Satoh K, Doi K, Nagata T, Kishimoto N, Suzuki K et al (2007). Gene organization in rice revealed by full-length cDNA mapping and gene expression analysis through microarray. PLoS ONE 2(11): e1235. (DOI: 10.1371/journal.pone.0001235).

Rice (Oryza sativa L.) is a model organism for the functional genomics of monocotyledonous plants since the genome size is considerably smaller than those of other monocotyledonous plants. Although highly accurate genome sequences of indica and japonica rice are available, additional resources such as full-length complementary DNA (FL-cDNA) sequences are also indispensable for comprehensive analyses of gene structure and function. We cross-referenced 28.5K individual loci in the rice genome defined by mapping of 578K FL-cDNA clones with the 56K loci predicted in the TIGR genome assembly.

Spooner DM, Nuñez J, Trujillo G, del Rosario Herrera M, Guzmán F and Ghislain M (2007). Extensive simple sequence repeat genotyping of potato landraces supports a major reevaluation of their gene pool structure and classification. Proceedings of the National Academy of Sciences of the United States of America 104(49):19398–19403 (DOI: 10.1073/pnas.0709796104). View online

Varshney RK, Horres R, Molina C, Nayak S, Jungmann R, Swamy P, Winter P, Jayashree B, Kahl G and Hoisington DA (2007). Extending the repertoire of microsatellite markers for genetic linkage mapping and germplasm screening in chickpea. Journal of SAT Agricultural Research 5(1):3pp.

Molecular markers and genetic linkage maps are the prerequisites for undertaking molecular breeding activities. However, the progress towards development of a reasonable number of molecular markers has been very slow in cultivated species of chickpea (Cicer arietinum). One of the main reasons for this may be attributed to the low level of genetic diversity present in the cultivated gene pools of these species, at least with the detection tools that are currently available. Among various molecular markers currently available, microsatellite or SSR (simple sequence repeat) markers are often chosen as the preferred markers for a variety of applications in breeding because of their multi-allelic nature, co-dominant inheritance, relative abundance and extensive genome coverage (Gupta and Varshney 2000).

Vadez V, Krishnamurthy L, Kashiwagi JW, Kholova J, Devi JM, Sharma KK, Bhatnagar-Mathur P, Hoisington DA, Hash CT, Bidinger FR, and Keatinge JDH (2007). Exploiting the functionality of root systems for dry, saline, and nutrient deficient environments in a changing climate.  Journal of SAT Agricultural Research 4(1): 64pp. (Special Symposium edition).

Increasing episodes of drought, lack of sufficient nutrients, exposure to toxic minerals, and soil compaction are just a few examples of the environmental constraints that the roots are exposed to during plant growth. Understanding how roots respond to these stresses is crucial for improving crop production under such conditions. Yet, investigating roots is a very difficult task and, therefore, very little is known about the precise role that the roots play in contributing to plant adaptation to hostile environments.

Heslop-Harrison JS and Schwarzacher T (2007). Domestication, genomics and the future for banana. Annals of Botany 100(5):1073–1084. (DOI: 10.1093/aob/mcm191).

Varshney RK, Nayak S, Jayashree B, Eshwar K, Upadhyaya HD and Hoisington DA (2007). Development of cost-effective SNP assays for chickpea genome analysis and breeding. Journal of SAT Agricultural Research 3(1):29–31.

Although microsatellite or simple sequence repeat (SSR) markers have been the preferred markers for plant genetics and breeding, single nucleotide polymorphisms (SNPs) are the most common class that detect the smallest unit of genetic variation present in genomes (Rafalski 2002). Marker technologies exploiting the potential of SNPs provide the possibility of constructing genetic maps at 100-fold higher marker densities than with other types of DNA polymorphisms (Cho et al. 1999, Sachidanandam et al. 2001). Identification and mapping of SNPs has been initiated recently for crop species like rice (Oryza sativa) (Feltus et al. 2004), maize (Zea mays) (Tenaillon et al. 2001), wheat (Triticum aestivum) (Somers et al. 2003), barley (Hordeum vulgare) (Kota et al. 2001, Rostoks et al. 2005), ryegrass (Lolium multiflorum) (Miura et al. 2005) and rye (Secale cereale) (Varshney et al. 2007).

Szakács É, Molnár-Láng M (2007). Development and molecular cytogenetic identification of new winter wheat/winter barley (‘Martonvásári 9 kr1’/ ‘Igri’) disomic addition lines. Genome 50(1):43–50. (DOI: 10.1139/G06-134). View online

Diaz G, Ryba M, Nelson R, Leung H and Leach J (2007). Detection of deletion mutants in rice via overgo hybridization onto membrane spotted arrays. Plant Molecular Biology Reporter 25(1–2):17–26. (DOI: 10.1007/s11105-007-0002-7). Not open access: view abstract

van Hintum T  (2007). Data resolution: a jackknife procedure for determining the consistency of molecular marker datasets. Theoretical and Applied Genetics 115 (3):343–349. (DOI: 10.1007/s00122-007-0566-5).

The results of genetic diversity studies using molecular markers not only depend on the biology of the studied objects but also on the quality of the marker data. Poor data quality may hamper the correct answering of biological questions. A new statistic is proposed to estimate the quality of a marker data set with regard to its ability to describe the structure of the biological material under study. This statistic is called data resolution (DR). It is calculated by splitting a marker data set at random into two sets each with half the number of markers. In each set, similarities between all pairs of objects are calculated.

Heinemann A, Dingkuhn M, Luquet M, Combres JC and Chapman SC (2007). Characterization of drought stress environments for upland rice and maize in central Brazil. Euphytica published online 10th October 2007. Also printed in 2008. (DOI: 10.1007/s10681-007-9579-z). Not open access: view abstract