SNP markers and their impact on plant breeding

Genetic analysis of QTLs for lysine content in four maize DH populations

BACKGROUND

Low levels of the essential amino acid lysine in maize endosperm is considered to be a major problem regarding the nutritional quality of food and feed. Increasing the lysine content of maize is important to improve the quality of food and feed nutrition. Although the genetic basis of quality protein maize (QPM) has been studied, the further exploration of the quantitative trait loci (QTL) underlying lysine content variation still needs more attention.

RESULTS

Eight maize inbred lines with increased lysine content were used to construct four double haploid (DH) populations for identification of QTLs related to lysine content. The lysine content in the four DH populations exhibited continuous and normal distribution. A total of 12 QTLs were identified in a range of 4.42-12.66% in term of individual phenotypic variation explained (PVE) which suggested the quantitative control of lysine content in maize. Five main genes involved in maize lysine biosynthesis pathways in the QTL regions were identified in this study.

CONCLUSIONS

The information presented will allow the exploration of candidate genes regulating lysine biosynthesis pathways and be useful for marker-assisted selection and gene pyramiding in high-lysine maize breeding programs.

Sequencing vs. amplification for the estimation of allele dosages in sugarcane (Saccharum spp.)

Premise

Detecting single-nucleotide polymorphisms (SNPs) in a cost-effective way is fundamental in any plant breeding pipeline. Here, we compare three genotyping techniques for their ability to reproduce the allele dosage of SNPs of interest in sugarcane (Saccharum spp.).

Methods

To identify a reproducible technique to estimate allele dosage for the validation of SNP markers, the correlation between Flex-Seq, kompetitive allele-specific PCR (KASP), and genotyping-by-sequencing and restriction site-associated DNA sequencing (GBS+RADseq) was determined for a set of 76 SNPs. To find alternative methodologies for allele dosage estimation, the KASP and Flex-Seq techniques were compared for the same set of SNPs. For the three techniques, a population of 53 genotypes from the diverse sugarcane panel of the Centro de Investigación de la Caña de Azúcar (Cenicaña), Colombia, was selected.

Results

The average Pearson correlation coefficients between GBS+RADseq and Flex-Seq, GBS+RADseq and KASP, and Flex-Seq and KASP were 0.62 ± 0.27, 0.38 ± 0.27, and 0.38 ± 0.30, respectively.

Discussion

Flex-Seq reproduced the allele dosages determined using GBS+RADseq with good levels of precision because of its depth of sequencing and ability to target specific positions in the genome. Additionally, Flex-Seq outperformed KASP by allowing the conversion of a higher number of SNPs and a more accurate estimation of the allele dosage. Flex-Seq has therefore become the genotyping methodology of choice for marker validation at Cenicaña.

Comprehensive genetic diversity and genome-wide association studies revealed the genetic basis of avocado fruit quality traits

Introduction

Avocado (Persea americana) is a highly nutritious fruit gaining worldwide popularity. However, its cultivation is currently reliant on a limited number of cultivars with restricted genetic diversity. This study aims to investigate the genetic diversity and population structure of avocado germplasm and identify genetic loci associated with key fruit quality traits that influence customer preference.

Methods

A diversity panel of 110 avocado accessions was analyzed using 4,706 high-quality single nucleotide polymorphisms (SNPs). Genetic diversity and population structure were analyzed using pairwise FST, AMOVA, admixture analysis, and phylogenetic analysis. Genome-wide association studies (GWAS) were conducted targeting nine fruit quality traits using two models: General Linear Model (GLM) with Principal Component Analysis (PCA) and Mixed Linear Model (MLM) with PCA and kinship (PCA + K).

Results

The analysis revealed three distinct populations corresponding to the three avocado ecotypes: Guatemalan, West Indian, and Mexican. Phylogenetic analysis indicated a closer relationship between the Guatemalan and West Indian races compared to the Mexican race in our Florida germplasm collection. GWAS led to identification of 12 markers within 11 genomic regions significantly associated with fruit quality traits such as fruit color, shape, taste, and skin texture. These markers explained between 14.84% to 43.96% of the phenotypic variance, with an average of 24.63%. Annotation of these genomic regions unveiled candidate genes potentially responsible for controlling these traits.

Discussion

The findings enhance our understanding of genetic diversity and population structure in avocado germplasm. The identified genetic loci provide valuable insights into the genetic basis of fruit quality traits, aiding breeding programs in developing improved avocado cultivars. Marker-assisted selection can accelerate the development of new varieties, promoting a more diverse and resilient avocado market.

Genome-wide association analyses using multilocus models on bananas (Musa spp.) reveal candidate genes related to morphology, fruit quality, and yield

Bananas (Musa spp.) are an essential fruit worldwide and rank as the fourth most significant food crop for addressing malnutrition due to their rich nutrients and starch content. The potential of their genetic diversity remains untapped due to limited molecular breeding tools. Our study examined a phenotypically diverse group of 124 accessions from the Colombian Musaceae Collection conserved in AGROSAVIA. We assessed 12 traits categorized into morphology, fruit quality, and yield, alongside sequence data. Our sequencing efforts provided valuable insights, with an average depth of about 7× per accession, resulting in 187,133 single-nucleotide polymorphisms (SNPs) against Musa acuminata (A genome) and 220,451 against Musa balbisiana (B genome). Population structure analysis grouped samples into four and five clusters based on the reference genome. By using different association models, we identified marker-trait associations (MTAs). The mixed linear model revealed four MTAs, while the Bayesian-information and linkage-disequilibrium iteratively nested keyway and fixed and random model for circulating probability unification models identified 82 and 70 MTAs, respectively. We identified 38 and 40 candidate genes in linkage proximity to significant MTAs for the A genome and B genome, respectively. Our findings provide insights into the genetic underpinnings of morphology, fruit quality, and yield. Once validated, the SNP markers and candidate genes can potentially drive advancements in genomic-guided breeding strategies to enhance banana crop improvement.

GeCKO: user-friendly workflows for genotyping complex genomes using target enrichment capture. A use case on the large tetraploid durum wheat genome

BACKGROUND

Genotyping of individuals plays a pivotal role in various biological analyses, with technology choice influenced by multiple factors including genomic constraints, number of targeted loci and individuals, cost considerations, and the ease of sample preparation and data processing. Target enrichment capture of specific polymorphic regions has emerged as a flexible and cost-effective genomic reduction method for genotyping, especially adapted to the case of very large genomes. However, this approach necessitates complex bioinformatics treatment to extract genotyping data from raw reads. Existing workflows predominantly cater to phylogenetic inference, leaving a gap in user-friendly tools for genotyping analysis based on capture methods. In response to these challenges, we have developed GeCKO (Genotyping Complexity Knocked-Out). To assess the effectiveness of combining target enrichment capture with GeCKO, we conducted a case study on durum wheat domestication history, involving sequencing, processing, and analyzing variants in four relevant durum wheat groups.

RESULTS

GeCKO encompasses four distinct workflows, each designed for specific steps of genomic data processing: (i) read demultiplexing and trimming for data cleaning, (ii) read mapping to align sequences to a reference genome, (iii) variant calling to identify genetic variants, and (iv) variant filtering. Each workflow in GeCKO can be easily configured and is executable across diverse computational environments. The workflows generate comprehensive HTML reports including key summary statistics and illustrative graphs, ensuring traceable, reproducible results and facilitating straightforward quality assessment. A specific innovation within GeCKO is its 'targeted remapping' feature, specifically designed for efficient treatment of targeted enrichment capture data. This process consists of extracting reads mapped to the targeted regions, constructing a smaller sub-reference genome, and remapping the reads to this sub-reference, thereby enhancing the efficiency of subsequent steps.

CONCLUSIONS

The case study results showed the expected intra-group diversity and inter-group differentiation levels, confirming the method's effectiveness for genotyping and analyzing genetic diversity in species with complex genomes. GeCKO streamlined the data processing, significantly improving computational performance and efficiency. The targeted remapping enabled straightforward SNP calling in durum wheat, a task otherwise complicated by the species' large genome size. This illustrates its potential applications in various biological research contexts.

Genetic variation mining of the Chinese mitten crab (Eriocheir sinensis) based on transcriptome data from public databases

At present, public databases house an extensive repository of transcriptome data, with the volume continuing to grow at an accelerated pace. Utilizing these data effectively is a shared interest within the scientific community. In this study, we introduced a novel strategy that harnesses SNPs and InDels identified from transcriptome data, combined with sample metadata from databases, to effectively screen for molecular markers correlated with traits. We utilized 228 transcriptome datasets of Eriocheir sinensis from the NCBI database and employed the Genome Analysis Toolkit software to identify 96 388 SNPs and 20 645 InDels. Employing the genome-wide association study analysis, in conjunction with the gender information from databases, we identified 3456 sex-biased SNPs and 639 sex-biased InDels. The KOG and KEGG annotations of the sex-biased SNPs and InDels revealed that these genes were primarily involved in the metabolic processes of E. sinensis. Combined with SnpEff annotation and PCR experimental validation, a highly sex-biased SNP located in the Kelch domain containing 4 (Klhdc4) gene, CHR67-6415071, was found to alter the splicing sites of Klhdc4, generating two splice variants, Klhdc4_a and Klhdc4_b. Additionally, Klhdc4 exhibited robust expression across the ovaries, testes, and accessory glands. The sex-biased SNPs and InDels identified in this study are conducive to the development of unisexual cultivation methods for E. sinensis, and the alternative splicing event caused by the sex-biased SNP in Klhdc4 may serve as a potential mechanism for sex regulation in E. sinensis. The analysis strategy employed in this study represents a new direction for the rational exploitation and utilization of transcriptome data in public databases.

