A k-mer-based bulked segregant analysis approach to map seed traits in unphased heterozygous potato genomes

High-throughput sequencing-based methods for bulked segregant analysis (BSA) allow for the rapid identification of genetic markers associated with traits of interest. BSA studies have successfully identified qualitative (binary) and quantitative trait loci (QTLs) using QTL mapping. However, most require population structures that fit the models available and a reference genome. Instead, high-throughput short-read sequencing can be combined with BSA of k-mers (BSA-k-mer) to map traits that appear refractory to standard approaches. This method can be applied to any organism and is particularly useful for species with genomes diverged from the closest sequenced genome. It is also instrumental when dealing with highly heterozygous and potentially polyploid genomes without phased haplotype assemblies and for which a single haplotype can control a trait. Finally, it is flexible in terms of population structure. Here, we apply the BSA-k-mer method for the rapid identification of candidate regions related to seed spot and seed size in diploid potato. Using a mixture of F1 and F2 individuals from a cross between 2 highly heterozygous parents, candidate sequences were identified for each trait using the BSA-k-mer approach. Using parental reads, we were able to determine the parental origin of the loci. Finally, we mapped the identified k-mers to a closely related potato genome to validate the method and determine the genomic loci underlying these sequences. The location identified for the seed spot matches with previously identified loci associated with pigmentation in potato. The loci associated with seed size are novel. Both loci are relevant in future breeding toward true seeds in potato.

darrowii) Diploid Blueberry Population

Blueberries (Vaccinium sect. Cyanococcus) are a dietary source of phenolic acids, including chlorogenic acid (CGA) and related compounds such as acetylated caffeoylquinic acid (ACQA) and caffeoylarbutin (CA). These compounds are known to be potent antioxidants with potential health benefits. While the chemistry of these compounds has been extensively studied, the genetic analysis has lagged behind. Understanding the genetic basis for traits with potential health implications may be of great use in plant breeding. By characterizing genetic variation related to fruit chemistry, breeders can make more efficient use of plant diversity to develop new cultivars with higher concentrations of these potentially beneficial compounds. Using a large interspecific F1 population, developed from a cross between the temperate V. corymbosum var. ceasariense and the subtropical V. darrowii, with 1025 individuals genotyped using genotype-by-sequencing methods, of which 289 were phenotyped for phenolic acid content, with data collected across 2019 and 2020, we have identified loci associated with phenolic acid content. Loci for the compounds clustered on the proximal arm of Vc02, suggesting that a single gene or several closely associated genes are responsible for the biosynthesis of all four tested compounds. Within this region are multiple gene models similar to hydroxycinnamoyl CoA shikimate/quinate hydroxycinnamoyltransferase (HCT) and UDP glucose:cinnamate glucosyl transferase (UGCT), genes known to be involved in the CGA biosynthesis pathway. Additional loci on Vc07 and Vc12 were associated with caffeoylarbutin content, suggesting a more complicated biosynthesis of that compound.

Pleiotropy or linkage? Their relative contributions to the genetic correlation of quantitative traits and detection by multitrait GWA studies

Genetic correlations between traits may cause correlated responses to selection. Previous models described the conditions under which genetic correlations are expected to be maintained. Selection, mutation, and migration are all proposed to affect genetic correlations, regardless of whether the underlying genetic architecture consists of pleiotropic or tightly linked loci affecting the traits. Here, we investigate the conditions under which pleiotropy and linkage have different effects on the genetic correlations between traits by explicitly modeling multiple genetic architectures to look at the effects of selection strength, degree of correlational selection, mutation rate, mutational variance, recombination rate, and migration rate. We show that at mutation-selection(-migration) balance, mutation rates differentially affect the equilibrium levels of genetic correlation when architectures are composed of pairs of physically linked loci compared to architectures of pleiotropic loci. Even when there is perfect linkage (no recombination within pairs of linked loci), a lower genetic correlation is maintained than with pleiotropy, with a lower mutation rate leading to a larger decrease. These results imply that the detection of causal loci in multitrait association studies will be affected by the type of underlying architectures, whereby pleiotropic variants are more likely to be underlying multiple detected associations. We also confirm that tighter linkage between nonpleiotropic causal loci maintains higher genetic correlations at the traits and leads to a greater proportion of false positives in association analyses.

