Quantitative Genetics and Maize Breeding

Jianming Yu, Professor and Pioneer Distinguished Chair in Maize Breeding

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Department of Agronomy, Iowa State University, Ames, IA 50011-1051

Phone: 515-294-2757, Fax: 515-294-3163, Email: jmyu@iastate.edu

Jianming Yu is Professor and Pioneer Distinguished Chair in Maize Breeding in the Department of Agronomy, Iowa State University. The focus of Yu’s program is to address significant questions in quantitative genetics by combining cutting-edge genomic technologies and maize breeding. All members of this research program conduct empirical experiments in plant breeding and genetics and contribute to summer and winter nursery work, and many of them also carry out computer simulations or bioinformatics research to generalize their specific findings to a broad context. Yu teaches a graduate student class, AGRON 621 - Advanced Plant Breeding, each Spring semester. Guiding questions addressed by this program include:

  • How can we leverage design thinking, genetic design, and experimental design to plan out our research?

  • How can we efficiently identify genes underlying quantitative traits so that the resulting empirical findings can help answer fundamental questions?

  • How should we design the current plant breeding methods to make better use of genetic resources and high throughput genotyping and phenotyping technologies?

Yu's research integrates knowledge in Plant Breeding, Quantitative Genetics, Genomics, Molecular Genetics, and Statistics, and has the ultimate goal of developing and implementing new strategies and methods in trait dissection and crop improvement. Current research includes Genome-Wide Association Studies (GWAS) with diverse germplasm or multiple designed mapping populations (such as Nested Association Mapping, NAM; or meta-QTL analysis), Genomic Selection (GS; or Genome-Wide Selection GWS) to efficiently integrate high throughput genotyping into various breeding processes, Gene Cloning for traits with agronomic and domestication importance, Genotype-by-Environment Interaction (GEI) and Epistasis dissection to causal polymorphic sites, Genome and Chromosome Size Evolution across taxonomic groups, and Genome-Wide Base Composition changes and underlying principles. Check out a list of news releases about our research.

Dr. Yu is a faculty member of three Graduate Programs: Plant Breeding and Genetics (PB&G) in Agronomy, Interdepartmental Genetics and Genomics (IG2), and Interdepartmental Plant Biology (IPB).

(YouTube) Integrating Design, Analytics, and Genomics in Crop Improvement, or (UNLMeidaHub)

(YouTube) Towards a Better Understanding of Genes, Organisms, and Environments

(YouTube) Pattern Discovery, Predictive Modeling, and Design in Plant Breeding and Genetics

(YouTube) Genomic Selection: Historical Context, Technical Details, Empirical Findings, and Perspectives

(YouTube) Quantitative Genetics in the Era of High Throughput Genotyping and Phenotyping

Research Highlights

[Breeding Strategy]

Yu, X., X. Li, T. Guo, C. Zhu, Y. Wu, S.E. Mitchell, K.L. Roozeboom, D. Wang, M.L. Wang, G.A. Pederson, T.T. Tesso, P.S. Schnable, R. Bernardo, and J. Yu*. 2016. Genomic prediction contributing to a promising global strategy to turbocharge gene banks. Nature Plants 2:16150.

Yu, J.* 2009. Realizing the potential of ultrahigh throughput genomic technologies in plant breeding. The Plant Genome 2:2.

Bernardo, R.*, and J. Yu. 2007. Prospects for genomewide selection for quantitative traits in maize. Crop Science 47:1082-1090.

[Complex Trait Dissection]

Li, Xin, T. Guo, Q. Mu, Xianran Li*, and J. Yu*. 2018. Genomic and environmental determinants and their interplay underlying phenotypic plasticity. PNAS (online).

Li, Xin, Xianran Li, E. Fridman, T.T. Tesso, and J. Yu*. 2015. Dissecting repulsion linkage in the dwarfing gene Dw3 region for sorghum plant height provides insights into heterosis. PNAS 112:11823-11828.

Li, X., C. Zhu, C.-T. Yeh, W. Wu, K. Petsch, E. Takacs, F. Tian, G. Bai, E.S. Buckler, G.J. Muehlbauer, M.C.P. Timmermans, M.J. Scanlon, P.S. Schnable* and J. Yu*. 2012. Genic and non-genic contributions to natural variation of quantitative traits in maize. Genome Research 22:2436-2444.

