Genome-Wide Haplotype Changes Produced by Artificial Selection during Modern Rice Breeding in Japan

During the last 90 years, the breeding of rice has delivered cultivars with improved agronomic and economic characteristics. Crossing of different lines and successive artificial selection of progeny based on their phenotypes have changed the chromosomal constitution of the ancestors of modern rice; however, the nature of these changes is unclear. The recent accumulation of data for genome-wide single-nucleotide polymorphisms (SNPs) in rice has allowed us to investigate the change in haplotype structure and composition. To assess the impact of these changes during modern breeding, we studied 177 Japanese rice accessions, which were categorized into three groups: landraces, improved cultivars developed from 1931 to 1974 (the early breeding phase), and improved cultivars developed from 1975 to 2005 (the late breeding phase). Phylogenetic tree and structure analysis indicated genetic differentiation between non-irrigated (upland) and irrigated (lowland) rice groups as well as genetic structuring within the irrigated rice group that corresponded to the existence of three subgroups. Pedigree analysis revealed that a limited number of landraces and cultivars was used for breeding at the beginning of the period of systematic breeding and that 11 landraces accounted for 70% of the ancestors of the modern improved cultivars. The values for linkage disequilibrium estimated from SNP alleles and the haplotype diversity determined from consecutive alleles in five-SNP windows indicated that haplotype blocks became less diverse over time as a result of the breeding process. A decrease in haplotype diversity, caused by a reduced number of polymorphisms in the haplotype blocks, was observed in several chromosomal regions. However, our results also indicate that new haplotype polymorphisms have been generated across the genome during the breeding process. These findings will facilitate our understanding of the association between particular haplotypes and desirable phenotypes in modern Japanese rice cultivars

Single-nucleotide polymorphism discovery by high-throughput sequencing in sorghum

<p>Abstract</p> <p>Background</p> <p>Eight diverse sorghum (<it>Sorghum bicolor </it>L. Moench) accessions were subjected to short-read genome sequencing to characterize the distribution of single-nucleotide polymorphisms (SNPs). Two strategies were used for DNA library preparation. Missing SNP genotype data were imputed by local haplotype comparison. The effect of library type and genomic diversity on SNP discovery and imputation are evaluated.</p> <p>Results</p> <p>Alignment of eight genome equivalents (6 Gb) to the public reference genome revealed 283,000 SNPs at ≥82% confirmation probability. Sequencing from libraries constructed to limit sequencing to start at defined restriction sites led to genotyping 10-fold more SNPs in all 8 accessions, and correctly imputing 11% more missing data, than from semirandom libraries. The SNP yield advantage of the reduced-representation method was less than expected, since up to one fifth of reads started at noncanonical restriction sites and up to one third of restriction sites predicted <it>in silico </it>to yield unique alignments were not sampled at near-saturation. For imputation accuracy, the availability of a genomically similar accession in the germplasm panel was more important than panel size or sequencing coverage.</p> <p>Conclusions</p> <p>A sequence quantity of 3 million 50-base reads per accession using a <it>Bsr</it>FI library would conservatively provide satisfactory genotyping of 96,000 sorghum SNPs. For most reliable SNP-genotype imputation in shallowly sequenced genomes, germplasm panels should consist of pairs or groups of genomically similar entries. These results may help in designing strategies for economical genotyping-by-sequencing of large numbers of plant accessions.</p

Development of a RAD-Seq Based DNA Polymorphism Identification Software, AgroMarker Finder, and Its Application in Rice Marker-Assisted Breeding

Abstract Rapid and accurate genome-wide marker detection is essential to the marker-assisted breeding and functional genomics studies. In this work, we developed an integrated software, AgroMarker Finder (AMF: http://erp.novelbio.com/AMF), for providing graphical user interface (GUI) to facilitate the recently developed restriction-site associated DNA (RAD) sequencing data analysis in rice. By application of AMF, a total of 90,743 high-quality markers (82,878 SNPs and 7,865 InDels) were detected between rice varieties JP69 and Jiaoyuan5A. The density of the identified markers is 0.2 per Kb for SNP markers, and 0.02 per Kb for InDel markers. Sequencing validation revealed that the accuracy of genome-wide marker detection by AMF is 93%. In addition, a validated subset of 82 SNPs and 31 InDels were found to be closely linked to 117 important agronomic trait genes, providing a basis for subsequent marker-assisted selection (MAS) and variety identification. Furthermore, we selected 12 markers from 31 validated InDel markers to identify seed authenticity of variety Jiaoyuanyou69, and we also identified 10 markers closely linked to the fragrant gene BADH2 to minimize linkage drag for Wuxiang075 (BADH2 donor)/Jiachang1 recombinants selection. Therefore, this software provides an efficient approach for marker identification from RAD-seq data, and it would be a valuable tool for plant MAS and variety protection

Identification of SNP and SSR Markers in Finger Millet Using Next Generation Sequencing Technologies

Finger millet is an important cereal crop in eastern Africa and southern India with excellent grain storage quality and unique ability to thrive in extreme environmental conditions. Since negligible attention has been paid to improving this crop to date, the current study used Next Generation Sequencing (NGS) technologies to develop both Simple Sequence Repeat (SSR) and Single Nucleotide Polymorphism (SNP) markers. Genomic DNA from cultivated finger millet genotypes KNE755 and KNE796 was sequenced using both Roche 454 and Illumina technologies. Non-organelle sequencing reads were assembled into 207 Mbp representing approximately 13% of the finger millet genome. We identified 10,327 SSRs and 23,285 non-homeologous SNPs and tested 101 of each for polymorphism across a diverse set of wild and cultivated finger millet germplasm. For the 49 polymorphic SSRs, the mean polymorphism information content (PIC) was 0.42, ranging from 0.16 to 0.77. We also validated 92 SNP markers, 80 of which were polymorphic with a mean PIC of 0.29 across 30 wild and 59 cultivated accessions. Seventy-six of the 80 SNPs were polymorphic across 30 wild germplasm with a mean PIC of 0.30 while only 22 of the SNP markers showed polymorphism among the 59 cultivated accessions with an average PIC value of 0.15. Genetic diversity analysis using the polymorphic SNP markers revealed two major clusters; one of wild and another of cultivated accessions. Detailed STRUCTURE analysis confirmed this grouping pattern and further revealed 2 sub-populations within wild E. coracana subsp. africana. Both STRUCTURE and genetic diversity analysis assisted with the correct identification of the new germplasm collections. These polymorphic SSR and SNP markers are a significant addition to the existing 82 published SSRs, especially with regard to the previously reported low polymorphism levels in finger millet. Our results also reveal an unexploited finger millet genetic resource that can be included in the regional breeding programs in order to efficiently optimize productivity