Journal articles 2014
Documents
Detection of candidate R genes and single nucleotide polymorphisms for downy mildew resistance in maize inbred lines by association analysis
Wongkaew A, Phumichai C, Chunwongse J, Jampatong S, Grudloyma P, Pulam T and Doungchan W (2014). Detection of candidate R genes and single nucleotide polymorphisms for downy mildew resistance in maize inbred lines by association analysis. Euphytica 197(1):109–118 (DOI: 10.1007/s10681-013-1056-2). Not open access; view abstract. (G4007.04)
Wongkaew A, Phumichai C, Chunwongse J, Jampatong S, Grudloyma P, Pulam T and Doungchan W (2014). Detection of candidate R genes and single nucleotide polymorphisms for downy mildew resistance in maize inbred lines by association analysis. Euphytica 197(1):109–118 (DOI: 10.1007/s10681-013-1056-2). Not open access; view abstract. (G4007.04)
N- and P- mediated seminal root elongation response in rice seedlings
Ogawa S, Gomez Selvaraj M, Joseph Fernando A, Lorieux M, Ishitani M, McCouch S and Arbelaez JD (2014). N- and P- mediated seminal root elongation response in rice seedlings. Plant and Soil 375(1-2):303–315 (DOI: 10.1007/s11104-013-1955-y). First published in November 2013. Not open access; view abstract. (G3005.10)
Ogawa S, Gomez Selvaraj M, Joseph Fernando A, Lorieux M, Ishitani M, McCouch S and Arbelaez JD (2014). N- and P- mediated seminal root elongation response in rice seedlings. Plant and Soil 375(1-2):303–315 (DOI: 10.1007/s11104-013-1955-y). First published in November 2013. Not open access; view abstract. (G3005.10)
A chromosomal genomics approach to assess and validate the desi and kabuli draft chickpea genome assemblies
Ruperao P, Chan CKK, Azam S, Karafiátová M, Hayashi S, Čížková J, Saxena RK, Šimková H, Song C, Vrána J, Chitikineni A, Visendi P, Gaur PM, Millán T, Singh KB, Taran B, Wang J, Batley J, Doležel J, Varshney RK and Edwards D (2014). A chromosomal genomics approach to assess and validate the desi and kabuli draft chickpea genome assemblies. Plant Biotechnology Journal 12:778–786 (DOI: 10.1111/pbi.12182). Not open access; view abstract.
Ruperao P, Chan CKK, Azam S, Karafiátová M, Hayashi S, Čížková J, Saxena RK, Šimková H, Song C, Vrána J, Chitikineni A, Visendi P, Gaur PM, Millán T, Singh KB, Taran B, Wang J, Batley J, Doležel J, Varshney RK and Edwards D (2014). A chromosomal genomics approach to assess and validate the desi and kabuli draft chickpea genome assemblies. Plant Biotechnology Journal 12:778–786 (DOI: 10.1111/pbi.12182). Not open access; view abstract.
Comparing simple root phenotyping methods on a core set of rice genotypes
Shrestha R, Al-Shugeairy Z, Al-Ogaidi F, Munasinghe M, Radermacher M, Vandenhirtz J and Price AH (2014). Comparing simple root phenotyping methods on a core set of rice genotypes. Plant Biology 16(3):632–642. First published online in September 2013. Not open access; view abstract. (G3008.06)
Shrestha R, Al-Shugeairy Z, Al-Ogaidi F, Munasinghe M, Radermacher M, Vandenhirtz J and Price AH (2014). Comparing simple root phenotyping methods on a core set of rice genotypes. Plant Biology 16(3):632–642. First published online in September 2013. Not open access; view abstract. (G3008.06)
Physiological and molecular analysis of aluminium tolerance in selected Kenyan maize lines
Matonyei TK, Cheprot RK, Liu J, Piñeros MA, Shaff JE, Gudu S, Were B, Magalhaes JV and Kochian LV (2014). Physiological and molecular analysis of aluminium tolerance in selected Kenyan maize lines. Plant and Soil 377(1–2):357–367 (DOI: 10.1007/s11104-013-1976-6). Not open access; view abstract. (G 7010.03.05)
Matonyei TK, Cheprot RK, Liu J, Piñeros MA, Shaff JE, Gudu S, Were B, Magalhaes JV and Kochian LV (2014). Physiological and molecular analysis of aluminium tolerance in selected Kenyan maize lines. Plant and Soil 377(1–2):357–367 (DOI: 10.1007/s11104-013-1976-6). Not open access; view abstract. (G 7010.03.05)
High throughput screening of rooting depth in rice using buried herbicide
Al-Shugeairy Z, Islam MS, Shrestha R, Al-Ogaidi F, Norton GJ and Price AH (2014). High throughput screening of rooting depth in rice using buried herbicide. Annals of Applied Biology 165(1):96–107 (DOI: 10.1111/aab.12118). Not open access; view abstract. (G3008.06)
Al-Shugeairy Z, Islam MS, Shrestha R, Al-Ogaidi F, Norton GJ and Price AH (2014). High throughput screening of rooting depth in rice using buried herbicide. Annals of Applied Biology 165(1):96–107 (DOI: 10.1111/aab.12118). Not open access; view abstract. (G3008.06)
Identification of QTLs for seedling vigor in winter wheat
Li X-M, Chen X-M, Xiao Y-G, Xia X-C, Wang D-S, He Z-H and Wang H-J (2014). Identification of QTLs for seedling vigor in winter wheat. Euphytica 198(2):199–209 (DOI: 10.1007/s10681-014-1092-6). Not open access; view abstract. (G7010.02.01)