Zhu, C., X. Li, and J. Yu* 2011. Integrating rare-variant testing, function prediction, and gene network in composite resequencing-based genome-wide association studies (CR-GWAS). G3 1:233-243.

Sun, G., C. Zhu, S. Yang, W. Song, M. H. Kramer, H.-P. Piepho, and J. Yu*. 2010. Variation explained in mixed model association mapping. Heredity 105:333-340.

Zhang, Z.*, E. Ersoz, C.-Q. Lai, R.J. Todhunter, H.K. Tiwari, M.A. Gore, P.J. Bradbury, J. Yu, D.K. Arnett, J.M. Ordovas, and E.S. Buckler. 2010. Mixed linear model approach adapted for genome-wide association studies. Nature Genetics 42:355-360.

Zhu, C., and J. Yu*. 2009. Nonmetric multidimensional scaling corrects for populationstructure in association mapping with different sample types. Genetics 182:875-888.

Yu, J.*, Z. Zhang, C. Zhu, D. Tabanao, G. Pressoir, M.R. Tuinstra, S. Kresovich, R.J. Todhunter, and E.S. Buckler. 2009. Simulation appraisal of the adequacy of number of background markers for relationship estimation in association mapping. The Plant Genome 2:63-77.

Zhu, C., M. Gore, E.S. Buckler, and J. Yu*. 2008. Status and prospects of association mapping in plants. The Plant Genome 1:5-20.

Yu, J., J.B. Holland, M.D. McMullen, and E.S. Buckler*. 2008. Genetic design and statistical power of nested association mapping in maize. Genetics 138:539-551.

Yu, J., G. Pressoir, W.H. Briggs, I. Vroh Bi, M. Yamasaki, J.F. Doebley, M.D. McMullen, B.S. Gaut, D. Nielsen, J.B. Holland, S. Kresovich, and E.S. Buckler*. 2006. A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nature Genetics 38:203-208.

Yu, J., and E.S. Buckler*. 2006. Genetic association mapping and genome organization of maize. Current Opinion in Biotechnology 17:155-160.

[Genes and Genetics]

Lin, Z., X. Li, L.M. Shannon, C.-T. Yeh, M.L. Wang, G. Bai, Z. Peng, J. Li, H.N. Trick, T.E. Clemente, J. Doebley, P.S. Schnable, M.R. Tuinstra, T.T. Tesso, F. White, and J. Yu*. 2012. Parallel domestication of the Shattering1 genes in cereals. Nature Genetics 44:720–724.

Wu, Y., X. Li, W. Xiang, C. Zhu, Z. Lin, Y. Wu, J. Li, S. Pandravada, D.D. Ridder, G. Bai, M.L. Wang, H.N. Trick, S.R. Bean, M.R. Tuinstra, T.T. Tesso, and J. Yu*. 2012. Presence of tannins in sorghum grains is conditioned by different natural alleles of Tannin1. PNAS 109:10281-10286.

Wisser, R.J.*, J.M. Kolkman, M.E. Patzoldt, J.B. Holland, J. Yu, M. Krakowsky, R.J. Nelson, and P.J. Balint-Kurti. 2011. Multivariate analysis of maize disease resistances suggests a pleiotropic genetic basis and implicates a glutathione S-transferase gene. PNAS 108:7339-7344.

Tian, Z., Q. Qian, Q. Liu, M. Yan, X. Liu, C. Yan, G. Liu, Z. Gao, S. Tang, D. Zeng, Y. Wang, J. Yu*, M. Gu*, and J. Li*. 2009. Allelic diversities in rice starch biosynthesis lead to a diverse array of rice eating and cooking qualities. PNAS 106:21760-21765.

Buckler, E.S.*, J.B. Holland*, ..., J. Yu, Z. Zhang, S. Kresovich*, and M.M. Mullen* 2009. The genetic architecture of maize flowering time. Science 325:714-718.

[Genomes and Chromosomes]

Li, X., M.J. Scanlon, and J. Yu*. 2015. Evolutionary patterns of DNA base composition and correlation to polymorphisms in DNA repair systems. Nucleic Acids Research 43:3614-3625.

