Bridging the genotyping gap: using genotyping by sequencing (GBS) to add high-density SNP markers and new value to traditional bi-parental mapping and breeding populations

The genetics of Ug99 stem rust resistance in spring wheat variety 'Linkert'

Wheat stem rust caused by Puccinia graminis f. sp. tritici (Pgt) threatens wheat production worldwide. The objective of this study was to characterize wheat stem rust resistance in 'Linkert', a variety with adult plant resistance effective to emerging wheat stem rust pathogen strain Ug99. Two doubled haploid (DH) populations and one recombinant inbred line (RIL) population were developed with 'Linkert' as a stem rust resistant parent. Hard red spring wheat variety 'Forefront' and genetic stock 'LMPG' were used as stem rust susceptible parents of the DH populations. Breeding line 'MN07098-6' was used as a susceptible parent of the RIL population. Both DH and RIL populations with their parents were evaluated both at the seedling stage and in the field against Pgt races. Genotyping data of the DH populations were generated using the wheat iSelect 90k SNP assay. The RIL population was genotyped by genotyping-by-sequencing. We found QTL consistently associated with wheat stem rust resistance on chromosome 2BS for the Linkert/Forefront DH population and the Linkert/MN07098-6 RIL population both in Ethiopia and Kenya. Additional reliable QTL were detected on chromosomes 5BL (125.91 cM) and 4AL (Sr7a) for the Linkert/LMPG population in Ethiopia and Kenya. Different QTL identified in the populations reflect the importance of examining the genetics of resistance in populations derived from adapted germplasm (Forefront and MN07098-6) in addition to a genetic stock (LMPG). The associated markers in this study could be used to track and select for the identified QTL in wheat breeding programs.

The chickpea WIP2 gene underlying a major QTL contributes to lateral root development

Lateral roots are a major component of root system architecture, and lateral root count (LRC) positively contributes to yield under drought in chickpea. To understand the genetic regulation of LRC, a biparental mapping population derived from two chickpea accessions having contrasting LRCs was genotyped by sequencing, and phenotyped to map four major quantitative trait loci (QTLs) contributing to 13-32% of the LRC trait variation. A single- nucleotide polymorphism tightly linked to the locus contributing to highest trait variation was located on the coding region of a gene (CaWIP2), orthologous to NO TRANSMITTING TRACT/WIP domain protein 2 (NTT/WIP2) gene of Arabidopsis thaliana. A polymorphic simple sequence repeat (SSR) in the CaWIP2 promoter showed differentiation between low versus high LRC parents and mapping individuals, suggesting its utility for marker-assisted selection. CaWIP2 promoter showed strong expression in chickpea apical root meristem and lateral root primordia. Expression of CaWIP2 under its native promoter in the Arabidopsis wip2wip4wip5 mutant rescued its rootless phenotype to produce more lateral roots than the wild-type plants, and led to formation of amyloplasts in the columella. CaWIP2 expression also induced the expression of genes that regulate lateral root emergence. Our study identified a gene-based marker for LRC which will be useful for developing drought-tolerant, high-yielding chickpea varieties.

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.

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.

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.

High-Density Linkage Mapping of Agronomic Trait QTLs in Wheat under Water Deficit Condition using Genotyping by Sequencing (GBS)

Improvement of grain yield is the ultimate goal for wheat breeding under water-limited environments. In the present study, a high-density linkage map was developed by using genotyping-by-sequencing (GBS) of a recombinant inbred line (RIL) population derived from the cross between Iranian landrace #49 and cultivar Yecora Rojo. The population was evaluated in three locations in Iran during two years under irrigated and water deficit conditions for the agronomic traits grain yield (GY), plant height (PH), spike number per square meter (SM), 1000 kernel weight (TKW), grain number per spike (GNS), spike length (SL), biomass (BIO) and harvest index (HI). A linkage map was constructed using 5831 SNPs assigned to 21 chromosomes, spanning 3642.14 cM of the hexaploid wheat genome with an average marker density of 0.62 (markers/cM). In total, 85 QTLs were identified on 19 chromosomes (all except 5D and 6D) explaining 6.06–19.25% of the traits phenotypic variance. We could identify 20 novel QTLs explaining 8.87–19.18% of phenotypic variance on chromosomes 1A, 1B, 1D, 2B, 3A, 3B, 6A, 6B and 7A. For 35 out of 85 mapped QTLs functionally annotated genes were identified which could be related to a potential role in drought stress.

Identification of QTL under Brassinosteroid-Combined Cold Treatment at Seedling Stage in Rice Using Genotyping-by-Sequencing (GBS)

Cold stress is a major threat to the sustainability of rice yield. Brassinosteroids (BR) application can enhance cold tolerance in rice. However, the regulatory mechanism related to cold tolerance and the BR signaling pathway in rice has not been clarified. In the current study, the seedling shoot length (SSL), seedling root length (SRL), seedling dry weight (SDW), and seedling wet weight (SWW) were used as the indices for identifying cold tolerance under cold stress and BR-combined cold treatment in a backcross recombinant inbred lines (BRIL) population. According to the phenotypic characterization for cold tolerance and a high-resolution SNP genetic map obtained from the GBS technique, a total of 114 QTLs were identified, of which 27 QTLs were detected under cold stress and 87 QTLs under BR-combined cold treatment. Among them, the intervals of many QTLs were coincident under different treatments, as well as different traits. A total of 13 candidate genes associated with cold tolerance or BR pathway, such as BRASSINAZOLE RESISTANT1 (OsBZR1), OsWRKY77, AP2 domain-containing protein, zinc finger proteins, basic helix-loop-helix (bHLH) protein, and auxin-induced protein, were predicted. Among these, the expression levels of 10 candidate genes were identified under different treatments in the parents and representative BRIL individuals. These results were helpful in understanding the regulation relationship between cold tolerance and BR pathway in rice.

Descriptive Genomic Analysis and Sequence Genotyping of the Two Papaya Species (Vasconcellea pubescens and Vasconcellea chilensis) Using GBS Tools

A genotyping by sequencing (GBS) approach was used to analyze the organization of genetic diversity in V. pubescens and V. chilensis. GBS identified 4675 and 4451 SNPs/INDELs in two papaya species. The cultivated orchards of V. pubescens exhibited scarce genetic diversity and low but significant genetic differentiation. The neutrality test yielded a negative and significant result, suggesting that V. pubescens suffered a selective sweep or a rapid expansion after a bottleneck during domestication. In contrast, V. chilensis exhibited a high level of genetic diversity. The genetic differentiation among the populations was slight, but it was possible to distinguish the two genetic groups. The neutrality test indicated no evidence that natural selection and genetic drift affect the natural population of V. chilensis. Using the Carica papaya genome as a reference, we identified critical SNPs/INDELs associated with putative genes. Most of the identified genes are related to stress responses (salt and nematode) and vegetative and reproductive development. These results will be helpful for future breeding and conservation programs of the Caricaceae family.

