Identification of a novel QTL and candidate gene associated with grain size using chromosome segment substitution lines in rice

A Structure Variation in qPH8.2 Detrimentally Affects Plant Architecture and Yield in Rice

Plant height is an important agronomic trait associated with plant architecture and grain yield in rice (Oryza sativa L.). In this study, we report the identification of quantitative trait loci (QTL) for plant height using a chromosomal segment substitution line (CSSL) population with substituted segments from japonica variety Nipponbare (NIP) in the background of the indica variety 9311. Eight stable QTLs for plant height were identified in three environments. Among them, six loci were co-localized with known genes such as semidwarf-1 (sd1) and Grain Number per Panicle1 (GNP1) involved in gibberellin biosynthesis. A minor QTL qPH8.2 on chromosome 8 was verified and fine-mapped to a 74 kb region. Sequence comparison of the genomic region revealed the presence/absence of a 42 kb insertion between NIP and 9311. This insertion occurred predominantly in temperate japonica rice. Comparisons on the near-isogenic lines showed that the qPH8.2 allele from NIP exhibits pleiotropic effects on plant growth, including reduced plant height, leaf length, photosynthetic capacity, delayed heading date, decreased yield, and increased tiller angle. These results indicate that qPH8.2 from temperate japonica triggers adverse effects on plant growth and yield when introduced into the indica rice, highlighting the importance of the inter-subspecies crossing breeding programs.

GS6.1 controls kernel size and plant architecture in rice

MAIN CONCLUSION

A novel QTL GS6.1 increases yield per plant by controlling kernel size, plant architecture, and kernel filling in rice. Kernel size and plant architecture are critical agronomic traits that greatly influence kernel yield in rice. Using the single-segment substitution lines (SSSLs) with an indica cultivar Huajingxian74 as a recipient parent and American Jasmine as a donor parent, we identified a novel quantitative trait locus (QTL), named GS6.1. Near isogenic line-GS6.1 (NIL-GS6.1) produces long and narrow kernels by regulating cell length and width in the spikelet hulls, thus increasing the 1000-kernel weight. Compared with the control, the plant height, panicles per plant, panicle length, kernels per plant, secondary branches per panicle, and yield per plant of NIL-GS6.1 are increased. In addition, GS6.1 regulates the kernel filling rate. GS6.1 controls kernel size by modulating the transcription levels of part of EXPANSINs, kernel filling-related genes, and kernel size-related genes. These results indicate that GS6.1 might be beneficial for improving kernel yield and plant architecture in rice breeding by molecular design.

Understanding the regulation of cereal grain filling: The way forward

During grain filling, starch and other nutrients accumulate in the endosperm; this directly determines grain yield and grain quality in crops such as rice (Oryza sativa), maize (Zea mays), and wheat (Triticum aestivum). Grain filling is a complex trait affected by both intrinsic and environmental factors, making it difficult to explore the underlying genetics, molecular regulation, and the application of these genes for breeding. With the development of powerful genetic and molecular techniques, much has been learned about the genes and molecular networks related to grain filling over the past decades. In this review, we highlight the key factors affecting grain filling, including both biological and abiotic factors. We then summarize the key genes controlling grain filling and their roles in this event, including regulators of sugar translocation and starch biosynthesis, phytohormone-related regulators, and other factors. Finally, we discuss how the current knowledge of valuable grain filling genes could be integrated with strategies for breeding cereal varieties with improved grain yield and quality.

Integration of Auxin, Brassinosteroid and Cytokinin in the Regulation of Rice Yield

Crop varieties with a high yield are most desirable in the present context of the ever-growing human population. Mostly, the yield traits are governed by a complex of numerous molecular and genetic facets modulated by various quantitative trait loci (QTLs). With the identification and molecular characterizations of yield-associated QTLs over recent years, the central role of phytohormones in regulating plant yield is becoming more apparent. Most often, different groups of phytohormones work in close association to orchestrate yield attributes. Understanding this cross talk would thus provide new venues for phytohormone pyramiding by editing a single gene or QTL(s) for yield improvement. Here, we review a few important findings to integrate the knowledge on the roles of auxin, brassinosteroid and cytokinin and how a single gene or a QTL could govern cross talk among multiple phytohormones to determine the yield traits.

