Statistical method for testing the neutral mutation hypothesis by DNA polymorphism.

The majority of agronomic traits are controlled by multiple genes that cause minor phenotypic effects, making the identification of these genes difficult Here we introduce MutMap, a method based on whole-genome resequencing of pooled DNA from a segregating population of plants that show a useful phenotype In MutMap, a mutant is crossed directly to the original wild-type line and then selfed, allowing unequivocal segregation in second filial generation (F(2)) progeny of subtle phenotypic differences This approach is particularly amenable to crop species because it minimizes the number of genetic crosses (n = 1 or 0) and mutant F(2) progeny that are required We applied MutMap to seven mutants of a Japanese elite rice cultivar and identified the unique genomic positions most probable to harbor mutations causing pale green leaves and semidwarfism, an agronomically relevant trait These results show that MutMap can accelerate the genetic improvement of rice and other crop plants

/pdf/genome-sequencing-reveals-agronomically-important-loci-in-2v1h9yey4q.pdf

Genome sequencing reveals agronomically important loci in rice using MutMap

More accurate and precise phenotyping strategies are necessary to empower high-resolution linkage mapping and genome-wide association studies and for training genomic selection models in plant improvement. Within this framework, the objective of modern phenotyping is to increase the accuracy, precision and throughput of phenotypic estimation at all levels of biological organization while reducing costs and minimizing labor through automation, remote sensing, improved data integration and experimental design. Much like the efforts to optimize genotyping during the 1980s and 1990s, designing effective phenotyping initiatives today requires multi-faceted collaborations between biologists, computer scientists, statisticians and engineers. Robust phenotyping systems are needed to characterize the full suite of genetic factors that contribute to quantitative phenotypic variation across cells, organs and tissues, developmental stages, years, environments, species and research programs. Next-generation phenotyping generates significantly more data than previously and requires novel data management, access and storage systems, increased use of ontologies to facilitate data integration, and new statistical tools for enhancing experimental design and extracting biologically meaningful signal from environmental and experimental noise. To ensure relevance, the implementation of efficient and informative phenotyping experiments also requires familiarity with diverse germplasm resources, population structures, and target populations of environments. Today, phenotyping is quickly emerging as the major operational bottleneck limiting the power of genetic analysis and genomic prediction. The challenge for the next generation of quantitative geneticists and plant breeders is not only to understand the genetic basis of complex trait variation, but also to use that knowledge to efficiently synthesize twenty-first century crop varieties.

https://link.springer.com/content/pdf/10.1007%2Fs00122-013-2066-0.pdf

Next-generation phenotyping: requirements and strategies for enhancing our understanding of genotype–phenotype relationships and its relevance to crop improvement

https://www.ndsu.edu/pubweb/~mcclean/plsc731/homework/papers/kovach%20et%20al.%20-%20new%20insights%20into%20the%20history%20of%20rice%20domestication.pdf

New insights into the history of rice domestication

To subvert rice (Oryza sativa) host defenses, the devastating ascomycete fungus pathogen Magnaporthe oryzae produces a battery of effector molecules, including some with avirulence (AVR) activity, which are recognized by host resistance (R) proteins resulting in rapid and effective activation of innate immunity. To isolate novel avirulence genes from M. oryzae ,w e examined DNA polymorphisms of secreted protein genes predicted from the genome sequence of isolate 70-15 and looked for an association with AVR activity. This large-scale study found significantly more presence/absence polymorphisms than nucleotide polymorphisms among 1032 putative secreted protein genes. Nucleotide diversity of M. oryzae among 46 isolates of a worldwide collection was extremely low (u = 8.2 3 10 25 ), suggestive of recent pathogen dispersal. However, no association between DNA polymorphism and AVR was identified. Therefore, we used genome resequencing of Ina168, an M. oryzae isolate that contains nine AVR genes. Remarkably, a total of 1.68 Mb regions, comprising 316 candidate effector genes, were present in Ina168 but absent in the assembled sequence of isolate 70-15. Association analyses of these 316 genes revealed three novel AVR genes, AVR-Pia, AVR-Pii, and AVR-Pik/km/kp, corresponding to five previously known AVR genes, whose products are recognized inside rice cells possessing the cognate R genes. AVR-Pia and AVR-Pii have evolved by gene gain/loss processes, whereas AVR-Pik/km/kp has evolved by nucleotide substitutions and gene gain/loss.