Li, X., C. Zhu, Z. Lin, Y. Wu, D. Zhang, G. Bai, W. Song, J. Ma, G.J. Muehlbauer, M.J. Scanlon, M. Zhang*, and J. Yu*. 2011. Chromosome size in diploid eukaryotic species centers on the average length with a conserved boundary. Molecular Biology and Evolution 28:1901–1911.


UPDATE (01/23/2022) Congratulations to Qi Mu for her paper on phenotypic plasticity!

UPDATE (11/30/2021) Congratulations to Matthew Dzievit for his paper on comprehensive assessment of genomic prediction, featured on the Cover of The Plant Genome!

Congratulations to Jinyu Wang for her paper on high throughput phenotyping to dissect seasonal vegetation index!

UPDATE (06/07/2021) Congratulations to Xianran Li and Tingting Guo for an integrated framework for GWAS and GS under GxE.

Molecular Plant publication: An integrated framework reinstating the environmental dimension for GWAS and genomic selection in crops

New Release: Sensing what plants sense: Integrated framework helps scientists explain biology and predict crop performance

UPDATE (01/14/2021) Congratulations to Laura Tibbs Cortes for an in-depth review of GWAS in plants.

The Plant Genome publication: Status and prospects of genome-wide association studies in plants

UPDATE (11/03/2020) Congratulations to Xiaoqing Yu for the 2nd paper on the topic of "Turbocharging Gene Banks through Genomic Prediction".

Plant Biotechnology Journal publication: Genomic prediction of maize micro-phenotypes provides insights for optimizing selection and mining diversity

UPDATE (08/03/2020) A set of relevant documents: National Academies of Sciences Report, “Science Breakthroughs 2030"; USDA's Agriculture Innovation Agenda; ASA-CSSA-SSSA and other allied societies' response to the RFI from USDA,

UPDATE (04/19/2020) Congratulations to Tingting Guo for the major discovery that led to a conceptual model in genetics: multiple levels of reaction norms to bridge the gaps among individual gene discovery, field-level phenotypic plasticity, and genomic diversity and adaptation.

Genome Research publication: Dynamic effects of interacting genes underlying rice flowering-time phenotypic plasticity and global adaptation

UPDATE (12/02/2019) Congratulations to Dr. Xianran Li for leading the completion of a study that discovered the first example of "domestication triangle" (domesticator-human, domesticate-sorghum, and environment-bird)!

Nature Plants publication: Allelochemicals targeted to balance competing selections in African agroecosystems.

New release: Sorghum study illuminates relationship between humans, crops and the environment in domestication.

News and Views by Nature Plants: When bitter is better.

UPDATE (11/11/2019) Congratulations to Dr. Zhongwei Lin for his group's dedicated research in cloning the stiff1 gene underlying stalk strength in maize! A 27.2-kilobase (kb) insertion of a transposable element was found to be responsible for the stiff stalk in B73 and other maize inbreds. The large-scale field testing was made possible by the stalk bending strength testing method developed by Lin's group.

Plant Cell Publication: A large transposon insertion in the stiff1 promoter increases stalk strength in maize

Many historically important maize inbreds (B14, B37, B64, B68, B73, and B84) were derived from the Iowa Stiff Stalk Synthetic (BSSS) population, originally put together by George F. Sprague in 1930s. These inbreds have had a prominent role in commercial hybrids either directly as parental inbreds to generate the F1 hybrids or indirectly in producing modified versions to be used as parental inbreds.

UPDATE (06/10/2019): Congratulations to Dr. Guihua Bai for his group's dedicated research to clone the gene underlying Fusarium head blight, a fungal disease that threatens wheat production worldwide.

Nature Genetics publication: A deletion mutation in TaHRC confers Fhb1 resistance to Fusarium head blight in wheat

News release: Twenty-year study nets resistance to Fusarium head blight

News and Views by Nature Genetics: A new player contributing to durable Fusarium resistance

UPDATE (04/25/2019): Congratulations to Jinyu Wang! Her first-author paper, Genome-wide nucleotide patterns and potential mechanisms of genome divergence following domestication in maize and soybean, is published in Genome Biology. This continues our discovery journey about genomes and chromosomes started by Xianran Li.

