Predicting the size of the progeny mapping population required to positionally clone a gene

Understanding grain development in the Poaceae family by comparing conserved and distinctive pathways through omics studies in wheat and maize

The Poaceae family, commonly known as the grass family, encompasses a diverse group of crops that play an essential role in providing food, fodder, biofuels, environmental conservation, and cultural value for both human and environmental well-being. Crops in Poaceae family are deeply intertwined with human societies, economies, and ecosystems, making it one of the most significant plant families in the world. As the major reservoirs of essential nutrients, seed grain of these crops has garnered substantial attention from researchers. Understanding the molecular and genetic processes that controls seed formation, development and maturation can provide insights for improving crop yield, nutritional quality, and stress tolerance. The diversity in photosynthetic pathways between C3 and C4 plants introduces intriguing variations in their physiological and biochemical processes, potentially affecting seed development. In this review, we explore recent studies performed with omics technologies, such as genomics, transcriptomics, proteomics and metabolomics that shed light on the mechanisms underlying seed development in wheat and maize, as representatives of C3 and C4 plants respectively, providing insights into their unique adaptations and strategies for reproductive success.

Genome-wide association study presents insights into the genetic architecture of drought tolerance in maize seedlings under field water-deficit conditions

Introduction

Drought stress is one of the most serious abiotic stresses leading to crop yield reduction. Due to the wide range of planting areas, the production of maize is particularly affected by global drought stress. The cultivation of drought-resistant maize varieties can achieve relatively high, stable yield in arid and semi-arid zones and in the erratic rainfall or occasional drought areas. Therefore, to a great degree, the adverse impact of drought on maize yield can be mitigated by developing drought-resistant or -tolerant varieties. However, the efficacy of traditional breeding solely relying on phenotypic selection is not adequate for the need of maize drought-resistant varieties. Revealing the genetic basis enables to guide the genetic improvement of maize drought tolerance.

Methods

We utilized a maize association panel of 379 inbred lines with tropical, subtropical and temperate backgrounds to analyze the genetic structure of maize drought tolerance at seedling stage. We obtained the high quality 7837 SNPs from DArT's and 91,003 SNPs from GBS, and a resultant combination of 97,862 SNPs of GBS with DArT's. The maize population presented the lower her-itabilities of the seedling emergence rate (ER), seedling plant height (SPH) and grain yield (GY) under field drought conditions.

Results

GWAS analysis by MLM and BLINK models with the phenotypic data and 97862 SNPs revealed 15 variants that were significantly independent related to drought-resistant traits at the seedling stage above the threshold of P < 1.02 × 10-5. We found 15 candidate genes for drought resistance at the seedling stage that may involve in (1) metabolism (Zm00001d012176, Zm00001d012101, Zm00001d009488); (2) programmed cell death (Zm00001d053952); (3) transcriptional regulation (Zm00001d037771, Zm00001d053859, Zm00001d031861, Zm00001d038930, Zm00001d049400, Zm00001d045128 and Zm00001d043036); (4) autophagy (Zm00001d028417); and (5) cell growth and development (Zm00001d017495). The most of them in B73 maize line were shown to change the expression pattern in response to drought stress. These results provide useful information for understanding the genetic basis of drought stress tolerance of maize at seedling stage.

Genome-wide association studies for soybean epicotyl length in two environments using 3VmrMLM

Germination of soybean seed is the imminent vital process after sowing. The status of plumular axis and radicle determine whether soybean seed can emerge normally. Epicotyl, an organ between cotyledons and first functional leaves, is essential for soybean seed germination, seedling growth and early morphogenesis. Epicotyl length (EL) is a quantitative trait controlled by multiple genes/QTLs. Here, the present study analyzes the phenotypic diversity and genetic basis of EL using 951 soybean improved cultivars and landraces from Asia, America, Europe and Africa. 3VmrMLM was used to analyze the associations between EL in 2016 and 2020 and 1,639,846 SNPs for the identification of QTNs and QTN-by-environment interactions (QEIs)".A total of 180 QTNs and QEIs associated with EL were detected. Among them, 74 QTNs (ELS_Q) and 16 QEIs (ELS_QE) were identified to be associated with ELS (epicotyl length of single plant emergence), and 60 QTNs (ELT_Q) and 30 QEIs (ELT_QE) were identified to be associated with ELT (epicotyl length of three seedlings). Based on transcript abundance analysis, GO (Gene Ontology) enrichment and haplotype analysis, ten candidate genes were predicted within nine genic SNPs located in introns, upstream or downstream, which were supposed to be directly or indirectly involved in the process of seed germination and seedling development., Of 10 candidate genes, two of them (Glyma.04G122400 and Glyma.18G183600) could possibly affect epicotyl length elongation. These results indicate the genetic basis of EL and provides a valuable basis for specific functional studies of epicotyl traits.

