Adapting Genotyping-by-Sequencing for Rice F2 Populations

MCPtaggR: R package for accurate genotype calling in reduced representation sequencing data by eliminating error-prone markers based on genome comparison

Reduced representation sequencing (RRS) offers cost-effective, high-throughput genotyping platforms such as genotyping-by-sequencing (GBS). RRS reads are typically mapped onto a reference genome. However, mapping reads harbouring mismatches against the reference can potentially result in mismapping and biased mapping, leading to the detection of error-prone markers that provide incorrect genotype information. We established a genotype-calling pipeline named mappable collinear polymorphic tag genotyping (MCPtagg) to achieve accurate genotyping by eliminating error-prone markers. MCPtagg was designed for the RRS-based genotyping of a population derived from a biparental cross. The MCPtagg pipeline filters out error-prone markers prior to genotype calling based on marker collinearity information obtained by comparing the genome sequences of the parents of a population to be genotyped. A performance evaluation on real GBS data from a rice F2 population confirmed its effectiveness. Furthermore, our performance test using a genome assembly that was obtained by genome sequence polishing on an available genome assembly suggests that our pipeline performs well with converted genomes, rather than necessitating de novo assembly. This demonstrates its flexibility and scalability. The R package, MCPtaggR, was developed to provide functions for the pipeline and is available at https://github.com/tomoyukif/MCPtaggR.

Loss-of-function of an α-SNAP gene confers resistance to soybean cyst nematode

Plant-parasitic nematodes are one of the most economically impactful pests in agriculture resulting in billions of dollars in realized annual losses worldwide. Soybean cyst nematode (SCN) is the number one biotic constraint on soybean production making it a priority for the discovery, validation and functional characterization of native plant resistance genes and genetic modes of action that can be deployed to improve soybean yield across the globe. Here, we present the discovery and functional characterization of a soybean resistance gene, GmSNAP02. We use unique bi-parental populations to fine-map the precise genomic location, and a combination of whole genome resequencing and gene fragment PCR amplifications to identify and confirm causal haplotypes. Lastly, we validate our candidate gene using CRISPR-Cas9 genome editing and observe a gain of resistance in edited plants. This demonstrates that the GmSNAP02 gene confers a unique mode of resistance to SCN through loss-of-function mutations that implicate GmSNAP02 as a nematode virulence target. We highlight the immediate impact of utilizing GmSNAP02 as a genome-editing-amenable target to diversify nematode resistance in commercially available cultivars.

Fantastic genes: where and how to find them? Exploiting rice genetic resources for the improvement of yield, tolerance, and resistance to a wide array of stresses in rice

Rice production is a critical component of global food security. To date, rice is grown in over 100 countries and is the primary source of food for more than 3 billion people. Despite its importance, rice production is facing numerous challenges that threaten its future viability. One of the primary problems is the advent of climate change. The changing climatic conditions greatly affect the growth and productivity of rice crop and the quality of rice yield. Similarly, biotic stresses brought about by pathogen and pest infestations are greatly affecting the productivity of rice. To address these issues, the utilization of rice genetic resources is necessary to map, identify, and understand the genetics of important agronomic traits. This review paper highlights the role of rice genetic resources for developing high-yielding and stress-tolerant rice varieties. The integration of genetic, genomic, and phenomic tools in rice breeding programs has led to the development of high-yielding and stress-tolerant rice varieties. The collaboration of multidisciplinary teams of experts, sustainable farming practices, and extension services for farmers is essential for accelerating the development of high-yielding and stress-tolerant rice varieties.

Genetic analysis and QTL mapping of domestication-related traits in chili pepper (Capsicum annuum L.)

Chili pepper (Capsicum annuum L.) is one of the oldest and most phenotypically diverse pre-Columbian crops of the Americas. Despite the abundance of genetic resources, the use of wild germplasm and landraces in chili pepper breeding is limited. A better understanding of the evolutionary history in chili peppers, particularly in the context of traits of agronomic interest, can contribute to future improvement and conservation of genetic resources. In this study, an F₂:₃ mapping population derived from a cross between a C. annuum wild accession (Chiltepin) and a cultivated variety (Puya) was used to identify genomic regions associated with 19 domestication and agronomic traits. A genetic map was constructed consisting of 1023 single nucleotide polymorphism (SNP) markers clustered into 12 linkage groups and spanning a total of 1,263.87 cM. A reciprocal translocation that differentiates the domesticated genome from its wild ancestor and other related species was identified between chromosomes 1 and 8. Quantitative trait locus (QTL) analysis detected 20 marker-trait associations for 13 phenotypes, from which 14 corresponded to previously identified loci, and six were novel genomic regions related to previously unexplored domestication-syndrome traits, including form of unripe fruit, seedlessness, deciduous fruit, and growth habit. Our results revealed that the genetic architecture of Capsicum domestication is similar to other domesticated species with few loci with large effects, the presence of QTLs clusters in different genomic regions, and the predominance of domesticated recessive alleles. Our analysis indicates the domestication process in chili pepper has also had an effect on traits not directly related to the domestication syndrome. The information obtained in this study provides a more complete understanding of the genetic basis of Capsicum domestication that can potentially guide strategies for the exploitation of wild alleles.

Genetic Variation of Blast (Pyricularia oryzae Cavara) Resistance in the Longistaminata Chromosome Segment Introgression Lines (LCSILs) and Potential for Breeding Use in Kenya

In Kenya's rice-growing areas, Basmati varieties have been produced in monoculture since the late 1980s. This has resulted in the breakdown of the resistance (R) gene-mediated response of the local Basmati varieties to blast disease caused by Pyricularia oryzae. To improve blast resistance in Kenyan Basmati varieties, continuous identification of R genes and suitable breeding materials for Basmati are necessary. Longistaminata chromosome segment introgression lines (LCSILs) with the Kernel Basmati genetic background, developed using a rice line called potential low-input adaptable-1 (pLIA-1) derived from a cross between Taichung 65 (T65) (a rice variety in the Japonica Group) and O. longistaminata, are expected to contain useful blast R genes derived from O. longistaminata or T65. In this study, we investigated the genetic variation of blast R genes in LCSILs and their parents by using a new international differential system for designating blast races based on the gene-for-gene theory and molecular characterization using single nucleotide polymorphism (SNP) markers. LCSILs and their parents were classified into three groups-A, B1, and B2-based on reaction patterns to the standard differential blast isolates (SDBIs). Group A, including pLIA-1, showed the highest resistance in all groups, followed by groups B1 and B2. Kernel Basmati in group B1 was considered to possess Pik-p or Pi7(t), Pi19(t), and other unknown R genes. In addition to these R genes, LCSIL 6, 12, 27, 28, and 40, in group A, were determined to possess one of Pish, Piz-t, or both genes that confer resistance to the Kenyan blast races. These lines can be used for efficiently pyramiding blast R genes in the local Basmati varieties.

Domesticating Vigna stipulacea: Chromosome-Level genome assembly reveals VsPSAT1 as a candidate gene decreasing hard-seededness

To increase food production under the challenges presented by global climate change, the concept of de novo domestication-utilizing stress-tolerant wild species as new crops-has recently gained considerable attention. We had previously identified mutants with desired domestication traits in a mutagenized population of the legume Vigna stipulacea Kuntze (minni payaru) as a pilot for de novo domestication. Given that there are multiple stress-tolerant wild legume species, it is important to establish efficient domestication processes using reverse genetics and identify the genes responsible for domestication traits. In this study, we identified VsPSAT1 as the candidate gene responsible for decreased hard-seededness, using a Vigna stipulacea isi2 mutant that takes up water from the lens groove. Scanning electron microscopy and computed tomography revealed that the isi2 mutant has lesser honeycomb-like wax sealing the lens groove than the wild-type, and takes up water from the lens groove. We also identified the pleiotropic effects of the isi2 mutant: accelerating leaf senescence, increasing seed size, and decreasing numbers of seeds per pod. While doing so, we produced a V. stipulacea whole-genome assembly of 441 Mbp in 11 chromosomes and 30,963 annotated protein-coding sequences. This study highlights the importance of wild legumes, especially those of the genus Vigna with pre-existing tolerance to biotic and abiotic stresses, for global food security during climate change.