UPDATE (04/21/2019): James McNellie's paper was highlighted in the April issue of CSA News.

Make Crops Climate Ready

UPDATE (01/06/2019): Congratulations to Tingting Guo! Her first-author paper, Optimal Designs for Genomic Selection in Hybrid Crops, is published in Molecular Plant.

"design thinking and data mining techniques can be leveraged to optimize genomic prediction of hybrid performance."

"effective genomic prediction models can be established with a training set 2~13% of the size of the whole set, enabling the efficient exploration of the enormous inference space of genetic combinations."

UPDATE (01/05/2019): Congratulations to Matt Dzievit! His first-author paper, Dissection of leaf angle variation in maize through genetic mapping and meta-analysis, is published in the Plant Genome.

Genomic Hotspots Control Maize Leaf Angle

UPDATE (12/09/2018): Fourth National Climate Assessment.

On this edition of River to River, host Ben Kieffer talks with one of the contributors to the report, agronomist and Iowa State University emeritus professor Gene Takle, as well as two Iowa farmers, to get a sense of how Iowa’s ag community may be preparing for a harsher climate and unpredictable growing seasons. Podcast: Iowa Farmers React to National Climate Assessment Warnings.

UPDATE (11/01/2018): Congratulations to James McNellie! His first-author paper, Genetic mapping of foliar and tassel heat stress tolerance in maize, is published in Crop Science.

UPDATE (6/11/2018): A major methodology paper on G x E (phenotypic plasticity, reaction norm, genomic and environment determinants, genome-wide QTL/marker/gene effect continuum, genomic prediction across environments, and joint genomic regression analysis) is published today PNAS. An 8-year study and a truly enjoyable journey of learning and discovering!!!

Genomic and environmental determinants and their interplay underlying phenotypic plasticity

"This is a small step in transforming a traditional approach, but a huge leap in understanding of plasticity and predicting the performance." - Jianming Yu, 2018

UPDATE (6/4/2018): Two very insightful review/perspective papers in Statistics can help us understand narrowly the comparison of GWAS (and QTL mapping, gene cloning, mutation-based developmental biology research) and Genomic Prediction and Genomic Selection, and broadly the connections among scientific hypothesis, hypothesis-driven research, data-driven research, explanation versus prediction.

To Explain or to Predict? Galit Shmueli 2010, Statistical Science 25:289-310.

Statistical Modeling: The Two Cultures. Leo Breiman 2001, Statistical Science 16:199–231.

UPDATE (5/24/2017): The Challenge of Change, Harnessing University Discovery, Engagement, and Learning to Achieve Food and Nutrition Security is released by the APLU.

  • Challenge 1. Increase yields, profitability, and environmental sustainability simultaneously

  • Challenge 2. Develop the varieties and breeds needed for sustainable food systems

  • Challenge 3. Decrease food loss and waste through more efficient distribution systems

  • Challenge 4. Create and share resources that serve all populations

  • Challenge 5. Ensure inclusive and equitable food systems

  • Challenge 6. Address the dual burdens of undernutrition and obesity to ensure full human potential

  • Challenge 7. Ensure a safe and secure food supply that protects and improves public health

UPDATE (10/3/2016): Congratulations to Xiaoqing Yu for publishing findings from a major research project, Genomic prediction contributing to a promising global strategy to turbocharge genebanks, in Nature Plants! "The success of this project illustrates that a global, cost-effective strategy may be designed to assess the vast amount of valuable germplasm archived in 1,750 gene banks."

Please also read this excellent News and Views article, Plant breeding: Effective use of genetic diversity, from Dr. Patrick Brown.

UPDATE (05/8/2016): Congratulations to Sivakumar Sukumaran for publishing his drought tolerance dissertation research, QTL mapping for grain yield, flowering time, and stay-green traits in sorghum using genotyping-by-sequencing markers, in Crop Science! It represents dedicated research with extensive field components.

UPDATE (12/3/2015): Congratulations to Jinliang Yang from Pat Schnable's group for his discovery, Extreme-phenotype genome-wide association study (XP-GWAS): a method for identifying trait-associated variants by sequencing pools of individuals selected from a diversity panel! Great to design and investigate different ways of identifying the signals.

