Genotyping-by-sequencing Research Articles

STAC: A tool to leverage genetic marker data for crop research and breeding

AbstractAs genotyping by sequencing (GBS) becomes more prevalent and cost‐effective, there is a benefit in being able to apply the data to solve a variety of problems. However, high degrees of missing data and overreliance on single nucleotide polymorphisms (SNPs), while ignoring other forms of genetic variation, frequently plague attempts to make full use of GBS sequence data. Here we have developed two R scripts to serve as a tool in haplotype determination at loci of interest within biparental populations. One of these scripts, Sparse Tag Allele Caller (STAC), provides both automated calling and visual representations of the data around a locus of interest to assist in rapid data compilation decision‐making. The other script, STAC Integrate, allows automated quality control and logic‐based integration of presence/absence data with SNP data, while also rendering global overviews of recombination and coverage across the genome. These scripts are designed to be used together to maximize the utility of the available data. These tools were validated on a biparental population of wheat that was genotyped through GBS. They successfully enabled haplotype determination of a locus that was difficult to directly genotype, and their systemic accuracy was demonstrated in multiple populations and species. These scripts may serve as a tool for researchers attempting to make better use of GBS and other genetic marker data for both research and crop breeding decisions.

Genetic Variation and Association Analysis of Phenolic Compounds in Rapeseed (Brassica napus L.) Mutant Lines Using Genotyping-by-Sequencing (GBS)

The concentration of phenolic compounds in rapeseed is important because they are either anti-nutritional compounds or directly related to antioxidant activity. In this study, single nucleotide polymorphisms (SNPs) were identified using genotyping-by-sequencing (GBS), and an association study was conducted to investigate phenolic content in 95 rapeseed mutant lines derived from gamma rays and their original cultivar. A total of 3,196,318 SNPs were detected, resulting in the identification of a set of 70,208 union SNPs used to perform association studies. Seven compounds were identified, sinapine being the major phenolic compound (91.2–99.2%) in all genotypes. An association study was conducted for seven compounds and total phenolic content (TPC). It identified 241 SNPs that were significantly associated with these compounds, total sinapine content (TSC), and TPC. Based on the SNP markers detected, BnaC02g20420D was associated with dihexose, BnaC08g30570D with progoitrin, BnaA01g06890D with methyl sinapate, BnaA09g16810D with sinapine(4-O-8′)guaiacyl, BnaCnng39930D with trans-sinapine 1, BnaA07g31720D with trans-sinapine 2, BnaC03g31950D with sinapoyl malate, and BnaAnng27700D with TPC. These were selected as candidate genes that may play a key role in rapeseed. The SNP markers associated with these key phenolic compounds can be used as targets in breeding programs to reduce anti-nutritional components.

Genomics goes deeper in fisheries science: The case of the blackspot seabream (Pagellus bogaraveo) in the northeast Atlantic

Recent advances in genomics are an essential contributor to the assessment of fish stocks by providing a fine-scale identification of the species' genetic boundaries. The blackspot seabream, Pagellus bogaraveo, is a commercial sparid distributed across the northeast (NE) Atlantic and the Mediterranean. Within the NE Atlantic, three P. bogaraveo stocks are currently defined: Azores; Atlantic Iberian waters; Celtic Sea and the Bay of Biscay. We used a genotyping-by-sequencing (GBS) approach to better define the spatial scale at which the species occurs in the NE Atlantic. Our findings revealed the existence of an additional genetic cluster in the eastern Atlantic (Gulf of Cádiz) that was not identified in previous studies based on mitochondrial DNA or microsatellite data. The combined effect of ocean circulation patterns, complex bathymetry and the existence of local upwelling may play an important role on the retention of blackspot seabream larvae and adults, providing an explanation for the genetic differentiation between the specimens caught off the Gulf of Cádiz and Peniche (Portugal). Results presented here revealed hidden intra-specific genetic differentiation and can inform a finer-scale sampling to determine the new stock boundaries in the Atlantic Iberian coasts.