Functional Allele Validation by Gene Editing to Leverage the Wealth of Genetic Resources for Crop Improvement

Advances in molecular technologies over the past few decades, such as high-throughput DNA marker genotyping, have provided more powerful plant breeding approaches, including marker-assisted selection and genomic selection. At the same time, massive investments in plant genetics and genomics, led by whole genome sequencing, have led to greater knowledge of genes and genetic pathways across plant genomes. However, there remains a gap between approaches focused on forward genetics, which start with a phenotype to map a mutant locus or QTL with the goal of cloning the causal gene, and approaches using reverse genetics, which start with large-scale sequence data and work back to the gene function. The recent establishment of efficient CRISPR-Cas-based gene editing promises to bridge this gap and provide a rapid method to functionally validate genes and alleles identified through studies of natural variation. CRISPR-Cas techniques can be used to knock out single or multiple genes, precisely modify genes through base and prime editing, and replace alleles. Moreover, technologies such as protoplast isolation, in planta transformation, and the use of developmental regulatory genes promise to enable high-throughput gene editing to accelerate crop improvement.

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.

Combined QTL mapping and association study reveals candidate genes for leaf number and flowering time in maize

KEY MESSAGE

Twelve QTL for flowering and leaf number were detected. The ZmWRKY14Hap4 could increase leaf number, flowering time and biomass yield which are promising for silage maize breeding. Silage maize, one of the most important feedstock for ruminants, is widely grown from temperate regions to the tropics. Flowering time and leaf number are two significantly correlated traits and important for the quality, adaptation and biomass yield of silage maize. In this study, a recombinant inbred line population consisting of 215 individuals and an association panel of 369 inbred lines were analysed in field conditions in three locations for 2 consecutive years, and five, four and three quantitative trait loci for the total leaf number, days to anthesis (DTA) and silking (DTS) were detected, which could explain 48.55, 35.37 and 34.22% of total phenotypic variation, respectively. Association analysis of qLN10 on chromosome 10 found that ZmWRKY14 was the candidate gene for leaf number, whose expression level was negatively correlated with the leaf number. There are five haplotypes for ZmWRKY14, and haplotype 4 could significantly increase flowering time, leaf number and biomass yield, but has no obvious influence on ear weight. The optimal allelic combination of ZmWRKY14 and ZCN8 could further increase leaf number and biomass yield. The results will provide important genetic information for silage maize breeding.

Genetic dissection of maize drought tolerance for trait improvement

Maize is one of the most important crops, but its production is threatened by drought stress worldwide. Thus, increased drought tolerance has been a major goal of maize breeding. Conventional breeding strategies have led to significantly increase of maize yields; however, these strategies often fail to meet the need for drought stress tolerance enhancement. Here, we focus on progress related to the genetic dissection of drought tolerance in maize at different developmental stages achieved through linkage mapping and association mapping. Moreover, recent molecular breeding systems, including transgenic, genome-wide marker-assisted selection, and genome editing technologies, have provided a more direct, efficient, and accurate approach for trait improvement. We also provide perspectives on future directions regarding multi-omics studies and maize improvement. Overall, the application of acquired knowledge will facilitate maize breeding to meet the challenges.

A novel, validated, and plant height-independent QTL for spike extension length is associated with yield-related traits in wheat

A novel, stably expressed, and plant height-independent QTL for spike extension length on 5AS was identified and validated in different populations using a newly developed and tightly linked KASP marker. As an important component of plant height (PH), spike extension length (SEL) plays a significant role in formation of an ideotype in wheat. Despite the fact that numerous loci for SEL in wheat have been reported, our knowledge on PH-independent loci remains to be limited. In this study, two recombinant inbred line (RIL) populations genotyped using the Wheat55K SNP were used to detect quantitative trait loci (QTL) controlling SEL across six environments. A total of 30 QTL for SEL were detected in these two RIL populations, and four of them, i.e., QSEL.sicau-2CN-4D, QSEL.sicau-2SY-4B.2, QSEL.sicau-2SY-4D.1, and QSEL.sicau-2CN-5A, were stably expressed. Genetic and conditional QTL analysis showed that the first three were significantly associated with PH, while the last one, QSEL.sicau-2CN-5A, is independent of PH. Comparison of genetic and physical maps suggested that only QSEL.sicau-2CN-5A located on chromosome arm 5AS is likely a novel QTL. A Kompetitive Allele-Specific PCR (KASP) marker, KASP-AX-110413733, tightly linked to this novel QTL was developed to successfully confirm its effect in three different genetic populations. Further, in the interval where QSEL.sicau-2CN-5A was located on 'Chinese Spring' wheat reference genome, three promising genes mainly expressed in wheat stem were predicated and they all encode the cytochrome P450 that was demonstrated to be closely associated with SEL elongation in rice. In addition, significant correlations between SEL and PH, spikelet number per spike, and thousand-grain weight were also detected. Altogether, our results broaden our understanding on genetic basis of SEL and will be useful for marker-based selection of lines with different SELs and fine mapping the novel and PH-independent QTL QSEL.sicau-2CN-5A.

