Crop Breeding Chips and Genotyping Platforms: Progress, Challenges, and Perspectives

Development of an Axiom Sugarcane100K SNP array for genetic map construction and QTL identification

An Axiom Sugarcane100K SNP array has been designed and successfully utilized to construct the sugarcane genetic map and to identify the QTLs associated with SCYLV resistance. To accelerate genetic studies in sugarcane, an Axiom Sugarcane100K single-nucleotide polymorphism (SNP) array was designed and customized in this study. Target enrichment sequencing 300 sugarcane accessions selected from the world collection of sugarcane and related grass species yielded more than four million SNPs, from which a total of 31,449 single-dose (SD) SNPs and 68,648 low-dosage (33,277 SD and 35,371 double dose) SNPs from two datasets, respectively, were selected and tiled on Affymetrix Axiom SNP array. Most of selected SNPs (91.77%) were located within genic regions (12,935 genes), with an average of 7.1 SNPs/gene according to sorghum gene models. This array was used to genotype 469 sugarcane clones, including one F₁ population derived from the cross between Green German and IND81-146, one selfing population derived from CP80-1827, and 11 diverse sugarcane accessions as controls. Results of genotyping revealed a high polymorphic SNP rate (77.04%) among the 469 samples. Three linkage maps were constructed by using SD SNP markers, including a genetic map for Green German with 3482 SD SNP markers spanning 3336 cM, a map for IND81-146 with 1513 SD SNP markers spanning 2615 cM, and a map for CP80-1827 with 536 SD SNP markers spanning 3651 cM. Quantitative trait loci (QTL) analysis identified 18 QTLs controlling Sugarcane yellow leaf virus resistance segregating in the two mapping populations, harboring 27 disease-resistant genes. This study demonstrated the successful development and utilization of a SNP array as an efficient genetic tool for high-throughput genotyping in highly polyploid sugarcane.

SNP and Haplotype-Based Genomic Selection of Quantitative Traits in Eucalyptus globulus

Eucalyptus globulus (Labill.) is one of the most important cultivated eucalypts in temperate and subtropical regions and has been successfully subjected to intensive breeding. In this study, Bayesian genomic models that include the effects of haplotype and single nucleotide polymorphisms (SNP) were assessed to predict quantitative traits related to wood quality and tree growth in a 6-year-old breeding population. To this end, the following markers were considered: (a) ~14 K SNP markers (SNP), (b) ~3 K haplotypes (HAP), and (c) haplotypes and SNPs that were not assigned to a haplotype (HAP-SNP). Predictive ability values (PA) were dependent on the genomic prediction models and markers. On average, Bayesian ridge regression (BRR) and Bayes C had the highest PA for the majority of traits. Notably, genomic models that included the haplotype effect (either HAP or HAP-SNP) significantly increased the PA of low-heritability traits. For instance, BRR based on HAP had the highest PA (0.58) for stem straightness. Consistently, the heritability estimates from genomic models were higher than the pedigree-based estimates for these traits. The results provide additional perspectives for the implementation of genomic selection in Eucalyptus breeding programs, which could be especially beneficial for improving traits with low heritability.

Domesticating the Undomesticated for Global Food and Nutritional Security: Four Steps

Ensuring the food and nutritional demand of the ever-growing human population is a major sustainability challenge for humanity in this Anthropocene. The cultivation of climate resilient, adaptive and underutilized wild crops along with modern crop varieties is proposed as an innovative strategy for managing future agricultural production under the changing environmental conditions. Such underutilized and neglected wild crops have been recently projected by the Food and Agricultural Organization of the United Nations as ‘future smart crops’ as they are not only hardy, and resilient to changing climatic conditions, but also rich in nutrients. They need only minimal care and input, and therefore, they can be easily grown in degraded and nutrient-poor soil also. Moreover, they can be used for improving the adaptive traits of modern crops. The contribution of such neglected, and underutilized crops and their wild relatives to global food production is estimated to be around 115–120 billion US$ per annum. Therefore, the exploitation of such lesser utilized and yet to be used wild crops is highly significant for climate resilient agriculture and thereby providing a good quality of life to one and all. Here we provide four steps, namely: (i) exploring the unexplored, (ii) refining the unrefined traits, (iii) cultivating the uncultivated, and (iv) popularizing the unpopular for the sustainable utilization of such wild crops as a resilient strategy for ensuring food and nutritional security and also urge the timely adoption of suitable frameworks for the large-scale exploitation of such wild species for achieving the UN Sustainable Development Goals.

Development of an integrated 200K SNP genotyping array and application for genetic mapping, genome assembly improvement and genome wide association studies in pear (Pyrus)

Pear (Pyrus; 2n = 34), the third most important temperate fruit crop, has great nutritional and economic value. Despite the availability of many genomic resources in pear, it is challenging to genotype novel germplasm resources and breeding progeny in a timely and cost-effective manner. Genotyping arrays can provide fast, efficient and high-throughput genetic characterization of diverse germplasm, genetic mapping and breeding populations. We present here 200K AXIOM^® PyrSNP, a large-scale single nucleotide polymorphism (SNP) genotyping array to facilitate genotyping of Pyrus species. A diverse panel of 113 re-sequenced pear genotypes was used to discover SNPs to promote increased adoption of the array. A set of 188 diverse accessions and an F₁ population of 98 individuals from 'Cuiguan' × 'Starkrimson' was genotyped with the array to assess its effectiveness. A large majority of SNPs (166 335 or 83%) are of high quality. The high density and uniform distribution of the array SNPs facilitated prediction of centromeric regions on 17 pear chromosomes, and significantly improved the genome assembly from 75.5% to 81.4% based on genetic mapping. Identification of a gene associated with flowering time and candidate genes linked to size of fruit core via genome wide association studies showed the usefulness of the array in pear genetic research. The newly developed high-density SNP array presents an important tool for rapid and high-throughput genotyping in pear for genetic map construction, QTL identification and genomic selection.

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.

Genome-Wide Association Study Reveals Candidate Genes for Flowering Time Variation in Common Bean (Phaseolus vulgaris L.)

The common bean is one of the most important staples in many areas of the world. Extensive phenotypic and genetic characterization of unexplored bean germplasm are still needed to unlock the breeding potential of this crop. Dissecting genetic control of flowering time is of pivotal importance to foster common bean breeding and to develop new varieties able to adapt to changing climatic conditions. Indeed, flowering time strongly affects yield and plant adaptation ability. The aim of this study was to investigate the genetic control of days to flowering using a whole genome association approach on a panel of 192 highly homozygous common bean genotypes purposely developed from landraces using Single Seed Descent. The phenotypic characterization was carried out at two experimental sites throughout two growing seasons, using a randomized partially replicated experimental design. The same plant material was genotyped using double digest Restriction-site Associated DNA sequencing producing, after a strict quality control, a dataset of about 50 k Single Nucleotide Polymorphisms (SNPs). The Genome-Wide Association Study revealed significant and meaningful associations between days to flowering and several SNP markers; seven genes are proposed as the best candidates to explain the detected associations.

Generating High Density, Low Cost Genotype Data in Soybean [Glycine max (L.) Merr.]

Obtaining genome-wide genotype information for millions of SNPs in soybean [Glycine max (L.) Merr.] often involves completely resequencing a line at 5X or greater coverage. Currently, hundreds of soybean lines have been resequenced at high depth levels with their data deposited in the NCBI Short Read Archive. This publicly available dataset may be leveraged as an imputation reference panel in combination with skim (low coverage) sequencing of new soybean genotypes to economically obtain high-density SNP information. Ninety-nine soybean lines resequenced at an average of 17.1X were used to generate a reference panel, with over 10 million SNPs called using GATK's Haplotype Caller tool. Whole genome resequencing at approximately 1X depth was performed on 114 previously ungenotyped experimental soybean lines. Coverages down to 0.1X were analyzed by randomly subsetting raw reads from the original 1X sequence data. SNPs discovered in the reference panel were genotyped in the experimental lines after aligning to the soybean reference genome, and missing markers imputed using Beagle 4.1. Sequencing depth of the experimental lines could be reduced to 0.3X while still retaining an accuracy of 97.8%. Accuracy was inversely related to minor allele frequency, and highly correlated with marker linkage disequilibrium. The high accuracy of skim sequencing combined with imputation provides a low cost method for obtaining dense genotypic information that can be used for various genomics applications in soybean.

