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Premise There is a general lack of consensus on the best practices for filtering of single‐nucleotide polymorphisms (SNPs) and whether it is better to use SNPs or include flanking regions (full “locus”) in phylogenomic analyses and subsequent comparative methods. Methods Using genotyping‐by‐sequencing data from 22 Glycine species, we assessed the effects of SNP vs. locus usage and SNP retention stringency. We compared branch length, node support, and divergence time estimation across 16 datasets with varying amounts of missing data and total size. Results Our results revealed five aspects of phylogenomic data usage that may be generally applicable: (1) tree topology is largely congruent across analyses; (2) filtering strictly for SNP retention (e.g., 90–100%) reduces support and can alter some inferred relationships; (3) absolute branch lengths vary by two orders of magnitude between SNP and locus datasets; (4) data type and branch length variation have little effect on divergence time estimation; and (5) phylograms alter the estimation of ancestral states and rates of morphological evolution. Discussion Using SNP or locus datasets does not alter phylogenetic inference significantly, unless researchers want or need to use absolute branch lengths. We recommend against using excessive filtering thresholds for SNP retention to reduce the risk of producing inconsistent topologies and generating low support.

Premise An informatics approach was used for the construction of an Axiom genotyping array from heterogeneous, high‐throughput sequence data to assess the complex genome of loblolly pine (Pinus taeda). Methods High‐throughput sequence data, sourced from exome capture and whole genome reduced‐representation approaches from 2698 trees across five sequence populations, were analyzed with the improved genome assembly and annotation for the loblolly pine. A variant detection, filtering, and probe design pipeline was developed to detect true variants across and within populations. From 8.27 million variants, a total of 642,275 were evaluated and 423,695 of those were screened across a range‐wide population. Results The final informatics and screening approach delivered an Axiom array representing 46,439 high‐confidence variants to the forest tree breeding and genetics community. Based on the annotated reference genome, 34% were located in or directly upstream or downstream of genic regions. Discussion The Pita50K array represents a genome‐wide resource developed from sequence data for an economically important conifer, loblolly pine. It uniquely integrates independent projects that assessed trees sampled across the native range. The challenges associated with the large and repetitive genome are addressed in the development of this resource.

Premise Detecting single‐nucleotide polymorphisms (SNPs) in a cost‐effective way is fundamental in any plant breeding pipeline. Here, we compare three genotyping techniques for their ability to reproduce the allele dosage of SNPs of interest in sugarcane (Saccharum spp.). Methods To identify a reproducible technique to estimate allele dosage for the validation of SNP markers, the correlation between Flex‐Seq, kompetitive allele‐specific PCR (KASP), and genotyping‐by‐sequencing and restriction site–associated DNA sequencing (GBS+RADseq) was determined for a set of 76 SNPs. To find alternative methodologies for allele dosage estimation, the KASP and Flex‐Seq techniques were compared for the same set of SNPs. For the three techniques, a population of 53 genotypes from the diverse sugarcane panel of the Centro de Investigación de la Caña de Azúcar (Cenicaña), Colombia, was selected. Results The average Pearson correlation coefficients between GBS+RADseq and Flex‐Seq, GBS+RADseq and KASP, and Flex‐Seq and KASP were 0.62 ± 0.27, 0.38 ± 0.27, and 0.38 ± 0.30, respectively. Discussion Flex‐Seq reproduced the allele dosages determined using GBS+RADseq with good levels of precision because of its depth of sequencing and ability to target specific positions in the genome. Additionally, Flex‐Seq outperformed KASP by allowing the conversion of a higher number of SNPs and a more accurate estimation of the allele dosage. Flex‐Seq has therefore become the genotyping methodology of choice for marker validation at Cenicaña. Resumen Premisa Detectar polimorfismos de un único nucleótido (SNP) de forma costo‐efectiva es fundamental en cualquier programa de mejoramiento genético. En este artículo nosotros comparamos tres técnicas de genotipado para medir su habilidad en reproducir las dosis alélicas de SNPs de interés en caña de azúcar (Saccharum spp.). Métodos Para identificar una técnica reproducible para la estimación de dosis alélicas durante los pasos de validación de marcadores, la correlación entre Flex‐Seq, kompetitive allele‐specific PCR (KASP), y genotyping‐by‐sequencing and restriction site–associated DNA sequencing (GBS+RADseq) fue determinada para un set de 76 SNPs. Para identificar metodologías alternativas en la estimación de las dosis alélicas, las tecnologías KASP y Flex‐Seq fueron comparadas para el mismo grupo de SNPs. Para las tres técnicas, una población de 53 genotipos fue seleccionados de la población diversa de caña de azúcar del Centro de Investigación de la Caña de Azúcar (Cenicaña), Colombia. Resultados El promedio del coeficiente de correlación de Pearson entre GBS+RADseq y Flex‐Seq, GBS+RADseq y KASP, y Flex‐Seq y KASP fue de 0.62 ± 0.27, 0.38 ± 0.27, y 0.38 ± 0.30, respectivamente. Discusión Flex‐Seq reprodujo las dosis alélicas determinadas usando GBS+RADseq con buenos niveles de precisión debido a su profundidad de secuenciación y habilidad de secuenciar posiciones especificas en el genoma. Adicionalmente, Flex‐Seq superó a KASP al permitir la conversión de un número mayor de SNPs y al estimar las dosis alélicas de forma más precisa. Flex‐Seq por tanto se convierte en la metodología de genotipado de elección para la validación de marcadores en Cenicaña.

