Resolution of genetic map expansion caused by excess heterozygosity in plant recombinant inbred populations

Genetic diversity and grouping of pigeonpea [Cajanus cajan Millspaugh] Germplasm using SNP markers and agronomic traits

Knowledge of genetic interrelationships and grouping among pigeonpea germplasm collections is fundamental to selecting breeding parents with unique genetic constitutions. The objectives of this study were to assess the genetic diversity and genetic grouping present among 81 pigeonpea genotypes collected from Malawi, Tanzania and Kenya using 4122 single nucleotide polymorphism (SNP) markers and complementary morphological traits. The SNP markers and phenotypic traits revealed significant genetic variation among the assessed genotypes. The test genotypes were resolved into three distinct clusters based on both marker systems. The mean gene diversity and the polymorphic information content (PIC) were 0.14 and 0.11, suggesting moderate genetic differentiation among the genotypes. The analysis of molecular variance revealed that differences among populations accounted for only 2.7% of the variation, while within the population (among individuals) accounted for 97.3% of the variation. The results based on the DArT SNP genotyping complemented the phenotypic data and led to the selection of unique pigeonpea genotypes for effective breeding programs in Malawi and related agroecologies. This suggested that unique breeding populations could be created by identifying and selecting divergent individuals as parental lines. There is a need to create a new genetic variation or introgress genes from genetically unrelated parents to increase the genetic base of the current pigeonpea breeding populations.

GBS-Based SNP Map Pinpoints the QTL Associated With Sorghum Downy Mildew Resistance in Maize (Zea mays L.)

Sorghum downy mildew (SDM), caused by the biotrophic fungi Peronosclerospora sorghi, threatens maize production worldwide, including India. To identify quantitative trait loci (QTL) associated with resistance to SDM, we used a recombinant inbred line (RIL) population derived from a cross between resistant inbred line UMI936 (w) and susceptible inbred line UMI79. The RIL population was phenotyped for SDM resistance in three environments [E1-field (Coimbatore), E2-greenhouse (Coimbatore), and E3-field (Mandya)] and also utilized to construct the genetic linkage map by genotyping by sequencing (GBS) approach. The map comprises 1516 SNP markers in 10 linkage groups (LGs) with a total length of 6924.7 cM and an average marker distance of 4.57 cM. The QTL analysis with the phenotype and marker data detected nine QTL on chromosome 1, 2, 3, 5, 6, and 7 across three environments. Of these, QTL namely qDMR1.2, qDMR3.1, qDMR5.1, and qDMR6.1 were notable due to their high phenotypic variance. qDMR3.1 from chromosome 3 was detected in more than one environment (E1 and E2), explaining the 10.3% and 13.1% phenotypic variance. Three QTL, qDMR1.2, qDMR5.1, and qDMR6.1 from chromosomes 1, 5, and 6 were identified in either E1 or E3, explaining 15.2%–18% phenotypic variance. Moreover, genome mining on three QTL (qDMR3.1, qDMR5.1, and qDMR6.1) reveals the putative candidate genes related to SDM resistance. The information generated in this study will be helpful for map-based cloning and marker-assisted selection in maize breeding programs.

Selected genome regions for fruit weight and shelf life in tomato RILs discernible by markers based on genomic sequence information

Fruit weight (FW) and shelf life (SL) are important traits in commercial fresh market tomatoes. A tomato RIL population was developed by antagonistic and divergent selection for both traits from an interspecific cross between the Solanum lycopersicum L. cv. "Caimanta" and the S. pimpinellifolium L. accession "LA0722". The objective of this work was to evaluate phenotypic and genetic components for FW and SL. Phenotypic data from RILs were collected during 3-year trials. Sixteen SSR, 62 InDels developed based on the genome sequences of "Caimanta" and "LA0722", and four functional markers for fruit size genes were used. FW and SL had a significant genetic variability, and both traits showed a genotype by year interaction. Genome-wide molecular characterization of the population demonstrated that is genetically structured according to FW. Marker data was used to study changes on allelic frequencies at loci between the phenotypic extreme group of RILs for FW and SL. Twenty four markers were associated to FW, the LC gene in chromosome 2 and other six markers in chromosomes 1, 2, 6, and 11 presented the most significant associations. Finally, we reported three new genomic regions located on chromosomes 9, 10 and 12 that underlie SL in tomato.

