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Cowpea (Vigna unguiculata [L.] Walp., diploid, 2 n = 22) is a major crop used as a protein source for human consumption as well as a quality feed for livestock. It is drought and heat tolerant and has been bred to develop varieties that are resilient to changing climates. Plant adaptation to new climates and their yield are strongly affected by flowering time. Therefore, understanding the genetic basis of flowering time is critical to advance cowpea breeding. The aim of this study was to perform genome-wide association studies (GWAS) to identify marker trait associations for flowering time in cowpea using single nucleotide polymorphism (SNP) markers. A total of 368 accessions from a cowpea mini-core collection were evaluated in Ft. Collins, CO in 2019 and 2020, and 292 accessions were evaluated in Citra, FL in 2018. These accessions were genotyped using the Cowpea iSelect Consortium Array that contained 51,128 SNPs. GWAS revealed seven reliable SNPs for flowering time that explained 8–12% of the phenotypic variance. Candidate genes including FT , GI , CRY2 , LSH3 , UGT87A2 , LIF2 , and HTA9 that are associated with flowering time were identified for the significant SNP markers. Further efforts to validate these loci will help to understand their role in flowering time in cowpea, and it could facilitate the transfer of some of this knowledge to other closely related legume species. [ABSTRACT FROM AUTHOR]

Enabled by the next generation sequencing, target enrichment sequencing (TES) is a powerful method to enrich genomic regions of interest and to identify sequence variations. The objective of this study was to explore the feasibility of probe design from transcript sequences for TES application in calling sequence variants in peanut, an important allotetraploid crop with a large genome size. In this study, we applied an in-solution hybridization method to enrich DNA sequences of seven peanut genotypes. Our results showed that it is feasible to apply TES with probes designed from transcript sequences in polyploid peanut. Using a set of 31,123 probes, a total of 5131 and 7521 genes were targeted in peanut A and B genomes, respectively. For each genotype used in this study, the probe target capture regions were efficiently covered with high depth. The average on-target rate of sequencing reads was 42.47%, with a significant amount of off-target reads coming from genomic regions homologous to target regions. In this study, when given predefined genomic regions of interest and the same amount of sequencing data, TES provided the highest coverage of target regions when compared to whole genome sequencing, RNA sequencing, and genotyping by sequencing. Single nucleotide polymorphism (SNP) calling and subsequent validation revealed a high validation rate (85.71%) of homozygous SNPs, providing valuable markers for peanut genotyping. This study demonstrated the success of applying TES for SNP identification in peanut, which shall provide valuable suggestions for TES application in other non-model species without a genome reference available. [ABSTRACT FROM AUTHOR]

Background: Sugarcane (Saccharum spp.) is one of the most important economic crops because of its high sugar production and biofuel potential. Due to the high polyploid level and complex genome of sugarcane, it has been a huge challenge to investigate genomic sequence variations, which are critical for identifying alleles contributing to important agronomic traits. In order to mine the genetic variations in sugarcane, genotyping by sequencing (GBS), was used to genotype 14 representative Saccharum complex accessions. GBS is a method to generate a large number of markers, enabled by next generation sequencing (NGS) and the genome complexity reduction using restriction enzymes. Results: To use GBS for high throughput genotyping highly polyploid sugarcane, the GBS analysis pipelines in 14 Saccharum complex accessions were established by evaluating different alignment methods, sequence variants callers, and sequence depth for single nucleotide polymorphism (SNP) filtering. By using the established pipeline, a total of 76,251 non-redundant SNPs, 5642 InDels, 6380 presence/absence variants (PAVs), and 826 copy number variations (CNVs) were detected among the 14 accessions. In addition, non-reference based universal network enabled analysis kit and Stacks de novo called 34,353 and 109,043 SNPs, respectively. In the 14 accessions, the percentages of single dose SNPs ranged from 38.3% to 62.3% with an average of 49.6%, much more than the portions of multiple dosage SNPs. Concordantly called SNPs were used to evaluate the phylogenetic relationship among the 14 accessions. The results showed that the divergence time between the Erianthus genus and the Saccharum genus was more than 10 million years ago (MYA). The Saccharum species separated from their common ancestors ranging from 0.19 to 1.65 MYA. Conclusions: The GBS pipelines including the reference sequences, alignment methods, sequence variant callers, and sequence depth were recommended and discussed for the Saccharum complex and other related species. A large number of sequence variations were discovered in the Saccharum complex, including SNPs, InDels, PAVs, and CNVs. Genome-wide SNPs were further used to illustrate sequence features of polyploid species and demonstrated the divergence of different species in the Saccharum complex. The results of this study showed that GBS was an effective NGS-based method to discover genomic sequence variations in highly polyploid and heterozygous species. [ABSTRACT FROM AUTHOR]