Yunbi Xu

Chromosomal regions associated with segregation distortion of molecular markers in F2, backcross, doubled haploid, and recombinant inbred populations in rice (Oryza sativa L.).

Abstract Chromosomal regions associated with marker segregation distortion in rice were compared based on six molecular linkage maps. Mapping populations were derived from one interspecific backcross and five intersubspecific (indica / japonica) crosses, including two F2 populations, two doubled haploid (DH) populations, and one recombinant inbred (RI) population. Mapping data for each population consisted of 129–629 markers. Segregation distortion was determined based on chi-square analysis (P < 0.01) and was observed at 6.8–31.8% of the mapped marker loci. Marker loci associated with skewed allele frequencies were distributed on all 12 chromosomes. Distortion in eight chromosomal regions bracketed previously identified gametophyte (ga) or sterility genes (S). Distortion in three other chromosomal regions was found only in DH populations, where japonica alleles were over-represented, suggesting that loci in these regions may be associated with preferential regeneration of japonica genotypes during anther culture. Three additional clusters of skewed markers were observed in more than one population in regions where no gametophytic or sterility loci have previously been reported. A total of 17 segregation distortion loci may be postulated based on this study and their locations in the rice genome were estimated.

Microsatellite marker development, mapping and applications in rice genetics and breeding

Microsatellites are simple, tandemly repeated di- to tetra-nucleotide sequence motifs flanked by unique sequences. They are valuable as genetic markers because they are co-dominant, detect high levels of allelic diversity, and are easily and economically assayed by the polymerase chain reaction (PCR). Results from screening a rice genomic library suggest that there are an estimated 5700-10 000 microsatellites in rice, with the relative frequency of different repeats decreasing with increasing size of the motif. A map consisting of 120 microsatellite markers demonstrates that they are well distributed throughout the 12 chromosomes of rice. Five multiple copy primer sequences have been identified that could be mapped to independent chromosomal locations. The current level of genome coverage provided by these simple sequence length polymorphisms (SSLPs) in rice is sufficient to be useful for genotype identification, gene and quantitative trait locus (QTL) analysis, screening of large insert libraries, and marker-assisted selection in breeding. Studies of allelic diversity have documented up to 25 alleles at a single locus in cultivated rice germplasm and provide evidence that amplification in wild relatives of Oryza sativa is generally reliable. The availability of increasing numbers of mapped SSLP markers can be expected to complement existing RFLP and AFLP maps, increasing the power and resolution of genome analysis in rice.

Maize HapMap2 identifies extant variation from a genome in flux

Whereas breeders have exploited diversity in maize for yield improvements, there has been limited progress in using beneficial alleles in undomesticated varieties. Characterizing standing variation in this complex genome has been challenging, with only a small fraction of it described to date. Using a population genetics scoring model, we identified 55 million SNPs in 103 lines across pre-domestication and domesticated Zea mays varieties, including a representative from the sister genus Tripsacum. We find that structural variations are pervasive in the Z. mays genome and are enriched at loci associated with important traits. By investigating the drivers of genome size variation, we find that the larger Tripsacum genome can be explained by transposable element abundance rather than an allopolyploid origin. In contrast, intraspecies genome size variation seems to be controlled by chromosomal knob content. There is tremendous overlap in key gene content in maize and Tripsacum, suggesting that adaptations from Tripsacum (for example, perennialism and frost and drought tolerance) can likely be integrated into maize.

Increased food and ecosystem security via perennial grains

Perennial grains hold promise, especially for marginal landscapes or with limited resources where annual versions struggle. Despite doubling of yields of major grain crops since the 1950s, more than one in seven people suffer from malnutrition (1). Global population is growing; demand for food, especially meat, is increasing; much land most suitable for annual crops is already in use; and production of nonfood goods (e.g., biofuels) increasingly competes with food production for land (2). The best lands have soils at low or moderate risk of degradation under annual grain production but make up only 12.6% of global land area (16.5 million km2) (3). Supporting more than 50% of world population is another 43.7 million km2 of marginal lands (33.5% of global land area), at high risk of degradation under annual grain production but otherwise capable of producing crops (3). Global food security depends on annual grains—cereals, oilseeds, and legumes—planted on almost 70% of croplands, which combined supply a similar portion of human calories (4, 5). Annual grain production, though, often compromises essential ecosystem services, pushing some beyond sustainable boundaries (5). To ensure food and ecosystem security, farmers need more options to produce grains under different, generally less favorable circumstances than those under which increases in food security were achieved this past century. Development of perennial versions of important grain crops could expand options.