Application of a High-Density Single Nucleotide Polymorphism Genetic Map in Mapping Quantitative Trait Loci of Early-Maturing Traits in Upland Cotton

(1) Background: Mapping QTLs for early-maturing traits is necessary for the development of early-maturing variety breeding. (2) Methods: In this research, a high-density genetic map (HDGM) was constructed using an F2 population with 100 individuals and single nucleotide polymorphism markers (SNPs) developed using the genotyping-by-sequencing (GBS) method. (3) Results: The HDGM, which covered a total distance of 3167.14 cM, harbored 5454 SNPs with an average marker interval of 0.58 cM. In total, 18 QTLs for four early-maturing characters were detected and explained 11.6–46.4% of phenotypic variation (PV). Two QTLs of the whole growing period (WGP) and height of the node of the first fruiting branch (HNFFB) were identified as stable QTLs. In total, 125 candidate genes were identified in the confidence intervals of these stable QTLs. Presumably, Gh_D03G0857 may play an important role in regulating earliness. (4) Conclusions: This research will provide new information about fine mapping of QTLs for earliness traits, molecular marker assisted selection (MAS) of earliness traits, and pyramiding breeding as well.

Genome-wide association study of fiber yield-related traits uncovers the novel genomic regions and candidate genes in Indian upland cotton (Gossypium hirsutum L.).

Upland cotton (Gossypium hirsutum L.) is a major fiber crop that is cultivated worldwide and has significant economic importance. India harbors the largest area for cotton cultivation, but its fiber yield is still compromised and ranks 22nd in terms of productivity. Genetic improvement of cotton fiber yield traits is one of the major goals of cotton breeding, but the understanding of the genetic architecture underlying cotton fiber yield traits remains limited and unclear. To better decipher the genetic variation associated with fiber yield traits, we conducted a comprehensive genome-wide association mapping study using 117 Indian cotton germplasm for six yield-related traits. To accomplish this, we generated 2,41,086 high-quality single nucleotide polymorphism (SNP) markers using genotyping-by-sequencing (GBS) methods. Population structure, PCA, kinship, and phylogenetic analyses divided the germplasm into two sub-populations, showing weak relatedness among the germplasms. Through association analysis, 205 SNPs and 134 QTLs were identified to be significantly associated with the six fiber yield traits. In total, 39 novel QTLs were identified in the current study, whereas 95 QTLs overlapped with existing public domain data in a comparative analysis. Eight QTLs, qGhBN_SCY_D6-1, qGhBN_SCY_D6-2, qGhBN_SCY_D6-3, qGhSI_LI_A5, qGhLI_SI_A13, qGhLI_SI_D9, qGhBW_SCY_A10, and qGhLP_BN_A8 were identified. Gene annotation of these fiber yield QTLs revealed 2,509 unique genes. These genes were predominantly enriched for different biological processes, such as plant cell wall synthesis, nutrient metabolism, and vegetative growth development in the gene ontology (GO) enrichment study. Furthermore, gene expression analysis using RNAseq data from 12 diverse cotton tissues identified 40 candidate genes (23 stable and 17 novel genes) to be transcriptionally active in different stages of fiber, ovule, and seed development. These findings have revealed a rich tapestry of genetic elements, including SNPs, QTLs, and candidate genes, and may have a high potential for improving fiber yield in future breeding programs for Indian cotton.

Genetic mapping of quantitative trait loci associated with drought tolerance in chickpea (Cicer arietinum L.)