Quantitative Trait Loci Mapping Analysis for Cold Tolerance Under Cold Stress and Brassinosteroid-Combined Cold Treatment at Germination and Bud Burst Stages in Rice

Low temperature is one of the major abiotic stresses limiting seed germination and early seedling growth in rice. Brassinosteroid (BR) application can improve cold tolerance in rice. However, the regulatory relationship between cold tolerance and BR in rice remains undefined. Here, we constructed a population of 140 backcross recombinant inbred lines (BRILs) derived from a cross between a wild rice (Dongxiang wild rice, DXWR) and a super rice (SN265). The low-temperature germination rate (LTG), survival rate (SR), plant height (PH), and first leaf length (FLL) were used as indices for assessing cold tolerance under cold stress and BR-combined cold treatment at seed germination and bud burst stages. A high-resolution SNP genetic map, covering 1,145 bin markers with a distance of 3188.33 cM onto 12 chromosomes, was constructed using the GBS technique. A total of 73 QTLs were detected, of which 49 QTLs were identified under cold stress and 24 QTLs under BR-combined cold treatment. Among these, intervals of 30 QTLs were pairwise coincident under cold stress and BR-combined cold treatment, as well as different traits including SR and FLL, and PH and FLL, respectively. A total of 14 candidate genes related to cold tolerance or the BR signaling pathway, such as CBF/DREB (LOC_Os08g43200), bHLH (LOC_Os07g08440 and LOC_Os07g08440), WRKY (LOC_Os06g30860), MYB (LOC_Os01g62410 and LOC_Os05g51160), and BRI1-associated receptor kinase 1 precursor (LOC_Os06g16300), were located. Among these, the transcript levels of 10 candidate genes were identified under cold stress and BR-combined cold treatment by qRT-PCR. These findings provided an important basis for further mining the genes related to cold tolerance or the BR signaling pathway and understanding the molecular mechanisms of cold tolerance in rice.

Construction of High-Density Genetic Map and Identification of a Bruchid Resistance Locus in Mung Bean (Vigna radiata L.)

Mung bean (Vigna radiata L.) is an economically important grain legume cultivated in Asian countries. High-density genetic linkage is a valuable and effective tool for mapping quantitative trait loci (QTL). In the current study, a high-resolution genetic map containing 4,180 single-nucleotide polymorphisms (SNPs) was assigned to 11 linkage groups (LGs) and spanning 1,751.39 cM in length was constructed for mung bean, and the average distance between adjacent markers was 0.42 cM. Bruchids (Callosobruchus spp.) cause significant damage to and loss of legume seeds. A locus for bruchid resistance was detected. The gene Vradi05g03810, encoding a probable resistance-specific protein, was found to be the most likely key candidate gene in mung beans. A 69-bp sequence deletion was identified in the coding region by comparing the cDNA sequences of bruchid-resistant and bruchid-susceptible lines. This SNP-based high-density linkage map is one of the first to be constructed across the mung bean genome. This map will not only facilitate the genetic mapping of genes or complex loci that control important agronomic traits but also offer a tool for promoting future genetics and comparative genomic studies in Vigna.

Investigation of genetic relationships within three Miscanthus species using SNP markers identified with SLAF-seq

BACKGROUND

Miscanthus, which is a leading dedicated-energy grass in Europe and in parts of Asia, is expected to play a key role in the development of the future bioeconomy. However, due to its complex genetic background, it is difficult to investigate phylogenetic relationships in this genus. Here, we investigated 50 Miscanthus germplasms: 1 female parent (M. lutarioriparius), 30 candidate male parents (M. lutarioriparius, M. sinensis, and M. sacchariflorus), and 19 offspring. We used high-throughput Specific-Locus Amplified Fragment sequencing (SLAF-seq) to identify informative single nucleotide polymorphisms (SNPs) in all germplasms.

RESULTS

We identified 257,889 SLAF tags, of which 87,162 were polymorphic. Each tag was 264-364 bp long. The obtained 724,773 population SNPs were used to investigate genetic relationships within three species of Miscanthus. We constructed a phylogenetic tree of the 50 germplasms using the obtained SNPs and grouped them into two clades: one clade comprised of M. sinensis alone and the other one included the offspring, M. lutarioriparius, and M. sacchariflorus. Genetic cluster analysis had revealed that M. lutarioriparius germplasm C3 was the most likely male parent of the offspring.

CONCLUSIONS

As a high-throughput sequencing method, SLAF-seq can be used to identify informative SNPs in Miscanthus germplasms and to rapidly characterize genetic relationships within this genus. Our results will support the development of breeding programs with the focus on utilizing Miscanthus cultivars with elite biomass- or fiber-production potential for the developing bioeconomy.

Genome-wide SNP discovery, linkage mapping, and analysis of QTL for morpho-physiological traits in rice during vegetative stage under drought stress

Drought tolerance in rice is controlled by several genes and is inherited quantitatively. Low genetic map density and the use of phenotypic traits that do not reflect the corresponding tolerance level have been obstacles in genetic analyses performed to identify genes that control drought-tolerant traits in rice. The current study aimed to construct a genetic map from high-density single-nucleotide polymorphism (SNP) markers generated from genome sequences of recombinant inbred lines (RILs), derived from IR64 × Hawara Bunar. Moreover, it sought to analyze the quantitative trait loci (QTL) and identify the drought tolerance candidate genes. A linkage map along 1980 cM on the 12 rice chromosomes was constructed employing 55,205 SNP markers resulting from the RIL genome sequences. A total of 175 morpho-physiological traits pertaining to drought stress were determined. A total of 41 QTLs were detected in 13 regions on rice chromosomes 1, 3, 6, 8, 9, and 12. Moreover, three hotspot QTL regions were found on chromosomes 6 and 8, along with two major QTL on chromosome 9. Differential gene expression for the loci within the QTL physical map intervals revealed many potential candidate genes. The markers tightly linked to the QTL and their candidate genes can potentially be used for pyramiding in marker-assisted breeding in order to achieve genetic improvement concerning the tolerance of rice to drought stress.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12298-021-01095-y.

Fingerprint construction through genotyping by sequencing for applied breeding in Brassica rapa

This study evaluated genotyping by sequencing (GBS) protocol for fingerprinting Brassica rapa and the data derived were more reliable than the re-sequencing data of B. rapa. Of the 10 enzyme solutions used to analyze the numbers of genotypes and single nucleotide polymorphisms (SNPs) in B. rapa, five solutions showed better results, namely: A (HaeIII, 450-500 bp), E (RsaI+HaeIII, 500-550 bp), F (RsaI+HaeIII, 500-600 bp), G (RsaI+HaeIII, 'All' fragment), and J (RsaI+EcoRV-HF®, 'All' fragment). The five enzyme solutions showed less than 40% similarity in different individuals from various samples, and 90% similarity in between two individuals from one sample. The E enzyme solution was most suitable for fingerprinting B. rapa revealing well-distributed SNPs in the whole genome. Of the 82 highly inbred lines and 18 F1 lines of B. rapa sequenced by GBS in E enzyme solution, known parents of 10 F1 lines were verified and male parents were discovered for 8 F1 lines that had only known female parents. This study provided a valuable method for screening parents for F1 lines in B. rapa for applied breeding through efficient evaluation of GBS with varied library construction strategies.

High-Frequency Homologous Recombination Occurred Preferentially in Populus

Homologous recombination (HR), the most significant event in meiosis, has important implications for genetic diversity and evolution in organisms. Heteroduplex DNA (hDNA), the product of HR, can be captured by artificially induced chromosome doubling during the development of the embryo sac to inhibit postmeiotic segregation, subsequently, and hDNAs are directly detected using codominant simple sequence repeat (SSR) markers. In the present study, two hybrid triploid populations derived from doubling the chromosomes of the embryo sac induced by high temperature in Populus tomentosa served as starting materials. Eighty-seven, 62, and 79 SSR markers on chromosomes 01, 04, and 19, respectively, that were heterozygous in the maternal parent and different from the paternal parent were screened to detect and characterize the hDNA in P. tomentosa. The results showed that the hDNA frequency patterns on chromosomes changed slightly when the number of SSR primers increased. The highest hDNA frequency occurred at the adjacent terminal on chromosomes, which was slightly higher than those at the terminals in the two genotypic individuals, and the hDNA frequency gradually decreased as the locus-centromere distance decreased. With the increase in the number of SSR markers employed for detection, the number of recombination events (REs) detected significantly increased. In regions with high methylation or long terminal repeat (LTR) retrotransposon enrichment, the frequency of hDNA was low, and high frequencies were observed in regions with low sequence complexity and high gene density. High-frequency recombination occurring at high gene density regions strongly affected the association between molecular markers and quantitative trait loci (QTLs), which was an important factor contributing to the difficulty encountered by MAS in achieving the expected breeding results.