Identification of Genomic Regions Associated with High Grain Zn Content in Polished Rice Using Genotyping-by-Sequencing (GBS)

Globally, micronutrient (iron and zinc) enriched rice has been a sustainable and cost-effective solution to overcome malnutrition or hidden hunger. Understanding the genetic basis and identifying the genomic regions for grain zinc (Zn) across diverse genetic backgrounds is an important step to develop biofortified rice varieties. In this case, an RIL population (306 RILs) obtained from a cross between the high-yielding rice variety MTU1010 and the high-zinc rice variety Ranbir Basmati was utilized to pinpoint the genomic region(s) and QTL(s) responsible for grain zinc (Zn) content. A total of 2746 SNP markers spanning a genetic distance of 2445 cM were employed for quantitative trait loci (QTL) analysis, which resulted in the identification of 47 QTLs for mineral (Zn and Fe) and agronomic traits with 3.5-36.0% phenotypic variance explained (PVE) over the seasons. On Chr02, consistent QTLs for grain Zn polished (qZnPR.2.1) and Zn brown (qZnBR.2.2) were identified. On Chr09, two additional reliable QTLs for grain Zn brown (qZnBR.9.1 and qZnBR.9.2) were identified. The major-effect QTLs identified in this study were associated with few key genes related to Zn and Fe transporter activity. The genomic regions, candidate genes, and molecular markers associated with these major QTLs will be useful for genomic-assisted breeding for developing Zn-biofortified varieties.

Utilization of Genotyping-by-Sequencing (GBS) for Rice Pre-Breeding and Improvement: A Review

Molecular markers play a crucial role in the improvement of rice. To benefit from these markers, genotyping is carried out to identify the differences at a specific position in the genome of individuals. The advances in sequencing technologies have led to the development of different genotyping techniques such as genotyping-by-sequencing. Unlike PCR-fragment-based genotyping, genotyping-by-sequencing has enabled the parallel sequencing and genotyping of hundreds of samples in a single run, making it more cost-effective. Currently, GBS is being used in several pre-breeding programs of rice to identify beneficial genes and QTL from different rice genetic resources. In this review, we present the current advances in the utilization of genotyping-by-sequencing for the development of rice pre-breeding materials and the improvement of existing rice cultivars. The challenges and perspectives of using this approach are also highlighted.

Linkage analysis and residual heterozygotes derived near isogenic lines reveals a novel protein quantitative trait loci from a Glycine soja accession

Modern soybean [Glycine max (L.) Merr] cultivars have low overall genetic variation due to repeated bottleneck events that arose during domestication and from selection strategies typical of many soybean breeding programs. In both public and private soybean breeding programs, the introgression of wild soybean (Glycine soja Siebold and Zucc.) alleles is a viable option to increase genetic diversity and identify new sources for traits of value. The objectives of our study were to examine the genetic architecture responsible for seed protein and oil using a recombinant inbred line (RIL) population derived from hybridizing a G. max line ('Osage') with a G. soja accession (PI 593983). Linkage mapping identified a total of seven significant quantitative trait loci on chromosomes 14 and 20 for seed protein and on chromosome 8 for seed oil with LOD scores ranging from 5.3 to 31.7 for seed protein content and from 9.8 to 25.9 for seed oil content. We analyzed 3,015 single F4:9 soybean plants to develop two residual heterozygotes derived near isogenic lines (RHD-NIL) populations by targeting nine SNP markers from genotype-by-sequencing, which corresponded to two novel quantitative trait loci (QTL) derived from G. soja: one for a novel seed oil QTL on chromosome 8 and another for a novel protein QTL on chromosome 14. Single marker analysis and linkage analysis using 50 RHD-NILs validated the chromosome 14 protein QTL, and whole genome sequencing of RHD-NILs allowed us to reduce the QTL interval from ∼16.5 to ∼4.6 Mbp. We identified two genomic regions based on recombination events which had significant increases of 0.65 and 0.72% in seed protein content without a significant decrease in seed oil content. A new Kompetitive allele-specific polymerase chain reaction (KASP) assay, which will be useful for introgression of this trait into modern elite G. max cultivars, was developed in one region. Within the significantly associated genomic regions, a total of eight genes are considered as candidate genes, based on the presence of gene annotations associated with the protein or amino acid metabolism/movement. Our results provide better insights into utilizing wild soybean as a source of genetic diversity for soybean cultivar improvement utilizing native traits.

A Novel Combination of Genes Causing Temperature-Sensitive Hybrid Weakness in Rice

Reproductive isolation is an obstacle for plant breeding when a distant cross is demanded. It can be divided into two main types based on different growth stages: prezygotic isolation and postzygotic isolation. The hybrid weakness, which is a type of postzygotic isolation, can become a problem in crop breeding. In order to overcome reproductive isolation, it is necessary to elucidate its mechanism. In this study, genetic analysis for low temperature-dependent hybrid weakness was conducted in a rice F2 population derived from Taichung 65 (T65, Japonica) and Lijiangxintuanheigu (LTH, Japonica). The weak and severe weak plants in F2 showed shorter culm length, late heading, reduced panicle number, decreased grain numbers per panicle, and impaired root development in the field. Our result also showed that hybrid weakness was affected by temperature. It was observed that 24°C enhanced hybrid weakness, whereas 34°C showed recovery from hybrid weakness. In terms of the morphology of embryos, no difference was observed. Therefore, hybrid weakness affects postembryonic development and is independent of embryogenesis. The genotypes of 126 F2 plants were determined through genotyping-by-sequencing and a linkage map consisting of 862 single nucleotide polymorphism markers was obtained. Two major quantitative trait loci (QTLs) were detected on chromosomes 1 [hybrid weakness j 1 (hwj1)] and 11 [hybrid weakness j 2 (hwj2)]. Further genotyping indicated that the hybrid weakness was due to an incompatible interaction between the T65 allele of hwj1 and the LTH allele of hwj2. A large F2 populations consisting of 5,722 plants were used for fine mapping of hwj1 and hwj2. The two loci, hwj1 and hwj2, were mapped in regions of 65-kb on chromosome 1 and 145-kb on chromosome 11, respectively. For hwj1, the 65-kb region contained 11 predicted genes, while in the hwj2 region, 22 predicted genes were identified, two of which are disease resistance-related genes. The identified genes along these regions serve as preliminary information on the molecular networks associated with hybrid weakness in rice.

High-Density Mapping of Quantitative Trait Loci Controlling Agronomically Important Traits in Quinoa (Chenopodium quinoa Willd.)

Quinoa is a pseudocereal originating from the Andean regions. Despite quinoa's long cultivation history, genetic analysis of this crop is still in its infancy. We aimed to localize quantitative trait loci (QTL) contributing to the phenotypic variation of agronomically important traits. We crossed the Chilean accession PI-614889 and the Peruvian accession CHEN-109, which depicted significant differences in days to flowering, days to maturity, plant height, panicle length, and thousand kernel weight (TKW), saponin content, and mildew susceptibility. We observed sizeable phenotypic variation across F2 plants and F3 families grown in the greenhouse and the field, respectively. We used Skim-seq to genotype the F2 population and constructed a high-density genetic map with 133,923 single nucleotide polymorphism (SNPs). Fifteen QTL were found for ten traits. Two significant QTL, common in F2 and F3 generations, depicted pleiotropy for days to flowering, plant height, and TKW. The pleiotropic QTL harbored several putative candidate genes involved in photoperiod response and flowering time regulation. This study presents the first high-density genetic map of quinoa that incorporates QTL for several important agronomical traits. The pleiotropic loci can facilitate marker-assisted selection in quinoa breeding programs.

Genotyping by sequencing-based linkage map construction and identification of quantitative trait loci for yield-related traits and oil content in Jatropha (Jatropha curcas L.)

