So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

Human biochemical genetics

DNA sequencing with chain terminating inhibitors

In recent years, molecular markers have been utilized for a variety of applications including examination of genetic relationships between individuals, mapping of useful genes, construction of linkage maps, marker assisted selections and backcrosses, population genetics and phylogenetic studies. Among the available molecular markers, microsatellites or simple sequence repeats (SSRs) which are tandem repeats of one to six nucleotide long DNA motifs, have gained considerable importance in plant genetics and breeding owing to many desirable genetic attributes including hypervariability, multiallelic nature, codominant inheritance, reproducibility, relative abundance, extensive genome coverage including organellar genomes, chromosome specific location and amenability to automation and high throughput genotyping. High degree of allelic variation revealed by microsatellite markers results from variation in number of repeat-motifs at a locus caused by replication slippage and/or unequal crossing-over during meiosis. In spite of limited understanding of the functions of the SSR motifs within the plant genes, SSRs are being widely utilized in plant genome analysis. Microsatellites can be developed directly from genomic DNA libraries or from libraries enriched for specific microsatellites. Alternatively, microsatellites can also be found by searching public databases such as GenBank and EMBL or through cross-species transferability. At present, EST databases are an important source of candidate genes, as these can generate markers directly associated with a trait of interest and may be transferable in close relative genera. A large number of SSR based techniques have been developed and a quantum of literature has accumulated regarding the applicability of SSRs in plant genetics and genomics. In this review we discuss the recent developments (last 4–5 years) made in plant genetics using SSR markers.

Microsatellite markers: an overview of the recent progress in plants

Heritability (H) on a progeny mean basis is frequently estimated in recurrent selection experiments for the purpose of estimating the expected progress from family selection; however, appropriate measures of precision have been developed for only a few heritability estimators. The objective of this research was to develop a measure of precision for H for certain balanced linear models. Exact confidence intervals for H were derived and are not restricted to a specific experimental design. The confidence intervals were applied to sorghum [Sorghum bicolor (L.) Moench] half-sib family data.

An exact confidence interval for heritability on a progeny mean basis

In mammals, cadmium is widely considered as a non-genotoxic carcinogen acting through a methylation-dependent epigenetic mechanism. Here, the effects of Cd treatment on the DNA methylation patten are examined together with its effect on chromatin reconfiguration in Posidonia oceanica. DNA methylation level and pattern were analysed in actively growing organs, under short- (6 h) and long- (2 d or 4 d) term and low (10 mM) and high (50 mM) doses of Cd, through a Methylation-Sensitive Amplification Polymorphism technique and an immunocytological approach, respectively. The expression of one member of the CHROMOMETHYLASE (CMT) family, a DNA methyltransferase, was also assessed by qRT-PCR. Nuclear chromatin ultrastructure was investigated by transmission electron microscopy. Cd treatment induced a DNA hypermethylation, as well as an up-regulation of CMT, indicating that de novo methylation did indeed occur. Moreover, a high dose of Cd led to a progressive heterochromatinization of interphase nuclei and apoptotic figures were also observed after long-term treatment. The data demonstrate that Cd perturbs the DNA methylation status through the involvement of a specific methyltransferase. Such changes are linked to nuclear chromatin reconfiguration likely to establish a new balance of expressed/repressed chromatin. Overall, the data show an epigenetic basis to the mechanism underlying Cd toxicity in plants.

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In Posidonia oceanica cadmium induces changes in DNA methylation and chromatin patterning

The identification of quantitative trait loci (QTLs) affecting agronomically important traits enable to understand their underlying genetic mechanisms and genetic basis of their complex interactions. The aim of the present study was to detect QTLs for 12 agronomic traits related to staygreen, plant early development, grain yield and its components, and some growth characters by analyzing replicated phenotypic datasets from three crop seasons, using the population of 168 F7 RILs of the cross 296B × IS18551. In addition, we report mapping of a subset of genic-microsatellite markers. A linkage map was constructed with 152 marker loci comprising 149 microsatellites (100 genomic- and 49 genic-microsatellites) and three morphological markers. QTL analysis was performed by using MQM approach. Forty-nine QTLs were detected, across environments or in individual environments, with 1–9 QTLs for each trait. Individual QTL accounted for 5.2–50.4% of phenotypic variance. Several genomic regions affected multiple traits, suggesting the phenomenon of pleiotropy or tight linkage. Stable QTLs were identified for studied traits across different environments, and genetic backgrounds by comparing the QTLs in the study with previously reported QTLs in sorghum. Of the 49 mapped genic-markers, 18 were detected associating either closely or exactly as the QTL positions of agronomic traits. EST marker Dsenhsbm19, coding for a key regulator (EIL-1) of ethylene biosynthesis, was identified co-located with the QTLs for plant early development and staygreen trait, a probable candidate gene for these traits. Similarly, such exact co-locations between EST markers and QTLs were observed in four other instances. Collectively, the QTLs/markers identified in the study are likely candidates for improving the sorghum performance through MAS and map-based gene isolations.