Using probabilistic genotypes in linkage analysis of polyploids

In polyploids, linkage mapping is carried out using genotyping with discrete dosage scores. Here, we use probabilistic genotypes and we validate it for the construction of polyploid linkage maps. Marker genotypes are generally called as discrete values: homozygous versus heterozygous in the case of diploids, or an integer allele dosage in the case of polyploids. Software for linkage map construction and/or QTL analysis usually relies on such discrete genotypes. However, it may not always be possible, or desirable, to assign definite values to genotype observations in the presence of uncertainty in the genotype calling. Here, we present an approach that uses probabilistic marker dosages for linkage map construction in polyploids. We compare our method to an approach based on discrete dosages, using simulated SNP array and sequence reads data with varying levels of data quality. We validate our approach using experimental data from a potato (Solanum tuberosum L.) SNP array applied to an F1 mapping population. In comparison to the approach based on discrete dosages, we mapped an additional 562 markers. All but three of these were mapped to the expected chromosome and marker position. For the remaining three markers, no physical position was known. The use of dosage probabilities is of particular relevance for map construction in polyploids using sequencing data, as these often result in a higher level of uncertainty regarding allele dosage.

Genetic architecture of root and shoot ionomes in rice (Oryza sativa L.)

KEY MESSAGE

Association analysis for ionomic concentrations of 20 elements identified independent genetic factors underlying the root and shoot ionomes of rice, providing a platform for selecting and dissecting causal genetic variants. Understanding the genetic basis of mineral nutrient acquisition is key to fully describing how terrestrial organisms interact with the non-living environment. Rice (Oryza sativa L.) serves both as a model organism for genetic studies and as an important component of the global food system. Studies in rice ionomics have primarily focused on above ground tissues evaluated from field-grown plants. Here, we describe a comprehensive study of the genetic basis of the rice ionome in both roots and shoots of 6-week-old rice plants for 20 elements using a controlled hydroponics growth system. Building on the wealth of publicly available rice genomic resources, including a panel of 373 diverse rice lines, 4.8 M genome-wide single-nucleotide polymorphisms, single- and multi-marker analysis pipelines, an extensive tome of 321 candidate genes and legacy QTLs from across 15 years of rice genetics literature, we used genome-wide association analysis and biparental QTL analysis to identify 114 genomic regions associated with ionomic variation. The genetic basis for root and shoot ionomes was highly distinct; 78 loci were associated with roots and 36 loci with shoots, with no overlapping genomic regions for the same element across tissues. We further describe the distribution of phenotypic variation across haplotypes and identify candidate genes within highly significant regions associated with sulfur, manganese, cadmium, and molybdenum. Our analysis provides critical insight into the genetic basis of natural phenotypic variation for both root and shoot ionomes in rice and provides a comprehensive resource for dissecting and testing causal genetic variants.

QTL Analysis of Stem Elongation and Flowering Time in Lettuce Using Genotyping-by-Sequencing

Lettuce plants tend to undergo floral initiation by elongation of flower stalks (bolting) under high-temperature and long-day conditions, which is a serious problem for summer lettuce production. Our objective was to generate a high-density genetic map using SNPs obtained from genotyping-by-sequencing (GBS) analysis of F5 recombinant inbred lines (RILs) and to map QTLs involved in stem growth and flowering time in lettuce. A set of 127 intra-specific RIL mapping populations derived from a cross between two varieties, green and red leaf lettuce, were used to identify QTLs related to the number of days from sowing to bolting (DTB), to flowering of the first flower (DTF), to seed-setting of the first flower (DTS), and the total number of leaves (LN), plant height (PH), and total number of branches of main inflorescence (BN) for two consecutive years. Of the 15 QTLs detected, one that controls DTB, DTF, DTS, LN, and PH detected on LG 7, and another QTL that controls DTF, DTS, and PH detected on LG 1. Analysis of the genomic sequence corresponding to the QTL detected on LG 7 led to the identification of 22 putative candidate genes. A consistent QTL related to bolting and flowering time, and corresponding candidate genes has been reported. This study will be valuable in revealing the genetic basis of stem growth and flowering time in lettuce.

Genetic mapping identifies a rice naringenin O-glucosyltransferase that influences insect resistance

Naringenin, the biochemical precursor for predominant flavonoids in grasses, provides protection against UV damage, pathogen infection and insect feeding. To identify previously unknown loci influencing naringenin accumulation in rice (Oryza sativa), recombinant inbred lines derived from the Nipponbare and IR64 cultivars were used to map a quantitative trait locus (QTL) for naringenin abundance to a region of 50 genes on rice chromosome 7. Examination of candidate genes in the QTL confidence interval identified four predicted uridine diphosphate-dependent glucosyltransferases (Os07g31960, Os07g32010, Os07g32020 and Os07g32060). In vitro assays demonstrated that one of these genes, Os07g32020 (UGT707A3), encodes a glucosyltransferase that converts naringenin and uridine diphosphate-glucose to naringenin-7-O-β-d-glucoside. The function of Os07g32020 was verified with CRISPR/Cas9 mutant lines, which accumulated more naringenin and less naringenin-7-O-β-d-glucoside and apigenin-7-O-β-d-glucoside than wild-type Nipponbare. Expression of Os12g13800, which encodes a naringenin 7-O-methyltransferase that produces sakuranetin, was elevated in the mutant lines after treatment with methyl jasmonate and insect pests, Spodoptera litura (cotton leafworm), Oxya hyla intricata (rice grasshopper) and Nilaparvata lugens (brown planthopper), leading to a higher accumulation of sakuranetin. Feeding damage from O. hyla intricata and N. lugens was reduced on the Os07g32020 mutant lines relative to Nipponbare. Modification of the Os07g32020 gene could be used to increase the production of naringenin and sakuranetin rice flavonoids in a more targeted manner. These findings may open up new opportunities for selective breeding of this important rice metabolic trait.

High-density mapping for gray leaf spot resistance using two related tropical maize recombinant inbred line populations

Gray leaf spot (GLS) caused by Cercospora zeae-maydis or Cercospora zeina is one of the devastating maize foliar diseases worldwide. Identification of GLS-resistant quantitative trait loci (QTL)/genes plays an urgent role in improving GLS resistance in maize breeding practice. Two groups of recombinant inbred line (RIL) populations derived from CML373 × Ye107 and Chang7-2 × Ye107 were generated and subjected to genotyping-by-sequencing (GBS). A total of 1,929,222,287 reads in CML373 × Ye107 (RIL-YCML) and 2,585,728,312 reads in Chang7-2 × Ye107 (RIL-YChang), with an average of 10,961,490 (RIL-YCML) and 13,609,096 (RIL-YChang) reads per individual, were got, which was roughly equal to 0.70-fold and 0.87-fold coverage of the maize B73 RefGen_V4 genome for each F₇ individual, respectively. 6418 and 5139 SNP markers were extracted to construct two high-density genetic maps. Comparative analysis using these physically mapped marker loci demonstrated a satisfactory colinear relationship with the reference genome. 11 GLS-resistant QTL have been detected. The individual QTL accounted for 1.53-24.00% of the phenotypic variance explained (PVE). The new consensus QTL (qYCM-DS3-3/qYCM-LT3-1/qYCM-LT3-2) with the largest effect was located in chromosome bin 3.05, with an interval of 2.7 Mb, representing 13.08 to 24.00% of the PVE. Further gene annotation indicated that there were four candidate genes (GRMZM2G032384, GRMZM2G041415, GRMZM2G041544, and GRMZM2G035992) for qYCM-LT3-1, which may be related to GLS resistance. Combining RIL populations and GBS-based high-density genetic maps, a new larger effect QTL was delimited to a narrow genomic interval, which will provide a new resistance source for maize breeding programs.