Promiscuous potato: elucidating genetic identity and the complex genetic relationships of a cultivated potato germplasm collection

A total of 3,860 accessions from the global in trust clonal potato germplasm collection w3ere genotyped with the Illumina Infinium SolCAP V2 12K potato SNP array to evaluate genetic diversity and population structure within the potato germplasm collection. Diploid, triploid, tetraploid, and pentaploid accessions were included representing the cultivated potato taxa. Heterozygosity ranged from 9.7% to 66.6% increasing with ploidy level with an average heterozygosity of 33.5%. Identity, relatedness, and ancestry were evaluated using hierarchal clustering and model-based Bayesian admixture analyses. Errors in genetic identity were revealed in a side-by-side comparison of in vitro clonal material with the original mother plants revealing mistakes putatively occurring during decades of processing and handling. A phylogeny was constructed to evaluate inter- and intraspecific relationships which together with a STRUCTURE analysis supported both commonly used treatments of potato taxonomy. Accessions generally clustered based on taxonomic and ploidy classifications with some exceptions but did not consistently cluster by geographic origin. STRUCTURE analysis identified putative hybrids and suggested six genetic clusters in the cultivated potato collection with extensive gene flow occurring among the potato populations, implying most populations readily shared alleles and that introgression is common in potato. Solanum tuberosum subsp. andigena (ADG) and S. curtilobum (CUR) displayed significant admixture. ADG likely has extensive admixture due to its broad geographic distribution. Solanum phureja (PHU), Solanum chaucha (CHA)/Solanum stenotomum subsp. stenotomum (STN), and Solanum tuberosum subsp. tuberosum (TBR) populations had less admixture from an accession/population perspective relative to the species evaluated. A core and mini core subset from the genebank material was also constructed. SNP genotyping was also carried out on 745 accessions from the Seed Savers potato collection which confirmed no genetic duplication between the two potato collections, suggesting that the collections hold very different genetic resources of potato. The Infinium SNP Potato Array is a powerful tool that can provide diversity assessments, fingerprint genebank accessions for quality management programs, use in research and breeding, and provide insights into the complex genetic structure and hybrid origin of the diversity present in potato genetic resource collections.

Dissecting the Genetic Diversity of USDA Cowpea Germplasm Collection Using Kompetitive Allele Specific PCR-Single Nucleotide Polymorphism Markers

Cowpea (Vigna unguiculata L. Walp) is an important grain legume crop of the subtropics, particularly in West Africa, where it contributes to the livelihoods of small-scale farmers. Despite being a drought-resilient crop, cowpea production is hampered by insect pests, diseases, parasitic weeds, and various abiotic stresses. Genetic improvement can help overcome these limitations, and exploring diverse cowpea genetic resources is crucial for cowpea breeding. This study evaluated the genetic diversity of 361 cowpea accessions from the USDA core collection for the species using 102 Kompetitive Allele Specific PCR (KASP) single nucleotide polymorphism (SNP) markers. A total of 102 KASP-SNP was validated in the germplasm panel, and 72 showed polymorphism across the germplasm panel. The polymorphism information content (PIC) of all SNPs ranged from 0.1 to 0.37, with an average of 0.29, while the mean observed heterozygosity was 0.52. The population structure revealed three distinct populations that clustered into two major groups after phylogenetic analysis. Analysis of molecular variance (AMOVA) indicated greater genetic variation within populations than among populations. Although cowpea generally has a narrow genetic diversity, the accessions used in this study exhibited considerable variation across geographical regions, sub-species, and improvement status. These results indicated that the selected KASP genotyping assay can provide robust and accurate genotyping data for application in the selection and management of cowpea germplasm in breeding programs and genebanks.

Genome-wide genetic architecture for plant maturity and drought tolerance in diploid potatoes

Cultivated potato (Solanum tuberosum) is known to be highly susceptible to drought. With climate change and its frequent episodes of drought, potato growers will face increased challenges to achieving their yield goals. Currently, a high proportion of untapped potato germplasm remains within the diploid potato relatives, and the genetic architecture of the drought tolerance and maturity traits of diploid potatoes is still unknown. As such, a panel of 384 ethyl methanesulfonate-mutagenized diploid potato clones were evaluated for drought tolerance and plant maturity under field conditions. Genome-wide association studies (GWAS) were conducted to dissect the genetic architecture of the traits. The results obtained from the genetic structure analysis of the panel showed five main groups and seven subgroups. Using the Genome Association and Prediction Integrated Tool-mixed linear model GWAS statistical model, 34 and 17 significant quantitative trait nucleotides (QTNs) were found associated with maturity and drought traits, respectively. Chromosome 5 carried most of the QTNs, some of which were also detected by using the restricted two-stage multi-locus multi-allele-GWAS haploblock-based model, and two QTNs were found to be pleiotropic for both maturity and drought traits. Using the non-parametric U-test, one and three QTNs, with 5.13%-7.4% phenotypic variations explained, showed favorable allelic effects that increase the maturity and drought trait values. The quantitaive trait loci (QTLs)/QTNs associated with maturity and drought trait were found co-located in narrow (0.5-1 kb) genomic regions with 56 candidate genes playing roles in plant development and senescence and in abiotic stress responses. A total of 127 potato clones were found to be late maturing and tolerant to drought, while nine were early to moderate-late maturing and tolerant to drought. Taken together, the data show that the studied germplasm panel and the identified candidate genes are prime genetic resources for breeders and biologists in conventional breeding and targeted gene editing as climate adaptation tools.

Genomic resources for a historical collection of cultivated two-row European spring barley genotypes

Barley genomic resources are increasing rapidly, with the publication of a barley pangenome as one of the latest developments. Two-row spring barley cultivars are intensely studied as they are the source of high-quality grain for malting and distilling. Here we provide data from a European two-row spring barley population containing 209 different genotypes registered for the UK market between 1830 to 2014. The dataset encompasses RNA-sequencing data from six different tissues across a range of barley developmental stages, phenotypic datasets from two consecutive years of field-grown trials in the United Kingdom, Germany and the USA; and whole genome shotgun sequencing from all cultivars, which was used to complement the RNA-sequencing data for variant calling. The outcomes are a filtered SNP marker file, a phenotypic database and a large gene expression dataset providing a comprehensive resource which allows for downstream analyses like genome wide association studies or expression associations.

Applications of some advanced sequencing, analytical, and computational approaches in medicinal plant research: a review

The potential active chemicals found in medicinal plants, which have long been employed as natural medicines, are abundant. Exploring the genes responsible for producing these compounds has given new insights into medicinal plant research. Previously, the authentication of medicinal plants was done via DNA marker sequencing. With the advancement of sequencing technology, several new techniques like next-generation sequencing, single molecule sequencing, and fourth-generation sequencing have emerged. These techniques enshrined the role of molecular approaches for medicinal plants because all the genes involved in the biosynthesis of medicinal compound(s) could be identified through RNA-seq analysis. In several research insights, transcriptome data have also been used for the identification of biosynthesis pathways. miRNAs in several medicinal plants and their role in the biosynthesis pathway as well as regulation of the disease-causing genes were also identified. In several research articles, an in silico study was also found to be effective in identifying the inhibitory effect of medicinal plant-based compounds against virus' gene(s). The use of advanced analytical methods like spectroscopy and chromatography in metabolite proofing of secondary metabolites has also been reported in several recent research findings. Furthermore, advancement in molecular and analytic methods will give new insight into studying the traditionally important medicinal plants that are still unexplored.

Identification and high-throughput genotyping of single nucleotide polymorphism markers in a non-model conifer (Abies nordmanniana (Steven) Spach)

Single nucleotide polymorphism (SNP) markers are powerful tools for investigating population structures, linkage analysis, and genome-wide association studies, as well as for breeding and population management. The availability of SNP markers has been limited to the most commercially important timber species, primarily due to the cost of genome sequencing required for SNP discovery. In this study, a combination of reference-based and reference-free approaches were used to identify SNPs in Nordmann fir (Abies nordmanniana), a species previously lacking genomic sequence information. Using a combination of a genome assembly of the closely related Silver fir (Abies alba) species and a de novo assembly of low-copy regions of the Nordmann fir genome, we identified a high density of reliable SNPs. Reference-based approaches identified two million SNPs in common between the Silver fir genome and low-copy regions of Nordmann fir. A combination of one reference-free and two reference-based approaches identified 250 shared SNPs. A subset of 200 SNPs were used to genotype 342 individuals and thereby tested and validated in the context of identity analysis and/or clone identification. The tested SNPs successfully identified all ramets per clone and five mislabeled individuals via identity and genomic relatedness analysis. The identified SNPs will be used in ad hoc breeding of Nordmann fir in Denmark.