High-quality, genome-wide SNP genotypic data for pedigreed germplasm of the diploid outbreeding species apple, peach, and sweet cherry through a common workflow

High-quality genotypic data is a requirement for many genetic analyses. For any crop, errors in genotype calls, phasing of markers, linkage maps, pedigree records, and unnoticed variation in ploidy levels can lead to spurious marker-locus-trait associations and incorrect origin assignment of alleles to individuals. High-throughput genotyping requires automated scoring, as manual inspection of thousands of scored loci is too time-consuming. However, automated SNP scoring can result in errors that should be corrected to ensure recorded genotypic data are accurate and thereby ensure confidence in downstream genetic analyses. To enable quick identification of errors in a large genotypic data set, we have developed a comprehensive workflow. This multiple-step workflow is based on inheritance principles and on removal of markers and individuals that do not follow these principles, as demonstrated here for apple, peach, and sweet cherry. Genotypic data was obtained on pedigreed germplasm using 6-9K SNP arrays for each crop and a subset of well-performing SNPs was created using ASSIsT. Use of correct (and corrected) pedigree records readily identified violations of simple inheritance principles in the genotypic data, streamlined with FlexQTL software. Retained SNPs were grouped into haploblocks to increase the information content of single alleles and reduce computational power needed in downstream genetic analyses. Haploblock borders were defined by recombination locations detected in ancestral generations of cultivars and selections. Another round of inheritance-checking was conducted, for haploblock alleles (i.e., haplotypes). High-quality genotypic data sets were created using this workflow for pedigreed collections representing the U.S. breeding germplasm of apple, peach, and sweet cherry evaluated within the RosBREED project. These data sets contain 3855, 4005, and 1617 SNPs spread over 932, 103, and 196 haploblocks in apple, peach, and sweet cherry, respectively. The highly curated phased SNP and haplotype data sets, as well as the raw iScan data, of germplasm in the apple, peach, and sweet cherry Crop Reference Sets is available through the Genome Database for Rosaceae.

Genome-Wide Analyses Reveal Footprints of Divergent Selection and Drought Adaptive Traits in Synthetic-Derived Wheats

Crop-wild introgressions have long been exploited without knowing the favorable recombination points. Synthetic hexaploid wheats are one of the most exploited genetic resources for bread wheat improvement. However, despite some QTL with major effects, much less is known about genome-wide patterns of introgressions and their effects on phenotypes. We used two genome-wide association approaches: SNP-GWAS and haplotype-GWAS to identify SNPs and haplotypes associated with productivity under water-limited conditions in a synthetic-derived wheat (SYN-DER) population. Haplotype-GWAS further enriched and identified 20 more genomic regions associated with drought adaptability that did not overlap with SNP-GWAS. Since GWAS is biased to the phenotypes in the study and may fail to detect important genetic diversity during breeding, we used five complementary analytical approaches (t-test, Tajima’s D, nucleotide diversity (π), Fst, and EigenGWAS) to identify divergent selections in SYN-DER compared to modern bread wheat. These approaches consistently pinpointed 89 ‘selective sweeps’, out of which 30 selection loci were identified on D-genome. These key selections co-localized with important functional genes of adaptive traits such as TaElf3-D1 (1D) for earliness per se (Eps), TaCKX-D1 (3D), TaGS1a (6D) and TaGS-D1 (7D) for grain size, weight and morphology, TaCwi-D1 (5D) influencing drought tolerance, and Vrn-D3 (7D) for vernalization. Furthermore, 55 SNPs and 23 haplotypes of agronomic and physiological importance such as grain yield, relative water content and thousand grain weight in SYN-DER, were among the top 5% of divergent selections contributed by synthetic hexaploid wheats. These divergent selections associated with improved agronomic performance carry new alleles that have been introduced to wheat. Our results demonstrated that GWAS and selection sweep analyses are powerful approaches for investigating favorable introgressions under strong selection pressure and the use of crop-wild hybridization to assist the improvement of wheat yield and productivity under moisture limiting environments.

Molecular Characterization of 87 Functional Genes in Wheat Diversity Panel and Their Association With Phenotypes Under Well-Watered and Water-Limited Conditions

Modern breeding imposed selection for improved productivity that largely influenced the frequency of superior alleles underpinning traits of breeding interest. Therefore, molecular diagnosis for the allelic variations of such genes is important to manipulate beneficial alleles in wheat molecular breeding. We analyzed a diversity panel largely consisted of advanced lines derived from synthetic hexaploid wheats for allelic variation at 87 functional genes or loci of breeding importance using 124 high-throughput KASP markers. We also developed two KASP markers for water-soluble carbohydrate genes (TaSST-D1 and TaSST-A1) associated with plant height and thousand grain weight (TGW) in the diversity panel. KASP genotyping results indicated that beneficial alleles for genes underpinning flowering time (Ppd-D1 and Vrn-D3), thousand grain weight (TaCKX-D1, TaTGW6-A1, TaSus1-7B, and TaCwi-D1), water-soluble carbohydrates (TaSST-A1), yellow-pigment content (Psy-B1 and Zds-D1), and root lesion nematodes (Rlnn1) were fixed in diversity panel with frequency ranged from 96.4 to 100%. The association analysis of functional genes with agronomic and biochemical traits under well-watered (WW) and water-limited (WL) conditions revealed that 21 marker-trait associations (MTAs) were consistently detected in both moisture conditions. The major developmental genes such as Vrn-A1, Rht-D1, and Ppd-B1 had the confounding effect on several agronomic traits including plant height, grain size and weight, and grain yield in both WW and WL conditions. The accumulation of favorable alleles for grain size and weight genes additively enhanced grain weight in the diversity panel. Graphical genotyping approach was used to identify accessions with maximum number of favorable alleles, thus likely to have high breeding value. These results improved our knowledge on the selection of favorable and unfavorable alleles through unconscious selection breeding and identified the opportunities to deploy alleles with effects in wheat breeding.

A new genomic tool for walnut (Juglans regia L.): development and validation of the high-density Axiom™ J. regia 700K SNP genotyping array

Over the last 20 years, global production of Persian walnut (Juglans regia L.) has grown enormously, likely reflecting increased consumption due to its numerous benefits to human health. However, advances in genome-wide association (GWA) studies and genomic selection (GS) for agronomically important traits in walnut remain limited due to the lack of powerful genomic tools. Here, we present the development and validation of a high-density 700K single nucleotide polymorphism (SNP) array in Persian walnut. Over 609K high-quality SNPs have been thoroughly selected from a set of 9.6 m genome-wide variants, previously identified from the high-depth re-sequencing of 27 founders of the Walnut Improvement Program (WIP) of University of California, Davis. To validate the effectiveness of the array, we genotyped a collection of 1284 walnut trees, including 1167 progeny of 48 WIP families and 26 walnut cultivars. More than half of the SNPs (55.7%) fell in the highest quality class of 'Poly High Resolution' (PHR) polymorphisms, which were used to assess the WIP pedigree integrity. We identified 151 new parent-offspring relationships, all confirmed with the Mendelian inheritance test. In addition, we explored the genetic variability among cultivars of different origin, revealing how the varieties from Europe and California were differentiated from Asian accessions. Both the reconstruction of the WIP pedigree and population structure analysis confirmed the effectiveness of the Applied Biosystems™ Axiom™ J. regia 700K SNP array, which initiates a novel genomic and advanced phase in walnut genetics and breeding.

Multiomics analysis reveals a distinct mechanism of oleaginousness in the emerging model alga Chromochloris zofingiensis

Chromochloris zofingiensis, featured due to its capability to simultaneously synthesize triacylglycerol (TAG) and astaxanthin, is emerging as a leading candidate alga for production uses. To better understand the oleaginous mechanism of this alga, we conducted a multiomics analysis by systematically integrating time-resolved transcriptomes, lipidomes and metabolomes in response to nitrogen deprivation. The data analysis unraveled the distinct mechanism of TAG accumulation, which involved coordinated stimulation of multiple biological processes including supply of energy and reductants, carbon reallocation from protein and starch, and 'pushing' and 'pulling' carbon to TAG synthesis. Unlike the model alga Chlamydomonas, de novo fatty acid synthesis in C. zofingiensis was promoted, together with enhanced turnover of both glycolipids and phospholipids, supporting the drastic need of acyls for TAG assembly. Moreover, genomewide analysis identified many key functional enzymes and transcription factors that had engineering potential for TAG modulation. Two genes encoding glycerol-3-phosphate acyltransferase (GPAT), the first committed enzyme for TAG assembly, were found in the C. zofingiensis genome; in vivo functional characterization revealed that extrachloroplastic GPAT instead of chloroplastic GPAT played a central role in TAG synthesis. These findings illuminate distinct oleaginousness mechanisms in C. zofingiensis and pave the way towards rational manipulation of this alga to becone an emerging model for trait improvements.