Elucidation of the genetic basis of drought tolerance is vital for genomics-assisted breeding of drought tolerant crop varieties. Here, we used genotyping-by-sequencing (GBS) to identify single nucleotide polymorphisms (SNPs) in recombinant inbred lines (RILs) derived from a cross between a drought tolerant chickpea variety, Pusa 362 and a drought sensitive variety, SBD 377. The GBS identified a total of 35,502 SNPs and subsequent filtering of these resulted in 3237 high-quality SNPs included in the eight linkage groups. Fifty-one percent of these SNPs were located in the genic regions distributed throughout the genome. The high density linkage map has total map length of 1069 cm with an average marker interval of 0.33 cm. The linkage map was used to identify 9 robust and consistent QTLs for four drought related traits viz. membrane stability index, relative water content, seed weight and yield under drought, with percent variance explained within the range of 6.29%–90.68% and LOD scores of 2.64 to 6.38, which were located on five of the eight linkage groups. A genomic region on LG 7 harbors quantitative trait loci (QTLs) explaining > 90% phenotypic variance for membrane stability index, and > 10% PVE for yield. This study also provides the first report of major QTLs for physiological traits such as membrane stability index and relative water content for drought stress in chickpea. A total of 369 putative candidate genes were identified in the 6.6 Mb genomic region spanning these QTLs. In-silico expression profiling based on the available transcriptome data revealed that 326 of these genes were differentially expressed under drought stress. KEGG analysis resulted in reduction of candidate genes from 369 to 99, revealing enrichment in various signaling pathways. Haplotype analysis confirmed 5 QTLs among the initially identified 9 QTLs. Two QTLs, qRWC1.1 and qYLD7.1, were chosen based on high SNP density. Candidate gene-based analysis revealed distinct haplotypes in qYLD7.1 associated with significant phenotypic differences, potentially linked to pathways for secondary metabolite biosynthesis. These identified candidate genes bolster defenses through flavonoids and phenylalanine-derived compounds, aiding UV protection, pathogen resistance, and plant structure.The study provides novel genomic regions and candidate genes which can be utilized in genomics-assisted breeding of superior drought tolerant chickpea cultivars.

Developing adapted wheat lines with broad-spectrum resistance to stem rust: Introgression of Sr59 through backcrossing and selections based on genotyping-by-sequencing data.

Control of stem rust, caused by Puccinia graminis f.sp. tritici, a highly destructive fungal disease of wheat, faces continuous challenges from emergence of new virulent races across wheat-growing continents. Using combinations of broad-spectrum resistance genes could impart durable stem rust resistance. This study attempted transfer of Sr59 resistance gene from line TA5094 (developed through CSph1bM-induced T2DS·2RL Robertsonian translocation conferring broad-spectrum resistance). Poor agronomic performance of line TA5094 necessitates Sr59 transfer to adapted genetic backgrounds and utility evaluations for wheat improvement. Based on combined stem rust seedling and molecular analyses, 2070 BC1F1 and 1230 BC2F1 plants were derived from backcrossing BAJ#1, KACHU#1, and REEDLING#1 with TA5094. Genotyping-by-sequencing (GBS) results revealed the physical positions of 15,116 SNPs on chromosome 2R. The adapted genotypes used for backcrossing were found not to possess broad-spectrum resistance to selected stem rust races, whereas Sr59-containing line TA5094 showed resistance to all races tested. Stem rust seedling assays combined with kompetitive allele-specific PCR (KASP) marker analysis successfully selected and generated the BC2F2 population, which contained the Sr59 gene, as confirmed by GBS. Early-generation data from backcrossing suggested deviations from the 3:1 segregation, suggesting that multiple genes may contribute to Sr59 resistance reactions. Using GBS marker data (40,584 SNPs in wheat chromosomes) to transfer the recurrent parent background to later-generation populations resulted in average genome recovery of 71.2% in BAJ#1*2/TA5094, 69.8% in KACHU#1*2/TA5094, and 70.5% in REEDLING#1*2/TA5094 populations. GBS data verified stable Sr59 introgression in BC2F2 populations, as evidenced by presence of the Ph1 locus and absence of the 50,936,209 bp deletion in CSph1bM. Combining phenotypic selections, stem rust seedling assays, KASP markers, and GBS data substantially accelerated transfer of broad-spectrum resistance into adapted genotypes. Thus, this study demonstrated that the Sr59 resistance gene can be introduced into elite genetic backgrounds to mitigate stem rust-related yield losses.

Genotyping-by-sequencing reveals a high number and quality of single nucleotide polymorphisms in guinea pigs (Cavia porcellus) from the Peruvian Andes.

