Genotyping-by-Sequencing on Pooled Samples and its Use in Measuring Segregation Bias during the Course of Androgenesis in Barley

Genome-wide family prediction unveils molecular mechanisms underlying the regulation of agronomic traits in Urochloa ruziziensis

Tropical forage grasses, particularly those belonging to the Urochloa genus, play a crucial role in cattle production and serve as the main food source for animals in tropical and subtropical regions. The majority of these species are apomictic and tetraploid, highlighting the significance of U. ruziziensis, a sexual diploid species that can be tetraploidized for use in interspecific crosses with apomictic species. As a means to support breeding programs, our study investigates the feasibility of genome-wide family prediction in U. ruziziensis families to predict agronomic traits. Fifty half-sibling families were assessed for green matter yield, dry matter yield, regrowth capacity, leaf dry matter, and stem dry matter across different clippings established in contrasting seasons with varying available water capacity. Genotyping was performed using a genotyping-by-sequencing approach based on DNA samples from family pools. In addition to conventional genomic prediction methods, machine learning and feature selection algorithms were employed to reduce the necessary number of markers for prediction and enhance predictive accuracy across phenotypes. To explore the regulation of agronomic traits, our study evaluated the significance of selected markers for prediction using a tree-based approach, potentially linking these regions to quantitative trait loci (QTLs). In a multiomic approach, genes from the species transcriptome were mapped and correlated to those markers. A gene coexpression network was modeled with gene expression estimates from a diverse set of U. ruziziensis genotypes, enabling a comprehensive investigation of molecular mechanisms associated with these regions. The heritabilities of the evaluated traits ranged from 0.44 to 0.92. A total of 28,106 filtered SNPs were used to predict phenotypic measurements, achieving a mean predictive ability of 0.762. By employing feature selection techniques, we could reduce the dimensionality of SNP datasets, revealing potential genotype-phenotype associations. The functional annotation of genes near these markers revealed associations with auxin transport and biosynthesis of lignin, flavonol, and folic acid. Further exploration with the gene coexpression network uncovered associations with DNA metabolism, stress response, and circadian rhythm. These genes and regions represent important targets for expanding our understanding of the metabolic regulation of agronomic traits and offer valuable insights applicable to species breeding. Our work represents an innovative contribution to molecular breeding techniques for tropical forages, presenting a viable marker-assisted breeding approach and identifying target regions for future molecular studies on these agronomic traits.

Testing a candidate meiotic drive locus identified by pool sequencing

Meiotic drive biases the transmission of alleles in heterozygous individuals, such that Mendel's law of equal segregation is violated. Most examples of meiotic drive have been discovered over the past century based on causing sex ratio distortion or the biased transmission of easily scoreable genetic markers that were linked to drive alleles. More recently, several approaches have been developed that attempt to identify distortions of Mendelian segregation genome wide. Here, we test a candidate female meiotic drive locus in Drosophila melanogaster, identified previously as causing a ∼54:46 distortion ratio using sequencing of large pools of backcross progeny. We inserted fluorescent visible markers near the candidate locus and scored transmission in thousands of individual progeny. We observed a small but significant deviation from the Mendelian expectation; however, it was in the opposite direction to that predicted based on the original experiments. We discuss several possible causes of the discrepancy between the 2 approaches, noting that subtle viability effects are particularly challenging to disentangle from potential small-effect meiotic drive loci. We conclude that pool sequencing approaches remain a powerful method to identify candidate meiotic drive loci but that genotyping of individual progeny at early developmental stages may be required for robust confirmation.