One hundred single-copy nuclear sequence markers for olive variety identification: a case of fingerprinting database construction in China

Olive is an ancient oil-producing tree, widely cultivated in Mediterranean countries, and now spread to other areas of the world, including China. Recently, several molecular databases were constructed in different countries and platforms for olive identification using simple sequence repeats (SSRs) or single-nucleotide polymorphisms (SNPs). However, comparing their results across laboratories was difficult. Herein, hundreds of polymorphic single-copy nuclear sequence markers were developed from the olive genome. Using the advantage of multiplex PCR amplification and high-throughput sequencing, a fingerprint database was constructed for the majority of olives cultivated in China. We used 100 high-quality sequence loci and estimated the genetic diversity and structure among all these varieties. We found that compared with that based on SSRs, the constructed fingerprint database based on these 100 sequences or a few of them, could provide a reliable olive variety identification platform in China, with high discrimination among different varieties using the principle of BLAST algorithm. An example of such identification platform based on this study was displayed on the web for the olive database in China (http://olivedb.cn/jianding). After resolving redundant genotypes, we identified 126 olive varieties with distinct genotypes in China. These varieties could be divided into two clusters, and it was revealed that the grouping of the varieties has a certain relationship with their origin. Herein, it is concluded that these single-copy orthologous nuclear sequences could be used to construct a universal fingerprint database of olives across different laboratories and platforms inexpensively. Based on such a database, variety identification can be performed easily by any laboratory, which would further facilitate olive breeding and variety exchange globally.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01434-9.

Pheno- and genotyping in vitro dauer juvenile recovery in the nematode Heterorhabditis bacteriophora

The entomopathogenic nematode (EPN) Heterorhabditis bacteriophora is an effective biological-control agent of insect pests. The dauer juveniles (DJs) seek for, infect insects, and release cells of the carried symbiotic bacterium of the genus Photorhabdus. Inside the host, the DJs perceive signals from the insect's haemolymph that trigger the exit from the arrested stage and the further development to mature adults. This developmental step is called DJ recovery. In commercial production, a high and synchronous DJ recovery determines the success of liquid-culture mass production. To enhance the understanding about genetic components regulating DJ recovery, more than 160 mutant- and 25 wild type inbred lines (WT ILs) were characterized for DJ recovery induced by cell-free bacterial supernatant. The mutant lines exhibited a broader DJ recovery range than WT ILs (4.6-67.2% vs 1.6-35.7%). A subset of mutant lines presented high variability of virulence against mealworm (Tenebrio molitor) (from 22 to 78% mortality) and mean time survival under oxidative stress (70 mM H2O2; from 10 to 151 h). Genotyping by sequencing of 96 mutant lines resulted in more than 150 single nucleotide polymorphisms (SNPs), of which four results are strongly associated with the DJ recovery trait. The present results are the basis for future approaches in improving DJ recovery by breeding under in vitro liquid-culture mass production in H. bacteriophora. This generated platform of EMS-mutants is as well a versatile tool for the investigation of many further traits of interest in EPNs. KEYPOINTS: • Exposure to bacterial supernatants of Photorhabdus laumondii induces the recovery of Heterorhabditis bacteriophora dauer juveniles (DJs). Both, the bacteria and the nematode partner, influence this response. However, the complete identity of its regulators is not known. • We dissected the genetic component of DJ recovery regulation in H. bacteriophora nematodes by generating a large array of EMS mutant lines and characterizing their recovery pheno- and genotypes. • We determined sets of mutants with contrasting DJ recovery and genotyped a subset of the EMS-mutant lines via genotyping by sequencing (GBS) and identified SNPs with significant correlation to the recovery trait.

Genome-wide association study (GWAS) with high-throughput SNP chip DNA markers identified novel genetic factors for mesocotyl elongation and seedling emergence in rice (Oryza sativa L.) using multiple GAPIT models

This study employed a joint strategy high-density SNP Chip DNA markers and multiple Genome Association and Prediction Integrated Tool (GAPIT) models [(Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK), Fixed and random model Circulating Probability Uniform (FarmCPU), General Linear Model (GLM), and Settlement of Mixed Linear Model (MLM) Under Progressively Exclusive Relationship (SUPER)], to investigate novel genetic factors controlling mesocotyl elongation and seedling emergence for direct-seeded rice. Genotype data (230,526 SNP Chip DNA makers) of 117 doubled haploid lines (derived from a cross between 93-11 (Oryza sativa L. ssp. indica) and Milyang352 (O. sativa L. ssp. japonica) were used to perform a Genome-Wide Association Study (GWAS). Results revealed the association between five (5) topmost significant SNP markers, of which number two [AX-155741269, Chr2: 15422406 bp, and AX-155200917, Chr7: 23814085 bp, explaining 37.5% and 13.8% of the phenotypic variance explained (PVE)] are linked to the mesocotyl elongation loci, while three (AX-282097034 and AX-283652873, Chr9: 9882817 bp and 1023383 bp, PVE 64.5%, and 20.2%, respectively, and AX-154356231, Chr1: 17413989 bp, PVE 21.1%) are tightly linked to the loci controlling seedling emergence. The qMEL2-1 and qSEM9-1 are identified as major QTLs explaining 37.5% and 64.5% of the PVE for mesocotyl elongation and seedling emergence, respectively. The AX-282097034 (Chr9: 9882817 bp) was co-detected by four GAPIT models (BLINK, FarmCPU, SUPER, and GLM), while AX-155741269 was co-detected by BLINK and SUPER. Furthermore, a high estimated heritability (Mesocotyl elongation: h2 = 0.955; seedling emergence: h2 = 0.863; shoot length: h2 = 0.707) was observed. Genes harbored by qMEL2-1 and qSEM9-1 have interesting annotated molecular functions that could be investigated through functional studies to uncover their roles during mesocotyl elongation and seedling emergence events in rice. Furthermore, the presence of genes encoding transcription factors, growth- and stress response, or signaling-related genes would suggest that mesocotyl elongation and seedling emergence from deep direct-seeded rice might involve an active signaling cascade and transport of molecules, which could be elucidated through functional analysis. Likewise, genomic selection analysis suggested markers useful for downstream marker-assisted selection (MAS).

On the usefulness of mock genomes to define heterotic pools, testers, and hybrid predictions in orphan crops

The advances in genomics in recent years have increased the accuracy and efficiency of breeding programs for many crops. Nevertheless, the adoption of genomic enhancement for several other crops essential in developing countries is still limited, especially for those that do not have a reference genome. These crops are more often called orphans. This is the first report to show how the results provided by different platforms, including the use of a simulated genome, called the mock genome, can generate in population structure and genetic diversity studies, especially when the intention is to use this information to support the formation of heterotic groups, choice of testers, and genomic prediction of single crosses. For that, we used a method to assemble a reference genome to perform the single-nucleotide polymorphism (SNP) calling without needing an external genome. Thus, we compared the analysis results using the mock genome with the standard approaches (array and genotyping-by-sequencing (GBS)). The results showed that the GBS-Mock presented similar results to the standard methods of genetic diversity studies, division of heterotic groups, the definition of testers, and genomic prediction. These results showed that a mock genome constructed from the population's intrinsic polymorphisms to perform the SNP calling is an effective alternative for conducting genomic studies of this nature in orphan crops, especially those that do not have a reference genome.

Development of SNP markers linked to purple blotch resistance for marker-assisted selection in onion (Allium cepa L.) breeding

Purple blotch (PB), caused by Alternaria porri (Ellis) Cifferi, is one of the most destructive diseases of onion worldwide. Rapid development and deployment of resistant onion varieties is the most effective approach to control this disease. A single dominant gene, ApR1 was previously linked to PB resistance in onion cultivar 'Arka Kalyan'. In this study, an advanced RIL population derived from a cross between the resistant (Arka Kalyan) and susceptible (Agrifound Rose) cultivar of onion was used to fine map the resistant locus with SNP markers. Twenty plants from the RIL population, ten each with disease resistance and susceptibility trait, were subjected to restriction site-associated DNA sequencing (RAD-Seq) and generated 7388 single nucleotide polymorphisms (SNPs). Correlation analysis between marker genotypes and PB disease phenotype on the 20 plants identified 27 SNPs as candidate markers linked to ApR1 gene for PB resistance. Six candidate SNPs were converted to Kompetitive Allele-Specific PCR (KASP) markers designated as ApRsnip5, ApRsnip8, ApRsnip14, ApRsnip21, ApRsnip23 and ApRsnip25. Marker-trait association based on disease phenotyping and KASP genotyping data on 153 RILs confirmed that all six KASP markers were tightly associated with ApR1 gene within the genetic distance of 1.3 CentiMorgan (cM). ApRsnip14 co-segregated with the ApR1 locus. Further, the six KASP markers were tested on 27 onion lines with different genetic backgrounds. ApRsnip14, ApRsnip21, ApRsnip5 and ApRsnip23 not only showed the correct resistance allele in 3 resistance genotypes, but also clustered together in the remaining 24 susceptible lines. Alternatively, ApRsnip8 and ApRsnip25 exhibited false positives in two onion lines which do not have the R-gene. Overall, our results suggest that ApRsnip14 and ApRsnip23 with their close linkage to ApR1 locus and greater applicability on breeding germplasm are recommended in marker-assisted selection for PB resistance in onion breeding program.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03562-7.

