Biology subjects

Snodgrass, S. J.

Publications and source records attributed to Snodgrass, S. J..

5 recordsLinked to original sources

bioRxiv2026

Maize genetic diversity is largely unstructured by human ethnolinguistic diversity in its center of origin

Population structure and environmental features often capture major axes of genetic variation in many species. Yet the impacts of human activity often remain unquantified. For domesticated species that rely on human activity for survival and dispersal, human movements and cultural differences may play key roles patterning genetic diversity. Maize is a staple crop of enormous cultural importance to indigenous peoples of the Americas, but cannot survive or disperse without farmers. Using publicly available genotyping and passport data from almost 2,000 traditional maize varieties, more than 500 whole genome sequences of humans from Mexico, and indigenous linguistic maps, we quantify anthropogenic effects on maize genetic diversity in the Americas. Maize shows very little overall structure, highlighting the effectiveness of indigenous farmers in moving and mixing maize populations. While principal components of maize diversity show meaningful correlations to human genetic diversity, our linear modeling suggests little additional impact of human population structure beyond shared geography. Though differences in maize diversity are often patterned by language locally, we find only weak genome-wide effects at larger spatial scales. Despite the relatively weak global signal of anthropogenic effects, linguistic GWAS, outlier FST analyses, and selection scans identified loci associated with specific languages. Leveraging landscape-level sequencing data, we highlight how anthropogenic factors have shaped patterns of maize genetic diversity across Mesoamerica.

evolutionary biology↗

bioRxiv2024

Maize and wild relatives show distinct patterns of genome downsizing following polyploidy

Plant genomes are smaller than expected despite the ubiquity of polyploidy due to the process of genome downsizing called fractionation. This process causes loss of DNA sequences, including genes, until genomes return to a diploid-like state, though some duplicates remain from the polyploid ancestor. Fractionation can affect the copies of ancestral diploid genomes (i.e., subgenomes) differently, resulting in one being preferentially retained and the other preferentially lost. While previous work suggested fractionation occurs shortly after a polyploidy event, few studies have been able to densely sample descendent genomes from the same whole genome duplication event. The Tripsacinae subtribe of grasses, which includes the genera Tripsacum and Zea and the economically and culturally important maize (Zea mays ssp. mays), originates from an ancient allopolyploid ([~]5-12 MYA). We use publicly available genome assemblies from the Tripsacinae subtribe of grasses to investigate the patterns and timing of fractionation relative to the outgroup sorghum, which does not share the allotetraploidy event. Our results show the majority of fractionation following polyploidy occurred in a common ancestor of modern species and that one subgenome is preferentially retained, in keeping with previous studies of maize. However, Tripsacum retains a greater proportion of duplicate genes (homoeologs) than Zea, potentially related to the fewer chromosomal rearrangements observed in this genus. Multiple, nested deletion events were commonly observed in alignments to a single sorghum reference exon, and some homoeologs show fractionation of different exons across genomes. Further, [~]35% of homoeologous pairs of exons show differential fractionation, where fractionation patterns differ between species. Altogether, this suggests multiple origins of fractionation for a given homoeolog may be common. We demonstrate that fractionation is a much more dynamic process in the Tripsacinae than previously predicted.

genomics↗

bioRxiv2024

The utility of environmental data from traditionalvarieties for climate-adaptive maize breeding

Maintaining crop yields in the face of climate change is a major challenge facing plant breeding today. Considerable genetic variation exists in ex-situ collections of traditional crop varieties, but identifying adaptive loci and testing their agronomic performance in large populations in field trials is costly. Here, we study the utility of climate and genomic data for identifying promising traditional varieties to incorporate into maize breeding programs. To do so, we use phenotypic data from more than 4,000 traditional maize varieties grown in 13 trial environments. First, we used genotype data to predict environmental characteristics of germplasm collections to identify varieties that may be locally adapted to target environments. Second, we used environmental GWAS (envGWAS) to identify genetic loci associated with historical divergence along climatic gradients, such as the putative heat shock protein hsftf9 and the large-scale adaptive inversion Inv4m. Finally, we compared the value of environmental data and envGWAS-prioritized loci to genomic data for prioritizing traditional varieties. We find that maize yield traits are best predicted by genomic data, and that envGWAS-identified variants provide little direct predictive information over patterns of population structure. We also find that adding environment-of-origin variables does not improve yield component prediction over kinship or population structure alone, but could be a useful selection proxy in the absence of sequencing data. While our results suggest little utility of environmental data for selecting traditional varieties to incorporate in breeding programs, environmental GWAS is nonetheless a potentially powerful approach to identify individual novel loci for maize improvement, especially when coupled with high density genotyping.

evolutionary biology↗

bioRxiv2023

Phenotypic variation in maize can be largely explained by genetic variation at transcription factor binding sites

Comprehensive maps of functional variation at transcription factor (TF) binding sites (cis-elements) are crucial for elucidating how genotype shapes phenotype. Here we report the construction of a pan-cistrome of the maize leaf under well-watered and drought conditions. We quantified haplotype-specific TF footprints across a pan-genome of 25 maize hybrids and mapped over two-hundred thousand genetic variants (termed binding-QTL) linked to cis-element occupancy. Three lines of evidence support the functional significance of binding-QTL: i) they coincide with numerous known causative loci that regulate traits, including VGT1, Trehalase1, and the MITE transposon near ZmNAC111 under drought; ii) their footprint bias is mirrored between inbred parents and by ChIP-seq; iii) partitioning genetic variation across genomic regions demonstrates that binding-QTL capture the majority of heritable trait variation across [~]70% of 143 phenotypes. Our study provides a promising approach to make previously hidden cis-variation more accessible for genetic studies and multi-target engineering of complex traits.

genomics↗

bioRxiv2021

De novo assembly, annotation, and comparative analysis of 26 diverse maize genomes

We report de novo genome assemblies, transcriptomes, annotations, and methylomes for the 26 inbreds that serve as the founders for the maize nested association mapping population. The data indicate that the number of pan-genes exceeds 103,000 and that the ancient tetraploid character of maize continues to degrade by fractionation to the present day. Excellent contiguity over repeat arrays and complete annotation of centromeres further reveal the locations and internal structures of major cytological landmarks. We show that combining structural variation with SNPs can improve the power of quantitative mapping studies. Finally, we document variation at the level of DNA methylation, and demonstrate that unmethylated regions are enriched for cis-regulatory elements that overlap QTL and contribute to changes in gene expression. One sentence summaryA multi-genome analysis of maize reveals previously unknown variation in gene content, genome structure, and methylation.

genomics↗