Faculty and Researchers
Yefim I. Ronin Ph.D.
For more research information, see the Korol Lab. Website
Genetic mapping, especially QTL mapping; Optimization theory; Identification, adaptation and control of dynamic systems; Theory of statistical decisions and its biological applications; Automata models of dynamic systems.
The main subjects of my activity:
- Development of new methods and model for genetic mapping of quantitative trait loci (QTL-mapping) and efficient algorithms for QTL data analysis.
- Using the algorithms of QTL-mapping to analyze concrete data generated at the Institute of Evolution and its collaborators in Israel and abroad (wheat, cattle, etc.).
- Development of new methods and algorithms for mapping marker loci (construction of multilocus maps).
- Development of methods and algorithms for multilocus consensus mappinganalysis
1. Development of new methods and model for genetic mapping of quantitative trait loci (QTL- mapping) and efficient algorithms for QTL data analysis.
In many situations, QTLs with pleotropic effects on numerous traits fail to be detected and mapped, if each of the individual effects is low. But even for significant effects, the mapping resolution and location precision based on single-trait analysis remain disappointingly low. These properties could be significantly improved by moving to multiple-trait (vector) QTL analysis. In particular, such analysis may include searching "vector QTLs" with highly significant multivariate effects even if none of the single-trait effects is significant, or may include improving the quality of single-trait mapping results by using vector-QTL analysis (increasing the power of QTL detection and precision of QTL location). The proposed here a approximate multiple-trait analysis of linked QTL includes: (1) Reduction of the initial multivariate trait space - two-QTL analysis for backcross population employing two- and three-dimensional models (for situations with and without epistasis); for F2 these will be 3- and 8-dimensional models, correspondingly; (2) In case of clear multimodality of the resulting LOD graph (caused by increased resolution of multivariate model), the chromosome is "dissected" into single or two-QTL segments; the precision of such approximation may be sufficient when the chromosome harbors a few strong (interacting) vector-QTLs. The proposed approach was verified on Monte-Carlo simulations and on real data on wheat and barley. The observed great improvement of the multivariate approach derives from the possibility of taking into account numerous interconnections between the traits and the QTLs, unraveling the genetic architecture of the multivariate phenotype as an integral system. In particular, this concerns the epistatic interactions of the pleotropic QTLs.
2. Using the algorithms of QTL-mapping to analyze concrete data generated at the Institute of Evolution and its collaborators in Israel and abroad (wheat, cattle, etc.)
Wild emmer wheat, Triticum dicoccoides, is the progenitor of modern tetraploid and hexaploid cultivated wheats. Our objectivewas to map domestication-related quantitative trait loci (QTL)in T.dicoccoides. The studied traits include brittle rachis,heading date, plant height, grain size, yield, and yield components.Our mapping population was derived from a cross between T.dicoccoidesand Triticum durum. Approximately 70domestication QTL effectswere detected, nonrandomly distributed among and along chromosomes.Seven domestication syndrome factors were proposed, each affecting5-11 traits. We showed: (i) clustering and strong effects of someQTLs; (ii) remarkable genomic association of strong domestication-relatedQTLs with gene-rich regions; and (iii) unexpected predominanceof QTL effects in the A genome. The A genome of wheat may haveplayed a more important role than the B genome during domesticationevolution. The cryptic beneficial alleles at specific QTLs derivedfrom T.dicoccoides may contribute to wheat and cerealimprovement.