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.

QTG-Finder: A Machine-Learning Based Algorithm To Prioritize Causal Genes of Quantitative Trait Loci in Arabidopsis and Rice

Linkage mapping is one of the most commonly used methods to identify genetic loci that determine a trait. However, the loci identified by linkage mapping may contain hundreds of candidate genes and require a time-consuming and labor-intensive fine mapping process to find the causal gene controlling the trait. With the availability of a rich assortment of genomic and functional genomic data, it is possible to develop a computational method to facilitate faster identification of causal genes. We developed QTG-Finder, a machine learning based algorithm to prioritize causal genes by ranking genes within a quantitative trait locus (QTL). Two predictive models were trained separately based on known causal genes in Arabidopsis and rice. An independent validation analysis showed that the models could recall about 64% of Arabidopsis and 79% of rice causal genes when the top 20% ranked genes were considered. The top 20% ranked genes can range from 10 to 100 genes, depending on the size of a QTL. The models can prioritize different types of traits though at different efficiency. We also identified several important features of causal genes including paralog copy number, being a transporter, being a transcription factor, and containing SNPs that cause premature stop codon. This work lays the foundation for systematically understanding characteristics of causal genes and establishes a pipeline to predict causal genes based on public data.

High Resolution Genetic and Physical Mapping of a Major Powdery Mildew Resistance Locus in Barley

Powdery mildew caused by Blumeria graminis f. sp. hordei is a foliar disease with highly negative impact on yield and grain quality in barley. Thus, breeding for powdery mildew resistance is an important goal and requires constantly the discovery of new sources of natural resistance. Here, we report the high resolution genetic and physical mapping of a dominant race-specific powdery mildew resistance locus, originating from an Ethiopian spring barley accession 'HOR2573,' conferring resistance to several modern mildew isolates. High-resolution genetic mapping narrowed down the interval containing the resistance locus to a physical span of 850 kb. Four candidate genes with homology to known disease resistance gene families were identified. The mapped resistance locus coincides with a previously reported resistance locus from Hordeum laevigatum, suggesting allelism at the same locus in two different barley lines. Therefore, we named the newly mapped resistance locus from HOR2573 as MlLa-H. The reported co-segregating and flanking markers may provide new tools for marker-assisted selection of this resistance locus in barley breeding.

Genome-wide Association Studies in Maize: Praise and Stargaze

Genome-wide association study (GWAS) has become a widely accepted strategy for decoding genotype-phenotype associations in many species thanks to advances in next-generation sequencing (NGS) technologies. Maize is an ideal crop for GWAS and significant progress has been made in the last decade. This review summarizes current GWAS efforts in maize functional genomics research and discusses future prospects in the omics era. The general goal of GWAS is to link genotypic variations to corresponding differences in phenotype using the most appropriate statistical model in a given population. The current review also presents perspectives for optimizing GWAS design and analysis. GWAS analysis of data from RNA, protein, and metabolite-based omics studies is discussed, along with new models and new population designs that will identify causes of phenotypic variation that have been hidden to date. The joint and continuous efforts of the whole community will enhance our understanding of maize quantitative traits and boost crop molecular breeding designs.

Development of a next-generation NIL library in Arabidopsis thaliana for dissecting complex traits

Background

The identification of the loci and specific alleles underlying variation in quantitative traits is an important goal for evolutionary biologists and breeders. Despite major advancements in genomics technology, moving from QTL to causal alleles remains a major challenge in genetics research. Near-isogenic lines are the ideal raw material for QTL validation, refinement of QTL location and, ultimately, gene discovery.

Results

In this study, a population of 75 Arabidopsis thaliana near-isogenic lines was developed from an existing recombinant inbred line (RIL) population derived from a cross between physiologically divergent accessions Kas-1 and Tsu-1. First, a novel algorithm was developed to utilize genome-wide marker data in selecting RILs fully isogenic to Kas-1 for a single chromosome. Seven such RILs were used in 2 generations of crossing to Tsu-1 to create BC1 seed. BC1 plants were genotyped with SSR markers so that lines could be selected that carried Kas-1 introgressions, resulting in a population carrying chromosomal introgressions spanning the genome. BC1 lines were genotyped with 48 genome-wide SSRs to identify lines with a targeted Kas-1 introgression and the fewest genomic introgressions elsewhere. 75 such lines were selected and genotyped at an additional 41 SNP loci and another 930 tags using 2b-RAD genotyping by sequencing. The final population carried an average of 1.35 homozygous and 2.49 heterozygous introgressions per line with average introgression sizes of 5.32 and 5.16 Mb, respectively. In a simple case study, we demonstrate the advantage of maintaining heterozygotes in our library whereby fine-mapping efforts are conducted simply by self-pollination. Crossovers in the heterozygous interval during this single selfing generation break the introgression into smaller, homozygous fragments (sub-NILs). Additionally, we utilize a homozygous NIL for validation of a QTL underlying stomatal conductance, a low heritability trait.

