed based on analysis of a core collection of 115 cucumber accessions. Our results provide new genetic insights for gaining a better understanding of the genetic basis of PM resistance in cucumber, and pave the way for further utilization in cucumber PM resistance breeding programs.

Fine mapping of qKRN8, a QTL for maize kernel row number, and prediction of the candidate gene

KEY MESSAGE: qKRN8, a major QTL for kernel row number in maize, was fine mapped to an interval of ~ 520 kb on chromosome 8 and the key candidate gene was identified via expression analysis. Kernel row number (KRN) is one of the most important yield-influencing traits and is closely associated with female inflorescence development in maize (Zea mays L.). In this study, an F2:3 population derived from a cross between V54 (low KRN line) and Lian87 (high KRN line) was used to map quantitative trait loci (QTLs) conferring KRN in maize. We identified 12 QTLs for KRN in four environments, each explaining 1.40-14.95% of phenotypic variance. Among these, one novel major QTL (named qKRN8) was mapped to bin 8.03 in all four environments, explaining 8.79-14.95% of phenotypic variation. By combining map-based cloning with progeny testing of recombinants, we ultimately mapped qKRN8 to an ~ 520 kb genomic interval, harboring six putative candidate genes. Among them, one candidate gene showed contrasted expression level in immature ears of the near-isogenic lines qKRN8Lian87 and qKRN8V54. These findings should facilitate molecular breeding for KRN and the further identification of the polymorphism underlying this QTL.

Next Generation Sequencing Based Forward Genetic Approaches for Identification and Mapping of Causal Mutations in Crop Plants: A Comprehensive Review

The recent advancements in forward genetics have expanded the applications of mutation techniques in advanced genetics and genomics, ahead of direct use in breeding programs. The advent of next-generation sequencing (NGS) has enabled easy identification and mapping of causal mutations within a short period and at relatively low cost. Identifying the genetic mutations and genes that underlie phenotypic changes is essential for understanding a wide variety of biological functions. To accelerate the mutation mapping for crop improvement, several high-throughput and novel NGS based forward genetic approaches have been developed and applied in various crops. These techniques are highly efficient in crop plants, as it is relatively easy to grow and screen thousands of individuals. These approaches have improved the resolution in quantitative trait loci (QTL) position/point mutations and assisted in determining the functional causative variations in genes. To be successful in the interpretation of NGS data, bioinformatics computational methods are critical elements in delivering accurate assembly, alignment, and variant detection. Numerous bioinformatics tools/pipelines have been developed for such analysis. This article intends to review the recent advances in NGS based forward genetic approaches to identify and map the causal mutations in the crop genomes. The article also highlights the available bioinformatics tools/pipelines for reducing the complexity of NGS data and delivering the concluding outcomes.

Morphological and metabolic profiling of a tropical-adapted potato association panel subjected to water recovery treatment reveals new insights into plant vigor

Potato (Solanum tuberosum L.) is one of the world's most important crops, but it is facing major challenges due to climatic changes. To investigate the effects of intermittent drought on the natural variability of plant morphology and tuber metabolism in a novel potato association panel comprising 258 varieties we performed an augmented block design field study under normal irrigation and under water-deficit and recovery conditions in Ica, Peru. All potato genotypes were profiled for 45 morphological traits and 42 central metabolites via nuclear magnetic resonance. Statistical tests and norm of reaction analysis revealed that the observed variations were trait specific, that is, genotypic versus environmental. Principal component analysis showed a separation of samples as a result of conditional changes. To explore the relational ties between morphological traits and metabolites, correlation-based network analysis was employed, constructing one network for normal irrigation and one network for water-recovery samples. Community detection and difference network analysis highlighted the differences between the two networks, revealing a significant correlational link between fumarate and plant vigor. A genome-wide association study was performed for each metabolic trait. Eleven single nucleotide polymorphism (SNP) markers were associated with fumarate. Gene Ontology analysis of quantitative trait loci regions associated with fumarate revealed an enrichment of genes regulating metabolic processes. Three of the 11 SNPs were located within genes, coding for a protein of unknown function, a RING domain protein and a zinc finger protein ZAT2. Our findings have important implications for future potato breeding regimes, especially in countries suffering from climate change.

