Biology subjects

Wisser, R. J.

Publications and source records attributed to Wisser, R. J..

4 recordsLinked to original sources

bioRxiv2026

Disentangling shape and size variation to compare canopy architecture in maize

{middle dot} Comparing maize canopies is confounded by two problems: plants differ in the number of phytomers they produce, and phytomer size scales with that number. Position along the shoot is therefore an unreliable basis for comparison, confounding shape with size. {middle dot} We first position the floral transition (tassel initiation, T.I.) within shoot development, revealing it as the landmark that organizes a conserved canopy shape. This provides the foundation for aligning canopies that differ in phytomer number. {middle dot} Focusing on the leaf blade, we used functional data analysis on a maize panel across controlled and field environments to decompose variation in blade-length profiles, which was dominated (77%) by overall amplitude, identifying scaling as the major source of size variation. Because blades enlarge with each phytomer until the transition, later T.I. yields a larger maximum; this T.I.-linked component explains up to one-third of scaling variation, reinforced by a shared genetic association between T.I. and blade size with the flowering-time gene ZmCCT10. {middle dot} Regressing out this component leaves a residual that defines a new, heritable axis of intrinsic scaling, independent of flowering time. It distinguishes hyper- and hypo-scaling genotypes consistently across environments, offering a selection target decoupled from phenology.

plant biology↗

bioRxiv2024

A reaction norm for flowering time plasticity reveals physiological footprints of maize adaptation

Understanding how plant phenotypes are shaped by their environments is crucial for addressing questions about crop adaptation to new environments. This study focused on analyzing the genetic variability underlying genotype-by-environment interactions and adaptation for flowering time in maize. We present a physiological reaction norm for flowering time plasticity (PRN-FTP), modeled from multi-environment trial networks and decomposed into its physiological components. We show how genotype-specific differences in developmental responses to temperature fluctuations condition differences in photoperiod perceived among genotypes. This occurs not only across but also within common environments, as the perception of photoperiod is altered by variation in rates of development and durations for becoming sensitized to photoperiod. Using a new metric for envirotyping sensed photoperiods for maize, it was found that, at high latitudes, different genotypes in the same environment can experience up to hours-long differences in photoperiod. This emphasizes the importance of considering genotype-specific differences in the experienced environment when investigating plasticity. Modeling the PRN-FTP for globally representative breeding material showed that tropical and temperate germplasm occupy distinct territories of the trait space for PRN-FTP parameters. Placed in the historical context of maize, our findings suggest that the geographical spread and breeding of maize was mediated by a specific modality of ecophysiological adaptation of flowering time. Our study has implications for understanding crop adaptation and for future crop improvement efforts. Article SummaryMaize adjusts its flowering time across environments using genetic pathways tuned to cues like temperature and day length. This study models how different varieties perceive and respond to these factors, revealing that genotypes can perceive the same environment in distinct ways. By disentangling the ecophysiological basis of genotype-environment interactions, the research explores maize diversity and highlights how adaptation and breeding have shaped distinct strategies for flowering time regulation in tropical and temperate varieties.

plant biology↗

bioRxiv2020

SPEARS: Standard Performance Evaluation of Ancestral Reconstruction through Simulation

MotivationAncestral haplotype maps provide useful information about genomic variation and biological processes. Reconstructing the descendent haplotype structure of homologous chromosomes, particularly for large numbers of individuals, can help with characterizing the recombination landscape, elucidating genotype-to-phenotype relationships, improving genomic predictions and more. Inferring haplotype maps from sparse genotype data is an efficient approach to whole-genome haplotyping, but this is a non-trivial problem. A standardized approach is needed to validate whether haplotype reconstruction software, conceived population designs and existing data for a given population provides accurate haplotype information for further inference. ResultsWe introduce SPEARS, a pipeline for whole simulation-based appraisal of genome-wide ancestral haplotype inference. The pipeline generates virtual genotypes (truth data) with real-world missing data structure. It then proceeds to mimic analysis in practice, capturing sources of error due to imputation and reconstruction of ancestral haplotypes. Standard metrics allow researchers to assess which features of haplotype structure or regions of the genome are sufficiently accurate for analysis and reporting. Haplotype maps for 1,000 outcross progeny from a multi-parent population of maize is used to demonstrate SPEARS. Availabilityhttps://github.com/maizeatlas/spears

bioinformatics↗

bioRxiv2017

Clustering of Circular Consensus Sequences: Accurate Error Correction and Assembly of Single Molecule Real-Time Reads from Multiplexed Amplicon Libraries

BACKGROUNDTargeted resequencing with high-throughput sequencing (HTS) platforms can be used to efficiently interrogate the genomes of large numbers of individuals. A critical challenge for research and applications using HTS data, especially from long-read platforms, is errors arising from technological limits and bioinformatic algorithms.\n\nRESULTSA single molecule real-time (SMRT) sequencing-error correction and assembly pipeline, C3S-LAA, was developed for libraries of pooled amplicons. By uniquely leveraging the structure of SMRT sequence data (comprised of multiple low quality subreads from which higher quality circular consensus sequences are formed) to cluster raw reads, C3S-LAA produced accurate consensus sequences and assemblies of overlapping amplicons from single sample and multiplexed libraries. In contrast, despite read depths in excess of 100X per amplicon, the standard long amplicon analysis module from Pacific Biosciences generated unexpected numbers of amplicon sequences with substantial inaccuracies in the consensus sequences. A bootstrap analysis showed that the C3S-LAA pipeline per se was effective at removing bioinformatic sources of error, but in rare cases a read depth of nearly 400X was not sufficient to overcome minor but systematic errors inherent to amplification or sequencing.\n\nCONCLUSIONSC3S-LAA uses a novel processing algorithm for SMRT amplicon-sequence data that produces accurate consensus sequences and local sequence assemblies. The community standard long amplicon analysis module from Pacific Biosciences is prone to substantial errors that raise concerns about findings based on this pipeline. The method developed here removed this confounding bioinformatics source of error, allowing for the identification of limited instances of errors due to DNA amplification or sequencing.

bioinformatics↗