Retrospective genomic analysis of sorghum adaptation to temperate-zone grain production

Background

Sorghum is a tropical C₄ cereal that recently adapted to temperate latitudes and mechanized grain harvest through selection for dwarfism and photoperiod-insensitivity. Quantitative trait loci for these traits have been introgressed from a dwarf temperate donor into hundreds of diverse sorghum landraces to yield the Sorghum Conversion lines. Here, we report the first comprehensive genomic analysis of the molecular changes underlying this adaptation.

Results

We apply genotyping-by-sequencing to 1,160 Sorghum Conversion lines and their exotic progenitors, and map donor introgressions in each Sorghum Conversion line. Many Sorghum Conversion lines carry unexpected haplotypes not found in either presumed parent. Genome-wide mapping of introgression frequencies reveals three genomic regions necessary for temperate adaptation across all Sorghum Conversion lines, containing the Dw1, Dw2, and Dw3 loci on chromosomes 9, 6, and 7 respectively. Association mapping of plant height and flowering time in Sorghum Conversion lines detects significant associations in the Dw1 but not the Dw2 or Dw3 regions. Subpopulation-specific introgression mapping suggests that chromosome 6 contains at least four loci required for temperate adaptation in different sorghum genetic backgrounds. The Dw1 region fractionates into separate quantitative trait loci for plant height and flowering time.

Conclusions

Generating Sorghum Conversion lines has been accompanied by substantial unintended gene flow. Sorghum adaptation to temperate-zone grain production involves a small number of genomic regions, each containing multiple linked loci for plant height and flowering time. Further characterization of these loci will accelerate the adaptation of sorghum and related grasses to new production systems for food and fuel.     

Prediction accuracies for growth and wood attributes of interior spruce in space using genotyping-by-sequencing

Background

Genomic selection (GS) in forestry can substantially reduce the length of breeding cycle and increase gain per unit time through early selection and greater selection intensity, particularly for traits of low heritability and late expression. Affordable next-generation sequencing technologies made it possible to genotype large numbers of trees at a reasonable cost.

Results

Genotyping-by-sequencing was used to genotype 1,126 Interior spruce trees representing 25 open-pollinated families planted over three sites in British Columbia, Canada. Four imputation algorithms were compared (mean value (MI), singular value decomposition (SVD), expectation maximization (EM), and a newly derived, family-based k-nearest neighbor (kNN-Fam)). Trees were phenotyped for several yield and wood attributes. Single- and multi-site GS prediction models were developed using the Ridge Regression Best Linear Unbiased Predictor (RR-BLUP) and the Generalized Ridge Regression (GRR) to test different assumption about trait architecture. Finally, using PCA, multi-trait GS prediction models were developed. The EM and kNN-Fam imputation methods were superior for 30 and 60% missing data, respectively. The RR-BLUP GS prediction model produced better accuracies than the GRR indicating that the genetic architecture for these traits is complex. GS prediction accuracies for multi-site were high and better than those of single-sites while multi-site predictability produced the lowest accuracies reflecting type-b genetic correlations and deemed unreliable. The incorporation of genomic information in quantitative genetics analyses produced more realistic heritability estimates as half-sib pedigree tended to inflate the additive genetic variance and subsequently both heritability and gain estimates. Principle component scores as representatives of multi-trait GS prediction models produced surprising results where negatively correlated traits could be concurrently selected for using PCA2 and PCA3.

Conclusions

The application of GS to open-pollinated family testing, the simplest form of tree improvement evaluation methods, was proven to be effective. Prediction accuracies obtained for all traits greatly support the integration of GS in tree breeding. While the within-site GS prediction accuracies were high, the results clearly indicate that single-site GS models ability to predict other sites are unreliable supporting the utilization of multi-site approach. Principle component scores provided an opportunity for the concurrent selection of traits with different phenotypic optima.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1597-y) contains supplementary material, which is available to authorized users.     

Genetic dissection of Al tolerance QTLs in the maize genome by high density SNP scan

Background

Aluminum (Al) toxicity is an important limitation to food security in tropical and subtropical regions. High Al saturation on acid soils limits root development, reducing water and nutrient uptake. In addition to naturally occurring acid soils, agricultural practices may decrease soil pH, leading to yield losses due to Al toxicity. Elucidating the genetic and molecular mechanisms underlying maize Al tolerance is expected to accelerate the development of Al-tolerant cultivars.

