Human serum albumin (HSA) is widely used in clinical and cell culture applications. Conventional production of HSA from human blood is limited by the availability of blood donation and the high risk of viral transmission from donors. Here, we report the production of Oryza sativa recombinant HSA (OsrHSA) from transgenic rice seeds. The level of OsrHSA reached 10.58% of the total soluble protein of the rice grain. Large-scale production of OsrHSA generated protein with a purity >99% and a productivity rate of 2.75 g/kg brown rice. Physical and biochemical characterization of OsrHSA revealed it to be equivalent to plasma-derived HSA (pHSA). The efficiency of OsrHSA in promoting cell growth and treating liver cirrhosis in rats was similar to that of pHSA. Furthermore, OsrHSA displays similar in vitro and in vivo immunogenicity as pHSA. Our results suggest that a rice seed bioreactor produces cost-effective recombinant HSA that is safe and can help to satisfy an increasing worldwide demand for human serum albumin.

BackgroundExtensive studies on heterosis in plants using transcriptome analysis have identified differentially expressed genes (DEGs) in F1 hybrids. However, it is not clear why yield in heterozygotes is superior to that of the homozygous parents or how DEGs are produced. Global allele-specific expression analysis in hybrid rice has the potential to answer these questions.ResultsWe report a genome-wide allele-specific expression analysis using RNA-sequencing technology of 3,637–3,824 genes from three rice F1 hybrids. Of the expressed genes, 3.7% exhibited an unexpected type of monoallelic expression and 23.8% showed preferential allelic expression that was genotype-dependent in reciprocal crosses. Those genes exhibiting allele-specific expression comprised 42.4% of the genes differentially expressed between F1 hybrids and their parents. Allele-specific expression accounted for 79.8% of the genes displaying more than a 10-fold expression level difference between an F1 and its parents, and almost all (97.3%) of the genes expressed in F1, but non-expressed in one parent. Significant allelic complementary effects were detected in the F1 hybrids of rice.ConclusionsAnalysis of the allelic expression profiles of genes at the critical stage for highest biomass production from the leaves of three different rice F1 hybrids identified genotype-dependent allele-specific expression genes. A cis-regulatory mechanism was identified that contributes to allele-specific expression, leading to differential gene expression and allelic complementary effects in F1 hybrids.

Artificial selection of high yield crops and better livestock is paramount importance in breeding programs. Selection of elite parents with preferred traits from a phalanx of inbred lines is extremely laborious, time-consuming and highly random. General combining ability (GCA) was proposed and has been widely used for the evaluation of parents in hybrid breeding for more than half a century. However, the genetic and molecular basis of GCA has been largely overlooked. Here, we present two pleotropic QTLs are accounting for GCA of days to heading (DTH), plant height (PH) and spikelet per panicle (SPP) using an F2-based NCII design, the BC3F2 population as well as a set of nearly isogenic lines (NILs) with five testers. Both GCA1 and GCA2 were loss-of-function gene in low-GCA parent and gain-of-function gene in high-GCA parent, encoding the putative Pseudo-Response Regulators, OsPRR37 and Ghd7, respectively. Overexpression of GCA1 in low-GCA parent significantly increases GCA effects in three traits. Our results demonstrate that two GCA loci associate with OsPRR37 and Ghd7 and reveal that the genes responsible for important agronomic traits could simultaneously account for GCA effects.

The circadian clock enables organisms to rapidly adapt to the ever-changing environmental conditions that are caused by daily light/dark cycles. Circadian clock genes universally affect key agricultural traits, particularly flowering time. Here, we show that OsPRR37, a circadian clock gene, delays rice flowering time in an expression level-dependent manner. Using high-throughput mRNA sequencing on an OsPRR37 overexpressing transgenic line (OsPRR37-OE5) and the recipient parent Guangluai4 that contains the loss-of-function Osprr37, we identify 14,992 genes that display diurnal rhythms, which account for 52.9% of the transcriptome. Overexpressing OsPRR37 weakens the transcriptomic rhythms and alters the phases of rhythmic genes. In total, 3,210 differentially expressed genes (DEGs) are identified, among which 1,863 rhythmic DEGs show a correlation between the change of absolute amplitudes and the mean expression levels. We further reveal that OsPRR37 functions as a transcriptional repressor to repress the expression levels and amplitudes of day-phased clock genes. More importantly, OsPRR37 confers expanded regulation on the evening-phased rhythmic DEGs by repressing the morning-phased rhythmic DEGs. Further study shows that OsPRR37 expands its regulation on flowering pathways by repressing Ehd1. Thus, our results demonstrate an expanded regulation mechanism of the circadian clock on the diurnal rhythms of the transcriptome.

The selection of homozygous lines is a crucial step in the characterization of newly generated transgenic plants. This is particularly time- and labor-consuming when transgenic stacking is required. Here, we report a fast and accurate method based on quantitative real-time PCR with a rice gene RBE4 as a reference gene for selection of homozygous lines when using multiple transgenic stacking in rice. Use of this method allowed can be used to determine the stacking of up to three transgenes within four generations. Selection accuracy reached 100 % for a single locus and 92.3 % for two loci. This method confers distinct advantages over current transgenic research methodologies, as it is more accurate, rapid, and reliable. Therefore, this protocol could be used to efficiently select homozygous plants and to expedite time- and labor-consuming processes normally required for multiple transgene stacking. This protocol was standardized for determination of multiple gene stacking in molecular breeding via marker-assisted selection.