Biology subjects

Blow, M. J.

Publications and source records attributed to Blow, M. J..

5 recordsLinked to original sources

bioRxiv2026

Uncovering genetic mechanisms underlying trait variation in switchgrass using explainable artificial intelligence

Uncovering the genetic architecture of quantitative traits is challenging because polygenic control yields small individual gene effects and because gene-gene and genotype-by-environment interactions add further complexity. To understand the genetic basis of polygenic traits and their plasticity across environments, we integrated genome-wide SNPs and RNA-seq transcript data with interpretable statistical and machine learning models in a switchgrass (Panicum virgatum) diversity panel grown at contrasting field sites in Michigan and Texas. Notably, in addition to single environments, our trait prediction models were able to predict phenotypic differences, across environments i.e., plasticity. By interpreting trait prediction models with explainable machine learning methods, we identified genes that are the most predictive of flowering time and annual biomass production across environments, based on their associated gene expression levels and nearby SNPs. This approach recovered canonical flowering regulators and revealed novel, environment-specific candidate flowering genes. Further, transcriptome models consistently recovered more switchgrass genes homologous to experimentally validated genes in Arabidopsis and rice than SNP-based models. Feature interaction scores from the models also allow the identification of trait and environment-dependent gene-gene interactions, where flowering time showed stronger and more abundant interactions than biomass. While some of the interactions identified are consistent with the link between flowering time and yield, most are novel predictors that need to be further evaluated. These findings provide insight into the genetic basis of trait variation and plasticity across environments and help prioritize candidate genes for functional validation and cultivar improvement.

genetics↗

bioRxiv2024

scMicrobe PTA: Near Complete Genomes From Single Bacterial Cells

Microbial genomes produced by single-cell amplification are largely incomplete. Here, we show that primary template amplification (PTA), a novel single-cell amplification technique, generated nearly complete genomes from three bacterial isolate species. Furthermore, taxonomically diverse genomes recovered from aquatic and soil microbiomes using PTA had a median completeness of 81%, whereas genomes from standard amplification approaches were usually <30% complete. PTA-derived genomes also included more associated viruses and biosynthetic gene clusters.

genomics↗

bioRxiv2021

Topologically Associating Domain Boundaries are Commonly Required for Normal Genome Function

Topologically associating domain (TAD) boundaries are thought to partition the genome into distinct regulatory territories. Anecdotal evidence suggests that their disruption may interfere with normal gene expression and cause disease phenotype1-3, but the overall extent to which this occurs remains unknown. Here we show that TAD boundary deletions commonly disrupt normal genome function in vivo. We used CRISPR genome editing in mice to individually delete eight TAD boundaries (11-80kb in size) from the genome in mice. All deletions examined resulted in at least one detectable molecular or organismal phenotype, which included altered chromatin interactions or gene expression, reduced viability, and anatomical phenotypes. For 5 of 8 (62%) loci examined, boundary deletions were associated with increased embryonic lethality or other developmental phenotypes. For example, a TAD boundary deletion near Smad3/Smad6 caused complete embryonic lethality, while a deletion near Tbx5/Lhx5 resulted in a severe lung malformation. Our findings demonstrate the importance of TAD boundary sequences for in vivo genome function and suggest that noncoding deletions affecting TAD boundaries should be carefully considered for potential pathogenicity in clinical genetics screening.

genomics↗

bioRxiv2021

DNA methylation patterns in bacteria of the genus Ensifer during free living growth and during nitrogen-fixing symbiosis with Medicago spp.

Methylation of specific DNA sequences is ubiquitous in bacteria and has known roles in immunity and regulation of cellular processes, such as the cell cycle. Using single-molecule real-time sequencing, six genome-wide methylated motifs were identified across four Ensifer strains, five of which were strain-specific. Only the GANTC motif, recognized by the cell cycle-regulated CcrM methyltransferase, was methylated in all strains. In actively dividing cells, methylation of GANTC motifs increased progressively from the ori to ter regions in each replicon, in agreement with a cell cycle-dependent regulation of CcrM. In contrast, there was near full genome-wide GANTC methylation in the early stage of symbiotic differentiation. This was followed by a moderate decrease in the overall extent methylation and a progressive decrease in chromosomal GANTC methylation from the ori to ter regions in later stages of differentiation. We interpret these observations as evidence of dysregulated and constitutive CcrM activity during terminal differentiation, and we hypothesize that it is a driving factor for endoreduplication of terminally differentiated bacteroids.

microbiology↗

bioRxiv2019

Genome-Wide Fetalization of Enhancer Architecture in Heart Disease

Heart disease is associated with re-expression of key transcription factors normally active only during prenatal development of the heart. However, the impact of this reactivation on the genome-wide regulatory landscape in heart disease has remained obscure. Here we show that pervasive epigenomic changes occur in heart disease, with thousands of regulatory sequences reacquiring fetal-like chromatin signatures. We used RNA-seq and ChIP-seq targeting a histone modification associated with active transcriptional enhancers to generate genome-wide enhancer maps from left ventricle tissue from 18 healthy controls and 18 individuals with idiopathic dilated cardiomyopathy (DCM). Healthy individuals had a highly reproducible epigenomic landscape, consisting of more than 31,000 predicted heart enhancers. In contrast, we observed reproducible disease-associated gains or losses of activity at more than 7,500 predicted heart enhancers. Next, we profiled human fetal heart tissue by ChIP-seq and RNA-seq. Comparison with adult tissues revealed that the heart disease epigenome and transcrip-tome both shift toward a fetal-like state, with 3,400 individual enhancers sharing fetal regulatory properties. Our results demonstrate widespread epigenomic changes in DCM, and we provide a comprehensive data resource (http://heart.lbl.gov) for the mechanistic exploration of heart disease etiology.

genomics↗