UPDATE (11/23/2015): Congratulations to Samuel Leiboff from Mike Scanlon's group for his discovery, Genetic control of morphometric diversity in the maize shoot apical meristem! GWAS revealed unexpected candidate genes implicated in hormone transport, cell division, and cell size for maize shoot apical meristem morphology.

UPDATE (09/08/2015): Congratulations to Xin Li for his discovery, Dissecting repulsion linkage in the dwarfing gene Dw3 region for sorghum plant height provides insights into heterosis. Theories on heterosis were proposed more than a century ago, but specific examples are still scarce. QTL mapping, trait component mapping, repulsion linkage, GWAS, multi-locus mixed model, designed crosses, and breeding implications.

UPDATE (06/05/2015): The 2015 APSIM Training Course at ISU went very well. I enjoyed learning many aspects of crop models. It would be great if more plant breeders and geneticists get involved so that future developments would be geared towards things we are interested.

UPDATE (03/11/2015): Congratulations to Xianran Li for his major discovery with broad impact, Evolutionary Patterns of DNA Base Composition and Correlation to Polymorphisms in DNA Repair Systems! Genome integrity, DNA repair, replication, evolution, mutation, cancer research, etc.

UPDATE (02/21/2015): Please note the 2015 Advanced Topics in Plant Breeding Summer Institute, June 29-July 4, 2015, Ames IA.

June 29-30: Genomic Prediction in Plant Breeding

July 1-2: Transforming Plant Breeding into an Engineering Discipline

July 3-4: Doubled Haploids in Plant Breeding

UPDATE (10/23/2014): Congratulations to Zhiwu Zhang for leading the GWAS method research published in BMC Biology, Enrichment of statistical power for genome-wide association studies.

UPDATE (06/09/2014): Two great review/perspective papers that deserve atttention, if one wants to have a solid understanding on GxE and its implications in plant breeding: 1. Predicting the future of plant breeding: complementing empirical evaluation with genetic prediction (Cooper et al. 2014); 2. The statistical analysis of multi-environment data: modeling genotype-by-environment interaction and its genetic basis (Malosetti et al. 2013).

UPDATE (04/29/2014): Vision and Change in Undergraduate Biology Education is a very relevant document for faculty.

UPDATE (02/01/2014): Graduate students in ISU Plant Breeding and Genetics program will host the 2014 R. F. Baker Plant Breeding Symposium, Moore’s Law: Does phenotyping get a turn? High throughput phenotyping advances, on Thursday, March 6, 2014.

UPDATE (12/13/2013): This document from ASPB, Unleashing a Decade of Innovation in Plant Science, has been out for a while.

Chapter 1. Predicting Traits: Increase the ability to predict plant traits from plant genomes in diverse environments.

Chapter 2. Assembling Traits: Assemble plant traits in different ways to solve problems

Chapter 3. Harnessing Plant Chemistry: Discover, catalog, and utilize plant-derived chemicals

Chapter 4. From Data to Solutions: Enhance the ability to find answers in a torrent of data

Chapter 5. Reimagine Graduate Training: Create a T-training environment for plant science doctoral students

UPDATE (11/05/2013): The principle underlying GWAS it to identify the signal flanking the causal gene, not necessarily the functional polymophisms (QTNs), particularly when there are multiple alleles with different QTNs. Check out Geoff Morris's new paper, Dissecting genome-wide association signals for loss-of-function phenotypes in sorghum flavonoid pigmentation traits, in G3.

UPDATE (07/05/2013): Pre-harvest sprouting (PHS) is a major issue in wheat production. I still remember how bad the bread tasted in some years when I was growing up. I was told that it is because of "Ya Mai Mian (Sprouted Wheat Flour, i.e., flour made from wheat kernels that are sprouted before harvest). Well, after years of research, we now have a better understanding of the genetics behind the different levels of PHS resistance in wheat. Check out the QTL cloning paper from Dr. Guihua Bai's group in Genetics. Congratulations!.

UPDATE (07/01/2013): The impact factor of The Plant Genome from CSSA is 2.463.

UPDATE (02/06/2013): Take a look at this candidate gene association mapping paper in drought tolerance of perennial ryegrass from Dr. Yiwei Jiang's group at Purdue. Congratulations to the first-author, Xiaoqing Yu!