Application of a high-resolution genetic map for chromosome-scale genome assembly and fine QTLs mapping of seed size and weight traits in castor bean

Castor bean (Ricinus communis L., Euphorbiaceae) is a critical biodiesel crop and its seed derivatives have important industrial applications. Due to lack of a high-density genetic map, the breeding and genetic improvement of castor bean has been largely restricted. In this study, based on a recombinant inbred line (RIL) population consisting of 200 individuals, we generated 8,896 high-quality genomic SNP markers and constructed a high-resolution genetic map with 10 linkage groups (LGs), spanning 1,852.33 centiMorgan (cM). Based on the genetic map, 996 scaffolds from the draft reference genome were anchored onto 10 pseudo-chromosomes, covering 84.43% of the castor bean genome. Furthermore, the quality of the pseudo-chromosome scale assembly genome was confirmed via genome collinearity analysis within the castor bean genome as well as between castor bean and cassava. Our results provide new evidence that the phylogenetic position of castor bean is relatively solitary from other taxa in the Euphorbiaceae family. Based on the genetic map, we identified 16 QTLs that control seed size and weight (covering 851 candidate genes). The findings will be helpful for further research into potential new mechanisms controlling seed size and weight in castor bean. The genetic map and improved pseudo-chromosome scale genome provide crucial foundations for marker-assisted selection (MAS) of QTL governing important agronomic traits, as well as the accelerated molecular breeding of castor bean in a cost-effective pattern.

Sorghum stem aerenchyma formation is regulated by SbNAC_D during internode development

Sorghum bicolor is a drought-resilient C4 grass used for production of grain, forage, sugar, and biomass. Sorghum genotypes capable of accumulating high levels of stem sucrose have solid stems that contain low levels of aerenchyma. The D-locus on SBI06 modulates the extent of aerenchyma formation in sorghum stems and leaf midribs. A QTL aligned with this locus was identified and fine-mapped in populations derived from BTx623*IS320c, BTx623*R07007, and BTx623*Standard broomcorn. Analysis of coding polymorphisms in the fine-mapped D-locus showed that genotypes that accumulate low levels of aerenchyma encode a truncated NAC transcription factor (Sobic.006G147400, SbNAC_d1), whereas parental lines that accumulate higher levels of stem aerenchyma encode full-length NAC TFs (SbNAC-D). During vegetative stem development, aerenchyma levels are low in nonelongated stem internodes, internode growing zones, and nodes. Aerenchyma levels increase in recently elongated internodes starting at the top of the internode near the center of the stem. SbNAC_D was expressed at low levels in nonelongated internodes and internode growing zones and at higher levels in regions of stem internodes that form aerenchyma. SbXCP1, a gene encoding a cysteine protease involved in programmed cell death, was induced in SbNAC_D genotypes in parallel with aerenchyma formation in sorghum stems but not in SbNAC_d1 genotypes. Several sweet sorghum genotypes encode the recessive SbNAC_d1 allele and have low levels of stem aerenchyma. Based on these results, we propose that SbNAC_D is the D-gene identified by Hilton (1916) and that allelic variation in SbNAC_D modulates the extent of aerenchyma formation in sorghum stems.

The Sorghum bicolor reference genome: improved assembly, gene annotations, a transcriptome atlas, and signatures of genome organization

Sorghum bicolor is a drought tolerant C4 grass used for the production of grain, forage, sugar, and lignocellulosic biomass and a genetic model for C4 grasses due to its relatively small genome (approximately 800 Mbp), diploid genetics, diverse germplasm, and colinearity with other C4 grass genomes. In this study, deep sequencing, genetic linkage analysis, and transcriptome data were used to produce and annotate a high-quality reference genome sequence. Reference genome sequence order was improved, 29.6 Mbp of additional sequence was incorporated, the number of genes annotated increased 24% to 34 211, average gene length and N50 increased, and error frequency was reduced 10-fold to 1 per 100 kbp. Subtelomeric repeats with characteristics of Tandem Repeats in Miniature (TRIM) elements were identified at the termini of most chromosomes. Nucleosome occupancy predictions identified nucleosomes positioned immediately downstream of transcription start sites and at different densities across chromosomes. Alignment of more than 50 resequenced genomes from diverse sorghum genotypes to the reference genome identified approximately 7.4 M single nucleotide polymorphisms (SNPs) and 1.9 M indels. Large-scale variant features in euchromatin were identified with periodicities of approximately 25 kbp. A transcriptome atlas of gene expression was constructed from 47 RNA-seq profiles of growing and developed tissues of the major plant organs (roots, leaves, stems, panicles, and seed) collected during the juvenile, vegetative and reproductive phases. Analysis of the transcriptome data indicated that tissue type and protein kinase expression had large influences on transcriptional profile clustering. The updated assembly, annotation, and transcriptome data represent a resource for C4 grass research and crop improvement.