Developing Genetic Engineering Techniques for Control of Seed Size and Yield

Many signaling pathways regulate seed size through the development of endosperm and maternal tissues, which ultimately results in a range of variations in seed size or weight. Seed size can be determined through the development of zygotic tissues (endosperm and embryo) and maternal ovules. In addition, in some species such as rice, seed size is largely determined by husk growth. Transcription regulator factors are responsible for enhancing cell growth in the maternal ovule, resulting in seed growth. Phytohormones induce significant effects on entire features of growth and development of plants and also regulate seed size. Moreover, the vegetative parts are the major source of nutrients, including the majority of carbon and nitrogen-containing molecules for the reproductive part to control seed size. There is a need to increase the size of seeds without affecting the number of seeds in plants through conventional breeding programs to improve grain yield. In the past decades, many important genetic factors affecting seed size and yield have been identified and studied. These important factors constitute dynamic regulatory networks governing the seed size in response to environmental stimuli. In this review, we summarized recent advances regarding the molecular factors regulating seed size in Arabidopsis and other crops, followed by discussions on strategies to comprehend crops' genetic and molecular aspects in balancing seed size and yield.

Insights into the Regulation of Rice Seed Storability by Seed Tissue-Specific Transcriptomic and Metabolic Profiling

Non-dormant seeds are continuously aging and deteriorating during storage, leading to declining seed vigor, which is a challenge for the rice seed industry. Improving the storability of seeds is of great significance to ensure the quality of rice and national food security. Through a set of chromosome segment substitution lines population constructed using japonica rice NIP as donor parent and indica rice ZS97 as recurrent parent, we performed seed storability QTL analysis and selected four non-storable NILs to further investigate the storability regulatory mechanisms underlying it. The seeds were divided into four tissues, which were the embryo, endosperm, aleurone layer, and hull, and tissue-specific transcriptome and metabolome analyses were performed on them. By exploring the common differentially expressed genes and differentially accumulated metabolites, as well as the KEGG pathway of the four non-storable NILs, we revealed that the phenylpropanoid biosynthesis pathway and diterpenoid biosynthesis pathway played a central role in regulating seed storability. Integrated analysis pinpointed 12 candidate genes that may take part in seed storability. The comprehensive analysis disclosed the divergent and synergistic effect of different seed tissues in the regulation of rice storability.

QTL mapping of drought-related traits in the hybrids of Populus deltoides 'Danhong'×Populus simonii 'Tongliao1'

BACKGROUND

Poplar trees provide a large amount of wood material, but many parts of the world are arid or semi-arid areas because of insufficient annual precipitation, which seriously affects the growth of poplar trees. Populus simonii 'Tongliao1' shows strong tolerance to stress environments, and Populus deltoides 'Danhong' shows a stronger growth rate in a suitable environment. To identify drought tolerance-related QTLs and genes, an F₁ population derived from the cross between the 'Danhong' and 'Tongliao 1' Populus was assessed under drought stress.

RESULTS

We measured drought-related traits such as the relative height growth, relative diameter growth, leaf senescence number, specific leaf area, and leaf relative water content in the population under control and drought environments. The results showed that drought stress reduced the plant height relative growth, ground diameter relative growth, specific leaf area and leaf relative water content and increased the number of leaf drops. A total of 208 QTLs were identified by QTL mapping analysis, and they consisted of 92, 63 and 53 QTLs under control, drought stress treatment and drought index conditions, respectively. A molecular identification marker for drought tolerance, np2841, which was associated with a QTL (qDLRWC-LG10-1) for relative leaf water content, was initially developed. We mined 187 candidate genes for QTL regions of five traits under a drought environment. The reference genome annotation for Populus trichocarpa and a homologous gene analysis of Arabidopsis thaliana identified two candidate genes, Potri.003G171300 and Potri.012G123900, with significant functions in response to drought stress. We identified five key regulatory genes (Potri.006G273500, Potri.007G111500, Potri.007G111600, Potri.007G111700, and Potri.007G111800) related to drought tolerance through the poplar coexpression network.