Molecular plant breeding.

1. Introduction 2. Molecular Breeding Tools: Markers and Maps 3. Molecular Breeding Tools: Omics and Arrays 4. Populations in Genetics and Breeding 5. Plant Genetic Resources: Management, Evaluation and Enhancement 6. Molecular Dissection of Complex Traits: Theory 7. Molecular Dissection of Complex Traits: Practice 8. Marker-assisted Selection: Theory 9. Marker-assisted Selection: Practice 10. Genotype-by-environment Interaction 11. Isolation and Functional Analysis of Genes 12. Gene Transfer and Genetically Modified Plants 13. Intellectual Property Rights and Plant Variety Protection 14. Breeding Informatics 15. Decision Support Tools.

Joint linkage-linkage disequilibrium mapping is a powerful approach to detecting quantitative trait loci underlying drought tolerance in maize.

This paper describes two joint linkage–linkage disequilibrium (LD) mapping approaches: parallel mapping (independent linkage and LD analysis) and integrated mapping (datasets analyzed in combination). These approaches were achieved using 2,052 single nucleotide polymorphism (SNP) markers, including 659 SNPs developed from drought-response candidate genes, screened across three recombinant inbred line (RIL) populations and 305 diverse inbred lines, with anthesis-silking interval (ASI), an important trait for maize drought tolerance, as the target trait. Mapping efficiency was improved significantly due to increased population size and allele diversity and balanced allele frequencies. Integrated mapping identified 18 additional quantitative trait loci (QTL) not detected by parallel mapping. The use of haplotypes improved mapping efficiency, with the sum of phenotypic variation explained (PVE) increasing from 5.4% to 23.3% for single SNP-based analysis. Integrated mapping with haplotype further improved the mapping efficiency, and the most significant QTL had a PVE of up to 34.7%. Normal allele frequencies for 113 of 277 (40.8%) SNPs with minor allele frequency (<5%) in 305 lines were recovered in three RIL populations, three of which were significantly associated with ASI. The candidate genes identified by two significant haplotype loci included one for a SET domain protein involved in the control of flowering time and the other encoding aldo/keto reductase associated with detoxification pathways that contribute to cellular damage due to environmental stress. Joint linkage–LD mapping is a powerful approach for detecting QTL underlying complex traits, including drought tolerance.

Genetic association mapping identifies single nucleotide polymorphisms in genes that affect abscisic acid levels in maize floral tissues during drought

In maize, water stress at flowering causes loss of kernel set and productivity. While changes in the levels of sugars and abscisic acid (ABA) are thought to play a role in this stress response, the mechanistic basis and genes involved are not known. A candidate gene approach was used with association mapping to identify loci involved in accumulation of carbohydrates and ABA metabolites during stress. A panel of single nucleotide polymorphisms (SNPs) in genes from these metabolic pathways and in genes for reproductive development and stress response was used to genotype 350 tropical and subtropical maize inbred lines that were well watered or water stressed at flowering. Pre-pollination ears, silks, and leaves were analysed for sugars, starch, proline, ABA, ABA-glucose ester, and phaseic acid. ABA and sugar levels in silks and ears were negatively correlated with their growth. Association mapping with 1229 SNPs in 540 candidate genes identified an SNP in the maize homologue of the Arabidopsis MADS-box gene, PISTILLATA, which was significantly associated with phaseic acid in ears of well-watered plants, and an SNP in pyruvate dehydrogenase kinase, a key regulator of carbon flux into respiration, that was associated with silk sugar concentration. An SNP in an aldehyde oxidase gene was significantly associated with ABA levels in silks of water-stressed plants. Given the short range over which decay of linkage disequilibrium occurs in maize, the results indicate that allelic variation in these genes affects ABA and carbohydrate metabolism in floral tissues during drought.