Results

Five genomic regions were significantly associated with Al tolerance, using 54,455 SNP markers in a recombinant inbred line population derived from Cateto Al237. Candidate genes co-localized with Al tolerance QTLs were further investigated. Near-isogenic lines (NILs) developed for ZmMATE2 were as Al-sensitive as the recurrent line, indicating that this candidate gene was not responsible for the Al tolerance QTL on chromosome 5, qALT5. However, ZmNrat1, a maize homolog to OsNrat1, which encodes an Al³⁺ specific transporter previously implicated in rice Al tolerance, was mapped at ~40 Mbp from qALT5. We demonstrate for the first time that ZmNrat1 is preferentially expressed in maize root tips and is up-regulated by Al, similarly to OsNrat1 in rice, suggesting a role of this gene in maize Al tolerance. The strongest-effect QTL was mapped on chromosome 6 (qALT6), within a 0.5 Mbp region where three copies of the Al tolerance gene, ZmMATE1, were found in tandem configuration. qALT6 was shown to increase Al tolerance in maize; the qALT6-NILs carrying three copies of ZmMATE1 exhibited a two-fold increase in Al tolerance, and higher expression of ZmMATE1 compared to the Al sensitive recurrent parent. Interestingly, a new source of Al tolerance via ZmMATE1 was identified in a Brazilian elite line that showed high expression of ZmMATE1 but carries a single copy of ZmMATE1.

Conclusions

High ZmMATE1 expression, controlled either by three copies of the target gene or by an unknown molecular mechanism, is responsible for Al tolerance mediated by qALT6. As Al tolerant alleles at qALT6 are rare in maize, marker-assisted introgression of this QTL is an important strategy to improve maize adaptation to acid soils worldwide.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-153) contains supplementary material, which is available to authorized users.     

Precisely mapping a major gene conferring resistance to Hessian fly in bread wheat using genotyping-by-sequencing

Background

One of the reasons hard red winter wheat cultivar ‘Duster’ (PI 644016) is widely grown in the southern Great Plains is that it confers a consistently high level of resistance to biotype GP of Hessian fly (Hf). However, little is known about the genetic mechanism underlying Hf resistance in Duster. This study aimed to unravel complex structures of the Hf region on chromosome 1AS in wheat by using genotyping-by-sequencing (GBS) markers and single nucleotide polymorphism (SNP) markers.

Results

Doubled haploid (DH) lines generated from a cross between two winter wheat cultivars, ‘Duster’ and ‘Billings’ , were used to identify genes in Duster responsible for effective and consistent resistance to Hf. Segregation in reaction of the 282 DH lines to Hf biotype GP fit a one-gene model. The DH population was genotyped using 2,358 markers developed using the GBS approach. A major QTL, explaining 88% of the total phenotypic variation, was mapped to a chromosome region that spanned 178 cM and contained 205 GBS markers plus 1 SSR marker and 1 gene marker, with 0.86 cM per marker in genetic distance. The analyses of GBS marker sequences and further mapping of SSR and gene markers enabled location of the QTL-containing linkage group on the short arm of chromosome 1A. Comparative mapping of the common markers for the gene for QHf.osu-1A^d in Duster and the Hf-resistance gene for QHf.osu-1A⁷⁴ in cultivar ‘2174’ showed that the two Hf resistance genes are located on the same chromosome arm 1AS, only 11.2 cM apart in genetic distance. The gene at QHf.osu-1A^d in Duster has been delimited within a 2.7 cM region.

Conclusion

Two distinct resistance genes exist on the short arm of chromosome 1A as found in the two hard red winter cultivars, 2174 and Duster. Whereas the Hf resistance gene in 2174 is likely allelic to one or more of the previously mapped resistance genes (H9, H10, H11, H16, or H17) in wheat, the gene in Duster is novel and confers a more consistent phenotype than 2174 in response to biotype GP infestation in controlled-environment assays.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1297-7) contains supplementary material, which is available to authorized users.     

Single step genome-wide association studies based on genotyping by sequence data reveals novel loci for the litter traits of domestic pigs

In this study, data genotyping by sequence (GBS) was used to perform single step GWAS (ssGWAS) to identify SNPs associated with the litter traits in domestic pigs and search for candidate genes in the region of significant SNPs. After quality control, 167,355 high-quality SNPs from 532 pigs were obtained. Phenotypic traits on 2112 gilt litters from 532 pigs were recorded including total number born (TNB), number born alive (NBA), and litter weight born alive (LWB). A single-step genomic BLUP approach (ssGBLUP) was used to implement the genome-wide association analysis at a 5% genome-wide significance level. A total of 8, 23 and 20 significant SNPs were associated with TNB, NBA, and LWB, respectively, and these significant SNPs accounted for 62.78%, 79.75%, and 58.79% of genetic variance. Furthermore, 1 (SSC14: 16314857), 4 (SSC1: 81986236, SSC1: 66599775, SSC1: 161999013, and SSC1: 267883107), and 5 (SSC9: 29030061, SSC2: 32368561, SSC5: 110375350, SSC13: 45619882 and SSC13: 45647829) significant SNPs for TNB, NBA, and LWB were inferred to be novel loci. At SSC1, the AIM1 and FOXO3 genes were found to be associated with NBA; these genes increase ovarian reproductive capacity and follicle number and decrease gonadotropin levels. The genes SLC36A4 and INTU are involved in cell growth, cytogenesis and development were found to be associated with LWB. These significant SNPs can be used as an indication for regions in the Sus scrofa genome for variability in litter traits, but further studies are expected to confirm causative mutations.     