Genotyping-by-Sequencing Derived High-Density Linkage Map and its Application to QTL Mapping of Flag Leaf Traits in Bread Wheat

Winter wheat parents ‘Harry’ (drought tolerant) and ‘Wesley’ (drought susceptible) were used to develop a recombinant inbred population with future goals of identifying genomic regions associated with drought tolerance. To precisely map genomic regions, high-density linkage maps are a prerequisite. In this study genotyping-by- sequencing (GBS) was used to construct the high-density linkage map. The map contained 3,641 markers distributed on 21 chromosomes and spanned 1,959 cM with an average distance of 1.8 cM between markers. The constructed linkage map revealed strong collinearity in marker order across 21 chromosomes with POPSEQ-v2.0, which was based on a high-density linkage map. The reliability of the linkage map for QTL mapping was demonstrated by co-localizing the genes to previously mapped genomic regions for two highly heritable traits, chaff color, and leaf cuticular wax. Applicability of linkage map for QTL mapping of three quantitative traits, flag leaf length, width, and area, identified 21 QTLs in four environments, and QTL expression varied across the environments. Two major stable QTLs, one each for flag leaf length (Qfll.hww-7A) and flag leaf width (Qflw.hww-5A) were identified. The map constructed will facilitate QTL and fine mapping of quantitative traits, map-based cloning, comparative mapping, and in marker-assisted wheat breeding endeavors.

Effect of Co-segregating Markers on High-Density Genetic Maps and Prediction of Map Expansion Using Machine Learning Algorithms

Advances in sequencing and genotyping methods have enable cost-effective production of high throughput single nucleotide polymorphism (SNP) markers, making them the choice for linkage mapping. As a result, many laboratories have developed high-throughput SNP assays and built high-density genetic maps. However, the number of markers may, by orders of magnitude, exceed the resolution of recombination for a given population size so that only a minority of markers can accurately be ordered. Another issue attached to the so-called 'large p, small n' problem is that high-density genetic maps inevitably result in many markers clustering at the same position (co-segregating markers). While there are a number of related papers, none have addressed the impact of co-segregating markers on genetic maps. In the present study, we investigated the effects of co-segregating markers on high-density genetic map length and marker order using empirical data from two populations of wheat, Mohawk × Cocorit (durum wheat) and Norstar × Cappelle Desprez (bread wheat). The maps of both populations consisted of 85% co-segregating markers. Our study clearly showed that excess of co-segregating markers can lead to map expansion, but has little effect on markers order. To estimate the inflation factor (IF), we generated a total of 24,473 linkage maps (8,203 maps for Mohawk × Cocorit and 16,270 maps for Norstar × Cappelle Desprez). Using seven machine learning algorithms, we were able to predict with an accuracy of 0.7 the map expansion due to the proportion of co-segregating markers. For example in Mohawk × Cocorit, with 10 and 80% co-segregating markers the length of the map inflated by 4.5 and 16.6%, respectively. Similarly, the map of Norstar × Cappelle Desprez expanded by 3.8 and 11.7% with 10 and 80% co-segregating markers. With the increasing number of markers on SNP-chips, the proportion of co-segregating markers in high-density maps will continue to increase making map expansion unavoidable. Therefore, we suggest developers improve linkage mapping algorithms for efficient analysis of high-throughput data. This study outlines a practical strategy to estimate the IF due to the proportion of co-segregating markers and outlines a method to scale the length of the map accordingly.