Genetic mapping of quantitative trait loci and a major locus for resistance to grey leaf spot in maize

The genetic basis of GLS resistance was dissected using two DH populations sharing a common resistant parent. A major QTL repeatedly detected in multiple developmental stages and environments was fine mapped in a backcross population. Grey leaf spot (GLS), caused by Cercospora zeae-maydis or Cercospora zeina, is a highly destructive foliar disease worldwide. However, the mechanism of resistance against GLS is not well understood. To study the inheritance of this resistance, we developed two doubled haploid (DH) populations sharing a common resistant parent. The two DH populations were grown in two locations representing the typical maize-growing mountain area in Southwest China for 2 years. GLS disease severity was investigated 2 or 3 times until maturity in the 2 years, and the area under the disease progress curve was calculated. Two high-density linkage maps were constructed by genotyping-by-sequencing. A total of 22 quantitative trait loci (QTLs) were detected for GLS resistance, with most QTLs being repeatedly detected in different stages, locations and years. The confidence intervals of two major QTLs (qGLS_Y2-2 and qGLS_Z2-1) on chromosome 2 from the two DH populations overlapped with each other and were integrated into one consensus QTL (qGLS_YZ2-1). Using highly resistant and highly susceptible plants from a BC₃ population, we fine mapped this genetic locus to a genomic region of 2.4 Mb. Using a panel of 255 inbred lines from breeding programmes, we detected associations between markers in the qGLS_YZ2-1 region and GLS resistance. The peak marker (ID-B1) will be very useful for marker-assisted breeding for GLS resistance.

Localization of quantitative trait loci for cucumber fruit shape by a population of chromosome segment substitution lines

Cucumber fruit shape, a significant agronomic trait, is controlled by quantitative trait loci (QTLs). Feasibility of chromosome segment substitution lines (CSSLs) is well demonstrated to map QTLs, especially the minor-effect ones. To detect and identify QTLs with CSSLs can provide new insights into the underlying mechanisms regarding cucumber fruit shape. In the present study, 71 CSSLs were built from a population of backcross progeny (BC4F2) by using RNS7 (a round-fruit cucumber) as the recurrent parent and CNS21 (a long-stick-fruit cucumber) as the donor parent in order to globally detect QTLs for cucumber fruit shape. With the aid of 114 InDel markers covering the whole cucumber genome, 21 QTLs were detected for fruit shape-related traits including ovary length, ovary diameter, ovary shape index, immature fruit length, immature fruit diameter, immature fruit shape index, mature fruit length, mature fruit diameter and mature fruit shape index, and 4 QTLs for other traits including fruit ground and flesh color, and seed size were detected as well. Together our results provide important resources for the subsequent theoretical and applied researches on cucumber fruit shape and other traits.

Metabolomics analysis and metabolite-agronomic trait associations using kernels of wheat (Triticum aestivum) recombinant inbred lines

Plants produce numerous metabolites that are important for their development and growth. However, the genetic architecture of the wheat metabolome has not been well studied. Here, utilizing a high-density genetic map, we conducted a comprehensive metabolome study via widely targeted LC-MS/MS to analyze the wheat kernel metabolism. We further combined agronomic traits and dissected the genetic relationship between metabolites and agronomic traits. In total, 1260 metabolic features were detected. Using linkage analysis, 1005 metabolic quantitative trait loci (mQTLs) were found distributed unevenly across the genome. Twenty-four candidate genes were found to modulate the levels of different metabolites, of which two were functionally annotated by in vitro analysis to be involved in the synthesis and modification of flavonoids. Combining the correlation analysis of metabolite-agronomic traits with the co-localization of methylation quantitative trait locus (mQTL) and phenotypic QTL (pQTL), genetic relationships between the metabolites and agronomic traits were uncovered. For example, a candidate was identified using correlation and co-localization analysis that may manage auxin accumulation, thereby affecting number of grains per spike (NGPS). Furthermore, metabolomics data were used to predict the performance of wheat agronomic traits, with metabolites being found that provide strong predictive power for NGPS and plant height. This study used metabolomics and association analysis to better understand the genetic basis of the wheat metabolism which will ultimately assist in wheat 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.