Whole-genome strategies for marker-assisted plant breeding

Molecular breeding for complex traits in crop plants requires understanding and manipulation of many factors influencing plant growth, development and responses to an array of biotic and abiotic stresses. Molecular marker-assisted breeding procedures can be facilitated and revolutionized through whole-genome strategies, which utilize full genome sequencing and genome-wide molecular markers to effectively address various genomic and environmental factors through a representative or complete set of genetic resources and breeding materials. These strategies are now increasingly based on understanding of specific genomic regions, genes/alleles, haplotypes, linkage disequilibrium (LD) block(s), gene networks and their contribution to specific phenotypes. Large-scale and high-density genotyping and genome-wide selection are two important components of these strategies. As components of whole-genome strategies, molecular breeding platforms and methodologies should be backed up by high throughput and precision phenotyping and e-typing (environmental assay) with strong support systems such as breeding informatics and decision support tools. Some basic strategies are discussed in this article, including (1) seed DNA-based genotyping for simplifying marker-assisted selection (MAS), reducing breeding cost and increasing scale and efficiency, (2) selective genotyping and phenotyping, combined with pooled DNA analysis, for capturing the most important contributing factors, (3) flexible genotyping systems, such as genotyping by sequencing and arraying, refined for different selection methods including MAS, marker-assisted recurrent selection and genomic selection (GS), (4) marker-trait association analysis using joint linkage and LD mapping, and (5) sequence-based strategies for marker development, allele mining, gene discovery and molecular breeding.

Leaf-level water use efficiency determined by carbon isotope discrimination in rice seedlings: genetic variation associated with population structure and QTL mapping.

Increasing the water use efficiency (WUE) of our major crop species is an important target of agricultural research. Rice is a major water consumer in agriculture and it is also an attractive genetic model. We evaluated leaf-level WUE in young rice seedlings using carbon isotope discrimination (∆13C) as an indicator of the trait. A survey of ∆13C was undertaken in 116 diverse germplasm accessions representing O. sativa, O. glaberrima and four wild Oryza species. O. sativa cultivars were classified into sub-populations based on SSR markers, and significant differences in ∆13C were observed among the five genetically defined groups. While individual accessions explained a greater proportion of the variation than did sub-population, indica rice varieties had the lowest ∆13C values overall, indicating superior WUE, while temperatejaponica had the highest ∆13C. O sativa accessions had a similar or greater range of ∆13C values than wild Oryza species, while domesticated O. glaberrima had a narrower range. Correlation analysis identified leaf morphological and physiological traits that were significantly associated with ∆13C, including longer leaves, more drooping leaves, higher tillering ability, and lower leaf nitrogen content. These trait associations were investigated by quantitative trait locus (QTL) mapping using backcross inbred lines derived from a cross between Nipponbare (temperatejaponica) and Kasalath (aus). Seven QTL for ∆13C were identified using composite interval analysis, located in five chromosomal regions. The QTL with the largest additive effect came from Kasalath and co-localized with QTL for leaf length, tiller number and nitrogen content.

How can we use genomics to improve cereals with rice as a reference genome

Rice serves as a model crop for cereal genomics. The availability of complete genome sequences, together with various genomic resources available for both rice and Arabidopsis, have revolutionized our understanding of the genetic make-up of crop plants. Both macrocolinearity revealed by comparative mapping and microcolinearity revealed by sequence comparisons among the grasses indicate that sequencing and functional analysis of the rice genome will have a significant impact on other cereals in terms of both genomic studies and crop improvement. The availability of mutants, introgression libraries, and advanced transformation techniques make functional genomics in rice and other cereals more manageable than ever before. A wide array of genetic markers, including anchor markers for comparative mapping, SSRs and SNPs are widely used in genetic mapping, germplasm evaluation and marker assisted selection. An integrated database that combines genome information for rice and other cereals is key to the effective utilization of all genomics resources for cereal improvement. To maximize the potential of genomics for plant breeding, experiments must be further miniaturized and costs must be reduced. Many techniques, including targeted gene disruption or allele substitution, insertional mutagenesis, RNA interference and homologous recombination, need to be refined before they can be widely used in functional genomic analysis and plant breeding.