Genetic composition and diversity of Arabica coffee in the crop's center of origin and its impact on four major fungal diseases

Conventional wisdom states that genetic variation reduces disease levels in plant populations. Nevertheless, crop species have been subject to a gradual loss of genetic variation through selection for specific traits during breeding, thereby increasing their vulnerability to biotic stresses such as pathogens. We explored how genetic variation in Arabica coffee sites in southwestern Ethiopia was related to the incidence of four major fungal diseases. Sixty sites were selected along a gradient of management intensity, ranging from nearly wild to intensively managed coffee stands. We used genotyping-by-sequencing of pooled leaf samples (pool-GBS) derived from 16 individual coffee shrubs in each of the sixty sites to assess the variation in genetic composition (multivariate: reference allele frequency) and genetic diversity (univariate: mean expected heterozygosity) between sites. We found that genetic composition had a clear spatial pattern and that genetic diversity was higher in less managed sites. The incidence of the four fungal diseases was related to the genetic composition of the coffee stands, but in a specific way for each disease. In contrast, genetic diversity was only related to the within-site variation of coffee berry disease, but not to the mean incidence of any of the four diseases across sites. Given that fungal diseases are major challenges of Arabica coffee in its native range, our findings that genetic composition of coffee sites impacted the major fungal diseases may serve as baseline information to study the molecular basis of disease resistance in coffee. Overall, our study illustrates the need to consider both host genetic composition and genetic diversity when investigating the genetic basis for variation in disease levels.

High-throughput estimation of allele frequencies using combined pooled-population sequencing and haplotype-based data processing

BACKGROUND

In addition to heterogeneity and artificial selection, natural selection is one of the forces used to combat climate change and improve agrobiodiversity in evolutionary plant breeding. Accurate identification of the specific genomic effects of natural selection will likely accelerate transfer between populations. Thus, insights into changes in allele frequency, adequate population size, gene flow and drift are essential. However, observing such effects often involves a trade-off between costs and resolution when a large sample of genotypes for many loci is analysed. Pool genotyping approaches achieve high resolution and precision in estimating allele frequency when sequence coverage is high. Nevertheless, high-coverage pool sequencing of large genomes is expensive.

RESULTS

Three pool samples (n = 300, 300, 288) from a barley backcross population were generated to assess the population's allele frequency. The tested population (BC2F21) has undergone 18 generations of natural adaption to conventional farming practice. The accuracies of estimated pool-based allele frequencies and genome coverage yields were compared using three next-generation sequencing genotyping methods. To achieve accurate allele frequency estimates with low sequence coverage, we employed a haplotyping approach. Low coverage allele frequencies of closely located single polymorphisms were aggregated into a single haplotype allele frequency, yielding 2-to-271-times higher depth and increased precision. When we combined different haplotyping tactics, we found that gene and chip marker-based haplotype analyses performed equivalently or better compared with simple contig haplotype windows. Comparing multiple pool samples and referencing against an individual sequencing approach revealed that whole-genome pool re-sequencing (WGS) achieved the highest correlation with individual genotyping (≥ 0.97). In contrast, transcriptome-based genotyping (MACE) and genotyping by sequencing (GBS) pool replicates were significantly associated with higher error rates and lower correlations, but are still valuable to detect large allele frequency variations.

CONCLUSIONS

The proposed strategy identified the allele frequency of populations with high accuracy at low cost. This is particularly relevant to evolutionary plant breeding of crops with very large genomes, such as barley. Whole-genome low coverage re-sequencing at 0.03 × coverage per genotype accurately estimated the allele frequency when a loci-based haplotyping approach was applied. The implementation of annotated haplotypes capitalises on the biological background and statistical robustness.

Genetic characterization of carrot root shape and size using genome-wide association analysis and genomic-estimated breeding values

The principal phenotypic determinants of market class in carrot-the size and shape of the root-are under primarily additive, but also highly polygenic, genetic control. The size and shape of carrot roots are the primary determinants not only of yield, but also market class. These quantitative phenotypes have historically been challenging to objectively evaluate, and thus subjective visual assessment of market class remains the primary method by which selection for these traits is performed. However, advancements in digital image analysis have recently made possible the high-throughput quantification of size and shape attributes. It is therefore now feasible to utilize modern methods of genetic analysis to investigate the genetic control of root morphology. To this end, this study utilized both genome wide association analysis (GWAS) and genomic-estimated breeding values (GEBVs) and demonstrated that the components of market class are highly polygenic traits, likely under the influence of many small effect QTL. Relatively large proportions of additive genetic variance for many of the component phenotypes support high predictive ability of GEBVs; average prediction ability across underlying market class traits was 0.67. GWAS identified multiple QTL for four of the phenotypes which compose market class: length, aspect ratio, maximum width, and root fill, a previously uncharacterized trait which represents the size-independent portion of carrot root shape. By combining digital image analysis with GWAS and GEBVs, this study represents a novel advance in our understanding of the genetic control of market class in carrot. The immediate practical utility and viability of genomic selection for carrot market class is also described, and concrete guidelines for the design of training populations are provided.

