Item No. 1 of 1

INVESTIGATOR: Koltes, J.; Koltes, J. E.

PERFORMING INSTITUTION:
IOWA STATE UNIVERSITY
2229 Lincoln Way
AMES, IOWA 50011

A SYSTEMS GENETICS APPROACH TO IDENTIFY EPIGENETIC VARIANTS ASSOCIATED WITH SKELETAL MUSCLE NUTRIENT CONTENT

NON-TECHNICAL SUMMARY: Epigenetics is the study of mutations and mechanisms "above" the DNA code that fine-tune expression of genes and pathways. Epigenetic modifications of DNA are known to play a role in diabetes, obesity, skeletal muscle growth and development. Notable epigenetic mechanisms include imprinting (e.g. phenotype depending upon whether dam or sire was the source of the genetic effect), DNA methylation (inherited and environmentally regulated), and non-coding RNA such as microRNAs. The objective of this research proposal is to evaluate the potential relationship of microRNAs, and allele specific expression (a surrogate measure of DNA methylation and imprinting) with iron and fatty acid content in bovine skeletal muscle. The proposal uses a systems genetics framework, incorporating genetic information from multiple levels of control (genetic, transcriptional, and epigenetic) in the analysis of phenotypes. The utility of this research is both applied and basic in nature. This proposal will determine if epigenetic markers are important in livestock selection schemes to improve beef nutrient content, which would add value to the US beef industry. Epigenetic studies in livestock will also act as a model for human diseases such as obesity and hemochromatosis. A database and bioinformatic tools developed in this proposal will facilitate future livestock epigenetic research. Furthermore, this proposal addresses two USDA priority areas: 1) keep American agriculture competitive while ending world hunger; and 2) improve nutrition and end childhood obesity.

OBJECTIVES: The overall GOALS of this proposal include: 1) determining the association of epigenetic variants with bovine skeletal muscle nutrient content; and 2) providing faculty-in-training experiences. The following specific aims address the research objectives of this proposal. SPECIFIC AIM 1: Identify miRNA and allele specific expression (ASE) variants associated with total iron content and fatty acid content in skeletal muscle with divergent phenotypes. The objective of this aim is to find transcripts, miRNAs, ASE SNPs and networks that are associated with muscle iron content and fat traits (e.g. marbling, back fat, fatty acid profile). SPECIFIC AIM 2: Develop an online livestock community resource for the discovery and cataloguing of epigenetic variants. The objective of this aim is to develop a database to catalogue ASE variants, splice variants, non-coding RNAs, and methylated DNA in livestock. EXPECTED OUTPUTS: Completion of proposed research is expected to result in the discovery of transcripts, non-coding RNAs, ASE markers and pathways that are associated with iron and fat content in muscle as well as a public database of epigenetic variants in livestock. The accomplishment of these aims and additional professional development training will prepare Dr. Koltes for an independent, tenure-track faculty position.

APPROACH: A combination of research and professional development experiences are proposed to achieve the goals laid out in this grant. RESEARCH: A systems genetics approach is proposed to investigate the association of epigenetic variants with bovine skeletal muscle fat and iron content. Development of bioinformatics tools will be critical in achieving this task. To achieve research AIM1: RNAseq analysis will be used to profile the mRNA and non-coding RNA transcriptome to characterize differences in expression between phenotypically extreme animals (high and low) for bovine skeletal muscle iron content and saturated fatty acid levels. Sequences will be aligned to the UMD3.1 bovine genome, and analyzed for differential splicing and expression using TopHat, Cufflinks and R software. Annotation of short reads will be performed using annotation tools at AgBase (Mississippi State University). Differentially expressed RNAs will be validated by realtime PCR. To determine the extent and location of allele specific expression (ASE) of SNPs, 54k SNP chip genotypes will be compared to SNPs called from RNAseq data. SNPs exhibiting ASE will be validated using single nucleotide extension genotyping to compare allelic ratios. Network co-expression analysis will be used to find pathways associated with fat and iron traits. AIM2: A database will be developed at animalgenome.org to allow public access and promote data sharing of epigenetic variants in livestock. In order to achieve these objectives, a web-based interface will be developed to allow data deposition and retrieval by the livestock community. A pipeline will be developed in PHP and Perl to facilitate this process with data distribution being achieved using Biomart. Multiple data formats suitable for visualization and analysis will be available for download. The pipeline, tools, and database will be developed and tested using data examples from EBI's European Nucleotide Archeive database. Tools used to detect epigenetic variants will be developed in R and Perl to allow easy distribution to the community. PROFESSIONAL DEVELOPMENT: To facilitate my training as a future faculty member, I will have the opportunity to participate in an array of seminars, present data at conferences, mentor undergraduate students and participate in grant writing. I will have the opportunity to teach lectures in Animal Science 352: Genetic improvement of domestic animals, and Animal Science 345: Growth and Development of Domestic Animals. Koltes will work closely with the instructors of these courses and his mentor to hone teaching skills. This proposal will allow him to develop his own independent research program in epigenetics and develop broadly applicable skills in bioinformatics. To achieve the objectives of this goal, Koltes has established work relationships and sought mentorship from several faculty members at ISU as well as at other institutions.