Bacterial wilt (BW) disease, which is caused by Ralstonia solanacearum, is one globally prevalent plant disease leading to significant losses of crop production and yield with the involvement of a diverse variety of monocot and dicot host plants. In particular, the BW of the soil-borne disease seriously influences solanaceous crops, including peppers (sweet and chili peppers), paprika, tomatoes, potatoes, and eggplants. Recent studies have explored genetic regions that are associated with BW resistance for pepper crops. However, owing to the complexity of BW resistance, the identification of the genomic regions controlling BW resistance is poorly understood and still remains to be unraveled in the pepper cultivars. In this study, we performed the quantitative trait loci (QTL) analysis to identify genomic loci and alleles, which play a critical role in the resistance to BW in pepper plants. The disease symptoms and resistance levels for BW were assessed by inoculation with R. solanacearum. Genotyping-by-sequencing (GBS) was utilized in 94 F2 segregating populations originated from a cross between a resistant line, KC352, and a susceptible line, 14F6002-14. A total of 628,437 single-nucleotide polymorphism (SNP) was obtained, and a pepper genetic linkage map was constructed with putative 1550 SNP markers via the filtering criteria. The linkage map exhibited 16 linkage groups (LG) with a total linkage distance of 828.449 cM. Notably, QTL analysis with CIM (composite interval mapping) method uncovered pBWR-1 QTL underlying on chromosome 01 and explained 20.13 to 25.16% by R2 (proportion of explained phenotyphic variance by the QTL) values. These results will be valuable for developing SNP markers associated with BW-resistant QTLs as well as for developing elite BW-resistant cultivars in pepper breeding programs.

Marker-assisted selection (MAS) refers to the use of molecular markers to assist phenotypic selections in crop improvement. Several types of molecular markers, such as single nucleotide polymorphism (SNP), have been identified and effectively used in plant breeding. The application of next-generation sequencing (NGS) technologies has led to remarkable advances in whole genome sequencing, which provides ultra-throughput sequences to revolutionize plant genotyping and breeding. To further broaden NGS usages to large crop genomes such as maize and wheat, genotyping-by-sequencing (GBS) has been developed and applied in sequencing multiplexed samples that combine molecular marker discovery and genotyping. GBS is a novel application of NGS protocols for discovering and genotyping SNPs in crop genomes and populations. The GBS approach includes the digestion of genomic DNA with restriction enzymes followed by the ligation of barcode adapter, PCR amplification and sequencing of the amplified DNA pool on a single lane of flow cells. Bioinformatic pipelines are needed to analyze and interpret GBS datasets. As an ultimate MAS tool and a cost-effective technique, GBS has been successfully used in implementing genome-wide association study (GWAS), genomic diversity study, genetic linkage analysis, molecular marker discovery and genomic selection under a large scale of plant breeding programs.