Quantitative Trait Loci Mapping for Earliness, Fruit, and Seed Related Traits Using High Density Genotyping-by-Sequencing-Based Genetic Map in Bitter Gourd (Momordica charantia L.)

Bitter gourd (Momordica charantia L.) is an important vegetable crop having numerous medicinal properties. Earliness and yield related traits are main aims of bitter gourd breeding program. High resolution quantitative trait loci (QTLs) mapping can help in understanding the molecular basis of phenotypic variation of these traits and thus facilitate marker-assisted breeding. The aim of present study was to identify genetic loci controlling earliness, fruit, and seed related traits. To achieve this, genotyping-by-sequencing (GBS) approach was used to genotype 101 individuals of F₄ population derived from a cross between an elite cultivar Punjab-14 and PAUBG-6. This population was phenotyped under net-house conditions for three years 2018, 2019, and 2021. The linkage map consisting of 15 linkage groups comprising 3,144 single nucleotide polymorphism (SNP) markers was used to detect the QTLs for nine traits. A total of 50 QTLs for these traits were detected which were distributed on 11 chromosomes. The QTLs explained 5.09-29.82% of the phenotypic variance. The highest logarithm of the odds (LOD) score for a single QTL was 8.68 and the lowest was 2.50. For the earliness related traits, a total of 22 QTLs were detected. For the fruit related traits, a total of 16 QTLs and for seed related traits, a total of 12 QTLs were detected. Out of 50 QTLs, 20 QTLs were considered as frequent QTLs (FQ-QTLs). The information generated in this study is very useful in the future for fine-mapping and marker-assisted selection for these traits in bitter gourd improvement program.

Next Generation Sequencing Based Forward Genetic Approaches for Identification and Mapping of Causal Mutations in Crop Plants: A Comprehensive Review

The recent advancements in forward genetics have expanded the applications of mutation techniques in advanced genetics and genomics, ahead of direct use in breeding programs. The advent of next-generation sequencing (NGS) has enabled easy identification and mapping of causal mutations within a short period and at relatively low cost. Identifying the genetic mutations and genes that underlie phenotypic changes is essential for understanding a wide variety of biological functions. To accelerate the mutation mapping for crop improvement, several high-throughput and novel NGS based forward genetic approaches have been developed and applied in various crops. These techniques are highly efficient in crop plants, as it is relatively easy to grow and screen thousands of individuals. These approaches have improved the resolution in quantitative trait loci (QTL) position/point mutations and assisted in determining the functional causative variations in genes. To be successful in the interpretation of NGS data, bioinformatics computational methods are critical elements in delivering accurate assembly, alignment, and variant detection. Numerous bioinformatics tools/pipelines have been developed for such analysis. This article intends to review the recent advances in NGS based forward genetic approaches to identify and map the causal mutations in the crop genomes. The article also highlights the available bioinformatics tools/pipelines for reducing the complexity of NGS data and delivering the concluding outcomes.

The Hessian fly recessive resistance gene h4 mapped to chromosome 1A of the wheat cultivar 'Java' using genotyping-by-sequencing

The recessive Hessian fly resistance gene h4 and flanking SNP markers were located to a 642 kb region in chromosome 1A of the wheat cultivar 'Java.' Hessian fly (HF), Mayetiola destructor, is one of the most destructive insect pests in wheat worldwide. The wheat cultivar 'Java' was reported to carry a recessive gene (h4) for HF resistance; however, its chromosome location has not been determined. To map the HF resistance gene in Java, two populations of recombinant inbred lines (RILs) were developed from 'Bobwhite' × Java and 'Overley' × Java, respectively, and were phenotyped for responses to infestation of HF Great Plains biotype. Analysis of phenotypic data from the F₁ and the RIL populations confirmed that one recessive gene conditioned HF resistance in Java. Two linkage maps were constructed using single-nucleotide polymorphism (SNP) markers generated by genotyping-by-sequencing (GBS). The h4 gene was mapped to the distal end of the short arm of chromosome 1A, which explained 60.4 to 70.5% of the phenotypic variation for HF resistance in the two populations. The GBS-SNPs in the h4 candidate interval were converted into Kompetitive Allele-Specific Polymerase Chain Reaction (KASP) markers to eliminate the missing data points in GBS-SNPs. Using the revised maps with KASP markers, h4 was further located to a 642 kb interval (6,635,984-7,277,935 bp). The two flanking KASP markers, KASP3299 and KASP1871, as well as four other closely linked KASP markers, may be useful for pyramiding h4 with other HF resistance genes in breeding.

The Hessian fly recessive resistance gene h4 mapped to chromosome 1A of the wheat cultivar 'Java' using genotyping-by-sequencing

The recessive Hessian fly resistance gene h4 and flanking SNP markers were located to a 642 kb region in chromosome 1A of the wheat cultivar 'Java.' Hessian fly (HF), Mayetiola destructor, is one of the most destructive insect pests in wheat worldwide. The wheat cultivar 'Java' was reported to carry a recessive gene (h4) for HF resistance; however, its chromosome location has not been determined. To map the HF resistance gene in Java, two populations of recombinant inbred lines (RILs) were developed from 'Bobwhite' × Java and 'Overley' × Java, respectively, and were phenotyped for responses to infestation of HF Great Plains biotype. Analysis of phenotypic data from the F₁ and the RIL populations confirmed that one recessive gene conditioned HF resistance in Java. Two linkage maps were constructed using single-nucleotide polymorphism (SNP) markers generated by genotyping-by-sequencing (GBS). The h4 gene was mapped to the distal end of the short arm of chromosome 1A, which explained 60.4 to 70.5% of the phenotypic variation for HF resistance in the two populations. The GBS-SNPs in the h4 candidate interval were converted into Kompetitive Allele-Specific Polymerase Chain Reaction (KASP) markers to eliminate the missing data points in GBS-SNPs. Using the revised maps with KASP markers, h4 was further located to a 642 kb interval (6,635,984-7,277,935 bp). The two flanking KASP markers, KASP3299 and KASP1871, as well as four other closely linked KASP markers, may be useful for pyramiding h4 with other HF resistance genes in breeding.

Optimization of the genotyping-by-sequencing SNP calling for diversity analysis in cape gooseberry (Physalis peruviana L.) and related taxa

A robust Genotyping-By-Sequencing (GBS) pipeline platform was examined to provide accurate discovery of Single Nucleotide Polymorphisms (SNPs) in a cape gooseberry (Physalis peruviana L.) and related taxa germplasm collection. A total of 176 accessions representing, wild, weedy, and commercial cultivars as well as related taxa from the Colombian germplasm bank and other world repositories were screened using GBS. The pipeline parameters mnLCov of 0.5 and a mnScov of 0.7, tomato and potato genomes, and cape gooseberry transcriptome for read alignments, were selected to better assess diversity and population structure in cape gooseberry and related taxa. A total of 7,425 SNPs, derived from P. peruviana common tags (unique 64 bp sequences shared between selected species), were used. Within P. peruviana, five subpopulations with a high genetic diversity and allele fixation (H_E: 0.35 to 0.36 and F_IS: -0.11 to -0.01, respectively) were detected. Conversely, low genetic differentiation (F_ST: 0.01 to 0.05) was also observed, indicating a high gene flow among subpopulations. These results contribute to the establishment of adequate conservation and breeding strategies for Cape gooseberry and closely related Physalis species.

Genome-wide SNP discovery and core marker sets for assessment of genetic variations in cultivated pumpkin (Cucurbita spp.)