PROGRESS: 2011/08 TO 2014/07
Target Audience: The target audience reached by this project during FY2014 includes both the research community and graduate students in the form of publications, abstracts, talks, posters and teaching in the classroom. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided? A major goal of this proposal was to provide faculty-in-training experiences that provide professional development toward the goal of becoming an independent, tenure-track faculty member. This NIFA post-doctoral fellowship provided me with opportunities to present research findings at professional meetings, organize a scientific meeting, and obtain invaluable teaching experience. Research findings were presented at professional meetings, including the ISAFG meeting (2011), an invited talk in the systems biology session of the animal breeding and genetics section of the national animal science meeting (2012), a USDA project directors meeting (2012), two talks at PAG (2013), and an invited talk for the animal epigenetics session at the 2014 PAG meeting. Attending and presenting research at meetings helped me to network with other researchers interested in genomics and epigenetics. In addition, I helped organize the graduate student and post-doc orientated Gordon Research Seminar associated with the Gordon Research Conference on Quantitative Genetics and Genomics (2013). This was an excellent experience in how to manage, fund and organize a conference. Teaching opportunities included the presentation of 15 lectures and 8 labs in two undergraduate courses: animal breeding and genetics and growth and development. The interactions and advisement by teaching mentors (Drs. Huiatt and D. Spurlock) provided me with invaluable experience in teaching in both small and large classroom settings. These teaching experiences were an invaluable experience in course design, evaluation and management of small and large class sizes. In addition, I developed a tutorial class on bioinformatics for graduate students and visiting scientists at Iowa State University (2012). This 10-week course covered basic bioinformatics, basic programming skills, next-generation sequencing analysis, and concepts in systems biology analysis. This opportunity allowed me to build the core components of a new graduate level bioinformatics class to introduce students to next generation sequencing analysis. I also presented 3 lectures for the graduate student course in genome analysis (ANS556), including the topics: RNA-seq analysis, gene co-expression network analysis, and systems genetics analysis (2014). This teaching opportunity allowed me to instruct graduate students on cutting-edge methods used during my post-doctoral fellowship. How have the results been disseminated to communities of interest? Differential expression, PCIT network analysis and initial allele specific expression analysis results were presented at an invited talk in the systems biology in animal breeding and genetics section of the national animal science meeting in Phoenix, Arizona during the summer of 2012. In addition, results were presented in two posters at the ISAFG meeting in Dublin, Ireland in the fall of 2011 and at the USDA PD meeting in the summer of 2012. Systems genetics, and allele specific expression results from this study have been disseminated to the community through conference presentations and posters (PAG and ISAG) and one paper (Koesterke et al., 2013). They have also been presented at departmental seminars at Iowa State. The livestock epigenetics database results have been disseminated to the research community through a conference talk (PAG). In addition, one additional paper was published describing additional enhancements to the PCIT algorithm (Koesterke et al., 2014). Three manuscripts are currently in progress to describe: 1) the systems genetics analysis of bovine skeletal muscle iron content; 2) differential expression of miRNA associated with saturated fatty acid content of bovine skeletal muscle; and 3) allele specific expression in bovine skeletal muscle. In addition, work on livestock epiDB is still in development, but preliminary results are being made available online. A publication will be forthcoming upon completion of the website and database. The beta version of the database and website are available at: http://nagrp.ansci.iastate.edu/eric/epidb/. What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