BACKGROUND

Jatropha (Jatropha curcas L.) has been considered as a potential bioenergy crop and its genetic improvement is essential for higher seed yield and oil content which has been hampered due to lack of desirable molecular markers.

METHODS AND RESULTS

An F₂ population was created using an intraspecific cross involving a Central American line RJCA9 and an Asiatic species RJCS-9 to develop a dense genetic map and for Quantitative trait loci (QTL) identification. The genotyping-by-sequencing (GBS) approach was used to genotype the mapping population of 136 F₂ individuals along with the two parental lines for classification of the genotypes based on single nucleotide polymorphism (SNPs). NextSeq 2500 sequencing technology provided a total of 517.23 million clean reads, with an average of ~ 3.8 million reads per sample. We analysed 411 SNP markers and developed 11 linkage groups. The total length of the genetic map was 4092.3 cM with an average marker interval of 10.04 cM. We have identified a total of 83 QTLs for various yield and oil content governing traits. The percentage of phenotypic variation (PV) was found to be in the range of 8.81 to 65.31%, and a QTL showed the maximum PV of 65.3% for a total seed number on the 6th linkage group (LG).

CONCLUSIONS

The QTLs detected in this study for various phenotypic traits will lay down the path for marker-assisted breeding in the future and cloning of genes that are responsible for phenotypic variation.

Characterization and Mapping of retr04, retr05 and retr06 Broad-Spectrum Resistances to Turnip Mosaic Virus in Brassica juncea, and the Development of Robust Methods for Utilizing Recalcitrant Genotyping Data

Turnip mosaic virus (TuMV) induces disease in susceptible hosts, notably impacting cultivation of important crop species of the Brassica genus. Few effective plant viral disease management strategies exist with the majority of current approaches aiming to mitigate the virus indirectly through control of aphid vector species. Multiple sources of genetic resistance to TuMV have been identified previously, although the majority are strain-specific and have not been exploited commercially. Here, two Brassica juncea lines (TWBJ14 and TWBJ20) with resistance against important TuMV isolates (UK 1, vVIR24, CDN 1, and GBR 6) representing the most prevalent pathotypes of TuMV (1, 3, 4, and 4, respectively) and known to overcome other sources of resistance, have been identified and characterized. Genetic inheritance of both resistances was determined to be based on a recessive two-gene model. Using both single nucleotide polymorphism (SNP) array and genotyping by sequencing (GBS) methods, quantitative trait loci (QTL) analyses were performed using first backcross (BC₁) genetic mapping populations segregating for TuMV resistance. Pairs of statistically significant TuMV resistance-associated QTLs with additive interactive effects were identified on chromosomes A03 and A06 for both TWBJ14 and TWBJ20 material. Complementation testing between these B. juncea lines indicated that one resistance-linked locus was shared. Following established resistance gene nomenclature for recessive TuMV resistance genes, these new resistance-associated loci have been termed retr04 (chromosome A06, TWBJ14, and TWBJ20), retr05 (A03, TWBJ14), and retr06 (A03, TWBJ20). Genotyping by sequencing data investigated in parallel to robust SNP array data was highly suboptimal, with informative data not established for key BC₁ parental samples. This necessitated careful consideration and the development of new methods for processing compromised data. Using reductive screening of potential markers according to allelic variation and the recombination observed across BC₁ samples genotyped, compromised GBS data was rendered functional with near-equivalent QTL outputs to the SNP array data. The reductive screening strategy employed here offers an alternative to methods relying upon imputation or artificial correction of genotypic data and may prove effective for similar biparental QTL mapping studies.

Meiosis in crops: from genes to genomes

Meiosis is a key feature of sexual reproduction. During meiosis homologous chromosomes replicate, recombine, and randomly segregate, followed by the segregation of sister chromatids to produce haploid cells. The unique genotypes of recombinant gametes are an essential substrate for the selection of superior genotypes in natural populations and in plant breeding. In this review we summarize current knowledge on meiosis in diverse monocot and dicot crop species and provide a comprehensive resource of cloned meiotic mutants in six crop species (rice, maize, wheat, barley, tomato, and Brassica species). Generally, the functional roles of meiotic proteins are conserved between plant species, but we highlight notable differences in mutant phenotypes. The physical lengths of plant chromosomes vary greatly; for instance, wheat chromosomes are roughly one order of magnitude longer than those of rice. We explore how chromosomal distribution for crossover recombination can vary between species. We conclude that research on meiosis in crops will continue to complement that in Arabidopsis, and alongside possible applications in plant breeding will facilitate a better understanding of how the different stages of meiosis are controlled in plant species.

RAD-R scripts: R pipeline for RAD-seq from FASTQ files to linkage maps construction and run R/QTL, operating only at copying and pasting scripts into R console

Coupled with the reduction in sequencing costs, the number of RAD-seq analysis have been surging, generating vast genetic knowledge in relation with many crops. Specialized platforms might be intimidating to non-expert users and difficult to implement on each computer despite the growing interest in the usage of the dataset obtained by high-throughput sequencing. Therefore, RAD-R scripts were developed on Windows10 for RAD-seq analysis, allowing users who are not familiar with bioinformatics to easily analyze big sequence data. These RAD-R scripts that run a flow from raw sequence reads of F₂ population for the self-fertilization plants to the linkage map construction as well as the QTL analysis can be also useful to many users with limited experience due to the simplicity of copying Excel cells into the R console. During the comparison of linkage maps constructed by RAD-R scripts and Stacks, RAD-R scripts were shown to construct the linkage map with less missing genotype data and a shorter total genetic distance. QTL analysis results can be easily obtained by selecting the reliable genotype data that is visually inferred to be appropriate for error correction from the genotype data files created by RAD-R scripts.

Genome-Wide Scanning Enabled SNP Discovery, Linkage Disequilibrium Patterns and Population Structure in a Panel of Fonio (Digitaria exilis [Kippist] Stapf) Germplasm

White fonio (Digitaria exilis) is a staple food for millions of people in arid and semi-arid areas of West Africa. Knowledge about nutritional and health benefits, insights into morphological diversity, and the recent development of genomic resources call for a better understanding of the genetic structure of the extant germplasm gathered throughout the region in order to set up a robust breeding program. We assessed the genetic diversity and population structure of 259 fonio individuals collected from six countries from West Africa (Nigeria, Benin, Guinea, Mali, Burkina Faso and Niger) in this study using 688 putative out of 21,324 DArTseq-derived SNP markers. Due to the inbreeding and small population size, the results revealed a substantial level of genetic variability. Furthermore, two clusters were found irrespective of the geographic origins of accessions. Moreover, the high level of linkage disequilibrium (LD) between loci observed resulted from the mating system of the crop, which is often associated with a low recombination rate. These findings fill the gaps about the molecular diversity and genetic structure of the white fonio germplasm in West Africa. This was required for the application of genomic tools that can potentially speed up the genetic gain in fonio millet breeding for complex traits such as yield, and other nutrient contents.

Cryptic introgressions contribute to transgressive segregation for early blight resistance in tomato

We identified cryptic early blight resistance introgressions in tomato breeding lines and demonstrated efficient genotypic selection for resistance in the context of a tomato breeding program. Early blight is a widespread and problematic disease affecting tomatoes (Solanum lycopersicum). Caused by the fungal pathogen Alternaria linariae (syn. A. tomatophila), symptoms include lesions on tomato stems, fruit, and foliage, often resulting in yield losses. Breeding tomatoes with genetic resistance would enhance production sustainability. Using cross-market breeding populations, we identified several quantitative trait loci (QTL) associated with early blight resistance. Early blight resistance putatively derived from 'Campbell 1943' was confirmed in modern fresh market tomato breeding lines. This resistance offered substantial protection against early blight stem lesions (collar rot) and moderate protection from defoliation. A distinctive and potentially novel form of early blight foliar resistance was discovered in a processing tomato breeding line and is probably derived from S. pimpinellifolium via 'Hawaii 7998'. Additional field trials validated the three most promising large-effect QTL, EB-1.2, EB-5, and EB-9. Resistance effects for EB-5 and EB-9 were consistent across breeding populations and environments, while EB-1.2's effect was population specific. Using genome-wide marker-assisted backcrossing, we developed fresh market tomato lines that were near-isogenic for early blight QTL. Resistance in these lines was largely mediated by just two QTL, EB-5 and EB-9, that together captured 49.0 and 68.7% of the defoliation and stem lesion variance, respectively. Our work showcases the value of mining cryptic introgressions in tomato lines, and across market classes, for use as additional sources of disease resistance.