Guinea pigs are a major source of animal protein for Peruvian Andean families. Despite the economic and cultural relevance of guinea pigs, their genomic characterization has been scarcely addressed. Genotyping-by-sequencing (GBS) has emerged as an affordable alternative to genotyping of livestock and native animals. Here, we report the use of GBS for single nucleotide polymorphism (SNP) discovery of traditionally raised guinea pigs from six regions of the Peruvian Andes and one group of breeding animals. The paired-end (2 × 150 bp) sequencing of 40 guinea pig DNA samples generated a mean of 6.4 million high-quality sequencing reads per sample. We obtained an average sequencing depth of 10× with an 88.5% mapping rate to the Cavia porcellus reference genome. A total of 279 965 SNPs (102 SNPs/Mbp) were identified after variant calling and quality filtering. Based on this SNP set, we assessed the genetic diversity and distance within our selected guinea pig populations. An overall average minor allele frequency of 0.13, an observed heterozygosity of 0.31, an expected heterozygosity of 0.35, and an F-value of 0.1 were obtained, while the SNP-based neighbor-joining tree suggests a closer genetic relationship between individuals from geographically close locations. We showed that GBS is a cost-effective tool for SNP discovery and genetic characterization of Peruvian guinea pig populations. Therefore, it may be considered as a suitable and affordable tool for genomic characterization of poorly studied native animal species.

Genome-wide association mapping and genomic prediction for late blight and potato cyst nematode resistance in potato (Solanum tuberosum L.).

Potatoes are an important source of food for millions of people worldwide. Biotic stresses, notably late blight and potato cyst nematodes (PCN) pose a major threat to potato production worldwide, and knowledge of genes controlling these traits is limited. A genome-wide association mapping study was conducted to identify the genomic regulators controlling these biotic stresses, and the genomic prediction accuracy was worked out using the GBLUP model of genomic selection (GS) in a panel of 222 diverse potato accessions. The phenotype data on resistance to late blight and two PCN species (Globodera pallida and G. rostochiensis) were recorded for three and two consecutive years, respectively. The potato panel was genotyped using genotyping by sequencing (GBS), and 1,20,622 SNP markers were identified. A total of 7 SNP associations for late blight resistance, 9 and 11 for G. pallida and G. rostochiensis, respectively, were detected by additive and simplex dominance models of GWAS. The associated SNPs were distributed across the chromosomes, but most of the associations were found on chromosomes 5, 10 and 11, which have been earlier reported as the hotspots of disease-resistance genes. The GS prediction accuracy estimates were low to moderate for resistance to G. pallida (0.04-0.14) and G. rostochiensis (0.14-0.21), while late blight resistance showed a high prediction accuracy of 0.42-0.51. This study provides information on the complex genetic nature of these biotic stress traits in potatoes and putative SNP markers for resistance breeding.

Genome-wide association study to identify novel loci and genes for Fusarium root rot resistance in sweet potato using genotyping-by-sequencing.

Fusarium root rot, caused by Fusarium solani, is a major post-harvest disease in sweet potatoes (Ipomoea batatas (L.) Lam.). An effective strategy for controlling this disease is the development of resistant varieties. In this study, a genome-wide association study (GWAS) was conducted on 96 sweet potato genotypes to identify novel candidate loci and dissect the genetic basis of Fusarium root rot resistance. Genotyping was performed using genotyping-by-sequencing (GBS), and 44,255 SNPs were identified after filtering. The genotypes (n = 96) were evaluated through resistance tests in 2021 and 2022, separately and combined. The GWAS identified two significant SNP markers (LG3_22903756 and LG4_2449919) on chromosomes 3 and 4 associated with Fusarium root rot resistance, respectively. Lesion length showed significant differences between homozygous A and G alleles of LG3_22903756, which can potentially be used to develop molecular markers for selecting accessions resistant to Fusarium root rot. Expression analysis of 11 putative genes flanking the significant SNPs revealed the alteration in the expression of nine genes, indicating their possible involvement in Fusarium root rot resistance. The results of this study will aid in the marker-assisted selection and functional analysis of candidate genes for Fusarium root rot resistance in sweet potatoes.

Genetic characterization of root architectural traits in barley (Hordeum vulgare L.) using SNP markers.