IMPACT: 2011/08 TO 2014/07
What was accomplished under these goals? The impact of this project includes the identification of genes, epigenetic regulators and networks important in the regulation of skeletal muscle iron and fatty acid content. In addition, we have identified mutations that may directly explain the variation in these traits and assist in selection for healthier beef. Software developed in this project will help researchers look at combined regulation of multiple data types in a network that was not previously computationally possible. The identification of allele specific expression (ASE) in skeletal muscle indicates that knowing which markers exhibit ASE may be important to marker selection for genomic selection and understanding regulation of iron and fatty acid content above the genetic level (i.e. epigenetics, post-transcriptional regulation). The results of the iron study are also useful to broader biology and human medicine because new regulators of iron uptake were identified in this study, which may be useful in understanding human iron storage diseases. The development of the livestock epigenetics database (EpiDB) provides a new public resource that will help researchers identify relevant genes in trait association and gene expression studies. EpiDB will also allow new hypotheses about genetic and epigenetic regulation to be generated by integrating different processed data types into an easy to search and view format that was not previously available in an automated way. Finally, professional development in the form of project management, teaching, and speaking opportunities provided faculty-in-training experiences that were invaluable in my career development. Goal 1 of this project was to determine the association of epigenetic variants with bovine skeletal muscle nutrient content. Objective 1 was to identify miRNA and allele specific expression (ASE) variants associated with total iron content and fatty acid content in skeletal muscle with divergent phenotypes. The goal of this objective was to find transcripts, miRNAs, ASE SNPs and networks that are associated with muscle iron content and fat traits (e.g. marbling, back fat, or fatty acid profile). EXPERIMENTS AND DATA COLLECTED included the following. 1) Transcripts identified in an RNAseq analysis were analyzed to identify differentially expressed genes associated with iron and fatty acid content in skeletal muscle. An analysis of gene enrichment, pathway enrichment and co-expression network analysis was used to identify pathways and regulators important to these traits. 2) To facilitate the creation of systems genetics networks and identify regulators, efficient algorithms were developed to process the large amount RNAseq based data generated by this project. 3) Variants identified in this study were used in combination with 50k SNPchip data to identify ASE. 4) Small RNAs were analyzed to identify associations with divergent iron and saturated fatty acid content. SUMMARY & DISCUSSION: 1) Analysis of extreme skeletal muscle total iron content samples indicated 3010 differentially expressed (DE) transcripts (q < 0.05). Enrichment of DE transcripts within networks known to regulate iron homeostasis serve as a proof of principal that we do observe changes in expression in genes critical to iron metabolism. Several pathways known to regulate iron were identified as enriched, including the activin receptor/SMAD4 pathway (p< 2.25E-9) and BMP6 (p < 6.38E-8). These pathways have documented roles in the iron diseases anemia and hemochromatosis, respectively. In addition, genetic variants were detected that will be genotyped in additional populations to determine their possible associations with iron and fatty acid content. Variants in known and novel regulators of iron and fatty acid homeostasis were identified (e.g. iron: TFRC, SLC40A1, HFE3; fatty acid: FASN, SCAP, SCD5). Putative causal genetic variants have been identified based on the predicted impact on the respective proteins. The analysis of extreme samples for saturated fatty acid ratio identified 88 DE transcripts (q<0.05). 2) The enhanced version of PCIT was developed with a speed up of 1000000x over the original software with up to 1000000 nodes (e.g. combination of gene expression and epigenetic modifications) without the use of RAM (Koesterke et al., 2013). Additional filters were also added to reduce the amount of data written to file, which was a major bottleneck for efficiency (Koesterke et al., 2014). The modified PCIT algorithm allows researchers to analyze larger, integrated systems level network data using less computing resources. 3) A total of 277 candidate ASE loci were identified (q < 0.05). Allele Specific Expression may indicate regions of the genome that are regulated by cis-regulators or epigenetic mechanisms such as imprinting and methylation. 4) A total of 130 DE small RNAs (q < 0.15) were identified in individuals with divergent saturated to unsaturated fatty acid content. Interestingly, many of the DE small RNAs were 5s rRNAs, with only a few DE miRNAs. No small RNAs were identified as DE due to iron content. KEY OUCOMES & ACCOMPLISHMNETS: 1) This research identified transcripts associated with iron and fatty acid content as well as putative causal mutations near QTL peaks. Two putative, novel transcriptional regulators of iron content in skeletal muscle were also identified (CNOT7, INS5). 2) The modified PCIT software allows large-scale systems genetics network analysis that was previously not possible. 3) These results provide the first report of ASE markers detected in bovine skeletal muscle. This finding may indicate epigenetic or post-transcriptional regulation of iron and fatty acid content in skeletal muscle. 4) The small non-coding RNAs associated with fatty acid content indicate the first report of epigenetic regulators of saturated fatty acid ratio in bovine skeletal muscle. Objective 2 was to develop an online livestock community resource for the discovery and cataloguing of epigenetic variants. The goal of this objective was to develop a database to catalogue ASE variants, splice variants, non-coding RNAs, and methylated DNA in livestock. EXPERIMENTS/DATA COLLECTED included the following. Public data from the SRA database at NCBI were captured using automated scripts to identify tissue-specific RNAseq, miRNAseq, ChIPseq, and Methylseq data in cattle, chicken, horse, sheep, and pigs. The MySQL database and website that distributes this data is designed to allow users to identify and download data using species, tissue and experiment level queries. SUMMARY & DISCUSSION: Automated pipelines were created to search for data at SRAdb, download the data, process RNAseq, methylation and ASE data. These pipelines use Bowtie2, HtSeq, SAMtools as well as a host of custom scripts to process and load expression data into the database. The software currently provides tissue-specific RNAseq expression data for cattle (chicken, horse, pig, and sheep data will follow). Users can search experimental level metadata to identify gene expression datasets of interest at the website. Epigenetics data (allele specific expression, methylation, miRNA) will follow and populate the database soon. Web links are provided to relevant data summaries at NCBI to allow users to find all experimental details for queried studies. A full summary of the current progress and plans for scheduled improvements is provided at the website. KEY OUCOMES & ACCOMPLISHMNETS: The first version of the livestock epigenetics database was released at: http://nagrp.ansci.iastate.edu/eric/epidb/. This software and database represent the first public data knowledgebase of gene and epigenetic expression levels for livestock. GOAL2: Provide faculty-in-training experiences. Details on the activities and outcomes for goal 2 are provided in the section’ “What opportunities for training and professional development has the project provided”.