There is a need to explore renewable alternatives (e.g., biofuels) that can produce energy sources to help reduce the reliance on fossil oils. In addition, the consumption of fossil oils adversely affects the environment and human health via the generation of waste water, greenhouse gases, and waste solids. , originated from southeastern Europe and southwestern Asia, is being re-embraced as an industrial oilseed crop due to its high seed oil content (36-47%) and high unsaturated fatty acid composition (>90%), which are suitable for jet fuel, biodiesel, high-value lubricants and animal feed. 's agronomic advantages include short time to maturation, low water and nutrient requirements, adaptability to adverse environmental conditions and resistance to common pests and pathogens. These characteristics make it an ideal crop for sustainable agricultural systems and regions of marginal land. However, the lack of genetic and genomic resources has slowed the enhancement of this emerging oilseed crop and exploration of its full agronomic and breeding potential. Here, a core of 213 spring accessions was collected and genotyped. The genotypic data was used to characterize genetic diversity and population structure to infer how natural selection and plant breeding may have affected the formation and differentiation within the natural populations, and how the genetic diversity of this species can be used in future breeding efforts. A total of 6,192 high-quality single nucleotide polymorphisms (SNPs) were identified using genotyping-by-sequencing (GBS) technology. The average polymorphism information content (PIC) value of 0.29 indicate moderate genetic diversity for the spring panel evaluated in this report. Population structure and principal coordinates analyses (PCoA) based on SNPs revealed two distinct subpopulations. Sub-population 1 (POP1) contains accessions that mainly originated from Germany while the majority of POP2 accessions (>75%) were collected from Eastern Europe. Analysis of molecular variance (AMOVA) identified 4% variance among and 96% variance within subpopulations, indicating a high gene exchange (or low genetic differentiation) between the two subpopulations. These findings provide important information for future allele/gene identification using genome-wide association studies (GWAS) and marker-assisted selection (MAS) to enhance genetic gain in breeding programs.

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.

Background Research on orphan crops is often hindered by a lack of genomic resources. With the advent of affordable sequencing technologies, genotyping an entire genome or, for large-genome species, a representative fraction of the genome has become feasible for any crop. Nevertheless, most genotyping-by-sequencing (GBS) methods are geared towards obtaining large numbers of markers at low sequence depth, which excludes their application in heterozygous individuals. Furthermore, bioinformatics pipelines often lack the flexibility to deal with paired-end reads or to be applied in polyploid species. Results UGbS-Flex combines publicly available software with in-house python and perl scripts to efficiently call SNPs from genotyping-by-sequencing reads irrespective of the species’ ploidy level, breeding system and availability of a reference genome. Noteworthy features of the UGbS-Flex pipeline are an ability to use paired-end reads as input, an effective approach to cluster reads across samples with enhanced outputs, and maximization of SNP calling. We demonstrate use of the pipeline for the identification of several thousand high-confidence SNPs with high representation across samples in an F 3 -derived F 2 population in the allotetraploid finger millet. Robust high-density genetic maps were constructed using the time-tested mapping program MAPMAKER which we upgraded to run efficiently and in a semi-automated manner in a Windows Command Prompt Environment. We exploited comparative GBS with one of the diploid ancestors of finger millet to assign linkage groups to subgenomes and demonstrate the presence of chromosomal rearrangements. Conclusions The paper combines GBS protocol modifications, a novel flexible GBS analysis pipeline, UGbS-Flex, recommendations to maximize SNP identification, updated genetic mapping software, and the first high-density maps of finger millet. The modules used in the UGbS-Flex pipeline and for genetic mapping were applied to finger millet, an allotetraploid selfing species without a reference genome, as a case study. The UGbS-Flex modules, which can be run independently, are easily transferable to species with other breeding systems or ploidy levels.