Increasing attention is paid to providing new tools to breeders for targeted breeding for specific root traits that are beneficial in low-fertility, drying soils; however, such information is not available for barley (Hordeum vulgare L.). A panel of 191 barley accessions (originating from Australia, Europe, and Africa) was phenotyped for 26 root and shoot traits using the semi-hydroponic system and genotyped using 21 062 high-quality single nucleotide polymorphism (SNP) markers generated by genotyping-by-sequencing (GBS). The population structure analysis of the barley panel identified six distinct groups. We detected 1199 significant (P<0.001) marker-trait associations (MTAs) with r2 values up to 0.41. The strongest MTAs were found for root diameter in the top 20 cm and the longest root length. Based on the physical locations of these MTAs in the barley reference genome, we identified 37 putative QTLs for the root traits, and three QTLs for shoot traits, with nine QTLs located in the same physical regions. The genomic region 640-653 Mb on chromosome 7H was significant for five root length-related traits, where 440 annotated genes were located. The putative QTLs for various root traits identified in this study may be useful for genetic improvement regarding the adaptation of new barley cultivars to suboptimal environments and abiotic stresses.

QTL mapping of oleic acid content in modern VNIIMK sunflower (Helianthus annuus L.) lines by using GBS-based SNP map.

Oleic acid is a monounsaturated fatty acid increasing oil oxidative stability. High content of oleic acid is thus a valuable trait in oilseed crops. Sunflower (Helianthus annuus L.) normally accumulates linoleic acid as a major fatty acid, but a mutant expressing a high oleic phenotype form was previously obtained by chemical mutagenesis and mapped on the sunflower genome. Several studies suggest the presence of additional genes involved in the control of the high content of oleic acid, with their expression possibly depending on the genetic background. To test this hypothesis, we performed a QTL mapping of the high oleic acid trait within two independent F2 crosses involving lines with contrasting oleic acid content from the Pustovoit All-Russia Research Institute of Oil Crops (VNIIMK) collection. We applied genotyping-by-sequencing (GBS) to construct single nucleotide polymorphism-based genetic maps and performed QTL mapping using quantitative and qualitative encoding for oleic acid content. Our results support the finding that the oleic acid content in the assessed crosses is controlled by one major effect locus. However, different dominant/recessive effects of the major locus were reported for both crosses. Additionally, a possible translocation between chromosome 7 and 14 was reported in one assessed cross. We defined a set of single nucleotide polymorphism markers for each cross which could be used for marker-assisted selection.

First Vanilla planifolia High-Density Genetic Linkage Map Provides Quantitative Trait Loci for Resistance to Fusarium oxysporum.

Fusarium oxysporum f. sp. radicis-vanillae (Forv), the causal agent of root and stem rot disease, is the main pathogen affecting vanilla production. Sources of resistance have been reported in Vanilla planifolia G. Jackson ex Andrews, the main cultivated vanilla species. In this study, we developed the first high-density genetic map in this species with 1,804 genotyping-by-sequencing (GBS)-generated single nucleotide polymorphism (SNP) markers using 125 selfed progenies of the CR0040 traditional vanilla cultivar. Sixteen linkage groups (LG) were successfully constructed, with a mean of 113 SNPs and an average length of 207 cM per LG. The map had a high density with an average of 5.45 SNP every 10 cM and an average distance of 1.85 cM between adjacent markers. The first three LG were aligned against the first assembled chromosome of CR0040, and the other 13 LG were correctly associated with the other 13 assembled chromosomes. The population was challenged with the highly pathogenic Forv strain Fo072 using the root-dip inoculation method. Five traits were mapped, and 20 QTLs were associated with resistance to Fo072. Among the genes retrieved in the CR0040 physical regions associated with QTLs, genes potentially involved in biotic resistance mechanisms, coding for kinases, E3 ubiquitin ligases, pentatricopeptide repeat-containing proteins, and one leucine-rich repeat receptor underlying the qFo72_08.1 QTL have been highlighted. This study should provide useful resources for marker-assisted selection in V. planifolia.