PUBLICATIONS (not previously reported): 2011/08 TO 2014/07
1. Type: Conference Papers and Presentations Status: Published Year Published: 2012 Citation: Koltes, J.E., Tait, R.G. Tait Jr, Fritz, E.R., Mishra, B.P., Van Eenennaam, A.L., Mateescu, R.G., Van Overbeke, D.L., Garmyn, A.J., Liu, Q., Duan, Q., Nettleton, D., Beitz, D., Garrick, D., and J.M. Reecy. 2012. A systems-genetics analysis of bovine skeletal muscle iron content. National Animal Science Meeting, Animal Breeding and Genetics section on systems biology, Phoenix, AZ, USA.
2. Type: Conference Papers and Presentations Status: Published Year Published: 2014 Citation: Koltes JE, Fritz-Waters E, Hu Z-L and JM Reecy. 2014. Livestock EpiDB: a database and discovery tool integrating epigenetics and gene expression profiles. Proc. of Plant and Animal Genome XXII. San Diego, CA, USA.
3. Type: Journal Articles Status: Published Year Published: 2014 Citation: Koesterke, L., J.E. Koltes, N.T. Weeks, K. Milfeld, M. Vaughn, J.M. Reecy and D. Stanzione. Discovery of biological networks using an optimized PCIT algorithm on Stampede?s Intel Xeon and Xeon Phi processors. 2014. Concurrency and Computation Practice and Experience. doi: 10.1002/cpe.3252, March 2014. http://onlinelibrary.wiley.com/doi/10.1002/cpe.3252/abstract