Drosophila sechellia: A Genetic Model for Behavioral Evolution and Neuroecology

Defining the mechanisms by which animals adapt to their ecological niche is an important problem bridging evolution, genetics, and neurobiology. We review the establishment of a powerful genetic model for comparative behavioral analysis and neuroecology, Drosophila sechellia. This island-endemic fly species is closely related to several cosmopolitan generalists, including Drosophila melanogaster, but has evolved extreme specialism, feeding and reproducing exclusively on the noni fruit of the tropical shrub Morinda citrifolia. We first describe the development and use of genetic approaches to facilitate genotype/phenotype associations in these drosophilids. Next, we survey the behavioral, physiological, and morphological adaptations of D. sechellia throughout its life cycle and outline our current understanding of the genetic and cellular basis of these traits. Finally, we discuss the principles this knowledge begins to establish in the context of host specialization, speciation, and the neurobiology of behavioral evolution and consider open questions and challenges in the field.

Phylogenetic Community Structure and Niche Differentiation in Termites of the Tropical Dry Forests of Colombia

The mechanisms that structure species communities are still debated. We addressed this question for termite assemblages from tropical dry forests in Colombia. These forests are endangered and poorly understood ecosystems and termites are important ecosystem engineers in the tropics. Using biodiversity and environmental data, combined with phylogenetic community analyses, trait mapping, and stable isotopes studies, we investigated the termite community composition of three protected dry forests in Colombia. Our data suggest that the structuring mechanisms differed between sites. Phylogenetic overdispersion of termite assemblages correlated with decreasing rainfall and elevation and increasing temperature. Food niche traits-classified as feeding groups and quantified by δ¹⁵N‰ and δ¹³C‰ isotope signatures-were phylogenetically conserved. Hence, the overdispersion pattern implies increasing interspecific competition with decreasing drier and warmer conditions, which is also supported by fewer species occurring at the driest site. Our results are in line with a hypothesis that decreased biomass production limits resource availability for termites, which leads to competition. Along with this comes a diet shift: termites from drier plots had higher δ¹³C signatures, reflecting higher δ¹³C values in the litter and more C4 plants. Our study shows how a phylogenetic community approach combined with trait analyses can contribute to gaining the first insights into mechanisms structuring whole termite assemblages.

Vasopressin and the Neurogenetics of Parental Care

Making robust connections between genetic variation, neurophysiology, and social behavior remains a challenge. A study by Bendesky et al. (2017) tackles this challenge by dissecting the genetic architecture of parental care in deer mice to discover an important contribution of vasopressin signaling to the evolution of nest building.

Genetic Mapping and Biochemical Basis of Yellow Feather Pigmentation in Budgerigars

Parrot feathers contain red, orange, and yellow polyene pigments called psittacofulvins. Budgerigars are parrots that have been extensively bred for plumage traits during the last century, but the underlying genes are unknown. Here we use genome-wide association mapping and gene-expression analysis to map the Mendelian blue locus, which abolishes yellow pigmentation in the budgerigar. We find that the blue trait maps to a single amino acid substitution (R644W) in an uncharacterized polyketide synthase (MuPKS). When we expressed MuPKS heterologously in yeast, yellow pigments accumulated. Mass spectrometry confirmed that these yellow pigments match those found in feathers. The R644W substitution abolished MuPKS activity. Furthermore, gene-expression data from feathers of different bird species suggest that parrots acquired their colors through regulatory changes that drive high expression of MuPKS in feather epithelia. Our data also help formulate biochemical models that may explain natural color variation in parrots. VIDEO ABSTRACT.

QTL-seq approach identified genomic regions and diagnostic markers for rust and late leaf spot resistance in groundnut (Arachis hypogaea L.)

