20th May 2013 by CareliaJuarez No Comments
K. Kleinknecht, J. Möhring, K.P. Singh, P.H. Zaidi, G.N. Atlin and H.P. Piepho
The maize (Zea mays L.) growing area in India is divided into five zones for cultivar testing. During triannual testing of genotypes in official trials within the All-India Coordinated Maize Improvement Program (AICMIP), a large number of entries is rejected each year. Therefore, only a low number of entries is carried forward to the advanced stage of testing. The subdivision of the breeding sites into zones results in limited data per zone. Hence, the question arises how to select the best genotypes per zone and how information can be borrowed across zones to improve the accuracy of selection within zones. We compared the performance of best linear unbiased prediction (BLUP) using the correlation of genetic effects between zones with best linear unbiased estimation (BLUE) based on data per zone. In both cases, data were analyzed using a mixed model. We used simulations to calculate correlations between the true simulated values and the predicted genotype values obtained by BLUE and BLUP using the same models. The data structure and the variance components used in simulations were based on the analysis of 40 triannual series of four different maize maturity groups. Best linear unbiased prediction outperformed BLUE in 38 out of 40 series and on average across all series. An advantage of BLUP was observed for varying genetic correlations between zones. We conclude that the use of BLUP enhanced the estimation accuracy in zoned AICMIP maize testing trials and can be recommended for future use in these trials.
Tags: Best linear unbiased prediction, maize, Statistics
Categories: Articles of CIMMYTs scientists, Crop Science
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20th May 2013 by CareliaJuarez No Comments
German Muttoni, Natalia Palacios-Rojas, Luis Galicia, Aldo Rosales, Kevin V. Pixley and Natalia de Leon
Maize is one of the most important crops worldwide. Historically, breeding efforts in this crop have been primarily focused on the improvement of grain yield and stability and just recently also on the potential utility of maize stover (above ground biomass excluding the grain) as a source of biomass for the production of feed, fiber and cellulosic ethanol. The International Maize and Wheat Improvement Center (CIMMYT) holds one of the largest maize germplasm collections in the world and therefore is an important source of phenotypic and genetic diversity for many traits. Our objectives were to assess the phenotypic diversity for cell wall composition and biomass digestibility in Mexican tropical, subtropical and highland maize landraces and elite maize lines (CMLs) in the CIMMYT germplasm collection, as well as to evaluate the relationship between place of origin of these materials and phenotypic expression of biomass compositional traits. The range of variation for neutral detergent fiber for three groups of landraces was from 47 to 73%. Slightly larger levels of phenotypic variation were observed for this trait in the set of CMLs evaluated (42 to 78%). Some of the inbred lines, such as CML 507, presented superior characteristics in terms of cell wall composition and digestibility. The Tuxpeño tropical-subtropical race, widely used in CIMMYT breeding programs, formed a cluster characterized by high cell wall content and low biomass digestibility. The CIMMYT germplasm collection appears to be a vast source of untapped genetic and phenotypic variation for the improvement of maize biomass composition.
Tags: Biomass digestibility, Cell wall composition, Genetic diversity, Maize landraces, Stover quality
Categories: Articles of CIMMYTs scientists, Maydica
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20th May 2013 by CareliaJuarez No Comments
M.T. Vinayan, Raman Babu, T. Jyothsna, P.H. Zaidi and M. Blümmel
A panel of 276 inbred lines from CIMMYT’s Drought tolerant maize for Africa program was test crossed to maize line CML312 and the single crosses were evaluated for grain and stover yields, plant height (PH), days to 50% anthesis (DtA50) and silking, stover nitrogen (N), neutral (NDF) and acid detergent fiber (ADF), acid detergent lignin (ADL), in vitro organic matter digestibility (IVOMD) and metabolizable energy (ME) content. Most stover fodder quality traits were highly significantly different among the lines except ADF. These differences were substantial among best and worst lines for the traits, with stover N varying threefold and NDF, ADF and IVOMD by more than 10 percentage units. Among the agronomic traits, significant positive associations were observed among grain and stover yield. Grain yield was significantly negatively associated with DtA50 and Anthesis to silking interval (AtS) and positively with PH. Stover yield was significantly negatively associated with DtA50 and positively with PH. Desirable stover quality traits N, IVOMD and ME were significantly negatively associated with grain yield (R2 = 0.25–0.28) while undesirable quality traits NDF, ADF and ADL were significantly positively associated with grain yield (R2 = 0.04–0.23). Stover yields were largely unrelated fodder quality traits except for a significant negative association with NDF and ADF (R2 = 0.04 to 0.08). GWAS analysis carried out using GBS (genotyping by sequencing) and a 55K SNPs genotypic dataset revealed several regions of significant association for N, ADF and IVOMD, each explaining from 3 to 9% of phenotypic variance for these fodder quality traits. SYN7725 from the 55K chip on chromosome 4 explained the largest proportion of phenotypic variance (~9%) for ADF and had a robust minor allele frequency (MAF) of 0.35. A specific genomic region on chromosome 3 (132.7–149.2 Mb) was found to be significantly associated with all the three forage quality traits, with the largest effect on IVOMD. This region merits attention for further validation and marker-assisted introgressions. A cellulose-related candidate gene, Xyloglucan endotransglucosylase/hydrolase (xth1, GRMZM2G119783) was also identified closer to the peak on chr.10 (~76.9 Mb) for ADF, which has been previously demonstrated to have a significant role in fiber elongation in cotton.