Vitis vinifera genotyping toolbox to highlight diversity and germplasm identification

The contribution of vine cultivation to human welfare as well as the stimulation of basic social and cultural features of civilization has been great. The wide temporal and regional distribution created a wide array of genetic variants that have been used as propagating material to promote cultivation. Information on the origin and relationships among cultivars is of great interest from a phylogenetics and biotechnology perspective. Fingerprinting and exploration of the complicated genetic background of varieties may contribute to future breeding programs. In this review, we present the most frequently used molecular markers, which have been used on Vitis germplasm. We discuss the scientific progress that led to the new strategies being implemented utilizing state-of-the-art next generation sequencing technologies. Additionally, we attempted to delimit the discussion on the algorithms used in phylogenetic analyses and differentiation of grape varieties. Lastly, the contribution of epigenetics is highlighted to tackle future roadmaps for breeding and exploitation of Vitis germplasm. The latter will remain in the top of the edge for future breeding and cultivation and the molecular tools presented herein, will serve as a reference point in the challenging years to come.

Multi-locus genome-wide association study of chickpea reference set identifies genetic determinants of Pratylenchus thornei resistance

Pratylenchus thornei is an economically important species of root-lesion nematode adversely affecting chickpea (Cicer arietinum) yields globally. Integration of resistant crops in farming systems is recognised as the most effective and sustainable management strategy for plant-parasitic nematodes. However, breeding for P. thornei resistance in chickpea is limited by the lack of genetic diversity. We deployed a genome-wide association approach to identify genomic regions and candidate genes associated with P. thornei resistance in 285 genetically diverse chickpea accessions. Chickpea accessions were phenotyped for P. thornei resistance in replicated glasshouse experiments performed for two years (2018 and 2020). Whole genome sequencing data comprising 492,849 SNPs were used to implement six multi-locus GWAS models. Fourteen chickpea genotypes were found to be resistant to P. thornei. Of the six multi-locus GWAS methods deployed, FASTmrMLM was found to be the best performing model. In all, 24 significant quantitative trait nucleotides (QTNs) were identified, of which 13 QTNs were associated with lower nematode population density and 11 QTNs with higher nematode population density. These QTNs were distributed across all of the chickpea chromosomes, except chromosome 8. We identified, receptor-linked kinases (RLKs) on chromosomes 1, 4 and 6, GDSL-like Lipase/Acylhydrolase on chromosome 3, Aspartic proteinase-like and Thaumatin-like protein on chromosome 4, AT-hook DNA-binding and HSPRO2 on chromosome 6 as candidate genes for P. thornei resistance in the chickpea reference set. New sources of P. thornei resistant genotypes were identified that can be harnessed into breeding programs and putative candidate P. thornei resistant genes were identified that can be explored further to develop molecular markers and accelerate the incorporation of improved P. thornei resistance into elite chickpea cultivars.

Assessment of the Genetic Diversity and Population Structure of the Peruvian Andean Legume, Tarwi (Lupinus mutabilis), with High Quality SNPs

Lupinus mutabilis Sweet (Fabaceae), “tarwi” or “chocho”, is an important grain legume in the Andean region. In Peru, studies on tarwi have mainly focused on morphological features; however, they have not been molecularly characterized. Currently, it is possible to explore the genetic parameters of plants with reliable and modern methods such as genotyping by sequencing (GBS). Here, for the first time, we used single nucleotide polymorphism (SNP) markers to infer the genetic diversity and population structure of 89 accessions of tarwi from nine Andean regions of Peru. A total of 5922 SNPs distributed along all chromosomes of tarwi were identified. STRUCTURE analysis revealed that this crop is grouped into two clusters. A dendrogram was generated using the UPGMA clustering algorithm and, like the principal coordinate analysis (PCoA), it showed two groups that correspond to the geographic origin of the tarwi samples. AMOVA showed a reduced variation between clusters (7.59%) and indicated that variability within populations is 92.41%. Population divergence (Fst) between clusters 1 and 2 revealed low genetic difference (0.019). We also detected a negative Fis for both populations, demonstrating that, like other Lupinus species, tarwi also depends on cross-pollination. SNP markers were powerful and effective for the genotyping process in this germplasm. We hope that this information is the beginning of the path towards a modern genetic improvement and conservation strategies of this important Andean legume.

Genotyping by Sequencing (GBS) for Genome-Wide SNP Identification in Plants

Marker-assisted selection has played a pivotal role in developing several elite varieties in the past two decades. Molecular markers employed in plant breeding programs have recently shifted from microsatellites or simple sequence repeats (SSRs) to single nucleotide polymorphisms (SNPs) due to the ubiquity of SNP markers in the genome and the availability of various high-throughput SNP genotyping platforms. Rapid advances in sequencing technologies and the reduction in sequencing cost have facilitated SNP discovery in several plant species including non-model organisms with little or no genomic resources. Despite the lower cost of sequencing, genome complexity reduction approaches are still useful for SNP identification because many applications do not require every base of the genome to be sequenced. Genotyping-by-sequencing (GBS) is a quick and affordable reduced representation method that can simultaneously identify and genotype a large number of SNPs that has been successfully applied to a wide range of plant species. This chapter describes a robust two-enzyme GBS method for SNP discovery and genotyping that has been verified in non-model plant species.

Application of SolCAP Genotyping in Potato (Solanum tuberosum L.) Association Mapping

Potato variety development entails a number of breeding steps, as well as testing and, finally, commercialization. Historically, phenotypic assesment were carried out to select and germplasm development. The US Department of Agriculture (USDA) funded the Solanaceae Coordinated Agricultural Project (SolCAP) to decode genomic resources into tools that breeders and geneticists can use. This project resulted in the creation of a genome-wide single-nucleotide polymorphism (SNP) array that can be used to evaluate elite potato-breeding germplasm. This array was used to genotype a diverse panel of Solanum species, as well as numerous biparental, diploid, and tetraploid populations. It has high marker density to generate genetic maps that can be used to identify numerous quantitative trait loci (QTLs) for agronomic, quality, biotic, and abiotic resistance traits. Up to now, numerous QTLs for important traits have been identified using new diploid and tetraploid genetic maps. SNP markers were used to assess germplasm relationships and fingerprint varieties and identify candidate genes. The Infinium 8303 SolCAP Potato array offers a common set of SNP markers that can be used for mapping, germplasm assessment, and fingerprinting with confidence. This array has also been helpful in furthering our understanding of the potato genome. Furthermore, some other Infinium potato arrays (i.e., 12 K, 20 K, and 25 K) have been genotyped, and breeders can map quantitative trait loci (QTLs) across multiple populations to improve our understanding of economically important traits and lead to marker-assisted selection (MAS) and breeding and, ultimately, improved varieties.

Transcriptomic Approach for Global Distribution of SNP/Indel and Plant Genotyping

Single Nucleotide Polymorphisms (SNPs) are the most common structural variants found in any genome. They have been used for different genetic studies, from the understanding of genetic structure of populations to the development of breeding selection markers. In this chapter we present the use of transcriptomic data obtained from contrasting phenotypes for a target trait, in searching of SNPs and insertions/deletions (InDels). This approach has the advantage that the identified markers are in or close to differentially expressed genes, and so they have higher chances to tag the genes underlying the phenotypic expression of a particular trait.

Genetic dissection of QTLs for oil content in four maize DH populations

Oil is one of the main components in maize kernels. Increasing the total oil content (TOC) is favorable to optimize feeding requirement by improving maize quality. To better understand the genetic basis of TOC, quantitative trait loci (QTL) in four double haploid (DH) populations were explored. TOC exhibited continuously and approximately normal distribution in the four populations. The moderate to high broad-sense heritability (67.00-86.60%) indicated that the majority of TOC variations are controlled by genetic factors. A total of 16 QTLs were identified across all chromosomes in a range of 3.49-30.84% in term of phenotypic variation explained. Among them, six QTLs were identified as the major QTLs that explained phenotypic variation larger than 10%. Especially, qOC-1-3 and qOC-2-3 on chromosome 9 were recognized as the largest effect QTLs with 30.84% and 21.74% of phenotypic variance, respectively. Seventeen well-known genes involved in fatty acid metabolic pathway located within QTL intervals. These QTLs will enhance our understanding of the genetic basis of TOC in maize and offer prospective routes to clone candidate genes regulating TOC for breeding program to cultivate maize varieties with the better grain quality.

