Application of an Improved 2-Dimensional High-Throughput Soybean Root Phenotyping Platform to Identify Novel Genetic Variants Regulating Root Architecture Traits

Nutrient-efficient root system architecture(RSA)is becoming an important breeding objective for generating crop varieties with improved nutrient and water acquisition efficiency.Genetic variants shaping soybean RSA is key in improving nutrient and water acquisition.Here,we report on the use of an improved 2-dimensional high-throughput root phenotyping platform that minimizes background noise by imaging pouch-grown root systems submerged in water.We also developed a background image cleaning Python pipeline that computationally removes images of small pieces of debris and filter paper fibers,which can be erroneously quantified as root tips.This platform was used to phenotype root traits in 286 soybean lines genotyped with 5.4 million single-nucleotide polymorphisms.There was a substantially higher correlation in manually counted number of root tips with computationally quantified root tips(95%correlation),when the background was cleaned of nonroot materials compared to root images without the background corrected(79%).Improvements in our RSA phenotyping pipeline significantly reduced overestimation of the root traits influenced by the number of root tips.Genome-wide association studies conducted on the root phenotypic data and quantitative gene expression analysis of candidate genes resulted in the identification of 3 putative positive regulators of root system depth,total root length and surface area,and root system volume and surface area of thicker roots(DOF1-like zinc finger transcription factor,protein of unknown function,and C2H2 zinc finger protein).We also identified a putative negative regulator(gibberellin 20 oxidase 3)of the total number of lateral roots.

Maize Carbohydrate Partitioning Defective33 Encodes an MCTP Protein and Functions in Sucrose Export from Leaves

To sustain plant growth,development,and crop yield,sucrose must be transported from leaves to distant parts of the plant,such as seeds and roots.To identify genes that regulate sucrose accumulation and transport in maize(Zea mays),we isolated carbo/iydrafe part/f/ofi/ngf defecf/Ve33(cpd33),a recessive mutant that accumulated excess starch and soluble sugars in mature leaves.The cpd33 mutants also exhibited chlorosis in the leaf blades,greatly diminished plant growth,and reduced fertility.Cpd33 encodes a protein containing multiple C2 domains and transmembrane regions.Subcellular localization experiments showed the CPD33 protein localized to plasmodesmata(PD),the plasma membrane,and the endoplasmic reticulum.We also found that a loss-of-function mutant of the CPD33 homolog in Arabidopsis,QUIRKY,had a similar carbohydrate hyperaccumulation phenotype.Radioactively labeled sucrose transport assays showed that sucrose export was significantly lower in cpd33 mutant leaves relative to wild-type leaves.However,PD transport in the adaxial-abaxial direction was unaffected in cpd33 mutant leaves.Intriguingly,transmission electron microscopy revealed fewer PD at the companion cell-sieve element interface in mutant phloem tissue,providing a possible explanation for the reduced sucrose export in mutant leaves.Collectively,our results suggest that CPD33 functions to promote symplastic transport into sieve elements.

PARK16 locus:Differential effects of the non-coding rs823114 on Parkinson's disease risk,RNA expression,and DNA methylation

Understanding the genetic basis of Parkinson’s disease(PD)has dramatically progressed since the identification of the first genetic mutation in alpha-synuclein,to become a highly complex model of oligogenic disease(Lubbe et al.,2016;Keogh et al.,2018).