/pdf/association-genetics-reveals-three-novel-avirulence-genes-254qsve3i9.pdf

Association Genetics Reveals Three Novel Avirulence Genes from the Rice Blast Fungal Pathogen Magnaporthe oryzae

Polymorphism over ∼26 kb of DNA sequence spanning 22 loci and one region distributed on chromosomes 1, 2, 3 and 4 was studied in 30 accessions of cultivated rice, Oryza sativa, and its wild relatives. Phylogenetic analysis using all the DNA sequences suggested that O. sativa ssp. indica and ssp. japonica were independently domesticated from a wild species O. rufipogon. O. sativa ssp. indica contained substantial genetic diversity (π = 0.0024), whereas ssp. japonica exhibited extremely low nucleotide diversity (π = 0.0001) suggesting the origin of the latter from a small number of founders. O. sativa ssp. japonica contained a larger number of derived and fixed non-synonymous substitutions as compared to ssp. indica. Nucleotide diversity and genealogical history substantially varied across the 22 loci. A locus, RLD15 on chromosome 2, showed a distinct genealogy with ssp. japonica sequences distantly separated from those of O. rufipogon and O. sativa ssp. indica. Linkage disequilibrium (LD) was analyzed in two different regions. LD in O. rufipogon decays within 5 kb, whereas it extends to ∼50 kb in O. sativa ssp. indica.

Large-scale DNA polymorphism study of Oryza sativa and O. rufipogon reveals the origin and divergence of Asian rice.

Most traits of interest to medical, agricultural and animal scientists show continuous variation and complex mode of inheritance. DNA-based markers are being deployed to analyse such complex traits, that are known as quantitative trait loci (QTL). In conventional QTL analysis, F2, backcross populations, recombinant inbred lines, backcross inbred lines and double haploids from biparental crosses are commonly used. Introgression lines and near isogenic lines are also being used for QTL analysis. However, such populations have major limitations like predominantly relying on the recombination events taking place in the F1 generation and mapping of only the allelic pairs present in the two parents. The second generation mapping resources like association mapping, nested association mapping and multiparent intercross populations potentially address the major limitations of available mapping resources. The potential of multiparent intercross populations in gene mapping has been discussed here. In such populations both linkage and association analysis can be conductted without encountering the limitations of structured populations. In such populations, larger genetic variation in the germplasm is accessed and various allelic and cytoplasmic interactions are assessed. For all practical purposes, across crop species, use of eight founders and a fixed population of 1000 individuals are most appropriate. Limitations with multiparent intercross populations are that they require longer time and more resource to be generated and they are likely to show extensive segregation for developmental traits, limiting their use in the analysis of complex traits. However, multiparent intercross population resources are likely to bring a paradigm shift towards QTL analysis in plant species.

Multiparent intercross populations in analysis of quantitative traits

Molecular markers linked to QTL contributing to agronomic and fibre quality traits would be useful for cotton improvement. We have attempted to tag yield and fibre quality traits with AFLP and SSR markers using F2 and F3 populations of a cross between two Gossypium hirsutum varieties, PS56-4 and RS2013. Out of 50 AFLP primer combinations and 177 SSR primer pairs tested, 32 AFLP and four SSR primers were chosen for genotyping F2 individuals. Marker-trait associations were studied for eight agronomic and five fibre quality traits through simple and multiple regression analysis (MRA) using a set of 92 AFLP polymorphic loci and four SSR markers. Simple linear regression analysis (SLRA) identified 23 markers for eight different traits whereas multiple regression analysis identified 30 markers for at least one of the 13 traits. SSR marker BNL 3502 was consistently identified to be associated with fibre strength. While all the markers identified in SLRA were also detected in MRA, as many as 16 of the 30 markers were identified to be associated with respective traits in both F2 and F3 generations. The markers explained up to 41 per cent of phenotypic variation for individual traits. A number of markers were found to be associated with multiple traits suggesting clustering of QTLs for fibre quality traits in cotton.

Association of AFLP and SSR markers with agronomic and fibre quality traits in Gossypium hirsutum L.

Use of TILLING for reverse and forward genetics of rice.

A total 177 simple sequence repeat (SSR) markers were screened using a set of 47 Upland cotton genotypes comprising 14 commercial varieties, 14 germplasm accessions and 19 advanced breeding lines to identify informative markers for genetic diversity assessment and fingerprinting in G. hirsutum. Only 21% (381177) of SSR markers tested showed polymorphism with a mean of 2.18 alleles per locus and with average polymorphism information content (PIC) of 0.32. The SSR markers revealed a Jaccard’ similarity coefficient ranging between 0.43 and 0.89, with an average of 0.67 among accessions. Cluster analysis using unweighted pair group method with arithmetic averages (UPGMA) and principal component analysis (PCA) indicated that majority of the genotypes were very closely related. All the 47 genotypes showed heterorygosity for at least one of the SSR loci. We discovered 19 rare and 6 unique alleles among the tested genotypes of cotton. Fingerprint based on all the 38 loci revealed a probability of identical match by chance of 3.98x10. A set of ten SSR markers was identified which could distinguish all the 47 genotypes with a moderate probability of identical match by chance (XDn = 0.01).

Arunita Rakshit

Papers

Large-scale DNA polymorphism study of Oryza sativa and O. rufipogon reveals the origin and divergence of Asian rice.

Multiparent intercross populations in analysis of quantitative traits

Association of AFLP and SSR markers with agronomic and fibre quality traits in Gossypium hirsutum L.

Use of TILLING for reverse and forward genetics of rice.

Evaluation of SSR Markers for the Assessment of Genetic Diversity and Fingerprinting of Gossypium hirsutum Accessions