Sorghum Dw2 Encodes a Protein Kinase Regulator of Stem Internode Length

Sorghum is an important C4 grass crop grown for grain, forage, sugar, and bioenergy production. While tall, late flowering landraces are commonly grown in Africa, short early flowering varieties were selected in US grain sorghum breeding programs to reduce lodging and to facilitate machine harvesting. Four loci have been identified that affect stem length (Dw1-Dw4). Subsequent research showed that Dw3 encodes an ABCB1 auxin transporter and Dw1 encodes a highly conserved protein involved in the regulation of cell proliferation. In this study, Dw2 was identified by fine-mapping and further confirmed by sequencing the Dw2 alleles in Dwarf Yellow Milo and Double Dwarf Yellow Milo, the progenitor genotypes where the recessive allele of dw2 originated. The Dw2 locus was determined to correspond to Sobic.006G067700, a gene that encodes a protein kinase that is homologous to KIPK, a member of the AGCVIII subgroup of the AGC protein kinase family in Arabidopsis.

QTLs Associated with Crown Root Angle, Stomatal Conductance, and Maturity in Sorghum

Three factors that directly affect the water inputs in cropping systems are root architecture, length of the growing season, and stomatal conductance to water vapor (). Deeper-rooted cultivars will perform better under water-limited conditions because they can access water stored deeper in the soil profile. Reduced limits transpiration rate () and thus throughout the vegetative phase conserves water that may be used during grain filling in water-limited environments. Additionally, growing early-maturing varieties in regions that rely on soil-stored water is a key water management strategy. To further our understanding of the genetic basis underlying root depth, growing season length, and we conducted a quantitative trait locus (QTL) study. A QTL for crown root angle (a proxy for root depth) new to sorghum was identified in chromosome 3. For , a QTL in chromosome seven was identified. In a follow-up field study it was determined that the QTL for was associated with reduced but not with net carbon assimilation rate () or shoot biomass. No differences in guard-cell length or stomatal density were observed among the lines, leading to the conclusion that the observed differences in must be explained by partial stomatal closure. The well-studied maturity gene was identified in the QTL for maturity. The transgressive segregation of the population was explained by the possible interaction of with other loci. Finally, the most probable position of the genes underlying the QTLs and candidate genes were proposed.

Genetic Determinants of Crop Timing and Quality Traits in Two Interspecific Petunia Recombinant Inbred Line Populations

The rate at which plants develop new nodes (development rate) is a major determinant of crop production time, yet the genetic control of this process, including genetic interactions with crop quality parameters, is poorly understood. We employed a modified genotyping-by-sequencing approach and generated genetic linkage maps with 6,291 and 3,297 single nucleotide polymorphisms (SNPs) for the interspecific Petunia recombinant inbred line (RIL) population - P. axillaris × P. exserta (AE) and P. integrifolia × P. axillaris (IA), respectively. Comparative mapping between the populations revealed perfect collinearity of marker order but different recombination frequency at the corresponding linkage groups (LGs). Quantitative trait loci (QTL) mapping conducted for development traits and other important quality traits indicated QTL clustered on chromosome 1, 2, 4 and 6 for the AE population and chromosome 1, 2, 5 and 6 for the IA population. Additionally, 209 differentially expressed unique transcripts were identified in shoot apex tissue between fast- and slow-developing RILs, 13 of which mapped to within 1 cM of a development rate QTL. These results will facilitate the identification of novel genes controlling crop timing and quality traits in Petunia and highlight the power of using multiple interspecific populations to elucidate genetic determinants of natural variation.

Quantitative trait loci mapping of heat tolerance in broccoli (Brassica oleracea var. italica) using genotyping-by-sequencing

Five quantitative trait loci and one epistatic interaction were associated with heat tolerance in a doubled haploid population of broccoli evaluated in three summer field trials. Predicted rising global temperatures due to climate change have generated a demand for crops that are resistant to yield and quality losses from heat stress. Broccoli (Brassica oleracea var. italica) is a cool weather crop with high temperatures during production decreasing both head quality and yield. Breeding for heat tolerance in broccoli has potential to both expand viable production areas and extend the growing season but breeding efficiency is constrained by limited genetic information. A doubled haploid (DH) broccoli population segregating for heat tolerance was evaluated for head quality in three summer fields in Charleston, SC, USA. Multiple quantitative trait loci (QTL) mapping of 1,423 single nucleotide polymorphisms developed through genotyping-by-sequencing identified five QTL and one positive epistatic interaction that explained 62.1% of variation in heat tolerance. The QTL identified here can be used to develop markers for marker-assisted selection and to increase our understanding of the molecular mechanisms underlying plant response to heat stress.

Wheat Landrace Genome Diversity

Understanding the genomic complexity of bread wheat is important for unraveling domestication processes, environmental adaptation, and for future of...