In Search of Species-Specific SNPs in a Non-Model Animal (European Bison (Bison bonasus))-Comparison of De Novo and Reference-Based Integrated Pipeline of STACKS Using Genotyping-by-Sequencing (GBS) Data

The European bison is a non-model organism; thus, most of its genetic and genomic analyses have been performed using cattle-specific resources, such as BovineSNP50 BeadChip or Illumina Bovine 800 K HD Bead Chip. The problem with non-specific tools is the potential loss of evolutionary diversified information (ascertainment bias) and species-specific markers. Here, we have used a genotyping-by-sequencing (GBS) approach for genotyping 256 samples from the European bison population in Bialowieza Forest (Poland) and performed an analysis using two integrated pipelines of the STACKS software: one is de novo (without reference genome) and the other is a reference pipeline (with reference genome). Moreover, we used a reference pipeline with two different genomes, i.e., Bos taurus and European bison. Genotyping by sequencing (GBS) is a useful tool for SNP genotyping in non-model organisms due to its cost effectiveness. Our results support GBS with a reference pipeline without PCR duplicates as a powerful approach for studying the population structure and genotyping data of non-model organisms. We found more polymorphic markers in the reference pipeline in comparison to the de novo pipeline. The decreased number of SNPs from the de novo pipeline could be due to the extremely low level of heterozygosity in European bison. It has been confirmed that all the de novo/Bos taurus and Bos taurus reference pipeline obtained SNPs were unique and not included in 800 K BovineHD BeadChip.

Development of an Aus-Derived Nested Association Mapping (Aus-NAM) Population in Rice

A genetic resource for studying genetic architecture of agronomic traits and environmental adaptation is essential for crop improvements. Here, we report the development of a rice nested association mapping population (aus-NAM) using 7 aus varieties as diversity donors and T65 as the common parent. Aus-NAM showed broad phenotypic variations. To test whether aus-NAM was useful for quantitative trait loci (QTL) mapping, known flowering genes (Ehd1, Hd1, and Ghd7) in rice were characterized using single-family QTL mapping, joint QTL mapping, and the methods based on genome-wide association study (GWAS). Ehd1 was detected in all the seven families and all the methods. On the other hand, Hd1 and Ghd7 were detected in some families, and joint QTL mapping and GWAS-based methods resulted in weaker and uncertain peaks. Overall, the high allelic variations in aus-NAM provide a valuable genetic resource for the rice community.

Genetic Mapping by Sequencing More Precisely Detects Loci Responsible for Anaerobic Germination Tolerance in Rice

Direct seeded rice (DSR) is a mainstay for planting rice in the Americas, and it is rapidly becoming more popular in Asia. It is essential to develop rice varieties that are suitable for this type of production system. ASD1, a landrace from India, possesses several traits desirable for direct-seeded fields, including tolerance to anaerobic germination (AG). To map the genetic basis of its tolerance, we examined a population of 200 F_2:3 families derived from a cross between IR64 and ASD1 using the restriction site-associated DNA sequencing (RAD-seq) technology. This genotyping platform enabled the identification of 1921 single nucleotide polymorphism (SNP) markers to construct a high-resolution genetic linkage map with an average interval of 0.9 cM. Two significant quantitative trait loci (QTLs) were detected on chromosomes 7 and 9, qAG7 and qAG9, with LOD scores of 7.1 and 15.0 and R² values of 15.1 and 29.4, respectively. Here, we obtained more precise locations of the QTLs than traditional simple sequence repeat and low-density SNP genotyping methods and may help further dissect the genetic factors of these QTLs.

Identification of Promising RILs for High Grain Zinc Through Genotype × Environment Analysis and Stable Grain Zinc QTL Using SSRs and SNPs in Rice (Oryza sativa L.)

Polished rice is one of the commonly consumed staple foods across the world. However, it contains limited nutrients especially iron (Fe) and zinc (Zn). To identify promising recombinant inbred lines (RILs) for grain Zn and single plant yield, 190 RILs developed from PR116 and Ranbir Basmati were evaluated in two environments (E1 and E2). A subset of 44 contrasting RILs for grain Zn was screened in another two environments (E3 and E4). Phenotypic data was collected for 10 traits, viz., days to 50% flowering, plant height, panicle length, number of tillers, single plant yield (SPY), test weight, Fe and Zn in brown (IBR, ZBR), and polished rice (IPR, ZPR). Stepwise regression analysis of trait data in 190 RILs and a subset of 44 RILs revealed the interdependence of ZPR, ZBR, IPR, and IBR and the negative association of grain Zn with single plant yield. Based on the additive main effect and multiplicative interaction (AMMI) and genotype and genotype × environment interaction (GGE) analyses of the subset of 44 RILs across four environments (E1-E4), six promising RILs were identified for ZPR with >28 ppm. Mapping of 190 RILs with 102 simple sequence repeats (SSRs) resulted in 13 QTLs for best linear unbiased estimates (BLUEs) of traits including advantage over check (AOC). Using genotype-based sequencing (GBS), the subset of 44 RILs was mapped with 1035 single-nucleotide polymorphisms (SNPs) and 21 QTLs were identified. More than 100 epistatic interactions were observed. A major QTL qZPR.1.1 (PV 37.84%) and another QTL qZPR.11.1 (PV 15.47%) were identified for grain Zn in polished rice. A common major QTL (qZBR.2.1 and qZPR.2.1) was also identified on chromosome 2 for grain Zn content across SSR and SNP maps. Two potential candidate genes related to transporters were identified based on network analyses in the genomic regions of QTL < 3 Mb. The RILs identified for grain Zn and SPY were nominated for national evaluation as under rice biofortification, and two QTLs identified based on BLUEs could be used in the rice biofortification breeding programs.

Linkage mapping and QTL analysis of flowering time using ddRAD sequencing with genotype error correction in Brassica napus

BACKGROUND

Brassica napus is an important oilseed crop cultivated worldwide. During domestication and breeding of B. napus, flowering time has been a target of selection because of its substantial impact on yield. Here we use double digest restriction-site associated DNA sequencing (ddRAD) to investigate the genetic basis of flowering in B. napus. An F₂ mapping population was derived from a cross between an early-flowering spring type and a late-flowering winter type.

RESULTS

Flowering time in the mapping population differed by up to 25 days between individuals. High genotype error rates persisted after initial quality controls, as suggested by a genotype discordance of ~ 12% between biological sequencing replicates. After genotype error correction, a linkage map spanning 3981.31 cM and compromising 14,630 single nucleotide polymorphisms (SNPs) was constructed. A quantitative trait locus (QTL) on chromosome C2 was detected, covering eight flowering time genes including FLC.

CONCLUSIONS

These findings demonstrate the effectiveness of the ddRAD approach to sample the B. napus genome. Our results also suggest that ddRAD genotype error rates can be higher than expected in F₂ populations. Quality filtering and genotype correction and imputation can substantially reduce these error rates and allow effective linkage mapping and QTL analysis.