Comparison of TaqMan, KASP and rhAmp SNP genotyping platforms in hexaploid wheat

Advances in high-throughput genotyping enable the generation of genome-scale data much more easily and at lower cost than ever before. However, small-scale and cost-effective high-throughput single-nucleotide polymorphism (SNP) genotyping technologies are still under development. In this study, we compared the performances of TaqMan, KASP and rhAmp SNP genotyping platforms in terms of their assay design flexibility, assay design success rate, allele call rate and quality, ease of experiment run and cost per sample. Fifty SNP markers linked to genes governing various agronomic traits of wheat were chosen to design SNP assays. Design success rates were 39/50, 49/50, and 49/50 for TaqMan, KASP, and rhAmp, respectively, and 30 SNP assays were manufactured for genotyping comparisons across the three platforms. rhAmp showed 97% of samples amplified while TaqMan and KASP showed 93% and 93.5% of amplifications, respectively. Allele call quality of rhAmp was 97%, while it was 98% for both TaqMan and KASP. rhAmp and KASP showed significantly better (p < 0.001) allele discrimination than TaqMan; however, TaqMan showed the most compact cluster. Based on the current market, rhAmp was the least expensive technology followed by KASP. In conclusion, rhAmp provides a reliable and cost-effective option for targeted genotyping and marker-assisted selection in crop genetic improvement.

Transcriptional profiling of contrasting genotypes revealed key candidates and nucleotide variations for drought dissection in Camellia sinensis (L.) O. Kuntze

Tea is popular health beverage consumed by millions of people worldwide. Drought is among the acute abiotic stress severely affecting tea cultivation, globally. In current study, transcriptome sequencing of four diverse tea genotypes with inherent contrasting genetic response to drought (tolerant & sensitive) generated more than 140 million reads. De novo and reference-based assembly and functional annotation of 67,093 transcripts with multifarious public protein databases yielded 54,484 (78.2%) transcripts with significant enrichment of GO and KEGG drought responsive pathways in tolerant genotypes. Comparative DGE and qRT analysis revealed key role of ABA dependent & independent pathways, potassium & ABC membrane transporters (AtABCG22, AtABCG11, AtABCC5 & AtABCC4) and antioxidant defence system against oxidative stress in tolerant genotypes, while seems to be failed in sensitive genotypes. Additionally, highly expressed UPL3HECT E3 ligases and RING E3 ligases possibly enhance drought tolerance by actively regulating functional modification of stress related genes. Further, ascertainment of, 80803 high quality putative SNPs with functional validation of key non-synonymous SNPs suggested their implications for developing high-throughput genotyping platform in tea. Futuristically, functionally relevant genomic resources can be potentially utilized for gene discovery, genetic engineering and marker-assisted genetic improvement for better yield and quality in tea under drought conditions.

Utilization of the Genomewide Wheat 55K SNP Array for Genetic Analysis of Stripe Rust Resistance in Common Wheat Line P9936

Breeding for resistance to stripe rust (caused by Puccinia striiformis f. tritici) is essential for reducing losses in yield and quality in wheat. To identify genes for use in breeding, a biparental population of 186 recombinant inbred lines (RILs) from a cross of the Chinese landrace Mingxian 169 and CIMMYT-derived line P9936 was evaluated in field nurseries either artificially or naturally inoculated in two crop seasons. Each of the RILs and parents was genotyped with the wheat 55K single-nucleotide polymorphism (SNP) 'Breeders' array and a genetic linkage map with 8,225 polymorphic SNP markers spanning 3,593.37 centimorgans was constructed. Two major quantitative trait loci (QTL) and two minor QTL were identified. The major QTL QYr.nwafu-3BS.2 and QYr.nwafu-7BL on chromosomes arms 3BS and 7BL were detected in all field locations and explained an average 20.4 and 38.9% of phenotypic variation stripe rust severity, respectively. QYr.nwafu-3BS.2 likely corresponds to the locus Yr30/Sr2 and QYr.nwafu-7BL may be a resistance allele identified previously in CIMMYT germplasm. The other minor QTL had limited individual effects but increased resistance when in combinations with other QTL. Markers linked to QYr.nwafu-7BL were converted to kompetitive allele-specific polymerase chain reaction markers and validated in a panel of wheat accessions. Wheat accessions carrying the same haplotype as P9936 at the identified SNP loci had lower average stripe rust severity than the average severity of all other haplotypes.

Identification and validation of a novel major QTL for all-stage stripe rust resistance on 1BL in the winter wheat line 20828

A major, likely novel stripe rust resistance QTL for all-stage resistance on chromosome arm 1BL identified in a 1.76-cM interval using a saturated linkage map was validated in four populations with different genetic backgrounds. Stripe rust is a globally important disease of wheat. Identification and utilization of new resistance genes are essential for breeding resistant cultivars. Wheat line 20828 has exhibited high levels of stripe rust resistance for over a decade. However, the genetics of stripe rust resistance in this line has not been studied. A set of 199 recombinant inbred lines (RILs) were developed from a cross between 20828 and a susceptible cultivar Chuannong 16. The RIL population was genotyped with the Wheat55K SNP (single nucleotide polymorphism) array and SSR (simple sequence repeat) markers and evaluated in four environments with current predominant Puccinia striiformis f. sp. tritici t races including CYR32, CYR33 and CYR34. Four stable QTL were located on chromosomes 1B (2 QTL), 4A and 6A. Among them, the major QTL, QYr.sicau-1B.1 (LOD = 23-28, PVE = 16-39%), was localized to a 1.76-cM interval flanked by SSR markers Xwmc216 and Xwmc156 on chromosome 1BL. Eight resistance genes were previously identified in the physical interval of QYr.sicau-1B.1. Compared with previous studies, QYr.sicau-1B.1 is a new gene for resistant to stripe rust. It was further verified by analysis of the closely linked SSR markers Xwmc216 and Xwmc156 in four other populations with different genetic backgrounds. QYr.sicau-1B.1 reduced the stripe rust disease index by up to 82.8%. Three minor stable QTL (located on chromosomes 1B, 4A and 6A, respectively) also added to the resistance level of QYr.sicau-1B.1. Our results provide valuable information for further fine mapping and cloning as well as molecular-assisted breeding with QYr.sicau-1B.1.

A major QTL co-localized on chromosome 6BL and its epistatic interaction for enhanced wheat stripe rust resistance

Co-localization of a major QTL for wheat stripe rust resistance to a 3.9-cM interval on chromosome 6BL across both populations and another QTL on chromosome 2B with epistatic interaction. Cultivars with diverse resistance are the optimal strategy to minimize yield losses caused by wheat stripe rust (Puccinia striiformis f. sp. tritici). Two wheat populations involving resistant wheat lines P10078 and Snb"S" from CIMMYT were evaluated for stripe rust response in multiple environments. Pool analysis by Wheat660K SNP array showed that the overlapping interval on chromosome 6B likely harbored a major QTL between two populations. Then, linkage maps were constructed using KASP markers, and a co-localized locus with large effect on chromosome 6BL was detected using QTL analysis in both populations. The coincident QTL, named QYr.nwafu-6BL.2, explained 59.7% of the phenotypic maximum variation in the Mingxian 169 × P10078 and 52.5% in the Zhengmai 9023 × Snb"S" populations, respectively. This co-localization interval spanning 3.9 cM corresponds to ~ 30.5-Mb genomic region of the newest common wheat reference genome (IWGSC RefSeq v.1.0). In addition, another QTL was also detected on chromosome 2B in Zhengmai 9023 × Snb"S" population and it can accelerate expression of QYr.nwafu-6BL.2 to enhance resistance with epistatic interaction. Allowing for Pst response, marker genotypes, pedigree analysis and relative genetic distance, QYr.nwafu-6BL.2 is likely to be a distinct adult plant resistance QTL. Haplotype analysis of QYr.nwafu-6BL.2 revealed specific SNPs or alleles in the target region from a diversity panel of 176 unrelated wheat accessions. This QTL region provides opportunity for further map-based cloning, and haplotypes analysis enables pyramiding favorable alleles into commercial cultivars by marker-assisted selection.