Identification and fine mapping of a major locus controlling branching in Brassica napus

A candidate branching-controlling gene for qDBA09 was identified after delimiting a Brassica napus recessive locus within a 270-kb interval on chromosome A09. Although branching is an important trait associated with the adaptation and yield potential of rapeseed (Brassica napus), the genetic mechanisms underlining branching in this crop remain poorly understood. In this study, we characterized a naturally occurring rapeseed mutant, db1, which showed an ultrahigh branching density phenotype. By combining bulked segregant analysis (BSA) and the Brassica 60K SNP BeadChip Array, we identified two major quantitative trait loci (QTLs), qDBA09 and qDBC06, which were subsequently confirmed using the traditional QTL-mapping approach. Analysis of 208 individuals from a BC₁F₃ population indicated that the qDBA09 locus is a single Mendelian factor and that the dense branching phenotype is controlled by a single recessive gene. Furthermore, QTL analysis confirmed that qDBA09 explained between 9.5 and 70.5% of the variation in branching-related traits. Using 7785 individuals from the BC₁F₃ population, we mapped qDBA09 to a DNA fragment of approximately 270 kb in length that contained 27 predicted genes, three of which were identified as potentially involved in the control of the dense branching trait. Based on the reported function of these genes, together with sequence comparisons and co-segregation analysis, we identified a potential candidate gene for the qDBA09 locus. The present findings lay the foundations for further in-depth research on the branching mechanisms of B. napus.

Genetic mapping of green curd gene Gr in cauliflower

Gr5.1 is the major locus for cauliflower green curd color and mapped to an interval of 236 Kbp with four most likely candidate genes. Cauliflower with colored curd enhances not only the visual appeal but also the nutritional value of the crop. Green cauliflower results from ectopic development of chloroplasts in the normal white curd. However, the underlying genetic basis is unknown. In this study, we employed QTL-seq analysis to identify the loci that were associated with green curd phenotype in cauliflower. A F2 population was generated following a cross between a white curd (Stovepipe) and a green curd (ACX800) cauliflower plants. By whole-genome resequencing and SNP analysis of green and white F2 bulks, two QTLs were detected on chromosomes 5 (Gr5.1) and 7 (Gr7.1). Validation by traditional genetic mapping with CAPS markers suggested that Gr5.1 represented a major QTL, whereas Gr7.1 had a minor effect. Subsequent high-resolution mapping of Gr5.1 in the second large F2 population with additional CAPS markers narrowed down the target region to a genetic and physical distance of 0.3 cM and 236 Kbp, respectively. This region contained 35 genes with four of them representing the best candidates for the green curd phenotype in cauliflower. They are LOC106295953, LOC106343833, LOC106345143, and LOC106295954, which encode UMP kinase, DEAD-box RNA helicase 51-like, glutathione S-transferase T3-like, and protein MKS1, respectively. These findings lay a solid foundation for the isolation of the Gr gene and provide a potential for marker-assisted selection of the green curd trait in cauliflower breeding. The eventual isolation of Gr will also facilitate better understanding of chloroplast biogenesis and development in plants.

Linking genotype to phenotype to identify genetic variation relating to host susceptibility in the mountain pine beetle system