UPDATE (01/21/2013): The workshop GS + GWAS at the 2013 PAG meeting was a great success! The meeting room was too small and folks had to sit on the floor, stand in the back of the room,, or even watched from outside of the glass doors. Zhiwu took some very nice pictures and they were passed to the meeting organizer.

Thanks to all speakers, my co-organizer, Dr. Dorian Garrick, and who attended!

UPDATE (01/20/2013): Another significant publication from our NSF SAM group, Mendelian and non-Mendelian regulation of gene expression in the maize shoot apex, at PLoS Genetics. Congratulations to Lin Li!

UPDATE (12/13/2012): My graduate student published his first-author paper, Association Mapping for Grain Quality in a Diverse Sorghum Collection, at The Plant Genome.

, News came that The Plant Genome will get its Impact Factor in 2013.

UPDATE (08/25/2012): This is a new paper from the SAM (Shoot Apical Meristem) group, Ontogeny of the Maize Shoot Apical Meristem, at Plant Cell. It is classified as a Large-Scale Biology article, and open access.

UPDATE (06/18/2012): Check out this paper, Genic and non-genic contributions to natural variation of quantitative traits in maize, at Genome Research. In this research, we addressed several critical questions in genetic architecture of complex quantitative traits: genic versus nongenic contribution, allele frequency and genetic effect, appropriate genome scans with NAM, and sequencing/genotyping priority of future routine GWAS in species with complex genomes. A comprehensive, exploratory research.

UPDATE (06/13/2012): Here is another paper from our group, Presence of tannins in sorghum grains is conditioned by different natural alleles of Tannin1, at PNAS. It involves QTL mapping, meta-QTL fine mapping, association mapping, transformation validation with an Arabidopsis mutant, and nucleotide diversity analysis across wild, landraces, and cultivars. More broadly, it involves domestication, natural selection, and health benefit. Technically, you will see the effect of allele frequency in association mapping, and the general direction of the research => “haplotype”.

[NOTE: A quick comparison of three recent gene-cloning results in sorghum => multiple, natural alleles in Ma1 (flowering time), Sh1 (shattering), and Tan1 (tannin).]

UPDATE (05/29/2012): This is a News and Views article by Kenneth Olsen at Nature Genetics about the Sh1 paper: One gene’s shattering effects.

UPDATE (05/22/2012): Take a look at our new paper, Parallel domestication of the Shattering1 genes in cereals, at Nature Genetics. It contains the map-based cloning of Sh1, haplotype analysis and association mapping, diverse origins of sorghum, comparative genomics across cereals, rice mutant analysis, and maize high-resolution QTL analysis with GBS markers. You will have to praise either the mother nature or the wisdom of ancient farmers who made this transition from the hunter-gatherer stage to agriculture.

UPDATE (04/14/2012): Computer Simulation in Plant Breeding is a comprehensive review chapter in Advances in Agronomy that highlights the critical role of computer simulation in breeding method comparison, genetic mapping, gene network and genotype-by-environment interaction, and crop modeling research. The indispensable role of computer simulation in many classic and contemporary research topics were reviewed, including breeding method, mapping power and resolution, marker-assisted selection, genomic selection, association mapping, meta-QTL analysis, plant breeding process, crop modeling, virtual plan and E-cell, and climate change.

UPDATE (10/24/2011): Here is a good example of the broad application of association mapping. Once you have assembled a diverse population, there are many traits that you can work on, such as soilborne wheat mosaic virus in U.S. winter wheat. Take a look at this new paper from Dr. Guihua Bai’s group in Phytopathology 101:1322-1329. It is essentially a combination of germplasm screening + association mapping + allelic dynamics analysis + robust markers for selection all at once. You may argue that the trait itself is not that complex though. But a very nice work.

UPDATE (08/10/2011): Validating the gene-trait relationship identified through mutational study in natural populations can be challenging, so is identifying new genes through association mapping. Ever wonder why? “Frequency” is one of the key factors that make us struggle and the ultimate reason is “Genetics”, not the lack of “Super-Statistics” for you. It sure helps to take an integrated approach to tackle various issues in GWAS. Checkout Chengsong’s paper on Rare-Variant Testing, Function Prediction, and Gene Network in G3 (open access).