Uncovering Genomic Regions Associated With 36 Agro-Morphological Traits in Indian Spring Wheat Using GWAS

Wheat genetic improvement by integration of advanced genomic technologies is one way of improving productivity. To facilitate the breeding of economically important traits in wheat, SNP loci and underlying candidate genes associated with the 36 agro-morphological traits were studied in a diverse panel of 404 genotypes. By using Breeders' 35K Axiom array in a comprehensive genome-wide association study covering 4364.79 cM of the wheat genome and applying a compressed mixed linear model, a total of 146 SNPs (-log10 P ≥ 4) were found associated with 23 traits out of 36 traits studied explaining 3.7-47.0% of phenotypic variance. To reveal this a subset of 260 genotypes was characterized phenotypically for six quantitative traits [days to heading (DTH), days to maturity (DTM), plant height (PH), spike length (SL), awn length (Awn_L), and leaf length (Leaf_L)] under five environments. Gene annotations mined ∼38 putative candidate genes which were confirmed using tissue and stage specific gene expression data from RNA Seq. We observed strong co-localized loci for four traits (glume pubescence, SL, PH, and awn color) on chromosome 1B (24.64 cM) annotated five putative candidate genes. This study led to the discovery of hitherto unreported loci for some less explored traits (such as leaf sheath wax, awn attitude, and glume pubescence) besides the refined chromosomal regions of known loci associated with the traits. This study provides valuable information of the genetic loci and their potential genes underlying the traits such as awn characters which are being considered as important contributors toward yield enhancement.

Investigation and genome-wide association study for Fusarium crown rot resistance in Chinese common wheat

BACKGROUND

Fusarium crown rot (FCR) is a severe and chronic disease in common wheat and is able to cause serious yield loss and health problems to human and livestock.

RESULTS

Here, 234 Chinese wheat cultivars were evaluated in four greenhouse experiments for FCR resistance and genome-wide association studies (GWAS) were performed using the wheat 660 K genotyping assay. The results indicated that most cultivars evaluated showed FCR disease index (DI) of 40-60, while some cultivars showed stably good FCR resistance (DI < 30). GWAS identified 286 SNPs to be significantly associated with FCR resistance, of which 266, 6 and 8 were distributed on chromosomes 6A, 6B and 6D, respectively. The significant SNPs on 6A were located in a 7.0-Mb region containing 51 annotated genes. On the other hand, QTL mapping using a bi-parental population derived from UC1110 and PI610750 detected three QTLs on chromosomes 6A (explaining 7.77-10.17% of phenotypic variation), 2D (7.15-9.29%) and 2A (5.24-6.92%). The 6A QTL in the UC1110/PI610750 population falls into the same chromosomal region as those detected from GWAS, demonstrating its importance in Chinese materials for FCR resistance.

CONCLUSION

This study could provide useful information for utilization of FCR-resistant wheat germplasm and further understanding of molecular and genetics basis of FCR resistance in common wheat.

Genome-wide association studies of seven agronomic traits under two sowing conditions in bread wheat

BACKGROUND

Wheat is a cool seasoned crop requiring low temperature during grain filling duration and therefore increased temperature causes significant yield reduction. A set of 125 spring wheat genotypes from International Maize and Wheat Improvement Centre (CIMMYT-Mexico) was evaluated for phenological and yield related traits at three locations in Pakistan under normal sowing time and late sowing time for expose to prolonged high temperature. With the help of genome-wide association study using genotyping-by-sequencing, marker trait associations (MTAs) were observed separately for the traits under normal and late sown conditions.

RESULTS

Significant reduction ranging from 9 to 74% was observed in all traits under high temperature. Especially 30, 25, 41 and 66% reduction was observed for days to heading (DH), plant height (PH), spikes per plant (SPP) and yield respectively. We identified 55,954 single nucleotide polymorphisms (SNPs) using genotyping by sequencing of these 125 hexaploid spring wheat genotypes and conducted genome-wide association studies (GWAS) for days to heading (DH), grain filled duration (GFD), plant height (PH), spikes per plant (SPP), grain number per spike (GNS), thousand kernel weight (TKW) and grain yield per plot (GY). Genomic regions identified through GWAS explained up to 13% of the phenotypic variance, on average. A total of 139 marker-trait associations (MTAs) across three wheat genomes (56 on genome A, 55 on B and 28 on D) were identified for all the seven traits studied. For days to heading, 20; grain filled duration, 21; plant height, 23; spikes per plant, 13; grain numbers per spike, 8; thousand kernel weight, 21 and for grain yield, 33 MTAs were detected under normal and late sown conditions.

CONCLUSIONS

This study identifies the essential resource of genetics research and underpins the chromosomal regions of seven agronomic traits under normal and high temperature. Significant relationship was observed between the number of favored alleles and trait observations. Fourteen protein coding genes with their respective annotations have been searched with the sequence of seven MTAs which were identified in this study. These findings will be helpful in the development of a breeder friendly platform for the selection of high yielding wheat lines at high temperature areas.

A wheat protein kinase gene TaSnRK2.9-5A associated with yield contributing traits

We developed breeder-friendly high-throughput and cost-effective KASP marker for marker-assisted selection for grain yield related traits in wheat. Plant-specific protein kinase, SnRK2s, is a major family of signaling genes associated with metabolic regulations, nutrient utilization and response to external stimuli. In the present study, three copies of TaSnRK2.9 were isolated from chromosomes 5A, 5B and 5D of wheat (Triticum aestivum L.). The coding regions of TaSnRK2.9-5A, TaSnRK2.9-5B and promoter region of TaSnRK2.9-5D were investigated for sequence polymorphism. Single nucleotide polymorphisms (SNPs) were identified for TaSnRK2.9-5A, while no polymorphism was identified in TaSnRK2.9-5B and TaSnRK2.9-5D. The nucleotide sequence of TaSnRK2.9-5A consisted of 2180 bp having eight introns and nine exons. Three SNPs were identified at 308 nt, 698 nt and 1700 nt. For high-throughput genotyping, two kompetitive allele-specific PCR (KASP) markers were developed. Four haplotypes Hap-5A-1, Hap-5A-2, Hap-5A-3 and Hap-5A-4 were detected in wheat populations collected from China, Europe and Pakistan. Association analysis was performed with mixed linear model in TASSEL (v 5.0). The results indicated that Hap-5A-1/2 of TaSnRK2.9-5A were significantly associated with high thousand kernel weight, while Hap-5A-4 with high grains per spike. Overexpressing transgenic rice also showed higher grains per spike which is in accordance with association analysis results. Geographic distribution and allelic frequency indicted that the favored haplotypes were positively selected in Chinese (Hap-5A-1/2), Pakistani (Hap-5A-1), east European (Hap-5A-1) and west European (Hap-5A-4) wheat breeding. The results suggest that the developed KASP markers can be utilized in yield improvement by marker-assisted selection in wheat breeding.

Development of model web-server for crop variety identification using throughput SNP genotyping data

Crop varieties or genotypes of a given species are pivotal for agricultural production and ownership, management and improvement of their germplasm is a great challenge. Its morphological identification requires time, cost and descriptors are often compromised statistically due to phenotypic plasticity. Development of DNA based signature of varieties can overcome these limitations. There is a global need to implement world trade organization (WTO) and intellectual property rights (IPR) guidelines of Plant Breeders Rights (PBR) where DUS (distinctness, uniformity and stability) testing can be supplemented by DNA profile. Universalization and minimization of SNP number without compromising identification accuracy is the major challenge in development of varietal profile by rapid genotype assay. Besides this, there is no server-based approach reducing computational skill with global accessibility of referral phenotypic and genotypic data. We report world’s first model web server for crop variety identification using >350 Indian wheat varieties and Axiom 35 K SNP chip data. Standard filtering and linkage disequilibrium approach were used to develop varietal signature in Linux using HTML, Java, PHP and MySQL with provision of QR code generator to facilitate bar-coding. Phylogenetic tree constructed by selected SNPs confirms six major trait based clusters of varieties and their pedigree. Our user friendly server based tool, VISTa (Variety Identification System of Triticum aestivum) (http://webtom.cabgrid.res.in/vista) can be used in DUS testing having dispute resolution of sovereignty and access benefit sharing (ABS) issues. This model approach can be used in other crops with pan-global level management of crop germplasm in endeavour of crop productivity.

