The terminal 1 cm of the three seminal roots of each plant were collected at 6 and 16 DAG. Roots from 12 plants were pooled per replication to obtain sufficient RNA, and four pools were used as replications for each time point/ genotype combination. RNA samples were extracted using the Spectrum Plant Total RNA Kit . Messenger RNA was purified from total RNA using poly-T oligo attached magnetic beads. After fragmentation, the first-strand cDNA was synthesized using random hexamer primers, followed by the second strand cDNA synthesis using dTTP for a non-directional library. The library for transcriptome sequencing was ready after end repair, Atailing, adapter ligation, size selection, amplification, and purification. The library was checked with Qubit and real-time PCR for quantification and bioanalyzer for size distribution detection. The quantified libraries were pooled and sequenced on Illumina platforms. The clustering of the index-coded samples was performed according to the manufacturer’s instructions . After cluster generation, the library preparations were sequenced on an Illumina platform and paired-end reads were generated. The number of reads per sample and different quality and mapping statistics are described in source data of Fig. 6. Reads were mapped to the Chinese Spring Genome RefSeq v1.0 combined with the 1RS arm from cultivar Aikang58, allowing a maximum of 1 SNP. Reads were mapped using the splicing aware STAR aligner from the Lexogen pipeline. Reads mapping to more than one location were distributed equally among the identical targets. Expression values were calculated using the trimmed mean of M-values normalization method. The sequence of the 1RS.1BL translocation in AK58 is available only as a preprint and no final gene names have been published,round plastic pot so we provide a table with the different names and genome coordinates to facilitate future cross-reference.

Approximately 750 million tons of wheat are produced worldwide every year , but further increases are required to feed a growing human population. One understudied area that can contribute to these yield increases is the role of different root architectures on wheat adaptation to different soils. Although some progress has been made in the understanding of root development and architecture in Arabidopsis , this knowledge is lacking in grass species . There have been some examples of phenotypic selection of root architecture in breeding programs , but those methods are laborious and can be accelerated by a better understanding of the genes controlling wheat root architecture. Rye , a close relative of wheat, is more tolerant to water shortages than wheat, and has been reported to have a more robust root system. The translocation of the short arm of rye chromosome one to wheat chromosome 1B contributes to above ground biomass and better performance under drought stress . To address bread making quality problems associated with the 1RS.1BL translocation , a recombinant 1RS chromosome including two wheat 1BS chromosome segment introgressions was developed to eliminate the two rye regions associated with the bread-making quality problems . We introgressed the newly engineered chromosome into the spring wheat variety ‘Hahn’ and generated 1RS/1RSww near isogenic lines . Previous field trials showed that the Hahn 1RS lines had significantly higher yield and better canopy water status than the 1RSWW NILs in both well-watered and water-stressed environments, although the differences were larger in the latter . From a cross between Hahn-1RSWW and Hahn-1RS, we generated two additional NILs, one carrying the distal and the other the proximal wheat segment . The two NILs carrying the distal rye region showed significant improvements in grain yield and canopy water status compared to NILs carrying the distal wheat segment .

The 1RSxR NILs also showed higher carbon isotope discrimination and increased stomatal conductance, suggesting improved access to soil moisture relative to the 1RSxW NILs . In the winter of 2013, heavy rains waterlogged a UC Davis experimental field that affected the four 1RS NILs at the early tillering stage. Although the affected areas were irregular, the 1RSxR were less affected than the 1RSxW NILs. Based on this observation and previous results, we hypothesized that the 1RSxR lines might have a more extensive root system than the 1RSxW lines, which helped them tolerate both waterlogging in this experiment and water shortages in the previously published experiments . The first objective of this study was to characterize the effect of the wheat-rye polymorphism in the distal region of the 1RS.1BL translocation on root architecture in the field, and on plant biomass and grain yield under normal, excessive or reduced irrigation. After we observed that the lines with the distal wheat segment had shorter seminal roots than the lines with the distal rye segment in hydroponic conditions, we also decided to study the effect of these genotypes on seminal root growth rates, distribution of reactive oxygen species, and distribution of lateral roots. The implications of the observed differences in root development and architecture are discussed. In this study, we used four near isogenic lines that showed differences in grain yield in previous work . The recurrent common wheat parent of these NILs is the spring wheat cultivar ‘Hahn’ developed by the International Maize and Wheat Improvement Center . The Hahn cultivar carries the complete 1RS translocation from rye, and the three NILs differed from Hahn either in the presence of a distal interstitial segment of wheat chromatin , a proximal interstitial segment of wheat chromatin , or both . The interstitial wheat segments were introgressed from the common wheat cultivar ‘Pavon 76’ to eliminate the Sec-1 locus from 1RS and to incorporate the Glu-B3/Gli-B1 locus from 1BS into the 1RS chromosome to improve bread-making quality .