Trypanosomosis, or sleeping sickness, is a major disease constrainton livestock productivity in sub-Saharan Africa. To identifyquantitative trait loci (QTL) controlling resistance to trypanosomosisin cattle, an experimental cross was made between trypanotolerantAfrican N'Dama (Bos taurus) and trypanosusceptible improvedKenya Boran (Bos indicus) cattle. Sixteen phenotypic traitswere defined describing anemia, body weight, and parasitemia.One hundred seventy-seven F2 animals and their parents andgrandparents were genotyped at 477 molecular marker loci coveringall 29 cattle autosomes. Total genome coverage was 82%. PutativeQTL were mapped to 18 autosomes at a genomewise false discoveryrate of <0.20. The results are consistent with a singleQTL on 17 chromosomes and two QTL on BTA16. Individual QTLeffects ranged from 6% to 20% of the phenotypic variance ofthe trait. Excluding chromosomes with ambiguous or nontrypanotoleranceeffects, the allele for resistance to trypanosomosis originatedfrom the N'Dama parent at nine QTL and from the Kenya Boranat five QTL, and at four QTL there is evidence of an overdominantmode of inheritance. These results suggest that selection fortrypanotolerance within an F2 cross between N'Dama and Borancattle could produce a synthetic breed with higher trypanotolerancelevels than currently exist in the parental breeds.
3. Development of new methods and algorithms for mapping marker loci (construction of multilocus maps).
The orderingproblem in linkagegroups with many dozens or even hundreds of markers belongs to the field of discrete optimization on a setof all possible orders, amounting to n!/2 for n loci; henceit is considered an NP-hard problem. Several authors attemptedto employ the methods developed in the well-known travelingsalesman problem (TSP) for multilocus ordering, using the assumptionthat for a set of linked loci the true order will be the onethat minimizes the total length of the linkage group. A novel,fast, and reliable algorithm developed for the TSP and basedon evolution-strategy discrete optimization was applied in thisstudy for multilocus ordering on the basis of pairwise recombinationfrequencies. The quality of derived maps under various complications(dominant vs. codominant markers, marker misclassification,negative and positive interference, and missing data) was analyzedusing simulated data with 50-400 markers. High performanceof the employed algorithm allows systematic treatment of theproblem of verification of the obtained multilocus orders onthe basis of computing-intensive bootstrap and/or jackknifeapproaches for detecting and removing questionable marker scores,thereby stabilizing the resulting maps. Parallel calculationtechnology can easily be adopted for further acceleration ofthe proposed algorithm. Real data analysis (on maize chromosome1 with 230 markers) is provided to illustrate the proposed methodology.
To solve the problem of multipoint gene ordering with a particular focus on "dominance" complication that acts differently in conditions of coupling-phase and repulsion-phase markers we split the dataset into two complementary subsets each containing shared codominant markers and dominant markers in the coupling-phase only. Multilocus ordering in the proposed algorithm is based on pairwise recombination frequencies and using the well-known travelling salesman problem (TSP) formalization. To obtain accurate results, we developed a multiphase algorithm that includes synchronized-marker ordering of two subsets assisted by re-sampling-based map verification, combining the resulting maps into an integrated map followed by verification of the integrated map. A new synchronized Evolution-Strategy discrete optimization algorithm was developed here for the proposed multilocus ordering approach in which common codominant markers facilitate stabilization of the marker order of the two complementary maps. High performance of the employed algorithm allows systematic treatment for the problem of verification of the obtained multilocus orders, based on computing-intensive bootstrap and jackknife technologies for detection and removing unreliable marker scores. The efficiency of the proposed algorithm was demonstrated on simulated and real data .
4. Development of methods and algorithms for multilocus consensus mapping analysis.
Numerous molecular mapping projects generated an abundance of mapping data on model and agricultural organisms have. Consequently, many multilocus maps were constructed in different laboratories using diverse mapping populations and marker sets for the same organism. These data can be (and were) independently analyzed to create maps for each population. As noted above, the quality of constructed maps may be affected by various complications. Therefore, one would expect some inconsistencies between different versions of the maps for the same organism. This indeed proves to be the case for many organisms, calling for new efforts to revise and integrate the mapping information and generate consensus maps.
Grigorenko V., Mukhin V., Neimark Yu., Rapoport A., Ronin Y. 1973. Construction of automaton playing up automata set. Izv. (Proc.) of The USSR Akad. of Science, Technical Cybernetics, 5: 94-98.