CONCLUSION

In this study, our results indicate that the QTLs can effectively enhance the drought tolerance of poplar. It is a step closer towards unravelling the genetic basis of poplar drought tolerance-related traits, and to providing validated candidate genes and molecular markers for future genetic improvement.

Introgression Lines: Valuable Resources for Functional Genomics Research and Breeding in Rice (Oryza sativa L.)

The narrow base of genetic diversity of modern rice varieties is mainly attributed to the overuse of the common backbone parents that leads to the lack of varied favorable alleles in the process of breeding new varieties. Introgression lines (ILs) developed by a backcross strategy combined with marker-assisted selection (MAS) are powerful prebreeding tools for broadening the genetic base of existing cultivars. They have high power for mapping quantitative trait loci (QTLs) either with major or minor effects, and are used for precisely evaluating the genetic effects of QTLs and detecting the gene-by-gene or gene-by-environment interactions due to their low genetic background noise. ILs developed from multiple donors in a fixed background can be used as an IL platform to identify the best alleles or allele combinations for breeding by design. In the present paper, we reviewed the recent achievements from ILs in rice functional genomics research and breeding, including the genetic dissection of complex traits, identification of elite alleles and background-independent and epistatic QTLs, analysis of genetic interaction, and genetic improvement of single and multiple target traits. We also discussed how to develop ILs for further identification of new elite alleles, and how to utilize IL platforms for rice genetic improvement.

Identification, pyramid, and candidate gene of QTL for yield-related traits based on rice CSSLs in indica Xihui18 background

Chromosome segment substitution line (CSSL) is important for functional analysis and design breeding of target genes. Here, a novel rice CSSL-Z431 was identified from indica restorer line Xihui18 as recipient and japonica Huhan3 as donor. Z431 contained six segments from Huhan3, with average substitution length of 2.12 Mb. Compared with Xihui18, Z431 increased panicle number per plant (PN) and displayed short-wide grains. The short-wide grain of Z431 was caused by decreased length and increased width of glume cell. Then, thirteen QTLs were identified in secondary F2 population from Xihui18/Z431. Again, eleven QTLs (qPL3, qPN3, qGPP12, qSPP12, qGL3, qGW5, qRLW2, qRLW3, qRLW5, qGWT3, qGWT5-2) were validated by six single-segment substitution lines (SSSLs, S1-S6) developed in F3. In addition, fifteen QTLs (qPN5, qGL1, qGL2, qGL5, qGW1, qGW5-1, qRLW1, qRLW5-2, qGWT1, qGWT2, qYD1, qYD2, qYD3, qYD5, qYD12) were detected by these SSSLs, while not be identified in the F2 population. Multiple panicles of Z431 were controlled by qPN3 and qPN5. OsIAGLU should be the candidate gene for qPN3. The short-wide grain of Z431 was controlled by qGL3, qGW5, etc. By DNA sequencing and qRT-PCR analysis, two best candidate genes for qGL3 and qGW5 were identified, respectively. In addition, pyramid of different QTLs in D1-D3 and T1-T2 showed independent inheritance or various epistatic effects. So, it is necessary to understand all genetic effects of target QTLs for designing breeding. Furthermore, these secondary substitution lines improved the deficiencies of Xihui18 to some extent, especially increasing yield per plant in S1, S3, S5, D1-D3, T1, and T2.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01284-x.