Three pumpkin species Cucurbita maxima, C. moschata, and C. pepo are commonly cultivated worldwide. To identify genome-wide SNPs in these cultivated pumpkin species, we collected 48 F1 cultivars consisting of 40 intraspecific hybrids (15 C. maxima, 18 C. moschata, and 7 C. pepo) and 8 interspecific hybrids (C. maxima x C. moschata). Genotyping by sequencing identified a total of 37,869 confident SNPs in this collection. These SNPs were filtered to generate a subset of 400 SNPs based on polymorphism and genome distribution. Of the 400 SNPs, 288 were used to genotype an additional 188 accessions (94 F1 cultivars, 50 breeding lines, and 44 landraces) with a SNP array-based platform. Reliable polymorphisms were observed in 224 SNPs (78.0%) and were used to assess genetic variations between and within the four predefined populations in 223 cultivated pumpkin accessions. Both principal component analysis and UPGMA clustering found four major clusters representing three pumpkin species and interspecific hybrids. This genetic differentiation was supported by pairwise Fst and Nei's genetic distance. The interspecific hybrids showed a higher level of genetic diversity relative to the other three populations. Of the 224 SNPs, five subsets of 192, 96, 48, 24, and 12 markers were evaluated for variety identification. The 192, 96, and 48 marker sets identified 204 (91.5%), 190 (85.2%), and 141 (63.2%) of the 223 accessions, respectively, while other subsets showed <25% of variety identification rates. These SNP markers provide a molecular tool with many applications for genetics and breeding in cultivated pumpkin.

NGSEP3: accurate variant calling across species and sequencing protocols

MOTIVATION

Accurate detection, genotyping and downstream analysis of genomic variants from high-throughput sequencing data are fundamental features in modern production pipelines for genetic-based diagnosis in medicine or genomic selection in plant and animal breeding. Our research group maintains the Next-Generation Sequencing Experience Platform (NGSEP) as a precise, efficient and easy-to-use software solution for these features.

RESULTS

Understanding that incorrect alignments around short tandem repeats are an important source of genotyping errors, we implemented in NGSEP new algorithms for realignment and haplotype clustering of reads spanning indels and short tandem repeats. We performed extensive benchmark experiments comparing NGSEP to state-of-the-art software using real data from three sequencing protocols and four species with different distributions of repetitive elements. NGSEP consistently shows comparative accuracy and better efficiency compared to the existing solutions. We expect that this work will contribute to the continuous improvement of quality in variant calling needed for modern applications in medicine and agriculture.

AVAILABILITY AND IMPLEMENTATION

NGSEP is available as open source software at http://ngsep.sf.net.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

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.

De novo Genome Assembly of the indica Rice Variety IR64 Using Linked-Read Sequencing and Nanopore Sequencing

IR64 is a rice variety with high-yield that has been widely cultivated around the world. IR64 has been replaced by modern varieties in most growing areas. Given that modern varieties are mostly progenies or relatives of IR64, genetic analysis of IR64 is valuable for rice functional genomics. However, chromosome-level genome sequences of IR64 have not been available previously. Here, we sequenced the IR64 genome using synthetic long reads obtained by linked-read sequencing and ultra-long reads obtained by nanopore sequencing. We integrated these data and generated the de novo assembly of the IR64 genome of 367 Mb, equivalent to 99% of the estimated size. Continuity of the IR64 genome assembly was improved compared with that of a publicly available IR64 genome assembly generated by short reads only. We annotated 41,458 protein-coding genes, including 657 IR64-specific genes, that are missing in other high-quality rice genome assemblies IRGSP-1.0 of japonica cultivar Nipponbare or R498 of indica cultivar Shuhui498. The IR64 genome assembly will serve as a genome resource for rice functional genomics as well as genomics-driven and/or molecular breeding.

Fine mapping and gene cloning in the post-NGS era: advances and prospects

Improvement in traits of agronomic importance is the top breeding priority of crop improvement programs. Majority of these agronomic traits show complex quantitative inheritance. Identification of quantitative trait loci (QTLs) followed by fine mapping QTLs and cloning of candidate genes/QTLs is central to trait analysis. Advances in genomic technologies revolutionized our understanding of genetics of complex traits, and genomic regions associated with traits were employed in marker-assisted breeding or cloning of QTLs/genes. Next-generation sequencing (NGS) technologies have enabled genome-wide methodologies for the development of ultra-high-density genetic linkage maps in different crops, thus allowing placement of candidate loci within few kbs in genomes. In this review, we compare the marker systems used for fine mapping and QTL cloning in the pre- and post-NGS era. We then discuss how different NGS platforms in combination with advanced experimental designs have improved trait analysis and fine mapping. We opine that efficient genotyping/sequencing assays may circumvent the need for cumbersome procedures that were earlier used for fine mapping. A deeper understanding of the trait architectures of agricultural significance will be crucial to accelerate crop improvement.

Root transcriptome reveals efficient cell signaling and energy conservation key to aluminum toxicity tolerance in acidic soil adapted rice genotype

Aluminium (Al) toxicity is the single most important contributing factor constraining crop productivity in acidic soils. Hydroponics based screening of three rice genotypes, a tolerant (ARR09, AR), a susceptible (IR 1552, IR) and an acid soil adapted landrace (Theruvii, TH) revealed that AR accumulates less Al and shows minimum decrease in shoot and root biomass under Al toxicity conditions when compared with IR. Transcriptome data generated on roots (grown in presence or absence of Al) led to identification of ~1500 transcripts per genotype with percentage annotation ranging from 21.94% (AR) to 29.94% (TH). A total of 511, 804 and 912 DEGs were identified in genotypes AR, IR and TH, respectively. IR showed upregulation of transcripts involved in exergonic processes. AR appears to conserve energy by downregulating key genes of glycolysis pathway and maintaining transcript levels of key exergonic step enzymes under Al stress. The tolerance in AR appears to be as a result of novel mechanism as none of the reported Al toxicity genes or QTLs overlap with significant DEGs. Components of signal transduction and regulatory machinery like transcripts encoding zinc finger protein, calcieurin binding protein and cell wall associated transcripts are among the highly upregulated DEGs in AR, suggesting increased and better signal transduction in response to Al stress in tolerant rice. Sequencing of NRAT1 and glycine-rich protein A3 revealed distinct haplotype for indica type AR. The newly identified components of Al tolerance will help in designing molecular breeding tools to enhance rice productivity in acidic soils.

Genome wide association study of 5 agronomic traits in olive (Olea europaea L.)

Olive (Olea europaea L.) is one of the most economically and historically important fruit crops worldwide. Genetic progress for valuable agronomic traits has been slow in olive despite its importance and benefits. Advances in next generation sequencing technologies provide inexpensive and highly reproducible genotyping approaches such as Genotyping by Sequencing, enabling genome wide association study (GWAS). Here we present the first comprehensive GWAS study on olive using GBS. A total of 183 accessions (FULL panel) were genotyped using GBS, 94 from the Turkish Olive GenBank Resource (TOGR panel) and 89 from the USDA-ARS National Clonal Germplasm Repository (NCGR panel) in the USA. After filtering low quality and redundant markers, GWAS was conducted using 24,977 SNPs in FULL, TOGR and NCGR panels. In total, 52 significant associations were detected for leaf length, fruit weight, stone weight and fruit flesh to pit ratio using the MLM_K. Significant GWAS hits were mapped to their positions and 19 candidate genes were identified within a 10-kb distance of the most significant SNP. Our findings provide a framework for the development of markers and identification of candidate genes that could be used in olive breeding programs.