Identification of quantitative trait loci for agronomically important traits and their association with genic-microsatellite markers in sorghum

The shoot fly is one of the most destructive insect pests of sorghum at the seedling stage. Deployment of cultivars with improved shoot fly resistance would be facilitated by the use of molecular markers linked to QTL. The objective of this study was to dissect the genetic basis of resistance into QTL, using replicated phenotypic data sets obtained from four test environments, and a 162 microsatellite marker-based linkage map constructed using 168 RILs of the cross 296B (susceptible) × IS18551 (resistant). Considering five component traits and four environments, a total of 29 QTL were detected by multiple QTL mapping (MQM) viz., four each for leaf glossiness and seedling vigor, seven for oviposition, six for deadhearts, two for adaxial trichome density and six for abaxial trichome density. The LOD and R
 2 (%) values of QTL ranged from 2.6 to 15.0 and 5.0 to 33%, respectively. For most of the QTL, IS18551 contributed resistance alleles; however, at six QTL, alleles from 296B also contributed to resistance. QTL of the related component traits were co-localized, suggesting pleiotropy or tight linkage of genes. The new morphological marker Trit for trichome type was associated with the major QTL for component traits of resistance. Interestingly, QTL identified in this study correspond to QTL/genes for insect resistance at the syntenic maize genomic regions, suggesting the conservation of insect resistance loci between these crops. For majority of the QTL, possible candidate genes lie within or very near the ascribed confidence intervals in sorghum. Finally, the QTL identified in the study should provide a foundation for marker-assisted selection (MAS) programs for improving shoot fly resistance in sorghum.

Identification of quantitative trait loci for resistance to shoot fly in sorghum [Sorghum bicolor (L.) Moench]

Sorghum, a cereal of economic importance ensures food and fodder security for millions of rural families in the semi-arid tropics. The objective of the present study was to identify and validate quantitative trait loci (QTL) for grain yield and other agronomic traits using replicated phenotypic data sets from three post-rainy dry sorghum crop seasons involving a mapping population with 245 F9 recombinant inbred lines derived from a cross of M35-1 × B35. A genetic linkage map was constructed with 237 markers consisting of 174 genomic, 60 genic and 3 morphological markers. The QTL analysis for 11 traits following composite interval mapping identified 91 QTL with 5–12 QTL for each trait. QTL detected in the population individually explained phenotypic variation between 2.5 and 30.3 % for a given trait and six major genomic regions with QTL effect on multiple traits were identified. Stable QTL across seasons were identified. Of the 60 genic markers mapped, 21 were found at QTL peak or tightly linked with QTL. A gene-based marker XnhsbSFCILP67 (Sb03g028240) on SBI-03, encoding indole-3-acetic acid-amido synthetase GH3.5, was found to be involved in QTL for seven traits. The QTL-linked markers identified for 11 agronomic traits may assist in fine mapping, map-based gene isolation and also for improving post-rainy sorghum through marker-assisted breeding.

Mapping QTL for grain yield and other agronomic traits in post-rainy sorghum [Sorghum bicolor (L.) Moench].

Molecular variation within defined genes underlying specific biochemical or physiological functions provide candidate gene-based markers which show very close association with the trait of interest and thus should enable to design superior genotypes. We explored microsatellite loci in a total of 9,892 subtracted drought stress ESTs of sorghum (6,295 after flowering ESTs and 3,597 before flowering ESTs) available in the NCBI dbEST database. Analysis of 9,892 ESTs identified 221 non-redundant ESTs with SSRs, from which 109 functional SSRs were developed. Among them 62 EST-microsatellites (56.8%) exhibited polymorphism for at least one sorghum genotype among the five tested and yielded a total of 161 alleles, with an average of 2.59 alleles per marker. We present a microsatellite linkage map using a RIL population derived from the cross 296B and IS18551. The map contains 128 microsatellite loci distributed over 15 linkage groups, and spanning a genetic distance of 1,074.5 cM. The map includes map positions of 28 drought EST-microsatellites developed and seven new genomic-SSRs, and are distributed throughout the map. The developed EST markers include genes coding for important regulatory proteins and functional proteins that are involved in stress related metabolism. The drought EST-microsatellites will have applications in functional diversity studies, association studies, QTL studies for drought, and other agronomically important traits in sorghum, and comparative genomics studies between sorghum and other members of the Poaceae family.

Exploration and mapping of microsatellite markers from subtracted drought stress ESTs in Sorghum bicolor (L.) Moench

Forage sorghum cultivars grown in India are susceptible to various foliar diseases, of which anthracnose, rust, zonate leaf spot, drechslera leaf blight and target leaf spot cause severe damage. We report here the quantitative trait loci (QTLs) conferring resistance to these foliar diseases. QTL analysis was undertaken using 168 F7 recombinant inbred lines (RILs) of a cross between a female parental line 296B (resistant) and a germplasm accession IS18551 (susceptible). RILs and parents were evaluated in replicated field trials in two environments. A total of twelve QTLs for five foliar diseases on three sorghum linkage groups (SBI-03, SBI-04 and SBI-06) were detected, accounting for 6.9–44.9% phenotypic variance. The morphological marker Plant color (Plcor) was associated with most of the QTL across years and locations. The QTL information generated in this study will aid in the transfer of foliar disease resistance into elite susceptible sorghum breeding lines through marker-assisted selection.

R. Madhusudhana

Papers

Identification of quantitative trait loci for agronomically important traits and their association with genic-microsatellite markers in sorghum

Identification of quantitative trait loci for resistance to shoot fly in sorghum [Sorghum bicolor (L.) Moench]

Mapping QTL for grain yield and other agronomic traits in post-rainy sorghum [Sorghum bicolor (L.) Moench].

Exploration and mapping of microsatellite markers from subtracted drought stress ESTs in Sorghum bicolor (L.) Moench

Identification of quantitative trait loci associated with resistance to foliar diseases in sorghum [Sorghum bicolor (L.) Moench]