Reliable in silico identification of sequence polymorphisms and their application for extending the genetic map of sugar beet (Beta vulgaris)

Genomic characterization of a nematode tolerance locus in sugar beet

BACKGROUND

Infection by beet cyst nematodes (BCN, Heterodera schachtii) causes a serious disease of sugar beet, and climatic change is expected to improve the conditions for BCN infection. Yield and yield stability under adverse conditions are among the main breeding objectives. Breeding of BCN tolerant sugar beet cultivars offering high yield in the presence of the pathogen is therefore of high relevance.

RESULTS

To identify causal genes providing tolerance against BCN infection, we combined several experimental and bioinformatic approaches. Relevant genomic regions were detected through mapping-by-sequencing using a segregating F2 population. DNA sequencing of contrasting F2 pools and analyses of allele frequencies for variant positions identified a single genomic region which confers nematode tolerance. The genomic interval was confirmed and narrowed down by genotyping with newly developed molecular markers. To pinpoint the causal genes within the potential nematode tolerance locus, we generated long read-based genome sequence assemblies of the tolerant parental breeding line Strube U2Bv and the susceptible reference line 2320Bv. We analyzed continuous sequences of the potential locus with regard to functional gene annotation and differential gene expression upon BCN infection. A cluster of genes with similarity to the Arabidopsis thaliana gene encoding nodule inception protein-like protein 7 (NLP7) was identified. Gene expression analyses confirmed transcriptional activity and revealed clear differences between susceptible and tolerant genotypes.

CONCLUSIONS

Our findings provide new insights into the genomic basis of plant-nematode interactions that can be used to design and accelerate novel management strategies against BCN.

Investigation of the expansin gene family in sugar beet (Beta vulgaris) by the genome-wide level and their expression responses under abiotic stresses

Sugar beet (Beta vulgaris ssp. vulgaris) is primarily used in sugar production worldwide. Expansins are a gene family of cell wall proteins effective in regulating cell wall structure. They also participate in developmental stages, including cell and leaf growth, root development, and fruit ripening. This study comprehensively characterizes the expansin gene family members found in the sugar beet genome. In addition, in silico expression analysis of sugar beet expansin genes under variable abiotic stress conditions and expression profiles of expansin genes under combined drought and heat stresses by the qRT-PCR method were evaluated in the study. A total of 31 sugar beet expansin genes were identified. BvuEXLA-02 and BvuEXLB-02 genes can have abiotic stress tolerance roles besides their roles in normal development. Determining the properties of sugar beet expansin, family members can help enable the cellulose hydrolysis mechanism and raise plant biomass. Elucidating expression profiles of the sugar beet expansin genes under variable stress conditions can support improving plant productivity. The results of the current study may also contribute to the deep understanding of sugar beet expansin genes in the future.

Genomic and transcriptomic-based analysis of agronomic traits in sugar beet (Beta vulgaris L.) pure line IMA1

Sugar beet (Beta vulgaris L.) is an important sugar-producing and energy crop worldwide. The sugar beet pure line IMA1 independently bred by Chinese scientists is a standard diploid parent material that is widely used in hybrid-breeding programs. In this study, a high-quality, chromosome-level genome assembly for IMA1was conducted, and 99.1% of genome sequences were assigned to nine chromosomes. A total of 35,003 protein-coding genes were annotated, with 91.56% functionally annotated by public databases. Compared with previously released sugar beet assemblies, the new genome was larger with at least 1.6 times larger N50 size, thereby substantially improving the completeness and continuity of the sugar beet genome. A Genome-Wide Association Studies analysis identified 10 disease-resistance genes associated with three important beet diseases and five genes associated with sugar yield per hectare, which could be key targets to improve sugar productivity. Nine highly expressed genes associated with pollen fertility of sugar beet were also identified. The results of this study provide valuable information to identify and dissect functional genes affecting sugar beet agronomic traits, which can increase sugar beet production and help screen for excellent sugar beet breeding materials. In addition, information is provided that can precisely incorporate biotechnology tools into breeding efforts.

The effect of heat stress on sugar beet recombination

Meiotic recombination plays a crucial role in plant breeding through the creation of new allelic combinations. Therefore, lack of recombination in some genomic regions constitutes a constraint for breeding programmes. In sugar beet, one of the major crops in Europe, recombination occurs mainly in the distal portions of the chromosomes, and so the development of simple approaches to change this pattern is of considerable interest for future breeding and genetics. In the present study, the effect of heat stress on recombination in sugar beet was studied by treating F₁ plants at 28 °C/25 °C (day/night) and genotyping the progeny. F₁ plants were reciprocally backcrossed allowing the study of male and female meiosis separately. Genotypic data indicated an overall increase in crossover frequency of approximately one extra crossover per meiosis, with an associated increase in pericentromeric recombination under heat treatment. Our data indicate that the changes were mainly induced by alterations in female meiosis only, showing that heterochiasmy in sugar beet is reduced under heat stress. Overall, despite the associated decrease in fertility, these data support the potential use of heat stress to foster recombination in sugar beet breeding programmes.

