A curated list of genes that control elemental accumulation in plants

Abstract

Understanding the mechanisms underlying plants' adaptation to their environment will require knowledge of the genes and alleles underlying elemental composition. Modern genetics is capable of quickly, and cheaply indicating which regions of DNA are associated with particular phenotypes in question, but most genes remain poorly annotated, hindering the identification of candidate genes. To help identify candidate genes underlying elemental accumulations, we have created the known ionome gene (KIG) list: a curated collection of genes experimentally shown to change uptake, accumulation, and distribution of elements. We have also created an automated computational pipeline to generate lists of KIG orthologs in other plant species using the PhytoMine database. The current version of KIG consists of 176 known genes covering 5 species, 23 elements and their 1588 orthologs in 10 species. Analysis of the known genes demonstrated that most were identified in the model plant Arabidopsis thaliana, and that transporter coding genes and genes altering the accumulation of iron and zinc are overrepresented in the current list.

Variation in phosphorus and sulfur content shapes the genetic architecture and phenotypic associations within the wheat grain ionome

“…Orthology analysis was performed for genes residing within the identified QTL intervals relative to a reference list of 97 primary ionome genes (Whitt et al , ). We found 82 wheat orthologs for 66 primary ionome genes residing within 46 QTLs (Table S20).…”

“… IDs and annotation of wheat CGs are according to wild emmer wheat reference genome (Avni et al , ), IDs of primary ionome genes are according to a curated list of genes (Whitt et al , ). …”

“…We believe that despite the relatively large number of genes that reside within ionome QTL intervals, the functional annotations of the CGs can be used for identification of the most promising ones, as demonstrated in Table . An alternative approach based on identification of wheat homologs of curated list of known ionome genes (Whitt et al , ) also showed promising results especially in the case of functional matches between QTLs and these genes (Table ). Obviously, the limitations caused by insufficient mapping resolution of QTL analysis may be considerably relaxed by applying our ‘adjustment’ approach in GWAS.…”

“…The obtained results showed that this adjustment is crucial for understanding of the physiological and genetic regulation of mineral composition of wheat grain ionome. We further used the whole genome assembly of wild emmer wheat (Avni et al , ) for identification of promising CGs that are associated with the ionome traits as well as for orthology analysis of known ionome genes (Whitt et al , ).…”

Element content and distribution has limited, tolerance metric dependent, impact on salinity tolerance in cultivated sunflower (Helianthus annuus)

“…While the role of sodium and potassium during salinity stress has been extensively studied (Shabala and Cuin, 2008; Shabala, 2017; Wu et al , 2018) less focus has been placed on other elements (Broadley et al , 2012; Lewis, 2018). Over the past decade inductively coupled plasma mass spectroscopy (ICP-MS) has opened up the door for relatively inexpensive analysis of elemental content of plant tissue (Salt et al , 2008), leading to the identification of a host of genes involved in plant elemental content (Whitt et al , 2018). In previous work on cultivated sunflower ICP-MS analysis revealed leaf sulfur content, besides potassium, to play a role in salinity tolerance (Temme et al , 2019).…”