Rust and late leaf spot (LLS) are the two major foliar fungal diseases in groundnut, and their co-occurrence leads to significant yield loss in addition to the deterioration of fodder quality. To identify candidate genomic regions controlling resistance to rust and LLS, whole-genome resequencing (WGRS)-based approach referred as 'QTL-seq' was deployed. A total of 231.67 Gb raw and 192.10 Gb of clean sequence data were generated through WGRS of resistant parent and the resistant and susceptible bulks for rust and LLS. Sequence analysis of bulks for rust and LLS with reference-guided resistant parent assembly identified 3136 single-nucleotide polymorphisms (SNPs) for rust and 66 SNPs for LLS with the read depth of ≥7 in the identified genomic region on pseudomolecule A03. Detailed analysis identified 30 nonsynonymous SNPs affecting 25 candidate genes for rust resistance, while 14 intronic and three synonymous SNPs affecting nine candidate genes for LLS resistance. Subsequently, allele-specific diagnostic markers were identified for three SNPs for rust resistance and one SNP for LLS resistance. Genotyping of one RIL population (TAG 24 × GPBD 4) with these four diagnostic markers revealed higher phenotypic variation for these two diseases. These results suggest usefulness of QTL-seq approach in precise and rapid identification of candidate genomic regions and development of diagnostic markers for breeding applications.

Adapting Genotyping-by-Sequencing for Rice F2 Populations

Rapid and cost-effective genotyping of large mapping populations can be achieved by sequencing a reduced representation of the genome of every individual in a given population, and using that information to generate genetic markers. A customized genotyping-by-sequencing (GBS) pipeline was developed to genotype a rice F2 population from a cross of Oryza sativa ssp. japonica cv. Nipponbare and the African wild rice species O. longistaminata While most GBS pipelines aim to analyze mainly homozygous populations, we attempted to genotype a highly heterozygous F2 population. We show how species- and population-specific improvements of established protocols can drastically increase sample throughput and genotype quality. Using as few as 50,000 reads for some individuals (134,000 reads on average), we were able to generate up to 8154 informative SNP markers in 1081 F2 individuals. Additionally, the effects of enzyme choice, read coverage, and data postprocessing are evaluated. Using GBS-derived markers, we were able to assemble a genetic map of 1536 cM. To demonstrate the usefulness of our GBS pipeline, we determined quantitative trait loci (QTL) for the number of tillers. We were able to map four QTL to chromosomes 1, 3, 4, and 8, and partially confirm their effects using introgression lines. We provide an example of how to successfully use GBS with heterozygous F2 populations. By using the comparatively low-cost MiSeq platform, we show that the GBS method is flexible and cost-effective, even for smaller laboratories.

QTL-seq for rapid identification of candidate genes for 100-seed weight and root/total plant dry weight ratio under rainfed conditions in chickpea

Terminal drought is a major constraint to chickpea productivity. Two component traits responsible for reduction in yield under drought stress include reduction in seeds size and root length/root density. QTL-seq approach, therefore, was used to identify candidate genomic regions for 100-seed weight (100SDW) and total dry root weight to total plant dry weight ratio (RTR) under rainfed conditions. Genomewide SNP profiling of extreme phenotypic bulks from the ICC 4958 × ICC 1882 population identified two significant genomic regions, one on CaLG01 (1.08 Mb) and another on CaLG04 (2.7 Mb) linkage groups for 100SDW. Similarly, one significant genomic region on CaLG04 (1.10 Mb) was identified for RTR. Comprehensive analysis revealed four and five putative candidate genes associated with 100SDW and RTR, respectively. Subsequently, two genes (Ca_04364 and Ca_04607) for 100SDW and one gene (Ca_04586) for RTR were validated using CAPS/dCAPS markers. Identified candidate genomic regions and genes may be useful for molecular breeding for chickpea improvement.

