To ask about the relationship between GC articles and you may recombination price i implement a few approaches

(A) GC content variance around CO breakpoints (blue dots and line). The window 0 on the x-axis is the GC content of the breakpoints and the negative and positive values represent the distance away from the breakpoints. Each of these windows is defined as 2 kb sequence and the GC content is calculated for each window. The red dots and line are one of the GC content random samples simulated like the numbers of CO breakpoints (blue dot and line). After 10,000 repeats, not one of random samples is as what is chat zozo extreme as the observed (blue line) (P <0.0001). (B) Relationship between recombination and GC content. When the chromosomes are dissected into 10 kb non-overlapping regions, recombination rate (cM/Mb) and GC content can be obtained for each of them. After the bins are sorted by the GC content, the windows are divided into 31 groups based on GC content (approximately 20% to 51%, 1% interval), and the average (and s.e.m.) recombination rates reported for each group.

In both we dissect the genome into 10 kb non-overlapping windows of which there are 19,297. First, we ask about the raw correlation between GC% and cM/Mb for these windows, which as expected is positive and significant (Spearman’s rho = 0.192; P <10 -15 ). Second, we wish to know the average effect of increasing one unit in either parameter on the other. Given the noise in the data (and given that current recombination rate need not imply the ancestral recombination rate) we approach this issue using a smoothing approach. We start by rank ordering all windows by GC content and then dividing them into blocks of 1% GC range, after excluding windows with more than 10% ‘N'. The resulting plot is highly skewed by bins with very high GC (55% to 58%) as these have very few data points (Additional file 1: Figure S10E) (the same outliers likely effect the raw correlation too). Removing these three results in a more consistent trend (Additional file 1: Figure S10F). This also suggests that below circa 20% GC the recombination rate is zero (Additional file 1: Figure S10F). Removing those with GC <20% and, more generally, any bins with fewer than 100 windows (all bins with GC < 20% have fewer than 100 windows) leaves 18,680 (96.8%) of the windows, these having a GC content between approximately 20% and 51%.

Dating between recombination and GC-content

Of the observance, i imagine one typically a 1 cm/Mb escalation in recombination price was regarding the a rise in GC posts around 0.5%. On the other hand a 1% rise in GC articles represents an approximately 2 cM/Mb escalation in recombination rate. We conclude you to definitely considering the visible rareness out-of NCO gene conversion, about regarding bee genome, extrapolation regarding GC stuff to average crossing-more than rates for this reason seems to be justifiable, about to own GC content more 20%. I notice also one in the significant GC material this new recombination price is over otherwise underestimated. This might reflect a great discordance ranging from latest and past recombination rates.

These are regularly build Figure 4B, hence presents a fairly sounds-free (after smoothing) monotonic dating between the two variables

Crossing-over price is additionally of this nucleotide range, gene occurrence, and you may duplicate count type nations (Figure S11-S13 for the Extra file step 1) . Considering our very own elimination of hetSNPs out of studies the latter result is not trivially a good CNV relevant artifact. Our very own good-level analyses reveal an optimistic relationship anywhere between nucleotide diversity and you can recombination rates whatsoever the latest scales out of 10, 100, 200, otherwise five hundred kb series window (Figure S11 for the Most file step 1). That it bolsters earlier in the day analyses, certainly and that stated this new trend but think it is getting non-significant, when you find yourself other stated a pattern between populace genetic rates of recombination and you can hereditary diversity. The fresh new pattern accords on the perception you to recombination causes shorter Mountain-Robertson disturbance thus permitting significantly lower rates from hitchhiking and you will history selection, very permitting greater diversity. I also select an effective negative correlation ranging from recombination and you will gene thickness (Profile S12 for the More file 1) and you will an effective confident relationship ranging from recombination and also the duration of multi-backup places at the some windows brands (Shape S13 inside the More document step 1). The brand new relationship with CNVs try in line with a task to possess low-allelic recombination promoting duplications and deletions via irregular crossing over .