Stable SNP Allele Associations With High Grain Zinc Content in Polished Rice (Oryza sativa L.) Identified Based on ddRAD Sequencing

Polished rice is widely consumed staple food across the globe, however, it contains limited nutrients especially iron (Fe) and zinc (Zn). To identify promising genotypes for grain Zn, a total of 40 genotypes consisting 20 rice landraces, and 20 released high yielding rice varieties were evaluated in three environments (wet seasons 2014, 2015 and 2016) for nine traits including days to 50% flowering (DFF), plant height (PH), panicle length (PL), total number of tillers (TNT), single plant yield (SPY), Fe and Zn in brown (IBR, ZBR) and polished rice (IPR, ZPR). Additive Main Effect and Multiplicative Interaction (AMMI), Genotype and Genotype × Environment Interaction (GGE) analyses identified genotypes G22 (Edavankudi Pokkali), G17 (Taraori Basmati), G27 (Chittimuthyalu) and G26 (Kalanamak) stable for ZPR and G8 (Savitri) stable for SPY across three environments. Significant negative correlation between yield and grain Zn was reaffirmed. Regression analysis indicated the contribution of traits toward ZPR and SPY and also desirable level of grain Zn in brown rice. A total of 39,137 polymorphic single nucleotide polymorphisms (SNPs) were obtained through double digest restriction site associated DNA (dd-RAD) sequencing of 40 genotypes. Association analyses with nine phenotypic traits revealed 188 stable SNPs with six traits across three environments. ZPR was associated with SNPs located in three putative candidate genes (LOC_Os03g47980, LOC_Os07g47950 and LOC_Os07g48050) on chromosomes 3 and 7. The genomic region of chromosome 7 co localized with reported genomic regions (rMQTL₇.₁) and OsNAS3 candidate gene. SPY was found to be associated with 12 stable SNPs located in 11 putative candidate genes on chromosome 1, 6, and 12. Characterization of rice landraces and varieties in terms of stability for their grain Zn and yield identified promising donors and recipients along with genomic regions in the present study to be deployed rice Zn biofortification breeding program.

Evaluation of variant calling tools for large plant genome re-sequencing

BACKGROUND

Discovering single nucleotide polymorphisms (SNPs) from agriculture crop genome sequences has been a widely used strategy for developing genetic markers for several applications including marker-assisted breeding, population diversity studies for eco-geographical adaption, genotyping crop germplasm collections, and others. Accurately detecting SNPs from large polyploid crop genomes such as wheat is crucial and challenging. A few variant calling methods have been previously developed but they show a low concordance between their variant calls. A gold standard of variant sets generated from one human individual sample was established for variant calling tool evaluations, however hitherto no gold standard of crop variant set is available for wheat use. The intent of this study was to evaluate seven SNP variant calling tools (FreeBayes, GATK, Platypus, Samtools/mpileup, SNVer, VarScan, VarDict) with the two most popular mapping tools (BWA-mem and Bowtie2) on wheat whole exome capture (WEC) re-sequencing data from allohexaploid wheat.

RESULTS

We found the BWA-mem mapping tool had both a higher mapping rate and a higher accuracy rate than Bowtie2. With the same mapping quality (MQ) cutoff, BWA-mem detected more variant bases in mapping reads than Bowtie2. The reads preprocessed with quality trimming or duplicate removal did not significantly affect the final mapping performance in terms of mapped reads. Based on the concordance and receiver operating characteristic (ROC), the Samtools/mpileup variant calling tool with BWA-mem mapping of raw sequence reads outperformed other tests followed by FreeBayes and GATK in terms of specificity and sensitivity. VarDict and VarScan were the poorest performing variant calling tools with the wheat WEC sequence data.

CONCLUSION

The BWA-mem and Samtools/mpileup pipeline, with no need to preprocess the raw read data before mapping onto the reference genome, was ascertained the optimum for SNP calling for the complex wheat genome re-sequencing. These results also provide useful guidelines for reliable variant identification from deep sequencing of other large polyploid crop genomes.

Adapting Genotyping-by-Sequencing and Variant Calling for Heterogeneous Stock Rats

The heterogeneous stock (HS) is an outbred rat population derived from eight inbred rat strains. HS rats are ideally suited for genome wide association studies; however, only a few genotyping microarrays have ever been designed for rats and none of them are currently in production. To address the need for an efficient and cost effective method of genotyping HS rats, we have adapted genotype-by-sequencing (GBS) to obtain genotype information at large numbers of single nucleotide polymorphisms (SNPs). In this paper, we have outlined the laboratory and computational steps we took to optimize double digest genotype-by-sequencing (ddGBS) for use in rats. We evaluated multiple existing computational tools and explain the workflow we have used to call and impute over 3.7 million SNPs. We have also compared various rat genetic maps, which are necessary for imputation, including a recently developed map specific to the HS. Using our approach, we obtained concordance rates of 99% with data obtained using data from a genotyping array. The principles and computational pipeline that we describe could easily be adapted for use in other species for which reliable reference genome sets are available.

Identification of male heterogametic sex-determining regions on the Atlantic herring Clupea harengus genome

The sex determination system of Atlantic herring Clupea harengus L., a commercially important fish, was investigated. Low coverage whole-genome sequencing of 48 females and 55 males and a genome-wide association study revealed two regions on chromosomes 8 and 21 associated with sex. The genotyping data of the single nucleotide polymorphisms associated with sex showed that 99.4% of the available female genotypes were homozygous, whereas 68.6% of the available male genotypes were heterozygous. This is close to the theoretical expectation of homo/heterozygous distribution at low sequencing coverage when the males are factually heterozygous. This suggested a male heterogametic sex determination system in C. harengus, consistent with other species within the Clupeiformes group. There were 76 protein coding genes on the sex regions but none of these genes were previously reported master sex regulation genes, or obviously related to sex determination. However, many of these genes are expressed in testis or ovary in other species, but the exact genes controlling sex determination in C. harengus could not be identified.

Role of NGS and SNP genotyping methods in sugarcane improvement programs

Sugarcane (Saccharum spp.) is one of the most economically significant crops because of its high sucrose content and it is a promising biomass feedstock for biofuel production. Sugarcane genome sequencing and analysis is a difficult task due to its heterozygosity and polyploidy. Long sequence read technologies, PacBio Single-Molecule Real-Time (SMRT) sequencing, the Illumina TruSeq, and the Oxford Nanopore sequencing could solve the problem of genome assembly. On the applications side, next generation sequencing (NGS) technologies played a major role in the discovery of single nucleotide polymorphism (SNP) and the development of low to high throughput genotyping platforms. The two mainstream high throughput genotyping platforms are the SNP microarray and genotyping by sequencing (GBS). This paper reviews the NGS in sugarcane genomics, genotyping methodologies, and the choice of these methods. Array-based SNP genotyping is robust, provides consistent SNPs, and relatively easier downstream data analysis. The GBS method identifies large scale SNPs across the germplasm. A combination of targeted GBS and array-based genotyping methods should be used to increase the accuracy of genomic selection and marker-assisted breeding.

Natural variations at the Stay-Green gene promoter control lifespan and yield in rice cultivars

Increased grain yield will be critical to meet the growing demand for food, and could be achieved by delaying crop senescence. Here, via quantitative trait locus (QTL) mapping, we uncover the genetic basis underlying distinct life cycles and senescence patterns of two rice subspecies, indica and japonica. Promoter variations in the Stay-Green (OsSGR) gene encoding the chlorophyll-degrading Mg⁺⁺-dechelatase were found to trigger higher and earlier induction of OsSGR in indica, which accelerated senescence of indica rice cultivars. The indica-type promoter is present in a progenitor subspecies O. nivara and thus was acquired early during the evolution of rapid cycling trait in rice subspecies. Japonica OsSGR alleles introgressed into indica-type cultivars in Korean rice fields lead to delayed senescence, with increased grain yield and enhanced photosynthetic competence. Taken together, these data establish that naturally occurring OsSGR promoter and related lifespan variations can be exploited in breeding programs to augment rice yield.