PROGRESS: 2012/08/01 TO 2013/07/31
Target Audience: Researchers in animal science, animal genetics, systems biology, molecular nutrition and mineral and fatty acid metabolism. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided? An important objective of this grant was to provide leadership and professional development opportunities for my career advancement. This project has provided research training in the area of bioinformatics and epigenetics as well as opportunities to improve my scientific presentation and leadership skills. I gave two talks at PAG in 2012 and helped to organize the graduate student and post-doc orientated Gordon Research Seminar associated with the Gordon Research Conference on Quantitative Genetics and Genomics. These speaking and leadership opportunities have helped me to network with additional researchers interested in genomics and epigenetics. In addition, I have developed a tutorial class on bioinformatics for graduate students and visiting scientists at Iowa State University. This course covers basic bioinformatics, handy programming skills, basic next generation sequencing analysis, and concepts in systems biology analysis. These opportunities have helped me to build the core components of a bioinformatics class to introduce students to next generation sequencing analysis. How have the results been disseminated to communities of interest? Results from this study have been disseminated to the community through conference presentations, proceedings, posters and one paper. They have also been presented at departmental seminars at Iowa State. Two manuscripts are currently in the process of being submitted to journals describing the updated PCIT software and methodology for analyzing methylation data. What do you plan to do during the next reporting period to accomplish the goals? The goals for the next reporting period will include the following. 1) Improvement of the RIF software to accommodate large datasets and systems level network regulator scoring. 2) Determine if miRNAs are differentially expressed as a function of iron or fatty acid content in bovine skeletal muscle. 3) Integrate ASE, miRNA and RNAseq data into a systems level network and RIF analysis to determine if any there is evidence of epigenetic regulators of networks. 4) Complete the development of the livestock EpiDB epigenetics database. This includes the completion of automated SRA tools pipelines to download NCBI data and create data summary tracks for visualization. The database and associated tools and data resources will be made available through the animalgenome.org website.

IMPACT: 2012/08/01 TO 2013/07/31
What was accomplished under these goals? Accomplishments during the past year include the following. 1) Development of R software to test for allele specific expression (ASE) in RNAseq data. 2) Development of an enhanced Fortran-based PCIT algorithm. 3) Development of new methodology for the analysis of methylation data in livestock. 4) Initial development of a livestock epigenetics database (livestock EpiDB). OUTCOMES/IMPACTS: 1) To identify regions of the genome that may be influenced by epigenetic mechanisms, a statistical methodology was developed as R software to identify ASE of SNPs identified in RNAseq data. An analysis of bovine skeletal muscle RNAseq data identified 277 candidate ASE loci (q < 0.05). Genes exhibiting ASE in skeletal muscle enriched for placental tissue expression (FDR < 0.05), which is consistent with previous findings from imprinted genes. These results provide the first report of ASE detected on a whole transcriptome scale in bovine skeletal muscle. The ASE events may result in the identification of cis-regulators, differential splicing or methylation events that may regulate iron and fatty acid metabolism in cattle. 2) An objective of this grant is to develop more efficient methods of integrating multiple layers of systems genetics data. To meet this objective, I’ve collaborated with researchers in computer science at the Texas Advanced Computing Center (TACC, University of Texas) (Lars Koesterke) and Iowa State University (Nathan Weeks) to develop an enhanced version of PCIT with a speed up of 1000000x over the original software. The software now allows for networks containing up to 1000000 nodes (e.g. combination of gene expression, methylation, ASE, miRNA, etc.) without the use of RAM. This research has resulted in the development of an enhanced software that is capable of analyzing large-scale data (>40000 nodes) using a partial correlation method that was previously not computationally feasible. This software will allow researchers to analyze larger, integrated systems level network data using less computing resources. 3) Another goal of this grant was to develop new methodology for use in expression and epigenetics data. As a proof of principal, I used our enhanced PCIT software (Koesterke et al., 2013) to identify co-methylated pathways from DNA methylation data. A study investigating the impact of varying levels of omega3 (N3) fatty acids in the maternal diet on offspring DNA methylation and inflammatory response was analyzed. The objective of the analysis was to identify pathways and pathway regulators impacted by N3 fatty acid mediated methylation. To identify putative regulators of pathway specific DNA methylation, methylation data was analyzed with an implementation the Regulatory Impact Factor (RIF) analysis (Reverter et al., 2010). Putative epigenetic mediators of inflammatory response were identified as well as known PPAR-gamma pathway members (e.g. a known receptor pathway for N3 fatty acids). This research provides a new way to analyze methylation data as it is the first to use co-expression methodology to identify co-methylated pathways. This methodology is novel since it focuses on promoter methylation levels and changes in promoter methylation correlation across networks of many promoter methylation events using the RIF methodology coupled with gene ontology enrichment analysis. Application of this method provided novel information about nutritional epigenetic effects of maternal omega 3 fatty acid feeding on offspring. 4) Initial development of a livestock epigenetics database and accompanying resources is well underway. Automated pipelines to process methylation and ASE data have been developed. These pipelines use Bowtie2, HtSeq, Cufflinks, SAMtools as well as a host of custom scripts to capture expression information from publically available next generation sequencing data at the National Center for Biotechnology Information (NCBI). This research will result in a new public data repository and data summarization resource that will allow researchers to compare multiple data tracks simultaneously and facilitate systems level analysis.

