Maloof Lab:Jose M. Jimenez-Gomez

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Section of Plant Biology
1002 Life Sciences, One Shields Ave.
University of California Davis
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Jose M Jimenez-Gomez, PhD.

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The information contained in this website may be outdated.
Please use my this website instead: Jimenez Gomez Lab.



Starting in October 2010, I am a Junior Group Leader in the Department of Plant Breeding and Genetics at the Max Planck Institute for Plant Breeding in Cologne. I worked as a Postdoctoral fellow in Julin Maloof's lab in the Section of Plant Biology at the University of California Davis.

In 2005, I completed my PhD. in JM Martinez-Zapater's lab at the CNB (National Center for Biotechnology) in Madrid, Spain, where I performed a quantitative genetic analysis of flowering time in tomato [1].

My main interests are based on the application of modern genetic and bioinformatic techniques to the study of plant natural variation, evolution and domestication. To do this I survey different plant species and populations presenting variation in interesting characteristics, and analyze the responsible molecular mechanism. Here is an small description of some of my recent work in the Maloof lab:

QTL and Network analysis of the shade avoidance response in Arabidopsis



It is well known that plants from different light environments exhibit different degrees of responsiveness to similar light stimulus. For example, plants accommodated to sunny environments detect foliar shade from neighboring vegetation and respond increasing their petioles/stems and reducing the time to reproduction, a phenomenon called the "shade avoidance response". On the other hand, plants adapted to live under dense canopies are less sensitive to the shade and have a reduced shade avoidance response. To identify the molecular mechanisms underlying this differences we are performing QTL analysis using a previously developed, well characterized Recombinant Inbred Line set descent from two different natural populations of Arabidopsis thaliana: Bayreuth, originary from the German low altitude fallow lands, and Shahdara, from the high mountains of Tadjikistan [2].
We grew replicated individual RILs in environments simulating shade and sun conditions and characterized them on a number of traits associated with the shade avoidance response syndrome. For the QTL analysis we calculated a shade avoidance response index fitting fixed effect models to the phenotipic data, and used an available genetic map for the population that includes more than 500 Single Feature Polymorphism (SFP) markers [3].


LOD score graph for several of the traits measured



We focused in a chromosomal region containing close to 400 genes to fine map and identify the gene responsible for the differences found in the response to shade in the Bay-0 x Sha population. To do this we employed traditional genetic approaches as well as genomic and network analysis. This network analysis is based on coexpression of the candidate genes with other genes across microarray experiments [4], colocalization with expression QTLs [5], functional categorization [6] and presence of polymorphisms between the parental lines [7]. The use of this bioinformatic approach allowed us to identify ELF3 as the candidate gene for the shade avoidance QTL, which was then confirmed by traditional fine mapping and cloning.

Fragment of a gene network



In the publication of this work, ELF3 alleles of Bay-0 and Sha are shown to differentially affect the shade avoidance response in flowering time and circadian rhtyhms [8]

Expresion profiling and Single Nuncleotide Polymorphism discovery in cultivated tomato and its wild relatives



Tomato is a specially interesting species because of its natural history, phenotypic diversity among its wild relatives and economic importance. To study the genomic variation among the wild tomato species, we first mined the numerous tomato EST sequences available in the databases in search of polymorphisms. In this dataset, we estimated divergence rates among genes from selected species, and obtained a new set of molecular markers useful in natural variation studies. We performed functional and evolutionary pre-genomic analyses, which gave us an idea of which gene families evolve more rapidly/slowly and have been important during tomato domestication. The results from this work were published [9] and are available to the community here. Now, we are using RNAseq to sequence the transcriptome of four tomato species grown in sun and shade: S. lycopersicum var M82, S. pennellii, S. pimpinellifollium and S. habrochaites. We developed bioinformatic pipelines to analyze the more than 400 million reads obtained fronm different tissues, species and conditions. The pipeline include scripts that filter and map the reads, detect polymorphisms, calculte their effect on the proteins, perform evolutionary analyses and calculate genome-wide expression levels. Using this methods we identified more than 500.000 polymorphisms in these four speceies and calculated expression differences between species, tissues and environmental conditions.