Tags: Genomic regions for stover fodder quality, Genotyping by sequencing, Maize stover fodder quality
Categories: Articles of CIMMYTs scientists, Field Crops Research
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13th May 2013 by CareliaJuarez No Comments
G. Dignat, C. Welcker, M. Sawlins, J.M. Ribaut and F. Tardieu
We have tested to what extent the growth ability of several organs of maize share a common genetic control. Every night, leaf elongation rate reaches a maximum value (LERmax) that has a high heritability, is repeatable between experiments and is correlated with final leaf length. Firstly, we summarized quantitative trait loci (QTLs) of LERmax and of leaf length in three mapping populations. Among the 14 consensus QTLs (cQTLs) of leaf length, seven co-located with cQTLs of LERmax with consistent allelic effects. Nine cQTLs of LERmax(4% of the genome) were highly reliable and confirmed by introgression lines. We then compared these QTLs with those affecting the growths of leaves, shoots, roots or young reproductive organs, detected with the same mapping populations in three field experiments or in literature datasets. Five of the nine most reliable cQTLs of LERmax co-located with QTLs involved in the growth of other organs (but not in flowering time) with consistent allelic effects. Reciprocally, two-thirds of the 20 QTLs of growth of different organs co-located with cQTLs of LERmax. Hence, LERmax, as determined in a phenotyping platform, is an indicator of the growth ability of other organs of the plant in controlled or in-field conditions.
Tags: Leaf growth, Meta-analysis, Pleiotropy, qtl
Categories: Articles of CIMMYTs scientists, Plant Cell and Environment
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13th May 2013 by CareliaJuarez No Comments
Laurel Cooper, Ramona L. Walls, Justin Elser, Maria A. Gandolfo, Dennis W. Stevenson, Barry Smith, Justin Preece, Balaji Athreya, Christopher J. Mungall, Stefan Rensing, Manuel Hiss, Daniel Lang, Ralf Reski, Tanya Z. Berardini, Donghui Li, Eva Huala, Mary Schaeffer, Naama Menda, Elizabeth Arnaud, Rosemary Shrestha, Yukiko Yamazaki and Pankaj Jaiswal
The Plant Ontology (PO; http://www.plantontology.org/) is a publicly available, collaborative effort to develop and maintain a controlled, structured vocabulary (‘ontology’) of terms to describe plant anatomy, morphology and the stages of plant development. The goals of the PO are to link (annotate) gene expression and phenotype data to plant structures and stages of plant development, using the data model adopted by the Gene Ontology. From its original design covering only rice, maize and Arabidopsis, the scope of the PO has been expanded to include all green plants. The PO was the first multispecies anatomy ontology developed for the annotation of genes and phenotypes. Also, to our knowledge, it was one of the first biological ontologies that provides translations (via synonyms) in non-English languages such as Japanese and Spanish. As of Release #18 (July 2012), there are about 2.2 million annotations linking PO terms to >110,000 unique data objects representing genes or gene models, proteins, RNAs, germplasm and quantitative trait loci (QTLs) from 22 plant species. In this paper, we focus on the plant anatomical entitybranch of the PO, describing the organizing principles, resources available to users and examples of how the PO is integrated into other plant genomics databases and web portals. We also provide two examples of comparative analyses, demonstrating how the ontology structure and PO-annotated data can be used to discover the patterns of expression of theLEAFY (LFY) and terpene synthase (TPS) gene homologs.