Mapping of QTLs for Yield Traits Using F2:3:4 Populations Derived From Two Alien Introgression Lines Reveals qTGW8.1 as a Consistent QTL for Grain Weight From Oryza nivara

Wild introgressions play a crucial role in crop improvement by transferring important novel alleles and broadening allelic diversity of cultivated germplasm. In this study, two stable backcross alien introgression lines 166s and 14s derived from Swarn/Oryza nivara IRGC81848 were used as parents to generate populations to map quantitative trait loci (QTLs) for yield-related traits. Field evaluation of yield-related traits in F₂, F₃, and F₄ population was carried out in normal irrigated conditions during the wet season of 2015 and dry seasons of 2016 and 2018, respectively. Plant height, tiller number, productive tiller number, total dry matter, and harvest index showed a highly significant association to single plant yield in F₂, F₃, and F₄. In all, 21, 30, and 17 QTLs were identified in F₂, F_2:3, and F_2:4, respectively, for yield-related traits. QTLs qPH6.1 with 12.54% phenotypic variance (PV) in F₂, qPH1.1 with 13.01% PV, qTN6.1 with 10.08% PV in F_2:3, and qTGW6.1 with 15.19% PV in F_2:4 were identified as major effect QTLs. QTLs qSPY4.1 and qSPY6.1 were detected for grain yield in F₂ and F_2:3 with PV 8.5 and 6.7%, respectively. The trait enhancing alleles of QTLs qSPY4.1, qSPY6.1, qPH1.1, qTGW6.1, qTGW8.1, qGN4.1, and qTDM5.1 were from O. nivara. QTLs of the yield contributing traits were found clustered in the same chromosomal region. qTGW8.1 was identified in a 2.6 Mb region between RM3480 and RM3452 in all three generations with PV 6.1 to 9.8%. This stable and consistent qTGW8.1 allele from O. nivara can be fine mapped for identification of causal genes. From this population, lines C₂12, C₂124, C₂128, and C₂143 were identified with significantly higher SPY and C₂103, C₂116, and C₂117 had consistently higher thousand-grain weight values than both the parents and Swarna across the generations and are useful in gene discovery for target traits and further crop improvement.

Identification of Genomic Regions Controlling Chalkiness and Grain Characteristics in a Recombinant Inbred Line Rice Population Based on High-Throughput SNP Markers

Rice (Oryza sativa L.) is the primary food for half of the global population. Recently, there has been increasing concern in the rice industry regarding the eating and milling quality of rice. This study was conducted to identify genetic information for grain characteristics using a recombinant inbred line (RIL) population from a japonica/indica cross based on high-throughput SNP markers and to provide a strategy for improving rice quality. The RIL population used was derived from a cross of "Kaybonnet (KBNT lpa)" and "ZHE733" named the K/Z RIL population, consisting of 198 lines. A total of 4133 SNP markers were used to identify quantitative trait loci (QTLs) with higher resolution and to identify more accurate candidate genes. The characteristics measured included grain length (GL), grain width (GW), grain length to width ratio (RGLW), hundred grain weight (HGW), and percent chalkiness (PC). QTL analysis was performed using QTL IciMapping software. Continuous distributions and transgressive segregations of all the traits were observed, suggesting that the traits were quantitatively inherited. A total of twenty-eight QTLs and ninety-two candidate genes related to rice grain characteristics were identified. This genetic information is important to develop rice varieties of high quality.

Metabolomics and complementary techniques to investigate the plant phytochemical cosmos

Covering: up to 2021Plants and their associated microbial communities are known to produce millions of metabolites, a majority of which are still not characterized and are speculated to possess novel bioactive properties. In addition to their role in plant physiology, these metabolites are also relevant as existing and next-generation medicine candidates. Elucidation of the plant metabolite diversity is thus valuable for the successful exploitation of natural resources for humankind. Herein, we present a comprehensive review on recent metabolomics approaches to illuminate molecular networks in plants, including chemical isolation and enzymatic production as well as the modern metabolomics approaches such as stable isotope labeling, ultrahigh-resolution mass spectrometry, metabolome imaging (spatial metabolomics), single-cell analysis, cheminformatics, and computational mass spectrometry. Mass spectrometry-based strategies to characterize plant metabolomes through metabolite identification and annotation are described in detail. We also highlight the use of phytochemical genomics to mine genes associated with specialized metabolites' biosynthesis. Understanding the metabolic diversity through biotechnological advances is fundamental to elucidate the functions of the plant-derived specialized metabolome.