Toward the sequence-based breeding in legumes in the post-genome sequencing era

Efficiency of breeding programs of legume crops such as chickpea, pigeonpea and groundnut has been considerably improved over the past decade through deployment of modern genomic tools and technologies. For instance, next-generation sequencing technologies have facilitated availability of genome sequence assemblies, re-sequencing of several hundred lines, development of HapMaps, high-density genetic maps, a range of marker genotyping platforms and identification of markers associated with a number of agronomic traits in these legume crops. Although marker-assisted backcrossing and marker-assisted selection approaches have been used to develop superior lines in several cases, it is the need of the hour for continuous population improvement after every breeding cycle to accelerate genetic gain in the breeding programs. In this context, we propose a sequence-based breeding approach which includes use of independent or combination of parental selection, enhancing genetic diversity of breeding programs, forward breeding for early generation selection, and genomic selection using sequencing/genotyping technologies. Also, adoption of speed breeding technology by generating 4-6 generations per year will be contributing to accelerate genetic gain. While we see a huge potential of the sequence-based breeding to revolutionize crop improvement programs in these legumes, we anticipate several challenges especially associated with high-quality and precise phenotyping at affordable costs, data analysis and management related to improving breeding operation efficiency. Finally, integration of improved seed systems and better agronomic packages with the development of improved varieties by using sequence-based breeding will ensure higher genetic gains in farmers' fields.

Rapid gene cloning in cereals

The large and complex genomes of many cereals hindered cloning efforts in the past. Advances in genomics now allow the rapid cloning of genes from humanity's most valuable crops. The past two decades were characterized by a genomics revolution that entailed profound changes to crop research, plant breeding, and agriculture. Today, high-quality reference sequences are available for all major cereal crop species. Large resequencing and pan-genome projects start to reveal a more comprehensive picture of the genetic makeup and the diversity among domesticated cereals and their wild relatives. These technological advancements will have a dramatic effect on dissecting genotype-phenotype associations and on gene cloning. In this review, we will highlight the status of the genomic resources available for various cereal crops and we will discuss their implications for gene cloning. A particular focus will be given to the cereal species barley and wheat, which are characterized by very large and complex genomes that have been inaccessible to rapid gene cloning until recently. With the advancements in genomics and the development of several rapid gene-cloning methods, it has now become feasible to tackle the cloning of most agriculturally important genes, even in wheat and barley.

Back to the future: revisiting MAS as a tool for modern plant breeding

KEY MESSAGE

New models for integration of major gene MAS with modern breeding approaches stand to greatly enhance the reliability and efficiency of breeding, facilitating the leveraging of traditional genetic diversity. Genetic diversity is well recognised as contributing essential variation to crop breeding processes, and marker-assisted selection is cited as the primary tool to bring this diversity into breeding programs without the associated genetic drag from otherwise poor-quality genomes of donor varieties. However, implementation of marker-assisted selection techniques remains a challenge in many breeding programs worldwide. Many factors contribute to this lack of adoption, such as uncertainty in how to integrate MAS with traditional breeding processes, lack of confidence in MAS as a tool, and the expense of the process. However, developments in genomics tools, locus validation techniques, and new models for how to utilise QTLs in breeding programs stand to address these issues. Marker-assisted forward breeding needs to be enabled through the identification of robust QTLs, the design of reliable marker systems to select for these QTLs, and the delivery of these QTLs into elite genomic backgrounds to enable their use without associated genetic drag. To enhance the adoption and effectiveness of MAS, rice is used as an example of how to integrate new developments and processes into a coherent, efficient strategy for utilising genetic variation. When processes are instituted to address these issues, new genes can be rolled out into a breeding program rapidly and completely with a minimum of expense.

From markers to genome-based breeding in wheat

Recent technological advances in wheat genomics provide new opportunities to uncover genetic variation in traits of breeding interest and enable genome-based breeding to deliver wheat cultivars for the projected food requirements for 2050. There has been tremendous progress in development of whole-genome sequencing resources in wheat and its progenitor species during the last 5 years. High-throughput genotyping is now possible in wheat not only for routine gene introgression but also for high-density genome-wide genotyping. This is a major transition phase to enable genome-based breeding to achieve progressive genetic gains to parallel to projected wheat production demands. These advances have intrigued wheat researchers to practice less pursued analytical approaches which were not practiced due to the short history of genome sequence availability. Such approaches have been successful in gene discovery and breeding applications in other crops and animals for which genome sequences have been available for much longer. These strategies include, (i) environmental genome-wide association studies in wheat genetic resources stored in genbanks to identify genes for local adaptation by using agroclimatic traits as phenotypes, (ii) haplotype-based analyses to improve the statistical power and resolution of genomic selection and gene mapping experiments, (iii) new breeding strategies for genome-based prediction of heterosis patterns in wheat, and (iv) ultimate use of genomics information to develop more efficient and robust genome-wide genotyping platforms to precisely predict higher yield potential and stability with greater precision. Genome-based breeding has potential to achieve the ultimate objective of ensuring sustainable wheat production through developing high yielding, climate-resilient wheat cultivars with high nutritional quality.

Genomic Selection in Aquaculture: Application, Limitations and Opportunities With Special Reference to Marine Shrimp and Pearl Oysters

Within aquaculture industries, selection based on genomic information (genomic selection) has the profound potential to change genetic improvement programs and production systems. Genomic selection exploits the use of realized genomic relationships among individuals and information from genome-wide markers in close linkage disequilibrium with genes of biological and economic importance. We discuss the technical advances, practical requirements, and commercial applications that have made genomic selection feasible in a range of aquaculture industries, with a particular focus on molluscs (pearl oysters, Pinctada maxima) and marine shrimp (Litopenaeus vannamei and Penaeus monodon). The use of low-cost genome sequencing has enabled cost-effective genotyping on a large scale and is of particular value for species without a reference genome or access to commercial genotyping arrays. We highlight the pitfalls and offer the solutions to the genotyping by sequencing approach and the building of appropriate genetic resources to undertake genomic selection from first-hand experience. We describe the potential to capture large-scale commercial phenotypes based on image analysis and artificial intelligence through machine learning, as inputs for calculation of genomic breeding values. The application of genomic selection over traditional aquatic breeding programs offers significant advantages through being able to accurately predict complex polygenic traits including disease resistance; increasing rates of genetic gain; minimizing inbreeding; and negating potential limiting effects of genotype by environment interactions. Further practical advantages of genomic selection through the use of large-scale communal mating and rearing systems are highlighted, as well as presenting rate-limiting steps that impact on attaining maximum benefits from adopting genomic selection. Genomic selection is now at the tipping point where commercial applications can be readily adopted and offer significant short- and long-term solutions to sustainable and profitable aquaculture industries.

Global status of 47 major wheat loci controlling yield, quality, adaptation and stress resistance selected over the last century

BACKGROUND

Wheat breeding over the last 100 years has increased productivity by adapting genotypes to local conditions, but the genomic changes and selection signals that caused phenotypic change during breeding are essentially unknown. Studying and understanding human selection of multiple important genes controlling key phenotypic traits will promote wheat molecular breeding.

RESULTS

A total of 1152 diverse global wheat materials were genotyped based on KASP markers from 47 genes controlling grain yield, grain quality, adaptation, and stress resistance. Significant phenotypic variations between landraces and modern cultivars were found in 11 adaptive and yield-related traits. Thirty-six improvement-selective favorable alleles, including 22 positive prolonged and 14 negative selection alleles, were identified through comparing frequency spectra. Sus1-7A-Hap-H, Sus1-7B-Hap-T, Sus2-2A-Hap-A, TGW6-A1a, Cwi-4A-Hap-C, vrn-A1, PHS1-PHS+ and Lr34+ were subjected to strong selection, and overwhelmingly strong selection had occurred before improvement selection at Psy-A1b, Psy-B1a or b, Psy-D1a and Cwi-5D-Hap-C. However, Rht-B1b, Rht-D1b and 1BL.1RS were rare or absent in Chinese landraces but present in modern Chinese cultivars and introduced accessions. Importantly, Lr68+, Fhb1+, Wx-B1b and Yr15+, currently existing at a low frequency, should be regarded as further major improvement targets in global wheat breeding. Gene flow analysis showed that introduced cultivars especially from the former USSR and Italy contributed to enriched genetic variation in modern Chinese cultivars.