Whole-genome sequencing of a year-round fruiting jackfruit (Artocarpus heterophyllus Lam.) reveals high levels of single nucleotide variation

Jackfruit (Artocarpus heterophyllus Lam.) is the national fruit of Bangladesh and produces fruit in the summer season only. However, jackfruit is not commercially grown in Bangladesh because of an extremely high variation in fruit quality, short seasonal fruiting (June-August) and susceptibility to abiotic stresses. Conversely, a year-round high yielding (ca. 4-fold higher than the seasonal variety) jackfruit variety, BARI Kanthal-3 developed by the Bangladesh Agricultural Research Institute (BARI) derived from a wild accession found in Ramgarh of Chattogram Hiltracts of Bangladesh, provides fruits from September to June. This study aimed to generate a draft whole-genome sequence (WGS) of BARI Kanthal-3 to obtain molecular insights including genes associated with year-round fruiting trait of this important unique variety. The estimated genome size of BARI Kanthal-3 was 1.04-gigabase-pair (Gbp) with a heterozygosity rate of 1.62%. De novo assembly yielded a scaffolded 817.7 Mb genome while a reference-guided approach, yielded 843 Mb of genome sequence. The estimated GC content was 34.10%. Variant analysis revealed that BARI Kanthal-3 included 5.7 M (35%) and 10.4 M (65%) simple and heterozygous single nucleotide polymorphisms (SNPs), and about 90% of all these polymorphisms are in inter-genic regions. Through BUSCO assessment, 97.2% of the core genes were represented in the assembly with 1.3% and 1.5% either fragmented or missing, respectively. By comparing identified orthologous gene groups in BARI Kanthal-3 with five closely and one distantly related species of 10,092 common orthogroups were found across the genomes of the six species. The phylogenetic analysis of the shared orthogroups showed that A. heterophyllus was the closest species to BARI Kanthal-3 and orthogroups related to flowering time were found to be more highly prevalent in BARI Kanthal-3 compared to the other Arctocarpus spp. The findings of this study will help better understanding the evolution, domestication, phylogenetic relationships, year-round fruiting of this highly nutritious fruit crop as well as providing a resource for molecular breeding.

Genetic basis of maize kernel protein content revealed by high-density bin mapping using recombinant inbred lines

Maize with a high kernel protein content (PC) is desirable for human food and livestock fodder. However, improvements in its PC have been hampered by a lack of desirable molecular markers. To identify quantitative trait loci (QTL) and candidate genes for kernel PC, we employed a genotyping-by-sequencing strategy to construct a high-resolution linkage map with 6,433 bin markers for 275 recombinant inbred lines (RILs) derived from a high-PC female Ji846 and low-PC male Ye3189. The total genetic distance covered by the linkage map was 2180.93 cM, and the average distance between adjacent markers was 0.32 cM, with a physical distance of approximately 0.37 Mb. Using this linkage map, 11 QTLs affecting kernel PC were identified, including qPC7 and qPC2-2, which were identified in at least two environments. For the qPC2-2 locus, a marker named IndelPC2-2 was developed with closely linked polymorphisms in both parents, and when tested in 30 high and 30 low PC inbred lines, it showed significant differences (P = 1.9E-03). To identify the candidate genes for this locus, transcriptome sequencing data and PC best linear unbiased estimates (BLUE) for 348 inbred lines were combined, and the expression levels of the four genes were correlated with PC. Among the four genes, Zm00001d002625, which encodes an S-adenosyl-L-methionine-dependent methyltransferase superfamily protein, showed significantly different expression levels between two RIL parents in the endosperm and is speculated to be a potential candidate gene for qPC2-2. This study will contribute to further research on the mechanisms underlying the regulation of maize PC, while also providing a genetic basis for marker-assisted selection in the future.

Novel Single-Nucleotide Variants for Morpho-Physiological Traits Involved in Enhancing Drought Stress Tolerance in Barley

Barley (Hordeum vulgare L.) thrives in the arid and semi-arid regions of the world; nevertheless, it suffers large grain yield losses due to drought stress. A panel of 426 lines of barley was evaluated in Egypt under deficit (DI) and full irrigation (FI) during the 2019 and 2020 growing seasons. Observations were recorded on the number of days to flowering (NDF), total chlorophyll content (CH), canopy temperature (CAN), grain filling duration (GFD), plant height (PH), and grain yield (Yield) under DI and FI. The lines were genotyped using the 9K Infinium iSelect single nucleotide polymorphisms (SNP) genotyping platform, which resulted in 6913 high-quality SNPs. In conjunction with the SNP markers, the phenotypic data were subjected to a genome-wide association scan (GWAS) using Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK). The GWAS results indicated that 36 SNPs were significantly associated with the studied traits under DI and FI. Furthermore, eight markers were significant and common across DI and FI water regimes, while 14 markers were uniquely associated with the studied traits under DI. Under DI and FI, three (11_10326, 11_20042, and 11_20170) and five (11_20099, 11_10326, 11_20840, 12_30298, and 11_20605) markers, respectively, had pleiotropic effect on at least two traits. Among the significant markers, 24 were annotated to known barley genes. Most of these genes were involved in plant responses to environmental stimuli such as drought. Overall, nine of the significant markers were previously reported, and 27 markers might be considered novel. Several markers identified in this study could enable the prediction of barley accessions with optimal agronomic performance under DI and FI.

An overview of remote monitoring methods in biodiversity conservation

Conservation of biodiversity is critical for the coexistence of humans and the sustenance of other living organisms within the ecosystem. Identification and prioritization of specific regions to be conserved are impossible without proper information about the sites. Advanced monitoring agencies like the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) had accredited that the sum total of species that are now threatened with extinction is higher than ever before in the past and are progressing toward extinct at an alarming rate. Besides this, the conceptualized global responses to these crises are still inadequate and entail drastic changes. Therefore, more sophisticated monitoring and conservation techniques are required which can simultaneously cover a larger surface area within a stipulated time frame and gather a large pool of data. Hence, this study is an overview of remote monitoring methods in biodiversity conservation via a survey of evidence-based reviews and related studies, wherein the description of the application of some technology for biodiversity conservation and monitoring is highlighted. Finally, the paper also describes various transformative smart technologies like artificial intelligence (AI) and/or machine learning algorithms for enhanced working efficiency of currently available techniques that will aid remote monitoring methods in biodiversity conservation.

Perspective for genomic-enabled prediction against black sigatoka disease and drought stress in polyploid species

Genomic selection (GS) in plant breeding is explored as a promising tool to solve the problems related to the biotic and abiotic threats. Polyploid plants like bananas (Musa spp.) face the problem of drought and black sigatoka disease (BSD) that restrict their production. The conventional plant breeding is experiencing difficulties, particularly phenotyping costs and long generation interval. To overcome these difficulties, GS in plant breeding is explored as an alternative with a great potential for reducing costs and time in selection process. So far, GS does not have the same success in polyploid plants as with diploid plants because of the complexity of their genome. In this review, we present the main constraints to the application of GS in polyploid plants and the prospects for overcoming these constraints. Particular emphasis is placed on breeding for BSD and drought-two major threats to banana production-used in this review as a model of polyploid plant. It emerges that the difficulty in obtaining markers of good quality in polyploids is the first challenge of GS on polyploid plants, because the main tools used were developed for diploid species. In addition to that, there is a big challenge of mastering genetic interactions such as dominance and epistasis effects as well as the genotype by environment interaction, which are very common in polyploid plants. To get around these challenges, we have presented bioinformatics tools, as well as artificial intelligence approaches, including machine learning. Furthermore, a scheme for applying GS to banana for BSD and drought has been proposed. This review is of paramount impact for breeding programs that seek to reduce the selection cycle of polyploids despite the complexity of their genome.

Genetic dissection of fruit maturity date in apricot (P. armeniaca L.) through a Single Primer Enrichment Technology (SPET) approach

Background

Single primer enrichment technology (SPET) is an emerging and increasingly popular solution for high-throughput targeted genotyping in plants. Although SPET requires a priori identification of polymorphisms for probe design, this technology has potentially higher reproducibility and transferability compared to other reduced representation sequencing (RRS) approaches, also enabling the discovery of closely linked polymorphisms surrounding the target one.

Results

The potential for SPET application in fruit trees was evaluated by developing a 25K target SNPs assay to genotype a panel of apricot accessions and progenies. A total of 32,492 polymorphic sites were genotyped in 128 accessions (including 8,188 accessory non-target SNPs) with extremely low levels of missing data and a significant correlation of allelic frequencies compared to whole-genome sequencing data used for array design. Assay performance was further validated by estimating genotyping errors in two biparental progenies, resulting in an overall 1.8% rate. SPET genotyping data were used to infer population structure and to dissect the architecture of fruit maturity date (MD), a quantitative reproductive phenological trait of great agronomical interest in apricot species. Depending on the year, GWAS revealed loci associated to MD on several chromosomes. The QTLs on chromosomes 1 and 4 (the latter explaining most of the phenotypic variability in the panel) were the most consistent over years and were further confirmed by linkage mapping in two segregating progenies.

Conclusions

Besides the utility for marker assisted selection and for paving the way to in-depth studies to clarify the molecular bases of MD trait variation in apricot, the results provide an overview of the performance and reliability of SPET for fruit tree genetics.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08901-1.