Li X-M, Chen X-M, Xiao Y-G, Xia X-C, Wang D-S, He Z-H and Wang H-J (2014). Identification of QTLs for seedling vigor in winter wheat. Euphytica 198(2):199–209 (DOI: 10.1007/s10681-014-1092-6). Not open access; view abstract. (G7010.02.01)
An Integrated SNP Mining and Utilization (ISMU) pipeline for next generation sequencing data
Azam S, Rathore A, Shah TM, Telluri M, Amindala B, Ruperao P, Katta MAVS and Varshney RK (2014). An Integrated SNP Mining and Utilization (ISMU) pipeline for next generation sequencing data. PLoS ONE 9(7):e101754 (DOI:10.1371/journal.pone.0101754).
Abstract: Open source single nucleotide polymorphism (SNP) discovery pipelines for next generation sequencing data commonly requires working knowledge of command line interface, massive computational resources and expertise which is a daunting task for biologists. Further, the SNP information generated may not be readily used for downstream processes such as genotyping. Hence, a comprehensive pipeline has been developed by integrating several open source next generation sequencing (NGS) tools along with a graphical user interface called Integrated SNP Mining and Utilization (ISMU) for SNP discovery and their utilization by developing genotyping assays. The pipeline features functionalities such as pre-processing of raw data, integration of open source alignment tools (Bowtie2, BWA, Maq, NovoAlign and SOAP2), SNP prediction (SAMtools/SOAPsnp/CNS2snp and CbCC) methods and interfaces for developing genotyping assays. The pipeline outputs a list of high quality SNPs between all pairwise combinations of genotypes analyzed, in addition to the reference genome/sequence. Visualization tools (Tablet and Flapjack) integrated into the pipeline enable inspection of the alignment and errors, if any. The pipeline also provides a confidence score or polymorphism information content value with flanking sequences for identified SNPs in standard format required for developing marker genotyping (KASP and Golden Gate) assays. The pipeline enables users to process a range of NGS datasets such as whole genome re-sequencing, restriction site associated DNA sequencing and transcriptome sequencing data at a fast speed. The pipeline is very useful for plant genetics and breeding community with no computational expertise in order to discover SNPs and utilize in genomics, genetics and breeding studies. The pipeline has been parallelized to process huge datasets of next generation sequencing. It has been developed in Java language and is available at http://hpc.icrisat.cgiar.org/ISMU as a standalone free software.
Azam S, Rathore A, Shah TM, Telluri M, Amindala B, Ruperao P, Katta MAVS and Varshney RK (2014). An Integrated SNP Mining and Utilization (ISMU) pipeline for next generation sequencing data. PLoS ONE 9(7):e101754 (DOI:10.1371/journal.pone.0101754).
Abstract: Open source single nucleotide polymorphism (SNP) discovery pipelines for next generation sequencing data commonly requires working knowledge of command line interface, massive computational resources and expertise which is a daunting task for biologists. Further, the SNP information generated may not be readily used for downstream processes such as genotyping. Hence, a comprehensive pipeline has been developed by integrating several open source next generation sequencing (NGS) tools along with a graphical user interface called Integrated SNP Mining and Utilization (ISMU) for SNP discovery and their utilization by developing genotyping assays. The pipeline features functionalities such as pre-processing of raw data, integration of open source alignment tools (Bowtie2, BWA, Maq, NovoAlign and SOAP2), SNP prediction (SAMtools/SOAPsnp/CNS2snp and CbCC) methods and interfaces for developing genotyping assays. The pipeline outputs a list of high quality SNPs between all pairwise combinations of genotypes analyzed, in addition to the reference genome/sequence. Visualization tools (Tablet and Flapjack) integrated into the pipeline enable inspection of the alignment and errors, if any. The pipeline also provides a confidence score or polymorphism information content value with flanking sequences for identified SNPs in standard format required for developing marker genotyping (KASP and Golden Gate) assays. The pipeline enables users to process a range of NGS datasets such as whole genome re-sequencing, restriction site associated DNA sequencing and transcriptome sequencing data at a fast speed. The pipeline is very useful for plant genetics and breeding community with no computational expertise in order to discover SNPs and utilize in genomics, genetics and breeding studies. The pipeline has been parallelized to process huge datasets of next generation sequencing. It has been developed in Java language and is available at http://hpc.icrisat.cgiar.org/ISMU as a standalone free software.