CONCLUSIONS

This work objectively reports human selection on favorable alleles of multiple crucial genes in Asia, Europe, North America and CIMMYT, and traces the distribution of important genes in global wheat for molecular breeding.

Evaluation and Recommendations for Routine Genotyping Using Skim Whole Genome Re-sequencing in Canola

Whole genome sequencing offers genome wide, unbiased markers, and inexpensive library preparation. With the cost of sequencing decreasing rapidly, many plant genomes of modest size are amenable to skim whole genome resequencing (skim WGR). The use of skim WGR in diverse sample sets without the use of imputation was evaluated in silico in 149 canola samples representative of global diversity. Fastq files with an average of 10x coverage of the reference genome were used to generate skim samples representing 0.25x, 0.5x, 1x, 2x, 3x, 4x, and 5x sequencing coverage. Applying a pre-defined list of SNPs versus de novo SNP discovery was evaluated. As skim WGR is expected to result in some degree of insufficient allele sampling, all skim coverage levels were filtered at a range of minimum read depths from a relaxed minimum read depth of 2 to a stringent read depth of 5, resulting in 28 list-based SNP sets. As a broad recommendation, genotyping pre-defined SNPs between 1x and 2x coverage with relatively stringent depth filtering is appropriate for a diverse sample set of canola due to a balance between marker number, sufficient accuracy, and sequencing cost, but depends on the intended application. This was experimentally examined in two sample sets with different genetic backgrounds: 1x coverage of 1,590 individuals from 84 Australian spring type four-parent crosses aimed at maximizing diversity as well as one commercial F1 hybrid, and 2x coverage of 379 doubled haploids (DHs) derived from a subset of the four-parent crosses. To determine optimal coverage in a simpler genetic background, the DH sample sequence coverage was further down sampled in silico. The flexible and cost-effective nature of the protocol makes it highly applicable across a range of species and purposes.

Development of High-Throughput SNP Genotyping Assays for Rapid Detection of Strawberry Colletotrichum Species and the G143A Mutation

Colletotrichum spp. cause major diseases of strawberry and disease management depends on the species present. However, species identification based on symptoms and spore morphology is difficult. Therefore, development of molecular techniques for trustworthy and high-throughput identification of Colletotrichum spp. is vital for the accurate diagnosis. A high-resolution melting (HRM) assay was developed for simultaneous identification and differentiation of Colletotrichum spp. from fungal colonies or from symptomatic strawberry tissue. HRM markers were designed based on the internal transcribed spacer region of Colletotrichum acutatum and C. gloeosporioides from strawberry, and accurately identified and differentiated the two species. In addition, for the rapid detection of a single-nucleotide polymorphism (SNP) in the cytochrome b (cytb) gene of C. acutatum and C. gloeosporioides associated with resistance to quinone-outside inhibitor fungicides, an endpoint SNP genotyping analysis was developed. The HRM and endpoint SNP genotyping assays are useful methods that can be implemented in plant diagnostic clinics for the rapid and accurate identification of Colletotrichum spp. and detection of the G143A mutation in the cytb gene of C. acutatum and C. gloeosporioides.

Multiple Facets of Marine Invertebrate Conservation Genomics

Conservation genomics aims to preserve the viability of populations and the biodiversity of living organisms. Invertebrate organisms represent 95% of animal biodiversity; however, few genomic resources currently exist for the group. The subset of marine invertebrates includes the most ancient metazoan lineages and possesses codes for unique gene products and possible keys to adaptation. The benefits of supporting invertebrate conservation genomics research (e.g., likely discovery of novel genes, protein regulatory mechanisms, genomic innovations, and transposable elements) outweigh the various hurdles (rare, small, or polymorphic starting materials). Here we review best conservation genomics practices in the laboratory and in silico when applied to marine invertebrates and also showcase unique features in several case studies of acroporid corals, crown-of-thorns starfish, apple snails, and abalone. Marine conservation genomics should also address how diversity can lead to unique marine innovations, the impact of deleterious variation, and how genomic monitoring and profiling could positively affect broader conservation goals (e.g., value of baseline data for in situ/ex situ genomic stocks).

Development and Application of High-Density Axiom Cajanus SNP Array with 56K SNPs to Understand the Genome Architecture of Released Cultivars and Founder Genotypes

As one of the major outputs of next-generation sequencing (NGS), a large number of genome-wide single-nucleotide polymorphisms (SNPs) have been developed in pigeonpea [ (L.) Huth.]. However, SNPs require a genotyping platform or assay to be used in different evolutionary studies or in crop improvement programs. Therefore, we developed an Axiom SNP array with 56K SNPs uniformly distributed across the genome and assessed its utility in a genetic diversity study. From the whole-genome resequencing (WGRS) data on 104 pigeonpea lines, ∼2 million sequence variations (SNPs and insertion-deletions [InDels]) were identified, from which a subset of 56,512 unique and informative sequence variations were selected to develop the array. The Axiom SNP array developed was used for genotyping 103 pigeonpea lines encompassing 63 cultivars released between 1960 and 2014 and 40 breeding, germplasm, and founder lines. Genotyping data thus generated on 103 pigeonpea lines provided 51,201 polymorphic SNPs and InDels. Genetic diversity analysis provided in-depth insights into the genetic architecture and trends in temporal diversity in pigeonpea cultivars. Therefore, the continuous use of the high-density Axiom SNP array developed will accelerate high-resolution trait mapping, marker-assisted breeding, and genomic selection efforts in pigeonpea.

Genome-Wide Association Studies for Spot Blotch (Cochliobolus sativus) Resistance in Bread Wheat Using Genotyping-by-Sequencing

Spot blotch is a severe biotic menace of wheat caused by Cochliobolus sativus (syn. Bipolaris sorokiniana). Spot blotch is liable to major yield losses in warm humid regions. A genome-wide association study using genotyping-by-sequencing (GBS) markers was conducted to identify genomic regions associated with spot blotch resistance in a diversity panel of 159 spring wheat genotypes. In total, 87,096 GBS markers covering the whole genome, with an average polymorphism information content value of 0.276, were applied. Linkage disequilibrium (LD) analysis indicated that the LD decay extent was approximately 100 Mbp. The panel was evaluated for disease severity (DS) and area under disease progress curve (AUDPC) for 2 years. In total, 24 marker-trait associations (MTA) were identified for DS and AUDPC of spot blotch, with 11 on chromosome 5B, 3 on 3A, 2 on 6B, and 1 each on 1A, 2A, 1D, 2D, 4B, 5A, 7A, and 7B. A marker on chromosome 7B significantly explained 14% of the phenotypic variation of spot blotch severity as well as 11% of AUDPC. Five markers-three on chromosome 5B, one on 3A, and one on 7B-were associated with both DS and AUDPC with R² ranging from 8 to 12%. Significant MTA can be utilized to develop wheat germplasm with resistance to spot blotch.

Can genomics deliver climate-change ready crops?

Development of climate resilient crops with accelerating genetic gains in crops will require integration of different disciplines/technologies, to see the impact in the farmer's field. In this review, we summarize how we are utilizing our germplasm collections to identify superior alleles/haplotypes through NGS based sequencing approaches and how genomics-enabled technologies together with precise phenotyping are being used in crop breeding. Pre-breeding and genomics-assisted breeding approaches are contributing to the more efficient development of climate-resilient crops. It is anticipated that the integration of several disciplines/technologies will result in the delivery of climate change ready crops in less time.

Advances in Wheat and Pathogen Genomics: Implications for Disease Control

The gene pool of wheat and its wild and domesticated relatives contains a plethora of resistance genes that can be exploited to make wheat more resilient to pathogens. Only a few of these genes have been isolated and studied at the molecular level. In recent years, we have seen a shift from classical breeding to genomics-assisted breeding, which makes use of the enormous advancements in DNA sequencing and high-throughput molecular marker technologies for wheat improvement. These genomic advancements have the potential to transform wheat breeding in the near future and to significantly increase the speed and precision at which new cultivars can be bred. This review highlights the genomic improvements that have been made in wheat and its pathogens over the past years and discusses their implications for disease-resistance breeding.