PUBLICATIONS: 2012/08/01 TO 2013/07/31
1. Type: Conference Papers and Presentations Status: Other Year Published: 2012 Citation: Koltes, J.E., Tait, R.G. Tait Jr, Fritz, E.R., Mishra, B.P., Van Eenennaam, A.L., Mateescu, R.G., Van Overbeke, D.L., Garmyn, A.J., Liu, Q., Duan, Q., Nettleton, D., Beitz, D., Garrick, D., and J.M. Reecy. 2012. Systems-genetics analysis of bovine skeletal muscle iron level. Proc of Plant and Animal Genome XXI. San Diego, CA, USA.
2. Type: Conference Papers and Presentations Status: Other Year Published: 2013 Citation: Koesterke, L., J.E. Koltes, N.T. Weeks, K. Milfeld, M. Vaughn, J.M. Reecy and D. Stanzione. Optimizing the PCIT algorithm on Stampedeās Xeon and Xeon Phi processors for faster discovery of biological networks. 2013. Proceedings of the XSEDE2013 Conference. San Diego, CA, USA. doi>10.1145/2484762.2484794
3. Type: Conference Papers and Presentations Status: Other Year Published: 2013 Citation: Koltes JE, Vaughn MW, Fritz ER, Alexander LJ, and JM Reecy. 2013. Mining RNA sequencing data for evidence of allele specific expression in cattle. Proc of Plant and Animal Genome XXI. San Diego, CA, USA.

PROGRESS: 2011/08/01 TO 2012/07/31
OUTPUTS: The objectives of this research are to identify genetic and epigenetic regulators of bovine skeletal muscle iron and fatty acid content and develop bioinformatics resources to aid discovery of epigenetic variants in livestock. In addition, this project seeks to provide professional development training in preparation for an independent, tenure-track faculty position. 1) To identify regulators of iron and fatty acid content in bovine skeletal muscle, transcriptional profiling was conducted by RNAseq analysis. To identify differentially expressed (DE) transcripts, R software was developed with the help of Dr. Dan Nettleton. 2) To determine the importance of transcripts as potential regulators or iron homeostasis, network analyses were used to determine which networks and biological pathways were enriched from the list of DE transcripts. Pathway Studio was used to identify putative regulators based on PubMed information. 3) To identify novel networks associated with skeletal muscle iron content, differentially expressed (DE) transcripts were analyzed using the partial correlation with information theory (PCIT) method. Specific outputs include the development of software that uses an adaptation of the PCIT method to analyze all possible partial correlation relationships for the whole muscle transcriptome using high performance computing. Using this methodology, candidate regulators of total skeletal muscle iron content were identified that exhibit differential correlation with DE transcripts. 4) To meet the objective of finding SNPs responsible for variation in muscle iron and fatty acid content, variants were called from RNAseq data to determine if putative causal mutations were present. 5) To identify regions of the genome that may be influenced by epigenetic mechanisms, methods are being developed to identify SNPs exhibiting allele specific expression using SNP data. 6) To meet the objective of enhancing my professional development, I have presented research at three professional meetings, taught lectures and labs in two different courses and participated in the development of teaching materials for these courses. 6a) Research from this project was presented in an invited talk in the systems biology in animal breeding and genetics section of the National Animal Science Meeting in Phoenix, Arizona during the summer of 2012. In addition, results were presented in two posters at the ISAFG meeting in Dublin, Ireland, in the fall of 2011 and at the USDA PD meeting in the summer of 2012. 6b) Development of teaching skills involved teaching a total of 15 lectures and 8 labs in two undergraduate courses: animal breeding and genetics and growth and development. The interactions and advisement by Drs. Huiatt and Spurlock provided me with invaluable experience in teaching in both small and large classroom settings. Topics instructed included growth and development and animal breeding and genetics. PARTICIPANTS: USDA- Miles City, Montana: Dr. Alexander provided RNAseq data contrasting high and low levels of saturated fatty acids that is being used for the development of methods to identify allele specific expression. Iowa State University: Eric Fritz, JR Tait and Dan Nettleton provided assistance and training with software and statistical methods for next generation sequencing analysis. Ted Huiatt and Diane Spurlock served as teaching mentors. James Reecy served as the mentor for this project and provided instruction on project management, teaching, and development of research. James Koltes has served as the principal investigator for this post-doctoral research and training fellowship and has been primarily responsible for the activities presented here. Mississippi State University/University of Arizona: Fiona McCarthy provided assistance by developing software for annotation of next generation sequencing data. These collaborations provided important training opportunities for analyzing next generation sequencing data as well as professional development in the form of teaching experience and guidance. TARGET AUDIENCES: Researchers in animal science, animal genetics, molecular nutrition and mineral and fatty acid metabolism. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