Engineering meiotic recombination pathways in rice

In the last 15 years, outstanding progress has been made in understanding the function of meiotic genes in the model dicot and monocot plants Arabidopsis and rice (Oryza sativa L.), respectively. This knowledge allowed to modulate meiotic recombination in Arabidopsis and, more recently, in rice. For instance, the overall frequency of crossovers (COs) has been stimulated 2.3- and 3.2-fold through the inactivation of the rice FANCM and RECQ4 DNA helicases, respectively, two genes involved in the repair of DNA double-strand breaks (DSBs) as noncrossovers (NCOs) of the Class II crossover pathway. Differently, the programmed induction of DSBs and COs at desired sites is currently explored by guiding the SPO11-1 topoisomerase-like transesterase, initiating meiotic recombination in all eukaryotes, to specific target regions of the rice genome. Furthermore, the inactivation of 3 meiosis-specific genes, namely PAIR1, OsREC8 and OsOSD1, in the Mitosis instead of Meiosis (MiMe) mutant turned rice meiosis into mitosis, thereby abolishing recombination and achieving the first component of apomixis, apomeiosis. The successful translation of Arabidopsis results into a crop further allowed the implementation of two breakthrough strategies that triggered parthenogenesis from the MiMe unreduced clonal egg cell and completed the second component of diplosporous apomixis. Here, we review the most recent advances in and future prospects of the manipulation of meiotic recombination in rice and potentially other major crops, all essential for global food security.

Genotyping-by-sequencing based QTL mapping for rice grain yield under reproductive stage drought stress tolerance

QTLs for rice grain yield under reproductive stage drought stress (qDTY) identified earlier with low density markers have shown linkage drag and need to be fine mapped before their utilization in breeding programs. In this study, genotyping-by-sequencing (GBS) based high-density linkage map of rice was developed using two BC₁F₃ mapping populations namely Swarna*2/Dular (3929 SNPs covering 1454.68 cM) and IR11N121*2/Aus196 (1191 SNPs covering 1399.68 cM) with average marker density of 0.37 cM to 1.18 cM respectively. In total, six qDTY QTLs including three consistent effect QTLs were identified in Swarna*2/Dular while eight qDTY QTLs including two consistent effect QTLs were identified in IR11N121*2/Aus 196 mapping population. Comparative analysis revealed four stable and novel QTLs (qDTY_2.4, qDTY_3.3, qDTY_6.3, and qDTY_11.2) which explained 8.62 to 14.92% PVE. However, one of the identified stable grain yield QTL qDTY_1.1 in both the populations was located nearly at the same physical position of an earlier mapped major qDTY QTL. Further, the effect of the identified qDTY_1.1 was validated in a subset of lines derived from five mapping populations confirming robustness of qDTY_1.1 across various genetic backgrounds/seasons. The study successfully identified stable grain yield QTLs free from undesirable linkages of tall plant height/early maturity utilizing high density linkage maps.

1k-RiCA (1K-Rice Custom Amplicon) a novel genotyping amplicon-based SNP assay for genetics and breeding applications in rice

BACKGROUND

While a multitude of genotyping platforms have been developed for rice, the majority of them have not been optimized for breeding where cost, turnaround time, throughput and ease of use, relative to density and informativeness are critical parameters of their utility. With that in mind we report the development of the 1K-Rice Custom Amplicon, or 1k-RiCA, a robust custom sequencing-based amplicon panel of ~ 1000-SNPs that are uniformly distributed across the rice genome, designed to be highly informative within indica rice breeding pools, and tailored for genomic prediction in elite indica rice breeding programs.

RESULTS

Empirical validation tests performed on the 1k-RiCA showed average marker call rates of 95% with marker repeatability and concordance rates of 99%. These technical properties were not affected when two common DNA extraction protocols were used. The average distance between SNPs in the 1k-RiCA was 1.5 cM, similar to the theoretical distance which would be expected between 1,000 uniformly distributed markers across the rice genome. The average minor allele frequencies on a panel of indica lines was 0.36 and polymorphic SNPs estimated on pairwise comparisons between indica by indica accessions and indica by japonica accessions were on average 430 and 450 respectively. The specific design parameters of the 1k-RiCA allow for a detailed view of genetic relationships and unambiguous molecular IDs within indica accessions and good cost vs. marker-density balance for genomic prediction applications in elite indica germplasm. Predictive abilities of Genomic Selection models for flowering time, grain yield, and plant height were on average 0.71, 0.36, and 0.65 respectively based on cross-validation analysis. Furthermore the inclusion of important trait markers associated with 11 different genes and QTL adds value to parental selection in crossing schemes and marker-assisted selection in forward breeding applications.

CONCLUSIONS

This study validated the marker quality and robustness of the 1k-RiCA genotypic platform for genotyping populations derived from indica rice subpopulation for genetic and breeding purposes including MAS and genomic selection. The 1k-RiCA has proven to be an alternative cost-effective genotyping system for breeding applications.

Genotyping by sequencing can reveal the complex mosaic genomes in gene pools resulting from reticulate evolution: a case study in diploid and polyploid citrus

BACKGROUND AND AIMS

Reticulate evolution, coupled with reproductive features limiting further interspecific recombinations, results in admixed mosaics of large genomic fragments from the ancestral taxa. Whole-genome sequencing (WGS) data are powerful tools to decipher such complex genomes but still too costly to be used for large populations. The aim of this work was to develop an approach to infer phylogenomic structures in diploid, triploid and tetraploid individuals from sequencing data in reduced genome complexity libraries. The approach was applied to the cultivated Citrus gene pool resulting from reticulate evolution involving four ancestral taxa, C. maxima, C. medica, C. micrantha and C. reticulata.

METHODS

A genotyping by sequencing library was established with the restriction enzyme ApeKI applying one base (A) selection. Diagnostic single nucleotide polymorphisms (DSNPs) for the four ancestral taxa were mined in 29 representative varieties. A generic pipeline based on a maximum likelihood analysis of the number of read data was established to infer ancestral contributions along the genome of diploid, triploid and tetraploid individuals. The pipeline was applied to 48 diploid, four triploid and one tetraploid citrus accessions.

KEY RESULTS

Among 43 598 mined SNPs, we identified a set of 15 946 DSNPs covering the whole genome with a distribution similar to that of gene sequences. The set efficiently inferred the phylogenomic karyotype of the 53 analysed accessions, providing patterns for common accessions very close to that previously established using WGS data. The complex phylogenomic karyotypes of 21 cultivated citrus, including bergamot, triploid and tetraploid limes, were revealed for the first time.

CONCLUSIONS

The pipeline, available online, efficiently inferred the phylogenomic structures of diploid, triploid and tetraploid citrus. It will be useful for any species whose reproductive behaviour resulted in an interspecific mosaic of large genomic fragments. It can also be used for the first generations of interspecific breeding schemes.

High-density linkage map construction and mapping QTL for yield and yield components in autotetraploid alfalfa using RAD-seq

BACKGROUND

Alfalfa (Medicago sativa L.) is an important forage crop grown worldwide. Alfalfa is called the "queen of forage crops" due to its high forage yield and nutritional characteristics. The aim of this study was to undertake quantitative trait loci (QTL) mapping of yield and yield-related traits in an F₁ population of two alfalfa varieties that differ in their yield and yield-related traits.

RESULTS

We constructed a high-density linkage map using single nucleotide polymorphism (SNP) markers generated by restriction-site associated DNA sequencing (RAD-seq). The linkage map contains 4346 SNP and 119 simple sequence repeat (SSR) markers, with 32 linkage groups for each parent. The average marker distances were 3.00 and 1.32 cM, with coverages of 3455 cM and 4381 cM for paternal and maternal linkage maps, respectively. Using these maps and phenotypic data, we identified a total of 21 QTL for yield and yield components, including five for yield, five for plant height, five for branch number, and six for shoot diameter. Among them, six QTL were co-located for more than one trait. Five QTL explained more than 10% of the phenotypic variation.