Comparative genome-wide mapping versus extreme pool-genotyping and development of diagnostic SNP markers linked to QTL for adult plant resistance to stripe rust in common wheat

A major stripe rust resistance QTL on chromosome 4BL was localized to a 4.5-Mb interval using comparative QTL mapping methods and validated in 276 wheat genotypes by haplotype analysis. CYMMIT-derived wheat line P10103 was previously identified to have adult plant resistance (APR) to stripe rust in the greenhouse and field. The conventional approach for QTL mapping in common wheat is laborious. Here, we performed QTL detection of APR using a combination of genome-wide scanning and extreme pool-genotyping. SNP-based genetic maps were constructed using the Wheat55 K SNP array to genotype a recombinant inbred line (RIL) population derived from the cross Mingxian 169 × P10103. Five stable QTL were detected across multiple environments. A fter comparing SNP profiles from contrasting, extreme DNA pools of RILs six putative QTL were located to approximate chromosome positions. A major QTL on chromosome 4B was identified in F_2:4 contrasting pools from cross Zhengmai 9023 × P10103. A consensus QTL (LOD = 26-40, PVE = 42-55%), named QYr.nwafu-4BL, was defined and localized to a 4.5-Mb interval flanked by SNP markers AX-110963704 and AX-110519862 in chromosome arm 4BL. Based on stripe rust response, marker genotypes, pedigree analysis and mapping data, QYr.nwafu-4BL is likely to be a new APR QTL. The applicability of the SNP-based markers flanking QYr.nwafu-4BL was validated on a diversity panel of 276 wheat lines. The additional minor QTL on chromosomes 4A, 5A, 5B and 6A enhanced the level of resistance conferred by QYr.nwafu-4BL. Marker-assisted pyramiding of QYr.nwafu-4BL and other favorable minor QTL in new wheat cultivars should improve the level of APR to stripe rust.

SNP-based pool genotyping and haplotype analysis accelerate fine-mapping of the wheat genomic region containing stripe rust resistance gene Yr26

NGS-assisted super pooling emerging as powerful tool to accelerate gene mapping and haplotype association analysis within target region uncovering specific linkage SNPs or alleles for marker-assisted gene pyramiding. Conventional gene mapping methods to identify genes associated with important agronomic traits require significant amounts of financial support and time. Here, a single nucleotide polymorphism (SNP)-based mapping approach, RNA-Seq and SNP array assisted super pooling analysis, was used for rapid mining of a candidate genomic region for stripe rust resistance gene Yr26 that has been widely used in wheat breeding programs in China. Large DNA and RNA super-pools were genotyped by Wheat SNP Array and sequenced by Illumina HiSeq, respectively. Hundreds of thousands of SNPs were identified and then filtered by multiple filtering criteria. Among selected SNPs, over 900 were found within an overlapping interval of less than 30 Mb as the Yr26 candidate genomic region in the centromeric region of chromosome arm 1BL. The 235 chromosome-specific SNPs were converted into KASP assays to validate the Yr26 interval in different genetic populations. Using a high-resolution mapping population (> 30,000 gametes), we confined Yr26 to a 0.003-cM interval. The Yr26 target region was anchored to the common wheat IWGSC RefSeq v1.0 and wild emmer WEWSeq v.1.0 sequences, from which 488 and 454 kb fragments were obtained. Several candidate genes were identified in the target genomic region, but there was no typical resistance gene in either genome region. Haplotype analysis identified specific SNPs linked to Yr26 and developed robust and breeder-friendly KASP markers. This integration strategy can be applied to accelerate generating many markers closely linked to target genes/QTL for a trait of interest in wheat and other polyploid species.

A comparison between genotyping-by-sequencing and array-based scoring of SNPs for genomic prediction accuracy in winter wheat

The utilization of DNA molecular markers in plant breeding to maximize selection response via marker-assisted selection (MAS) and genomic selection (GS) has revolutionized plant breeding. A key factor affecting GS applicability is the choice of molecular marker platform. Genotyping-by-sequencing scored SNPs (GBS-scored SNPs) provides a large number of markers, albeit with high rates of missing data. Array scored SNPs are of high quality, but the cost per sample is substantially higher. The objectives of this study were 1) compare GBS-scored SNPs, and array scored SNPs for genomic selection applications, and 2) compare estimates of genomic kinship and population structure calculated using the two marker platforms. SNPs were compared in a diversity panel consisting of 299 hard winter wheat (Triticum aestivum L.) accessions that were part of a multi-year, multi-environments association mapping study. The panel was phenotyped in Ithaca, Nebraska for heading date, plant height, days to physiological maturity and grain yield in 2012 and 2013. The panel was genotyped using GBS-scored SNPs, and array scored SNPs. Results indicate that GBS-scored SNPs is comparable to or better than Array-scored SNPs for genomic prediction application. Both platforms identified the same genetic patterns in the panel where 90% of the lines were classified to common genetic groups. Overall, we concluded that GBS-scored SNPs have the potential to be the marker platform of choice for genetic diversity and genomic selection in winter wheat.

Development and evaluation of high-density Axiom® CicerSNP Array for high-resolution genetic mapping and breeding applications in chickpea

To accelerate genomics research and molecular breeding applications in chickpea, a high-throughput SNP genotyping platform 'Axiom^® CicerSNP Array' has been designed, developed and validated. Screening of whole-genome resequencing data from 429 chickpea lines identified 4.9 million SNPs, from which a subset of 70 463 high-quality nonredundant SNPs was selected using different stringent filter criteria. This was further narrowed down to 61 174 SNPs based on p-convert score ≥0.3, of which 50 590 SNPs could be tiled on array. Among these tiled SNPs, a total of 11 245 SNPs (22.23%) were from the coding regions of 3673 different genes. The developed Axiom^® CicerSNP Array was used for genotyping two recombinant inbred line populations, namely ICCRIL03 (ICC 4958 × ICC 1882) and ICCRIL04 (ICC 283 × ICC 8261). Genotyping data reflected high success and polymorphic rate, with 15 140 (29.93%; ICCRIL03) and 20 018 (39.57%; ICCRIL04) polymorphic SNPs. High-density genetic maps comprising 13 679 SNPs spanning 1033.67 cM and 7769 SNPs spanning 1076.35 cM were developed for ICCRIL03 and ICCRIL04 populations, respectively. QTL analysis using multilocation, multiseason phenotyping data on these RILs identified 70 (ICCRIL03) and 120 (ICCRIL04) main-effect QTLs on genetic map. Higher precision and potential of this array is expected to advance chickpea genetics and breeding applications.

Utilization of a Wheat55K SNP Array for Mapping of Major QTL for Temporal Expression of the Tiller Number

Maximum tiller number and productive tiller number are important traits for wheat grain yield, but research involving the temporal expression of tiller number at different quantitative trait loci (QTL) levels is limited. In the present study, a population set of 371 recombined inbred lines derived from a cross between Chuan-Nong18 and T1208 was used to construct a high-density genetic map using a Wheat55K SNP Array and to perform dynamic QTL analysis of the tiller number at four growth stages. A high-density genetic map containing 11,583 SNP markers and 59 SSR markers that spanned 4,513.95 cM and was distributed across 21 wheat chromosomes was constructed. A total of 28 single environmental QTL were identified in the recombined inbred lines population, and among these, seven QTL were stable and used for multi-environmental and dynamic analysis. These QTL were mapped to chromosomes 2D, 4A, 4D, 5A, 5D, and 7D, respectively. Each QTL explained 1.63-21.22% of the observed phenotypic variation, with an additive effect from -20.51 to 11.59. Dynamic analysis showed that cqTN-2D.2 can be detected at four growth stages of tillering, explaining 4.92-17.16% of the observed phenotypic variations and spanning 13.71 Mb (AX-109283238-AX-110544009: 82189047-95895626) according to the physical location of the flanking markers. The effects of the stable QTL were validated in the recombined inbred lines population, and the beneficial alleles could be utilized in future marker-assisted selection. Several candidate genes for MTN and PTN were predicted. The results provide a better understanding of the QTL selectively expressing the control of tiller number and will facilitate future map-based cloning. 9.17% SNP markers showed best hits to the Chinese Spring contigs. It was indicated that Wheat55K Array was efficient and valid to construct a high-density wheat genetic map.