Dissection of quantitative traits by bulk segregant mapping in a protoploid yeast species

Since more than a decade ago, Saccharomyces cerevisiae has been used as a model to dissect complex traits, revealing the genetic basis of a large number of traits in fine detail. However, to have a more global view of the genetic architecture of traits across species, the examination of the molecular basis of phenotypes within non-conventional species would undoubtedly be valuable. In this respect, the Saccharomycotina yeasts represent ideal and potential non-model organisms. Here we sought to assess the feasibility of genetic mapping by bulk segregant analysis in the protoploid Lachancea kluyveri (formerly S. kluyveri) yeast species, a distantly related species to S. cerevisiae For this purpose, we designed a fluorescent mating-type marker, compatible with any mating-competent strains representative of this species, to rapidly create a large population of haploid segregants (>10(5) cells). Quantitative trait loci can be mapped by selecting and sequencing an enriched pool of progeny with extreme phenotypic values. As a test bed, we applied this strategy and mapped the causal loci underlying halotolerance phenotypes in L. kluyveri Overall, this study demonstrates that bulk segregant mapping is a powerful way for investigating the genetic basis of natural variations in non-model yeast organisms and more precisely in L. kluyveri.

Emerging Genomic Tools for Legume Breeding: Current Status and Future Prospects

Legumes play a vital role in ensuring global nutritional food security and improving soil quality through nitrogen fixation. Accelerated higher genetic gains is required to meet the demand of ever increasing global population. In recent years, speedy developments have been witnessed in legume genomics due to advancements in next-generation sequencing (NGS) and high-throughput genotyping technologies. Reference genome sequences for many legume crops have been reported in the last 5 years. The availability of the draft genome sequences and re-sequencing of elite genotypes for several important legume crops have made it possible to identify structural variations at large scale. Availability of large-scale genomic resources and low-cost and high-throughput genotyping technologies are enhancing the efficiency and resolution of genetic mapping and marker-trait association studies. Most importantly, deployment of molecular breeding approaches has resulted in development of improved lines in some legume crops such as chickpea and groundnut. In order to support genomics-driven crop improvement at a fast pace, the deployment of breeder-friendly genomics and decision support tools seems appear to be critical in breeding programs in developing countries. This review provides an overview of emerging genomics and informatics tools/approaches that will be the key driving force for accelerating genomics-assisted breeding and ultimately ensuring nutritional and food security in developing countries.

Targeted sequence capture provides insight into genome structure and genetics of male sterility in a gynodioecious diploid strawberry, Fragaria vesca ssp. bracteata (Rosaceae)

Gynodioecy is a sexual system wherein females coexist with hermaphrodites. It is of interest not only because male-sterile plants are advantageous in plant breeding but also because it can be a crucial step in the evolutionary transition to entirely separate sexes (dioecy) from a hermaphroditic ancestor. The gynodioecious diploid wild strawberry, Fragaria vesca ssp. bracteata (Rosaceae), is a member of a clade with both dioecious and cultivated species, making it an ideal model in which to study the genetics of male sterility. To create a genetic map of F. v. ssp. bracteata, we identified informative polymorphisms from genomic sequencing (3−5x coverage) of two outbred plants from the same population. Using targeted enrichment, we sequenced 200 bp surrounding each of 6575 polymorphisms in 48 F1 offspring, yielding genotypes at 98% of targeted sites with mean coverage >100x, plus more than 600-kb high-coverage nontargeted sequence. With the resulting linkage map of 7802 stringently filtered markers (5417 targeted), we assessed recombination rates and genomic incongruities. Consistent with past work in strawberries, male sterility is dominant, segregates 1:1, and maps to a single location in the female. Further mapping an additional 55 offspring places male sterility in a gene-dense, 338-kb region of chromosome 4. The region is not syntenic with the sex-determining regions in the closely related octoploids, F. chiloensis and F. virginiana, suggesting either independent origins or translocation. The 57 genes in this region do not include protein families known to control male sterility and thus suggest alternate mechanisms for the suppression of male function.

Pigeonpea genomics initiative (PGI): an international effort to improve crop productivity of pigeonpea (Cajanus cajan L.)