Full article
The use of SNP markers for linkage mapping in diploid and tetraploid peanuts
Bertioli DJ, Ozias-Akins P, Chu Y, Dantas KM, Santos SP, Gouvea E, Guimarães PM, Leal-Bertioli SCM, Knapp SJ and Moretzsohn MC (2014). The use of SNP markers for linkage mapping in diploid and tetraploid peanuts. G3 4(1):89–96. First published online in November 2013. (G6010.01)
Abstract: Single nucleotide polymorphic markers (SNPs) are attractive for use in genetic mapping and marker-assisted breeding because they can be scored in parallel assays at favorable costs. However, scoring SNP markers in polyploid plants like the peanut is problematic because of interfering signal generated from the DNA bases that are homeologous to those being assayed. The present study used a previously constructed 1536 GoldenGate SNP assay developed using SNPs identified between two A. duranensis accessions. In this study, the performance of this assay was tested on two RIL mapping populations, one diploid (A. duranensis × A. stenosperma) and one tetraploid [A. hypogaea cv. Runner IAC 886 × synthetic tetraploid (A. ipaënsis × A. duranensis)4×]. The scoring was performed using the software GenomeStudio version 2011.1. For the diploid, polymorphic markers provided excellent genotyping scores with default software parameters. In the tetraploid, as expected, most of the polymorphic markers provided signal intensity plots that were distorted compared to diploid patterns and that were incorrectly scored using default parameters. However, these scorings were easily corrected using the GenomeStudio software. The degree of distortion was highly variable. Of the polymorphic markers, approximately 10% showed no distortion at all behaving as expected for single-dose markers, and another 30% showed low distortion and could be considered high-quality. The genotyped markers were incorporated into diploid and tetraploid genetic maps of Arachis and, in the latter case, were located almost entirely on A genome linkage groups.
Bertioli DJ, Ozias-Akins P, Chu Y, Dantas KM, Santos SP, Gouvea E, Guimarães PM, Leal-Bertioli SCM, Knapp SJ and Moretzsohn MC (2014). The use of SNP markers for linkage mapping in diploid and tetraploid peanuts. G3 4(1):89–96. First published online in November 2013. (G6010.01)
Abstract: Single nucleotide polymorphic markers (SNPs) are attractive for use in genetic mapping and marker-assisted breeding because they can be scored in parallel assays at favorable costs. However, scoring SNP markers in polyploid plants like the peanut is problematic because of interfering signal generated from the DNA bases that are homeologous to those being assayed. The present study used a previously constructed 1536 GoldenGate SNP assay developed using SNPs identified between two A. duranensis accessions. In this study, the performance of this assay was tested on two RIL mapping populations, one diploid (A. duranensis × A. stenosperma) and one tetraploid [A. hypogaea cv. Runner IAC 886 × synthetic tetraploid (A. ipaënsis × A. duranensis)4×]. The scoring was performed using the software GenomeStudio version 2011.1. For the diploid, polymorphic markers provided excellent genotyping scores with default software parameters. In the tetraploid, as expected, most of the polymorphic markers provided signal intensity plots that were distorted compared to diploid patterns and that were incorrectly scored using default parameters. However, these scorings were easily corrected using the GenomeStudio software. The degree of distortion was highly variable. Of the polymorphic markers, approximately 10% showed no distortion at all behaving as expected for single-dose markers, and another 30% showed low distortion and could be considered high-quality. The genotyped markers were incorporated into diploid and tetraploid genetic maps of Arachis and, in the latter case, were located almost entirely on A genome linkage groups.
QTL analysis of fertile spike number in wheat
Ma H, Dong F, Liang Z, Wang S, Wang H, Jing R and Sun D (2014). QTL analysis of fertile spike number in wheat. Journal of Agriculture 4(4):5−8. Article in Chinese with abstract in English. Not open access; view journal website. (G7010.02.01)
Ma H, Dong F, Liang Z, Wang S, Wang H, Jing R and Sun D (2014). QTL analysis of fertile spike number in wheat. Journal of Agriculture 4(4):5−8. Article in Chinese with abstract in English. Not open access; view journal website. (G7010.02.01)