Generation of Doubled Haploid Barley by Interspecific Pollination with Hordeum bulbosum

The generation of doubled haploid barley plants by means of the so-called "Bulbosum" method has been practiced for meanwhile five decades. It rests upon the pollination of barley by its wild relative Hordeum bulbosum. This can result in the formation of hybrid embryos whose further development is typically associated with the loss of the pollinator's chromosomes. In recent years, this principle has, however, only rarely been used owing to the availability of efficient methods of anther and microspore culture. On the other hand, immature pollen-derived embryogenesis is to some extent prone to segregation bias in the resultant populations of haploids, which is due to its genotype dependency. Therefore, the principle of uniparental genome elimination has more recently regained increasing interest within the plant research and breeding community. The development of the present protocol relied on the use of the spring-type barley cultivar Golden Promise. The protocol is the result of a series of comparative experiments, which have addressed various methodological facets. The most influential ones included the method of emasculation, the temperature at flowering and early embryo development, the method, point in time and concentration of auxin administration for the stimulation of caryopsis development, the developmental stage at embryo dissection, as well as the nutrient medium used for embryo rescue. The present protocol allows the production of haploid barley plants at an efficiency of ca. 25% of the pollinated florets.

Optimizing sampling design and sequencing strategy for the genomic analysis of quantitative traits in natural populations

Mapping the genes underlying ecologically relevant traits in natural populations is fundamental to develop a molecular understanding of species adaptation. Current sequencing technologies enable the characterization of a species' genetic diversity across the landscape or even over its whole range. The relevant capture of the genetic diversity across the landscape is critical for a successful genetic mapping of traits and there are no clear guidelines on how to achieve an optimal sampling and which sequencing strategy to implement. Here we determine, through simulation, the sampling scheme that maximizes the power to map the genetic basis of a complex trait in an outbreeding species across an idealized landscape and draw genomic predictions for the trait, comparing individual and pool sequencing strategies. Our results show that quantitative trait locus detection power and prediction accuracy are higher when more populations over the landscape are sampled and this is more cost-effectively done with pool sequencing than with individual sequencing. Additionally, we recommend sampling populations from areas of high genetic diversity. As progress in sequencing enables the integration of trait-based functional ecology into landscape genomics studies, these findings will guide study designs allowing direct measures of genetic effects in natural populations across the environment.

Comparing Pool-seq, Rapture, and GBS genotyping for inferring weak population structure: The American lobster (Homarus americanus) as a case study

Unraveling genetic population structure is challenging in species potentially characterized by large population size and high dispersal rates, often resulting in weak genetic differentiation. Genotyping a large number of samples can improve the detection of subtle genetic structure, but this may substantially increase sequencing cost and downstream bioinformatics computational time. To overcome this challenge, alternative, cost-effective sequencing approaches, namely Pool-seq and Rapture, have been developed. We empirically measured the power of resolution and congruence of these two methods in documenting weak population structure in nonmodel species with high gene flow comparatively to a conventional genotyping-by-sequencing (GBS) approach. For this, we used the American lobster (Homarus americanus) as a case study. First, we found that GBS, Rapture, and Pool-seq approaches gave similar allele frequency estimates (i.e., correlation coefficient over 0.90) and all three revealed the same weak pattern of population structure. Yet, Pool-seq data showed F ST estimates three to five times higher than GBS and Rapture, while the latter two methods returned similar F ST estimates, indicating that individual-based approaches provided more congruent results than Pool-seq. We conclude that despite higher costs, GBS and Rapture are more convenient approaches to use in the case of species exhibiting very weak differentiation. While both GBS and Rapture approaches provided similar results with regard to estimates of population genetic parameters, GBS remains more cost-effective in project involving a relatively small numbers of genotyped individuals (e.g., <1,000). Overall, this study illustrates the complexity of estimating genetic differentiation and other summary statistics in complex biological systems characterized by large population size and migration rates.