Identifying genetic variants responsible for phenotypic variation under selective pressure has the potential to enable productive gains in natural resource conservation and management. Despite this potential, identifying adaptive candidate loci is not trivial, and linking genotype to phenotype is a major challenge in contemporary genetics. Many of the population genetic approaches commonly used to identify adaptive candidates will simultaneously detect false positives, particularly in nonmodel species, where experimental evidence is seldom provided for putative roles of the adaptive candidates identified by outlier approaches. In this study, we use outcomes from population genetics, phenotype association, and gene expression analyses as multiple lines of evidence to validate candidate genes. Using lodgepole and jack pine as our nonmodel study species, we analyzed 17 adaptive candidate loci together with 78 putatively neutral loci at 58 locations across Canada (N > 800) to determine whether relationships could be established between these candidate loci and phenotype related to mountain pine beetle susceptibility. We identified two candidate loci that were significant across all population genetic tests, and demonstrated significant changes in transcript abundance in trees subjected to wounding or inoculation with the mountain pine beetle fungal associate Grosmannia clavigera. Both candidates are involved in central physiological processes that are likely to be invoked in a trees response to stress. One of these two candidate loci showed a significant association with mountain pine beetle attack status in lodgepole pine. The spatial distribution of the attack-associated allele further coincides with other indicators of susceptibility in lodgepole pine. These analyses, in which population genetics was combined with laboratory and field experimental validation approaches, represent first steps toward linking genetic variation to the phenotype of mountain pine beetle susceptibility in lodgepole and jack pine, and provide a roadmap for more comprehensive analyses.

Introgressed Saltol QTL Lines Improves the Salinity Tolerance in Rice at Seedling Stage

Rice is a staple food crop in Asia and plays a crucial role in the economy of this region. However, production of rice and its cultivating areas are under constant threat of soil salinity. A major QTL, Saltol, responsible for salinity tolerance at seedling stage has been mapped on chromosome 1 using Pokkali/IR29 Recombinant Inbred Lines (RIL) population. The present study was aimed to incorporate Saltol Quantitative Trait Loci (QTL) in two high yielding mega rice varieties i.e. Pusa44 and Sarjoo52 through Marker Assisted Backcross Breeding (MABB). To improve the seedling stage salinity tolerance in these cultivars, we introgressed the Saltol QTL from donor parent FL478 a derivative of Pokkali. A total of three backcrosses (BC₃) followed by selfing have led to successful introgression of Saltol QTL. Foreground selection at each breeding cycle was done using micro-satellite markers RM3412 and AP3206 to confirm Saltol QTL. The precise transfer of Saltol region was established using recombinant selection through flanking markers RM493 and G11a. Finally, 10 Saltol near isogenic lines (NILs) of Pusa44 and eight NILs of Sarjoo52 were successfully developed. These NILs (BC₃F₄) were evaluated for seedling stage salinity under hydroponic system. The NILs PU99, PU176, PU200, PU215, PU229, PU240, PU241, PU244, PU252, PU263 of Pusa44 and SAR17, SAR23, SAR35, SAR39, SAR77, SAR87, SAR123, SAR136 NILs of Sarjoo52 confirmed tolerance to salinity with low salt injury score of 3 or 5. Ratio of Na⁺/K⁺ content of Saltol NILs ranged from 1.26 to 1.85 in Pusa44 and 1.08 to 1.69 in Sarjoo52. The successfully developed NILs were further phenotyped stringently for morphological traits to estimate Phenotypic Recovery. Background selection of NILs along with parents was carried out with 50K SNP chip and recovered 94.83-98.38% in Pusa44 NILs and 94.51 to 98.31% in Sarjoo52 NILs of recurrent genome. The present study of MAB has accelerated the development of salt tolerant lines in the genetic background of Pusa44 and Sarjoo52. These NILs could be used for commercial cultivation in saline affected area.

Genome-Wide Correlation of 36 Agronomic Traits in the 287 Pepper (Capsicum) Accessions Obtained from the SLAF-seq-Based GWAS

There are many agronomic traits of pepper (Capsicum L.) with abundant phenotypes that can benefit pepper growth. Using specific-locus amplified fragment sequencing (SLAF-seq), a genome-wide association study (GWAS) of 36 agronomic traits was carried out for 287 representative pepper accessions. To ensure the accuracy and reliability of the GWAS results, we analyzed the genetic diversity, distribution of labels (SLAF tags and single nucleotide polymorphisms (SNPs)) and population differentiation and determined the optimal statistical model. In our study, 1487 SNPs were highly significantly associated with 26 agronomic traits, and 2126 candidate genes were detected in the 100-kb region up- and down-stream near these SNPs. Furthermore, 13 major association peaks were identified for 11 key agronomic traits. Then we examined the correlations among the 36 agronomic traits and analyzed SNP distribution and found 37 SNP polymerization regions (total size: 264.69 Mbp) that could be selected areas in pepper breeding. We found that the stronger the correlation between the two traits, the greater the possibility of them being in more than one polymerization region, suggesting that they may be linked or that one pleiotropic gene controls them. These results provide a theoretical foundation for future multi-trait pyramid breeding of pepper. Finally, we found that the GWAS signals were highly consistent with those from the nuclear restorer-of-fertility (Rf) gene for cytoplasmic male sterility (CMS), verifying their reliability. We further identified Capana06g002967 and Capana06g002969 as Rf candidate genes by functional annotation and expression analysis, which provided a reference for the study of cytoplasmic male sterility in Capsicum.