Genomes of the wild beets Beta patula and Beta vulgaris ssp. maritima

We present draft genome assemblies of Beta patula, a critically endangered wild beet endemic to the Madeira archipelago, and of the closely related Beta vulgaris ssp. maritima (sea beet). Evidence-based reference gene sets for B. patula and sea beet were generated, consisting of 25 127 and 27 662 genes, respectively. The genomes and gene sets of the two wild beets were compared with their cultivated sister taxon B. vulgaris ssp. vulgaris (sugar beet). Large syntenic regions were identified, and a display tool for automatic genome-wide synteny image generation was developed. Phylogenetic analysis based on 9861 genes showing 1:1:1 orthology supported the close relationship of B. patula to sea beet and sugar beet. A comparative analysis of the Rz2 locus, responsible for rhizomania resistance, suggested that the sequenced B. patula accession was rhizomania susceptible. Reference karyotypes for the two wild beets were established, and genomic rearrangements were detected. We consider our data as highly valuable and comprehensive resources for wild beet studies, B. patula conservation management, and sugar beet breeding research.

Two sugar beet chitinase genes, BvSP2 and BvSE2, analysed with SNP Amplifluor-like markers, are highly expressed after Fusarium root rot inoculations and field susceptibility trial

BACKGROUND

The pathogens from Fusarium species can cause Fusarium root rot (RR) and other diseases in plant species including sugar beet (Beta vulgaris L.), and they have a strong negative impact on sugar beet yield and quality.

METHODS

A total of 22 sugar beet breeding lines were evaluated for the symptoms of RR after inoculation with Fusarium oxysporum Sch., isolate No. 5, and growth in a field trial. Two candidate genes for RR resistance, BvSP2 and BvSE2, encoding chitinases Class IV and III, respectively, were previously identified in sugar beet, and used for genotyping using modern Amplifluor-like single nucleotide polymorphism (SNP) genotyping approach. The qPCR expression analysis was used to verify responses of the candidate genes for RR infections.

RESULTS

A strong association of two SNP markers for BvSP2 and BvSE2 with resistance to RR in sugar beet was found in our study. Very high BvSP2 expression (100-fold compared to Controls) was observed in three RR resistant accessions (2182, 2236 and KWS2320) 14 days after inoculation which returned to the control level on Day 18. RR sensitive breeding line 2210 showed a delay in mRNA level, reaching maximal expression of BvSP2 18 days after inoculation. The gene BvSE2, showed a strong expression level in leaf samples from the infected field trial only in the breeding line 2236, which showed symptoms of RR, and this may be a response to other strains of F. oxysporum.

The Genetics of Plant Metabolism

Plant metabolic studies have traditionally focused on the role and regulation of the enzymes catalyzing key reactions within specific pathways. Within the past 20 years, reverse genetic approaches have allowed direct determination of the effects of the deficiency, or surplus, of a given protein on the biochemistry of a plant. In parallel, top-down approaches have also been taken, which rely on screening broad, natural genetic diversity for metabolic diversity. Here, we compare and contrast the various strategies that have been adopted to enhance our understanding of the natural diversity of metabolism. We also detail how these approaches have enhanced our understanding of both specific and global aspects of the genetic regulation of metabolism. Finally, we discuss how such approaches are providing important insights into the evolution of plant secondary metabolism.

Crop wild relative populations of Beta vulgaris allow direct mapping of agronomically important genes

Rapid identification of agronomically important genes is of pivotal interest for crop breeding. One source of such genes are crop wild relative (CWR) populations. Here we used a CWR population of <200 wild beets (B. vulgaris ssp. maritima), sampled in their natural habitat, to identify the sugar beet (Beta vulgaris ssp. vulgaris) resistance gene Rz2 with a modified version of mapping-by-sequencing (MBS). For that, we generated a draft genome sequence of the wild beet. Our results show the importance of preserving CWR in situ and demonstrate the great potential of CWR for rapid discovery of causal genes relevant for crop improvement. The candidate gene for Rz2 was identified by MBS and subsequently corroborated via RNA interference (RNAi). Rz2 encodes a CC-NB-LRR protein. Access to the DNA sequence of Rz2 opens the path to improvement of resistance towards rhizomania not only by marker-assisted breeding but also by genome editing.

Variation among wild relatives of crop plants can be used to identify genes underlying traits of agronomic importance. Here, the authors show that a modified mapping-by-sequencing approach can rapidly identify the genetic basis for viral resistance in sugar beet using wild beet populations in their natural habitat.