IonBreeders: bioinformatics plugins toward genomics-assisted breeding

Polymorphism information generated by next-generation sequencing (NGS) technologies has enabled applications of genome-wide markers assisted breeding. However, handling such large-scale data remains a challenge for experimental researchers and breeders, calling for the urgent development of a flexible and straightforward analysis tool for NGS data. We developed "IonBreeders" as bioinformatics plugins that implement general analysis steps from genotyping to genomic prediction. IonBreeders comprises three plugins, "ABH", "IMPUTATION", and "GENOMIC PREDICTION", for format conversion of genotyping data, preprocessing and imputation of genotyping data, and genomic prediction, respectively. "ABH" converts genotyping data derived from NGS into the ABH format, which is acceptable for our further plugins and with other breeding software tools, R/qtl, MapMaker, and AntMap. "IMPUTATION" filters out non-informative markers and imputes missing marker genotypes. In "GENOMIC PREDICTION", users can use four statistical methods based on their target trait, quantitative trait locus effect, and number of markers, and construct a prediction model for genomic selection. IonBreeders is operated in Torrent Suite, but can also handle genotype data in standard formats, e.g., Variant Call Format (VCF), by format conversion using free software or our provided scripts.

A CIN-like TCP transcription factor (LsTCP4) having retrotransposon insertion associates with a shift from Salinas type to Empire type in crisphead lettuce (Lactuca sativa L.)

To improve several agronomic traits in crisphead lettuce (Lactuca sativa L.) under high-temperature growth conditions, we investigated the correlation among those traits in multiple cultivars and performed genetic mapping of their causal genes. In a field cultivation test of Empire type (serrated leaf) and Salinas type (wavy leaf) cultivars, Empire type cultivars showed increased tipburn susceptibility and late bolting compared with Salinas type cultivars. We attempted genetic mapping of leaf shape and bolting time by ddRAD-seq using the F2 population derived from a cross between 'VI185' (Empire type) and 'ShinanoGreen' (Salinas type). These analyses suggested that both traits are controlled by a single locus in LG5. Genotyping of 51 commercial lettuce cultivars with a tightly linked marker (LG5_v8_252.743Mbp) at this locus showed an association between its genotype and the serrated leaf phenotype. By further fine mapping and transcriptome analysis, a gene encoding putative CIN-like TCP transcription factor was determined to be a candidate gene at this locus and was designated as LsTCP4. An insertion of retrotransposable element was found in the allele of 'VI185', and its transcript level in the leaves was lower than that in 'ShinanoGreen'. Because shapes of leaf epidermal cells in 'VI185' were similar to those in the TCP family mutant of Arabidopsis thaliana, the leaf shape phenotype was likely caused by reduced expression of LsTCP4. Furthermore, because it is known that the TCP family protein also controls flowering time via interaction with FT in A. thaliana, it was highly possible that LsTCP4 gave pleiotropic effects on both leaf shape and bolting time in lettuce.

Multiple Small-Effect Alleles of Indica Origin Enhance High Iron-Associated Stress Tolerance in Rice Under Field Conditions in West Africa

Understanding the genetics of field-based tolerance to high iron-associated (HIA) stress in rice can accelerate the development of new varieties with enhanced yield performance in West African lowland ecosystems. To date, few field-based studies have been undertaken to rigorously evaluate rice yield performance under HIA stress conditions. In this study, two NERICA × O. sativa bi-parental rice populations and one O.sativa diversity panel consisting of 296 rice accessions were evaluated for grain yield and leaf bronzing symptoms over multiple years in four West African HIA stress and control sites. Mapping of these traits identified a large number of QTLs and single nucleotide polymorphisms (SNPs) associated with stress tolerance in the field. Favorable alleles associated with tolerance to high levels of iron in anaerobic rice soils were rare and almost exclusively derived from the indica subpopulation, including the most favorable alleles identified in NERICA varieties. These findings highlight the complex genetic architecture underlying rice response to HIA stress and suggest that a recurrent selection program focusing on an expanded indica genepool could be productively used in combination with genomic selection to increase the efficiency of selection in breeding programs designed to enhance tolerance to this prevalent abiotic stress in West Africa.

Joint linkage and association mapping of complex traits in shrub willow (Salix purpurea L.)

BACKGROUND AND AIMS

Increasing energy demands and the necessity to reduce greenhouse gas emissions are key motivating factors driving the development of lignocellulosic crops as an alternative to non-renewable energy sources. The effects of global climate change will require a better understanding of the genetic basis of complex adaptive traits to breed more resilient bioenergy feedstocks, like willow (Salix spp.). Shrub willow is a sustainable and dedicated bioenergy crop, bred to be fast-growing and high-yielding on marginal land without competing with food crops. In a rapidly changing climate, genomic advances will be vital for the sustained improvement of willow and other non-model bioenergy crops. Here, joint genetic mapping was used to exploit genetic variation garnered from both recent and historical recombination events in S. purpurea.

METHODS

A panel of North American naturalized S. purpurea accessions and full-sib F2S. purpurea population were genotyped and phenotyped for a suite of morphological, physiological, pest and disease resistance, and wood chemical composition traits, collected from multi-environment and multi-year replicated field trials. Controlling for population stratification and kinship in the association panel and spatial variation in the F2, a comprehensive mixed model analysis was used to dissect the complex genetic architecture and plasticity of these important traits.

KEY RESULTS

Individually, genome-wide association (GWAS) models differed in terms of power, but the combined approach, which corrects for yearly and environmental co-factors across datasets, improved the overall detection and resolution of associated loci. Although there were few significant GWAS hits located within support intervals of QTL for corresponding traits in the F2, many large-effect QTL were identified, as well as QTL hotspots.

CONCLUSIONS

This study provides the first comparison of linkage analysis and linkage disequilibrium mapping approaches in Salix, and highlights the complementarity and limits of these two methods for elucidating the genetic architecture of complex bioenergy-related traits of a woody perennial breeding programme.

QTL analysis for carbon assimilate translocation-related traits during maturity in rice (Oryza sativa L.)

Problems with carbon assimilate translocation from source organs to sink (grains) during ripening cause yield losses in rice (Oryza sativa L.), especially in high-sink-capacity varieties. We conducted a genetic analysis of traits related to such translocation by using recombinant inbred lines. Shoot weight (SW) of T65, a japonica parent, was retained from heading to late maturity, whereas that of DV85, an aus parent, was greater than that of T65 at 5 days after heading (DAH) and then decreased until 20 DAH. This difference was observed clearly under standard-fertilizer but not low-fertilizer conditions. Non-structural carbohydrate (NSC) contents in the parents showed a tendency similar to that for SW. QTL analysis revealed pleiotropic QTLs on chromosomes 5 and 10, probably by associations with heading date QTLs. A QTL associated with harvest index and NSC at 5 DAH was detected on chromosome 1. By considering the temporal changes of the traits, we found a QTL for decrease in SW on chromosome 11; the DV85 allele of this QTL facilitated assimilate translocation and suppressed biomass growth. A suggestive QTL for NSC decrease was located on chromosome 2. These QTLs could represent potential targets for controlling carbon assimilate translocation in breeding programs.

Characterization of introgression from the teosinte Zea mays ssp. mexicana to Mexican highland maize

Background

The spread of maize cultivation to the highlands of central Mexico was accompanied by substantial introgression from the endemic wild teosinte Zea mays ssp. mexicana, prompting the hypothesis that the transfer of beneficial variation facilitated local adaptation.

Methods

We used whole-genome sequence data to map regions of Zea mays ssp. mexicana introgression in three Mexican highland maize individuals. We generated a genetic linkage map and performed Quantitative Trait Locus mapping in an F₂ population derived from a cross between lowland and highland maize individuals.

Results

Introgression regions ranged in size from several hundred base pairs to Megabase-scale events. Gene density within introgression regions was comparable to the genome as a whole, and over 1,000 annotated genes were located within introgression events. Quantitative Trait Locus mapping identified a small number of loci linked to traits characteristic of Mexican highland maize.

Discussion

Although there was no strong evidence to associate quantitative trait loci with regions of introgression, we nonetheless identified many Mexican highland alleles of introgressed origin that carry potentially functional sequence variants. The impact of introgression on stress tolerance and yield in the highland environment remains to be fully characterized.