Tags: Bioinformatics, Comparative genomics, Genome annotation, Ontology, Plant anatomy, Terpene synthase
Categories: Articles of CIMMYTs scientists
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13th May 2013 by CareliaJuarez No Comments
Mohammad Farkhari, Alan Krivanek, Yunbi Xu, Tingzhao Rong, Mohammad R. Naghavi, Bahman Y. Samadi and Yanli Lu
Large-scale selective genotyping and high-throughput analysis are two important strategies for low-cost and high-effective genetic mapping. In this study, selective genotyping was applied to four maize F2 populations. Thirty plants were selected from each of the two tails of the original F2 populations to represent extreme resistant and susceptible plants to root lodging, and genotyped individually with 1536 single nucleotide polymorphisms (SNPs). A quantitative trait locus (QTL) was declared when at least three closely linked SNPs showed significant allele frequency difference between the two tails. Nine QTL were identified for root lodging across the four populations, which were located on chromosomes 2, 4, 5, 7, 8 and 10 and one of them was shared between two populations. A total of 20 segregation distortion regions (SDRs) were identified across the four populations, one of which was co-localized with a QTL on chromosome 4. The tightly linked SNPs identified in this study can be used for marker-assisted selection for root lodging. Selective genotyping, when combined with pooled DNA analysis, can be used to develop strategies for high-throughput genetic mapping for all crops.
Tags: High-throughput genetic mapping, maize, Quantitative trait loci, Root lodging, Segregation distortion regions, Selective genotyping
Categories: Articles of CIMMYTs scientists, Plant Breeding
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13th May 2013 by CareliaJuarez No Comments
P.G. Pardey, J.M. Beddow, D.J. Kriticos, T.M. Hurley, R.F. Park, E. Duveiller, R.W. Sutherst, J.J. Burdon and D. Hodson
Stem rust caused by Puccinia graminis f. sp. tritici is a potentially devastating fungal disease that can kill wheat plants and small grain cereals but more typically reduces foliage, root growth, and grain yields [e.g., (1, 2)]. After years of success in keeping the disease at bay, new virulent races (collectively referred to as “Ug99”) have emerged, with the potential to infect much of the world’s wheat (3). Despite, or because of, the success of past research, these programs saw an eventual rundown in support (4). We estimate global wheat losses over the past 50 years absent investments in research to limit impacts of stem rust and discuss how this can inform decisions about “right-sizing” research investments.
Tags: rust
Categories: Articles of CIMMYTs scientists, Science
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13th May 2013 by CareliaJuarez No Comments
J. Crossa, P. Pérez, J. Hickey, J. Burgueño, L. Ornella, J. Cerón-Rojas, X. Zhang, S. Dreisigacker, R. Babu, Y. Li, D. Bonnett and K. Mathews
Genomic selection (GS) has been implemented in animal and plant species, and is regarded as a useful tool for accelerating genetic gains. Varying levels of genomic prediction accuracy have been obtained in plants, depending on the prediction problem assessed and on several other factors, such as trait heritability, the relationship between the individuals to be predicted and those used to train the models for prediction, number of markers, sample size and genotype × environment interaction (GE). The main objective of this article is to describe the results of genomic prediction in International Maize and Wheat Improvement Center’s (CIMMYT’s) maize and wheat breeding programs, from the initial assessment of the predictive ability of different models using pedigree and marker information to the present, when methods for implementing GS in practical global maize and wheat breeding programs are being studied and investigated. Results show that pedigree (population structure) accounts for a sizeable proportion of the prediction accuracy when a global population is the prediction problem to be assessed. However, when the prediction uses unrelated populations to train the prediction equations, prediction accuracy becomes negligible. When genomic prediction includes modeling GE, an increase in prediction accuracy can be achieved by borrowing information from correlated environments. Several questions on how to incorporate GS into CIMMYT’s maize and wheat programs remain unanswered and subject to further investigation, for example, prediction within and between related bi-parental crosses. Further research on the quantification of breeding value components for GS in plant breeding populations is required.