IMPACT: 2011/08/01 TO 2012/07/31
Current results provide an improved understanding of genetic and transcriptional regulation of iron and saturated fatty acid content in skeletal muscle. Analysis of extreme samples for skeletal muscle total iron content indicated 3010 DE transcripts (q < 0.05). The analysis of extreme samples for skeletal muscle saturated fatty acid ratio identified 88 DE transcripts (q < 0.05). Enrichment of DE transcripts within networks known to regulate iron homeostasis serve as a proof of principal that we do observe changes in expression in genes critical to iron metabolism. Several pathways known to regulate iron were identified as enriched, including the activin receptor/SMAD4 pathway (p < 2.25E-9), BMP6 (p < 6.38E-8), and STAT1 (p < 1.3 E-27). The identification of SMAD4 and BMP6 are important because of their documented roles in the iron diseases anemia and hemochromatosis, respectively. In addition, genetic variants detected from this research are important because they will be genotyped in additional populations to determine their possible associations with iron and fatty acid content. We have already identified a number of known and novel regulators of iron and fatty acid homeostasis (e.g. iron: TFRC, SLC40A1, HFE3; fatty acid: FASN,SCAP, SCD5). Putative causal genetic variants have been identified in these regulators based on their predicted impact on the respective proteins (i.e. early stop codons, frameshifts, non-synonymous mutations). This research may result in the identification of causal mutations that will directly improve our understanding of iron and fatty acid metabolism in cattle and other mammals. This research has also resulted in the development of new network analysis software through the modification of existing methods. This modified approach will allow all transcripts to be tested as possible regulators of genetic control. This is a significant improvement over the previous method where only a limited number of regulators could be investigated due to computational limitations. Furthermore, the development of this new software was critical in our discovery of two putative novel regulators of iron content in skeletal muscle (CNOT7, INS5). This research lays the foundation for on-going research into the epigenetic mechanisms regulating iron and fatty acid metabolism in skeletal muscle. Variants identified in this study are currently being used to identify allele specific expression that may indicate regions of the genome that are regulated by imprinting, methylation or cis-regulators. Initially, 3000-4000 transcripts have been identified that may exhibit allele specific expression. Teaching experiences were an invaluable experience in course design, evaluation and management of small and large class sizes. The impact of this project includes the identification of DE genes important in iron and fatty acid homeostasis in skeletal muscle as well as the identification of transcriptional regulators and putative causal mutations for these traits. Furthermore, teaching and project management training opportunities have enhanced my professional development skills, providing the foundation for a new research program.

PUBLICATIONS: 2011/08/01 TO 2012/07/31
1. Koltes, J.E., Tait, R.G. Tait Jr, Fritz, E.R., Mishra, B.P., Van Eenennaam, A.L., Mateescu, R.G., Van Overbeke, D.L., Garmyn, A.J., Liu, Q., Duan, Q., Nettleton, D., Beitz, D., Garrick, D., and J.M. Reecy. 2012. A systems-genetics analysis of bovine skeletal muscle iron content. Proc. of the International Society of Animal Genetics. P2050. Cairns, Australia.
2. Koltes, J.E., Tait, R.G. Tait Jr, Fritz, E.R., Mishra, B.P., Van Eenennaam, A.L., Mateescu, R.G., Van Overbeke, D.L., Garmyn, A.J., Liu, Q., Duan, Q., Beitz, D., Garrick, D., and J.M. Reecy. 2011. Investigating the genetic control of bovine skeletal muscle iron content. Int. Society of Anim. Funct. Genom. Dublin, Ireland.