Improving genomic predictions by correction of genotypes from genotyping by sequencing in livestock populations

Background

Genotyping by sequencing (GBS) is a robust method to genotype markers. Many factors can influence the genotyping quality. One is that heterozygous genotypes could be wrongly genotyped as homozygotes, dependent on the genotyping depths. In this study, a method correcting this type of genotyping error was demonstrated. The efficiency of this correction method and its effect on genomic prediction were assessed using simulated data of livestock populations.

Results

Chip array (Chip) and four depths of GBS data was simulated. After quality control (call rate ≥ 0.8 and MAF ≥ 0.01), the remaining number of Chip and GBS SNPs were both approximately 7,000, averaged over 10 replicates. GBS genotypes were corrected with the proposed method. The reliability of genomic prediction was calculated using GBS, corrected GBS (GBSc), true genotypes for the GBS loci (GBSr) and Chip data. The results showed that GBSc had higher rates of correct genotype calls and higher correlations with true genotypes than GBS. For genomic prediction, using Chip data resulted in the highest reliability. As the depth increased to 10, the prediction reliabilities using GBS and GBSc data approached those using true GBS data. The reliabilities of genomic prediction using GBSc data were 0.604, 0.672, 0.684 and 0.704 after genomic correction, with the improved values of 0.013, 0.009, 0.006 and 0.001 at depth = 2, 4, 5 and 10, respectively.

Conclusions

The current study showed that a correction method for GBS data increased the genotype accuracies and, consequently, improved genomic predictions. These results suggest that a correction of GBS genotype is necessary, especially for the GBS data with low depths.

Electronic supplementary material

The online version of this article (10.1186/s40104-019-0315-z) contains supplementary material, which is available to authorized users.

Assembling the genome of the African wild rice Oryza longistaminata by exploiting synteny in closely related Oryza species

The African wild rice species Oryza longistaminata has several beneficial traits compared to cultivated rice species, such as resistance to biotic stresses, clonal propagation via rhizomes, and increased biomass production. To facilitate breeding efforts and functional genomics studies, we de-novo assembled a high-quality, haploid-phased genome. Here, we present our assembly, with a total length of 351 Mb, of which 92.2% was anchored onto 12 chromosomes. We detected 34,389 genes and 38.1% of the genome consisted of repetitive content. We validated our assembly by a comparative linkage analysis and by examining well-characterized gene families. This genome assembly will be a useful resource to exploit beneficial alleles found in O. longistaminata. Our results also show that it is possible to generate a high-quality, functionally complete rice genome assembly from moderate SMRT read coverage by exploiting synteny in a closely related Oryza species.

Stefan Reuscher et al. assembled the genome of an African wild rice species to facilitate breeding efforts and functional genomic studies. They used SMRT sequencing, chromosomal synteny between rice species, and a linkage map to assemble the 351 Mb genome into 12 chromosomes.

Colocalization of QTLs for hull-cracked rice and grain size in elite rice varieties in Japan

The control of insects that consume cereal grains is important for the production and storage of grains. Hull-cracked rice, which has splits in the hull, becomes more susceptible to insects both in the paddy field and during storage. The development of varieties with a low frequency of hull-cracked rice is the most economical and effective strategy to avoid insect damage and the environmental risks from agricultural chemical entering rice grains. In this study, we identified that QTLs for the frequency of hull-cracked rice and for grain width are located on the same chromosome using recombinant inbred lines derived from a cross between the elite rice varieties in Hokkaido, Japan, which are from the same pedigree and are genetically closely related. These QTLs were detected close to different molecular markers, which were separated by 1,101,675 bp, on chromosome 5 in the reference Nipponbare genome. In addition, low coefficient values of the phenotype were found between hull-cracked rice and grain size. These results suggested that the ratio of hull-cracked rice is independent of grain size. Using these QTLs, new varieties with low hull-cracked rice could be developed regardless of grain size.

High-throughput genotyping-by-sequencing facilitates molecular tagging of a novel rust resistance gene, R 15 , in sunflower (Helianthus annuus L.)

A novel rust resistance gene, R ₁₅ , derived from the cultivated sunflower HA-R8 was assigned to linkage group 8 of the sunflower genome using a genotyping-by-sequencing approach. SNP markers closely linked to R ₁₅ were identified, facilitating marker-assisted selection of resistance genes. The rust virulence gene is co-evolving with the resistance gene in sunflower, leading to the emergence of new physiologic pathotypes. This presents a continuous threat to the sunflower crop necessitating the development of resistant sunflower hybrids providing a more efficient, durable, and environmentally friendly host plant resistance. The inbred line HA-R8 carries a gene conferring resistance to all known races of the rust pathogen in North America and can be used as a broad-spectrum resistance resource. Based on phenotypic assessments of 140 F₂ individuals derived from a cross of HA 89 with HA-R8, rust resistance in the population was found to be conferred by a single dominant gene (R ₁₅ ) originating from HA-R8. Genotypic analysis with the currently available SSR markers failed to find any association between rust resistance and any markers. Therefore, we used genotyping-by-sequencing (GBS) analysis to achieve better genomic coverage. The GBS data showed that R ₁₅ was located at the top end of linkage group (LG) 8. Saturation with 71 previously mapped SNP markers selected within this region further showed that it was located in a resistance gene cluster on LG8, and mapped to a 1.0-cM region between three co-segregating SNP makers SFW01920, SFW00128, and SFW05824 as well as the NSA_008457 SNP marker. These closely linked markers will facilitate marker-assisted selection and breeding in sunflower.

Diversity analysis and genome-wide association studies of grain shape and eating quality traits in rice (Oryza sativa L.) using DArT markers

Microarray-based markers such as Diversity Arrays Technology (DArT) have become the genetic markers of choice for construction of high-density maps, quantitative trait loci (QTL) mapping and genetic diversity analysis based on their efficiency and low cost. More recently, the DArT technology was further developed in combination with high-throughput next-generation sequencing (NGS) technologies to generate the DArTseq platform representing a new sequencing tool of complexity-reduced representations. In this study, we used DArTseq markers to investigate genetic diversity and genome-wide association studies (GWAS) of grain quality traits in rice (Oryza sativa L.). The study was performed using 59 rice genotypes with 525 SNPs derived from DArTseq platform. Population structure analysis revealed only two distinct genetic clusters where genotypes were grouped based on environmental adaptation and pedigree information. Analysis of molecular variance indicated a low degree of differentiation among populations suggesting the need for broadening the genetic base of the current germplasm collection. GWAS revealed 22 significant associations between DArTseq-derived SNP markers and rice grain quality traits in the test genotypes. In general, 2 of the 22 significant associations were in chromosomal regions where the QTLs associated with the given traits had previously been reported, the other 20 significant SNP marker loci were indicative of the likelihood discovery of novel alleles associated with rice grain quality traits. DArTseq-derived SNP markers that include SNP12_100006178, SNP13_3052560 and SNP14_3057360 individually co-localised with two functional gene groups that were associated with QTLs for grain width and grain length to width ratio on chromosome 3, indicating trait dependency or pleiotropic-effect loci. This study demonstrated that DArTseq markers were useful genomic resources for genome-wide association studies of rice grain quality traits to accelerate varietal development and release.

Genome-wide association mapping of virulence gene in rice blast fungus Magnaporthe oryzae using a genotyping by sequencing approach

Magnaporthe oryzae is a fungal pathogen causing blast disease in many plant species. In this study, seventy three isolates of M. oryzae collected from rice (Oryza sativa) in 1996-2014 were genotyped using a genotyping-by-sequencing approach to detect genetic variation. An association study was performed to identify single nucleotide polymorphisms (SNPs) associated with virulence genes using 831 selected SNP and infection phenotypes on local and improved rice varieties. Population structure analysis revealed eight subpopulations. The division into eight groups was not related to the degree of virulence. Association mapping showed five SNPs associated with fungal virulence on chromosome 1, 2, 3, 4 and 7. The SNP on chromosome 1 was associated with virulence against RD6-Pi7 and IRBL7-M which might be linked to the previously reported AvrPi7.