Background Common bean is an important staple crop in the tropics of Africa, Asia and the Americas. Particularly smallholder farmers rely on bean as a source for calories, protein and micronutrients. Drought is a major production constraint for common bean, a situation that will be aggravated with current climate change scenarios. In this context, new tools designed to understand the genetic basis governing the phenotypic responses to abiotic stress are required to improve transfer of desirable traits into cultivated beans. Results A multiparent advanced generation intercross (MAGIC) population of common bean was generated from eight Mesoamerican breeding lines representing the phenotypic and genotypic diversity of the CIAT Mesoamerican breeding program. This population was assessed under drought conditions in two field trials for yield, 100 seed weight, iron and zinc accumulation, phenology and pod harvest index. Transgressive segregation was observed for most of these traits. Yield was positively correlated with yield components and pod harvest index (PHI), and negative correlations were found with phenology traits and micromineral contents. Founder haplotypes in the population were identified using Genotyping by Sequencing (GBS). No major population structure was observed in the population. Whole Genome Sequencing (WGS) data from the founder lines was used to impute genotyping data for GWAS. Genetic mapping was carried out with two methods, using association mapping with GWAS, and linkage mapping with haplotype-based interval screening. Thirteen high confidence QTL were identified using both methods and several QTL hotspots were found controlling multiple traits. A major QTL hotspot located on chromosome Pv01 for phenology traits and yield was identified. Further hotspots affecting several traits were observed on chromosomes Pv03 and Pv08. A major QTL for seed Fe content was contributed by MIB778, the founder line with highest micromineral accumulation. Based on imputed WGS data, candidate genes are reported for the identified major QTL, and sequence changes were identified that could cause the phenotypic variation. Conclusions This work demonstrates the importance of this common bean MAGIC population for genetic mapping of agronomic traits, to identify trait associations for molecular breeding tool design and as a new genetic resource for the bean research community.

Background This article describes the development of Multi-parent Advanced Generation Inter-Cross populations (MAGIC) in rice and discusses potential applications for mapping quantitative trait loci (QTLs) and for rice varietal development. We have developed 4 multi-parent populations: indica MAGIC (8 indica parents); MAGIC plus (8 indica parents with two additional rounds of 8-way F1 inter-crossing); japonica MAGIC (8 japonica parents); and Global MAGIC (16 parents – 8 indica and 8 japonica ). The parents used in creating these populations are improved varieties with desirable traits for biotic and abiotic stress tolerance, yield, and grain quality. The purpose is to fine map QTLs for multiple traits and to directly and indirectly use the highly recombined lines in breeding programs. These MAGIC populations provide a useful germplasm resource with diverse allelic combinations to be exploited by the rice community. Results The indica MAGIC population is the most advanced of the MAGIC populations developed thus far and comprises 1328 lines produced by single seed descent (SSD). At the S4 stage of SSD a subset (200 lines) of this population was genotyped using a genotyping-by-sequencing (GBS) approach and was phenotyped for multiple traits, including: blast and bacterial blight resistance, salinity and submergence tolerance, and grain quality. Genome-wide association mapping identified several known major genes and QTLs including Sub1 associated with submergence tolerance and Xa4 and xa5 associated with resistance to bacterial blight. Moreover, the genome-wide association study (GWAS) results also identified potentially novel loci associated with essential traits for rice improvement. Conclusion The MAGIC populations serve a dual purpose: permanent mapping populations for precise QTL mapping and for direct and indirect use in variety development. Unlike a set of naturally diverse germplasm, this population is tailor-made for breeders with a combination of useful traits derived from multiple elite breeding lines. The MAGIC populations also present opportunities for studying the interactions of genome introgressions and chromosomal recombination.