Molecular evolution of PHYTOCHROME B



PHYTOCHROME B (PHYB) is the main plant photoreceptor involved in the shade avoidance response. This gene has been reported to be under selective pressure, suggesting that plants with different shade avoidance responses may have different functional alleles of PHYB. Under these presumptions we are sequencing and cloning PHYB genes from a number of species with diverse shade avoidance behaviors. We will soon test if the variation in light responses between these plants are due to particular amino-acid changes in this photoreceptor.

amino-acid changes in a fragment of the PHYB gene in 8 species, red and black bars indicate non-conserved/conserved amino-acid changes respectively



References


  1. Jiménez-Gómez JM, Alonso-Blanco C, Borja A, Anastasio G, Angosto T, Lozano R, and Martínez-Zapater JM. Quantitative genetic analysis of flowering time in tomato. Genome. 2007 Mar;50(3):303-15. DOI:10.1139/g07-009 | PubMed ID:17502904 | HubMed [Jimenez-Gomez07]
  2. Loudet O, Chaillou S, Camilleri C, Bouchez D, and Daniel-Vedele F. Bay-0 x Shahdara recombinant inbred line population: a powerful tool for the genetic dissection of complex traits in Arabidopsis. Theor Appl Genet. 2002 May;104(6-7):1173-1184. DOI:10.1007/s00122-001-0825-9 | PubMed ID:12582628 | HubMed [Loudet02]
  3. West MA, van Leeuwen H, Kozik A, Kliebenstein DJ, Doerge RW, St Clair DA, and Michelmore RW. High-density haplotyping with microarray-based expression and single feature polymorphism markers in Arabidopsis. Genome Res. 2006 Jun;16(6):787-95. DOI:10.1101/gr.5011206 | PubMed ID:16702412 | HubMed [West06]
  4. [Riken]
  5. West MA, Kim K, Kliebenstein DJ, van Leeuwen H, Michelmore RW, Doerge RW, and St Clair DA. Global eQTL mapping reveals the complex genetic architecture of transcript-level variation in Arabidopsis. Genetics. 2007 Mar;175(3):1441-50. DOI:10.1534/genetics.106.064972 | PubMed ID:17179097 | HubMed [West07]
  6. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Issel-Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, and Sherlock G. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet. 2000 May;25(1):25-9. DOI:10.1038/75556 | PubMed ID:10802651 | HubMed [GO_Classification]
  7. Clark RM, Schweikert G, Toomajian C, Ossowski S, Zeller G, Shinn P, Warthmann N, Hu TT, Fu G, Hinds DA, Chen H, Frazer KA, Huson DH, Schölkopf B, Nordborg M, Rätsch G, Ecker JR, and Weigel D. Common sequence polymorphisms shaping genetic diversity in Arabidopsis thaliana. Science. 2007 Jul 20;317(5836):338-42. DOI:10.1126/science.1138632 | PubMed ID:17641193 | HubMed [Clark07]
  8. Jiménez-Gómez JM, Wallace AD, and Maloof JN. Network analysis identifies ELF3 as a QTL for the shade avoidance response in Arabidopsis. PLoS Genet. 2010 Sep 9;6(9):e1001100. DOI:10.1371/journal.pgen.1001100 | PubMed ID:20838594 | HubMed [Jimenez-Gomez10]
  9. Jiménez-Gómez JM and Maloof JN. Sequence diversity in three tomato species: SNPs, markers, and molecular evolution. BMC Plant Biol. 2009 Jul 3;9:85. DOI:10.1186/1471-2229-9-85 | PubMed ID:19575805 | HubMed [Jimenez-Gomez09]
All Medline abstracts: PubMed | HubMed