High-density genetic map construction and QTLs identification for plant height in white jute (Corchorus capsularis L.) using specific locus amplified fragment (SLAF) sequencing

Background

Genetic mapping and quantitative trait locus (QTL) detection are powerful methodologies in plant improvement and breeding. White jute (Corchorus capsularis L.) is an important industrial raw material fiber crop because of its elite characteristics. However, construction of a high-density genetic map and identification of QTLs has been limited in white jute due to a lack of sufficient molecular markers. The specific locus amplified fragment sequencing (SLAF-seq) strategy combines locus-specific amplification and high-throughput sequencing to carry out de novo single nuclear polymorphism (SNP) discovery and large-scale genotyping. In this study, SLAF-seq was employed to obtain sufficient markers to construct a high-density genetic map for white jute. Moreover, with the development of abundant markers, genetic dissection of fiber yield traits such as plant height was also possible. Here, we present QTLs associated with plant height that were identified using our newly constructed genetic linkage groups.

Results

An F₈ population consisting of 100 lines was developed. In total, 69,446 high-quality SLAFs were detected of which 5,074 SLAFs were polymorphic; 913 polymorphic markers were used for the construction of a genetic map. The average coverage for each SLAF marker was 43-fold in the parents, and 9.8-fold in each F₈ individual. A linkage map was constructed that contained 913 SLAFs on 11 linkage groups (LGs) covering 1621.4 cM with an average density of 1.61 cM per locus. Among the 11 LGs, LG1 was the largest with 210 markers, a length of 406.34 cM, and an average distance of 1.93 cM between adjacent markers. LG11 was the smallest with only 25 markers, a length of 29.66 cM, and an average distance of 1.19 cM between adjacent markers. ‘SNP_only’ markers accounted for 85.54% and were the predominant markers on the map. QTL mapping based on the F₈ phenotypes detected 11 plant height QTLs including one major effect QTL across two cultivation locations, with each QTL accounting for 4.14–15.63% of the phenotypic variance.

Conclusions

To our knowledge, the linkage map constructed here is the densest one available to date for white jute. This analysis also identified the first QTL in white jute. The results will provide an important platform for gene/QTL mapping, sequence assembly, genome comparisons, and marker-assisted selection breeding for white jute.

Genomics-based strategies for the use of natural variation in the improvement of crop metabolism

Next-generation genomics holds great potential in the study of plant phenotypic variation. With several crop reference genomes now available, the affordable costs of de novo genome assembly or target resequencing offer the opportunity to mine the enormous amount of genetic diversity hidden in crop wild relatives. Wide introgressions from these wild ancestors species or land races represent a possible strategy to improve cultivated varieties. In this review, we discuss the mechanisms underlying metabolic diversity within plant species and the possible strategies (and barriers) to introgress novel metabolic traits into cultivated varieties. We show how deep genomic surveys uncover various types of structural variants from extended gene pools of major crops and highlight how this variation may be used for the improvement of crop metabolism.

SBMDb: first whole genome putative microsatellite DNA marker database of sugarbeet for bioenergy and industrial applications

DNA marker plays important role as valuable tools to increase crop productivity by finding plausible answers to genetic variations and linking the Quantitative Trait Loci (QTL) of beneficial trait. Prior approaches in development of Short Tandem Repeats (STR) markers were time consuming and inefficient. Recent methods invoking the development of STR markers using whole genomic or transcriptomics data has gained wide importance with immense potential in developing breeding and cultivator improvement approaches. Availability of whole genome sequences and in silico approaches has revolutionized bulk marker discovery. We report world's first sugarbeet whole genome marker discovery having 145 K markers along with 5 K functional domain markers unified in common platform using MySQL, Apache and PHP in SBMDb. Embedded markers and corresponding location information can be selected for desired chromosome, location/interval and primers can be generated using Primer3 core, integrated at backend. Our analyses revealed abundance of 'mono' repeat (76.82%) over 'di' repeats (13.68%). Highest density (671.05 markers/Mb) was found in chromosome 1 and lowest density (341.27 markers/Mb) in chromosome 6. Current investigation of sugarbeet genome marker density has direct implications in increasing mapping marker density. This will enable present linkage map having marker distance of ∼2 cM, i.e. from 200 to 2.6 Kb, thus facilitating QTL/gene mapping. We also report e-PCR-based detection of 2027 polymorphic markers in panel of five genotypes. These markers can be used for DUS test of variety identification and MAS/GAS in variety improvement program. The present database presents wide source of potential markers for developing and implementing new approaches for molecular breeding required to accelerate industrious use of this crop, especially for sugar, health care products, medicines and color dye. Identified markers will also help in improvement of bioenergy trait of bioethanol and biogas production along with reaping advantage of crop efficiency in terms of low water and carbon footprint especially in era of climate change. Database URL: http://webapp.cabgrid.res.in/sbmdb/.