Multi-Omics Approaches to Improve Clubroot Resistance in Brassica with a Special Focus on Brassica oleracea L

Brassica oleracea is an agronomically important species of the Brassicaceae family, including several nutrient-rich vegetables grown and consumed across the continents. But its sustainability is heavily constrained by a range of destructive pathogens, among which, clubroot disease, caused by a biotrophic protist Plasmodiophora brassicae, has caused significant yield and economic losses worldwide, thereby threatening global food security. To counter the pathogen attack, it demands a better understanding of the complex phenomenon of Brassica-P. brassicae pathosystem at the physiological, biochemical, molecular, and cellular levels. In recent years, multiple omics technologies with high-throughput techniques have emerged as successful in elucidating the responses to biotic and abiotic stresses. In Brassica spp., omics technologies such as genomics, transcriptomics, ncRNAomics, proteomics, and metabolomics are well documented, allowing us to gain insights into the dynamic changes that transpired during host-pathogen interactions at a deeper level. So, it is critical that we must review the recent advances in omics approaches and discuss how the current knowledge in multi-omics technologies has been able to breed high-quality clubroot-resistant B. oleracea. This review highlights the recent advances made in utilizing various omics approaches to understand the host resistance mechanisms adopted by Brassica crops in response to the P. brassicae attack. Finally, we have discussed the bottlenecks and the way forward to overcome the persisting knowledge gaps in delivering solutions to breed clubroot-resistant Brassica crops in a holistic, targeted, and precise way.

Identification of single major QTL and candidate gene(s) governing hull-less seed trait in pumpkin

The hull-less pumpkin (Cucurbita pepo) seed does not require de-hulling before use for human consumption, as a result highly preferred by the oil, nut, and baking industries. In hull-less seeds, a single recessive gene is responsible for the absence of outer thick seed coat layers; however, the genomic region and gene(s) controlling the trait are unclear to date. In this study, four crosses attempted to derive F₂ and backcross populations confirmed the single recessive gene inheritance of hull-less seed trait in populations adapted to the sub-tropical climate. The candidate genomic region for hull-less seed trait was identified through the BSA-QTLseq approach using bulks of F_2:3 progenies from a cross of HP111 (hulled) and HLP36 (hull-less). A novel genomic region on chromosome 12 ranging from 1.80 to 3.86 Mb was associated with the hull-less seed trait. The re-sequencing data identified a total of 396 SNPs within this region and eight were successfully converted into polymorphic KASP assays. The genotyping of segregating F₂ (n = 160) with polymorphic KASP assays resulted in a 40.3 cM partial linkage map and identified Cp_3430407 (10 cM) and Cp_3498687 (16.1 cM) as flanking markers for hull-less locus (Cphl-1). These flanking markers correspond to the 68.28 kb region in the reference genome, and the marker, Cp_3430407 successfully predicted the genotype in 93.33% of the C. pepo hull-less germplasm lines, thus can be used for marker-assisted selection in parents polymorphic for the hull-less seed trait. The Cphl-1-linked genomic region (2.06 Mb) encompasses a total of 182 genes, including secondary cell wall and lignin biosynthesis-related transcriptional factors viz., "NAC" (Cp4.1LG12g04350) and "MYB" (Cp4.1LG12g03120). These genes were differentially expressed in the seeds of hulled and hull-less genotypes, and therefore could be the potential candidate genes governing the hull-less seed trait in pumpkin.

Genotyping by Sequencing Advancements in Barley

Barley is considered an ideal crop to study cereal genetics due to its close relationship with wheat and diploid ancestral genome. It plays a crucial role in reducing risks to global food security posed by climate change. Genetic variations in the traits of interest in crops are vital for their improvement. DNA markers have been widely used to estimate these variations in populations. With the advancements in next-generation sequencing, breeders could access different types of genetic variations within different lines, with single-nucleotide polymorphisms (SNPs) being the most common type. However, genotyping barley with whole genome sequencing (WGS) is challenged by the higher cost and computational demand caused by the large genome size (5.5GB) and a high proportion of repetitive sequences (80%). Genotyping-by-sequencing (GBS) protocols based on restriction enzymes and target enrichment allow a cost-effective SNP discovery by reducing the genome complexity. In general, GBS has opened up new horizons for plant breeding and genetics. Though considered a reliable alternative to WGS, GBS also presents various computational difficulties, but GBS-specific pipelines are designed to overcome these challenges. Moreover, a robust design for GBS can facilitate the imputation to the WGS level of crops with high linkage disequilibrium. The complete exploitation of GBS advancements will pave the way to a better understanding of crop genetics and offer opportunities for the successful improvement of barley and its close relatives.

Bioinformatics approaches and applications in plant biotechnology

BACKGROUND

In recent years, major advance in molecular biology and genomic technologies have led to an exponential growth in biological information. As the deluge of genomic information, there is a parallel growth in the demands of tools in the storage and management of data, and the development of software for analysis, visualization, modelling, and prediction of large data set.

MAIN BODY

Particularly in plant biotechnology, the amount of information has multiplied exponentially with a large number of databases available from many individual plant species. Efficient bioinformatics tools and methodologies are also developed to allow rapid genome sequence and the study of plant genome in the 'omics' approach. This review focuses on the various bioinformatic applications in plant biotechnology, and their advantages in improving the outcome in agriculture. The challenges or limitations faced in plant biotechnology in the aspect of bioinformatics approach that explained the low progression in plant genomics than in animal genomics are also reviewed and assessed.

CONCLUSION

There is a critical need for effective bioinformatic tools, which are able to provide longer reads with unbiased coverage in order to overcome the complexity of the plant's genome. The advancement in bioinformatics is not only beneficial to the field of plant biotechnology and agriculture sectors, but will also contribute enormously to the future of humanity.

Authentication of Hippophae rhamnoides ssp. sinensis and ssp. mongolica Based on Single Nucleotide Polymorphism at Ribosomal DNA and Their Vitamin Content Analysis

Hippophae rhamnoides widely known as sea buckthorn berries (SB) are rich in vitamins and phytonutrients. The subspecies ssp. sinensis and ssp. mongolica are highly valued for their medicinal properties and vitamin contents, hence domesticated widely across Eurasia and Southeast Asia. Due to the frequent usage of these two subspecies, accurate identification is required to prevent economically motivated adulteration. In this study, we report the single nucleotide polymorphism (SNP) based molecular markers to easily distinguish these two subspecies at 45S nrDNA region. From the determined 45S rDNA region, we designed two primers (5′ sinensis and 5′ mongolica) and developed a multiplex PCR profile. The developed primers effectively distinguished the sea buckthorn subspecies in commercial products as well. Along with the development of subspecies specific primers, we have profiled vitamin contents from H. rhamnoides ssp. sinensis and ssp. mongolica and found ascorbic acid and riboflavin contents were high in both ssp. sinensis and spp. mongolica, yet the content of folic acid was high only in ssp. mongolica. Thus, we provide species specific primers and vitamin profile as an effective authentication of H. rhamnoides.

Data mining of transcriptional biomarkers at different cotton fiber developmental stages

Advancement of the gene expression study provides comprehensive information on pivotal genes at different cotton fiber development stages. For the betterment of cotton fiber yield and their quality, genetic improvement is a major target point for the cotton community. Therefore, various studies were carried out to understand the transcriptional machinery of fiber leading to the detailed integrative as well as innovative study. Through data mining and statistical approaches, we identified and validated the transcriptional biomarkers for staged specific differentiation of fiber. With the unique mapping read matrix of ~ 200 cotton transcriptome data and sequential statistical analysis, we identified several important genes that have a deciding and specific role in fiber cell commitment, initiation and elongation, or secondary cell wall synthesis stage. Based on the importance score and validation analysis, IQ domain 26, Aquaporin, Gibberellin regulated protein, methionine gamma lyase, alpha/beta hydrolases, and HAD-like superfamily have shown the specific and determining role for fiber developmental stages. These genes are represented as transcriptional biomarkers that provide a base for molecular characterization for cotton fiber development which will ultimately determine the high yield.

Genome-Wide Association Study and Genomic Prediction for Bacterial Wilt Resistance in Common Bean (Phaseolus vulgaris) Core Collection

Common bean (Phaseolus vulgaris) is one of the major legume crops cultivated worldwide. Bacterial wilt (BW) of common bean (Curtobacterium flaccumfaciens pv. flaccumfaciens), being a seed-borne disease, has been a challenge in common bean producing regions. A genome-wide association study (GWAS) was conducted to identify SNP markers associated with BW resistance in the USDA common bean core collection. A total of 168 accessions were evaluated for resistance against three different isolates of BW. Our study identified a total of 14 single nucleotide polymorphism (SNP) markers associated with the resistance to BW isolates 528, 557, and 597 using mixed linear models (MLMs) in BLINK, FarmCPU, GAPIT, and TASSEL 5. These SNPs were located on chromosomes Phaseolus vulgaris [Pv]02, Pv04, Pv08, and Pv09 for isolate 528; Pv07, Pv10, and Pv11 for isolate 557; and Pv04, Pv08, and Pv10 for isolate 597. The genomic prediction accuracy was assessed by utilizing seven GP models with 1) all the 4,568 SNPs and 2) the 14 SNP markers. The overall prediction accuracy (PA) ranged from 0.30 to 0.56 for resistance against the three BW isolates. A total of 14 candidate genes were discovered for BW resistance located on chromosomes Pv02, Pv04, Pv07, Pv08, and Pv09. This study revealed vital information for developing genetic resistance against the BW pathogen in common bean. Accordingly, the identified SNP markers and candidate genes can be utilized in common bean molecular breeding programs to develop novel resistant cultivars.