G3: Genes, Genomes, Genetics is a new open-access journal by the Genetics Society of America.

UPDATE (08/09/2011): One of the common issues in association mapping is that some of the important genes may have different allelic frequencies in subpopulatoins. Controlling for population structure may, unfortunately, reduce the signal strength even we know it should be a true positive. Check out MingLi’s new paper online first at Theoretical and Applied Genetics to see what happened to the FAD2A gene and the association mapping of oleic acid, linoleic acid, and O/L content in peanut.

UPDATE (07/31/2011): Check out Clare Nelson’s paper in SNP discovery in sorghum through restriction-site associated DNA (RAD) approach in BMC Genomics (open access). Several groups are working on genotyping-by-sequencing (GBS). Once the pipelines of multiplexing, alignment, SNP calling, and imputation are optimized, it would be great to see that students in Plant Breeding and Genetics will have more time to work on phenotyping, analysis, and interpretation, rather than scoring SSRs (of course, a bit experience in this can only help).

UPDATE (05/20/2011): Finally, our paper in chromosome size, genome size, and repeat proportion is published in MBE. It is open access (Ouch! It cost a lot!). I agreed that we packed way too much work in a single paper. But please take a look at Fig. 3a and Supplementary Fig. 3. before you are bored with those derivation and simulation. I hope someone figures out how birds (and some other species) maintain genome integrity during mitosis and meiosis with those macrochromosomes and microchromosomes.

I guess we HAVE TO be serious to make such a general statement (Solute to my true statistician coauthors!).

UPDATE (05/05/2011): You’ve got to love “Quantitative Genetics”! See Randy Wisser’s great research in multi-trait association mapping of maize multiple disease resistance in PNAS.

UPDATE (01/10/2011): It is interesting to read individual papers about sequenced genomes. Will it be interesting to read a paper in which 68 eukaryotic genomes were analyzed all together? How about analysis of 128 species with sequenced genomes? Check out our stunning discovery of a fundamental and widely relevant principle: chromosome size variation in diploid eukaryotic species has a conserved boundary. Online first in Molecular Biology and Evolution.

UPDATE (09/17/2010): Diversity and population structure analysis of 205 US elite winter wheat germplasm by Guihua Bai’s group is available at The Plant Genome. These analyses laid the groundwork for further trait mapping with this panel of elite wheat germplasm.

UPDATE (02/22/2010): Most of us do not have to worry about the computational burden for the large scale genome-wide association analysis (GWAS). But if you do, either you are a big boss or you are working for a big boss :-). Check out some new algorithms Zhiwu Zhang worked out in his new Nat Genetics publication (online first soon): sire model to reduce the dimension of the matrix; and noiteration for each marker and simply obtaining the solution with the variance component estimates from the model without the marker.

Another GREAT example to study “Quantitative Genetics”! (Others: QK mixed model, NAM, and genome-wide selection)

UPDATE (01/30/2010): Wondering how to properly use R2 for mixed models and our new publication “Variation explained in mixed-model association mapping” will be online first in Heredity.

UPDATE (12/15/2009): Check out the results of a comprehensive analysis of rice eating and cooking qualities with candidate gene association mapping plus transformation validation. This is collaboration led by Dr. Jiayang Li at Institute of Genetics and Developmental Biology, Chinese Academy of Sciences. Published in PNAS.

UPDATE (09/16/2009): Our initial molecular analysis of US historic sweet sorghum collection is Online First at Theoretical and Applied Genetics.

UPDATE (08/19/2009): We are funded by DOE/USDA Biomass Genomics Research to study nitrogen use efficiency in sweet sorghum with University of Nebraska.

UPDATE (08/07/2009): The first phase of MaizeNAM analysis (Yu et al. 2008) results are out in Science 325:714-718 (multi-family linkage analysis for flowering time) and Science 325:737-740 (linkage map and residual heterozygosity in pericentralmeric regions implicated for heterosis).

UPDATE (07/30/2009): Graduate Research Assistantship available. See Employment for details.

UPDATE (07/29/2009): Zhu and Yu 2009 in Genetics July issue. A systematic examination of genetic relationships in association mapping and corresponding methods, dimension determination, non-metric multidimentional scaling, … Sorry for a long story. See Publications.