A comparison of genotyping-by-sequencing analysis methods on low-coverage crop datasets shows advantages of a new workflow, GB-eaSy

BACKGROUND

Genotyping-by-sequencing (GBS), a method to identify genetic variants and quickly genotype samples, reduces genome complexity by using restriction enzymes to divide the genome into fragments whose ends are sequenced on short-read sequencing platforms. While cost-effective, this method produces extensive missing data and requires complex bioinformatics analysis. GBS is most commonly used on crop plant genomes, and because crop plants have highly variable ploidy and repeat content, the performance of GBS analysis software can vary by target organism. Here we focus our analysis on soybean, a polyploid crop with a highly duplicated genome, relatively little public GBS data and few dedicated tools.

RESULTS

We compared the performance of five GBS pipelines using low-coverage Illumina sequence data from three soybean populations. To address issues identified with existing methods, we developed GB-eaSy, a GBS bioinformatics workflow that incorporates widely used genomics tools, parallelization and automation to increase the accuracy and accessibility of GBS data analysis. Compared to other GBS pipelines, GB-eaSy rapidly and accurately identified the greatest number of SNPs, with SNP calls closely concordant with whole-genome sequencing of selected lines. Across all five GBS analysis platforms, SNP calls showed unexpectedly low convergence but generally high accuracy, indicating that the workflows arrived at largely complementary sets of valid SNP calls on the low-coverage data analyzed.

CONCLUSIONS

We show that GB-eaSy is approximately as good as, or better than, other leading software solutions in the accuracy, yield and missing data fraction of variant calling, as tested on low-coverage genomic data from soybean. It also performs well relative to other solutions in terms of the run time and disk space required. In addition, GB-eaSy is built from existing open-source, modular software packages that are regularly updated and commonly used, making it straightforward to install and maintain. While GB-eaSy outperformed other individual methods on the datasets analyzed, our findings suggest that a comprehensive approach integrating the results from multiple GBS bioinformatics pipelines may be the optimal strategy to obtain the largest, most highly accurate SNP yield possible from low-coverage polyploid sequence data.

Genetic variation and population structure of maize inbred lines adapted to the mid-altitude sub-humid maize agro-ecology of Ethiopia using single nucleotide polymorphic (SNP) markers

BACKGROUND

Molecular characterization is important for efficient utilization of germplasm and development of improved varieties. In the present study, we investigated the genetic purity, relatedness and population structure of 265 maize inbred lines from the Ethiopian Institute of Agricultural Research (EIAR), the International Maize and Wheat Improvement Centre (CIMMYT) and the International Institute of Tropical Agriculture (IITA) using 220,878 single nucleotide polymorphic (SNP) markers obtained using genotyping by sequencing (GBS).

RESULTS

Only 22% of the inbred lines were considered pure with <5% heterogeneity, while the remaining 78% of the inbred lines had a heterogeneity ranging from 5.1 to 31.5%. Pairwise genetic distances among the 265 inbred lines varied from 0.011 to 0.345, with 89% of the pairs falling between 0.301 and 0.345. Only <1% of the pairs had a genetic distance lower than 0.200, which included 14 pairs of sister lines that were nearly identical. Relative kinship analysis showed that the kinship coefficients for 59% of the pairs of lines was close to zero, which agrees with the genetic distance estimates. Principal coordinate analysis, discriminant analysis of principal components (DAPC) and the model-based population structure analysis consistently suggested the presence of three groups, which generally agreed with pedigree information (genetic background). Although not distinct enough, the SNP markers showed some level of separation between the two CIMMYT heterotic groups A and B established based on pedigree and combining ability information.

CONCLUSIONS

The high level of heterogeneity detected in most of the inbred lines suggested the requirement for purification or further inbreeding except those deliberately maintained at early inbreeding level. The genetic distance and relative kinship analysis clearly indicated the uniqueness of most of the inbred lines in the maize germplasm available for breeders in the mid-altitude maize breeding program of Ethiopia. Results from the present study facilitate the maize breeding work in Ethiopia and germplasm exchange among breeding programs in Africa. We suggest the incorporation of high density molecular marker information in future heterotic group assignments.

High-density genetic linkage map construction by F2 populations and QTL analysis of early-maturity traits in upland cotton (Gossypium hirsutum L.)

Due to China’s rapidly increasing population, the total arable land area has dramatically decreased; as a consequence, the competition for farming land allocated for grain and cotton production has become fierce. Therefore, to overcome the existing contradiction between cotton grain and fiber production and the limited farming land, development of early-maturing cultivars is necessary. In this research, a high-density linkage map of upland cotton was constructed using genotyping by sequencing (GBS) to discover single nucleotide polymorphism (SNP) markers associated with early maturity in 170 F₂ individuals derived from a cross between LU28 and ZHONG213. The high-density genetic map, which was composed of 3978 SNP markers across the 26 cotton chromosomes, spanned 2480 cM with an average genetic distance of 0.62 cM. Collinearity analysis showed that the genetic map was of high quality and accurate and agreed well with the Gossypium hirsutum reference genome. Based on this high-density linkage map, QTL analysis was performed on cotton early-maturity traits, including FT, FBP, WGP, NFFB, HNFFB and PH. A total 47 QTLs for the six traits were detected; each of these QTLs explained between 2.61% and 32.57% of the observed phenotypic variation. A major region controlling early-maturity traits in Gossypium hirsutum was identified for FT, FBP, WGP, NFFB and HNFFB on chromosome D03. QTL analyses revealed that phenotypic variation explained (PVE) ranged from 10.42% to 32.57%. Two potential candidate genes, Gh_D03G0885 and Gh_D03G0922, were predicted in a stable QTL region and had higher expression levels in the early-maturity variety ZHONG213 than in the late-maturity variety LU28. However, further evidence is required for functional validation. This study could provide useful information for the dissection of early-maturity traits and guide valuable genetic loci for molecular-assisted selection (MAS) in cotton breeding.

Genetic Variation and Population Structure of Oryza glaberrima and Development of a Mini-Core Collection Using DArTseq

The sequence variation present in accessions conserved in genebanks can best be used in plant improvement when it is properly characterized and published. Using low cost and high density single nucleotide polymorphism (SNP) assays, the genetic diversity, population structure, and relatedness between pairs of accessions can be quickly assessed. This information is relevant for different purposes, including creating core and mini-core sets that represent the maximum possible genetic variation contained in the whole collection. Here, we studied the genetic variation and population structure of 2,179 Oryza glaberrima Steud. accessions conserved at the AfricaRice genebank using 27,560 DArTseq-based SNPs. Only 14% (3,834 of 27,560) of the SNPs were polymorphic across the 2,179 accessions, which is much lower than diversity reported in other Oryza species. Genetic distance between pairs of accessions varied from 0.005 to 0.306, with 1.5% of the pairs nearly identical, 8.0% of the pairs similar, 78.1% of the pairs moderately distant, and 12.4% of the pairs very distant. The number of redundant accessions that contribute little or no new genetic variation to the O. glaberrima collection was very low. Using the maximum length sub-tree method, we propose a subset of 1,330 and 350 accessions to represent a core and mini-core collection, respectively. The core and mini-core sets accounted for ~61 and 16%, respectively, of the whole collection, and captured 97-99% of the SNP polymorphism and nearly all allele and genotype frequencies observed in the whole O. glaberrima collection available at the AfricaRice genebank. Cluster, principal component and model-based population structure analyses all divided the 2,179 accessions into five groups, based roughly on country of origin but less so on ecology. The first, third and fourth groups consisted of accessions primarily from Liberia, Nigeria, and Mali, respectively; the second group consisted primarily of accessions from Togo and Nigeria; and the fifth and smallest group was a mixture of accessions from multiple countries. Analysis of molecular variance showed between 10.8 and 28.9% of the variation among groups with the remaining 71.1-89.2% attributable to differences within groups.