Tags: Bayesian LASSO, Genomic selection, Genotype x environment interaction, Reproducing kernel Hilbert space regression
Categories: Articles of CIMMYTs scientists, Heredity
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6th May 2013 by CareliaJuarez No Comments
Sukhwinder Singh, Ravi P. Singh, Sridhar Bhavani, Julio Huerta-Espino and Eric Eugenio Lopez-Vera
Races of stem rust fungus pose a major threat to wheat production worldwide. We mapped adult plant resistance (APR) to Ug99 in 141 lines of a PBW343/Muu recombinant inbred lines (RILs) population by phenotyping them for three seasons at Njoro, Kenya in field trials and genotyping them with Diversity Arrays Technology (DArT) markers. Moderately susceptible parent PBW343 and APR parent Muu displayed mean stem rust severities of 66.6 and 5 %, respectively. The mean disease severity of RILs ranged from 1 to 100 %, with an average of 23.3 %. Variance components for stem rust severity were highly significant (p < 0.001) for RILs and seasons and the heritability (h 2) for the disease ranged between 0.78 and 0.89. Quantitative trait loci (QTL) analysis identified four consistent genomic regions on chromosomes 2BS, 3BS, 5BL, and 7AS; three contributed by Muu (QSr.cim-2BS, QSr.cim-3BS and QSr.cim-7AS) and one (QSr.cim-5BL) derived from PBW343. RILs with flanking markers for these QTLs had significantly lower severities than those lacking the markers, and combinations of QTLs had an additive effect, significantly enhancing APR. The QTL identified on chromosome 3BS mapped to the matching region as the known APR gene Sr2. Four additional QTLs on chromosomes 1D, 3A, 4B, and 6A reduced disease severity significantly at least once in three seasons. Our results show a complex nature of APR to stem rust where Sr2 and other minor slow rusting resistance genes can confer a higher level of resistance when present together.
Tags: genetics, QTL mapping
Categories: Articles of CIMMYTs scientists, Theroetical and Applied Genetics
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6th May 2013 by CareliaJuarez No Comments
Krishna Prasad Devkota, Ahmad Manschadi, John P.A. Lamers, Mina Devkota, and Paul L.G. Viek
Increasing water shortage and low water productivity in the irrigated drylands of Central Asia are compelling farmers to develop and adopt resource conservation technologies. Nitrogen (N) is the key nutrient for crop production in rice–wheat cropping systems in this region. Nitrogen dynamics of dry seeded rice-(aerobic, anaerobic) planted in rotation with wheat (well drained, aerobic) can differ greatly from those of conventional rice cultivation. Soil mineral N dynamics in flood irrigated rice has extensively been studied and understood, however, the impact of establishment method and residue levels on this dynamics remains unknown. Experiments on resource conservation technologies were conducted between 2008 and 2009 to assess the impact of two establishment methods (beds and flats) in combination with three (R0, R50 and R100) residue levels and two irrigation modes (alternate wet and dry (AWD) irrigation (all zero till), and a continuously flooded conventional tillage (dry tillage)) with water seeded rice (WSR) on the mineral N dynamics under dry seeded rice (DSR)-surface seeded wheat systems. N balance from the top 80 cm soil layers indicated that 32–70% (122–236 kg ha−1) mineral N was unaccounted (lost) during rice cropping. The amount of unaccounted mineral N was affected by the irrigation method. Residue retention increased (p < 0.001) the unaccounted mineral N content by 38%. With AWD irrigation, the N loss was not different among dry seeded rice in flat (DSRF), dry seeded rice in bed (DSRB), and conventional tillage WSR. Under different irrigation, establishment methods and residue levels, unaccounted mineral N was mainly affected by plant N uptake and soil mineral N content. Major amounts (43–58%) of unaccounted mineral N from DSR field occurred between seeding and panicle initiation (PI). During the entire rice and wheat growing seasons, NH4
N consistently remained at very high levels, while, NO3N remained at very low levels in all treatments. In rice, the irrigation method affected NH4N content. Effect of residue retention and establishment methods were not significant on NH4N and NO3N dynamics in both crops and years. Further evidence of the continuously fluctuating water filled pore spaces (WFPS) of 64% and the microbial aerobic activity of 93% at the top 10 cm soil surface during rice growing season indicates soil in the DSR treatments was under frequent aerobic–anaerobic transformation, a conditions very conducive for higher amounts of N loss. In DSR treatments, the losses appeared to be caused by a combination of denitrification, leaching and N immobilization. When intending to use a DSR management strategies need to be developed for appropriate N management, irrigation scheduling, and residue use to increase mineral N availability and uptake before this practices can be recommended.
Tags: Alternate wet and dry irrigation, Alternative establishment methods, Dry seeded rice, N balance, Residue retention
Categories: Articles of CIMMYTs scientists
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