CONCLUSIONS

We used RAD-seq to construct a linkage map for alfalfa that greatly enhanced marker density compared to previous studies. This high-density linkage map of alfalfa is a useful reference for mapping yield-related traits. Identified yield-related loci could be used to validate their usefulness in developing markers for maker-assisted selection in breeding populations to improve yield potential in alfalfa.

Next-Generation Sequencing Accelerates Crop Gene Discovery

The identification and isolation of genes underlying quantitative trait loci (QTLs) associated with agronomic traits in crops have been recently accelerated thanks to next-generation sequencing (NGS)-based technologies combined with plant genetics. With NGS, various revisited genetic approaches, which benefited from higher marker density, have been elaborated. These approaches improved resolution in QTL position and assisted in determining functional causative variations in genes. Examples of QTLs/genes associated with agronomic traits in crops and identified using different strategies based on whole-genome sequencing (WGS)/whole-genome resequencing (WGR) or RNA-seq are presented and discussed in this review. More specifically, we summarize and illustrate how NGS boosted bulk-segregant analysis (BSA), expression profiling, and the construction of polymorphism databases to facilitate the detection of QTLs and causative genes.

Criteria for evaluating molecular markers: Comprehensive quality metrics to improve marker-assisted selection

Despite strong interest over many years, the usage of quantitative trait loci in plant breeding has often failed to live up to expectations. A key weak point in the utilisation of QTLs is the “quality” of markers used during marker-assisted selection (MAS): unreliable markers result in variable outcomes, leading to a perception that MAS products fail to achieve reliable improvement. Most reports of markers used for MAS focus on markers derived from the mapping population. There are very few studies that examine the reliability of these markers in other genetic backgrounds, and critically, no metrics exist to describe and quantify this reliability. To improve the MAS process, this work proposes five core metrics that fully describe the reliability of a marker. These metrics give a comprehensive and quantitative measure of the ability of a marker to correctly classify germplasm as QTL[+]/[–], particularly against a background of high allelic diversity. Markers that score well on these metrics will have far higher reliability in breeding, and deficiencies in specific metrics give information on circumstances under which a marker may not be reliable. The metrics are applicable across different marker types and platforms, allowing an objective comparison of the performance of different markers irrespective of the platform. Evaluating markers using these metrics demonstrates that trait-specific markers consistently out-perform markers designed for other purposes. These metrics also provide a superb set of criteria for designing superior marker systems for a target QTL, enabling the selection of an optimal marker set before committing to design.

Construction of a high-density linkage map and QTL detection of downy mildew resistance in Vitis aestivalis-derived 'Norton'

A major QTL for downy mildew resistance was detected on chromosome 18 (Rpv27) in Vitis aestivalis-derived 'Norton' based on a high-resolution linkage map with SNP and SSR markers as well as 2 years of field and laboratory phenotyping data. Grapevine downy mildew caused by the oomycete Plasmopara viticola is one of the most widespread and destructive diseases, particularly in humid viticultural areas where it damages green tissues and defoliates vines. Traditional Vitis vinifera wine grape cultivars are susceptible to downy mildew whereas several North American and a few Asian cultivars possess various levels of resistance to this disease. To identify genetic determinants of downy mildew resistance in V. aestivalis-derived 'Norton,' a mapping population with 182 genotypes was developed from a cross between 'Norton' and V. vinifera 'Cabernet Sauvignon' from which a consensus map was constructed via 411 simple sequence repeat (SSR) markers. Using genotyping-by-sequencing, 3825 single nucleotide polymorphism (SNP) markers were also generated. Of these, 1665 SNP and 407 SSR markers were clustered into 19 linkage groups in 159 genotypes, spanning a genetic distance of 2203.5 cM. Disease progression in response to P. viticola was studied in this population for 2 years under both laboratory and field conditions, and strong correlations were observed among data sets (Spearman correlation coefficient = 0.57-0.79). A quantitative trait loci (QTL) analysis indicated a resistance locus on chromosome 18, here named Rpv27, explaining 33.8% of the total phenotypic variation. Flanking markers closely linked with the trait can be further used for marker-assisted selection in the development of new cultivars with resistance to downy mildew.

Genotyping Polyploids from Messy Sequencing Data

Detecting and quantifying the differences in individual genomes (i.e., genotyping), plays a fundamental role in most modern bioinformatics pipelines. Many scientists now use reduced representation next-generation sequencing (NGS) approaches for genotyping. Genotyping diploid individuals using NGS is a well-studied field, and similar methods for polyploid individuals are just emerging. However, there are many aspects of NGS data, particularly in polyploids, that remain unexplored by most methods. Our contributions in this paper are fourfold: (i) We draw attention to, and then model, common aspects of NGS data: sequencing error, allelic bias, overdispersion, and outlying observations. (ii) Many datasets feature related individuals, and so we use the structure of Mendelian segregation to build an empirical Bayes approach for genotyping polyploid individuals. (iii) We develop novel models to account for preferential pairing of chromosomes, and harness these for genotyping. (iv) We derive oracle genotyping error rates that may be used for read depth suggestions. We assess the accuracy of our method in simulations, and apply it to a dataset of hexaploid sweet potato (Ipomoea batatas). An R package implementing our method is available at https://cran.r-project.org/package=updog.

Heat Stress Tolerance in Rice (Oryza sativa L.): Identification of Quantitative Trait Loci and Candidate Genes for Seedling Growth Under Heat Stress

Productivity of rice, world's most important cereal is threatened by high temperature stress, intensified by climate change. Development of heat stress-tolerant varieties is one of the best strategies to maintain its productivity. However, heat stress tolerance is a multigenic trait and the candidate genes are poorly known. Therefore, we aimed to identify quantitative trait loci (QTL) for vegetative stage tolerance to heat stress in rice and the corresponding candidate genes. We used genotyping-by-sequencing to generate single nucleotide polymorphic (SNP) markers and genotype 150 F8 recombinant inbred lines (RILs) obtained by crossing heat tolerant "N22" and heat susceptible "IR64" varieties. A linkage map was constructed using 4,074 high quality SNP markers that corresponded to 1,638 recombinationally unique events in this mapping population. Six QTL for root length and two for shoot length under control conditions with 2.1-12% effect were identified. One QTL rlht5.1 was identified for "root length under heat stress," with 20.4% effect. Four QTL were identified for "root length under heat stress as percent of control" that explained the total phenotypic variation from 5.2 to 8.6%. Three QTL with 5.3-10.2% effect were identified for "shoot length under heat stress," and seven QTL with 6.6-19% effect were identified for "shoot length under heat stress expressed as percentage of control." Among the QTL identified six were overlapping between those identified using shoot traits and root traits: two were overlapping between QTL identified for "shoot length under heat stress" and "root length expressed as percentage of control" and two QTL for "shoot length as percentage of control" were overlapping a QTL each for "root length as percentage of control" and "shoot length under heat stress." Genes coding 1,037 potential transcripts were identified based on their location in 10 QTL regions for vegetative stage heat stress tolerance. Among these, 213 transcript annotations were reported to be connected to stress tolerance in previous research in the literature. These putative candidate genes included transcription factors, chaperone proteins (e.g., alpha-crystallin family heat shock protein 20 and DNAJ homolog heat shock protein), proteases, protein kinases, phospholipases, and proteins related to disease resistance and defense and several novel proteins currently annotated as expressed and hypothetical proteins.