Fine mapping and candidate gene analysis of qhkw5-3, a major QTL for kernel weight in maize

KEY MESSAGE: qhkw5-3, a major QTL for kernel weight in maize, was mapped to an interval of 125.3 kb between the InDel markers InYM20 and InYM36, and the candidate genes were analysed. Yield, of which kernel weight is a major component, is the primary trait of interest in maize breeding programmes. In our previous study, a major QTL (named qhkw5-3), which controls hundred-kernel weight, was identified and mapped to the interval between simple sequence repeat (SSR) markers SYM033 and SYM108 on chromosome 5, using an F_2:3 population derived from a cross between the maize inbred line Zheng58 and the single-segment substitution line Z22. In order to fine map qhkw5-3, a larger BC₁F₁ segregating population of 14,759 seeds, derived from a (Z22 × Zheng58) × Z22 cross, was screened using the SSR markers SYM036 and SYM119. Forty genotypes with donor chromosomal fragments of different lengths were obtained. Progeny testing results indicated that qhkw5-3 was mapped to an interval of 442.6 kb between the SSR markers SYM077 and SYM084. Overlap mapping results, based on seven homozygous recombinant lines, showed that qhkw5-3 was narrowed down to an interval of 125.3 kb between the InDel markers InYM20 and InYM36. Within this interval, six candidate genes were analysed using qRT-PCR. The results of this study lay the foundations for cloning and functional analysis of qhkw5-3 and will contribute to advancing our knowledge of the genetic basis of yield traits in maize.

Identification of quantitative trait loci governing subgynoecy in cucumber

QTL-seq analysis identified three major QTLs conferring subgynoecy in cucumbers. Furthermore, sequence and expression analyses predicted candidate genes controlling subgynoecy. The cucumber (Cucumis sativus L.) is a typical monoecious having individual male and female flowers, and sex differentiation is an important developmental process that directly affects its fruit yield. Subgynoecy represents a sex form with a high degree of femaleness and would have alternative use as gynoecy under limited resource conditions. Recently, many studies have been reported that QTL-seq, which integrates the advantages of bulked segregant analysis and high-throughput whole-genome resequencing, can be a rapid and cost-effective way of mapping QTLs. Segregation analysis in the F₂ and BC₁ populations derived from a cross between subgynoecious LOSUAS and monoecious BMB suggested the quantitative nature of subgynoecy in cucumbers. Both genome-wide SNP profiling of subgynoecious and monoecious bulks constructed from F₂ and BC₁ plants consistently identified three significant genomic regions, one on chromosome 3 (sg3.1) and another two on short and long arms of chromosome 1 (sg1.1 and sg1.2). Classical QTL analysis using the F₂ confirmed sg3.1 (R² = 42%), sg1.1 (R² = 29%) and sg1.2 (R² = 18%) as major QTLs. These results revealed the unique genetic inheritance of subgynoecious line LOSUAS through two distinct major QTLs, sg3.1 and sg1.1, which mainly increase degree of femaleness, while another QTL, sg1.2, contributes to decrease it. This study demonstrated that QTL-seq allows rapid and powerful detection of QTLs using preliminary generation mapping populations such as F₂ or BC₁ population and further that the identified QTLs could be useful for molecular breeding of cucumber lines with high yield potential.