The genetic diversity of Ethiopian barley genotypes in relation to their geographical origin

Ethiopia is recognized as a center of diversity for barley, and its landraces are known for the distinct genetic features compared to other barley collections. The genetic diversity of Ethiopian barley likely results from the highly diverse topography, altitude, climate conditions, soil types, and farming systems. To get detailed information on the genetic diversity a panel of 260 accessions, comprising 239 landraces and 21 barley breeding lines, obtained from the Ethiopian biodiversity institute (EBI) and the national barley improvement program, respectively were studied for their genetic diversity using the 50k iSelect single nucleotide polymorphism (SNP) array. A total of 983 highly informative SNP markers were used for structure and diversity analysis. Three genetically distinct clusters were obtained from the structure analysis comprising 80, 71, and 109 accessions, respectively. Analysis of molecular variance (AMOVA) revealed the presence of higher genetic variation (89%) within the clusters than between the clusters (11%), with moderate genetic differentiation (PhiPT = 0.11) and five accessions were detected as first-generation migrants using Monte Carlo resampling methods. The Mantel test revealed that the genetic distance between accessions is poorly associated with their geographical distance. Despite the observed weak correlation between geographic distance and genetic differentiation, for some regions like Gonder, Jimma, Gamo-Gofa, Shewa, and Welo, more than 50% of the landraces derived from these regions are assigned to one of the three clusters.

Genome-Wide Association Study of Resistance to Phytophthora capsici in the Pepper (Capsicum spp.) Collection

One of the most serious pepper diseases is Phytophthora blight, which is caused by Phytophthora capsici. It is crucial to assess the resistance of pepper genetic resources to Phytophthora blight, understand the genetic resistances, and develop markers for selecting resistant pepper materials in breeding programs. In this study, the resistance of 342 pepper accessions to P. capsici was evaluated. The disease severity score method was used to evaluate the phenotypic responses of pepper accessions inoculated with the KCP7 isolate. A genome-wide association study (GWAS) was performed to identify single nucleotide polymorphisms (SNPs) linked to P. capsici (isolate KCP7) resistance. The pepper population was genotyped using the genotype-by-sequencing (GBS) method, and 45,481 SNPs were obtained. A GWAS analysis was performed using resistance evaluation data and SNP markers. Significantly associated SNPs for P. capsici resistance at 4 weeks after inoculation of the GWAS pepper population were selected. These SNPs for Phytophthora blight resistance were found on all chromosomes except Chr.05, Chr.09, and Chr.11. One of the SNPs found on Chr.02 was converted into a high-resolution melting (HRM) marker, and another marker (QTL5-1) from the previous study was applied to pepper accessions and breeding lines for validation and comparison. This SNP marker was selected because the resistance phenotype and the HRM marker genotype matched well. The selected SNP was named Chr02-1126 and was located at 112 Mb on Chr.02. The Chr02-1126 marker predicted P. capsici resistance with 78.5% accuracy, while the QTL5-1 marker predicted resistance with 80.2% accuracy. Along with the marker for major quantitative traits loci (QTLs) on Chr.05, this Chr02-1126 marker could be used to accurately predict Phytophthora blight resistance in pepper genetic resources. Therefore, this study will assist in the selection of resistant pepper plants in order to breed new phytophthora blight-resistant varieties.

Exploring transposable element-based markers to identify allelic variations underlying agronomic traits in rice

Transposable elements (TEs) are a major force in the production of new alleles during domestication; nevertheless, their use in association studies has been limited because of their complexity. We have developed a TE genotyping pipeline (TEmarker) and applied it to whole-genome genome-wide association study (GWAS) data from 176 Oryza sativa subsp. japonica accessions to identify genetic elements associated with specific agronomic traits. TE markers recovered a large proportion (69%) of single-nucleotide polymorphism (SNP)-based GWAS peaks, and these TE peaks retained ca. 25% of the SNPs. The use of TEs in GWASs may reduce false positives associated with linkage disequilibrium (LD) among SNP markers. A genome scan revealed positive selection on TEs associated with agronomic traits. We found several cases of insertion and deletion variants that potentially resulted from the direct action of TEs, including an allele of LOC_Os11g08410 associated with plant height and panicle length traits. Together, these findings reveal the utility of TE markers for connecting genotype to phenotype and suggest a potential role for TEs in influencing phenotypic variations in rice that impact agronomic traits.

Genome-wide SNPs reveal the fine-scale population structure of Laodelphax striatellus in China using double-digest restriction site-associated DNA sequencing

The small brown planthopper (SBPH), Laodelphax striatellus (Fallén) is one of the most destructive rice pests and has caused serious economic losses in China. To clarify the genetic differentiation and population genetic structure of this insect pest, we investigated the genomic polymorphisms, genetic differentiation, and phylogeography of 31 SBPH populations from 28 sampling sites from three climatic zones of China using double-digest restriction site-associated DNA sequencing (ddRADseq). In total, 2,813,221,369 high-quality paired-end reads from 306 individuals and 1925 single nucleotide polymorphisms (SNPs) were obtained. Low levels of genetic diversity and significant genetic differentiation were observed among the SBPH populations, and three genetic clusters were detected in China. Neutrality tests and bottleneck analysis provided strong evidence for recent rapid expansion with a severe bottleneck in most populations. Our work provides new insights into the genetics of the SBPH and will contribute to the development of effective management strategies for this pest.

Genetic Diversity, Population Structure and Linkage Disequilibrium Analyses in Tropical Maize Using Genotyping by Sequencing

Several maize breeding programs in India have developed numerous inbred lines but the lines have not been characterized using high-density molecular markers. Here, we studied the molecular diversity, population structure, and linkage disequilibrium (LD) patterns in a panel of 314 tropical normal corn, two sweet corn, and six popcorn inbred lines developed by 17 research centers in India, and 62 normal corn from the International Maize and Wheat Improvement Center (CIMMYT). The 384 inbred lines were genotyped with 60,227 polymorphic single nucleotide polymorphisms (SNPs). Most of the pair-wise relative kinship coefficients (58.5%) were equal or close to 0, which suggests the lack of redundancy in the genomic composition in the majority of inbred lines. Genetic distance among most pairs of lines (98.3%) varied from 0.20 to 0.34 as compared with just 1.7% of the pairs of lines that differed by <0.20, which suggests greater genetic variation even among sister lines. The overall average of 17% heterogeneity was observed in the panel indicated the need for further inbreeding in the high heterogeneous genotypes. The mean nucleotide diversity and frequency of polymorphic sites observed in the panel were 0.28 and 0.02, respectively. The model-based population structure, principal component analysis, and phylogenetic analysis revealed three to six groups with no clear patterns of clustering by centers-wise breeding lines, types of corn, kernel characteristics, maturity, plant height, and ear placement. However, genotypes were grouped partially based on their source germplasm from where they derived.

Population Genetics and Development of a Core Collection from Elite Germplasms of Xanthoceras sorbifolium Based on Genome-Wide SNPs

Xanthoceras sorbifolium is one of the most important species of woody oil. In this study, whole genome re-sequencing of 119 X. sorbifolium germplasms was conducted and, after filtering, 105,685,557 high-quality SNPs were identified, which were used to perform population genetics and core collection development analyses. The results from the phylogenetic, population structure, and principal component analyses showed a high level of agreement, with 119 germplasms being classified into three main groups. The germplasms were not completely classified based on their geographical origins and flower colors; furthermore, the genetic backgrounds of these germplasms were complex and diverse. The average polymorphsim information content (PIC) values for the three inferred groups clustered by structure analysis and the six classified color groups were 0.2445 and 0.2628, respectively, indicating a low to medium informative degree of genetic diversity. Moreover, a core collection containing 29.4% (35) out of the 119 X. sorbifolium germplasms was established. Our results revealed the genetic diversity and structure of X. sorbifolium germplasms, and the development of a core collection will be useful for the efficient improvement of breeding programs and genome-wide association studies.