Pigeonpea (Cajanus cajan), an important food legume crop in the semi-arid regions of the world and the second most important pulse crop in India, has an average crop productivity of 780 kg/ha. The relatively low crop yields may be attributed to non-availability of improved cultivars, poor crop husbandry and exposure to a number of biotic and abiotic stresses in pigeonpea growing regions. Narrow genetic diversity in cultivated germplasm has further hampered the effective utilization of conventional breeding as well as development and utilization of genomic tools, resulting in pigeonpea being often referred to as an 'orphan crop legume'. To enable genomics-assisted breeding in this crop, the pigeonpea genomics initiative (PGI) was initiated in late 2006 with funding from Indian Council of Agricultural Research under the umbrella of Indo-US agricultural knowledge initiative, which was further expanded with financial support from the US National Science Foundation's Plant Genome Research Program and the Generation Challenge Program. As a result of the PGI, the last 3 years have witnessed significant progress in development of both genetic as well as genomic resources in this crop through effective collaborations and coordination of genomics activities across several institutes and countries. For instance, 25 mapping populations segregating for a number of biotic and abiotic stresses have been developed or are under development. An 11X-genome coverage bacterial artificial chromosome (BAC) library comprising of 69,120 clones have been developed of which 50,000 clones were end sequenced to generate 87,590 BAC-end sequences (BESs). About 10,000 expressed sequence tags (ESTs) from Sanger sequencing and ca. 2 million short ESTs by 454/FLX sequencing have been generated. A variety of molecular markers have been developed from BESs, microsatellite or simple sequence repeat (SSR)-enriched libraries and mining of ESTs and genomic amplicon sequencing. Of about 21,000 SSRs identified, 6,698 SSRs are under analysis along with 670 orthologous genes using a GoldenGate SNP (single nucleotide polymorphism) genotyping platform, with large scale SNP discovery using Solexa, a next generation sequencing technology, is in progress. Similarly a diversity array technology array comprising of ca. 15,000 features has been developed. In addition, >600 unique nucleotide binding site (NBS) domain containing members of the NBS-leucine rich repeat disease resistance homologs were cloned in pigeonpea; 960 BACs containing these sequences were identified by filter hybridization, BES physical maps developed using high information content fingerprinting. To enrich the genomic resources further, sequenced soybean genome is being analyzed to establish the anchor points between pigeonpea and soybean genomes. In addition, Solexa sequencing is being used to explore the feasibility of generating whole genome sequence. In summary, the collaborative efforts of several research groups under the umbrella of PGI are making significant progress in improving molecular tools in pigeonpea and should significantly benefit pigeonpea genetics and breeding. As these efforts come to fruition, and expanded (depending on funding), pigeonpea would move from an 'orphan legume crop' to one where genomics-assisted breeding approaches for a sustainable crop improvement are routine.

Development of a genomic microsatellite library in perennial ryegrass (Lolium perenne) and its use in trait mapping

BACKGROUND AND AIMS

Perennial ryegrass (Lolium perenne) is one of the key forage and amenity grasses throughout the world. In the UK it accounts for 70 % of all agricultural land use with an estimated farm gate value of 6 billion pounds per annum. However, in terms of the genetic resources available, L. perenne has lagged behind other major crops in Poaceae. The aim of this project was therefore the construction of a microsatellite-enriched genomic library for L. perenne to increase the number of genetic markers available for both marker-assisted selection in breeding programmes and gene isolation.

METHODS

Primers for 229 non-redundant microsatellite markers were designed and used to screen two L. perenne genotypes, one amenity and one forage. Of the 229 microsatellites, 95 were found to show polymorphism between amenity and forage genotypes. A selection of microsatellite primers was selected from these 95 and used to screen two mapping populations derived from intercrossing and backcrossing the two forage and amenity grass genotypes.

KEY RESULTS AND CONCLUSIONS

The utility of the resulting genetic maps for analysis of the genetic control of target traits was demonstrated by the mapping of genes associated with heading date to linkage groups 4 and 7.