Accurate Genotype Imputation in Multiparental Populations from Low-Coverage Sequence

Many different types of multiparental populations have recently been produced to increase genetic diversity and resolution in QTL mapping. Low-coverage, genotyping-by-sequencing (GBS) technology has become a cost-effective tool in these populations, despite large amounts of missing data in offspring and founders. In this work, we present a general statistical framework for genotype imputation in such experimental crosses from low-coverage GBS data. Generalizing a previously developed hidden Markov model for calculating ancestral origins of offspring DNA, we present an imputation algorithm that does not require parental data and that is applicable to bi- and multiparental populations. Our imputation algorithm allows heterozygosity of parents and offspring as well as error correction in observed genotypes. Further, our approach can combine imputation and genotype calling from sequencing reads, and it also applies to called genotypes from SNP array data. We evaluate our imputation algorithm by simulated and real data sets in four different types of populations: the F2, the advanced intercross recombinant inbred lines, the multiparent advanced generation intercross, and the cross-pollinated population. Because our approach uses marker data and population design information efficiently, the comparisons with previous approaches show that our imputation is accurate at even very low ([Formula: see text]) sequencing depth, in addition to having accurate genotype phasing and error detection.

An imputation platform to enhance integration of rice genetic resources

As sequencing and genotyping technologies evolve, crop genetics researchers accumulate increasing numbers of genomic data sets from various genotyping platforms on different germplasm panels. Imputation is an effective approach to increase marker density of existing data sets toward the goal of integrating resources for downstream applications. While a number of imputation software packages are available, the limitations to utilization for the rice community include high computational demand and lack of a reference panel. To address these challenges, we develop the Rice Imputation Server, a publicly available web application leveraging genetic information from a globally diverse rice reference panel assembled here. This resource allows researchers to benefit from increased marker density without needing to perform imputation on their own machines. We demonstrate improvements that imputed data provide to rice genome-wide association (GWA) results of grain amylose content and show that the major functional nucleotide polymorphism is tagged only in the imputed data set.

An Immortalized Genetic Mapping Population for Perennial Ryegrass: A Resource for Phenotyping and Complex Trait Mapping

To address the lack of a truly portable, universal reference mapping population for perennial ryegrass, we have been developing a recombinant inbred line (RIL) mapping population of perennial ryegrass derived via single seed descent from a well-characterized F2 mapping population based on genetically distinct inbred parents in which the natural self-incompatibility (SI) system of perennial ryegrass has been overcome. We examined whether it is possible to create a genotyping by sequencing (GBS) based genetic linkage map in a small population of the F6 generation of this population. We used 41 F6 genotypes for GBS with PstI/MspI-based libraries. We successfully developed a genetic linkage map comprising 6074 SNP markers, placing a further 22080 presence and absence variation (PAV) markers on the map. We examined the resulting genetic map for general and RIL specific features. Overall segregation distortion levels were similar to those experienced in the F2 generation, but segregation distortion was reduced on linkage group 6 and increased on linkage group 7. Residual heterozygosity in the F6 generation was observed at a level of 5.4%. There was a high proportion of chromosomes (30%) exhibiting the intact haplotype of the original inbred parents of the F1 genotype from which the population is derived, pointing to a tendency for chromosomes to assort without recombining. This could affect the applicability of these lines and might make them more suitable for situations where repressed recombination is an advantage. Inter- and intra-chromosomal linkage disequilibrium (LD) analysis suggested that the map order was robust. We conclude that this RIL population, and subsequent F7 and F8 generations will be useful for genetic analysis and phenotyping of agronomic and biological important traits in perennial ryegrass.

Tools for Genetic Studies in Experimental Populations of Polyploids

Polyploid organisms carry more than two copies of each chromosome, a condition rarely tolerated in animals but which occurs relatively frequently in the plant kingdom. One of the principal challenges faced by polyploid organisms is to evolve stable meiotic mechanisms to faithfully transmit genetic information to the next generation upon which the study of inheritance is based. In this review we look at the tools available to the research community to better understand polyploid inheritance, many of which have only recently been developed. Most of these tools are intended for experimental populations (rather than natural populations), facilitating genomics-assisted crop improvement and plant breeding. This is hardly surprising given that a large proportion of domesticated plant species are polyploid. We focus on three main areas: (1) polyploid genotyping; (2) genetic and physical mapping; and (3) quantitative trait analysis and genomic selection. We also briefly review some miscellaneous topics such as the mode of inheritance and the availability of polyploid simulation software. The current polyploid analytic toolbox includes software for assigning marker genotypes (and in particular, estimating the dosage of marker alleles in the heterozygous condition), establishing chromosome-scale linkage phase among marker alleles, constructing (short-range) haplotypes, generating linkage maps, performing genome-wide association studies (GWAS) and quantitative trait locus (QTL) analyses, and simulating polyploid populations. These tools can also help elucidate the mode of inheritance (disomic, polysomic or a mixture of both as in segmental allopolyploids) or reveal whether double reduction and multivalent chromosomal pairing occur. An increasing number of polyploids (or associated diploids) are being sequenced, leading to publicly available reference genome assemblies. Much work remains in order to keep pace with developments in genomic technologies. However, such technologies also offer the promise of understanding polyploid genomes at a level which hitherto has remained elusive.

Deciphering genetic factors that determine melon fruit-quality traits using RNA-Seq-based high-resolution QTL and eQTL mapping

Combined quantitative trait loci (QTL) and expression-QTL (eQTL) mapping analysis was performed to identify genetic factors affecting melon (Cucumis melo) fruit quality, by linking genotypic, metabolic and transcriptomic data from a melon recombinant inbred line (RIL) population. RNA sequencing (RNA-Seq) of fruit from 96 RILs yielded a highly saturated collection of > 58 000 single-nucleotide polymorphisms, identifying 6636 recombination events that separated the genome into 3663 genomic bins. Bin-based QTL analysis of 79 RILs and 129 fruit-quality traits affecting taste, aroma and color resulted in the mapping of 241 QTL. Thiol acyltransferase (CmThAT1) gene was identified within the QTL interval of its product, S-methyl-thioacetate, a key component of melon fruit aroma. Metabolic activity of CmThAT1-encoded protein was validated in bacteria and in vitro. QTL analysis of flesh color intensity identified a candidate white-flesh gene (CmPPR1), one of two major loci determining fruit flesh color in melon. CmPPR1 encodes a member of the pentatricopeptide protein family, involved in processing of RNA in plastids, where carotenoid and chlorophyll pigments accumulate. Network analysis of > 12 000 eQTL mapped for > 8000 differentially expressed fruit genes supported the role of CmPPR1 in determining the expression level of plastid targeted genes. We highlight the potential of RNA-Seq-based QTL analysis of small to moderate size, advanced RIL populations for precise marker-assisted breeding and gene discovery. We provide the following resources: a RIL population genotyped with a unique set of SNP markers, confined genomic segments that harbor QTL governing 129 traits and a saturated set of melon eQTLs.

Accounting for Errors in Low Coverage High-Throughput Sequencing Data When Constructing Genetic Maps Using Biparental Outcrossed Populations

Next-generation sequencing is an efficient method that allows for substantially more markers than previous technologies, providing opportunities for building high-density genetic linkage maps, which facilitate the development of nonmodel species' genomic assemblies and the investigation of their genes. However, constructing genetic maps using data generated via high-throughput sequencing technology (e.g., genotyping-by-sequencing) is complicated by the presence of sequencing errors and genotyping errors resulting from missing parental alleles due to low sequencing depth. If unaccounted for, these errors lead to inflated genetic maps. In addition, map construction in many species is performed using full-sibling family populations derived from the outcrossing of two individuals, where unknown parental phase and varying segregation types further complicate construction. We present a new methodology for modeling low coverage sequencing data in the construction of genetic linkage maps using full-sibling populations of diploid species, implemented in a package called GUSMap. Our model is based on the Lander-Green hidden Markov model but extended to account for errors present in sequencing data. We were able to obtain accurate estimates of the recombination fractions and overall map distance using GUSMap, while most existing mapping packages produced inflated genetic maps in the presence of errors. Our results demonstrate the feasibility of using low coverage sequencing data to produce genetic maps without requiring extensive filtering of potentially erroneous genotypes, provided that the associated errors are correctly accounted for in the model.