Genetic diversity and population structure of some Nigerian and four African countries' sorghum landraces [Sorghum bicolor (L.) Moench] using Genotyping-By-Sequencing (GBS) SNP markers

A genotyping-by-sequencing (GBS) approach was used in this study to assess the genetic variability and population structure of fifty sorghum landrace accessions collected from the major sorghum growing areas in Nigeria and four other African countries. There were 7078 SNP markers found in the sorghum genome that were widely distributed. An average polymorphism information content (PIC) value of 0.26 was observed for the SNP markers. Gene diversity (He) was substantial among the selected accessions (0.30). Nigeria's northeast accessions showed the highest gene diversity (0.32). Although molecular variation varied by only 2% among populations and by 98% within populations, principal coordinate analysis and cluster analysis revealed three major groups unrelated to geographical origin. This is an indication of high gene flow among populations (Nm = 7.71). However, due to the considerable similarity within populations, many accessions from similar states tend to cluster together. The population structure analysis at K=3 revealed three subpopulations, with 42% of the accessions evaluated being admixed together. A high number of private alleles (162) were identified in accession samples. This shows the potential for beneficial traits in sorghum breeding.

Genotyping-by-sequencing (GBS) reveals greater somatic mutations than simple sequence repeats (SSRs) in micropropagated cannabis plants

Genotyping-by-sequencing (GBS) reveals greater somatic mutations than simple sequence repeats (SSRs) in micropropagated cannabis plants

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

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

Development of an SNP marker set for marker-assisted backcrossing using genotyping-by-sequencing in tetraploid perilla.

High-quality molecular markers are essential for marker-assisted selection to accelerate breeding progress. Compared with diploid species, recently diverged polyploid crop species tend to have highly similar homeologous subgenomes, which is expected to limit the development of broadly applicable locus-specific single-nucleotide polymorphism (SNP) assays. Furthermore, it is particularly challenging to make genome-wide marker sets for species that lack a reference genome. Here, we report the development of a genome-wide set of kompetitive allele specific PCR (KASP) markers for marker-assisted recurrent selection (MARS) in the tetraploid minor crop perilla. To find locus-specific SNP markers across the perilla genome, we used genotyping-by-sequencing (GBS) to construct linkage maps of two F2 populations. The two resulting high-resolution linkage maps comprised 2326 and 2454 SNP markers that spanned a total genetic distance of 2133cM across 16 linkage groups and 2169cM across 21 linkage groups, respectively. We then obtained a final genetic map consisting of 22 linkage groups with 1123 common markers from the two genetic maps. We selected 96 genome-wide markers for MARS and confirmed the accuracy of markers in the two F2 populations using a high-throughput Fluidigm system. We confirmed that 91.8% of the SNP genotyping results from the Fluidigm assay were the same as the results obtained through GBS. These results provide a foundation for marker-assisted backcrossing and the development of new varieties of perilla.

Ultra-High-Density Genetic Maps of Jatropha curcas × Jatropha integerrima and Anchoring Jatropha curcas Genome Assembly Scaffolds

Genetic maps facilitate an understanding of genome organization and the mapping of genes and QTLs for traits of interest. Our objective was to develop a high-density genetic map of Jatropha and anchoring scaffolds from genome assemblies. We developed two ultra-high-density genetic linkage maps of Jatropha curcas × Jatropha intergerrima using a backcross (BC1) population using SNP, AFLP and SSR markers. First, SNPs were identified through genotyping-by-sequencing (GBS). The polymorphic SNPs were mapped to 3267 Jat_r4.5 scaffolds and 484 Wu_JatCur_1.0 scaffolds, and then these genomic scaffolds were mapped/anchored to the genetic linkage groups along with the AFLP and SSR markers for each genome assembly separately. We successfully mapped 7284 polymorphic SNPs, and 54 AFLP and SSR markers on 11 linkage groups using the Jat_r4.5 genomic scaffolds, resulting in a genome length of 1088 cM and an average marker interval of 0.71 cM. We mapped 7698 polymorphic SNPs, and 99 AFLP and SSR markers on 11 linkage groups using the Wu_JatCur_1.0 genomic scaffolds, resulting in a genome length of 870 cM and an average marker interval of 1.67 cM. The mapped SNPs were annotated to various regions of the genome, including exon, intron and intergenic regions. We developed two ultra-high-density linkage maps anchoring a high number of genome scaffolds to linkage groups, which provide an important resource for the structural and functional genomics as well as for molecular breeding of Jatropha while also serving as a framework for assembling and ordering whole genome scaffolds.