Understanding the genomic complexity of bread wheat (Triticum aestivum L.) is a cornerstone in the quest to unravel the processes of domestication and the following adaptation of domesticated wheat to a wide variety of environments across the globe. Additionally, it is of importance for future improvement of the crop, particularly in the light of climate change. Focusing on the adaptation after domestication, a nested association mapping (NAM) panel of 60 segregating biparental populations was developed, mainly involving landrace accessions from the core set of the Watkins hexaploid wheat collection optimized for genetic diversity. A modern spring elite variety, “Paragon,” was used as common reference parent. Genetic maps were constructed following identical rules to make them comparable. In total, 1611 linkage groups were identified, based on recombination from an estimated 126,300 crossover events over the whole NAM panel. A consensus map, named landrace consensus map (LRC), was constructed and contained 2498 genetic loci. These newly developed genetics tools were used to investigate the rules underlying genome fluidity or rigidity, e.g., by comparing marker distances and marker orders. In general, marker order was highly correlated, which provides support for strong synteny between bread wheat accessions. However, many exceptional cases of incongruent linkage groups and increased marker distances were also found. Segregation distortion was detected for many markers, sometimes as hot spots present in different populations. Furthermore, evidence for translocations in at least 36 of the maps was found. These translocations fell, in general, into many different translocation classes, but a few translocation classes were found in several accessions, the most frequent one being the well-known T5B:7B translocation. Loci involved in recombination rate, which is an interesting trait for plant breeding, were identified by QTL analyses using the crossover counts as a trait. In total, 114 significant QTL were detected, nearly half of them with increasing effect from the nonreference parents.

3D Sorghum Reconstructions from Depth Images Identify QTL Regulating Shoot Architecture

Dissecting the genetic basis of complex traits is aided by frequent and nondestructive measurements. Advances in range imaging technologies enable the rapid acquisition of three-dimensional (3D) data from an imaged scene. A depth camera was used to acquire images of sorghum (Sorghum bicolor), an important grain, forage, and bioenergy crop, at multiple developmental time points from a greenhouse-grown recombinant inbred line population. A semiautomated software pipeline was developed and used to generate segmented, 3D plant reconstructions from the images. Automated measurements made from 3D plant reconstructions identified quantitative trait loci for standard measures of shoot architecture, such as shoot height, leaf angle, and leaf length, and for novel composite traits, such as shoot compactness. The phenotypic variability associated with some of the quantitative trait loci displayed differences in temporal prevalence; for example, alleles closely linked with the sorghum Dwarf3 gene, an auxin transporter and pleiotropic regulator of both leaf inclination angle and shoot height, influence leaf angle prior to an effect on shoot height. Furthermore, variability in composite phenotypes that measure overall shoot architecture, such as shoot compactness, is regulated by loci underlying component phenotypes like leaf angle. As such, depth imaging is an economical and rapid method to acquire shoot architecture phenotypes in agriculturally important plants like sorghum to study the genetic basis of complex traits.

Application of Population Sequencing (POPSEQ) for Ordering and Imputing Genotyping-by-Sequencing Markers in Hexaploid Wheat

The advancement of next-generation sequencing technologies in conjunction with new bioinformatics tools enabled fine-tuning of sequence-based, high-resolution mapping strategies for complex genomes. Although genotyping-by-sequencing (GBS) provides a large number of markers, its application for association mapping and genomics-assisted breeding is limited by a large proportion of missing data per marker. For species with a reference genomic sequence, markers can be ordered on the physical map. However, in the absence of reference marker order, the use and imputation of GBS markers is challenging. Here, we demonstrate how the population sequencing (POPSEQ) approach can be used to provide marker context for GBS in wheat. The utility of a POPSEQ-based genetic map as a reference map to create genetically ordered markers on a chromosome for hexaploid wheat was validated by constructing an independent de novo linkage map of GBS markers from a Synthetic W7984 × Opata M85 recombinant inbred line (SynOpRIL) population. The results indicated that there is strong agreement between the independent de novo linkage map and the POPSEQ mapping approach in mapping and ordering GBS markers for hexaploid wheat. After ordering, a large number of GBS markers were imputed, thus providing a high-quality reference map that can be used for QTL mapping for different traits. The POPSEQ-based reference map and whole-genome sequence assemblies are valuable resources that can be used to order GBS markers and enable the application of highly accurate imputation methods to leverage the application GBS markers in wheat.