Wheat genetic resources in the post-genomics era: promise and challenges

Background

Wheat genetic resources have been used for genetic improvement since 1876, when Stephen Wilson (Transactions and Proceedings of the Botanical Society of Edinburgh 12: 286) consciously made the first wide hybrid involving wheat and rye in Scotland. Wide crossing continued with sporadic attempts in the first half of 19th century and became a sophisticated scientific discipline during the last few decades with considerable impact in farmers' fields. However, a large diversity of untapped genetic resources could contribute in meeting future wheat production challenges.

Perspectives and Conclusion

Recently the complete reference genome of hexaploid (Chinese Spring) and tetraploid (Triticum turgidum ssp. dicoccoides) wheat became publicly available coupled with on-going international efforts on wheat pan-genome sequencing. We anticipate that an objective appraisal is required in the post-genomics era to prioritize genetic resources for use in the improvement of wheat production if the goal of doubling yield by 2050 is to be met. Advances in genomics have resulted in the development of high-throughput genotyping arrays, improved and efficient methods of gene discovery, genomics-assisted selection and gene editing using endonucleases. Likewise, ongoing advances in rapid generation turnover, improved phenotyping, envirotyping and analytical methods will significantly accelerate exploitation of exotic genes and increase the rate of genetic gain in breeding. We argue that the integration of these advances will significantly improve the precision and targeted identification of potentially useful variation in the wild relatives of wheat, providing new opportunities to contribute to yield and quality improvement, tolerance to abiotic stresses, resistance to emerging biotic stresses and resilience to weather extremes.

Efficient genome-wide genotyping strategies and data integration in crop plants

Next-generation sequencing (NGS) has revolutionized plant and animal research by providing powerful genotyping methods. This review describes and discusses the advantages, challenges and, most importantly, solutions to facilitate data processing, the handling of missing data, and cross-platform data integration. Next-generation sequencing technologies provide powerful and flexible genotyping methods to plant breeders and researchers. These methods offer a wide range of applications from genome-wide analysis to routine screening with a high level of accuracy and reproducibility. Furthermore, they provide a straightforward workflow to identify, validate, and screen genetic variants in a short time with a low cost. NGS-based genotyping methods include whole-genome re-sequencing, SNP arrays, and reduced representation sequencing, which are widely applied in crops. The main challenges facing breeders and geneticists today is how to choose an appropriate genotyping method and how to integrate genotyping data sets obtained from various sources. Here, we review and discuss the advantages and challenges of several NGS methods for genome-wide genetic marker development and genotyping in crop plants. We also discuss how imputation methods can be used to both fill in missing data in genotypic data sets and to integrate data sets obtained using different genotyping tools. It is our hope that this synthetic view of genotyping methods will help geneticists and breeders to integrate these NGS-based methods in crop plant breeding and research.

Fast-Forwarding Genetic Gain

'Speed breeding' enables scientists to exploit gene bank accessions and mutant collections for an unparalleled rapid gene discovery and gene deployment. Combining speed breeding and other leading-edge plant breeding technologies with strategic global partnerships, has the potential to achieve the genetic gain targets required to deliver our future crops.

Trends in plant research using molecular markers

A deep bibliometric analysis has been carried out, obtaining valuable parameters that facilitate the understanding around the research in plant using molecular markers. The evolution of the improvement in the field of agronomy is fundamental for its adaptation to the new exigencies that the current world context raises. In addition, within these improvements, this article focuses on those related to the biotechnology sector. More specifically, the use of DNA markers that allow the researcher to know the set of genes associated with a particular quantitative trait or QTL. The use of molecular markers is widely extended, including: restriction fragment length polymorphism, random-amplified polymorphic DNA, amplified fragment length polymorphism, microsatellites, and single-nucleotide polymorphisms. In addition to classical methodology, new approaches based on the next generation sequencing are proving to be fundamental. In this article, a historical review of the molecular markers traditionally used in plants, since its birth and how the new molecular tools facilitate the work of plant breeders is carried out. The evolution of the most studied cultures from the point of view of molecular markers is also reviewed and other parameters whose prior knowledge can facilitate the approach of researchers to this field of research are analyzed. The bibliometric analysis of molecular markers in plants shows that top five countries in this research are: US, China, India, France, and Germany, and from 2013, this research is led by China. On the other hand, the basic research using Arabidopsis is deeper in France and Germany, while other countries focused its efforts in their main crops as the US for wheat or maize, while China and India for wheat and rice.

Recent insights into cotton functional genomics: progress and future perspectives

Functional genomics has transformed from futuristic concept to well-established scientific discipline during the last decade. Cotton functional genomics promise to enhance the understanding of fundamental plant biology to systematically exploit genetic resources for the improvement of cotton fibre quality and yield, as well as utilization of genetic information for germplasm improvement. However, determining the cotton gene functions is a much more challenging task, which has not progressed at a rapid pace. This article presents a comprehensive overview of the recent tools and resources available with the major advances in cotton functional genomics to develop elite cotton genotypes. This effort ultimately helps to filter a subset of genes that can be used to assemble a final list of candidate genes that could be employed in future novel cotton breeding programme. We argue that next stage of cotton functional genomics requires the draft genomes refinement, re-sequencing broad diversity panels with the development of high-throughput functional genomics tools and integrating multidisciplinary approaches in upcoming cotton improvement programmes.

Development and Applications of a High Throughput Genotyping Tool for Polyploid Crops: Single Nucleotide Polymorphism (SNP) Array

Polypoid species play significant roles in agriculture and food production. Many crop species are polyploid, such as potato, wheat, strawberry, and sugarcane. Genotyping has been a daunting task for genetic studies of polyploid crops, which lags far behind the diploid crop species. Single nucleotide polymorphism (SNP) array is considered to be one of, high-throughput, relatively cost-efficient and automated genotyping approaches. However, there are significant challenges for SNP identification in complex, polyploid genomes, which has seriously slowed SNP discovery and array development in polyploid species. Ploidy is a significant factor impacting SNP qualities and validation rates of SNP markers in SNP arrays, which has been proven to be a very important tool for genetic studies and molecular breeding. In this review, we (1) discussed the pros and cons of SNP array in general for high throughput genotyping, (2) presented the challenges of and solutions to SNP calling in polyploid species, (3) summarized the SNP selection criteria and considerations of SNP array design for polyploid species, (4) illustrated SNP array applications in several different polyploid crop species, then (5) discussed challenges, available software, and their accuracy comparisons for genotype calling based on SNP array data in polyploids, and finally (6) provided a series of SNP array design and genotype calling recommendations. This review presents a complete overview of SNP array development and applications in polypoid crops, which will benefit the research in molecular breeding and genetics of crops with complex genomes.

Rapid identification of an adult plant stripe rust resistance gene in hexaploid wheat by high-throughput SNP array genotyping of pooled extremes

High-throughput SNP array analysis of pooled extreme phenotypes in a segregating population by KASP marker genotyping permitted rapid, cost-effective location of a stripe rust resistance QTL in wheat. German wheat cultivar "Friedrichswerther" has exhibited high levels of adult plant resistance (APR) to stripe rust in field environments for many years. F_2:3 lines and F₆ recombinant inbred line (RILs) populations derived from a cross between Friedrichswerther and susceptible landrace Mingxian 169 were evaluated in the field in 2013, 2016 and 2017. Illumina 90K iSelect SNP arrays were used to genotype bulked extreme pools and parents; 286 of 1135 polymorphic SNPs were identified on chromosome 6B. Kompetitive Allele-Specific PCR (KASP) markers were used to verify the chromosome region associated with the resistance locus. A linkage map was constructed with 18 KASP-SNP markers, and a major effect QTL was identified within a 1.4 cM interval flanked by KASP markers IWB71602 and IWB55937 in the region 6BL3-0-0.36. The QTL, named QYr.nwafu-6BL, was stable across environments, and explained average 54.4 and 47.8% of the total phenotypic variation in F_2:3 lines and F₆ RILs, respectively. On the basis of marker genotypes, pedigree analysis and relative genetic distance QYr.nwafu-6BL is likely to be a new APR QTL. Combined high-throughput SNP array genotyping of pooled extremes and validation by KASP assays lowers sequencing costs compared to genome-wide association studies with SNP arrays, and more importantly, permits rapid isolation of major effect QTL in hexaploid wheat as well as improving accuracy of mapping in the QTL region. QYr.nwafu-6BL with flanking KASP markers developed and verified in a subset of 236 diverse lines can be used in marker-assisted selection to improve stripe rust resistance in breeding programs.