Neimark Yu., Ronin Y. 1977. On adaptive search by automata and on its convergence. Automatics and Telemechanics. Acad. of Sci., USSR , 2: 102-110.
Kogan M., Neimark Yu., Ronin Y. 1982. Search adaptive stabilization and control with extrapolator. In: Problems of cybernetics, ed. by Ya.Z. Tsypkin, Acad. of Sci. USSR: 103-116.
Ronin Y. 1983. To the analysis of the gradient procedures of identification under unlimited disturbances. In: Dynamics of systems. Control, adaptation and optimization. Gorky: 3-20
Neimark Yu., Ronin Y., Kogan M. 1988. Averaging method under random disturbances. In: Asymptotic methods of mathematical physics, Naukova Dumka, Kiev: 203-210.
Neimark Yu., Ronin Y., Chachkhiani T. 1989. Parallel clustering by automata. Intern. Fair Conference CAIP-89 Computer Analysis of Images and Patterns, 3 IC on Automatic Image Processing, Leipzig: 71-73.
Ronin Y., Kirzhner V., Korol A. 1995. Linkage between loci of quantitative traits and marker loci. Multi-trait analysis with a single marker. Theor. Appl. Genet., 90: 776-786. (Link)
Korol A., Ronin Y., Kirzhner V. 1995. Interval mapping of quantitative trait loci employing correlated trait complexes. Genetics, 140: 1137-1147. (Link)
Ronin Y., Korol A., Fahima T., Kirzhner V., Nevo E. 1996. Sequential estimation of linkage between PCR-generated markers and a target gene based on stepwise bulked analysis. Biometrics, 52(4): 1428-1439. (Link)
Ronin Y., Korol A., Weller J. 1998. Selective genotyping to detect quantitative trait loci affecting multiple traits. Theor. Appl. Genet, 97: 1169-1178. (Link)
Ronin Y., Korol A., Nevo E. 1999. Single-and multiple-trait analysis of linked QTLs: some asymptotic analytical approximation. Genetics, 151: 387-396. (Link)
Korol A., Ronin Y., Itskovich A., Peng J., Nevo E. 2001. Enhanced efficiency of QTL mapping analysis based on multivariate complexes of quantitative traits. Genetics, 157: 1789-1803. (Link)
Hanotte O., Ronin Y., Agaba M., Nilsson P., Gelhaus A., Horstmann R., Sugimoto Y., Kemp S., Gibson J., Korol A., Soller M., Teale A. 2003. Mapping of quantitative trait loci controlling trypanotolerance in a cross of tolerant West African N'Dama and susceptible East African Boran cattle.Proc. Natl. Acad. Sci. USA, 100 (13): 7443-7448. (Link)
Peng J., Ronin Y., Fahima T., Röder M., Li Y., Nevo E., Korol A. 2003. Domestication quantitative trait loci in Triticum dicoccoides, the progenitor of wheat. Proc. Natl. Acad. Sci. USA, 100 (5): 2489-2494. (Link)
Ronin Y., Korol A., Shtemberg M., Nevo E., Soller M. 2003. High-resolution mapping of quantitative trait loci by selective recombinant genotyping. Genetics, 164: 1657-1666. (Link)
Mester D., Ronin Y., Minkov D., Nevo E., Korol A. 2003. Constructing large scale genetic maps using evolutionary strategy algorithm. Genetics, 165: 2269-2282. (Link)
Atzmon G., Ronin Y., Korol A., Yonash N., cheng H., Hillel J. 2006. QTLs associated with growth traits and abdominal fat weight and their interactions with gender and hatch in commercial meat-type chickens. Animal Genetics, 37(4): 352-358. (Link)
Fu Y., Wen T-J., Ronin Y., Chen H., Guo L., Mester D., Yang Y., Lee M., Korol A., Ashlock D., Schnable P. 2006. Genetic dissection of intermated recombinant inbred lines using a new genetic map of maize. Genetics, 174:1671-1683. (Link)