Conclusions

The present results introduce a new and valuable resource to the Brassicaceae research community that enables rapid fine-mapping of candidate loci in parallel with QTL validation. These attributes along with dense marker coverage and genome-wide chromosomal introgressions make this population an ideal starting point for discovery of genes underlying important complex traits of agricultural and ecological significance.

A high-density genetic linkage map of a black spruce (Picea mariana) × red spruce (Picea rubens) interspecific hybrid

Genetic maps provide an important genomic resource of basic and applied significance. Spruce (Picea) has a very large genome size (between 0.85 × 1010 and 2.4 × 1010 bp; 8.5-24.0 pg/1C, a mean of 17.7 pg/1C ). We have constructed a near-saturated genetic linkage map for an interspecific backcross (BC1) hybrid of black spruce (BS; Picea mariana (Mill.) B.S.P.) and red spruce (RS; Picea rubens Sarg.), using selectively amplified microsatellite polymorphic loci (SAMPL) markers. A total of 2284 SAMPL markers were resolved using 31 SAMPL-MseI selective nucleotide primer combinations. Of these, 1216 SAMPL markers showing Mendelian segregation were mapped, whereas 1068 (46.8%) SAMPL fragments showed segregation distortion at α = 0.05. Maternal, paternal, and consensus maps consistently coalesced into 12 linkage groups, corresponding to the haploid chromosome number (1n = 1x = 12) of 12 in the genus Picea. The maternal BS map consisted of 814 markers distributed over 12 linkage groups, covering 1670 cM, with a mean map distance of 2.1 cM between adjacent markers. The paternal BS × RS map consisted of 773 markers distributed over 12 linkage groups, covering 1563 cM, with a mean map distance of 2.0 cM between adjacent markers. The consensus interspecific hybrid BC1 map consisted of 1216 markers distributed over 12 linkage groups, covering 1865 cM (98% genome coverage), with a mean map distance of 1.5 cM between adjacent markers. The genetic map reported here provides an important genomic resource in Picea, Pinaceae, and conifers.

Genetic analysis of root elongation induced by phosphorus deficiency in rice (Oryza sativa L.): fine QTL mapping and multivariate analysis of related traits

Root elongation induced by phosphorus deficiency has been reported as one of the adaptive mechanisms in plants. Genetic differences were found in rice for the root elongation under phosphorus deficiency (REP), for which a distinct quantitative trait locus (QTL) was detected on the long arm of chromosome 6. Subsequently, the effect and position of the QTL, designated as qREP-6, were confirmed using chromosome segment substitution lines (CSSLs), in which the background of a japonica cultivar, 'Nipponbare' with non-REP, was partially substituted by chromosomal segments from an indica cultivar, 'Kasalath' with remarkable REP. Out of 54 CSSLs, two lines (CSSL28 and CSSL29) that retain a common 'Kasalath'-derived segment on the long arm of chromosome 6 showed a significantly high REP. The high REP lines also showed high adaptabilities such as enhanced tillering ability and shoot phosphorus content. Accordingly, conditional dependencies between the related traits were assessed using a graphical Gaussian model (GGM). Direct interactions between REP and root length, and between root length and tiller number were detected under P deficiency in CSSLs. Furthermore, qREP-6 for REP and qTNP-6 for tiller number under P deficiency were fine-mapped with an F(2) population of a cross between Nipponbare and CSSL29. A region containing qREP-6 accounted for more than half of the phenotypic variance, the most plausible interval of which contained 37 candidate genes. The result provides a foundation for cloning of the qREP-6 gene which will be applicable to study P deficiency-dependent response and to improve rice's adaptability to P deficiency stress.

[Analysis of features of 15 successful positional cloning of QTL in rice]

As the most efficient strategy in gene clone, positional cloning has been used widely in QTL cloning in rice. The objective of this paper is to make summary features of QTL positional cloning based on 15 successful positional cloning attempts. (1) most of the populations used in the analysis were derived from interspecific or intersubspecies; (2) the target QTL had been identified with very large phenotypic effects; (3) the candidate genomic region was usually narrowed down to 40 kb; (4) the primary mapping result was exact; and the fine mapping population was more than 6,000, while the number of recessive population was more than 1,500. Otherwise, the nodus of QTL positional cloning and the corresponding solving methods were discussed.