Genotyping-by-sequencing performance in selected livestock species

Application of next generation sequencing for large scale genotyping in livestock is limited by high costs and challenging data analysis process. However, available restriction enzyme-based enrichment techniques like e.g. genotyping-by-sequencing (GBS) are promising tools allowing reduction of financial outlies by a high sample multiplexing and narrowing down the sequenced genome areas to the randomly distributed read tags. In this study, we tested the performance of standard, PstI endonuclease-adapted GBS protocol for population genetics in cattle, horse and sheep with application of different, including low-depth sequencing setups. It was found that the detected SNPs display desirable polymorphism parameters and are evenly scattered across the whole genome including gene coding regions. It was also shown that the SNPs can be successfully applied in population genetics, revealing the genetic differentiation of the studied breeds. The GBS approach represents a cost-effective alternative to existing genotyping methods which may find adoption in various research applications.     

Genome complexity of harmful microalgae

During the past decade, next generation sequencing (NGS) technologies have provided new insights into the diversity, dynamics, and metabolic pathways of natural microbial communities. But, these new techniques face challenges related to the genome size and level of genome complexity of the species under investigation. Moreover, the coverage depth and the short-read length achieved by NGS based approaches also represent a major challenge for assembly. These factors could limit the use of these high-throughput sequencing methods for species lacking a reference genome and characterized by a high level of complexity. In the present work, the evolutionary history, mainly consisting of gene transfer events from bacteria and unicellular eukaryotes to microalgae, including harmful species, is discussed and reviewed as it relates to NGS application in microbial communities, with a particular focus on harmful algal bloom species and dinoflagellates. In the context of genetic population studies, genotyping-by-sequencing (GBS), an NGS based approach, could be used for the discovery and analysis of single nucleotide polymorphisms (SNPs). The NGS technologies are still relatively new and require further improvement. Specifically, there is a need to develop and standardize tools and approaches to handle large data sets, which have to be used for the majority of HAB species characterized by evolutionary highly dynamic genomes.     

A high density GBS map of bread wheat and its application for dissecting complex disease resistance traits

Background

Genotyping-by-sequencing (GBS) is a high-throughput genotyping approach that is starting to be used in several crop species, including bread wheat. Anchoring GBS tags on chromosomes is an important step towards utilizing them for wheat genetic improvement. Here we use genetic linkage mapping to construct a consensus map containing 28644 GBS markers.

Results

Three RIL populations, PBW343 × Kingbird, PBW343 × Kenya Swara and PBW343 × Muu, which share a common parent, were used to minimize the impact of potential structural genomic variation on consensus-map quality. The consensus map comprised 3757 unique positions, and the average marker distance was 0.88 cM, obtained by calculating the average distance between two adjacent unique positions. Significant variation of segregation distortion was observed across the three populations. The consensus map was validated by comparing positions of known rust resistance genes, and comparing them to wheat reference genome sequences recently published by the International Wheat Genome Sequencing Consortium, Rye and Ae. tauschii genomes. Three well-characterized rust resistance genes (Sr58/Lr46/Yr29, Sr2/Yr30/Lr27, and Sr57/Lr34/Yr18) and 15 published QTLs for wheat rusts were validated with high resolution. Fifty-two per cent of GBS tags on the consensus map were successfully aligned through BLAST to the right chromosomes on the wheat reference genome sequence.

Conclusion

The consensus map should provide a useful basis for analyzing genome-wide variation of complex traits. The identified genes can then be explored as genetic markers to be used in genomic applications in wheat breeding.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1424-5) contains supplementary material, which is available to authorized users.     

Spiked GBS: a unified,open platform for single marker genotyping and whole-genome profiling

Background

In plant breeding, there are two primary applications for DNA markers in selection: 1) selection of known genes using a single marker assay (marker-assisted selection; MAS); and 2) whole-genome profiling and prediction (genomic selection; GS). Typically, marker platforms have addressed only one of these objectives.

Results

We have developed spiked genotyping-by-sequencing (sGBS), which combines targeted amplicon sequencing with reduced representation genotyping-by-sequencing. To minimize the cost of targeted assays, we utilize a small percent of sequencing capacity available in runs of GBS libraries to “spike” amplified targets of a priori alleles tagged with a different set of unique barcodes. This open platform allows multiple, single-target loci to be assayed while simultaneously generating a whole-genome profile. This dual-genotyping approach allows different sets of samples to be evaluated for single markers or whole genome-profiling. Here, we report the application of sGBS on a winter wheat panel that was screened for converted KASP markers and newly-designed markers targeting known polymorphisms in the leaf rust resistance gene Lr34.

Conclusions

The flexibility and low-cost of sGBS will enable a range of applications across genetics research. Specifically in breeding applications, the sGBS approach will allow breeders to obtain a whole-genome profile of important individuals while simultaneously targeting specific genes for a range of selection strategies across the breeding program.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1404-9) contains supplementary material, which is available to authorized users.