No observed association for mitochondrial SNPs with preterm delivery and related outcomes

BACKGROUND: Preterm delivery (PTD) is the leading cause of neonatal morbidity and mortality. Epidemiologic studies indicate recurrence of PTD is maternally inherited creating a strong possibility that mitochondrial variants contribute to its etiology. This study examines the association between mitochondrial genotypes with PTD and related outcomes. METHODS: This study combined, through meta-analysis, two case-control, genome-wide association studies (GWAS); one from the Danish National Birth Cohort (DNBC) Study and one from the Norwegian Mother and Child Cohort Study (MoBa) conducted by the Norwegian Institute of Public Health. The outcomes of PTD (≤36 weeks), very PTD (≤32 weeks) and preterm prelabor rupture of membranes (PPROM) were examined. 135 individual SNP associations were tested using the combined genome from mothers and neonates (case vs. control) in each population and then pooled via meta-analysis. RESULTS: After meta-analysis there were four SNPs for the outcome of PTD below p≤0.10, and two below p≤0.05. For the additional outcomes of very PTD and PPROM there were three and four SNPs respectively below p≤0.10. CONCLUSION: Given the number of tests no single SNP reached study wide significance (p=0.0006). Our study does not support the hypothesis that mitochondrial genetics contributes to the maternal transmission of PTD and related outcomes

Spreading of Heterochromatin Is Limited to Specific Families of Maize Retrotransposons

Steven R. Eichten is with University of Minnesota, Nathanael A. Ellis is with University of Georgia, Irina Makarevitch is with Hamline University, Cheng-Ting Yeh is with Iowa State University, Jonathan I. Gent is with University of Georgia, Lin Guo is with University of Georgia, Karen M. McGinnis is with Florida State University, Xiaoyu Zhang is with University of Georgia, Patrick S. Schnable is with Iowa State University, Matthew W. Vaughn is with UT Austin, R. Kelly Dawe is with University of Georgia, Nathan M. Springer is with University of Minnesota.Transposable elements (TEs) have the potential to act as controlling elements to influence the expression of genes and are often subject to heterochromatic silencing. The current paradigm suggests that heterochromatic silencing can spread beyond the borders of TEs and influence the chromatin state of neighboring low-copy sequences. This would allow TEs to condition obligatory or facilitated epialleles and act as controlling elements. The maize genome contains numerous families of class I TEs (retrotransposons) that are present in moderate to high copy numbers, and many are found in regions near genes, which provides an opportunity to test whether the spreading of heterochromatin from retrotransposons is prevalent. We have investigated the extent of heterochromatin spreading into DNA flanking each family of retrotransposons by profiling DNA methylation and di-methylation of lysine 9 of histone 3 (H3K9me2) in low-copy regions of the maize genome. The effects of different retrotransposon families on local chromatin are highly variable. Some retrotransposon families exhibit enrichment of heterochromatic marks within 800–1,200 base pairs of insertion sites, while other families exhibit very little evidence for the spreading of heterochromatic marks. The analysis of chromatin state in genotypes that lack specific insertions suggests that the heterochromatin in low-copy DNA flanking retrotransposons often results from the spreading of silencing marks rather than insertion-site preferences. Genes located near TEs that exhibit spreading of heterochromatin tend to be expressed at lower levels than other genes. Our findings suggest that a subset of retrotransposon families may act as controlling elements influencing neighboring sequences, while the majority of retrotransposons have little effect on flanking sequences.The Texas Advanced Computing Center (TACC) at the University of Texas at Austin provided HPC and storage resources. The Minnesota Supercomputing Institute and Georgia Advanced Computing Resource Center provided access to computational resources and software for data analyses. The research was supported by grants from the National Science Foundation (DBI-0607123 and IOS-0922095). JIG is funded by an NIH fellowship (NIGMS F32GM095223). This work was created in part using resources or cyberinfrastructure provided by iPlant Collaborative. The iPlant Collaborative is funded by a grant from the National Science Foundation (#DBI-0735191) (www.iplantcollaborative.org). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Texas Advanced Computing Center (TACC