The source of this 1RS arm was the rye cultivar ‘Petkus’, and the resulting 1RS.1BL translocation became widely distributed in wheat breeding programs around the world . Controlled water logging experiments were conducted during the 2013-2014 and 2015-2016 growing seasons. An additional experiment was performed in 2014-2015 but it was not analyzed due to severe weed problems. The experiments were planted in November and harvested in June . The two water logging experiments were organized in a split-plot randomized complete block design with four blocks in 2014 and three blocks in 2016. Within each block, the main factor was irrigation treatment, and within each irrigation treatment – block combination, the Hahn 1RS, 1RSWW, 1RSRW, and 1RSWR genotypes were used as sub-plots. The average trait values of the 1RSxR and 1RSxW NILs were compared to determine the effect of the distal rye and wheat chromosome segments. In the 2014 field experiment, each block included two different irrigation regimes as main plots. The first treatment was based on plant needs and normal practices in California’s Sacramento Valley and is designated hereafter as normal irrigation. The second treatment, referred hereafter as water logging, consisted of artificial flooding twice a week starting in late January and ending in late March during the tillering stage, followed by normal irrigation. Water was applied via flood irrigation, and the soil profile remained saturated. While plants were not kept fully or partially submerged, there were persistent pools of water on the soil surface indicating a waterlogged environment. Each genotype was planted in three adjacent 1 m rows with 30.5 cm spacing between rows at a rate of 30 grains per row. Genotypes were separated by an empty row , and treatments were separated by a minimum of a border row, an irrigation levee, and another border row,round pot leaving in excess of three meters between experimental units of different treatments. Experimental units were replicated six times within each of the four blocks in an RCBD pattern and were used as sub-samples. At the end of the season, each set of three rows was harvested and grain yield was recorded. The average of the six sub-samples was used as a single data point in the statistical analysis. Canopy Spectral Reflectance measurements were taken for all sub-samples on two days . Sub-samples were averaged within days, and day averages were used as repeated measures. Canopy spectral reflectance measurements were taken with the “ASD HandHeld 2 Pro” spectrometer from Malvern Panalytical. Measurements were taken using a “scanning” method in which 50 measurements were taken on a single plot and averaged to give a single reflectance spectrum. From these measurements, differences in biomass between genotypes were estimated using the Normalized Difference Vegetation Index , which was calculated using the formula /, where R = reflectance at the specified wavelength. In the 2016 field experiment, each block included three irrigation treatments. The first treatment was grown under normal irrigation as described above.

The water logging treatment included flood irrigations three times a week, from the beginning of February to the end of February, followed by normal irrigation. The terminal drought treatment was grown under normal irrigation conditions until late March , and no additional irrigations after that point. Within each block–treatment combination, each genotype was machine sown in 2.23 m2 plots , which were combine-harvested at maturity. In 2016, CSR measurements were taken as described above on March 24th , April 6th , April 13th and April 28th . Days were used as repeated measurements and were analyzed as sub-sub-plots in an RCBD split-split-plot design using conservative degrees of freedom for days and all their interactions . After the CSR measurements were completed, an irrigation pipe ruptured flooding several sections of the experiment on April 29th, resulting in increased variability in the final yield measurements. Flooding was irregular and inconsistent across blocks, with major effects on replications two and three of the drought treatment and replication two of the waterlogging treatment. The field experiment to estimate root length was conducted after a maize crop harvested in the summer of 2016.Plots were machine sown in 4.5 m2 plots in November 2016 and were grown under normal irrigation conditions. To obtain soil core samples at specific depths and avoid differential soil compaction, we excavated ~2 m deep trenches cutting perpendicular across the middle of plots including complete blocks one , three and six to expose the root system. We took horizontal soil core samples from the center of each block at 20 cm intervals using a thin-walled copper pipe . Core samples were taken from 20 to 140 cm in the first block and from 20 to 180 cm in blocks three and six after we discovered the presence of roots at 140 cm in block 1. Plants were at the tillering stage at the time of the root sampling.Soil core samples were washed using a hydro-pneumatic elutriation system from Gillison’s Variety Fabrications, Inc. . After washing and sorting white turgid roots from other organic matter and decayed roots of the previous maize crop , we suspended the roots in water and scanned them using an EPSON Expression 11000XL flatbed scanner. Scanned root images were analyzed using the WinRhizo software package. Measurements of dry root biomass are not reported because they were too variable due to small biomass, stray soil contaminants, and changes in ambient moisture. The 20 cm sampling point was not used because the large amount of root biomass and organic matter present in these samples made them difficult to clean and measure. Since all root measurements were performed using soil cores of identical volume we refer to these measures as densities . Differences in total root length, surface and volume density, average root diameter, and root tips and fork densities were analyzed using a split-plot design with genotypes as main plots and depth as subplot. This is a conservative statistical analysis because it reduces the df for genotype from 3 to 1. Therefore, we also compared the two same pairs of genotypes using statistical contrasts in an ANOVA including all four genotypes. To account for the inability to randomize depths, we used a conservative estimate of the df for subplots and for the interaction between subplot and main plot. Conservative df were calculated by dividing their df by the number of subplots. This strategy is similar to that used for repeated measures in time and does not affect comparisons among main plots , which are the main objective of this study. Homogeneity of variance and normality of the residuals was confirmed for all the individual ANOVAs performed at each depth for all parameters.