Mapping QTL for Yield and Its Component Traits Using Wheat (Triticum aestivum L.) RIL Mapping Population from TAM 113 × Gallagher

Understanding genetic architectures of yield and yield-related traits of wheat (Triticum aestivum L.) grown under dryland or irrigated conditions is pivotal for developing modern high-yielding germplasm and cultivars. The objectives of this study were to detect quantitative trait loci (QTL) linked to yield and yield components using a mapping population derived from ‘TAM 113’/‘Gallagher’, including 191 recombinant inbred lines (RILs). The population was grown in McGregor, College Station, and Bushland, Texas, for three consecutive years from 2019 to 2021. A high-density genetic map covering all 21 chromosomes was constructed using a set of 8,075 single nucleotide polymorphisms (SNPs) obtained using genotyping-by-sequencing (GBS). A total of 147 QTLs for 16 yield-related traits were identified, which included 16 QTLs consistently detected in multiple experiments and 8 QTLs that showed pleiotropic effects. Of them, five pleiotropic QTLs overlapped with the consistent QTL. They increased grain yield (YLD) up to 37.64 g m−2, thousand kernel weight (TKW) up to 1.33 g, harvest (HI) up to 0.97%, kernel length up to 0.08 mm, and kernel width up to 0.04 mm with Gallagher alleles and increased YLD up to 22.21 g m−2, kernels spike−1 up to 1.77, TKW up to 1.14 g, and HI up to 3.72% with TAM 113 alleles. One major and consistent QTL on chromosome 2D at 34.4 Mbp overlapped with the major photoperiod gene Ppd-D1 and was affected by multiple traits, including kernel diameter (DIAM), TKW, kernel hardness index (KHI), heading date (HD), and plant height (PH). Another QTL cluster region on 7D between 52 and 66 Mbp, encompassing one consistent and three pleiotropic QTLs. One of the pleiotropic QTLs at 52 Mbp increased YLD up to 24.16 g m−2, HI up to 1%, and DIAM up to 0.03 mm. This study dissected genetic loci associated with yield and yield-related traits, providing valuable information on wheat improvement using marker-assisted selection (MAS).

Evaluating restriction enzyme selection for reduced representation sequencing in conservation genomics.

Conservation genomic studies in non-model organisms generally rely on reduced representation sequencing techniques based on restriction enzymes to identify population structure as well as candidate loci for local adaptation. While the expectation is that the reduced representation of the genome is randomly distributed, the proportion of the genome sampled might depend on the GC content of the recognition site of the restriction enzyme used. Here, we evaluated the distribution and functional composition of loci obtained after a reduced representation approach using Genotyping-by-Sequencing (GBS). To do so, we compared experimental data from two endemic fish species (Symphodus ocellatus and Symphodus tinca, EcoT22I enzyme) and two ecosystem engineer sea urchins (Paracentrotus lividus and Arbacia lixula, ApeKI enzyme). In brief, we mapped the sequenced loci to the phylogenetically closest reference genome available (Labrus bergylta in the fish and Strongylocentrotus purpuratus in the sea urchin datasets), classified them as exonic, intronic and intergenic, and studied their function by using Gene Ontology (GO) terms. We also simulated the effect of using both enzymes in the two reference genomes. In both simulated and experimental data, we detected an enrichment towards exonic or intergenic regions depending on the restriction enzyme used and failed to detect differences between total loci and candidate loci for adaptation in the empirical dataset. Most of the functions assigned to the mapped loci were shared between the four species and involved a myriad of general functions. Our results highlight the importance of restriction enzyme selection and the need for high-quality annotated genomes in conservation genomic studies.