Transmission ratio distortion is frequent in Arabidopsis thaliana controlled crosses

The equal probability of transmission of alleles from either parent during sexual reproduction is a central tenet of genetics and evolutionary biology. Yet, there are many cases where this rule is violated. The preferential transmission of alleles or genotypes is termed transmission ratio distortion (TRD). Examples of TRD have been identified in many species, implying that they are universal, but the resolution of species-wide studies of TRD are limited. We have performed a species-wide screen for TRD in over 500 segregating F2 populations of Arabidopsis thaliana using pooled reduced-representation genome sequencing. TRD was evident in up to a quarter of surveyed populations. Most populations exhibited distortion at only one genomic region, with some regions being repeatedly affected in multiple populations. Our results begin to elucidate the species-level architecture of biased transmission of genetic material in A. thaliana, and serve as a springboard for future studies into the biological basis of TRD in this species.

Temporal changes in genetic diversity and forage yield of perennial ryegrass in monoculture and in combination with red clover in swards

Agricultural grasslands are often cultivated as mixtures of grasses and legumes, and an extensive body of literature is available regarding interspecific interactions, and how these relate to yield and agronomic performance. However, knowledge of the impact of intraspecific diversity on grassland functioning is scarce. We investigated these effects during a 4-year field trial established with perennial ryegrass (Lolium perenne) and red clover (Trifolium pratense). We simulated different levels of intraspecific functional diversity by sowing single cultivars or by combining cultivars with contrasting growth habits, in monospecific or bispecific settings (i.e. perennial ryegrass whether or not in combination with red clover). Replicate field plots were established for seven seed compositions. We determined yield parameters and monitored differences in genetic diversity in the ryegrass component among seed compositions, and temporal changes in the genetic composition and genetic diversity at the within plot level. The composition of cultivars of both species affected the yield and species abundance. In general, the presence of clover had a positive effect on the yield. The cultivar composition of the ryegrass component had a significant effect on the yield, both in monoculture, and in combination with clover. For the genetic analyses, we validated empirically that genotyping-by-sequencing of pooled samples (pool-GBS) is a suitable method for accurate measurement of population allele frequencies, and obtained a dataset of 22,324 SNPs with complete data. We present a method to investigate the temporal dynamics of cultivars in seed mixtures grown under field conditions, and show how cultivar abundances vary during subsequent years. We screened the SNP panel for outlier loci, putatively under selection during the cultivation period, but none were detected.

Adaptive selection of founder segments and epistatic control of plant height in the MAGIC winter wheat population WM-800

BACKGROUND

Multi-parent advanced generation intercross (MAGIC) populations are a newly established tool to dissect quantitative traits. We developed the high resolution MAGIC wheat population WM-800, consisting of 910 F4:6 lines derived from intercrossing eight recently released European winter wheat cultivars.

RESULTS

Genotyping WM-800 with 7849 SNPs revealed a low mean genetic similarity of 59.7% between MAGIC lines. WM-800 harbours distinct genomic regions exposed to segregation distortion. These are mainly located on chromosomes 2 to 6 of the wheat B genome where founder specific DNA segments were positively or negatively selected. This suggests adaptive selection of individual founder alleles during population development. The application of a genome-wide association study identified 14 quantitative trait loci (QTL) controlling plant height in WM-800, including the known semi-dwarf genes Rht-B1 and Rht-D1 and a potentially novel QTL on chromosome 5A. Additionally, epistatic effects controlled plant height. For example, two loci on chromosomes 2B and 7B gave rise to an additive epistatic effect of 13.7 cm.

CONCLUSION

The present study demonstrates that plant height in the MAGIC-WHEAT population WM-800 is mainly determined by large-effect QTL and di-genic epistatic interactions. As a proof of concept, our study confirms that WM-800 is a valuable tool to dissect the genetic architecture of important agronomic traits.