Harnessing Genetic Variation in Leaf Angle to Increase Productivity of Sorghum bicolor

The efficiency with which a plant intercepts solar radiation is determined primarily by its architecture. Understanding the genetic regulation of plant architecture and how changes in architecture affect performance can be used to improve plant productivity. Leaf inclination angle, the angle at which a leaf emerges with respect to the stem, is a feature of plant architecture that influences how a plant canopy intercepts solar radiation. Here we identify extensive genetic variation for leaf inclination angle in the crop plant Sorghum bicolor, a C4 grass species used for the production of grain, forage, and bioenergy. Multiple genetic loci that regulate leaf inclination angle were identified in recombinant inbred line populations of grain and bioenergy sorghum. Alleles of sorghum dwarf-3, a gene encoding a P-glycoprotein involved in polar auxin transport, are shown to change leaf inclination angle by up to 34° (0.59 rad). The impact of heritable variation in leaf inclination angle on light interception in sorghum canopies was assessed using functional-structural plant models and field experiments. Smaller leaf inclination angles caused solar radiation to penetrate deeper into the canopy, and the resulting redistribution of light is predicted to increase the biomass yield potential of bioenergy sorghum by at least 3%. These results show that sorghum leaf angle is a heritable trait regulated by multiple loci and that genetic variation in leaf angle can be used to modify plant architecture to improve sorghum crop performance.

Second-Generation Linkage Maps for the Pacific Oyster Crassostrea gigas Reveal Errors in Assembly of Genome Scaffolds

The Pacific oyster Crassostrea gigas, a widely cultivated marine bivalve mollusc, is becoming a genetically and genomically enabled model for highly fecund marine metazoans with complex life-histories. A genome sequence is available for the Pacific oyster, as are first-generation, low-density, linkage and gene-centromere maps mostly constructed from microsatellite DNA makers. Here, higher density, second-generation, linkage maps are constructed from more than 1100 coding (exonic) single-nucleotide polymorphisms (SNPs), as well as 66 previously mapped microsatellite DNA markers, all typed in five families of Pacific oysters (nearly 172,000 genotypes). The map comprises 10 linkage groups, as expected, has an average total length of 588 cM, an average marker-spacing of 1.0 cM, and covers 86% of a genome estimated to be 616 cM. All but seven of the mapped SNPs map to 618 genome scaffolds; 260 scaffolds contain two or more mapped SNPs, but for 100 of these scaffolds (38.5%), the contained SNPs map to different linkage groups, suggesting widespread errors in scaffold assemblies. The 100 misassembled scaffolds are significantly longer than those that map to a single linkage group. On the genetic maps, marker orders and intermarker distances vary across families and mapping methods, owing to an abundance of markers segregating from only one parent, to widespread distortions of segregation ratios caused by early mortality, as previously observed for oysters, and to genotyping errors. Maps made from framework markers provide stronger support for marker orders and reasonable map lengths and are used to produce a consensus high-density linkage map containing 656 markers.

RIG: Recalibration and interrelation of genomic sequence data with the GATK

Recent advances in variant calling made available in the Genome Analysis Toolkit (GATK) enable the use of validated single-nucleotide polymorphisms and indels to improve variant calling. However, large collections of variants for this purpose often are unavailable to research communities. We introduce a workflow to generate reliable collections of single-nucleotide polymorphisms and indels by leveraging available genomic resources to inform variant calling using the GATK. The workflow is demonstrated for the crop plant Sorghum bicolor by (i) generating an initial set of variants using reduced representation sequence data from an experimental cross and association panels, (ii) using the initial variants to inform variant calling from whole-genome sequence data of resequenced individuals, and (iii) using variants identified from whole-genome sequence data for recalibration of the reduced representation sequence data. The reliability of variants called with the workflow is verified by comparison with genetically mappable variants from an independent sorghum experimental cross. Comparison with a recent sorghum resequencing study shows that the workflow identifies an additional 1.62 million high-confidence variants from the same sequence data. Finally, the workflow's performance is validated using Arabidopsis sequence data, yielding variant call sets with 95% sensitivity and 99% positive predictive value. The Recalibration and Interrelation of genomic sequence data with the GATK (RIG) workflow enables the GATK to accurately identify genetic variation in organisms lacking validated variant resources.