Revealing the Genetic Structure and Differentiation in Endangered Pinus bungeana by Genome-Wide SNP Markers

Understanding the genetic variation and differentiation of natural populations is essential for their protection, specifically if the species status is endangered as with Pinus bungeana. Here, we used 346,840 high density and strong specificity SNP loci to carry out genetic analyses (i.e., genetic diversity, genetic structure, phylogeny, and geographical differentiation) on 52 P. bungeana individuals from 5 populations (4 natural and one artificial) representing the main regions of the species distribution in China. Genetic diversity assessment indicated a trend of genetic diversity gradual decrease from west to east across the species distribution areas. Population genetic structure, PCA and phylogenetic analyses consistently indicated that populations in the central and eastern regions were clustered together, while those from the western regions were separated. Mantel test values indicated the presence of geographic isolation among populations, an important factor contributing to the observed genetic differentiation. The maximum likelihood tree and potential migration events inferred from TreeMix analysis indicated the presence of historical genetic exchanges between the west of Qinling Mountains and the Lvliang Mountains populations. Based on the generated genetic information, in situ and ex situ conservation strategies for P.bungeana germplasm resources are proposed, these strategies could be valuable for the conservation, protection and genetic improvement of this endangered species.

Whole-genome resequencing of Coffea arabica L. (Rubiaceae) genotypes identify SNP and unravels distinct groups showing a strong geographical pattern

BACKGROUND

Coffea arabica L. is an economically important agricultural crop and the most popular beverage worldwide. As a perennial crop with recalcitrant seed, conservation of the genetic resources of coffee can be achieved through the complementary approach of in-situ and ex-situ field genebank. In Ethiopia, a large collection of C. arabica L. germplasm is preserved in field gene banks. Here, we report the whole-genome resequencing of 90 accessions from Choche germplasm bank representing garden and forest-based coffee production systems using Illumina sequencing technology.

RESULTS

The genome sequencing generated 6.41 billion paired-end reads, with a mean of 71.19 million reads per sample. More than 93% of the clean reads were mapped onto the C. arabica L. reference genome. A total of 11.08 million variants were identified, among which 9.74 million (87.9%) were SNPs (Single nucleotide polymorphisms) and 1.34 million (12.1%) were InDels. In all accessions, genomic variants were unevenly distributed across the coffee genome. The phylogenetic analysis using the SNP markers displayed distinct groups.

CONCLUSIONS

Resequencing of the coffee accessions has allowed identification of genetic markers, such as SNPs and InDels. The SNPs discovered in this study might contribute to the variation in important pathways of genes for important agronomic traits such as caffeine content, yield, disease, and pest in coffee. Moreover, the genome resequencing data and the genetic markers identified from 90 accessions provide insight into the genetic variation of the coffee germplasm and facilitate a broad range of genetic studies.

Genetic diversity of local and introduced cassava germplasm in Burundi using DArTseq molecular analyses

In Burundi most small-scale farmers still grow traditional cassava landraces that are adapted to local conditions and have been selected for consumer preferred attributes. They tend to be susceptible, in varying degrees, to devastating cassava viral diseases such as Cassava Brown Streak Disease (CBSD) and Cassava Mosaic Disease (CMD) with annual production losses of US$1 billion. For long term resistance to the disease, several breeding strategies have been proposed. A sound basis for a breeding program is to understand the genetic diversity of both landraces and elite introduced breeding cultivars. This will also assist in efforts to conserve landraces ahead of the broad distribution of improved varieties which have the possibility of replacing landraces. Our study aimed at determining the genetic diversity and relationships within and between local landraces and introduced elite germplasm using morphological and single nucleotide polymorphism (SNP) markers. A total of 118 cultivars were characterized for morphological trait variation based on leaf, stem and root traits, and genetic variation using SNP markers. Results of morphological characterization based on Ward’s Method revealed three main clusters and five accessions sharing similar characteristics. Molecular characterization identified over 18,000 SNPs and six main clusters and three pairs of duplicates which should be pooled together as one cultivar to avoid redundancy. Results of population genetic analysis showed low genetic distance between populations and between local landraces and elite germplasm. Accessions that shared similar morphological traits were divergent at the molecular level indicating that clustering using morphological traits was inconsistent. Despite the variabilities found within the collection, it was observed that cassava germplasm in Burundi have a narrow genetic base.

DNA-Based Tools to Certify Authenticity of Rice Varieties—An Overview

Rice (Oryza sativa L.) is one of the most cultivated and consumed crops worldwide. It is mainly produced in Asia but, due to its large genetic pool, it has expanded to several ecosystems, latitudes and climatic conditions. Europe is a rice producing region, especially in the Mediterranean countries, that grow mostly typical japonica varieties. The European consumer interest in rice has increased over the last decades towards more exotic types, often more expensive (e.g., aromatic rice) and Europe is a net importer of this commodity. This has increased food fraud opportunities in the rice supply chain, which may deliver mixtures with lower quality rice, a problem that is now global. The development of tools to clearly identify undesirable mixtures thus became urgent. Among the various tools available, DNA-based markers are considered particularly reliable and stable for discrimination of rice varieties. This review covers aspects ranging from rice diversity and fraud issues to the DNA-based methods used to distinguish varieties and detect unwanted mixtures. Although not exhaustive, the review covers the diversity of strategies and ongoing improvements already tested, highlighting important advantages and disadvantages in terms of costs, reliability, labor-effort and potential scalability for routine fraud detection.

Improve Soybean Variety Selection Accuracy Using UAV-Based High-Throughput Phenotyping Technology

The efficiency of crop breeding programs is evaluated by the genetic gain of a primary trait of interest, e.g., yield, achieved in 1 year through artificial selection of advanced breeding materials. Conventional breeding programs select superior genotypes using the primary trait (yield) based on combine harvesters, which is labor-intensive and often unfeasible for single-row progeny trials (PTs) due to their large population, complex genetic behavior, and high genotype-environment interaction. The goal of this study was to investigate the performance of selecting superior soybean breeding lines using image-based secondary traits by comparing them with the selection of breeders. A total of 11,473 progeny rows (PT) were planted in 2018, of which 1,773 genotypes were selected for the preliminary yield trial (PYT) in 2019, and 238 genotypes advanced for the advanced yield trial (AYT) in 2020. Six agronomic traits were manually measured in both PYT and AYT trials. A UAV-based multispectral imaging system was used to collect aerial images at 30 m above ground every 2 weeks over the growing seasons. A group of image features was extracted to develop the secondary crop traits for selection. Results show that the soybean seed yield of the selected genotypes by breeders was significantly higher than that of the non-selected ones in both yield trials, indicating the superiority of the breeder's selection for advancing soybean yield. A least absolute shrinkage and selection operator model was used to select soybean lines with image features and identified 71 and 76% of the selection of breeders for the PT and PYT. The model-based selections had a significantly higher average yield than the selection of a breeder. The soybean yield selected by the model in PT and PYT was 4 and 5% higher than those selected by breeders, which indicates that the UAV-based high-throughput phenotyping system is promising in selecting high-yield soybean genotypes.

Assessment of Genetic Diversity and Relatedness in an Andean Potato Collection from Argentina by High-Density Genotyping

Native potatoes are the most diverse among cultivated potato species and thus constitute a valuable source for identifying genes for potato improvement. Nevertheless, high-density mapping, needed to reveal allelic diversity, has not been performed for native Argentinian potatoes. We present a study of the genetic variability and population structure of 96 Andigena potatoes from Northwestern Argentina performed using a subset of 5035 SNPs with no missing data and full reproducibility. These high-density markers are distributed across the genome and present a good coverage of genomic regions. A Bayesian approach revealed the presence of: (I) a major group comprised of most of the Andean accessions; (II) a smaller group containing the out-group cv. Spunta and the sequenced genotype DM; and (III) a third group containing colored flesh potatoes. This grouping was also consistent when maximum likelihood trees were constructed and further confirmed by a principal coordinate analysis. A group of 19 accessions stored as Andean varieties clustered consistently with group Tuberosum accessions. This was in agreement with previous studies and we hypothesize that they may be reintroductions of European-bred long day-adapted potatoes. The present study constitutes a valuable source for allele mining of genes of interest and thus provides a tool for association mapping studies.

Genome-wide core sets of SNP markers and Fluidigm assays for rapid and effective genotypic identification of Korean cultivars of lettuce (Lactuca sativa L.)

Lettuce is one of the economically important leaf vegetables and is cultivated mainly in temperate climate areas. Cultivar identification based on the distinctness, uniformity, and stability (DUS) test is a prerequisite for new cultivar registration. However, DUS testing based on morphological features is time-consuming, labor-intensive, and costly, and can also be influenced by environmental factors. Thus, molecular markers have also been used for the identification of genetic diversity as an effective, accurate, and stable method. Currently, genome-wide single nucleotide polymorphisms (SNPs) using next-generation sequencing technology are commonly applied in genetic research on diverse plant species. This study aimed to establish an effective and high-throughput cultivar identification system for lettuce using core sets of SNP markers developed by genotyping by sequencing (GBS). GBS identified 17 877 high-quality SNPs for 90 commercial lettuce cultivars. Genetic differentiation analyses based on the selected SNPs classified the lettuce cultivars into three main groups. Core sets of 192, 96, 48, and 24 markers were further selected and validated using the Fluidigm platform. Phylogenetic analyses based on all core sets of SNPs successfully discriminated individual cultivars that have been currently recognized. These core sets of SNP markers will support the construction of a DNA database of lettuce that can be useful for cultivar identification and purity testing, as well as DUS testing in the plant variety protection system. Additionally, this work will facilitate genetic research to improve breeding in lettuce.