An efficient pipeline to generate data for studies in plastid population genomics and phylogeography

PREMISE OF THE STUDY

Seed dispersal contributes to gene flow and is responsible for colonization of new sites and range expansion. Sequencing chloroplast haplotypes offers a way to estimate contributions of seed dispersal to population genetic structure and enables studies of population history. Whole-genome sequencing is expensive, but resources can be conserved by pooling samples. Unfortunately, haplotype associations among single-nucleotide polymorphisms (SNPs) are lost in pooled samples, and treating SNP allele frequencies as independent markers provides biased estimates of genetic structure.

METHODS

We developed sampling methodologies and an application, CallHap, that uses a least-squares algorithm to evaluate the fit between observed and predicted SNP allele frequencies from pooled samples based on haplotype network phylogeny structure, thus enabling pooling for chloroplast sequencing for large-scale studies of chloroplast genomic variation. This method was tested using artificially constructed test networks and pools, and pooled samples of Lasthenia californica (California goldfields) from southern Oregon, USA.

RESULTS

CallHap reliably recovered network topologies and haplotype frequencies from pooled samples.

DISCUSSION

The CallHap pipeline allows for the efficient use of resources for estimation of genetic structure for studies using nonrecombining haplotypes such as intraspecific variation in chloroplast, mitochondrial, bacterial, or viral DNA.

Sequencing of Single Pollen Nuclei Reveals Meiotic Recombination Events at Megabase Resolution and Circumvents Segregation Distortion Caused by Postmeiotic Processes

Meiotic recombination is a fundamental mechanism to generate novel allelic combinations which can be harnessed by breeders to achieve crop improvement. The recombination landscape of many crop species, including the major crop barley, is characterized by a dearth of recombination in 65% of the genome. In addition, segregation distortion caused by selection on genetically linked loci is a frequent and undesirable phenomenon in double haploid populations which hampers genetic mapping and breeding. Here, we present an approach to directly investigate recombination at the DNA sequence level by combining flow-sorting of haploid pollen nuclei of barley with single-cell genome sequencing. We confirm the skewed distribution of recombination events toward distal chromosomal regions at megabase resolution and show that segregation distortion is almost absent if directly measured in pollen. Furthermore, we show a bimodal distribution of inter-crossover distances, which supports the existence of two classes of crossovers which are sensitive or less sensitive to physical interference. We conclude that single pollen nuclei sequencing is an approach capable of revealing recombination patterns in the absence of segregation distortion.

Extent and overlap of segregation distortion regions in 12 barley crosses determined via a Pool-GBS approach

Extent and overlap of segregation distortion regions in 12 barley crosses determined via a Pool-GBS approach. Segregation distortion is undesirable as it alters the frequency of alleles and can reduce the chances of obtaining a particular combination of alleles. In this work, we have used a pooled genotyping-by-sequencing (Pool-GBS) approach to estimate allelic frequencies and used it to examine segregation distortion in 12 segregating populations of barley derived from androgenesis. Thanks to the extensive genome-wide SNP coverage achieved (between 674 and 1744 markers), we determined that the proportion of distorted markers averaged 28.9 % while 25.3 % of the genetic map fell within segregation distortion regions (SDRs). These SDRs were characterized and identified based on the position of the marker showing the largest distortion and the span of each SDR. Summed across all 12 crosses, 36 different SDR peaks could be distinguished from a total of 50 SDRs and a majority of these SDRs (27 of 36) were observed in only one population. While most shared SDRs were common to only two crosses, two SDRs (SDR3.1 and SDR4.2) were exceptionally recurrent (seen in five and four crosses, respectively). Because of the broad span of most SDRs, an average of 30 % of crosses showed segregation distortion in any given chromosomal segment. In reciprocal crosses, although some SDRs were clearly shared, others were unique to a single direction. In summary, segregation distortion is highly variable in its extent and the number of loci underpinning these distortions seems to be quite large even in a narrow germplasm such as six-row spring barley.