Construction of genetic linkage map and identification of QTLs related to agronomic traits in DH population of maize (Zea mays L.) using SSR markers

BACKGROUND

In this study, we used phenotypic and genetic analysis to investigate Double haploid (DH) lines derived from normal corn parents (HF1 and 11S6169). DH technology offers an array of advantages in maize genetics and breeding as follows: first, it significantly shortens the breeding cycle by development of completely homozygous lines in two or three generations; and second, it simplifies logistics, including requiring less time, labor, and financial resources for developing new DH lines compared with the conventional RIL population development process.

OBJECTIVES

In our study, we constructed a maize genetic linkage map using SSR markers and a DH population derived from a cross of normal corn (HF1) and normal corn (11S6169).

METHODS

The DH population used in this study was developed by the following methods: we crossed normal corn (HF1) and normal corn (11S6169), which are parent lines of a normal corn cultivar, in 2014; and the next year, the F₁ hybrids were crossed with a tropicalized haploid inducer line (TAIL), which is homozygous for the dominant marker gene R1-nj (Nanda and Chase in Crop Sci 6:213-215, 1966), and we harvested seeds of the haploid lines.

RESULTS

A total of 200 SSR markers were assigned to 10 linkage groups that spanned 1145.4 cM with an average genetic distance between markers of 5.7 cM. 68 SSR markers showed Mendelian segregation ratios in the DH population at a 5% significance threshold. A total of 15 quantitative trait loci (QTLs) for plant height (PH), ear height (EH), ear height ratio (ER), leaf length (LL), ear length (EL), set ear length (SEL), set ear ratio (SER), ear width (EW), 100 kernel weight (100 KW), and cob color (CC) were found in the 121 lines in the DH population.

CONCLUSION

The results of this study may help to improve the detection and characterization of agronomic traits and provide great opportunities for maize breeders and researchers using a DH population in maize breeding programs.

Identification of QTL underlying the leaf length and area of different leaves in barley

Leaf is the main organ of photosynthesis, which significantly impacts crop yield. A high-density linkage map containing 1894 single nucleotide polymorphism (SNP) and 68 simple sequence repeats (SSR) markers was used to identify quantitative trait locus (QTL) for flag leaf length (FLL), second leaf length (SLL), third leaf length (TLL), fourth leaf length (FOLL), flag leaf area (FLA), second leaf area (SLA), third leaf area (TLA) and fourth leaf area (FOLA). In total, 57 QTLs underlying the top four leaf length and area traits were identified and mapped on chromosome 2H, 3H, 4H and 7H. Individual QTL accounted for 5.17% to 37.11% of the phenotypic variation in 2015 and 2016. A major stable QTL qFLL2-2 close to the marker 2HL_25536047 was identified on the long arm of chromosome 2H. The most important QTL clustered region at M_256210_824 - 2HL_23335246 on chromosome 2H was associated with FLL, SLL, FLA and SLA and explained high phenotypic variation. These findings provide genetic basis for improving the leaf morphology of barley. In addition, our results suggested that the top four leaves were significantly positively correlated with plant height and some yield-related traits.

Identification of QTL underlying the leaf length and area of different leaves in barley

Leaf is the main organ of photosynthesis, which significantly impacts crop yield. A high-density linkage map containing 1894 single nucleotide polymorphism (SNP) and 68 simple sequence repeats (SSR) markers was used to identify quantitative trait locus (QTL) for flag leaf length (FLL), second leaf length (SLL), third leaf length (TLL), fourth leaf length (FOLL), flag leaf area (FLA), second leaf area (SLA), third leaf area (TLA) and fourth leaf area (FOLA). In total, 57 QTLs underlying the top four leaf length and area traits were identified and mapped on chromosome 2H, 3H, 4H and 7H. Individual QTL accounted for 5.17% to 37.11% of the phenotypic variation in 2015 and 2016. A major stable QTL qFLL2-2 close to the marker 2HL_25536047 was identified on the long arm of chromosome 2H. The most important QTL clustered region at M_256210_824 - 2HL_23335246 on chromosome 2H was associated with FLL, SLL, FLA and SLA and explained high phenotypic variation. These findings provide genetic basis for improving the leaf morphology of barley. In addition, our results suggested that the top four leaves were significantly positively correlated with plant height and some yield-related traits.