Genome-Wide Prediction of Transcription Start Sites in Conifers

Abstract

The identification of promoters is an essential step in the genome annotation process, providing a framework for gene regulatory networks and their role in transcription regulation. Despite considerable advances in the high-throughput determination of transcription start sites (TSSs) and transcription factor binding sites (TFBSs), experimental methods are still time-consuming and expensive. Instead, several computational approaches have been developed to provide fast and reliable means for predicting the location of TSSs and regulatory motifs on a genome-wide scale. Numerous studies have been carried out on the regulatory elements of mammalian genomes, but plant promoters, especially in gymnosperms, have been left out of the limelight and, therefore, have been poorly investigated. The aim of this study was to enhance and expand the existing genome annotations using computational approaches for genome-wide prediction of TSSs in the four conifer species: loblolly pine, white spruce, Norway spruce, and Siberian larch. Our pipeline will be useful for TSS predictions in other genomes, especially for draft assemblies, where reliable TSS predictions are not usually available. We also explored some of the features of the nucleotide composition of the predicted promoters and compared the GC properties of conifer genes with model monocot and dicot plants. Here, we demonstrate that even incomplete genome assemblies and partial annotations can be a reliable starting point for TSS annotation. The results of the TSS prediction in four conifer species have been deposited in the Persephone genome browser, which allows smooth visualization and is optimized for large data sets. This work provides the initial basis for future experimental validation and the study of the regulatory regions to understand gene regulation in gymnosperms.

Keywords: TATA-box; conifer; gymnosperms; promoter prediction; transcription factor binding site; transcription start site.

Figure 1

Frequency of the TATA(A/T)A(A/T) motif in the TSS-centered promoter region.

Figure 2

Distribution of DNA free energy around TSS position predicted by TSSPlant.

Figure 3

Positional distribution of transcription factor binding sites (TFBS) in Larix sibirica, Picea abies, Picea glauca, and Pinus taeda based on PWM scanning using TRANSFAC. (a) AP2/EREBP-related factors; (b) Homeodomain; (c) Heat shock transcription factors; (d) Myb transcription factors.

Figure 4

Orthologous genes of FLORICAULA/LEAFY-like proteins in L. sibirica, P. taeda, P. abies, and P. glauca with corresponding predicted TSS positions (depicted by the vertically-oriented labels) in their upstream regions are aligned using the genome browser Persephone. Red, yellow, green, and blue boxes represent exons. Light blue ribbon-like connectors indicate identical areas, blue lines mark nucleotide substitutions, and red lines indicate indels. The visualization is available at https://web.persephonesoft.com/?bookmark=43C6DEFD15C23F5F40A8AFF25F844042 (accessed on 31 January 2022).

Figure 5

Orthologous genes of WLIM2a in L. sibirica, P. abies, and P. glauca with corresponding predicted TSS positions (depicted by the vertically-oriented labels) in their upstream regions. Red, green, and blue boxes represent exons. Light blue ribbon-like connectors indicate identical areas, blue lines mark nucleotide substitutions, and red lines indicate indels. The visualization is available at https://web.persephonesoft.com/?bookmark=4239E3155493E8E21C61A9932BD502EE (accessed on 31 January 2022).

Figure 6

Some GC statistics for four conifer species, Larix sibirica, Picea abies, Picea glauca, Pinus taeda, and two model plant species, Arabidopsis thaliana and Oryza sativa: (a) GC₃ gradient of coding sequences, (b) GC₃ gradient slope, (c) GC₃ distribution across all CDSs, (d) CG-skew around TSSs.

Figure 7

The difference in coding sequence length between GC₃-poor and GC₃-rich genes; 10% and 90% quantiles were used to divide genes into GC₃-poor and GC₃-rich classes (blue and red, respectively).

Figure 8

Distribution of the exon number per gene in GC₃-poor and GC₃-rich genes in L. sibirica, P. abies, P. glauca, and P. taeda. The number of genes in the GC3-poor and GC3-rich categories was the same within each organism.